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With the appearance of additional review functionality on e-commerce platforms emotional changes in composite reviews have become more diverse. How consumers process the emotional changes in composite reviews is an important concern for companies. This study investigates the impact of explores how changes in the emotional valence and emotional intensity of composite reviews on consumers' information adoption.

Based on emotion as social information theory, this study constructs a double mediation model of how the change in emotional valence of composite reviews affects consumers' adoption intention and examines the moderating effect of the dynamic change of emotional intensity. One field and three online experiments were conducted to test the proposed hypotheses.

Consumers were more likely to adopt positive–negative composite reviews than negative–positive composite reviews. Compared to negative–positive composite reviews, positive–negative composite reviews led to higher perceived empathy and lower motivational suspicion, which, in turn, led to higher information adoption. Moreover, dynamic changes in emotional intensity played a moderating role in this effect. Interestingly, the amount of attribute difference changed the differences in perceived empathy and motivated consumer suspicion generated by the composite review when considering the reviewer’s attribute difference description.

The findings have important theoretical contributions that deepen business and consumer understanding of the impact of composite reviews and have practical implications for improving the management of composite reviews by businesses.

This study aims to explore the connection between travel content consumption in social networks and social comparison, envy as well as travel intention. It analyzes whether tourists’ travel intention is affected by travel content consumption in social networks, and more importantly, whether social comparison and envy play a mediating role in this process.

Data was collected through intercept in four popular tourist spots in Guangzhou and Zhuhai in South China. A self-administered questionnaire was used. A total of 400 participants were recruited, and 291 valid questionnaires were obtained. Bias-corrected nonparametric percentile bootstrap mediation variable test method was used to test hypotheses.

The study yielded three results. First, travel content consumption in the social networks positively influences travel intention. Second, travel content consumption in social networks indirectly affects travel intention through social comparison and envy. Third, the control variables, such as gender, age, education and income, mainly affect envy.

This study constructs a theoretical framework of stimulus–cognitive appraisal–emotion–behavioral responses. To the best of the authors’ knowledge, it is the first study to reveal that the internal psychological mechanism of travel content consumption affects travel intention. It also discloses that envy of seemingly negative emotions can encourage positive behaviors in certain situations.

This study aims to investigate a randomized 3 (endorser type: celebrity vs CEO vs expert) × 2 (product type: hedonic vs utility) between-respondents factorial experiment to inspect the effects of the endorsers and product types on consumers’ engagement in BRM through brand-relationship variables [i.e. self-brand connection (SBC), perceived product attachment (PPA) and source credibility (SC)]. Marketing in a digital era is witnessing a rising trend of “brand resurrection as revolution” led by consumer power. The successful revitalization of various dead brands provides some new opportunities for companies to engage millennial consumers in brand resurrection movements (BRM) through the right choice of brand endorsers. The new-found love of companies for the revitalization of long-forgotten brands has attracted considerable interest among scholars and marketing practitioners. Despite the brand resurrection’s high practical relevance, little is known in marketing research about how to revive failing brands back to life.

Using source credibility theory (SCT) as a lens, this study conducted two studies (i.e. Study 1, N = 300; Study 2, N = 300) and builds on an analysis of data from Pakistani millennials. The hypotheses were inspected using both structural equation modeling and SPSS’s PROCESS macro.

Through two studies, the authors find that the match between endorser types and product types affects customer motivation to engage in BRM via SBC, PPA and SC (i.e. attractiveness, trustworthiness and expertise).[AQ2] The results showed that for utilitarian products, both SBC and PPA mediate the link between endorser types and BRM, but for hedonic products, PPA does not play a role. Similarly, the authors’ results indicate that for hedonic products, attractiveness, trustworthiness and expertise mediate the link between endorser types and BRM, but for utilitarian products, trustworthiness does not play a role.

The results of this research will help marketing managers devise effective brand endorsers strategies in reviving failing brands. Specifically, this endeavor highlights that understanding brand advertisements merely in terms of celebrity endorsement restricts the full potential that brand advertisements could have and also that a comprehensive understanding must include expert and chief executive officers (CEO) endorsers. Therefore, one of the central contributions of this research is the introduction of expert and CEO endorsers and the evidence that both celebrity (i.e. celebrity and CEO) and non-celebrity endorsers (i.e. experts) have an impact on consumers’ motivation to engage in BRM.

To the best of the authors’ knowledge, this is one of the first endeavors of its kind to empirically explore consumer attitude/motivation behind participation in reviving failing brands. The significance of this work is underscored by the fact that numerous dead brands are being brought back by companies because of consumer–brand co-creation movements.

This paper aims to explore the effect of teacher–student collaboration on academic innovation in universities in different stages of collaboration.

