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Artificial intelligence and augmented reality are two key tools gaining importance in the digital era due to their wide range of applications in different fields and sectors. Industry 4.0 lays emphasis principally on the technology used to help the business remain competitive and sustainable. Sustainable development goals are another important objective of the UN which has laid responsibility for every business to support addressing the global challenges. Purpose: This chapter essentially aims to present the standpoint of artificial intelligence and augmented reality in meeting the sustainability perspective of organizations. Information about the study is gathered through secondary approaches, critically reviewing published literature, scientific reports, and statistical data accessible through business reports, and corporate websites. Further analyzed to present the perspectives of the authors in the study. Globally artificial intelligence market size is predicted to reach $190 billion by 2025, while the funding for startups doubled during the period 2011–2020 globally. The investment in artificial intelligence is going to reach $500 by 2024 resulting in substantial revenue returns. The augmented reality market size could reach $97 billion by 2028. Artificial intelligence today is increasingly used in many fields and is attracting multiple applications in many sectors such as manufacturing, retail, education, IT, and health care and has also contributed to sustainable development the same time by providing energy conservation options, optimization, and reduction of resources, minimizing wastage, offering timely assistance on maintenance schedules, practices which are enabling organizations to reach closer to sustainability and transformation.

The study aims to embrace the lingering call for more empirical studies that can theorize the role of digital platforms in digital entrepreneurship. Hence, this study seeks to reveal the liminal space entrepreneurial experience of third-party application developers, by investigating how the platform boundary resources promote third-party entrepreneurial actions, as they transition through the disoriented, uncertain and ambiguous processes of digital entrepreneurship development.

To conduct this investigation, an expert interview qualitative method was used. This approach is a well-established technique in the field of social sciences, which allowed a detailed exploration of the theory of liminality. Liminality refers to the transitional phase that individuals or groups experience when moving from one social or cultural context to another. The expert interview method is appropriate for this study because it involves engaging with knowledgeable individuals who have extensive experience and expertise in the subject area being investigated. Through in-depth and unstructured interviews, the experts were able to provide valuable insights and perspectives about the phenomenon investigated.

The research findings demonstrate that digital platform boundary resources play a significant role in the behaviour of third-party developers’ who engage in the development of digital entrepreneurship in today’s market. The study highlights three ways that show how these resources (software development kit (SDK), API, integrated development environment (IDE), libraries, frameworks) enable third-party developers to create new applications that are used to pursue entrepreneurship in a digital platform, leading to increased user engagement and revenue generation.

The research addresses the critical roles of digital platform boundary resources in digital entrepreneurship development processes. Also, using liminality theory, the research explicated the core experiences of third-party developers as they navigated the challenges and ambiguities experienced in the pursuit of entrepreneurship. Thus, contributing to the existing body of knowledge in literature and practice.

Despite the rapid advancement of blockchain technology across various sectors, scholarly research on its application within family businesses remains significantly underdeveloped. This study aims to address this gap by examining the application of blockchain technology within family businesses to identify key application domains, benefits and implementation challenges.

The study employs a conceptual approach, drawing on existing literature on family businesses and blockchain technology. This review aimed to identify the unique characteristics of family businesses, their challenges and the distinctive features of blockchain technology that can potentially be mapped to each other. Based on the literature review, we develop a conceptual framework exploring blockchain technology applications in family businesses. Real-world case studies of family businesses that have implemented blockchain technology were identified to provide practical insights and implementation challenges.

Blockchain technology possesses transformative potential for family businesses across several critical domains. It includes enhancing trust and transparency in operations, improving governance and decision-making and facilitating succession planning and intergenerational wealth management. Case study evidence illustrates the tangible benefits of blockchain, including enhanced supply chain transparency, optimized business processes, increased customer trust and resultant business sustainability. Blockchain technology implementation challenges include data privacy concerns, integration with legacy systems, regulatory uncertainty and change management issues.

This study is limited by its reliance on existing literature and case studies. It may not capture the full spectrum of challenges and opportunities associated with blockchain applications in family businesses. Future research should focus on longitudinal and empirical research to provide a deeper understanding of the impact of blockchain technology application in family businesses.

