Previous research on supply risk management mainly focuses on the general risk management process based on case studies. In this study, we explore supply risk management via the relational approach ...in the Chinese business environment (i.e., guanxi) from the buying firm's perspective. We develop a theoretical model grounded in the social capital theory. Theorizing from the three forms of social capital (i.e., obligation, expectation, and trustworthiness; information channel; and norms and effective sanctions), we hypothesize that when a buying firm faces supply risk, it tends to form guanxi networks with its key supplier to reduce risk. We collect data to test the model by surveying manufacturing firms in Hong Kong and apply structural equation modeling to analyze the survey data. The research findings show that purchasing firms form guanxi networks with their key suppliers when they perceive supply risk. We also find that with guanxi development between the buyer and the supplier, both communication and supplier trust are improved, which in turn are positively related to supplier performance. This research contributes to theory by identifying the role of guanxi in supply risk management and to practice by providing insights to purchasing professionals that guide their effort in managing supply risk.
There is a broad consensus that mankind must reduce carbon emissions to mitigate global warming. It is generally accepted that carbon emission trading is one of the most effective market-based ...mechanisms to curb the amount of carbon emissions. This paper investigates how firms manage carbon footprints in inventory management under the carbon emission trading mechanism. We derive the optimal order quantity, and analytically and numerically examine the impacts of carbon trade, carbon price, and carbon cap on order decisions, carbon emissions, and total cost. We make interesting observations from the numerical examples and provide managerial insights from the analytical results.
•The optimal decisions considering the platform-enabled power and remanufacturing are explored.•Marketplace mode and reselling mode are considered in our work.•Whether to adopt blockchain for the ...manufacturer is analyzed.•The quantity and social welfare coordination challenges are discussed.
Blockchain technology has been widely used in many industries. One current application is in remanufacturing. In this paper we consider the combination of remanufacturing and blockchain, and model a supply chain composed of a manufacturer, a third-party firm, and an online platform. Among them, the manufacturer faces the cap-and-trade regulation and adopts blockchain to record the information on the used products and then remanufactures products. The platform has the power to expand the potential market size and can operate in the marketplace or reselling mode. The third-party firm collects used products for the manufacturer. We conduct a Stackelberg game analysis and obtain the following major findings: First, the optimal production quantities and optimal collection rates with and without blockchain in the marketplace and reselling modes increase with the allocated cap and platform-enabled power. Second, in the reselling or marketplace mode, the manufacturer should not adopt blockchain if the emissions intensity is low; otherwise, it should adopt blockchain. Third, selecting the reselling (marketplace) mode is more profitable for the manufacturer if the platform-enabled power is low (high). Fourth, for quantity coordination, the reselling mode under the wholesale price contract can always coordinate the manufacturer and platform, and the manufacturer, online platform, and third-party firm. However, the marketplace mode with a commission rate can only coordinate the manufacturer, online platform, and third-party firm. For social welfare coordination, the manufacturer, online platform, and third-party firm can achieve coordination in the marketplace or reselling mode. Finally, extending the work to consider the cross-channel effect, we find that the major findings for both quantity coordination and social welfare coordination in the reselling and marketplace modes still hold.
As supply chain risks refer to the risks transmitted among supply chain members and supply chain management (SCM) is concerned with close collaboration among chain members to enhance the chain׳s ...overall performance, we argue that we need to use an SCM perspective in supply chain risk management (SCRM). We identify risk information sharing and risk sharing mechanism as two important joint SCRM practices. Drawing on the literature on agency theory and collaborative relationships, we argue that the effectiveness of these two joint practices in improving financial performance can be strengthened by collaborative relationship characteristics including relationship length, supplier trust, and shared SCRM understanding. We empirically test our conceptual model using the data collected from 350 manufacturing firms in China. The results suggest that both risk information sharing and risk sharing mechanism improve financial performance, and the effectiveness of the former is strengthened by relationship length and supplier trust, while that of the latter is strengthened by shared SCRM understanding. We contribute to research and practice by identifying two useful joint SCRM practices and ascertaining the conditions under which each of the practices is particularly effectively.
•A truck-based drone delivery routing problem with time windows is studied.•A tailed branch-and-price-and-cut algorithm with some enhancement strategies is devised.•Experiment results show the ...flexibility and performance of the developed algorithm.•Experiment results highlight the value of the truck-based drone delivery over the truck-only delivery.
Increasing e-commerce activities poses a tough challenge for logistics distribution. With the development of new technology, firms attempt to leverage drones for parcel delivery to improve delivery efficiency and reduce overall costs. We consider the truck-based drone delivery routing problem with time windows. In our setting, a set of trucks and drones (each truck is associated with a drone) collaborate to serve customers, where a drone can take off from its associated truck at a node, independently serve one or more customers within the time windows, and return to the truck at another node along the truck route. To solve the problem, we develop an enhanced branch-and-price-and-cut algorithm incorporating a bounded bidirectional labelling algorithm to solve the challenging pricing problem. To improve the algorithm, we use the subset-row inequalities to tighten the lower bound and apply enhancement strategies, which solve the pricing problem efficiency. We perform extensive numerical studies to evaluate the performance of the developed algorithm, assess the gain of the truck-based drone delivery over the truck-only delivery, and provide some managerial insights.
