Pub Date : 2023-09-25DOI: 10.1177/09722629231168696
Huang Jing, Abdullah Al Mamun, Farzana Naznen, Mohd Helmi Ali
This study aimed to examine the influence of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating condition (FC), hedonic motivation (HM), perceived trust (PT) and lifestyle compatibility (LC) on the intention to adopt M-payment (IMP) as well as the mediating effect of IMP on the adoption of M-payment (AMP). This study adopted a cross-sectional design and collected quantitative data through an online survey from 309 respondents in China. The results revealed the significant positive influence of PE, EE, FC, HM, PT and LC on the IMP. The IMP was found to positively and significantly mediate the relationships of all predictors (except SI) and the actual usage of M-payment. Artificial neural network results validated the high prediction accuracy of the data fitness and highlighted the importance of PE, EE and LC on the IMP among Chinese users.
{"title":"Sustainable Financial Development Through Mobile Payment: Using SEM-ANN Analysis","authors":"Huang Jing, Abdullah Al Mamun, Farzana Naznen, Mohd Helmi Ali","doi":"10.1177/09722629231168696","DOIUrl":"https://doi.org/10.1177/09722629231168696","url":null,"abstract":"This study aimed to examine the influence of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating condition (FC), hedonic motivation (HM), perceived trust (PT) and lifestyle compatibility (LC) on the intention to adopt M-payment (IMP) as well as the mediating effect of IMP on the adoption of M-payment (AMP). This study adopted a cross-sectional design and collected quantitative data through an online survey from 309 respondents in China. The results revealed the significant positive influence of PE, EE, FC, HM, PT and LC on the IMP. The IMP was found to positively and significantly mediate the relationships of all predictors (except SI) and the actual usage of M-payment. Artificial neural network results validated the high prediction accuracy of the data fitness and highlighted the importance of PE, EE and LC on the IMP among Chinese users.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135814659","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 : 2023-09-24DOI: 10.1177/09722629231172048
Chiranjib Paul, Prabir Kumar Das
Bollywood movies made in the Hindi language are regarded as one of the most popular Indian movies. Bollywood movies like other Indian movies are successful in retaining their characteristics, which is significantly different than Hollywood movies. Overseas earnings contribute a significant pie of Bollywood movies’ total revenue. International revenue prediction requires a new approach due to the changing release strategy by the investors. Movie investors worldwide are moving away from sequential release first in the domestic market followed by release in the international markets to simultaneous release both in the domestic and the international markets. Revenue prediction at an early stage before committing money to the project is more valuable than prediction at a later stage just before or after the movie’s release. We utilize multiple machine learning algorithms to improve the baseline prediction accuracy significantly. Extreme gradient boosting, the best algorithm, reduces the baseline prediction error by 18.05%. Adopting different algorithms to different scenarios improves prediction accuracy relative to applying one algorithm across all scenarios. As an example, robust regression generates the highest prediction accuracy for movies with higher star power, whereas extreme gradient boosting achieves the highest prediction accuracy for movies with lower star power. More accurate prediction before committing money to the movie project strengthens investors’ judgement and reduces investment risk. Our study addresses a new trend of simultaneous movie releases in domestic and international markets and predicts international revenue without knowledge of domestic performance.
