leadership and team-regulation effects on performance

Leadership and Team-Regulation Effects on Performance

Dissertation zur Erlangung des

akademischen Grades eines

Doctor rerum naturalium (Dr.rer.nat.)

vorgelegt von

Lucia Andrea Görke

an der

Mathematisch-Naturwissenschaftliche Sektion

Fachbereich Psychologie

Konstanz, 2019

Konstanzer Online-Publikations-System (KOPS) URL: http://nbn-resolving.de/urn:nbn:de:bsz:352-2-t90wxkkvix099

Tag der mündlichen Prüfung: 11.07.2019

1. Referent: Prof. Dr. Peter Gollwitzer

2. Referent: Dr. J. Lukas Thürmer

3. Referent: Prof. Dr. Florian Kunze

ix

Acknowledgments

„It always takes two to tango“ lautet eine der Weisheiten aus meinem Studium der

Internationale Beziehungen. Ohne den Anderen geht es nicht. In diesem Sinne möchte

ich hier allen danken, die mich auf dem Weg zu dieser Arbeit auf die vielfältigste

Weise unterstützt haben.

Allen voran möchte ich meinen drei Doktorvätern danken. Meinem Doktorvater Peter

Gollwitzer möchte ich dafür danken, dass er mir diese Promotion ermöglicht hat. Seine

Begeisterung und sein Ideenreichtum haben unsere wissenschaftlichen Diskussionen

und Projekte der letzten Jahre geprägt.

Genauso gilt mein Dank Lukas Thürmer, der diese Arbeit durch sein Feedback mit

ermöglicht hat. Insbesondere bin ich ihm dankbar, dass er mir einen Aufenthalt an der

University of Pittsburgh ermöglicht hat.

Florian Kunze danke ich dafür, dass er mit mir mein Feldprojekt zielführend

unterstützt hat und er sich genauso wenig, wie ich von jeglicher Unwegsamkeit hat

abhalten lassen. Ohne sein wertvolles Feedback und seine Begeisterung sowohl für

meine wissenschaftliche Arbeit, als auch für die Präsentationen in den Organisationen

wäre diese Arbeit so nicht zustande gekommen. Ebenfalls danke ich ihm, dass er mich

in den Bewerbungen für Konferenzen unterstützt hat.

Inge Schweiger-Gallo möchte ich dafür danken, dass sie wie eine vierte Doktormutter

für mich war. Ich danke ihr für die anhaltende Kooperation mit dem Team der

Universität Madrid und ihre wissenschaftliche Unterstützung.

Ohne die Unterstützung der Teams der AG Sozialpsychologie & Motivation sowie des

Teams des Lehrstuhls Organizational Behavior würde ich diese Widmung nicht

schreiben können. Ich danke hierfür Andreas Danielowski, Johannes Doerflinger,

x

Theresa Goecke, Lucas Keller, Mike Bieleke, Max Reinwald, Andra Toadar, Anja

Weiergräber, Frank Wieber und Sophia Zimmermann.

Ein großer Dank gilt auch den JungWissenschaftlerinnen, die meine Arbeit unterstützt

haben. Dafür danke ich Sonja Beck, Teresa Ehrler, Selina Graulich und Hannah Knauf.

Für Ihren Einsatz möchte ich mich ganz besonders bei Marlene Alberghina und Julia

Grünewaldt bedanken.

Der Graduiertenschule für Entscheidungswissenschaften (GSDS) und dem

Zukunftskolleg der Universität Konstanz danke ich für die finanzielle Unterstützung

und den Zugang zur interdisziplinären Forschung. Jutta Obenland und Justine Overall

danke ich für ihre Unterstützung von administrativer Seite.

Den Teilnehmern der Kolloquien der New York University und der Universität St.

Gallen danke ich für Ihre stets hilfreichen Rückmeldungen.

Der Allianz Suisse, insbesondere Christine Kalkschmidt und Matthias Etter danke ich,

dass sie mit mir über die letzten Jahre eine wissenschaftliche Kooperation aufgebaut

haben. Meine Forschung im Bereich organisationales Verhalten wäre ohne sie so nicht

möglich gewesen. Hanna Martin danke ich für ihre kompetente Korrektur meiner

Arbeit.

Jeder Weg in die Wissenschaft hat einen Anfang. Dieser begann mit Carlo Masala. Ich

danke ihm, dass er mich für die Wissenschaft und die „parsimonious theories“

begeistert hat. Meinen weiteren wissenschaftlichen Weg und die Inspiration zum

Thema dieser Dissertation verdanke ich meinen „Role Models“: Emilio Galli-Zugaro,

Isabelle Kürschner und Isabell Welpe. Hans Jonas sagte einmal über Hannah Arendt,

dass sie ein Genie der Freundschaft sei. Dies trifft genauso auf Kathrin Morgenstern

zu, sie war und ist ein nicht wegzudenkender Teil meines wissenschaftlichen Weges.

xi

Mein größter Dank gilt meiner Familie, meiner großartigen Mutter Pia, meinem

Bruder Simon mit Nadine, Lilith und Smilla sowie meinem Partner Leo. Ohne ihre

Fürsorge und Unterstützung wäre diese Arbeit zu keinem Ende gekommen.

Widmung

In Gedenken für Frau Professor Marianne Hammerl (*1959 - † 2008)

xii

Abstract

This dissertation is about the regulation of behavior in the organizational domain. The

aim of the following three research papers was to identify potential obstacles to

effective performance as a precondition for people to apply supportive regulatory

strategies (Paper I and Paper III) and to show how people overcome these obstacles

and perform effectively (Paper II). I reflected on the self-regulation strategy

implementation intentions in tandem with leadership to identify and overcome

obstacles to effective performance.

The focus of the first paper was a prototype analysis on the emotion concept of

envy in two studies. My coauthors and I systematically differentiated between envy in

three different Western cultures by mapping their internal structures, their constitutive

features, and their degree of overlap with regards to the same emotion in different

countries. Taken together, the results confirmed that a prototype approach is useful to

study the internal structure of emotions on a cross-cultural level and to unraveling their

constitutive features and degree of overlap with regards to the same emotion in

different countries.

While the first paper revealed which features constitute envy and thereby led

to a greater understanding when envy could be a potential obstacle to effective

performance, the second paper demonstrated how the regulation of team behavior with

the use of transactional leadership and implementation intentions improved team

performance in a hidden profile task. My coauthors and I assumed that teams in the

intervention group that focused on the regulation of team behavior had a higher

decision quality in hidden profile tasks, compared to those in the control group that

received no intervention. The results of an experimental study revealed a significant

xiii

difference between the intervention and control teams. Descriptively, teams with

leaders solved more hidden profiles than teams in the control group, but

implementation intentions on its own or in tandem with leadership were the most

efficient team strategy to solve hidden profile problems. In conclusion, the application

of regulation strategies in the second paper expanded the findings of the research in

the first paper, indicating that the regulation of behavior through transactional

leadership and implementation intentions are efficient means to improve team

performance in the organizational context.

Finally, the third paper identified age stereotypes towards older subordinates

as potential obstacles for younger leaders, when they evaluate the performance of older

subordinates. In a field study, my coauthors and I investigated how the direction of age

dissimilarities in these non-traditional leader-subordinate constellations influenced

performance evaluations of subordinates. Drawing on the shifted-standard model of

stereotype-based judgements, we hypothesized and found that leader-subordinate age

dissimilarity effects are asymmetrical and positively related to performance

evaluations in non-traditional leader-subordinate constellations.

In sum, the three papers suggest that people perform effectively with leadership

and implementation intentions, and that envy as well as age differences potentially act

as obstacles to effective performance outcomes in the organizational context and thus

may need to be regulated.

xiv

Zusammenfassung

Die vorliegende Dissertation untersucht die Regulation von menschlichem Verhalten

in Organisationen. Besondere Aufmerksamkeit bei einer Beschäftigung mit diesem

Thema verdient die selbstregulatorische Strategie des Wenn-Dann-Planens (auch als

Durchführungsintentionen bezeichnet). In den folgenden drei Forschungsarbeiten

steht das Zusammenspiel von Wenn-Dann-Plänen und Mitarbeiterführung als zentrale

verhaltensregulatorische Strategie im Mittelpunkt. Die vorliegenden Arbeiten haben

sich zum Ziel gesetzt mögliche Hindernisse auf dem Weg zu einer effizienten

Performanz zu identifizieren (Forschungsarbeiten I und III) und mit Hilfe von Wenn-

Dann-Plänen und Führungskräften zu bewältigen (Forschungsarbeit II).

Im Fokus der ersten Forschungsarbeit stand die Untersuchung der

konstituierenden Merkmale (Prototyp) der Emotion Neid. In zwei Studien

untersuchten wir die interne Struktur von Neid und seine Überlappungen mit

verwandten Emotionen, in drei verschiedenen Kulturen, mithilfe eines Prototypen-

Ansatzes. Die Ergebnisse unserer Analysen bestätigten unsere Annahme, dass der

Prototypen Ansatz geeignet ist, um die interne Struktur von Neid, seine

konstituierenden Merkmale und seine Verwandtschaft zu ähnlichen Emotionen

kulturübergreifend zu untersuchen. Die erste Forschungsarbeit hat gezeigt, durch

welche Merkmale sich die Emotion Neid auszeichnet. Diese Ergebnisse bilden eine

erste Richtschnur, um aufzuzeigen welche Merkmale von Neid

leistungsbeeinträchtigend sein können und wie man sie mit verhaltensregulatorischen

Strategien adressieren kann.

Die zweite Forschungsarbeit hat sich dem Thema gewidmet, wie Teams mit

Hilfe von verhaltensregulatorischen Mitteln effizienter in ihrer Leistung sein können.

xv

In dieser Arbeit nahmen meine Ko-Autoren und ich an, dass die sich die Leistung von

Teams in Hidden Profile Aufgaben, welche eine verhaltensregulatorische Intervention

erhalten, im Vergleich zur Kontrollgruppe ohne Intervention verbessert. Die

Ergebnisse der experimentellen Studie zeigten einen signifikanten Unterschied

zwischen der Interventions- und Kontrollgruppe. Von deskriptiver Seite zeigten die

Ergebnisse außerdem, dass geführte Teams mehr Aufgaben richtig lösten als Teams in

der Kontrollgruppe. Teams, welche autonom, oder im Zusammenhang mit einer

Führungskraft, Wenn-Dann-Pläne nutzten, konnten die meisten richtigen gelösten

Aufgaben vorweisen. Über die Identifikation von potentiellen Hindernissen

(Forschungsarbeit I) hinaus, verdeutlicht die zweite Arbeit wie die Anwendung von

verhaltensregulatorischen Strategien Teams effizienter Hidden Profile Aufgaben lösen

lässt.

Abschließend gilt es in der dritten Forschungsarbeit Altersstereotype von

jungen Führungskräften gegenüber älteren Mitarbeitern, als potentielle, regulierbare

und zu regulierende Hindernisse von Führungskräften, vorzustellen. Mithilfe von

Felddaten wurde untersucht inwiefern Altersunterschiede zwischen Führungskraft und

Mitarbeiter die Leistungsbeurteilung von Mitarbeitern beeinflusst, wenn entgegen

traditioneller Postenbesetzung die Führungskraft jünger ist als ihr Mitarbeiter.

Abgeleitet von den theoretischen Annahmen des „shifted-standard model of

stereotype-based judgements“ nahmen meine Ko-Autoren und ich an, dass die

Altersunterschiede zwischen jüngerer Führungskraft und älterem Mitarbeiter

einseitige, positive Leistungsbeurteilungen zufolge haben. Diese Annahme konnte

durch die Analyse der Daten bestätigt werden.

Die Gesamtschau der drei Forschungsarbeiten zeigt, dass Führung und

xvi

Durchführungsintentionen effiziente verhaltensregulatorische Strategien für eine

effiziente Performanz sind. Zudem identifizieren die vorliegenden Forschungsarbeiten

Neid und Altersdifferenzen als Maße die Regulationsbedarf in Organisationen haben.

xvii

Table of Contents

Acknowledgments .............................................................................................. ix

Abstract .............................................................................................................. xii

Zusammenfassung ........................................................................................... xiv

Table of Contents ............................................................................................ xvii

List of Tables .................................................................................................... xxi

List of Figures ................................................................................................. xxiii

Synopsis ................................................................................................................. 1

The Role of Obstacles to Effective Performance ................................................... 2

Research Paper I: Are Different Countries Equally Green with Envy .................. 5

Mastering Performance with Leadership and Implementation Intentions ............. 8

Research Paper II: Transactional Leadership and Implementation Intentions ...... 9

Research Paper III: Exploring Asymmetry .......................................................... 13

General Discussion ............................................................................................. 15

Implications ......................................................................................................... 17

Summary and Conclusion .................................................................................... 20

Research Paper I ................................................................................................ 21

Are Different Countries Equally Green with Envy? A Comparison of the

Internal Structure of Envy in the US, Spain, and Germany .............. 21

Abstract ............................................................................................................... 22

Introduction ........................................................................................................ 23

Two Types of Envy: Benign vs. Malicious Envy ................................................ 23

Delimiting Envy from Other Emotions ............................................................... 24

The Present Research ........................................................................................... 26

Study 1: Assessing the Characteristic Features of Envy, Envidia, and Neid

.................................................................................................................. 28

Method ................................................................................................................. 28

Preliminary Data Reduction ................................................................................. 28

Results and Discussion....................................................................................... 29

xviii

Study 2: Internal Structure of Envy, Envidia, and Neid ................................ 31

Method ................................................................................................................. 34

Results and Discussion....................................................................................... 34

General Discussion ............................................................................................. 40

Future Directions ................................................................................................. 45

Workplace Envy .................................................................................................. 48

Tables and Figures ............................................................................................. 50

Research Paper II .............................................................................................. 61

Transactional Leadership and Implementation Intentions: A Team

Regulation Perspective on Performance in Hidden Profiles .............. 61

Abstract ............................................................................................................... 62

Introduction ........................................................................................................ 63

When Do Teams Perform Effectively? ................................................................ 64

A Team Regulation Perspective on Effective Performance ................................ 66

Obstacles to Effective Team Performance ........................................................... 67

Improving Team Performance with Transactional Leadership and

Implementation Intentions ........................................................................ 69

Towards Integrating Transactional Leadership and Implementation Intentions . 75

Method ................................................................................................................ 77

Participants and Design ....................................................................................... 77

Hidden Profile Task Overview ............................................................................ 77

Manipulation of Transactional Leadership .......................................................... 78

Manipulation of Implementation Intentions ........................................................ 80

Procedure ............................................................................................................. 80

Measures .............................................................................................................. 82

Data Analysis ....................................................................................................... 83

Results ................................................................................................................. 84

Tests of Direct Effects ......................................................................................... 85

Tests of Mediation ............................................................................................... 86

Additional Findings on Biases ............................................................................. 88

Discussion ........................................................................................................... 89

xix

Contributions ....................................................................................................... 92

Practical Implications .......................................................................................... 95

Limitations and Future Research ......................................................................... 97

Conclusion ......................................................................................................... 100

Research Paper III ........................................................................................... 101

Exploring Asymmetry: The Influence of Leader-Subordinate Age

Dissimilarities on Performance Evaluations ...................................... 101

Abstract ............................................................................................................. 102

Introduction ...................................................................................................... 103

Explaining Asymmetrical Effects of Age Dissimilarity in Non-Traditional

Leader Subordinate Constellations ......................................................... 107

The Paradox of Positive Performance Evaluations in Non-Traditional Leader

Subordinate Constellations ..................................................................... 109

How to Test Age Dissimilarity Patterns Beyond Difference Scores ................. 111

Method .............................................................................................................. 113

Sample and Data ................................................................................................ 113

Measures ............................................................................................................ 113

Data Analytic Strategy ....................................................................................... 114

Results ............................................................................................................... 116

Multilevel Response Surface Analysis .............................................................. 117

Additional Findings ........................................................................................... 118

Discussion ......................................................................................................... 119

Contributions ..................................................................................................... 120

Implications ....................................................................................................... 125

Limitations ......................................................................................................... 127

Future Directions ............................................................................................... 128

Conclusion ......................................................................................................... 130

References ......................................................................................................... 131

Eigenabgrenzung ............................................................................................. 150

xxi

List of Tables

Table 1. Percentage of Constitutive Features of Envy, Envidia, and Neid (Study 1). 50

Table 2. Mean Centrality Ratings of the Features of Envy, Envidia, and Neid (Study

2). ................................................................................................................................ 53

Table 3. Comparisons of Central and Peripheral Prototypical Features (Study 2)... 56

Table 4. Hidden and Manifest Profile Task: Distribution of Information .................. 79

Table 5. Team Level Means, and Standard Deviations of Discussion Intensity, and

Discussion about the Correct Candidate .................................................................... 90

Table 6. Team Level Discussion Bias Means and Standard Deviations .................... 91

Table 7. Means, Standard Deviations, and Correlations of the Study Variables ..... 121

Table 8. Multilevel Polynomial Regression Model Results ...................................... 122

Table 9. Results for the Average Response Surface .................................................. 122

xxiii

List of Figures

Figure 1. Associative network for USA (Study 2) ..............................................58

Figure 2. Associative network for Spain (Study 2). ............................................59

Figure 3. Associative network for Germany (Study 2). ......................................60

Figure 4. Hidden profile team performance model .............................................75

Figure 5. Percentage of correct team HP decisions.. ...........................................87

Figure 6. Team discussion intensity. ...................................................................93

Figure 7. Mentioned and repeated shared and unshared items ............................94

Figure 8. Average response surface relating leader age and subordinate age with

performance evaluations.. ......................................................................119

1 Synopsis

Synopsis

This dissertation is taking a leadership and team regulation perspective on

performance. I seek answers to questions such as these: What obstacles to effective

performance do individuals and teams encounter in organizations? How can

individuals and teams benefit from leaders and regulation strategies to overcome these

obstacles and perform effectively?

In the three research papers that follow, I have reflected on the self-regulation

strategy implementation intentions (Gollwitzer, 1993, 1999, 2014) in combination

with leadership to identify and overcome obstacles to effective performance in the

organizational domain. Implementation intentions, also known as if-then plans, are

among the most commonly used and rigorously validated instruments in a variety of

societal and motivational domains (Sheeran & Webb, 2016). Therefore,

implementation intentions offer promising prospects to enhance performance in the

organizational context. If we adopt the perspective of implementation intentions as a

self-regulatory strategy that people apply autonomously, leadership can be

conceptualized as an additional external means to regulate people’s behavior and

consequently to influence performance outcomes (Peterson & Behfar, 2005).

Given the manifest importance of implementation intentions and leadership as

a means to regulate behavior in the organizational context, I chose to address the

subject in an interdisciplinary way, by applying the theoretical and methodological

knowledge from industrial-organizational and social psychology, as well as

organizational behavior. This approach is designed to employ a wide range of theories

and methodologies (i.e., network analysis, content analysis, response surface analysis),

allowing me to draw on research designs ranging from high internal to high external

2 Synopsis

validity (i.e., a questionnaire study in Paper I, an experimental study in Paper II, and a

field study in Paper III).

In the following, I will integrate my research papers in a common framework

and demonstrate how they contribute to the encompassing issue of this dissertation. I

present my synopsis in three sections. The first section elaborates on potential

obstacles to effective performance and introduces the regulation of behavior with

implementation intentions and leadership as two strategies to overcome obstacles on

both individual and team levels. In the second section, I present my papers in the

methodological order from high internal to high external validity: First, I identify

obstacles to effective performance with a questionnaire study (Paper I). Second, I

move to the application of the behavior regulation strategies leadership and

implementation intentions in an experimental setting (Paper II). Third, I shift the focus

to a field study, illuminating how potential obstacles to effective performance affect

relations in a leader-subordinate dyad (Paper III). My third and concluding section

points out implications and contributions of my research and opens the door to further

research.

The Role of Obstacles to Effective Performance

In order to be able to accomplish goals such as effective performance, people

need to be committed to the goal and to be able to implement it successfully. A strong

goal commitment is essential for goal accomplishment, but often not, for itself

sufficient (Gollwitzer, 1993, 1999, 2014). As demonstrated in a meta-analysis by

Webb and Sheeran (2006), a large increase in goal commitment (d = 0.66) only

modestly increases goal directed behavior (d = 0.36). If individuals or teams want to

reach a goal, they are facing a variety of challenges: A challenge can be starting an

action at all, retaining resources, or staying on your path towards goal achievement

3 Synopsis

(Gollwitzer, 1999). Therefore, Gollwitzer (1993) suggests to plan out when, where,

and how to reach a goal by the use of so-called implementation intentions as an

effective means to keep up with these challenges. Implementation intentions are an

effective type of specific plans to enhance goal striving. They provide an option to

close the gap between having strong goal intentions and achieving those goals.

Whereas goal intentions are restricted to a wished-for outcome, implementation

intentions are organized in the form of if-then plans: they determine when, where, and

how an individual accomplishes a set goal (i.e., “If I encounter situation S, then I will

show response R!”; Gollwitzer, 1993, 1999, 2014).

If people form implementation intentions to accomplish goals effectively, then

what is the role of obstacles in this process? Individuals who furnish their goals with

implementation intentions need to identify an obstacle that stands in the way of the

aspired goal (Gollwitzer, 1993). In the process of goal striving an obstacle serves as a

goal relevant situational cue and is then linked to the response that is implemental to

accomplish the goal (Gollwitzer, 1999).

Prior studies have shown the considerable impact of furnishing goals with

implementation intentions in various domains (e.g., health or consumer issues; for

review and meta-analyses see Adriaanse, Vinkers, De Ridder, Hox, & De Wit, 2011;

Bélanger-Gravel, Godin, & Amireault, 2013; Gollwitzer, 2014; Gollwitzer & Sheeran,

2006). For instance, one meta-analysis showed that the creation of if then plans

supports people in realizing goals and performing better; this analysis found a medium

to large effect (d = 0.65) of implementation intentions including more than 8,000

subjects (Gollwitzer & Sheeran, 2006).

Nevertheless, to my knowledge, potential obstacles to goal accomplishment

have rarely been studied in the organizational context so far (for an exception assessing

4 Synopsis

the effects of implementation intentions on the team level, see Thürmer, Wieber, &

Gollwitzer, 2015b). In this context specifically, the identification of potential obstacles

to effective performance on different organizational levels contributes to the research

and application of implementation intentions. Further, the research of obstacles to

effective performance illuminates what kind of obstacles require the regulation of

human behavior at all and which situations might benefit from the use of self-

regulatory strategies such as implementation intentions. The reviewed literature

showed that furnishing one’s goal with implementation intentions is an effective

means to regulate behavior.

Yet, research on emotions as potential obstacles to effective performance is

still in its infancy. I decided to assess the emotion envy in my first paper. There exist

different definitions of envy such as more benign or malicious forms of the emotion

(Van de Ven, Zeelenberg, & Pieters, 2009). Consequently, researchers present

conflicting findings which forms of envy are effective means for people to improve

their performance and when they are decreasing performance (Van de Ven,

Zeelenberg, & Pieters, 2011). These conflicting findings suggest that research about

the undetected internal structure and features of envy might be necessary to enable a

better understanding of the conditions under which the emotion affects performance.

Research about the internal structure of the emotion concept of envy and its

behavioral consequences, such as how the emotion affects our performance, have been

so far studied in separate literatures and researchers have made few attempts (e.g.,

Lange, Weidman, & Crusius, 2018) to present an integrated definition and theory of

envy. Parts of my research focuses on the question whether envy has a detrimental

behavioral effect on performance and therefore serves as an obstacle that individuals

may be able to overcome by applying self-regulation strategies.

5 Synopsis

To do this, it is necessary to study what constitutes the emotion envy as a

precondition for further research on the regulation of envy as an obstacle. One

established method to assess the structure of emotions is the probabilistic view of

emotion concepts (Fehr, 1988). This method allows to map the internal structure and

content of the emotion concept of envy by identifying central and noncentral features

of the emotion. Thus, we examined how the concepts of envy differed across cultures.

Research Paper I: Are Different Countries Equally Green with Envy

The initial approach to identify potential obstacles to effective performance

encompasses the assessment and differentiation of the emotion envy across three

cultures. The assessment of the internal structure of the emotion concept of envy was

the focus of two studies. We systematically differentiated between envy in three

different potentially local conceptions of Western cultures by mapping their internal

structures.

Envy has attracted much attention only during the last decade (Moran &

Schweitzer, 2008; Smith & Kim, 2007). Still, little is known about the internal

structure of its everyday concept. Within a probabilistic view of concepts (Fehr, 1988),

we tested to what extent envy and its translation equivalents of envidia in Spanish and

Neid in German have overlapping constitutive features. Thus, the present research

mapped the internal structure and content of the emotion concept of envy.

