Tampere University of Technology Author(s) Mäkinen, Saku; Dedehayir, Ozgür

Title Business Ecosystems’ Evolution – An Ecosystem Clockspeed Perspective Citation Mäkinen, Saku; Dedehayir, Ozgür 2013. Business Ecosystems’ Evolution – An Ecosystem Clockspeed Perspective. In: Adner, Ron; Oxley, Joanne; Silverman, Brian (ed.). Advances in Strategic Management vol. 30, 99-125. Year 2013 DOI http://dx.doi.org/10.1108/S0742-3322(2013)0000030007 Version Post-print URN http://URN.fi/URN:NBN:fi:tty-201311211470 Copyright This article is (c) Emerald Group Publishing and permission has been granted for this version to appear here (http://www.tut.fi/dpub). Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited.

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Business Ecosystems’ Evolution – An Ecosystem Clockspeed Perspective

Mäkinen, Saku J. and Dedehayir, Ozgur

CITER Center for Innovation and Technology Research Department of Industrial Management

Tampere University of Technology PO Box 541, FI-33101 Tampere, Finland

email: saku.makinen@tut.fi Abstract There is a growing need for measures assessing technological changes in systemic contexts as business ecosystems replace standalone products. In these ecosystem contexts organizations are required to manage their innovation processes in increasingly networked and complex environments. In this paper, we introduce the technology and ecosystem clockspeed measures that can be used to assess the temporal nature of technological changes in a business ecosystem. We analyze systemic changes in the personal computer (PC) ecosystem, explicitly focusing on subindustries central to the delivery of PC gaming value to the end-user. Our results show that the time-based intensity of technological competition in intertwined subindustries of a business ecosystem may follow various trajectories during the evolution of the ecosystem. Hence, the technology and ecosystem clockspeed measures are able to pinpoint alternating dynamics in technological changes amongst the subindustries in the business ecosystem. We subsequently discuss organizational considerations and theoretical implications of the proposed measures. Keywords: business ecosystem; technological system; reverse salient; industry clockspeed

This paper has been published in Advances in Strategic Management http://dx.doi.org/10.1108/S0742-3322(2013)0000030007

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1 Introduction

The evolution of industries is marked by changing competitive environments and patterns of technological variation (Audretsch, 1995; Malerba, Nelson, Orsenigo, & Winter, 1999; Wezel, 2005). During the course of this progression, organizations make technological and competitive choices along the time path of industry evolution. These activities determine the rates of product and process innovation (e.g. Abernathy & Utterback, 1978), the entry and exit of organizations (e.g. S. Klepper, 1996), and the changing basis of product competition (e.g. Christensen, 1997) that are witnessed throughout the industry’s development. Timing of the technological choices is especially important for attaining and retaining competitive advantage in dynamic environemnts (e.g. Brown & Eisenhardt, 1997). Additional layers of challenges are created in organizations as the contemporary global business is increasingly based on activities of business ecosystems consisting of multiple industries rather than activities contained in a traditional single industry – value chain domain.

There is a growing need to measure the rate of change of the industry in its systemic industry context as business ecosystems increasingly replace standalone products (R. Adner, 2012; R. Adner & Kapoor, 2010). In these systemic contexts, organizations face the need to manage their innovation processes in an intertwined environment, where actors form business ecosystems and influence their decision-making (R. Adner, 2006; Tiwana, Konsynski, & Bush, 2010). Traditionally, industry change has been measured using different parameters, such as the number of organizations in the industry (e.g. Chesbrough, 2003), the number of industry patents (e.g. Brockhoff, Ernst, & Hundhausen, 1999), and the industry’s annual turnover (e.g. Gooroochurn & Hanley, 2007). In this paper, we focus on the clockspeed measure of industry change, which compares the rates of change in the industry’s product technology, process technology, and organizational capability (Fine, 1998). While the clockspeed measure has traditionally been used to evaluate the rate of change of specific industries with intra-industry focus, we extend this measure to include multiple industries forming a business ecosystem.

Here we view the business ecosystem as a network of subindustries that specialize in producing the interdependent technical sub-systems of a hierarchically structured technological system (Clark, 1985; Murmann & Frenken, 2006; Tushman & Murmann, 1998). In this manner, subindustries are interdependently connected to one another due to the interrelatedness of their output technologies. Systemic industries may therefore produce complex product systems (CoPS) such as aircraft engines, flight simulators, and offshore oil platforms (Hobday, 1998; Miller, Hobday, Leroux-Demers, & Olleros, 1995) as well as modular systems such as PCs (personal computers) and automobiles (Baldwin & Clark, 1997; Langlois & Robertson, 1992). All these business ecosystems integrate functionally interdependent sub-systems, produced by their own specialized subindustries, into holistic systemic products.

In business ecosystems, a clockspeed measure that compares the pace of change of a particular subindustry with respect to the pace of change of other interdependent subindustries can greatly aid organizations in coping with their dynamic environments. This is because the innovation processes of organizations in ecosystems are intertwined with performance improvements in the sub-system technologies that are central to their own subindustry, as well as with the interfaces between other interdependent subindustries that produce interdependent technological sub-systems (Ethiraj & Puranam, 2004). Moreover, an organization inside a subindustry may remain more

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competitive by utilizing information about the rate of change of interdependent subindustries, as performance deficiencies in component and complementary technologies can jeopardize the ability of the organization to create its own value for end-users (R. Adner & Kapoor, 2010).

