Journal of Business Logistics最新文献

This paper investigates how current megatrends (i.e., aging population, growing urbanization, shifts in consumer demands, geopolitical shifts, depletion of natural resources, climate change) are changing the supply chain landscape and the role of Industry 4.0 (I4.0) technologies to support alignment with these changes. Building on contingency theory, the study employs focus-group interviews with various experts to generate new insights into fitting supply chain capabilities and enabling technologies. Data collected in the focus groups helped us to identify five supply chain capabilities as prevalent and mostly fitting the external contingencies, i.e., customer-driven, urban-centered, resource-efficient, fast reactive, and human-centered supply chain. Moreover, this study highlights and compares the potential of I4.0 technologies and their applications in supporting specific supply chain capabilities. The findings of this study can inform supply chain managers in the definition of capabilities to be enhanced at the supply chain level and contribute toward understanding the extent of I4.0 technologies in empowering supply chains to face turbulent and changing conditions.

The possibility of product substitution due to a stockout provides retailers with a buffer against lost sales but can also complicate the management of inventory because both substitute and primary demand affect inventory levels. Since most retailers make their inventory decisions around a desired service level (e.g., fill rate), it is important to understand how customer substitution behavior can influence different measures of customer service. In this study, an extensive theoretical framework is presented and used to develop a decision tree approach for predicting realized item and category fill rates. We find that item fill rate is primarily a function of the target service level of the focal item and the willingness to switch from an alternate item to the focal item. Category fill rate is influenced by the target service level of both items, with willingness to switch amplifying their effect. The decision tree approach is found to be an accurate predictor in most cases, however, it tends to overestimate item fill rate when the willingness to substitute from the alternate item increases. The approach also accurately predicts category fill rates, outside of scenarios with asymmetric substitutability.

While greater competitive activity is generally associated with competitive advantage, certain competitive actions by a supplier may have spillover effects that adversely impact buying firms, leading them to reduce future purchases from the supplier. We study the effects of competitive actions in the context of vertical buyer–supplier relationships. Specifically, leveraging insights from screening theory, we examine how a supplier firm's value-diminishing competitive actions—moves that may negatively impact buyer firms—lead to subsequent reductions in the buyer's procurement allocations and how contextual factors moderate such adverse effects. We test the associated hypotheses using a panel dataset comprising 12,690 dyadic buyer–supplier observations. A series of econometric analyses provide consistent evidence that a supplier's value-diminishing actions are associated with decreases in the buyer's purchases from the supplier, thus highlighting the “dark side” of competitive actions. Furthermore, we find that the supplier's downstream vertical relatedness and the degree to which rival suppliers pursue value-diminishing actions moderate this effect. Our findings, thus, add to our understanding of factors that shape the success and continuity of supply chain relationships and help supplier firms evaluate the economic viability of their competitive actions.

Global supply chains operate in a volatile environment characterized by risks like the 2008–2009 financial crisis, trade disputes, and the COVID-19 pandemic. Maritime shipping firms, the backbone of global supply chains, are particularly affected by this volatility. In response, these firms have pursued two strategies. First, they have acquired tangible assets to increase their capacity. These assets, however, are neither easily re-deployable to other uses nor quickly adjustable, preventing firms from flexibly matching supply and demand. Second, these firms have pursued global supply chain integration by acquiring similar firms or firms in their upstream or downstream supply chain to diversify into other supply chain activities. Anecdotal evidence suggests that some firms have successfully pursued these strategies, but others have failed, eventually exiting the market. We posit that one explanation for this difference may be how effectively these firms manage their assets relative to their supply chain integration activities. We test this proposition by drawing from resource-based theory and transaction cost economics and using longitudinal data for 148 maritime shipping firms. We also test post hoc whether typically acquired supply chain activities are beneficial. Our findings offer insights into asset management and global supply chain integration and offer advice to practitioners.

Our research reveals the continued and evolving role of the human factor in decision making in digitalized retail supply chains. We compare managerial roles in a pre- and post-COVID era through conducting in-depth interviews of 25 executives spanning the retail supply chain ecosystem. We use grounded theory to develop four main contributions. First, we find that the involvement of managerial judgment is found to be progressively greater moving up the retail supply chain, away from the customer and the demand signal. Second, integration of analytics and judgment is now the primary method of decision making, and we identify elements needed for success. Third, we develop an essential framework for a successful integration process. Fourth, we isolate the necessary components of a successful process for analytics/artificial intelligence (AI) implementation. Our paper offers important insights into how analytics and AI are—and should be used—in judgment and decision making and opportunities for researchers to understand the changing role of the human factor in digitalized retail supply chains.