Study I: Assessing the Characteristic Features of Envy, Envidia, and Neid

In Study 1, the features of the concept of envy were generated according to the

procedure of Fehr (1988) via an open-ended questionnaire. One hundred sixty-five

German, 117 US-American, and 133 Spanish participants provided descriptions of

envy and listed the most accessible constitutive features of the concept in terms of its

definition, elicitors, and typical physical reactions. As a result, envy was mostly

6 Synopsis

defined as referring to not having something, to what someone else has, and as being

elicited by money, academic success, talent, character traits, or travelling. Referencing

to the physical reactions, the participants of all three countries reported feeling anger

when experiencing envy. Yet, the remaining features of envy, envidia and Neid were

generated by the participants of two countries or one country only.

Study II: Internal Structure of Envy, Envidia, and Neid

In Study 2, we mapped the internal structure of envy by determining the degree

to which each feature is central or typical of the concept of envy. Therefore, 122 US-

American, 124 German, and 158 Spanish participants rated on a forced-choice

questionnaire the degree of typicality of those constitutive features that were

mentioned by at least 10% of the respondents of Study 1. The questionnaire comprised

the three main groups of statements, referring to physical symptoms, situations, and

the definition of envy. Consistent with other research on envy, the features that were

rated with ratings higher than 8 and thus were regarded as most typical of envy and its

equivalent terms in German and Spanish by the participants of all three countries were

those which linked it to a comparison with others and as referring to what one would

also like to have.

Yet, other features of envy, envidia and Neid belonging to the definition,

situations, and physical symptoms held different degrees of typicality. Indeed,

participants’ ratings of typicality differed even with regards to the extent to which they

conceived envy to be an emotion. Though the largest connected component of envy,

envidia, and Neid shared a group of central features, network analyses showed that the

components did differ regarding their constituent peripheral features, the density of

their networks, and betweenness centrality of the nodes.

7 Synopsis

Conclusion

Together, these results confirm that a prototype approach in combination with

a network analysis is useful to study the internal structure of emotions on a cross-

cultural level, unraveling their constitutive features and the degree of overlap with

regards to the same emotion in different countries. Network analyses showed that the

largest connected component of envy, envidia, and Neid shared a group of central

features. However, they did differ with respect to their constituent peripheral features,

the density of their networks and betweenness centrality of the nodes.

Knowing the internal structure and the constitutive features of the emotion

envy is helpful to understand when people experience and how individuals react to

experiencing the emotion. This is a first step to identify which features of envy are a

potential obstacle to someone’s performance that might be addressed with

implementation intentions in the future.

From a methodological point of view, we, however, cannot fully ensure

internal validity and the generalizability to other settings (external validity) (Shadish,

Cook, & Campbell, 2002). The analysis of prototypes categories of envy was derived

on the basis of a correlational structure (no deliberate manipulation of a variable) as

reported by the participants of the study in their daily life. Even though, Robinson and

Clore (2002) suggested that the validity in self-reports about current experienced

emotions is higher than self-reports, conducted in more time distance, the validity

might be still limited due to a social desirability bias of respondents.

Further, to improve the validity it might be relevant to establish a clear causal

relationship between envy and performance to address unanswered questions about

how and when individuals who experience envy may need self-regulatory strategies to

enhance their performance. The correlational nature of our design has prevented us

8 Synopsis

from estimating so far the causal effect of self-regulation strategies on performance.

My second study was therefore designed to address this gap.

In my second research paper I conducted an experimental study to examine the

effects of self-regulation strategies on team performance. Research Paper II

demonstrated how the application of regulation strategies helps people to overcome

obstacles and to perform effectively. In organizational contexts, leadership is an

effective means to regulate people’s behavior (Peterson & Behfar, 2005). Below, I

integrate leadership and the use of implementation intentions in my theoretical

framework before I summarize my second paper.

Mastering Performance with Leadership and Implementation Intentions

In addition to the research on the individual level, recent work by Wieber,

Thürmer, and Gollwitzer (2012) revealed that if-then plans are a successful strategy to

overcome obstacles in collective goal attainment and enhance team performance. Their

findings demonstrated that implementation intentions can help teams to increase their

engagement in decision making situations such as when teams are confronted with

hidden profile tasks or with escalation of commitment situations (Thürmer et al.,

2015b; Wieber et al., 2012). As the reviewed literature above showed implementation

intentions are an effective behavior regulation strategy for individuals (for a meta-

analysis see e.g., Gollwitzer & Sheeran, 2006) and teams (e.g., Thürmer et al., 2015b).

When teams form implementation intentions, they are autonomously

improving their performance within the team. An alternative perspective in the

organizational domain is that leaders regulate the behavior of people externally

(Peterson & Behfar, 2005). On a team level, leaders apply regulation strategies such

as fostering self-awareness among team members, establishing standards, setting team

goals or providing team members with feedback to close the gap between goal progress

9 Synopsis

and achieving the goal of effective team performance (Bass, 1990; Carver & Scheier,

2002).

Are teams that apply autonomously regulation strategies performing more

effectively than teams that are regulated externally by a leader? And if so, when taken

both measures together, does leadership reinforce the effect of implementation

intentions or does leadership hinder the execution of implementation intentions?

Finally, what kind of obstacles to effective performance for leaders themselves can be

identified when they monitor teams? Research Paper II provides answers on how to

fill these gaps in research by investigating how external and internal team regulation

with leadership and implementation intentions jointly or in comparison help teams to

perform effectively. Thus, I contribute to the research on regulation strategies in the

organizational domain by identifying potential obstacles for leaders concerning

performance evaluation standards in organizations (Paper III). The following part of

this synopsis presents an overview of my second research paper.

Research Paper II: Transactional Leadership and Implementation Intentions

In an experimental study, I investigated how transactional leadership and

implementation intentions can improve team performance in a hidden profile (HP)

task.

Team Performance in Hidden Profile Tasks

HP tasks have been shown to be valid and reliable measures for team

performance in experimental studies (meta-analyses by Lu, Yuan, & McLeod, 2012;

Mesmer-Magnus & DeChurch, 2009). HPs are team-decision tasks (Stasser & Titus,

1987). In these tasks, prior to a team discussion, each team member possesses two

types of information: information that is available to all team members (shared

information) and information that is uniquely available to each single team member

10 Synopsis

(unshared information) (Stasser & Titus, 1985). Both types of information have

different implications of decisions for the teams. Because solving the decision-task

correctly mandates the use of unshared information, teams that manage to discuss the

unshared information arrive at the correct solution with a higher probability (Stasser

& Titus, 1985). This is a good example of how teams perform effectively when the

sum of their collective work exceeds the sum of the work of individual team members

working alone (Kozlowski & Ilgen, 2006). Still, teams consistently fail to solve HP

tasks (Lu et al., 2012).

In an experimental study, Thürmer et al. (2015b) employed implementation

intentions as a self-regulation strategy to help teams to overcome the consistent failure

of teams in HP tasks. Results revealed that teams with if-then plans solved significantly

more HP tasks than did teams with control instructions (Thürmer, Wieber, &

Gollwitzer, 2015a). In the second research paper, we extended the research of Thürmer

et al. (2015b) and examined the effects of external and internal team regulation on HP

performance. We investigated whether team processes can be regulated externally

through transactional leadership (Bass, 1990; Vancouver, 2000) and internally through

the application of implementation intentions (Gollwitzer, 1993, 1999, 2014).

Transactional leaders set goals and expectations for followers and provide feedback to

support them during the process of goal achievement (Bass, 1990).

The research question was whether transactional leadership and

implementation intentions jointly contribute to increase the solution rate of HP tasks.

Theoretical models on team synergy suggest that team discussion bias (Stasser

& Titus, 1985) and team discussion intensity (Schulz-Hardt, Brodbeck, Mojzisch,

Kerschreiter, & Frey, 2006) are the key factors to solve HPs correctly. A bias occurs

if the information that is discussed by the team discussion does not reflect the whole

11 Synopsis

information that is available to the team members (Schulz-Hardt & Mojzisch, 2012).

Teams with a sufficient discussion intensity discuss more information about the correct

alternative and solve the HP effectively with a greater likelihood (Schulz-Hardt et al.,

2006).

We expected that collective implementation intentions improve decision

quality by increasing discussion intensity and a decreasing discussion bias. We

hypothesized that both transactional leadership and implementation intentions

improve team discussions and decisions in HP situations. We moreover explore

potential additive and interactive effects of both interventions. In our experiment, 99

teams either formed implementation intentions or not and were either assigned a leader

or not. In the following, they worked on a HP task. To detect the correct solution of

the HP, they had to share the information they received prior to the discussion during

the task.

The Effects of Transactional Leadership and Implementation Intentions on Team

Performance

Descriptive analyses showed that teams that applied implementation intentions

in isolation or in tandem with transactional leadership solved most of the HP problems.

In comparison, teams with implementation intentions solved more HPs than teams

with leaders. Still, teams with leaders solved HP problems four times more often than

the control group. A Pearson Chi-square test showed that teams in the intervention

group with transactional leadership and implementation intentions solved significantly

more HP problems than teams without intervention. Further, team discussion intensity

fully mediated the relation between leadership and team discussion on the correct

alternative, but not the association on team decision quality. Across analyses no

interaction effects between the two experimental manipulations occurred.

12 Synopsis

In sum, the results of this study support my assumption that both transactional

leadership and implementation intentions help teams solve HPs. In a direct

comparison, teams with implementation intentions were more likely to solve the HP

task correctly than teams with leaders. However, teams with leaders had the highest

discussion intensity, which indirectly affected the discussion on the correct HP

alternative.

Conclusion

The results of Research Paper II show that teams perform better when they

either have an external leader or use implementation intentions. This is a promising

approach to overcome potential obstacles to effective performance in other areas of

research such as the regulation of emotions (Research Paper I). In the second paper I

have taken further methodological steps towards a higher validity. Methodologically,

conducting an experimental study improved the internal validity compared to using a

correlational study design in my first research paper.

In my second paper, I improved the internal validity of the study by showing

that the manipulation of the predictor came before we assessed the outcome, they

covary and there are no alternative ways to explain the association between predictors

and outcomes (Shadish et al., 2002). Hence, the validation process is limited to some

aspects of external validity. We could not demonstrate a causal relationship that is

generalizable to individuals across settings, times, operationalizations as well as

different contexts, which is necessary to ensure a high external validity (Shadish et al.,

2002). I cannot fully ensure that the results are generalizable to everyday life in

organizations, which might limit the conditions under which the causal relationship

holds in our experimental study (Dipboye & Flanagan, 1979). Therefore, I conducted

13 Synopsis

a study in the field (Paper III) to address the limitations of artificial situations in the

laboratory.

From a theoretical perspective, the third paper focuses on the potential

identification of implicit age stereotypes as obstacles for leaders standing in their way

to an objective performance evaluation of subordinates. As addressed below, the

application of self-regulatory strategies might help leaders to address these obstacles.

Research Paper III: Exploring Asymmetry

Scholars have begun to illuminate the impact of implementation intentions as

a possibility to reduce implicit stereotypes–“the introspectively unidentified (or in-

accurately identified) traces of past experience that mediate attributions of qualities to

members of a social category” (Greenwald & Banaji, 1995, p. 15). Indeed, several

experimental studies using self-regulatory strategies found that implementation

intentions inhibited the activation and application of race and gender stereotypes (e.g.,

Brandstätter, Lengfelder, & Gollwitzer, 2001; Mendoza, Gollwitzer, & Amodio, 2010;

Rees, Rivers, & Sherman, 2019; Stewart & Payne, 2008).

Implicit Age Stereotypes and Implementation Intentions

Why are implicit stereotypes relevant in the organizational domain and how

could implementation intentions be used to reduce their influence? In the third research

paper we build on the vast knowledge on implicit stereotypes and investigated how the

direction of age dissimilarities influences performance evaluations of subordinates in

organizations. Specifically, we addressed the more recent phenomenon when younger

leaders evaluate the performance of older subordinates, which contradict traditional

leadership relationships.

Drawing on the shifted-standard model of stereotype-based judgements

(Biernat, Fuegen, & Kobrynowicz, 2010; Biernat & Manis, 1994; Biernat, Manis, &

14 Synopsis

Nelson, 1991), we hypothesized that leader-subordinate age dissimilarity effects are

asymmetrical and positively related to performance evaluations in non-traditional

leader-subordinate constellations. The logic underlying the shifted-standard model is

that leaders apply different performance evaluation standards for subordinates

depending on the perceived age stereotypes of leaders toward older subordinates

(Biernat et al., 1991; Biernat & Manis, 1994). We therefore posit that positive

performance evaluations of older subordinates are evoked by a leader’s positive bias

due to age stereotypes.

Differentiating Leader and Subordinate Age with Response Surface Analysis

Previous empirical studies applied primarily difference scores (Chattopadhyay,

1999; Liden, Stilwell, & Ferris, 1996) as a statistical technique to assess relational

demographic differences. We applied multilevel response surface analysis (RSA) as

an alternative contribution to overcome several limitations of the difference score

method (Edwards, 2001, 2002; Edwards & Parry, 1993). For example, difference

scores cut a naturally three-dimensional relationship down to two dimensions and thus

produce less reliable results (Edwards, 2002). Therefore, RSA allowed us more

elaborate hypothesis tests compared to traditional difference scores (Edwards, 2002;

Nestler, Humberg, & Schönbrodt, in press).

The Effects of Age Dissimilarities on Performance Evaluations

Results based on company data from 1,165 leader-subordinate dyads supported

the hypothesis derived from our theoretical model. An optimal margin effect revealed

that leader-subordinate age dissimilarity effects are asymmetrical and positively

related to performance evaluations in non-traditional leader-subordinate-

constellations. In other words, the direction of the leader-subordinate constellation

15 General Discussion

matters for age dissimilarity influences on performance evaluations. As expected,

younger leaders evaluated the performance of older subordinates more favorably.

Conclusion

Like Research Paper I, Research Paper III indirectly contributes to the research

on implementation intentions by identifying potential obstacles to effective

performance in the organizational domain. In the third paper, my coauthors and I

identified implicit age stereotypes of leaders about subordinates as potential obstacles

to objective performance evaluations. In contrast to Research Paper I and Research

Paper II, we used field data gathered in a company and thereby demonstrated excellent

external validity (Shadish et al., 2002). Moreover, Research Paper III highlighted that

the direction of age dissimilarities in leader-subordinate constellations matters for

performance evaluations. Analysis with RSA and the application of the shifted

standard model provided an alternative explanation of why age stereotypes might play

a role when leaders evaluate older subordinates differently.

General Discussion

The three research papers of my dissertation helped to identify and overcome

obstacles to effective performance in the organizational domain. Together, the results

suggest that emotions such as envy as well as age stereotypes identify as potential

obstacles for people to perform effectively. Moreover, external (i.e., transactional lead-

ership) and internal (i.e., implementation intentions) team regulation helps teams to

overcome obstacles and thus to improve team performance. In the pages that follow, I

discuss the contributions and implications of this dissertation. Thus, limitations and

future directions of research are highlighted in an integrated framework of the three

research papers.


Contributions

Below, I illuminate the contribution of each paper in the overall context of the

regulation of team and leader behavior in the organizational context (e.g., Peterson

& Behfar, 2005). This dissertation offers two central contributions to the theory and

research on the regulation of team and leader behavior in the organizational context.

First, I expanded the understanding of potential obstacles to effective performance in

organizations, which is a critical, yet neglected issue in the fields of psychological and

organizational research. Specifically, addressing the emotion envy and age stereotypes

of leaders as potential obstacles to effective performance has not been the focus of

research before. Therefore, I provided a first step for research investigating how to

regulate these obstacles with implementation intentions.

The second contribution is about the integration of implementation intentions

and transactional leadership into a common theoretical framework. We presented

teams that are regulated externally (Peterson & Behfar, 2005) by transactional leaders

and autonomous teams that regulate their behavior internally by applying collective

team regulation strategies such as implementation intentions (Thürmer et al., 2015b)

to perform effectively. Moreover, the research of implementation intentions on team

level (for an overview see Thürmer et al., 2015a) has been conducted so far in the

laboratory with team members working autonomously on independent tasks, isolated

from the support of leaders. I contributed by opening the field of collective behavior

regulation research to leadership. The idea of leadership as a function that help teams

to identify their obstacles and to regulate team behavior with regard to goal

accomplishment is not new (Bass, 1985; Morgeson, DeRue, & Karam, 2010). First, I

offered an empirical test and showed that my application of self-regulation theory to

team leadership is useful. Second, I contributed to the research of leadership in teams


by comparing the effectiveness of team regulation through leadership to

implementation intentions that were applied autonomously by the team. I created an

opportunity for researchers to expand their understanding when the regulation of team

behavior is helpful through leadership and under which circumstances teams can

perform independently.

Implications

The findings across the three papers of my dissertation yield important

practical implications as well. The findings indicate that implementation intentions and

leadership help teams to improve their performance. Moreover, leaders might need to

regulate their behavior and could make use of implementation intentions when they

face obstacles to their evaluation standards such as the influence of implicit age

stereotypes in non-traditional leader-subordinate constellations. Additionally, certain

types of envy may affect performance at the workplace. In organizations leaders and

teams may draw on these insights and apply regulatory strategies in their teams or

individually (for the application of implementation intentions in practical settings see

Oettingen, Wittchen, & Gollwitzer, 2013b).

The findings suggest that teams may perform effectively even without a leader

when they apply implementation intentions. Therefore, implementation intentions for

teams may simultaneously enhance team performance in virtual settings, which

becomes increasingly relevant for organizations (e.g., Geister, Konradt, & Hertel,

2006). Here, team members that work from different geographic locations may

perceive themselves as disconnected from their organization, their leaders, and the

central goals of their teams (Fiol & O'Connor, 2005). In this context, applying team

implementation intentions can be particularly important for effective performance.


Limitations and Future Directions

The present work has some limitations that should be addressed in future

research. I also offer possible future avenues how to intertwine the concepts of my

three research papers in a single line of research.

First, although I illuminated the conceptual structures and the features of the

emotion envy in Research Paper I, it is necessary to go a step further and test which

components of envy affect individual performance. In a recent meta-analysis Lange et

al. (2018) propose a Pain-driven Dual Envy theory which reveals that envy consists of

three components: pain, benign envy, and malicious envy. As illustrated elsewhere

(Görke, Bieleke & Gollwitzer, 2019), we assume that benign envy motivates people

to level up and improve their performance, whereas malicious envy leads to a decrease

in performance, and pain. Accordingly, it is necessary for future research to

experimentally manipulate the effect of experienced envy on performance in a neutral

perceptual task (i.e., functioning as an incidental emotion; e.g., Andrade & Ariely,

2009; Pham, 2007).

This task has previously been used to investigate cognitive performance (e.g.,

Voss, Rothermund, & Brandtstädter, 2008), and has been applied to study the impact

of various psychological variables on performance, such as conformity (Germar,

Albrecht, Voss, & Mojzisch, 2016; Germar, Schlemmer, Krug, Voss, & Mojzisch,

2014), framing effects (Voss et al., 2008), and fear of failure (Lerche, Neubauer, &

Voss, 2018). Despite its simplicity, it allows researchers to reliably measure decision

speed and accuracy as primary indicators of performance. Moreover, these measures

can further be used to draw inferences about the cognitive processes underlying

performance. Critically, before participants start working on the task, they will be

instructed to describe a personal situation in which they experienced malicious versus


benign envy (envy conditions), or they will be instructed to describe a neutral situation

(control condition). We expect that performance – in terms of speed and accuracy –

will differ as a function of these conditions. Participants experiencing benign envy

should be motivated to perform better than participants experiencing malicious envy,

which will likely result in better performance (i.e., faster and or more accurate

decisions). In a next step, it should be investigated if implementation intentions or

leadership can help individuals to overcome those components of envy that impair

peoples’ performances.

Second, I identified age stereotypes as potential obstacles for leaders to

evaluate the performance of subordinates accurately in an unbiased way. However, we

did not assess moderating factors such as emotions (e.g., Kunze & Menges, 2016) that

might affect how leaders evaluate older subordinates. For example, it may be the case

that leaders who envy younger subordinates might show an abusive leadership style

(e.g., Li, Zhang, Law, & Yan, 2015) which in turn might affect the performance

evaluation of subordinates negatively. In this context, implementation intentions might

help to inhibit age stereotypes of leaders about subordinates and the influence of

negative components of envy.

Finally, our study about the regulation of team behavior with leadership and

implementation intentions, did not embrace how good team members handle emotions

such as envy, that occur in the team (e.g., Menges & Kilduff, 2015). Research on the

effective regulation of emotions on a team level is still scarce and precisely it is

relevant to understand how teams could collectively regulate their behavior to perform

effectively.


Summary and Conclusion

The present research identified potential obstacles to effective performance and

investigated how people can regulate their behavior with leadership and the use of

implementation intentions to overcome obstacles to effective performance. The first

paper conceptualized the emotion of envy as a potential obstacle for effective

performance in a questionnaire study. The second paper addressed in an experimental

study how transactional leadership and implementation intentions helped teams to

perform effectively in a HP task. The third paper showed how age dissimilarities in

non-traditional leader subordinate constellations influence performance evaluations of

subordinates using real-world data.

In conclusion, the findings presented suggest that people can perform

effectively with the help of leadership and implementation intentions, and that

emotions and age differences affect performance outcomes in the organizational

context. This demonstration advances existing theory, research, and practice of

implementation intentions on the individual and team level. It also offers a novel

perspective on regulation processes in the organizational context.

21 Research Paper I

Research Paper I

Are Different Countries Equally Green with Envy? A Comparison

of the Internal Structure of Envy in the US, Spain, and Germany

Inge Schweiger Gallo1, Lucia A. Görke2, 3, Miguel A. Alonso1, Reyes Herrero

López1, Peter M. Gollwitzer2, 4

1 Departamento de Antropología Social y Psicología Social,

Universidad Complutense de Madrid, Spain

2 Department of Psychology, University of Konstanz, Germany

3 Graduate School of Decision Sciences, University of Konstanz, Germany

4 Department of Psychology, New York University, USA

https://www.ucm.es/dep-psicologia-social/directorio/?eid=3216

22 Abstract

Abstract

Based on a probabilistic view of emotion concepts, we mapped the internal structure

and content of the emotion concept of envy and its translation equivalents of envidia

in Spanish and Neid in German. In Study 1 (total N = 415), the features of the concept

of envy, envidia, and Neid were generated via an open-ended questionnaire. In Study

2 (total N = 404), participants rated the degree of typicality of the constitutive features

on a forced-choice questionnaire. Network analyses revealed that even though the

largest connected component of envy, envidia, and Neid shared a group of central

features, they did differ with respect to their constituent peripheral features as well as

the density of their networks and betweenness centrality of the nodes. These results

suggest that a prototype approach combined with network analysis is a useful approach

for studying the internal structure of everyday emotion concepts and the degree of

overlap with respect to the translation equivalents in different countries.

Keywords: envy, network analyses, everyday emotion concept, prototype

approach

23 Introduction

Introduction

Envy is a common emotion in our everyday life, affecting both physical and

psychological health (overview by Smith & Kim, 2007): Envy has been reported to

correlate with low self-esteem (Fiske, 2010; Parrott & Smith, 1993) depression

(Cohen-Charash, 2009; Fiske, 2010), anxiety, negative mood, and to lead to hostility

and a negative group atmosphere (Cohen-Charash, 2009), as well as aggressive

behaviors (Cohen-Charash, 2009; Smith & Kim, 2007). Research by Milfont and

Gouveia (2009) also found that envy is negatively related to life satisfaction, vitality,

and happiness. Envy is known to activate pain-related neural circuitry when the

possessions of the envied person (e.g., abilities, qualities, and social status) are

superior and the comparison domain is self-relevant (Takahashi et al., 2009). The

definition by Smith and Kim (2007) highlights this pain-related association: “envy is

an unpleasant and often painful blend of feelings characterized by inferiority, hostility,

and resentment caused by a comparison with a person or group of persons who possess

something we desire” (p. 49); and authors such as Tai, Narayanan and McAllister

(2012) do consider such pain as the defining quality of envy.

Two Types of Envy: Benign vs. Malicious Envy

Though research on envy was still in its beginnings a decade ago (Moran

& Schweitzer, 2008; Smith & Kim, 2007) and little research had addressed envy as

compared to other feelings (Miceli & Castelfranchi, 2007), fortunately envy has

attracted more attention and research over the last years. One intriguing stream of

research suggests a distinction between benign envy (i.e., a benign form of envy, free

of hostile feelings; e.g., Fiske, 2010; Smith & Kim, 2007) and malicious envy (which

is related to hostile feelings and may lead to hostile reactions; Smith & Kim, 2007).

This distinction has allowed for recognizing that there is more to envy than a mere

24 Introduction

maliciousness with dysfunctional consequences, as envy may also be associated with

positive consequences and serve adaptive functions (e.g., energizing goal-directed

behaviors to improve oneself; Tangney & Salovey, 1999).

