Seeking the Robust Core of Organizational Learning Theory

International Journal of Collaborative Enterprise *DRAFT*

ABSTRACT

Organizational learning theory (OLT) has become a hot topic of conversation in academic journals. However, the variety of descriptions seem to suggest no unified understanding of what OLT is. In this paper, I draw on a sample of 12 recent papers as samples of normal science and exemplars of our present level of scholarship to conduct a propositional analysis of the structure of OLT. This analysis identifies the core of OLT and finds that OLT has a robustness of 0.16 on a scale of zero to one. This low level of robustness suggests that OLT may be of limited efficacy in application. This paper creates a benchmark for the progress of OLT and suggests opportunities for advancing our understanding of OLT.

KEYWORDS: organizational learning, T@ theory, theory of theory, metatheory, robustness

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Introduction

Organizational learning theory (OLT) was introduced by Cyert and March in the sixties, and has since been adopted my many authors. For example, Spender (2008) looks at OLT in terms of knowledge management, Antonacopoulou & Chiva (2007) look at OLT through the lens of Complexity Science, and (Elkjaer, 2004) suggests a “third way” of OLT that involves intuition, emotion, and reflection. The diversity suggested by these articles calls into question what exactly OLT is.

The importance of OLT as a topic for study is evidenced by the large number of articles related to this topic in recent years. In the Academy of Management Journal alone there were nine articles in 2006, seven in 2005, and six in 2004. This large set of articles suggests an opportunity to conduct a study of OLT and so create a benchmark along the evolutionary path of the theory.

This article presents what might be considered the AoM version of OLT – which readers may wish to compare with their own understandings and the versions of OLT presented in the present journal. In that process, the present analysis may be understood as an example of the benefits of metatheoretical analysis for the cross-pollination of ideas.

Our recent understanding of OLT may be generally described as understanding organizational success (e.g. Miller, Zhao, & Calantone, 2006) by balancing exploration (which provides information of uncertain value) and exploitation (the use of existing knowledge in predictable ways). Organizations that fail to balance may fall into “competency traps” (e.g. Taylor & Greve, 2006). Despite the large body of work describing OLT, “there is little common agreement about what organizational learning represents” (Shipton, 2006).

Famously, Popper (2002) argued for the need to improve social theory. A call echoed in various forms by an increasing number of authors (e.g. Glaser, 2002; Grapentine, 1998; Hitt & Smith, 2005; Lewis & Grimes, 1999; Oberschall, 2000; Starbuck, 2003; Wallis, 2007; K. E. Weick, 2005). Including more specific calls for improved theory in education (Ghoshal, 2005), and improved theory in practice (Kernick, 2006; McElroy, 2000). In seeming frustration with the lack of advancement in theory, there has even been a call for the abolition of theory (Burrell, 1997) and the adoption of as essentially a-theoretical approach to organizational change.

Following the call toward better theory, This study will draw on 12 articles recently published in the AoM Journal and suggest ways to develop OLT in a more purposeful way that may result in a theory that is more efficacious in practice.

It is assumed in this metatheoretical approach that each article may be seen as a novel version of OLT. That is to say that the assumptions, propositions, and hypotheses, serve to highlight various aspects of the broader body of theory; and, by highlighting some areas, each article may also be seen as obscuring other areas of theory – much in the same way that a metaphor both reveals and conceals (Morgan, 1996). The present study is not concerned with finding which of those 12 might be seen as better than the others. Rather, the concern is with developing an understanding of OLT as a whole that is more than the sum of its parts.

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Theoretical Foundations of Theory

Weick (1989) discusses theory as, “an ordered set of assertions” (p. 517). That insight begs the highly relevant question of just how well ordered those assertions might be. Parson and Shills note four similar levels of systemization of theory – moving toward increasing “levels of systemization” (Friedman, 2003, p. 518). Similarly, Dubin (1978) describes four levels of efficacy in theory; and these levels may be understood as reflecting the structure of the theory. This study will seek the third of Dubin’s levels by looking at covariation - how several concepts might impel change in one another.