{"title":"Early-stage Prediction of International Revenue of Bollywood Movies—Emphasis on Simultaneous Over Sequential Release","authors":"Chiranjib Paul, Prabir Kumar Das","doi":"10.1177/09722629231172048","DOIUrl":"https://doi.org/10.1177/09722629231172048","url":null,"abstract":"Bollywood movies made in the Hindi language are regarded as one of the most popular Indian movies. Bollywood movies like other Indian movies are successful in retaining their characteristics, which is significantly different than Hollywood movies. Overseas earnings contribute a significant pie of Bollywood movies’ total revenue. International revenue prediction requires a new approach due to the changing release strategy by the investors. Movie investors worldwide are moving away from sequential release first in the domestic market followed by release in the international markets to simultaneous release both in the domestic and the international markets. Revenue prediction at an early stage before committing money to the project is more valuable than prediction at a later stage just before or after the movie’s release. We utilize multiple machine learning algorithms to improve the baseline prediction accuracy significantly. Extreme gradient boosting, the best algorithm, reduces the baseline prediction error by 18.05%. Adopting different algorithms to different scenarios improves prediction accuracy relative to applying one algorithm across all scenarios. As an example, robust regression generates the highest prediction accuracy for movies with higher star power, whereas extreme gradient boosting achieves the highest prediction accuracy for movies with lower star power. More accurate prediction before committing money to the movie project strengthens investors’ judgement and reduces investment risk. Our study addresses a new trend of simultaneous movie releases in domestic and international markets and predicts international revenue without knowledge of domestic performance.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135926481","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 : 2023-09-24DOI: 10.1177/09722629231172580
None Shivani, Bhag Singh Bodla
Sentiments, opinions and emotions are considered as the basis for various kinds of analysis and anticipations. Sentiment analysis as a concept of generating the polarity from written, visual and verbal content is burgeoning in the advanced technological era. The article aims to carry out a bibliometric visualization study that reviews the current status, worldwide collaboration, evolution and potential emergence of machine learning-based sentiment analysis in the area of financial market along with several other themes. A corpus of 610 research publications from the Web of Science database during 2008–2022 is the base for depicting the contribution of eminent authors, journals, countries and research themes. Outcomes of the study reveal the wide scope of the ‘Sentiment Analysis’ theme in the existing research world along with providing a direction for future studies which may embed several advanced topics. The theme-related publications are segmented into four clusters where the ‘sentiment analysis and predictions using machine learning’ reflects the future emergence with existing growth. This concept has widely spread in India, China and the USA. Potential researchers can implement this concept in the stock market and financial predictions, sarcasm detection and behavioural mapping as major contributions to the firms’ effective decisions.
情感、观点和情绪被认为是各种分析和预测的基础。情感分析作为一种从书面、视觉和口头内容中产生极性的概念，在先进的技术时代蓬勃发展。本文旨在进行文献计量可视化研究，回顾金融市场领域基于机器学习的情感分析的现状、全球合作、演变和潜在出现，以及其他几个主题。2008-2022年期间，来自Web of Science数据库的610篇研究出版物的语料库是描绘杰出作者、期刊、国家和研究主题贡献的基础。该研究的结果揭示了“情绪分析”主题在现有研究界的广泛范围，并为未来的研究提供了一个方向，该研究可能包含几个高级主题。与主题相关的出版物分为四类，其中“使用机器学习的情感分析和预测”反映了现有增长的未来出现。这个概念在印度、中国和美国广泛传播。潜在的研究人员可以在股票市场和金融预测、讽刺检测和行为映射中实施这一概念，作为公司有效决策的主要贡献。
{"title":"Sentiment Analysis Using Machine Learning in Stock Market: A Bibliometric Visualization","authors":"None Shivani, Bhag Singh Bodla","doi":"10.1177/09722629231172580","DOIUrl":"https://doi.org/10.1177/09722629231172580","url":null,"abstract":"Sentiments, opinions and emotions are considered as the basis for various kinds of analysis and anticipations. Sentiment analysis as a concept of generating the polarity from written, visual and verbal content is burgeoning in the advanced technological era. The article aims to carry out a bibliometric visualization study that reviews the current status, worldwide collaboration, evolution and potential emergence of machine learning-based sentiment analysis in the area of financial market along with several other themes. A corpus of 610 research publications from the Web of Science database during 2008–2022 is the base for depicting the contribution of eminent authors, journals, countries and research themes. Outcomes of the study reveal the wide scope of the ‘Sentiment Analysis’ theme in the existing research world along with providing a direction for future studies which may embed several advanced topics. The theme-related publications are segmented into four clusters where the ‘sentiment analysis and predictions using machine learning’ reflects the future emergence with existing growth. This concept has widely spread in India, China and the USA. Potential researchers can implement this concept in the stock market and financial predictions, sarcasm detection and behavioural mapping as major contributions to the firms’ effective decisions.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135925745","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 : 2023-09-24DOI: 10.1177/09722629231193543
Amlan Ray, Akash Doifode, None Badri Narayanan G, None Deepika M. G.
