Journal of Operations Management最新文献

We investigate the impact of performance feedback delivered to front-line workers through new digital technologies in the manufacturing sector. Our study takes place in a globally operating manufacturing company that employs smartwatches for real-time control on the shop floor. In a large-scale and multi-site field experiment, we examine 29,669 machine status reports to assess the productivity effects of providing near real-time feedback to workers via smartwatches. We develop our hypotheses drawing on construal-level theory and its central idea of psychological distance. Initially, we observe production without feedback to establish comparability between treatment groups. Subsequently, we allocate various combinations of feedback to workers in four separate areas in two manufacturing plants. We manipulate whether the feedback is targeted at individuals with psychologically close feedback (“you did…”) or targeted at the team with relatively psychologically distant feedback (“your team did…”). Furthermore, we vary the message framing: positive framing emphasizes completed tasks, while negative framing emphasizes unfinished tasks. Our findings indicate that positively framed feedback, targeting individuals directly, enhances productivity more than other feedback combinations. Our study contributes new theoretical insights into the interplay between feedback framing and targets in fast-paced and highly automated batch production environments.

The use of part-time employees to support operations has been a contentious topic in the literature. While part-time employees add cost-effective flexibility to operations, their impact on operational outcomes has largely been documented as negative. However, there are a number of sectors (e.g., non-profit) which rely heavily on part-time employees, with anecdotal evidence supporting their role in improving outcomes. Through this research, we seek to shed light on these contradicting perspectives. We do so by investigating the impact of the percentage of part-time employees in the workforce dedicated to the Supplemental Nutrition Assistance Program (SNAP) outreach efforts at United States (U.S.) food banks on the effectiveness of this initiative. SNAP is the largest domestic hunger program in the U.S., assisting over 42 million individuals, and food banks play a critical role in outreach and enrollment for SNAP. We utilize data on the operational characteristics and SNAP activities of food banks that are members of the Feeding America network and U.S. Census data on the demographic characteristics of their service area. We find that an increased percentage of part-time FTEs (full-time equivalent) in a food bank's workforce dedicated to SNAP outreach efforts increases its effectiveness, particularly in relation to operational and contextual factors that can benefit from a more flexible workforce. Based on these findings and our review of the literature, we propose a conceptual framework on the effectiveness of part-time employees in different settings.

This study empirically examines how induced learning through adopting a set of best practices and learning-by-doing improved a hospital's care of ischemic stroke patients using ad hoc teams. While previous studies in healthcare operations management conducted in ad hoc team environments predominantly focused on volume-based learning (learning by doing, team familiarity via interactions among team members), our study focuses on induced learning in ad hoc teams through best practice adoptions. The analysis uses secondary data (Data period: January 2009–March 2017) about stroke patients from a comprehensive stroke center (CSC) in a U.S. tertiary teaching hospital as it adopted the U.S. American Heart Association/American Stroke Association (AHA/ASA) Target:Stroke best practices. The ad hoc stroke teams provide the initial care and their performance is measured using “Door-to-Needle (DTN)” time and its sub-time segments. The DTN time is measured as the time elapsed between the stroke patient's arrival at the hospital's emergency department (ED) and the appropriate infusion of “Tissue Plasminogen Activator (TPA)” (i.e., a thrombolytic medication informally referred to as a “clot buster”). We found that adopting these best practices improved ischemic stroke care beyond improvement due to repetition. We also found that the neurologist's recent experience providing stroke care for the prior patient is positively associated with meeting the time performance goal for the current patient. This study provides insights into the use of management mechanisms to adopt and sustain best practices in healthcare that are generalizable to other organizations with ad hoc team environments.

