Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective
This paper aims to investigate the role of big data analytical (technological, management, talent) capabilities of family businesses and examines the dual aspects of family leadership focus and family members’ concerns to sustain the business. Further, the study explains the generational transition,...
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2-s2.0-85204578976 Sawangchai A.; Khalid R.; Raza M.; Alshuaibi M.S.; Valeri M.; kasuma J. Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective 2024 Journal of Family and Economic Issues 10.1007/s10834-024-09984-6 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204578976&doi=10.1007%2fs10834-024-09984-6&partnerID=40&md5=2fe7ea7628e9d2b9c31572afc0ef7f19 This paper aims to investigate the role of big data analytical (technological, management, talent) capabilities of family businesses and examines the dual aspects of family leadership focus and family members’ concerns to sustain the business. Further, the study explains the generational transition, innovation, and tradition paradox and proposes a solution to maintain the family legacy. Family businesses are crucial sources of wealth in Southeast Asian countries and 80% of Thailand’s family businesses are owned by second or third generations and so on. The data is collected from Phuket, Thailand which is a regional hub of family businesses. The respondents of study 203 businesses were chosen for data collection and further interpreted through Smart PLS 4.0. The results found that big data analytics management capabilities are significantly associated with the innovation and learning performance of family members and sustainable family business excellence. specifically, talent capabilities and technological capabilities have an insignificant association with a direct relationship with sustainable family business excellence. Furthermore, the moderating role of family members’ adaptability to change is particularly insignificant, associated with big data analytics technological capabilities and sustainable family business excellence. The study analysis revealed mixed findings and generally advocated the need for big data implications in a family business. Most literature focused on non-family businesses, and this study is one of the pioneering studies that discuss big data integration in a family business as a driver of sustainable excellence. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer 10580476 English Article |
author |
Sawangchai A.; Khalid R.; Raza M.; Alshuaibi M.S.; Valeri M.; kasuma J. |
spellingShingle |
Sawangchai A.; Khalid R.; Raza M.; Alshuaibi M.S.; Valeri M.; kasuma J. Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective |
author_facet |
Sawangchai A.; Khalid R.; Raza M.; Alshuaibi M.S.; Valeri M.; kasuma J. |
author_sort |
Sawangchai A.; Khalid R.; Raza M.; Alshuaibi M.S.; Valeri M.; kasuma J. |
title |
Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective |
title_short |
Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective |
title_full |
Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective |
title_fullStr |
Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective |
title_full_unstemmed |
Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective |
title_sort |
Sustainability and Technology Go Hand in Hand to Achieve Excellence in Thai Family Businesses: A Big Data Analytical Perspective |
publishDate |
2024 |
container_title |
Journal of Family and Economic Issues |
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container_issue |
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doi_str_mv |
10.1007/s10834-024-09984-6 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204578976&doi=10.1007%2fs10834-024-09984-6&partnerID=40&md5=2fe7ea7628e9d2b9c31572afc0ef7f19 |
description |
This paper aims to investigate the role of big data analytical (technological, management, talent) capabilities of family businesses and examines the dual aspects of family leadership focus and family members’ concerns to sustain the business. Further, the study explains the generational transition, innovation, and tradition paradox and proposes a solution to maintain the family legacy. Family businesses are crucial sources of wealth in Southeast Asian countries and 80% of Thailand’s family businesses are owned by second or third generations and so on. The data is collected from Phuket, Thailand which is a regional hub of family businesses. The respondents of study 203 businesses were chosen for data collection and further interpreted through Smart PLS 4.0. The results found that big data analytics management capabilities are significantly associated with the innovation and learning performance of family members and sustainable family business excellence. specifically, talent capabilities and technological capabilities have an insignificant association with a direct relationship with sustainable family business excellence. Furthermore, the moderating role of family members’ adaptability to change is particularly insignificant, associated with big data analytics technological capabilities and sustainable family business excellence. The study analysis revealed mixed findings and generally advocated the need for big data implications in a family business. Most literature focused on non-family businesses, and this study is one of the pioneering studies that discuss big data integration in a family business as a driver of sustainable excellence. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. |
publisher |
Springer |
issn |
10580476 |
language |
English |
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Article |
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scopus |
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Scopus |
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1812871795162742784 |