A Study On Diners’ Opinion Towards Induction Of Service Robots In Gujarat Restaurants

Authors

  • Sujay Vikram Singh Senior Research Fellow, Department of History of Art & Tourism Management, Banaras Hindu University, Varanasi
  • Shashank Rajauria Lecturer, Institute of Hotel Management, Ahmedabad, Gujarat
  • Vishrut Verma Junior Research Fellow, Department of History of Art & Tourism Management, Banaras Hindu University, Varanasi

DOI:

https://doi.org/10.48165/pjhas.2023.9.2.1

Keywords:

Artificial Intelligence, Diners, Innovativeness, Restaurants, Service Robots

Abstract

Background: The rapid development of technology has allowed the restaurant sector to integrate a wide range of  technologies into service settings. Service robots can boost efficiency and food service revenues. This study examines  consumer approval of diner service robots. Objectives: (a) To analyse diners' views on restaurant robots, (b) To  know the effect of demographic considerations on robot introduction in restaurants and (c) To examines diners views  on prospects and difficulties that affect service robot attitudes. Methodology: An exploratory research design with  structured questionnaire was distributed to 362 participants among which 337 were suitable for the study. Purposive  sampling was used to obtain diner’s perspective of inducting service robots in restaurants at major cities of Gujarat  (Ahmedabad, Surat, Baroda, Gandhinagar & Rajkot). Data analysis was done on the basis of demographic profile and  frequency of visit to the restaurants by using SPSS 25.0. Results: Based on admissible Eigen values, the study derived  three criteria for diner acceptance of service robots that explained 72.28% of variance. Hypotheses showed age and  gender influenced service robot induction. Education did not affect service robot acceptance. The study suggests that  people's views on robots affect their views on restaurant robots. Conclusion: The study shows that service robots could  assist restaurants. It specifies service robots' study operations. Diner acceptance of service robots will give a theoretical  framework for other service industries in technological acceptance and consumer behavior. 

References

Aggarwal, P., & McGill, A. L. (2007). Is that car smiling at me? Schema congruity as a basis for evaluating anthropomorphized products. Journal of consumer research, 34(4), 468-479.

Bartneck, C., Kanda, T., Mubin, O., & Al Mahmud, A. (2007). The perception of animacy and intelligence based on a robot’s embodiment. In 2007 7th IEEE-RAS International Conference on Humanoid Robots (pp. 300–305). Pittsburgh, PA, USA: IEEE. doi: 10.1094. PDIS-91-4-0467B.

Berezina, K., Ciftci, O., & Cobanoglu, C. (2019). Robots, artificial intelligence, and service automation in restaurants. In Robots, artificial intelligence, and service automation in travel, tourism and hospitality. Emerald Publishing Limited, 185-219

Choe, J. Y., Kim, J. J., & Hwang, J. (2022). Innovative robotic restaurants in Korea: merging a technology acceptance model and theory of planned behaviour. Asian Journal of Technology Innovation, 30(2), 466-489.

Chuah, S. H. W., Aw, E. C. X., & Yee, D. (2021). Unveiling the complexity of consumers’ intention to use service robots: An fsQCA approach. Computers in Human Behavior, 123, 106870.

Das, S., Das, I., Shaw, R. N., & Ghosh, A. (2021). Advance machine learning and artificial intelligence applications in service robot. In Artificial Intelligence for Future Generation Robotics (pp. 83-91). Elsevier.

Garcia-Haro, J. M., Oña, E. D., Hernandez-Vicen, J., Martinez, S., & Balaguer, C. (2020). Service robots in catering applications: A review and future challenges. Electronics, 10(1), 47.

Go, H., Kang, M., & Suh, S. C. (2020). Machine learning of robots in tourism and hospitality: interactive technology acceptance model (iTAM)–cutting edge. Tourism review, 75(4), 625-636.

; 9(2) : 1-10

Ivanov, S. H., & Webster, C. (2017). Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies–a cost-benefit analysis. Artificial Intelligence and Service Automation by Travel, Tourism and Hospitality Companies–A Cost

Benefit Analysis.