Both benign and malicious envy are unpleasant and frustrating, but whereas

benign envy is elicited in situations that are perceived as deserved, malicious envy

arises when a situation is perceived as undeserved (van de Ven, Zeelenberg, & Pieters,

2009). Further, they shift attention differently to environmental stimuli at early levels

of processing (Crusius & Lange, 2014), and they also have different motivational and

behavioral consequences: Whereas benign envy shifts attention towards means to

attain an envy-related object (Crusius & Lange, 2014) and is characterized by a

positive motivation to improve oneself (van de Ven et al., 2009; van de Ven,

Zeelenberg, & Pieters, 2011) as long as the improvement is perceived as attainable

(van de Ven et al., 2011), malicious envy on the other hand intends to pull down the

superior other (van de Ven et al., 2009) and shifts attention toward the envied person

(Crusius & Lange, 2014).

Benign envy has been found to lead to improved performance as compared to

participants who felt admiration or malicious envy (van de Ven et al., 2011). Whereas

some research suggests that envy is better conceived of as two types rather than in

terms of one dimension (Falcon, 2015), Cohen-Charash and Larson (2017) recently

advocated for considering envy as a unitary construct arguing that a distinction

between different types of envy is neither endorsed by theory nor supported by

empirical findings.

Delimiting Envy from Other Emotions

Earlier research has described envy as being constituted of various emotions

(Cohen-Charash, 2009) and has explicated the relationship between envy and other

25 Introduction

emotions, such as jealousy (Fiske, 2010; Miceli & Castelfranchi, 2007; Quintanilla &

de Lopez, 2013; Smith & Kim, 2007) or shame and anger (Fiske, 2010). More

specifically, both jealousy and envy have long been regarded as synonyms (Foster et

al., 1972) and thus were often confused (Smith & Kim, 2007). However, whereas

jealousy implies losing something that is already in one’s possession, envy refers to

the wish to possess what another person has (Foster et al., 1972; Parrott & Smith, 1993)

who is in a better position (van de Ven, 2016). Thus, as compared to jealousy where

three actors are involved (i.e., oneself, the envied other, and the relationship one fears

to lose; Smith, Kim, & Parrott, 1988), envy only involves the dyad of an envier and an

envied person (Parrott & Smith, 1993).

Given the difficulties to delineate envy from other feelings and thus to establish

whether or not they are part of other feelings (Miceli & Castelfranchi, 2007), we deem

a prototype approach as pertinent to analyze the content (i.e., unique or shared

attributes) of the everyday concept of envy as well as its translation equivalents in

different countries. The prototype approach originated from research by Rosch (1973),

who conceived of concepts as organized around prototypes rather than as having a

number of necessary and sufficient defining attributes. A membership in a category is

thus determined by resemblance, and members vary in the degree to which they are

members (Russell, 1991b). Accordingly, the border between categories is fuzzy (i.e.,

there are no sharp boundaries which separate members from nonmembers).

Previous research on shame (Hurtado de Mendoza, Fernández-Dols, Parrott, &

Carrera, 2010), vengeance (Elshout, Nelissen, & van Beest, 2015), love (Fehr &

Russell, 1991), modesty (Gregg, Hart, Sedikides, & Kumashiro, 2008), gratitude

(Lambert, Graham, & Fincham, 2009), grima (Schweiger Gallo, Fernández-Dols,

Gollwitzer, & Keil, 2017), and even the concept of emotion itself (Fehr & Russell,

26 Introduction

1984) has shown that a prototype approach allows for identifying the features of

emotion concepts, and thus to delineate their internal structures. Identifying the

internal structure of everyday emotion concepts is an important prerequisite to enhance

our knowledge and understanding of emotion concepts, and it allows for the

delineation of emotion concepts from one another. Indeed, research on emotions such

as disgust discovered that disgust may be composed by different constructs (e.g.,

socio-moral disgust and core disgust; Simpson, Carter, Anthony, & Overton, 2006).

Even more so, cross-cultural research has suggested that disgust is not a

homogeneous category of emotion, as words commonly translated as disgust may not

refer to the same concept (e.g., the translations of disgust into Korean and Malayalam;

Han, Kollareth, & Russell, 2016). In the present research, a prototype approach was

expected to lay the foundations for uncovering via network analyses the structure of

interconnections and relations between the features as well as the relevance of the

single features of envy and its translation equivalents of envidia and Neid.

The Present Research

As little research has so far addressed the everyday concept of envy, our aims

were threefold: First of all, we targeted the analysis of the antecedents and physical

correlates of envy and of two of its translation equivalents (i.e., envidia in Spanish and

Neid in German). Thus, we assessed the internal structure of envy, envidia, and Neid,

exploring whether and to what extent the features of envy and its translation

equivalents relate to each other within the respective country and between countries.

Second, we wanted to find out whether or not the differentiation of benign and

malicious envy also holds true with regard to the everyday conceptions of envy.

Previous research has suggested that some languages, such as Dutch, have different

words for the positive and negative type of envy, respectively: benijden (benign envy)

27 Introduction

vs. afgunst (malicious envy; van de Ven et al., 2009). Therefore, we looked at two

languages that are known to have only one word for envy (i.e., Spanish and English),

and a language that has two words for the two different types of envy (i.e., German:

missgönnen and beneiden; Crusius & Lange, 2014) by using the direct translations that

encompass both benign and malicious envy (i.e., Neid and envidia). Given that even

though the Spanish language does not have a single word for a benign form of envy,

Spanish speakers are used to speak of “envidia sana,” (see also Rodriguez Mosquera,

Parrott, & Hurtado de Mendoza, 2010) which is equivalent to benign envy, we

hypothesized that the participants of Germany, Spain, and US would differentiate

between a positive vs. a negative form of envy and that this differentiation would also

reflect itself in the internal structure of envy, envidia and Neid, respectively.

Third, we aimed at analyzing how envy relates to other feelings. Based on the

Shaver, Schwartz, Kirson, and O'Connor (1987) hierarchy of English emotion terms

where the anger category was found to contain a subcategory of envy and jealousy, as

well as previous research linking envy to jealousy and anger (e.g., Fiske, 2010), we

hypothesized that English speakers would relate envy to jealousy and anger. As most

research so far has been done with English speakers, and less so with German (e.g.,

Crusius & Lange, 2014) or Spanish (e.g., van de Ven et al., 2009) speakers, we made

no specific predictions for envidia and Neid regarding their relationship to other

everyday emotion concepts.

In order to maximize power in both studies, we based the sample size on

previous research. The sample size used in Study 1 was expected to allow for the

generation of sufficient features, and thus to reflect adequately the characteristic

features of envy, envidia, and Neid. Actually, we somewhat exceeded the sample sizes

of previous cross-cultural research, such as the Hurtado de Mendoza et al. (2010)

28 Study 1: Assessing the Characteristic Features of Envy, Envidia, and Neid

studies (Ns = 24 and 54 in Study 1, and Ns = 120 and 120 in Study 2). In Study 2, we

targeted a similar sample size as in Study 1, as a total N of more than 400 participants

would allow detecting an anticipated medium effect size of f = 0.15. Moreover, our

sample sizes equal or even somewhat exceeded those from previous research based on

prototype approaches, such as studies compiling features and assessing centrality

ratings of gratitude (Lambert et al., 2009), listing of characteristics and estimation of

prototypicality of modesty (Gregg et al., 2008), or listing of features and quantifying

of feature centrality of vengeance (Elshout et al., 2015).

Study 1: Assessing the Characteristic Features of Envy, Envidia, and Neid

Method

Participants. One-hundred and seventeen US (females 84; mean age M =

19.44, SD = 1.67), 133 Spanish (females 94; mean age M = 20.42, SD = 2.33) and 165

German participants (females 144; mean age M = 20.76, SD = 3.70) contributed data.

Only those data stemming from participants whose mother tongue was English,

Spanish, and German, respectively, were considered. Participants gave their consent

after being informed of the nature of the study.

Materials and procedure. First of all, participants were asked to define envy

or the equivalent in Spanish (i.e., envidia) or German (i.e., Neid) before listing the

elicitors of envy. More specifically, participants were asked to stop either after a

minute or after having listed 10 elicitors. Participants also described their bodily

reactions when experiencing envy/envidia/Neid. Finally, all participants were asked to

fill out demographic variables, and were thanked or thanked and compensated.

Preliminary Data Reduction

Based on Fehr's (1988) procedure, which has been proven effective for coding

features of everyday emotion concepts (e.g., Hurtado de Mendoza et al., 2010;

29 Results and Discussion

Lambert et al., 2009; Schweiger Gallo et al., 2017), we performed a category analysis

for each of the three questions: the definition, elicitors, and physical reactions of envy.

We first organized participants’ responses into minimally inclusive linguistic units.

Responses such as “Envy is an emotion in which you want something that another

person has” were, for example, divided into the linguistic units of “emotion,” “want

something,” “that another person has.” These linguistic units were then grouped

together into one category whenever the grammatical form of the listed features was

identical or almost identical (e.g., a verb inflected in different tenses, plural and

singular forms of a noun, etc.), when they were modified by adjectives, or identical in

meaning. “That another individual has,” “that another person has,” “that other people

have,” and “that others have” were for example grouped into one category. In cases

where the two coders did not agree, consensus was reached by discussion.

The extraction of attributes yielded 376 linguistic units for the definition of

envy, 635 linguistic units for envidia, and 809 linguistic units for Neid, which were

grouped into 93, 139, and 151 categories, respectively. The coding procedure also

yielded a total of 448 elicitors of envy, 449 of envidia, and 668 of Neid. These

linguistic units were assorted into 84 categories for envy, 86 categories for envidia,

and 72 categories for Neid. Finally, 66 categories of physical responses of envy, 76 of

envidia, and 86 of Neid were created out of 247, 257, and 347 linguistic units,

respectively.

Results and Discussion

We focused on the linguistic units referred to by at least 10% of the respondents

of any of the three samples (see Table 1). Consistent with the literature on envy

highlighting the importance of social comparison processes (Miceli & Castelfranchi,

2007), such processes were mentioned by participants of all three countries (“what


another person has” and “what you do not have”), as well as the desire to have what

the other possesses, either expressed as a wish (Spanish and US participants) or as

referring to what one would like to have (German and Spanish respondents). Indeed,

Fiske (2010) already suggested that a wish to have something underlies envy. Our

finding is also consistent with previous research, where the wish to have what another

person possesses was found to be the most prototypical element in descriptions of envy

(Parrott & Smith, 1993), and with experimental research suggesting that negative

social comparisons not only induce envy but also lead to impulsive behavioral

approach tendencies to acquire the desired good (mostly in individuals who lack self-

regulatory resources; Crusius & Mussweiler, 2012). However, the generated features

seem to fit better with an approach highlighting the expression of a wish to have what

the other has rather than not wanting the other person to have it (see Fiske, 2010).

The participants of all three countries also related envy mostly to money,

academic success, talent, character traits, and travelling. This is consistent with recent

research by Navarro-Carrillo, Beltrán-Morillas, Valor-Segura, and Expósito (2017)

who found that personal skills/competences such as intelligence, social skills, and

success were most frequently referred to with 33% of the mentions, followed by work

and/or academic issues (e.g., grades and performance on exams). Our data also fit

nicely with those by Rodriguez Mosquera et al. (2010) who found that the most

common source of envy was academic achievement, as well as with those by Henniger

and Harris (2015), who found that scholastic success was reported mainly by young

people. As regards the physical reactions, the participants of all three countries

reported anger responses. This finding is consistent with previous theorizing by Fiske

(2010) who highlighted the relationship between envy and other emotions, primarily

anger.

31 Study 2: Internal Structure of Envy, Envidia, and Neid

Further features of envy, envidia, and Neid for the definition, elicitors, as well

as the physical symptoms were generated by the participants of two countries or one

country only (e.g., it was said to cause nervousness by Spanish participants only).

Contrary to our predictions, only Spanish participants characterized envy as negative

(23%), good (12%), and bad (10%) and thus referred to both a positive and a negative

form of envy. Finally, only US participants related envy to jealousy and sadness. Thus,

consistent with our third assumption, English speakers linked envy to jealousy and

anger, whereas German and Spanish speakers did not relate envy to jealousy, but to

anger.

Study 2: Internal Structure of Envy, Envidia, and Neid

In Study 2, we targeted the analysis of groups of features within envy, envidia,

and Neid, as well as the relationship between features and the relevance of these

features within the network via network analyses. Thus, we relied on a network

approach, as it can be expected to unravel the internal structure of the everyday concept

of envy and its translation equivalents within and between the three countries.

A social network is composed by nodes (i.e., actors) and edges (i.e., relations

between the nodes). Earlier research applying social network analysis, for example,

have conceptualized e-mail accounts as a set of nodes and e-mails as connecting these

nodes (Gloor, Fronzetti Colladon, Grippa, & Giacomelli, 2017) or phone users as

nodes and communication between nodes as edges (Xu & Zhang, 2012). Those nodes

that are connected by a tie are conceptualized as neighbors, whereas nodes without

connections are called isolates (Easley & Kleinberg, 2010; Hanneman & Riddle,

2005).

As compared to social network analyses per se, which analyze the links

between actors, we focused on “the structure of a system based on shared meaning”


(Doerfel & Barnett, 1999, p. 589), as semantic networks do. Therefore, in the present

study, we draw on the logic of cognitive theories of associative structures (e.g., Collins,

A. M. & Loftus, 1975) which have been applied, for example, in representations of

consumer brand associations (Grebitus & Bruhn, 2008; overview of consumer brand

network approaches by Henderson, Iacobucci, & Calder, 1998). Thus, we modeled the

features of envy (and envidia and Neid) as associative networks by conceptualizing

features as nodes and the links between nodes as representing associations between the

nodes in order to assess the importance of the features within each of the networks.

First of all, we calculated the density of each of the networks. Density is usually

defined as the sum of the values of all ties divided by the number of possible ties

(Hanneman & Riddle, 2005). It measures tie strength between actors, with high density

indicating strong ties between ties (Marsden, 1987). For instance, highly related topics

and keywords have been reported to be indicators of dense semantic networks (Lee,

Lee, Kim, & Lee, 2013).

Further, one of the structures suitable to analysis is that of connected groups of

nodes (i.e., communities). Within one community nodes tend to be highly similar and

to share features, as compared to nodes of different communities with which they have

low similarity (Gündüz-Öğüdücü & Etaner-Uyar, 2014). Further, these groups of

nodes are characterized by dense connections within each community and fewer ones

between communities (Newman & Girvan, 2004). Detecting communities (e.g.,

communities of researchers working in a specific field or a citation network composed

by related papers on a specific topic; Girvan & Newman, 2002) bears the

methodological advantage of allowing to analyze the structure of networks at an

intermediate level of analysis (i.e., densely connected subgraphs) and unravelling


relationships between the nodes that may not be apparent at other levels of analyses

(Lancichinetti, Kivelä, Saramäki, & Fortunato, 2010).

Next to discovering the communities within each of the concepts, and to

analyze the structure of each of the subgroups (i.e., analyzing the network at the node

level), we also calculated one of the most popular indices of centrality: betweenness

centrality (Freeman, 1979). Betweenness centrality describes the relevance of an actor

due to its position with respect to other actors (i.e., an actor is central if situated

between other actors; Wasserman & Faust, 1994). Thus, betweenness refers to the

shortest path between various parties (Butts, 2008). Standardized measures range from

0 to 1 (i.e., when a node is situated on all shortest paths). This centrality index allows

for gaining insights into “the structural importance or prominence of a node in the

network” (Borgatti, Mehra, Brass, & Labianca, 2009, p. 894), and thus for identifying

those nodes that are particularly influential in spreading activation within the network

(Henderson et al., 1998) — having a higher probability of getting activated or

activating other features (Grebitus & Bruhn, 2008). Returning to the example of e-mail

networks, an employee with a high betweenness centrality would act as intermediary

in the information flow between other actors (Gloor et al., 2017). In sum, betweenness

centrality is expected to allow for assessing the extent to which the features of the

everyday concept of envy (or its translation equivalents) have a prominent role within

their respective networks and their position as intermediaries between nodes.

Participants were asked to indicate the extent to which they considered each of

the statements presented to them as typical of the envy concept. They were told that

whereas the number 0 indicated that the statement was not typical of envy, the number

5 indicated that it was more or less typical, and 10 meant that it was very typical. The

items were listed in random order.


Method

Participants. One-hundred twenty-two US participants (females 93; mean age

M = 19.50, SD = 3.56), 158 Spanish (females 109; mean age M = 28.41, SD = 13.43),

and 124 German (females 98; mean age M = 21.99, SD = 5.61) participants contributed

data. Participants gave their consent after being informed of the nature of the study.

Materials and procedure. Participants were given a forced-choice

questionnaire containing the 51 items extracted from Study 1. These items were taken

from those categories mentioned by at least 10% of the participants in each country.

Statements referring to the definition and elicitors of envy/envidia/Neid where framed

as “Envy refers to/is…” or “Envy is caused by…,” whereas the physical reactions were

described as “Envy causes….” Each item was selected among the responses of the

participants and whenever possible, we chose the item mentioned by a higher number

of participants within each category. In those cases where the same feature was

extracted in two or even all three countries, we chose the item with the highest number

of mentions. “Anger,” for example, was mentioned by all three samples; as it was more

frequently mentioned by Spanish participants (37 %) than by US (17 %) and German

participants (10 %), this item was selected among the linguistic units extracted from

the responses of the Spanish participants.

Results and Discussion

First of all, we mapped the internal structure of envy, envidia and Neid,

respectively, by computing the network metrics of community detection, density, and

betweenness centrality. These measures allowed for analyzing the main groups and

subgroups that comprised each of the emotion concepts, as well as the relevance of the

position of the features (i.e., betweenness centrality; Freeman, 1979) and tie strength

(i.e., density) between features. Further, we assessed which of the features of the main


communities detected in the everyday emotion concepts of envy, envidia, and Neid

were considered to be central as opposed to peripheral. In a final step, we then

compared the ratings of prototypicality between envy, envidia, and Neid.

Network analyses. We first generated three matrixes, one for each country.

Each matrix is an undirected, valued network composed of a set of nodes (features of

envy, envidia or Neid, respectively), and of a set of ties connecting these nodes. In

order to detect communities within each of the networks (i.e., to identify subtypes of

related cases; see Figures 1-3 for layouts generated using the algorithm of Kamada and

Kawai (1989), we relied on a technique known as the Louvain optimization method

which has been shown to have a good quality detecting communities and to be more

accurate than other community detection methods in terms of modularity (Blondel,

Guillaume, Lambiotte, & Lefebvre, 2008). In line with past research on social

networks, we established θ = 0.5 as the threshold (e.g., Xu & Zhang, 2012).

The mean network density of the US network was D = 0.11. Applying the

Louvain algorithm, we identified six groups of nodes. The largest connected

community contained 19 vertices (i.e., nodes; 37.26% of the network). This main

community comprised three subgroups: One subgroup entailed twelve features

pertaining to elicitors and interpersonal relationships (e.g., people who have a big and

close family, people with lots of money), as represented by an orange color in Figure

1. Importantly, the feature of better appearance showed the highest betweenness

centrality of this network (CB = 0.04), followed by nice home (CB = 0.02). Thus, the

feature of better appearance had the strongest position within the network, with more

nodes (i.e., features) linked to it than any other feature. Attached to this subgroup was

a second smaller subgroup of two features: people with a happy relationship (CB =

0.01) and people with a special talent such as singing well (yellow color). In addition,


the main community included a third subgroup of five achievement-related features

(e.g., people who get a better grade than you with less effort, people getting a better

grade than you; blue color). Next to this main community, a second community

contained eight features related to physical symptoms and characteristics (e.g.,

negative, tensing up; light pink color). Another community of six features contained

features related to whether or not having something (e.g., refers to another person who

has something, you don’t; refers to what you also would like to have; black color), and

the last community included the two features of people with willpower and to not

begrudging someone something (light grey color).

The mean network density of the network of Spain was D = 0.14. The analysis

of the community structure revealed that the size of its largest component was greater

than the largest component in the US network (22 vertices, 43.14%), and that the

network included five differentiated communities: The main community was

composed by three smaller subgroups and included the features with the greatest

betweenness centrality of the whole network. The elicitors of envidia where located in

different subgroups within this main community, including a group with eleven

features (lilac color in Figure 2) articulated around the features of people who are given

a new car (CB = 0.02), people with a nice home (CB = 0.02), and people with a state-

of-the-art mobile phone (CB = 0.02). Also, within the main community, a subgroup of

six features referred mostly to interpersonal relationships (e.g., people with lots of

friends, people with a happy relationship; yellow color) and included the feature of

successful people, which showed the highest betweenness centrality of the whole

network (CB = 0.04). Within a third subgroup of five features referring to achievement

and grades (light green color), the features of people getting a better grade than you

(CB = 0.02) and people who get a better grade than you with less effort (CB = 0.02)


showed higher betweenness centrality scores than the remaining features. Further,

another community with six features contained physical aspects (e.g., causes stomach

age; light grey color), while two other communities contained the features related to

something negative (negative, bad, negative feeling; white color), and related to

whether or not having something (e.g., refers to what you do not have, refers to what

you also would like to have; blue color), respectively. One final community entailed

two features referring to tensing up and anger (pink color).

Finally, the mean network density of the German network was D = 0.15 and

thus the highest of all three networks. The size of the largest component was also

higher compared to the Spanish and US networks (27 vertices, 52.94 %). A total of

seven communities were extracted: Similar to the Spanish network, all features with

the greatest betweenness centrality were located in a main community comprising four

subgroups: three of the features, people who get a better grade than you with less effort

(CB = 0.04), people with nice clothes (CB = 0.03), and people with a good job (CB =

0.03), were located within a subgroup of eleven features referring to elicitors and

achievement (as represented by a lilac color in Figure 3).

Another three of the features with the highest betweenness centrality were

located within a subgroup of six features referring mainly to elicitors and to whether

or not having something (red color): the features of people with a nice home (CB =

0.06), people with a state-of-the-art mobile phone (CB = 0.02) and referring to what

someone else has (CB = 0.02). The feature of people with a nice home had the strongest

position within the network, with more nodes (i.e., features) linked to it than any other

feature.

Another subgroup of three features was organized around the feature of people

with lots of money (CB = 0.03) and included features referring to possessions (blue


color). A final subgroup of six features referred to interpersonal relationships and

social aspects (e.g., people with a happy relationship, successful people; yellow color).

With respect to the other communities, one with three features referred to the negative

character of Neid (negative, bad, negative feeling; white color), whereas another

community with two features included emotion and feeling (green color), and the last

community entailed two physical symptoms: racing heart and feeling hot (grey color).

Centrality ratings. Based on a median split of the ratings (Fehr, 1988), those

features of the English envy with ratings higher than 6.23 were considered central of

envy (see Table 2). This procedure yielded 26 central features. The feature “refers to

a comparison with others” was judged to be the most typical feature of the category,

followed by “refers to what you also would like to have,” “feeling jealous,” and

“feeling.” All of these features received ratings higher than 8 points, as compared to

“good” and “causes stomach ache” which were rated as the least typical features with

ratings lower than 3 points.

With respect to envidia, those features with ratings higher than 5.99 were

considered central of envidia. This procedure yielded 28 central features, whereby only

two features received ratings higher than 8 points: “a comparison with others” and

“what you also would like to have.” As happened to be the case with envy, the features

of “good” and “causes stomach ache” received ratings lower than 3 points. This was

also true for the feature of “causes feeling hot.”

Finally, the median split for the ratings of the German Neid was 6.04, and thus

25 features were regarded as being central. The features with ratings higher than 8

points included “refers to a comparison with others,” “refers to what you also would

like to have,” and “feeling.” On the other hand, “causes stomach ache,” “causes feeling

hot,” and “good” were rated as being the least typical features.


Prototypicality of central and peripheral features. To further analyze how

the features of the main community of each network related to one another, in a last

step we identified those features extracted via network analyses which had been

identified as being central vs. peripheral of envy or its translation equivalents and

subjected them to one-way ANOVAs. One-factorial ANOVAs revealed that the

participants of all three countries did not differ with respect to the ratings given to the

central features of successful people, people with lots of luck, and people getting a

better grade than you (all Fs<1), nor to the features of people with a better appearance,

F(2, 401) = 2.24, ns, people with a good job, F(2, 401) = 1.65, ns, people with a nice

figure, F(2, 401) = 1.53, ns, people with lots of money, F(2, 401) = 2.26, ns, and better

grades than you with less effort, F(2, 401) = 2.05, ns. A marginal significant difference

was found for the feature of achieving something with great ease what doesn’t come

as easy to you, F(2, 401) = 2.49, p = .08, with post-hoc comparisons revealing that

Spanish participants considered this feature as marginally less prototypical than US

participants (see Table 3).

