Description
Within the fields of strategic management and organizational theory, an organization’s environment is considered to be the notional space in which organizations exist. The environment consists of political, technological, economic and competitive dimensions that influence how organizations should function.
A Case Studies on Multidimensional Conceptualization of Environmental Velocity
Environmental velocity has emerged as an important concept but remains theoreti- cally underdeveloped, particularly with respect to its multidimensionality. In re- sponse, we develop a framework that examines the variations in velocity across multiple dimensions of the environment (homology) and the causal linkages between those velocities (coupling). We then propose four velocity regimes based on different patterns of homology and coupling and argue that the conditions of each regime have important implications for organizations.
Environmental velocity1 has become an im- portant concept for characterizing the conditions of organizational environments. Bourgeois and Eisenhardt (1988) introduced this concept to the management literature in their study of strate- gic decision making in the microcomputer in- dustry. They described this industry as a "high- velocity environment" — one characterized by "rapid and discontinuous change in demand, competitors, technology and/or regulation, such that information is often inaccurate, unavail- able, or obsolete" (Bourgeois & Eisenhardt, 1988: 816). From the perspective that the environment is a source of information that managers use to maintain or modify their organizations (Aldrich, 1979, Scott, 1981), velocity has important impli- cations for organizations. Studies have found, for example, that success in high-velocity indus- tries is related to fast, formal strategic decision- making processes (Eisenhardt, 1989; Judge & Miller, 1991); high levels of team and process
We are grateful to associate editor Mason Carpenter and three anonymous reviewers for their helpful and construc- tive comments. The development of this paper also benefited from comments from Joel Baum, Danny Breznitz, Sebastian Fixson, Mark Freel, Rick Iverson, Danny Miller, Dave Thomas, Andrew von Nordenflycht, Mark Wexler, Carsten Zimmermann, and seminar participants at Simon Fraser University and the 2008 INFORMS Organization Science Pa- per Development Workshop. We are also grateful to the Canadian Social Sciences and Humanities Research Coun- cil for funding that supported this research. 1 To increase the paper's readability, we use the terms environmental velocity and velocity interchangeably.
integration (Smith et al., 1994); rapid organiza- tional adaptation and fast product innovation (Eisenhardt & Tabrizi, 1995); and the use of heu- ristic reasoning processes (Oliver & Roos, 2005). More generally, research on velocity has shown that it affects how managers interpret their en- vironments (Nadkarni & Barr, 2008; Nadkarni &Narayanan, 2007a), further highlighting the ef- fects of environmental dynamism on key orga- nizational members (Dess & Beard, 1984). A common feature of the treatment of environmental velocity in the literature has been the use of singular categorical descriptors to char- acterize industries —most typically as "low," "moderate," or "high" velocity (e.g., Bourgeois &Eisenhardt, 1988; Eisenhardt, 1989; Eisenhardt & Tabrizi, 1995; Judge & Miller, 1991; Nadkarni &Narayanan, 2007a,b). Although Bourgeois and Eisenhardt (1988) defined environmental veloc- ity in terms of change (rate and direction) in multiple dimensions (demand, competitors, technology, and regulation), research on veloc- ity has tended to overlook its multidimensionality, instead assuming that a single velocity can be determined by aggregating the paces of change across all the dimensions of an organi- zation's environment. This assumption over- looks the fact that environmental velocity is a vector quantity jointly defined by two attributes (the rate and the direction of change) and that organizational environments are composed of multiple dimensions, each of which may be as- sociated with a distinct rate and direction of change.
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In this paper we aim to advance understand- ing of environmental velocity by developing a theoretical framework that articulates its multi- dimensionality and by exploring the implica- tions of this framework for understanding the organization-environment relationship. We ar- gue that while there may be cases in which organizational environments can be accurately specified by a single descriptor (e.g., high veloc- ity), a multidimensional conceptualization opens up a number of opportunities. First, it provides a basis for more fine-grained descrip- tions of the patterns of change that occur in organizational environments. An understanding of a firm's environmental velocity as composed of multiple, distinct rates and directions of change across multiple dimensions allows us to move beyond characterizations of industries as high or low velocity and the assumption that all dimensions change at similar rates and in sim- ilar directions (Bourgeois & Eisenhardt, 1988; Eisenhardt, 1989; Judge & Miller, 1991; Smith et al., 1994). Perhaps most important in this regard, a multidimensional conceptualization allows for an examination of the relationships among the dimensions of velocity, which we argue can have a profound impact on organizations. Second, a multidimensional conceptualiza- tion of velocity offers a foundation for more con- sistent operationalizations of the construct, which would help improve the reliability and validity of research that employs it. Our review of the environmental velocity literature indi- cates a reliance on singular descriptors of ve- locity, which has led to inconsistent operation- alizations of the construct. Thus, while it has sometimes been claimed that people can recognize a high-velocity environment when they see one (Judge & Miller, 1991), the different ways that the velocity of the same industry has been cat- egorized by different researchers would seem to indicate otherwise. Such inconsistencies may be due to focusing on one or two particularly sa- lient velocity dimensions or to combining data for multiple velocity dimensions without consid- ering the aggregation errors that can occur if the dimensions do not perfectly covary. Finally, by understanding that the environ- ments of organizations have multiple, distinct velocities, it is possible to identify different pat- terns of environmental velocity whose condi- tions affect organizations in ways that go be- yond the insights that have emerged from
studies characterizing velocity as simply high or low. Specifically, we explain how the multidi- mensionality of velocity can affect the degree to which an organization's activities will be en- trained and adjusted over time. We then high- light how these implications apply to two pro- cesses that have been central to prior research on velocity: strategic decision making and new product development. Our exclusive focus on environmental velocity differs from prior research that has sought to characterize organizational environments in terms of a set of core properties —most com- monly some variation of complexity, dynamism, and munificence (Aldrich, 1979; Dess & Beard, 1984; Scott, 1981). In pursuing this aim, we rec- ognize the trade-offs among generalizability, ac- curacy, and simplicity (Blalock, 1982) inherent in examining one aspect of the environment in depth while bracketing other important environ- mental dimensions. Research focused on the general organizational environment has strived for "high levels of simplicity and generalizability, with a corresponding sacrifice of accuracy" (Dess & Rasheed, 1991: 703). This approach has been characterized as "collapsing" the hetero- geneity of the environment into a more parsimo- nious set of properties (Keats & Hitt, 1988). In contrast, we focus on a single specific aspect of environmental dynamism— velocity—and ex- plore in detail its dimensions, how the velocities of these dimensions vary and interact, and the consequences of those differences and interac- tions. Our approach follows other studies that have examined specific environmental con- structs, such as uncertainty (Milliken, 1987) and munificence (Castrogiovanni, 1991). An impor- tant consequence of focusing on a single aspect of the environment is that any normative or pre- dictive claims we make must be made with ceteris paribus restrictions placed on them. This, of course, complicates the application of such claims in research or practice but also allows a deeper examination of specific phenomena (Pi- etroski & Rey, 1995). We present our arguments as follows. First, we review the concept of environmental velocity as it has been developed in management re- search, focusing on the opportunities that this work presents for developing a multidimen- sional conceptualization. Second, we present our framework by defining several fundamental dimensions of the organizational environment
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and defining the key aspects of velocity —the rate and direction of change —for each dimen- sion. Third, we examine the potential relation- ships among velocity dimensions (such as prod- ucts and technology) by introducing three concepts: (1) "velocity homology," which is the degree to which velocity dimensions have sim- ilar rates and directions of change at a point in time; (2) "velocity coupling," which is the degree to which the velocities of different dimensions affect one another over time; and (3) "velocity regimes," which represent patterns of velocity homology and velocity coupling. Fourth, we ex- plore the implications of our framework for or- ganization-environment relationships and for strategic decision making and new product development. ENVIRONMENTAL VELOCITY IN MANAGEMENT RESEARCH In physics, velocity refers to the rate of displacement or movement of a body in a particular direction. Thus, it is a vector quantity jointly defined by two distinct attributes: the rate of change and the direction of change. The defini- tion of high-velocity environments articulated by Bourgeois and Eisenhardt (1988) captured these two attributes, referring to rapid and dis- continuous change in multiple dimensions of the environment, such as demand, competitors, technology, and regulation. The notion of high velocity provided an evocative way to charac- terize the fast-moving, high-technology industry that was the context of their studies, and it com- plemented a number of similar but conceptually distinct environmental constructs, including dy- namism (Baum & Wally, 2003; Dess & Beard, 1984; Lawrence & Lorsch, 1967), turbulence (Em- ery & Trist, 1965; Terreberry, 1968), and hypertur- bulence (McCann & Selsky, 1984). More recently, environmental velocity has been used in con- junction with or as a synonym for other related environmental constructs, such as "clockspeed" (i.e., the speed of change in an industry; Fine, 1998; Nadkarni & Narayanan, 2007a,b) and hy- percompetition (Bogner & Barr, 2000; D'Aveni, 1994). Table 1 lists some of the major studies in stra- tegic management and organization theory in which the concept of environmental velocity plays a central role. For each study the table delineates the phenomenon of interest, the in-
dustry context, the level (high, moderate, or low) of velocity considered, and the measures em- ployed (if any). Looking across these studies, we identify three themes that characterize much of the existing research in the area and provide the motivation for the theoretical framework that we develop. First, existing studies have predominantly fo- cused on high-velocity environments, with lim- ited attention to other potential patterns of ve- locity. Consequently, we know relatively little, for instance, about the velocity-related chal- lenges faced by firms operating in low-velocity environments, where the slow pace of change may be associated with protracted development lead times, long decision horizons, and rela- tively infrequent feedback. Also, and more generally, the focus on high-velocity environments may be a significant factor in the treatment of velocity in terms of singular categorical descrip- tors; the term high-velocity environment itself seems to imply that multiple dimensions of the environment (e.g., products, markets, technol- ogy) combine nonproblematically to produce a single, cumulative, high level of velocity. While this may be true in some cases, it is not clear that it applies broadly across firms and industries. Second, high-velocity environments are often presented as synonymous with high-technology industries, perhaps because Bourgeois and Eisenhardt's initial study focused on the early microcomputer industry. Industries have been categorized as high velocity simply because they are technology intensive (Smith et al., 1994) or are built around an evolving scientific base (Eisenhardt & Tabrizi, 1995), regardless of whether other environmental dimensions ex- hibit low or modest rates of change or relatively continuous directions. Judge and Miller (1991), for instance, identified the biotechnology indus- try as high velocity, despite its relatively long product development lead times and product life cycles (both ten to twenty years). Finally, existing research tends to lack an ex- plicit measurement model or justification for the categorization of specific organizational con-texts or industries. Instead, researchers declare that they are studying high-velocity environ- ments and reiterate Bourgeois and Eisenhardt's (1988) original definition without significant ex- planation or direct evidence (the studies by Judge and Miller [1991] and Nadkarni and Barr
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TABLE 1 Environmental Velocity in Management Research
Example Studies Bourgeois & Eisenhardt (1988) Eisenhardt & Bourgeois (1988) Eisenhardt (1989) Judge & Miller (1991) Smith et al. (1994) Management/Organization Phenomena Pace and style of strategic decision making Politics of strategic decision making Rapid strategic decision making Antecedents and outcomes of decision speed The effect of team demography and team process Level of Velocity (Industry Context) High (microcomputer industry) High (microcomputer industry) High (microcomputer industry) High (biotechnology), medium (hospital), and low (textile) High (informational, electrical, biomedical, environmental) High (computer) High (computer) High (health care) High (IT) High (toys and IT tools) High and low (industries not specified) High (computer), medium (auto), and low (steel) High (computers, toys) and low (aircraft, steel) High (computers, toys) and low (aircraft, steel) High (semiconductor, cosmetic) and low (aircraft, petrochemical) High and low (conceptual simulation model) Conceptualization of Velocity Uniform change in the rate and direction of demand, competition, technology, and regulation As per Bourgeois & Eisenhardt (1988) As per Bourgeois & Eisenhardt (1988) Aggregation of industry growth and perceived pace of technological, regulatory, and competitive change Rate of change in product, demand, and competition Velocity Measures Used Illustrative statistics and examples Illustrative statistics and examples Illustrative statistics and examples Industry data and survey data from firms Illustrative statistics
Eisenhardt & Tabrizi (1995) Brown & Eisenhardt (1997) Stepanovich & Uhrig (1999) Bogner & Barr (2000) Oliver & Roos (2005) Brauer & Schmidt (2006) Davis & Shirato (2007) Nadkarni & Narayanan (2007a) Nadkarni & Narayanan (2007b) Nadkarni & Barr (2008)
Rapid organizational adaptation and fast product innovation Continuous organization change Strategic decision-making practices Cognitive and sensemaking abilities Team-based decision making Temporal development of a firm's strategy implementation A firm's propensity to launch World Trade Organization actions How cognitive construction by firms drives industry velocity Relationship between strategic schemas and strategic flexibility How velocity affects managerial cognition, which in turn affects the relationship between industry context and strategic action The performance and structural implications of velocity
As per Bourgeois & Eisenhardt (1988) As per Bourgeois & Eisenhardt (1988) Rate of change in demand, competition, technology, and regulations A form of hypercompetition Rate of change and the time available to make decisions A form of dynamism and volatility The number of product lines and the rate of product turnover Rate of change (clockspeed) for product, process, and organizational dimensions The rate of industry change (clockspeed) As per Bourgeois & Eisenhardt (1988)
Illustrative statistics and examples Illustrative statistics and examples An illustrative example None None Industry market returns data R&D expenditure/ total revenue Industry clockspeeds Industry clockspeeds A review of existing literature and matching using industry attributes A Poisson distribution of new opportunities
Davis, Eisenhardt, & Bingham (2009)
The speed or rate at which new opportunities emerge in the environment
[2008] representing notable exceptions). This variation in the extent to which velocity has been operationalized has resulted in some coun- terintuitive and inconsistent categorizations of industry velocity. Studies of health care, for in- stance, have labeled those environments as both high velocity (Stepanovich & Uhrig, 1999) and moderate velocity (Judge & Miller, 1991). Furthermore, our understanding of velocity and its effects across industry contexts has largely focused on only one attribute of velocity—the rate of change —since prior research has tended to use measures associated with the clockspeed of an industry (e.g., Nadkarni & Narayanan, 2007a; Oliver & Roos, 2005; Smith et al., 1994) or
has equated velocity with the speed at which new opportunities emerge (Davis, Eisenhardt, &Bingham, 2009). Looking across these themes, we see that re- search on environmental velocity has provided interesting and influential insights, particularly into the nature of organizational processes op- erating in fast-changing, high-technology in- dustries. We suggest, however, that the con- struct itself requires a more finegrained examination, since existing research tends to assume that it can be adequately represented by an aggregation of the rates of change across different environmental dimensions or by a fo- cus on change in only one dimension of the
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environment to the exclusion of others. In con- trast, we believe that a multidimensional conceptualization of velocity would provide a stronger foundation for clarifying and opera- tionalizing its characteristics and for better understanding its diversity and impacts on organizations. ENVIRONMENTAL VELOCITY AS A MULTIDIMENSIONAL CONCEPT The core understanding of environmental velocity that we propose is that organizational environments are composed of multiple dimen- sions, each of which is associated with its own rate and direction of change. This simple notion, we argue, has profound effects on how we un- derstand and research velocity and on the or- ganizational reactions to velocity we expect and prescribe. In this section we begin to construct our theoretical framework, first by defining the basic concepts of rate of change and direction of change as they apply to the organizational en- vironment in general, and then by describing how these basic concepts apply to some primary dimensions of the organizational environment. The Rate and Direction of Change Environmental velocity is a vector quantity defined by the rate and direction of change ex- hibited by one or more dimensions of the orga- nizational environment over a specified period. The rate of change is the amount of change in a dimension of the environment over a specified period of time, synonymous with such concepts as pace, speed, clock rate, or frequency of change. The direction of change, while often mentioned in studies citing Bourgeois and Eisenhardt's (1988) definition, has attracted relatively little attention beyond that. One possible reason for this is the relative difficulty of de- scribing the direction of environmental change. Whereas the velocity of a physical object can be described simply as moving eastward at 50 km/ hr, similarly straightforward descriptions of the direction of change of an organizational envi- ronment are not so obvious. This is particularly the case when we consider the direction of change across different industry dimensions, such as products, technology, and regulation, the direction of each of which could be de- scribed in numerous distinct ways.
