Search results

This study aims to explore the dimensions and sub-factors of Airbnb hosts’ affinity-seeking strategies. It also aims to build a conceptual framework of hosts’ affinity-seeking strategies and their impact on Airbnb guests’ feelings of affection toward their host and/or the homestay and their behavioral intentions.

Based on 150,161 Inside Airbnb online reviews in three major US cities, this study uses semantic analysis to explore processes through which hosts’ affinity-seeking strategies are constructed.

A conceptual framework is proposed to identify two dimensions (warmth and competency) and their sub-factors (“presenting friendly attitudes,” “showing personality traits,” “providing service and help” and “promoting social interaction and sharing”) of Airbnb homestay hosts’ affinity-seeking strategies. The framework shows a positive relationship between these strategies and guests’ affection and behavior in response.

The research findings provide valuable insights to hosts for improving their affinity and strengthening their competitive advantages. They also offer guidance to destination management organizations on how to build a positive destination image.

To the best of the authors’ knowledge, this study is the first to conceptualize Airbnb homestay hosts’ affinity-seeking strategies. It contributes to the literature by incorporating social cognition theory and service theory in the analysis of these strategies.

This paper aims to research the influence of pressure, friction factors, roughness and actuating speed to the mixed lubrication models of outstroke and instroke.

Mixed lubrication model is solved by finite volume method, which consists of coupled fluid mechanics, deformation mechanics and contact mechanics analyses. The influence of friction factor on the finite element model is also considered. Then, contact pressure, film thickness, friction and leakage have been studied.

It was found that the amount of leakage is sensitive to the film thickness. The larger the film thickness is, the greater the influence received from the friction factor, however, the effect of oil film on the friction is negligible. The friction is determined mainly by the contact pressure. The trend of friction and leakage influenced by actuating velocity and roughness is also obtained.

The influence of friction factor on the finite element model is considered. This can make the calculation more accurate.

The main purpose of this study is to explore the effect of three dimensions of “home feeling” – home-as-practical, home-as-social and home-as-attachment – on the online rating of homestays and additionally considers the accommodation’s attribute performance and level of sharing.

To achieve the research aims, more than 9,738,335 items of user-generated content concerning 743,953 Airbnb listings covering 35 cities were collected as the study data. These data are analyzed through hierarchical regression.

The results show that all three dimensions of home feeling positively affect the online rating; all three dimensions negatively moderate the relationship between attribute performance and online rating; the size of the moderating effect of each dimension on the relationship between attribute performance and online rating gradually increases in the order home-as-practical, home-as-social and home-as-attachment; and as the level of sharing increases, the moderating effect of home feeling on the relationship between attribute performance and online rating diminishes.

This study contributes to the literatures on the role of home feeling in homestays, the online rating of homestays and the motivations of guests who choose different room types. The findings of this study can help hosts better understand the formation of online rating of homestays, make targeted improvements in rooms and services and create a home feeling for specific degrees of sharing. This in turn will help them to improve the online rating of their homestays, establish an excellent online reputation and, ultimately, increase sales.

This study advances knowledge by confirming three dimensions of home feeling not only have direct positive impacts on online rating but also mitigate the impact of attribute performance on online rating. This effect differs significantly in magnitude with the degree of sharing.

Online employee reviews have a substantial impact on employee recruitment, retention and the overall perception of a company’s image, making them a crucial element of its online reputation. Consequently, these reviews play a vital role in shaping the company’s competitiveness in the talent market. This study aims to investigate the role of employee loyalty in online reputation in the tourism and hospitality sector.

This study collected online reviews posted by 334,428 employees across 173 companies in the tourism and hospitality sector. Then, this study proposed a method for measuring employee loyalty toward the company through text comments. Furthermore, the role of employee loyalty in online reputation through regression models was analyzed.

Employee loyalty is positively associated with the closed-form evaluations, and the length and readability of open-ended comments is directly and positively associated with review helpfulness and is indirectly associated with review helpfulness through employee online reviews. Employees’ perception of job instability has a significant moderating effect on the above relationships.

