Pub Date : 2024-04-15DOI: 10.1177/09721509241238537
Isma Zaighum, Ameenullah Aman, Mohd Zaini B. Abd Karim
The study investigated how national culture acts as a mediating factor in the connection between peer effects and corporate capital structure in enterprises from emerging market nations. The methodology employs a two-stage least squares technique, incorporating fixed effects and an instrumental variable approach, to analyze the regression results obtained from ordinary least squares. The results indicate that the level of influence exerted by peers is significant for a firm when determining its own level of leverage. Furthermore, it has been noted that enterprises tend to adopt similar cultural traits as their peers, such as minimal power distance, high uncertainty avoidance, individualism and masculinity. Hence, managers may consider their peers’ decisions on leverage in the industry while making assessments about the appropriate level of leverage for their own company. Furthermore, as emerging economies often encounter perplexing and uncertain circumstances, obtaining reliable information from peers’ financial decisions can potentially mitigate the duration and cost associated with making this crucial decision.
{"title":"Do Peers and National Culture Matter for Capital Structure Decisions of Emerging Market Corporations?","authors":"Isma Zaighum, Ameenullah Aman, Mohd Zaini B. Abd Karim","doi":"10.1177/09721509241238537","DOIUrl":"https://doi.org/10.1177/09721509241238537","url":null,"abstract":"The study investigated how national culture acts as a mediating factor in the connection between peer effects and corporate capital structure in enterprises from emerging market nations. The methodology employs a two-stage least squares technique, incorporating fixed effects and an instrumental variable approach, to analyze the regression results obtained from ordinary least squares. The results indicate that the level of influence exerted by peers is significant for a firm when determining its own level of leverage. Furthermore, it has been noted that enterprises tend to adopt similar cultural traits as their peers, such as minimal power distance, high uncertainty avoidance, individualism and masculinity. Hence, managers may consider their peers’ decisions on leverage in the industry while making assessments about the appropriate level of leverage for their own company. Furthermore, as emerging economies often encounter perplexing and uncertain circumstances, obtaining reliable information from peers’ financial decisions can potentially mitigate the duration and cost associated with making this crucial decision.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"19 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140596463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-09DOI: 10.1177/09721509241238556
Shanu Srivastava, Anu Mohta, V Shunmugasundaram
This study aimed to determine the drivers of mobile payment FinTech adoption. The study was conducted with 306 generation Y (Gen Y) and generation Z (Gen Z) FinTech users, and data were analyzed using structural equation modelling (SEM) through partial least squares and analysis of variance (ANOVA). The present study investigates some interesting and novel associations among variables that contribute to the literature, such as the mediating effect of effort expectancy, facilitating condition, performance expectancy and social influence between the association of financial literacy and behavioural intention, and investigates the unified theory of acceptance and use of technology (UTAUT) constructs (effort expectancy, facilitating condition, performance expectancy and social influence), technology acceptance model 3 (TAM 3) constructs (perceived enjoyment and self-efficacy), financial literacy and demographic features as drivers of FinTech adoption. The results indicate that effort expectancy, performance expectancy, facilitating conditions, financial literacy and self-efficacy are strong drivers of FinTech adoption. Perceived enjoyment and social influence do not influence users’ behavioural intention to adopt mobile payment services.JEL Codes: G41, O30, O31, 033
本研究旨在确定采用移动支付金融科技的驱动因素。研究对象为 306 名 Y 世代（Y 代）和 Z 世代（Z 代）金融科技用户，通过偏最小二乘法和方差分析（ANOVA）使用结构方程模型（SEM）对数据进行分析。本研究调查了一些有趣而新颖的变量之间的关联，如努力预期、便利条件、绩效预期和社会影响在金融知识与行为意向之间的中介效应，并调查了接受和使用技术的统一理论（UTAUT）建构（努力预期、便利条件、绩效预期和社会影响）、技术接受模型 3（TAM 3）建构（感知乐趣和自我效能）、金融知识和人口特征作为金融科技采用的驱动因素。结果表明，努力预期、绩效预期、便利条件、金融知识和自我效能是采用金融科技的强大驱动力。感知到的乐趣和社会影响并不影响用户采用移动支付服务的行为意向：G41, O30, O31, 033
