Copyright © 2010 by Theodore F. Piepenbrock Working papers are distributed in draft form for purposes of comment and discussion only. They may not be reproduced without permission of the copyright holder.

Toward a Theory of the Evolution of Business Ecosystems: Inter-Organizational Architectures, Competitive Dynamics, Firm Performance and Industrial Co-Evolution

Dr. Theodore F. Piepenbrock MIT Sloan School of Management

tfp@mit.edu

July 2010

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TOWARD A THEORY OF THE EVOLUTION OF BUSINESS ECOSYSTEMS: Inter-Organizational Architectures, Competitive Dynamics, Firm Performance & Industrial Co-Evolution

INTRODUCTION Dominant Designs, Disruptive Innovations and Dynamic Capabilities

Significant research exists in the field of technology and innovation management, which

has generated theory about the causes and consequences of technological innovation on the life-

cycles and evolution of firms and industries. While this research agenda has generated powerful

concepts like dominant designs (Abernathy & Utterback, 1978) and disruptive technological

innovations (Christensen & Bower, 1996; Adner 2002), a gap exists in understanding the

organizational mechanisms which both enable and constrain the evolution of technology and

innovation trajectories. My research therefore attempts to bring adjacent discourse to bear on

this topic, namely strategic management’s dynamic capabilities (Eisenhardt & Martin, 2000;

Teece et al., 1997) in order to build a theory of the evolution of innovation ecosystems.

Ecosystem Evolution and Inter-Species Competition

The question of how dynamic capabilities, which underpin the emergence of dominant

designs and disruptive technological innovations, are created and sustained over time motivates a

larger, more general question posed by evolutionary theorists in economics (Nelson & Winter,

1982; Nelson, 1991) and sociology (Hannan & Freeman, 1977; Carroll, 1993): “Why do firms in

the same industry vary systematically in performance over time?” My research, therefore seeks a

systematic explanation of a longitudinal phenomenon, which inevitably requires characterizing

the evolution of inter-species competition within the ecosystem as both the organizations (firms)

and their environments (markets and technologies) are co-evolving.1

1 Such an explanation must embrace questions about entry order of incumbents and newcomers (e.g. Mitchell, 1989), and will inevitably shed light on the industry structure vs. capabilities debate (Henderson & Mitchell, 1997).

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RESEARCH METHODOLOGY A Three-Stage Mixed-Methods Study

As building and testing grounded theory (Glaser & Strauss, 1967) of ecosystem evolution

implies the study of a longitudinal phenomenon, I employed a three-stage mixed-methods

research logic in which I collected and analyzed data and tested hypotheses from three temporal

regimes: past, present and future, using the following methods: historical comparative analysis,

field-based case studies and dynamic simulation modeling. Each is described below.

In-depth Field-based Case Study. I build grounded theory (Eisenhardt, 1989; Yin,

2003) from an in-depth, field-based case study, in which coding of observational, interview and

archival data, generated robust sets of constructs and propositions. The field-based data were

largely taken from over 3,500 hours of clinical methods participant observation (Schein, 1987)

and ethnography (Van Maanen, 1988) with over 200 managers and executives in the extended

enterprises of a competitive duopoly, spread over seven years from 2002 to 2009.

Historical Comparative Analysis. I extend the analysis back in time following methods

of business history (Chandler, 1962, Christensen, 1993; Penrose, 1960) using secondary data

sources in the theoretical sample. Historical data sources included public documents and official

records (e.g. annual company reports and SEC filings), private documents (e.g. internal company

memos) and mass media (e.g. interviews of leaders in the business press and trade journals).

Dynamic Simulation Models. In order to formalize and test the emerging theoretical

framework, dynamic simulation models were created to integrate the explicit causal structures

and to explore the dynamic behavior (Davis, Eisenhardt, and Bingham, 2007). The models

utilized a system of simultaneous differential equations (Forrester, 1961; Sterman, 2000), which

captured the interacting state variables of industry and firm growth.

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Research Setting & Empirical Sample

A theoretical sample (Eisenhardt, 1989; Yin, 2003) was chosen to expose and explain

variance in both the dependent variable (firm performance) and independent variable (inter-

organizational architecture), while balancing the needs for generalizability and parsimony in this

exploratory stage of grounded theory building. As a result, pairs of dominant firms (incumbent

and late entrant) were chosen from three industries ranging from manufacturing to services, and

in socio-economic environments including the US, Europe and Japan: Boeing and Airbus in the

global commercial airplanes industry, General Motors and Toyota Motors in the global

automotive industry, and United Airlines and Southwest Airlines in the US airline industry.