In this paper, we aim to enhance current understanding of business ecosystem dynamics by extending the clockspeed measures developed by Dedehayir & Mäkinen (2011) to the business ecosystem context. We first apply the “technological industry clockspeed”, which we refer to as the technology clockspeed measure that evaluates the time lag between successively higher levels of technological product performance in a given subindustry. Secondly, we apply the “systemic technological industry clockspeed”, which we refer to as the ecosystem clockspeed measure that informs of the temporal nature of the performance discrepancies that emerge between interrelated sub-systems over time. In these states of technological disequilibrium (Rosenberg, 1976), we focus on the sub-system, which, due to its performance deficiency, hinders the value delivery of the ecosystem’s holistic product. The ecosystem clockspeed therefore measures the duration of time required for the performance deficient sub-system to attain the performance levels of more advanced sub-systems. We demonstrate the use of these clockspeed measures in a longitudinal study of the PC ecosystem, focusing on key subindustries that produce the sub-systems central for computer gaming.

The evolutionary trajectories of technology clockspeed facilitate informed views on monitoring, outlining, and planning competitive activity within a given subindustry. This information can be used, for example, in seeking synchrony between interlinked subindustries’ output to maximize end-user value or designing competitive actions centering on timing technological performance improvements. The ecosystem clockspeed, in turn, provides information on the business ecosystem’s holistic performance delivery, over time. The ability to assess the evolution of the business ecosystem in its entirety allows actors to implement strategic, competitive actions. Our empirical results, for instance, suggest that the ecosystem clockspeed may progress through distinctively differing time paths, with increasing temporal latencies expected as the technological paradigm matures in interdependent subindustries. Hence, more than the dynamics of change in a firm’s own subindustry, such stylized patterns can help these actors identify the shifting competitive priorities in the business ecosystem in which they are positioned.

2 Theoretical background 2.1 Industry dynamics and clockspeed

Industries not only change due to competitive dynamics, but they do so at different rates, as a result of the differing pace of introduction and utilization of technological innovations in the industry (Audretsch, 1995; S. Klepper & Graddy, 1990; Suarez & Lanzolla, 2005). The changing pace of industry development thus requires the timely modification of an organization’s activities and assets in order to remain competitive in the industry (McGahan, 2000; McGahan, 2004). Eisenhardt & Martin (2000) underline organizational responses to varying industry conditions by comparing the dynamic capability of firms that negotiate moderately dynamic markets (i.e. where change is frequent, though largely predictable) and firms competing in high-velocity markets (i.e. where change is nonlinear and less predictable). Studies of the computer industry indicate the need to adopt strategy making decisions and product development efforts in such high-velocity market contexts (Brown & Eisenhardt, 1997; K. M. Eisenhardt & Tabrizi, 1995; K. M. Eisenhardt, 1989). Romanelli & Tushman (1994) further demonstrate that punctuated changes in the U.S. computer

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industry acted as external stimuli that necessitated organizational adaptation through similarly revolutionary transformations.

Different metrics have been developed to evaluate and explain the rates of change of industries. Of these, the clockspeed measure of industry change introduced by Fine (1998) remains prominent, allowing the differentiation of high clockspeed industries from low clockspeed industries (Guimaraes, Cook, & Natarajan, 2002; Mendelson & Pillai, 1999; Nadkarni & Narayanan, 2007; Souza, Bayus, & Wagner, 2004). However, organizations positioned in dynamically changing competitive environments additionally require a temporal clockspeed measure of industries that can detect possible life cycle effects (Fine, 1998), thereby providing a guideline for the implementation of innovation processes. To address this issue, Dedehayir & Mäkinen (2011) have recently expanded Fine’s industry clockspeed framework by introducing a measure that evaluates the time between successively higher levels of technological performance in the industry’s product technology1. We define this temporal latency as technology clockspeed. To align with Fine’s definition of product clockspeed, which measures the frequency of new product introductions in a given industry, the technology clockspeed measures the rate of new technological performance levels that are introduced in the industry, without taking into account the magnitudes of these performance level increases.

2.2 The clockspeed measure in business ecosystems

Just as biological ecosystems consist of a variety of interdependent species, business ecosystems analogously depict interdependent networks of organizations, which collectively produce a holistic, integrated technological system that creates value for customers (Agerfalk & Fitzgerald, 2008; Bahrami & Evans, 1995; Basole, 2009; Lusch, 2010; Teece, 2007). In this network, each member contributes to the ecosystem’s overall wellbeing and is dependent on other members for its survival. These organizations co-evolve by working cooperatively as well as competitively in the creation of products and services (Moore, 1993). The business ecosystem may comprise a variety of actors, including suppliers, complementors, system integrators, distributors, advertisers, finance providers, universities and research institutions, regulatory authorities and standard-setting bodies, and the judiciary as well as customers (Iyer & Davenport, 2008; Li, 2009; Meyer, Gaba, & Colwell, 2005; Pierce, 2009; Whitley & Darking, 2006).

