Search Results - subject:"restaurant technology"

An integrated model of artificially intelligent (AI) facial recognition technology adoption based on perceived risk theory and extended TPB : a comparative analysis of US and South Korea

Hwang, Jinsoo; Kim, Jungsun; Joo, Kyu-Hyeon; Choe, Ja Young - In: Journal of hospitality marketing & management 33 (2024) 8, pp. 1071-1099

Persistent link: https://www.econbiz.de/10015084027

The antecedents and consequences of task–technology fit of facial recognition payment systems in the restaurant industry: cultural differences

Kim, Jinkyung Jenny; Kim, Jungsun (Sunny); Joo, Kyu-Hyeon; … - In: Journal of Hospitality and Tourism Technology 15 (2024) 3, pp. 397-416

Purpose The purpose of this study is to investigate the key predictors and outcomes of task–technology fit (TTF) of facial recognition payment systems with the moderating role of cultural differences in the restaurant industry. Design/methodology/approach The survey responses were collected...

Persistent link: https://www.econbiz.de/10015350972

AI and robotics in the European restaurant sector : assessing potentials for process innovation in a high-contact service industry

Blöcher, Katharina; Alt, Rainer - In: Electronic markets : EM ; the international journal of … 31 (2021) 3, pp. 529-551

Persistent link: https://www.econbiz.de/10012666406

Restaurant menus and COVID-19: implications for technology adoption in the post-pandemic era

Iskender, Ali; Sirakaya-Turk, Ercan; Cardenas, David - In: Consumer Behavior in Tourism and Hospitality 18 (2023) 4, pp. 587-605

Purpose This paper aims to systematically explore the experiences of restaurant patrons with quick response (QR) code menus during the pandemic to extract insights pertaining to the acceptance of technology adoption in service settings for the post-COVID era. Design/methodology/approach COVID-19...

Persistent link: https://www.econbiz.de/10014691349

A projective approach to understanding the Generation Z’s experience with service robots in restaurants

Ma, Caiwei; Chen, Po-Ju; Ren, Lianping; Fan, Alei; … - In: Journal of Hospitality and Tourism Technology 14 (2023) 5, pp. 717-731

Purpose This study aims to investigate Generation Z’s perception of and experience with restaurant service robots. Design/methodology/approach Established on the servicescape theoretical framework and following Zaltman Metaphoric Elicitation Technique, 34 in-depth interviews were conducted...

Persistent link: https://www.econbiz.de/10014874029

AI and robotics in the European restaurant sector: Assessing potentials for process innovation in a high-contact service industry

Blöcher, Katharina; Alt, Rainer - In: Electronic Markets 31 (2020) 3, pp. 529-551

The restaurant technology market is rapidly evolving and is transforming the restaurant business as a significant …

Persistent link: https://www.econbiz.de/10014504237

Let's face it : are customers ready for facial recognition technology at quick-service restaurants?

Ciftci, Olena; Choi, Eun-Kyong; Berezina, Katerina - In: International journal of hospitality management 95 (2021), pp. 1-12

Persistent link: https://www.econbiz.de/10012547991

Consumer responses to interactive restaurant self-service technology (IRSST) : the role of gadget-loving propensity

Ahn, Jee Ahe; Seo, Soobin - In: International journal of hospitality management 74 (2018), pp. 109-121

Persistent link: https://www.econbiz.de/10011924621