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Fresh product loss rates in supply chain operations are particularly high due to the nature of perishable products. The purpose of this paper is to maximize profit through the contract between retailer and supplier. The optimized prices for the retailer and the supplier, taking the fresh-keeping effort into consideration, are derived.

To address this issue, the authors consider a two-echelon supply chain consisting of a retailer and a supplier (i.e. wholesaler) for two scenarios: centralized and decentralized decision making. The authors start from investigating the optimal decision in the centralized supply chain and then comparing the results with those of the decentralized decision. Meanwhile, a fresh-keeping cost-sharing contract and a fresh-keeping cost- and revenue-sharing contract are designed. Numerical examples are provided, and managerial insights are discussed at the end.

The results show that the centralized decision is more profitable than the decentralized decision; a fresh product supply chain (FPSC) can only be coordinated through a fresh-keeping cost- and revenue-sharing contract; the optimal retail price, wholesale price and fresh-keeping effort can all be achieved; and the profit of a FPSC is positively related to consumers’ sensitivity to freshness and negatively correlated with their sensitivity to price.

This research is based on the assumption that demand is relatively stable. It has not addressed when demand is stochastic.

The findings would be useful for managers in fresh food sector in terms of how to deal with suppliers in order to maximize total profit while also provide freshest food to the customers.

Few studies have considered fresh-keeping effort as a decision variable in the modelling of supply chain. In this paper, a mathematical model for the fresh-keeping effort and for price decisions in a supply chain is developed. In particular, fresh-keeping cost-sharing contract and revenue-sharing contract are examined simultaneously in the study of the supply chain coordination problem.

Using information systems via data mining and cluster analysis technologies, consumers' strategic behaviour can be measured, and their patience levels can be accurately described. This paper investigates the retailer's pricing and ordering policies when facing strategic consumers with different levels of patience and discusses the impacts of consumers' patience levels and proportions on retailers' maximum expected profits.

By cluster analysing transaction data on the number of websites visited, browsing time and purchase decision time, consumers' patience levels can be obtained. The authors formulate a newsvendor model considering customers' different patience levels. Three scenarios are investigated: two segments of consumers with two different levels of patience (Scenario I), multiple segments of consumers with different levels of patience (Scenario II) and a continuum of consumers whose levels of patience follow a continuous distribution (Scenario III). Then, general formulas are deduced for retailers' optimal prices, ordering quantities and profits.

Under Scenario I, if the proportion of less patient consumers is greater (less) than a threshold, the retailer's optimal price is equal to the less (more) patient consumers' reserve price. Under Scenario II, once the proportion of fully strategic consumers exceeds a certain threshold, the retailers' optimal price is equal to the fully strategic consumers' reserve price regardless of consumers' patience levels and proportions. Under Scenario III, the retailer's pricing and ordering policies depend on the distribution of their patience level.

Few studies have considered consumers' different levels of patience when making retailer pricing and ordering decisions. In this paper, strategic consumer behaviour is measured, and consumers' patience levels and proportions are obtained by cluster analysing consumer transaction data recorded by an information system. Three scenarios in which strategic consumers may be heterogeneous and have different patience levels are investigated. The results can guide retailer decision-making.

With the development of e-commerce and mobile payment, platform sales become unstoppable, and many manufacturers also encroach on online market by establishing direct selling channels. Channel conflict intensifies in online market and quality differentiation and is widely used in business practice as an effective way to alleviate such a competition. The authors study a retail platform's sales strategy and interactions with an upstream manufacturer's encroachment strategy in this paper. Unlike most online marketplace and encroachment research, product quality selection is also engaged in the present research to capture the motivation above.

The authors analyze a game-theoretical model that the platform as the first/second mover participates in strategic decision-making, and then jointly decides the product quality level with manufacturer.

The authors find that encroachment always profits the manufacturer and almost hurts the platform. Interestingly, the first-mover advantage can help the platform guide the manufacturer encroachment and promote a “win–win” situation when product quality level is relatively slight or obvious. Nevertheless, the second-mover advantage can help the platform alleviate the profit loss caused by encroachment when product quality level is moderate. Furthermore, suffered from encroachment loss, the platform can make a credible threat by sales termination to restrain manufacturer encroachment.