The technological systems produced by business ecosystems are hierarchically structured networks of interdependent technical sub-systems (Clark, 1985; Murmann & Frenken, 2006; Tushman & Murmann, 1998). The modularization of these product and process systems often leads to the emergence of specialized subindustries that focus on manufacturing a particular module or sub-system (Brusoni & Prencipe, 2001; Ethiraj & Puranam, 2004; Ulrich, 1995). In this manner, the business ecosystem provides value to the end-user by integrating functionally interdependent sub-systems that are produced by their own specialized subindustries. In the aircraft ecosystem, for example, engines and airframes are distinct sub-systems integrated by aircraft builders such as Airbus and Boeing (Bonaccorsi & Giuri, 2000; Schilling, 2000), while microprocessors, graphics processors, and software are sub-systems are integrated by computer makers in the PC ecosystem (Ethiraj & Puranam, 2004; Macher & Mowery, 2004).

1 This evolution is traditionally observed as S-curves (e.g. Foster, 1986).

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The systemic relationship between these subindustries suggests that changes in the technological output of one subindustry may affect the technological output of other, interdependent subindustries and also the output of the business ecosystem as a whole. Consequently, technological evolution in business ecosystems is curbed by the emergence of bottlenecks when a particular sub-system (e.g. complement or component technology) lacks development and does not deliver the level of performance demanded by the focal firm (R. Adner & Kapoor, 2007; Kapoor & Adner, 2007). The centrality of such blockades to performance and value creation has been recognized in the literature for some time. For instance, Rosenberg (1969) proposes that when the main impulse for technological evolution is economical, to derive favorable economic conditions, managers of firms should approach the most economically restrictive constraints first. These constraints therefore emerge as economical needs that require technological solutions, and the development of these solutions subsequently drives technological evolution. Rosenberg labels these constraints as ‘focusing devices’, which importantly act as sources of technological change.

According to Rosenberg three focusing devices have historically triggered technological development; (i) the unpredictability of labor, (ii) the unavailability of resources and other overarching constraints, and (iii) technological imbalances. In this paper, our aim is to understand the evolution of business ecosystems through the focusing device of technological balances, which initiate ‘compulsive sequences’ that drive technological change (Rosenberg, 1969). More specifically, we address the performance imbalances that appear, say, between the components of complex machines or operations, which compulsively necessitate the improvement of the component that lacks the performance capacity of other components. Innovations that overcome the insufficient performance capacity, in turn, reveal the insufficient performance of another component, which is then resolved through further innovations2.

In the context of business ecosystems, these constraints, or reverse salients3, have been shown to hinder the attainment of a higher level of technological performance by either limiting the focal firm’s “ability to create value with its product” or by “constraining the customer’s ability to derive full benefit from consuming” the firm’s product (R. Adner & Kapoor, 2010). For example, Philips, Sony, and Thompson incurred heavy financial losses by developing and introducing the high-definition television in the 1990s, concurrently failing to deliver value to the end-user due to performance deficiencies in complementary technologies such as studio production equipment, signal compression technologies, and broadcasting standards (R. Adner, 2012).

With respect to the generic depiction of business ecosystems, the reverse salient can reside in two locations (see Fig. 1).

2 The machining operation in the manufacturing of bicycle hubs in the 19th century exemplifies such technological imbalance. At this time, bicycle hubs were produced by machining the outside and the inside of the hub. Despite process improvements which increased the speed of machining the outside of the bicycle hub, the overall pace of hub production remained unchanged. This was because the machining technology that was used to form the inside of the hub was inadequate to keep up with the speed of forming the outside of the hub. Subsequently, economic benefits from the improvements in the outside forming process were not realized until the inside drilling process was quickened. This was achieved through the implementation of oil-tube drilling, which had previously been used in the drilling of gun barrels (Rosenberg, 1969; Rosenberg, 1976). 3 The evolution of technological systems is marked by differences in the performance levels delivered by their sub-systems. In this state of imbalance, the sub-system that delivers the lowest level of performance and hence curbs the performance of the holistic system is referred to as the “reverse salient” (Hughes, 1983), and the state of imbalance manifest in the system due to the appearance of a reverse salient is referred to as “reverse salience”.

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------------------------------------ Take in Figure 1 ------------------------------------

In Fig. 1, a state of technological imbalance emerges when the performance of the reverse

salient sub-system (e.g. the technological sub-system produced by Supplier 1 or Complementor 1) is lower than the performance of the interdependent (i.e. salient) sub-system (e.g. the technological sub-system of the Focal Firm, in Fig. 1)4. The length of time required for the reverse salient to attain the salient sub-system’s performance level informs the reverse salient sub-system’s rate of development in the technological system context5. This duration of time concurrently informs the rate of development of the reverse salient subindustry (i.e. the subindustry producing the reverse salient sub-system) in the business ecosystem context. We subsequently use this delay to measure the ecosystem clockspeed. Similar to the technology clockspeed, shorter spans of time needed for the reverse salient to attain the technological performance levels of the salient sub-system indicate faster ecosystem clockspeeds.

Following Dedehayir & Mäkinen’s framework, the ecosystem clockspeed extends Fine’s notion of industry clockspeed to the business ecosystem arena. This measure is founded on earlier depictions of a basic unit of the business ecosystem, which constitutes a focal firm that is directly connected to its suppliers, customers, and complementors (R. Adner, 2012; R. Adner & Kapoor, 2010). Using the rate of technological change in the focal firm’s subindustry as reference, the ecosystem clockspeed measures the delays in the subindustries’ technologies attaining the same performance levels, across time. The ecosystem clockspeed is thus a quantitative tool intended to be used specifically as a basic unit measure of temporal latencies attached to technological discrepancies in business ecosystems.