In order to describe the direction of change in a way that allows comparison across industry dimensions, we follow Bourgeois and Eisen- hardt (1988), who suggest that the direction of change varies in terms of its degree of continu- ity-discontinuity. They argue that continuous change represents an extension of past devel- opment (e.g., continuously faster computer tech- nology), whereas discontinuous change represents a shift in direction (the move from film to digital photography, or the shifts that occur in fashion industries). Discontinuities, therefore, can be represented by inflection points in the trajectories that describe change in a dimension over time (e.g., technology price-performance curves or demand curves for specific products). To more fully articulate a continuum of continuous-discontinuous change, we draw on Wholey and Brittain's (1989) three-part concep- tualization of environmental variation, arguing that the direction of change is discontinuous to the extent that shifts in the trajectory of change are more recurrent, with greater amplitude and with greater unpredictability over a period of time. This approach helps us distinguish between relatively regular, predictable (e.g., sea- sonal) variations in environmental velocity and irregular types of change that are more difficult to predict and, consequently, more challenging in terms of organizational responses (Milliken, 1987). We suggest that such variations in the continuity-discontinuity of a velocity dimen- sion's trajectory allow for the use of structural equation modeling (Kline, 2004) and difference scores (Edwards, 1994) to produce growth models that measure transitions in change over time (Bliese, Chan, & Ployhart, 2007; Singer & Willett, 2003). Furthermore, to operationalize the rate and direction of change of each velocity dimension, we suggest that the measures will require scale uniformity to allow the relative differences be- tween the dimensions to be compared and cor- related (Downey, Hellriegel, & Slocum, 1975; Mil- liken, 1987). To achieve this, we suggest that the rate and direction of change will be some form of scalar measure (e.g., change/time). Therefore, even though what is changing will vary for each of the dimensions, their relative rates and direc- tions of change can be determined and com- pared by using the same period of time for the different dimensions (i.e., new products per year and changes in product direction per year).
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Dimensions of Environmental Velocity The second way in which we break down the concept of environmental velocity is in terms of the dimensions of the organizational environ- ment that are changing. While the dimensions of the environment that are salient for any par- ticular study will vary according to the specifics of the research project, there are several that have been widely used in prior research on or- ganizational environments. We use the four di- mensions suggested by Bourgeois and Eisen- hardt (1988)— demand, competitors, technology, and regulation —and to this list we add a fifth dimension—products. We do this because prior research on environmental velocity has tended to merge the technology and product dimen- sions, and we argue that they often have dissim- ilar rates and directions of change, which makes separating them important for our purposes. Archibugi and Pianta (1996) point to the impor- tance of this distinction when they argue that product changes need not be technical but can also include changes in the aesthetic, branding, or pricing features of a product. Our discussion of environmental dimensions is not meant to be exhaustive; rather, it is meant to highlight the heterogeneity of environmental dimensions that motivates our development of a multidimen- sional conceptualization of velocity. Technological velocity. Technological velocity is the rate and direction of change in the pro-
duction processes and component technologies that underlie a specific industrial context, such as float glass technology in glass manufactur- ing, genetic engineering in the biotechnology industry, and rolling mills in metals processing. See Table 2 for a summary of the definitions for each of the velocity dimensions on which we focus. The rate of technological change is the amount of change in those technologies over a specific time period, including the creation of new technologies, the refinement of existing technologies, and the recombination of compo- nent technologies. The rate of technological change varies dramatically across industries. Drawing on patents as an indicator of the rate of technological change, one can argue, for instance, that the electronics industry exhibits a more rapid rate of technological change than does the oil industry. In 2006, rankings for the number of patents granted in the United States showed that the top five positions were held by electronics companies, whereas the oil industry firms Shell and Exxon occupied positions 126 and 139, respectively (IFI, 2008). Although some technological change is either not patentable or not patented for strategic reasons, the rate of patenting can nevertheless provide a useful indication of the technological rate of change since it is a relatively direct and publicly avail- able indicator of the proprietary technological
TABLE 2 Environmental Velocity: Dimension Definitions and Example Measures
Definition/Example Measures Velocity dimension definition Technological Product Demand Regulatory Competitive
Example measures of the rate of change in the dimension Example measures of the direction of change in the dimension
The rate and direction The rate and direction The rate and direction The rate and direction The rate and direction of change in the of change in new of change in the of change in laws of change in the production product willingness and and regulations that structure of processes and introductions and ability of the market affect an industry competition within component product to pay for goods an industry technologies that enhancements and services underlie a specific industrial context The number of new The number of new The change in The number of new The change in patents and products introduced industry sales in a and amended laws industry population copyrights granted in a given period given period and/or regulations size and density in a given period (i.e., product introduced in a (i.e., number and clockspeed) given period size of firms) in a given period The changes in the The change in the The change in the The change in the The change in direction of the nature of product trend (e.g., growth nature and scope of industry growth relationship features as versus decline) and the control provided trends (e.g., growth between the price perceived by the nature (e.g., by new laws and versus decline) in a and technical market in a given personal versus regulations in a given period performance of period impersonal) of given period technology in a demand in a given given period period
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outputs of an industry (Archibugi & Pianta, 1996; Griliches, 1990). The direction of technological change refers to the trajectories along which technological advancements take place (Abernathy & Clark, 1985; Dosi, 1982; Tushman & Anderson, 1986). Distinguishing between continuous and discontin- uous directions of technological change is most easily understood in terms of performance/price curves. Continuous technological change in- volves a series of improvements that enhance the performance of the technology (e.g., ad- vances in photographic film technology focused on improving contrast quality, light sensitivity, and speed). Such changes move a technology smoothly along a performance/price curve, usu- ally at a decreasing rate, thus creating a concave downward performance/price curve. In contrast, discontinuous technological change involves "architectural" (Henderson & Clark, 1990) or "radical" innovations that "dramatically advance an industry's price vs. performance frontier" (Anderson & Tushman, 1990: 604). These innovations temporarily alter the shape of the performance/price curve such that it becomes concave upward until the immediate benefits of the innovation are exhausted. Product velocity. This dimension is the rate and direction of new product introductions and product enhancements. We define products as any combination of ideas, services, and goods offered to the market (Kotler, 1984). The rate of change in products can vary tremendously across industries and across market segments within an industry. In terms of the former, Fine (1998) and Nadkarni and Narayanan (2007a,b) show that the movie, toy, and athletic footwear industries have relatively high rates of product change (new products launched every three to six months), whereas the aircraft, petrochemi- cal, and paper industries have low rates of prod- uct change (new products launched every ten to twenty years). The direction of change for products can be described as continuous when new product introductions represent improvements on previ- ously important product attributes, and discon- tinuous when the new products introduce fundamentally new attributes for consumer choice. Adner and Levinthal's (2001) study of the personal computer industry between 1974 and 1998 provides an example of relatively continu- ous product change, with only two major inflec-
tion points with respect to price (in 1981 and 1988) and no major inflection points with respect to performance. In contrast, fashion products, such as clothing, music, and travel, all change frequently through the creation of new products and the transformation and repackaging of ex- isting ones. Such variations in product change across industries are associated with differ- ences in the complexity, risk, and impact of the product change. While velocity research has often lumped to- gether product and technological velocities, our definitions of their rates and directions of change illustrate the importance of distinguish- ing between them. Over the past several de- cades, for example, the underlying materials and production processes in the automobile industry have changed more rapidly and dis- continuously than have the end products themselves. In contrast, textile production technolo- gies have changed more slowly and continuously than the fashion products they are used to create. Demand velocity. Demand velocity is the rate and direction of change of the willingness and ability of the market to pay for goods or services, including changes in the number and types of transactions and market segments. The rate of change in demand varies tremendously across industries, with some experiencing rapid growth or decline and others facing steady growth for years. Such variance is influenced by a wide range of factors, including changes in taste, new rival products, substitutes, comple- ments, changes in relative prices, business cy- cle fluctuations, and switching costs. Empirical research has used summary industry sales fig- ures as an indicator of the rate of change in demand (e.g., Bourgeois & Eisenhardt, 1988). The direction of change for demand is contin- uous when there is a steady progression of in- creasing or decreasing sales to a consistent set of consumers. Conversely, change in the direc- tion of demand is discontinuous when there are frequent, significant, unpredictable shifts in the growth, decline, or steady state of demand, or a radical change in the segments that compose the overall market. For example, demand veloc- ity in the U.S. restaurant industry from 1970 to 1995 was relatively continuous, with sales gains made nearly every year during that period (Harrington, 2001). In contrast, the demand for commodities, such as copper and gold, can be
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highly volatile owing to a wide range of macroeconomic influences, exemplifying the case of a discontinuous demand velocity. Similarly, the Nintendo Corporation created discontinuous change in the demographics of demand since its Wii games console appealed to nontraditional market segments, such as families, women, and older people. Regulatory velocity. We define regulatory velocity as the rate and direction of change in the regulations and/or laws that directly affect the firm or industry under consideration. This in- cludes government action (e.g., changes in laws, regulations, and polices) and industry self- regulation (e.g., voluntary standards and codes). It is a dimension that can open or close markets, present organizations with compliance costs, and necessitate strategic shifts in practices. The rate of regulatory change is a function of the creation of new laws or regulations, or changes to existing laws or regulations, in a time period. It can vary greatly across industrial, national, and historical contexts, and it often depends on other factors, such as technology (e.g., regula- tions for stem cell research), business scandals (e.g., the Enron scandal), health and safety is- sues (e.g., mad cow disease), and demographic shifts (e.g., an increase in the retired population). The direction of change in regulation is continuous to the degree that new regulations re- semble the old in scope, form, or substantive areas of concern, and it is discontinuous to the degree that they address new issues, focus on different kinds of behaviors, or employ new prin- ciples. For example, the U.S. airline industry from 1938 to 1975 experienced changes in regu- lations that were relatively continuous, in that the Civil Aeronautics Board (CAB) restricted prices, flight frequency, and flight capacity (Vietor, 1990). Then, in 1975, the direction of reg- ulatory change changed as the CAB began ex- perimenting with limited deregulation, and in 1978 the industry was completely deregulated and the CAB abolished. Competitive velocity. Competitive velocity is the rate and direction of change in the structural determinants of industry profitability (Barney, 1986; Porter, 1980). Its rate of change is, in part, a function of the entrance and exit of industry rivals (Hannan & Carroll, 1992), as well as the speed with which firms respond to competitors' strategic moves or other shifts in the environ-
ment (Bowman & Gatignon, 1995). Such mea- sures describe the overall pace at which the competitive conditions that define an industry are changing—a factor that has been shown to influence firm performance across a wide range of industries, including the automotive (Hannan, Carroll, Dundon, & Torres, 1995), computer (Hen- derson, 1999), and insurance (Ranger-Moore, 1997) industries. The direction of change in competitive struc- ture involves continuity-discontinuity with re- spect to the value chain in an industry (Jaco- bides & Winter, 2005), the nature of rivals (Porter, 1980; Schumpeter, 1950), or changes in market contestability (Hatten & Hatten, 1987). Change incompetitive structure is continuous to the de- gree that these characteristics remain constant and stable over time. Conversely, the change in direction in competitive structure is discontinu- ous to the degree that industry value chains are in flux (Jacobides, 2005) and existing bases of competition are challenged by firms introducing new products, pioneering new markets or sources of supply, or implementing new means of production (Schumpeter, 1950). RELATIONSHIPS AMONG VELOCITY DIMENSIONS: VELOCITY HOMOLOGY, VELOCITY COUPLING, AND VELOCITY REGIMES An important benefit of a multidimensional conceptualization of environmental velocity is the potential it provides to examine the differ- ences and relationships among the velocities of different dimensions. To that end, we introduce three concepts: (1) velocity homology—the rela- tive similarity among the rates and directions of change of different dimensions; (2) velocity cou- pling—the degree to which the velocities of dif- ferent dimensions are causally connected; and (3) velocity regimes —the different patterns of environmental velocity that emerge from varia- tions in velocity homology and velocity coupling. Velocity Homology The term homology was coined by the paleontologist Richard Owen (1843) to explain the morphological similarities among organisms. It has been used by management scholars to describe the degree to which two phenomena are similar
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(Chen, Bliese, & Mathieu, 2005; Glick, 1985; Han- lon, 2004) and is consistent with the homogene- ityheterogeneity aspect of environmental com- plexity (Aldrich, 1979; Dess & Beard, 1984). In our framework, velocity homology is the degree to which the rates and directions of change of dif- ferent dimensions are similar to each other over a period of time. Thus, "high homology" de- scribes a condition in which the velocities of different dimensions in a given environment ex- hibit relatively similar rates and directions of change, whereas "low homology" describes rel- atively dissimilar rates and directions of change. To help explain velocity homology, we present a map of the velocities of different dimensions, with the rate of change and the direction of change on each axis (see Figure 1). With this image of velocity (based on the fashion apparel industry example we present in the following sections), homology is represented by the close- ness of the points. Thus, low homology (as is the case in Figure 1) is represented by relatively spread out points, and high homology would be represented by relatively tightly clustered points. To operationalize this concept of homol- ogy, we suggest using distance measures and methods, such as cluster analysis (Ketchen &
Shook, 1996), factor analysis (Segars & Grover, 1993), and multidimensional scaling (Cox & Cox, 2001), all of which are considered suitable for assessing interdimension similarity in construct composition (Harrison & Klein, 2007; Law, Wong, & Mobley, 1998). An assumption of a highly homologous set of velocities typified much of the early work on highvelocity environments, in which industries such as microcomputers were characterized by "rapid and discontinuous change" across multi- ple dimensions (Bourgeois & Eisenhardt, 1988: 816). An assumption of high homology carried over to subsequent studies, with limited consid- eration of the degree to which homology might vary across firms and industries. Most studies seem to have aggregated the velocities of differ- ent dimensions, regardless of the variance among these dimensions, thereby assuming similarity (i.e., high homology in our terms) among the velocities of different environmental dimensions. Consequently, we know relatively little about the conditions and effects of low- homology environments, where the velocity properties of a firm's multiple environmental di- mensions are highly dissimilar. To illustrate and clarify the concept of homol- ogy, we present the example of the apparel in-
FIGURE 1 Fashion Apparel Industry Example
Discontinuous Demand
Direction of change
Competitive
Product
Regulatory Continuous Low
Technological
Rate of change
High
Key: The solid lines indicate tight coupling and the dashed lines loose coupling.