This special issue explores big data analytics and applications for logistics and supply chain management by examining novel methods, practices, and opportunities. The articles present and analyse a ...variety of opportunities to improve big data analytics and applications for logistics and supply chain management, such as those through exploring technology-driven tracking strategies, financial performance relations with data driven supply chains, and implementation issues and supply chain capability maturity with big data. This editorial note summarizes the discussions on the big data attributes, on effective practices for implementation, and on evaluation and implementation methods.
We present an algorithm that incorporates a tabu search procedure into the framework of path relinking to generate solutions to the job shop scheduling problem (JSP). This tabu search/path relinking ...(TS/PR) algorithm comprises several distinguishing features, such as a specific relinking procedure to effectively construct a path linking the initiating solution and the guiding solution, and a reference solution determination mechanism based on two kinds of improvement methods. We evaluate the performance of TS/PR on almost all of the benchmark JSP instances available in the literature. The test results show that TS/PR obtains competitive results compared with state-of-the-art algorithms for JSP in the literature, demonstrating its efficacy in terms of both solution quality and computational efficiency. In particular, TS/PR is able to improve the upper bounds for 49 out of the 205 tested instances and it solves a challenging instance that has remained unsolved for over 20years.
•A physical store fulfills orders for both online and offline customers.•We propose the strategy for deciding the buy-online-pick-up-in-store service area.•We provide retailer a guideline for judging ...the product type for in-store pickup.•We ascertain the impacts of order cancellation policies on the optimal decisions.•We prove the superiority of reserve-online-pay-in-store mode over in-store pickup.
Retailers increasingly adopt the buy-online-pick-up-in-store (BOPS) mode of order fulfillment. We study BOPS in this paper by developing a theoretical model in which a physical retailer (store) adopting BOPS uses a recommended service area to fulfill orders from both determined (online) and casual (offline) customers in one order cycle. We obtain three major findings: (i) The ratio of unit inventory cost to BOPS customers’ arrival rate to the store is the key factor that determines the size of the BOPS service area. (ii) From the point of view of product type, we provide the retailer with practical guidelines for judging whether a certain type of product should be allowed for BOPS or not. (iii) When orders can be cancelled, a moderate cancellation policy (MCP) is more beneficial to the retailer than a liberal/strict cancellation policy (LCP/SCP). Furthermore, compared with the reserve-online-pick-up-and-pay-in-store (ROPS) mode, BOPS is less profitable under LCP/SCP, but they have the same profitability under MCP.
Just-in-time job-shop scheduling (JIT-JSS) is a variant of the job-shop scheduling problem, in which each operation has a distinct due-date and any deviation of the operation completion time from its ...due-date incurs an earliness or tardiness penalty. We develop a variable neighbourhood search (VNS) algorithm to solve JIT-JSS. The algorithm operates by decomposing JIT-JSS into smaller problems, obtaining optimal or near-optimal sequences of performing the operations for those smaller problems, and generating a schedule, i.e., determining the completion time of the operations, for JIT-JSS. The algorithm uses several neighbourhood structures, including the new relaxation neighbourhoods developed in this study, to obtain a quality sequence. The relaxation neighbourhoods partially destruct (relax) the sequence and then re-construct (sequence) certain operations. Differing from the classical neighbourhoods, in which manipulations are performed either randomly or myopically, the moves in the new neighbourhoods are made with reference to other operations, so their impacts on the whole sequence are well considered. By solving a set of 72 benchmark instances, ranging from 10 to 20 jobs and 20 to 200 operations, and comparing the outcomes of the proposed algorithm with the state-of-the-art solution methods in the literature, we obtain new best solutions for nearly 57% of the instances, including new best solutions for 80% of the instances with 20 jobs. The computational results demonstrate the efficacy of the proposed VNS algorithm.
We consider the case where a large-scale entry of ride-hailing vehicles have significant impacts on the taxi market, which may result in many taxi drivers being forced to withdraw from the transport ...industry or promote the development of the whole transport industry. Specifically, we examine how an on-demand ride-hailing platform in competition with the traditional taxi industry designs its pricing strategies under the unregulated and regulated pricing scenarios, and we focus on government supervision strategies in the transport industry in view of the development of on-demand ride-hailing platforms and their impacts on both society and the traditional taxi industry. We find that the monopolistic on-demand ride-hailing platform's price rate and profit under the unregulated pricing scenario are relatively higher than those under the regulated pricing scenario. We also find that the government should encourage competition between on-demand ride-hailing platforms and the traditional taxi industry. In addition, the government's regulatory measures should depend on its situation and its degrees of attention to various stakeholders because the adjustment effects of the regulatory measures are different. When the taxi supply is less than customer demand, increasing the total number of taxis is the best regulatory measure, but when the taxi supply exceeds customer demand, the best regulatory measure depends on the specific situation. This suggests that the government should adopt pertinent supervisory policies to maximize the overall social welfare and profit based on the actual situation it is in.
•We consider the case where ride-hailing vehicles have significant impacts on the taxi market.•We examine how an on-demand ride-hailing platform in competition designs its pricing strategies.•Government supervision strategies and their impacts on society and the taxi industry are investigated.•Governments should encourage competition between platforms and taxi industry.
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