Embracing the Big Data Analytics Capabilities on Firm’s Performance in the Digital Transformation Era of Family-Owned Businesses: A Study of the Fashion Industry of Pakistan

Authors

  • Amna Aslam Department of Management Studies, Bahria Business School, Bahria University, Islamabad, Pakistan
  • Asif Khurshid Associate Professor, Department of Management Studies, Bahria Business School, Bahria University, Islamabad, Pakistan.

Keywords:

Big Data Analytics Capabilities, Strategic Innovation, Firm Performance and Family- Owned Businesses.

Abstract

In today’s times, the advancements in the technological world have been growing day by day since the upcoming of the several breakthrough innovations such as innovative tosols and techniques which helps businesses to upgrade their practices with help of artificial intelligence, big data analytics, cloud computing and business intelligence which has been shifting the business paradigms (Zeng & Khan, 2018; Sheng et al., 2019). However, big data analytics is also playing a huge role in these times as it is found as a true game changer in today’s businesses which increases the strategic as well as operation performances of the firm by uplifting the efficiency in the firm decision making (Wamba, Gunasekaran, Akter, Ren, Fan, Dubey & Childe, 2017). Moreover, researchers claim that big data analytics can be a major indicator and driver of strategic innovation in the firm which results as a high profitability in the firm’s performance. (Zhang & Yuan, 2023).Moreover, big data analytics supports the instincts of the management and creativity through the prompt and continuous availability of real-time information (Cheah, 2017). Moreover, researchers claim that big data analytics can be a major indicator and driver of strategic innovation in the firm which results as a high profitability in the firm’s performance. (Zhang & Yuan, 2023). Additionally, innovation takes place based on the data-driven models for decision making allows organizations to develop and design innovative products and services which may address the consumer needs as well as minimize the innovation-based risk (Ji, Yu, Tan, Kumar & Gupta., 2024).In this study the data was collected through family-owned business managers. The sample size of the study was 236 managers from textile industry of family-owned business via using purposive sampling technique. This study was built on quantitate approach where data was collected via surveys. For the analysis purpose the data was analyzed via PLS-SEM for quantitative data Furthermore, the findings of this research study indicates that big data analytics capabilities have a positive effect on the strategic innovation of the firm which increases the firm’s performance such as market performance as well as financial performance of an organization. Technological transformation plays an important role as it enhance the business practices in economy where the transitions of business can positively impact in a developing county such as Pakistan.

References

Anderson, R. C., & Reeb, D. M. (2004). Board composition: Balancing family influence in S&P 500 firms. Administrative science quarterly, 49(2), 209-237.

Astrachan, J. H., & Shanker, M. C. (2003). Family businesses’ contribution to the US economy: A closer look. Family business review, 16(3), 211-219.

Aversa, P., Haefliger, S., Hueller, F., & Reza, D. G. (2021). Customer complementarity in the digital space: Exploring Amazon’s business model diversification. Long Range Planning, 54(5), 101985.

Bell, E., Bryman, A., & Harley, B. (2022). Business research methods. Oxford university press.

Benzidia, S., Bentahar, O., Husson, J., & Makaoui, N. (2024). Big data analytics capability in healthcare operations and supply chain management: the role of green process innovation. Annals of Operations Research, 333(2), 1077-1101.

Bradlow, E. T., Gangwar, M., Kopalle, P., & Voleti, S. (2017). The role of big data and predictive analytics in retailing. Journal of retailing, 93(1), 79-95.

Carrillo-Carrillo, F., & Alcalde-Heras, H. (2020). Modes of innovation in an emerging economy: a firm-level analysis from Mexico. Innovation, 22(3), 334-352..

Che, Y., Li, Y., Fam, K. S., & Bai, X. (2018). Buyer–seller relationship, sales effectiveness and sales revenue: a social network perspective. nankai Business review international, 9(4), 414-436.

Cheah, R., Teo, F. Y., & Goh, B. H. A Big Data Approach To Water Resources Engineering In Malaysia.

Ciampi, F., Demi, S., Magrini, A., Marzi, G., & Papa, A. (2021). Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation. Journal of Business Research, 123, 1-13.

Cillo, V., Petruzzelli, A. M., Ardito, L., & Del Giudice, M. (2019). Understanding sustainable innovation: A systematic literature review. Corporate Social Responsibility and Environmental Management, 26(5), 1012-1025.

Covin, J. G., & Miller, D. (2014). International entrepreneurial orientation: Conceptual considerations, research themes, measurement issues, and future research directions. Entrepreneurship theory and practice, 38(1), 11-44.

Covin, J. G., & Slevin, D. P. (1989). Strategic management of small firms in hostile and benign environments. Strategic management journal, 10(1), 75-87.

De Massis, A., Audretsch, D., Uhlaner, L., & Kammerlander, N. (2018). Innovation with Limited Resources: Management Lessons from the G erman M ittelstand. Journal of Product Innovation Management, 35(1), 125-146.