With regards to the peripheral features, no differences were found for people

with a happy relationship, people who are given a new car, people who are popular,

people with nice clothes, people getting a better grade than you, all Fs<1, nor people

with lots of friends F(2, 401) = 1.11, ns, or smart people F(2, 401) = 1.78, ns. In

contrast, US participants gave higher ratings for the feature of people with a nice home

than Spanish and German participants, F(2, 401) = 3.77, p = .02. Importantly, this was

the only node with a higher betweenness centrality in all three networks. US

participants also scored higher than Spanish participants on the feature of people with

a special talent such as singing well, F(2, 401) = 3.36, p = .04.


Differences were also found in the ratings of people who have a big and close

family, F(2, 401) = 4.34, p = .01, with Spanish participants scoring higher than US

participants, as well as with respect to people with more tasty food, F(2, 401) = 2.51,

p = .08, where German participants gave higher ratings than US participants. Finally,

Spanish participants considered the feature of people with a state-of-the-art mobile

phone, F(2, 401) = 4.93, p = .01, as more prototypical than German participants. Thus,

whereas the central features of the main group of features of the everyday concept of

envy and its translation equivalents did not differ between countries, peripheral

features of envy (or envidia or Neid) received different ratings of prototypicality.

General Discussion

Envy is considered to be one of the seven deadly sins according to the Catholic

church and has been reported to be the second sin a sample of members of various

churches personally most struggled with (Capps & Haupt, 2011). Still, little research

has specifically analyzed the content and internal structure of envy. Thus, in the

present research we systematically differentiated between envy in three Western

countries by mapping their internal structures. The present research broadens our

knowledge about envy in several relevant ways. Indeed, the findings of the present

research are expected to advance the theoretical and empirical literature and thus to

allow for developing new measures, but also for refining methodological procedures,

including those targeting the assessment, induction, and regulation of envy.

First of all, we address the lay conceptions of envy instead of relying on current

research concepts of envy. Uncovering the everyday concept of envy indeed adds to

research on envy by unveiling the internal structure of envy, envidia, and Neid,

respectively, and by highlighting the importance of its underlying features (i.e.,

differentiating core vs. peripheral features), thus contributing to the definition and


operationalization of envy. In Study 1, envy and its translation equivalents of envidia

and Neid were found to be defined as referring to what you do not have and to what

someone else has, thus confirming the importance given in previous research to social

comparison processes (Miceli & Castelfranchi, 2007). In line with the often-quoted

definition by Parrott and Smith (1993) stating that “envy occurs when a person lacks

another's superior quality, achievement, or possession and either desires it or wishes

that the other lacked it” (p. 906), participants also described envy as being elicited by

money, academic success, talent, character traits, and travelling.

In Study 2, we mapped the internal structure of envy by determining the degree

to which each feature is central or typical of the everyday concepts of envy, envidia,

and Neid. Applying the novel methodological approach of network analysis, we

studied the structure of interconnections in the respective networks uncovering the

relations between the features and assessing the relevance of single features (i.e.,

nodes) within each of the networks of envy, envidia, and Neid. The network analyses

revealed that these networks differed with respect to the sets of communities and

underlying connections. Whereas envy, envidia, and Neid shared a group of central

features, they also differed with respect to the peripheral features. Thus, the network

analyses indicate interesting cross-cultural variations in the internal structure of envy,

envidia, and Neid, including variations in network properties, which have been largely

neglected in past research on envy.

One prominent approach which can accommodate these cross-cultural

differences (e.g., the differences between the US and Spain with regards to

achievement, having a nice home or talent) relates to considering the value orientations

of vertical individualism and horizontal collectivism (e.g., Singelis, Triandis, Bhawuk,

& Gelfand, 1995). Indeed, research by Rodriguez Mosquera et al. (2010) found that


European Americans scored higher on vertical individualism and valued achievement

more than the Spanish did. The Spanish, on their part, scored higher on horizontal

collectivism and valued cooperation and connectedness more than the European

Americans. This value focused approach is even more advisable if we take into account

that the present research combined different cultural value orientations. According to

the World Values Survey (Inglehart et al., 2014), the US are located in the English-

speaking cluster and are characterized by higher self-expression values than Spain as

well as more traditional values than both Germany (located in the “Protestant Europe”

cluster) and Spain (located in the Catholic Europe cluster). Respecting these

dimensions might aid in providing valuable insights to address the differences of the

internal structures of envy and its translation equivalents given that the US, for

example, scored higher on features related to traditional values (e.g., home, family,

and talent).

Second, there has been ample disagreement on the conceptualization of envy

and whether or not envy is best represented as one construct or as two types of envy,

namely benign envy vs. malicious envy. Thus, we also asked whether benign and

malicious envy would be differentiated when it comes to the everyday concept of envy

and its translation equivalents of envidia and Neid. Though we combined a language

which differentiates between a benign and malicious form of envy (i.e., German;

Lange & Crusius, 2015) and two languages that do not (i.e., Spanish and English), this

difference was generated by the participants of one of the countries only (i.e., Spain,

Study 1). Moreover, the differentiation between a positive and a negative form of envy

did not reach significance in Study 2 in neither of the three countries, and it received

the lowest rating of prototypicality in each of the networks. Interestingly, the network

analyses revealed for all of the three countries that the feature characterizing envy as


good was not related to any other feature but was isolated. Thus, the present data allow

us to determine whether or not laypersons think of envy as two components rather than

as one dimension (Falcon, 2015). Our results suggest that the everyday concept of envy

is mainly composed of features related to malicious envy, providing empirical support

for Cohen-Charash and Larson’s (2017) assumption that envy should be regarded as a

unitary construct. Given these findings, we support van de Ven's (2016) suggestion to

encourage researchers to clarify whether the subtypes of envy (i.e., benign vs.

malicious) or the higher-order general envy are targeted in future research.

Furthermore, future research may for example restrict the distinction between

“benign” and “malicious” envy to research focusing on the motivational dynamics of

envy, where benign envy has been found to motivate self-improvement and malicious

envy to motivate harming the envied other (van de Ven et al., 2009).

Third, the present research also takes up Cohen-Charash and Larson’s (2017)

suggestion to address whether or not “various words for envy represent culture-

specific or universal emotions” (p. 176). The present studies, however, do not only

inform research on envy, but also emotion research in general. Indeed, there has been

ample debate about the nature of emotion categories (e.g., Feldman Barrett, Khan, Dy,

& Brooks, 2018), and whether or not the translation of emotion words allows for

capturing the same features in different languages. Indeed, we advance research on

categories of emotion by suggesting that words commonly translated as envy in two

other Western languages do share some constitutive features with the English envy,

whereas we also observed differences in the way people from Spain and Germany

conceive of envidia and Neid. Thus, standard translation–back translation tests, which

often underlie cross-cultural comparison of emotion categories, might not properly

asses the constitutive features of some categories of emotions. Here, discovery-based


approaches are expected to shed more light into the internal structure of different

everyday emotion concepts and thus help to disentangle whether or not emotion

concepts can be defined in terms of necessary and sufficient characteristics or, to the

contrary, might be characterized by fuzzy borders between categories.

Fourth, the present research also advances envy research by assessing how

envy relates to other feelings. Consistent with previous research pointing to the

relationship of envy and anger, the participants of all three countries reported feeling

anger when experiencing envy. However, consistent with earlier research on cultures

of honor (Pedersen, Forster, & McCullough, 2014), anger was mentioned more

frequently and was also more prototypical in Spain. Next to anger, one subgroup of

the Spanish and US network, respectively, included sadness among their features. As

the role of sadness has not been the focus of previous research on envy, our findings

endorse the need of comparing envy with sadness, along with other everyday emotion

concepts. Here, a prototype approach might also be helpful in differentiating between

envy and resentment (van de Ven, Zeelenberg, & Pieters, 2012), admiration (van de

Ven et al., 2011; van de Ven et al., 2012), or so-called “problematic social emotions”

such as guilt and shame (Tangney & Salovey, 1999) by assessing the extent to which

their features are unique or do overlap with those of envy.

Finally, despite going nameless in some countries (e.g., Spain), the meaning of

Schadenfreude, pleasure at the misfortune of others (Russell, 1991a, 1991b; van Dijk

& Ouwerkerk, 2014), has been incorporated into our everyday knowledge and has

often been related to envy. Scholars disagree, however, on the role of envy in

Schadenfreude. It has been suggested, for example, that Schadenfreude does not

constitute a different emotion, but is subsumed as a consequence or part of envy

(Quintanilla & de Lopez, 2013). Some research also found that envy had a direct and


unique impact on Schadenfreude but only when malicious envy was considered;

benign envy was not associated with more intense Schadenfreude (van de Ven et al.,

2015).

Most recently, it has also been suggested that Schadenfreude can be promoted

via undeserved misfortunes; in these cases, the feelings of resentment lead to a re-

construction of an undeserved misfortune into a deserved misfortune (Berndsen,

Tiggemann, & Chapman, 2017). Given that much research is needed in order to

disentangle the relationship between envy and Schadenfreude, a prototype approach

might aid in delineating the features of both envy and Schadenfreude, as well as

comparing their internal structures. Moreover, research on envy could target a

language with different words for the positive and negative type of envy in order to

compare their internal structures, as well as to clarify the extent to which envy and

Schadenfreude comprise different emotion concepts or are simply parts of the same

emotion concept.

Future Directions

The present research adds to the literature on an emotion which has been

suggested to be pan-human and present in every culture (Foster et al., 1972) by

mapping its internal structure in three different countries. Though to the best of our

knowledge, network analyses have not yet been used in research on emotion concepts,

the present research points to the relevance of these analyses for unraveling the internal

structure of everyday emotion concepts, and thus for assessing the constitutive features

of each emotion concept. Indeed, we suggest that network analyses are a suitable and

relevant approach in emotion research allowing to analyze the overall structure of a

specific emotion concept, the communities that constitute each network, the

relationship of its nodes, and the relevance of each of these nodes within the network.


Thus, network analyses bear the potential to enhance our understanding and

knowledge about everyday emotion concepts. In this regard, future research might

benefit from using network analyses and combining other techniques from network

analysis, such as core/periphery analysis, to assess which features are located within

the core of each concept as opposed to being part of the periphery, or degree centrality

to analyze the number of nodes that are adjacent to a given node (Freeman, 1979) and

thus the number of features one feature relates to.

By applying network analyses to the everyday emotion concept of envy, we

contribute to a better understanding of the features and their relationships within envy

and its translation equivalents of envidia and Neid. Indeed, the present research

suggests that despite its variability in the internal structure, envy, envidia, and Neid

share a core of features and thus point to a common set of constitutive characteristics

and elicitors. These findings might inform emotion research by pointing to

characteristics and elicitors that can evoke envy in different countries and may

therefore serve to substantiate future research on envy, such as designing studies that

target the elicitation and reduction of envy. In this regard, recent work by Schweiger

Gallo et al. (2017) has laid the foundation for research on the internal structure of an

emotion and its subsequent regulation by first analyzing the content universe of the

emotion concept of grima (i.e., the aversive experience evoked when hearing for

example a scratch on a board or plate) and thereafter addressing its regulation via

implementation intentions.

In the same vein, as the present research allows for disentangling the features

of envy and its translation equivalents of envidia and Neid, the generated knowledge

may improve the induction of the emotion in future studies by focusing, for example,

on stimuli related to successful people, people with a better appearance or people with


lots of money, all of which were identified as central features of the everyday emotion

concept of envy and its translation equivalents of envidia and Neid. Moreover, research

on the regulation of emotions might also profit from the obtained insights as they may

help to target the down-regulation of features eliciting envy (e.g., travelling to a place

where one also wants to travel), but also the up-regulation of features of envy, envidia,

or Neid, such as when an adaptive consequence of envy is targeted (e.g., an improved

performance leading to higher grades). Interestingly, emotion regulation strategies

could differentially focus on central or peripheral features depending on the targeted

intensity of the emotion.

One might argue that the samples of the present two studies are not fully

representative because they are restricted to students. However, our research is in line

with research on emotion concepts, also recurring mainly to student samples. One

possible reason for this common restriction is that people of different ages and

professional backgrounds can be expected to share the everyday concept of envy with

that of students. Notwithstanding, more research is necessary to compare everyday

conceptions of envy and other emotion concepts both on a cross-cultural level and

within cultures. Thus, further research on envy might also focus on non-Western

cultures rather than only on Western cultures, as our studies did.

Moreover, the comparison of other emotion concepts such as disgust and its

translation equivalents in other countries might also advance our knowledge on the

conceptual and experiential differences of the internal structure of emotion concepts

and even shed light on the question of whether or not direct translations (and back-

translations) adequately assess emotion concepts and their assumed conceptual

equivalence.


Workplace Envy

An intriguing field of study is envy at the workplace. Indeed, our results are

relevant to the work environment, where little research on envy has been done so far

(Moran & Schweitzer, 2008) and where “its work-related consequences has been

surprisingly neglected” (Duffy, Scott, Shaw, Tepper, & Aquino, 2012, p. 643). This is

the more surprising, as workplace envy and its consequences are widespread in the

organizational context: One reason for this is that envy often results from social

comparisons, such as comparisons among job seekers in the job market (Dineen,

Duffy, Henle, & Lee, 2017). Employees also compete with each other about limited

resources and perceived unequal benefits at the workplace (Duffy, Shaw, &

Schaubroeck, 2008) .Workplace envy can also be evoked by coveted resources and

benefits received by others such as high-end expensive office furniture, employee

status, and financial advantages, including stock options, bonuses, and job positions

(Tai et al., 2012; Menon & Thompson, 2010).

Studies on the consequences of workplace envy revealed mixed results. On the

one hand, envy leads to negative outcomes: High levels of envy and of perceived

unfairness have been found to lead to higher levels of sabotaging behavior toward the

envied person (Cohen-Charash & Mueller, 2007) and to harm performance at the

organizational level (Duffy & Shaw, 2000). Further, workplace envy is associated with

a decrease of trust and higher levels of social undermining within the team (Dunn &

Schweitzer, 2004; Duffy et al., 2012); it leads to negative effects on team work as

individuals are less likely to share relevant information with the envied team member

(Fischer, Kastenmüller, Frey, & Peus, 2009).

On the other hand, workplace envy may be associated with positive outcomes:

Constructive envy can enhance individual performance in general (van de Ven et al.,


2011) and turn into a motivator at work (Kets de Vries, 1992; Cohen-Charash, 2009),

especially if an individual admires the envied person. In summary, research about the

effects of workplace envy reveals an unclear pattern of the behavioral consequences

of envy. In our opinion, attempting to shed more light into the consequences of

workplace envy and its action tendencies and underlying processes, requires to first

analyze the content and structure of workplace envy.

50 Tables and Figures

Tables and Figures

Table 1

Percentage of Constitutive Features of Envy, Envidia, and Neid Mentioned by at Least

10% of the Participants (Study 1)

Features Frequency of mentions for

Envy Envidia Neid

Definition

Jealousy 54%

What someone else has 49% 16% 36%

Wish 42% 33%

Wanting something 33%

Not having 13% 17% 21%

Another person who has something,

you don’t

10% 26%

Refers to what you also would like to

have

22% 60%

Feeling 56% 18%

Not begrudging 41%

Refers to another person 21% 35%

Negative 23%

Comparison with others 19%

Owning something 17%

Emotion 17%

Refers to something 14%

Refers to something material 13%

Good 12%

What you would like to be able to do 12%


Table 1 (continued)

Percentage of Constitutive Features of Envy, Envidia, and Neid Mentioned by

at Least 10% of the Participants (Study 1)

Bad 10%

Negative feeling 13%

Physical

reactions

Tensing up 21% 18%

Changes in temperature 21% 10%

Anger 17% 37% 10%

Symptoms in the stomach 12% 25%

Sadness 12%

Increased heart rate 11% 16%

Changes in the face 19% 16%

Nervousness 12%

Elicitors

Money 31% 31% 16%

Academic success 31% 11% 18%

Physical appearance 26% 27%

Relationships 23% 21%

Talent 21% 19% 26%

Success 17%

Character traits 15% 25% 16%

Travelling 12% 25% 25%

Friendship 12% 10%

Clothes and accessories 10% 18%

Intelligence 10%


Table 1 (continued)

Percentage of Constitutive Features of Envy, Envidia, and Neid Mentioned by

at Least 10% of the Participants (Study 1)

Social skills 19%

Cars 19%

Having a nice figure 15%

Better grades with less effort 13%

Achieving something with less effort 17% 12%

Home 12%

Technology 11%

Family 11%

Job 11%

Luck 11% 10%

Time 10%

Food 10%


Table 2

Mean Centrality Ratings of the Features of Envy, Envidia, and Neid Clustered by

Prototypicality (Study 2)

Features Concept

Envy Envidia Neid

M (SD) M (SD) M (SD)

Comparison with others 8.53 (2.20) 8.34 (2.43) 9.08 (1.68)

Also would like to have 8.48 (1.71) 8.15 (2.24) 8.54 (2.00)

Feeling jealous 8.45 (2.07) 6.84 (3.30) 5.44 (3.18)

Feeling 8.41 (2.03) 7.53 (2.72) 8.03 (2.41)

What you do not have 8.33 (1.96) 7.22 (2.92) 6.50 (3.18)

Emotion 8.28 (2.20) 5.85 (3.30) 7.69 (2.64)

What someone else has 8.02 (1.92) 7.88 (2.29) 7.16 (2.39)

Negative 7.98 (2.20) 7.53 (2.64) 7.19 (2.65)

Another has something, you don’t 7.97 (2.12) 7.65 (2.69) 7.98 (2.14)

Negative feeling 7.93 (2.31) 7.42 (2.64) 7.63 (2.63)

Wanting something 7.84 (2.32) 7.43 (2.52) 7.91 (2.16)

Achieve with great ease, comes not as easy to you 7.72 (2.35) 7.05 (2.71) 7.23 (2.47)

Would like to be able to do 7.64 (1.98) 7.05 (2.74) 6.37 (2.83)

Something 7.48 (2.54) 6.78 (2.82) 7.98 (2.41)

Better grade than you with less effort 7.12 (2.52) 6.70 (2.77) 6.44 (2.74)

People with a nice figure 7.06 (2.68) 6.47 (2.99) 6.64 (2.77)

People with lots of money 7.00 (2.58) 6.52 (3.13) 6.22 (2.94)

Bad 6.96 (2.42) 7.78 (2.36) 6.31 (2.86)

People with a better appearance 6.93 (2.46) 6.23 (2.95) 6.46 (2.70)

Another person 6.92 (2.53) 7.61 (2.63) 7.23 (2.76)

Wish 6.64 (2.43) 7.34 (2.59) 7.80 (2.24)


Table 2 (continued)

Mean Centrality Ratings of the Features of Envy, Envidia, and Neid Clustered

by Prototypicality (Study 2)

Sadness 6.63 (2.47) 6.06 (2.81) 6.13 (2.66)

People with lots of luck 6.43 (2.93) 6.32 (3.17) 6.65 (2.74)

Successful people 6.39 (2.57) 6.33 (3.07) 6.29 (2.76)

People with a good job 6.38 (2.73) 6.68 (2.94) 6.06 (2.73)

People getting a better grade than you 6.38 (2.57) 6.19 (3.04) 5.89 (2.82)

Smart people 6.17 (2.51) 5.56 (2.97) 5.75 (2.52)

Cannot go out to have fun, but your friends can 6.11 (2.78) 5.28 (2.96) 4.63 (2.94)

People with a nice home 5.96 (2.56) 5.18 (3.09) 5.06 (2.66)

Anger 5.93 (2.80) 6.89 (2.68) 5.41 (2.72)

Tensing up 5.90 (2.78) 7.50 (2.49) 7.05 (2.59)

People who are popular 5.85 (2.84) 5.67 (3.16) 5.99 (2.94)

Travels to a place where I also wanted to travel 5.84 (2.61) 5.70 (3.05) 5.85 (2.93)

People with lots of friends 5.48 (2.73) 5.01 (3.06) 5.01 (2.95)

People who are given a new car 5.47 (2.94) 5.11 (3.11) 4.95 (3.12)

People with a special talent such as singing well 5.37 (2.66) 4.61 (3.00) 5.33 (2.70)

Something material 5.35 (2.33) 5.53 (2.93) 4.58 (2.81)

People with nice clothes 5.34 (2.45) 4.95 (3.05) 4.97 (2.74)

People with a happy relationship 5.33 (3.03) 4.97 (3.34) 5.18 (3.06)

People who have a big and close family 5.05 (2.79) 4.05 (3.01) 4.73 (2.93)

Ugly face 5.04 (2.97) 6.30 (2.56) 4.47 (2.81)

Owning something 4.74 (2.88) 5.92 (3.00) 5.27 (2.91)

Nervousness 4.37 (2.98) 5.47 (2.96) 4.35 (2.79)

Feeling hot 4.37 (2.89) 2.35 (2.65) 2.78 (2.48)

People with a state-of-the-art mobile phone 4.20 (2.72) 4.77 (3.31) 3.65 (2.84)


Table 2 (continued)

Mean Centrality Ratings of the Features of Envy, Envidia, and Neid Clustered

by Prototypicality (Study 2)

Not begrudging someone something 4.04 (2.62) 3.18 (2.91) 5.41 (3.35)

Racing heart 4.02 (2.72) 3.63 (3.12) 3.51 (2.82)

People with willpower 3.82 (2.64) 4.30 (3.16) 4.58 (2.75)

People with more tasty food 3.72 (2.83) 4.06 (3.08) 4.58 (3.16)

Stomach ache 2.98 (2.71) 2.46 (2.52) 2.96 (2.77)

Good 2.34 (1.99) 2.84 (2.50) 2.59 (2.24)


Tab

le 3

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pari

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of

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(co

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toty

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61 Research Paper II

Research Paper II

Transactional Leadership and Implementation Intentions: A Team

Regulation Perspective on Performance in Hidden Profiles

Lucia A. Görke1, 2, J. Lukas Thürmer2, 3, 4, Florian Kunze2, 4, Peter M. Gollwitzer1, 5



3 Department of Psychology, Paris Lodron University Salzburg, Austria

4 Department of Politics and Public Administration, University of Konstanz,

Germany


62 Abstract

Abstract

Teams can make better decisions, when they pool and integrate their initially unshared

information, but seldom do they use this potential. In this research, we investigate how

external and internal team regulation strategies help teams to perform effectively in a

hidden profile task. In our experiment, teams (N = 99) either received implementation

intentions or not and were assigned a leader or not, and then worked on a hidden profile

task where they had to share their information to identify the best decision alternative.

Results showed that both transactional leadership (i.e., external team regulation) and

implementation intentions (i.e., internal team regulation), improved the quality of team

decisions in hidden profiles. Teams with leaders moreover discussed more of the

available information on hidden profiles including information on the correct decision

alternative. We discuss how team regulation can improve team performance.

Keywords: decision making; self-regulation; team regulation; implementation

intentions; hidden-profile paradigm; team performance; transactional leadership;

leadership

63 Introduction

Introduction

In today's fast-changing and complex world, organizations count more and

more on team-work. During the last twenty years the amount of teamwork in

organizations has increased by 50 percent (Cross, Rebele, & Grant, 2016). This implies

that teams constantly need to adapt to the difficulties of the unexpected to achieve their

goals effectively (Kozlowski & Ilgen, 2006). What helps teams to adapt to difficulties

is self-regulation. Following James' (1890), we understand self-regulation as a tool that

helps individuals to handle difficulties such as obstacles or temptations that are

standing in the way of accomplishing goals and perform effectively. In the same vein,

the cycle to handle difficulties to accomplish goals remains the same for individuals

and teams. Therefore, similar to individual processes of self-regulation we use the

word team regulation to describe regulation processes on a team level (Peterson

& Behfar, 2005).

Traditionally, goal directed team behavior is regulated through external

leadership (Peterson & Behfar, 2005). Leaders facilitate the regulation of team

behavior by monitoring team action and progress towards a goal (Kozlowski, Bell, &

Blawath, 2012; Kozlowski & Ilgen, 2006). If we think of leadership as a team

regulation competence, we have a transactional leadership style in mind (Bass, 1985;

Burns, 1978). Transactional leadership is based on an exchange relationship between

leaders and followers (Bass, 1985, 1999). Leaders set goals and expectations for

followers and provide feedback to support them during the process of goal

achievement.

At the same time there exists a trend towards autonomous teams without a

designated leader (van Mierlo, Rutte, Seinen, & Kompier, 2001). The idea of

autonomous teams is that they are authorized and responsible for the majority of

64 Introduction

decisions at the workplace (Rao, Thornberry, & Weintraub, 1987). They often

supervise themselves and cannot rely on the external support of a leader (Rao et al.,

1987). How can team regulation help autonomous teams to perform effectively?