Within a body of theory, there may be some concepts that are more closely related to one another, and other concepts that are not so closely related. Drawing on Lakatos, (1970) Wallis (Wallis, 2008) suggests that if a body of theory is understood to be a collection of concepts, those concepts which are less closely related to one another may be understood as inhabiting the outer belt of the theory. Those aspects of concepts of a theory that are more closely interrelated are said to inhabit the core of the theory.

For example, a list of assertions (e.g. A is true, B is true, C is true) might be seen as existing in the belt. These concepts need not be related to one another in any way, except for the fact that an author chose to assemble them into some sort of list. Such a theory would be seen as having a low level of structure. In contrast, Newton’s formula (F=ma) might be seen as highly structured because it is possible to identify changes in one aspect (e.g. force) from changes in other aspects (e.g. mass & acceleration). Such understanding has been long sought in the social sciences but has remained elusive. Wallis’s (2008) contribution to metatheory suggests how the propositions used to describe or define a theory provide data that are useful in identifying the structure of the theory. One goal of this paper is to advance OLT by improving our understanding of its structure.

Looking at the interrelationships between the propositions of the theory, therefore, might aid the development of the epistemological validity of the theory. Especially where the propositions might be seen as, “reciprocally or mutually related” (Webster's, 1989, p. 744). With such a view, a body of theory might be seen as a kind of system and, “…any part of the system can only be fully understood in terms of its relationships with the other parts of the whole system.” (Harder, Robertson, & Woodward, 2004, p. 83, drawing on Freeman). It seems, therefore, that every concept within a theory might best be understood through other concepts within that body of theory. Significantly, this perspective seems to fit with Dubin’s (above) assertion that theories of higher efficacy have explanations and concepts that are co-causal and goes a long way toward explaining the effectiveness of Newton’s formula and other robust, useful, theories of physics.

However, the path for achieving such a structure is often ambiguous or based on the idea that the theory will somehow emerge from data found in organizational observations – as seen in calls for social scientists to engage in empirical research. Rather than study human organizations through the lens of OLT, however, the present study looks at OLT, itself. The lens purposefully employed is the above understanding of the structure of theory. This approach is in contrast to other methods of analyzing theory such as the historical development of the theory or testing the

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theory in application. In short, instead of looking at data through the conscious or unconscious use of a theory, this study will look at the theory as if it is data. Wallis (2008) provides a methodology for using the theory as data to determine the “robustness” of the theory.

It should be noted here that most writers in the field of OLT might use the term “robustness” in a way that refers to the statistical significance of a proposition or hypothesis. In contrast, the present study uses the term robustness as it might be used in a conversation of theories found in physics where robustness represents the “internal integrity” of the theory. The robustness of a theory may be understood as the ratio of co-causal propositions to the total number of propositions in the theory. For example, if a theory consists of a list of ten propositions where none of the ideas are conceptually related to any others, that theory would have a robustness of zero. In contrast, Newton’s F=ma is a theory where each aspect may be understood as being defined, described, or circumscribed by the other two aspects. That theory has a robustness of one.

To determine the robustness of an organizational theory, Wallis suggests a five-step process:

1. Identify a specific body of theory.2. Search the literature for concise definitions.3. Identify causal propositions4. Link casual propositions according to related concepts (where one aspect is influenced by

two or more others).5. Identify the total number of propositions and compare to the number of co-causal

propositions (creating a ratio between zero and one).

For the present analysis, I began with the intention to investigate the concise propositions that the collected authors use to define the extent of OLT. During the course of my reading, however, I found the authors of OLT do not spend much space describing or defining what OLT “is.” It appears that there are structural differences between the papers used by Wallis (located in the broad conversation around complexity theory) and the articles used in this study (located in the conversation around OLT from the “perspective” of the AoM Journal). Therefore, I found that the concise propositions anticipated from Wallis’ methodology were “tangled” in the more general conversation.