This paper innovatively explores the strategic interaction between manufacturer encroachment and quality differentiation in a platform supply chain, and further analyzes the first-mover advantage in this interaction, which fills the gaps of previous platform research and has great significances to enterprise production and operational decision in business practice.

The purpose of this paper is to find the optimal power structure that drives green practices in the supply chain and coordinate the costs and benefits of green practices in supply chain under different power structures.

This paper developed a supply chain of one supplier and one manufacturer, in which the supplier and the manufacturer are responsible for the “greening” of products. Then, the game theory modeling method is used to explore the influence of different power structures on green practices in the supply chain. Finally, the authors developed a green cost-sharing contract made by the leader; regarding optimal supply chain profits and green performance, the proposed contracts and the non-coordination situation are compared and tested by a numerical simulation.

The increase of the green practice difficulty of any member in the supply chain will not only reduce the greenness of products at that stage but will also reduce the green investment of the supply chain partner. Becoming a channel leader does not necessarily mean being more profitable than being a follower, and when the green practice difficulty of the leader is less than a certain threshold, ceding dominant power to the follower may benefit both sides. A green cost-sharing contract made by the leader is not necessarily beneficial to all enterprises.

This paper helps to better understand the role of the power relation in realizing the industry's green goals and helps decision-makers to achieve win-win cooperation by adjusting power relations and optimizing green cost-sharing contracts.

The purpose of this paper is to find the optimal environmental quality criteria for a strategic eco-labeling authority with three objectives (i.e. maximizing the aggregate environmental quality, maximizing the industry profit and maximizing the social welfare). Particularly, the authors investigate how the existence of imperfectly informed consumers affects labeling criteria determination and competition among firms.

A game-theoretic modeling approach was adopted in this paper. A three-stage sequential game was modeled and backward induction was used to solve for a subgame perfect Nash equilibrium. To investigate the impacts of the existence of imperfectly informed consumers, the equilibrium, if all consumers are perfectly informed of the eco-label, was studied as a benchmark.

A more strict eco-labeling criterion improves revenues for both the labeled and unlabeled firms. It is interesting to find that the eco-labeling criteria to maximize industry profits are stricter than the criteria to maximize social welfare. Moreover, when the fraction of imperfectly informed consumers increases, the eco-labeling criteria to maximize aggregate environmental quality or industry profits will be more strict, while the criteria to maximize the social welfare will be looser.

The authors analyze the equilibrium strategies for firms against the eco-labeling criteria certified by authority with different objectives. The obtained optimal labeling strategies could provide insightful guidelines for the certifying authority to select the best suitable labeling criteria to achieve its goals.

With the booming of live commerce, sellers provide products through not only their traditional channels but also the anchors who show products by live broadcast, forming a live commerce supply chain. In fact, such selling mode generates two effects: the live broadcast service of the anchor affects the return rate of products sold live (live commerce effect) and related products of the manufacturer sold via its own channel (live commerce spillover effect). In this paper, the authors investigate the impacts of both live commerce and live commerce spillover effect on the price decisions as well as the anchor's service effort.

The authors establish a live commerce supply chain model where the manufacturer sells related products directly and by the anchor with a wholesale price contract. The manufacturer decides the price of product sold directly based on the anchor's broadcast effort since there exists the live commerce spillover effects. Backward induction is used to solve the Stackelberg game between the manufacturer and the anchor.

The results show that (1) the existence of the live commerce spillover effect brings more profit to the manufacturer while it reduces the anchor's profit. Moreover, the total profit of the live commerce supply chain first decreases and then increases as the intensity of the live commerce spillover effect improves. (2) The pricing of products sold directly by the manufacturer and sold through the anchor is nonmonotonic with respect to the live commerce spillover effect. (3) The increase in return cost always leads to an increase in the profit of the anchor, whether it is borne by the anchor or by the consumer. (4) If the baseline return probability is high, the anchor should increase her effort, thus securing more profit. However, the spillover effect of live commerce and the horizontal differences between products will discourage the anchor from increasing the live streaming service level.

