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The uncertainty of the interval variable is represented by interval factor, and the interval variable is described as its mean value multiplied by its interval factor. Based on interval arithmetic rules, an analytical method of interval finite element for uncertain structures but not probabilistic structure or fuzzy structure is presented by combining the interval analysis with finite element method. The static analysis of truss with interval parameters under interval load is studied and the expressions of structural interval displacement response and stress response are deduced. The influences of uncertainty of one of structural parameters or load on the displacement and stress of the structure are examined through examples and some significant conclusions are obtained.

Interest in reverse logistics (RL) as a critical component of supply chain management (SCM) is gaining more traction with both practitioners and academics. Because of RL’s growing strategic importance, it is imperative to conduct a timely and comprehensive literature review and to identify associated opportunities for future research. The paper aims to discuss these issues.

In this paper, the researchers conduct an extensive bibliometric analysis of published academic articles on RL for the period of 1992-2015. Specifically, the CiteSpace software is utilized to conduct document co-citation analysis and burst detection analysis on 912 selected RL articles and their 22,642 references.

This research identifies the most influential RL research publications/citations in each of the five periods and their research contribution. Using co-citation analysis, the authors are able to identify and illustrate major research themes, knowledge groups, and future research opportunities in the RL field.

In contrast to existing literature review studies in the logistics field, the study uses impact factor as a key article selection criterion. The influential articles identified in this process well represent the core literature and RL body of knowledge and have important implications for future research.

Prior research demonstrated that China's Outward FDI (OFDI) is aimed at sustaining long-term economic growth by promoting industrialization and technological upgrading in the country. However, empirical evidence on the effectiveness of this strategy remains scarce. This study intends to fill this gap by exploiting endogenous changes in industrial productivity stemming from OFDI to examine if China's new strategy to spur OFDI is economically beneficial for the industries involved.

The authors employed the two-step system-GMM and pooled mean group approaches on a panel dataset of 18 Chinese industries over the 2004–2017 period. The industrial sectors are further classified into the state dominated and non-state dominated ones to evaluate whether the productivity growth impact of OFDI varies by the level of ownership structure. Besides, the dataset is further decomposed into the ex ante and ex-post BRI era to test if this initiative has altered the underlying relationship.

The results provide robust evidence that China's OFDI through reverse spillover effects promotes productivity growth in the domestic industries, and such productivity gains are greater for the non-state dominated industries, and the OFDI in the BRI era. The findings suggest that OFDI can act as a catch-up strategy to release excess capacity and acquire technology and smart business practices.

This study is the first attempt to highlight the reverse productivity spillovers associated with OFDI at the industrial level. The study's findings guide the government officials and the practitioners of foreign investment to better understand the implications of their investment projects in terms of technology improvements and to optimize market opportunities.

This study aims to provide a time- and price-sensitive market strategy for merchants to handle the markdown price strategy. The market demand for perishable products is usually price – and quality (freshness) – sensitive. The proper handling of markdown-price strategies can help merchants enhance competitiveness and maximize operational performance.

A markdown strategy consisting of price and markdown time was developed to explore the properties of market strategies based on the dynamic quality evaluation. The strategy considers multiple price discounts and multiple markdown times. The optimal price decisions in each stage and the optimal markdown times were derived during the selling season.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.

The purpose of this paper is to explore the underlying mechanisms through which integration capability and learning capability influence IT outsourcing performance from vendor’s perspective.

This paper develops a moderated mediation model to explain the underlying influence processes of integration capability and learning capability on vendor’s performance. A sample of 237 vendor firms was obtained from China through two separated surveys. The hypotheses were tested with the partial least squares method and bias-corrected bootstrapping method.

The empirical results indicate that external integration capability (EIC) mediates the effect of internal integration capability (IIC) on vendor outsourcing performance, and the relationship between EIC and vendor performance is positively moderated by learning capability, while learning capability has a negative moderating effect on the link between IIC and vendor performance. Further, the conditional indirect effect is suggested. The indirect effect of IIC on vendor performance through EIC becomes non-significant when learning capability is low.

This study highlights the counterintuitive notion that learning capability may not always have uniformly positive effects and figure out the mechanism through which integration capability and learning capability can effectively improve IT outsourcing performance.

The purpose of this paper is to study the use of outsourcing as a mechanism to cope with supply chain uncertainty, more specifically, how to deal with sudden arrival of higher priority jobs that require immediate processing, in an in-house manufacturer's facility from the perspective of outsourcing. An operational level schedule of production and distribution of outsourced jobs to the manufacturer's facility should be determined for the subcontractor in order to achieve overall optimality.

The problem is of bi-criteria in that both the transportation cost measured by number of delivery vehicles and schedule performance measured by jobs’ delivery times. In order to obtain the problem's Pareto front, we propose dynamic programming (DP) heuristic solution procedure based on integrated decision making, and population-heuristic solution procedures using different encoding schemes based on sequential decision making. Computational studies are designed and carried out by randomly generating comparative variations of numerical problem instances.