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dustry and focus on the industry segment in- volved in the design and supply of seasonal fashion apparel. This includes brands sold pri- marily through ownbrand stores (e.g., Gap, Zara, and American Apparel) and brands sold through a mixture of own-brand stores and in- dependent stores (e.g., Armani, Benetton, and Levi's). We chose this industry because aca- demic studies and business reports suggest that from 1985 through 2005 the velocities of different dimensions in this industry spanned a diverse range of rates and directions of change (Djelic & Ainamo, 1999; The Economist, 2005; Jacobides &Billinger, 2006; Taplin & Winterton, 1995). Beginning with the product dimension, this segment of fashion retailing is associated with a relatively high rate of change and a moder- ately discontinuous direction. This is illustrated by the operations of Zara, one of Europe's lead- ing fashion brands. Zara launches some 11,000 new products annually, most of which are com- pletely new products as perceived by the cus- tomer and typically take only five weeks from design to retail store ( The Economist, 2005). Even casual fashion houses, such as Sweden's Hennes & Mauritz (H&M) and the American chain Gap, roll out between 2,000 and 4,000 prod- ucts each year. Moreover, the rate of change in products has increased, with the emergence of "fast fashion" as a dominant strategy for mass market designers/retailers (Doeringer & Crean, 2006). We argue that the direction of product change is moderately discontinuous, because although these firms launch many new prod- ucts, they represent a mix of new items and extensions of existing products. This view is consistent with studies of the rate and direction of change in women's formal wear (Lowe &Lowe, 1990). The technologies that underpin the fashion industry have been changing rapidly over the past twenty years (cf. Richardson, 1996) but at a relatively slower rate than changes in fashion products. Although manufacturing technology in the apparel industry has remained stable for nearly a century (Audet & Safadi, 2004), there have been advances in the manufacture of tex- tiles, as well as in communication and information technologies, that have facilitated the move to quick response (Forza & Vinelli, 1997) and fast fashion (Doeringer & Crean, 2006) strategies in fashion design and retailing. The direction of these changes has been relatively continuous
over the past twenty or so years —toward greater automation and efficiency in textile manufac- turing, more rapid response to customer de- mands, and more efficient communication and coordination in fashion design and retailing (Doeringer & Crean, 2006; The Economist, 2005). In contrast to product and technological veloc- ities, regulatory change in this industry has, for the past two decades, occurred relatively slowly and continuously. The regulation that affects this industry most significantly is directed at the manufacture of clothing and the protection of consumer rights, both of which have changed slowly over that period. With respect to the man- ufacture of garments, the Multi Fibre Arrange- ment (MFA) was introduced in 1974 as a short- term measure to govern world trade in textiles and garments, imposing quotas on the amount developing countries could export to developed countries (Spinanger, 1999). This regulation underwent only minor modifications until it ex- pired in 2005 (Audet & Safadi, 2004). National- level regulation tends to focus on labor and employment standards. In response to the shift of clothing manufacturing from developed to emerging economies, the governments of West- ern nations have been reluctant to further regu- late (and potentially stifle) clothing manufactur- ing, much of which occurs as home-based work (Ng, 2007). Change in demand for fashion apparel has, for the past twenty years, occurred moderately slowly, with a high degree of discontinuity. Re- searchers argue that the fashion industry is characterized by low to moderate levels of pos- itive sales growth each year (Nueno & Quelch, 1998), with occasional major demographic and lifestyle shifts and changes in customer prefer- ences (Danneels, 2003; Siggelkow, 2001). Al- though the direction of change in demand for fashion has oscillated between relative stability and discontinuity over the last 150 years (Djelic & Ainamo, 1999), the past 20-year period has been associated with customers becoming more demanding, arbitrary, and heterogeneous (Djelic & Ainamo, 1999; The Economist, 2005). The competitive velocity of the fashion indus- try has long fascinated observers. In recent years it has altered as increased cost pressures have led firms to engage in rapid-fire attempts to source the lowest-cost materials and to move labor-intensive aspects of the value chain to countries with lower costs. The industry has also
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experienced constant shifts in the major centers of production (Dosi, Freeman, & Fabiani, 1994). By way of example, U.S. employment levels in this sector in 2002 were a third of what they were in the early 1980s (Doeringer & Crean, 2006). The intersection of cost pressures and the increasing rate of change in consumer preference and de- mand has led to significant shifts in firms' strat- egies, particularly speeding up the supply chain (Richardson, 1996) and altering organizational structures and boundaries (Djelic & Ainamo 1999; Jacobides & Billinger, 2006; Siggelkow, 2001). Such conditions characterize change that is both moderately rapid and continuous in nature. The fashion industry points to two important issues with respect to understanding homology among environmental velocity dimensions. First, it highlights that the organizational envi- ronment is composed of a number of distinct dimensions, each of which is defined by its own rate and direction of change — or velocity. Sec- ond, we see that there are significant differ- ences in the rates and directions of change (low homology) across the five dimensions that we have considered. This makes the idea of describing the industry as having a single veloc- ity, whether based on an "average" across di- mensions or on the velocity of whichever dimension might be considered most important, misleading both to researchers attempting to understand the industry and to managers need- ing to make strategic decisions.
Velocity Coupling A second important aspect of the relationship between velocity dimensions is the degree to which and the ways in which they interact over time. We examine these interactions through the concept of coupling. This is the degree to which elements of a system, including product compo- nents (Baldwin & Clark, 1997; Sanchez & Ma- honey, 1996), individuals (DiTomaso, 2001), or- ganizational subunits (Meyer & Rowan, 1977; Weick, 1976, 1982), and organizations (Afuah, 2001; Brusoni, Prencipe, & Pavitt, 2001), are caus- ally linked to each other (Orton & Weick, 1990; Weick, 1976). In our framework velocity coupling is the degree to which the velocities of different dimensions in an organizational environment are causally connected —the degree to which a
change in the velocity of one dimension causes a change in the velocity of another. Weick (1976) defined loosely coupled systems as those in which the properties of constitutive elements are relatively independent, whereas the properties of elements in tightly coupled sys- tems are strongly mutually dependent. Weick (1982) further argued that loose coupling in- volves causal effects that are relatively periodic, occasional, and negligible, whereas tight cou- pling involves relatively continuous, constant, and significant causal effects. Thus, we de- scribe the velocities of different dimensions of a firm's environment as loosely coupled when changes in the velocity of one dimension (e.g., technology velocity) have relatively little imme- diate, direct impact on the velocities of other dimensions (e.g., product velocity), and we de- scribe them as tightly coupled when the rela- tionship between the velocities of different di- mensions involve significant immediate, direct causal effects. To determine the degree of cou- pling between velocity dimensions, we suggest using structural equation modeling (Kline, 2004), which is recommended for operationalizing covariance between construct variables (Law et al., 1998). Although coupling and homology both de- scribe the relationships among velocity dimen- sions, they are separate, distinguishable as- pects of those relationships. The velocities of different dimensions can have high levels of interdependence (coupling), regardless of whether they exhibit similar rates and direc- tions of change (homology). Homology is a first- order property of velocity, describing the similarity among velocities over a period of time. In contrast, coupling is a second-order property, describing the degree to which changes in the velocity of a dimension affect the velocity of another dimension over the same specified pe- riod of time. The distinction between homology and coupling is observable in the biotechnology industry, which experiences high rates and dis- continuous directions of technological change but relatively slow, continuous regulatory and product velocities (Zollo, Reuer, & Singh, 2002). While these dimensions have very different ve- locities (low homology), there is evidence to sug- gest that they are relatively tightly coupled. This is illustrated by the impacts of the 2001 U.S. regulation on stem cell research, which restricted research to twenty-one stem cell lines (a
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family of constantly dividing cells) and, in turn, limited the rate and direction of U.S. stem cell research activity (i.e., technological velocity) rel- ative to other countries. In 2009 this regulation was overturned, permitting research on up to 1,000 new stem cell lines, allowing "U.S. human embryonic stemcell research to thrive at last" (Hayden, 2009: 130). We again draw on the fashion apparel indus- try to illustrate the idea of coupling among ve- locity dimensions. Beginning with products, changes in the velocity of this dimension have been attributed to increases in the adoption of new communications, design, and manufactur- ing technologies, suggesting a relatively tight coupling between product and technological ve- locity dimensions. Perhaps most significant, changes in the direction of technology have im- proved the ability of fashion apparel firms to gather market feedback and, thus, to develop new product offerings at a faster rate (Jacobides& Billinger, 2006; Kraut, Steinfield, Chan, Butler, & Hoag, 1999; Richardson, 1996). Similarly, the velocity of demand has been tightly coupled to product velocity over the past two decades: in- dustry observers argue that the perceived new arbitrariness of customer demand has forced fashion organizations to frequently engage in large-scale market explorations (Cammet, 2006; Jacobides & Billinger, 2006). In contrast, there is little evidence of a strong relationship between product velocity and competitive velocity. Prod- uct velocity appears to be primarily driven by changes in market demand and the product in- novation programs of existing organizations exploiting those changes, as opposed to a flow of new entrants (Cammet, 2006). In terms of the velocity of regulation in this industry, there is evidence that it is tightly cou- pled to the velocities of competition, demand, and products, with changes in international trade regulations (Spinanger, 1999) and domes- tic labor standards (Ng, 2007) leading to increas- ing imports from developing economies, both creating and satisfying the demand for cheaper fashion products. Similarly, the velocities of competition and demand appear to be tightly coupled, with firms in this industry attempting to predict and adapt to what Siggelkow (2001) calls "fitdestroying changes" that can signifi- cantly alter their competitive positions. There is also tight coupling between the velocity of tech- nology and the velocity of demand. For example,
in their study of the U.S. fashion apparel indus- try in the 1980s, Abernathy, Dunlop, Hammond, and Weil (1999) explain how changes in demand led to "lean retailing," which, in turn, required firms to drastically alter their information and production technologies to enable new working practices. In contrast, there is little evidence to suggest that changes in the velocity of technol- ogy for the fashion industry will affect or are affected by changes in the velocities of competition or regulation. In this illustrative example (see Figure 1), we argue that seven of ten possible dyadic connec- tions among velocity dimensions are relatively tightly coupled (designated by solid lines) such that changes in the velocity of one dimension will affect the velocity of another. We have ar- gued that the three other connections are loosely coupled, as indicated by the dotted lines. Thus, although not all of the velocity dimensions of the fashion industry exhibit strong causal connections to each other, we suggest that this industry can be described as a rela- tively tightly coupled environment. Any assign- ment of such a category is somewhat arbitrary without a formal measurement of coupling, so for now we follow work on modular (loosely cou- pled) and integrated (tightly coupled) organiza- tional forms that suggests that when at least 50 percent of the system elements are tightly cou- pled to each other, the system can be considered tightly coupled (Schilling & Steensma, 2001).
Velocity Regimes We propose the concept of a velocity regime as a way to describe the pattern of velocity homology and velocity coupling within an organizational environment. Although both these characteristics of velocity vary continuously, we focus on combinations of high or low homology and tight or loose coupling to more clearly illus- trate how they vary and the effects of these variations. The result is a typology (see Figure 2) with four distinct velocity regimes that repre- sent ideal types, rather than an exhaustive tax- onomy of velocity conditions. To illustrate and visualize the degrees of homology and coupling that characterize each regime, we have embed- ded a variation of Figure 1 into each cell of Figure 2. Like Figure 1, these embedded figures present illustrative sets of velocities, the rela-
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FIGURE 2 Environmental Velocity Regimes
Con?icted velocity regime R Tight Direction of change C Direction of change D
Integrated velocity regime
R
D C
T P
T Rate of change
P Rate of change
Velocity coupling
Divergent velocity regime R Direction of change Loose T Rate of change P D
Simple velocity regime
C
Direction of change
R T P
D C
Rate of change
Low
Velocity homology
High product
Key: T technological velocity, R regulatory velocity, D demand velocity, C competitive velocity, and P velocity. The solid lines indicate tight coupling and the dashed lines loose coupling.
tive positions of which indicate their rates and directions of change for different dimensions. The first velocity regime in our typology oc- curs when environmental dimensions are highly homologous and loosely coupled to each other. We call this the "simple velocity regime" be- cause it has similar rates and directions of change across all dimensions. Thus, regardless of whether these dimensions are all changing slowly and continuously or rapidly and discon- tinuously, we argue that it is the relative unifor- mity of the change in strategic information that makes the environment relatively analyzable (Daft & Weick, 1984). Furthermore, because the velocities of the multiple dimensions are loosely coupled, they are free to vary independently so that changes in the velocity of one dimension are unlikely to affect the velocities of other dimensions.
