{"title":"Differentiation and Integration in Organizational Learning: A Garbage Can Model","authors":"Sangyoon Yi, Nils Stieglitz, T. Knudsen","doi":"10.1108/S0742-332220180000040006","DOIUrl":null,"url":null,"abstract":"Abstract \nIn this study, the authors unpack the micro-level processes of knowledge accumulation (experiential learning) and knowledge application (problem solving) to examine how task allocation structures influence organizational learning. The authors draw on untapped potential of the classical garbage can model (GCM), and extend it to analyze how restrictions on project participation influence differentiation and integration of organizational members’ knowledge and consequently organizational efficiency in solving the diverse, changing problems from an uncertain task environment. To isolate the effects of problem or knowledge diversity and experiential learning, the authors designed three simulation experiments to identify the most efficient task allocation structure in conditions of (1) knowledge homogeneity, (2) knowledge heterogeneity, and (3) experiential learning. The authors find that free project participation is superior when the members’ knowledge and the problems they solve are homogenous. When problems and knowledge are heterogeneous, the design requirement is on matching specialists to problem types. Finally, the authors found that experiential learning creates a dynamic problem where the double duty of adapting the members’ specialization and matching the specialists to problem types is best solved by a hierarchic structure (if problems are challenging). Underlying the efficiency of the hierarchical structure is an adaptive role of specialized members in organizational learning and problem solving: their narrow but deep knowledge helps the organization to adapt the knowledge of its members while efficiently dealing with the problems at hand. This happens because highly specialized members reduce the necessary scope of knowledge and learning for other members during a certain period of time. And this makes it easier for the generalists and for the organization as a whole, to adapt to unforeseen shifts in knowledge demand because they need to learn less. From this nuanced perspective, differentiation and integration may have a complementary, rather than contradictory, relation under environmental uncertainty and problem diversity.","PeriodicalId":46550,"journal":{"name":"Advances in Strategic Management-A Research Annual","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/S0742-332220180000040006","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Strategic Management-A Research Annual","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/S0742-332220180000040006","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 3
Abstract
Abstract
In this study, the authors unpack the micro-level processes of knowledge accumulation (experiential learning) and knowledge application (problem solving) to examine how task allocation structures influence organizational learning. The authors draw on untapped potential of the classical garbage can model (GCM), and extend it to analyze how restrictions on project participation influence differentiation and integration of organizational members’ knowledge and consequently organizational efficiency in solving the diverse, changing problems from an uncertain task environment. To isolate the effects of problem or knowledge diversity and experiential learning, the authors designed three simulation experiments to identify the most efficient task allocation structure in conditions of (1) knowledge homogeneity, (2) knowledge heterogeneity, and (3) experiential learning. The authors find that free project participation is superior when the members’ knowledge and the problems they solve are homogenous. When problems and knowledge are heterogeneous, the design requirement is on matching specialists to problem types. Finally, the authors found that experiential learning creates a dynamic problem where the double duty of adapting the members’ specialization and matching the specialists to problem types is best solved by a hierarchic structure (if problems are challenging). Underlying the efficiency of the hierarchical structure is an adaptive role of specialized members in organizational learning and problem solving: their narrow but deep knowledge helps the organization to adapt the knowledge of its members while efficiently dealing with the problems at hand. This happens because highly specialized members reduce the necessary scope of knowledge and learning for other members during a certain period of time. And this makes it easier for the generalists and for the organization as a whole, to adapt to unforeseen shifts in knowledge demand because they need to learn less. From this nuanced perspective, differentiation and integration may have a complementary, rather than contradictory, relation under environmental uncertainty and problem diversity.
期刊介绍:
Advances in Strategic Management is dedicated to communicating innovative, new research that advances theory and practice in Strategic Management. The domain of the series encompasses, but is not limited to, corporate and business unit strategy, strategic organization and process, alliances and networks, and competitive dynamics. The series is committed to expanding the scope of Strategic Management theory and analysis and enriching practice by: -Encouraging multitheoretical approaches that span multiple social science disciplines -Welcoming papers using a diversity of innovative research methods -Creating focused volumes that explore in depth promising new research directions, consolidate research streams, and address significant current theoretical and practical problems.