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QWERTY is dead; long live path dependence
Research Policy 42 (2013) 1191–1194
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Discussion
QWERTY is dead; long live path dependence Jean-Philippe Vergne ∗ Ivey Business School, Western University, Canada
a r t i c l e
i n f o
Article history: Received 17 October 2012 Accepted 13 February 2013 Available online 17 April 2013
1. R.I.P QWERTY In many respects, Kay (2013) delivers a final blow to the persistent belief that the QWERTY case provides empirical evidence of path dependence. Liebowitz and Margolis threw the first punch more than twenty years ago when they argued, quite convincingly, that the commonly accepted narrative “of the market’s rejection of Dvorak [did] not report the true history” and that, in fact, “the continued use of Qwerty [was] efficient given the current understanding of keyboard design” (Liebowitz and Margolis, 1990: p. 2). Nearly twenty years later, in an attempt to replicate the QWERTY case in a controlled lab experiment, Hossain and Morgan (2009) found that “the market always manages to solve the QWERTY problem. In 60 iterations of dynamic platform competition, our subjects never got stuck on the inferior platform” (Hossain and Morgan, 2009: p. 435). And they concluded: “While the QWERTY effect is certainly an interesting theoretical possibility, the dearth of examples of the phenomenon, both in the field and now in the lab, leads us to conclude that the danger lies more in the minds of theorists than in the reality of the marketplace” (Hossain and Morgan, 2009: p. 440). Kay (2013) is thus consistent with both Liebowitz and Margolis (1990) and Hossain and Morgan (2009) when he argues that, “if you could rerun the tape of history here as many times as you like, choosing when to introduce Dvorak, QWERTY would always win.” So what is the QWERTY story really about? To find out, Kay (2013) explores both the internal and external selection environments (Vergne and Durand, 2011) faced by Christopher L. Sholes, QWERTY’s original inventor. According to Kay’s account, Sholes was an entrepreneur with industry experience in printing and media, who secured both financial and marketing support to launch a
∗ Corresponding author at: Ivey Business School, Western University, 1151 Richmond Street North, London, Ontario N6A 3K7, Canada. E-mail address: [email protected] 0048-7333/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.respol.2013.03.009
new, carefully designed technology. He was savvy enough to make the revolutionary machine look familiar to potential (female) typists by presenting it on a sewing machine stand (Kay, 2013: p. 7). He designed the best technology of his time by making infrequent pairs of letters contiguous on the typebasket to minimize jamming (i.e., one could type Mark Twain’s Life on the Mississippi entirely with QWERTY and only 146 co-occurrences of contiguous letters would be problematic, against 2358 with a Dvorak keyboard). Finally, Sholes enhanced his keyboard’s market appeal by ensuring that salespersons could impress prospective clients by typing the word “typewriter” in a split second, and to that end he positioned the letters T, Y, P, E, W, R, and I on the same row. In other words, Kay (2013) tells us a story about how, in a nascent industry, the most strategically savvy entrepreneur, who also happens to be selling the best product, ends up winning the market competition. Kay’s paper thus raises the following question: as scholars, do we need a theory called path dependence, based on the mathematical properties of non-ergodic Markov chains (David, 2001), to shed light on the QWERTY case? And Kay’s paper also suggests a clear answer: as per Occam’s razor, no, path dependence is not required to explain QWERTY’s dominance.
2. Some misinterpretations around David’s seminal paper David opened his 1985 paper on “QWERTY-nomics” with a caveat: “standing alone, my story will be simply illustrative and does not establish how much of the world works this way. That is an open empirical issue and I would be presumptuous to claim to have settled it, or to instruct you in what to do about it” (David, 1985: p. 332). And he concluded his paper with questions, not answers. He found the QWERTY story “intriguing” and expressed the belief that there may be more QWERTY worlds lying out there, “worlds we do not yet fully perceive or understand,” then ended with a call for “exploring” those worlds (David, 1985: p. 336). Did David ever present the QWERTY case as undisputable empirical evidence of path dependence? To the best of my knowledge, no, he did not.
