Knowledge that Transforms

We study the incentives of a group of retailers, organized as a trade association and sourcing the product from a single manufacturer, to exchange private forecast information. We compare two widely used policies by the trade association in practice: exclusionary information exchange and non‐exclusionary information exchange. Under the exclusionary policy, only retailers who contribute their private information are exposed to the pool of shared information, whereas under the non‐exclusionary policy, all of the members of the trade association are exposed to the pool of shared information regardless of any contribution to this pool. We show that when the wholesale price is exogenous, the retailers have an incentive to share information under both policies. However, when the manufacturer is aware of the exchange of information among the retailers, she sets the wholesale price more aggressively, even without being exposed to the actual shared information. This wholesale pricing effect reduces the retailers' incentives to share information to such extent that under the non‐exclusionary policy, no information is shared in equilibrium. Under the exclusionary policy, it is possible to reach a full information‐sharing equilibrium, but this equilibrium can make the retailers worse‐off compared with the case in which no information is shared. Furthermore, it is also possible for the manufacturer to become worse‐off when the retailers share information. We also discuss the effect of market size on the incentives of the retailers to exchange information and how by committing to a certain wholesale price level early, the manufacturer can induce the retailers to exchange information.

Sourcing from multiple suppliers with different characteristics is common in practice for various reasons. This paper studies a dynamic procurement planning problem in which the firm can replenish inventory from a fast and a slow supplier, both with uncertain capacities. The optimal policy is characterized by two reorder points, one for each supplier. Whenever the pre‐order inventory level is below the reorder point, a replenishment order is issued to the corresponding supplier. Interestingly, the reorder point for the slow supplier can be higher than that of the fast even if the former has a higher cost, lower reliability, and smaller capacity than the latter, suggesting the possibility of ordering exclusively from an inferior slow supplier in the short term. Moreover, the firm may allocate a larger portion of the long‐term total order quantity to the slow supplier than to the fast, even if the former does not possess any cost or reliability advantage over the latter. Such phenomena, different from the observations made in previous studies, happen when the demand is uncertain and the supply is limited or unreliable. Our observations highlight the importance of incorporating both demand uncertainty and supplier characteristics (i.e., cost, lead time, capacity and uncertainty) in a unified framework when formulating supplier selection and order allocation strategies.

We present a framework to describe and analyze operational risk in financial services from an operations management perspective, focusing in particular on process design, process management, and human behavior aspects. The financial services industry differs from other service industries in ways that affect the nature of the operational risks it is subject to. In recent decades, many books and papers have focused on operational risk in financial services; however, this literature has focused mainly on the conceptual and statistical aspects of operational risk management and not on its operational aspects. Operational risk in financial services has not received much attention from the operations management community. The framework presented here is based on the premise that operational risk in financial services can reap significant benefits from research done in the theory and practice of operations management in manufacturing industries as well as in other services industries. The objective of this study is to propose particular challenges and questions raised in the practice of operational risk management that may stimulate future research in this particular area of operations management.

The current state of outpatient healthcare delivery is characterized by capacity shortages and long waits for appointments, yet a substantial fraction of valuable doctors’ capacity is wasted due to no‐shows. In this study, we examine the effect of wait to appointment on patient flow, specifically on a patient's decision to schedule an appointment and to subsequently arrive to it. These two decisions may be dependent, as appointments are more likely to be scheduled by patients who are more patient and are thereby more likely to show up. To estimate the effect of wait on these two decisions, we introduce the willingness to wait (WTW), an unobservable variable that affects both bookings and arrivals for appointments. Using data from a large healthcare system, we estimate WTW with a state‐of‐the‐art non‐parametric method. The WTW, in turn, allows us to estimate the effect of wait on no‐shows. We observe that the effect of increased wait on the likelihood of no‐shows is disproportionately greater among patients with low WTW. Thus, although reducing the wait to an appointment will enable a provider to capture more patient bookings, the effects of wait time on capacity utilization can be non‐monotone. Our counterfactual analysis suggests that increasing wait times can sometimes be beneficial for reducing no‐shows.

We study the funds allocation problem for a resource‐constrained non‐profit organization (NPO) that implements social development projects for public good. In addition to raising funds from donors who contribute prior to project implementation (“traditional donors”), the NPO uses a novel approach, which we term as the “ex‐post funding” approach, to also raise funds from donors who contribute based on the results delivered by the NPO (“ex‐post donors”). In this approach, the NPO uses its initial funds to implement early phases of the project, creates “results‐certificates” from the completed phases, and invites ex‐post donors to purchase these certificates. The donations raised from selling the results‐certificates are used to recover the NPO's own funds used in the project implementation. Operationalizing this approach is complicated when the project must incur a large fixed cost before any benefits are delivered by the project and the total benefit delivered is time sensitive. We show that for a given amount of initial funds available, there exists a threshold amount of funds that the NPO should raise from traditional donors before implementing the project phases so as to maximize the total expected benefit delivered. Through numerical studies, we analyze how the threshold of funds raised from traditional donors and the total benefit delivered vary with donor characteristics such as donor willingness to give and the proportion of donors who contribute prior to project implementation. Our numerical studies suggest that even with relatively small amount of initial funds, the NPO can deliver substantially higher benefit by using the ex‐post funding approach when compared to using a traditional approach that requires the NPO to raise all the funds required upfront.