The study proposes the live commerce supply chain model where the anchor balances the cost and benefit of her live broadcast effort, which lowers the consumers expected return possibility. In addition the live commerce spillover effect is introduced, reducing the expected return rate for the related products without live broadcast (in the direct channel). With the inter-influence of live commerce, the price competition between the live anchor and the manufacturer becomes more complex. By solving the typical live commerce game model, managerial insights are given for the decision makers among the live commerce supply chain.

The purpose of this paper is to compare and evaluate the personal cloud storage products (PCSPs) in China and find the gap among them for promoting their service level. There are five representative products including Baidu cloud, Tencent cloud, Qihoo 360-cloud, Kingsoft cloud and Huawei DBank.

This study, first, extracts corresponding indicators based on the extant literature to evaluate PCSPs, and then collects the data about each index by investigation and the performance test, finally proposes a model to rank PCSPs, which applies analytic hierarchy process (AHP) to determine the indexed weights and the technique for order preference by similarity to ideal solution-grey relational analysis calculate evaluation score of each PCSP.

Among them, Qihoo 360-cloud gets the highest evaluation score contributed by large space, file editing and fast transmission speed. The rest are Kingsoft cloud, Baidu cloud, Huawei DBank and Tencent cloud in order. These storage products are all want of the addition or improvement of the online editing service similar as Google Docs.

AHP method is subjective, some of the data is incomplete, and some accidental error and systematic error exist in the actual testing process.

The findings can assist users in selecting more suitable products and offer cloud storage providers (CSPs) a general direction of improving their product performance.

Contributing to improve the overall level of the cloud storage services in China.

The study perfects the evaluation index system of the PCSP and fills the research gap in studying PCSPs in China, and expands the application field of the multiple criteria decision-making problems. This evaluation process and results have implied that CSPs in China should provide good services of large capacity, cooperation and security with the good internet environment of economical, high and stable speed by institutions and internet access providers.

This study aims to investigate the production and abrasive wear rate of functionally graded TiB₂/Al composites. TiB₂ particles have been spontaneously formed in liquid matrix using in situ technique. The properties of composites such as hardness, abrasive wear rate and microstructure have been examined.

In situ TiB₂ reinforcement phase was synthesized by using a liquid Al–Ti–B system. A semi-solid composite (Al_(l)-TiB_2(s)) prepared at 900°C was solidified under a centrifugal force to both grade functionally and give the final shape to materials. Abrasive wear test of materials was conducted using the pin-on-disk method at room temperature. The wear tests were carried out with two different loads of 1 Newton (N) and 2 N, a sliding velocity of 3.5 m s⁻¹ and a sliding distance of 75 m.

This research provided the following findings; TiB₂ particles can be successfully synthesized with in situ reaction technique in molten aluminum. It was determined that abrasive wear rate increases with increasing load and decreases with increasing TiB₂ reinforcement content within matrix.

In previous studies, there have been many trials on the in situ production of TiB₂-reinforced aluminum matrix composites. However, there are few studies on production of in situ TiB₂-reinforced aluminum matrix functionally graded materials. At the same time, there is no study that the properties of composite, such as hardness and abrasive wear rate, are examined together according to centrifugal force.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2019-0538/

A vital job for one sharing business is dynamically dispatching shared items to balance the demand-supply of different sharing points in one sharing network. In order to construct a highly efficient dispatch strategy, this paper proposes a new dispatching algorithm based on the findings of sharing network characteristics.

To that end, in this paper, the profit-changing process of single sharing points is modeled and analyzed first. And then, the characteristics of the whole sharing network are investigated. Subsequently, some interesting propositions are obtained, based on which an algorithm (named the Two-step random forest reinforcement learning algorithm) is proposed.

The authors discover that the sharing points of a common sharing network could be categorized into 6 types according to their profit dynamics; a sharing network that is made up of various combinations of sharing stations would exhibit distinct profit characteristics. Accounting for the characteristics, a specific method for guiding the dynamic dispatch of shared products is developed and validated.

Because the suggested method considers the interaction features between sharing points in a sharing network, its computation speeds and the convergence efficacy to the global optimum scheme are better than similar studies. It suits better to the sharing business requiring a higher time-efficiency.