Year: 2025
Type: article
Abstract: This research, motivated by collaboration with a leading manufacturer and distributor of building products, introduces two distribution network design models considering federally mandated hours of service restrictions on truck drivers and drop-and-swap trailer operations. A key feature of the drop-and-swap transport mode is the decoupling of linehaul and last-mile delivery operations, which enables geographic extension of last-mile delivery routes while complying with hours of service driver regulations and providing next-day delivery service. The models simultaneously determine the profit-maximizing size, number, and location of order fulfillment facilities and satellite drop-and-swap terminals, and systemwide transportation flows. A case study of the firm's distribution network reveals that the new location models improve profitability by approximately 5% when compared with traditional network design approaches. An experimental study of five marketing and operational characteristics shows when the models are most advantageously applied. Overall, profit improvements range from 2.32% to 10.97% on a set of 288 test problems. The research provides new insights for integrated facility location and transportation strategic design. The potential application of the models in a variety of e-commerce scenarios is promising. Realizing the role of their consumers in mitigating environmental problems, companies have started leveraging gamification technology with persuasive interventions to induce consumers’ behavioral changes. Ant Forest—a gamified initiative launched by a prominent Chinese fintech company—empowers users to manage their ecological footprint and promote ethical behavior. However, the research community has primarily focused on Ant Forest's adoption and continuation intention, paying limited attention to how gamification promotes users’ environmentally responsible behavior (ERB) in the postadoption stage. This study contributes to this domain by developing a model based on persuasion and motivation theories and the “affordances–psychological outcomes–behavioral outcomes” framework. This model highlights the impact of gamification on consumers’ ERB through psychological need satisfaction and belief or attitude persuasion. A total of 1869 survey responses regarding the use of Ant Forest were collected from nine cities in China. The results demonstrate that, from gamification experiences with Ant Forest, users perceive psychological need satisfaction (i.e., perceived autonomy, competence, and relatedness), which significantly explains their green beliefs and attitudes (i.e., green task performance, green belief confirmation, and green self-identity), leading to increased ERB. Additionally, users with a higher green absorptive capacity demonstrate a stronger link between green beliefs or attitudes and ERB. This research shifts the focus from adoption and continuation intention to postadoption behavioral modification and offers insights into creating effective gamification systems for fostering ethical behavior and addressing environmental concerns. During the last decade, several retailers have started to combine traditional store deliveries with the fulfillment of online sales to consumers from omnichannel warehouses, which are increasingly being automated. A popular option is to use autonomous mobile robots (AMRs) in collaboration with human pickers. In this approach, the pickers’ unproductive walking time can be reduced even further by zoning the storage system, where the pickers stay within their zone periphery and robots transport order totes between the zones. However, the robotic systems’ optimal zoning strategy is unclear: few zones are particularly good for large store orders, while many zones are particularly good for small online orders. We study the effect of no zoning (NZ) and progressive zoning strategies on throughput capacity for balanced zone configurations with both fixed and dynamic order profiles. We first develop queuing network models to estimate pick throughput capacity that correspond to a given number of AMRs and picking with a fixed number of zones. We demonstrate that the throughput capacity is dependent on the chosen zoning strategy. However, the magnitude of the gains achieved is influenced by the size of the orders being processed. We also show that using a dynamic switching strategy has little effect on throughput performance. In contrast, a fixed switching strategy benefiting from changes in the order profile has the potential to increase throughput performance by 17% compared to the NZ strategy, albeit at a higher robot cost. In many countries, healthcare systems encounter the issue of imbalance between supply and demand in a hierarchical structure. The comprehensive hospitals, which possess more high-quality resources, are often overwhelmed, while their counterparts, community hospitals, are often idle. To address this imbalance issue, certain payment schemes are generally considered effective in motivating comprehensive hospitals to divert patients downstream via resource transfer. In addition to two particular payment schemes, namely, patient payment (PP) and fee-for-capacity (FFC), this study also considers two hospital alliance models, the government-led (GL-type) and the hospital-forged (HF-type) alliance, for effectively overcoming the imbalance issue. Compared to the HF-type alliance, in which each community hospital determines the price paid to the comprehensive hospital for transferring resources, the GL-type alliance requires the payment price to be set by the regulator. Methodologically, this study devises a three-stage sequential game to characterize the dynamics among the various entities, such as the regulator, the comprehensive hospital, the community hospitals, and the patients. Equilibrium results, in terms of the capacity sinking rate and patient transfer rate, are derived, and scheme and alliance performances are evaluated using various measurements, such as patient utility, and hospital and social welfare. We find that a direct payment scheme (FFC) under a centralized alliance model (GL-type alliance) is more effective for both making decisions (about the patient transfer rate, capacity sinking rate, and payment price) and the performances (of each hospital's welfare, patient welfare, the waiting time per patient, and social welfare). Furthermore, our study examines the impacts of the alliance scale and finds that social welfare is first decreasing and then increasing with alliance scale. Therefore, it is suggested to establish either a one-to-one hospital alliance (consisting of a comprehensive and a community hospital) or a large-scale (e.g., a comprehensive and 10 community hospitals) hospital alliance. Depending on the patient's condition, up to 60% of inpatients are discharged to post-acute care facilities (PACFs). These patients may experience several days of nonmedical inpatient stay until the hospital finds a facility that fits their needs, contributing to overcrowding in upstream units. This article studies the feasibility of creating a “postdischarge unit” (PDU) for medically ready-for-discharge patients who experience transfer delays, to improve access to inpatient beds. We use a multistage stochastic program, solved with a dual dynamic programming algorithm, to address the PDU size and capacity question. The random variable is the number of bed requests from upstream units (e.g., emergency department). Our numerical analysis, using data from a large hospital, shows that a PDU can reduce costs and significantly reduce the number of patients waiting for transfer to PACFs that are occupying inpatient beds, as long as the percentage of these patients in the hospital is more than 4%. Compared to current practice in our partner hospital, a PDU could increase access to inpatient beds by up to 13% and result in 2%–21% cost savings. Results show that PDU capacity in hospitals with a larger number of patients waiting for transfer is more sensitive to variation in PDU renovation and operational costs. In addition to using fewer medical staff, a PDU can improve discharge transitions to lower levels of care and more efficiently utilize social workers and physical therapists assisting these patients.
Source: Decision Sciences
DOI: 10.1111/deci.12662
Language: English
Subfield: Building and Construction
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4407414850