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The purpose of this paper is to conceptualize the influencing characteristics of user-generated content over perceived structure of social platforms to plan various business practices to improve the social commerce activities especially in emerging markets.

In first step, key factors are identified from the systematic literature studies and experts’ opinion. Second, total interpretive structural modeling is used to interpret the complexity of relationships among various factors. Further, fuzzy-MICMAC analysis is used to determine the most driving factors to improve the social commerce.

The study illustrates hierarchical relationships that can help policy designers, business leaders and decision makers to gain maximum benefits of mining the user-generated content to implement the people-oriented changes to improve economic capability of a country.

The applicability of the study findings can be deployed mostly in emerging economies. The study has not considered the data security, cyberbullying, authenticity and reliability of shared content spread virally over social sites.

The paper will assist policy makers, business planners and solution providers to give importance to public-led influencing patterns to offer business solutions based on people demand and choices.

The customers’ engagement, sharing reviews, getting suggestions from other people and finding new trends through user-generated content would enable higher social commerce activities.

The paper develops hierarchical relationships to represent the advancements in business and marketing activities based on influencing patterns and behavior of users over social sites.

This paper aims to identify the key factors to design efficient, healthy and potentially economical neighbourhood places in the surroundings of smart cities to reduce the urban polarization for the sustainable urban development.

A two-stage methodology is followed. First, the key factors for neighbourhood are identified from literature studies. The selected factors are validated by sample t-tests. Second, the total interpretive structural modeling is used to interpret the complexity of relationships among various factors. Further, cross-impact matrix multiplication is applied for classification analysis to find the most driving factors for neighbourhood design.

The contribution of this research is to show hierarchical relationships among the various factors to design the neighbourhood places as smart from the perspectives of city planners and decision makers.

The applicability of the research findings is limited to developing countries mainly where population is large and most of cities have high pressure on its infrastructure to fulfil the citizens’ demands.

This paper will aid policymakers, city planners and government officials to design a sustainable smart city model in which smart neighbourhood would also be the potential solution to decrease pressure on a city’s critical infrastructure especially in developing countries.

A smart city could be considered as the centre point of smart initiatives to develop a place smart, and it should continue beyond the city boundaries to enhance the facilities, services, resources utilization and working environment in neighbourhood places also.

The study explores the various literature on neighbourhood planning and then link with smart city development as current need of urban development scenario. The authors propose a hierarchical relation framework to develop the neighbourhood places as smart places to meet the future demand of urbanization in developing countries like India.

The purpose of this paper is to identify and build a hierarchy of the factors influencing competitiveness of electronics manufacturing industry (EMI) at the industry level and apply the interpretive structural modeling, fuzzy Matriced’ Impacts Croisés Multiplication Appliquée á UN Classement (i.e. the cross-impact matrix multiplication applied to classification; MICMAC) and analytic hierarchy process (AHP) approaches. These factors have been explained with respect to managerial and government policymakers’ standpoint in Indian context.

This study presents a hierarchy and weight-based model that demonstrates mutual relationships among the significant factors of competitiveness of the Indian EMI.

This study covers a wide variety of factors that form the bedrock of the competitiveness of the EMI. Interpretive structural modeling and fuzzy MICMAC are used to cluster the influential factors of competitiveness considering the driving and dependence power. AHP is used to rank the factors on the basis of weights. Results show that the “government role” and “foreign exchange market” have a significantly high driving power. On the other hand, the “capital resource availability” and “productivity measures” come at the top of the interpretive structural modeling hierarchy, implying high dependence power.

The study has strong practical implications for both the manufacturers and the policymakers. The manufacturers need to focus on the factors of competitiveness to improve performance, and at the same time, the government should come forward to build a suitable environment for business in light of the huge demand and frame suitable policies.

The lackluster performance of the industry is because of the existing electronics policies and environmental conditions. The proposed interpretive structural modeling and fuzzy MICMAC and AHP frameworks suggest a better understanding of the key factors and their mutual relationship to analyze competitiveness of the electronics manufacturing industry in view of the Indian Government’s “Make in India” initiatives.