Dekimpe, M. G. (2020). Retailing and retailing research in the age of big data analytics. International Journal of Research in Marketing, 37(1), 3-14.

Dubey, R., Gunasekaran, A., Papadopoulos, T., Childe, S. J., Shibin, K. T., & Wamba, S. F. (2017). Sustainable supply chain management: framework and further research directions. Journal of cleaner production, 142, 1119-1130.

Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big Data consumer analytics and the transformation of marketing. Journal of business research, 69(2), 897-904.

Ferasso, M., Beliaeva, T., Kraus, S., Clauss, T., & Ribeiro‐Soriano, D. (2020). Circular economy business models: The state of research and avenues ahead. Business strategy and the environment, 29(8), 3006-3024.

Finney, R. Z., Lueg, J. E., & Campbell, N. D. (2008). Market pioneers, late movers, and the resource-based view (RBV): A conceptual model. Journal of Business Research, 61(9), 925-932.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.

Gandomi, A. H., Chen, F., & Abualigah, L. (2022). Machine learning technologies for big data analytics. Electronics, 11(3), 421.

Gedajlovic, E., Carney, M., Chrisman, J. J., & Kellermanns, F. W. (2012). The adolescence of family firm research: Taking stock and planning for the future. Journal of management, 38(4), 1010-1037.

George, G., McGahan, A. M., & Prabhu, J. (2012). Innovation for inclusive growth: Towards a theoretical framework and a research agenda. Journal of management studies, 49(4), 661-683.

Giglio, S., Kelly, B., & Xiu, D. (2022). Factor models, machine learning, and asset pricing. Annual Review of Financial Economics, 14(1), 337-368.

Grant, R. M. (1991). The resource-based theory of competitive advantage: implications for strategy formulation. California management review, 33(3), 114-135.

Habbershon, T. G., & Williams, M. L. (1999). A resource-based framework for assessing the strategic advantages of family firms. Family business review, 12(1), 1-25.

Haenlein, M., & Kaplan, A. M. (2004). A beginner's guide to partial least squares analysis. Understanding statistics, 3(4), 283-297.

Hamel, G., & Prahalad, C. K. (1990). Strategic intent. Mckinsey quarterly, (1), 36-61.

Han, C.; Gao, S. A chain multiple mediation model linking strategic, management, and technological innovations to firm competitiveness. Bras. Gestão Negócios 2020, 21, 879–905.

Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M., Singh, H., Teece, D., & Winter, S. G. (2009). Dynamic capabilities: Understanding strategic change in organizations. John Wiley

Jaskiewicz, P., Combs, J. G., & Rau, S. B. (2015). Entrepreneurial legacy: Toward a theory of how some family firms nurture transgenerational entrepreneurship. Journal of business venturing, 30(1), 29-49.

Javid, A. Y. (2012). Impact of family ownership concentration on the firm's performance (evidence from Pakistani capital market). Journal of Asian Business Strategy, 2(3), 63.

Ji, G., Yu, M., Tan, K. H., Kumar, A., & Gupta, S. (2024). Decision optimization in cooperation innovation: the impact of big data analytics capability and cooperative modes. Annals of Operations Research, 333(2), 871-894.

Johnson, J. S., Friend, S. B., & Lee, H. S. (2017). Big data facilitation, utilization, and monetization: Exploring the 3Vs in a new product development process. Journal of Product Innovation Management, 34(5), 640-658.

Johnson, J. S., Friend, S. B., & Lee, H. S. (2017). Big data facilitation, utilization, and monetization: Exploring the 3Vs in a new product development process. Journal of Product Innovation Management, 34(5), 640-658.

Ketchen Jr, D. J., Hult, G. T. M., & Slater, S. F. (2007). Toward greater understanding of market orientation and the resource‐based view. Strategic management journal, 28(9), 961-964.

Kline, R. B. (1998). Software review: Software programs for structural equation modeling: Amos, EQS, and LISREL. Journal of psychoeducational assessment, 16(4), 343-364.

Kraus, S., Burtscher, J., Vallaster, C., & Angerer, M. (2018). Sustainable entrepreneurship orientation: Reflection on status-quo research on factors facilitating responsible managerial practices∗. In Sustainable Entrepreneurship (pp. 75-98). Routledge.

Li, Y., Zhang, Y., Timofte, R., Van Gool, L., Yu, L., Li, Y., ... & Wang, X. (2023). NTIRE 2023

challenge on efficient super-resolution: Methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 1922-1960).

Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the entrepreneurial orientation construct and linking it to performance. Academy of management Review, 21(1), 135-172.

Lutfi, A., Alsyouf, A., Almaiah, M. A., Alrawad, M., Abdo, A. A. K., Al-Khasawneh, A. L., ... & Saad, M. (2022). Factors influencing the adoption of big data analytics in the digital transformation era: Case study of Jordanian SMEs. Sustainability, 14(3), 1802.