{"title":"What Drives Mobile Payment Fin Tech Adoption in India?","authors":"Shanu Srivastava, Anu Mohta, V Shunmugasundaram","doi":"10.1177/09721509241238556","DOIUrl":"https://doi.org/10.1177/09721509241238556","url":null,"abstract":"This study aimed to determine the drivers of mobile payment FinTech adoption. The study was conducted with 306 generation Y (Gen Y) and generation Z (Gen Z) FinTech users, and data were analyzed using structural equation modelling (SEM) through partial least squares and analysis of variance (ANOVA). The present study investigates some interesting and novel associations among variables that contribute to the literature, such as the mediating effect of effort expectancy, facilitating condition, performance expectancy and social influence between the association of financial literacy and behavioural intention, and investigates the unified theory of acceptance and use of technology (UTAUT) constructs (effort expectancy, facilitating condition, performance expectancy and social influence), technology acceptance model 3 (TAM 3) constructs (perceived enjoyment and self-efficacy), financial literacy and demographic features as drivers of FinTech adoption. The results indicate that effort expectancy, performance expectancy, facilitating conditions, financial literacy and self-efficacy are strong drivers of FinTech adoption. Perceived enjoyment and social influence do not influence users’ behavioural intention to adopt mobile payment services.JEL Codes: G41, O30, O31, 033","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"18 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140596521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-03DOI: 10.1177/09721509241231107
Virendra Balon, Avinash Bagul, Rupesh Kumar
This study aims to identify the key barriers influencing green supply chain management (GSCM) practices for the construction industry. The study is based on a survey of 20 manager-level employees from the Indian construction industry. Considering the extensive literature review and expert opinion, 15 key barriers influencing GSCM practices were identified and the interrelationship among them was established using multi-criteria-based Interpretative Structure Modelling methodology. Furthermore, by using Matrix Cross-Reference Multiplication Applied for Classification analysis, the barriers were classified as autonomous, dependent, linkage, and independent barriers to understand their relative importance. The barriers were grouped into a three-group hierarchy and it was found that the lower group of barriers, that is, green design, suppliers and green materials, certifications, and financial constraints were highly influencing GSCM practices implementation. The study can help construction practitioners develop a supply chain strategy focusing on critical barriers hindering the adoption of GSCM practices.
{"title":"Green Construction Supply Chain Barriers Assessment: Evidence from Indian Construction Industry","authors":"Virendra Balon, Avinash Bagul, Rupesh Kumar","doi":"10.1177/09721509241231107","DOIUrl":"https://doi.org/10.1177/09721509241231107","url":null,"abstract":"This study aims to identify the key barriers influencing green supply chain management (GSCM) practices for the construction industry. The study is based on a survey of 20 manager-level employees from the Indian construction industry. Considering the extensive literature review and expert opinion, 15 key barriers influencing GSCM practices were identified and the interrelationship among them was established using multi-criteria-based Interpretative Structure Modelling methodology. Furthermore, by using Matrix Cross-Reference Multiplication Applied for Classification analysis, the barriers were classified as autonomous, dependent, linkage, and independent barriers to understand their relative importance. The barriers were grouped into a three-group hierarchy and it was found that the lower group of barriers, that is, green design, suppliers and green materials, certifications, and financial constraints were highly influencing GSCM practices implementation. The study can help construction practitioners develop a supply chain strategy focusing on critical barriers hindering the adoption of GSCM practices.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"12 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140596514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-01DOI: 10.1177/09721509241232195
Muhammad Wasim Akram, Salman Mirza, Shaza Mahar
Human inappropriate behaviour is being criticised for changing the climate because it wastes resources, pollutes water and contaminates the air, thereby demeaning the environment. To contribute to the United Nations’ sustainable development goals for 2019, companies have begun to focus on green human resource initiatives to promote green perspectives in their employees. In this regard, green human resource management may assist companies in motivating their employees towards environmentally friendly practices, but green perceived organisational support remains unexplored in this context. To address this gap, based on the theory of planned behaviour, this study aims to investigate the effect of green human resource management on employee green behaviour through the mediation effect of green perceived organisational support in the higher education sector of Pakistan. The questionnaire survey was used to collect data from the employees of the higher education sector. Findings show that green human resource management is a strong predictor of employee green behaviour, while green perceived organisational support is a significant mediator between green human resource management and employee green behaviour. Theoretical implications and practical significance have been addressed in this study.
