market orientation, innovativeness, and performance of food companies

7/27/2019 Market Orientation, Innovativeness, And Performance of Food Companies

1/22

Journal of Agribusiness 27, 1/2 (Spring/Fall 2009): 85106 2009 Agricultural Economics Association of Georgia

Market Orientation, Innovativeness, and

Performance of Food Companies

Aaron J. Johnson, Clay C. Dibrell, and Eric Hansen

Food processors have seen escalating levels of competition over the past threedecades. An underlying objective of this research is to gain a greater under-

standing of how food companies thrive in the face of this increased competition.This study incorporates market orientation theory (competitor orientation,customer orientation, and interfunctional coordination) and firm innovativeness toexplain differences in firm financial performance. A national survey of food

processors was conducted and structural equation modeling was used to test thehypotheses. The results show that the more successful firms are more internallyfocused (interfunctional coordination and innovativeness) than externally focused(competitor and customer orientation).

Key Words: firm performance, food industry, innovativeness, market orientation,structural equation modeling

Agribusinesses, especially food companies, have seen escalating levels of compe-tition over the past three decades (van Duren et al., 2003), creating significantchallenges to maintaining economic viability. An even greater challenge thansurvivability is the development of the means by which the agribusiness firm canthrive in the face of this increased competition.

Previous studies have examined the performance of agribusinesses. For example,van Duren et al. (2003) found that specific managerial factors were considered bymanagers to influence profitability. Other studies (e.g., Schumacher and Boland,2005; Pendell and Boland, 2005) report that firm factors (i.e., firm resources) aredominant in explaining performance. Despite the usefulness of studies like these,they do not exhaust the issue. Van Duren et al. employed a case study approach,interviewing only five firms. The small number of observations limits the study inoffering generalizations to the food industry, let alone other agribusiness industries.The Boland studies applied regression analysis to a larger data set to identify thesource of variance in return on assets. However, the data sets were comprisedof secondary data, and neither of the Boland studies looked at the specific resources

Aaron J. Johnson is assistant professor of agribusiness, Department of Agricultural Economics and RuralSociology, College of Agricultural and Life Sciences, University of Idaho; Clay C. Dibrell is associate professor ofmanagement, Department of Management, School of Business Administration, University of Mississippi; and EricHansen is professor of forest products marketing, Department of Wood Science and Engineering, College ofForestry, Oregon State University. This research was supported by USDA-National Institute of Food andAgriculture Multicommodity Research funds.


2/22

86 Spring/Fall 2009 Journal of Agribusiness

or functions undertaken by the firms to obtain higher performance. While thesestudies note the importance of firm factors, additional analysis is needed tounderstand specific actions.

More can be learned about creating a competitive advantage in a highly com-petitive market environment like that of the food industry. Additional theory andtools from the management and marketing sciences offer an opportunity to gaingreater insights into the functions of agribusiness firms that influence firmperformance. Accordingly, we borrow from these disciplines through applicationof market orientation theory linked with a firms innovation practices (i.e.,innovativeness) to more aptly explain the path to greater firm performance in thefood industry.

Market orientation has been mentioned in qualitative studies (van Duren et al.,2003) in the agribusiness field, but few studies have directly tested hypothesizedrelationships in a quantitative manner. In addition, no earlier studies have focusedon the U.S. market. Our study is based on a U.S. national survey of food proces-sors, ranging from small to large, to determine what impact market orientationand innovativeness have on firm performance.

A brief review of the theory and related literature is provided, followed by thedevelopment of testable hypotheses. The survey method employed and the chosenstatistical approach, structural equation model estimation, are explained in somedetail. The results are discussed and implications are drawn for management infood firms. Finally, the studys limitations are discussed along with ideas forfurther research.

Theoretical Background

Market Orientation

Kohli and Jaworski (1990) and Narver and Slater (1990) were early pioneers ininvestigating market orientation. According to Narver and Slater, market orienta-tion consists of a focus on customers (customer orientation), an intimate under-standing of competitors (competitor orientation), and integration of all functionswithin the company to create superior customer value (interfunctional coordin-ation). Providing superior customer value is key for maximizing long-term profit(Narver and Slater) and sustainable competitive advantage (Kumar, Subramanian,

and Yauger, 1998). Active integration of functional groups within the companyto create superior value results in a behavioral culture that guides the wayemployees think and act (Dobni and Luffman, 2003).