Based on collaboration life cycle, this paper divided teacher–student collaboration into initial, growth and mature stages to explore how teacher–student collaboration affects academic innovation.

Collecting data from National Science Foundation of China, the empirical analysis found that collaboration increases the publication of local (Chinese) papers at all stages. However, teacher–student collaboration did not significantly improve the publication of international (English) papers in the initial stage. In the growth stage, teacher–student collaboration has a U-shaped effect on publishing English papers, while its relationship is positive in the mature stage.

The results offer suggestions for teachers and students to choose suitable partners and also provide some implications for improving academic innovation.

This paper constructed a model in which the effect of teacher–student collaboration on academic innovation in universities was established.

For the basic problems on platform innovation, such as platform innovation connotation and characteristics, the driving mechanism and the influence mechanism are less been studied. This study aims to explore how to achieve platform innovation in traditional service enterprises.

Based on the theory of enterprise network and binary learning, respectively, this paper discusses the behavior of binary learning based on network structure and network impact on efficiency and innovative platform innovation, and analyzed the realization of the platform innovation path.

The research draws the following conclusions: the network structure-based exploitative learning can promote the efficiency platform innovation, while the network behavior-based exploratory learning can promote the novelty platform innovation. The interaction between network structure and network behavior embedded in traditional services is more conducive to exploratory learning so as to promote novelty platform innovation, and the platform innovation of traditional service enterprises is a process from efficiency-oriented to novelty-oriented. The innovation effect generated by exploratory learning based on network behavior is much higher than that generated by exploitative learning based on network structure. The theoretical contributions of this study are as follows: first, this study compares the similarities and differences between service innovation of platform-oriented enterprises and platform innovation of service enterprises. On this basis, it clearly defines the concept of platform innovation and divides it into two categories: efficiency platform innovation and novelty platform innovation. Second, it reveals the two paths for traditional service enterprises to realize platform innovation, and the interaction between these two paths are also explored, which promotes the scenario-based and dynamic study of platform innovation in traditional service enterprise. The conclusion of this study provides theoretical reference for traditional service enterprises to carry out platform innovation.

Theoretical contribution of this paper lies in: first, the concept of platform innovation is clearly defined. Current research about platform innovation is mainly around the innovation of platform enterprise and the platform innovation of traditional enterprise, but there is no document that makes clear distinction; some literature even equates innovation of platform enterprise with platform innovation of traditional enterprise. In this paper, through a detailed literature review and analysis, clearly define the concept of platform innovation and divided into efficiency platform innovation and novel platform innovation, which has made theoretical contribution to the depth of the research. Second, expand the platform innovation research of traditional service industry. In recent years, the platform innovation research of traditional enterprise has become a hot spot, but they focus on the attention of the platform transformation of traditional manufacturing industry, such as Haier; the traditional service industries seem to be “empty,” but, in fact, the traditional service industry platform innovation is of great significance and more worth looking forward to. In this paper, the longitudinal case studies can promote academic concerns focus on the traditional service industry, and also provides the theory instruction practice. Third, it promotes the platform innovation research of traditional enterprise and dynamic analysis. Based on the theory of enterprise network and binary learning, respectively, it discusses the behavior of binary learning based on network structure and network impact on efficiency and innovative platform innovation, and analyzed the realization of the platform innovation path. On the one hand, it enriches the research type of platform innovation; on the other hand, the dynamic evolution mechanism of platform innovation research can make up for the deficiency of the existing literature.

The purpose of the paper is to develop a hybrid method to prioritize risk factors (RFs) of sustainable supply chain (SSC) considering sustainable customer requirements (CRs) and uncertain evaluation.

In the proposed method, fuzzy Kano model (FKM) is applied to prioritize sustainable CRs considering customer satisfaction (CS) and objective weight of each CR, the interval-valued intuitionistic fuzzy (IVIF) set theory is integrated with quality function deployment (QFD) to translate the sustainable CRs into RFs of SSC under uncertain environment and the IVIF cross-entropy is used to conduct objective analysis to prioritize RFs. Finally, a case in air-conditioner-manufacturing company is presented to demonstrate the proposed method.

A case study of SSC risk management, the comparative analysis and associated discussions are conducted to illustrate the feasibility and effectiveness of the proposed method. The results obtained from the case study shows that RF5 (market share reduction) is the most important RF in the SSC. Compared with the existing methods, the proposed method can integrate sustainable CRs into SSC's RFs, handle uncertain information effectively and obtain objective importance of RFs.

