AbstractOur research investigates a joint inventory replenishment and pricing problem, where a seller controls the price of a leading product while restocking for all the products. We demonstrate that the seller's expected value functions present an structure, recommending an optimal order‐up‐to inventory‐level and list‐price policy. Our findings reveal divergent economic relationships between products from the seller's and customer's perspectives, suggesting managers broaden their strategies beyond customer viewpoints. We extend the pricing and inventory analysis to scenarios involving three substitute products under both price and inventory control. In these situations, we further reveal that sellers and customers uniformly view product inventories as substitutes, and the corresponding value functions are submodular and mutually diagonally dominant.

AbstractCompanies have increasingly used supply chain financing instead of bank financing when engaging with financially constrained suppliers. We investigate the effectiveness of different financing mechanisms at supporting supply chain responsibility. We consider a decentralized supply chain where a buyer sources from a financially constrained supplier who borrows from either a bank or the buyer to finance his production. The buyer audits the supplier for responsibility compliance and will refuse to accept and pay for the order if the supplier fails the audit. We find that under conventional bank financing, the bank is concerned with the supplier's audit failure and will raise the interest rate. This not only hinders the supplier's compliance effort but also hurts the profitability of every stakeholder. In contrast, under buyer financing, the buyer may offer the supplier a low interest rate to motivate him to be more compliant when the supplier's collateral is of low value. However, if the supplier's collateral is of high value, the buyer may be tempted to set a high interest rate to exploit the supplier—leading to a reduction in supplier's compliance and supply chain profitability. Thus, we conclude that buyer (bank) financing is more preferable for encouraging responsibility when the supplier has low (high) collateral. Our findings suggest that buyer financing may not always be an effective approach for encouraging supply chain responsibility. As such, we propose an alternative mechanism under which the buyer offers a reward to the supplier if he passes the audit while the supplier continues to borrow from a bank. We prove that this combination of bank financing and buyer reward always improves the compliance level and in most cases increases the total supply chain profit. It is even more effective than buyer financing in encouraging responsibility especially when the supplier's collateral is of low value.

AbstractMuch interest exists in physicians’ ability and willingness to adapt their practice styles, as research demonstrates that many physicians practice in ways that are not aligned with the best available scientific evidence. We exploit migration patterns of primary care physicians in Massachusetts over a span of 8 years by tracking physician migrations to practice sites comprised of new peers who shared actual physical working space. We examined whether a patient's likelihood of receiving an inappropriate referral for diagnostic imaging, specifically a magnetic resonance imaging (MRI), was associated with a change in the work environment of the referring physician. Study results indicate that migrating physicians changed their practice style for imaging relatively soon after migration in conformance with the average practice style of their new peer group regardless of whether or not the practice style was aligned with evidence‐based standards for diagnostic imaging. To place our results in context, a 1 percentage point difference in average inappropriate MRI referral rates between a migrating physician's new and previous work environment was associated with approximately a 14% change in the probability that a patient received an inappropriate MRI referral. The effect diminished with greater variability in inappropriate MRI referral rates within the new peer group. The results show that physician practice style may deviate from evidence‐based standards and vary markedly among physicians within a work environment. At the same time, physician practice style is also malleable in either direction—more or less likely to deviate from evidence‐based standards in conformance with the average practice style of their new peer group. These results imply that healthcare managers can employ various institutional‐level interventions to influence physician behavior in the direction of evidence‐based practice by including strategies directed towards developing strong peer influence in physicians’ work environments.

