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This study aims to explore the social networks and network interactions of bed-and-breakfast (B&B) entrepreneurs in rural China. In addition, it evaluates how such network interactions relate to rural resilience.

In-depth interviews were performed in two locations: Ningbo and Dujiangyan, China. Purposive sampling was combined with snowball sampling to select interviewees. The 154 interviews involved 29 B&B owners and relevant social actors. All codes and data were analyzed using the discourse analysis framework.

The B&B owners’ social networks were identified based on strategic goals, revealing a business operation network, business development network and business citizenship network. Challenges in seeking financial support for rural B&Bs during the pandemic were specified along with network interactions. The institutional adaptation approach was used to evaluate network interaction in rural B&B business. It was argued that other networks would react based on primary network members’ goal compatibility and the effectiveness of the primary network in addressing obstacles.

This study indicates that the rural B&B entrepreneurs’ interactions with various networks could influence on business resilience, community resilience as well as rural resilience.

By combining the institutional adaptation typology with social network theory, this study generates a new typology of network interactions for rural B&Bs. The typology helps to explain how and why B&B entrepreneurs make decisions and provides a broader scope of social networks involved in these business operations.

This study aims to review the progress of research on artificial intelligence (AI) relating to the hospitality and tourism industry, focusing on the content, focal points, key terms and trends of AI research.

A total of 491 referred papers are selected from the Web of Science core collection database. These papers, published in the past 30 years (1991–2021), are analyzed by using Gephi and VOSviewer software.

AI research shows a growing trend since 1991, and the number of publications and citations increased significantly since 2018, indicating that AI became a focus for researchers. AI studies are grouped into four clusters, namely, AI technology, technology acceptance, customers’ perception and future trends. The research focus changed from AI technology in the early stage to customers’ attitudes toward and willingness to accept AI.

The findings contribute to advance knowledge development, identify research gaps and shed light on future research. The results offer practical enlightenment for governments, tourism destinations and hospitality organization.

The results offer practical enlightenment for governments, tourism destinations and hospitality organization.

This study is the initial attempt to provide a systematic review of AI research relating to the tourism and hospitality fields.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.

This paper employs nationwide, large-scale field survey data to provide the first empirical evidence on the impact of human educational capital on the acquisition of health entitlement among Chinese migrant workers. The findings of this study hold significant practical implications for the formulation of policies aimed at improving the health protection of migrant workers, as well as for socioeconomic policies during China's transitional period.

Using the IVProbit model, this research examines how human educational capital influences the attainment of health entitlement among migrant workers in China by analyzing the impact and mechanism of education on health entitlement. The study is based on the China Migrants Dynamic Survey (CMDS) data from 2018, which include 100,177 observations.

For migrant workers in China, higher levels of education have a significant positive effect on the acquisition of health entitlements, including medical insurance, health records and health education. The positive impact of human educational capital on health entitlements is more significant for non-provincial cities and young-generation migrant workers. The results also show that human educational capital can influence the acquisition of health entitlements through mediators such as financial status, social integration and health status.

This study represents the first empirical attempt to evaluate the influence of human educational capital on the access of migrant workers in China to health rights and interests. Additionally, the study develops a theoretical framework to examine how the impact of human educational capital varies across migrant workers with different characteristics and their access to health entitlements.

The Public–Private Partnership (PPP) modality plays an important role in the procurement of global infrastructure projects. Regarding PPP's complex transaction structure, pricing of a PPP project is critical to both parties where the government pursues a high value for money (VFM) and the investor strives to maximize its financial gains. Despite the straightforward win–win principle, a formidable compromise is often the case to end up with a fairly acceptable price, subject to many determinants such as the risk profile, expected return, technological innovation and capacities of both parties. Among them, this study chooses to examine the “managing flexibility” (MF) capacity of investors in pricing of a PPP project, in light of the widely recognized importance of a real-option perspective toward the long term, complex and uncertain PPP arrangement. This study addresses two major questions: (1) how is MF in PPP projects to be valued and (2) how are PPP projects to be priced when considering a project's MF value.

A binomial tree model is used to evaluate the MF value in PPP projects. Based on the developed MF pricing model, net present value (NPV) and adjusted VFM value are then calculated. Finally, a multi-objective decision-making method (MODM) was adopted to determine the optimal level of returns based on invested capital (ROIC), return on operation maintenance (ROOM) and concession period.

