Introduction

In this chapter we extend replication theory (Winter & Szulanski, 2001) by theoretically and empirically examining the extent, determinants, and performance consequences of variation in firms that utilize a strategy of replication, specifically variation in fundamental routines which we shall refer to both as variation and adaptation hereafter. Adaptation, in this, sense does not necessarily infer intentionality. Although it may contain significant elements of intention, we use the term to refer to change of any kind to firm routines, whether the change arises from intention, “drift” (Knott, 2001), or is directly induced by the environment. This usage reflects the idea that routines are operated by humans and that the majority of change requires human action, whether passive or active, resulting in human caused modification to the original routine. In addition, the term has widespread usage and its use here is intended to connect the discussion on variation to the broader literature.

While the previous two chapters addressed aspects of the process of replication this chapter addresses the effects of replication when it is repeatedly employed. In this chapter we explore variation in replicator systems since variation is an essential part of firm innovation and change. Moreover, there is some controversy as to whether or not replicator firms will exhibit sufficient degrees of internal variation to allow for firm innovation, and hence, firm survival in changing environments. If they do not,

replication strategy is likely to be o f little use to any firm except those in stable environments or those wishing to only succeed for a short time. The potential for

extensive internal variation belies conventional wisdom in the management field and may provide a basis for understanding change and innovation in such firms despite an

intensive firm level focus on the exploitation o f existing knowledge assets and the inertia associated with such a focus.

Typically, replication has been conceived o f as a simple process entailing the repeated application of a clever business model across geographic space resulting in an extreme form of exploitation commonly referred to as “cookie-cutter” strategy. Indeed, while some have argued that while the initial creation of a suitable business model for replication involves a period of innovation and exploration (Winter & Szulanski, 2001), once that period is complete the repeated exploitation of an existing business model is argued to result in difficulties commonly associated with exploitation (Winter & Szulanski, 2001) including competency traps (Lee et al., 2003; Levinthal & March, 1993), organizational inertia (Crossan & Berdrow, 2003; March, 1991), and the inability to adapt to changing conditions (Miller, 1993). Organizational inertia due to replication is further compounded by a strong firm incentive to reduce unit level variation in order to maintain control over branding and capture efficiencies from operating a system of similar units such as economies of scale in purchasing, training and monitoring, and the ability to more easily introduce incremental change.

Inertia, either by choice because of firm incentives or as a result of the basic strategy, however, would suggest that most firms employing replication as a strategy should expand rapidly and then stagnate and decay in existing markets with new firms gaining market share at a brisk pace. Indeed, the inhibited variation inherent in extensive exploitation suggests that, following the fundamental theorem of natural selection

(Fisher, 1929), firms with greater ability to change, and hence greater variation, are likely to have competitive superiority, something belied by the growth of this type of firm. Even a short survey of replicator firms and industries where replication strategy dominates suggests, however, that while some firms grow quickly and then fail to change with the environment (which occurs with firms employing other strategies as well) many

replicator firms appear to be vibrant over a long period of time. In many representative industries there is relatively little chum among leading firms. Such anecdotal evidence suggests the need to more closely study the “exploitation” phase of replication strategy.

If firms employing a replication strategy continue to survive and even thrive in turbulent environments they must possess a mechanism for change. Two possibilities exist. First, the center may possess both the dynamic capabilities necessary to leam and alter the fundamental business model as well as capabilities for transferring that model both to existing and new units. Second, a replicator firm, as a system of similar units, may exhibit variance in fundamental routines leading either to change through unit level selection or unit level learning and the diffusion of practices. Both possibilities may exist simultaneously. The existence of either type of mechanism for change extends

replication strategy from the process o f replication itself to the ongoing management o f a changing network requiring both the management of variation both during the initial replication process and later as well as the repeated replication of newly developed practices.

Of course, while conventional wisdom in the management literature consigns replicator firms to a category o f low variation because of extensive replication there are dissenting voices. For instance, in the economics literature one of the primary

motivations for franchising is argued to be increased local adaptation, and assumed profit maximization, due to local agents being owners as well as managers (Jensen & Meckling,

1976; Minkler, 1992; Rubin, 1978). In addition, previous work in organization theory, while not replicator specific, argues that local units, especially in international contexts, will adapt in order to fit local institutional and market environments (Hannon et al., 1995; Kostova & Roth, 2002), creating variation within the firm. Indeed, there is a

longstanding debate over the benefits and extent o f standardized practices vs. practices tailored to be locally responsive (Bartlett & Ghoshal, 1989; Prahalad & Doz, 1987) with some arguing that change originates from practices which vary at the periphery of the organization rather than from dynamic capabilities at the center (Andersson & Forsgren,

2000).

In practice one is not likely to find either the extreme of conventional wisdom, with little to no variation, or the extreme where all units are adapted completely to their varied environments. Indeed, one may find a differential pattern of inertia and change

depending on the level of analysis, center vs. units. Clearly some unit level adaptation is likely to occur as units attempt to maximize their local potential. However, the center has an incentive to maintain a tightly controlled standardized business model in order to 1) maintain branding, 2) provide efficiencies both in economies of scale in purchasing and marketing, and 3) reduce learning and monitoring costs (Blair & Lafontaine, 2005; Bradach, 1998), an incentive which is complicated both by the difficulty o f enforcing strict adherence to a standardized business model (Knott, 2001), the cost of enforcing adherence (Blair & Lafontaine, 2005), and the degree to which local maximization attempts create system-wide diminishing returns, i.e.; at lower levels of adaptation variation may result in a net positive for the system a whole. Such questions suggest the need to examine more closely the issue of variation in replicator organizations.

Perhaps due to the difficulty of obtaining quality intra-firm data in significant quantity, even within the literature suggesting that intra-firm variation is likely there is little empirical evidence describing the extent, effects, and causes of variation within replicator firms. This chapter seeks to fill that gap by asking three fundamental questions 1) how much variation is there within replicator firms, 2) why should replicator firms

care about the level of variation, and 3) if variation matters, where does it come from? If variation has performance consequences, an answer to the third question may potentially provide actionable levers for managing that variation.

To adequately address the questions we use a unique intra-firm dataset involving 11 years of monthly performance and product mix data for a census of all U.S. units

(approximately 3,500) within a single replicator firm supplemented with extensive firm archival data for a sample of units. This data allows us to track changes in total variation for a series of dependent variables measuring changes both in performance and the fundamental routines comprising the replicated business model. Specifically, we track variation at the center and partition total variation into two component levels, within-unit and between-unit variation. In addition, using the archival data, we partition each level into its potential antecedents, providing a more nuanced discussion of the nature of the variation and suggesting a series of strategic implications for replicator firms. Answering all three questions has the potential to expand the debate within the management

literature concerning replicator organizations, providing an empirical foundation for future research on the nature of change within such firms.

The first task, then, is to assess the extent of variation. The first section of the chapter shows empirically that replicator firms, despite their focus on exploiting existing knowledge, can exhibit a high degree of unit level variation along a number of

dimensions including performance, the alteration of the existing business model, and the creation of new routines. The second task is to explore the effects of the observed variation using methods for analyzing panel data. Finally, the third task, using hierarchical linear modeling, is to explore the determinants of the variation, including their relative effects. Finally, we conclude by discussing the potential implications of the analyses for the competitive advantage of replicator firms.

4.2. The Extent of Variation in Replicator Firms