Disruptive Technologies and Innovation in Hospitality: A Computer-Assisted Qualitative Data Analysis Approach

Lee, Minwoo; Sisson, Annamarie D.; Costa, Rui; Bai, Billy

doi:10.1177/10963480231156080

Cited by 22 publications

(10 citation statements)

References 46 publications

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“…As a result, many turn to technology innovations for help (Park et al. , 2023; Lee et al. , 2023; Lee et al.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

“…Landman, 2022) and their impact on profitability (Mun and Jang, 2018), and most recently, a debilitating shortage of labor (Kwok, 2022). As a result, many turn to technology innovations for help (Park et al, 2023;Lee et al, 2023;Lee et al, 2021). One such technology-driven major shift is the central kitchen operation (Cooper, 2021), enabled by multiple technological advances (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Estimating restaurants’ unconstrained demand: a systematic approach to reducing structural bias in forecast accuracy measures

2024

JHTT

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Purpose The diffusion of technologies from other sectors, and innovations in kitchen equipment, fueled structural changes within the foodservice industry. However, this change comes at a price of disrupting the critical step of assessing the demand forecast accuracy. This study aims to explore a surprisingly unique and elevated complexity when assessing the critically important demand forecast accuracy. Design/methodology/approach The paper develops a mathematical model to describe and explore the nature of the problem in structural biased demand forecast accuracy assessment. It then uses numerical simulation to construct a market example to gain better insights on the bias characteristics. Finally, the forecast accuracy measurement’s inherent bias is contrasted with that of other typical hospitality forecasting setups. Findings This paper outlines the theoretical underpinnings of how demand forecasts in the central kitchen setup are dynamic and thus produce a structural bias. More specifically, this paper discovers how, in this context of orders from a central location, the forecasts set the capacity constraints, and, consequently, generate a considerably more biased forecast accuracy measure. Relying on such forecast accuracy measures can lead to serious negative business outcomes. Originality/value To the best of the author’s knowledge, this study is the first to show that in the unique new technology enabled environment of central kitchen operation, where daily dish demand forecasts set the daily constrained capacity levels, the accuracy measure is severely biased, and consequently accuracy is likely to deteriorate, which in turn, could lead to suboptimal decisions. The major theoretical contribution of this study is a novel analytical model which explains and describes the bias in the accuracy measurement.

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“…As a result, many turn to technology innovations for help (Park et al. , 2023; Lee et al. , 2023; Lee et al.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating restaurants’ unconstrained demand: a systematic approach to reducing structural bias in forecast accuracy measures

2024

JHTT

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“…In this era of information consumption, constant evolution exists in the tourism industry with the emergence of new trends and technologies (Lee et al, 2023;Park et al, 2023). Among these advances, generative artificial intelligence (AI) stands out as a technology that will significantly affect the tourism industry (Dogru et al, 2023a;Garcia, 2023;Gursoy et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

“…In this era of information consumption, constant evolution exists in the tourism industry with the emergence of new trends and technologies (Lee et al. , 2023; Park et al.…”

Section: Introductionmentioning

confidence: 99%

Embracing the ChatGPT revolution: unlocking new horizons for tourism

Shi,

Lee,

Girish

et al. 2024

JHTT

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Purpose This study aims to investigate tourists’ attitudes and intentions regarding the usage of Chat Generative Pre-trained Transformer (ChatGPT) for accessing tourism information. Furthermore, by integrating the perceived risks associated with ChatGPT and the theory of planned behavior (TPB), this research examines the impact of three types of perceived risks, such as privacy risk, accuracy risk and overreliance risk, on tourists’ behavioral intention. Design/methodology/approach Data were gathered for this study by using two online survey platforms, thus resulting in a sample of 536 respondents. The online survey questionnaire assessed tourists’ perceived risks, attitude, subjective norm, perceived behavioral control, behavioral intention and demographic information related to their usage of ChatGPT. Findings The structural equation modeling analysis revealed that tourists express concerns about the associated risks of using ChatGPT to search for tourism information, specifically privacy risk, accuracy risk and overreliance risk. It was found that perceived risks significantly influence tourists’ attitude and intention toward the usage of ChatGPT, which is consistent with the hypotheses proposed in previous literature regarding tourists’ perceived risks of ChatGPT. Research limitations/implications This work is a preliminary empirical study that assesses tourists’ behavioral intention toward the use of ChatGPT in the field of tourism. Previous research has remained at the hypothetical level, speculating about the impact of ChatGPT on the tourism industry. This study investigates the behavioral intention of tourists who have used ChatGPT to search for travel information. Furthermore, this study provides evidence based on the outcome of this research and offers theoretical foundations for the sustainable development of generative AI in the tourism domain. This study has limitations in that it primarily focused on exploring the risks associated with ChatGPT and did not extensively investigate its range of benefits. Practical implications First, to address privacy concerns that pose significant challenges for chatbots various measures, such as data encryption, secure storage and obtaining user consent, are crucial. Second, despite concerns and uncertainties, the introduction of ChatGPT holds promising prospects for the tourism industry. By offering personalized recommendations and enhancing operational efficiency, ChatGPT has the potential to revolutionize travel experiences. Finally, recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. Social implications Recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. As their interest in adopting ChatGPT grows, increased investments and resources will be dedicated to developing and implementing ChatGPT solutions. This enhancement may involve creating customized ChatGPT solutions and actively engaging in training and development programs to empower employees in effectively using ChatGPT’s capabilities. Such initiatives can contribute to improved customer service and overall operations within the tourism industry. Originality/value This study integrates TPB with perceived risks in ChatGPT, thus providing empirical evidence. It highlights the importance of considering perceived risks in tourists’ intentions and contributes to the sustainable development of generative AI in tourism. As such, it provides valuable insights for practitioners and policymakers.

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“…The fourth article, by M. Lee et al (2023), is titled "Disruptive Technologies and Innovation in Hospitality: A Computer-Assisted Qualitative Data Analysis Approach." The authors pointed out that there is a need for a better understanding of the role of disruptive technologies and innovation in hospitality businesses.…”

mentioning

confidence: 99%