AbstractResearchers have increasingly turned to crowdfunding platforms to gain insights into entrepreneurial activity and dynamics. While previous studies have explored various factors influencing crowdfunding success, such as technology, communication, and marketing strategies, the role of visual elements that can be automatically extracted from images has received less attention. This is surprising, considering that crowdfunding platforms emphasize the importance of attention‐grabbing and high‐resolution images, and previous research has shown that image characteristics can significantly impact product evaluations. Indeed, a comprehensive review of empirical articles (n = 202) utilized Kickstarter data, focusing on the incorporation of visual information in their analyses. Our findings reveal that only 29.70% controlled for the number of images, and less than 12% considered any image details. In this manuscript, we contribute to the existing literature by emphasizing the significance of visual characteristics as essential variables in empirical investigations of crowdfunding success. We review the literature on image processing and its relevance to the business domain, highlighting two types of visual variables: visual counts (number of pictures and number of videos) and image details. Building upon previous work that discussed the role of color, composition, and figure–ground relationships, we introduce visual scene elements that have not yet been explored in crowdfunding, including the number of faces, the number of concepts depicted, and the ease of identifying those concepts. To demonstrate the predictive value of visual counts and image details, we analyze Kickstarter data using flexible machine learning models (Lasso, Ridge, Bayesian additive regression trees, and eXtreme Gradient Boosting). Our results highlight that visual count features are two of the top three predictors of success and highlight the ease at which researchers can incorporate some information about visual information. Our results also show that simple image detail features such as color matter a lot, and our proposed measures of visual scene elements can also be useful. By supplementing our article with R and Python codes that help authors extract image details (https://osf.io/ujnzp/), we hope to stimulate scholars in various disciplines to consider visual information data in their empirical research and enhance the impact of visual cues on crowdfunding success.

AbstractWe address a production/inventory problem for a single product and machine where demand is Poisson distributed, and the times for unit production and setup are constant. Demand not in stock is lost. We derive a solution for a produce‐up‐to policy that minimizes average cost per‐unit‐time, including costs of setup, inventory carrying, and lost sales. The machine is stopped periodically, possibly rendered idle, set up for a fixed period, and then restarted. The average cost function, which we derive explicitly, is quasi‐convex separately in the produce‐up‐to level Q, the low‐level R that prompts a setup, and jointly in R equals Q. We start by finding the minimizing value of Q where R equals 0, and then extend the search over larger R values. The discrete search may end with R less than Q, or on the matrix diagonal where R equals Q, depending on the problem parameters. Idle time disappears in the cycle when R equals Q, and the two parameter system folds into one. This hybrid policy is novel in make‐to‐stock problems with a setup time. The number of arithmetic operations to calculate costs in the (Q,R) matrix depends on a vector search over Q. The computation of the algorithm is bounded by a quadratic function of the minimizing value of Q. The storage requirements and number of cells visited are proportional to it.This article is protected by copyright. All rights reserved

AbstractAuto‐delivery is a subscription model widely employed in supply chains, whereby a supplier delivers products to a buyer (or multiple buyers) according to the buyer's choice of a constant shipping quantity to be delivered at prescheduled dates. The buyer enjoys a discount for the auto‐delivery orders and other benefits, including free subscription and cancellation. Because these benefits seem to all accrue to the buyer at the supplier's expense, the rationale for the supplier's decision to offer auto‐delivery and its impact on the profitability of both parties is an intriguing concern. We first develop a model that consists of a supplier and a single buyer, whereby the supplier offers a discount for the auto‐delivery orders and the buyer chooses the auto‐delivery quantity with the flexibility of cancelling the subscription. We derive the two parties' operating characteristics of their inventory systems and examine their optimal decisions. Our analysis shows that buyers benefit from the auto‐delivery discount; the supplier benefits from the demand‐expansion effect and the inventory‐reduction effect, a potential discount on the cost of the auto‐delivery units; and the supply chain benefits from reducing the bullwhip effect. We also find that channel coordination requires the supplier to pass the inventory‐related savings to the buyer through the auto‐delivery discount, which depends on the ratio of the two parties' holding cost rates. Moreover, we examine a model extension whereby the supplier announces a discount that is available for multiple buyers, we show that the supplier's optimal auto‐delivery discount under exponential demand can be determined based on the aggregate‐level demand information from all buyers. Finally, we discuss another model extension whereby the lead time of the supplier's recurring orders for auto‐delivery is longer than that of the regular orders and present a full analysis of the case when the lead time differential is one time period.

AbstractSocial media platforms like Facebook and Twitter have emerged as effective channels for advertising that enable consumer targeting based on demographics, interests, and user behavior. Social media marketers have utilized information spillover within these platforms to reach a larger customer base. This information spillover also exists across groups of users within the platform and enhances returns from social media advertising. Thus, this information spillover can be utilized to strategically sequence targeted advertising to amplify the returns from social media ads. In this paper, we present a theoretical model for information retention and show that the sequential advertising strategy is effective in targeting groups of users on a social media platform. In addition, we provide empirical evidence through two series of randomized field experiments. From experiments for a health services organization, we find that sequential advertising campaigns provide 23% more clicks when compared to campaigns that target groups simultaneously, which translates to a saving of 18.7% in the advertising budget to achieve similar results as simultaneous advertising. Additionally, we found that sequential advertising campaigns targeting a smaller group first followed by a larger group provide 10.7% additional clicks when compared to targeting a larger group first followed by a smaller group. These results were consistent for consumer packaged goods that were advertised on Facebook and Twitter. These results provide implications for social media advertising research and practice.

