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Using the analogy of “If you build it, they will come” from the movie Field of Dreams, this study aims to draw on relational signaling and commitment–trust theories to examine the role of different types of trust (cognitive, affective and relational) in the relationship between relational-encounter quality and customer loyalty to service employees and to the organization in the case of an integrated casino resort. The study confirms that building it (trust), they (customers) will come to the casino exhibited in their loyalty to casino hosts and their affiliated casinos.

The study was conducted with very important person (VIP) customers who have a designated VIP host to provide them with personal services at an integrated casino resort in Macau. The questionnaire was distributed to the respondents by VIP hosts using WeChat and Tencent QQ.

The study shows that different types of trust (cognitive, affective and relational) play a significant mediation role in the relationship between relational-encounter quality and the customers’ loyalty to the hosts and their affiliated casinos.

To the best of the authors’ knowledge, this study is the first to investigate the roles of different types of trust (cognitive, affective and relational) in the relational encounter between casino hosts and VIP customers and provides insights into the link between service employees and their firm through the nurturing of the service encounter with the firm’s key accounts.

Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China.

In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode.

The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency.

To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.