This paper contributes to the industry level competitiveness and dynamics of multi-factors approach and utilize the ISM–fuzzy MICMAC and AHP management decision tool in the identification and ranking of factors that influence the competitiveness of the EMI in the country.

Artificial intelligence (AI) is increasingly applied by businesses to optimize their processes and decision-making, develop effective and efficient strategies, and positively influence customer behaviors. Businesses use AI to generate behaviors such as customer retention (CR). The existing literature on “AI and CR” is vastly scattered. The paper aims to review the present research on AI in CR systematically and suggest future research directions to further develop the field.

The Scopus database is used to collect the data for systematic review and bibliometric analysis using the VOSviewer tool. The paper performs the following analysis: (1) year-wise publications and citations, (2) co-authorship analysis of authors, countries, and affiliations, (3) citation analysis of articles and journals, (4) co-occurrence visualization of binding terms, and (5) bibliographic coupling of articles.

Five research themes are identified, namely, (1) AI and customer churn prediction in CR, (2) AI and customer service experience in CR, (3) AI and customer sentiment analysis in CR, (4) AI and customer (big data) analytics in CR, and (5) AI privacy and ethical concerns in CR. Based on the research themes, fifteen future research objectives and a future research framework are suggested.

The paper has important implications for researchers and managers as it reveals vital insights into the latest trends and paths in AI-CR research and practices. It focuses on privacy and ethical issues of AI; hence, it will help the government develop policies for sustainable AI adoption for CR.

To the author's best knowledge, this paper is the first attempt to comprehensively review the existing research on “AI and CR” using bibliometric analysis.

The goal of this research is to look at how urban microfinance affects livelihood transformation in terms of poverty reduction, living standards, social well-being, empowerment and entrepreneurship.

This paper analyses the role of urban microfinance towards livelihood with special reference to Western Uttar Pradesh. Primary data were collected from 321 respondents who are users of a microfinance programme using a standardised questionnaire. The data were collected using a stratified random sampling technique, and the data were analysed using structural equation modelling.

Urban microfinance has a considerable impact on poverty reduction, the standard of living, social well-being, empowerment and entrepreneurship in the urban poor, according to the findings.

The fact that the majority of the borrowers were uneducated was the most significant barrier to them filling out the questionnaire. Their anxiety was the most significant psychological obstacle to successfully answering the questions, and it took time. As a result, it is urged that proper counselling be conducted before the poor borrowers fill out the questionnaire.

The current study highlights the factors that lead to the utilisation of microfinance services. This research will aid MFIs in selecting the appropriate products and services for the urban poor. The results of this study will aid them in understanding and meeting the expectations of microfinance CEOs.

This is a first study conducted in Northern zone of India measuring the roles urban microfinance institutions (MFIs) in uplifting the livelihood of urban poor.

The purpose of the study is to explore the relationship among organisation information technology support (OITS), knowledge sharing behaviour (KSB) and service innovation performance (SIP) in the context of the Indian Hospitality Industry (IHI). This study also attempts to examine the role of KSB as a mediator in the relationship between IT support and SIP and the firm age test as a moderating variable for service innovation performance.

Proposed relations are empirically examined, and the study was carried out on 115 employees from 71 randomly selected hotels situated in the major five travel destinations of Uttarakhand state of India. Initially, confirmatory factor analysis was performed to validate the construct, afterword structural equation modeling (SEM)-Path analysis was accomplished. The researcher examines the mediation and moderation relations of the variables through statistical tests executed with the help of AMOS 24 and SPSS 26.

The study result indicated that organisation IT support has a positive influence on knowledge sharing and SIP. The mediation result findings showed KSB is partially mediated between OITS and SIP. Sequentially, firm age moderation found the statistical results shown significant difference in young and old hotels.

This study only covers the aspect of the “knowledge sharing behaviour” dimension among the major organizations’ IT support capabilities and examined both variables that might be anticipated in SIP. Considering this limitation, new areas of research investigation are open to future researchers.