Behavioral Operations Management explicitly considers the effects of human behavior in process performance, influenced by cognitive biases, social preferences, and cultural norms. This broadening of Operations is even more critical in the context of the Management of Technology (MOT) than in the operations of established ongoing processes, because in innovation, people do not know well which tasks they will have to perform, they are exposed to risks, and they are subject to emergent interdependencies, all of which push psychological biases and social preferences to the fore. This article gives an overview of important behavioral challenges in MOT, setting them in the context of the phases of the stage gate process on the one hand, and the three levels of individual biases, group member interactions, and large group interactions (e.g., culture) on the other hand. The review suggests that previous work has not addressed a number of important questions in empirical effects and theoretical underpinnings, gaps that are very important for the performance of organizations in practice. The article concludes by offering opportunities for high‐impact future work.

In today's increasingly globalized environment, more and more companies recognize the mutual dependence of supply chain partners in value creation. When making business decisions, they take into consideration their partners’ bottom line profitability, especially in emerging markets. The question is, is this kind of practice sustainable? This study makes an attempt to formalize this issue by examining a stylized two‐party supply chain model in which each player maximizes its own profit while making a certain commitment to its partner. We compare five different games between the two supply‐chain partners, which reflect different power positions of the players and different levels of commitment. We identify conditions under which both players are better off with mutual commitments than without, a situation we call win–win. We show that win–win can be achieved if and only if the mutual commitments are comparable. Thus, the recognition of mutual dependence of the supply chain members needs to be translated into reciprocal concerns. In addition, different players’ commitments play different roles but together they have a similar effect as a profit sharing contract. Finally, we discuss the implications of our findings in the context of socially responsible operations. In particular, our analyses show that it is possible to care about the supply chain partners’ bottom line without sacrificing one's own profitability, and our models can be used as a tool to determine the commitment levels by evaluating the predicted outcome.

This paper studies two‐stage lot‐sizing problems with uncertain demand, where lost sales, backlogging and no backlogging are all considered. To handle the ambiguity in the probability distribution of demand, distributionally robust models are established only based on mean‐covariance information about the distribution. Based on shortest path reformulations of lot‐sizing problems, we prove that robust solutions can be obtained by solving mixed 0‐1 conic quadratic programs (CQPs) with mean‐risk objective functions. An exact parametric optimization method is proposed by further reformulating the mixed 0‐1 CQPs as single‐parameter quadratic shortest path problems. Rather than enumerating all potential values of the parameter, which may be the super‐polynomial in the number of decision variables, we propose a branch‐and‐bound‐based interval search method to find the optimal parameter value. Polynomial time algorithms for parametric subproblems with both uncorrelated and partially correlated demand distributions are proposed. Computational results show that the proposed models greatly reduce the system cost variation at the cost of a relative smaller increase in expected system cost, and the proposed parametric optimization method is much more efficient than the CPLEX solver.

On a daily basis, thousands of employees suffer from severe occupational accidents worldwide. These accidents not only lead to negative consequences for the physical and mental health of employees, but also to high costs for companies and the society as a whole. A large share of these accidents take place in warehouses. Prior research has demonstrated the critical role of leadership, and especially safety‐specific transformational leadership (SSTL), in reducing warehouse accidents. Yet several important questions concerning SSTL remain: What effects does SSTL have on outcomes other than safety, and what determines whether leaders display SSTL behaviors? To answer these questions, this research studies the relationship between SSTL of warehouse managers and not only occupational accidents, but also quality and productivity. Moreover, it investigates the managers who are most likely to display SSTL. Data from 87 warehouse managers and 1233 employees were used to test the conceptual model. The results suggest that the dispositional prevention focus of the manager (one of two possible motivational strategies that people deploy) positively relates to SSTL, and that SSTL negatively relates to occupational accidents. Furthermore, SSTL and its identified negative relationship with occupational accidents does not appear to have detrimental impact on productivity or quality. These results extend existing models of SSTL and safety, and can help companies to reduce the number of accidents and the associated costs by selecting and developing safety‐specific transformational leaders.

In humanitarian operations, the amount of funding received and the timing and predictability of funding strongly influence program performance. In this paper, we study the problem of allocating inventory procured using donor funding to patients in different health states over a finite horizon with the objective of minimizing the number of disease‐adjusted life periods lost. The funding received and the number of new patients of different health states entering the program in every period could be unpredictable and hence, resource allocation and rationing assume significance in this setting. We use a stochastic dynamic programming model with financial constraints to analyze the inventory allocation problem. We demonstrate that the optimal allocation policy is state dependent, provide analytical results regarding the impact of funding timing and funding variability in our problem context, and develop two heuristics for the inventory allocation problem. Our computational study indicates that the two heuristics perform reasonably well against the full information lower bound (roughly 5% gap on average) and in many instances, they offer significant benefits over the first‐come‐first‐serve heuristic frequently used in practice. We also provide computational insights regarding the impact of funding timing and funding level on program performance. Our analysis indicates that for short planning horizons (up to 4 periods), receiving additional funding is beneficial even if the funding is delayed while for medium to long planning horizons, there exist situations where receiving less overall funding in a timely manner might be better than receiving more total funding in a delayed fashion.