{"title":"Employee Green Behaviour in Pakistani Education Sector: Does Green Perceived Organisational Support Mediate the Relation between Green Human Resource Management and Employee Green Behaviours?","authors":"Muhammad Wasim Akram, Salman Mirza, Shaza Mahar","doi":"10.1177/09721509241232195","DOIUrl":"https://doi.org/10.1177/09721509241232195","url":null,"abstract":"Human inappropriate behaviour is being criticised for changing the climate because it wastes resources, pollutes water and contaminates the air, thereby demeaning the environment. To contribute to the United Nations’ sustainable development goals for 2019, companies have begun to focus on green human resource initiatives to promote green perspectives in their employees. In this regard, green human resource management may assist companies in motivating their employees towards environmentally friendly practices, but green perceived organisational support remains unexplored in this context. To address this gap, based on the theory of planned behaviour, this study aims to investigate the effect of green human resource management on employee green behaviour through the mediation effect of green perceived organisational support in the higher education sector of Pakistan. The questionnaire survey was used to collect data from the employees of the higher education sector. Findings show that green human resource management is a strong predictor of employee green behaviour, while green perceived organisational support is a significant mediator between green human resource management and employee green behaviour. Theoretical implications and practical significance have been addressed in this study.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"26 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140596460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-22DOI: 10.1177/09721509241237597
Nidhish H, Badrinarayan Srirangam Ramaprasad, K. Sankaran, K. P. Nandan Prabhu, Ravi Phadke
While social entrepreneurship scholars in the past have focused much on the building blocks of robust social entrepreneurship business models and sustainability factors including supportive ecosystem elements, it is not clear ‘what’ categories of the interactive ecosystem in which social entrepreneurs are located influence the choice of business models even before they operationalize their social ventures. Accordingly, this study espouses a mixed-method research design to address this issue. The authors collected data from 24 and 112 social entrepreneurs in two study phases, respectively. Four support factors—business, market, financial and policy were considered important by social entrepreneurs in India that they believe influenced their choice of business models. While policy and financial support factors were considered most important by social entrepreneurs with a pure social mission/impact orientation, market and business support were considered significant influential factors by social entrepreneurs with a profit orientation. Social entrepreneurs who sought a balance between social and economic missions, however, considered the presence of financial and market support to be crucial for choosing a relevant business model. To the best of our knowledge, this is the first study that investigates the inherent priori influence of prevalent ecosystem factors on social business model selection. It uniquely brings out an empirical association between ecosystem factors and business model preferences, affirming that factors pivotal to choice also underpin sustainability. Moreover, this study also unveils an interactive framework encompassing entrepreneur traits and their orientations, ecosystem factors, feedback and performance. Offering multiple actionable implications, this study offers key insights for policy decision-makers and practitioners.
{"title":"Do the Prevalent Entrepreneurial Ecosystem Factors Drive the Choice of Business Models? A Mixed-methods Study Involving Social Entrepreneurs in India","authors":"Nidhish H, Badrinarayan Srirangam Ramaprasad, K. Sankaran, K. P. Nandan Prabhu, Ravi Phadke","doi":"10.1177/09721509241237597","DOIUrl":"https://doi.org/10.1177/09721509241237597","url":null,"abstract":"While social entrepreneurship scholars in the past have focused much on the building blocks of robust social entrepreneurship business models and sustainability factors including supportive ecosystem elements, it is not clear ‘what’ categories of the interactive ecosystem in which social entrepreneurs are located influence the choice of business models even before they operationalize their social ventures. Accordingly, this study espouses a mixed-method research design to address this issue. The authors collected data from 24 and 112 social entrepreneurs in two study phases, respectively. Four support factors—business, market, financial and policy were considered important by social entrepreneurs in India that they believe influenced their choice of business models. While policy and financial support factors were considered most important by social entrepreneurs with a pure social mission/impact orientation, market and business support were considered significant influential factors by social entrepreneurs with a profit orientation. Social entrepreneurs who sought a balance between social and economic missions, however, considered the presence of financial and market support to be crucial for choosing a relevant business model. To the best of our knowledge, this is the first study that investigates the inherent priori influence of prevalent ecosystem factors on social business model selection. It uniquely brings out an empirical association between ecosystem factors and business model preferences, affirming that factors pivotal to choice also underpin sustainability. Moreover, this study also unveils an interactive framework encompassing entrepreneur traits and their orientations, ecosystem factors, feedback and performance. Offering multiple actionable implications, this study offers key insights for policy decision-makers and practitioners.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"31 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140204296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-22DOI: 10.1177/09721509241234033
