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This paper offers a bibliometric analysis of the scientific literature on social finance. It provides an overview of the research field by identifying gaps in the existing academic literature and presenting future research directions.

The study uses co-word analysis and visualization mapping techniques.

This study's findings show that the social finance research field comprises five main research clusters and four main research hotspots—impact investing, social entrepreneurship, social impact bonds, and social innovation—which represent the core of this research domain. The authors also identify the researchers and the research institutions that have contributed to the development of social finance. In addition, emerging research areas are mapped and discussed.

Compared with most previous literature reviews, this work provides a more complete and objective analysis of the entire social finance landscape by revealing the trends and evolving dynamics that characterize its development. To this end, clear terminological boundaries have not yet been established in social finance. The field appears immature because only a few researchers have contributed to it, and papers have yet to be published by top finance journals. Finally, the findings of this research provide directions for future studies.

This study aims to conduct a bibliometric analysis on “intertemporal choice” behavior of individuals from journals in the Scopus database between 1957 and 2023. The research covered the data on the said topic since it first originated in the Scopus database and carried out performance analysis and content analysis of papers in the business management and finance disciplines.

Bibliometric analysis, including science mapping and performance analysis, followed by content analysis of the papers of identified clusters, was conducted. Three clusters based on cocitation analysis and six themes (three major and three minor) were identified using the bibliometrix package in R studio. The content analysis of the papers in these clusters and themes have been discussed in this study, along with the thematic evolution of intertemporal choice research over the period of time, paving a way for future research studies.

The review unpacks publication and citation trends of intertemporal choice behavior, the most significant authors, journals and papers along with the major clusters and themes of research based on cocitation and degree of centrality and relevance, respectively, i.e. discounting experiments and intertemporal choice, impulsivity, risk preference, time-inconsistent preference, etc.

Over the past years, the research on “intertemporal choice” has flourished because of the increasing interest of researchers and scholars from different fields and the dynamic and pervasive nature of this topic. The well-developed and scattered body of knowledge on intertemporal choice has led to the need of applying a bibliometric analysis in the intertemporal choice literature.

Drawing from the Personal Construct Theory, this study aims to analyze the impact of using gamified apps on user behavior by investigating the service-related images and individual preferences of Generation Z (GenZ) consumers, as these emerge from gamified applications in a tourism context.

The repertory grid analysis (RGA) elicited the top elements that reflect GenZer perceptions in tourism from empirical studies in the UK and Greece. Generalized procrustes analysis was used to investigate the structure of the data for the creation of representative consensus biplots of the most important conceptual constructs to advance consumer decision-making modeling via gamification.

As per different gamified app best-practices considered, the authors extract not only common perceptual elements (e.g. place informative aspects, exploration, lodgings, food/catering) but also different image components (e.g. virtual/interactive, business vs commercial traveling, entertainment, heritage/cultural informative aspects) from comparing UK with Greek GenZers’ responses. These extracted attributes are then presented in two dimensional charts, respectively, toward creating tourist perception scales.

Notwithstanding the wide availability of gamified apps, research on gamification design in tourism and hospitality is still in the early phase. This study demonstrates the need to identify and optimize the formation of different images among GenZers. It also highlights the advantageous nature of the proposed combination of procrustes analysis with the RGA.

To the best of the authors’ knowledge, this research is among the first empirical ones toward creating scales for measuring tourist perceptions of GenZers coming from different consumer markets. It responds to scholars’ recent calls for better informing gamification design and improving contemporary consumer experience.

This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology.

Data analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness.

This study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance.

This study does not use a primary database, but uses secondary data from official sources that can be accessed by the public.

The paper includes implications for the development of intelligent technology based on big data and also requires policy innovation.

Sustainable tourism development.

This study finds the expansion of new theory competitiveness of ecotourism destinations.

Hotel servicescapes have been extensively examined in the literature; however, there has been less attention on green servicescapes that attract consumers to visit green hotels. This model explores the relationship among green servicescapes – green items, green surfaces, natural environment, green consumerism and their outcomes, including intentions to return and green evangelism with a moderating role of green perceived quality.

The multi-wave method was utilized to gather data from China's major cities, Beijing and Shanghai. A total of 462 responses were received over three waves. Subsequently, the data were analyzed employing structural equation modeling (SEM) in Smart PLS 4.

The findings indicated that green servicescape – green items, green surfaces and natural environment – have a positive impact on green consumerism. The authors have discovered that green consumerism leads to positive intentions among consumers to return and engage in green evangelism. Green perceived quality significantly moderated the relationship between green servicescape and green consumerism.

The study offers insightful contributions to academia and managerial fields, encompassing consumer psychology, consumer behaviour, the stimulus-organism-response (SOR) framework and servicescapes. Additionally, it assists hotel managers in addressing challenges stemming from the competitive environment and creating a more environmentally friendly atmosphere.

The research focused on the innovative reflective model of green consumerism model and adopted a pioneering approach to examine green servicescapes within the hotel industry. This study enhances understanding of consumer intentions to return and the influence of green consumerism on green evangelism, while also quantifying the significance of green perceived quality.