The Regional Comprehensive Economic Partnership (RCEP) agreement was concluded in the year 2020 between ASEAN and its five free trade agreement (FTA) partners excluding India, which was a part of the negotiation since its inception. RCEP remains important for India considering its volume of trade with member countries and FTAs it has with various members of the group. During signing of RCEP, India had FTAs with 12 members except China, Australia and New Zealand. Later, India signed an interim FTA with Australia in April 2022, followed by an Economic Cooperation and Trade Agreement in December 2022. The trade potential India has with these countries will be of interest to the policymakers for influencing its future direction of trade. India’s trade potential with Australia, China and New Zealand with whom it did not have an FTA till the signing of RCEP is important from the perspective of entering into bilateral trade agreements. In this article, the gravity model is used to measure India’s potential trade with RCEP as a block and individually with China, Australia and New Zealand. Here, a high-dimensional fixed effect Poisson pseudo-maximum likelihood model is used for measuring potential trade. A comparison of potential trade with the actual shows that India has more potential for expansion of exports than imports with RCEP as a block and in particular with China, Australia and New Zealand.
{"title":"Analysis of India’s Trade Potential with RCEP Members: A Study Using Gravity Model","authors":"Amlan Ray, Akash Doifode, None Badri Narayanan G, None Deepika M. G.","doi":"10.1177/09722629231193543","DOIUrl":"https://doi.org/10.1177/09722629231193543","url":null,"abstract":"The Regional Comprehensive Economic Partnership (RCEP) agreement was concluded in the year 2020 between ASEAN and its five free trade agreement (FTA) partners excluding India, which was a part of the negotiation since its inception. RCEP remains important for India considering its volume of trade with member countries and FTAs it has with various members of the group. During signing of RCEP, India had FTAs with 12 members except China, Australia and New Zealand. Later, India signed an interim FTA with Australia in April 2022, followed by an Economic Cooperation and Trade Agreement in December 2022. The trade potential India has with these countries will be of interest to the policymakers for influencing its future direction of trade. India’s trade potential with Australia, China and New Zealand with whom it did not have an FTA till the signing of RCEP is important from the perspective of entering into bilateral trade agreements. In this article, the gravity model is used to measure India’s potential trade with RCEP as a block and individually with China, Australia and New Zealand. Here, a high-dimensional fixed effect Poisson pseudo-maximum likelihood model is used for measuring potential trade. A comparison of potential trade with the actual shows that India has more potential for expansion of exports than imports with RCEP as a block and in particular with China, Australia and New Zealand.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135925406","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 : 2023-09-24DOI: 10.1177/09722629231173255
Po-Sheng Yang, Jin-Li Hu
Based on agency theory and overinvestment view, the research explores the possibility of severe agency problems caused by managers’ self-interest and promote information transparency to solve agency problems. Furthermore, according to the risk mitigation viewpoints, Corporate Social Responsibility (CSR) performance influences credit risk rating. Therefore, there is an interlocking relationship between the three parts, which are examined by panel data analysis. First, the Tobit regression is used to predict the enterprises’ ranking that did not win the CSR Award of Common Wealth Magazine. Second, the relationships among information transparency, CSR, and credit risk index (TCRI TM ) provided by Taiwan Economic Journal are analysed. The best model is chosen by using T test, LM test, and Hausman tests. Next, this research uses the fixed-effects model as empirical analysis. The major empirical findings of this paper are as follows: (a) Improving information transparency can promote CSR performance. (b) Improving information transparency helps obtain better credit ratings. (c) Better CSR performance helps obtain better credit ratings. In summary, all three factors positively affect a company, improving its investment environment and bringing about a good reputation. When business managers or decision-makers are developing business strategies, this could be something to take into account.
