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92 records from EconBiz based on author Name
1. Expanding the organizational design space : the emergence of AI robot bosses
Burton, Richard M.; Obel, Børge; Håkonsson, Dorthe Døjbak;2024
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link 2. Using old theories to find novel solutions in organizational design of large established firms
Obel, Børge; Gurkov, Igorʹ B.;2023
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
3. Strategic orientation of the firm towards its stakeholders and inclination towards sustainability : the conceptual framework
Obel, Børge; Gurkov, Igorʹ B.;2023
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link Link
4. New trends in organization design
Burton, Richard M.; Håkonsson, Dorthe Døjbak; Larsen, Erik R.; Obel, Børge;2020
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link Link Citations: 2 (based on OpenCitations)
5. Designing a sustainable organization : the four I's framework
Obel, Børge; Kallehave, Pernille;2022
Type: Aufsatz in Zeitschrift; Article in journal;
Availability:
Link 6. The science of organizational design : fit between structure and coordination
abstractOrganization design is a major factor determining an organization’s performance and how the people work together in these organizations. In the paper, we argue that designing organizations should be scientific-based and forward-looking. This raises challenges in designing organizations in contexts and situations that are new and have not been seen before. Experimentation of what is and what might be is the basis for exploring and examining what makes a good science for organizational design. Experimentation permits us to examine what might be for organization designs, which are not well understood or may not exist yet. Collaborative communities, new ventures, agile organizations, and temporary organizations are examples; experimentation permits us explore and examine what is and what might be and to examine the organizational design problem and perform experiments to understand the relationship between structure and coordination mechanisms of information, communications, decisions, trust, and incentives-the basis for the multi-contingency theory of organizational design.An organizational design must specify the fit between the structure of division of tasks in the organization with its coordination, or how to make these tasks work in concert. These tasks can be interdependent and uncertain. To design good organizations, we need empirical evidence about what is and exploration about what might be; we need a good theoretical basis for being able to generalize our knowledge. To illustrate our point, we examine two experiments on the classic M-form hypothesis-a computer simulation that examines coordination, organization structure, and interdependency and a laboratory experiment that examines the effect of incentives on opportunism and performance. Together, we find that the M-form is a robust organizational design, but with contingent conditions.Finally, we discuss how observation and experimentation together is the foundation for the development of scientific-based theory of organizational design.
Burton, Richard M.; Obel, Børge;2018
Type: Aufsatz in Zeitschrift; Article in journal;
Availability: Link
Link Citations: 64 (based on OpenCitations)
7. Forming a collaborative community : an agent-based simulation study of the effects of membership somposition
Obel, Børge; Håkonsson, Dorthe Døjbak; Snow, Charles C.; Bach, Lars A.;2019
Type: Aufsatz im Buch; Book section;
Availability: Link
8. New trends in organization design
Burton, Richard M.; Håkonsson, Dorthe Døjbak; Larsen, Erik Reimer; Obel, Børge;2020
Type: Article;
Availability:
Link Citations: 2 (based on OpenCitations)
9. The Science of Organizational Design : Fit Between Structure and Coordination
abstractOrganization design is a major factor determining an organization's performance and how the people work together in these organizations. In the paper, we argue that designing organizations should be scientific-based and forward-looking. This raises challenges in designing organizations in contexts and situations that are new and have not been seen before. Experimentation of what is and what might be is the basis for exploring and examining what makes a good science for organizational design. Experimentation permits us to examine what might be for organization designs, which are not well understood or may not exist yet. Collaborative communities, new ventures, agile organizations, and temporary organizations are examples; experimentation permits us explore and examine what is and what might be and to examine the organizational design problem and perform experiments to understand the relationship between structure and coordination mechanisms of information, communications, decisions, trust, and incentives — the basis for the multi-contingency theory of organizational design.An organizational design must specify the fit between the structure of division of tasks in the organization with its coordination, or how to make these tasks work in concert. These tasks can be interdependent and uncertain. To design good organizations, we need empirical evidence about what is and exploration about what might be; we need a good theoretical basis for being able to generalize our knowledge. To illustrate our point, we examine two experiments on the classic M-form hypothesis — a computer simulation that examines coordination, organization structure, and interdependency and a laboratory experiment that examines the effect of incentives on opportunism and performance. Together, we find that the M-form is a robust organizational design, but with contingent conditions.Finally, we discuss how observation and experimentation together is the foundation for the development of scientific-based theory of organizational design
Burton, Rich; Obel, Borge;2019
Availability: Link
10. The Validity of Computational Models in Organization Science : From Model Realism to Purpose of the Model
abstractComputational models are widely applied to address fundamental and practical issues in organization science. Yet, computational modeling in organization science continues to raise questions of validity. In this paper, we argue that computational validity is a balance of three elements: the question or purpose, the experimental design, and the computational model. Simple models which address the question are preferred. Non-simple, imbalanced computational models are not only inefficient but can lead to poor answers. The validity approach is compared with well-known validity criteria in social science. Finally we apply the approach to a number of computational modeling studies in organization science, beginning with Cyert's. They were pioneering and are examples of well designed computational models
Burton, Rich; Obel, Borge;2019
Availability: Link