Wallis (2008) states, “Concise definitions were used so that the study could cover as much ground as possible. It is also assumed that a concise definition includes the most important aspects of each author’s version of the theory.” In seeking an alternative, I found clear, and concise, statements in the supported hypotheses of each paper. In the following section, I will apply Wallis’ methodology to analyze the supported propositions found in 12 articles of OLT.

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Analysis of Hypotheses

My search began with an investigation of the Academy of Management website. There I found lists of topics along with the articles published for each of those topics. I then reviewed each article under the organizational learning heading. A few listed articles did not include a substantive discussion on organizational learning, and were subsequently dropped from this investigation. I chose to focus on articles from 2004-2006 (inclusive) to obtain an up-to-date “snapshot” of the body of theory. Therefore, this analysis might be considered a mid-century snapshot, benchmark, or milestone of OLT development. Similarly, as these articles are all drawn from the same journal, they might, in some sense, be thought of as representing another kind of focus – something more than a casual connection, but less formal than a school of thought.

For the present study, I use 12 articles from the Academy of Management Journal. They are: (Agarwal, Echambadi, Franco, & Sarkar, 2004; Arthur & Huntley, 2005; Beckman, 2006; Haleblian, Kim, & Rajagopalan, 2006; Hoang & Rothaermel, 2005; Hult, Ketchen, & Slater, 2004; Jansen, Van Den Bosch, & Volberda, 2005; Lavie & Rosenkopf, 2006; McFadyen & Cannella Jr, 2004; Subramaniam & Youndt, 2005; Wadhwa & Kotha, 2006; Zhang & Rajagopalan, 2004).

Due to limitations of space, the studies in this paper will be focused on the level of “concept” (with concepts presented as they are named by the authors and as they may be generally understood by most readers) and theory (as a collection of concepts). These studies will generally avoid what might be thought of as a sub-concept level of “interpretation.” Similarly, we will avoid what might be understood as a post-theorizing level of “application” and/or “testing.” In the present study, I have revised the hypotheses of the original authors. These revisions should be understood as necessary to allow the present analysis to fit within the context of this article and no alteration of the meaning developed by the original authors is intended.

These articles were set at differing levels of scale including: interpersonal, team, organizational, inter-organizational, and supply-chain. As each is part of the same body of theory, we may allow that the same insights might be applied across all of these levels. Such an assumption is based on the idea of “fractal similarity” (Gleick, 1987), where patterns of interaction have some similarity between larger and smaller levels of scale. Another example, which may justify applying theoretical insights between levels of scale, may be found in the use of metaphor (e.g. Morgan, 1996), where an insight from one aspect of life might be applied to another with some success.

Wallis (2008) claims that he combined the data into dimensions suggested by the data itself, rather than trying to fit the data into a pre-existing framework. In possible contrast, the present analysis found that of the hypotheses found in the set of 12 articles, most fit neatly into the general concepts of OLT as noted above in the introduction. Indeed, I was able, for the most part, to align the hypotheses with those concepts.

To summarize these concepts, and their relationships, we may note that more diversity in affiliations, more cross-functional interfaces (liaisons, project teams, task forces, etc), more job

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rotation, more active involvement with partnered firms, and more capital investment in firms – all were suggested by the hypotheses to cause more exploration and acquisition of new knowledge.

Similarly, more socialization tactics (e.g. interpersonal relationships leading to shared beliefs), more shared meaning, more connectedness (density of interpersonal communication linkages), more formalization (written routines), all lead to greater exploitation of existing information.

Another important aspect of OLT seems to be the balancing effect between exploration and exploitation of knowledge. This relationship is sometimes described as a “tendency” to find a balance between the two activities. Further, that balancing act may be said occur in domains of function (e.g. R&D), structure (e.g. partnership), and attribute (e.g. a different industry) (Lavie & Rosenkopf, 2006). Unless the causes and effects of this tendency can be explained, it must remain a vague and unsatisfactory description of a potentially important phenomenon. Overall, it is claimed that there is an “inverted U” shaped distribution between relationships (including the number and strength of those relationships) and the creation of knowledge. However, the cause of this relationship is not defined.

