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The purpose of this paper is to examine food safety behaviors of consumers and employees at university food courts.

Using a smartphone-based observation technique, a total of 149 consumers and 34 employees were observed at three food courts at a mid-western university in the USA. The observational tool recorded 30 sequential transactions of each individual, allowing researchers to identify the compliance rate to the rubric. Both descriptive statistics and multivariate analysis of variance were used for data analysis.

This study found a low compliance rate of food safety practices among consumers and employees at university food courts. Consumers’ food safety practices varied depending on gender, observed ethnicity and party size, while none of those factors was significant for employees. Specifically, females, Caucasians, and lone diners showed higher non-compliance rates than those of males, non-Caucasians and group diners.

The results of the study raise the pressing needs of developing effective risk communication strategies at university food courts for both consumers and employees in order to reduce the potential risk of foodborne illness outbreaks.

University food courts are not only major foodservice operations for on-campus populations as well as off-campus visitors and the local public, but also the presence of shared dining area pertains the potential risk of foodborne illnesses. However, lack of attention has been paid to the food safety issues at university food courts, and especially food safety behaviors of consumers. This study extended the knowledge of previous food safety literature by adopting a smartphone-based observation technique and developing a rubric customized for consumers and employees at university food courts.

Off-premise restaurant service has a new addition – food delivery robots. This new technology and off-premise service, in general, has received little research attention, despite continued year-over-year sales growth for both carry-out and delivery. Therefore, this study aims to analyze off-premise service modes, including food delivery robots, for service quality gaps between consumer expectations and actual performance and among the various modes.

Performance of three off-premise restaurant service modes (robot-delivery, human-delivery and carry-out) were evaluated using a mixed-methods approach. Consumer expectations were ascertained about food- and service-related performance factors using a survey, and a field observation study was conducted to obtain actual performance data for these factors. Findings from both approaches were compared to identify gaps and differences.

For food-related performance, consumers reported lower expectations for food safety and food quality from robot- and human-delivered food; however, no differences were observed among the three modes in the field study. Consumers also expected lower service-related performance from robot-delivery for service efficiency and ease of use (than human-delivery and carry-out) and monetary value (than carry-out). Consumers deemed robots the most sustainable and human-delivery the most convenient compared to other modes – however, not all service-related expectations aligned with actual performances.

This study was the first to comparatively examine off-premise restaurant service. Identification of a missing link in service gap analysis was among the theoretical contributions of this study. Managerially, this study provides previously unavailable insights into opportunities for improvement for off-premise service and use of delivery robots.

This study aims to identify articles examining human-robot interaction and the effects of robotic systems on employment.

In this research, electronic searches were performed for articles published between 2000 and 2022 in Emerald, Springer, PubMed, Science Direct, Wiley and Google Scholar. In the searches of robotic systems with keywords such as “motivation, job satisfaction, job loss, performance, job giving,” 5 quantitative and 5 qualitative studies were included in the systematic review. The selected research was conducted using the Johanna Briggs Analytical Cross-Sectional Studies Checklist from the Joanna Briggs Institute (JBI) critical evaluation lists and the JBI Critical Appraisal Checklist for Qualitative Research, depending on their type. The included studies are mostly on employee-robot collaboration.

Although the majority of the articles examined in this study are included in keywords or titles, it is determined that there is a gap in descriptive quantitative studies in the literature on the effects of employee-robot collaboration, robotic systems and robotic systems on variables such as motivation, job satisfaction, job loss, performance and employment, although they do not mention a framework that directly investigates human-robot interaction and the effects of robotic systems on employment.

There are several limitations in this study. One of them is that, although the databases are comprehensively scanned, only studies published in English between 2000 and 2022 are included in the systematic review. Another limitation is the heterogeneity between studies.

As a result of the authors’ findings, the practical effects of the research are reflected as follows: It serves as a guide for future studies to fill the gap in the field, especially for academics and researchers working in the field of social sciences on robotic systems and intelligent automations. In addition to the qualitative studies on this subject, there is a need for the use of robotic systems in the field of human resources and management and quantitative studies with more sample sizes, especially at the corporate (firms) and individual (employees) level. Considering that the number of studies on this subject is very insufficient, this research is important in terms of shedding light on future studies.

The authors believe that the impact of robotic systems on employment is one of the few conceptual articles that systematically examines 6 dimensions (job satisfaction, performance, job loss, employment, motivation, employment).