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This paper investigates how the channel leadership strategies develop a post-coronavirus disease (COVID-19) resilient agri-supply chain, which reduces supplier and retailer's price loss and enhances the logistics service quality level considering logistics outsourcing of agri-product especially for the rapidly changing market condition.

Based on the classical leadership theory, two channel leadership strategies, i.e. LPL and SL, are considered. The proposed framework first derives the equilibrium price and service quality level decision among the supplier, the logistics provider and the retailer. Then it compares both leadership strategies in terms of the equilibrium prices and service quality theoretically. This article also presents a case study of Arabian dates pricing and supply chain to test the theoretically derived propositions.

Selection of suitable leadership strategy is a critical factor for profit maximization of the supply chain drivers and proper optimization of equilibrium price and service quality. Here, the product's quality and the market's socio-economic condition play an important role in selecting a suitable leadership strategy. A random transformation of the physical market to an e-commerce portal creates a wide variation of the market's socio-economic parameters, affecting the equilibrium pricing and the logistics provider's service quality.

This study proposes a post-COVID-19 resilient agri-supply chain framework considering price and quality-dependent stochastic market demand, incorporating a wide range of socio-economic factors in the model to counteract the effect of rapid behavior change of agri-market due to COVID-19 norms. This research examines the effect of different channel leadership strategies to facilitate suitable decisions on prices and service quality and retrieve the profit of the supplier, retailer and logistics provider. The future models can incorporate competitiveness in logistics outsourcing, fourth-party logistics (4PL) and contract farming in the agri-supply chain. Each of the extensions can open avenues in different directions.

As the post-COVID-19 market and the customer behavior is randomly changing, and the traditional market is rapidly converting into supermarkets and e-commerce portals, this paper examines the model with a wide variety of e-commerce portals with multi-variation of product. It is conclusive that the product's quality and the market's socio-economic behavior significantly impact the equilibrium decision. The drivers of the supply chain must take them into account before choosing a particular channel leadership strategy.

This study considers a multi-product and multi-market (e-commerce) model by integrating a wide variety of products and the market's socio-economic parameters. The model is tested in a price and quality-dependent stochastic market condition, contributing to the literature by reconciling two different channel leadership strategies into the global logistics of fresh agri-product.

With refineries contributing 68% of CO₂ emissions from stationary combustion sources alone, smart technologies and the circular economy (CE) model for resource loop optimization can be a solution for carbon neutrality, especially within petroleum. Thus, this study aims to explore energy conservation by green technology improvement as a CE strategy for resource loop optimization and digital incorporation to maximize reprocessing lead ability rate and carbon-neutral benefits.

A game theory approach with Stackelberg equilibrium is considered under government cap-and-trade regulation to stimulate green technology improvement. The refinery acts as a Stackelberg leader and invests in green technology and the retailer as the Stackelberg follower, collects end-of-life lubricants against refund price and offers a two-part-tariff contract to the manufacturer having a significant role in smart technologies.

First, green technology improvement is directly influenced by the reprocessing capability and refund price and digital technologies are significant to consider. Second, a two-part-tariff contract coordinates the supply chain for limited reprocessing capability by the retailer. Lastly, the government can effectively manipulate the development of green technology by changing the permit price depending on the intentions.

The primary limitation is this study has focused on the petroleum sector and data was referenced from the oil refineries of a single country.

Overall, this study provides empirical guidance for policymakers on how to leverage energy-efficient smart technologies for lubricant reprocessing, enabling resource optimization as part of a CE strategy in the petroleum industry and advancing sustainable development goals.

The suggested model responds to the contemporary literature related to CO₂ emissions and CE initiatives across the petroleum sector with the extended role of smart technologies and government cap-and-trade regulations.

Different information sharing mechanisms and online platform information sharing to different charging models are compared and analyzed.

This paper uses the Stackelberg game model to study the demand information sharing and pricing decisions.

The results show that: (1) the retailer's pricing strategy is the highest when both of them obtain information, while the manufacturer's pricing strategy is affected by the related attributes of different products, such as the sensitivity of consumers to product prices; (2) in the online platform sales model, the demand information data sharing owned by the online platform can bring more expected profits to the whole supply chain and the members of the supply chain, and the higher the accuracy of the information, the higher the expected profit; (3) when the cost of obtaining demand information is zero, that is, the online platform shares the information data about market demand free of charge, the retailer and manufacturer tend to obtain information; (4) for the online platform, charging a certain fee can achieve higher expected profits than free sharing.

Based on the single platform online sales model, this paper uses the Stackelberg game model to study the demand information sharing and pricing decision of a manufacturer and a retailer selling products through the same online platform.

This study aims to establish a centralized decision-making game model and manufacturer-led Stackelberg game model based on factors of risk aversion of supply chain members and product greenness. The research aims to study whether the introduction of the “cost + risk sharing” contract affects coordination of this type of green supply by calculating the optimal decision of each mode.

This research designs a supply chain model under centralized and decentralized decision-making. This model uses the Stackelberg game to calculate the optimal decision under decentralized decision-making to evaluate the effect of a green supply chain and then analyze the “cost + risk sharing” contract and the degree of coordination of the supply chain. A sensitivity analysis is conducted on the centralized mode for the impact of variables on the supply chain.

This research finds a double marginalization effect in decentralized decision-making, and the risk aversion coefficient plays a decisive role in the utility of supply chain members. The specific range of risk- and cost-sharing factors allows supply chain members to achieve Pareto improvements and provides decision-making based on the corresponding management strategies according to each other’s risk preference degree.

The influence of each variable on the green supply chain in the centralized mode is studied by MATLAB numerical simulation. It provides reference for green supply chain members to formulate corresponding management strategies according to each other's risk preference degree.

