Search results

The purpose of this paper is to systematically analyze existing studies related to the adoption of smart technologies in cruise tourism services, particularly robots, artificial intelligence, service automation and virtual reality. More specifically, the authors intend to highlight the current state of research on this topic, present the findings within a conceptual framework and propose a research agenda.

The relevant literature was extracted using two major electronic databases, web of science (WoS) and Scopus. The authors identified 31 articles from high-quality journals and used a systematic review and the VOSviewer software to analyze them.

Since 2014, there has been an increase in the number of studies related to smart technologies in cruise tourism services. At first, researchers focused on Royal Caribbean’s robotic bartender arm, whereas other technologies such as digital signage, self-service options, facial recognition and virtual culinary experiences received less attention. However, the interest in exploring these last smart technologies has grown significantly since 2019. The adoption of RAISA in the cruise tourism service (ASCT) framework was proposed, identifying five major domains: cruise robotic technology, technology innovation, cruise passengers’ engagement behavior, cruise passengers’ technology readiness and privacy perception and knowledge expertise. These domains provide valuable guidance for future research in this field.

To the best of the authors’ knowledge, this is the first study to systematically analyze literature on the adoption of new technologies in cruise tourism services, specifically focusing on the major technologies available on cruise ships.

本文的主要目标是系统地分析与邮轮旅游服务中智能技术采用（RAISA）相关的现有研究, 特别是关于机器人、人工智能、服务自动化和虚拟现实等方面。具体而言, 我们意图突出此主题的当前研究现状, 将研究结果呈现在一个概念框架中, 并提出一个研究议程。

我们使用了两个主要的电子数据库 WoS 和 Scopus 提取相关文献。我们从高质量期刊中找到了 31 篇文章, 并采用系统综述和 VOSviewer 软件对它们进行了分析。

自 2014 年以来, 与邮轮旅游服务中智能技术相关的研究数量不断增加。最初, 研究人员着重关注皇家加勒比邮轮公司的机器人调酒师臂, 而其他技术, 如数字标识、自助选项、面部识别和虚拟烹饪体验等, 得到的关注较少。然而, 自 2019 年以来, 探索这些智能技术的兴趣显著增长。提出了 ASCT 框架, 识别了五个主要领域：邮轮机器人技术; 技术创新; 邮轮旅客参与行为; 邮轮旅客技术准备度; 以及隐私感知和专业知识。这些领域为该领域的未来研究提供了有价值的指导。

这是第一篇系统分析邮轮旅游服务中新技术采用文献的研究, 特别聚焦于邮轮上的主要技术。

This study examines the social organizational structure of one early childhood education (ECE) center in Finland and the relationship between this structure and the roles and the responsibilities of the members of the organization.

The research is a qualitative case study with ethnographic features. Its variables for content analysis are based on Henry Mintzberg's theory of organizational design.

The study's results show that the organizational structure of the ECE center follows the organizational configuration of a Professional bureaucracy and that the multiprofessional teams follow the configuration of a Simple structure. The structures for centralization and decentralization are suitable for a professional bureaucracy, but the roles of the members of the organization and the processes for shared decision-making lack clarification. The shortage of qualified ECE teachers disrupts the function of the organization and the work of ECE leaders.

The educational background of subjects may have affected the findings.

The study uses Henry Mintzberg's organizational structure theory to evaluate how and why power is distributed and activities are coordinated at the ECE center. The results also show what parts of the organization pose challenges that most commonly disrupt the organization's operations. With these findings, it is possible to expand the understanding of roles and responsibilities in the currently reforming ECE environment and what ECE centers need to function effectively. The study is part of a larger research project and will be continued to examine the leadership culture of the ECE center.

This study aims to test the mean and volatility spill over from the environmental, social, and governance (ESG) market to the stock markets of G7 countries. The study used ARMA-GARCH model to predict the results. The findings of the study reveal that as the spill over exists in the markets, however the mean volatility does not exist showing efficiency of the market as significant results depict that past prices cannot predict the future prices. It provides new insights for the international portfolio investors and policymakers by shedding light on how cross-markets correlate in two different markets.