Wieber, Thürmer, and Gollwitzer (2012) argued that implementation intentions are a

successful regulation strategy to overcome obstacles in goal attainment and for

effective team performance. Implementation intentions, also known as if-then plans,

create an option for teams to close the behavior gap between having strong intentions

and actually achieving a goal (Gollwitzer, 1993, 1999, 2014).

Teams can thus be regulated externally (Peterson & Behfar, 2005) by

transactional leaders or regulate their behavior internally by applying collective team

regulation strategies such as implementation intentions (Gollwitzer, 1993, 1999, 2014)

to perform effectively. If we combine transactional leadership (external regulation)

with implementation intentions (internal regulation) in an integrated model teams

might even perform more effectively. Before we develop such a theoretical model of

transactional leadership and implementation intentions, we need to explain what we

understand by effective team performance.

When Do Teams Perform Effectively?

One hope that fuels the use of teams is that teams collectively achieve

something that exceeds the sum of achievements of individual team members working

alone , that is, accomplish synergy (Larson, 2010). The prototypical decision situation

that allows teams to accomplish synergy is called a Hidden Profile (HP) (Stasser,

1988). HPs are decision situations where team members have two types of information

available before they begin a team discussion: unshared information (information that

is only available to one team member) and shared information (information that is

available to all team members) (Stasser, 1988; Stasser & Titus, 1985). Importantly, the

65 Introduction

shared information points to a suboptimal decision alternative, leading each individual

team member to form a suboptimal decision preference prior to the team discussion.

The team goal is to find collectively the correct decision alternative during the

discussion. An example for a HP alternative is to find the best job candidate among

candidate A, B, and C. The candidate with the best distribution of advantages and

disadvantages in the profile is the best HP decision alternative. Teams have the

potential to accomplish synergy if they uncover the “hidden” best decision alternative

by jointly sharing and integrating the initially unshared information (Reimer, Reimer,

& Czienskowski, 2010; van Swol, 2009). Paradoxically, experimental studies revealed

that teams consistently fail to solve HP tasks, and only show weak synergy (Lu et al.,

2012; Mesmer-Magnus & DeChurch, 2009; Reimer, Reimer, & Czienskowski, 2010).

The puzzle here is why teams fail to accomplish synergy in HP decision tasks,

despite the fact that they have the potential to identify the correct alternative.

Theoretical models on team synergy suggest that bias (Stasser & Titus, 1985) and

intensity (Schulz-Hardt et al., 2006) are the key factors for the discussion and

processing of information for teams to accomplish synergy in HP situations. A bias

occurs if the mentioned and repeated information during the team discussion does not

reflect the whole information that is available to the team members (Schulz-Hardt

& Mojzisch, 2012). The team discussion intensity is sufficient when they spend

enough time to discuss, repeat and reflect the available information in the HP task

(Schulz-Hardt et al., 2006; Thürmer, Wieber, Schultze, & Schulz-Hardt, 2018).

Empirical studies revealed that on average a stronger team discussion bias is related to

a lower decision quality of HP situations (Lu et al., 2012). For example, teams with a

given time limit for discussion showed a lower discussion intensity, and lower solution

rates of HPs (Campbell & Stasser, 2006).

66 Introduction

This study examines the question of how implementation intentions and

transactional leaders help solve HPs. We rely on theories on leadership team regulation

(Peterson & Behfar, 2005; Vancouver, 2000), transactional leadership (Bass, 1985,

1990; Burke et al., 2006a), self-regulation with implementation intentions (Gollwitzer,

1993, 1999, 2014), and team decision making in HPs (Lu et al., 2012) to develop

hypotheses about external (transactional leadership) and internal (implementation

intentions) team regulation strategy effects on team performance, and we explore our

hypotheses in a laboratory experimental team study. We suggest that transactional

leadership and implementation intentions both improve team decision quality in HPs.

We propose that both predictors increase the team discussion intensity and reduce a

potential team discussion bias, and thereby improve team performance in HP

situations. We moreover explore potential interactive effects of both interventions.

A Team Regulation Perspective on Effective Performance

We integrate transactional leadership (Bass, 1985, 1990; Burke et al., 2006a;

Burns, 1978) and implementation intentions (Gollwitzer, 2014; Thürmer et al., 2015b)

jointly in a theoretical model to demonstrate an alternative way to improve team

performance in HPs. Prior research by Thürmer et al. (2015b) has taken a first step

towards applying a self-regulation approach to HPs. Teams formed specific if-then

plans or received control instructions to take unshared information into consideration

and then worked on a HP task (Thürmer et al., 2015a).

In line with our reasoning about internal team regulation, teams with if-then

plans solved significantly more HP cases than did teams with control instructions

(Thürmer et al., 2015a). In the current research, we compare if-then planning to the

traditional external means of team regulation, namely transactional leadership. We

expand the knowledge of how obstacles for HP team decision quality such as a

67 Introduction

discussion bias and an insufficient discussion intensity (Schulz-Hardt & Mojzisch,

2012) can be addressed by transactional leaders and implementation intentions. In

comparison, we explore which intervention (transactional leadership vs.

implementation intentions) can be more helpful to handle HP obstacles, which has

been neglected so far in research on team performance in HPs (e.g., Schulz-Hardt et

al., 2006). Thus, our dynamic system approach enables us to compare external and

internal team regulation strategies (transactional leadership vs. implementation

intentions), and at the same time we can explore how both strategies interact with each

other.

Obstacles to Effective Team Performance

Numerous studies on HPs (for a meta-analysis see Reimer et al., 2010) have

linked the failure of teams to solve HPs solely to a discussion bias. More recent

research suggests that effective team performance in HPs requires an unbiased

discussion and a sufficient discussion intensity (Schulz-Hardt et al., 2006; Schulz-

Hardt & Mojzisch, 2012). A discussion is biased when team members mention or

repeat mainly the shared information that is available to every team member prior to

the team discussion (bias in favor of shared information) (Stasser & Titus, 1985). This

bias is an obstacle to solve HPs because the shared information points to a suboptimal

decision alternative, leading each individual team member to form a suboptimal

decision preference. Teams prefer to discuss shared information, because it will be

recognized by other team members and socially validated, which promotes the mutual

appreciation among team members, and makes it more likely for them to mention and

repeat shared information during the discussion (Mojzisch & Schulz-Hardt, 2010).

A second discussion bias is the bias in favor of preference consistent

information (shared and unshared information) (Schulz-Hardt, Giersiepen, &

68 Introduction

Mojzisch, 2016). This bias is nearly similar to the discussion bias in favor of shared

information. Team decisions on the correct HP alternative are often biased by the

preferences of the team members prior to the decision. These preferences are biased in

favor if shared information (Faulmüller, Mojzisch, Kerschreiter, & Schulz-Hardt,

2012; Sohrab, Waller, & Kaplan, 2015). This bias is another obstacle for team

members because they have a stable preference for alternatives they favorized prior to

the team discussion (Dennis, 1996; Faulmüller et al., 2012). Taken together, these

kinds of biases relate to a lower HP decision quality on average (Schulz-Hardt et al.,

2006).

Besides a discussion bias, the discussion intensity of a team influences the team

performance in HPs. Prior studies revealed that teams with enough discussion time

repeated and recalled more of the critical unshared information of HP situations

(Campbell & Stasser, 2006). HP experiments often focus on the discussion of unshared

information (e.g., Winquist & Larson, 1998) and on information about the best

alternative (e.g., Hollingshead, 1996) because both types of information point to the

correct solution in HP situations. An obstacle that arises by an insufficient discussion

intensity is that teams usually are not aware of the relevance to discuss unshared

information and information about the best alternative, and therefore frequently fail to

solve the HP (Stasser & Titus, 1985). A sufficient team discussion intensity can help

teams to mention and repeat more information, which should add to a higher team

discussion rate of unshared information and of the correct alternative (Schulz-Hardt

& Mojzisch, 2012). Additionally, studies revealed that a large amount of information

creates a high cognitive load (van Swol, Savadori, & Sniezek, 2003), and team

members who wait to mention unshared information until the end of the discussion

69 Introduction

(Larson, Christensen, Franz, & Abbott, 1998) represent obstacles for teams to solve

HPs.

Improving Team Performance with Transactional Leadership and

Implementation Intentions

Based on our discussion, we assume that both transactional leadership and

implementation intentions can improve team discussions and decisions in HP

situations. We moreover explore potential additive and interactive effects of both

interventions.

Transactional leadership. Transactional leadership is defined by an exchange

between leader and member, and concentrates on three dimensions (Bass, 1990; Bass

& Avolio, 1997; Burns, 1979): contingent reward, active management-by-exception,

and passive management-by-exception. Contingent reward focuses on the amount of

transactions between leaders and their team members (Bass, 1999). The leader sets

goal expectations and if the team members meet them, he/she will reward them (Bass,

1999). Management-by-exception refers to feedback the leaders provide for their

followers meaning to intervene when team members are on the wrong way by

accomplishing team goals and correct them with constructive feedback or encourage

them if they are already on the right track (Bass, 1985, 1999).

Why do we understand transactional leadership in terms of a team regulation

approach? In the perspective of team regulation (Peterson & Behfar, 2005)

transactional leadership includes monitoring team behavior and providing feedback

about the progress of team members (Bass, 1990). Feedback helps team members to

become aware of their progress towards goal attainment (Carver & Scheier, 2002).

Setting goals and helping them to achieve them is part of a leader’s work to regulate

team behavior externally and thus improve team performance (Vancouver, 2000;

70 Introduction

Vancouver & Day, 2005). Likewise, transactional leadership is primarily focused on

reaching team goals efficiently, initiate structure, plan, and provide positive feedback

if the team makes progress (Burke et al., 2006b). Therefore, it might be interesting

how transactional leadership is an effective means to regulate team behavior in HP

tasks.

Previous research presents a mixed pattern of findings on the effects of

leadership styles in HP situations for teams (review by Sohrab et al., 2015). On the one

hand, leadership demonstrated to be helpful to address HP obstacles such as leaders

kept the team focus on unshared information and encouraged the team members to

mention and repeat more information (shared and unshared) (Larson & Egan, in press).

For instance, a study by Meyer et al. (2016) showed that the leader’s frequency of

asking questions and showing mimicry mediated the influence of participative

leadership on HP decision quality. Their findings (Meyer et al., 2016) were remarkably

similar to those of previous studies on leadership in the HP field (Larson, Christensen,

Franz, & Abbott, 1998; Larson, Foster-Fishman, & Franz, 1998). In comparison to

their team members participative leaders tend to ask more questions, the exchange of

shared and unshared information in the team is increasing, as well as the focus on

unshared information during the discussion (Larson, Christensen, Abbott, & Franz,

1996; Larson, Foster-Fishman et al., 1998). However, leaders were taking part actively

in the team discussion and decision process, what makes it challenging to assess team

performance independent of leader performance.

On the other hand, a directive leadership style implicated a negative impact on

team decision quality in HPs when the leader showed a strong opinion in favor of the

suboptimal alternative during the team discussion (Cruz, Henningsen, & Smith, 1999).

That is because teams have a tendency to follow the selected preference of the leader,

71 Introduction

when they decide on the best HP alternative (Cruz et al., 1999). The opposite occurs

when directive leaders argue in favor of the best alternative, by encouraging the

discussion of unshared information (Henningsen, Henningsen, Jakobsen, & Borton,

2004). In a recent study, Nevicka, Ten Velden, De Hoogh, and van Vianen (2011)

revealed that narcissistic leadership behavior decreases team decision quality by

hindering information exchange.

Leadership behavior may either work effectively for teams to share information

and solve HP problems (e.g., Larson, Foster-Fishman et al., 1998), or prevent teams

from exchanging relevant information (e.g., Henningsen et al., 2004). We are

interested in how teams might benefit from a transactional leadership style to address

HP obstacles effectively. Part of a transactional leadership style is feedback, which is

useful to remind team members to exchange more unshared information instead of

repeating already known items or relying on preference consistent information

(Mojzisch & Schulz-Hardt, 2006). Transactional leadership should improve the overall

HP team decision quality by encouraging the exchange of information on the critical

unshared alternative. Discussing more unshared information on the alternatives helps

teams to discuss more about the correct candidate and is thereby expected to reduce

discussion bias (Dennis, 1996; Stasser & Titus, 1985).

Further, rewarding behavior of the leader for the optimal team decision might

encourage the team to share more information overall, which addresses the obstacle of

a discussion bias in favor of preference consistent information (Schulz-Hardt

& Mojzisch, 2012; Stasser & Titus, 1985). Transactional leadership interventions

encourage team members to bring up more unshared and new information by getting

positive and negative feedback from leaders (Bass, 1990). As a result, transactional

72 Introduction

leaders remind team members to remain open for all HP profiles, which is expected to

debias measures towards shared information (Stasser & Titus, 1987, 2003).

Another HP obstacle is an insufficient team discussion intensity (Schulz-Hardt

& Mojzisch, 2012). Transactional leaders initiate structure and provide helpful

feedback for successful task solving (Bass, 1990). Therefore, teams with a

transactional leader are expected to discuss longer, exchange more information on HP

alternatives, and repeat more information on average during discussions. All three

components are essential for a sufficient team discussion intensity and lead teams to

discuss more on the correct alternative (Schulz-Hardt et al., 2006).

We expect that transactional leadership improves HP team decision quality. HP

team decision quality is in turn significantly and positively influenced by the team

discussion on the correct alternative. We assume that teams with a transactional leader

have a lower discussion bias of shared and preference-consistent information and a

higher discussion intensity than teams without a transactional leader (see Figure 1).

Implementation intentions. Individuals are facing obstacles if they want to

reach a goal for several reasons such as starting an action at all, stay on course when

goal achievement has started, and manage resources carefully (Gollwitzer, 2014). In

this context Gollwitzer (1993, 1999; 2014) pointed out the importance of managing

such obstacles by suggesting an effective type of plan to enhance goal striving:

furnishing goals with implementation intentions. Whereas goal intentions just define

a wished-for outcome, implementation intentions are specified as if-then plans. They

determine when, where, and how an individual attains a set goal (i.e., “If I encounter

situation S, then I will show response R!”) (Gollwitzer, 1993, 1999, 2014).

Implementation intentions are based on a process that enhances goal achievement. This

process relies on psychological mechanisms that apply to the if- and then part of a plan.

73 Introduction

Both parts are mentally linked (Gollwitzer, 1993). In the first instance a cognitive

activation of the situation specified in the if-part of the plan occurs, and becomes

accessible for the memory (e.g., Parks-Stamm, Gollwitzer, & Oettingen, 2007). In the

next step the response to the situation specified in the if part is connected to the

situation defined in the then-part (Webb & Sheeran, 2007). This strong mental link

(critical situation and goal directed response) is followed by strategic automaticity,

which means that the execution of the response to a critical link happens

autonomously, unconsciously, and immediately (Gollwitzer, 1999, 2014).

The high impact of furnishing goals with implementation intentions is

supported by empirical data in many areas (e.g., health, and consumer issues; for

review and meta analyses see Adriaanse et al., 2011; Bélanger-Gravel et al., 2013;

Gollwitzer, 2014; Gollwitzer & Sheeran, 2006). A meta-analysis on if-then plans

including more than 8,000 subjects revealed medium-to-large effect (d = 0.65)

(Gollwitzer & Sheeran, 2006), demonstrating that if-then plans help people to realize

goals and perform better. Recent studies show that if-then plans are a successful self-

regulation strategy to improve performance at the team level (Thürmer et al., 2015b;

Wieber, Thürmer, & Gollwitzer, 2015). When teams form implementation intentions,

they specify a collective if-then plan on when, where, and how they perform action to

achieve a certain team goal. Thürmer et al. (2015b) suggested a self-regulation

approach on HPs for teams to take unshared information into consideration. Teams

addressed HP obstacles during team goal attainment by asking teams to find the best

alternatives in a HP task and either assigned helpful if-then plans or control

instructions with similar content. Analyses showed that teams who did not use if-then

planning never found the correct alternative (0%) in the HP task, but teams with if-

then plans selected the correct alternative in 12% of the cases (Thürmer et al., 2015b).

74 Introduction

Regarding the underlying processes, Thürmer et al. (2015b) demonstrated that

if-then plans were beneficial to teams for three reasons: First, if-then plans can help

teams not to fall back into the same routines of behavior, not being distracted by a high

cognitive load, and take opportunities when they come up. A team discussion bias

often results from not discussing the critical unshared information (Stasser & Titus,

1985, 1987). Forming if-then plans support teams to consider the alternatives they did

not prefer prior to the team discussion and should shift their focus of discussion on

unshared information and thereby buffer a bias in favor of shared information (Stasser

& Titus, 1985). Thus, we suggest that if-then-plans diminish a team discussion bias in

favor of preference consistent information. Instead of relying on the routine of

discussing information which is consistent with the preferences of the individual team

members if-then plans help them to stay open and reconsider all alternatives (Thürmer

et al., 2015b).

Further, if-then plans help team members to take the opportunity to bring new

information up and instead of repeating already known information what prevents

them of being distracted by a high cognitive load of information (Gollwitzer, 1999;

Wieber et al., 2012). Implementation intentions promote the goal achievement of

teams by pondering on the advantages of the alternatives and bring critical information

immediately and efficient on the discussion table (Gollwitzer, 1993, 1999, 2014). This

helps teams to reconsider information against their initial preference and supports them

to bring up more unshared information (Thürmer et al., 2015b, 2015a).

Another obstacle for teams to increase the HP solution rate is a sufficient

discussion intensity (Schulz-Hardt & Mojzisch, 2012). We expect that if-then plans

support teams to mention and repeat more information on the alternatives and therefore

spend longer time to discuss the available information. As a result, if-then plans are

75 Introduction

Figure 4. Hidden profile team performance model

assumed to improve the team discussion intensity in HP situations. In turn, the team

discussion intensity enhances the HP decision quality (solving the HP).

In summary, we expect that collective implementation intentions improve

decision quality by increasing discussion intensity and a decreasing discussion bias.

Teams that discuss more information about the correct alternative solve the HP

effectively with a greater likelihood. Because discussing the correct alternative is

associated with a greater likelihood of successfully finding the correct alternative

(Schulz-Hardt et al., 2006).

Towards Integrating Transactional Leadership and Implementation Intentions

So far, we presented transactional leadership and implementation intentions in

a competitive and comparative perspective. We speculate further that there might exist

interactive effects of transactional leadership and implementation intentions. One

possibility would be that the joint effect of transactional leadership and

implementation intentions is significantly greater than the sum of the parts. Besides

furnishing their goals with implementation intentions teams are reminded externally

by a leader to provide new information and to reconsider other alternatives than the

initially preferred ones (Schulz-Hardt & Mojzisch, 2012).

Previous studies indicated that external reminders such as short text messages

can strengthen implementation intentions and the accomplishment of goals (e.g.,

Prestwich, Perugini & Hurling, 2010). There are two underlying processes responsible

76 Introduction

for this mutual reinforcement (Prestwich & Kellar, 2014). First, external reminders

lead to a higher salience of cues. Implementation intentions enable an increased access

to these cues and raise the awareness of the if-then plan (Prestwich & Kellar, 2014).

The leader in the function of an external reminder might trigger the intended action

and reinforce the automaticity of the if-then plan. Team members might then react

more immediately and effectively compared to forming implementation intentions

without an external reminder. Second, external reminders by leaders should make the

mental link between an anticipated obstacle and the goal directed response stronger

and in turn increase the effect of implementation intentions (Prestwich & Kellar, 2014)

on team decision quality in HPs. Transactional leadership and implementation

intentions might jointly contribute to the team goal of solving HPs effectively.

Alternatively, we presume that the joint effect of leadership and

implementation intentions might be significantly less than the sum of the individual

effects. The fact that transactional leaders use reminders as an external team regulation

tool to support the goal achievement process in HP situations might hinder the

automaticity of if-then plans (Wicaksono, Hendley, & Beale, 2017). Team members

might rely on the reminders of the leader instead of exhibiting features of automaticity

such as reconsidering information immediately and efficiently in the actual situation

(Gollwitzer, 1999; Thürmer et al., 2015b). This could contribute to an impairment of

implementation intentions through external reminders by a leader. Prestwich et al.

(2010) assumed a positive interaction among external reminders and implementation

intentions. In contrast, we argue that there might exist interactive effects among

transactional leadership and implementation intentions in both directions. In summary,

we explore how interactions between transactional leadership and implementation

intentions may increase or decrease the team performance in HPs.

77 Method

Method

Participants and Design

Participants were recruited as triads and triads were randomly assigned to a 2

(Leader: yes vs. no) × 2 (Implementation Intention: yes vs. no) between group design.

The required sample size for the main effects predicting HP decision quality was

determined with a power analysis (1-β = .85) using G*Power3 (Faul, Erdfelder, Lang,

& Buchner, 2007) and assuming a medium effect size (Funder et al., 2014). Two

hundred ninety-seven students (215 women, 82 men, mean age 22 years) at a German

university participated in return for course credit or 12.50 EUR and a 2.50 EUR bonus

for the selection of the best alternative (see below). We decided to use incentives to

increase the personal relevance of the team decision (see, e.g., Greitemeyer, Schulz-

Hardt, Brodbeck, & Frey, 2006).

Hidden Profile Task Overview

In each condition, teams made two decisions: The decisions were based on two

cases of a recruiting agency looking for either a new manager or a new professor

(adapted from Greitemeyer et al., 2006, see Table 1 for the distribution of the HP info).

In each case, each member individually received positive, negative, and neutral

information about three different job candidates (A, B, & C) and then indicated their

individual preference according to this information. Teams then assembled to discuss

the respective case and to jointly decide on the best candidate. Lastly, team members

again individually indicated their revised preference. In each team, one of the cases

was solvable based on the individual information (manifest profile) and one case

required the entire team to pool the available information (hidden profile). The order

of the cases as well as the type of case (MP vs. HP) was counterbalanced. Their task

78 Method

is to exchange their information to find the optimal alternative – the given information

is always true, but team members can have different sets of information.

In the control condition participants had to solve a manifest profile. In the

manifest profile condition, all information was shared among the participants. In the

HP condition, the advantages of the best alternative were not available for the team

members without pooling the information during a team discussion. Each participant

received different information about the candidate and only by pooling the information

during the team discussion the optimal alternative can be chosen. In the manifest

profile condition, most of the information in favor of the optimal candidate was shared

among the participants. Team members could easily identify the best alternative

individually before the team discussion started. After the team discussion, participants

wrote down their decision on a sheet of paper, which was placed on the discussion

table. Participants were not aware of the different information distributions of the

candidates during the experiment.

Manipulation of Transactional Leadership

In the Leadership condition, the confederate was trained to show verbal

behaviors associated with a transactional leadership style whereas in the Assistant

condition the confederate was trained to write the protocol and show no other

behaviors besides assisting in writing and editing protocol documents (for details see

following section). The confederate was blind to all hypotheses of the experiment.

We trained two confederates who had not previously interacted with

participants. Before the experiment started, our two confederate leaders were trained

to exhibit the transactional leadership style to show constantly the same behavior

pattern. During our pre-experimental training sessions, they learned how to show

behaviors associated with transactional leadership style. To train our confederates, we

79 Method

used a script which we developed by using the definition of transactional leadership

(Bass & Avolio, 1997). Examples of behavior patterns showed by the confederates

include the following verbal behavior: “I did an internship at BMW, being part of the

Chief Financial Officer’s staff, and after finishing my internship they offered me a

position as a working student. For my team, it was a top priority to accomplish set

goals.” (Leader selection during the introduction round).

Table 4.

Hidden and Manifest Profile Task: Distribution of Information

Best

Alternative

Second

Third

Hidden-profile cases

Shared information

Positive 0 3 6

Neutral 3 0 0

Negative 3 3 0

Unshared information

Positive 9 3 0

Neutral 0 6 3

Negative 0 0 6

Total pre-discussion information per participant

Positive 3 4 6

Neutral 3 2 1

Negative 3 3 2

Manifest profile case

Shared information

Positive 6 3 0

Neutral 0 0 3

Negative 0 3 3

Unshared Information

Positive 3 3 6

Neutral 3 6 0

Negative 3 0 3

Total pre-discussion information per participant

Positive 7 4 2

Neutral 1 2 3

Negative 1 3 4

During the team discussion, the leader gave positive and negative feedback

“Great, you mentioned a new information item, keep it up” or “That information was

already mentioned during the discussion, please focus on information that wasn’t

mentioned yet.” Teams who could solve the tasks were rewarded with an extra bonus

80 Method

by the leader (contingent reward). In the Assistant condition (no Leadership) the

selection was consistent with the leader selection except that the confederate said,

“During my internship it was an important factor to do a good assistance job.”

In contrast to the leader the assistant confederate mentioned after the selection

that she is responsible to write the protocol during the team discussion. In general, the

confederates were trained to avoid certain behaviors during the discussion such as

leading the team discussion into a certain direction, having candidate preferences, or

bringing up their own information during the discussion.