Market orientation has seen extensive consideration in the literature during thepast two decades. Much of the work focuses on the impact of market orientationon firm performance. For example, of 36 studies investigated by Dawes (2000), atotal of 33 found some positive connection between market orientation and firmperformance. Growing evidence of a positive market orientation-performance linkhas generated increasing interest, and researchers have worked to better understand


3/22

Johnson, Dibrell, and Hansen Food Company Performance 87

the role of other phenomena in conjunction with the market orientation-performance relationship. Sufficient work with varying results has been con-ducted that Ellis (2006) performed a meta-analysis on previous work in an effortto sort out relationships among variables. Ellis relevant findings include evidenceto classify market orientation as a generic determinant of firm performance.However, the study found that (a) effects were stronger in large, mature markets;(b) Kohli, Jaworski, and Kumars (1993) MARKOR scale showed stronger effectsthan other scales; and (c) the managerial value of market orientation is affected bycultural and economic characteristics of the host country.

Despite the collective research, market orientation has seen limited attention inthe natural resources fields (Hansen, Dibrell, and Down, 2006; Hansen et al.,

2006; Narver and Slater, 1990), and surprisingly little work has been conductedspecific to agriculture (Martino and Tregear, 2001; Micheels and Gow, 2008a, b).Of the studies identified in our literature search, none investigated food firms inthe United States. Both studies by Micheels and Gow examined the agriculturalproduction sector. Martino and Tregear, and Mavondo and Farrell both investi-gated the food sector, but their focus was on Chile and Zimbabwe, respectively.Whereas Martino and Tregear (2001) had a small number of responses whichprohibited their ability to test the market orientation-performance connection,Mavondo and Farrell found no connections between market orientation andperformance with respect to 176 food manufacturing businesses in Zimbabwe.

Several qualitative/exploratory studies have been conducted. Kyriakopoulos,Meulenberg, and Nilsson (2004) considered the structure of Dutch cooperatives

on market orientation and performance, but did not specifically evaluate the linkbetween market orientation and performance. Lewis, Pick, and Vickerstaff (2001)studied three UK food and drink companies. They found the companies viewedmarketing rather negatively, yet concluded they were market oriented sincethey recognized customer concerns. Ottesen and Grnhaug (2005) investigatedmarket orientation understanding and practice within the Norwegian seafoodindustry, but did not consider performance issues. Finally, van Duren et al. (2003)concluded that aspects of customer orientation interact with other managementcharacteristics to help firms achieve success. However, their study was based onin-depth interviews with only five Canadian food companies.

Market Orientation and Innovativeness

Recent research has examined linkages of such topics as innovation (Han, Kim,and Srivastava, 1998; Hult, Hurley, and Knight, 2004), entrepreneurship (Hurleyand Hult, 1998; Matsuno, Mentzer, and zsomer, 2002), and the learning organi-zation (Hurley and Hult, 1998; Slater and Narver, 1995) with market orientation.Specifically, our research will test the connection between market orientation andinnovativeness. In its most basic definition, innovation is considered the adoptionof something new (Rogers, 2003). Hansen et al. (2006) define innovation as crea-tion and/or adoption of new ideas, processes, products, or services that are intended


4/22


to increase value to the customer and contribute to the performance or effective-ness of the firm. Innovativeness is slightly different from innovation because it isa characteristic of an individual or organization. The literature generally refers tonew products, processes, or business systems as general categories of innovationand/or innovativeness (Boer and During, 2001; Hovgaard and Hansen, 2004; Northand Smallbone, 2000).

According to Narver and Slater (1990), market-oriented firms tend to be moreinnovative, thus resulting in improved financial performance. For example, market-oriented firms are able to better adapt to changes in the environment, allowing forincremental innovation (Baker and Sinkula, 2002). A customer-centric cultureresulting from a market orientation creates opportunities for innovation via

customer ideas and expressed needs. Similarly, closely following competitormoves also facilitates innovation as the market-oriented company meets innova-tion adopted by the competition. Finally, interfunctional coordination allows ideasto flow across the organization, bolstering its ability to bring new product andservice concepts to fruition. The Hult, Hurley, and Knight (2004) study affirmsthis last connection, and it is supported by Woodside (2005).

