Omega-international Journal of Management Science最新文献

This paper focuses on a novel approach for managing cold chains of highly perishable products. We extend the classical and frequently applied economic order quantity model (EOQ) for its application in multi-echelon supply chains for highly perishable products. Literature shows that order-level inventory systems for perishable items are commonly modelled by parametric approaches e.g., a time-dependent (Weibull) deterioration rate. However, the deterioration of perishable fresh products is a complex process, heavily influenced by product dependent characteristics and, crucially, depending on environmental conditions. We take both time-temperature-dependent deterioration, and the multi-echelon aspect of cold chains into account and integrate both aspects into a generically applicable EOQ-based methodology. We demonstrate the concept from a real-life case study for cold chain management in floriculture. Two commonly used multi-echelon supply chains are considered and compared. The results show that the optimal order levels in different echelons of the supply chains are substantially different. In addition to the sojourn time, the temperature has a major impact on order levels, the total supply chain costs, and the remaining shelf-life at the retail level. We demonstrate that the proposed concept for extending the EOQ-based model to time- and temperature-dependent deterioration can be generalized and applied to other specific causes of product-dependent deterioration.

Multiple criteria decision making (MCDM) methods can be affected by preference reversal, meaning that the order of two alternatives is reversed after adding or deleting another alternative. Here, we focus on methods that produce rankings with ties (i.e., weak orders). In this context, one usually talks about rank reversal. Existing rank reversal probability simulation experiments are subject to improvement on the following points: (1) the small number of MCDM methods included, (2) the unclear relation between the rank reversal probability and the rank of the deleted alternative, and (3) the lack of consideration of ties. In this paper, considering both strict preferences and ties, we distinguish two new phenomena: tie breaking, i.e., the shift from a tie to a strict preference, and tie making, i.e., the shift from a strict preference to a tie. To investigate the probabilities of rank reversal, tie making, and tie breaking, a simulation study involving thirty versions of twelve MCDM methods and six simulation factors is set up. Results demonstrate that for MCDM methods using pairwise comparison data, deleting an alternative ranked first or last leads to smaller probabilities than deleting an alternative in the middle, while the opposite holds for the methods using evaluation data under criteria. Four findings and three suggestions are given to help decision makers select MCDM methods to use.

With the proliferation of e-commerce, there has been a remarkable surge in the volume of products sold online, accompanied by a corresponding increase in product returns. In order to stimulate consumer demand, retailers have adopted various promotional strategies, among which the bundling and add-on sales have emerged as the most prevalent. Nevertheless, there is currently no clearly dominant promotion model considering consumer return behavior. Consequently, we construct a game-theory model that considers product returns in the settings of an online retailer, an insurance company, and a continuum of consumers. Within our model, consumers are confronted with uncertainty regarding their valuations and only ascertain the true value of a purchased product after acquisition. Moreover, retailers must carefully consider the tradeoff between the bundling and add-on models: bundling sales may sell more products, but return products increase; on the other hand, add-on sales offer the advantage of single item returns but may result in a decrease in overall product sales. Our findings yield several noteworthy conclusions warranting further examination. First, add-on product substandard rate (Proportion of add-on products with substandard quality to all add-on products) has a significant influence on the retailer’s choice of sales model. More specifically, when the add-on product substandard rate is lower, retailers will definitely choose bundling sales. Otherwise, the retailer’s choice of sales model depends on both core product price and degree of discount. Second, in bundling sales, the better the match between core product and add-on product, the higher the retailer’s profit. However, in add-on sales, highly matched add-on product may hurt the retailer’s profit. Finally, add-on sales is a better choice for commercial groups that have both sales companies and insurance companies.