More knowledge acquisition leads to more knowledge distribution and related form of knowledge sharing within an organization. As the process of knowledge distribution may be understood as a process that is more routine than knowledge acquisition (R&D is less predictable than writing company procedures), it may be understood that acquisition leads to exploitation. Although, the exploitation suggested here is internal to the firm, while the exploitation more commonly discussed in the OLT literature refers to the exploitation of knowledge in a way that uses the distributed knowledge to better effect the market – outside the firm. Finally, more routinization (repetitious acts) reduces the ability of a firm to explore for new knowledge.

Firm success is another important aspect. Where, to some extent, firm success may be understood as deriving directly from the exploitation of knowledge, there are a number of other factors involved. More relay-based CEO succession seems to lead to more firm success (although, the CEO succession is also based on the success of the firm – leading us to say that success seems to cause success (seemingly, a useless tautology). And, firms with an imbalance of knowledge seem to spin-out more new firms. More usefully, more strategic instability and more industry instability seem to support firm success. Firms with more knowledge seem more likely to survive longer than firms with less knowledge. Firms with more knowledge seem to spin-out new firms that have more knowledge. More expertise in one area leads to continued activity in that area. This may become a “competency trap,” however that dimension is not developed as well as the others in this literature. Indeed, there seems to be more focus on the success of firms. In short, success leads to success, but there is insufficient exploration on what might be termed the “tipping point” (Gladwell, 2000) that leads a firm to success or failure. Such a discovery would be a significant addition to the body of organizational theory.

These relationships are reflected in figure 1.

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- - - - - - - - - - - - - - - - - - - - - - - - - - - - - [Insert figure 1 about here]

- - - - - - - - - - - - - - - - - - - - - - - - - - - - -

The graphic relationship between concepts shown in figure 1 makes it relatively easy to determine the robustness of OLT. It also serves to illustrate where the focus of recent OLT exploration. First, it should be noted how many dimensional concepts are strictly causal. That is to say that these concepts may be understood as introducing change into other concepts – but it is not well defined what causes change in them. For example, "more diverse affiliations" is causal to "more exploration." All well and good – but it begs the question shat causes more diverse affiliations?

If may be seen in figure 1 that exploration results from five other aspects – and exploration is reduced by exploitation. More exploration also leads to more distribution. Therefore, exploration (as a concept) may be understood as “concatenated” (Van de Ven, 2007) in the sense where two or more aspects of a theory are understood to affect another aspect of the theory. With sufficient co-catenation, it may be understood that all aspects are concatenated from other aspects – creating co-casual relationships. It is possible that the distribution of knowledge might be interpreted as a form of codification of knowledge, and so be considered as causal to exploitation. That connection, however, requires more explication.

Exploration is increased by three other aspects. And is a causal influence to firm success. The concept of exploitation, therefore, is also concatenated and counts as a co-causal dimension. Shared belief may be understood as representing a linear relationship between increasing socialization and increasing exploitation. Because shared beliefs has only one cause and one resulting dimension, it cannot be counted as a co-causal dimension. In terms of creating a functional model, the concept of shared beliefs might be dropped and replaced by recognizing the causal relationship between more socialization and more exploitation. To deepen this understanding, it would be necessary to understand how shared beliefs are increased according to additional causal dimensions.

Firm success is increased by strategic and industry instability, and by exploitation. As with exploration and exploitation, this is a concatenated dimension. However, changes in firm success are not explained as causal to anything.

Less connected concepts include the idea that diversity of knowledge has a linear effect on firm creation. Similarly, increased knowledge leads to longer life of the firm. While the idea of a balancing a firm’s short term versus long-term success may be understood as is canonical to OLT, that balance is not clear from this analysis. Perhaps an exploration into the statistical probability of firm success (as it relates to exploration and exploitation) might provide insights into this balance.