An example of a simple velocity regime is the U.K. tableware industry from the mid 1950s to the late 1970s. During this period, this industry was exposed to changes in regulations, de- mand, product, technology, and competition that were all relatively slow and continuous in na- ture (Imrie, 1989; Rowley, 1992). At the same time, this industry had relatively loose coupling among velocity dimensions. For example, when change did occur in the velocity of the product dimension during the 1970s, due to an increase in the rate at which product variety and customi- zation changed, the only other velocity dimen- sion to be affected was technology, whereby changes in the flexibility of production machin- ery altered at a similar rate (Carroll, Cooke, Hassard, & Marchington, 2002; Day, Burnett, For- rester, & Hassard, 2000). This combination of high homology and loosely coupled dimension
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velocities created an environment that analysts and scholars described as being uniformly sta- ble, consistent, and regular in nature (Imrie, 1989). The second environmental velocity regime in our typology occurs when the velocities of dif- ferent dimensions are highly homologous and tightly coupled. This creates what we call an "integrated velocity regime." This regime is in- tegrated in two senses: the velocity attributes of each dimension (i.e., rates and directions of change) are very similar, and the velocities of the dimensions are highly interdependent on each other for a period of time. The tight cou- pling differentiates this regime from the simple regime, presenting managers with the complex task of monitoring and responding to causally connected changes in a velocity. This is what Aldrich (1979: 77) calls the "everything's related syndrome," where a change in the velocity of one dimension reverberates throughout the ve- locities of other dimensions. Together, these conditions create an environment that is best understood as having, at least for a time, a sin- gle overarching velocity. Moreover, if all the di- mensions are changing rapidly and discontinu- ously, this situation will be exemplified by the "high-velocity" industries that have dominated research on environmental velocity. Consequently, an example of an integrated velocity regime is the global computer industry from approximately 1982 to 1995. During this pe- riod, which is known as the third era of the industry, the microprocessor and personal com- puter were invented (Malerba, Nelson, Orsenigo, & Winter, 1999), and most of the environmental dimensions were changing rapidly and in a dis- continuous direction. Firms were frequently en- tering and exiting the industry, as well as form- ing and breaking alliances with each other (Bresnahan & Malerba, 1999; Langlois, 1990). Technological substitution in hardware and software was a frequent occurrence, resulting in regular product innovations (Bourgeois & Eisen- hardt, 1988; Brown & Eisenhardt, 1997). While Eisenhardt and colleagues clearly argued that such conditions equated to multiple velocities undergoing similar "rapid and discontinuous change," we suggest there was also a signifi- cant level of interdependence among the veloc- ities of these dimensions. For example, studies have explained how the velocity of competition affected the rate at which new technologies and
products were developed, which, in turn, af- fected the rate at which new market segments were created (Bresnahan & Malerba, 1999; Lan- glois, 1990). This coupling among dimensions also brought about the wholesale change in the velocities that occurred around 1995 as the in- dustry began its fourth era —the age of the net- work (Malerba et al., 1999). The third velocity regime, which we call the "divergent velocity regime," has a set of dissim- ilar and loosely coupled velocities, so firms face diverse and possibly contradictory environmen- tal conditions. This potentially makes the envi- ronment more difficult to analyze, because some dimensions change slowly and continuously —generating modest amounts of information — while other dimensions change rapidly and dis- continuously —producing large quantities of information that quickly becomes inaccurate or obsolete. This set of dissimilar velocities pre- sents diverse temporal demands on the informa- tion processing and sensemaking abilities of managers. The relatively loose coupling among these dissimilar velocities, however, somewhat lessens the challenge of monitoring and re- sponding to environmental conditions, because changes in the velocities of different dimensions are relatively independent, limiting the poten- tial for rapid, widespread change in the flows of strategic information. An example industry of this regime would be the U.S. flat glass manufacturing industry from 1955 to 1975. During this period, the environmen- tal dimensions for this industry had very differ- ent and unconnected velocities. The technology—float glass production methods — that was developed to produce flat glass was adopted relatively quickly during this period compared to other process technology innovations (Teece, 2000). It was also a discontinuous change that revolutionized how flat glass was made, with productivity gains approaching 300 percent as the need for grinding the glass was eliminated (Anderson & Tushman, 1990). This led to signifi- cant price/performance improvements so that float glass products replaced existing flat glass products in a relatively rapid and continuous fashion, rising from 30 million square feet per year of glass in 1960 to 1,730 million square feet per year of glass in 1973 (Bethke, 1973). Because this change in demand was generated by exist- ing producers for existing automotive and con- struction customers, the pace and direction of
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competitive change remained relatively slow and continuous in nature. The only significant regulatory event for this industry was that the U.S. Tariff Commission and Treasury more fre- quently cited foreign producers for dumping flat glass on the U.S. market at prices lower than those in their own markets (Bethke, 1973). This link between the rate of government action and the increase in production capacity from the new technology appears to be the only major interdependency between the different veloci- ties of the dimensions for this industry during this period. The final velocity regime we propose is com- posed of dimensions whose velocities are rela- tively dissimilar and tightly coupled. We call this the "conflicted velocity regime," since orga- nizations operating with such a regime will ex- perience diverse and potentially contradictory velocities that are also highly interdependent. As in the case of the divergent regime, the low level of homology among velocity dimensions in the conflicted velocity regime leads to condi- tions that are, as a whole, inconsistent and rel- atively unanalyzable. However, the tight cou- pling among these heterogeneous velocities increases the difficulty associated with track- ing, understanding, and responding to changes in the conditions of this regime, because the causal variation makes the environment rela- tively unstable over time. Although neglected in the velocity literature, we believe that this kind of velocity regime may be quite common. Our example of the fashion industry since the mid 1980s illustrates the dynamics associated with the conflicted velocity regime. We argued that the rates and direction of change in this industry span a diverse range. We further argued that this industry's environmental dimensions are relatively tightly coupled. Such conditions de- fine an environment with a set of dimensions that are not only changing dissimilarly but are also highly interdependent. ORGANIZATIONAL AND STRATEGIC IMPLICATIONS The importance of environmental velocity is due to the impacts it has on key organizational and strategic processes. Thus, in this section we examine how a multidimensional conceptual- ization of environmental velocity would affect our understanding of these impacts. We explore
the implications of velocity homology and veloc- ity coupling in terms of their general impacts on organizing and on the processes of strategic de- cision making and new product development. Implications of Velocity Homology We argue that the notion of velocity homology significantly affects how we need to think about the relationship between an organization and the temporal characteristics of its environ- ment. The dominant notion that has emerged over the past two decades in the velocity litera- ture, and more broadly in research on time and organizations, has been the importance of orga- nizations operating "in time" with their environ- ments and in synchrony across their subunits and activities. This is the view of research on organizational "entrainment" (Ancona & Chong, 1996; McGrath, Kelly, & Machatka, 1984; Perez- ´ Nordtvedt, Payne, Short, & Kedia, 2008), which argues that "functional groups not only must be [internally] entrained with each other for the organization to work, there must also be exter- nal entrainment, at both the subsystem and sys- tem levels, to ensure adaptation to the environ- ment" (Ancona & Chong, 1996: 19). The impact of external entrainment on performance is echoed in research on high-velocity industries, which argues that organizational performance in such environments is associated with rapid decision making (Eisenhardt, 1989) and fast new product development (Eisenhardt & Tabrizi, 1995; Schoonhoven, Eisenhardt, & Lyman, 1990). In their discussion of "timepacing," Eisenhardt andBrown (1998) provide examples of the importance of external entrainment, including the household goods manufacturer that timed its product launch cycles to key retailers' shelf planning cycles and, thus, was able to win more shelf space. Our multidimensional conceptualization of velocity suggests that temporal alignment be- tween an organization's operations and its en- vironment is critically important but that varia- tions in homology create significant limits to the synchronization of activities within firms (inter- nal entrainment). If the velocities associated with different environmental dimensions are similar, as in our high-homology regimes (sim- ple and integrated), then it is appropriate to entrain the pace and direction of all organiza- tional activities to this uniform environmental
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velocity. This will be a relatively simple situa- tion to manage. However, if the dimension ve- locities differ significantly, as in our low- homology regimes (conflicted and divergent), then the situation will be more difficult to man- age. This is because the task of entraining or- ganizational activities with dissimilar dimen- sion velocities will lead to heterogeneous sets of paces and directions of activities within firms. Such differences create challenges for firms, in- cluding potential incoherence among subunits and activities, fragmented internal information flows, and the breakdown of issue capture and analysis across intraorganizational boundaries. Furthermore, managers who understand that changes in velocity homology conditions can be both endogenous and exogenous in nature will have not only the option of reactively entraining their organizations to their environment but also the option of trying to alter the speed and direc- tion of change in specific environmental dimen- sions to suit their organization. Firms might, for example, lobby to influence the rate at and di- rection in which legislators develop laws and regulations (i.e., shape what is regulated/ deregulated in an industry and the pace at which regulatory reform occurs), or undertake marketing activities to influence changes in demand. A central theme of research on environmental velocity has been its effect on strategic decision making—those "infrequent decisions made by the top leaders of an organization that critically affect organizational health and survival" (Eisenhardt & Zbaracki, 1992: 17). Following our general argument regarding the impact of ve- locity homology, we argue that variations in ho- mology reward strategic decision-making activ- ities that are individually entrained with the velocity of their relevant environmental dimen- sion. Thus, more effective strategic decision making in high-homology regimes (simple and integrated) will involve a set of activities with similar paces and directions. Such internal consistency will provide benefits in terms of greater efficiency and lowered task conflict (Gherardi & Strati, 1988). In contrast, strategic decision mak- ing in lowhomology regimes (conflicted and di- vergent) will be more effective when the pace and direction of strategic decision-making ac- tivities are dissimilar, because they are tailored to their relevant but distinct dimension velocities.
A second key strategic process that illustrates the implications of velocity homology is new product development—the set of activities that transforms ideas, needs, and opportunities into new marketable products (Cooper, 1990). Previ- ous research has shown the value of rapid new product development in high-velocity industries (Eisenhardt & Tabrizi, 1995) but leaves open the question of how this might change if we incor- porated a multidimensional conception of envi- ronmental velocity. Although new product development processes may seem to be primarily linked to the product dimension of the organiza- tional environment, they cut across a wide range of organizational functions, including re- search, development, design, manufacturing, le- gal, marketing, and sales. Consequently, each of these different new product development ac- tivities collects, interprets, and applies relevant information from different dimensions of the or- ganization's environment. Thus, the contribution of each function to new product development is likely to be more effective when that function is entrained with the environmental dimension for which it is more directly responsible. The ability of marketing, for instance, to effectively contrib- ute to the development of new products depends on its being entrained with the velocity of de- mand. This means that different new product development functions may need to operate at different speeds and in different directions in order to ensure process-environment entrain- ment. Again, this can potentially create signifi- cant organizational challenges in terms of coor- dination and integration across the stages of the new product development process. Implications of Velocity Coupling We argue that the notion of velocity coupling significantly affects how we think about the sta- bility of velocity conditions and impacts how organizations coordinate changes in the pace and direction of their internal activities. Previ- ous research has tended to treat environmental velocity not only as a unidimensional concept but as a relatively stable feature of organiza- tional environments. In contrast, we argue that variations in velocity coupling will lead to im- portant differences in the stability of the velocity conditions of environments. For firms operating in tightly coupled environments, a change in the velocity of any one dimension (e.g., technology)
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will have a broad impact on the velocity condi- tions of the regime, through its effects on the velocities of the other dimensions to which it is coupled (e.g., products, demand, competition). This suggests that regimes with tight velocity coupling (integrated and conflicted) will have relatively unstable velocity conditions. This ar- gument follows research on coupling in both organizational environments and organizations that has shown that tight coupling among ele- ments of a system increases the instability of that system (Aldrich, 1979; Dess & Beard, 1984; Terreberry, 1968). An important facet of this instability is the rhythms through which it occurs. The impacts of changes in the velocity of one dimension on the velocities of other dimensions are unlikely to occur instantaneously but, rather, over time, as the social and technologi- cal mechanisms that connect the dimensions are sequentially triggered and exert their impact. We argue that the environmental instability and sequencing of changes associated with tight coupling provide an advantage to certain firms over others. In particular, tightly coupled regimes (integrated and conflicted) will reward firms that employ mechanisms that sensitize them to velocity changes and allow them to rap- idly and effectively shift the paces of their inter- nal operations. Typical mechanisms could include strategic scanning systems that managers use to monitor and respond to changes in their environments (Aguilar, 1967; Daft & Weick, 1984) and "interactive control systems" (Simons, 1994) to promote external reflection and internal com- munication and action. These mechanisms are analogous to other traditional organizational in- tegration (Lawrence & Lorsch, 1967) and bound- ary-spanning (Galbraith, 1973) mechanisms, but with a focus on coordinating change in the pace and direction of organizational activities to match temporal instability in the environment. Moreover, sequenced changes in velocities provide an advantage to firms that recognize these causal connections and are consequently able to anticipate sequences of velocity changes. For example, increases in human ge- netic engineering technology in the late 1990s led geneticists and government agencies to call for more regulation to control the development and application of this technology. Those firms that anticipated the connection between technological velocity and regulatory velocity proac-
tively planned and shifted the velocities of their research advocacy units to better link with the activities of patient advocacy groups. These changes helped the industry to garner the pub- lic support necessary to overturn regulations (Campbell, 2009). Achieving this sequenced change in the pace and direction of organizational activities would involve the use of time-based mechanisms. These include scheduling and project deadlines, information technologies that align organization- al activities, and resource allocation rules that specify the time to be spent on decision tasks (McGrath, 1991). As with velocity homology, changes in veloc- ity coupling may stem from external conditions, or it may be that managers are able to increase or decrease the causal connections among ve- locity dimensions in order to create strategic advantage for their firms. One strategy to affect velocity coupling is to alter the degree of mod- ularity in products (Baldwin & Clark, 1997; Sanchez & Mahoney, 1996), technologies (Yaya- varam & Ahuja, 2008), organizations (Meyer &Rowan, 1977; Weick, 1976, 1982), or interorganizational networks and supply chains (Afuah, 2001; Brusoni et al., 2001). Such changes can af- fect the overall coupling among environmental dimensions, particularly if they establish new competitive standards. Furthermore, such changes can be hard to attain and therefore difficult to imitate, thus creating a competitive advantage. Shimano, for example, became the dominant supplier of bicycle drive train compo- nents (shifters, chains, derailleurs, etc.) by developing high-performing, tightly coupled component systems that changed the nature of the new product development and production func- tions for their customers, as well as the nature of end-user demand. Shimano's strategy altered the pace and direction of multiple velocity di- mensions for the bicycle industry and has been credited with helping Shimano gain almost 90 percent of the drive train market for mountain bicycles (Fixson & Park, 2008). The effects of velocity coupling on how organizations coordinate their activities can also be illustrated by considering strategic decision making and new product development pro- cesses. For strategic decision making, coordina- tion is an issue of social cognition within top management teams (Forbes & Milliken, 1999), which we argue is significantly affected by the
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"temporal orientation" of a team. A temporal orientation is a cognitive concept that describes how individuals and teams conceive of time —as "monochronic," a unified phenomenon that mo- tivates attention to individual events in serial fashion, or as "polychronic," a heterogeneous phenomenon that necessitates simultaneous at- tention to multiple events (Ancona, Okhuysen, & Perlow, 2001; Bluedorn & Denhardt, 1988; Hall, 1959). We argue that strategic decision making in tightly coupled regimes would benefit from a polychronic orientation on the part of top man- agement teams so that team members share a view of time as malleable and unstructured. This would help them to simultaneously coordi- nate strategic decision-making velocities and to pay continuous partial attention to a broad set of issues (Stone, 2007). In contrast, in loosely coupled regimes the benefits of multitasking, monitoring, and simultaneously adjusting to the velocities of different dimensions are lower. Such situations, we argue, reward a mono- chronic temporal orientation that leads senior management teams to engage in strategic deci- sion making in a relatively independent manner, focusing on one issue at a time. For new product development processes, the impact of velocity coupling rests on the ability of firms to recognize and predict the conditions under which a new product will be launched. The instability associated with tightly coupled regimes (integrated and conflicted) influences the effectiveness of different process control frameworks that help ensure that the right type of product innovation is launched at the right time (McCarthy, Tsinopoulos, Allen, & Rose- Anderssen, 2006). "Linear" new product develop- ment frameworks conceive of the process as a series of relatively discrete, sequential stages, with team members at each stage making deci- sions (go forward, kill the project, put the project on hold, etc.) about the progress and outputs of the process (McCarthy et al., 2006). These frame- works include the waterfall model (Royce, 1970) and the stage-gate method (Cooper, 1990), which assume and impose structures or "scaffolds" that restrict the amount of iterative feedback. We argue that such linear frameworks are best suited to new product development processes that operate in loosely coupled velocity regimes in which the activities within the new product development process are relatively discrete,
with changes in their paces and directions hav- ing limited impacts on each other. In contrast, "recursive" new product develop- ment frameworks conceive of the process as a system of interconnected, overlapping activities that generate iterative and nonlinear behaviors over time (McCarthy et al., 2006). These include Kline and Rosenberg's (1986) chain-linked model and Eisenhardt and Tabrizi's (1995) experiential model, both of which, we argue, are suited to tightly coupled velocity regimes because they facilitate improvisation and flexibility. These capabilities help managers of the process to focus on and accommodate both the greater in- stability and more turbulent information flows associated with these velocity regimes. CONCLUSION In the paper's introduction we suggested that a multidimensional conceptualization of environmental velocity presented three important opportunities to advance research in the area. First, we argued that it would allow a more fine-grained examination of environmental ve- locity so as to better understand the diversity of this construct across different organizational contexts. In our discussions of several indus- tries, including fashion, tableware, computers, and flat glass, we have shown that characteriz- ing these environments simply as high or low velocity overlooks the fact that environmental velocity is composed of multiple dimensions, each with a distinct velocity. Second, we argued that a multidimensional approach to velocity could lead to more reliable and, thus, more valid empirical research by of- fering a basis for more consistent operation- alizations of velocity. Consequently, with our framework we have urged researchers to con- sider both the rate and direction of change for multiple pertinent dimensions of the organiza- tional environment. This reveals homology and coupling relationships among the velocity di- mensions, which describe the different velocity regimes we propose. These concepts provide a basis to better specify environmental velocity and use appropriate operationalizations to mea- sure its diversity. This, in turn, helps avoid in- appropriate aggregations and inconsistent uses of the velocity construct. Third, we suggested that a multidimensional conceptualization of environmental velocity and
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the conditions of our proposed velocity regimes could provide insights into organizational and strategic processes beyond what has been pos- sible with a unidimensional concept. To this end, we have explored some general implica- tions for organizations that follow from velocity homology and velocity coupling, along with more specific implications for two key pro- cesses: strategic decision making and new prod- uct development. We have explained how vari- ations in velocity homology influence the degree to which a firm's activities or subunits will be synchronized (internal entrainment) as they seek to operate in time with their respective dimensions of the environment (external en- trainment). We have also described how varia- tions in velocity coupling affect the need for organizations to recognize the stability of their velocity regime and anticipate sequences of changes in the velocities of their environmental dimensions. In summary, the challenges of high-velocity environments have captured the attention of managers and scholars. However, the multidimensional nature of the velocity construct and its effects have not been explored. Our work builds on contingency approaches to organiza- tion-environment relations and work on time and organizations. To these traditions it offers a more nuanced understanding of one aspect of change in organizational environments, and it urges researchers to examine both the complex- ity and diversity of the construct and its effects on organizations. REFERENCES
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Academy of Management Review Ian P. McCarthy ([email protected]) is the Canada Research Chair in Technology and Operations Management in the Faculty of Business Administration at Simon Fraser University. He received his Ph.D. in industrial engineering from the University of Sheffield. His research deals with organizational taxonomy, organizational design, operations management, and innovation management. Thomas B. Lawrence ([email protected]) is the Weyerhaeuser Professor of Change Management and director of the CMA Centre for Strategic Change and Performance Measurement at Simon Fraser University. He received his Ph.D. in organizational analysis from the University of Alberta. His research focuses on institutions and agency in organizations and organizational fields. Brian Wixted ([email protected]) is a research fellow at the Centre for Policy Research on Science and Technology at Simon Fraser University. He received his Ph.D. from the University of Western Sydney. His research interests include the international geography of sectoral innovation systems and the governance of pub- licly funded research systems. Brian R. Gordon ([email protected]) is a doctoral candidate in business administration at Simon Fraser University. His research interests include knowledge and knowledge creation processes in strategy, entrepreneurship, and innovation.
