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The purpose of this paper is to present a new method and model for determining the optimal decision-making for the pricing strategy to the Fuji apple in Shaanxi of Chain which is representing fresh agricultural products under the e-commerce environment.

Considering the rapid development of information technology as well as internet that actually motivate the e-commerce, Fuji apple is a distinctive product in China’s Shaanxi; its sales channels have extended to online sales under the wave of e-commerce. Internet trading platforms make it possible to trade online in real time between suppliers and customers who live in different geographical areas. In this paper, the authors study how to price online to maximize the total revenue. The challenge is to optimally price two different qualities of apple. Based on the consumer surplus theory, the authors use the method that builds the function of the relationship between the proportion of consumers purchasing different qualities of products and price.

This paper presents a generalized model to determine the optimal pricing that maximizes the total revenue of a fruit grower over a finite planning horizon. The authors divided discount into two intervals and discussed the optimal discounting and pricing at both intervals. Then they determined the optimal pricing strategy for Fuji apple in Shaanxi of Chain under the e-commerce environment.

This paper makes up for the lack of existing studies of pricing under the e-commerce environment. A new method and approach to the traditional pricing strategy is established and applied to a management decision-making problem with Chinese characteristics in reality.

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.

The purpose of this paper is to propose a three-way group decision-making approach to address the selection of green supplier, by extending decision-theoretic rough set (DTRS) into hesitant fuzzy linguistic (HFL) environment, considering the flexible evaluation expression format of HFL term set (HFLTS) and the idea of minimum expected risk in DTRS.

Specifically, the authors first present the calculation method of the conditional probability and discuss the loss functions of DTRS with HFL element (HFLE), along with some associated properties being investigated in detail. Further, three-way group decisions rules can be deduced, followed by the cost of every green supplier candidate. Thus, based on these discussions, a novel green supplier selection DTRS model that combines multi-criteria group decision-making (MCGDM) and HFLTS is designed.

A numerical example of green supplier selection, the comparative analysis and associated discussions are conducted to illustrate the applicability and novelty of the presented model.

The selection of green supplier has played a critically strategic role in sustainable enterprise development due to continuous environmental concerns. This paper offers an insight for companies to select green supplier selection from the perspective of three-way group decisions.

This paper uses three-way decisions to address green supplier selection in the HFL context, which is considered as a MCGDM issue.

The purpose of this paper is to present a measure method of the uncertainty for rough fuzzy set based on general binary relation.

Rough set and fuzzy set are two different but complementary theories for expressing uncertainty information, and based on the combination of these two uncertainty theories of expressing and handling uncertainty information, the rough fuzzy set model and uncertainty measure based on general relation are discussed.

This paper reveals the intrinsic of the uncertainty for rough fuzzy set based on general relation and presents a new measure method by introducing the Shannon entropy to generalized approximation space.

The paper contributes to the discussion on the research of rough set and fuzzy set. The conclusions are useful in information processing with uncertainty.

The purpose of this paper is to present a new method for evaluation of emergency plans for unconventional emergency events by using the soft fuzzy rough set theory and methodology.

In response to the problems of insufficient risk identification, incomplete and inaccurate data and different preference of decision makers, a new model for emergency plan evaluation is established by combining soft set theory with classical fuzzy rough set theory. Moreover, by combining the TOPSIS method with soft fuzzy rough set theory, the score value of the soft fuzzy lower and upper approximation is defined for the optimal object and the worst object. Finally, emergency plans are comprehensively evaluated according to the soft close degree of the soft fuzzy rough set theory.

This paper presents a new perspective on emergency management decision making in unconventional emergency events. Also, the paper provides an effective model for evaluating emergency plans for unconventional events.

The paper contributes to decision making in emergency management of unconventional emergency events. The model is useful for dealing with decision making with uncertain information.

