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Several review articles have been published within the Artificial Intelligence (AI) literature that have explored a range of applications within the tourism and hospitality sectors. However, how efficiently the applied AI methods and algorithms have performed with respect to the type of applications and the multimodal sets of data domains have not yet been reviewed. Therefore, this paper aims to review and analyse the established AI methods in hospitality/tourism, ranging from data modelling for demand forecasting, tourism destination and behaviour pattern to enhanced customer service and experience.

The approach was to systematically review the relationship between AI methods and hospitality/tourism through a comprehensive literature review of papers published between 2010 and 2021. In total, 146 articles were identified and then critically analysed through content analysis into themes, including “AI methods” and “AI applications”.

The review discovered new knowledge in identifying AI methods concerning the settings and available multimodal data sets in hospitality and tourism. Moreover, AI applications fostering the tourism/hospitality industries were identified. It also proposes novel personalised AI modelling development for smart tourism platforms to precisely predict tourism choice behaviour patterns.

This review paper offers researchers and practitioners a broad understanding of the proper selection of AI methods that can potentially improve decision-making and decision-support in the tourism/hospitality industries.

This paper contributes to the tourism/hospitality literature with an interdisciplinary approach that reflects on theoretical/practical developments for data collection, data analysis and data modelling using AI-driven technology.

This paper aims to present concepts and tools for developing place branding that protects places from overbranding, redundant promotion and excessive tourism.

The concept of a product-based place brand that reflects local ways of life and local identities was introduced. A combination of projective, typological and narrative methods was applied. Three focus groups composed of future place managers were held in three countries (N = 27) to develop place brand vocabularies and typologies of verbal characteristics of abstract places as products for internal users (residents).

In most cases, the place brand vocabularies were consistent and compatible within each abstract type and were unique (mutually exclusive) between the types. The vocabularies contained both detailed and more generalized elements. For each place, short formulations of the general concept were found. Each brand vocabulary reflected the institutional, socio-psychological, cultural, historical and geographic differences of the countries involved in the research.

A conceptual and methodological framework for creating place brand vocabularies is offered, and it describes the close relationship between multiple internal brand attributes and their concise expressions appropriate for communication and high differentiation among brand attributes that facilitate the recognition of branded places by target and non-target audiences. The framework is applicable for designing verbal attributes of place brands for specific places to avoid overbranding effects.

In recent years, scholars have devoted increasing attention to the use of methods in new product development. Although their positive impact on product success has been confirmed by a series of studies, little research has so far been conducted into the determinants of the successful method application. The purpose of this paper is to analyze two key determinants for the successful use of methods.

The paper adopts a structural equation modeling approach and analyzes the subject based on a large empirical sample of 410 product development projects.

The way the new product development process is formalized and the extent of top management support have a significant influence on the successful application of methods. Both factors lead to the use of more methods overall and drive the more thorough and intensive deployment of the specific methods used.

The paper shows how firms that are seeking a more methodical approach to new product development can consciously create the right determinants for the successful adoption of methods and by doing that can increase the success rate of their new product development activities.

This research adds to the literature on success factors of new product development in two distinct ways. First, the paper investigates the subject at the level of specific product development projects, based on a large empirical sample and using a structural equation modeling approach, for the first time. Second, the methods investigated were chosen in a systematic, multi step process in which the methods used by several functions involved in new product development were taken into account.

Introduction: Healthcare facilities have witnessed deterioration, limited employee engagement, and communication gaps due to a lack of wireless technology. The Internet makes work and life quicker and more intelligent. The Internet of Things (IoT) is a scheme of interconnection equipped with unique identifiers in recent years. Artificial intelligence (AI) and IoT advancement allow employees to develop competent and predictive services and solutions in human resource (HR) practices. This chapter has been formulated to summarise and classify the existing research and better understand the past, present, and future of employee engagement by improving IoT interrelated devices in the healthcare industry.

Purpose: This study aims to categorise and overcome the challenges involved in HR practices. Effectively embracing IoT application-connected devices in the healthcare industry can enhance human resources management’s (HRM) role and measure performance assessment to improve employee engagement and productivity.

Methodology: In this study, the authors develop propositions dependent on a theory-based review. A systematic analysis was applied to minimise the challenges of HRM. The subject-related articles from different journal sources, like Scopus, Emerald, Web of Science, Springer, etc., were analysed based on engagement criteria. It was graphically recorded in a collective and informative way to emphasise the review outcomes. The study has presented the positive impacts of AI and IoT on engagement in health care.

Summary: This chapter accumulated theory-based knowledge about healthcare employee engagement and how IoT-based technology like AI can optimise employees’ engagement effectively. Further, it draws comparative benefits for a workforce to execute performance advancements and create future progressive aspects for healthcare employees.

This paper aims to explore the development of sustainability accounting information systems through lens of contingency theory. In this digital age when companies are confronted with massive sets of data, integration of financial and non-financial data, little empirical evidence exists on how sustainability issues are integrated or linked within internal corporate information systems.

A questionnaire-based survey, hypothesis testing, principal component methods and hierarchical clustering are used to provide original empirical evidence from major Lithuanian companies.

The main findings reveal that most companies surveyed include a sustainability strategy in their core strategy, but there is a lack of linkage with measuring and integrating sustainability outcomes within the entirety of corporate financial results. Unexpectedly, the association between stakeholders' involvement and sustainability accounting information system design was not as strong as hypothesized theoretically. Therefore, it deserves further investigation, constituting an important implication for future research. Specifically, three profiles of sustainability accounting information systems were explained, namely, integrated, fragmented and compliance systems.

The limitations of this study relate to the small sample size, as sustainability-related information is still regarded quite confidential.

This result could serve as a specific reference for companies to apply integrated sustainability accounting information systems that might serve as a good practice model for companies, however, fragmented and compliance profiles are the prevailing ones.

The findings are important for fostering corporate social responsibility by developing sustainability accounting information systems.

This paper contributes to the sustainability accounting and information systems literature by providing empirical evidence linking contingent factors with the development of sustainability accounting information systems.

Expert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.

The authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.

The authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.

Fuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

Data mining has been a popular research area in the past decades. Many researchers study data-mining theories, methods, applications and trends; however, there are very few studies on data-mining-related topics in social media. This paper aims to explore the topics related to data mining based on the data collected from Wikipedia.

In total, 402 data-mining-related articles were obtained from Wikipedia. These articles were manually classified into several categories by the coding method. Each category formed an article-term matrix. These matrices were analysed and visualized by the self-organizing map approach. Several clusters were observed in each category. Finally, the topics of these clusters were extracted by content analysis.

The articles obtained were classified into six categories: applications, foundation and concepts, methodologies, organizations, related fields and topics and technology support. Business, biology and security were the three prominent topics of the applications category. The technologies supporting data mining were software, systems, databases, programming languages and so forth. The general public was more interested in data-mining organizations than the researchers. They also focused on the applications of data mining in business more than in other fields.

This study will help researchers gain insight into the general public’s perceptions of data mining and discover the gap between the general public and themselves. It will assist researchers in finding new techniques and methods which will potentially provide them with new data-mining methods and research topics.

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.