3 Methodology

In our empirical study, we first employ the technology clockspeed measure to analyze the evolution of a given subindustry in the ecosystem with the rate of performance accumulation in its technology over time. Secondly, we apply the ecosystem clockspeed measure to compare the rates of technological performance development among the ecosystem’s subindustries. We measure the clockspeed from the technological evolution curves of the salient and the reverse salient sub-systems that are superimposed on a common set of axes (see Fig. 2).

------------------------------------ Take in Figure 2 ------------------------------------

4 We have shown the component and complement technologies to be the reverse salients in the figure to align with the previous works of Adner & Kapoor. However, it should be noted that in a state of technological imbalance, the reverse salient may also be the focal firm itself, when its technological performance is lower than the performances of the component or complement technologies. 5 In their extension of Fine’s (1998) notion of the industry clockspeed, Dedehayir & Mäkinen (2011) use this duration to measure the industry’s clockspeed in the systemic context (referred to as “systemic technological industry clockspeed”).

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Our schematic representation in Fig. 2 compares the evolution of the reverse salient’s technological performance parameter, represented by the dashed line, with the technological performance evolution of the salient sub-system, represented by the solid line. Fig. 2 illustrates the technology clockspeed measurements for both the salient and the reverse salient subindustries, denoted by ΔtTC,S and ΔtTC,RS, respectively. The technology clockspeed therefore informs us of the temporal separation of the steps of technological progression in the subindustry. In turn, the magnitude of ecosystem clockspeed at any point along the time axis is measured by calculating the temporal separation of the reverse salient from the salient trajectory at that point, denoted by ΔtEC. This separation reflects the length of time that is required for the reverse salient sub-system to attain the salient sub-system’s level of technological performance. 3.1 The PC gaming ecosystem

In our empirical illustration, we have studied the PC ecosystem that creates value for the end-user by integrating functionally interdependent sub-systems (e.g. hardware and software sub-systems) that are produced by their own specialized subindustries. However, our analysis focuses specifically on the value of the computer gaming function that the ecosystem delivers to the end-user, simultaneously directing our analytical lens to the sub-systems central for computer gaming and to the subindustries that produce these sub-systems. The PC ecosystem provided a suitable empirical setting for our illustration due to the significance of the PC as a platform for computer gaming since the 1990s (Hayes & Dinsey, 1995; Poole, 2004), due to its systemic nature (Baldwin & Clark, 1997; Langlois & Robertson, 1992), and also due to the highly dynamic nature of technological evolution observed in this context (K. M. Eisenhardt & Tabrizi, 1995; Rosas-Vega & Vokurka, 2000).

The video game industry, leading up to the 1990s, had been dominated by the console platform (Kent, 2001). The reasons for this domination were rather apparent. For the market, the console represented a relatively affordable and easy to operate machine that was solely dedicated to the gaming purpose. For the supply side, the console was a dedicated hardware platform that experienced generational leaps in technological performance from time to time. The hardware manufacturing was dominated by a few players, such as Nintendo and Sega, who also produced their own software. Nevertheless, companies that specialized in software development were also integrated into the industry to provide resources to quench the thirst of the gamer market for more games. The complete system of the hardware and software offered the market unequivocal and insurmountable gaming experience. In this manner, gaming on the console platform paved the way for the birth of the PC ecosystem delivering gaming value.

The PC had for a long time lacked the hardware sophistication that would allow good quality games to be played on it. For the most part, PCs were used for word processing and similar applications. Any technological developments in the PC hardware, leading up to the mid-1990s, were therefore seen to be pushed by game software that, in order to deliver satisfactory performance on the PC, needed higher hardware capacity. Subsequently, the PC began increasing penetration into households despite remaining significantly behind the game consoles, due to technological progress as well as more affordable prices. Key sub-systems such as the CPU had not only jumped to new technological platforms (e.g. Intel’s 486 processor), but also the prices had dropped substantially. Added to this, the components of the PC were upgradeable to higher technological levels, eliminating the need for the purchase of a complete system, which was inherent to console

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systems. This made better gaming experience available to the computer owner as long as the necessary hardware could be upgraded to the required level.

During the same period, a new data storage medium technology in the CD (compact disc) entered the fray. The industry (in particular console makers) saw this as a significant threat and a possible point of departure from the existing regime of game software that was supplied on cartridges and played on hardware suited for the cartridge format. Indeed, game developers such as Electronic Arts began refocusing on developing their game software for the CD format, and hardware developers began collaborating with CD manufacturers to incorporate the new format onto their consoles (Hayes & Dinsey, 1995).

The integration of the CD player into the PC platform enhanced the PC’s competitiveness with console machines for a greater share of the video game market. The refocusing of game software developers towards the CD medium from cartridges acted as a catalyst in the creation of this potential. Moreover, game developers were glad to have an alternative to the dominant consoles. Notwithstanding these developments, the complexity of the PC’s operation still remained an Achilles’ heel. The launch of Microsoft’s Windows 95 operating system, however, became a significant turning point for the rise of the PC in computer gaming application, as it significantly simplified game play, along with other functions, on the PC (Hayes & Dinsey, 1995).