In this study, we analyze the challenges faced by manufacturers in promoting sustainability throughout their supply chains when the supplier is capital-constrained, has private access to production cost information, and must choose between regular and sustainable production. We develop a dyadic supply chain model to determine the optimal advanced payment contract under asymmetric information. Our comparative results reveal that the optimal contract requires manufacturers to balance promoting sustainability, pricing information rent, and avoiding channel efficiency losses. The key factors in achieving this balance are (i) production cost efficiency, and (ii) the switching cost from regular to sustainable production. When the efficient supplier is more sustainably efficient, the mere existence of information asymmetry always leads to a less sustainable supply chain. However, if the efficient supplier is less sustainably efficient, the manufacturer may be better off encouraging the inefficient supplier to use sustainable operations where regular operations were used under full information. This reveals the bright side of information asymmetry regarding supplier sustainability risk. Although information asymmetry typically leads to channel loss, our study shows that it could result in a greener supply chain, albeit with lower profits for the parties involved. Our findings carry significant practical implications. It highlights that managerial strategies increasing consumers’ willingness-to-pay and awareness of sustainable production can mitigate the negative effects of information asymmetry while promoting supply chain sustainability. These levers not only contribute positively to the environment and society but also play a vital role in securing the long-term prosperity of businesses committed to sustainability.

Online retailing has been booming over the past several years as people grow increasingly comfortable with it and accustomed to its ease and speed. A major drawback of online retailing is the lack of consumer–product interaction before a purchase is finalized, which often leads to consumer dissatisfaction due to mismatched expectation of the received product. In response, retailers usually promise that online orders may be returned or exchanged free of extra charges, which can be processed either online (e.g., by mail) or onsite i.e., in-store dropoff. In this work, we study the implications of both online and onsite exchange policies in the setting of a queueing model that offers omnichannel services. Taking into account customers’ behavioral responses to these policies, we aim to inform the retailer of the one that generates a higher system revenue. Our results reveal that the online exchange policy is a double-edged sword: On the one hand, it helps eliminate the inconvenience cost for exchange customers to revisit the store; on the other hand, it can trigger more feedback orders and render a higher system congestion level, which in turn, deters future customers from placing orders. Specifically, we discover that online exchange becomes an inferior policy relative to in-store exchange when the market size is large.

A well-designed emergency medical services (EMS) system is essential to provide the best possible quality of care to patients in emergencies. Exogenous effects, such as demographic change or extreme weather conditions, lead to a continuous increase in emergency calls. On the other hand, emergency vehicles and qualified personnel are limited. Consequently, there is a continuous need to improve the existing EMS systems in order to optimize the use of the available resources. To assist decision makers in this complex task, we provide a decision support framework at the tactical site planning level. First, we analyze the given historical data to find suitable periods that have similar structures in terms of the number of calls and the time of day. We follow this approach to account for fluctuating demand and time-dependent travel times. A new stochastic, time-dependent, mixed-integer extension of the maximum expected coverage location problem (MEXCLP) is developed that accounts for ambulance site interdependencies. We conduct computational experiments for an existing EMS network structure to optimally locate sites and allocate ambulances. Furthermore, we analyze the benefit of additional ambulances and flexible waiting sites. A discrete-event simulation (DES) is used to evaluate the model solutions and to provide further insights into the trade-off between quality and cost of care for the given model solutions. Results based on anonymized real-world EMS data indicate that flexible waiting sites provide considerable potential savings in the use of ambulances while maintaining a high level of coverage.