As outlined above, it is not surprising that market orientation is claimed to bean antecedent to firm innovativeness (Han, Kim, and Srivastava, 1998; Jaworskiand Kohli, 1993: Narver and Slater, 1990). Han, Kim, and Srivastava were thefirst to explicitly test this relationship. Their work showed innovativeness to be amediator in the market orientation-performance relationship. Specific to agribus-iness firms, Mavondo and Farrell (2003) show that market orientation positively

impacts product innovation, and product innovation positively impacts financialperformance, thus inferring mediation by product innovation.

Hypotheses

Slater and Narver (1999) state that theory and empirical evidence suggest higherlevels of market orientation lead to enhanced performance, while other researchersare even stronger in their support of this notion (Kumar, Subramanian, andStrandholm, 2002). Still, Harris (2001) questions this conclusion after finding alimited market orientation-performance relationship when utilizing an objectivemethod for measuring performance. Little work has been done in testing thisrelationship with respect to U.S.-based food firms. Given the predominant

research finding is a positive relationship between market orientation and firmperformance, the first hypothesis is written with that expectation:

H1.Market orientation positively impacts food company performance.

Innovativeness, the propensity to create and/or adopt new products, processes,or business systems, positions a company well for developing new value for itscustomers. For example, a new product can better meet a customer need, there-by providing greater value. More efficient processing can lower manufacturercosts and subsequently result in a lower price for customers, again providing greater


5/22


6/22


mass of managerial capabilities necessary to implement market orientation andinnovation strategies (Swan and Newell, 1995).

After applying the aforementioned restrictions and removing 461 respondentsdue to reasons such as an incorrect address, request by the respondent to beremoved from our mailing list owing to company policy, or the respondent did notmeet the top management team position criterion, we received 358 usable surveysfor a response rate of 9.2%. Of those, 259 respondents completed all the questions.Our response rate is comparable to 10 to 12 percent typical for mailed surveys totop executives (Hambrick, Geletkanycz, and Fredrickson, 1993, p. 407), and ison par with other food industry-oriented surveys (Kinsey, Kaynts, and Ghosh, 2007).

The effects of nonresponse sample bias were tested by comparing a random

subsample of 50 firms from the early respondents (survey wave 1) versus arandom subsample of 50 firms from the late respondents (survey wave 2). Laterespondents often possess firm characteristics which are similar to those of non-respondents (Armstrong and Overton, 1977). No statistically significant differ-ences of the studied constructs were found between the two subsamples.

Since a survey design was used to gather the data, the data were examined forthe presence of common method bias. Following Harmans(1967)recommenda-tion, a principal components factor analysis was utilized in which commonmethod bias could be indicated if only one factor, or one factor that accounted foran extensive amount of the variance in the unrotated factor structure, were to beproduced. The factor analysis produced five factors reflective of the constructsbeing studied with Eigenvalues greater than one. The first factor accounted for 27%

out of a total of 60% of the explained variance, suggesting that the presence andeffects of common method bias were insignificant on the outcome of the study .

Questionnaire Development and Measures

Measurement scales employed for this study are well-established in the strategicmanagement and marketing extant literatures. For the market orientation and inno-vativeness scales, interval scales with anchors ranging from 15 (with 1 = not atall and 5 = to an extreme extent) were used (see the appendix for surveyinstrument excerpts).

Market Orientation

Given the fewer items in MKTOR and its superior statistical reliability overMARKOR (Pelham and Wilson, 1996), Narver and Slaters (1990) scale for marketorientation was selected as the basis for this study. Modifications based on addi-tional work by Lukas and Ferrell (2000) were made to the scale and an 11-item,three-dimension scale was employed to capture the extent of respondents firmorientation toward their markets. For all statistical tests, market orientation wasorganized into the following three factors as suggested by Narver and Slater:competitor orientation, customer orientation, and interfunctional coordination.


7/22


Innovativeness

To assess firm emphasis on innovation, a scale was adapted from Dess and Davis(1984) and Davis, Dibrell, and Janz (2002). This scale was selected as it focuseson a firms overall strategic emphasis on innovation and does not delineatebetween product and process innovations. The intention is to develop a moreencompassing understanding of firm innovativeness and how it is related to otherbusiness processes.