Of the 19 concepts depicted in figure 1, 16 are causal, linear, or resultant. Only 3 are concatenated, or co-causal. Therefore, this analysis suggests that OLT has a robustness of 0.16

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(the result of 3 divided by 19) on a scale of zero to one. This low level of robustness suggests that OLT is not a good candidate for falsification in the Popperian sense. Neither is it a model that might be applied with great success in practice. The robustness does suggest a high level of flexibility, so that the concept of OLT might be transferred easily to other areas of study (Wallis, 2008).

The low robustness of OLT may be understood as deriving from a relatively limited interpretation of Wallis’ methodology. It seems a relatively simple matter to increase the apparent robustness by describing many of the causal dimensions as examples of the resultant dimensions. For example, rather than saying more diverse affiliations cause more exploration, a reasonable interpretation would be to reframe increased diverse affiliation as a form of exploration. Generally, and from an ad hoc perspective, such an explication might result in a model of OLT that contained a greatly reduced number of concepts.

- - - - - - - - - - - - - - - - - - - - - -[Insert figure 2 about here]- - - - - - - - - - - - - - - - - - - - - -

By inferring a causal relationship between the distribution of knowledge and the exploitation of knowledge, exploitation may be understood as a co-casual dimension. However, the concepts of exploration and distribution are reduced to a linear role. This may suggest investigating additional causal dimensions for this concept. For example, we might ask what causes a firm to cease exploration? The firm may have exceeded its ability to explore, its ability to hold knowledge, or made a cost-to-benefit choice that values exploitation over exploration.

The relationships in figure 2 suggest a total of 11 dimensions, two of which are concatenated Firm success and exploitation). Therefore, This version of OLT might be understood as having a robustness of 0.18 (the result of 2 divided by 11). Not a great improvement, but one that may point the way toward further investigation and increasing robustness. A more rapid advancement may be seen in Hung & Kuo (2008) where the authors present a hypothesized model drawn from the OLT literature. In their paper, these authors develop their own structural model. Using the methods of propositional analysis, it may be seen that they found OLT at the level of 0.22 and advanced it to 0.33 level of robustness. In the next section, I will discuss still more opportunities for exploring OLT.

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Discussion and Opportunities

First, it should be noted that within the general body of OLT, some concepts are not well connected to the present model. For example, firm creation and length of firm life are, while useful concepts, not clearly connected to other concepts. Explicating those linkages would add greatly to the robustness of the model. Of course, any concepts might be conceivably linked through explication and/or experimentation. For example, we might ask if it is possible to relate knowledge instability to exploration opportunity.

A conflict between concepts was suggested, but not well resolved, by Hult, Ketchen, & Slater (2004), where the authors found correlation between improved performance stemming from exploration activity as well as from shared meaning (which may be understood as relating to the exploitability of knowledge). As the authors note, the process of exploration leads to the process of exploitation, so perhaps there is not so much a contradiction in assumption as there is a contradiction in explication. Here too, a dimensional approach may prove useful to the development of OLT. Specifically, by focusing our descriptive efforts of a dimension of OLT in terms of other dimensions of OLT, we force ourselves to test the assumptions of all the dimensions. If continued conversation along these lines makes sense, it may be held that the relationships between the conceptual dimensions also make sense and are therefore, to some degree, valid.

The exploitation of knowledge is generally held to define success in the short run. In the literature, however, there does not seem to be much discussion describing what is “short term” compared to, “what is long term.” This is a potentially rich area of investigation; it is also a path of investigation that may lead to a pitfall. As an example of a dangerous path, I speculate that some readers of this article may be mentally contemplating their memories for insights. Some might be thinking that “long” is one year. Another might be thinking of a number closer to ten or 20 years. This kind of thinking may result in attempting to describe the length of the term in a concrete number An example of the pitfall may be seen in (Alexander, Giesen, Munch, Anderson, & Smelser, 1987) where one author described a “group” as containing 30 or more individuals – an assertion that is obviously difficult to support. Authors in OLT would be well advised to avoid developing such an axiomatic definition of “short term.” One way to avoid this kind of pitfall might be to define the length of term according to industry. After all, long-term success for a firm in the telecom industry might be seen as short-term success for a firm engaged in the production of gravel.