SUMMARY OF MAJOR FINDINGS

Technological and Market Environments. A review of longitudinal industry-level data

of the theoretical sample reveals the changing rates of market growth and technological

innovation over the life cycle of an industry as illustrated in the large commercial airplane

industry in Figure 1. As the rates of technological innovation change from increasing to

decreasing, product innovation gives way to process innovation (Abernathy & Utterback, 1978)

and late entrants attack incumbents in underserved markets (Christensen & Bower, 1995).

Inter-Organizational Architectures. Additionally, the architectures of the inter-

organizational strategic networks (Gulati, 1998) similarly appear to evolve from highly integral

forms (which facilitate radical, discontinuous innovation) to highly modular forms (which

facilitate incremental, continuous innovations), before a new class of late entrant disruptive

innovator begins again with integral organizational architectures (Afuah, 2001; Baldwin &

Clark, 2000). A representation of the evolution of the inter-organizational architectures of

Boeing and Airbus in the large commercial airplane industry can be seen in Figure 2.

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Technology and Market Strategies. Longitudinal firm-level data of the theoretical

sample reveals the evolution of strategies of the dominant firms in both technology quality (i.e.

what types of innovation – differentiation or cost leadership) and market quantity (i.e. how fast

to supply the market). Incumbents (General Motors, United Airlines and Boeing) begin as

discontinuous or disruptive innovators (Christensen & Bower, 1996) offering products/services

to under-served mass markets at increasing rates of both technological performance (Abernathy

& Utterback, 1978) and market quantities. Eventually, they over-serve the markets, maintaining

a trajectory of continuous or sustaining innovations at decreasing rates of both technological

performance and market quantities.

Late entrants (Toyota Motors, Southwest Airlines and Airbus) also begin as disruptive

innovators offering products/services to over-served markets at increasing rates of both

cost/quality performance and market quantities. Eventually, they over-serve the markets,

maintaining a trajectory of continuous or sustaining innovations at decreasing rates of both

cost/quality performance and market quantities. Table 1 illustrates qualitative examples of

senior leaders’ discourse regarding their strategies for technology quality while Figures 3-5

illustrate quantitative examples of strategies for market quantity.

Firm Performance. A review of the longitudinal financial data of both top-line revenues

and bottom-line profits of the theoretical sample reveals that late entrant disruptive innovators

having integral inter-organizational architectures (Toyota, Southwest and Airbus) outperform

incumbent sustaining innovators having modular enterprise architectures (General Motors,

United and Boeing) over the long term. Interestingly, these late entrants, which are not focused

solely on maximization of shareholder value, deliver significantly more shareholder value than

their incumbent competitors, who are focused on shareholder value maximization.

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SUMMARY OF THEORETICAL FRAMEWORK

Inter-Organizational Architectures. From these empirical findings, I propose a

typology of inter-organizational architectures (Gulati, 1998) based on constituent architectural

components: objective functions, enterprise boundaries and stakeholder interfaces, see Figure 6.

A continuum of inter-organizational architectures, possessing different dynamic capabilities,

spans between the polar types of modular and integral (Sanchez & Mahoney, 1996; Schilling,

2000). This primary construct underpins the definition of an “organizational species”, and lays

the foundation for a theory of “inter-species competition” (Brittain & Freeman, 1980).

Fit-Form-Function-Performance Framework. The theoretical framework is

comprised of four constitutive construct sets representing the highest-level system properties of

environmental fitness (Burns & Stalker, 1961; Lawrence & Lorsch, 1967), inter-organization

architectural form (Sanchez & Mahoney, 1996; Schilling, 2000), firm function (Porter, 1980) and

performance. These constructs are linked by four pairs of propositions representing

technological innovation and market maturity variables as shown in Figure 7. The theoretical

framework also captures the evolutionary processes of variation, selection and retention, as

expressed in evolutionary sociology (Aldrich, 1979) and evolutionary economics (Nelson &

Winter, 1982). The framework captures the path-dependent evolution of heterogeneous

populations of inter-organizational architectures engaged in symbiotic inter-species competition

and posits the evolution of dominant designs in inter-organizational architectures that oscillate

between modular and integral states throughout an industry’s life-cycle. Architectural

innovation – at the extended enterprise level – is demonstrated to contribute to the failure of

established firms (Henderson & Clark, 1990; Tushman & Anderson 1986), with causal

mechanisms developed to explain tipping points as described in Figure 8.