In the resulting PC system, video gaming was made possible with the integration of two interdependent components; software and hardware. While the software provides the intelligence for the virtual worlds, characters, and plots of the games, the hardware provides the technical basis that enables the creation of the interactive environment. The resulting technical qualities, such as movement, graphics, and sound, make video games seemingly addictive and contagious (Hayes & Dinsey, 1995). The relentless pace of technological development in video games is a salient point of departure from other forms of entertainment such as television, movies, and music (Bethke, 2003). To a great extent, this is bestowed by technological enhancement of game software, through which game developers can increase the scope of existing plots and storylines, integrate more detail into the game environment, and deliver greater video and audio experience. It is the pursuit of realism that drives the development of these features in game software design. However, the enhancement of software increases its complexity, thus requiring greater hardware capacity to enable the game’s designed function. For computer games that are played on the PC, this means that the game software needs to utilize a greater amount of the hardware technological performance that is available.

Accordingly, the PC ecosystem analyzed in this paper constitutes the main subindustries that produce the hardware and software sub-systems required for delivering gaming performance value to the end-user. We subsequently identify the PC game software subindustry as the focal subindustry in our PC ecosystem schema and consider its linkages to four other subindustries that produce important and interdependent sub-systems (see Fig. 3).

------------------------------------ Take in Figure 3 ------------------------------------

On the supply side, we consider the CPU (central processing unit) and GPU (graphics

processing unit) that are integrated into the PC as crucial hardware components upon which the PC

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game software will function. Additionally, we analyze two software sub-systems, namely the DirectX6 and the OS (operating system), which are complementors of the PC game software and similarly necessary for the game to function.

In the typical development of game software there is an inherent need for the PC game developer to utilize the available levels of technological performance in interdependent sub-systems when commencing game software development. This necessarily imposes certain minimum temporal latency in using interdependent technologies. This delay is further exacerbated by the game developer’s need to test for compatibility with the connected software and hardware sub-systems, for example, by testing each new game’s capability to function with individual video cards (Ripolles & Chover, 2008). Furthermore, the search for market opportunities, the realization of game concepts, the availability of support from connected sub-systems, and waiting for the installed base to increase magnifies this latency. Also the desire to avoid risks of project delays and cost overruns in a highly dynamic ecosystem motivates game developers to delay their technology selection, at least to some extent (MacCormack, Verganti, & Iansiti, 2001). Notwithstanding the technological advancements in the interconnected sub-systems, these delays necessarily define the PC game software as the reverse salient from the end-user point of view, who is interested in maximizing the gaming performance on the holistic PC system. Our empirical study therefore illustrates the ecosystem clockspeed of the PC game subindustry, which, in producing game software, requires some duration of time to attain the technological performance levels embedded in the hardware and software products of the supplier and complementor subindustries. 3.2 The method and data

For the PC game software sub-system, we have considered that the software is designed to utilize at least some minimum level of performance provisioned by the interdependent sub-systems, such that the intended game qualities can materialize on the holistic PC system7. In our study, we have used the minimum hardware as well as the minimum software requirements stipulated by the PC game developer (i.e. the focal firm) as the technological performance indicator. In this manner, we identify a PC game as having a higher level of technological performance than another when its stipulated minimum requirements are higher than those of the latter. For the supplied hardware sub-systems, we have selected the performance indicator of processing speed (measured in Hertz) for the CPU and graphics memory (measured in megabytes, MB) for the GPU, since these are the parameters most important for PC game developers for game functionality. For the complementary software sub-systems, DirectX and the Windows operating system (OS), we denote the launches of successive versions of these technologies as performance increases that provide additional and better functionality.

Our empirical analysis proceeded as follows. First, we measured the technology clockspeeds of the subindustries that constitute the PC ecosystem by studying the technological evolutions of the corresponding hardware and software sub-systems. For technology clockspeed we measured the

6 DirectX, a Microsoft product, is designed to handle tasks such as multimedia, in particular for video game applications on Windows platforms. The DirectX interface concept was developed and employed soon after the launch of the Windows 95 operating system and onwards. Such interfaces include Direct3D, DirectDraw, and DirectMusic, such that the “X” in “DirectX” represents a particular interface. The DirectX software development kit (SDK) is made available for PC game developers to assist them in designing their products. 7 The game software stipulates a set of minimum performance requirements corresponding to the CPU, GPU, DirectX, and OS, with which the software will function as designed.

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number of days between the technological performance increases of the CPU and GPU product launches with processor speed and graphics memory, respectively. Similarly, we traced the number of days between the launch dates of successive versions of DirectX and the Windows OS. We also measured all the technology clockspeeds of the focal PC game subindustry with the number of days between successively increasing minimum requirements pertaining to these interdependent component and complement technologies. Second, we evaluated the ecosystem clockspeed of the PC game subindustry by superimposing the technology evolution curves of the PC game sub-system and the interdependent sub-systems onto respective sets of axes, and by calculating the time delays in the reverse salient’s attainment of the salient sub-system’s technological performance.

We collected data on CPU processor speeds from processor performance databases found on Intel and AMD (Advanced Micro Devices) corporate websites, the two primary manufacturers of CPUs, and we accessed GPU graphics memory data from the corporate websites of NVIDIA and ATI8, the two dominant players in the graphics processor industry. The launch dates of the DirectX and Windows OS versions were accessed from Microsoft’s corporate website. The data on PC game minimum requirements were, in turn, collected from the websites of game publishers and game developers, as well as from the gaming community, Gamespot.com, and the online vendor, Amazon.com.