AbstractProduct evaluation is an essential business process, and digital innovation has made it possible for companies to immediately process available information. We develop a model where a company continuously assesses information that follows a doubly stochastic Poisson process with a mean‐reverting and stochastic intensity. Accordingly, the company faces a two‐dimensional optimal stopping problem in which the company continues to evaluate the product if and only if the product reputation and information intensity remain in a continuation set. We employ a probabilistic approach to prove that the continuation set takes the form of an open interval for any fixed information arrival intensity. Given the complicated nature of the optimal solutions, we develop an asymptotic expansive solution, and numerical studies show that our solution performs well. We also analyze a heuristic solution where the company substitutes the dynamic intensity with a constant intensity. Interestingly, we find that this heuristic company does not necessarily benefit from having a higher product reputation.

AbstractThe paper proposes an optimization model for the allocation of vaccines to a heterogeneous population composed of several subpopulations with different sizes and epidemiological disease transmission parameters. As the objective, an aggregated function combining a standard utilitarian efficiency criterion with a Gini index–related penalty term is considered. Contrary to previous work, we adopt an outcome equity view: The inequity measure is not based on vaccination fractions or other input factors, but on the fractions of individuals escaping infection, as predicted by an susceptible‐infections‐removed (SIR) model. An adjusted pro rata (APR) policy of vaccine allocation minimizing inequity in this outcome view is introduced, and a numerical procedure for its determination is presented. The concepts are developed both for the case of segregated subpopulations and for that of interactions between the subpopulations. Interestingly, in a large number of instances, the optimal solution under the aggregated objective function turns out to be identical to APR. Whether APR is locally or even globally optimal in a concrete case depends on the relation of an inequity aversion parameter to certain threshold values. While the local optimality threshold can be determined by linear programming, the determination of the global optimality threshold, as the vaccine allocation problem itself, is a problem of nonconvex optimization. We suggest an exact optimization approach for smaller instances, and propose algorithms building on particle swarm optimization for threshold determination and allocation optimization at larger instances. Extensions to alternative outcome measures such as the number of fatalities are presented as well. In addition to the investigation of randomly generated instances, two test cases from the literature are revisited in the context of the present work. Moreover, a new case study based on data from the COVID‐19 outbreak in Austria in 2020 is introduced and analyzed.

AbstractIn practice, many retailers employ price‐matching guarantees (PMGs), committing to meet the price of an identical product at a competitor's outlet. Despite the profound linkage between retailers and manufacturers, existing literature has predominantly explored retailers' PMGs without contemplating the influence of manufacturers' wholesale pricing strategies. Employing a supply chain model comprising one manufacturer and two retailers, we scrutinize the implications of wholesale pricing—uniform or discriminatory—on supply chain members and consumers when retailers have the option to extend PMGs. Our analysis uncovers that retailers refrain from offering PMGs when the manufacturer is granted the discretion to set discriminatory wholesale prices—even if such offers align with the manufacturer's preferences. Conversely, under uniform wholesale pricing, PMGs thrive at equilibrium—even if the manufacturer opposes the practice—as long as the degree of demand or cost asymmetry between retailers and average hassle costs remains relatively modest. Although firms' preferences regarding PMGs vary, a Pareto zone exists where all entities prefer that either the efficient retailer under demand asymmetry or the inefficient retailer under cost asymmetry extends the PMG. Despite the potential advantages of PMGs for the more efficient retailer, the enforcement of uniform wholesale pricing diminishes supply chain profit, consumer welfare, and overall social welfare. The detrimental impacts on welfare owing to the imposition of uniform wholesale pricing persist, even amid the presence of hassle costs associated with price matching. Our findings thus instigate a dialogue for policymakers concerning the validity of regulating wholesale pricing when PMGs are in effect.