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This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

The advancement of technologies has made it possible for health-care organizations to provide convenient online services that enable people to manage their health conditions. Although many studies have investigated the adoption and benefits of e-health services, there has been little focus on health-oriented behaviors after adoption, particularly in relation to service quality and user satisfaction.

This paper is based on the SOR model and service quality theories to investigate behavioral responses, including word-of-mouth, intention to use and intention to act. The authors use a partial least squares structural equation modeling analysis with 194 participants and the diabetes risk test survey in Finland.

The results show that people are willing to engage in health self-management behaviors if they intend to use the e-health service and are satisfied with it. User satisfaction can be enhanced by improving the visual appeal of the website presentation, the quality of the presented information, as well as the usability of the website, all as components of e-health services.

The authors contribute by creating a construct “intention to act,” referring to health-oriented behaviors resulting from e-health service use. In addition, this study is among the first to apply the SOR model to investigate how user satisfaction leads to intention to use, intention to act and word-of-mouth.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.

This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.

The study aims to determine the role of online retail website experience on brand happiness and willingness to share personal information using the theoretical lens of the Stimulus-Organism-Response (SOR) framework. Further, it explores the role of brand intimacy and brand partner quality in mediating the path between brand happiness and willingness to share personal information.

This study used a cross-sectional survey design to collect data from 439 online retail consumers in India, using an online questionnaire. The data were analysed using Structural Equation Modelling in IBM Amos.

The present study found that online retail website experience is significantly related to brand happiness. The finding also supports that brand happiness was positively and significantly related to ‘consumers' willingness to share personal information. This relationship was fully mediated by brand intimacy. Brand happiness also mediated the relationship between website experience and the willingness to share personal information.

This study contributes to the emerging literature on brand happiness and willingness to share personal information. It establishes a central role of brand happiness as a driver and a mediator of consumers' willingness to share personal information with e-commerce retailers, extending the stimulus-organism-response framework in the context of brand happiness and willingness to share personal information. Further, the study establishes the role of website experience as a marketer (and brand) led driver of brand happiness.

The results have implications for the role of the website in enhancing the consumer experience, which in turn is a driver of brand happiness. Further, managers need to promote brand happiness with the help of website experience to enable consumers’ willingness to share personal information and help organizations customize their marketing campaigns.

This is among the first studies to evaluate brand happiness from the perspective of an online retail website experience and consider consumers’ willingness to share personal information from a branding rather than a technological perspective. Additionally, the study introduces the SOR framework in the context of brand happiness, with website experience acting as a stimulus for consumers, resulting in brand happiness, which is mediated by brand partner quality and brand intimacy (organism), leads to consumers' willingness to share personal information with online retail brands (response).

This study aims to reveal how mobile app stickiness is formed and how the stickiness formation process differs for apps of different social levels.

This study proposed and validated a stickiness formation model following the cognitive–affective–conative framework. Data were collected from surveys of 1,240 mobile app users and analyzed using structural equation modeling. Multigroup analysis was applied to contrast the stickiness formation process among apps of different social levels.

This study revealed a causal link between cognitive, affective and conative factors. It found partial mediation effects of trust in the association between perceptions and satisfaction, and the full mediation role of satisfaction and personal investment (PI) in the effects of subjective norm (SN) on stickiness. The multigroup analysis results suggested that social media affordances benefit stickiness through increased PI and strengthened effects of SN on PI. However, it damages stickiness through increased perceived privacy risk (PPR), decreased trust and strengthened effects of PPR on trust.

This study contributes to both stickiness scholars and practitioners, as it builds a model to understand the stickiness formation process and reveals the effects of the “go social” strategy. The novelty of this study is that it examined social influences, considered privacy issues and revealed two mediation mechanisms. The findings can guide the improvement of mobile app stickiness and the application of the “go social” strategy.

The research study provides empirical insights on the relationship between entrepreneurial leadership (EL), entrepreneurial passion for founding (EPF), entrepreneurial bricolage (EB) and project success (PS), in the case of freelancers. The study aims to get a better understanding of whether freelancers, who behave like entrepreneurial leaders, can successfully complete projects through EB.

The study collected data from 209 freelancers through snowball sampling, in two waves, with a time-lag of fourteen days, to better examine the causality of variables. Data were analyzed by Model No. 4 and 7 (i.e. mediation and moderation, respectively) of Process macro.

Drawing on the effectuation theory, the results show that EB mediates the relationship between EL and PS and EPF moderates this relationship.

The freelancers can formally establish businesses later, after knowing whether they can complete these new types of projects. These online freelancing platforms can provide special services to freelancers who first want to test their skills on unrelated projects. In sum, the paper suggests that freelancers can be successful entrepreneurial leaders.

The EL, EPF, EB and PS are studied in the context of the informal sector, i.e. freelancing, which is the emerging working style in the world. It provides an in-depth understanding of phenomena in freelancers that lacks background literature.

This research sought to examine the differential effect of chatbot banking artificial intelligence (AI) on consumer experience in the banking industry. A positivist paradigm was adopted to sample 389 consumers who were previously exposed to chatbot banking in Zimbabwe. A causal research design was employed whilst a quantitative approach was followed. In analysing data, the research study applied the structural equation modelling (SEM) technique. The authors found that chatbot banking significantly improves customer experience (CX) in the banking industry. Reliability and responsiveness of the chatbot need to be enhanced for effective improvements in CX. A need was also identified to enhance CX through the development of an ease-to-use chatbot which is embedded in everyday messaging applications of consumers. A significant association was also found between perceived benefits of chatbot banking and CX. This study informs the development of competitive advantage by banks and other related companies through AI-based CX management strategies. In times of pandemics and beyond, chatbot banking can be very instrumental in improving CX.

This chapter aims to discuss the challenges facing these countries building productive capacity for development. This chapter makes use of data published by international organizations as indicators for measuring the state of development in the Arab region. Several indicators are presented to compare Arab countries with other world regions. The use of data identifies some of the gaps that countries in the Arab region need to close to strengthen capacity building for development and fostering economic growth. The findings from the data presented reveal that the productive structure in most Arab countries remains weak to generate production linkages and provide incentives for investment in nonenergy sectors. The failure of the export-led growth model to diversify output and promote development in energy producing countries has increased the dependence of these countries on global trade. Fluctuations in commodity prices and uncertainty about global demand for energy have influenced the ability of the state to construct strategies for rapid transformation. Except for the energy sector, the productivity of nonoil sectors remains low reflecting inadequate incentives and ineffective entrepreneurial capabilities. The study examines the challenges for building productive capacity in the Arab world. It illustrates the failure of the led-export model and its inability to prompted economic diversification, especially in the Gulf countries. The study contributes to the literature on capacity building in the Arab world so that to encourage researchers and students of development conducting studies concerning the main development challenges facing these countries.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.