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David’s only confusing statement about the QWERTY case was that “competition in the absence of perfect futures markets drove the industry prematurely into standardization on the wrong system” (David, 1985: p. 336). Since then, both Liebowitz and Margolis (1990) and Kay (2013) have explained why the terms “prematurely” and “wrong system” were, in this context, perhaps not the most appropriate. But David’s misplaced words should not lead us to throw out the baby with the bathwater, expelling from our academic vocabulary every reference to path dependence. The biggest challenge with path dependence is not the theory itself but its empirical validation. That is, path dependence does not imply suboptimality but it can lead to it (David, 2001).1 Thus, the reason Kay’s findings imply that QWERTY cannot be explained by path dependence is not so much the fact that QWERTY is optimal – because nothing prevents path dependence from leading to the optimal equilibrium – but rather the paper’s conclusion that rerunning the tape of history would always lead to the same outcome. Why? Because path dependence refers to the contingent selection of a stable equilibrium in a sequential stochastic process. It follows, then, that path-dependent sequences, should they be rerun multiple times, do not always converge around the same equilibrium. Put formally, in path-dependent processes, for any set of initial conditions I and any outcome O, the probability that the outcome of the process is O, conditional on I, is strictly inferior to 1. Vergne and Durand (2010) call this property a core theorem of path dependence: ∀ (O, I), P(O | I) < 1. The fact that rerunning the tape of history would never change the outcome of the keyboard standardization process violates this theorem, which brings us to the true reason why, according to Kay’s paper, QWERTY is not the outcome of a path-dependent process.2 Because suboptimality is not readily explained by conventional economics, many scholars believed that a research design based on the ex post identification of supposedly suboptimal outcomes would be well suited to provide empirical evidence of path dependence. Such a research design would distinguish more easily between neoclassical equilibrium and lock-in (as induced by path dependence). While this research strategy has some face value, it has turned out to be a dead end. Despite an accumulation of historical case studies of so-called path-dependent trajectories over the past two decades, a significant portion of the scholarly community still does not “buy” the path dependence story. Sure, we could blame the sceptics. But I’d rather blame the method. More precisely, the problem is not the case study method itself but its incompatibility with the unique epistemological underpinnings of path dependence theory (Vergne and Durand, 2010). Following David’s template (David, 1985), case studies of alleged path-dependent systems typically proceed from the observation of a stable pattern (e.g., a technology or an institution that has been around for a while) to the conclusion that lock-in occurred (as evidenced by the observed stability). Then, with the benefit of hindsight, case study-based papers typically claim that the stability is accounted for by self-reinforcing mechanisms. The logic of the argument often looks like this: when something remains stable
1 From this viewpoint, Hossain and Morgan (2009) do not test path dependence per se, but the prediction that path dependence can lead to a suboptimal outcome owing to random shocks. In their study, they rerun the tape of history 60 times but lock-in always happens on the same (optimal) equilibrium. 2 Importantly, path dependence is not about hypersensitivity to initial conditions, a concept that comes from chaos theory and relates to deterministic (as opposed to stochastic) systems. Liebowitz and Margolis (1995) introduced confusion in the literature by conflating path dependence and chaos theory (and yet this does not affect in any way the validity of their critique of the QWERTY case). David (2001), in what is probably one of the clearest expositions of his views on path dependence, noted the misunderstanding and put an end to it by clarifying the distinction between deterministic chaos and path dependence in stochastic processes.
over time, we tend to get used to it, which then creates cognitive sunk costs and self-reinforcing learning loops. Quite problematically, however, most case studies of path dependence don’t even try to measure (i.e., quantify) such self-reinforcing mechanisms, but merely list them based on ad hoc assumptions about historical events as reconstructed by researchers from partial archival records. From this viewpoint, to argue that “small events” happened early on to select a path is not too difficult, since contingency is a pervasive feature of daily life. If the archival records show at some point that stability ceases, one can still argue that “path breaking” occurred due to some exogenous shock identified ex post. Seen from this perspective and using case study methodology, basically anything can be argued to be path-dependent (or if not, it’s because path-breaking occurred). Clearly, this line of case study-based reasoning has many issues. First, to prove that “small events” actually happened by chance is virtually impossible in case study research, so alternative explanations cannot be ruled out – for instance, the “small event” could be a mere symptom of an unobserved structural force that is the true cause behind lock-in (Vergne and Durand, 2010). Second, in complex social systems, multiple positive feedback loops are always at work, but so are negative feedback loops (Page, 2006). Without quantifying the loops, it is impossible to assess the extent to which the negative loops compensate for the positive ones. Third, while path dependence leads to lock-in in the long run, we, as researchers, cannot afford to define what we mean by “the long run” ex post, when lock-in, quite conveniently, has already occurred. Consider that, in 1995, we were all locked in using VHS. Ten years later, we all used DVDs. Now, imagine a counterfactual world where we were locked in using Betamax in 1995 instead of VHS and, because “one damn thing follows another” (David, 1985: p. 332), Sony began throwing tons of cash on R&D to develop SuperDVD, a 3D holographic image format that would make DVD look prehistoric. The story today would be quite different as a consequence, and, in “the long run,” Betamax would have been the optimal equilibrium. And here’s the twist: because path dependence is about stochastic systems, there is no way that, using path dependence theory, anyone could disprove that SuperDVD wouldn’t have existed had Betamax cornered the market in the 1990s. It follows that claims about suboptimality do not make sense from the viewpoint of path dependence theory itself (see Vergne and Durand, 2010, for a formal proof). In most case study research, path dependence theory is simply unfalsifiable. In fact, David himself (1985: 336) explained that QWERTY-like case studies were bound to be “simply illustrative.” True, case study research is very useful in generating new theory around phenomena that are not yet well understood – but in the case of path dependence, the very existence of the phenomenon is at stake, so before extending the theory using case studies, we’d be better off providing a robust research design that can, at last, establish path dependence as an empirical reality in the social sciences. David (1985) has opened an exciting avenue for research, but the path-dependence research community (myself included) is to be blamed for not having yet designed better methods to follow up on his seminal insight. Put simply, while I believe that path dependence is out there, I also believe that, so far, we just haven’t done a great job at observing it.