By comparing several existing performance metrics for the obtained Pareto fronts, it is found that DP heuristic outperforms population-heuristic in both solutions diversity and proximity to optimal Pareto front. Also in population-heuristic, sub-range keys representation appears to be a better encoding scheme for the problem than random keys representation.

This study contributes to the limited yet important knowledge body on using outsourcing approach to coping with possible supply chain disruptions in production scheduling due to sudden customer orders. More specifically, we used modeling methodology to confirm the importance of collaboration with subcontractors to effective supply chain risk management.

The purpose of this paper is to aggregate different preference information in group decision‐making process such as interval preference order, interval utility value, interval number reciprocal comparison matrix, and interval number complementary comparison matrix.

First, the consistency definitions of four kinds of uncertain preference information are defined. Then, the upper‐ and low errors are introduced to solve the inconsistent decision‐making case. Following that, the weight model for each uncertain preference is proposed, respectively.

The aggregation approach based on minimal group deviation errors is suggested in order to obtain the utmost consistent opinion. In addition, the consistency judgment level and consistency extent are defined owing to the aggregation result.

The calculation scale is large, if many decision makers will attend group decision‐making process.

A very useful approach for aggregation of the different preference in group decision‐making case.

Because of differences in knowledge structure, judgment level, and individual preference, decision makers express their judgment preferences via differently structured decision‐making processes. Owing to the complexity and uncertainty of decision‐making problems and the fuzziness of human thought, it is unrealistic to depict complex problems in the certain preference style. For decision‐making preference structures, group decision‐making aggregation approaches include the aggregation on the same kind of preference structure and the different kinds of preference structures. The study on the aggregation of the same kind of preference structure has received a deal of attention, but study into the aggregation of the different kinds of uncertainty preference structures is still a new field.

The purpose of this paper is to explore the underlying mechanisms through which interactivity and fairness perception impart influence on solvers’ continuance intention in crowdsourcing contest settings.

On basis of self-determination theory and social exchange theory, this study focuses on the mediating roles of motivation and platform trust to explain the underlying influence processes of interactivity and fairness perception on continuance intention. A sample of 306 solvers was obtained from an online crowdsourcing platform through two separated surveys. The hypotheses were tested using the partial least squares method and bias-corrected bootstrapping method.

The empirical results indicate that motivation and platform trust together fully mediate the effect of interactivity on continuance intention, and the effect of fairness perception on continuance intention is also fully mediated by motivation and platform trust. While motivation is found to have a stronger mediating effect than platform trust does.

This study contributes to the crowdsourcing research by figuring out the pathway through which interactivity and fairness perception influence solvers’ continuance intention.

This paper aims to propose a novel method to identify the parameters of robotic manipulators using the torque exerted by the robot joint motors (measured by current sensors).

Previous studies used additional sensors like force sensor and inertia measurement unit, or additional payload mounted on the end-effector to perform parameter identification. The settings of these previous works were complicated. They could only identify part of the parameters. This paper uses the torque exerted by each joint while performing Fourier periodic excited trajectories. It divides the parameters into a linear part and a non-linear part, and uses linear least square (LLS) parameter estimation and dual-swarm-based particle swarm optimization (DPso) to compute the linear and non-linear parts, respectively.

The settings are simpler and can identify the dynamic parameters, the viscous friction coefficients and the Coulomb friction coefficients of two joints at the same time. A SIASUN 7-Axis Flexible Robot is used to experimentally validate the proposal. Comparison between the predicted torque values and ground-truth values of the joints confirms the effectiveness of the method.

The proposed method identifies two joints at the same time with satisfying precision and high efficiency. The identification errors of joints do not accumulate.

This paper aims to present the design and experimental tests of an active circulating cooling system for the Experimental Advanced Superconducting Tokamak in-vessel inspection manipulator, which will help the current manipulator prototype to achieve a full-scale in-vessel high temperature environment compatibility.

The high-temperature effects and heat transfer conditions of the manipulator under in-vessel environment were analyzed. An active circulating cooling system was designed and implemented on the manipulator prototype. A simulative in-vessel inspection task in a high temperature environment of 100°C was carried out to evaluate the performance of the active circulating cooling system.

The proposed active circulating cooling system was proved effective in helping the manipulator prototype to achieve its basic in-vessel inspection capability in a high temperature environment. The active circulating cooling system performance can be further improved considering the cooling structure coefficient differences in different manipulator parts.

For the first time, the active circulating cooling system was implemented and tested on a full-scale of the in-vessel inspection manipulator. The experimental data of the temperature distribution inside the manipulator and the operating status of the circulating system were helpful to evaluate the current active circulating cooling system design and provided effective guidance for improving the overall system performance.