The applicability and functionality of the proposed model is investigated using a real project case. For a given return, extended NPV and adjusted VFM value were calculated and analyzed using sensitivity analysis. Factor influence is shown by the model to be dependent on factor impact on cash flow. Subsequently, a multi-objective decision-making (MODM) model was adopted to determine the optimal level of returns, where the solution approximates the real-world bidding price. Results confirm that the pricing model provides a reliable and practical PPP proposal pricing tool.

This study proposes an integrated framework for valuing MF in PPP projects and thus more accurately determine optimal pricing of PPP projects than revealed in extant research. The model offers a practical tool to aid in the valuation of PPP projects.

An experiential retailing strategy is considered cardiotonic for consumers and brands. When such a stimulus is used, what cognition and behaviors are generated is an issue worthy of study. Therefore, the purpose of this study is to explore the factors and mechanisms that affect consumer response and relationship quality through empirical research.

Based on theoretical deduction, this paper proposes a conceptual model that includes four antecedents: experiential scene atmosphere (ESA), highlight design, interaction approach and value fit. These affect consumer–brand relationship quality (CRQ) through consumer identification (CI), brand identity (BI) and experiential immersion degree. In two rounds of predictive tests, 624 and 481 valid data were collected, respectively, and the feasibility of the scale was verified scrupulously. Furthermore, 427 participants reported the participants' tendencies in a formal empirical study.

The results show that the direct effects of antecedents, mediators and dependent variables are significant. Although the mediating effect of BI in experiential highlighting design on CRQ is not supported, other consumer response variables have a full or partial mediating effect.

This study not only functions as an innovation of research perspective enriching the theoretical framework of the influence mechanism of experiential retailing, but also strengthens the discussion on the role of value fit, especially emotional value fit, in experiential retailing.

This paper aims to investigate how and when different dimensions of trust and contracts interact to influence the development to negotiation strategies. Specifically, it explores how different dimensions of trust and contracts are combined to influence dispute negotiation strategies when cooperation parties have or do not have expectations of continuity.

This paper theoretically identified and empirically examined the interaction effect of trust and contract on dispute negotiation strategies in contractor–subcontractor relationships, by developing a conceptual framework and conducting a questionnaire survey comprising more than 300 disputes in the Chinese construction industry. Hierarchical regression analysis was mainly used to test the hypotheses.

This paper finds that contractual control may weaken the effect of goodwill trust in fostering interest-based strategies in the presence of expectations of continuity, while it may strengthen the effect in the absence of expectations of continuity. Contractual coordination negatively moderates the relationship between goodwill trust and interest-based strategies only when parties have little expectations of continuity. Moreover, contractual control enhances the effectiveness of competence trust on fostering interest-based strategies.

This paper provides insights for practitioners to wisely use different governance mechanisms to manage negotiation strategies and generate desired outcomes of dispute resolution.

This paper provides a nuanced understanding of how the two types of governance mechanisms interact, by considering trust and contract as multi-dimensional constructs. It explicit the boundary conditions of both the substitute and complementary relationship between them.

This study examines the impact of formal and informal institutional distances on the foreign ownership strategies of emerging market firms (EMFs).

This is an empirical study relying on two sets of data collected over two time periods, 2006–2008 and 2017–2019, for publicly-listed Chinese companies.

Greater formal institutional distances in the host and home countries make EMFs less likely to use joint ventures (JVs), while greater informal distances make EMFs more likely to use the JVs. When both formal and informal institutional distances are high, the use of JVs is more likely. These results are affected by the goal of the foreign direct investment (FDI) project, with strategic asset-seeking (SAS) FDI projects favoring the use of wholly owned subsidiaries (WOSs).

This study relies on cross-sectional data from publicly-listed Chinese companies, which may limit the generalizability of the findings.

EMFs investing in advanced countries should carefully assess the tradeoffs between transactional cost efficiency and legitimacy in making their foreign ownership decisions. If the goal is to access strategic assets, EMFs should consider WOSs to ensure the transfer of strategic assets and create value for the parent company.

The findings show that formal and informal distances between institutions have different impacts on foreign ownership strategies, providing empirical evidence for the need to balance conflicting cost-efficiency and legitimacy considerations when businesses make such strategic decisions. The authors show how this balance depends on the goal of the FDI project.