3. Long live controlled research designs! To understand the role of contingent “small events,” we need to be able to manipulate the initial conditions of sequential processes in research designs. To assess the influence of self-reinforcing mechanisms, we need to be able to measure them. To demonstrate that lock-in does not always occur on the same outcome, we need some form of cross-sectional research design where a
J.-P. Vergne / Research Policy 42 (2013) 1191–1194
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Table 1 Contrasting five methods in the context of path dependence research. Laboratory experiment
Counterfactual modelling
Computer simulation
Pooled TSCS regression
Single/multiple case study (qualitative)
Direct observation of adoption patterns with human subjects
Answers the question “what if, in the past,. . .?”
Possibility of rerunning the tape of history multiple times
Real-world data
None
Key methodological construct
Controlled setting
Average treatment effect
Random seed
Autoregressive parameter
Story-telling
Likelihood of identifying real-world path-dependent sequences
Likely
Likely
Unclear
Very likely
Epistemologically impossible
Representative paper(s)
Hossain & Morgan (2009); Meyer & Kleinaltenkamp (2011)
n/a
Zott (2003); Akkermans & Romme (2008)
Jackson & Kollman (2010, 2012)
David (1985); Vergne & Durand (2010) (for a critique)
FEATURES Main strength
ALLOWS RESEARCHER TO. . . Rule out path dependence as an explanation
YES
YES
YES
YES
YES (Kay, 2013)
Assess the consequences of initial conditions on equilibrium
YES
YES
YES
YES
NO
Assess the impact of small events on intermediary outcomes
Depends on protocol
Depends on context
YES
Depends on context
NO
Evaluate the extent to which small events are “random”
Random events are defined by researcher
Depends on context
Random events are defined by researcher
NO
NO
Understand the role of the sequence of intermediary outcomes on equilibrium
YES
Depends on context
YES
YES
NO
Verify that lock-in does not always occur around the same equilibrium
YES
YES
YES
YES
NO
Measure self-reinforcing mechanisms
YES
Depends on context
YES
Depends on context
NO
Evaluate the system’s stability in the presence of exogenous shocks
Depends on protocol
YES
YES
Depends on context
NO
Verify that, for any (O, I), P(O | I) < 1
Depends on protocol
Depends on context
YES
Depends on context
NO
Test alternative theories
Depends on protocol
Depends on context
YES
YES
NO
dose of outcome variety is observed. To define lock-in in more objective terms, we need a clear understanding of when the “long run” is long enough – and, here again, comparing similar trajectories cross-sectionally seems essential. These methodological constraints derive directly from the nature of path-dependent processes. When we put them all together, we can build a shortlist of research methodologies suitable for investigating path dependence in non-trivial ways. Vergne and Durand (2010) already identified three potential candidates that overcome most of the previously mentioned methodological hurdles: computer simulations, counterfactual modelling, and controlled laboratory experiments. In the last couple of years, another significant methodological advance has been made in the field of political science. Drawing on Page (2006), Jackson and Kollman (2010) designed an econometric model with a time-varying autoregressive parameter whose value, at some point, becomes 1. Their model ensures that lock-in is caused endogenously by the sequencing of events – and not because some exogenous shock forces convergence of the process independently of its past states. Thus, their model is consistent with path dependence theory at multiple levels: it does predict lock-in, but allows lock-in to occur on suboptimal equilibria, and rules out alternative explanations (such as equilibrium dependence or inertia). In other words, Jackson and Kollman’s model is in line with both David’s account of path dependence and Vergne and Durand’s
methodological guidelines (David, 2001; Vergne and Durand, 2010). Table 1 below summarizes the five methods available to test path dependence theory. In their latest paper, Jackson and Kollman (2012) further specify their model by distinguishing between path-dependent processes and other types of dynamic processes – for instance, those processes in which past states affect intermediary outcomes but not equilibrium distribution (“the roads may differ but all roads lead to Rome”, p. 157). And they use an illuminating example to justify the need to finely identify the unique properties of path dependence. In countries transitioning from authoritarian to democratic regimes, they ask, does it matter to the final outcome whether economic reforms precede political reforms? If the sequence does not matter, then the process is not path-dependent. Needless to say, a single case study will never be able to establish whether the sequence matters to the outcome because it will always lack the counterfactual (or cross-sectional) evidence to contrast alternative sequences and their consequences. In fact, Jackson and Kollman (2012) make it crystal clear what is required to test econometrically for path dependence: a consistent set of quantitative, pooled time-series cross-sectional data. And they conclude (p. 173): People often observe patterns in outcomes and call the process path dependent. We argue [. . .] that for equilibrium, or path, dependence, these processes must meet very stringent
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conditions, which means that true path dependence may occur rarely. With careful and proper analysis, many processes that are called path dependent may actually be equilibrium independent [. . .]. On closer examination, there are likely to be other distinct patterns that warrant detailed examination. These distinctions are not just about semantics. Whether a process is equilibrium dependent or equilibrium independent has important substantive and empirical implications. The political and economic transition example demonstrates that the determination of path dependence versus equilibrium independence could have profound policy consequences. Use of the terminology of path dependence without a well-grounded definition of an equilibrium and supporting empirical evidence leads to incoherent theories and poor predictions about future trajectories. Conversely, ignoring path dependence may lead to badly biased empirical results in empirical studies and wrong predictions.