This research innovatively considers manufacturers and retailers to explore the market demand for product greenness. It introduces a novel “cost + risk sharing” contract to coordinate the green supply chain.

The purpose of this study is to analyze the short-term development pattern and long-term development trend of the digital supply chain.

This study uses the combination of short-term game and long-term evolutionary game theory.

Findings of this study suggest that irrational decisions can make the evolutionary path of the digital supply chain complex and unpredictable.

This study proposes an evolutionary game model for the digital supply chain that can provide good guidance for the digitalization process of enterprises.

In order to encourage the high-water-consumption (HWC) manufacturers to carry out water-saving transformation relying on self-strength or outsourcing to a water-saving service company (WSSC) during production processes, government subsidies are provided according to water-saving efforts (WSE) or investment cost. In this context, the authors derive the participant's equilibrium decisions and the manufacturer's water-saving strategy. Additionally, the effects of subsidies on WSE and stakeholders' profits are discussed.

Mathematical models including optimization model and Stackelberg game model are constructed under different subsidy schemes.

The study finds that (1) there exists a threshold related to the subsidy coefficient for the HWC manufacturer when choosing between self-saving and outsourcing-saving. (2) When the technological competitive advantage between WSSC and manufacturer is within a certain range, government's subsidy promotes HWC enterprises to choose outsourcing-saving. (3) Given a water-saving mode, subsidy on investment cost is more effective for the government to achieve more environmental performance.

First, subsidy endogeneity can be considered to explore the optimal interval for government subsidies to maximize social welfare. Second, in outsourcing-saving, other types of contract can be discussed. Another extension is about model uncertainties. Finally, other policies on improving water efficiency can be also examined.

The paper includes implication for HWC manufacturers to select the best water-saving mode under subsidy, and it allows policymakers to understand the efficiency of proposed subsidies.

Decisions on water-saving efforts, selection of water-saving modes and operational planning are also regarded as business strategies in the paper. Particularly, the influences of different government subsidies are also considered and compared.

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

This paper explores how the manufacturer’s strategic choice (acquisition or investment) impacts product quality in a supply chain comprising two complementary suppliers and a common manufacturer.

The manufacturer faces six strategic choices to improve product quality: acquiring or investing in the high-capable supplier, the low-capable supplier, or both. As the Stackelberg leader, the manufacturer determines which strategy is adopted, while suppliers are separately responsible for components’ quality and wholesale prices. The authors use game theory and calculate the model with Mathematica.

The authors develop analytical models to analyze how acquisition costs, investment proportions, component importance and quality improvement coefficients influence decision-makers. The results show that the highest quality may not benefit the manufacturer. Investing in or acquiring a low-capable supplier is better than a high-capable supplier under certain conditions. If the gaps between two suppliers’ quality improvement coefficients and the importance of two components are dramatic, the manufacturer should choose an investment strategy.

This study contributes to the complementary supply chain management by comparing two kinds of strategies-acquisition and investment, with a high-capable supplier and a low-capable supplier.

Industry practice has shown that technology licensing has an important effect on the R&D cooperation between firms. Different licensing methods will significantly impact a supply chain member's cooperative and price R&D decisions. However, there is scant literature investigating the decision on technology licensing and its impact on a supply chain member's price and cooperative R&D decisions. To address this gap, the authors investigate the R&D cooperation and the technology licensing in a supply chain formed of an original equipment manufacturer (OEM), a contract manufacturer (CM), and a third-party manufacturer which will compete with the OEM when the technology licensing occurs.

The authors investigate two licensing patterns, royalty licensing, fixed fee licensing together with the no licensing, within the R&D cooperative supply chain by developing two three-stage and a two-stage Stackelberg models.

Compare to the no licensing strategy, technology licensing always benefits to the OEM and the society especially when the technology efficiency and the brand power of the third-party manufacturer are more significant; the royalty licensing benefits to the OEM more when the technology efficiency and the brand power of the third-party manufacturer are higher; the fixed fee licensing benefits to the OEM more when the technology efficiency and the brand power of the third-party manufacturer are lower.

The royalty licensing is more effective for mitigating price competition intensity and helping firms to maintain higher sales margins; the fixed fee licensing induces firms' lower sales margins but increases the firms' sales quantities; in most cases, the fixed fee licensing is optimal from the perspectives of consumer and society, however, the CM's investment intention to the R&D technology with the fixed fee licensing is lower.

So far, different licensing models under the R&D cooperation have not been investigated, and the authors propose two three-stage Stackelberg models with considering the competition caused by technology licensing under the R&D cooperation to deal with the cooperative R&D and technology licensing issues.

Hotels are considered one of the keys to tourism industry, without which it is impossible to visualize this industry. Setting the proper price for hotels has always been a nuisance for the decision makers because of its direct relationship with the demand for hotels. Thus, in the current study a Stackelberg game between the government (leader) and the hotels (follower) has been presented to determine the optimal price under competitive conditions. The selected hotels are different with respect to energy consumption and the environmental impact. Thus, the government makes efforts to control their prices with incentives and tariffs.

The fuzzy inference system (FIS) has also been applied to forecast the hotel demand. Therefore, first off, the demand forecast criteria have been chosen by the experts and in the continuation, it has been screened by fuzzy Delphi approach. Finally, the quantity of hotel demand is computed by the Mamdani inference system. A mathematical model has been presented for determining the optimal sequencing of hotels and minimizing the searches to find a hotel.

A case study based on the data extracted from online travel agencies (OTAs) has been presented to validate the proposed model. The results demonstrate that by the ranking position increase, the number of the tourists decreases and the higher the star number of a hotel, the lower its ranking position.

Considering the energy saving and environmental impacts in hotel pricing and considering the government's intervention in hotel revenues regarding the incentives and tariffs are the innovations of the present study.