An “ensemble” approach to decision-making involves aggregating the results from different decision makers solving the same problem (i.e., a division of labor without specialization). We draw on the ...literatures on machine learning-based Artificial Intelligence (AI) as well as on human decision-making to propose conditions under which human-AI ensembles can be useful. We argue that human and AI-based algorithmic decision-making can be usefully ensembled even when neither has a clear advantage over the other in terms of predictive accuracy, and even if neither alone can attain satisfactory accuracy in absolute terms. Many managerial decisions have these attributes, and collaboration between humans and AI is usually ruled out in such contexts because the conditions for specialization are not met. However, we propose that human-AI collaboration through ensembling is still a possibility under the conditions we identify.
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A common premise in prior research is that trust increases over time in relationships. Through a meta-analysis of 39 studies, we find that the bivariate correlation between trust and relationship ...duration (1) is on average positive and small, and (2) varies significantly across studies indicating the presence of unobserved moderators. We therefore build a theoretical framework to specify four different mechanisms—initial bias correction, change in relationship value, identification, and trust-based selection—that may affect the development of trust. We then argue that the relative strength of these mechanisms should influence whether trust increases, remains constant, or decreases over time.
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While many theories of the firm seek to explain when firms make rather than buy, in practice firms often make and buy the same input—they engage in plural sourcing. We argue that explaining the mix ...of external procurement and internal sourcing for the same input requires a consideration of complementarities across and constraints within modes of procurement. We create analytical foundations for making empirical predictions about when plural sourcing is likely to be optimal and why the optimal mix of internal and external sourcing may vary across situations. Our framework also proves useful for assessing the possible estimation biases in transaction level make-or-buy studies arising from ignoring complementarities and constraints.
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Rather than being passive observers and analysts of innovations in organizing, I argue that we can advance organizational science by prototyping and piloting new forms of organizing. While this may ...be a radical departure from our conventional ways of studying organizations, I believe that the return is worth the risk, particulary in a normatively oriented field like organizaion design. Equally important, recent conceptual and methodological advances actually make this possible.
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45.
Division of Labor Through Self-Selection Raveendran, Marlo; Puranam, Phanish; Warglien, Massimo
Organization science,
03/2022, Volume:
33, Issue:
2
Journal Article
Peer reviewed
Open access
Self-selection–based division of labor has gained visibility through its role in varied organizational contexts such as nonhierarchical firms, agile teams, and project-based organizations. Yet, we ...know relatively little about the precise conditions under which it can outperform the traditional allocation of work to workers by managers. We develop a computational agent-based model that conceives of division of labor as a matching process between workers’ skills and tasks. This allows us to examine in detail when and why different approaches to division of labor may enjoy a relative advantage. We find a specific confluence of conditions under which self-selection has an advantage over traditional staffing practices arising from matching: when employees are very skilled but at only a narrow range of tasks, the task structure is decomposable, and employee availability is unforeseeable. Absent these conditions, self-selection must rely on the benefits of enhanced motivation or better matching based on worker’s private information about skills, to dominate more traditional allocation processes. These boundary conditions are noteworthy both for those who study as well as for those who wish to implement forms of organizing based on self-selection.
We examine how groups differ from individuals in how they tackle two fundamental trade-offs in learning from experience—namely, between exploration and exploitation and between over- and ...undergeneralization from noisy data (which is also known as the “bias-variance” trade-off in the machine learning literature). Using data from an online contest platform (Kaggle) featuring groups and individuals competing on the same learning task, we found that groups, as expected, not only generate a larger aggregate of alternatives but also explore a more diverse range of these alternatives compared with individuals, even when accounting for the greater number of alternatives. However, we also discovered that this abundance of alternatives may make groups struggle more than individuals at generalizing the feedback they receive into a valid understanding of their task environment. Building on these findings, we theorize about the conditions under which groups may achieve better learning outcomes than individuals. Specifically, we propose a self-limiting nature to the group advantage in learning from experience; the group advantage in generating alternatives may result in potential disadvantages in the evaluation and selection of these alternatives.
Supplemental Material:
The online appendix is available at
https://doi.org/10.1287/orsc.2021.15239
.
How organization designs evolve between adaptation to changing conditions and the pressures toward persistence of the designs adopted at founding remains an understudied phenomenon. To fill this ...lacuna, we conducted a longitudinal, multicase study of eight young ventures. We find that, in these ventures, specific organization design
solutions
changed frequently, triggered by various internal and external developments, although the changes were typically incremental and myopic. However, the more abstract
principles
of design, captured in the founders’ logics of organizing, were less amenable to change. This explains why observations of imprinting effects in logics of organizing may be consistent with observations of dynamic change to organization designs.
Existing research suggests that in acquisitions of small technology-based firms by large established firms post-merger integration both enables and hinders acquirers' efforts to leverage the ...technology of acquired firms. This apparent paradex can be resolved once we account for the qualitatively distinct ways in which acquirers leverage technology acquisitions. Integration helps acquirers use the acquired firm's existing knowledge as an input to their own innovation processes (leveraging what they know), but hinders their reliance on the acquired firm as an independent source of ongoing innovation (leveraging what they do). We also show that experienced acquirers are better able to mitigate the disruptive consequences of the loss of autonomy entailed by integration, though we find no evidence that they achieve greater coordination benefits from integration.
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