Theoretically, the paper develops a customer-oriented model based on the FKM, QFD, IVIF sets and entropy theory to prioritize RFs of SSC under uncertain environment. The model enables to integrate sustainable CRs into RFs managements and is efficient to deal with the subjectivity and conduct objective analysis to prioritize RFs. In practice, the systematic and correct RFs' priorities analysis provides reliable decision support for the managers to take measures to avoid or mitigate the critical RFs.

Burnout among first-line police in China is high. The purpose of this paper is to examine the relationship between feedback environment, feedback orientation, psychological empowerment, and burnout as related to the police work.

An empirical study was conducted with a sample of 437 basic-level policemen and policewomen in the Shandong province of China. Participants completed a series of questionnaires including the supervisor feedback environment scale, feedback orientation scale, psychological empowerment scale, and the Maslach Burnout Inventory.

The results indicate that police supervisor feedback environment is negatively related to burnout. The relationship between the supervisor feedback environment and burnout is perfectly mediated by psychological empowerment and significantly moderated by feedback orientation. The mediation effect of psychological empowerment is significantly influenced by feedback orientation.

The findings have contributed to answering several recent questions in the feedback-burnout literature. The authors stress that leaders should strive to build a supportive feedback environment for employees.

This paper's purpose is to suggest that manufacturers strategically place soft orders for assembly materials with suppliers in Silk Road Economic Belt countries who probably doubt the realization of the soft orders placed.

First, a two-stage Stackelberg competition is constructed, taking into account the supplier's trust level in formulating the decision process in the assembly supply chain. The authors then provide a buyback contract to coordinate the supply chain, in which the manufacturer obtains enough supplies by sharing some of the perceived risks of not fully trusted suppliers. Furthermore, the authors conduct a numerical study to investigate the influence of trust under a decentralized case and a buyback contract.

The authors found that all supply chain partners in Silk Road Economic Belt countries experience potential losses due to not fully trusting certain conditions. The study also shows that, in Silk Road Economic Belt countries, operating under a buyback contract is better than being without one in terms of assembly supply chain performance.

On the one hand, the authors only consider the asymmetry of demand information without considering that of cost structure information. On the other hand, a natural extension of the paper is to integrate single-period transactions into the multi-period transaction problem setting. As all these issues require substantial effort, the authors reserve them for future exploration.

Doing business with not-fully-trustworthy partners in Silk Road Economic Belt countries is risky, and this study reveals how trust works in global cooperation and with strategic reactions in situations of partial trust.

With the prevalence of the sharing economy phenomenon, there are an increasing number of hosts on Airbnb who manage more than one listing. Managing more listings likely makes hosts more seasoned in terms of serving guests, but it may undermine host quality due to hosts’ constrained capability. This paper aims to examine the effects of host quality attributes and the number of listings per host on the reservation performance of these listings.

Using a large-scale but granular data set of 5,805 active listings of 4,608 Airbnb hosts in Austin, Texas, this study estimates the effects of host attributes (host quality and listing quantity) on the performance of the hosts’ Airbnb listings through a blend of regression models.

This study evidences that host quality attributes significantly influence listing performance through cue-based trust. In addition, this study finds a “trade-off” between host quality and the quantity of their listings. As the number of listings managed by a host increases, the performance effects of host quality diminish.

The business implications of this study include the suggestion that sharing economy businesses such as Airbnb should sustain service quality through incentivizing hosts to improve host quality while balancing the quantity of listings managed.

This study contributes to the literature through its meaningful theoretical extension in the sharing economy context and unique data-driven insights enabled by an analytical approach. It addresses the critical but less researched topic of host quality and listing quantity and generates important practical business and policy implications.

Protean career orientation is a key element that helps explain why workers plan and manage their careers. In the field of nursing, a protean career orientation assists nurses in job search, career mobility and adapting to changing demands. Few studies have explored how nurses’ protean career orientation will lead to job search and how to make better use of the protean career orientation. This study aims to explore how a protean career orientation influences job search via career optimism and the moderating role of mentoring relationships.

This study conducted a cross-sectional survey of 309 frontline nurses from China. The questionnaire was distributed to nurses through the snowball sampling method. Jamovi 1.2.2 was used for descriptive analysis and Pearson’s correlation analysis. The relationships between the variables and their significance were tested using Process Macro 3.3.

Results show that protean career orientation was significantly related to career optimism and positively related to job search. Career optimism was significantly related to job search. The indirect effect of protean career orientation on job search through career optimism was significant. The interaction between protean career orientation and mentoring relationships was also significantly related to career optimism.

To the best of the authors’ knowledge, this study is the first to demonstrate how nurses’ flexible career orientation significantly impacted job search through nurses’ career optimism. If nurses work in supportive mentoring relationships, the positive effect of the nurse’s protean career orientation on the job search is decreased.