We limited the list of PC games used in our empirical analysis to those that had been launched in the United States and which had been reviewed and rated by either one reputable online source, Gamespot.com, or one reputable printed source, PC Gamer magazine. We selected an observation interval stretching from August 1995 until the end of 2008. The beginning of the observation interval was selected to correspond to the launch of the Windows 95 operating system that established a new technological platform upon which hardware and PC game software could be developed, and which therefore produced a significant change in the gaming industry (Hayes & Dinsey, 1995). These limitations may curb our results, for example, due to the exclusion of many indie games that are not rated by our sources and are therefore omitted from our data set. However, at the same time, these limitations allow us to analyze a data set that is representative of the industry from the mainstream business and market perspectives. 4 Results and discussion

In Fig. 4 we present the technology clockspeeds of the salient subindustries, namely the CPU, GPU, DirectX, and Windows OS, which connect to the reverse salient PC game subindustry in the analyzed ecosystem. In our conceptualization, the shorter spans of time between successive product launches in these subindustries indicate faster clockspeeds, i.e. the lower the number of days between launches the faster the clockspeed is. Similarly, the decrease in the number of days between launches signifies acceleration and quickening of the clockspeed.

------------------------------------ Take in Figure 4 ------------------------------------

8 ATI was acquired by AMD in October 2006.

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Panel (a) indicates that a quickening of the clockspeed is witnessed after an early period of low technology clockspeed in the CPU subindustry. However, recent years (from 2003 onwards) show a slowing in the technology clockspeed. Interestingly, this period of time coincides with the technical limitations that materialized in CPU development, leading to difficulties in increasing processor speeds, which may have led to the increasing duration of time between successively higher performing CPUs. Visible in panel (a) is, for example, the rapid launch of Pentium II at 300 MHz right after the initial introduction of the 233 and 266 MHz versions, signifying Intel’s platform approach and its influence on the CPU subindustry’s technological development. Panels (b) and (c) show significant variation in the GPU and DirectX technology clockspeeds, respectively, while the technology clockspeed of the Windows OS in panel (d) displays a period of slowing following an early period of quickening. We also observe that DirectX stays on very fast clockspeed levels, which suggests a rapid succession of game launches with higher requirements, and signifies Microsoft’s commitment to satisfy market requirements related to DirectX for the game software performance.

Fig. 5, in turn, presents the technology clockspeed measures of the PC game subindustry, measured with the stated minimum technological performance requirements of the games pertaining to processor speed, graphics memory, DirectX version, and the Windows OS version, respectively.

------------------------------------ Take in Figure 5 ------------------------------------

In panel (a), we observe that the technology clockspeed of the PC game software

subindustry displays a period of quickening until the end of 2004, after which a period of high variation in the clockspeed is witnessed. This oscillation markedly started with the introduction of UberSoldier, a game which had “massive system requirements,” according to GameSpot. It still did not get positive feedback in general, although it presented, at its best, good game play in its first person shooter genre. Our observation suggests that designing games with a focus on CPU performance has been central to the competitiveness within the PC game subindustry for some period of time, although lately this focus has diminished.

By contrast, the technology clockspeed of the PC game subindustry indicates a slowing down in panel (b), high oscillation in panel (c), and rapid quickening and stabilization in panel (d). We interpret these clockspeed trends to suggest that the PC game subindustry has firstly a diminishing focus on developing games that rapidly utilize the highest possible GPU performance, given the rather slow and decelerating clockspeed shown in panel (b). This trend is illustrated with the launch of the highly successful game RoboBlitz in late 2006, when the technology clockspeed of the PC game subindustry in relation to the GPU minimum requirement was very slow. RoboBlitz was noted for its high graphics memory requirements, as being the first to be based on Unreal Engine 3, and having gained several honors, such as being nominated for the 2007 Independent Games Festival for Excellence in Visual Art award. The strategic choice to incorporate higher graphics performance despite a delayed release appears therefore to have been more attractive to the software developing firm than introducing a game earlier with lower graphics requirements. This is representative of the slow technology clockspeed observed in the panel. And further, despite the witnessed oscillation, the fast clockspeeds shown in panel (c) suggest that the PC game subindustry

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sees it important to integrate the latest DirectX versions when launching new products. And lastly, the PC game subindustry appears to have a stabilizing view both on the integration of the Windows OS versions into newly launched games, and on the expectation of market adoption of the new Windows OS versions.

While the technology clockspeed measures temporal latency internal to a given subindustry, the ecosystem clockspeed measures this latency between subindustries. To derive the ecosystem clockspeed, we next evaluate the temporal latency for the reverse salient PC game software subindustry’s attainment of salient subindustry performance levels. Fig. 6 displays the evolutions of the ecosystem clockspeeds across the timeframe of our analysis.