The most useful path of research (the one that will lead to the most robust theory), then, seems to be one which uses the existing dimensions of OLT to “close the loop” of interrelated concepts. For example, it may be possible to define or describe “term length” as a vector that results from industry instability where that stability is defined by the rate at which firms are entering and leaving the market. Another dimension of firm creation might be seen as the “imbalance” of knowledge. See especially (Agarwal et al., 2004), who suggest that new firm creation represents the opportunity to explore and exploit different forms of knowledge. Specifically, a new firm is more likely to be spun-out when the parent firm has technical knowledge, but not have the market exploitation knowledge to sell their technical knowledge as effectively as they might.

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Another opportunity to improve OLT that has some bearing on this line of investigation is suggested in Arthur et al., (2005) where more implementation of employee suggestions is shown to lead to lower production costs and so may be indicative of overall firm performance. Importantly, that study identified how the benefits of those suggestions (which may be seen as a form of creative exploration for new knowledge), seems to “level off” over time. This may be seen as lending credence to the idea that exploration leads to exploitation - and that there are limits to the effectiveness of exploration for knowledge. Additionally, it raises the question of related influences. That is to say, what barriers were raised over the time of the study that inhibited more exploration? Here is another opportunity to close the loop, and develop a more robust model for OLT. Generally, we may work to develop an understanding of how and why the employee suggestions tapered off over time. More specifically, we might develop that understanding in a way that may described in terms of existing multiple dimensions of OLT (e.g. some combination of firm success and the balancing process).

Another direction for exploration may be found by changing our understanding of the idea of a “competency trap.” The idea in OLT is that a firm will become so competent, that it will cease to explore for new knowledge and continue exploiting existing knowledge until other firms in the market surpass it. Instead of thinking of it as a form of success/failure, we may understood it as a type of balancing mechanism – in some way similar to the balance between exploration and exploitation. Additionally, a similar concept is explored in the area of evolutionary dynamics and complexity theory where firms are said to achieve “local peaks” of success within the “fitness landscape” (e.g. Fitzgerald & Eijnatten, 2002; Pascale, 1999). This is an area that seems under explored in the literature, in comparison to areas of exploration, exploitation, the balance between them, and firm success.

As most authors seem to be focused on the success of the firm, it may come as no surprise that OLT articles do not often address the question of where firms come from in the first place. Exceptions include Beckman (2006), who discusses the effect of founding members on the success of the organization. And, further back in the process of formation, Agarwal et al. (2004) discuss one method by which firms may be formed. Importantly, they relate firm formation to what might be termed an imbalance of knowledge when new firms are spun-out from a parent firm. This opens the door to understanding firm creation in terms of knowledge – and another opportunity to develop a more robust model of OLT.

Another, more general, opportunity to improve OLT might be to create a model that is applicable across multiple levels of scale – essentially asking how individual, team, organization, and industry exploration and exploitation might be understood as interrelated behaviors. There are also some similarities between OLT and other areas of study (e.g. complexity theory, peak performance theory, knowledge management) that might be explored with greater depth. Indeed, the dimensional approach used in the present analysis may be used to identify clear conceptual linkages between OLT and other theories of organizations. Such an exploration might begin to answer the call for greater unity between branches of the social sciences.

Finally, empirical studies might look at cycle time, or the oscillation, between exploration and exploitation activities – and relate those cycles to cycles in industry. Is there an oscillation at the

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industry level that forces an exploitive firm into a success trap and/or forces other firms to explore more. That is to say, more abstractly, it may be interesting to examine how oscillations on multiple levels affect one another.

Limitations and Conclusions

In frustration, Czarniawska (2001) notes how managers desire knowledge that is useable. These managers, whose world consists of “an odd mix of the ideal of rational theory and the enactment of remnants of that ideal” (K. Weick, 2003), seem frustrated by the inability of academia to provide tools that they perceive as useful. The present article suggests a path toward developing useful theory.

