Adding Interpersonal Learning and Tacit Knowledge to March's Exploration-Exploitation Model

Miller, Kent D.; Zhao, Meng; Calantone, Roger J.

doi:10.5465/amj.2006.22083027

Cited by 240 publications

(251 citation statements)

References 39 publications

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“…As we have seen, one of the most important aspects of the firm's strategic behaviour is improvement in production costs. If machine flexibility seeks the reduction of costs and waiting time, exploration and/or exploitation also attempt to reduce these production costs, whether in the short term through the exploitation of abilities or in the long term through the exploration of new ideas and products (Miller, Zhao, & Calantone, 2006).…”

Section: Exploration and Exploitation Strategies And Manufacturing Flmentioning

confidence: 99%

The relationship between exploration and exploitation strategies, manufacturing flexibility and organizational learning: An empirical comparison between Non-ISO and ISO certified firms

Tamayo-Torres

Gutiérrez

Moreno

2014

European Journal of Operational Research

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The markets in which organizations currently operate require them to use behaviour based on both exploitation strategy and exploration strategy, each of which contributes fundamental benefits for the firm's success. Exploitation strategy attempts to obtain the maximum advantage from existing abilities, whereas exploration strategy searches for new ways for the organization to adapt. Further, since manufacturing markets are characterized by short product life, they require a high level of manufacturing flexibility, which can play a crucial role in the development of the exploitation and exploration strategies. This study analyses the relationship of manufacturing flexibility to exploitation and exploration strategies, taking into account an issue of maximum international scope: the implementation of ISO standards. In many international markets, ISO implementation is crucial in enabling organizations to be competitive. However, no consensus has been reached concerning the real benefits that these systems provide to the organizations that implement them. The main goal of our study is to analyse whether there are significant differences in the relationship of manufacturing flexibility to exploitation and exploration strategies in ISO 9001:2000 certified organizations and non-certified organizations. Our results show that most of the relationships analysed are only significant in ISO certified organizations. As an added value, the study analyses the relationship of exploitation and exploration strategies to organizational learning orientation and finds this relationship to be significant in all cases.

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Section: Exploration and Exploitation Strategies And Manufacturing Flmentioning

confidence: 99%

The relationship between exploration and exploitation strategies, manufacturing flexibility and organizational learning: An empirical comparison between Non-ISO and ISO certified firms

Tamayo-Torres

Gutiérrez

Moreno

2014

European Journal of Operational Research

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“…Although at first surprising, this finding is consistent with earlier results (3, 8) that slow or intermediate rates of learning in organizations result in higher long-run performance than fast rates. In both cases, the explanation is that slowing down the rate at which individuals learn, either from the "organizational code" (3) or from each other (8,11,13), forces them to undertake more of their own exploration, which, in turn, reduces the likelihood that the collective will converge prematurely on a suboptimal solution.Although this explanation is persuasive, the evidence is based largely on agent-based simulations (2,3,8,11,13,14), which necessarily make certain assumptions about the agents' behavior, and therefore could be mistaken in ways that fundamentally undermine the conclusions. In addition, one recent experiment involving real human subjects (12) found an advantage for inefficient networks in problem spaces requiring exploration.…”

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“…In many organizational contexts, the tradeoff between exploration and exploitation is affected by the presence of other problem solvers who are attempting to solve the same or similar problems, and who communicate with each other through some network of formal or informal social ties (5)(6)(7)(8)(9)(10). Intuitively, it seems clear that communication networks should aid collaborative problem solving by allowing individual problem solvers to benefit from the experience of others, wherein the faster good solutions are spread, the better off every problem solver will be.…”

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Collaborative learning in networks

Mason

Watts²

2011

Proc. Natl. Acad. Sci. U.S.A.

300

306

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Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for realworld problem solving and possible extensions.M any problems that arise in science, business, and engineering are "complex" in the sense that they require optimization along multiple dimensions, where changes in one dimension can have different effects depending on the values of the other dimensions. A common way to represent problem complexity of this nature is with a "fitness landscape," a multidimensional mapping from some choice of solution parameters to some measure of performance, where complexity is expressed by the "ruggedness" of the landscape (1, 2). A simple problem, that is, would correspond to a relatively smooth landscape in which the optimal solution can be found by strictly local and incremental exploration around the current best solution. By contrast, a complex problem would correspond to a landscape with many potential solutions ("peaks") separated by low-performance "valleys." In the event that the peaks are of varying heights, purely local exploration on a rugged landscape can lead to solutions that are locally optimal but globally suboptimal. The result is that when solving complex problems, problem solvers must strike a balance between local exploitation of already discovered solutions and nonlocal exploration for potential new solutions (3, 4).In many organizational contexts, the tradeoff between exploration and exploitation is affected by the presence of other problem solvers who are attempting to solve the same or similar problems, and who communicate with each other through some network of formal or informal social ties (5-10). Intuitively, it seems clear that communication networks should aid collaborative p...

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“…Many authors focus those definitions on their differences at the level of analysis: (1) differences in radical or incremental innovation at an individual and team level (Taylor & Greve, 2006); (2) differences in alliance function, structure and attribute across time and between domains (Lavie & Rosenkopf, 2006); (3) differences in level of learning at a team and organizational level (Beckman, 2006); and (4) differences in rate of learning at an individual and organizational level (Miller et al, 2006). Gonçalo João 3 Gupta et al (2006) identify four central questions which the academic researcher must clarify before engaging the research.…”

Section: Introductionmentioning

confidence: 99%

Exploitation or Exploration? The Intelligent Approach

João¹

2015

SMQ

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This paper discusses knowledge management strategies based on exploitation or exploration and the competitive intelligence perspective in the creation and sharing of knowledge. It establishes differences and similarities between knowledge management and competitive intelligence regarding the definition, creation, and use of knowledge and intelligence, and proposes a theoretical framework for organizations to choose their own knowledge management strategies.

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Adding Interpersonal Learning and Tacit Knowledge to March's Exploration-Exploitation Model

Cited by 240 publications

References 39 publications

The relationship between exploration and exploitation strategies, manufacturing flexibility and organizational learning: An empirical comparison between Non-ISO and ISO certified firms

The relationship between exploration and exploitation strategies, manufacturing flexibility and organizational learning: An empirical comparison between Non-ISO and ISO certified firms

Collaborative learning in networks

Exploitation or Exploration? The Intelligent Approach

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