Journal of Operations Management最新文献

We explore how organizations leverage algorithms to improve knowledge work in contexts where the tasks require skilled work, as distinct from routine tasks that have traditionally been the focus of academic enquiry. Drawing on a multiple-case study of four business areas in a multinational energy firm undergoing a digital transformation, we find that contrary to what the literature predicts, tasks that require skilled work can also benefit from the adoption of algorithmic solutions. To benefit, business areas engaged in two distinct pathways for transforming knowledge work. The first focuses on automating a specific task, replacing human activity with algorithms in a single task. The second involves re-engineering an entire process, whereby sequences of steps adjacent to the task at hand are redesigned on integration of an algorithm. We find that these pathways have different effects on the ability to improve knowledge work, suggesting that alignment between the task and the pathway chosen is crucial to realizing any improvement. We also find that the ability to sustain any improvement depends on the adjustment of the knowledge regime—the practices and structures that sanction knowledge. Building on these findings, we propose a general process model for the adoption of algorithmic solutions in knowledge work. In the wider context of the future of work debate, our findings challenge the prevailing notion that a task's skill requirements determine the extent to which knowledge work can be improved by algorithmic solutions.

With the increasing digitization and networking of medical data and personal health information, information security has become a critical factor in vendor selection. However, limited understanding exists regarding how information security influences vendor selection. Drawing from the attention-based view (ABV), this study examines the potential impact of data breaches on hospitals' selection of electronic medical record system (EMRS) vendors. To test our hypotheses, we compile a unique dataset spanning 12 years of observations from US hospitals. Utilizing a coarsened exact matching (CEM) technique combined with a difference-in-differences (DiD) approach, our study shows that hospitals tend to replace their EMRS vendors after experiencing data breaches. Moreover, breached hospitals tend to prioritize information security in such a vendor replacement process by switching to star vendors and migrating towards a single-sourcing configuration. Further post-hoc analyses reveal that these impacts of data breaches are mitigated as the relationship between breached hospitals and vendors matures or when hospitals belong to large healthcare systems. Additionally, we find that the effects of data breaches are contingent on the scale of the breach and are short-term in nature. This research underscores the significance of information security as a crucial consideration in vendor selection for both academia and practitioners.

This research investigates growth inhibitors for smart services driven by condition-based maintenance (CBM). Despite the fast rise of Industry 4.0 technologies, such as smart sensoring, internet of things, and machine learning (ML), smart services have failed to keep pace. Combined, these technologies enable CBM to achieve the lean goal of high reliability and low waste for industrial equipment. Equipment located at customers throughout the world can be monitored and maintained by manufacturers and service providers, but so far industry uptake has been slow. The contributions of this study are twofold. First, it uncovers industry settings that impede the use of equipment failure data needed to train ML algorithms to predict failures and use these predictions to trigger maintenance. These empirical settings, drawn from four global machine equipment manufacturers, include either under- or over-maintenance (i.e., either too much or too little periodic maintenance). Second, formal analysis of a system dynamics model based on these empirical settings reveals a sweet spot of industry settings in which such inhibitors are absent. Companies that fall outside this sweet spot need to follow specific transition paths to reach it. This research discusses these paths, from both a research and practice perspective.

When making decisions about their commitments to environmental practices and performance, suppliers face heterogenous institutional logics and their diverse prescriptions for action. How do suppliers respond to such institutional complexity? We examine this question in the context of suppliers' voluntary public environmental disclosures (disclosure). Specifically, our study assembles a unique panel data set of global manufacturing suppliers and their annual contractual relationships with buyers. Building on the institutional logics perspective and the sustainable supply network literature, we hypothesize that suppliers selectively mimic the disclosure of their buyers by following market, corporate, and sustainability logics. Our study contributes to the institutional logics perspective and the sustainable supply network literature by indicating that in the context of disclosure, market and sustainability logics both actively shape suppliers' responses to institutional complexity. Furthermore, we find support for mimicry as a mechanism of buyer influence that can lead to disclosure heterogeneity across suppliers even when they follow the same logic, which opens new avenues for research. Our findings can be leveraged by buyers, policymakers, and other stakeholders interested in advancing transparency and sustainability in supply networks.