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doc_566932612.docx
Within the fields of strategic management and organizational theory, an organization’s environment is considered to be the notional space in which organizations exist. The environment consists of political, technological, economic and competitive dimensions that influence how organizations should function.
A Case Studies on Multidimensional Conceptualization of Environmental Velocity
Environmental velocity has emerged as an important concept but remains theoreti- cally underdeveloped, particularly with respect to its multidimensionality. In re- sponse, we develop a framework that examines the variations in velocity across multiple dimensions of the environment (homology) and the causal linkages between those velocities (coupling). We then propose four velocity regimes based on different patterns of homology and coupling and argue that the conditions of each regime have important implications for organizations.
Environmental velocity1 has become an im- portant concept for characterizing the conditions of organizational environments. Bourgeois and Eisenhardt (1988) introduced this concept to the management literature in their study of strate- gic decision making in the microcomputer in- dustry. They described this industry as a "high- velocity environment" — one characterized by "rapid and discontinuous change in demand, competitors, technology and/or regulation, such that information is often inaccurate, unavail- able, or obsolete" (Bourgeois & Eisenhardt, 1988: 816). From the perspective that the environment is a source of information that managers use to maintain or modify their organizations (Aldrich, 1979, Scott, 1981), velocity has important impli- cations for organizations. Studies have found, for example, that success in high-velocity indus- tries is related to fast, formal strategic decision- making processes (Eisenhardt, 1989; Judge & Miller, 1991); high levels of team and process
We are grateful to associate editor Mason Carpenter and three anonymous reviewers for their helpful and construc- tive comments. The development of this paper also benefited from comments from Joel Baum, Danny Breznitz, Sebastian Fixson, Mark Freel, Rick Iverson, Danny Miller, Dave Thomas, Andrew von Nordenflycht, Mark Wexler, Carsten Zimmermann, and seminar participants at Simon Fraser University and the 2008 INFORMS Organization Science Pa- per Development Workshop. We are also grateful to the Canadian Social Sciences and Humanities Research Coun- cil for funding that supported this research. 1 To increase the paper's readability, we use the terms environmental velocity and velocity interchangeably.
integration (Smith et al., 1994); rapid organiza- tional adaptation and fast product innovation (Eisenhardt & Tabrizi, 1995); and the use of heu- ristic reasoning processes (Oliver & Roos, 2005). More generally, research on velocity has shown that it affects how managers interpret their en- vironments (Nadkarni & Barr, 2008; Nadkarni &Narayanan, 2007a), further highlighting the ef- fects of environmental dynamism on key orga- nizational members (Dess & Beard, 1984). A common feature of the treatment of environmental velocity in the literature has been the use of singular categorical descriptors to char- acterize industries —most typically as "low," "moderate," or "high" velocity (e.g., Bourgeois &Eisenhardt, 1988; Eisenhardt, 1989; Eisenhardt & Tabrizi, 1995; Judge & Miller, 1991; Nadkarni &Narayanan, 2007a,b). Although Bourgeois and Eisenhardt (1988) defined environmental veloc- ity in terms of change (rate and direction) in multiple dimensions (demand, competitors, technology, and regulation), research on veloc- ity has tended to overlook its multidimensionality, instead assuming that a single velocity can be determined by aggregating the paces of change across all the dimensions of an organi- zation's environment. This assumption over- looks the fact that environmental velocity is a vector quantity jointly defined by two attributes (the rate and the direction of change) and that organizational environments are composed of multiple dimensions, each of which may be as- sociated with a distinct rate and direction of change.
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In this paper we aim to advance understand- ing of environmental velocity by developing a theoretical framework that articulates its multi- dimensionality and by exploring the implica- tions of this framework for understanding the organization-environment relationship. We ar- gue that while there may be cases in which organizational environments can be accurately specified by a single descriptor (e.g., high veloc- ity), a multidimensional conceptualization opens up a number of opportunities. First, it provides a basis for more fine-grained descrip- tions of the patterns of change that occur in organizational environments. An understanding of a firm's environmental velocity as composed of multiple, distinct rates and directions of change across multiple dimensions allows us to move beyond characterizations of industries as high or low velocity and the assumption that all dimensions change at similar rates and in sim- ilar directions (Bourgeois & Eisenhardt, 1988; Eisenhardt, 1989; Judge & Miller, 1991; Smith et al., 1994). Perhaps most important in this regard, a multidimensional conceptualization allows for an examination of the relationships among the dimensions of velocity, which we argue can have a profound impact on organizations. Second, a multidimensional conceptualiza- tion of velocity offers a foundation for more con- sistent operationalizations of the construct, which would help improve the reliability and validity of research that employs it. Our review of the environmental velocity literature indi- cates a reliance on singular descriptors of ve- locity, which has led to inconsistent operation- alizations of the construct. Thus, while it has sometimes been claimed that people can recognize a high-velocity environment when they see one (Judge & Miller, 1991), the different ways that the velocity of the same industry has been cat- egorized by different researchers would seem to indicate otherwise. Such inconsistencies may be due to focusing on one or two particularly sa- lient velocity dimensions or to combining data for multiple velocity dimensions without consid- ering the aggregation errors that can occur if the dimensions do not perfectly covary. Finally, by understanding that the environ- ments of organizations have multiple, distinct velocities, it is possible to identify different pat- terns of environmental velocity whose condi- tions affect organizations in ways that go be- yond the insights that have emerged from
studies characterizing velocity as simply high or low. Specifically, we explain how the multidi- mensionality of velocity can affect the degree to which an organization's activities will be en- trained and adjusted over time. We then high- light how these implications apply to two pro- cesses that have been central to prior research on velocity: strategic decision making and new product development. Our exclusive focus on environmental velocity differs from prior research that has sought to characterize organizational environments in terms of a set of core properties —most com- monly some variation of complexity, dynamism, and munificence (Aldrich, 1979; Dess & Beard, 1984; Scott, 1981). In pursuing this aim, we rec- ognize the trade-offs among generalizability, ac- curacy, and simplicity (Blalock, 1982) inherent in examining one aspect of the environment in depth while bracketing other important environ- mental dimensions. Research focused on the general organizational environment has strived for "high levels of simplicity and generalizability, with a corresponding sacrifice of accuracy" (Dess & Rasheed, 1991: 703). This approach has been characterized as "collapsing" the hetero- geneity of the environment into a more parsimo- nious set of properties (Keats & Hitt, 1988). In contrast, we focus on a single specific aspect of environmental dynamism— velocity—and ex- plore in detail its dimensions, how the velocities of these dimensions vary and interact, and the consequences of those differences and interac- tions. Our approach follows other studies that have examined specific environmental con- structs, such as uncertainty (Milliken, 1987) and munificence (Castrogiovanni, 1991). An impor- tant consequence of focusing on a single aspect of the environment is that any normative or pre- dictive claims we make must be made with ceteris paribus restrictions placed on them. This, of course, complicates the application of such claims in research or practice but also allows a deeper examination of specific phenomena (Pi- etroski & Rey, 1995). We present our arguments as follows. First, we review the concept of environmental velocity as it has been developed in management re- search, focusing on the opportunities that this work presents for developing a multidimen- sional conceptualization. Second, we present our framework by defining several fundamental dimensions of the organizational environment
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and defining the key aspects of velocity —the rate and direction of change —for each dimen- sion. Third, we examine the potential relation- ships among velocity dimensions (such as prod- ucts and technology) by introducing three concepts: (1) "velocity homology," which is the degree to which velocity dimensions have sim- ilar rates and directions of change at a point in time; (2) "velocity coupling," which is the degree to which the velocities of different dimensions affect one another over time; and (3) "velocity regimes," which represent patterns of velocity homology and velocity coupling. Fourth, we ex- plore the implications of our framework for or- ganization-environment relationships and for strategic decision making and new product development. ENVIRONMENTAL VELOCITY IN MANAGEMENT RESEARCH In physics, velocity refers to the rate of displacement or movement of a body in a particular direction. Thus, it is a vector quantity jointly defined by two distinct attributes: the rate of change and the direction of change. The defini- tion of high-velocity environments articulated by Bourgeois and Eisenhardt (1988) captured these two attributes, referring to rapid and dis- continuous change in multiple dimensions of the environment, such as demand, competitors, technology, and regulation. The notion of high velocity provided an evocative way to charac- terize the fast-moving, high-technology industry that was the context of their studies, and it com- plemented a number of similar but conceptually distinct environmental constructs, including dy- namism (Baum & Wally, 2003; Dess & Beard, 1984; Lawrence & Lorsch, 1967), turbulence (Em- ery & Trist, 1965; Terreberry, 1968), and hypertur- bulence (McCann & Selsky, 1984). More recently, environmental velocity has been used in con- junction with or as a synonym for other related environmental constructs, such as "clockspeed" (i.e., the speed of change in an industry; Fine, 1998; Nadkarni & Narayanan, 2007a,b) and hy- percompetition (Bogner & Barr, 2000; D'Aveni, 1994). Table 1 lists some of the major studies in stra- tegic management and organization theory in which the concept of environmental velocity plays a central role. For each study the table delineates the phenomenon of interest, the in-
dustry context, the level (high, moderate, or low) of velocity considered, and the measures em- ployed (if any). Looking across these studies, we identify three themes that characterize much of the existing research in the area and provide the motivation for the theoretical framework that we develop. First, existing studies have predominantly fo- cused on high-velocity environments, with lim- ited attention to other potential patterns of ve- locity. Consequently, we know relatively little, for instance, about the velocity-related chal- lenges faced by firms operating in low-velocity environments, where the slow pace of change may be associated with protracted development lead times, long decision horizons, and rela- tively infrequent feedback. Also, and more generally, the focus on high-velocity environments may be a significant factor in the treatment of velocity in terms of singular categorical descrip- tors; the term high-velocity environment itself seems to imply that multiple dimensions of the environment (e.g., products, markets, technol- ogy) combine nonproblematically to produce a single, cumulative, high level of velocity. While this may be true in some cases, it is not clear that it applies broadly across firms and industries. Second, high-velocity environments are often presented as synonymous with high-technology industries, perhaps because Bourgeois and Eisenhardt's initial study focused on the early microcomputer industry. Industries have been categorized as high velocity simply because they are technology intensive (Smith et al., 1994) or are built around an evolving scientific base (Eisenhardt & Tabrizi, 1995), regardless of whether other environmental dimensions ex- hibit low or modest rates of change or relatively continuous directions. Judge and Miller (1991), for instance, identified the biotechnology indus- try as high velocity, despite its relatively long product development lead times and product life cycles (both ten to twenty years). Finally, existing research tends to lack an ex- plicit measurement model or justification for the categorization of specific organizational con-texts or industries. Instead, researchers declare that they are studying high-velocity environ- ments and reiterate Bourgeois and Eisenhardt's (1988) original definition without significant ex- planation or direct evidence (the studies by Judge and Miller [1991] and Nadkarni and Barr
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TABLE 1 Environmental Velocity in Management Research
Example Studies Bourgeois & Eisenhardt (1988) Eisenhardt & Bourgeois (1988) Eisenhardt (1989) Judge & Miller (1991) Smith et al. (1994) Management/Organization Phenomena Pace and style of strategic decision making Politics of strategic decision making Rapid strategic decision making Antecedents and outcomes of decision speed The effect of team demography and team process Level of Velocity (Industry Context) High (microcomputer industry) High (microcomputer industry) High (microcomputer industry) High (biotechnology), medium (hospital), and low (textile) High (informational, electrical, biomedical, environmental) High (computer) High (computer) High (health care) High (IT) High (toys and IT tools) High and low (industries not specified) High (computer), medium (auto), and low (steel) High (computers, toys) and low (aircraft, steel) High (computers, toys) and low (aircraft, steel) High (semiconductor, cosmetic) and low (aircraft, petrochemical) High and low (conceptual simulation model) Conceptualization of Velocity Uniform change in the rate and direction of demand, competition, technology, and regulation As per Bourgeois & Eisenhardt (1988) As per Bourgeois & Eisenhardt (1988) Aggregation of industry growth and perceived pace of technological, regulatory, and competitive change Rate of change in product, demand, and competition Velocity Measures Used Illustrative statistics and examples Illustrative statistics and examples Illustrative statistics and examples Industry data and survey data from firms Illustrative statistics
Eisenhardt & Tabrizi (1995) Brown & Eisenhardt (1997) Stepanovich & Uhrig (1999) Bogner & Barr (2000) Oliver & Roos (2005) Brauer & Schmidt (2006) Davis & Shirato (2007) Nadkarni & Narayanan (2007a) Nadkarni & Narayanan (2007b) Nadkarni & Barr (2008)
Rapid organizational adaptation and fast product innovation Continuous organization change Strategic decision-making practices Cognitive and sensemaking abilities Team-based decision making Temporal development of a firm's strategy implementation A firm's propensity to launch World Trade Organization actions How cognitive construction by firms drives industry velocity Relationship between strategic schemas and strategic flexibility How velocity affects managerial cognition, which in turn affects the relationship between industry context and strategic action The performance and structural implications of velocity
As per Bourgeois & Eisenhardt (1988) As per Bourgeois & Eisenhardt (1988) Rate of change in demand, competition, technology, and regulations A form of hypercompetition Rate of change and the time available to make decisions A form of dynamism and volatility The number of product lines and the rate of product turnover Rate of change (clockspeed) for product, process, and organizational dimensions The rate of industry change (clockspeed) As per Bourgeois & Eisenhardt (1988)
Illustrative statistics and examples Illustrative statistics and examples An illustrative example None None Industry market returns data R&D expenditure/ total revenue Industry clockspeeds Industry clockspeeds A review of existing literature and matching using industry attributes A Poisson distribution of new opportunities
Davis, Eisenhardt, & Bingham (2009)
The speed or rate at which new opportunities emerge in the environment
[2008] representing notable exceptions). This variation in the extent to which velocity has been operationalized has resulted in some coun- terintuitive and inconsistent categorizations of industry velocity. Studies of health care, for in- stance, have labeled those environments as both high velocity (Stepanovich & Uhrig, 1999) and moderate velocity (Judge & Miller, 1991). Furthermore, our understanding of velocity and its effects across industry contexts has largely focused on only one attribute of velocity—the rate of change —since prior research has tended to use measures associated with the clockspeed of an industry (e.g., Nadkarni & Narayanan, 2007a; Oliver & Roos, 2005; Smith et al., 1994) or
has equated velocity with the speed at which new opportunities emerge (Davis, Eisenhardt, &Bingham, 2009). Looking across these themes, we see that re- search on environmental velocity has provided interesting and influential insights, particularly into the nature of organizational processes op- erating in fast-changing, high-technology in- dustries. We suggest, however, that the con- struct itself requires a more finegrained examination, since existing research tends to assume that it can be adequately represented by an aggregation of the rates of change across different environmental dimensions or by a fo- cus on change in only one dimension of the
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environment to the exclusion of others. In con- trast, we believe that a multidimensional conceptualization of velocity would provide a stronger foundation for clarifying and opera- tionalizing its characteristics and for better understanding its diversity and impacts on organizations. ENVIRONMENTAL VELOCITY AS A MULTIDIMENSIONAL CONCEPT The core understanding of environmental velocity that we propose is that organizational environments are composed of multiple dimen- sions, each of which is associated with its own rate and direction of change. This simple notion, we argue, has profound effects on how we un- derstand and research velocity and on the or- ganizational reactions to velocity we expect and prescribe. In this section we begin to construct our theoretical framework, first by defining the basic concepts of rate of change and direction of change as they apply to the organizational en- vironment in general, and then by describing how these basic concepts apply to some primary dimensions of the organizational environment. The Rate and Direction of Change Environmental velocity is a vector quantity defined by the rate and direction of change ex- hibited by one or more dimensions of the orga- nizational environment over a specified period. The rate of change is the amount of change in a dimension of the environment over a specified period of time, synonymous with such concepts as pace, speed, clock rate, or frequency of change. The direction of change, while often mentioned in studies citing Bourgeois and Eisenhardt's (1988) definition, has attracted relatively little attention beyond that. One possible reason for this is the relative difficulty of de- scribing the direction of environmental change. Whereas the velocity of a physical object can be described simply as moving eastward at 50 km/ hr, similarly straightforward descriptions of the direction of change of an organizational envi- ronment are not so obvious. This is particularly the case when we consider the direction of change across different industry dimensions, such as products, technology, and regulation, the direction of each of which could be de- scribed in numerous distinct ways.
