Applications of the blockchain technology in supply chains have attracted extensive attention in both academia and industries. However, little research has investigated the effects of the blockchain ...technology on firms' operational strategies. In this paper, we investigate the impacts of the traceability enabled by the blockchain technology on a producer's decision whether to outsource delivery to a third-party logistics firm. We find that without the blockchain technology, the logistics firm has a moral hazard-an incentive to set the delivery quality at the lowest level even though improving the delivery quality is for free. The traceability enabled by the blockchain technology can resolve the logistics firm's moral hazard and encourage the producer to improve the production quality. Furthermore, when the delivery is cost-efficient for the producer, the traceability enabled by the blockchain technology motivates the producer to outsource the delivery to the logistics firm; otherwise, the producer's outsourcing decision is not affected. When quality cost is low, the blockchain technology makes the logistics firm improve its delivery quality significantly and encourages the producer to improve the production quality. When the quality cost is moderate, only under certain conditions, the blockchain technology has effects on both parties' decisions.
The concept “new retail” in e-commerce is to establish an offline channel and integrate it with the online retail channel. The development of new retail encounters three main problems: locations of ...the offline stores, the price competition with the traditional online retail, and the difficulty in consumer recognition in the two channels. In this paper, we present a duopoly model consisting of a new retail firm and an online firm, which sell the same product in two periods. The two firms compete for the market share using the behavior-based pricing (BBP), which means that in the second period each firm offers different prices to consumers with different purchasing histories/behaviors in the first period. We also solve the benchmark pricing model, where the histories/behaviors are not considered. The results of this paper provide valuable insights to the development of new retail in e-commerce. In the Nash equilibrium, each price of the new retail firm is higher than the corresponding price of the online firm due to a higher channel cost for the offline stores and high-speed deliveries. Under certain condition, the new retail firm will establish an offline channel with a larger hassle cost, which is a measure of the easiness of reaching the offline stores by the consumers, in the BBP model than that in the benchmark model. Interestingly, the difficulty in consumer recognition results in that the new retail firm occupies more market share and may obtain higher profit.
Carbon emission abatement is a hot topic in environmental sustainability and cap-and-trade regulation is regarded as an effective way to reduce the carbon emission. According to the real industrial ...practices, sustainable product implies that its production processes facilitate to reduce the carbon emission and has a positive response in market demand. In this paper, we study the sustainability investment on sustainable product with emission regulation consideration for decentralized and centralized supply chains. We first examine the order quantity of the retailer and sustainability investment of the manufacturer for the decentralized supply chain with one retailer and one manufacturer. After that, we extend our study to the centralized case where we determine the production quantity and sustainability investment for the whole supply chain. We derive the optimal order quantity (or production quantity) and sustainability investment, and find that the sustainability investment efficiency has a significant impact on the optimal solutions. Further, we conduct numerical studies and find surprisingly that the order quantity may be increasing in the wholesale price due to the effects of the sustainability and emission consideration. Moreover, we investigate the achievability of supply chain coordination by various contracts, and find that only revenue sharing contract can coordinate the supply chain whereas the buyback contract and two-part tariff contract cannot. Important insights and managerial implications are discussed.
This paper examines firms' post‐merger integration (PMI) strategy under price and service‐quality competition when facing either deterministic or stochastic demand. Although horizontal mergers are ...prevalent in practice and have been analyzed extensively in the literature, little attention has been paid to the choice of PMI level. We develop a game‐theoretic model, in which multiple firms compete on price and service quality with either deterministic or stochastic demand, and two of them decide whether and how to merge. The post‐merger firm can enjoy higher cost efficiency due to cost synergy and needs to choose between centralized and decentralized mergers (i.e., PMI level). A centralized merger allows centralized decision‐making and inventory pooling for the two participant firms, while a decentralized merger allows decentralized decision‐making and inventory transshipment between the participant firms. We highlight some interesting findings. First, under either deterministic or stochastic demand, we find that a centralized merger is not always beneficial since its collusion effect may induce the nonparticipant firm to adopt more aggressive strategies, and thus a decentralized merger may be more profitable and preferred by the post‐merger firm as it allows competition between the participants and leads to a more balanced market. Second, in a decentralized merger, stronger fixed cost synergy may backfire and hurt each participant as it could intensify service‐quality competition between the two participants, and risk pooling (via inventory transshipment) under stochastic demand may even reduce the participant firms' profits as it may intensify both service‐quality and price competition. Third, a participant firm's service quality, price, and in‐stock probability may be either improved or reduced after merging, depending on the PMI level, cost synergy, demand sensitivity, and demand uncertainty.
We consider three‐agent scheduling on a single machine in which the criteria of the three agents are to minimize the total weighted completion time, the weighted number of tardy jobs, and the total ...weighted late work, respectively. The problem is to find the set of all the Pareto‐optimal points, that is, the Pareto frontier, and their corresponding Pareto‐optimal schedules. Since the above problem is unary NP‐hard, we study the problem under the restriction that the jobs of the first agent have inversely agreeable processing times and weights, that is, the smaller the processing time of a job is, the greater its weight is. For this restricted problem, which is NP‐hard, we present a pseudo‐polynomial‐time algorithm to find the Pareto frontier. We also show that, for various special versions, the time complexity of solving the problem can be further reduced.