Manipulation of Implementation Intentions

Participants either formed implementation intentions or they formed goal

intentions in the control condition. At the beginning of the training every participant

defined the goal to select the optimal decision alternative (“I want to find the best

decision alternative”) while participants in the Implementation Intentions condition

further furnished the goal with the following if-then plans: (1) “When we start the team

discussion, then we remain open for all three alternatives, and we weigh all options,”

(2) “And if we repeat an already known information, then we will immediately name

a new piece of information,” and (3)”And if we take the decision sheet to note our

preferred alternative, then we will go over the advantages of the alternatives again.”

Participants in both conditions repeated the instructions in written form twice.

Procedure

Four participants arrived in the lab together for a team decision study, with one

participant actually being a trained confederate. After learning about the decision

cases, the instructor invited the students to introduce themselves and to share what

kind of experiences they attribute to effective decision making. Then, allegedly

depending on the individual contributions in the introduction round about effective

81 Method

team decision-making, one team member was selected to be either the leader of the

team (Leadership condition) or the assistant of the team (control condition/no

Leadership). The trained confederate showed behavior in line with the respective role

(leader or assistant) and mentioned respective expertise, thereby justifying that this

person was always selected (see Leadership manipulation above). The remaining team

consisted of the three actual participants with the confederate as an accompanying

team leader or team assistant.

After the leader selection, team participants received a training sheet with

implementation intentions or a control treatment (goal intentions; see below).

Following this training, teams worked on two consecutive decision cases. For each

decision case, participants individually received information about three decision

cases and made a preliminary decision about their preferred alternative. Teams then

discussed the respective decision case and came to a joint decision. After a team

discussion, participants again indicated their own preference and completed measures

of team cohesion, Cronbach’s 𝛼team = .74, adapted from Riordan and Weatherly

(1999), team identification, Cronbach’s 𝛼team = .88 (Doosje, Ellemers, & Spears,

1995), and goal commitment, Cronbach’s 𝛼team = .86 (Klein, Cooper, Molloy, &

Swanson, 2014). As a manipulation check, participants assessed the confederate by

completing the contingent reward items of the German version of the Multi Leadership

Questionnaire (MLQ), Cronbach’s 𝛼team = .83 (Felfe & Goihl, 2002). After the second

decision case ended, participants provided demographic information, were fully

debriefed about the used deception, and offered to withdraw their consent,

compensated, and thanked for their participation.

82 Method

Measures

Team decision quality. We measured team decision quality by assessing the

solution rate of the HP task, using the team questionnaire with the decisions about

the optimal candidate.

Team discussion intensity. We captured an overall measure of team

discussion intensity by the following measures on team level: proportion of

information mentioned, average repetition rate of information, and the discussion time.

The content of team discussion intensity was derived from videotapes of the

discussions. Our videotapes showed that one team did not mention any information at

all; therefore, we excluded it. We calculated team discussion intensity according to the

coding manual of Thürmer et al. (2018). Based on the team discussion content, two

independent coders filled in prepared forms. Coders were trained for the procedure

beforehand and were supported with a written coding instructions scheme for the

analysis of the videotapes. Information for each candidate was coded as the following:

“Mentioned” (i.e., an item was named for the first time), “Repeated” (i.e., an item can

be repeated by different team members several times). The coders assessed discussion

time directly from the video tapes. Both coders analyzed 94 team discussions overall

(5 videotapes did not contain the audio track and therefore had to be excluded from

the content analyses. Discussion time was videotaped correctly in all 99 cases). The

level of inter-rater-agreement for team discussion content was 81%. To analyze the

degree of inter-rater agreement across team members discussion content, we used a

two-way mixed, consistency, average-measures intraclass correlation coefficient

(ICC; McGraw & Wong, 1996). In line with Cicchetti (1994), the excellent ICC results

suggest a high degree of inter-rater-agreement (ICC = .96).

83 Method

We calculated a separate ICC for continuous data and level of inter-rater-

agreement (88%) for the 99 videotapes with discussion time. The two-way mixed ICC

(average and agreement measures) revealed an ICC with an excellent score (ICC =

.99) (Cicchetti, 1994). Both ICC values indicate that the measurement error by the two

raters is small, and consequently the power for follow-up analysis of discussion

intensity is not reduced fundamentally, and assumptions can be tested.

Team discussion bias. We deducted team discussion bias as another

dependent measure from the decision content of the video tapes. Measures from

Schulz-Hardt et al. (2006) were used to calculate the discussion bias. We applied

proportions of proportions of information mentioned and not absolute numbers to

calculate the discussion bias and to take relational differences between a single

category and the proportion of information overall mentioned into account. The

following bias measures were used: proportion of shared and unshared information

mentioned, proportion of preference consistent and inconsistent information

mentioned, the repetition rate of shared and unshared information as well as for

preference consistent and inconsistent information.

Team discussion about the correct candidate. We derived the measure about

the proportions of discussed content on the right candidate out of the mentioned and

repeated information by the team members about the candidates.

Data Analysis

We applied the statistical software R (R Core Team, 2018b) for the data

analysis. The estimation of the binary and multiple regression analysis was conducted

with the LME4 package (version 1.1–14; Bates, Mächler, Bolker, & Walker, 2015).

Graphs were plotted with GGPLOT2 (version 2.2.1; Wickham, 2009). Mediation

analysis was estimated with MEDIATION (version 4.4.6; Tingley, Yamamoto, Hirose,

84 Results

Keele, & Imai, 2014) . We applied the multistep procedure of Baron and Kenny (1986)

to test our mediation model. In preparation for testing our mediation model, we

developed an overall measure for team discussion intensity, based on z-transformed

and average values (Schulz-Hardt et al., 2006). We calculated measures for the

discussion bias according to the following procedure: An overall team discussion bias

was based on the repetition rates of preference consistent information and shared

information in the team discussion (Thürmer et al., 2018). We calculated the bias for

repeating shared information by dividing the repetition rate of shared information by

the entire repetition rate, consisting of shared and unshared information and the

preference consistent information bias by the following proportions of information:

the division of preference consistent information divided by the entire information

mentioned during the discussion (Thürmer et al., 2018). We determine the repetition

bias as the repetition rate of preference consistent information divided by the repetition

rate in total (Thürmer et al., 2018).

Results

Firstly, we analyzed the individual preferences prior to the team discussion to

control if our manipulation worked. Prior to the team discussion each individual

preference revealed that team members selected the optimal alternative in 30 out of

297 (10%) HP cases. In the manifest profile condition individual decision makers

were able to find the best alternative themselves: They chose the best alternative in

257 out of 297 (87%) cases. Before the team discussion, across trials chi-square tests

showed that there were no significant differences between the preferred choice of the

best candidate in the Leadership and the Assistant condition (control condition/no

= .57. (MP trail). The p(1) = .31, 2= .48. (HP trail), and χp (1) = .51, 2Leadership), χ

differences between individual MP preferences in the Implementation Intentions and

85 Results

= p(1) = 3.19, 2Goal Intentions condition (control team) were marginally significant χ

.07. Preferences for the optimal candidate were more prevalent in MP problems than

< 0.01.p (1) = 39.57, 2n HP problems, χi

Tests of Direct Effects

To test our hypotheses on direct positive effects transactional leadership and

implementation intentions on HP team decision quality, we considered the HP solution

rate (percent) and we conducted a chi-square test to test for significant differences

between the conditions. The results of the Pearson’s chi-square test revealed a

significant difference between teams in the intervention group (conditions included in

the intervention: Leadership and Implementation Intentions; Leadership and Goal

Intentions; Implementation Intentions and Goal Intentions) and the control group (no

intervention: Goal Intentions and Assistant) in the solution rate of HPs, χ2(1, N = 99)

= 2.72, p = .045.

Indeed, compared to the HP solution rate of 4% of the participants in the

control condition (Goal Intentions and Assistant/no Leadership), teams with an

Implementation Intention and a Leadership intervention had a strong increase in a

solution rate of 19% of HP decision cases. Interestingly, teams also showed a success

rate of 19% in solving HP tasks in the Implementation Intention condition without a

leader. Lastly, the data showed that teams in the pure Leader and Goal Intentions

condition (no Implementation Intentions) solved 17% of the tasks successfully. (Figure

1). Overall, 15 (15%) of 99 teams made the correct choice in the HP task, and 95 (96%)

out of 99 teams solved the manifest profile task correctly.

However, a binary logistic regression analysis for Leadership and

Implementation Intentions as separate interventions revealed no significant results.

Neither Leadership, Wald χ2(1) = 0.89, p = .37 (β = .51), nor Implementation

86 Results

Intentions, Wald χ2(1) = 1.11, p = .27 (β = .66) was a significant predictor in this

equation. Leadership and Implementation Intentions thus had a comparable effect on

HP team decision quality. We further explored whether the interactions between

Implementation Intentions and Leadership have significant positive associations with

the discussion on the correct alternative and HP team decision quality. Binary logistic

regression analyses revealed no Leadership × Implementation Intention interaction,

Wald χ2(1) = 0.89, p = .36 (β = 1.15). We thus did not observe interactive effects.

Tests of Mediation

As Figure 1 illustrates, we hypothesized that either discussion intensity (see

Table 2 for means and standard deviations) or discussion bias mediate the relationship

between Leadership or Implementation Intentions, and the discussion on the correct

alternative. We tested our hypotheses in two mediation models: The first model

assumed an indirect effect of Implementation Intentions on the discussion of the

correct candidate, mediated by team discussion intensity and team discussion bias. HP

team decision quality was in turn assumed to be influenced by the team discussion on

the correct alternative. In the second model an indirect effect was assumed, whereby

the association between Leadership and the discussion on the correct candidate was

transmitted by team discussion intensity and team discussion bias. HP team decision

quality was in turn supposed to be related to the team discussion on the correct

alternative. We chose the discussion on the correct alternative as a proximal mediator

because it directly influences team decision quality (see Figure 1) (e.g., Schulz-Hardt

et al., 2006).

Binary logistic regression showed that the team discussion about the right

candidate increased the probability to solve the HP correctly, although the test failed

to reach significance, p = .06, suggesting that teams that discussed more information

87 Results

about the correct alternative, have odds of solving the HP task 76.68 times higher, with

a 95% CI [− 0.15, 9.12].

As there was no significant association between the predictors (Leadership and

Implementation Intentions) and HP decision quality found, we decided to use the

discussion on the correct alternative as a single outcome for the mediation model.

Consequently, we tested in a first step of each mediation analysis if Leadership and

Implementation Intentions were a significant predictor of the discussion on the correct

alternative. Multiple regression analysis revealed that teams with leaders discussed the

best alternative more, B = .10, p < .001. However, in contradiction to our assumptions,

Implementation Intentions had no significant effects on the discussion about the

correct candidate, B = .0002, p = .91.

In a second step of the mediation analyses, we showed that teams with a leader

had a greater overall discussion intensity, B = 0.76, p < .001. In line with our

Figure 5. Percentage of correct team HP decisions for the different conditions.

Control = teams with an assistant that formed goal intentions; L = teams with a

leader that formed goal intentions; II = teams with an assistant that formed

implementation intentions; L II = teams with a leader that formed implementation

intentions.

88 Results

prediction, teams in the Leadership condition discussed more of the available

information, B = 0.13, p = .001, repeated more information, B = 0.13, p = .001, and

had longer discussions, B = 3.97, p < .001. Yet, Leadership had no significant effects

on team discussion bias, B = -0.01, p = .72. Contrary to our predictions, the

Implementation Intentions manipulation did not increase the discussion time, B = 0.57,

p = .53, the proportion of mentioned information, B = − 0.003, p = .93, the repetition

rates of available information, B = 0.28, p = .28, and the overall discussion intensity,

B = 0.29, p = .16. Further, there was no effect of Implementation Intentions on team

discussion bias observed, B = 0.004, p = .88. Therefore, we excluded Implementation

Intentions as a predictor and bias as a mediator at this point from our analysis.

In a third step of the analysis, a multiple regression showed that Leadership

and team discussion intensity predicted the discussion on the correct alternative, B =

0.35, p < .001. Results suggest that the effect of Leadership on the discussion of the

correct alternative was mediated by team discussion intensity. Additionally, bootstrap

results confirmed that the indirect effect was significant (p < .001), with a bootstrapped

95% CIs [.01, .07] for the indirect effect not containing zero.

Additional Findings on Biases

Finally, we present findings on team discussion bias, which showed that the

value for repeating shared information bias (.54) was not significantly different from

.50, t(89) = 1.28, p = .20. A multiple regression analysis for the effect of the

experimental conditions was not found to be significant: B = −0.05, p = .49

(Leadership condition), B = −0.09, p = .27 (Implementation Intentions condition). The

preference-consistent information bias value was .48, a t-test revealed to be

significantly lower than .50, t(94) = −1.75, p = .08. This result indicates a nearly

unbiased discussion for preference consistent information.

89 Discussion

Hence, we cannot confirm our hypotheses that Leadership and Implementation

Intentions decrease the bias for preference consistent information, because no

significant difference for the experimental condition evinced: B = −0.04, p = .19

(leadership condition), B = 0.03, p = .40 (implementation intentions condition). The

average repetition bias for information in line with the preference bias was .56, a t-test

was found to be marginal significantly different from .50, t(89) = 2.75, p = .07. A

multiple regression was not significant: B = −0.16, p = .12 (Leadership condition), B

= −0.004, p = .99 (Implementation Intentions condition).

Discussion

In this study, we examined the effects of external and internal team regulation

on HP team decision quality. Specifically, team processes can be regulated externally

through transactional leadership (Bass, 1990; Vancouver, 2000) and internally through

the application of implementation intentions (Gollwitzer, 1993, 1999, 2014). The

puzzle was why teams fail to accomplish synergy in HP decision tasks, in spite of

having the potential to identify the correct alternative collectively. Our research

question was how transactional leadership and implementation intentions jointly

contribute to increase the solution rate of HPs.

We chose our predictors based on our theoretical model and showed with an

experimental study of 99 teams that transactional leadership and implementation

intentions improve the HP decision quality. We found that implementation intentions

are the most efficient team strategy to solve HP problems, even though control teams

used the same strategies to recapitulate the advantages of all alternatives, with the

exception that they did not apply implementation intentions.

90 Discussion

Tab

le 5

Tea

m L

evel

Mea

ns,

and S

tand

ard

Dev

iati

ons

of

Dis

cuss

ion I

nte

nsi

ty, and D

iscu

ssio

n a

bout

the

Corr

ect

Candid

ate

E

xp

erim

enta

l co

nd

itio

n

L

ead

ersh

ip a

nd

Imp

lem

enta

tio

n

Inte

nti

ons

(n =

26

)

Lea

der

ship

and

Go

al

Inte

nti

ons

(n =

23

)

Ass

ista

nt

and

Imp

lem

enta

tio

n

Inte

nti

ons

(n =

27

)

Ass

ista

nt

and

Go

al

Inte

nti

ons

(n =

23

)

Mea

sure

M

S

D

M

SD

M

S

D

M

SD

Aver

age

pro

po

rtio

n o

f in

form

atio

n

Aver

age

rep

etit

ion r

ate

of

info

rmat

ion

Dis

cuss

ion t

ime

(min

)

Dis

cuss

ion a

bo

ut

the

Co

rrec

t C

and

idat

e

.51

.21

10

.27

.24

.15

.12

4.6

5

.13

.54

.23

11

.84

.29

.09

.12

3.9

0

.09

.42

.13

9.3

3

.18

.15

.15

5.5

2

.13

.41

.12

6.5

5

.13

.13

.21

.13

.09

91 Discussion

T

able

6

Tea

m L

evel

Dis

cuss

ion B

ias

Mea

ns

and S

tandard

Dev

iati

ons

E

xp

erim

enta

l co

nd

itio

n

L

ead

ersh

ip a

nd

Imp

lem

enta

tio

n

Inte

nti

ons

(n =

26

)

Lea

der

ship

and

Go

al

Inte

nti

ons

(n =

23

)

Ass

ista

nt

and

Imp

lem

enta

tio

n

Inte

nti

ons

(n =

27

)

Ass

ista

nt

and

Go

al

Inte

nti

ons

(n =

23

)

Mea

sure

M

S

D

M

SD

M

S

D

M

SD

Pro

po

rtio

n o

f sh

ared

in

form

atio

n

Pro

po

rtio

n o

f u

nsh

ared

in

form

atio

n

Intr

od

uct

ion b

ias

in f

avo

r o

f sh

ared

in

form

atio

n

Rep

etit

ion r

ate o

f sh

ared

in

form

atio

n

Rep

etit

ion r

ate o

f u

nsh

ared

in

form

atio

n

Rep

eati

ng s

har

ed i

nfo

rmat

ion b

ias

Rep

etit

ion b

ias

for

pre

fere

nce

co

nsi

sten

t in

form

atio

n

Pre

fere

nce

-co

nsi

stent

info

rmati

on b

ias

.38

.70

.35

.21

.24

.50

.54

.49

.14

.26

.09

.16

.14

.28

.18

.09

.43

.70

.39

.26

.22

.58

.48

.46

.08

.25

.11

.14

.20

.25

.20

.07

.36

.55

.42

.17

.18

.57

.59

.47

.12

.25

.16

.14

.20

.28

.21

.13

.36

.55

.39

.11

.11

.60

.67

.50

.13

.23

.13

.13

.21

.29

.24

.12

92 Discussion

In comparison, Implementation Intentions teams solved more HP cases in

percent than teams with leaders, yet both conditions included the same information

such as executed either by the if-then plan or the Leader. Teams with Leaders still

solved HP problems four times more often than the control team.

A transactional leadership and implementation intentions intervention is

helpful for HP decision quality because teams that participated in the intervention

group solved significantly more HP problems than teams without intervention.

Further, team discussion intensity fully mediated the relation between leadership and

team discussion on the correct alternative, but not the association on team decision

quality. Leaders helped teams to discuss more unshared information, which is a critical

component to solve the HP.

Through all analysis no interaction effects occurred. In sum, study results

supported our assumption that transactional leadership and implementation intentions

are helpful for teams to solve HPs. In comparison Implementation Intentions teams

solved more HPs than teams with Leaders, yet teams with Leaders had the highest

discussion intensity, which indirectly affected the discussion on the correct HP

alternative.

Contributions

Research on how teams solve HPs explores how predictors directly affect

effective HP team decision making, and how the mediation effect of process measures

such as team discussion intensity and team discussion bias indirectly relate to HP

decision quality (e.g., Brodbeck, Kerschreiter, Mojzisch, Frey, & Schulz-Hardt, 2002;

van Swol, 2016). We expanded this research in our study by exploring how external

and internal team regulation provide an alternative way to improve team decision

quality in HPs. Specifically, we integrated external team regulation through

93 Discussion

transactional leadership with internal team regulation through implementation

intentions to demonstrate how both factors contribute in comparison and jointly to

team decision quality in HPs. While different leadership approaches and

implementation intentions have already been discussed separately in HP paradigms

(Meyer et al., 2016; Schulz-Hardt & Brodbeck, 2012; Thürmer et al., 2015a), both

approaches to improving decision quality have not been applied together in one study

and both were not used in comparison yet.

Another contribution of this study is that we included team discussion intensity

and team discussion bias as process measures in our model. To our knowledge, only

one empirical study has covered both measures simultaneously in one model (for an

exception see Schulz-Hardt et al., 2006).

Figure 6. Team discussion intensity dependent on leadership and implementation

intentions. Control = teams with an assistant; Leader = teams with leaders; GI = Goal

Intentions; II = Implementation Intentions. A, Proportion of items mentioned. B,

Proportion of Repetition rate of discussed information; C, Team discussion times in

minutes.

94 Discussion

Therefore, we contribute to the understanding of how team discussion intensity

and team discussion bias are related to the solution of HPs. Additionally, we showed

from a team regulation perspective how transactional leadership and implementation

intentions addressed team discussion intensity and team discussion bias as an obstacle

for teams to solve HPs. A third contribution of this study is to the literature on HPs

and leadership (e.g., Cruz et al., 1999; Larson, Foster-Fishman et al., 1998; Meyer et

al., 2016).

To the best of our knowledge there is no literature regarding the association of

transactional leadership and the intensity and bias of team discussions in HPs so far.

This study contributes to the general knowledge concerning the contribution of

leadership to solve HPs effectively. We add to existing leadership research on HPs

Figure 7. Mentioned and repeated shared and unshared items dependent on

leadership and implementation intentions. Control = teams with an assistant; Leader

= teams with leaders; GI = Goal Intentions; II = Implementation Intentions. A,

Proportion of shared information mentioned. B, Proportion of unshared information

mentioned. C, Proportion of the repetition shared information mentioned. D,

Proportion of the repetition unshared information mentioned.

95 Discussion

with our perspective of transactional leadership as an external regulation tool of teams

to improve HP team decision making.

Practical Implications

Our findings indicate that teams often cannot reach their goals and perform

effectively, because they fail to regulate their behavior (Peterson & Behfar, 2005).

Therefore, one key practical implication from our research is how team regulation is

relevant for teams to address obstacles and to perform effectively in organizations. On

the one hand, team regulation is interesting for organizations that have traditional

teams with leaders, because leadership can function as a regulating tool for team

behavior.

On the other hand, organizations count more and more on autonomous teams

who could benefit from team regulation strategies to improve their team performance.

The suggested approach is interesting for practitioners who want to compare both

interventions to determine whether one yields better team performance than the other.

Appointing a leader is typically costlier than teaching teams efficient self-regulation

strategies, and the question therefore is whether a leader has an added benefit over

effective internal team regulation strategies.

We are not suggesting that companies use a HP task to compare external and

internal team regulation strategies. HPs have been used so far mainly in an

experimental setting and they are not designed for field studies (for one exception see

Stasser, Abele, & Parsons, 2012). However, positive effects of self-regulation with

implementation intentions have been shown in real-world settings. Specifically,

interventions using mental contrasting with implementation intentions (MCII) help

individuals to transform positive thoughts and fantasies about a desired future into the

aspired change of behavior (Oettingen, 2000; Oettingen, Wittchen, & Gollwitzer,

96 Discussion

2013a). MCII integrates two key features: mental contrasting, a strategy that helps to

pursue goals with strong goal commitment and goal striving, and the formation of self-

regulation with implementation intentions, an effective type of plan to enhance goal

striving (see also above). MCII was successfully shown in many applied settings such

as healthy eating behavior (Adriaanse et al., 2010), and an increase in individual

performance in the education sector (Duckworth, Grant, Loew, Oettingen, &

Gollwitzer, 2011). Thus, it might be also a helpful strategy for autonomous teams in

the organizational context to achieve their goals effectively.

An intervention for leadership in a team regulation perspective might be

especially helpful for organizations when they face obstacles such as an unstable

environment. For example, when teams have a high turnover rate, they must redefine

themselves. In this unstable period of redefinition, they are more prone to failure and

may need leadership to adapt to changes and create a new team vision (Peterson

& Behfar, 2005).

For practitioners, during meetings the costs of unproductive and wasted time

could be reduced with team regulation strategies; implementation intentions and

leadership could help to overcome existing meeting obstacles like ineffective task

management, team decision making, and unsatisfying mutual interaction between team

members and the leader (Rogelberg, Shanock, & Scott, 2012). Thus, it would be

interesting for team meetings how discussion bias and discussion intensity affect team

outcomes. Organizations need to identify, e.g., with a meeting protocol if they have a

biased discussion and sufficient discussion intensity to elaborate on relevant issues. In

a next step a development towards an unbiased discussion and a sufficient discussion

intensity can be supported by initiatives of the organization (see also Rogelberg et al.,

2012).

97 Discussion

Limitations and Future Research

It is widely known in team research on HPs (Greitemeyer et al., 2006) that it is

hard to accomplish a significant improvement of team decision quality. We had a

significant increase in HP decision quality between intervention condition (Leadership

and Implementation Intentions) compared to control teams. Descriptively, teams in the

Implementation Intentions condition solved even more HPs than teams with only

Leaders. Yet, one concern is that we showed in our analysis that both manipulations

help to solve HPs, but we cannot tell so far which one is more efficient nor could we

show any interaction effects in our regression analysis.

One reason might be a lack of statistical power for both manipulations,

Leadership (.50) and Implementation Intentions (.49) to find a medium effect size

(Cohen, 1988). A higher statistical power would add to the robustness of the results.

Apparently, teams discuss the available information sufficiently, when they were in

intervention teams. Another reason why they could not reach their full potential to

solve the HPs, might be that they did not use the resources that were required for

exceptional team performance (Hackman & Katz, 2010).

