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Information overload has become ubiquitous during a public health emergency. The research purpose is to examine the role of mixed emotions in the influence of perceived information overload on individuals’ information avoidance intention and the state of fear of missing out.

A mixed-methods approach was used in this study: a qualitative study of 182 semi-structured interviews and a quantitative study of 309 surveys.

The results show that perceived information overload negatively affects peace of mind and positively affects fatigue and fear. Emotions with a low activation level (peace of mind and fatigue) promote emotions with a high activation level (hope and fear), and peace of mind negatively influences fatigue. Additionally, peace of mind negatively affects information avoidance intention, while hope positively affects the state of fear of missing out. These two information processing outcomes are positively impacted by fatigue and fear.

This study extends existing knowledge by uncovering the underlying influence of mixed emotions on individuals’ different information processing outcomes caused by perceived information overload. It provides practical insights for online media platforms and Internet users regarding how to process overwhelming information during a public health emergency.

This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.

The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.

The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.

This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.

The growing number of firms leveraging social media ads highlight the urgent need for firms to understand social media ads and their effects on consumer perceptions and attitudes. This research examines whether and how different types of social media ads exert influences on ad engagement and how consumers’ psychological characteristics including regulatory orientation and lay rationalism moderate the influence of social media ads on ad engagement.

This research conducts three quasi experiments featuring two types of social media ads – interactive and transactional – to collect empirical evidence. Results are analyzed using ANOVA and Process in SPSS.

This research reveals that interactive ads lead to higher perceived enjoyment and perceived responsiveness, which further lead to higher ad engagement. Promotion focus moderates the effect of social media ads (interactive vs transactional ads) on perceived enjoyment and perceived responsiveness, and lay rationalism moderates the effect on perceived responsiveness, while prevention focus has no such effect.

First, this research establishes the connection between ad types and ad engagement in social media, which offers a new perspective to understand ad engagement. Second, it explores the underlying mechanisms of processing different types of social media ads. Third, it justifies the moderating effects of consumers’ regulatory orientation and lay rationalism on the effects of ad types on ad engagement, providing the first evidence on the moderating role of consumers’ lay rationalism in ad processing. This research helps firm marketers to fine-tune their social media ads according to consumer characteristics.

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

The motivation of value co-creation among the multi-actor in sharing economy was an important topic in interactive marketing communication research. This study investigated how customer gratitude expression leads to value co-creation of PSPs in the sharing economy, and also investigates the moderating effect of platform benevolent climate.

A three-wave field survey (Study 1) and two experiments (Studies 2 and 3) were given to respondents with sharing economy practitioners.

First, customer gratitude expression positively influenced PSP's perceived meaningful work, which in turn enhanced their value co-creation intention. Second, PSP's perceived platform benevolent climate moderated the relationship between customer gratitude expression and PSP's perceived meaningful work.

Prior research discussed PSPs' value co-creation intention mainly from the perspective of platforms and PSPs, but few considered customer-PSP interaction perspective. This study revealed how customer gratitude expression influences PSP's value co-creation intention in highly interactive digital business context, examined the boundary condition of gratitude expression, and extended the application scenarios of social information processing theory.

This chapter critically evaluates whether football can attain recognition as a national sport in China. Article No. 11, released by the Chinese government in 2015, aimed to develop a new national strategy centralised on the sport of football to foster consumption and enhance national soft power. Consequently, this also means encouraging Chinese football fans to support the national football team. Comparing the significance of local football clubs and the national football team to Chinese football fans is deemed meaningless and unable to generate useful information to comprehend Chinese people's attitudes towards local and national communities. Through literature comparisons with established Chinese national sports such as Chinese martial arts, badminton and table tennis, the discussion reveals that football currently falls short of meeting the general criteria of invention and popularity to be considered a Chinese national sport. In the specific Chinese context, it also proves that football fails to meet the criterion of politics, hindering its identification as a national sport. Consequently, the chapter rebuts the assumption and advocates for the validity of comparing how fans assess their fandom for local and national football teams.

This study aims to empirically examine the relationship between Internet use and personal privacy risk perceptions, the mediating effect of trust and the moderating effect of satisfaction on that relationship, which is exactly conducive to the practice of personal information protection.

A moderated mediation model will be employed to test the hypothesized relationships using the 2017 Chinese Society Survey data.

The authors find that Internet use positively relates to citizens' risk perceptions toward privacy security, and trust partially mediates the relationship between Internet use and privacy risk perception. In addition, the analysis of moderating effects showed that satisfaction with social life significantly enhances the negative impact on individuals' privacy risk perceptions of interpersonal trust. The positively moderating effect of satisfaction with local governments' work mainly reveals the relationship between interpersonal trust (or institutional trust) and citizens' privacy risk perception. Moreover, satisfaction with Internet platforms positively moderates the relationship between consumer trust and privacy risk perception.

This article contributes to the social risk amplification framework by applying it to the personal privacy information protection field, which was rarely discussed before. It also enriches privacy research by identifying the internal mechanism of how Internet use influences citizens' risk perceptions towards privacy information leakage.

Modular capacity units enable rapid reconfiguration, providing tactical flexibility to efficiently meet customer demand during disruptions and ensuring sustainability. Moreover, the Physical Internet (PI) enhances the potential of modular capacity in addressing efficiency, sustainability, and resilience challenges. To evaluate the sustainability and resilience advantages of the PI-enabled reconfigurable modular system (PI-M system), this paper studies a PI-enabled sustainable and resilient production-routing problem with modular capacity.

We develop a multi-objective optimization model to assess the sustainability and resilience benefits of combining PI and modular capacity in a chemical industry case study. A hybrid solution approach, combining the augmented e-constraint method, construction heuristic, and hybrid adaptive large neighborhood search, is developed.

The experimental results reveal that the proposed solution approach is capable of obtaining better solutions than the Gurobi and the existing heuristic in a shorter running time. Moreover, compared with the traditional system, the PI only and traditional with modular capacity systems, PI-M system has significant advantages in both sustainability and resilience.

To the best of our knowledge, this study is the first to integrate the PI and modular capacity and investigate sustainability and resilience in the production-routing problem.

Taking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.

The proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.

The proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.

By expanding the dimensions of the problem, the model verification space grows exponentially using automata.

Unlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.