In order to describe the direction of change in a way that allows comparison across industry dimensions, we follow Bourgeois and Eisen- hardt (1988), who suggest that the direction of change varies in terms of its degree of continu- ity-discontinuity. They argue that continuous change represents an extension of past devel- opment (e.g., continuously faster computer tech- nology), whereas discontinuous change represents a shift in direction (the move from film to digital photography, or the shifts that occur in fashion industries). Discontinuities, therefore, can be represented by inflection points in the trajectories that describe change in a dimension over time (e.g., technology price-performance curves or demand curves for specific products). To more fully articulate a continuum of continuous-discontinuous change, we draw on Wholey and Brittain's (1989) three-part concep- tualization of environmental variation, arguing that the direction of change is discontinuous to the extent that shifts in the trajectory of change are more recurrent, with greater amplitude and with greater unpredictability over a period of time. This approach helps us distinguish between relatively regular, predictable (e.g., sea- sonal) variations in environmental velocity and irregular types of change that are more difficult to predict and, consequently, more challenging in terms of organizational responses (Milliken, 1987). We suggest that such variations in the continuity-discontinuity of a velocity dimen- sion's trajectory allow for the use of structural equation modeling (Kline, 2004) and difference scores (Edwards, 1994) to produce growth models that measure transitions in change over time (Bliese, Chan, & Ployhart, 2007; Singer & Willett, 2003). Furthermore, to operationalize the rate and direction of change of each velocity dimension, we suggest that the measures will require scale uniformity to allow the relative differences be- tween the dimensions to be compared and cor- related (Downey, Hellriegel, & Slocum, 1975; Mil- liken, 1987). To achieve this, we suggest that the rate and direction of change will be some form of scalar measure (e.g., change/time). Therefore, even though what is changing will vary for each of the dimensions, their relative rates and direc- tions of change can be determined and com- pared by using the same period of time for the different dimensions (i.e., new products per year and changes in product direction per year).
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Dimensions of Environmental Velocity The second way in which we break down the concept of environmental velocity is in terms of the dimensions of the organizational environ- ment that are changing. While the dimensions of the environment that are salient for any par- ticular study will vary according to the specifics of the research project, there are several that have been widely used in prior research on or- ganizational environments. We use the four di- mensions suggested by Bourgeois and Eisen- hardt (1988)— demand, competitors, technology, and regulation —and to this list we add a fifth dimension—products. We do this because prior research on environmental velocity has tended to merge the technology and product dimen- sions, and we argue that they often have dissim- ilar rates and directions of change, which makes separating them important for our purposes. Archibugi and Pianta (1996) point to the impor- tance of this distinction when they argue that product changes need not be technical but can also include changes in the aesthetic, branding, or pricing features of a product. Our discussion of environmental dimensions is not meant to be exhaustive; rather, it is meant to highlight the heterogeneity of environmental dimensions that motivates our development of a multidimen- sional conceptualization of velocity. Technological velocity. Technological velocity is the rate and direction of change in the pro-
duction processes and component technologies that underlie a specific industrial context, such as float glass technology in glass manufactur- ing, genetic engineering in the biotechnology industry, and rolling mills in metals processing. See Table 2 for a summary of the definitions for each of the velocity dimensions on which we focus. The rate of technological change is the amount of change in those technologies over a specific time period, including the creation of new technologies, the refinement of existing technologies, and the recombination of compo- nent technologies. The rate of technological change varies dramatically across industries. Drawing on patents as an indicator of the rate of technological change, one can argue, for instance, that the electronics industry exhibits a more rapid rate of technological change than does the oil industry. In 2006, rankings for the number of patents granted in the United States showed that the top five positions were held by electronics companies, whereas the oil industry firms Shell and Exxon occupied positions 126 and 139, respectively (IFI, 2008). Although some technological change is either not patentable or not patented for strategic reasons, the rate of patenting can nevertheless provide a useful indication of the technological rate of change since it is a relatively direct and publicly avail- able indicator of the proprietary technological
TABLE 2 Environmental Velocity: Dimension Definitions and Example Measures
Definition/Example Measures Velocity dimension definition Technological Product Demand Regulatory Competitive
Example measures of the rate of change in the dimension Example measures of the direction of change in the dimension
The rate and direction The rate and direction The rate and direction The rate and direction The rate and direction of change in the of change in new of change in the of change in laws of change in the production product willingness and and regulations that structure of processes and introductions and ability of the market affect an industry competition within component product to pay for goods an industry technologies that enhancements and services underlie a specific industrial context The number of new The number of new The change in The number of new The change in patents and products introduced industry sales in a and amended laws industry population copyrights granted in a given period given period and/or regulations size and density in a given period (i.e., product introduced in a (i.e., number and clockspeed) given period size of firms) in a given period The changes in the The change in the The change in the The change in the The change in direction of the nature of product trend (e.g., growth nature and scope of industry growth relationship features as versus decline) and the control provided trends (e.g., growth between the price perceived by the nature (e.g., by new laws and versus decline) in a and technical market in a given personal versus regulations in a given period performance of period impersonal) of given period technology in a demand in a given given period period
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outputs of an industry (Archibugi & Pianta, 1996; Griliches, 1990). The direction of technological change refers to the trajectories along which technological advancements take place (Abernathy & Clark, 1985; Dosi, 1982; Tushman & Anderson, 1986). Distinguishing between continuous and discontin- uous directions of technological change is most easily understood in terms of performance/price curves. Continuous technological change in- volves a series of improvements that enhance the performance of the technology (e.g., ad- vances in photographic film technology focused on improving contrast quality, light sensitivity, and speed). Such changes move a technology smoothly along a performance/price curve, usu- ally at a decreasing rate, thus creating a concave downward performance/price curve. In contrast, discontinuous technological change involves "architectural" (Henderson & Clark, 1990) or "radical" innovations that "dramatically advance an industry's price vs. performance frontier" (Anderson & Tushman, 1990: 604). These innovations temporarily alter the shape of the performance/price curve such that it becomes concave upward until the immediate benefits of the innovation are exhausted. Product velocity. This dimension is the rate and direction of new product introductions and product enhancements. We define products as any combination of ideas, services, and goods offered to the market (Kotler, 1984). The rate of change in products can vary tremendously across industries and across market segments within an industry. In terms of the former, Fine (1998) and Nadkarni and Narayanan (2007a,b) show that the movie, toy, and athletic footwear industries have relatively high rates of product change (new products launched every three to six months), whereas the aircraft, petrochemi- cal, and paper industries have low rates of prod- uct change (new products launched every ten to twenty years). The direction of change for products can be described as continuous when new product introductions represent improvements on previ- ously important product attributes, and discon- tinuous when the new products introduce fundamentally new attributes for consumer choice. Adner and Levinthal's (2001) study of the personal computer industry between 1974 and 1998 provides an example of relatively continu- ous product change, with only two major inflec-
tion points with respect to price (in 1981 and 1988) and no major inflection points with respect to performance. In contrast, fashion products, such as clothing, music, and travel, all change frequently through the creation of new products and the transformation and repackaging of ex- isting ones. Such variations in product change across industries are associated with differ- ences in the complexity, risk, and impact of the product change. While velocity research has often lumped to- gether product and technological velocities, our definitions of their rates and directions of change illustrate the importance of distinguish- ing between them. Over the past several de- cades, for example, the underlying materials and production processes in the automobile industry have changed more rapidly and dis- continuously than have the end products themselves. In contrast, textile production technolo- gies have changed more slowly and continuously than the fashion products they are used to create. Demand velocity. Demand velocity is the rate and direction of change of the willingness and ability of the market to pay for goods or services, including changes in the number and types of transactions and market segments. The rate of change in demand varies tremendously across industries, with some experiencing rapid growth or decline and others facing steady growth for years. Such variance is influenced by a wide range of factors, including changes in taste, new rival products, substitutes, comple- ments, changes in relative prices, business cy- cle fluctuations, and switching costs. Empirical research has used summary industry sales fig- ures as an indicator of the rate of change in demand (e.g., Bourgeois & Eisenhardt, 1988). The direction of change for demand is contin- uous when there is a steady progression of in- creasing or decreasing sales to a consistent set of consumers. Conversely, change in the direc- tion of demand is discontinuous when there are frequent, significant, unpredictable shifts in the growth, decline, or steady state of demand, or a radical change in the segments that compose the overall market. For example, demand veloc- ity in the U.S. restaurant industry from 1970 to 1995 was relatively continuous, with sales gains made nearly every year during that period (Harrington, 2001). In contrast, the demand for commodities, such as copper and gold, can be
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highly volatile owing to a wide range of macroeconomic influences, exemplifying the case of a discontinuous demand velocity. Similarly, the Nintendo Corporation created discontinuous change in the demographics of demand since its Wii games console appealed to nontraditional market segments, such as families, women, and older people. Regulatory velocity. We define regulatory velocity as the rate and direction of change in the regulations and/or laws that directly affect the firm or industry under consideration. This in- cludes government action (e.g., changes in laws, regulations, and polices) and industry self- regulation (e.g., voluntary standards and codes). It is a dimension that can open or close markets, present organizations with compliance costs, and necessitate strategic shifts in practices. The rate of regulatory change is a function of the creation of new laws or regulations, or changes to existing laws or regulations, in a time period. It can vary greatly across industrial, national, and historical contexts, and it often depends on other factors, such as technology (e.g., regula- tions for stem cell research), business scandals (e.g., the Enron scandal), health and safety is- sues (e.g., mad cow disease), and demographic shifts (e.g., an increase in the retired population). The direction of change in regulation is continuous to the degree that new regulations re- semble the old in scope, form, or substantive areas of concern, and it is discontinuous to the degree that they address new issues, focus on different kinds of behaviors, or employ new prin- ciples. For example, the U.S. airline industry from 1938 to 1975 experienced changes in regu- lations that were relatively continuous, in that the Civil Aeronautics Board (CAB) restricted prices, flight frequency, and flight capacity (Vietor, 1990). Then, in 1975, the direction of reg- ulatory change changed as the CAB began ex- perimenting with limited deregulation, and in 1978 the industry was completely deregulated and the CAB abolished. Competitive velocity. Competitive velocity is the rate and direction of change in the structural determinants of industry profitability (Barney, 1986; Porter, 1980). Its rate of change is, in part, a function of the entrance and exit of industry rivals (Hannan & Carroll, 1992), as well as the speed with which firms respond to competitors' strategic moves or other shifts in the environ-
ment (Bowman & Gatignon, 1995). Such mea- sures describe the overall pace at which the competitive conditions that define an industry are changing—a factor that has been shown to influence firm performance across a wide range of industries, including the automotive (Hannan, Carroll, Dundon, & Torres, 1995), computer (Hen- derson, 1999), and insurance (Ranger-Moore, 1997) industries. The direction of change in competitive struc- ture involves continuity-discontinuity with re- spect to the value chain in an industry (Jaco- bides & Winter, 2005), the nature of rivals (Porter, 1980; Schumpeter, 1950), or changes in market contestability (Hatten & Hatten, 1987). Change incompetitive structure is continuous to the de- gree that these characteristics remain constant and stable over time. Conversely, the change in direction in competitive structure is discontinu- ous to the degree that industry value chains are in flux (Jacobides, 2005) and existing bases of competition are challenged by firms introducing new products, pioneering new markets or sources of supply, or implementing new means of production (Schumpeter, 1950). RELATIONSHIPS AMONG VELOCITY DIMENSIONS: VELOCITY HOMOLOGY, VELOCITY COUPLING, AND VELOCITY REGIMES An important benefit of a multidimensional conceptualization of environmental velocity is the potential it provides to examine the differ- ences and relationships among the velocities of different dimensions. To that end, we introduce three concepts: (1) velocity homology—the rela- tive similarity among the rates and directions of change of different dimensions; (2) velocity cou- pling—the degree to which the velocities of dif- ferent dimensions are causally connected; and (3) velocity regimes —the different patterns of environmental velocity that emerge from varia- tions in velocity homology and velocity coupling. Velocity Homology The term homology was coined by the paleontologist Richard Owen (1843) to explain the morphological similarities among organisms. It has been used by management scholars to describe the degree to which two phenomena are similar
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(Chen, Bliese, & Mathieu, 2005; Glick, 1985; Han- lon, 2004) and is consistent with the homogene- ityheterogeneity aspect of environmental com- plexity (Aldrich, 1979; Dess & Beard, 1984). In our framework, velocity homology is the degree to which the rates and directions of change of dif- ferent dimensions are similar to each other over a period of time. Thus, "high homology" de- scribes a condition in which the velocities of different dimensions in a given environment ex- hibit relatively similar rates and directions of change, whereas "low homology" describes rel- atively dissimilar rates and directions of change. To help explain velocity homology, we present a map of the velocities of different dimensions, with the rate of change and the direction of change on each axis (see Figure 1). With this image of velocity (based on the fashion apparel industry example we present in the following sections), homology is represented by the close- ness of the points. Thus, low homology (as is the case in Figure 1) is represented by relatively spread out points, and high homology would be represented by relatively tightly clustered points. To operationalize this concept of homol- ogy, we suggest using distance measures and methods, such as cluster analysis (Ketchen &
Shook, 1996), factor analysis (Segars & Grover, 1993), and multidimensional scaling (Cox & Cox, 2001), all of which are considered suitable for assessing interdimension similarity in construct composition (Harrison & Klein, 2007; Law, Wong, & Mobley, 1998). An assumption of a highly homologous set of velocities typified much of the early work on highvelocity environments, in which industries such as microcomputers were characterized by "rapid and discontinuous change" across multi- ple dimensions (Bourgeois & Eisenhardt, 1988: 816). An assumption of high homology carried over to subsequent studies, with limited consid- eration of the degree to which homology might vary across firms and industries. Most studies seem to have aggregated the velocities of differ- ent dimensions, regardless of the variance among these dimensions, thereby assuming similarity (i.e., high homology in our terms) among the velocities of different environmental dimensions. Consequently, we know relatively little about the conditions and effects of low- homology environments, where the velocity properties of a firm's multiple environmental di- mensions are highly dissimilar. To illustrate and clarify the concept of homol- ogy, we present the example of the apparel in-
FIGURE 1 Fashion Apparel Industry Example
Discontinuous Demand
Direction of change
Competitive
Product
Regulatory Continuous Low
Technological
Rate of change
High
Key: The solid lines indicate tight coupling and the dashed lines loose coupling.