Eddy Suprihadi, Nevi Danila
As the demand for investment products tied to environmental, social and governance (ESG) concerns rises, ESG stock indices have been established. These indices aim to aid investors in navigating and assessing the risks associated with firms based on ESG factors and potential investment returns. The objective of the article is to predict ESG stock indices using a machine learning approach. We use daily data of Dow Jones Sustainability Index (DJSI) World, DJSI Asia Pacific and DJSI Emerging Market from 2018 to 2022 as samples. Two-layer ensemble model – combination of support vector machine (SVM), random forest (RF), long short-term memory (LSTM) and gated recurrent unit (GRU) algorithms – is employed to forecast the indices. The results show that the ensemble model accurately forecasts the indices, with the prediction line closely matching the actual values. It gives the implication that investors are able to improve investment decisions, assist in managing investment risk, and optimize their portfolio diversification. Meanwhile, policymakers are able to anticipate economic trends, inflation and interest rates, assisting in the development of successful economic policies.This research article presents a machine learning approach for predicting ESG stock indices. The proposed model combines SVM, RF, LSTM and GRU algorithms to create a powerful two-layer ensemble model that outperforms individual models. The results show that the ensemble model accurately forecasts ESG stock indices, with the prediction line closely matching the actual values. The model offers insights into the behaviour of different algorithms, highlighting their strengths and limitations. The proposed model can guide decision-making processes, support investment strategies, and ultimately contribute to advancing sustainable investment practices.
{"title":"Forecasting ESG Stock Indices Using a Machine Learning Approach","authors":"Eddy Suprihadi, Nevi Danila","doi":"10.1177/09721509241234033","DOIUrl":"https://doi.org/10.1177/09721509241234033","url":null,"abstract":"As the demand for investment products tied to environmental, social and governance (ESG) concerns rises, ESG stock indices have been established. These indices aim to aid investors in navigating and assessing the risks associated with firms based on ESG factors and potential investment returns. The objective of the article is to predict ESG stock indices using a machine learning approach. We use daily data of Dow Jones Sustainability Index (DJSI) World, DJSI Asia Pacific and DJSI Emerging Market from 2018 to 2022 as samples. Two-layer ensemble model – combination of support vector machine (SVM), random forest (RF), long short-term memory (LSTM) and gated recurrent unit (GRU) algorithms – is employed to forecast the indices. The results show that the ensemble model accurately forecasts the indices, with the prediction line closely matching the actual values. It gives the implication that investors are able to improve investment decisions, assist in managing investment risk, and optimize their portfolio diversification. Meanwhile, policymakers are able to anticipate economic trends, inflation and interest rates, assisting in the development of successful economic policies.This research article presents a machine learning approach for predicting ESG stock indices. The proposed model combines SVM, RF, LSTM and GRU algorithms to create a powerful two-layer ensemble model that outperforms individual models. The results show that the ensemble model accurately forecasts ESG stock indices, with the prediction line closely matching the actual values. The model offers insights into the behaviour of different algorithms, highlighting their strengths and limitations. The proposed model can guide decision-making processes, support investment strategies, and ultimately contribute to advancing sustainable investment practices.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"9 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140204376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-22DOI: 10.1177/09721509241225334
Diksha Saini, Balwinder Singh
The focus of this research is on the Upper Echelon Theory, asserting that CEO&’s cognitive attributes exert a major effect on organizational outcomes. The present study adds to the behavioural finance and strategic management literature by investigating the association between Chief Executive Officer&’s (CEO) confidence and firm profitability in the Indian context. A sample of S&P BSE 100 Indian firms for five financial years has been used to examine the aforementioned relationship, using panel regression analysis. The findings reveal that CEO overconfidence favourably impacts the company&’s profitability as overconfident CEOs enjoy the early mover advantage in the market through quick and innovative decisions and gain competitive strength by overinvesting in good but risky projects. These findings contribute novel insights to the existing literature by exploring the most prevalent managerial behavioural bias and its impact on corporate profitability in the Indian context. The analysis may assist the policymakers responsible for framing recruitment and compensation policies and developing an optimum monitoring system to capitalize on the cognitive traits of top executives in India.