This study contributes to the literature on loyalty in the tourism and hospitality industry, online reputation and employee risk perception. These findings offer a more profound understanding of the extra-role behaviors demonstrated by loyal employees, provide a theoretical foundation for the formation of a company’s online reputation and contribute to helping the tourism and service industry better address risk events. These conclusions provide valuable insights for companies in the fields of human resource management and online reputation management.

To the best of the authors’ knowledge, this study is the first to reveal the impact of employee loyalty on the company’s online reputation and provides important theoretical and practical implications for management.

Complex cost structures and multiple conflicting objectives make selecting an appropriate cloud service difficult. The purpose of this study is to propose a novel group consensus decision making method for cloud services selection with knowledge deficit by trust functions.

This article proposes a knowledge deficit-based multi-criteria group decision-making (MCGDM) method for cloud-service selection based on trust functions. Firstly, the concept of trust functions and a ranking method is developed to express the decision-making opinions. Secondly, a novel 3D normalized trust degree (NTD) is defined to measure the consensus levels. Thirdly, a knowledge deficit-based interactive consensus model is proposed for the inconsistent experts to modify their decision opinions. Finally, a real case study has been carried out to illustrate the framework and compare it with other methods.

The proposed method is practical and effective which is verified by the real case study. Knowledge deficit is an important concept in cloud service selection which is verified by the comparison of the proposed recommended mechanism based on KDD with the conventional recommended mechanism based on average value. A 3D NTD which considers three values (trust, not trust and knowledge deficit) is defined to measure the consensus levels. A knowledge deficit-based interactive consensus model is proposed to help decision-makers reach group consensus. The proposed group consensus model enables the inconsistent decision-makers to accept the revised opinions of those with less knowledge deficit, rather than accepting the recommended opinions averagely.

The proposed a knowledge deficit-based MCGDM cloud service selection method considers group consensus in cloud service selection. The concept of knowledge deficit is considered in modeling the group consensus measuring and reaching method.

This study aims to comprehensively investigate the relationship between government subsidies and innovation performance in Chinese enterprises listed on the SSE STAR Market.

An unbalanced sample, covering 285 observations in 215 enterprises listed on the SSE STAR Market from 2019 to 2020, was used to explore the relationships between government subsidies, R&D investment, CEO shareholding and innovation performance. Counterfactual analysis is added for robustness testing.

Empirical evidence confirms that government subsidies have an inverted U-shaped relationship with R&D investment and innovation performance. Meanwhile, R&D investment is a mediating variable between government subsidies and innovation performance. Moreover, CEO shareholding plays a moderating role between government subsidies and R&D investment. The higher the CEO ownership, the steeper the inverted U-shaped relationship.

The government should introduce a dynamic mechanism to reasonably control subsidy amounts and strengthen the supervision of subsidy use. Enterprise managers should be aware of how incentives affect the firm’s innovation and implement a coordinated development of government subsidy policies and internal enterprise governance.

This study adds new empirical evidence for the relationship between government subsidies and enterprise innovation performance. The risk incentive provided by stock options is an important micro mechanism to compensate for the lack of government subsidies. The study identifies ways to promote firm innovation based on the synergistic effect of internal and external mechanisms.

This study aims to explore how attribute performance and hosts’ service quality attributes affect room sales on peer-to-peer (P2P) platforms from the cue congruence perspective.

More than 9.53 million reviews concerning 258,473 listings located in 35 major cities worldwide were collected from Airbnb. Data was collected from December 2019 to December 2020 and was analysed using a generalised linear model.

Results show that when attribute performance and hosts’ service quality attributes give positive signals, Airbnb room sales are significantly higher than when the two kinds of cues give inconsistent or negative signals; when attribute performance gives positive signals and hosts’ service quality attributes give negative signals, room sales are higher than when the former gives negative signals and the latter give positive signals; surprisingly, when both kinds of cues give negative signals, room sales are higher than when attribute performance gives positive signals and hosts’ service quality attributes give negative signals.