Within the scope of the research, articles about service robots were examined by the systematic review method.

The research aims to evaluate the articles on service robots, an artificial intelligence (AI) application in restaurant businesses, using a systematic review method. In systematic reviews, the data obtained as a result of scanning databases to find an answer to a research question are synthesized and reported. The criterion sampling technique, one of the purposeful sampling methods, was used for the sample of the research. Inclusion and exclusion criteria were applied within the scope of screening.

The articles on service robots were carried out between 2018 and 2023. In terms of research methods, most of the articles are quantitative, while there are studies on mixed and qualitative methods. In studies, data were generally collected by survey technique. The keywords of the studies on service robots are examined; the most commonly used words were service robot and AI, technology, restaurant, satisfaction, revisit intention, consumer behavior, intention, preference, hospitality and foods. The objectives of the articles pertinent to service robots are mostly to determine people's attitudes and acceptance toward these services focuses.

The studies seem to focus more on customer acceptance, trust, expectations, risks, adaptation, reasons for preference, impact on creative services, emotional and cognitive effects and human–robot interaction. Despite this, it is observed that there are fewer studies on topics such as the development of service robots in restaurant businesses, their reflections on the future, future opportunities and the quality of chef service robots. Based on this, it is recommended to consider studies that will serve as a reference for revealing innovative opportunities that can meet future expectations in order to increase the quality of service robots in restaurant businesses.

This study aims to explore the role of frontline service employees’ (FSEs) awareness that their job can be substituted by smart technology, artificial intelligence, robotics and algorithms (STARA) in their job autonomy and proactive service performance and when these relationships can be buffered. Drawing on the cognitive appraisal theory of stress, the study examined the mediating relationship between FSEs’ STARA awareness, job autonomy and proactive service performance and the moderating effects of self-efficacy and resilience on this relationship.

The authors administered two-wave online surveys to 301 South Korean FSEs working in various service sectors (e.g. retailing, food/beverage, hospitality/tourism and banking). The Time 1 survey measured respondents’ STARA awareness, self-efficacy, resilience and job autonomy, and the Time 2 survey assessed their proactive service performance.

FSEs’ STARA awareness negatively affected their subsequent proactive service performance through decreased job autonomy. The negative association between STARA awareness and job autonomy was weaker when FSEs’ self-efficacy was high than when it was low. While the authors observed no significant moderation of resilience, the author found a marginally significant three-way interaction between STARA awareness, self-efficacy and resilience. Specifically, STARA awareness was negatively related to job autonomy only when both self-efficacy and resilience were low. When either self-efficacy or resilience was high, the association between STARA awareness and job autonomy became nonsignificant, suggesting the buffering roles of the two personal resources.

Given that the measurement of variables relied on self-reported data, rater biases might have affected the findings of the study. Moreover, the simultaneous measurement of STARA awareness, self-efficacy, resilience and job autonomy could preclude causal inferences between these variables. The authors encourage future studies to use a more rigorous methodology to reduce rater biases and establish stronger causality between the variables.

Service firms can decrease FSEs’ STARA awareness through training in the knowledge and skills necessary to work with these technologies. To promote FSEs’ proactive service performance in this context, service firms need to involve them in decisions related to STARA adoption and allow them to craft their jobs. Service managers should provide FSEs with social support and exercise empowering and supportive leadership to help them view STARA as a challenge rather than a threat.

Distinct from prior research on STARA awareness and employee outcomes, the study identified proactive service performance as a key outcome in the STARA context. By presenting self-efficacy and resilience as crucial personal resources that buffer FSEs from the deleterious impact of STARA awareness, the study provides practitioners with insights that can help FSEs maintain their job autonomy and proactive service performance in times of digitalization and automation.