4. Two alternative paths for future research Organization and management scholars have done a poor job at exploring path dependence empirically. But that can change if we acknowledge the shortcomings of our prior work. We, as researchers, need to decide whether we want path dependence to finally become a credible explanation for (at least some) patterns of technology adoption, organizational lock-in, or institutional dominance. To that end, Vergne and Durand (2010) and Jackson and Kollman (2012) offer clear methodological guidelines that some have already followed (e.g., Meyer and Kleinaltenkamp, 2011). Alternatively, we can keep using the term “path dependence” as a trendy, catch-all phrase to describe virtually every sequence of events where history seems to matter on the surface, even when better (and testable) alternative models can readily explain the observed phenomena (e.g., first-mover advantage, organizational inertia, hypersensitivity to initial conditions). Should we decide to stick to the latter course of action, we shouldn’t be surprised to find, in a few years, that most management and organization journal articles refer to “path dependence” at some point.3 While some advocates of path dependence may see such a future as representing an academic victory, the increasing pervasiveness of a buzzword with little empirical content will actually raise serious issues regarding our ability, as scholars, to design robust and
3 The proportion of management papers referring to path dependence has continuously increased, from 6.15% in 1998–2002 to 10.5% in 2003–2007 (Vergne and Durand, 2010). In 2011, 21.6% of the papers published in Research Policy used the term (Kay, 2013). Years ago, David already noted that “the rising popularity of the term ‘path dependence’ has spawned a variety of usages, a perceptible measure of confusion, and even some outright misinformation” (David, 2001: 15).
testable theories. We can only hope that Kay’s fascinating investigation of QWERTY will redirect our methodological effort toward the more rigorous research path. And then, perhaps, some day, social scientists will further our understanding of the actual pathdependent phenomena that quite likely lie somewhere out there, unexplored. Acknowledgement I gratefully acknowledge the support provided by Research Policy Editor Martin Kenney, and the comments given by Rodolphe Durand on an earlier draft of the paper. Any remaining errors are mine. References Akkermans, H., Romme, A.G.L., 2008. How partnership behaviour evolves in networks: path dependency, social figuration and life events. In: Paper presented at the conference ‘Studying Path Dependencies of Businesses, Institutions, and Technologies’, Freie Universität, 28–29 February. David, P.A., 1985. Clio and the economics of QWERTY. The American Economic Review 75 (2), 332–337. David, P.A., 2001. Path dependence, its critics and the quest for “historical economics”. In: Garrouste, P., Ioannides, S. (Eds.), Evolution and Path Dependence in Economic Ideas: Past and Present. Edward Elgar Publishing, Cheltenham (UK). Hossain, T., Morgan, J., 2009. The quest for QWERTY. American Economic Review 99 (2), 435–440. Jackson, J.E., Kollman, K., 2010. A formulation of path dependence with an empirical example. Quarterly Journal of Political Science 5 (3), 257–289. Jackson, J.E., Kollman, K., 2012. Modeling, measuring, and distinguishing path dependence, outcome dependence, and outcome independence. Political Analysis 20 (2), 157–174. Kay, N., 2013. Rerun the tape of history and QWERTY always wins. Research Policy, 1–28. Liebowitz, S.J., Margolis, S.E., 1990. The fable of the keys. Journal of Law and Economics 33 (1), 1–25. Liebowitz, S.J., Margolis, S.E., 1995. Path dependence, lock-in, and history. Journal of Law, Economics, and Organization 11 (1), 205–226. Meyer, T., Kleinaltenkamp, M., 2011. Does quality win? A simulation study on technological path dependence in two-sided markets with an application to platform competition in the smartphone industry. In: Proceedings of the 2011 Australian and New Zealand Marketing Academy. Page, S.E., 2006. Path dependence. Quarterly Journal of Political Science 1 (1), 87–115. Vergne, J.-P., Durand, R., 2010. The missing link between the theory and empirics of path dependence: conceptual clarification, testability issue, and methodological implications. Journal of Management Studies 47 (4), 736–759. Vergne, J.-P, Durand, R., 2011. The path of most persistence: an evolutionary perspective on path dependence and dynamic capabilities. Organization Studies 32 (3), 365–382. Zott, C., 2003. Dynamic capabilities and the emergence of intra-industry differential firm performance: insights from a simulation study. Strategic Management Journal 24, 97–125.
