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Intuitionistic linguistic fuzzy information (ILFI), characterized by linguistic terms and intuitionistic fuzzy sets (IFSs), can easily express the fuzzy information in the process of muticriteria decision making (MCDM) and muticriteria group decision making (MCGDM) problems. The purpose of this paper is to provide an overview of aggregation operators (AOs) and applications of ILFI.

First, some meaningful AOs for ILFI are summarized, and some extended MCDM approaches for intuitionistic uncertain linguistic variables (IULVs), such as extended TOPSIS, extended TODIM, extended VIKOR, are discussed. Then, the authors summarize and analyze the applications about the AOs of IULVs.

IULVs, characterized by linguistic terms and IFSs, can more detailed and comprehensively express the criteria values in the process of MCDM and MCGDM. Therefore, lots of researchers pay more and more attention to the MCDM or MCGDM methods with IULVs.

The authors summarize and analyze the applications about the AOs of IULVs Finally, the authors point out some possible directions for future research.

This chapter studies crisis communication within the backdrop of tourism social media. The Scandinavian airline SAS is chosen as a case study due to the recognition of the airline’s social media presence during the 2010 ash cloud crisis. The study relies on netnographic and content analysis methods to examine Facebook postings throughout the life-cycle stages of the crisis as well as an interview with a social media representative at the airline. The social mediated crisis communication model is applied to situational crisis communication theory, and the findings show that social media provide a beneficial channel during a crisis. However, it is necessary for organizations to recognize stakeholders’ needs during a crisis as social media presence alone does not ensure success.

Drawing upon the Elaboration Likelihood Model, the purpose of this paper is to examine how the characteristics of social media moderate the effect of a firm’s apology on the attitude of its customers.

An online experiment including 360 active users of internet was employed to test the research model.

Results revealed that an after-crisis apology and firm reputation both have a positive effect on after-crisis user attitude toward the firm. Furthermore, the positive effect of apology becomes stronger as online media interactivity increases, whereas the positive effect of reputation becomes weaker.

This study included only one important characteristic of social media, and experimental scenarios were limited to car recall crisis. Considering that social media has so many platforms that may have different kinds of interactivity, further studies can be conducted to figure out the most suitable social media for firms to deal with an online crisis.

The results inform managers of the importance of after-crisis apology and firm reputation. It is worthwhile for managers to find out the levels of online media interactivity at which users focus on apology and reputation and accordingly conduct an effective online crisis management response strategy.

This study extends the literature on online crisis management and the literature on ELM by highlighting the role of online media interactivity in influencing the persuasive effectiveness of firm’s crisis response in the context of social media.

Driven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality control methods play an essential role in the quality improvement of assembly products. This paper aims to review the development of data-driven modeling methods for process monitoring and fault diagnosis in multi-station assembly systems. Furthermore, the authors discuss the applications of the methods proposed and present suggestions for future studies in data mining for quality control in product assembly.

This paper provides an outline of data-driven process monitoring and fault diagnosis methods for reduction in variation. The development of statistical process monitoring techniques and diagnosis methods, such as pattern matching, estimation-based analysis and artificial intelligence-based diagnostics, is introduced.

A classification structure for data-driven process control techniques and the limitations of their applications in multi-station assembly processes are discussed. From the perspective of the engineering requirements of real, dynamic, nonlinear and uncertain assembly systems, future trends in sensing system location, data mining and data fusion techniques for variation reduction are suggested.

This paper reveals the development of process monitoring and fault diagnosis techniques, and their applications in variation reduction in multi-station assembly.

The purpose of this paper is to analyze the crisis information posted by publics on the social media platform Instagram about leading fast food companies as well as the responses by the companies and their general use of Instagram.

In two quantitative content analyses, 711 Instagram posts were identified in a two-week constructed time period that related to the ten largest fast food chains in the world.

It was found that negative content about these companies is posted by customers and employees alike and that the negative tonality primarily stems from issues with service and the work environment. The study also showed that the companies are just starting to discover Instagram and have very little engagement with users. None of the companies responded to the negative posts of customers and employees.

