Problem definition: Large language models (LLMs) are being increasingly leveraged in business and consumer decision-making processes. Because LLMs learn from human data and feedback, which can be biased, determining whether LLMs exhibit human-like behavioral decision biases (e.g., base-rate neglect, risk aversion, confirmation bias, etc.) is crucial prior to implementing LLMs into decision-making contexts and workflows. To understand this, we examine 18 common human biases that are important in operations management (OM) using the dominant LLM, ChatGPT. Methodology/results: We perform experiments where GPT-3.5 and GPT-4 act as participants to test these biases using vignettes adapted from the literature (“standard context”) and variants reframed in inventory and general OM contexts. In almost half of the experiments, Generative Pre-trained Transformer (GPT) mirrors human biases, diverging from prototypical human responses in the remaining experiments. We also observe that GPT models have a notable level of consistency between the standard and OM-specific experiments as well as across temporal versions of the GPT-3.5 model. Our comparative analysis between GPT-3.5 and GPT-4 reveals a dual-edged progression of GPT’s decision making, wherein GPT-4 advances in decision-making accuracy for problems with well-defined mathematical solutions while simultaneously displaying increased behavioral biases for preference-based problems. Managerial implications: First, our results highlight that managers will obtain the greatest benefits from deploying GPT to workflows leveraging established formulas. Second, that GPT displayed a high level of response consistency across the standard, inventory, and non-inventory operational contexts provides optimism that LLMs can offer reliable support even when details of the decision and problem contexts change. Third, although selecting between models, like GPT-3.5 and GPT-4, represents a trade-off in cost and performance, our results suggest that managers should invest in higher-performing models, particularly for solving problems with objective solutions. Funding: This work was supported by the Social Sciences and Humanities Research Council of Canada [Grant SSHRC 430-2019-00505]. The authors also gratefully acknowledge the Smith School of Business at Queen’s University for providing funding to support Y. Chen’s postdoctoral appointment. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0279 .

In this study, we examine the extent to which employees recognize the importance of information technologies and systems (IT/S) in developing and implementing environmental initiatives. To address this question, we first review past research on this topic and draw on a framework for examining environmental motivating forces, strategies, and employee environmental orientations. We then analyze qualitative data based on in-depth interviews with employees in financial services organizations. Our aim is to develop a richer understanding of how employees currently view IT/S issues in relation to environmental sustainability and if similarities exist between different types of financial institutions. We also assess the extent to which these employee perceptions align with both actual organizational practices, as captured in interviews with information technology managers, and practices espoused by organizations, as reflected on their corporate websites. Our findings suggest that organizations are still in the infancy stage of awareness and adoption of “Green” IT/S. As a result, we identify four types of gaps: knowledge gaps, practice gaps, opportunity gaps, and knowing—doing gaps. We suggest that future research should draw on absorptive capacity, organizational learning, and social marketing theories to help align employees’ attitudes, cognitions, and behaviors and to drive environmental changes.

Although information systems development (ISD) projects are critical to organizations and improving them has been the focus of considerable research, successful projects remain elusive. Focusing on the cognitive aspects of ISD projects, we investigate how and why mutual understanding (MU) among key stakeholder groups (business and information technology managers, users, and developers) changes within and across projects, and how it affects project success. We examine relationships among project planning and control mechanisms; sensegiving and sensemaking activities by, and MU among, these stakeholder groups; and project success. Combining deductive and inductive approaches for theory building, we develop an initial model based on the literature and then modify it based on the results of a longitudinal embedded mixed-methods study of 13 projects at 2 organizations over a 10-year period. The results provide insights into the development of MU within projects, including (1) how MU changes during projects as a result of cognitive activities (sensegiving and sensemaking); (2) how planning and control mechanisms (and the associated artifacts) affect these cognitive activities; (3) how MU, and achieving it early in the project, affects success; and (4) how stakeholder engagement (in terms of depth, scope, and timing) affects the relationships in (1) and (2). The results also indicate that project management mechanisms, stakeholder engagement, and MU may change (either improve or deteriorate) across projects, depending on the disagreements among stakeholders in previous projects, the introduction of new project elements in subsequent projects, and the reflection on previous projects.

Information system (IS) project alignment has been defined as the degree to which an IS's project deliverables are consistent with the project's objectives, which are shaped by the organization's IS strategy. These objectives may change as the project unfolds, reflecting emergent opportunities, limitations, and strategy (Jenkin and Chan, 2005). The IS project alignment process refers to the sequence and flow of events that lead to project alignment and, thus, strategy execution. To develop an understanding of project alignment processes – how IS projects become aligned or misaligned – this study examines nine projects across two organizational settings to analyze the key events and processes of project alignment. By analyzing three different project patterns using different organizational metaphors, this study explains evidence contradicting widely held beliefs about project management. Rather than planning and process maturity, the results of this study highlight the importance of executing processes, change, learning, knowing in practice, and heedful interrelating between project team members to align final project deliverables. This research, based on an empirical study, contributes to both the IS alignment and project management literatures by further developing the emerging concept of project alignment to include a process view of how to achieve alignment of final project deliverables with IS project objectives and the IS strategy.