Risk-Averse Ride-Hailing Platform Operations With Safety Risk-Averse Consumers Under Pandemics: Roles of Blockchain Technology and Government Sponsors

Today, ride-hailing platform operations are popular. Facing pandemics (e.g., COVID-19) some customers feel unsafe for the ride-hailing service and possess a "safety risk-averse" (SRA) attitude. The proportion of this type of SRA customers is unfortunately unknown, which makes it difficult for the ride-hailing platform to decide its optimal service price. In this article, understanding that blockchain technology (BT) based systems can help improve market estimation for the proportion of SRA customers, we conduct a theoretical study to explore the impacts that the BT-based system can bring to the platform, customers, and drivers. We consider the case in which the platform is risk-averse (in profit) and serves a market with both SRA and non-SRA customers. We analytically prove that using BT, the optimal service price will be increased and BT is especially helpful for the case with a more risk-averse ride-hailing platform. However, whether it is more or less significant for the more risk-averse SRA customers depends on their degree of risk aversion. We uncover that when the use of BT is beneficial to the customers, it will also be beneficial to the drivers, and vice versa. We derive in closed-form the analytical conditions under which the use of BT can be beneficial to the ride-hailing platform, customers, and drivers (i.e., achieving "all-win"). When all-win cannot be achieved automatically, we explore how governments can provide sponsors to help. We further extend the analysis to consider the general case in which BT incurs both a fixed cost as well as a cost increasing in demand. We prove that the main conclusion remains robust. In addition, we reveal that the required amount of government sponsor to achieve all-win is the same between the two different costing models explored in this article.

Toward supply chain viability theory: from lessons learned through COVID-19 pandemic to viable ecosystems

The COVID-19 pandemic has triggered new research areas in supply chain resilience. One of these new areas is viability. Viability extends the resilience understanding from performance-based assessment of firm's responses to disruptions towards survivability of both supply chains and associated ecosystems not only during some short-term disruptions but also under conditions of long-term crises. To explore the state-of-the-art knowledge on methods, models, capabilities, and technologies of supply chain viability, we edited this important IJPR special issue. To introduce the special issue, we review the existing literature on supply chain viability, conceptualise seven major pillars of supply chain viability theory (i.e. viable supply chain design, viability in process planning and control, ripple effect, intertwined and reconfigurable supply networks, ecosystems, digital supply chain, and Industry 5.0), and establish some associated future research directions. The findings of this editorial paper, as well as the articles in the special issue, can be used by researchers and practitioners alike to consolidate recent advances and practices of viability in supply chain networks and lay the solid foundation for further developments in this area. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Reforming global supply chain management under pandemics: The GREAT-3Rs framework

The recent outbreak of Coronavirus disease 2019 (COVID-19) has posed serious threats and challenges to global supply chain management (GSCM). To survive the crisis, it is critical to rethink the proper setting of global supply chains and reform many related operational strategies. We hence attempt to reform the GSCM from both supply and demand sides considering different pandemic stages (i.e., pre, during, and post-pandemic stages). In this research paper, we combine a careful literature review with real-world case studies to examine the impacts and specific challenges brought by the pandemic to global supply chains. We first classify the related literature from the demand and supply sides. Based on the insights obtained, we search publicly available information and report real practices of GSCM under COVID-19 in nine top global enterprises. To achieve responsiveness, resilience, and restoration (3Rs), we then propose the "GREAT-3Rs” framework, which shows the critical issues and measures for reforming GSCM under the three pandemic stages. In particular, the "GREAT” part of the framework includes five critical domains, namely, "government proactive policies and measures,” "redesigning global supply chains,” "economic and financing strategies under risk,” "adjustment of operations,” and "technology adoption,” to help global enterprises to survive the pandemic;"3Rs” are the outputs that can be achieved after using the "GREAT” strategies under the three pandemic stages. Finally, we establish a future research agenda from five aspects. © 2022 Production and Operations Management Society.

Sourcing decisions with uncertain time-dependent supply from an unreliable supplier

Recently, an increasing number of companies have encountered random production disruptions due to the COVID-19 pandemic. In this study, we investigate a two-stage supply chain in which a retailer can order products from a low-price ("cheap”) unreliable supplier (who may be subject to an uncertain production disruption and partially deliver the order) and an "expensive” reliable supplier at Stage 1 and a more "expensive” backup supplier at Stage 2. If the disruption happens, only the products that were produced before the disruption time can be obtained from the unreliable supplier. It is found that in the case with imperfect demand information updating, the unreliable supplier is always used while the reliable supplier can be abandoned. The time-dependent supply property of the unreliable supplier reduces the retailer's willingness of adopting the dual sourcing strategy at Stage 1, compared with the scenario with all-or-nothing supply. Different from the case with imperfect demand information updating, either the reliable or unreliable supplier can be abandoned in the case with perfect demand information updating. We derive the optimal ordering decisions and the conditions where single sourcing or dual sourcing is adopted at Stage 1. We conduct numerical experiments motivated by the sourcing problem of 3M Company in the US during the COVID-19 and observe that the unreliable supplier is more preferable when the demand uncertainty before or after the emergency order is higher. Interestingly, the retailer tends to order more from the unreliable supplier when the production disruption probability is larger in some cases. © 2022 The Author(s)

Share it or buy it? Exploring the effects of product brand attachment on commercial sharing services

Commercial sharing services (CSSs) provide consumers with temporary access to products or services. Consumers can use CSSs to communicate an identity by renting products from specific brands. Applying the theory of the extended self, we proposed an attachment-based account of CSS usage. Across four studies, we found consistent evidence that consumers were less likely to rent the products of their strongly attached brands via CSSs because these brands were regarded as part of their extended selves, and thus sharing these products with others would contaminate the self. However, this effect was mitigated when consumers' psychological ownership of the shared product was augmented. Our findings reveal that psychological ownership can replace the role of actual ownership in the sharing context, rendering profound implications for understanding the relationships among self, brand, and product in sharing services.

Roles of Innovation Leadership on Using Big Data Analytics to Establish Resilient Healthcare Supply Chains to Combat the COVID-19 Pandemic: A Multimethodological Study

This article empirically examines the effect of big data analytics (BDA) on healthcare supply chain (HSC) innovation, supply chain responsiveness, and supply chain resilience under the moderating effect of innovation leadership in the context of the COVID-19 pandemic. The scanning interpretation-action-performance model and organization information processing theory are used to explain BDA, HSC innovation, responsiveness, and resilience relationships. First, the hypotheses were tested using data collected from 190 experienced respondents working in the healthcare industry. Our structural equation modeling analysis using the partial least squares (PLS) method revealed that BDA capabilities play a pivotal role in building a responsive HSC and improving innovation, which has contributed to resilience during the current pandemic situation. High innovation leadership strengthens the effect of BDA capabilities on HSC innovation. High innovation leadership also increases the effect of BDA capabilities on responsiveness. Second, we validated and supplemented the empirical research findings using inputs collected in 30 semistructured qualitative questionnaires. Our article makes a unique contribution from the perspective of innovation leaderships. In particular, we argue that the role of innovative leadership in the COVID-19 pandemic situation is critical as it indirectly affects HSC resilience when BDA is in place.