Disasters affect hundreds of millions of people every year and the response of governments is crucial in alleviating the suffering of those affected. Despite the importance of contracting in response to disasters, research on this topic is conspicuous by its absence. This paper begins to address this gap by investigating the choice of procurement contract type by US federal agencies during disaster management operations. The research relies on 47,560 contracts issued by the US federal government in response to 14 major disasters between 2005 and 2016. We build on agency theory to investigate the choice of the contract type made by federal agencies at the different stages of a relief operation. This research provides empirical evidence of the key factors underpinning the choice of contract in the context of disaster management, namely the amount of spend per contract and the type of acquisition (product or service), and reveals the moderating role of the stage of the relief operation.

Appointing individuals drawn from suppliers and customers to a firm's board of directors is an increasingly popular practice that can enhance the interorganizational relationship and generate relational rents. Yet, such board members may act in the best interest of their primary employer rather than the shareholders of the firm whose board they serve on, thus creating potential agency conflicts. Drawing on the relational view and agency theory, we explore the tension between rent generation and agency costs and consider how a firm can design governance mechanisms to effectively leverage customer or supplier representation on the board of directors. The associated hypotheses are tested using a large panel dataset constructed from multiple archival sources, and our findings suggest that supplier and customer board members are a double-edged sword: While they generate value in some instances, they can also be associated with lower performance depending on the levels of two key governance mechanisms—the number of inside directors on the board and the proportion of outcome-based board member compensation.

This research examines the impact of leader disability status on the operational performance of teams that include individuals with disabilities (IWD) using longitudinal micro-data from an apparel manufacturing company in a competitive integrative employment environment. To aid in developing the research hypotheses and in interpreting the empirical findings, the quantitative analysis is complemented with qualitative data collected through interviews involving managers and workers with and without disabilities at the focal firm and two other large companies that employ IWD. A beneficial moderating effect of leader-worker disability status similarity on team performance is hypothesized and subsequently tested using Prais-Winsten regression. The results show that a leader with a disability has a potentially beneficial impact on team performance as the number of workers with disabilities in the team increases, resulting in improved productivity (measured in labor hours per garment) and quality (measured in operator defects per garment). The theoretical, managerial, and policy implications of the study provide actionable insights for the creation of an inclusive labor force.

As the US healthcare system transitions from volume to value, various value-based programs tie medical reimbursements to hospital performance relative to national top performers (i.e., benchmarks). However, prior studies report very limited results on how such benchmarks affect care delivery and patient outcomes across multiple performance fronts. This study examines how general acute care hospitals progress toward benchmarks measured by performance frontiers in technical efficiency, clinical quality, and patient experience over time, subjecting to external market conditions and internal focuses. Based on a panel dataset comprising hospitals in California from 2012 and 2019, our results find support for competitive-distance-driven progression rates, suggesting that hospitals' competitive positions measured by their distances to benchmarks drive performance improvements. Yet, the effect diminishes as they move closer to performance frontiers. In addition, we find that market competition reduces the progression rate of technical efficiency. Finally, our results also suggest that focus improves performance progression rates, yet its effects are curvilinear.

The increased digitalization of shop floors has provided unprecedented opportunities for real-time sharing of process and resource details. Visualization boards (VBs), which provide ubiquitous technology-enabled renderings of such details, salient to a local shop-floor setting, have the potential to play a significant role in this regard. Critical to the effectiveness of this role is the fit between VB design and shop-floor needs. In our study, we apply task-technology-fit theory in case examinations focused on identifying mismatch, implications of mismatch, and putative best practices in designs for future interventions. Our assessment capitalizes on both core operations management design principles as well as technology management design principles. We develop grounded propositions regarding guidelines that should be applied in future VB designs and deployments.