With the growth of e-commerce and associated home deliveries, understanding the role of drivers in shaping the customer experience in last-mile delivery is now more crucial than ever. Delivery drivers increasingly act as retailers' frontline employees and are thus instrumental in developing pseudorelationships between customers and retailers. Industry surveys, however, reveal that drivers admit to engaging in unprofessional behaviors with customers and often refuse to address customers' requests beyond package delivery. Following a middle-range theorizing approach and leveraging Cognitive Appraisal Theory, we investigate how two negative driver behaviors, inappropriate behavior and inflexibility, impact customer satisfaction and repurchase intentions. We also examine the moderating effect of driver affiliation, private versus outsourced, in altering the magnitude of customer responses. Results from a scenario-based experiment indicate that while the negative effects of driver inappropriate behavior on customer outcomes are mediated by anger, the effects of driver inflexibility are mediated by sadness. Moreover, the negative effect of driver inflexibility on customer outcomes is weaker for outsourced logistics than for private fleet drivers. In turn, driver inappropriate behavior exhibits similar negative effects on customer outcomes for both driver affiliations. These findings offer important insights for last-mile delivery strategy and operations research and practice.

Ensuring motor carriers comply with safety rules is critical to the efficient workings of supply chains and the safety of the motoring public. However, little is understood regarding how carriers respond to changes in the likelihood of inspection (a.k.a., “crackdowns”) undertaken by the Department of Transportation. Drawing on the regulatory compliance and criminology literature, we extend the rational cheater explanation that undergirds carrier safety research by incorporating principles from attention-based theory to devise new theoretical predictions regarding how carriers respond to announced versus unannounced inspection crackdowns. To test our theory, we rely on exogenous variation in the probability of inspection from the DOT's use of announced and unannounced inspection “blitzes.” We test predictions using a longitudinal dataset of nearly 10 million truck inspections from 2012 to 2016. We find firms with lower costs of compliance, and higher costs of avoiding inspections improve compliance prior to and during announced blitzes. Small firms with lower costs of avoidance tend to avoid announced blitzes. Unannounced blitzes result in no changes in compliance or avoidance, providing evidence that awareness is driving our results.

Retail firms have developed new product and service offerings to meet the changing needs of omnichannel customers. While, prior research has documented these offerings in detail, little is yet known about how retail firms can best adapt different aspects of their organizations to the new omnichannel environment. We specifically focus on the intra-firm changes that affected the role of the firm's supply chain organization and its interactions with other business entities within the retail enterprise. This paper provides an in-depth understanding of the new business processes, organizational structures, governance mechanisms and customer interactions; collectively described as the retail business model (BM). Drawing on the tenets of BM theory, we present findings from a qualitative study of 15 leading U.S. omnichannel retailers to identify key elements of the new retail BM, develop a conceptual framework of the BM innovation process, and highlight the pivotal role of the supply chain organization in helping firms adapt and implement the omnichannel strategy. We conclude by developing research propositions to articulate the connections among different elements of the BM innovation process and how firms can institutionalize this process to respond to the everchanging retail business environment.

This study exploits service modularity in front-end logistics services in e-fulfillment, from a customer-centric approach, particularly in order management, delivery, and return. Through an online survey of UK customers, the service priorities of 494 respondents via AHP (Analytic Hierarchical Process) were analyzed. Extracting customers' service priorities, ordering behavior, and demographic information as input data, the clustering algorithm KAMILA (KAy-means for MIxed LArge data sets) was further applied. The three identified customer clusters (multichannel shoppers, infrequent shoppers, and online fans) provide preliminary evidence on how commonality and variability aspects of service modularity in front-end logistics services can optimize the number of service options and their performance levels. Therefore, our study, building on value co-creation and modularity, proposes a systematic way of exploiting service modularity for the customer segmentation process that addresses heterogeneous customer preferences cost-efficiently and uncomplicatedly. Furthermore, we provide a framework for the governance of front-end logistics services, guiding outsourcing decisions. Accordingly, it reveals the implications of customer priorities and service decomposition logic choices on value creation. Finally, the propositions formulated aim to develop theoretical foundations for explaining how the heterogeneity in customer priorities for logistics services can be managed with modularity, creating value both for customers and retailers.