Contents lists available at SciVerse ScienceDirect
Research Policy journal homepage: www.elsevier.com/locate/respol
Discussion
QWERTY is dead; long live path dependence Jean-Philippe Vergne ∗ Ivey Business School, Western University, Canada
a r t i c l e
i n f o
Article history: Received 17 October 2012 Accepted 13 February 2013 Available online 17 April 2013
1. R.I.P QWERTY In many respects, Kay (2013) delivers a final blow to the persistent belief that the QWERTY case provides empirical evidence of path dependence. Liebowitz and Margolis threw the first punch more than twenty years ago when they argued, quite convincingly, that the commonly accepted narrative “of the market’s rejection of Dvorak [did] not report the true history” and that, in fact, “the continued use of Qwerty [was] efficient given the current understanding of keyboard design” (Liebowitz and Margolis, 1990: p. 2). Nearly twenty years later, in an attempt to replicate the QWERTY case in a controlled lab experiment, Hossain and Morgan (2009) found that “the market always manages to solve the QWERTY problem. In 60 iterations of dynamic platform competition, our subjects never got stuck on the inferior platform” (Hossain and Morgan, 2009: p. 435). And they concluded: “While the QWERTY effect is certainly an interesting theoretical possibility, the dearth of examples of the phenomenon, both in the field and now in the lab, leads us to conclude that the danger lies more in the minds of theorists than in the reality of the marketplace” (Hossain and Morgan, 2009: p. 440). Kay (2013) is thus consistent with both Liebowitz and Margolis (1990) and Hossain and Morgan (2009) when he argues that, “if you could rerun the tape of history here as many times as you like, choosing when to introduce Dvorak, QWERTY would always win.” So what is the QWERTY story really about? To find out, Kay (2013) explores both the internal and external selection environments (Vergne and Durand, 2011) faced by Christopher L. Sholes, QWERTY’s original inventor. According to Kay’s account, Sholes was an entrepreneur with industry experience in printing and media, who secured both financial and marketing support to launch a
∗ Corresponding author at: Ivey Business School, Western University, 1151 Richmond Street North, London, Ontario N6A 3K7, Canada. E-mail address: [email protected] 0048-7333/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.respol.2013.03.009
new, carefully designed technology. He was savvy enough to make the revolutionary machine look familiar to potential (female) typists by presenting it on a sewing machine stand (Kay, 2013: p. 7). He designed the best technology of his time by making infrequent pairs of letters contiguous on the typebasket to minimize jamming (i.e., one could type Mark Twain’s Life on the Mississippi entirely with QWERTY and only 146 co-occurrences of contiguous letters would be problematic, against 2358 with a Dvorak keyboard). Finally, Sholes enhanced his keyboard’s market appeal by ensuring that salespersons could impress prospective clients by typing the word “typewriter” in a split second, and to that end he positioned the letters T, Y, P, E, W, R, and I on the same row. In other words, Kay (2013) tells us a story about how, in a nascent industry, the most strategically savvy entrepreneur, who also happens to be selling the best product, ends up winning the market competition. Kay’s paper thus raises the following question: as scholars, do we need a theory called path dependence, based on the mathematical properties of non-ergodic Markov chains (David, 2001), to shed light on the QWERTY case? And Kay’s paper also suggests a clear answer: as per Occam’s razor, no, path dependence is not required to explain QWERTY’s dominance.
2. Some misinterpretations around David’s seminal paper David opened his 1985 paper on “QWERTY-nomics” with a caveat: “standing alone, my story will be simply illustrative and does not establish how much of the world works this way. That is an open empirical issue and I would be presumptuous to claim to have settled it, or to instruct you in what to do about it” (David, 1985: p. 332). And he concluded his paper with questions, not answers. He found the QWERTY story “intriguing” and expressed the belief that there may be more QWERTY worlds lying out there, “worlds we do not yet fully perceive or understand,” then ended with a call for “exploring” those worlds (David, 1985: p. 336). Did David ever present the QWERTY case as undisputable empirical evidence of path dependence? To the best of my knowledge, no, he did not.