Firm Performance

Publicly available performance data did not exist for the firms surveyed. Giventhe lack of archival or secondary forms of financial performance data, the approachrecommended by Dess and Robinson (1984) and other scholars in this area (e.g.,Davis, Dibrell, and Janz, 2002; Matsuno and Mentzer, 2000) was executed. Theseauthors suggest the use of self-reported measures of firm financial performance inrelation to competitors in the industry provided by respondents. For instance,respondents were given five choices on an interval scale including whether thefirm was in the bottom 20% of firm financial performance in its industry to thetop 20% of firm performance in the industry.

A criticism of this approach is that respondents may be tempted to inflatefinancial performance responses. However, Dess and Robinson (1984), in theirstudy of self-reported responses compared to archival sources of financial results,

found little difference between the two sets. They suggest that the use of self-reported firm financial performance is appropriate for studies of firms for whicharchival sources of financial data are unavailable. All scale items are provided intable 1.

Analysis

Like other research questions in management (e.g., Hansen and Morrow, 2003),the relationships in figure 1 lend themselves to being tested through structuralequation modeling to test the theoretical paths among the different dimensionsand measurement issues. Structural equation modeling is based upon the analysisof correlation or covariance structures and is used in causal modeling (Bollen,

1989). Likewise, it allows for both the structural model and measurement modelto be analyzed simultaneously. The structural model can be expressed as:

(1) , B whererepresents the latent endogenous variables, denotesthe latent exogen-ous variables, and represents the latent errors in the equations. is the coeffi-cient matrix for latent endogenous variables, and is the coefficient matrix forlatent exogenous variables (Bollen, 1989). The measurement model is representedby the following equation:


8/22


Table 1. Measurement Items Used for Study Scales

Market Orientation:

Competitor Orientation We rapidly respond to competitive actions that threaten us.

Our salespeople regularly share information within ourorganization concerning competitors strategies.

Top management regularly discusses competitors strengths andstrategies.

Customer Orientation We give close attention to after-sales service.

We constantly monitor our level of commitment and orientationto serving customers needs.

Our business objectives are driven primarily by customer

satisfaction. We measure customer satisfaction systematically and

frequently.

Interfunctional Coordination Our managers understand how everyone in our business cancontribute to creating customer value.

All of our business functions (e.g., marketing/sales,manufacturing, etc.) are integrated in serving the needs of ourtarget markets.

All the departments in our company are responsive to oneanothers needs and requests.

Our top managers from across the company regularly visit ourcurrent and prospective customers.

Firm Innovativeness:

Developing new products Upgrading existing products appearance and performance

Producing specialty products

Maintaining low levels of inventory

Innovation in production processes

Innovation in marketing techniques

Firm Performance:

Total Market Share Growth

Total Sales Growth

Return on Sales

Return on Assets

(2) ,

,

x

y

x

y

where x is the symbol for the observed indicators of,and y is the symbol for theobserved indicators of; x denotes the coefficients relating x to , andy thecoefficients relating y to . The measurement errors forx and y are defined by and , respectively (Bollen).


9/22


Additionally, this method allows for testing of direct and indirect effects amongthe dimensions (Kline, 2005). Moreover, using structural equation modelingprovides the following three advantages over other statistical techniques such asmultiple regression (Miller and Drge, 1986, p. 548):

First, it models hypothetical constructsknown as latent variablesby speci-fying the error-in-variables measurement structure (Jreskog, 1969; Jreskog,1970). Second, [the structural equation modeling statistical technique] simul-taneously estimates a system of structural equations that reflects the relation-shipswith errors in equationsbetween underlying latent dependent andindependent constructs (Jreskog, 1978; Jreskog and Srbom, 1984; Jreskogand Srbom, 1982), subsuming classical simultaneous-equation and path-

analysis models. Third, because it avoids the confounding of measurementand structural parameters and errors, [the structural equation modelingstatistical technique] is particularly suitable for the analysis of nonexperi-mental data.

Structural equation modeling demonstrates a robust and powerful statisticaltechnique for the examination of the proposed model. The graphic representationof the statistical analysis of this study is provided in figure 2, which offers moredetail than the conceptual model displayed in figure 1.

For structural equation modeling in this study, the covariance structure gener-ated from the collected data was used, as it is considered to be more robust thanthe correlation matrix (Kline, 2005). LISREL 8.52 was employed for the confirm-atory factor analysis (i.e., testing for invariance of the measurement model) and

for hypothesis testing. To calculate descriptive statistics, correlations, and inter-item reliability, SPSS 14.0 was utilized.