Jeong, M., & Shin, H. H. (2020). Tourists’ experiences with smart tourism technology at smart destinations and their behavior intentions. Journal of Travel Research, 59(8), 1464-1477.

Kaur, J., Lavuri, R., Parida, R., & Singh, S. V. (2023). Exploring the impact of gamification elements in brand apps on the purchase intention of consumers. Journal of Global Information Management (JGIM), 31(1), 1-30.

Lin, I. Y., & Mattila, A. S. (2021). The value of service robots from the hotel guest’s perspective: A mixed method approach. International Journal of Hospitality Management, 94, 102876.

Liu, X. S., Yi, X. S., & Wan, L. C. (2022). Friendly or competent? The effects of perception of robot appearance and service context on usage intention. Annals of Tourism Research, 92, 103324.

Lu, L., Zhang, P., & Zhang, T. C. (2021). Leveraging “human likeness” of robotic service at restaurants. International Journal of Hospitality Management, 94, 102823.

Mara, M., & Appel, M. (2015). Effects of lateral head tilt on user perceptions of humanoid and android robots. Computers in Human Behavior, 44, 326-334.

Nozawa, C., Togawa, T., Velasco, C., & Motoki, K. (2022). Consumer responses to the use of artificial intelligence in luxury and non-luxury restaurants. Food Quality and Preference, 96, 104436.

Pande, S., & Gupta, K. P. (2022). Indian customers’ acceptance of service robots in restaurant services. Behaviour & Information Technology, 1-22.

Park, S. S., Tung, C. D., & Lee, H. (2021). The adoption of AI service robots: A comparison between credence and experience service settings. Psychology & Marketing, 38(4), 691-703.

Paul, J., Kaur, D. J., Arora, D. S., & Singh, S. V. (2022). Deciphering ‘urge to buy’: A meta-analysis of antecedents. International Journal of Market Research, 64(6), 773-798.

Pitardi, V., Wirtz, J., Paluch, S., & Kunz, W. H. (2021). Service robots, agency and embarrassing service encounters. Journal of service management, 33(2), 389- 414.

| 9 |

Reis, J., Melão, N., Salvadorinho, J., Soares, B., & Rosete, A. (2020). Service robots in the hospitality industry: The case of Henn-na hotel, Japan. Technology in Society, 63, 101423.

Rosete, A., Soares, B., Salvadorinho, J., Reis, J., & Amorim, M. (2020). Service robots in the hospitality industry: An exploratory literature review. In Exploring Service Science: 10th International Conference, IESS 2020, Porto, Portugal, February 5–7, 2020, Proceedings 10 (pp. 174-186). Springer International Publishing.

Salem, M., Eyssel, F., Rohlfing, K., Kopp, S., & Joublin, F. (2013). To err is human (-like): Effects of robot gesture on perceived anthropomorphism and likability. International Journal of Social Robotics, 5, 313-323.

Seo, K. H., & Lee, J. H. (2021). The emergence of service robots at restaurants: Integrating trust, perceived risk, and satisfaction. Sustainability, 13(8), 4431.

Shimmura, T., Ichikari, R., Okuma, T., Ito, H., Okada, K., & Nonaka, T. (2020). Service robot introduction to a restaurant enhances both labor productivity and service quality. Procedia CIRP, 88, 589-594.

Shin, H. H., & Jeong, M. (2020). Guests’ perceptions of robot concierge and their adoption intentions. International Journal of Contemporary Hospitality Management, 32(8), 2613-2633.

Tuomi, A., Tussyadiah, I. P., & Stienmetz, J. (2021). Applications and implications of service robots in hospitality. Cornell Hospitality Quarterly, 62(2), 232- 247.

Published

2023-11-29

How to Cite

A Study On Diners’ Opinion Towards Induction Of Service Robots In Gujarat Restaurants . (2023). PUSA Journal of Hospitality and Applied Sciences, 9(2), 1–10. https://doi.org/10.48165/pjhas.2023.9.2.1