This study examines the patterns of technological cooperation or technological competition between an incumbent firm and an entrant firm in Information and Communications Technology (ICT) markets. The incumbent firm in ICT markets often licenses its key technology to a new entrant, who is usually the rival to the incumbent and has the option to enter the market early through licensing in the technology (i.e., technological cooperation), or to delay its entry for producing a higher quality product through in-house R&D (i.e., technological competition). Using a game-theoretical model, we find that technological cooperation is an equilibrium strategy when the technology transfer rate and entrant's R&D capacity are intermediate; while two firms engage in technological competition when the technology transfer rate is high and the entrant's R&D capacity is low, or when the technology transfer rate is low and the entrant's R&D capacity is high. We also find that the high royalty rate and mitigated price competition incentivize technological cooperation, while firms engage in technological competition when the royalty rate is low, or when the royalty rate is high and the price competition is intense. In addition, the incentives for firms to form technological cooperation vary non-monotonically with the length of the entrant's in-house R&D phase, and technological cooperation is reached only when the in-house R&D phase is of medium length. From a social perspective, both fairly high and low technology transfer rates ensure higher social welfare under technological cooperation, which under certain conditions can lead to a win-win-win outcome for the incumbent, entrant, and consumers. Furthermore, technological cooperation is less likely to be an equilibrium strategy when the entrant's market entry timing under in-house R&D is endogenously determined. Our findings can explain the observations of the incumbent and entrant's technological cooperation or competition strategies and provide managerial implications for competing ICT firms and policymakers.

Customer churn prediction methods aim to identify customers with the highest probability of attrition, improve the effectiveness of customer retention campaigns, and maximize profits. However, previous studies have relied on a single classifier, leading to suboptimal predictive results. To address this issue, we propose a novel profit-driven weighted classifier that integrates a weighted strategy with multiple profit-driven ensemble members. We employ an artificial hummingbird optimization algorithm to determine the optimal weight coefficients of the profit-driven ensemble members based on the expected maximum profit criterion. We then calculate the Shapley additive explanation value to further improve the interpretability of the proposed weighted classifier. We conducted experiments and statistical tests on eight real-world datasets from different industries. The results show that the proposed weighted classifier significantly improves profits compared with comparative classifiers and provides strong interpretability based on the Shapley additive explanation value.

To encourage product market competition, uniform price regulation is imposed to forbid suppliers from price discrimination. This paper investigates the impact of price regulation on a supplier’s trade credit decision in a supply chain with two heterogeneous retailers. In the baseline model without price regulation, we show that it is optimal for the supplier to provide net term trade credit to both retailers if their working capital is at a low level. Under price regulation, the net term remains optimal in trade credit provision to the rich retailer. However, a two-part term emerges to be optimal in the supplier’s trade credit provision to the poor retailer when it is highly capital-constrained. Interestingly, in the presence of a capital disparity, we find that the price discount in two-part term trade credit is independent of the rich retailer’s capital level, justifying the stability and uniformity of two-part terms in practice. We also incorporate retailer competition into our analysis and further validate the optimality of two-part terms under price regulation. In numerical experiments, we analyze the policy implications of price regulation and observe that uniform price regulation can result in a higher wholesale price and impede trade credit provision, hurting both small businesses and consumers.

The rapid development and widespread application of the new generation information technology has not only promoted innovation in traditional business models, but also has even created new business models and new industries. The free trial, as one of the new business models, has been utilized by major enterprises to advertise and promote their products in the expectation of receiving more attention from consumers, increasing the potential value of products. However, the accompanying problem of setting the number of lucky customers and free trial operation scheme properly should be handled urgently. In reality, the purchasing decision of the consumer is influenced by a variety of factors, such as reviews, trial campaigns. Meanwhile, consumers have positive and negative perceptions of products and activities, which could be transmitted to surrounding consumers. Consequently, this paper discusses the problem of the free trial policy for the electronic product by considering the positive and negative network effects. It is attempted to be solved both theoretically and empirically. The consumer network utility, demand and product profit models are proposed to solve the problem, which produces empirically testable hypotheses and Management propositions. Then, these hypotheses are tested and these management propositions are validated by utilizing real operational data from Lenovo Mall. The test and validation results indicate that there is a significant increase in the price and demand for products after the merchant taking the free trial. Moreover, although the operating costs of the merchant are increased, a much larger boost is provided by the free trial to the merchant in total profit. It is worthwhile considering the accuracy in identifying the valuable consumer, which the success of the free trial depends on.