Dina Marie V. Zemke

Purpose: This study examines the effect of perceived job fit, technology readiness, social influence, and perceived difficulty of learning on restaurant employees’ intentions to collaborate with service robots and their turnover intentions if service robots were to be used. Design/methodology/approach: An online questionnaire was used to collect data on the perceptions and behavioral intentions of US restaurant employees regarding service robots. Responses from 483 participants were analyzed using confirmatory factor analysis (CFA) and structural equation modeling (SEM). Findings: Respondents are more willing to collaborate with service robots when they perceive a stronger alignment between the robots’ functionalities and their job tasks, receive greater social support for using robots in the workplace and experience fewer challenges in learning to use the technology. Conversely, those who perceive a poor job fit or encounter greater learning difficulties are more likely to consider leaving the organization if service robots are implemented. Employees’ technology readiness level has a nonsignificant effect on behavioral intentions. Comparative analyses reveal significant differences in behavioral intentions across demographic groups. Practical implications: Restaurants interested in implementing service robots should focus on effective job design and cultivate a supportive learning environment to enhance employee acceptance and mitigate potential turnover. Originality/value: The current study simultaneously examines employees’ intentions to collaborate with service robots and their turnover intentions in response to the implementation of robots. It offers a novel perspective on the impact of service robots on the hospitality workforce.

Purpose: Robotic technology is increasingly prevalent in the restaurant industry. The purpose of this study was to explore various factors that impact quick-service restaurant (QSR) guests’ attitudes toward robotics and the guests’ intentions to visit QSRs that deploy robotic technology.Design/methodology/approach: This study used an online survey that collected quantitative and qualitative data from a sample of 615 US-based adults who dine at QSRs at least once a month. The data were analyzed using confirmatory factor analysis and thematic content analysis.Findings: The results indicated that novelty-seeking, human interaction, perceived benefit, ethics, perceived ease of use and social influence were significantly associated with intentions to visit QSRs that use robots. The qualitative thematic analysis suggested that QSR guests are concerned about the social implications of using robotic technology, but not as concerned as some previous research suggested. QSR guests are receptive to robotics that improve the service experience.Research limitations/implications: The sample used for this study consisted of frequent QSR diners. The findings may not be generalizable across all types of restaurant guests, such as full-service or quick casual guests. The study also relied on the participants’ memories of restaurant experiences; future studies could focus on collecting data while a restaurant customer is in the service experience.Originality/value: The current research synthesizes theories in psychology and technology acceptance to study an emerging phenomenon in the hospitality industry. It innovatively examines the social influence and guests’ need for human interaction in their service experience. In addition, the findings from the qualitative data analysis supplement and extend the conclusions from the quantitative findings.

Hospitality firms are exploring opportunities to incorporate innovative technologies, such as robotics, into their operations. This qualitative study used focus groups to investigate diner perspectives on issues related to using robot technology in quick-service restaurant (QSR) operations. QSR guests have major concerns regarding the societal impact of robotics entering the realm of QSR operations; the cleanliness and food safety of robot technology; and communication quality, especially voice recognition, from both native and nonnative English speakers. Participants also offered opinions about the functionality and physical appearance of robots, the value of the “human touch,” and devised creative solutions for deploying this technology. Surprisingly, few differences in attitudes and perceptions were found between age groups, and the participants were highly ambivalent about the technology. Future research may consider further exploration of robot applications in other restaurant segments, using quantitative methods with a larger sample.