Thus, another reason concerning the solution rate of HPs might have been that

the repetition rate of information during the team discussion was selective, because

teams in the control condition that formed goal intentions had a higher repetition rate

than teams in the implementation intentions condition. These results suggest, that team

members might selectively repeat information, supporting their initial preferences on

the alternatives (e.g., Faulmüller et al., 2012), which would explain the higher

repetition rates in the control condition. Still, this might represent another study

limitation. Our manipulation revealed no effect on team discussion bias towards

preference consistent information and shared information. However, this result is in

98 Discussion

line with research conducted by Schulz-Hardt et al. (2006). In their study, discussion

intensity revealed to be the more powerful mediator on the discussion on the correct

alternative in comparison to team discussion bias. Like in our study, when we tested

the mediators in our models, we were only able to keep discussion intensity as a

significant mediator, indicating that discussion intensity is a more critical mediator to

team decision on the correct alternative and HP decision quality (see also Schulz-Hardt

& Mojzisch, 2012).

Finally, another limitation was the manipulation of a transactional leadership

style. We argue in line with Zehnder, Herz, and Bonardi (2017) that transactional

leadership is an appropriate leadership style as long as the task, the context for leaders

and their followers remain simple, then, such incentives as in our experiment, for

solving HP tasks correctly are adequate. Hence, HP tasks are complex to solve for

teams, consequently a potential concern is that beyond a simple experimental context,

team members require skills on several dimensions to solve the task such as managing

a high cognitive load of information (Stasser & Titus, 1985). Therefore, internal team

regulation with implementation intentions still might work as a strategy to solve HP

tasks. However, external team regulation through transactional leadership using

extrinsic rewards and incentives might reach their limit to motivate team members to

accomplish their goal to solve HPs.

This paper also opens avenues for future research. A transformational

leadership style could fill the gaps of transactional leadership in new research by

motivating and inspiring team members with a shared vision, and by shaping a

common identity (Bass, 1985). In particular components of a transformational

leadership style, such as individualized consideration and stimulating followers

intellectually, combined with idealized influence through leader charisma to inspire

followers, are known to be effective components for team performance (Bass, 1999;

99 Discussion

Hackman, 2006). Therefore, future researchers might consider transformational

leadership as an interesting path to help teams to solve complex team tasks such as

HPs.

A next step for future research would be to include different leadership styles

(Cruz et al., 1999; Meyer et al., 2016) as a moderator variable into a model, because

referring to our study, leadership is likely to influence team process measures such as

discussion intensity and discussion bias in HPs. A good start would be the integration

of leadership styles such as narcissistic team leadership that beget a negative effect on

team performance by blocking the pooling of information between team members

(Nevicka et al., 2011). Studies that might investigate leadership behavior such as an

abusive, dominant, controlling, and directive leadership style are also supposed to

inhibit information sharing among team members (e.g., Larson, 2010; Maner & Mead,

2010). It may have great promise to investigate if leaders who show one of the

leadership behaviors above would still be able to inhibit the discussion of information

if teams use implementation intentions that are specified on bringing the available

information on the table.

Research has also not fully considered if a leadership behavior that enhances

the sharing of information among team members such as a participative and supportive

leadership behavior (Meyer et al., 2016; Srivastava, Bartol, & Locke, 2006) reinforces

if-then plans and thereby improves team performance in HPs. Moreover, it should be

considered in future research to apply a more real-world case-scenario for the leader

selection such as that leaders are appointed to their position due to their performance.

Blinder and Morgan (2007) selected their leader for a team experiment by choosing

this individual of the team who outperformed the other members in a preliminary task.

Thus, future research should examine a multilevel approach to assess team

performance on different levels. Thürmer et al. (2015b) suggested that implementation

100 Discussion

intentions work on both the individual and the team level in HP decision making tasks.

For example, Breugst, Patzelt, Shepherd, and Aguinis (2012) investigated subjective

and objective team performance with a multilevel approach in a HP paradigm. Future

research could explore if and how implementation intentions and leadership may help

on an individual and a team level to evaluate performance on an individual and team

level (subjective performance) and compare it to the actual performance on both levels.

Our HP team discussion data were collected in the laboratory within a limited

time frame. That approach is useful, however what might be a fruitful task for a future

study, is a more realistic time frame of team-work, where we can assess the influence

of implementation intentions and leadership on team performance in long-term studies.

Conclusion

External and internal team regulation with transactional leadership and

implementation intentions helps teams to solve HP tasks more effectively. Teams with

leaders discuss available information on HP tasks more sufficiently, which leads to a

higher discussion on the correct alternative. The main message of this study is that

external and internal team regulation with transactional leadership and implementation

intentions are both relevant for teams to address obstacles in team decision making

processes and to perform well collectively.

101 Research Paper III

Research Paper III

Exploring Asymmetry: The Influence of Leader-Subordinate Age

Dissimilarities on Performance Evaluations

Lucia A. Görke1, 2, Florian Kunze2, 3, J. Lukas Thürmer2, 3, 4, Peter M. Gollwitzer1, 5



3 Department of Politics and Public Administration, University of Konstanz,

Germany

4 Department of Psychology, Paris Lodron University Salzburg, Austria


102 Abstract

Abstract

Age dissimilarity in leader-subordinate dyads influence performance evaluations in

companies. A more recent phenomenon in this context is that younger leaders evaluate

the performance of older subordinates, which contradict traditional leadership

relationships. The motivation of this research is to understand how the direction of age

dissimilarities in these non-traditional leader-subordinate constellations influences

performance evaluations of subordinates. Based on the shifted-standard model of

stereotype-based judgements, we hypothesized and found that leader-subordinate age

dissimilarity effects are asymmetrical and positively related to performance

evaluations in non-traditional leader-subordinate constellations. Analysis based on

company data from 1,165 leader-subordinate dyads supported our theoretical model

and revealed that the leader-subordinate constellation matters for age dissimilarity

influences on performance evaluations.

Keywords: leader–subordinate dyads, response surface analysis, multilevel

polynomial regression, age-dissimilarity; shifted-standard model; age stereotypes

103 Introduction

Introduction

Traditionally, people in organizations are gradually promoted into leadership

positions based on seniority and age (Cappelli & Novelli, 2010). More recently,

traditional career schemes have been altered by new age structures and many leaders

of today are younger than their subordinates (Knight, 2014). One reason for these

changes of age structures in organizations is that more older employees than ever stay

in the workforce (Cappelli & Novelli, 2010). Older employees still perform effectively

beyond their current employment levels (Coile, Milligan, & Wise, 2017), they are

healthier, and their overall life expectancy has increased (Fritzsche & Ghada, 2017).

In many countries, the standard retirement age has been raised or is planned to be

raised in the medium term and employees work longer and to a later age until they

retire (Coile et al., 2017).

In addition, the demographic change has contributed to a disproportionate

number of older employees in the workforce (Cappelli & Novelli, 2010). However,

older employees are less likely to be promoted, because leaders often have a

stereotypical image of them, which makes it more likely for younger employees to

move into leadership positions (Kooij et al., 2013). Contrary to traditional age norms

(Lawrence, 1988), many organizations today employ older employees at various career

levels and at positions that were filled by younger employees before. As a result, young

leaders often supervise older employees (Collins, Hair, & Rocco, 2009). Further,

organizational changes such as mergers or reorganizations frequently promote younger

employees into leadership positions, as they are rated more positively on information

technology skills and the adaptability to change (Ng & Feldman, 2012).

This increasing phenomenon that younger leaders supervise older employees

affects outcomes in organizations, such as team-level turnover or company

104 Introduction

performance (Buengeler, Homan, & Voelpel, 2016; Kunze & Menges, 2016).

Specifically, on a dyadic level age dissimilarities in non-traditional leader-subordinate

constellations revealed to influence performance evaluations of employees (e.g.,

Ferris, Judge, Chachere, & Liden, 1991; Tsui, Porter, & Egan, 2002). We understand

age dissimilarity as the differences between two individuals in a leader-subordinate

dyad characterized by their chronological age (Chattopadhyay, 1999). In our study,

performance evaluations comprise a leader’s subjective evaluation of subordinate

performance (e.g., Ferris et al., 1991). A frequently used framework to explain age

dissimilarity effects on work related outcomes in a dyad or a group provides the

similarity-attraction paradigm (e.g., Tsui, Egan, & O'Reilly, 1992; Tsui & O'Reilly,

1989; Vecchio, 1993).

Although, the similarity-attraction paradigm (Byrne, 1971) has received

empirical support (e.g., Tsui et al., 2002), similarity-attraction theorists face challenges

to explain effects of age dissimilarities in non-traditional leader-subordinate

constellations. The similarity-attraction paradigm proposes that more interpersonal age

similarity in leader subordinate dyad is associated with a higher inter-individual

attraction between leader and subordinate, which in turn is related to positive outcomes

such as higher subordinate performance evaluations (Tsui & O'Reilly, 1989). More

age dissimilarity between leader and subordinate is vice versa related to lower inter-

individual attraction and leads to lower work-related outcomes (e.g., Liden et al.,

1996).

A central challenge for the similarity-attraction paradigm is that it assumes a

non-directional effect of age-dissimilarity on work related outcomes (Perry, Kulik, &

Zhou, 1999). The similarity-attraction paradigm assumes that work related outcomes

are influenced by a certain amount of age dissimilarity between leader and subordinate

105 Introduction

and not by the direction of the age dissimilarity (older leader-younger subordinate or

younger leader-older subordinate) (Perry et al., 1999). However, empirical studies

have shown that the direction of the effect can be essential for work related outcomes

(e.g., Tsui et al., 2002; Vecchio, 1993). For example, it mattered for outcomes such as

performance evaluations if the subordinate was supervised by a younger or by an older

leader (e.g., Tsui et al., 2002; Vecchio, 1993). Therefore, it poses a challenge for the

similarity-attraction paradigm to explain the occurrence of one-directional effects.

Thus, contrary to the assumption of the similarity-attraction paradigm a group of

studies reported positive effects of age dissimilarity on performance evaluations in

leader-subordinate dyads (e.g., Ferris et al., 1991; Vecchio, 1993).

These findings raise a puzzle: Why are there one-directional and positive

effects of age dissimilarity on performance evaluations in leader subordinate dyads,

even though the similarity-attraction paradigm would predict that age dissimilarity has

negative effects on outcomes regardless of the specific leader-subordinate

constellation. In this study, we propose that the specific constellation of leader-

subordinate age dissimilarities matters for performance evaluations. More specifically,

we examine an asymmetrical effect (Chattopadhyay, 1999) of leader-subordinate age

dissimilarities by exploring the case of non-traditional leadership constellations when

the leader is younger than the subordinate.

The motivation of our research is to explain asymmetrical effects of age-

dissimilarities in non-traditional leader-subordinate constellations with the shifted

standard model of stereotype-based judgements (Biernat & Manis, 1994). The

assumptions considered in this model are that leaders assign subordinates to a higher

or lower standard of competence based on age stereotypes, which influences the

performance evaluations of subordinates (Biernat et al., 2010). Further, we introduce

106 Introduction

multilevel response surface analysis (RSA) (Edwards & Parry, 1993; Nestler et al., in

press) as an alternative method to test asymmetrical effects of age dissimilarity in

leader subordinate dyads.

Our study addresses the following question: How do leaders evaluate the

performance of subordinates in dyads when the leader is younger than the subordinate?

Contrary to the similarity-attraction paradigm (Byrne, 1971) we use the shifted

standard model (Biernat & Manis, 1994) to derive our hypotheses on asymmetrical

effects of age dissimilarity in leader subordinate dyads. We propose a positive

association of leader-subordinate age dissimilarities and performance evaluations

when the leader is younger than the subordinate. We perform multilevel RSA tests on

1,165 dyads in a company to explore age dissimilarity effects of leader performance

evaluations of subordinates in non-traditional leader-subordinate constellations.

This study contributes to the similarity-attraction paradigm by identifying

asymmetrical relationships of age dissimilarities in non-traditional leader-subordinate

constellations. There has not been much research yet neither on genuine leader-

subordinate age dissimilarity effects (for an overview see Rosing & Jungmann, 2016),

nor on asymmetrical dissimilarity effects of younger leaders with older subordinates

(for exceptions see Kunze & Menges, 2016; Tsui, Xin, & Egan, 1995; van der Heijden

et al., 2010).

Only few studies exist about influences of age dissimilarity on subjective

subordinate performance evaluations in leader-subordinate dyads (e.g., Ferris et al.,

1991; Vecchio, 1993) and to our knowledge they do not discuss asymmetrical effects

of age dissimilarity on performance evaluations. Research findings from previous

studies on age dissimilarities have been mostly conducted on group level

(Chattopadhyay, George, & Shulman, 2008; Kearney, 2008) and explanations for age

107 Introduction

dissimilarity outcomes involve foremost societal status-based approaches (Buengeler

et al., 2016) , the theory of age grading, and age norms (Lawrence, 1984, 1988) or the

similarity-attraction paradigm in isolation (Tsui & O'Reilly, 1989).

In this study, we explain how age stereotype biases and the application of

different standards can influence performance evaluations of subordinates, thus

expanding the relational demography framework on the dyadic level. Further, a

methodological contribution of this study is that it alternatively proposes multilevel

RSA to measure age dissimilarity outcomes in leader-subordinate constellations.

Explaining Asymmetrical Effects of Age Dissimilarity in Non-Traditional

Leader Subordinate Constellations

Age dissimilarities in leader-subordinate dyads have an influence on

performance evaluations of subordinates (Tsui & O'Reilly, 1989). Specifically, leaders

in non-traditional leader-subordinate constellations respond differently to being

dissimilar in age to their subordinates. These asymmetries appear for example when

age dissimilarities between leaders and subordinates are associated with lower

performance evaluations for younger subordinates, but higher performance

evaluations for older subordinates, or the effect is significant only in one direction

(e.g., Ferris et al., 1991; Tsui et al., 2002; Vecchio, 1993). For instance, one empirical

study revealed that older leaders evaluate the performance of subordinates positively,

yet they found no association of age dissimilarity and performance evaluations of

subordinates, when the leaders were younger than the subordinates (Vecchio, 1993).

In the same vein, Tsui et al. (2002) reported significantly negative effects of leader-

subordinate age dissimilarity influences on performance evaluations of subordinates,

when the leader was younger, on the opposite side older leaders evaluated the

performance of subordinates as overall higher.

108 Introduction

Other empirical studies revealed asymmetrical results in the opposite direction

(Ferris et al., 1991; Shore, Cleveland, & Goldberg, 2003; Vecchio, 1993). For

example, two studies revealed that age dissimilarities between leaders and their work

groups (Ferris et al., 1991) or their subordinates (Vecchio, 1993) were related to higher

performance evaluations, when the leader was younger compared to the work group

or the subordinate, but revealed no effect on performance evaluations, when the leader

was older. Paradoxically, the results suggest that performance evaluations of older

subordinates in non-traditional leader-subordinate constellations can be positive,

despite the fact that leaders and subordinates are dissimilar in age to each other. A

pattern might be that younger leaders hold age stereotype biases against older

subordinates on an unconscious level that subsequently influence performance

evaluations of older subordinates (Liden et al., 1996; Tsui et al., 2002).

In general, stereotypes about the performance of older subordinates such as

being not as skillful, being unproductive, and having a lack of motivation have

revealed to lead to biased evaluations of the performance of older workers (for a meta-

analysis see Ng & Feldman, 2012; Posthuma & Campion, 2009). Finkelstein, Burke,

and Raju (1995) have shown in in an empirical study that age stereotype biases

influence employee ratings in a hiring decision simulation, when raters where younger

than the job candidate they are supposed to hire. However, when an older individual

rated potential job candidates no differences were found between the ratings of

younger or older applicants (Finkelstein et al., 1995). This result indicates that younger

leaders might in general be more vulnerable to influences of age stereotypes when they

evaluate older employees (Finkelstein et al., 1995).

Furthermore, Vecchio (1993) points out that age dissimilarities have more

potential for problems in dyads in one direction when the leader is younger than the

109 Introduction

subordinate. Taking these findings into account, we argue that younger leaders tend to

rely more on age stereotypes when they evaluate older subordinates. Specifically, we

posit an asymmetrical effect of age dissimilarity in one direction for non-traditional

leader-subordinate constellations. Besides age stereotypes, double standards of young

leaders might be related to subordinate performance evaluations (Posthuma

& Campion, 2009; Roberson, Galvin, & Charles, 2007). How age stereotypes and

double standards of leaders for older subordinates can lead to positive performance

evaluations in non-traditional leader-subordinate constellations will be outlined in

more detail in the next section of the paper.

The Paradox of Positive Performance Evaluations in Non-Traditional Leader

Subordinate Constellations

Age stereotype biases and categorizations of subordinates into different

evaluation standards are combined in the shifted standard model of stereotype-based

judgements (Biernat et al., 1991; Biernat & Manis, 1994). In the shifting standard

model, age stereotypes set judgement standards for leaders to evaluate the performance

of subordinates (Biernat et al., 1991; Biernat & Manis, 1994). Age stereotypes are a

leader’s cognitions and a leader’s perceptions on age that serve as a ground for a

categorization of subordinates based on their age (Toomey & Rudolph, 2016). These

conscious or unconscious cognitions are for example that older subordinates are slower

and less open for modern technologies, which can lead to an overall lower prestige of

older subordinates (Posthuma, Wagstaff, & Campion, 2012).

Specifically, in non-traditional leader-subordinate constellations, young

leaders may have stereotypes on older subordinates. Leaders classify subordinates into

social categories according to their age stereotypes about subordinates. Based on these

social categories leaders shift their evaluation standards for subordinate performance

110 Introduction

(Biernat & Manis, 1994). In this study, the category a leader is using as a standard for

evaluations is “older subordinate vs. younger subordinate.” Thus, a leader might

evaluate the same performance behavior of older and younger subordinates differently,

because they are judged by different standards dependent on the social category they

are identified with (Biernat et al., 2010). This means that leaders associate age

stereotypes with lower standards for older subordinates than for younger subordinates

(Biernat & Kobrynowicz, 1997).

Older subordinates are related to lower standards because leaders’ perceived

impressions and descriptions of a subordinate rely partially on stereotypes they have

about the group of older subordinates (Biernat et al., 2010; Biernat & Manis, 1994).

These stereotypes serve as an evaluation standard for the leader. Leaders may hold

lower standards for the groups of older workers as they categorize them as group with

some deficiencies due to their age (Biernat & Kobrynowicz, 1997). For example, age

stereotypes exist about older subordinates that they are not capable of adapting to new

situations and have a lack of productiveness, for that reasons leaders assign them to a

lower standard of competence than younger subordinates (Posthuma et al., 2012). As

a result, leaders have a lower level of expectation of competence for subordinates with

a lower standard (Biernat & Kobrynowicz, 1997). Therefore, leaders evaluate the

performance of subordinates by shifting their evaluation standard within groups of

low-standard subordinates or high-standard subordinates (Biernat et al., 1991).

For instance, shifted standards become visible on subjective performance

evaluations scales ranging from 1 to 7, where an older subordinate may receive an

evaluation of 6 according to the lower evaluation standard of older subordinates, and

a younger subordinate with a similar performance receives a 4 among high-standard

subordinates. However, leaders still apply the same scale to evaluate low- and high

111 Introduction

standard subordinates, as a result age stereotypes influence performance evaluations

of subordinates with a high probability (Biernat & Kobrynowicz, 1997).

Paradoxically, using two standards on the same scale can lead to a positively

biased evaluation for older subordinates with a low-status (Roberson et al., 2007).

Positive bias evaluation effects can be found in empirical studies on race (e.g., Roth,

Huffcutt, & Bobko, 2003) and gender differences (e.g., Biernat et al., 1991). However,

to our knowledge no research on age used the shifted standard model so far. In this

study leaders used a subjective scale to evaluate the performance of subordinates. In

non-traditional leader subordinate- constellations we assume that performance

evaluations of older subordinates might be influenced by a positive bias of the leader.

We posit that older subordinates will receive positive performance evaluations

by the leader. Instead of expecting a broad age dissimilarity effect where age

dissimilarity between leader and subordinate is uniformly related to lower performance

evaluations, we assume a one-directional margin effect when the leader is younger

than the subordinate and hypothesize that:

H1: Leader-subordinate age dissimilarities will be positively related to performance

evaluations when the leader is younger than the subordinate.

How to Test Age Dissimilarity Patterns Beyond Difference Scores

Common approaches to test hypothesis on age similarity or dissimilarity

patterns are difference scores (e.g., Ferris et al., 1991; Kunze & Menges, 2016).

Difference scores are typically measured by correlating the algebraic, absolute, or

squared difference between two variables with an outcome measure (Edwards, 2002).

Although, the difference score method is frequently used in empirical research on age

(dis)similarity (Ferris et al., 1991; Liden et al., 1996), some concerns regarding their

112 Introduction

methodological limitations have been raised (Edwards, 2001; Edwards & Parry, 2018;

Johns, 1981).

The major methodological problem is that creating fixed difference scores can

be related to a loss of information in the data. For example, difference scores predict

the same outcome when leader and subordinate are both young at the same age level

or equally when they are both older at the same age level (Schönbrodt, Humberg, &

Nestler, 2018). Yet, difference scores do not consider higher or lower levels of age

(dis)similarity outcomes. As a result, due to implicit constraints on the data, essential

information remains untested when difference scores are used (Edwards, 2001, 2007).

In extreme cases this can lead to an erroneous support of a (dis)similarity hypothesis.

However, there is nothing in the data to suggest that a (dis)similarity effect is present

(Edwards, 1994, 2001).

A potential solution to this methodological problem is response surface

analysis (RSA). We offer multilevel RSA (Edwards, 2007; Edwards & Parry, 1993;

Nestler et al., in press; Zyphur, Zammuto, & Zhang, 2016) as a novel methodological

contribution to analyze age dissimilarity patterns in leader-subordinate dyads.

Multilevel RSA sets out a stark alternative to difference scores to test leader-

subordinate age dissimilarity influences (Nestler et al., in press). RSA also considers

the curvilinear relationship between age and performance evaluations by using higher

terms in the regression model (Avolio & Waldman, 1994; Ng & Feldman, 2008). It

allows us to assess more elaborate age effects than difference score tests do, such as

testing broad, marginal, and main effects (Edwards, 2002) of asymmetrical age

dissimilarity influences in leader-subordinate dyads.

RSA starts with the estimation of a multilevel polynomial regression model,

and we proceed by interpreting the average response surface and the aligned statistical

113 Method

parameters together (Edwards, 2007). In line with our theoretical assumption we are

not testing for a broad dissimilarity effect. We will test for direct main effects and

optimal margin effects to allow testing of age dissimilarities to a certain extent of age

dissimilarity between leader and subordinate (Edwards, 2002).

Method

Sample and Data

The sample consisted of data from a Swiss based financial service company

involved in insurance and asset management businesses. We used official firm people

metrics on employee performance ratings and demographic measures in the year 2017.

All data was provided on the individual level by the controlling and HR-department of

the Swiss headquarters. Data were analysed on a dyadic level from 2222 participants

in total.

We excluded 836 participants whose performance was not evaluated at all or

who did not formally report to a leader (no dyad). The exclusion limited the number

of samples available for the analysis to 1386 participants in total (1165 subordinates,

221 leaders). Our data included 660 female and 726 male subordinates (Age: MSub =

42.82, SDSub = 11.48); 56 female and 165 male leaders (Age: MLeader = 44.6, SDLeader

= 8.13).

Measures

Subordinate performance evaluation. Performance evaluations of the

subordinates were evaluated by their respective leaders using a management by

objectives (MBO) approach. Leaders rate their subordinates on a percentage scale

(range 80% to 130%). Subordinate evaluations are conducted once a year in the

company. The subordinate evaluation consists of personal goals, and strategic

organizational goals. Personal goals include the developmental goals of every

114 Method

employee. Organizational goals are strategic goals formed by each unit within the firm.

In addition to the annual performance evaluation, subordinates and leaders can adapt

the personal goals of the subordinate up to three times in a year if necessary.

Leader age. We measured the age of leaders in years as provided by the

company HR data. Age differences between leader and subordinate were calculated

with polynomial regression and RSA.

Subordinate age. Subordinate age in years was part of the provided company’s

HR metrics.

Control variables. Subordinate absenteeism was used as another dimension

of performance that can be possibly influenced by age (Ng & Feldman, 2008). We

used absenteeism as a control measure for performance to show that the influence of

age dissimilarity categorizations remains the same and therefore, we assumed that

identities and categorizations play a role for the leader, and leader bias affected

performance evaluations of the subordinate (Roberson et al., 2007). We chose leader

gender as a control measure to take into account that leader gender status can have an

impact on performance evaluation outcomes besides leader age as a status variable

(Ragins, 1991; Ridgeway, 2001). We assessed organizational tenure of the subordinate

in months as a proxy of the leader-subordinate dyad tenure. The tenure of leader-

subordinates’ relationships has influenced the evaluations of subordinates as previous

research has demonstrated (Schyns, Paul, Mohr, & Blank, 2005).