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David’s only confusing statement about the QWERTY case was that “competition in the absence of perfect futures markets drove the industry prematurely into standardization on the wrong system” (David, 1985: p. 336). Since then, both Liebowitz and Margolis (1990) and Kay (2013) have explained why the terms “prematurely” and “wrong system” were, in this context, perhaps not the most appropriate. But David’s misplaced words should not lead us to throw out the baby with the bathwater, expelling from our academic vocabulary every reference to path dependence. The biggest challenge with path dependence is not the theory itself but its empirical validation. That is, path dependence does not imply suboptimality but it can lead to it (David, 2001).1 Thus, the reason Kay’s findings imply that QWERTY cannot be explained by path dependence is not so much the fact that QWERTY is optimal – because nothing prevents path dependence from leading to the optimal equilibrium – but rather the paper’s conclusion that rerunning the tape of history would always lead to the same outcome. Why? Because path dependence refers to the contingent selection of a stable equilibrium in a sequential stochastic process. It follows, then, that path-dependent sequences, should they be rerun multiple times, do not always converge around the same equilibrium. Put formally, in path-dependent processes, for any set of initial conditions I and any outcome O, the probability that the outcome of the process is O, conditional on I, is strictly inferior to 1. Vergne and Durand (2010) call this property a core theorem of path dependence: ∀ (O, I), P(O | I) < 1. The fact that rerunning the tape of history would never change the outcome of the keyboard standardization process violates this theorem, which brings us to the true reason why, according to Kay’s paper, QWERTY is not the outcome of a path-dependent process.2 Because suboptimality is not readily explained by conventional economics, many scholars believed that a research design based on the ex post identification of supposedly suboptimal outcomes would be well suited to provide empirical evidence of path dependence. Such a research design would distinguish more easily between neoclassical equilibrium and lock-in (as induced by path dependence). While this research strategy has some face value, it has turned out to be a dead end. Despite an accumulation of historical case studies of so-called path-dependent trajectories over the past two decades, a significant portion of the scholarly community still does not “buy” the path dependence story. Sure, we could blame the sceptics. But I’d rather blame the method. More precisely, the problem is not the case study method itself but its incompatibility with the unique epistemological underpinnings of path dependence theory (Vergne and Durand, 2010). Following David’s template (David, 1985), case studies of alleged path-dependent systems typically proceed from the observation of a stable pattern (e.g., a technology or an institution that has been around for a while) to the conclusion that lock-in occurred (as evidenced by the observed stability). Then, with the benefit of hindsight, case study-based papers typically claim that the stability is accounted for by self-reinforcing mechanisms. The logic of the argument often looks like this: when something remains stable
1 From this viewpoint, Hossain and Morgan (2009) do not test path dependence per se, but the prediction that path dependence can lead to a suboptimal outcome owing to random shocks. In their study, they rerun the tape of history 60 times but lock-in always happens on the same (optimal) equilibrium. 2 Importantly, path dependence is not about hypersensitivity to initial conditions, a concept that comes from chaos theory and relates to deterministic (as opposed to stochastic) systems. Liebowitz and Margolis (1995) introduced confusion in the literature by conflating path dependence and chaos theory (and yet this does not affect in any way the validity of their critique of the QWERTY case). David (2001), in what is probably one of the clearest expositions of his views on path dependence, noted the misunderstanding and put an end to it by clarifying the distinction between deterministic chaos and path dependence in stochastic processes.
over time, we tend to get used to it, which then creates cognitive sunk costs and self-reinforcing learning loops. Quite problematically, however, most case studies of path dependence don’t even try to measure (i.e., quantify) such self-reinforcing mechanisms, but merely list them based on ad hoc assumptions about historical events as reconstructed by researchers from partial archival records. From this viewpoint, to argue that “small events” happened early on to select a path is not too difficult, since contingency is a pervasive feature of daily life. If the archival records show at some point that stability ceases, one can still argue that “path breaking” occurred due to some exogenous shock identified ex post. Seen from this perspective and using case study methodology, basically anything can be argued to be path-dependent (or if not, it’s because path-breaking occurred). Clearly, this line of case study-based reasoning has many issues. First, to prove that “small events” actually happened by chance is virtually impossible in case study research, so alternative explanations cannot be ruled out – for instance, the “small event” could be a mere symptom of an unobserved structural force that is the true cause behind lock-in (Vergne and Durand, 2010). Second, in complex social systems, multiple positive feedback loops are always at work, but so are negative feedback loops (Page, 2006). Without quantifying the loops, it is impossible to assess the extent to which the negative loops compensate for the positive ones. Third, while path dependence leads to lock-in in the long run, we, as researchers, cannot afford to define what we mean by “the long run” ex post, when lock-in, quite conveniently, has already occurred. Consider that, in 1995, we were all locked in using VHS. Ten years later, we all used DVDs. Now, imagine a counterfactual world where we were locked in using Betamax in 1995 instead of VHS and, because “one damn thing follows another” (David, 1985: p. 332), Sony began throwing tons of cash on R&D to develop SuperDVD, a 3D holographic image format that would make DVD look prehistoric. The story today would be quite different as a consequence, and, in “the long run,” Betamax would have been the optimal equilibrium. And here’s the twist: because path dependence is about stochastic systems, there is no way that, using path dependence theory, anyone could disprove that SuperDVD wouldn’t have existed had Betamax cornered the market in the 1990s. It follows that claims about suboptimality do not make sense from the viewpoint of path dependence theory itself (see Vergne and Durand, 2010, for a formal proof). In most case study research, path dependence theory is simply unfalsifiable. In fact, David himself (1985: 336) explained that QWERTY-like case studies were bound to be “simply illustrative.” True, case study research is very useful in generating new theory around phenomena that are not yet well understood – but in the case of path dependence, the very existence of the phenomenon is at stake, so before extending the theory using case studies, we’d be better off providing a robust research design that can, at last, establish path dependence as an empirical reality in the social sciences. David (1985) has opened an exciting avenue for research, but the path-dependence research community (myself included) is to be blamed for not having yet designed better methods to follow up on his seminal insight. Put simply, while I believe that path dependence is out there, I also believe that, so far, we just haven’t done a great job at observing it.