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dustry and focus on the industry segment in- volved in the design and supply of seasonal fashion apparel. This includes brands sold pri- marily through ownbrand stores (e.g., Gap, Zara, and American Apparel) and brands sold through a mixture of own-brand stores and in- dependent stores (e.g., Armani, Benetton, and Levi's). We chose this industry because aca- demic studies and business reports suggest that from 1985 through 2005 the velocities of different dimensions in this industry spanned a diverse range of rates and directions of change (Djelic & Ainamo, 1999; The Economist, 2005; Jacobides &Billinger, 2006; Taplin & Winterton, 1995). Beginning with the product dimension, this segment of fashion retailing is associated with a relatively high rate of change and a moder- ately discontinuous direction. This is illustrated by the operations of Zara, one of Europe's lead- ing fashion brands. Zara launches some 11,000 new products annually, most of which are com- pletely new products as perceived by the cus- tomer and typically take only five weeks from design to retail store ( The Economist, 2005). Even casual fashion houses, such as Sweden's Hennes & Mauritz (H&M) and the American chain Gap, roll out between 2,000 and 4,000 prod- ucts each year. Moreover, the rate of change in products has increased, with the emergence of "fast fashion" as a dominant strategy for mass market designers/retailers (Doeringer & Crean, 2006). We argue that the direction of product change is moderately discontinuous, because although these firms launch many new prod- ucts, they represent a mix of new items and extensions of existing products. This view is consistent with studies of the rate and direction of change in women's formal wear (Lowe &Lowe, 1990). The technologies that underpin the fashion industry have been changing rapidly over the past twenty years (cf. Richardson, 1996) but at a relatively slower rate than changes in fashion products. Although manufacturing technology in the apparel industry has remained stable for nearly a century (Audet & Safadi, 2004), there have been advances in the manufacture of tex- tiles, as well as in communication and information technologies, that have facilitated the move to quick response (Forza & Vinelli, 1997) and fast fashion (Doeringer & Crean, 2006) strategies in fashion design and retailing. The direction of these changes has been relatively continuous
over the past twenty or so years —toward greater automation and efficiency in textile manufac- turing, more rapid response to customer de- mands, and more efficient communication and coordination in fashion design and retailing (Doeringer & Crean, 2006; The Economist, 2005). In contrast to product and technological veloc- ities, regulatory change in this industry has, for the past two decades, occurred relatively slowly and continuously. The regulation that affects this industry most significantly is directed at the manufacture of clothing and the protection of consumer rights, both of which have changed slowly over that period. With respect to the man- ufacture of garments, the Multi Fibre Arrange- ment (MFA) was introduced in 1974 as a short- term measure to govern world trade in textiles and garments, imposing quotas on the amount developing countries could export to developed countries (Spinanger, 1999). This regulation underwent only minor modifications until it ex- pired in 2005 (Audet & Safadi, 2004). National- level regulation tends to focus on labor and employment standards. In response to the shift of clothing manufacturing from developed to emerging economies, the governments of West- ern nations have been reluctant to further regu- late (and potentially stifle) clothing manufactur- ing, much of which occurs as home-based work (Ng, 2007). Change in demand for fashion apparel has, for the past twenty years, occurred moderately slowly, with a high degree of discontinuity. Re- searchers argue that the fashion industry is characterized by low to moderate levels of pos- itive sales growth each year (Nueno & Quelch, 1998), with occasional major demographic and lifestyle shifts and changes in customer prefer- ences (Danneels, 2003; Siggelkow, 2001). Al- though the direction of change in demand for fashion has oscillated between relative stability and discontinuity over the last 150 years (Djelic & Ainamo, 1999), the past 20-year period has been associated with customers becoming more demanding, arbitrary, and heterogeneous (Djelic & Ainamo, 1999; The Economist, 2005). The competitive velocity of the fashion indus- try has long fascinated observers. In recent years it has altered as increased cost pressures have led firms to engage in rapid-fire attempts to source the lowest-cost materials and to move labor-intensive aspects of the value chain to countries with lower costs. The industry has also
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experienced constant shifts in the major centers of production (Dosi, Freeman, & Fabiani, 1994). By way of example, U.S. employment levels in this sector in 2002 were a third of what they were in the early 1980s (Doeringer & Crean, 2006). The intersection of cost pressures and the increasing rate of change in consumer preference and de- mand has led to significant shifts in firms' strat- egies, particularly speeding up the supply chain (Richardson, 1996) and altering organizational structures and boundaries (Djelic & Ainamo 1999; Jacobides & Billinger, 2006; Siggelkow, 2001). Such conditions characterize change that is both moderately rapid and continuous in nature. The fashion industry points to two important issues with respect to understanding homology among environmental velocity dimensions. First, it highlights that the organizational envi- ronment is composed of a number of distinct dimensions, each of which is defined by its own rate and direction of change — or velocity. Sec- ond, we see that there are significant differ- ences in the rates and directions of change (low homology) across the five dimensions that we have considered. This makes the idea of describing the industry as having a single veloc- ity, whether based on an "average" across di- mensions or on the velocity of whichever dimension might be considered most important, misleading both to researchers attempting to understand the industry and to managers need- ing to make strategic decisions.
Velocity Coupling A second important aspect of the relationship between velocity dimensions is the degree to which and the ways in which they interact over time. We examine these interactions through the concept of coupling. This is the degree to which elements of a system, including product compo- nents (Baldwin & Clark, 1997; Sanchez & Ma- honey, 1996), individuals (DiTomaso, 2001), or- ganizational subunits (Meyer & Rowan, 1977; Weick, 1976, 1982), and organizations (Afuah, 2001; Brusoni, Prencipe, & Pavitt, 2001), are caus- ally linked to each other (Orton & Weick, 1990; Weick, 1976). In our framework velocity coupling is the degree to which the velocities of different dimensions in an organizational environment are causally connected —the degree to which a
change in the velocity of one dimension causes a change in the velocity of another. Weick (1976) defined loosely coupled systems as those in which the properties of constitutive elements are relatively independent, whereas the properties of elements in tightly coupled sys- tems are strongly mutually dependent. Weick (1982) further argued that loose coupling in- volves causal effects that are relatively periodic, occasional, and negligible, whereas tight cou- pling involves relatively continuous, constant, and significant causal effects. Thus, we de- scribe the velocities of different dimensions of a firm's environment as loosely coupled when changes in the velocity of one dimension (e.g., technology velocity) have relatively little imme- diate, direct impact on the velocities of other dimensions (e.g., product velocity), and we de- scribe them as tightly coupled when the rela- tionship between the velocities of different di- mensions involve significant immediate, direct causal effects. To determine the degree of cou- pling between velocity dimensions, we suggest using structural equation modeling (Kline, 2004), which is recommended for operationalizing covariance between construct variables (Law et al., 1998). Although coupling and homology both de- scribe the relationships among velocity dimen- sions, they are separate, distinguishable as- pects of those relationships. The velocities of different dimensions can have high levels of interdependence (coupling), regardless of whether they exhibit similar rates and direc- tions of change (homology). Homology is a first- order property of velocity, describing the similarity among velocities over a period of time. In contrast, coupling is a second-order property, describing the degree to which changes in the velocity of a dimension affect the velocity of another dimension over the same specified pe- riod of time. The distinction between homology and coupling is observable in the biotechnology industry, which experiences high rates and dis- continuous directions of technological change but relatively slow, continuous regulatory and product velocities (Zollo, Reuer, & Singh, 2002). While these dimensions have very different ve- locities (low homology), there is evidence to sug- gest that they are relatively tightly coupled. This is illustrated by the impacts of the 2001 U.S. regulation on stem cell research, which restricted research to twenty-one stem cell lines (a
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family of constantly dividing cells) and, in turn, limited the rate and direction of U.S. stem cell research activity (i.e., technological velocity) rel- ative to other countries. In 2009 this regulation was overturned, permitting research on up to 1,000 new stem cell lines, allowing "U.S. human embryonic stemcell research to thrive at last" (Hayden, 2009: 130). We again draw on the fashion apparel indus- try to illustrate the idea of coupling among ve- locity dimensions. Beginning with products, changes in the velocity of this dimension have been attributed to increases in the adoption of new communications, design, and manufactur- ing technologies, suggesting a relatively tight coupling between product and technological ve- locity dimensions. Perhaps most significant, changes in the direction of technology have im- proved the ability of fashion apparel firms to gather market feedback and, thus, to develop new product offerings at a faster rate (Jacobides& Billinger, 2006; Kraut, Steinfield, Chan, Butler, & Hoag, 1999; Richardson, 1996). Similarly, the velocity of demand has been tightly coupled to product velocity over the past two decades: in- dustry observers argue that the perceived new arbitrariness of customer demand has forced fashion organizations to frequently engage in large-scale market explorations (Cammet, 2006; Jacobides & Billinger, 2006). In contrast, there is little evidence of a strong relationship between product velocity and competitive velocity. Prod- uct velocity appears to be primarily driven by changes in market demand and the product in- novation programs of existing organizations exploiting those changes, as opposed to a flow of new entrants (Cammet, 2006). In terms of the velocity of regulation in this industry, there is evidence that it is tightly cou- pled to the velocities of competition, demand, and products, with changes in international trade regulations (Spinanger, 1999) and domes- tic labor standards (Ng, 2007) leading to increas- ing imports from developing economies, both creating and satisfying the demand for cheaper fashion products. Similarly, the velocities of competition and demand appear to be tightly coupled, with firms in this industry attempting to predict and adapt to what Siggelkow (2001) calls "fitdestroying changes" that can signifi- cantly alter their competitive positions. There is also tight coupling between the velocity of tech- nology and the velocity of demand. For example,
in their study of the U.S. fashion apparel indus- try in the 1980s, Abernathy, Dunlop, Hammond, and Weil (1999) explain how changes in demand led to "lean retailing," which, in turn, required firms to drastically alter their information and production technologies to enable new working practices. In contrast, there is little evidence to suggest that changes in the velocity of technol- ogy for the fashion industry will affect or are affected by changes in the velocities of competition or regulation. In this illustrative example (see Figure 1), we argue that seven of ten possible dyadic connec- tions among velocity dimensions are relatively tightly coupled (designated by solid lines) such that changes in the velocity of one dimension will affect the velocity of another. We have ar- gued that the three other connections are loosely coupled, as indicated by the dotted lines. Thus, although not all of the velocity dimensions of the fashion industry exhibit strong causal connections to each other, we suggest that this industry can be described as a rela- tively tightly coupled environment. Any assign- ment of such a category is somewhat arbitrary without a formal measurement of coupling, so for now we follow work on modular (loosely cou- pled) and integrated (tightly coupled) organiza- tional forms that suggests that when at least 50 percent of the system elements are tightly cou- pled to each other, the system can be considered tightly coupled (Schilling & Steensma, 2001).
Velocity Regimes We propose the concept of a velocity regime as a way to describe the pattern of velocity homology and velocity coupling within an organizational environment. Although both these characteristics of velocity vary continuously, we focus on combinations of high or low homology and tight or loose coupling to more clearly illus- trate how they vary and the effects of these variations. The result is a typology (see Figure 2) with four distinct velocity regimes that repre- sent ideal types, rather than an exhaustive tax- onomy of velocity conditions. To illustrate and visualize the degrees of homology and coupling that characterize each regime, we have embed- ded a variation of Figure 1 into each cell of Figure 2. Like Figure 1, these embedded figures present illustrative sets of velocities, the rela-
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FIGURE 2 Environmental Velocity Regimes
Con?icted velocity regime R Tight Direction of change C Direction of change D
Integrated velocity regime
R
D C
T P
T Rate of change
P Rate of change
Velocity coupling
Divergent velocity regime R Direction of change Loose T Rate of change P D
Simple velocity regime
C
Direction of change
R T P
D C
Rate of change
Low
Velocity homology
High product
Key: T technological velocity, R regulatory velocity, D demand velocity, C competitive velocity, and P velocity. The solid lines indicate tight coupling and the dashed lines loose coupling.
tive positions of which indicate their rates and directions of change for different dimensions. The first velocity regime in our typology oc- curs when environmental dimensions are highly homologous and loosely coupled to each other. We call this the "simple velocity regime" be- cause it has similar rates and directions of change across all dimensions. Thus, regardless of whether these dimensions are all changing slowly and continuously or rapidly and discon- tinuously, we argue that it is the relative unifor- mity of the change in strategic information that makes the environment relatively analyzable (Daft & Weick, 1984). Furthermore, because the velocities of the multiple dimensions are loosely coupled, they are free to vary independently so that changes in the velocity of one dimension are unlikely to affect the velocities of other dimensions.