This study contributes to the literature by exploring the intersection of family businesses and blockchain technology, an area that has received limited academic attention. It identifies potential application domains of blockchain technology in family businesses and develops a conceptual framework based on existing literature. Through case studies, the research provides practical insights and valuable lessons for family businesses considering blockchain implementation. It also addresses key considerations and challenges, providing a clear roadmap for blockchain technology integration in family businesses. The study lays the groundwork for further research and exploration in blockchain technology and family businesses.

The article aims to provide a bibliometric and content analysis of the business application of blockchain technology.

Bibliometric analysis and content analysis were undertaken to accomplish the stated objectives of the study.

The results revealed publication and country collaboration trends, declining, emerging, and niche research areas, the topmost influential articles, authors, and most relevant journals.

As researchers have been myopic towards some mainstream research agendas studying the specific contexts of blockchain applications, this research believes a holistic approach to understanding blockchain technology's versatility to disrupt different business processes across a myriad of industries is lacking. In addition, to strengthen the research's conclusions, a content analysis of the most significant articles is conducted as part of the study.

This paper aims to examine the research conducted between 1938 and 2023 on applying Gestalt principles in management research, focusing on publishing and citation trends in this field.

A systematic literature review was conducted using PRISMA criteria, forming a three-phase strategy. A total of 394 articles from the Scopus database were reviewed. Bibliometric analysis involving co-citation and co-word analysis was used to explore the intellectual structure of the research area.

Eight application clusters were identified through co-citation analysis using Gestalt as a keyword. Co-word analysis revealed key themes and keywords over the period. Substantial literature exists on topics like organization, strategy, physical servicescape, coaching, learning and human resource management. However, Gestalt principles are minimally applied to online retail, social media, website design, mobile app design and emerging areas like Industry 4.0.

The study suggests that Gestalt principles can enhance marketing, communication, decision-making and leadership, according to the study. Understanding Gestalt concepts and how different industries adapt and apply them helps enable cross-industry learning, where successful strategies from one sector can be creatively implemented in others to solve problems.

This study fills a significant gap in the literature by highlighting the underexplored application of Gestalt principles in emerging business and management sectors. It provides a comprehensive discussion on future research directions and identifies specific areas where Gestalt principles can be innovatively applied, offering fresh insights and expanding the theoretical and practical understanding of their utility in modern business contexts.

This paper systematically reviews the evolution of Internet of Things (IoT) research in business and management over the past decade and a half. It synthesizes current knowledge, identifies major themes, gaps, and future opportunities to guide scholars on potential research directions within this exponentially growing domain.

A structured systematic literature review methodology filtered IoT publications across business/management journals using Scopus database. Detailed thematic and bibliometric analyses chronologically mapped the progress of peer-reviewed articles from 2005–2023. Both quantitative metrics and qualitative coding inductively revealed historical trends, topics, applications and research implications.

Analysis uncovered six primary IoT research themes - business models, technology, data, customers, organizations, and sustainability. Dominant focuses were found on technological enablers, business model innovation and customer experience transformations. While technical aspects are well-documented, strategic technology integrations and organizational change management require greater emphasis.

Focus restricted to academic articles published in management journals risks missing relevant papers published in other fields. Screening process involved some subjectivity. Lacks geographic analysis of research contexts. The rapidly evolving nature of technology domain risks findings’ generalizability.

Key enablers and success factors that we identified may support managerial decision making when it comes to IoT adoption.

We discuss advancing IoT innovation through ethics and sustainability lenses and these may help ensure responsible adoption.

This analysis weaves together the extant literature and offers an evidence-based research agenda for management scholars by chronicling the state, evolution, influential factors, and future opportunities within IoT literature. It highlights major thematic shifts and priority gaps to address.

This study aims to empirically investigate the relationship between artificial intelligence (AI) in marketing (AIM) and business performance from the resource-based view (RBV) perspective.

A survey strategy was used in this study to collect data from 225 small and medium enterprises (SMEs) respondents who were on the registered list of the Ghana Enterprise Agency in the Eastern Region of Ghana. Structural equation modeling – path analysis was used to estimate the impact of AIM on the performance of SMEs.

