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The present study aims to synthesize and conceptualize, through a systematic literature review (SLR), the current state of gamification knowledge in the tourism and hospitality (T&H) sector, providing a roadmap for future research recommendations for service research and practice.

The research is based on a systematic literature review and adopts a systematic quantitative approach to summarize existing evidence on gamification usage in the T&H sector, focusing on relevant service literature on gamification. The authors analyze 36 papers published between 2011 and 2019.

The authors synthesize existing knowledge into five themes describing gamification's role in T&H (Edutainment, Sustainable behavior, Engagement factors, Service provider-generated content and User-generated reviews). Then, a cross-analysis of the five themes reveals the pivotal elements (affordances, behavioral and psychological outcomes, and benefits) generated by gamification mechanics in T&H, simultaneously highlighting potential implications and relevant insights for service literature. The review identifies critical issues affecting gamification research and provides a future research agenda, considering opportunities for T&H and service research.

The study provides the first SLR investigating gamification in T&H. The findings present potential implications and relevant insights for T&H contributing to the construction of a more holistic understanding of gamification adoption in service research.

This study has two objectives. The first aim is to ascertain whether innovation and market orientation have direct, indirect, and causal effects on customer service. The second objective is to ascertain whether market orientation has a moderating effect on the relationship between innovation and customer service. This research follows three distinct methodologies. The first approach uses Cronbach’s alpha coefficient in order to check reliability while an exploratory factor analysis and a confirmatory factory analysis ascertain validity. The second method uses the analysis of structural equation models to test a causal link between variables. The third methodology uses a moderated regression analysis to verify the moderating effects. As our analysis results show, intelligence generation and intelligence dissemination have a moderating effect on the relationship between innovation and flexibility. These results can be interpreted as follows: firstly, customs clearance firms can provide superior service to customers if they strive to understand customer needs and provide them with flexible service at the same time. Secondly, these firms can enhance their flexibility of service in all departments though innovation and information sharing acquired from the market.

A systematic investigation of postgraduate leadership programs for health and/or human services offered by Australian higher education institutions was undertaken.

Quantitative analysis identified the core characteristics of the programs. A thematic analysis of the course learning outcomes was conducted and six major themes of disciplinary leadership and management knowledge; research and analytical skills; professional practice; communication and collaboration; creativity and innovation; and system knowledge are shared in this study.

The authors conclude that Australian universities have taken an evidence-based approach to leadership education.

More work might need to be undertaken to ensure leadership theories are incorporated into learning outcomes.

Cryptomarkets on the dark web have emerged as a hub for the sale of illicit drugs. They have made it easier for the customers to get access to illicit drugs online while ensuring their anonymity. The easy availability of potentially harmful drugs has resulted in a significant impact on public health. Consequently, law enforcement agencies put a lot of effort and resources into shutting down online markets on the dark web. A lot of research work has also been conducted to understand the working of customers and vendors involved in the cryptomarkets that may help the law enforcement agencies. In this research, we present a ranking methodology to identify and rank top markets dealing in harmful illicit drugs. Using named entity recognition, a harm score of a drug market is calculated to indicate the degree of threat followed by the ranking of drug markets. The top-ranked markets are the ones selling the most harmful drugs. The rankings thus obtained can be helpful to law enforcement agencies by locating specific markets selling harmful illicit drugs and their further monitoring.

The division of labor of e-commerce transaction system is an important research topic. However, there is a certain disparity between the current mainstream research model and the reality, which leads to a biased result. This paper aims to find the effects of transaction efficiency on the evolution of e-commerce transaction system’s division of labor and the relationships between the results and other parameters.

This paper puts forward a definition of transaction efficiency based on transaction services and establishes a model of middleman’s specialized production decision of transaction services on this basis.

The research results show that the transaction efficiency plays an important role on the change of middlemen’s division of labor level. The degree of economic specialization, price of commodities and transaction services and other associated factors also affect middlemen’s division of labor.

This paper is of great significance for evaluating the development level and forecast the development direction of e-commerce.

A number of literature contributions have underlined the importance of developing value-added logistics activities or VALS in order to help improve customers’ satisfaction. However, there is usually very little attention given regarding where to perform these VALS. This study aims to: (1) identify a comprehensive set of factors which may influence the location of VALS, (2) to analyze to what extent those factors influence location decisions, and (3) to distinguish the determinants behind the location choices for distribution centers and for the kind of VALS that will be developed in these distribution centers.

In this paper, we will present a conceptual framework on the locations of VALS in view of the identifying determinants for assigning VALS to logistical centers. We argue that the optimal location of VALS is determined by complex interactions between the determinants at the level of the choice of a distribution system, distribution center location factors, and different logistical characteristics regarding products.

The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers.

This paper uses a conceptual approach that is rooted in the service, robotics and AI literature.

The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level.

This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots.

This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future.

There are three aims of this research. One is to verify the mutual effects between internal collaboration and external collaboration, another is to prove performance improvement among different levels of supply chain collaboration, and the third is to analyze gaps between the two viewpoints. The population is Korean FDI firms in China and 208 data are used in the analysis. The data are treated with various methods: exploratory and confirmatory factor analyses, SEM, cluster analysis, ANOVA, MANOVA and post hoc analysis. The results are as follows. First, external collaboration and internal collaboration have positive effects on each other, which have a positive effect on performance. This means that efficiency of internal processes is the cause of promoting connection with external processes and information generated from the market is the basis of a variance of internal processes, followed by high performance. Second, service performance improvement is more definite than cost performance improvement among different levels of supply chain collaboration. Firms can achieve more definite results in service performance when they perform supply chain collaboration. Third, this research verifies both the viewpoint of directions of supply chain collaboration and the strategic choice viewpoint of supply chain collaboration to better understand supply chain collaboration. Both viewpoints approach supply chain collaboration from different viewpoints but they do explain the methods for performance improvement.

The aim of this paper is to understand if service innovation (Helkkula et al., 2018), based on artificial intelligence (AI) systems, may guarantee healthcare service ecosystem (H-SES) well-being (Frow et al., 2019; Beirão et al., 2017), taking into account that many doubts relieved in terms of transparency may compromise the patients' perceived quality of health services provided through AI systems.

A literature review on service innovation, detected in terms of value co-creation, and service ecosystem, investigated in terms of well-being, is drawn. To analyze the implications of service innovation on a H-SES well-being, through the technology acceptance degree and predisposition to use by actors, a case study based on TAM-model 3 determinants as categories is carried out.

AI-based service innovation archetypes in healthcare may be considered as antecedents of the service ecosystem well-being conditions as long as they enable actors to co-create value. To make it possible, a patient-driven service innovation is necessary in order to mitigate the risks of its inactivity due to fears in terms of transparency.

Service innovation and service ecosystem well-being may be studied in an integrated way, with a multidisciplinary approach, and are linked by value co-creation, because only thanks a patient-driven service innovation is possible to foster service ecosystem well-being in healthcare.

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.