Data Analytic Strategy

We used the statistical software R (R Core Team, 2018a) for data analysis. The

multilevel polynomial regression model was estimated with the LME4 package (version

1.1–14; Bates et al., 2015). RSA analysis and the visual presentation of the average

response surface were conducted using the RSA package (version 0.9.12; Schönbrodt

115 Method

& Humberg, 2018). For our multilevel average response surface analysis, the

interpretation of the response surface analysis basically followed the same manual as

the interpretation of a single RSA (see also Nestler et al., in press).

As a first step of analysis we controlled for sampling errors (Edwards, 2002;

Raudenbush & Bryk, 2002): To control for sampling errors we prepared the data by

grand-mean centering on the leader-age variable as one predictor, and on subordinate-

age as the second predictor. Afterwards, we established the squared and interaction

terms on the grand-mean centered variables. Then we standardized performance

evaluation as the outcome variable to enhance the interpretation of the multilevel

parameters on the response surface (Nestler et al., in press). Second, to test the

(dis)similarity hypothesis we estimated a multilevel polynomial regression model as a

basis for the RSA method.

PEim = b0m + b1mxim + b2myim + b3mx2im + b4mxim + b5my2

im + ɛim,

To predict performance evaluations (PE), we applied subordinate age (x),

leader age (y), the squared terms of both predictors, and the interaction of both terms

in the multilevel polynomial regression model. The index m indicates the Level 2 unit

(m = 1,…, N), and the index i reflects the Level 1 unit (i = 1,…, nm) in the multilevel

polynomial regression model. The multilevel polynomial regression model as used in

this context was applied to account for the nested data structure of the leader-

subordinate dyad: For every leader we assumed an intercept that is different for each

of the leader’s subordinate performance evaluation. In a third step, the resulting

polynomial unstandardized parameter estimates of the multilevel polynomial

regression model were applied to calculate the RSA model parameters. In a next step

we performed z-tests to test the five RSA parameters (â1; â2; â3; â4; â5) for significance.

116 Results

The average surface parameters were interpreted in combination with each

other to detect possible (dis)similarity and optimal margin effects: The response

surface parameters â1 and â2 reflect the linear slope and the curvature along the line of

congruence (LOC). The line of incongruence (LOIC) corresponds to the average

surface parameters â3 and â4 representing the slope and the curvature along line of

incongruence. The fifth response surface parameter (â5) stands for the first principal

axes (FPA, also called ridge line) equalling the LOC. The interpretation of results is

possible by interpreting the FPA, the LOC, and the LOIC (Edwards & Parry, 1993;

Humberg, Nestler, & Back, 2018).

It is difficult to interpret the surface parameters of the polynomial regression

based on the coefficients. To interpret the results, it helps to visualize the three-

dimensional average response surface. On the three-dimensional surface graph, the

LOC and LOIC were represented as blue lines at the bottom and surface of the graph

(see also Figure 1 for an example of an average response surface illustration). The

LOC (â1; â2) starts in the front corner and goes diagonally straight to the back corner.

Perpendicular to the LOC, the LOIC (â3 and â4) connects the corner of the cube form

the left to the right side. A bagplot on the surface limits the region of the interpretable

data to avoid extrapolation. The dashed line at the bottom and surface represent the

FPA. The darker the color of the surface the higher are the related outcome values

(performance evaluation).

Results

Table 1 provides descriptive measurements of the analyzed variables in the

study: mean, standard deviation, and correlations. Following the interpretation of

Zyphur, Zammuto, and Zhang (2016) we did not provide additional information about

descriptive measures as they are not informative for the interpretation of the response

117 Results

surface analysis. Table 2 tabulates the results of the multilevel polynomial regression

model. Table 3 shows the average response surface parameters.

Multilevel Response Surface Analysis

Supporting our hypothesis there was no broad congruence effect of leader-age

similarities found on performance evaluations. This hypothesis was first tested by

analyzing if the conditions of a broad congruence effect are met: For a broad

congruence effect the fixed effect RSA parameters need to be significantly positive for

â1, significantly negative for â4, and non-significant for â2, â3, and â5. However, the

present RSA parameters, summarized in Table 3 contradicted a similarity effect as the

result pattern for the RSA parameters differ: the slope of the response surface along

the LOC (â1 (â1 = b̂1 + b̂2 = − 0.00242) was significantly negative different from zero;

and the curvature of the LOC, â3 (â3 = b̂1 − b̂2 = 0.00135) significantly positive different

from zero; the other parameters were not significant (â2; â4; â5). As the visualization of

the response surface in Figure 1 illustrated the present RSA parameter structure rather

revealed that performance evaluations were not higher, when leader and subordinate

age patterns were similar: The FPA, represented as the dashed line in Figure 1, of the

surface is disposed from the LOC, because â3 was significantly different from zero.

Consequently, more age similarity between leader and subordinate was not

found to be related to higher performance evaluations. Second, to exclude a

congruence effect it is further necessary to define dissimilarity patterns of leader-

subordinate dyads and analyze if more leader-age dissimilarity was related to lower

performance evaluations in general. Therefore, we considered the slope along the

LOIC, and the curvature of the LOIC. Results demonstrated that the surface parameters

for the LOIC â3 and â4 were inconsistent with a broad dissimilarity pattern, because â3

118 Results

was significantly different from zero, and â4 (â4 = b̂3 − b̂4 + b̂5 = 0.00001) was not

significant negatively different from zero.

As a result, the response surface in Figure 1 did not had a U-shape as it would

have had in case of a congruent pattern of age-dissimilarity outcomes. The

dissimilarity response surface parameter results indicated that more and more age

dissimilarity per se was not related to lower performance evaluations.

Regarding Hypothesis 1, we assumed that leader-age dissimilarity has a

positive effect on performance evaluations of the subordinate but only, when the leader

is younger than the subordinate. Supporting our hypothesis, the present response

surface parameter pattern revealed an optimal margin effect (â3 ≠ 0) (Baumeister,

1989; Edwards; 2002; Edwards & Parry, 1993). As shown in Figure 1, independent of

the level, the performance evaluation was maximal for subordinates who were older

than their leaders to a certain extent. This finding was visualized by the dashed line in

Figure 1 representing the FPA shifted in the opposite direction to the LOC. However,

what is important is that we could not find the opposite result in dyads, when

subordinates were younger than the leaders.

Additional Findings

Additionally, we found a main effect of leader age and subordinate age on

performance evaluations: Leader-subordinate dyads which have a higher age (leader

and subordinate are both older) were related to lower subordinate performance

evaluations by the leader. The response surface in Figure 1 suggested the vertex to be

located at the back end of the LOC because of the significantly negative parameter â1

(slope along the LOC).

119 Discussion

Figure 8. The average response surface is relating leader age and subordinate age with

performance evaluations. LOC and LOIC are represented as blue lines at the bottom

and surface of the graph. The LOC starts in the front corner and goes diagonally

straight to the back corner. Perpendicular to the LOC, the LOIC connects the corner

of the cube from the left to the right side. A bagplot on the surface limits the region of

the interpretable data. The dashed lines at the bottom and surface represent the FPA.

Discussion

Given an increasingly multigenerational workforce, demographics in

organizations create alternative compositions of leader and subordinate combinations.

We began this study by arguing that the specific constellation of leader-subordinate

age dissimilarities matter for job related outcomes. Traditional career schemes of

organizations have been altered by new age structures. Consequently, the odds are

increasing that older employees will report to younger leaders (Cappelli & Novelli,

2010). In this study, we explored the prevalent influences of age dissimilarity in non-

traditional leader-subordinate constellations on performance evaluations. The puzzle

was why there are asymmetrical and opposite effects of age dissimilarity on

performance evaluations in non-traditional leader subordinate dyads to those we would

120 Discussion

typically expect by the similarity-attraction paradigm (Byrne, 1971). We were

interested in the question, of how leaders evaluate the performance of subordinates

when the leader is younger than the subordinate.

Our aim was to explain asymmetrical effects of leader-subordinate age

dissimilarities in non-traditional leader-subordinate constellations with the shifted

standard model (Biernat & Manis, 1994). We used the shifted standard model to

explain how bias can explain positive effects of age dissimilarity on performance

evaluations (Biernat et al., 1991; Biernat & Manis, 1994). Our theoretical predictions

were compared with empirical company data: They showed that leader-subordinate

dyads were related to the highest evaluation of subordinate performance, when the

leader is younger than the subordinate to a certain extent.

Additional findings indicated that older leaders evaluate the performance of

older subordinates relationally lower. Taken together, asymmetrical effects of age

dissimilarities in leader-subordinate dyads were related to higher performance

evaluations when the leader is younger than the subordinate. This finding was in line

with our theoretical prediction on the relationship between younger leaders and older

subordinates based on the proposition that positive performance evaluations of older

subordinates are evoked by a leader’s positive bias due to age stereotypes.

Contributions

The contributions of our study are two-fold starting from the theoretical

background and continuing to the methodological contributions. From a theoretical

point of view, the similarity-attraction paradigm examines how demographic

similarity or dissimilarity of an individual in relation to group members or in a dyad

affects job related outcomes (Byrne, 1971; Tsui & O'Reilly, 1989).

121 Discussion

Tab

le 7

Mea

ns,

Sta

ndard

Dev

iati

ons,

and C

orr

elati

ons

of

the

Stu

dy

Vari

able

s

Var

iab

le

M

SD

1

2

3

4

5

1.

Sub

ord

inat

e p

erfo

rmance

1

.03

0.0

8

2.

Sub

ord

inat

e ab

sente

eism

2

.16

10

.60

-.0

3

3.L

ead

er g

end

er

0.7

0

0.4

6

-.0

3

-.0

5*

4.

Lea

der

age

44

.6

8.1

3

-.1

8**

.04

.16

**

5.

Sub

ord

inat

e ag

e

42

.82

11

.48

-.1

7**

.01

.12

**

.1

6**

6.

Sub

ord

inat

e te

nure

1

29

.15

11

5.7

0

-.1

0**

-.0

4

.11

**

.1

3**

.5

7**

Note

: N

= 1

386;

* p

< .0

5. ** p

< .01.

122 Discussion

Table 8

Multilevel Polynomial Regression Model Results of the Predictors of Performance

Evaluation

Parameter Model

Fixed Effects

Coefficient (SE)

Intercept 1.046000*** (0.07248)

Subordinate age -0.000541* (0.00024)

Leader age -0.001860*** (0.00053)

Subordinate age2 -0.000036* (0.00002)

Subordinate age2 × Leader age2 0.000019 (0.00002)

Leader age2 0.000058 (0.00004)

Subordinate absenteeism -0.000144 (0.00017)

Leader gender -0.002634 (0.00780)

Subordinate tenure 0.000002 (0.00002)

Random Parameter

Variance (SD)

Intercept 0.001613 (0.04016)

Observations 1386

Marginal R2 / Conditional R2 0.037 / 0.300

Note. Standard errors are in parentheses for fixed effects. Standard

deviation is in parentheses for the random parameter. * p < .05. ** p < .01.

***p < 001.

Table 9

Results for the Average Response Surface

Parameter Value SE z p

â1 - 0.00242 0.00055 -4.360 <.001

â2 -0.00004 0.00005 -0.928 .35

â3 -0.00135 0.00057 -2.335 .02

â4 -0.00001 0.00005 -0.183 .85

â5 -0.00009 0.00005 -1.857 .06

Note. The estimated regression coefficients were b̂1 = -0.000541, b̂2 = -.001860,

b̂3 = -,0.000036, b̂4 = 0.000019, and b̂5 = 0.000019; â1 = slope along line of

congruence; â2 = curvature along line of congruence; â3 = slope along line of

incongruence; â4 = curvature along line of incongruence; â5 = FPA equals the

LOC

123 Discussion

For our study, this theory served as the basis to understand and extent the

research on age dissimilarity influences on performance evaluations. The first

theoretical contribution is that we added to this research by examining asymmetrical

effects of age dissimilarity influences in non-traditional leader-subordinate

constellations. Although, several findings have supported the similarity-attraction

paradigm (e.g., Tsui & O'Reilly, 1989), it was limited in its ability to explain

asymmetrical effects of age dissimilarity. We aimed to show that age dissimilarity in

dyads asymmetrically responded to subordinate performance evaluations.

In this study age dissimilarity corresponds to increased subordinate

performance evaluation, when the leader is younger than the subordinate but revealed

no influence in the opposite direction when the leader is older than the subordinate.

Previous research has studied asymmetrical age dissimilarities exclusively on group

level (Chattopadhyay, 1999), or they used predominantly gender and race as

demographic measures (Brief et al., 2005; Tsui et al., 1992). In this study, we extended

the research on relational demography by exploring asymmetrical influences of age

dissimilarity on a dyadic level. Age dissimilarity in this two-person relation gives us a

more profound and detailed understanding of how the direction of age dissimilarities

matters to leader and subordinate work-related outcomes.

Our second contribution is about the shifting standard model (Biernat et al.,

1991; Biernat & Manis, 1994) as a theoretical extension of the similarity-attraction

paradigm (Byrne, 1971). We applied the model with the goal to shed light on the

inconsistent findings reported in the literature on age dissimilarity effects on

performance outcomes. The shifting standard model illustrates how leaders that are

influenced by age stereotypes apply different evaluation standards for older

subordinates to evaluate their performance (for empirical studies see e.g., Colella,

DeNisi, & Varma, 1998). Therefore, paradoxically the performance evaluation of a

124 Discussion

low status individual can be high. This positive bias, induced by leader age stereotypes

on older subordinates is associated with a low subordinate status (Biernat et al., 2010).

Using the similarity-attraction model in isolation would let us assume that age

dissimilarity constantly results in low performance evaluations independent of the

direction of age dissimilarity between leader and subordinate. By extending the

similarity-attraction paradigm, we can explain positive performance evaluations as an

outcome of age dissimilarity in non-traditional leader-subordinate constellations

evoked by age stereotypes a leader might have on older subordinates. Therefore, we

add to the existing literature on age and relational demography. This is especially

relevant to gain more scientific knowledge on asymmetrical age-related outcomes in

the barely researched composition of younger leaders and older subordinates in dyads,

which constitutes the third theoretical contribution.

This study also makes a major methodological contribution providing an

alternative method to measure demographic dissimilarity without losing data

information. Previous empirical studies used primarily difference scores

(Chattopadhyay, 1999; Liden et al., 1996) to measure relational demographic

differences. We offered RSA as an alternative to overcome the limitations of the

difference score method (Edwards, 2001, 2002; Edwards & Parry, 1993). RSA made

it possible to test more elaborate forms of dissimilarity effects than traditional

difference scores (Edwards, 2002; Nestler et al., in press).

A second methodological contribution is that we applied multilevel RSA

(Nestler et al., in press) as a new methodological approach with the aim of taking

account for data with a nested structure in the leader-subordinate dyad. The findings

of this study provide opportunities for more research on demographic variables, such

as race or gender. The RSA modelling revealed small age dissimilarity effect sizes for

direct, and optimal margin effects. Hence, there certainly is a valid reason to consider

125 Discussion

the effect relevant, as the differences in percentage of the performance evaluation are

clearly visible (see also Figure 1).

Implications

In addition, our study has direct practical implications. Our findings revealed

that the direction of age dissimilarity in leader-subordinate dyads matters – but not any

constellation of age dissimilarity affected organizational outcomes. The results of our

investigation point out the underlying susceptibility to leader performance evaluation

bias due to age stereotypes. The bias problem that these performance evaluations

create is particularly acute in leader-subordinate dyads, when the subordinate is older

than the leader. Accordingly, one practical implication is to consider the influence of

age dissimilarities in organizations (Cappelli & Novelli, 2010), and to realize that

associated age stereotypes (Posthuma et al., 2012) can create an obstacle which can

result in biased performance evaluations of subordinates.

Our data alone cannot show what kind of consequences biased performance

evaluations have for subordinates. Hence, we can say that demographic differences,

such as age dissimilarities influence performance evaluations and one explanation for

that phenomenon is bias. As a result, companies which use subjective leader

performance evaluations on one scale cannot know how accurate and objective their

performance measurement tool is. Therefore, we suggest that the main goal to

overcome the issue of a biased performance evaluation is the creation of an objective

performance evaluation tool for leaders and to prevent age-bias at work. We propose

three practical steps to improve how companies include age diversity without age-bias

und unrelated to evaluations of employees.

A first practical step of a company would be to identify if there is a problem

with age and associated stereotypes. The assessment of age distributions in the

126 Discussion

company would facilitate the work of practitioners considerably as they need to know

in advance how multigenerational their workforce is. If age dissimilarities in the

company are relevant, then it might be helpful to use people data to find out if there is

any correlation between age and performance. In addition, it might be useful to provide

data on possible age stereotypes by using a questionnaire to assess leaders’ and

employees’ age stereotypes. In a third step, we would suggest for practitioners to

review the scale on which subordinates are evaluated by leaders critically. Evidence

from a variety of literature showed the detrimental influence of age dissimilarities on

biased performance evaluations in dyads (Tsui et al., 2002; Tsui & O'Reilly, 1989).

We offer two potential solutions, based on the different issues a company might

face. First, we suggest to train leaders to reduce bias in evaluations by applying

strategies to help deliberate processing instead of relying on easily available heuristics

(Fiske & Neuberg, 1990). Suppressing age-related thoughts is likely to be the first

thought that comes to mind when thinking about training to reduce bias in performance

evaluations. However, research showed that trying to ignore thoughts on age-

dissimilarities between ratees even resulted in more negative evaluations (Kulik, Perry,

& Bourhis, 2000). A rater training of those who evaluate employee performance can

additionally be supported by providing initiatives to raise awareness and prevent bias

at work on company level (e.g., Kunze, Boehm, & Bruch, 2011), which makes a

second practical contribution towards a fair performance evaluation system without

bias.

We recommend practitioners to keep in mind that leaders who evaluate

subordinate performance might have a certain level of in-group identification who they

perceive as similar or dissimilar in age to themselves (Tsui & O'Reilly, 1989). This

also might have a strong influence on ratings and should be included in people training.

127 Discussion

Limitations

The first limitation is that in this study, performance evaluations of

subordinates were subjectively rated by the leader on a percentage scale. In line with

our theoretical model, we assumed that those ratings are influenced by leader biases.

We supported our assumptions by introducing absenteeism as one control variable for

performance (Ng & Feldman, 2008). Adding our control variables did not change the

results, which theoretically indicated that identities and categorizations played a role

for the leader, and leader bias affected performance evaluations of the subordinate

(Roberson et al., 2007). Despite this control, it stays somehow unclear if the ratings

represented the actual performance of subordinates, and whether the evaluations were

accurate. Certainly, experimental research is necessary to validate these findings.

Another limitation of our research is that the test for the optimal margin effect

in the RSA was of explorative nature (Edwards, 2002). Therefore, future studies are

needed to cross-validate the optimal margin effect and the detected direct effect.

Further limitations of our research include that the nature of this study precludes any

inference about causal and effect relationships. Yet, we justified and explained the

predictions we tested. Our test theory makes unique and certain theoretical predictions.

Therefore, in our opinion the prediction seems to be fair and moves into the right

direction. Adding a multilevel moderator into our model might be helpful to clarify the

mechanisms behind a cause and its effect (King, Keohane, & Verba, 2012). The aim

of our field study was to provide external validity, and we showed the ability to

generalize from a limited set of observations. Previous research has found concurrent

and prospective associations between age dissimilarities and performance evaluations

in leader-subordinate dyads; still, only experimental research can establish causal

relationships. Lastly, our research was conducted with data from a single company in

128 Discussion

Switzerland. This makes it hard to generalize our findings to other countries with

different demographic structures.

Future Directions

Finally, we want to point out several avenues for future research. First, future

research might usefully add the shifted standards model to the relational demography

theory to explore how leader age or other demographic stereotypes influence work

related outcomes of a subordinate or a group. For example, employee turnover

intentions would be interesting to investigate in this context (e.g., Buengeler et al.,

2016). A second direction for future research in this context is to explore how leader-

subordinate age dissimilarity affects work related outcomes from the perspective of

the subordinate. Usually, subordinates or groups rate their leaders once a year in an

annual survey. Evaluations of the leader might also be biased due to age dissimilarity

influences between rater and rate (e.g., Zacher & Bal, 2012). Similarly, on the

methodological side, one could apply dyadic response surface analysis (Schönbrodt et

al., 2018) to investigate how age (dis)similarity is related to a dyadic work-related

outcome for both, leader, and subordinate (e.g., Zacher, Rosing, Henning, & Frese,

2011).

Further, self-evaluations of leaders also should be regarded in comparison with

leader evaluations of subordinates. Which brings us to the next point. It is vitally

important that future research considers the relationship between leader and

subordinate as a mechanism that can change asymmetrical age-dissimilarity outcomes

such as performance evaluations. Leader-member-exchange (LMX) measures (Graen

& Uhl-Bien, 1995) should be included as an intervening variable in future research, as

LMX might moderate the nature of the relation between asymmetrical leader-

subordinate age dissimilarity and work-related outcomes. Adding affective and

129 Discussion

emotional factors will be an important aspect of the future work to shed more light on

theoretical models about bias beside cognitive processes (e.g., Ferris, Judge, Rowland,

& Fitzgibbons, 1994). This might raise interesting questions in combination with

relational demography theory such as how age dissimilarity and emotions lead to a

higher or lower evaluation bias of performance on different levels. For example, the

emotion workplace envy might affect performance evaluation of age dissimilar dyads,

by changing the evaluation standard a leader confers to a subordinate.

Then, an interesting future work lies in the integration of group level factors in

the multilevel RSA, to address whether age dissimilarity processes at the dyadic level

are transferable to the group level. Adopting a longitudinal design in future research

would provide an interesting path to understand the evolution of asymmetrical age

dissimilarity effects in leader-subordinate dyads. Further research is needed to identify

precisely if positive or negative bias is present in leader evaluations of subordinate

performance by comparing subjective supervisor evaluations with previous

evaluations or objective measurements (Ng & Feldman, 2008).

Another interesting direction of future research refers to an unexpected

directional effect. The additional finding, not anticipated by our theoretical

assumptions, was when both leaders and subordinates are relatively old, subordinates

received lower performance evaluations. It could be interesting to examine “older”

dyads in context with research on biased age stereotypes and associated status

attributions. Further, it would be interesting to analyze how standards and accuracy of

performance evaluations change with leader age. Because our research was conducted

in the insurance- and finance industry, age stereotypes are more present than in other

organizations (Posthuma & Campion, 2009). Therefore, one might include the “type

of industry” as a contextual factor in future research to see if a special industry is more

130 Discussion

vulnerable for positive or negative biased performance evaluations due to age

dissimilarities, and what kind of resources would be necessary to buffer contextual

effects. In summary, our study confirms that the integration of asymmetrical relational

demography and bias research opens an exciting avenue for future research.

Conclusion

We began this study by arguing that the direction of effects matters for work

related age dissimilarity outcomes in dyads. In particular, we suggested that leader-

subordinate age dissimilarities were positively related to performance evaluations,

when the leader was younger than the subordinate to a certain extent. We imply that

age stereotypes about older subordinates can change the evaluation standards of

leaders and play a role in positive age biases of subordinate performance evaluations.

Finally, our overall implication is that effects of age dissimilarity on performance

evaluations in non-traditional leader-subordinate constellations are not uniform: they

are asymmetrical, and direction matters for age dissimilarity effects in dyads.

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150 Eigenabgrenzung

Eigenabgrenzung

Die Grundlage der vorliegenden Forschungsartikel meiner Dissertation bilden

interdisziplinäre Kooperationen und ich danke meinen Ko-Autoren für ihre darin

eingebrachte Arbeit, ihre Ideen und ihr Wissen. Grundsätzlich zeigt die Reihenfolge

der Autoren eines Artikels, welchen Umfang der Beitrag des jeweiligen Autoren hatte.

Unten stehend möchte ich offen legen, welche Beiträge ich selbst zu jedem der Artikel

geleistet habe.

Forschungsartikel I

Mitwirken an den folgenden Aspekten: Präzisierung des theoretischen Rahmens,

Erhebung und Auswertung der Daten, Interpretation und konzeptuelle Einordnung der

Ergebnisse, Erstellung von Teilen des Manuskripts.

Forschungsartikel II

Mitwirken an den folgenden Aspekten: Entwicklung der Idee und Konzeptualisierung

der Studie, Programmierung des experimentellen Paradigmas, Datenerhebung- und

Analyse der Daten, Interpretation und konzeptuelle Einordnung der Ergebnisse,

Erstellung des Manuskripts.

Forschungsartikel III

Mitwirken an den folgenden Aspekten: Akquise der Unternehmensdaten,

Ausarbeitung der Idee und Konzeptualisierung der Studie, Datenaufbereitung- und

Analyse der Daten, Interpretation und konzeptuelle Einordnung der Ergebnisse,

Erstellung des Manuskripts.

leadership and team-regulation effects on performance

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