The analyzed data shows that AIM has significant impact on the financial performance, customer performance, internal business process performance and learning and growth performance in the case of SMEs in Ghana. This study establishes the significance of AIM approach in achieving financial performance, customer performance, internal business process performance and learning and growth performance through the application of AIM determinants including, Internet of Things (IoT), collaborative decision-making systems (CDMS), virtual and augmented reality (VAR) and personalization.

Aside the aforementioned significance of this research study, this study has limitations. The sample size of this research study can be expanded to include SME respondents in other geographical areas that were not considered in this study. Future research studies should concentrate on how AIM can analyze customer communications and information such as posts on social media to develop future communications that may enhance customer engagement.

The practical implications comprise of two key items. First, this research study encourages SME owners and managers to develop an AIM method as a fundamental strategic goal in their pursuit to improve SME performance. Second, SME owners and managers should increasingly implement the four determinants of AIM indicated in this research study (i.e., IOT, CDMS, VAR and personalization) to develop essential resources for effective application of AIM to improve their performance.

The results of this study provide a strong support to RBV theory and the proposition that AIM and its determinants (i.e., IOT, CDMS, VAR and personalization) should be recognized as an essential strategic resource for improving the performance (i.e., financial performance, customer performance, internal business process performance and learning and growth performance) of SMEs. This study also contributes to the current body of knowledge on AIM and management, particularly in the context of an emerging economy.

The current study gives a quantitative analysis DT literature over the past ten years in domain of management and business where the field has witnessed a proliferation in studies. The study's primary areas of concentration were analyzing historical trends and identifying prospective future research opportunities in the field. Due of the way, it approaches innovation and problem-solving, design thinking has garnered a lot of interest from both academics and practitioners. Promoters and detractors, however, tend to have quite different perspectives on the program's core qualities, practicality and results.

The study adopts a bibliometric approach to a systematic literature review, where the analyses and visualizations are carried out using R Studio (Biblioshiny package) and VosViewer software. The study was conducted on 518 documents extracted from the Scopus database. To identify past research trends in the field, performance analysis based on productivity and/or impact of the research constituents was carried out to understand the intellectual structure of the field.

The study's findings indicated that few areas have received the most attention, which are presented as seven themes. While the emerging themes in the field include areas such as service design, service innovation, customer experience, innovation management, project management and 21st-century skills.

The studies are going deeper by breaking down concepts or processes and analyzing one aspect at a time, codesign and prototyping are such subareas within the realm of service or new product design and development.

This study is the first of its kind where a literature review has been conducted covering design thinking in the area of business management and accounting.

Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research.

The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification.

The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network.

The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area.

Augmented reality (AR) is revolutionizing the tourism and hospitality industry by offering immersive experiences as well as creating more engaging, informative and accessible travel experiences that attract tourists from around the globe. From virtual tours and immersive historical site recreations to navigation assistance and cultural education, AR technology is transforming the way we explore and interact with the destinations. This study aims to identify benefits, risks, tools and techniques of AR in the tourism and hospitality literature.

The authors conducted a systematic literature review to answer six research questions. The authors also identified 33 primary studies, dated from January 2010 to February 2024 and coded them via a thematic analysis. Related studies were obtained through searching in Web of Science and Scopus.

The results identified nine themes for benefits, eight themes for risks/disadvantages and four tools and applications-related themes. Through the thematic analysis, the major benefits of AR in the tourism and hospitality were found to be differentiated travel experiences, improved performance of tourism value chain, more effective marketing efforts of tourism businesses, enhanced tourists’ engagement, enhanced performance of tourism destinations, stimulated behavioral intentions, tourist empowerment and providing more value, interactivity and integrity. Furthermore, eight risks were identified: physical, privacy and security, social, service failure, technical, psychological, managerial, information and knowledge gaps. The authors also recognized four tools and applications-related themes, namely, AR-enabled tools, AR applications, AR-enabled apps and AR-based techniques.

To the best of the authors’ knowledge, this review provides the first systematic exploration of the existing literature on usage of AR in the context of tourism and hospitality value chain.