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The advent and development of digital platforms has helped enhance the international visibility of brands, products and services, and has also introduced a proliferation of online reviews. This study develops a big data analysis of customer online reviews of hospitality services to gauge the extent to which the cultural distance among service providers and their customers influences online review ratings. By examining almost 715,000 online reviews written by hotel customers from more than 100 different nationalities, the effect of national cultural differences among service customers and providers (namely cultural distance) on online review ratings is innovatively scrutinized. The paper, by considering reviewers’ behavioral features, demographics, and trip-related factors, reveals that the effect of national cultural distance on online review ratings is negative. Several implications for practitioners are also discussed.

[...]the advancement of digital technologies is radically transforming consumers’ information search and booking/purchase behaviours (Mariani et al., 2019), the way companies innovate (Mariani and Nambisan, 2021), as well as how gastronomy experiences are communicated, managed and marketed. [...]the purpose of this special issue is to broaden and deepen our knowledge of gastronomy experiences in hospitality and tourism, from a managerial perspective, in a rapidly changing world. 2. [...]of the selection, 30 papers were invited for submissions from which 15 papers were accepted. Data were collected from Korean domestic tourists, and the hypothesized relationships have been validated through structural equation modelling (SEM), suggesting that the four dimensions of gastronomy experience have a significant and positive effect on experience satisfaction. [...]the authors find that experience satisfaction influences indirectly the quality of life through subjective well-being which acts as a mediator. [...]the degree of co-creation has been found to positively moderate the effect experiences on experience satisfaction. [...]pleasant”, “interesting”, “fun”, “special” and “authentic” have been confirmed as valid keywords, which provide enough information to measure the tourists’ affective gastronomy experiences.

Purpose The purpose of this work is to survey the body of research revolving around big data (BD) and analytics in hospitality and tourism, by detecting macro topical areas, research streams and gaps and to develop an agenda for future research. Design/methodology/approach This research is based on a systematic literature review of academic papers indexed in the Scopus and Web of Science databases published up to 31 December 2020. The outputs were analyzed using bibliometric techniques, network analysis and topic modeling. Findings The number of scientific outputs in research with hospitality and tourism settings has been expanding over the period 2015–2020, with a substantial stability of the areas examined. The vast majority are published in academic journals where the main reference area is neither hospitality nor tourism. The body of research is rather fragmented and studies on relevant aspects, such as BD analytics capabilities, are virtually missing. Most of the outputs are empirical. Moreover, many of the articles collected relatively small quantities of records and, regardless of the time period considered, only a handful of articles mix a number of different techniques. Originality/value This work sheds new light on the emergence of a body of research at the intersection of hospitality and tourism management and data science. It enriches and complements extant literature reviews on BD and analytics, combining these two interconnected topics.

Tourism Management, Marketing, and Development recognizes the relevance of tourism and tourism activities as major economic drivers, with a specific focus on the role of destination management and marketing, performance and strategies, and sustainability.

Companies and destinations in the tourism sector are confronted with increasing managerial challenges and have to deal with a competitive, turbulent, and fast-changing environment. The understanding that both tourism companies and destinations endowed with the best assets (natural and cultural) cannot survive the escalating international competition without good managerial practices, has provided significant momentum for the development of the disciplinary field of tourism management in the last three decades. This volume recognizes the relevance of travel, tourism, and tourism activities as major economic drivers in the contemporary global economy, with a specific focus on performance, strategies, and sustainability. It is the collective intellectual effort of a number of international scholars, who cultivate original research on tourism management from a variety of theoretical perspectives. Together, they outline the importance for tourism companies and destinations to achieve and maintain a sustained competitive advantage by embracing sustainability and a Triple Bottom Line (TBL) approach to performance.