This analysis was subject to a number of limitations. First, it is essentially qualitative, so the opportunity exists to conduct future analyses along quantitative lines. Second, the sample size of the present study (12) was not as large as it might have been. Future studies might replicate and extend this study across a broader range of OLT literature. Additionally, this study provided a view of OLT from a limited temporal view, as the subject articles were published from 2004 to 2006 (inclusive). More insights might be obtained by expanding this study to include versions of OLT written and published in earlier years.

The present study is useful as it extends our understanding of OLT – providing a specific measurement of robustness as a milestone by which future development of OLT may be measured. Additionally, this study may be understood as defining the concepts that are central to OLT. Drawing on Lakatos(1970), Wallis (2008) might describe the concepts of exploration, exploitation, and firm success as existing in the “core” of OLT theory. All other concepts would be understood to exist in the outer belt.

This paper, to some degree, answers the growing call for improved understanding of theory. From a “theory of theory” or metatheoretical perspective, the present study is also useful in that it extends Wallis’ methodology of theory analysis by using hypotheses instead of propositions as a data set. This extention seems useful, but the effectiveness may be offset by the way that the formal hypotheses seem to be set in the a priori mold – the historical assumptions of the theory.

In this study, I focused on the supported hypotheses described by the various authors to determine the robustness of OLT. In general, I found that papers tended to included a collection of hypotheses that were not well related to one another (low robustness). The focus of the authors’ seemed to be on the relationships found within the data rather than the structure of the theory that they were drawing upon to inform their research. Some papers did include hypotheses that related to other hypotheses and a few (notably, Hult et al., 2004) specifically arranged their hypotheses so that the relationships were quite clear and (to some extent) co-causal. By combining the supported propositions from all of these articles into a single group, it was possible to develop some sense of robustness for the theory as a whole that would not be present in any sub-set of individual theories.

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In conclusion, the present study analyzed 12 recent articles relating to OLT. This benchmark study determined that the body of OLT has a robustness of 0.16. Many opportunities exist to complete the circle and improve the robustness of OLT. These include (but are, by no means limited to): explicating the relationships between existing aspects of OLT, developing a deeper understanding of the balancing effect between exploration and exploitation, understanding how firm success affects the processes of exploration and exploitation, and exploring the relationship between short and long term success.

As noted in the introduction to the present paper, the structure of a theory may relate to the effectiveness of the theory. Further, understanding the co-causal relationships between the propositions of a theory are important to understanding the robustness, and therefore the structure of a theory. For example, the effectiveness of Newton’s theory may be linked to the relationship between the aspects of that theory (Wallis, 2008).

Rather than a return to the past as suggested by Spender (2008), the present methodology suggests its usability as an effective tool for combining theories across multiple fields. These theories, well-concatenated, will provide useful insights that will advance the practices of managers.

Therefore, it is suggested that a more robust of OLT will provide practitioners with a tool to reliably guide their organizations toward short-term and long-term success. To achieve this goal, we must explore and explicate relationships between concepts until OLT becomes robust enough to be an exploitable form of knowledge.

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Figure #1 – dimensions of OLT as causal concepts.

16

More firm success

More exploration (acquisition of new knowledge)

More exploitation (use of existing knowledge)

Longer life of firm

More shared beliefs

More connectedness

More socialization

More formalization

More distribution of knowledge

More involvement with other firms

More cross-functional affiliations

More diverse affiliation

More job rotation

More industry instability

More strategic instability

More capital investment

More new firms created

More knowledge

Greater knowledge imbalance

Causes Less

Figure #2 – ad-hoc “reduced” version of OLT dimensional relationships

17

More firm success

More exploration (acquisition of new knowledge)

More exploitation (use of existing knowledge)

Longer life of firm

More socialization

More distribution of knowledge

More industry instability

More strategic instability

More new firms created

More knowledge

Greater knowledge imbalance

Causes Less