Results and Discussion

Before the model results are presented, we offer a brief description of the responsesobtained from the survey. A majority of respondent firms were 30-plus years old(46.5%) with only a small minority of firms being younger than three years(3.5%). Table 2 shows how the 259 usable responses were distributed across firmsize as determined by number of employees and how these firms break down withrespect to being family-owned. As expected, the number of responses is larger forsmaller firm size and the largest category of firm size had the lowest percentage

of family ownership. The size of sample firms was predominantly 1049 employees(55.6% of respondent firms), with only 9.7% of firms having more than 500employees. Approximately 87% of respondents in our sample identified them-selves as either the owner or CEO of the firm. The remaining respondentsclassified themselves as a vice-president (3.4%), general manager (7.3%), or oper-ations manager (2.2%).

These companies represent a smattering of product types and serve a variety ofsales channels. Figure 3 identifies the number of responses in different productcategories (when possible, these were classified along NAICS codes). Frozen food


10/22


1

2

21

1Competitor

Orientation

2Customer

Orientation

3Interfunctional

Coordination

1Innovativeness

2Performance

x11

x22

x33

x44

x55

x66

x77

x88

x99

x1010

x1111

11

11

31

42

52

6272

83

9310,3

11,3

11

21

12

13

22

23

21

32

31

y1 1

y2 2

y3 3

y4 4

y5 5

y6 6

y7 7

y8 8

y9 9

y10 10

21

31

41

51

61

72

82

92

10,2

21

Figure 2. Estimated hypothesized model

Table 2. Responses by Company Size (number of employees)

and Percentage Familial

No. of Employees Frequency % Family

1049 144 71

5099 44 64

100499 46 70

> 500 25 32

Total 259 66

manufacturing was the largest product category, followed closely by traditional

food-preserving methods such as canning and drying. The primary marketchannels these companies serve are as varied. Figure 4 breaks down the responsesby primary market channels served and by product category.

As reported in table 3, the studied constructs exhibit statistically significant(p < 0.05) relationships with other constructs in the correlation matrix whichwarranted further investigation. Additionally, there is no evidence of multicollin-earity among the constructs. Inter-item validity was indicated for the respectiveconstructs with the reported coefficient alphas ranging from 0.69 to 0.79, whichare within the acceptable range outlined by Nunnally (1978).


11/22


12/22


13/22


14/22


15/22


16/22


17/22


18/22


Dun and Bradstreet, Inc. (2004). Enhanced telemarketing record with NAICS codesand user area appended. Short Hills, NJ.

Ellis, P. D. (2006). Market orientation and performance: A meta-analysis and cross-national comparisons.Journal of Management Studies 43(5), 10891107.

Floyd, S. W., and B. Wooldridge. (1994). Dinosaurs or dynamos? Recognizing mid-dle managements strategic role.Academy of Management Executive 8(4), 4757.

Galbraith, J. R., and E. E. Lawler. (1993). Organizing for the Future: The New Logicfor Managing Complex Organizations. San Francisco: Jossey-Bass.

Gerbing, D. W., and J. C. Anderson. (1992). Monte Carlo evaluations of goodness-of-fit indices for structural equation models. Sociological Methods and Research21(2), 132160.

Gladwell, M. (2000). The Tipping Point: How Little Things Can Make a Big Differ-ence. Boston: Little, Brown, and Company.

Hambrick, R. C., M. A. Geletkanycz, and J. W. Fredrickson. (1993). Top executivecommitment to the status quo: Some tests of its determinants. Strategic Manage-ment Journal14(6), 401418.

Han, J. K., N. Kim, and R. K. Srivastava. (1998). Market orientation and organi-zational performance: Is innovation a missing link? Journal of Marketing62(4),3045.

Hansen, E., C. Dibrell, and J. Down. (2006). Market orientation, strategy, andperformance in the primary forest industry.Forest Science 52(3), 209220.

Hansen, E., S. Korhonen, E. Rametsteiner, and S. Shook. (2006). Current state-of-knowledge: Innovation research in the global forest sector. Journal of Forest

Products Business Research 3 (27 pp.). Online. Available at http://www.forest

prod.org/jfpbr-online.html. [Retrieved November 2008.]Hansen, M. H., and J. L. Morrow, Jr. (2003). Trust and the decision to outsource:Effective responses and cognitive processes. International Food and Agribusiness

Management Review 6(3), 4069.Harman, H. H. (1967). Modern Factor Analysis. Chicago: University of Chicago

Press.Harris, L. C. (2001). Market orientation and performance: Objective and subjective

empirical evidence from UK companies. Journal of Management Studies 38(1),1743.