The study has both theoretical and managerial implications for academicians, practitioners and researchers. An attempt to conceptualise detailed insights on organisational IT support adaptation and KSB enhancement, which further leads to lifting SIP. Moreover, the study recommended for professionals to implement KM practices and mobilise the knowledge resources optimally to achieve better organizational outcomes.

The study attempts to delineate the proposed relationship and provides valuable insights for practitioners and academicians by including the knowledge sharing dimension to improve the SIP context of the IHI.

This paper aims to purport deeper understanding of, and instigate theoretical elaboration to, multidimensional value created through different reverse supply chain (RSC) relationships.

By capturing the relationships (and their differences) constituted and embedded in three “extreme” case studies from global used clothing supply chain, the sources of multidimensional values are explored in line with Dyer and Singh’s (1998) relational theory.

In the RSC, when downstream relationships are typically more opportunistic, value is created using inter-personal ways of knowledge sharing and through use of informal safeguards. In contrast, the upstream RSC relationships are more symbiotic, and value is created through more seamless (and routinized) knowledge sharing practices, and additional use of more formal transaction-specific controls or financial incentives as safeguarding instruments.

The use of consolidated case studies may affect the consistency in the findings presented. Another limitation relates to deriving propositions per each source presented in relational theory.

Practitioners particularly from industries whose global RSCs include different natures of relationships and multiple value incentives can be benefited through this study.

The paper extends the original sources of value creation prescribed in relational theory by contextualizing them in RSCs. It depicts how multidimensional values are created relationally by dyadic partners as the nature of relationship differs between upstream and downstream.

The purpose of present study is to identify influential aspects of published literature, research streams and future research questions to set forth future research agenda based on comprehensive literature review using bibliometric and content analysis.

The study analyzed 285 documents from the international Scopus database using bibliometric analysis and content analysis. VOSviewer software is used for bibliometric analysis.

The study identified influential aspects of published literature; identified five significant research streams: (1) Demonetization and financial system, (2) Demonetization and financial technology, (3) Demonetization and financial market, (4) Demonetization and digital payment system and (5) Demonetization and governance and proposed 27 key future research questions to develop future research agenda.

The present study makes significant contribution to the literature by providing a framework for future research. The framework provides opportunities to future researchers to explore the web of relations among five identified research streams as future research agenda.

The present work is unique in its way of contribution, as to the best of researchers' knowledge no work was witnessed in published literature to cover demonetization in a detailed and comprehensive manner. The present study fills this gap by conducting bibliometric analysis and content analysis. The study proposed conceptual framework for demonetization characterization to understand the demonetization literature well; and also proposed framework for future researcher to be explored further.

With the changing times, the role of social media has increased manifold. It acts as one of the platforms for disseminating information to the public faster. Social media enables us to focus on widespread ways of reaching the target audience. The principal motto of this research study is to identify the role of social media in public health development with a systematic review of literature in terms of its practice, assistance and application in future areas of public health measures.

The research adopted a bibliometric analysis method to analyze the data from vast sources. The Scopus database was used to extract papers using appropriate keywords. Thus, the study tries to answer the following research questions: (1) to determine the key journals, authors and keywords in the public health development research; (2) to provide a theme-based cluster based on the keywords’ cooccurrences; and (3) to develop a research framework for the upcoming researchers.

The study's findings provide a path to understanding the present research stream regarding the highest publication in terms of journals and the year and relevance of social media in public health development. Five theme-based clusters have been identified based on keyword cooccurrences. Thus, future researchers can extend the research field using different themes and frameworks, adding value to the present research works.

This research work is helpful to the government, health practitioners, policymakers and researchers in investigating areas where social media can be implemented. Lastly, social media applications will provide health development measures and lucrative results to the public.

The research enumerates the significance of social media in public health development through bibliometric analysis. The research work analyzed, reviewed and measured the importance of social media in health development measures by recognizing its usage, application and potential future research directions. The theme-based clusters have also been identified from the keywords’ cooccurrences.