Purpose This work consists of a critical reflection on the extent to which hospitality and tourism management scholars have accurately used the term “analytics” and its five types (i.e. descriptive, exploratory, predictive, prescriptive and cognitive analytics) in their research. Only cognitive analytics, the latest and most advanced type, is based on artificial intelligence (AI) and requires machine learning (ML). As cognitive analytics constitutes the cutting edge in industry application, this study aims to examine in depth the extent cognitive analytics has been covered in the literature. Design/methodology/approach This study is based on a systematic literature review (SLR) of the hospitality and tourism literature on the topic of “analytics”. The SLR findings were complemented by the results of an additional search query based on “machine learning” and “deep learning” that was used as a robustness check. Moreover, the SLR findings were triangulated with recent literature reviews on related topics (e.g. big data and AI) to generate additional insights. Findings The findings of this study show that: there is a growing and accelerating body of research on analytics; the literature lacks a consistent use of terminology and definitions related to analytics. Specifically, publications rarely use scientific definitions of analytics and their different types; although AI and ML are key enabling technologies for cognitive analytics, hospitality and tourism management research did not explicitly link these terms to analytics and did not distinguish cognitive analytics from other forms of analytics that do not rely on ML. In fact, the term “cognitive analytics” is apparently missing in the hospitality and tourism management literature. Research limitations/implications This study generates a set of eight theoretical and three practical implications and advance theoretical and methodological recommendations for further research. Originality/value To the best of the authors’ knowledge, this is the first study that explicitly and critically examines the use of analytics in general, and cognitive analytics in particular, in the hospitality and tourism management literature.

Digitalisation is shaping the contemporary technological context of entrepreneurial activities, where firms grow through interacting with digital ecosystem stakeholders. This study investigates how incumbent firms seek entrepreneurial growth by re-configurating their knowledge bases in digital business ecosystems. We propose and develop a conceptual framework that blends the digital business ecosystem perspective and the knowledge-based view of the firm. Through a longitudinal case study of a Chinese textile manufacturing firm, we identify three pathways for entrepreneurial growth. The results contribute to the entrepreneurship literature by demonstrating how digital technologies foster corporate entrepreneurship in incumbent firms. The proposed framework extends the analytical power of the knowledge-based view by incorporating ecosystem elements into the firm’s internal and external knowledge management. The findings also generate relevant and actionable managerial implications for entrepreneurs, managers, and policymakers that are applicable in the context of digital business ecosystems.

In this study, we propose to model how intellectual capital (IC) attributes affect the performance of organizations operating in the performing arts sector, more specifically opera companies. In particular, the aim of this paper is twofold in that it seeks: (1) to analyze the role IC plays in performing arts organizations; and (2) to propose research hypotheses that suggest how IC affects the performance of these organizations. An in-depth qualitative approach was adopted. The research methodology deployed consists of a longitudinal case study of a major Italian opera house. The main findings of this study are two: (1) the identification of six attributes of IC that are deeply grounded in management theories and that make the definition of the IC construct more theoretically robust with respect to other studies that are less evidence-based; (2) the development of a model that shows how IC attributes affect the three different performance dimensions of performing arts organizations.

Purpose This paper aims to investigate antecedents of using non-travel-specific social media (specifically Facebook) for travel decision-making before a leisure trip. Design/methodology/approach Based on an online survey of 426 young travel consumers from Italy and Sweden, this work applies structural equation modeling and multi-group analysis. Findings The study finds support for most of the conventional TAM-related constructs: perceived usefulness, perceived enjoyment and intention, while ease of use is not found relevant in this context. Research limitations/implications Results shed light on the antecedents of using non-travel specific social media in two countries. Future research might focus on validating the factors identified and add others that might shape usage in the selected countries. Future studies could further investigate possible differences arising from culture, country of origin and age. The analysis can also be extended to other countries. Practical implications The analysis might help managers in the hospitality and tourism sector by providing an understanding of the cognitive factors which determine travelers’ decision to use Facebook for trip planning. Thus, managers should get to know these factors in their effort to influence social media in hospitality and tourism settings. Originality/value The findings offer interesting perspectives on the applicability of conventional models to the context of non-travel-specific social media platforms. The exploration of cross-cultural differences also adds to the extant body of knowledge.