{"title":"Information Transparency, Corporate Social Responsibility, and Credit Rating: Evidence from Taiwan’s Enterprises","authors":"Po-Sheng Yang, Jin-Li Hu","doi":"10.1177/09722629231173255","DOIUrl":"https://doi.org/10.1177/09722629231173255","url":null,"abstract":"Based on agency theory and overinvestment view, the research explores the possibility of severe agency problems caused by managers’ self-interest and promote information transparency to solve agency problems. Furthermore, according to the risk mitigation viewpoints, Corporate Social Responsibility (CSR) performance influences credit risk rating. Therefore, there is an interlocking relationship between the three parts, which are examined by panel data analysis. First, the Tobit regression is used to predict the enterprises’ ranking that did not win the CSR Award of Common Wealth Magazine. Second, the relationships among information transparency, CSR, and credit risk index (TCRI TM ) provided by Taiwan Economic Journal are analysed. The best model is chosen by using T test, LM test, and Hausman tests. Next, this research uses the fixed-effects model as empirical analysis. The major empirical findings of this paper are as follows: (a) Improving information transparency can promote CSR performance. (b) Improving information transparency helps obtain better credit ratings. (c) Better CSR performance helps obtain better credit ratings. In summary, all three factors positively affect a company, improving its investment environment and bringing about a good reputation. When business managers or decision-makers are developing business strategies, this could be something to take into account.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135925412","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 : 2023-09-10DOI: 10.1177/09722629231194396
Kuldeep Singh
This study investigates whether the relationship between green operations (GR-OPS) and corporate financial performance (CFP) is conditional on firms’ adherence to environmental, social and governance (ESG) practices. GR-OPS is quantified as an inverse of the energy intensity (ene-int) of the firm’s operations. CFP is proxied by return on equity and return on assets. The study uses panel data for non-financial firms listed on India’s Bombay Stock Exchange (BSE) 100 index. The ESG-sensitive firms are bifurcated from a broader list of BSE 100 index based on their belongingness to the BSE ESG 100 index for econometric analysis. The findings confirm that the impact of GR-OPS on CFP is subject to the firms’ adherence to ESG practices. A positive relationship between GR-OPS and CFP is established for ESG-sensitive firms, while the linkage is non-existent for non-ESG firms. Such findings are attributable to ESG sensitivity (reduced risks) and not the reduced operational costs due to reduced ene-int. The study claims that the benefits of ESG are evident via GR-OPS. Firms should attempt to meet ESG practices to unlock the financial benefits of GR-OPS. When coupled, these practices can reduce the overall risk of the firms as well as generate better economic profits. Adherence to ESG practices and GR-OPS will build environmentally and socially sensitive firms. This is a greater need of modern society, which is increasingly fighting social unrest, global health concerns and climate change.
{"title":"Green Operations and Corporate Financial Performance: Does the ESG Sensitivity Matter?","authors":"Kuldeep Singh","doi":"10.1177/09722629231194396","DOIUrl":"https://doi.org/10.1177/09722629231194396","url":null,"abstract":"This study investigates whether the relationship between green operations (GR-OPS) and corporate financial performance (CFP) is conditional on firms’ adherence to environmental, social and governance (ESG) practices. GR-OPS is quantified as an inverse of the energy intensity (ene-int) of the firm’s operations. CFP is proxied by return on equity and return on assets. The study uses panel data for non-financial firms listed on India’s Bombay Stock Exchange (BSE) 100 index. The ESG-sensitive firms are bifurcated from a broader list of BSE 100 index based on their belongingness to the BSE ESG 100 index for econometric analysis. The findings confirm that the impact of GR-OPS on CFP is subject to the firms’ adherence to ESG practices. A positive relationship between GR-OPS and CFP is established for ESG-sensitive firms, while the linkage is non-existent for non-ESG firms. Such findings are attributable to ESG sensitivity (reduced risks) and not the reduced operational costs due to reduced ene-int. The study claims that the benefits of ESG are evident via GR-OPS. Firms should attempt to meet ESG practices to unlock the financial benefits of GR-OPS. When coupled, these practices can reduce the overall risk of the firms as well as generate better economic profits. Adherence to ESG practices and GR-OPS will build environmentally and socially sensitive firms. This is a greater need of modern society, which is increasingly fighting social unrest, global health concerns and climate change.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136072816","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 : 2023-09-09DOI: 10.1177/09722629231172046
Saurabh Verma, Sunil Kumar Yadav, Ritu Raj
The present study seeks to identify the current research trends and streamline future research opportunities in masstige marketing by conducting a bibliometric analysis of available literature from Scopus and the Web of science databases between 2001 and 2022. The study analyses 111 articles from the database of Scopus and the Web of Science published between 2001 and 2022, using bibliometric analysis, performance and science mapping analysis. The study used biblioshiny as a tool to conduct the bibliometric analysis of the extracted data. The research findings revealed that the publication of articles has increased between 2001 and 2022. A total of 93.3% of authors contributed one article, 5.5% of authors contributed two articles, 0.8 % of authors contributed three articles, and only 0.4 % of authors contributed seven articles. Countries like the USA, UK, India, Portugal, France and China have found to be the maximum contributors towards masstige. Further, the Bradford’s law applied in the study has revealed the basic sources of studies on masstige.