Can productivity improve if workers identify more with the skills they use in their work environment? This paper reports the results of an experimental design that was peer-reviewed prior to collecting data. The research setting is a global manufacturer using a novel smartwatch-based system for distributing work tasks among factory floor workers. Drawing on the concepts of identification and helping in organizations, we hypothesized that fostering workers' identification with their own skills could serve as a mechanism to enhance helping behavior on the factory floor, which should improve productivity. We designed a compound skill-fostering treatment consisting of communication, meetings, and exercises regarding individual skills. We treat one large factory area for 2 weeks and keep a similar area in a sister factory as a control group for comparison in a difference-in-difference model. The results show that nudging skill identification increases workers' identification with skills, but we do not find evidence for increased helping behavior or increased productivity. Our results help develop theory around multiple sub-identities and provide guidance for future studies seeking to enhance identification in organizations.

Numerous studies on corporate social responsibility (CSR) indicate that firms adopt CSR practices for various reasons related to their supply chain. However, the necessity to conform to a firm's own industry CSR norm is overlooked. Conforming to one's industry CSR norm—a herding behavior known as CSR conformity—ensures firm in-group legitimacy and preserves internal resources for core business activities. On the other hand, deviating from industry norms sets a firm apart from its peers, making the firm more appealing to supply chain partners. Motivated by this dilemma, this study draws on middle-status conformity theory and explores how a firm's network prominence determines its CSR conformity. Panel data analyses of 1650 firm-year observations reveal an inverse U-shaped relationship between firm network prominence and its CSR conformity, indicating that firms with a mid-level network prominence engage in higher CSR conformity. However, the inverse U is flattened when a firm's supply chain partners (and their respective industries) share similar CSR standards, suggesting that a firm can only prioritize its own industry CSR norms if its supply chain partners share a compatible CSR standard. These findings highlight the importance of understanding CSR from an organizational conformity perspective, especially in the context of supply chain network.

Climate change, primarily driven by greenhouse gas emissions (GHGs), is a pressing environmental and societal concern. Carbon neutrality, or net zero, involves reducing carbon dioxide emissions, the most common GHG, and then balancing residual emissions through removing or offsetting. Particularly difficult challenges have emerged for firms seeking to reduce emissions from Scope 1 (internal operations) and Scope 3 (supply chain). Incremental changes are very unlikely to meet the objective of carbon neutrality. Synthesizing a framework that draws together both the means of achieving carbon neutrality and the scope of change helps to clarify opportunities for research by operations management scholars. Companies must assess and apply promising technologies, form new strategic relationships, and adopt novel practices while taking into account costs, risks, implications for stakeholders, and, most importantly, business sustainability. Research on carbon neutrality is encouraged to move beyond isolated discussions focused on specific tactics and embrace a more, though not fully, holistic examination. Research opportunities abound in both theoretical and empirical domains, such as exploring tradeoffs between different tactics, balancing portfolios, and investigating the strategic deployment of initiatives over time. As a research community, we are critically positioned to develop integrative insights at multiple levels, from individual processes to horizontal and vertical partnerships and ultimately to large-scale systemic realignment and change.

Research at the interface of operations management (OM) and gender bias has mostly focused on operational outcomes such as hiring decisions on behalf of the employer (or firm). Largely overlooked is how the design of operational processes exacerbates (or diminishes) the amount of gender bias exhibited on behalf of the customer in a people-centric operations environment. In this study, we conduct a randomized field experiment with a partner firm to assess gender mismatch and bias in client-consultant exchanges. The experimental design enables us to examine gender bias within dyadic exchanges when there are gender matches (female client-female consultant or male client-male consultant) or gender mismatches (female client-male consultant or male client-female consultant). We find that reporting the consultant's gender significantly increases the client's likelihood of leaving more and higher reviews, increases the clickthrough rate on recommended products, and that the effect is stronger for females than for male consultants. We also provide support for the heterogenous effects of client experience depending on the gender (mis)match in client-consultant exchanges, including whether the prior effects hold when there is gender masking or manipulation (e.g., reported female consultant when actually male). Our findings offer important theoretical contributions and practical implications for OM scholars and managers.

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.