------------------------------------ Take in Figure 6 ------------------------------------

The ecosystem clockspeed derived from the co-evolution of the PC game software and CPU subindustries in panel (a) shows a continuously increasing time delay of technological performance attainment. This suggests that the higher levels of computer gaming performance received by the end-user from the interdependence of the CPU and PC game software sub-systems requires longer lengths of time to materialize as the ecosystem evolves. This outcome contrasts with the PC game subindustry’s quickening technology clockspeed presented earlier (Fig. 5a). The combination of these results suggests that while PC game developers do see value in focusing on processor performance in the context of their own subindustry, they do not necessarily derive competitive advantage by pursuing the latest CPU hardware performance in the business ecosystem context. An example of long utilization times leading to the development of a successful game is the slowing down of the ecosystem clockspeed from 2002 to 2004 in panel (6a), with the launch of the game Painkiller in early 2004. This game followed the traditional first person shooter style in the footsteps of Quake and Doom and received acclaim in the industry despite (or due to) the slow ecosystem clockspeed. This industry acclaim, including the “PC Game of the Month” award from Gamespot, was due to the high performance of the game, for example, in its overall design and gameplay. In contrast, the longitudinal analysis of the PC game subindustry’s ecosystem clockspeed with respect to the GPU subindustry development in panel (b) shows three sequential eras marked by quickening, constant fast, and finally, slowing clockspeed. This finding indicates the diminishing competitive advantage that the PC game software developers derive from focusing on incorporating latest GPU advances in their minimum graphics performance requirements in the ecosystem context.

With respect to the complement technologies (panels (c) and (d)), we generally observe the growing focus of the PC game subindustry to utilize the latest DirectX and the Windows OS versions. The end-user consequently derives greater value in the form of gaming performance on the PC platform, as the potential of the complementary technologies is realized more readily. For instance, game developers are able to integrate the latest versions of DirectX more rapidly as this complement can be freely downloaded or supplied by game developers. A noteworthy turning point here is the utilization of Windows ME as a minimum requirement in PC games in late 2000. Windows ME was the successor to Windows 98, targeted specifically for home PC users, and released after Windows 2000, which was a business-oriented operating system. In contrast to

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Windows 2000, Windows ME did not achieve substantial penetration in the marketplace, which may be one of the reasons why Windows 2000 was stated as a minimum requirement much sooner than Windows ME. After the launch of Windows XP, which penetrated the market quickly, game developers included this version as a minimum requirement much more rapidly, while subsequent Service Packs increased the pace of this development.

Finally, to explore the temporal dynamics of the ecosystem clockspeed and provide a more substantive indication of the holistic picture of the evolution of the subindustries, we plotted all the ecosystem clockspeed measures on the same figure, with fitted polynomial trend lines, in Fig. 7. The polynomial fitting results underline the differing trends in our ecosystem clockspeed measures. Firstly, the reverse salient PC game subindustry shows a linear-like slowing trend (R² = 0,9448) in relation to the salient CPU subindustry. This trend signifies the diminishing gains from increasing CPU processing performance as a minimum requirement in PC games as the processor speeds stabilize and multi-core processors replace single core processors. Secondly, the PC game subindustry’s ecosystem clockspeed in relation to the GPU subindustry displays a trend line with a trough around 2000 to 2003 (R² = 0,5843), signifying the turning point in the importance of graphics memory to the PC game developing subindustry. Beyond the trough, it appears that the graphics memory available to end-users has reached a level that is sufficient to game developers, who no longer engage aggressively in introducing increasingly higher memory requirements into their products. In relation to the Windows operating system, the PC game subindustry shows a mirror image of the GPU trend line (R² = 0,6709), with a peak around 2000 to 2003. Therefore, the use of the Windows OS and the capabilities brought about with it to the end-user has become an important means of technological competition in game design. Similarly, the reverse salient PC game subindustry has remained on a fast-paced evolutionary track, with the DirectX trend line being very linear at low levels of temporal latency (R² = 0,1131).

------------------------------------ Take in Figure 7 ------------------------------------

Fig. 7 reveals a few notable features. Firstly, the trends of different ecosystem clockspeed

measures are rather heterogeneous. While the PC game subindustry has a rather stable ecosystem clockspeed in relation to DirectX, the ecosystem clockspeed is dramatically changing and dynamic in relation to the Windows operating system, despite both of these representing software sub-systems in the analyzed business ecosystem. Partially, this may be due to DirectX being free, readily distributable, and downloadable and important for game design. Secondly, the temporal stability of the clockspeed measures also varies substantially. The ecosystem clockspeed of the reverse salient PC game subindustry in relation to the salient GPU subindustry remains at the same level for much longer than, say, it does in relation to the CPU subindustry. And thirdly, in general, the ecosystem clockspeed measures pertaining to the hardware components are much slower than the clockspeed measures pertaining to the software sub-systems. It is also evident from Fig. 7 that the ecosystem clockspeed of the PC game subindustry in relation to the CPU subindustry has evolved steadily from fast ecosystem clockspeed, signifying the importance of time-based competition towards slower ecosystem clockspeed as the technology around single core processors has matured.

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5 Conclusion and implications

This paper applies clockspeed measures to assess the rate of change of a subindustry that is situated in the business ecosystem context. We have first applied the measure of a subindustry’s own technology clockspeed by evaluating the durations of time between the launch of products with successively higher technological performance. Secondly, we applied the measure of ecosystem clockspeed to evaluate the length of time required for the ecosystem’s reverse salient subindustry to attain the level of technological performance of its interdependent subindustries.

As a subindustry’s internal measure of innovative productivity, the evolutionary trajectories of the technology clockspeed show remarkable variation reflecting the evolving competitive rivalry within subindustries. In the ecosystem context, the focal subindustry’s technology clockspeed allows understanding of the temporal nature of technological competition within this subindustry. This information can be used, for example, in seeking synchrony between interlinked subindustries’ output to maximize end-user value (Davis, 2013) or designing competitive actions (Ferrier, Smith, & Grimm, 1999). Thereby, this measure may facilitate informed views on monitoring, outlining, and planning competitive activity that centers on improving technological performance of a subindustry. From the observed patterns of technology clockspeeds, we propose that different eras of technology clockspeed, in a similar manner to the traditional measures such as the number of organizations, products, or innovations (Abernathy & Utterback, 1978; Gort & Klepper, 1982; McGahan, 2000), could be linked to the different phases of industry evolution in future research.