This paper adds useful insights on understanding of cue congruence (incongruence) effect on room sales of P2P accommodation platforms. This study has practical implications for hosts, online platform managers and guests regarding how to use online strategies and promotions on the Airbnb platform.

This study is an early attempt to explore how the combination of attribute performance and hosts’ service quality attributes affects Airbnb room sales under the conditions of consistency and inconsistency.

This study analyzed Chinese higher education (HE) governance policies during the first four months of the 2020 COVID-19 pandemic, providing insight into HE management, policymaking and governance. This study also illuminates Chinese student experiences and real-time policy impact, providing insight into the effectiveness of HE crisis management.

Using frameworks of real-time policy evaluation, this paper analyzed theoretical and realized policy impacts through the theoretical framing of temporality. Using real-time evaluation methods, this paper first identified HE policy priorities and then used a mixed-methods approach of “policy as discourse” analysis and a quantitative survey from Chinese HE students to assess the theoretical and realized impact of policies.

An analysis of HE policies identified three priorities: pastoral care, graduate employment and ideological education. Discourse analysis revealed each priority of HE policies was intrinsically linked to mitigating societal, economic and political consequences of the epidemic. Survey data revealed the perceived effectiveness of policies mirrored China's top-down government structure. Additionally, students expressed strong support in the central government's crisis management, despite relatively little realized policy impact.

This paper presents a timely review of HE governance during a global pandemic by offering a snapshot of HE crisis management and contributing to the literature surrounding China's ongoing HE centralization. This paper also provides unique insight into HE's role in state development, variations between prescriptive and realized policy impact and the “crisis as opportunity” paradox in a contemporary setting.

Innovation networks provide an efficient mechanism for organizations to realize their potential for knowledge learning and innovation improvement. Firms situated within innovation networks require specific abilities to acquire the knowledge and the complementary assets that facilitate their innovation performance. Motivated by recent research studies in the area of social network and RBV, the purpose of this paper is to improve the understanding of the precise manner in which network capability affects a firm’s innovation performance.

Based on the data obtained from Chinese high-tech firms, the hypotheses are tested by using hierarchical multiple regressions.

This study identifies two types of network capabilities: network structural capability and network relational capability. The findings suggest that network structural capability has a greater positive impact on innovation performance than network relational capability does within an exploration-orientated network. However, network relational capability is more positively associated with innovation performance within an exploitation-orientated network.

A firm can enhance the value of its ego network by shaping and adjusting network configurations, rather than by passively reaping the benefits from existing relationships or ties with partners.

This paper contributes to strategic management theory and social network theory by illustrating how a networked firm can enable network value and appropriate this value according to its strategic purposes and by suggesting that a firm can improve its ego network’s value through exerting its network capabilities to shape and adjust network configurations. This paper also advances the contingent approach within social network research by offering a new complementary perspective and new evidence from a Chinese context.

Taiwan serves as a case study to investigate the association between the expansion and reform of higher education and the growth of science production. More specifically, what driving forces facilitated the growth of science production in different types of Taiwanese universities and other sectors, from 1980 to 2011.

The contribution charts differential contributions to overall production. Taiwanese data from Thomson Reuters’ Science Citation Index Expanded (SCIE) is analyzed to show the expansion of the higher education system and its relationship to the production of science. The author uses sociological organization theories to facilitate our understanding of how and why the landscape of science production changed.

Results show that the growth of science production is associated with processes of isomorphism and competition within the higher education system. Findings also suggest that universities quickly seized upon external opportunities and turned themselves into what is known as the “knowledge conglomerate.” Unique organizational features bolster universities’ position as the driving force behind advancing national innovation.

This study extends previous research by examining multiple sectors of higher education, using longitudinal and recent data, and highlighting themes that have been ignored or overlooked, such as competition and collaboration among universities and industry partners.