3. Long live controlled research designs! To understand the role of contingent “small events,” we need to be able to manipulate the initial conditions of sequential processes in research designs. To assess the influence of self-reinforcing mechanisms, we need to be able to measure them. To demonstrate that lock-in does not always occur on the same outcome, we need some form of cross-sectional research design where a
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Table 1 Contrasting five methods in the context of path dependence research. Laboratory experiment
Counterfactual modelling
Computer simulation
Pooled TSCS regression
Single/multiple case study (qualitative)
Direct observation of adoption patterns with human subjects
Answers the question “what if, in the past,. . .?”
Possibility of rerunning the tape of history multiple times
Real-world data
None
Key methodological construct
Controlled setting
Average treatment effect
Random seed
Autoregressive parameter
Story-telling
Likelihood of identifying real-world path-dependent sequences
Likely
Likely
Unclear
Very likely
Epistemologically impossible
Representative paper(s)
Hossain & Morgan (2009); Meyer & Kleinaltenkamp (2011)
n/a
Zott (2003); Akkermans & Romme (2008)
Jackson & Kollman (2010, 2012)
David (1985); Vergne & Durand (2010) (for a critique)
FEATURES Main strength
ALLOWS RESEARCHER TO. . . Rule out path dependence as an explanation
YES
YES
YES
YES
YES (Kay, 2013)
Assess the consequences of initial conditions on equilibrium
YES
YES
YES
YES
NO
Assess the impact of small events on intermediary outcomes
Depends on protocol
Depends on context
YES
Depends on context
NO
Evaluate the extent to which small events are “random”
Random events are defined by researcher
Depends on context
Random events are defined by researcher
NO
NO
Understand the role of the sequence of intermediary outcomes on equilibrium
YES
Depends on context
YES
YES
NO
Verify that lock-in does not always occur around the same equilibrium
YES
YES
YES
YES
NO
Measure self-reinforcing mechanisms
YES
Depends on context
YES
Depends on context
NO
Evaluate the system’s stability in the presence of exogenous shocks
Depends on protocol
YES
YES
Depends on context
NO
Verify that, for any (O, I), P(O | I) < 1
Depends on protocol
Depends on context
YES
Depends on context
NO
Test alternative theories
Depends on protocol
Depends on context
YES
YES
NO
dose of outcome variety is observed. To define lock-in in more objective terms, we need a clear understanding of when the “long run” is long enough – and, here again, comparing similar trajectories cross-sectionally seems essential. These methodological constraints derive directly from the nature of path-dependent processes. When we put them all together, we can build a shortlist of research methodologies suitable for investigating path dependence in non-trivial ways. Vergne and Durand (2010) already identified three potential candidates that overcome most of the previously mentioned methodological hurdles: computer simulations, counterfactual modelling, and controlled laboratory experiments. In the last couple of years, another significant methodological advance has been made in the field of political science. Drawing on Page (2006), Jackson and Kollman (2010) designed an econometric model with a time-varying autoregressive parameter whose value, at some point, becomes 1. Their model ensures that lock-in is caused endogenously by the sequencing of events – and not because some exogenous shock forces convergence of the process independently of its past states. Thus, their model is consistent with path dependence theory at multiple levels: it does predict lock-in, but allows lock-in to occur on suboptimal equilibria, and rules out alternative explanations (such as equilibrium dependence or inertia). In other words, Jackson and Kollman’s model is in line with both David’s account of path dependence and Vergne and Durand’s
methodological guidelines (David, 2001; Vergne and Durand, 2010). Table 1 below summarizes the five methods available to test path dependence theory. In their latest paper, Jackson and Kollman (2012) further specify their model by distinguishing between path-dependent processes and other types of dynamic processes – for instance, those processes in which past states affect intermediary outcomes but not equilibrium distribution (“the roads may differ but all roads lead to Rome”, p. 157). And they use an illuminating example to justify the need to finely identify the unique properties of path dependence. In countries transitioning from authoritarian to democratic regimes, they ask, does it matter to the final outcome whether economic reforms precede political reforms? If the sequence does not matter, then the process is not path-dependent. Needless to say, a single case study will never be able to establish whether the sequence matters to the outcome because it will always lack the counterfactual (or cross-sectional) evidence to contrast alternative sequences and their consequences. In fact, Jackson and Kollman (2012) make it crystal clear what is required to test econometrically for path dependence: a consistent set of quantitative, pooled time-series cross-sectional data. And they conclude (p. 173): People often observe patterns in outcomes and call the process path dependent. We argue [. . .] that for equilibrium, or path, dependence, these processes must meet very stringent
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conditions, which means that true path dependence may occur rarely. With careful and proper analysis, many processes that are called path dependent may actually be equilibrium independent [. . .]. On closer examination, there are likely to be other distinct patterns that warrant detailed examination. These distinctions are not just about semantics. Whether a process is equilibrium dependent or equilibrium independent has important substantive and empirical implications. The political and economic transition example demonstrates that the determination of path dependence versus equilibrium independence could have profound policy consequences. Use of the terminology of path dependence without a well-grounded definition of an equilibrium and supporting empirical evidence leads to incoherent theories and poor predictions about future trajectories. Conversely, ignoring path dependence may lead to badly biased empirical results in empirical studies and wrong predictions.