We consider the single‐machine Pareto‐scheduling problem to minimize the weighted number of tardy jobs and total weighted late work simultaneously. The problem is to find the set of all the ...Pareto‐optimal points, that is, the Pareto frontier, and their corresponding Pareto‐optimal schedules. We consider the corresponding weighted‐sum scheduling problem and primary‐secondary scheduling problems, being subproblems of the general Pareto‐scheduling problem. The NP‐hardness of the general problem follows directly from the NP‐hardness of the two constituent single‐criterion problems. We present a pseudo‐polynomial algorithm and a fully polynomial‐time approximation scheme (FPTAS) running in weakly polynomial time to deal with the general problem. When all the jobs have a common due date, we further provide an FPTAS running in strongly polynomial time. We also study some special cases of the general problem where the jobs have equal processing times, a common due date, or a common weight, and analyze their computational complexity status.
Modular integrated construction (MiC) becomes a promising solution to improve production efficiency in the construction industry. However, the off‐site production and on‐site installation processes ...of MiC pose challenges to collaboration efficiency among the multiple stakeholders involved, including subcontractors, contractors, and consumers. These challenges stem from information dispersion, which impedes effective collaboration and communication. Such problems can be solved by introducing a blockchain‐based cyber‐physical service platform, which can facilitate information sharing and collaboration across the supply chain. In this paper, we study the impacts of MiC and blockchain technology on construction supply chains and reveal several important insights. First, we find that there exists a first‐mover advantage in the traditional construction supply chain, where subcontractors engage in a sequential game, and the subcontractor who produces first obtains more profit than the counterparts. Moreover, the contractor's ability to increase profits by reducing the unit cost of construction time is limited, but it can improve the effectiveness of the time gap due to early delivery. Second, we show that MiC should not be introduced if it significantly reduces collaboration efficiency in the supply chain. Interestingly, increasing the unit cost of construction for subcontractors can actually result in greater profits for all members of the supply chain. Regarding adopting blockchain technology, our findings suggest that supply chain members generally hold similar attitudes. Specifically, when the value of blockchain in improving collaboration efficiency is below a certain threshold, its adoption may not be beneficial, despite its potential to enable rapid production and early delivery.
ABSTRACT
In this article we consider operational risk and use data analytics to estimate the credit portfolio risk. Specifically, we consider situations in which managers need to make the optimal ...operational decision on total provision for risk to hedge against the potential risk in the entire supply chain. We build a new structural credit model integrated with data analytics to analyze the joint default risk of credit portfolio. Our model enables the decision maker to better assess the risk of a supply chain, so that they could determine the optimal operational decisions with total provision for risk, and react in a timely manner to economic and environmental changes. We propose an efficient simulation method to estimate the default probability of the credit portfolio with the risk factors having the multivariate t‐copula. Moreover, we develop a three‐step importance sampling (IS) method for the t‐copula credit portfolio risk measurement model to achieve an accurate estimation of the tail probability of the credit portfolio loss distribution. We apply the Levenberg–Marquardt algorithm to estimate the mean‐shift vector of the systematic risk factors after the probability measure change. Besides, we empirically examine the changes in the credit portfolio risks of 60 listed Chinese firms in different industries using our proposed method. The results show that our model can help the decision maker make the optimal operational decisions with total provision for risk, which hedges against the potential risk in the entire supply chain.
In this article, we study bicriterion Pareto‐scheduling on a single machine of equal‐length jobs, where one of the criteria is the total weighted late work. Motivated by two Pareto‐scheduling open ...problems where one criterion is the total (weighted) late work and the other criterion is the weighted number of tardy jobs, we show that 12 constrained scheduling problems unaddressed in the literature are binary NP$$ NP $$‐hard, implying that the Pareto‐scheduling versions of these problems are also binary NP$$ NP $$‐hard. Moreover, we introduce the concept of dummy due dates (DDD) for equal‐length jobs to be scheduled in equal‐length intervals. Intriguingly, we find that a DDD‐based technique outperforms the existing solution methods and improves the known time complexities of the related problems. In addition, we extend our research to the two‐agent scheduling model under the assumption of equal‐length or partially equal‐length jobs by including the total weighted late work as the criterion of one agent. For these problems, our results also improve the known time complexity results.
Facing the growing concern of environmental impact, green service (GS) has emerged as an important research topic in production and operations management. However, empirical research on GS is ...hindered by the lack of theoretically developed and empirically validated measurement scales covering various practices in service operations of a supply chain. GS indicates the strategic orientation of firms in developing a combination of practices and routines to reduce environmental impact in service operations that span from product development to servicing customers. Grounded in the natural resource‐based view (NRBV), this study conceptualizes GS from the supply chain perspective and in the consumer‐product context to develop a GS measurement model. Collecting secondary and primary data in both qualitative and quantitative forms, this study reports the development of GS multi‐item measurement scales using a multi‐method research design that combines interviews, content analysis, and mass survey. GS is operationalized as a multi‐dimensional construct reflecting three complementary dimensions, namely pollution prevention‐, product‐, and long‐term development‐oriented GS practices, where each of them comprises three sub‐dimensions, resulting in a total of 34 measurement items. The empirically validated scales can be used to advance theory and practices of GS, while providing a useful reference for firms to evaluate their GS efforts, and identify areas for improvement.
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