Purpose: Firms that serve customers in the service environment rely on a well-designed servicescape. This is particularly true in the hotel industry, where the hotel’s design is an important part of the product mix. However, despite design’s importance, there is no common instrument available to measure hotel design quality. The purpose of this paper is to present a quantitative method, the Design Quality Indicator, to measure guests’ evaluations of hotel design quality. Design/methodology/approach: Nearly 5,000 guests of two full-service hotel brands were surveyed soon after a hotel stay (within two weeks of check-out). The DQI’s factor structure is tested using principle components analysis and confirmatory factor analysis to improve the reliability, validity and parsimony of the instrument. Findings: The study yields a DQI instrument that is reduced from 92 to 41 measurement items, with good reliability and validity, enabling more efficient data collection and analysis. Research limitations/implications: This study only examines guests’ assessments of two full-service hotel brands. The instrument can be used to explore design’s relationship with numerous outcome variables, such as satisfaction, loyalty, and repatronage intentions, as well as property performance outcomes. Practical implications: The methods demonstrated can be used by hotel owners and operators to inform resource allocation decisions, particularly when planning for renovations. Originality/value: This study provides a reliable, validated quantitative assessment of hotel design quality. It is also one of the few studies that elicits feedback about a guest’s actual hotel stay, rather than a hypothesized or simulated stay.

Purpose: The purpose of this paper is to test the relationships between a hotel’s design quality and the property’s business performance.Design/methodology/approach: Hotel guests’ assessments of the design quality of hotels that they recently visited are tested using the design quality indicator (DQI). Business performance is measured using indexed values for each property’s occupancy, average daily rate (ADR) and revenue per available room (RevPAR). The data are analyzed using exploratory factor analysis and a variation of a hedonic pricing model.Findings: Factor analysis reduced the DQI instrument to 19 measurement items. Factors that measure navigability and signage positively impact occupancy index. Factors that measure flexible space usage negatively impact the RevPAR and ADR indices. Factors that reflect aesthetic constructs, including Urban & Social Integration and Character & Form, positively impact the RevPAR and ADR indices.Research limitations/implications: The study examines a nationwide sample of guests from two full-service brands of a single multi-brand hotel company. The study provides a parsimonious, validated design measurement instrument and a revised hedonic pricing analysis.Practical implications: Hoteliers can use this technique to assist with resource allocation decisions. Aesthetic elements, including the building’s Urban & Social Integration with its surroundings and its Character & Form, lead to higher ADR and RevPAR performance. Managers should ensure a coherent layout and good signage program to drive occupancy.Originality/value: This study offers a technique to measure design quality and a new method of performing a hedonic pricing analysis.

Purpose: The purpose of this study is to investigate the determinants of customers’ intentions to use location-based services (LBS) offered by a hotel. The study examined whether hotel customers’ coupon proneness, trust, privacy concerns and familiarity with LBS are significant determinants of their intentions to use LBS. Design/methodology/approach: An online survey using a scenario-based narrative was administered to collect data from participants who have smartphones and have stayed at a full-service hotel within the previous 12 months. A research model tested data collected from 402 hotel customers, using confirmatory factor analysis and structural equation modeling. Findings: Three proposed determinants (i.e. familiarity, coupon proneness and trust) positively influenced customers’ intentions to use LBS. Out of the four dimensions of privacy concerns (concerns of collection, error, unauthorized secondary use and improper access), only concerns about data collection negatively influenced customers’ intentions to use a hotel’s LBS. Originality/value: This study extends the literature on LBS adoption and other technology with privacy issues by modifying existing models and empirically testing it in the new context of hotels.

This study presents a method to measure hotel design quality and its relationships with guest satisfaction and with behavioural intentions. Hotel design quality is measured using the Design Quality Indicator (DQI). A partial least squares analysis reveals that the DQI predicts guest satisfaction with both statistical and practical significance. In addition, satisfaction is shown to predict guest behavioural intentions. This study extends theory by providing a means of measuring beliefs about a service environment’s design and provides practical implications by developing a means of measuring guest satisfaction with a hotel’s design.

This exploratory study expands the current literature on servicescapes by examining the total noise environment in restaurants and the impact of ambient noise levels and general restaurant attributes on customer satisfaction and loyalty behavior, defined as the customer's willingness to return to a restaurant and motivation to recommend it. The researchers surveyed guests at one casual dining restaurant in the Southwestern United States. The results showed that services, physical attributes, and quality of food and beverage had significant impact on overall satisfaction, overall atmosphere, and loyalty behaviors. Noise level factors such as effects of noise and appropriateness of noise levels, influenced overall satisfaction, but not loyalty behaviors.