本研究旨在通过对2001年至2022年间来自Scopus和Web of science数据库的可用文献进行文献计量分析，确定当前的研究趋势，并简化大规模营销领域未来的研究机会。该研究分析了2001年至2022年期间Scopus和Web of Science数据库中发表的111篇文章，使用了文献计量学分析、绩效和科学地图分析。本研究使用文献计量学作为工具，对提取的数据进行文献计量学分析。研究结果显示，从2001年到2022年，论文的发表量有所增加。共有93.3%的作者贡献了一篇文章，5.5%的作者贡献了两篇文章，0.8%的作者贡献了三篇文章，只有0.4%的作者贡献了七篇文章。研究发现，美国、英国、印度、葡萄牙、法国和中国等国家是大规模人口的最大贡献者。此外，研究中应用的布拉德福德定律揭示了按摩研究的基本来源。
{"title":"Trends in the Evaluation of Masstige Marketing: A Bibliometric Analysis Using R","authors":"Saurabh Verma, Sunil Kumar Yadav, Ritu Raj","doi":"10.1177/09722629231172046","DOIUrl":"https://doi.org/10.1177/09722629231172046","url":null,"abstract":"The present study seeks to identify the current research trends and streamline future research opportunities in masstige marketing by conducting a bibliometric analysis of available literature from Scopus and the Web of science databases between 2001 and 2022. The study analyses 111 articles from the database of Scopus and the Web of Science published between 2001 and 2022, using bibliometric analysis, performance and science mapping analysis. The study used biblioshiny as a tool to conduct the bibliometric analysis of the extracted data. The research findings revealed that the publication of articles has increased between 2001 and 2022. A total of 93.3% of authors contributed one article, 5.5% of authors contributed two articles, 0.8 % of authors contributed three articles, and only 0.4 % of authors contributed seven articles. Countries like the USA, UK, India, Portugal, France and China have found to be the maximum contributors towards masstige. Further, the Bradford’s law applied in the study has revealed the basic sources of studies on masstige.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192431","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 : 2023-09-09DOI: 10.1177/09722629231188596
Vandana Dangi
The knowledge of the interconnectedness between liquid and futures markets of cryptocurrencies amidst dynamic contemporary environment can be enriched through the full characterization of the direction, persistence and intensity of information flows between these markets. So, the present study attempts to investigate the static and dynamic connexions between liquid and futures markets of Bitcoin, Ethereum, Litecoin, Ripple XRP and Bitcoin Cash from June 2018 to June 2022. The connexion between their liquid and futures markets is first investigated using unconditional correlation, Johansen’s cointegration, vector error correction and Wald’s block exogeneity. Their estimates discern connexions encompassing significant long-run relationships between their liquid and futures markets; momentous unidirectional long-run causality from their futures market to liquid market; and momentous bidirectional short-run causality from their liquid market to futures market and from their futures market to liquid market. The present treatise encompasses methodological advancement in the investigation of interconnectedness between these markets by employing a dynamic conditional correlation model and a wavelet transform framework. Their discerned estimates indicate that the markets of Bitcoin, Litecoin, Ethereum and Bitcoin Cash have only momentous long-run perseverance, lingering and spillover effects of shocks’ sway on conditional correlations. However, there is momentous short- and long-run perseverance, lingering and spillover effects in the case of Ripple XRP. The wavelet coherence analysis also confirms these results by indicating a bidirectional short-run causal relation and a long-run positive comovement between liquid returns and futures returns of these cryptocurrencies. These discernments may help investors, portfolio managers and policymakers to enhance hedging effectiveness through optimal portfolio allocation and monitor financial contagion to attain and sustain financial stability in economies.