{"title":"Unravelling the Impact of Executive Confidence on Firm Profitability","authors":"Diksha Saini, Balwinder Singh","doi":"10.1177/09721509241225334","DOIUrl":"https://doi.org/10.1177/09721509241225334","url":null,"abstract":"The focus of this research is on the Upper Echelon Theory, asserting that CEO&’s cognitive attributes exert a major effect on organizational outcomes. The present study adds to the behavioural finance and strategic management literature by investigating the association between Chief Executive Officer&’s (CEO) confidence and firm profitability in the Indian context. A sample of S&P BSE 100 Indian firms for five financial years has been used to examine the aforementioned relationship, using panel regression analysis. The findings reveal that CEO overconfidence favourably impacts the company&’s profitability as overconfident CEOs enjoy the early mover advantage in the market through quick and innovative decisions and gain competitive strength by overinvesting in good but risky projects. These findings contribute novel insights to the existing literature by exploring the most prevalent managerial behavioural bias and its impact on corporate profitability in the Indian context. The analysis may assist the policymakers responsible for framing recruitment and compensation policies and developing an optimum monitoring system to capitalize on the cognitive traits of top executives in India.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"2016 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140204314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-19DOI: 10.1177/09721509241230811
Irshad Ahmad Para, Tosib Alam
This article shows the relationship between health outcomes and economic growth for the period of 2002–2020 among the northern states of India. By using pooled ordinary least squares, fixed effect and random effect model, the study examines the impact of infant mortality, birth rate and death rate on gross state domestic product per capita at a constant price. The study takes gross capital formation and gross enrolment ratio as control variables. Data from the Reserve Bank of India and EPWRF states of India were retrieved and used in the study. The result shows that health outcomes and economic growth have a relatively substantial and significant association with each other. The results demonstrate that economic growth increases by 1% with a decrease in infant mortality rate by its elasticity coefficient –0.32. The results show that economic growth will increase by 1% with the increase in birth rate, gross enrolment ratio and gross fixed capital formation by its slope coefficients, that is, 0.10, 0.32 and 1.78 which are statistically significant at 1%, 5% and 1% level of significance. The finding of the study demonstrates that health outcomes remain a vital determinant in improving economic growth among the northern states. Our results advocate that the government spending on health should be improved; moreover, the government should frame health policies to boost health outcomes to level the disparities in health outcomes among the northern states of India.
{"title":"Dynamics of Economic Growth and Health Outcomes Among the Northern States of India: A Panel Data Analysis","authors":"Irshad Ahmad Para, Tosib Alam","doi":"10.1177/09721509241230811","DOIUrl":"https://doi.org/10.1177/09721509241230811","url":null,"abstract":"This article shows the relationship between health outcomes and economic growth for the period of 2002–2020 among the northern states of India. By using pooled ordinary least squares, fixed effect and random effect model, the study examines the impact of infant mortality, birth rate and death rate on gross state domestic product per capita at a constant price. The study takes gross capital formation and gross enrolment ratio as control variables. Data from the Reserve Bank of India and EPWRF states of India were retrieved and used in the study. The result shows that health outcomes and economic growth have a relatively substantial and significant association with each other. The results demonstrate that economic growth increases by 1% with a decrease in infant mortality rate by its elasticity coefficient –0.32. The results show that economic growth will increase by 1% with the increase in birth rate, gross enrolment ratio and gross fixed capital formation by its slope coefficients, that is, 0.10, 0.32 and 1.78 which are statistically significant at 1%, 5% and 1% level of significance. The finding of the study demonstrates that health outcomes remain a vital determinant in improving economic growth among the northern states. Our results advocate that the government spending on health should be improved; moreover, the government should frame health policies to boost health outcomes to level the disparities in health outcomes among the northern states of India.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"70 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140169526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mergers and acquisitions have been important means of company expansion, restructuring, and diversification. In mergers and acquisitions, Indian banks play a critical role. The study aimed to discover, determine, and create an empirical model that evaluates the interdependence and interaction of enablers. Through literature and unstructured interviews, 10 enablers influencing Indian banks’ financing decisions for merger and acquisition transactions were identified. Total interpretive structural modelling (TISM) and the Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) technique establish the relationship between identified enablers. Governance and regulatory framework, political stability, and economic stability are major independent enablers for financing mergers and acquisitions. Transparency and disclosure, infrastructure, technical skills, and information communication technology act as linkage enablers for the participation of banks in merger and acquisition transactions. The study makes a novel contribution by identifying enablers through a literature search and ‘experts’ opinions. The TISM model determines the priority of the enablers by displaying hierarchical interconnection and dependency. This study reviews the literature to generalize the findings and focus on significant drivers for increased investment. To encourage merger and acquisition activity, practitioners must focus on elements with significant driving power. It will assist the practitioners, managers, and authorities in prioritizing their efforts.