The analysis only evaluated posts with negative hashtags about ten fast food companies. Future research should expand the analysis to all posts about a certain sector as well as expand the scope of the research beyond the fast food sector.

The results of the study are a call-to-action for public relations professionals to engage with their publics on Instagram and actively use the app as a pre-crisis monitoring and crisis response tool in their social media plans.

Instagram is a fast-growing social media channel, yet research into this platform is lacking. The findings of this study should be a challenge to public relations practitioners to put Instagram next to Facebook and Twitter at the center of their social media strategy.

The spatiotemporal compression effect of China–Europe Railway Express (CR-Express) can reduce the flow costs of resources between China’s node cities. Additionally, it can break through the limitations of low-added-value marine products, significantly impacting the logistics industry efficiency. However, there are few literature verifying and analyzing its heterogeneity. This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.

First, this study uses panel data to measure the efficiency of node city logistics industry. Secondly, this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model. Finally, according to the node city difference, the sample city experimental group is grouped for heterogeneity analysis.

The results show that CR-Express can promote the urban logistics industry efficiency, with an average effect of 4.55%. According to the urban characteristics classification, the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious. The improvement effect of node cities and central cities in central and western China is stronger, especially in the sample of megacities and type I big cities. Compared with non-value chain industrial products, the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.

Under the background of double cycle development, this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

This study aims to design a controller which can improve the end-effector low-frequency chattering resulting from the measurement noise and the time delay in the on-orbit tasks. The rendezvous point will move along the rendezvous ring owing to the error of the camera, and the manipulators’ collision need be avoided. In addition, owing to the dynamics coupling, the manipulators’ motion will disturb the spacecraft, and the low tracking accuracy of the end-effector needs to be improved.

This paper proposes a minimum disturbance controller based on the synchronous and adaptive acceleration planning to improve the tracking error and the disturbance energy. The synchronous and adaptive acceleration planning method plans the optimal rendezvous point and designs synchronous approaching method and provides an estimation method of the rendezvous point acceleration. A minimum disturbance controller is designed based on the energy conservation to optimize the disturbance resulting from the manipulator’s motion.

The acceleration planning method avoids the collision of two end-effectors and reduces the error caused by the low-frequency chattering. The minimum disturbance controller minimizes the disturbance energy of the manipulators’ motion transferred to the spacecraft. Experiment results show that the proposed method improves the low-frequency chattering, and the average position tracking error reduces by 30%, and disturbance energy reduces by 30% at least. In addition, it has good performances in the synchronous motion and adaptive tracking.

Given the immeasurability of the target satellite acceleration in space, this paper proposes an estimation method of the acceleration. This paper proposes a synchronous and adaptive acceleration planning method. In addition, the rendezvous points are optimized to avoid the two end-effectors collisions. By the energy conservation, the minimum disturbance controller is designed to ensure a satisfying tracking error and reduce the disturbance energy resulting from the manipulators’ motion.

The purpose of this paper is to examine public–private partnership (PPP) approaches for the construction of rental retirement villages in Australia and to allocate the investment proportions under a certain project return rate among three investors which are the government, private sectors and pension funds. The apportionment will achieve a minimum overall investment risk for the project.

Capital structure, particularly determination of investment apportionment proportions, is one of the key factors affecting the success of PPP rental retirement villages. Markowitz mean-variance model was applied to examine the investment allocations with minimum project investment risks under a certain projected return rate among the PPP partners for the construction of rental retirement villages.

The research findings validate the feasibility of the inclusion of pension funds in the construction of PPP rental retirement villages and demonstrate the existence of relationships between the project return rate and the investment allocation proportions.

This paper provides a quantitative approach for determination of the investment proportions among PPP partners to enrich the theory of PPP in relation to the construction of rental retirement villages. This has implications for PPP partners and can help these stakeholders make vital contributions in developing intellectual wealth in the PPP investment area while providing them with a detailed guide to decision making and negotiation in relation to investment in PPP rental retirement villages.