An example of a simple velocity regime is the U.K. tableware industry from the mid 1950s to the late 1970s. During this period, this industry was exposed to changes in regulations, de- mand, product, technology, and competition that were all relatively slow and continuous in na- ture (Imrie, 1989; Rowley, 1992). At the same time, this industry had relatively loose coupling among velocity dimensions. For example, when change did occur in the velocity of the product dimension during the 1970s, due to an increase in the rate at which product variety and customi- zation changed, the only other velocity dimen- sion to be affected was technology, whereby changes in the flexibility of production machin- ery altered at a similar rate (Carroll, Cooke, Hassard, & Marchington, 2002; Day, Burnett, For- rester, & Hassard, 2000). This combination of high homology and loosely coupled dimension
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velocities created an environment that analysts and scholars described as being uniformly sta- ble, consistent, and regular in nature (Imrie, 1989). The second environmental velocity regime in our typology occurs when the velocities of dif- ferent dimensions are highly homologous and tightly coupled. This creates what we call an "integrated velocity regime." This regime is in- tegrated in two senses: the velocity attributes of each dimension (i.e., rates and directions of change) are very similar, and the velocities of the dimensions are highly interdependent on each other for a period of time. The tight cou- pling differentiates this regime from the simple regime, presenting managers with the complex task of monitoring and responding to causally connected changes in a velocity. This is what Aldrich (1979: 77) calls the "everything's related syndrome," where a change in the velocity of one dimension reverberates throughout the ve- locities of other dimensions. Together, these conditions create an environment that is best understood as having, at least for a time, a sin- gle overarching velocity. Moreover, if all the di- mensions are changing rapidly and discontinu- ously, this situation will be exemplified by the "high-velocity" industries that have dominated research on environmental velocity. Consequently, an example of an integrated velocity regime is the global computer industry from approximately 1982 to 1995. During this pe- riod, which is known as the third era of the industry, the microprocessor and personal com- puter were invented (Malerba, Nelson, Orsenigo, & Winter, 1999), and most of the environmental dimensions were changing rapidly and in a dis- continuous direction. Firms were frequently en- tering and exiting the industry, as well as form- ing and breaking alliances with each other (Bresnahan & Malerba, 1999; Langlois, 1990). Technological substitution in hardware and software was a frequent occurrence, resulting in regular product innovations (Bourgeois & Eisen- hardt, 1988; Brown & Eisenhardt, 1997). While Eisenhardt and colleagues clearly argued that such conditions equated to multiple velocities undergoing similar "rapid and discontinuous change," we suggest there was also a signifi- cant level of interdependence among the veloc- ities of these dimensions. For example, studies have explained how the velocity of competition affected the rate at which new technologies and
products were developed, which, in turn, af- fected the rate at which new market segments were created (Bresnahan & Malerba, 1999; Lan- glois, 1990). This coupling among dimensions also brought about the wholesale change in the velocities that occurred around 1995 as the in- dustry began its fourth era —the age of the net- work (Malerba et al., 1999). The third velocity regime, which we call the "divergent velocity regime," has a set of dissim- ilar and loosely coupled velocities, so firms face diverse and possibly contradictory environmen- tal conditions. This potentially makes the envi- ronment more difficult to analyze, because some dimensions change slowly and continuously —generating modest amounts of information — while other dimensions change rapidly and dis- continuously —producing large quantities of information that quickly becomes inaccurate or obsolete. This set of dissimilar velocities pre- sents diverse temporal demands on the informa- tion processing and sensemaking abilities of managers. The relatively loose coupling among these dissimilar velocities, however, somewhat lessens the challenge of monitoring and re- sponding to environmental conditions, because changes in the velocities of different dimensions are relatively independent, limiting the poten- tial for rapid, widespread change in the flows of strategic information. An example industry of this regime would be the U.S. flat glass manufacturing industry from 1955 to 1975. During this period, the environmen- tal dimensions for this industry had very differ- ent and unconnected velocities. The technology—float glass production methods — that was developed to produce flat glass was adopted relatively quickly during this period compared to other process technology innovations (Teece, 2000). It was also a discontinuous change that revolutionized how flat glass was made, with productivity gains approaching 300 percent as the need for grinding the glass was eliminated (Anderson & Tushman, 1990). This led to signifi- cant price/performance improvements so that float glass products replaced existing flat glass products in a relatively rapid and continuous fashion, rising from 30 million square feet per year of glass in 1960 to 1,730 million square feet per year of glass in 1973 (Bethke, 1973). Because this change in demand was generated by exist- ing producers for existing automotive and con- struction customers, the pace and direction of
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competitive change remained relatively slow and continuous in nature. The only significant regulatory event for this industry was that the U.S. Tariff Commission and Treasury more fre- quently cited foreign producers for dumping flat glass on the U.S. market at prices lower than those in their own markets (Bethke, 1973). This link between the rate of government action and the increase in production capacity from the new technology appears to be the only major interdependency between the different veloci- ties of the dimensions for this industry during this period. The final velocity regime we propose is com- posed of dimensions whose velocities are rela- tively dissimilar and tightly coupled. We call this the "conflicted velocity regime," since orga- nizations operating with such a regime will ex- perience diverse and potentially contradictory velocities that are also highly interdependent. As in the case of the divergent regime, the low level of homology among velocity dimensions in the conflicted velocity regime leads to condi- tions that are, as a whole, inconsistent and rel- atively unanalyzable. However, the tight cou- pling among these heterogeneous velocities increases the difficulty associated with track- ing, understanding, and responding to changes in the conditions of this regime, because the causal variation makes the environment rela- tively unstable over time. Although neglected in the velocity literature, we believe that this kind of velocity regime may be quite common. Our example of the fashion industry since the mid 1980s illustrates the dynamics associated with the conflicted velocity regime. We argued that the rates and direction of change in this industry span a diverse range. We further argued that this industry's environmental dimensions are relatively tightly coupled. Such conditions de- fine an environment with a set of dimensions that are not only changing dissimilarly but are also highly interdependent. ORGANIZATIONAL AND STRATEGIC IMPLICATIONS The importance of environmental velocity is due to the impacts it has on key organizational and strategic processes. Thus, in this section we examine how a multidimensional conceptual- ization of environmental velocity would affect our understanding of these impacts. We explore
the implications of velocity homology and veloc- ity coupling in terms of their general impacts on organizing and on the processes of strategic de- cision making and new product development. Implications of Velocity Homology We argue that the notion of velocity homology significantly affects how we need to think about the relationship between an organization and the temporal characteristics of its environ- ment. The dominant notion that has emerged over the past two decades in the velocity litera- ture, and more broadly in research on time and organizations, has been the importance of orga- nizations operating "in time" with their environ- ments and in synchrony across their subunits and activities. This is the view of research on organizational "entrainment" (Ancona & Chong, 1996; McGrath, Kelly, & Machatka, 1984; Perez- ´ Nordtvedt, Payne, Short, & Kedia, 2008), which argues that "functional groups not only must be [internally] entrained with each other for the organization to work, there must also be exter- nal entrainment, at both the subsystem and sys- tem levels, to ensure adaptation to the environ- ment" (Ancona & Chong, 1996: 19). The impact of external entrainment on performance is echoed in research on high-velocity industries, which argues that organizational performance in such environments is associated with rapid decision making (Eisenhardt, 1989) and fast new product development (Eisenhardt & Tabrizi, 1995; Schoonhoven, Eisenhardt, & Lyman, 1990). In their discussion of "timepacing," Eisenhardt andBrown (1998) provide examples of the importance of external entrainment, including the household goods manufacturer that timed its product launch cycles to key retailers' shelf planning cycles and, thus, was able to win more shelf space. Our multidimensional conceptualization of velocity suggests that temporal alignment be- tween an organization's operations and its en- vironment is critically important but that varia- tions in homology create significant limits to the synchronization of activities within firms (inter- nal entrainment). If the velocities associated with different environmental dimensions are similar, as in our high-homology regimes (sim- ple and integrated), then it is appropriate to entrain the pace and direction of all organiza- tional activities to this uniform environmental
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velocity. This will be a relatively simple situa- tion to manage. However, if the dimension ve- locities differ significantly, as in our low- homology regimes (conflicted and divergent), then the situation will be more difficult to man- age. This is because the task of entraining or- ganizational activities with dissimilar dimen- sion velocities will lead to heterogeneous sets of paces and directions of activities within firms. Such differences create challenges for firms, in- cluding potential incoherence among subunits and activities, fragmented internal information flows, and the breakdown of issue capture and analysis across intraorganizational boundaries. Furthermore, managers who understand that changes in velocity homology conditions can be both endogenous and exogenous in nature will have not only the option of reactively entraining their organizations to their environment but also the option of trying to alter the speed and direc- tion of change in specific environmental dimen- sions to suit their organization. Firms might, for example, lobby to influence the rate at and di- rection in which legislators develop laws and regulations (i.e., shape what is regulated/ deregulated in an industry and the pace at which regulatory reform occurs), or undertake marketing activities to influence changes in demand. A central theme of research on environmental velocity has been its effect on strategic decision making—those "infrequent decisions made by the top leaders of an organization that critically affect organizational health and survival" (Eisenhardt & Zbaracki, 1992: 17). Following our general argument regarding the impact of ve- locity homology, we argue that variations in ho- mology reward strategic decision-making activ- ities that are individually entrained with the velocity of their relevant environmental dimen- sion. Thus, more effective strategic decision making in high-homology regimes (simple and integrated) will involve a set of activities with similar paces and directions. Such internal consistency will provide benefits in terms of greater efficiency and lowered task conflict (Gherardi & Strati, 1988). In contrast, strategic decision mak- ing in lowhomology regimes (conflicted and di- vergent) will be more effective when the pace and direction of strategic decision-making ac- tivities are dissimilar, because they are tailored to their relevant but distinct dimension velocities.
A second key strategic process that illustrates the implications of velocity homology is new product development—the set of activities that transforms ideas, needs, and opportunities into new marketable products (Cooper, 1990). Previ- ous research has shown the value of rapid new product development in high-velocity industries (Eisenhardt & Tabrizi, 1995) but leaves open the question of how this might change if we incor- porated a multidimensional conception of envi- ronmental velocity. Although new product development processes may seem to be primarily linked to the product dimension of the organiza- tional environment, they cut across a wide range of organizational functions, including re- search, development, design, manufacturing, le- gal, marketing, and sales. Consequently, each of these different new product development ac- tivities collects, interprets, and applies relevant information from different dimensions of the or- ganization's environment. Thus, the contribution of each function to new product development is likely to be more effective when that function is entrained with the environmental dimension for which it is more directly responsible. The ability of marketing, for instance, to effectively contrib- ute to the development of new products depends on its being entrained with the velocity of de- mand. This means that different new product development functions may need to operate at different speeds and in different directions in order to ensure process-environment entrain- ment. Again, this can potentially create signifi- cant organizational challenges in terms of coor- dination and integration across the stages of the new product development process. Implications of Velocity Coupling We argue that the notion of velocity coupling significantly affects how we think about the sta- bility of velocity conditions and impacts how organizations coordinate changes in the pace and direction of their internal activities. Previ- ous research has tended to treat environmental velocity not only as a unidimensional concept but as a relatively stable feature of organiza- tional environments. In contrast, we argue that variations in velocity coupling will lead to im- portant differences in the stability of the velocity conditions of environments. For firms operating in tightly coupled environments, a change in the velocity of any one dimension (e.g., technology)
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will have a broad impact on the velocity condi- tions of the regime, through its effects on the velocities of the other dimensions to which it is coupled (e.g., products, demand, competition). This suggests that regimes with tight velocity coupling (integrated and conflicted) will have relatively unstable velocity conditions. This ar- gument follows research on coupling in both organizational environments and organizations that has shown that tight coupling among ele- ments of a system increases the instability of that system (Aldrich, 1979; Dess & Beard, 1984; Terreberry, 1968). An important facet of this instability is the rhythms through which it occurs. The impacts of changes in the velocity of one dimension on the velocities of other dimensions are unlikely to occur instantaneously but, rather, over time, as the social and technologi- cal mechanisms that connect the dimensions are sequentially triggered and exert their impact. We argue that the environmental instability and sequencing of changes associated with tight coupling provide an advantage to certain firms over others. In particular, tightly coupled regimes (integrated and conflicted) will reward firms that employ mechanisms that sensitize them to velocity changes and allow them to rap- idly and effectively shift the paces of their inter- nal operations. Typical mechanisms could include strategic scanning systems that managers use to monitor and respond to changes in their environments (Aguilar, 1967; Daft & Weick, 1984) and "interactive control systems" (Simons, 1994) to promote external reflection and internal com- munication and action. These mechanisms are analogous to other traditional organizational in- tegration (Lawrence & Lorsch, 1967) and bound- ary-spanning (Galbraith, 1973) mechanisms, but with a focus on coordinating change in the pace and direction of organizational activities to match temporal instability in the environment. Moreover, sequenced changes in velocities provide an advantage to firms that recognize these causal connections and are consequently able to anticipate sequences of velocity changes. For example, increases in human ge- netic engineering technology in the late 1990s led geneticists and government agencies to call for more regulation to control the development and application of this technology. Those firms that anticipated the connection between technological velocity and regulatory velocity proac-
tively planned and shifted the velocities of their research advocacy units to better link with the activities of patient advocacy groups. These changes helped the industry to garner the pub- lic support necessary to overturn regulations (Campbell, 2009). Achieving this sequenced change in the pace and direction of organizational activities would involve the use of time-based mechanisms. These include scheduling and project deadlines, information technologies that align organization- al activities, and resource allocation rules that specify the time to be spent on decision tasks (McGrath, 1991). As with velocity homology, changes in veloc- ity coupling may stem from external conditions, or it may be that managers are able to increase or decrease the causal connections among ve- locity dimensions in order to create strategic advantage for their firms. One strategy to affect velocity coupling is to alter the degree of mod- ularity in products (Baldwin & Clark, 1997; Sanchez & Mahoney, 1996), technologies (Yaya- varam & Ahuja, 2008), organizations (Meyer &Rowan, 1977; Weick, 1976, 1982), or interorganizational networks and supply chains (Afuah, 2001; Brusoni et al., 2001). Such changes can af- fect the overall coupling among environmental dimensions, particularly if they establish new competitive standards. Furthermore, such changes can be hard to attain and therefore difficult to imitate, thus creating a competitive advantage. Shimano, for example, became the dominant supplier of bicycle drive train compo- nents (shifters, chains, derailleurs, etc.) by developing high-performing, tightly coupled component systems that changed the nature of the new product development and production func- tions for their customers, as well as the nature of end-user demand. Shimano's strategy altered the pace and direction of multiple velocity di- mensions for the bicycle industry and has been credited with helping Shimano gain almost 90 percent of the drive train market for mountain bicycles (Fixson & Park, 2008). The effects of velocity coupling on how organizations coordinate their activities can also be illustrated by considering strategic decision making and new product development pro- cesses. For strategic decision making, coordina- tion is an issue of social cognition within top management teams (Forbes & Milliken, 1999), which we argue is significantly affected by the
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"temporal orientation" of a team. A temporal orientation is a cognitive concept that describes how individuals and teams conceive of time —as "monochronic," a unified phenomenon that mo- tivates attention to individual events in serial fashion, or as "polychronic," a heterogeneous phenomenon that necessitates simultaneous at- tention to multiple events (Ancona, Okhuysen, & Perlow, 2001; Bluedorn & Denhardt, 1988; Hall, 1959). We argue that strategic decision making in tightly coupled regimes would benefit from a polychronic orientation on the part of top man- agement teams so that team members share a view of time as malleable and unstructured. This would help them to simultaneously coordi- nate strategic decision-making velocities and to pay continuous partial attention to a broad set of issues (Stone, 2007). In contrast, in loosely coupled regimes the benefits of multitasking, monitoring, and simultaneously adjusting to the velocities of different dimensions are lower. Such situations, we argue, reward a mono- chronic temporal orientation that leads senior management teams to engage in strategic deci- sion making in a relatively independent manner, focusing on one issue at a time. For new product development processes, the impact of velocity coupling rests on the ability of firms to recognize and predict the conditions under which a new product will be launched. The instability associated with tightly coupled regimes (integrated and conflicted) influences the effectiveness of different process control frameworks that help ensure that the right type of product innovation is launched at the right time (McCarthy, Tsinopoulos, Allen, & Rose- Anderssen, 2006). "Linear" new product develop- ment frameworks conceive of the process as a series of relatively discrete, sequential stages, with team members at each stage making deci- sions (go forward, kill the project, put the project on hold, etc.) about the progress and outputs of the process (McCarthy et al., 2006). These frame- works include the waterfall model (Royce, 1970) and the stage-gate method (Cooper, 1990), which assume and impose structures or "scaffolds" that restrict the amount of iterative feedback. We argue that such linear frameworks are best suited to new product development processes that operate in loosely coupled velocity regimes in which the activities within the new product development process are relatively discrete,
with changes in their paces and directions hav- ing limited impacts on each other. In contrast, "recursive" new product develop- ment frameworks conceive of the process as a system of interconnected, overlapping activities that generate iterative and nonlinear behaviors over time (McCarthy et al., 2006). These include Kline and Rosenberg's (1986) chain-linked model and Eisenhardt and Tabrizi's (1995) experiential model, both of which, we argue, are suited to tightly coupled velocity regimes because they facilitate improvisation and flexibility. These capabilities help managers of the process to focus on and accommodate both the greater in- stability and more turbulent information flows associated with these velocity regimes. CONCLUSION In the paper's introduction we suggested that a multidimensional conceptualization of environmental velocity presented three important opportunities to advance research in the area. First, we argued that it would allow a more fine-grained examination of environmental ve- locity so as to better understand the diversity of this construct across different organizational contexts. In our discussions of several indus- tries, including fashion, tableware, computers, and flat glass, we have shown that characteriz- ing these environments simply as high or low velocity overlooks the fact that environmental velocity is composed of multiple dimensions, each with a distinct velocity. Second, we argued that a multidimensional approach to velocity could lead to more reliable and, thus, more valid empirical research by of- fering a basis for more consistent operation- alizations of velocity. Consequently, with our framework we have urged researchers to con- sider both the rate and direction of change for multiple pertinent dimensions of the organiza- tional environment. This reveals homology and coupling relationships among the velocity di- mensions, which describe the different velocity regimes we propose. These concepts provide a basis to better specify environmental velocity and use appropriate operationalizations to mea- sure its diversity. This, in turn, helps avoid in- appropriate aggregations and inconsistent uses of the velocity construct. Third, we suggested that a multidimensional conceptualization of environmental velocity and
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the conditions of our proposed velocity regimes could provide insights into organizational and strategic processes beyond what has been pos- sible with a unidimensional concept. To this end, we have explored some general implica- tions for organizations that follow from velocity homology and velocity coupling, along with more specific implications for two key pro- cesses: strategic decision making and new prod- uct development. We have explained how vari- ations in velocity homology influence the degree to which a firm's activities or subunits will be synchronized (internal entrainment) as they seek to operate in time with their respective dimensions of the environment (external en- trainment). We have also described how varia- tions in velocity coupling affect the need for organizations to recognize the stability of their velocity regime and anticipate sequences of changes in the velocities of their environmental dimensions. In summary, the challenges of high-velocity environments have captured the attention of managers and scholars. However, the multidimensional nature of the velocity construct and its effects have not been explored. Our work builds on contingency approaches to organiza- tion-environment relations and work on time and organizations. To these traditions it offers a more nuanced understanding of one aspect of change in organizational environments, and it urges researchers to examine both the complex- ity and diversity of the construct and its effects on organizations. REFERENCES
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Academy of Management Review Ian P. McCarthy ([email protected]) is the Canada Research Chair in Technology and Operations Management in the Faculty of Business Administration at Simon Fraser University. He received his Ph.D. in industrial engineering from the University of Sheffield. His research deals with organizational taxonomy, organizational design, operations management, and innovation management. Thomas B. Lawrence ([email protected]) is the Weyerhaeuser Professor of Change Management and director of the CMA Centre for Strategic Change and Performance Measurement at Simon Fraser University. He received his Ph.D. in organizational analysis from the University of Alberta. His research focuses on institutions and agency in organizations and organizational fields. Brian Wixted ([email protected]) is a research fellow at the Centre for Policy Research on Science and Technology at Simon Fraser University. He received his Ph.D. from the University of Western Sydney. His research interests include the international geography of sectoral innovation systems and the governance of pub- licly funded research systems. Brian R. Gordon ([email protected]) is a doctoral candidate in business administration at Simon Fraser University. His research interests include knowledge and knowledge creation processes in strategy, entrepreneurship, and innovation.
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