4. Two alternative paths for future research Organization and management scholars have done a poor job at exploring path dependence empirically. But that can change if we acknowledge the shortcomings of our prior work. We, as researchers, need to decide whether we want path dependence to finally become a credible explanation for (at least some) patterns of technology adoption, organizational lock-in, or institutional dominance. To that end, Vergne and Durand (2010) and Jackson and Kollman (2012) offer clear methodological guidelines that some have already followed (e.g., Meyer and Kleinaltenkamp, 2011). Alternatively, we can keep using the term “path dependence” as a trendy, catch-all phrase to describe virtually every sequence of events where history seems to matter on the surface, even when better (and testable) alternative models can readily explain the observed phenomena (e.g., first-mover advantage, organizational inertia, hypersensitivity to initial conditions). Should we decide to stick to the latter course of action, we shouldn’t be surprised to find, in a few years, that most management and organization journal articles refer to “path dependence” at some point.3 While some advocates of path dependence may see such a future as representing an academic victory, the increasing pervasiveness of a buzzword with little empirical content will actually raise serious issues regarding our ability, as scholars, to design robust and
3 The proportion of management papers referring to path dependence has continuously increased, from 6.15% in 1998–2002 to 10.5% in 2003–2007 (Vergne and Durand, 2010). In 2011, 21.6% of the papers published in Research Policy used the term (Kay, 2013). Years ago, David already noted that “the rising popularity of the term ‘path dependence’ has spawned a variety of usages, a perceptible measure of confusion, and even some outright misinformation” (David, 2001: 15).
testable theories. We can only hope that Kay’s fascinating investigation of QWERTY will redirect our methodological effort toward the more rigorous research path. And then, perhaps, some day, social scientists will further our understanding of the actual pathdependent phenomena that quite likely lie somewhere out there, unexplored. Acknowledgement I gratefully acknowledge the support provided by Research Policy Editor Martin Kenney, and the comments given by Rodolphe Durand on an earlier draft of the paper. Any remaining errors are mine. References Akkermans, H., Romme, A.G.L., 2008. How partnership behaviour evolves in networks: path dependency, social figuration and life events. In: Paper presented at the conference ‘Studying Path Dependencies of Businesses, Institutions, and Technologies’, Freie Universität, 28–29 February. David, P.A., 1985. Clio and the economics of QWERTY. The American Economic Review 75 (2), 332–337. David, P.A., 2001. Path dependence, its critics and the quest for “historical economics”. In: Garrouste, P., Ioannides, S. (Eds.), Evolution and Path Dependence in Economic Ideas: Past and Present. Edward Elgar Publishing, Cheltenham (UK). Hossain, T., Morgan, J., 2009. The quest for QWERTY. American Economic Review 99 (2), 435–440. Jackson, J.E., Kollman, K., 2010. A formulation of path dependence with an empirical example. Quarterly Journal of Political Science 5 (3), 257–289. Jackson, J.E., Kollman, K., 2012. Modeling, measuring, and distinguishing path dependence, outcome dependence, and outcome independence. Political Analysis 20 (2), 157–174. Kay, N., 2013. Rerun the tape of history and QWERTY always wins. Research Policy, 1–28. Liebowitz, S.J., Margolis, S.E., 1990. The fable of the keys. Journal of Law and Economics 33 (1), 1–25. Liebowitz, S.J., Margolis, S.E., 1995. Path dependence, lock-in, and history. Journal of Law, Economics, and Organization 11 (1), 205–226. Meyer, T., Kleinaltenkamp, M., 2011. Does quality win? A simulation study on technological path dependence in two-sided markets with an application to platform competition in the smartphone industry. In: Proceedings of the 2011 Australian and New Zealand Marketing Academy. Page, S.E., 2006. Path dependence. Quarterly Journal of Political Science 1 (1), 87–115. Vergne, J.-P., Durand, R., 2010. The missing link between the theory and empirics of path dependence: conceptual clarification, testability issue, and methodological implications. Journal of Management Studies 47 (4), 736–759. Vergne, J.-P, Durand, R., 2011. The path of most persistence: an evolutionary perspective on path dependence and dynamic capabilities. Organization Studies 32 (3), 365–382. Zott, C., 2003. Dynamic capabilities and the emergence of intra-industry differential firm performance: insights from a simulation study. Strategic Management Journal 24, 97–125.