X-ray pulsar navigation (XPNAV) is an autonomous celestial navigation technology for deep space missions. The error in the pulse time of arrival used in pulsar navigation is large for various practical reasons and thus greatly reduces the navigation accuracy of spacecraft near the Earth and in deep space. This paper aims to propose a novel method based on ranging information that improves the performance of XPNAV.

This method replaces one pulsar observation with a satellite observation. The ranging information is the difference between the absolute distance of the satellite relative to the spacecraft and the estimated distance of the satellite relative to the spacecraft. The proposed method improves the accuracy of XPNAV by combining the ranging information with the observation data of two pulsars.

The simulation results show that the proposed method greatly improves the XPNAV accuracy by 70% compared with the conventional navigation method that combines the observations of three pulsars. This research also shows that a larger angle between the orbital plane of the satellite and that of the spacecraft provides higher navigation accuracy. In addition, a greater orbital altitude difference implies higher navigation accuracy. The position error and ranging error of the satellite have approximately linear relationships with the navigation accuracy.

The novelty of this study is that the satellite ranging information is integrated into the pulsar navigation by using mathematical geometry.

The purpose of this paper is to investigate the vibration suppression of industrial track robot and propose a practical solution.

Root‐cause analysis through dynamic modeling, and vibration suppression using the acceleration smoother.

The vibration is due to insufficient damping based on the model analysis. The solution achieved significant performance improvement without redesign of robot hardware and controller.

The design of the proposed acceleration smoother is still empirical based, which is unable to achieve optimal design.

This solution is very easy to implement. It is robust, reliable and is able to generate consistent results.

A very practical industrial solution, especially useful for upgrading the existing systems in the field without redesign the hardware and controller.

This paper aims to explore the influence of social support and the repatriation intention of expatriates in international constructions in the postpandemic era of COVID-19. Furthermore, test the mediation effect of team climate and individual resilience in this relationship.

A survey of 347 expatriates in international construction projects was conducted. A cross-level chain mediation model was employed to test the moderating effect of social support and repatriation intention. Then, statistical analysis with a bootstrap sample was used to test the mediation effect of the model.

The empirical results support that team climate, individual resilience and the chain mediating effect of team climate to individual resilience is significant among the influences of social support on repatriation intention. Social support can enhance the team climate of construction expatriates, promoting their resilience to reduce the repatriation intention further.

This study provides guidelines for international construction enterprises and managers to decide when and which expatriates should return home and formulate a series of policies to support expatriates and maintain a good team climate.

This study contributes to expatriate management literature by establishing the relationship between social support and repatriation intention. It provides a better understanding of how team-level factors impact individual thought. It takes team climate as one of the protective factors affecting individual psychological resilience. Also it takes social support as the antecedents of team atmosphere in case of emergencies.

This paper aims to propose two portfolio selection models with hesitant value-at-risk (HVaR) – HVaR fuzzy portfolio selection model (HVaR-FPSM) and HVaR-score fuzzy portfolio selection model (HVaR-S-FPSM) – to help investors solve the problem that how bad a portfolio can be under probabilistic hesitant fuzzy environment.

It is strictly proved that the higher the probability threshold, the higher the HVaR in HVaR-S-FPSM. Numerical examples and a case study are used to illustrate the steps of building the proposed models and the importance of the HVaR and score constraint. In case study, the authors conduct a sensitivity analysis and compare the proposed models with decision-making models and hesitant fuzzy portfolio models.

The score constraint can make sure that the portfolio selected is profitable, but will not cause the HVaR to decrease dramatically. The investment proportions of stocks are mainly affected by their HVaRs, which is consistent with the fact that the stock having good performance is usually desirable in portfolio selection. The HVaR-S-FPSM can find portfolios with higher HVaR than each single stock and has little sacrifice of extreme returns.

This paper fulfills a need to construct portfolio selection models with HVaR under probabilistic hesitant fuzzy environment. As a downside risk, the HVaR is more consistent with investors’ intuitions about risks. Moreover, the score constraint makes sure that undesirable portfolios will not be selected.