In addition to the technology clockspeed, the ecosystem clockspeed informs of the business ecosystem’s holistic performance delivery as the technological performance of the reverse salient subindustry improves over time. Our empirical results suggest that the ecosystem clockspeed may progress through distinctively differing time paths, with increasing temporal latencies expected as the technological paradigm matures in interdependent subindustries. Noteworthy is the maturation of the CPU subindustry in terms of the processor speed parameter. As the focus of the CPU performance enhancement shifts from processor speed to adding cores to the processor, the ecosystem clockspeed of the reverse salient PC game subindustry utilizing this parameter slows steadily. The slowing ecosystem clockspeed informs of the dynamics of interplay inside the business ecosystem as the product architecture changes and innovative effort is redirected to new areas. This finding is in line with Ethiraj and Posen (2013) in that the PC game developer receives design information from complementor and supplier firms, and this information consequently governs its product development efforts. This may reflect the shifting basis of competition that is expected to take place as the technological paradigm and bases of competition are changing (Christensen, 1997). Therefore, we may propose that the ecosystem clockspeed may be used in detecting and analyzing phases of industry evolution.

As demonstrated in our empirical illustration, the business ecosystem’s capacity to deliver holistic value to the end-user can be evaluated by comparing the clockspeed trajectories in different locations within the ecosystem. This comparison enables ecosystem members to identify the bottlenecks to value creation (R. Adner, 2012; R. Adner & Kapoor, 2010) and to assign priority to alleviate these blockages. Additionally, our empirical results suggest that the ecosystem clockspeed of the reverse salient subindustry may progress through distinctively differing time paths. These differences in trajectory, depending on the salient subindustry under scrutiny, thereby signify the influence of contingency factors. This presents ample opportunities for future studies on the

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possible reasons for these differences. We may propose, for instance, that differences in market and demand conditions heavily influence the nature of profitable innovative effort depending on the role of the subindustry in the business ecosystem, thus guiding the selection of component technologies utilized. Similarly, intra- and inter-industry competition inside the business ecosystem naturally influences technological choices and their timing. Future studies could also extend both the limited observation interval and industry setting of our present study to identify different industry evolution phases and contingency factors at play. Also future investigations may find fruitful grounds in assessing technological performance levels in relation to temporal measures during the industry life cycle.

In conclusion, our study attempts to design metrics for investigating the evolution of business ecosystems following the suggestion of prior scholars (e.g. McGahan, Argyres, & Baum, 2004). Our investigation is an attempt to build a part of the set of analytical measures that could be used to further explore business ecosystem dynamics and evolution of industries. The results of our work point to the significance of considering temporal aspects of this evolution from the holistic ecosystem perspective while emphasizing the dynamic nature of the evolution and its contingent nature on supply-demand side factors.

Acknowledgement We thank Ron Adner, Brian Silverman, and Joanne Oxley for insightful comments on earlier versions of this paper.

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Appendix

Fig. 1. A generic schema of a business ecosystem and location of reverse salient (adapted from

Adner and Kapoor 2010).

Supplier 1

Supplier 2

Focal Firm

Complementor 1

Complementor 2

Customer

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Fig. 2. Schema of clockspeed measurements from superimposed S-curves (ΔtTC and ΔtEC refer to

the technology clockspeed and the ecosystem clockspeed, respectively).

tech

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Fig. 3. A schema of the PC business ecosystem delivering gaming performance.

Software

CPU

GPU

PC

DirectX

Operating system OS

PC gaming Customer PC game

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(a) CPU sub-industry

(b) GPU sub-industry

(c) DirectX sub-industry

(d) Windows OS sub-industry

Fig. 4. The technology clockspeed of the salient subindustries measured as the number of days

between technology launches with successively higher performance.

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(a) The technology clockspeed (CPU)

(b) The technology clockspeed (GPU)

(c) The technology clockspeed (DirectX)

(d) The technology clockspeed (Windows OS)

Fig. 5. The technology clockspeed of the reverse salient PC game subindustry measured as the

number of days between game launches with successively higher minimum performance

requirements of CPU, GPU, DirectX, and Windows OS.

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(a) The ecosystem clockspeed (CPU_PCGAME)

(b) The ecosystem clockspeed (GPU_PCGAME)

(c) The ecosystem clockspeed (DX_PCGAME)

(d) The ecosystem clockspeed (OS_PCGAME)

Fig. 6. The ecosystem clockspeed of the reverse salient PC game subindustry, in relation to the four

connected subindustries.

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Fig. 7. The representation of trends in the ecosystem clockspeeds of the PC game subindustry, in

relation to the four connected subindustries.

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11.4.1995 5.1.1998 1.10.2000 28.6.2003 24.3.2006 18.12.2008

Number of days

DateCPU_PCGAME GPU_PCGAME OS_PCGAME DX_PCGAME

Poly. (CPU_PCGAME) Poly. (GPU_PCGAME) Poly. (OS_PCGAME) Poly. (DX_PCGAME)