并购一直是公司扩张、重组和多元化的重要手段。在并购中，印度银行发挥着至关重要的作用。本研究旨在发现、确定和创建一个实证模型，以评估各推动因素之间的相互依存和相互作用。通过文献和非结构化访谈，确定了影响印度银行并购交易融资决策的 10 个有利因素。总体解释性结构建模（TISM）和 MICMAC（Matrice d'Impacts Croisés Multiplication Appliqués à un Classement）技术建立了已确定的促进因素之间的关系。治理和监管框架、政治稳定和经济稳定是并购融资的主要独立促进因素。透明度和信息披露、基础设施、技术技能和信息通信技术是银行参与并购交易的关联促进因素。本研究通过文献检索和 "专家意见 "确定了促进因素，做出了新的贡献。TISM 模型通过显示层次性的相互联系和依赖关系来确定促进因素的优先级。本研究对文献进行了回顾，对研究结果进行了归纳，并重点关注了增加投资的重要推动因素。为鼓励并购活动，从业人员必须关注具有重大推动力的要素。这将有助于从业者、管理者和主管部门确定工作的优先次序。
{"title":"Analyzing the Hierarchical Structure of Enablers Affecting Indian Banks’ Merger and Acquisition Financing Decisions","authors":"Ravita Kharb, Neha Saini, Charu Shri, Kumar Dinesh","doi":"10.1177/09721509241227777","DOIUrl":"https://doi.org/10.1177/09721509241227777","url":null,"abstract":"Mergers and acquisitions have been important means of company expansion, restructuring, and diversification. In mergers and acquisitions, Indian banks play a critical role. The study aimed to discover, determine, and create an empirical model that evaluates the interdependence and interaction of enablers. Through literature and unstructured interviews, 10 enablers influencing Indian banks’ financing decisions for merger and acquisition transactions were identified. Total interpretive structural modelling (TISM) and the Matrice d’Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) technique establish the relationship between identified enablers. Governance and regulatory framework, political stability, and economic stability are major independent enablers for financing mergers and acquisitions. Transparency and disclosure, infrastructure, technical skills, and information communication technology act as linkage enablers for the participation of banks in merger and acquisition transactions. The study makes a novel contribution by identifying enablers through a literature search and ‘experts’ opinions. The TISM model determines the priority of the enablers by displaying hierarchical interconnection and dependency. This study reviews the literature to generalize the findings and focus on significant drivers for increased investment. To encourage merger and acquisition activity, practitioners must focus on elements with significant driving power. It will assist the practitioners, managers, and authorities in prioritizing their efforts.","PeriodicalId":47569,"journal":{"name":"Global Business Review","volume":"205 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140071361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-04DOI: 10.1177/09721509241232198
Madhuri Saripalle, Surabhi Somya
The telecom industry in India has witnessed exponential growth in the past decade; however, its profitability has been on the decline post 2008. This study analyzes the determinants of profitability of the industry during 2010–2022 using the conventional structure-conduct-performance paradigm. We estimate a dynamic panel data model to understand the role of endogeneity and profit persistence in the industry. Our findings are contrary to what the theory predicts and highlight the importance of the regulatory and institutional framework of the industry. Results suggest that there is profit persistence in the industry. The study finds that among conduct variables, export intensity has a positive impact while selling intensity has a negative impact on profitability. While size is not significant, concentration has a negative impact on profitability. Import has a negative impact on profitability. These results suggest that as the telecom industry transitioned from a monopoly to an oligopolistic market with players competing in different domains and services, selling and advertisement intensity has diminishing returns to profitability while export intensity emerges as an important driver of profitability. Results also suggest the importance of the production-linked incentive scheme encouraging exports and the need for regulating concentration and encouraging import substitution.
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