Despite enormous literature on Human Resource Management (HRM) practices in the context of Mergers and Acquisitions (M&As), researchers have not come up with a synthesis that integrates the role and importance of HRM practices during M&As. This study aims to identify, analyse and synthesise existing literature to discover associated HRM practices that facilitate organisational change during M&As.

Bibliometric analysis is performed using 473 research articles entailing 871 authors from 62 countries (published in Scopus and WoS listed journals), followed by a thematic cluster analysis using bibliographic coupling. The analysis is performed using different means as citation analysis, cluster analysis and keyword analysis to reveal the most significant publications, authors, keywords, trends and future research questions.

The results are primarily descriptive and aim at capturing a panoramic view of what was already written on the topic so far. The bibliometric analysis is conducted using different means like citation analysis, cluster analysis and keyword analysis to reveal the most significant publications, notable authors, keywords, current research trends and future research questions. Further, the bibliographic coupling analysis led to the identification of the following six clusters: (1) coping strategies during and post-M&As; (2) changes in individual and organisational identification during and post-M&As; (3) role of cultural and transformational leadership in M&As success; (4) HRM practices to develop employee capabilities post-M&As; (5) case studies and success stories of M&As; and (6) organisational readiness for M&As.

This study has theoretical and practical implications and suggests future research directions. The authors also propose an abstruse model for HRM practices during M&A process for further investigation.

This is the first bibliometric study to explore the vast extant literature in M&A research related to the role of HRM practices in the execution of successful M&As.

Bales of cotton run through the gins and textile mill instruments, stick to them and make it cumbersome for the ginning mill workers. This is so because more time and money have to be invested in cleaning these instruments. The stickiness of cotton causes health hazards to the workers, decreases the yarn quality and economic loss to the textile industry. The effect of cotton stickiness on textile ginning, various methods for cotton stickiness detection and the steps for reduction are discussed.

The different methods that are available for detecting and measuring cotton stickiness are described. The sugars that cause stickiness are either of plant origin (physiological sugars) or from the feeding insects (entomological origin). The methods for stickiness detection and reduction are discussed under physical, chemical and biological categories.

This review suggests possible ways to mitigate cotton stickiness.

One of the major issues of the textile industry is honeydew-contaminated cotton stickiness. However, there are few papers on detection methods for analyzing honeydew cotton stickiness along with the approaches to reduce stickiness. This paper summarizes different methods along with a study for detection as well as reduction of cotton stickiness.

Impact investors differ from venture capital firms as they invest to create social and commercial value. This paper pursues the question: how do impact investors select social enterprises? The aim of this study is to understand the selection and investing process of impact investors.

This study developed a database of 115 impact-investing firms across different geographies. Emails were sent to investors associated with each of the impact-investing firms found in the database, out of which 32 replied with consent for a telephonic or in-person interview.

The significant findings presented in the paper are the following. First, this study shows the impact-investing selection process model. The four major steps in the selection process are context, investment focus, venture analysis and decision. In each step, social values and missions become the defining characteristics of the selection process. Second, the findings also discuss the typologies of impact investors as a function of their selection approaches.

This paper discusses the impact investing strategy among social enterprises. It provides a framework for impact investing among investee social enterprises. As an impact investing professional, one learns investment strategy through this paper.

Impact investing is a growing field. It is believed that impact investing could greatly impact sustainable development goals, climate change goals and help in inclusive development. This study helps to further understand impact investing process and hopes to help social enterprises and impact investors make a better match, thereby, creating a greater overall social and environmental impact.

This study helps both practitioners and academics to understand the complexity of impact investing. This study helps develop heuristics that impact investors may use to make investments. This study provides a framework for investing, which the impact investing firms may use to invest.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

We aimed to analyze the impact of the transition to the hybrid model of teamwork and team dynamics from the perspective of the five key challenges, i.e. communication, coordination, connection, creativity and culture.

To achieve the stated aim, we conducted a literature review and then an exploratory qualitative study. We split the research into phases: December 2021 to January 2022 and July to August 2022. In the first phase, we conducted computer-assisted online interviews (CAWIs) with all members of the remote team and an in-depth interview with the manager. After the transition from remote to hybrid work in February 2022, we returned to the team to conduct in-depth interviews with team leaders and the manager.

We identified key findings, i.e. managerial implications of differences across the 5 Cs (communication, coordination, connection, creativity and culture) noted in the functioning of the analyzed team as the team shifted from fully remote work to the hybrid work model.

We concluded that if people do not spend time together and are not impregnated with the unique culture and values of a given organization, they will not feel a connection to its distinctive ethos and may choose to leave. In the longer-term, the last challenge may be the biggest single opportunity for employees post-pandemic and concurrently the single biggest challenge that organizational leadership will need to address, given that sustainable market success depends on talent.

The results showed that team communication, teamwork coordination, social and emotional connections among team members, nurturing of creativity, as well as of the organizational culture were of high importance to the team in the hybrid work model. Thus, we confirmed the findings of other authors. The study contributes to our understanding of the impact of the hybrid work model on teamwork and team dynamics and provides some guidance on how organizations can mitigate these, in particular through the team manager.