Hovgaard, A., and E. Hansen. (2004). Innovativeness in the forest products industry.Forest Products Journal54(1), 2633.

Hu, L.-T., and P. M. Bentler. (1999). Cutoff criteria for fit indexes in covariancestructure analysis: Conventional criteria versus new alternatives. Structural

Equation Modeling6(1), 155.Hult, G. T. M., R. F. Hurley, and G. A. Knight. (2004). Innovativeness: Its ante-

cedents and impact on business performance. Industrial Marketing Management33(5), 429438.

Hurley, R. F., and G. T. M. Hult. (1998). Innovation, market orientation, and organi-zational learning: An integration and empirical examination. Journal of Marketing62(3), 4254.

Jaworski, B. J., and A. K. Kohli. (1993). Market orientation: Antecedents and conse-quences.Journal of Marketing57(3), 5370.


19/22


20/22


Mavondo, F., and M. Farrell. (2003). Cultural orientation: Its relationship withmarket orientation, innovation, and organizational performance. Management

Decision 41(3), 241249.McDonald, R. P., and H. W. Marsh. (1990). Choosing a multivariate model: Non-

centrality and goodness of fit.Psychological Bulletin 107(2), 247255.Micheels, E., and H. Gow. (2008a). Market orientation and profitability: Evidence

from homogeneous markets. Paper presented at 2008 annual meetings of theAgricultural and Applied Economics Association, Orlando, FL, 2729 July.

. (2008b). Market-driven entrepreneurship: The convergence of market orien-tation and the resource-based view. Paper presented at 2008 InternationalCongress, Ghent, Belgium, 2629 August.

Miller, D., and C. Drge. (1986). Psychological and traditional determinants ofstructure.Administrative Science Quarterly 31(4), 539560.

Narver, J. C., and S. F. Slater. (1990). The effect of a market orientation on businessprofitability.Journal of Marketing54(4), 2035.

North, D., and D. Smallbone. (2000). The innovativeness and growth of rural SMEsduring the 1990s. Regional Studies 34(2), 145157.

Nunnally, J. C. (1978).Psychometric Theory, 2nd edition. New York: McGraw-Hill.Ottesen, G. G., and K. Grnhaug. (2005). Exploring how managers conceive and

practice market orientation in near perfect food markets. Journal of FoodProducts Marketing11(2), 5974.

Pelham, A. M., and D. T. Wilson. (1996). A longitudinal study of the impact of marketstructure, firm structure, strategy, and market orientation culture on dimensions ofsmall-firm performance.Journal of Academy of Marketing Science 24(1), 2743.

Pendell, D., and M. Boland. (2005). Persistence of profitability in family-owned foodbusinesses. Paper presented at 2005 annual meetings of the American Agricul-tural Economics Association, Providence, RI, 2527 July.

Rogers, E. M. (2003).Diffusion of Innovations, 5th edition. New York: Free Press.Salant, P., and D. A. Dillman. (1994).How to Conduct Your Own Survey. New York:

John Wiley and Sons, Inc.Schumacher, S., and M. Boland. (2005). The effects of industry and firm resources

on profitability in the food economy. Agribusiness: An International Journal21(1), 97108.

Slater, S. F., and J. C. Narver. (1995). Market orientation and the learning organi-zation.Journal of Marketing59(3), 6774.

. (1999). Market-oriented IS more than being customer-led. Strategic Man-agement Journal20(12), 11651168.

Swan, J. A., and S. Newell. (1995). The role of professional associations in technol-ogy diffusion. Organization Studies [Walter de Gruyter GmbH & Co. KG] 16(5),847874.

van Duren, E., D. Sparling, C. Turvey, and L. Lake. (2003). An assessment of thestrategies and strengths of medium-sized food processors. Agribusiness: An Inter-national Journal19(1), 115132.

Woodside, A. G. (2005). Firm orientations, innovativeness, and business performance:Advancing a system dynamics view following a comment on Hult, Hurley, andKnights 2004 study.Industrial Marketing Management34(3), 275279.


21/22


22/22

market orientation, innovativeness, and performance of food companies

Documents