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TABLES & FIGURES

Table 1: Sample Qualitative Data on Firm Strategies for Technology Quality

Industry Focal Firm (Architecture)

Quotation (Source)

Boeing (Modular)

“In 1966 The Boeing Company will observe its fiftieth anniversary. It is difficult to conceive any other half-century in man’s history more stimulating, challenging and more rewarding. In those fifty years man’s scientific and technological progress has surpassed the total of such advancement in all previous history, and Boeing is proud to have played a leading role in that fantastic acceleration. There is a moment now for a rededication to the next fifty years, and the next, and the next...” (Source: The Boeing Company, Annual Report, 1965). “Our products bring better value to our customers, and our pricing reflects that value. We also have a responsibility to our shareholders, and that means pricing that allows us to make our financial goals. Do I think that we will ever be the lower-price option? No. Do I think that should keep us from gaining more than 50 percent market share? I answer "no" to that as well. (Source: Scott Carson, Vice President of Sales, Boeing Commercial Airplanes, Boeing Frontiers, April 2005). “Fundamental, game-changing innovation like that we’re pursuing on the 787 usually has a ‘bleeding-edge’ quality to it – meaning it goes beyond ‘leading edge’ into a realm where both the risks and the potential returns are high.” “We’re on the bleeding edge of taking a big, big step that was just a quarter step too far.” (Sources: Jim McNerney, Chairman & CEO, The Boeing Company; BusinessWeek, 23 April 2008; The Chicago Tribune, 22 May 2008).

Large Com- mercial Airplanes

Airbus (Integral)

“When we set up 30 years ago, Airbus’ goal was to pool European capabilities and technological resources to build an aircraft that would reliably and cost-effectively carry passengers in true wide-body comfort. The name Airbus is synonymous with lower operating costs for airlines. Airbus has continually increased its market share. Why? Operational efficiency is the first and last word in analyzing Airbus’s unique market success.” (Source: EADS Annual Report 2000).

General Motors (Modular)

“Here’s what’s new about GM’s strategy this year: Nothing.” “GM brought brand differentiation to the world in the 1920s. As the decades passed, and our product portfolio expanded, we slowly drifted away from that simple but effective strategy. Today the GM product revolution again is strengthening our brands.” (Source: General Motors Annual Report, 2003, pp. 3 and 8).

Auto-mobiles

Toyota Motors (Integral)

“Cost Reduction is the Goal: At Toyota, as in all manufacturing industries, profit can be obtained only by reducing costs. Cost reduction must be the goal of consumer products manufacturers trying to survive in today’s marketplace.” (Source: Taiichi Ohno 1978).

United Airlines (Modular)

“We have chosen to close our discount subsidiary, Ted in order to focus on our strengths in serving our premium customers – the historic source of our competitive advantage.”

U.S. Airlines

Southwest Airlines (Integral)

“Southwest’s business model, like that of Toyota, is to provide a low-cost product by utilizing its resources efficiently, while providing record levels of reliable service.” (Source: Jody Hoffer Gittell, 2003 pp. 3-4.)

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Figure 1: Technological Trajectory of the Commercial Airplane Industry

Figure 2: Evolution of Dominant Designs in Inter-Organizational Architectures:

Commercial Airplane Industry

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Figure 3: Quantity Growth of Competing Inter-Organizational Architectures in the Commercial Airplane Industry

Figure 4: Quantity Growth of Competing Inter-Organizational Architectures in the Automotive Industry

Figure 5: Quantity Growth of Competing Inter-Organizational Architectures in the US Airline Industry

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Figure 6: Typology of Inter-Organizational Architectures

Figure 7: Overview of Theoretical Framework

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Inter-species Competition in a Diffusing, Commoditizing Market. The framework defines the state of evolutionary maturity of the environment in two dimensions: quantity and quality – that is, how much product/service is produced/consumed, and what type of product/service is produced/consumed. This section combines these two characterizations of the market environment into one model, where two different species of firms (characterized by the architectures of their respective inter-organizational networks) compete. The extent of competitive intensity is defined by the ability of each firm to overcome architectural inertia and transition from niche D to niche C as the market evolves. A summary of the coupled system of differential equations is shown below. rX>rY when (X+Y)<K/2 rX<rY when (X+Y)>K/2

dX/dt = rXX – rXX2/D – rXXYαXY/K – rXXYαXY/(D+C)

dY/dt = rYY – rYY2/C – rYXYαYX/K – rYXYαYX/(D+C) dK/dt = rdK (1 – K/CC) dD/dt = -rcD (1 – D/K) dC/dt = rcC (1 – C/K)

(1) (2) (3) (4) (5)

Figure 8 below summarizes the causal structure and resulting behavior of this nonlinear fourth-order formulation which results in S-shaped growth of the general market K, and the niche, C. Due to architectural inertia, each species is constrained to its own niche resulting in early exit, late entry and dominance-switching throughout the life-cycle of the industry.

Figure 8: Structure/Behavior of Inter-species Competition in a Diffusing, Commoditizing Market