{"title":"Connexion Between Cryptocurrencies Liquid and Futures Markets: Discernment from Static, Dynamic and Wavelet Approach","authors":"Vandana Dangi","doi":"10.1177/09722629231188596","DOIUrl":"https://doi.org/10.1177/09722629231188596","url":null,"abstract":"The knowledge of the interconnectedness between liquid and futures markets of cryptocurrencies amidst dynamic contemporary environment can be enriched through the full characterization of the direction, persistence and intensity of information flows between these markets. So, the present study attempts to investigate the static and dynamic connexions between liquid and futures markets of Bitcoin, Ethereum, Litecoin, Ripple XRP and Bitcoin Cash from June 2018 to June 2022. The connexion between their liquid and futures markets is first investigated using unconditional correlation, Johansen’s cointegration, vector error correction and Wald’s block exogeneity. Their estimates discern connexions encompassing significant long-run relationships between their liquid and futures markets; momentous unidirectional long-run causality from their futures market to liquid market; and momentous bidirectional short-run causality from their liquid market to futures market and from their futures market to liquid market. The present treatise encompasses methodological advancement in the investigation of interconnectedness between these markets by employing a dynamic conditional correlation model and a wavelet transform framework. Their discerned estimates indicate that the markets of Bitcoin, Litecoin, Ethereum and Bitcoin Cash have only momentous long-run perseverance, lingering and spillover effects of shocks’ sway on conditional correlations. However, there is momentous short- and long-run perseverance, lingering and spillover effects in the case of Ripple XRP. The wavelet coherence analysis also confirms these results by indicating a bidirectional short-run causal relation and a long-run positive comovement between liquid returns and futures returns of these cryptocurrencies. These discernments may help investors, portfolio managers and policymakers to enhance hedging effectiveness through optimal portfolio allocation and monitor financial contagion to attain and sustain financial stability in economies.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192247","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 : 2023-09-09DOI: 10.1177/09722629231185464
Raju Majumdar, Ankur Mittal, Shikha Bhardwaj
The primary purpose of the research is to identify the challenges faced by Indian urban women micro-entrepreneurs in their entrepreneurial journey. The challenges presented by the external environment as well as the deficiencies inherent in their skill sets are analysed to ascertain the most important barriers that continue to impede their growth. Findings indicate that limited funding and balancing responsibilities are the two major challenges faced by women entrepreneurs (WEs); the former being most important for micro-entrepreneurs engaged in manufacturing, while the latter poses the biggest challenge for those engaged in the services sector. Regarding skills, findings indicate that WEs appear to be least skilled in performing finance and information technology-related roles. To the extent that perceived skill gaps and challenges faced are closely related, the findings of this research present an alternative interpretation of the primacy of funding constraints faced by WEs.
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Pub Date : 2023-09-02DOI: 10.1177/09722629231182853
Shipra Pandey, Jayashree Mahesh
Given the significance of human resources and people management in the current dynamic environment, this article systematically identifies, synthesizes and analyses the research published on various themes and trends in people-centric human resource management (HRM). The systematic literature review method proposed by Denyer and Tranfield (2009) has been adopted for this study. The 227 studies have been categorized according to themes and analysed to understand research trends, consequences, limitations and potential future research areas. The analysis of the literature reveals that HRM has become more strategic than transactional in its research. Researchers are concentrating on analysing and improving human resource methods, which have an interdisciplinary impact. The focus is more on people-oriented HRM like ‘employee well-being’, ‘employee voice’, ‘work–family balance,’ etc., suggesting that organizations consider people as a source of competitive advantage. The findings also present a clear route for future research in this domain. The major contribution of this article is in identifying holistic views of themes, variables and theories paramount to people-centric HRM research. Insights identified in this study would enable future researchers to design their conceptual and empirical studies on emerging and relevant topics.
{"title":"Emerging Trends in People-Centric Human Resource Management: A Systematic Literature Review","authors":"Shipra Pandey, Jayashree Mahesh","doi":"10.1177/09722629231182853","DOIUrl":"https://doi.org/10.1177/09722629231182853","url":null,"abstract":"Given the significance of human resources and people management in the current dynamic environment, this article systematically identifies, synthesizes and analyses the research published on various themes and trends in people-centric human resource management (HRM). The systematic literature review method proposed by Denyer and Tranfield (2009) has been adopted for this study. The 227 studies have been categorized according to themes and analysed to understand research trends, consequences, limitations and potential future research areas. The analysis of the literature reveals that HRM has become more strategic than transactional in its research. Researchers are concentrating on analysing and improving human resource methods, which have an interdisciplinary impact. The focus is more on people-oriented HRM like ‘employee well-being’, ‘employee voice’, ‘work–family balance,’ etc., suggesting that organizations consider people as a source of competitive advantage. The findings also present a clear route for future research in this domain. The major contribution of this article is in identifying holistic views of themes, variables and theories paramount to people-centric HRM research. Insights identified in this study would enable future researchers to design their conceptual and empirical studies on emerging and relevant topics.","PeriodicalId":44860,"journal":{"name":"Vision-The Journal of Business Perspective","volume":"25 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2023-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87267284","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}
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