Madhavaram, S., & Hunt, S. D. (2008). The service-dominant logic and a hierarchy of operant resources: developing masterful operant resources and implications for marketing strategy. Journal of the academy of marketing science, 36, 67-82.

Majid, A., Yasir, M., Yasir, M., & Yousaf, Z. (2021). Network capability and strategic performance in SMEs: The role of strategic flexibility and organizational ambidexterity. Eurasian Business Review, 11(4), 587-610.

Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2018). Business intelligence and big data in hospitality and tourism: a systematic literature review. International Journal of Contemporary Hospitality Management, 30(12), 3514-3554.

Maroufkhani, P., Tseng, M. L., Iranmanesh, M., Ismail, W. K. W., & Khalid, H. (2020). Big data analytics adoption: Determinants and performances among small to medium-sized enterprises. International journal of information management, 54, 102190.

Masulis, R. W., Pham, P. K., & Zein, J. (2011). Family business groups around the world: Financing advantages, control motivations, and organizational choices. The Review of Financial Studies, 24(11), 3556-3600.

McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: the management revolution. Harvard business review, 90(10), 60-68.

Meroño-Cerdán, A. L., López-Nicolás, C., & Molina-Castillo, F. J. (2018). Risk aversion, innovation and performance in family firms. Economics of Innovation and new technology, 27(2), 189-203.

Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics and firm performance: Findings from a mixed-method approach. Journal of business research, 98, 261- 276.

Mikalef, P., Framnes, V. A., Danielsen, F., Krogstie, J., & Olsen, D. (2017). Big data analytics capability: antecedents and business value.

Mikalef, P., Pappas, I. O., Krogstie, J., & Giannakos, M. (2018). Big data analytics capabilities: a systematic literature review and research agenda. Information systems and e-business management, 16, 547-578.

Mikalef, P., Pappas, I. O., Krogstie, J., & Giannakos, M. (2018). Big data analytics capabilities: a systematic literature review and research agenda. Information systems and e-business management, 16, 547-578.

Miller, D. (2011). Miller (1983) revisited: A reflection on EO research and some suggestions for the future. Entrepreneurship theory and practice, 35(5), 873-894.

Miller, D., & Le Breton–Miller, I. (2011). Governance, social identity, and entrepreneurial orientation in closely held public companies. Entrepreneurship Theory and practice, 35(5), 1051- 1076.

Morgan, N. A., Vorhies, D. W., & Mason, C. H. (2009). Market orientation, marketing capabilities, and firm performance. Strategic management journal, 30(8), 909-920.

Muhammad, A., Yu, C. K., Qadir, A., Ahmed, W., Yousuf, Z., & Fan, G. (2022). Big data analytics capability as a major antecedent of firm innovation performance. The International Journal of Entrepreneurship and Innovation, 23(4), 268-279.

Nath, P., Nachiappan, S., & Ramanathan, R. (2010). The impact of marketing capability, operations capability and diversification strategy on performance: A resource-based view. Industrial Marketing Management, 39(2), 317-329.

Ngo, L. V., & O'Cass, A. (2009). Creating value offerings via operant resource-based capabilities. Industrial marketing management, 38(1), 45-59.

O'Cass, A., & Weerawardena, J. (2010). The effects of perceived industry competitive intensity and marketing-related capabilities: Drivers of superior brand performance. Industrial Marketing Management, 39(4), 571-581.

Olabode, O. E., Boso, N., Hultman, M., & Leonidou, C. N. (2022). Big data analytics capability and market performance: The roles of disruptive business models and competitive intensity. Journal of Business Research, 139, 1218-1230.

Paiola, M., & Gebauer, H. (2020). Internet of things technologies, digital servitization and business model innovation in BtoB manufacturing firms. Industrial Marketing Management, 89, 245-264.

Pejic Bach, M., Aleksic, A., & Merkac-Skok, M. (2018). Examining determinants of entrepreneurial intentions in Slovenia: applying the theory of planned behaviour and an innovative cognitive style. Economic research-Ekonomska istraživanja, 31(1), 1453-1471.

Pereira, L. S., Paredes, P., Hunsaker, D. J., López-Urrea, R., & Shad, Z. M. (2021). Standard single and basal crop coefficients for field crops. Updates and advances to the FAO56 crop water requirements method. Agricultural Water Management, 243, 106466.

Pieroni, M. P., McAloone, T. C., & Pigosso, D. C. (2019). Business model innovation for circular economy and sustainability: A review of approaches. Journal of cleaner production, 215, 198- 216.

Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20, 209-222.

Poza, E. J., & Daugherty, M. S. (2013). Family-owned business enterprises. Washington: South- Western Cengage Learning.

Pugliese, A., & Wenstøp, P. Z. (2007). Board members’ contribution to strategic decision-making in small firms. Journal of Management & Governance, 11, 383-404.

Qayyoum, H., Raza, M.R., Sadaf, A. (2023). Gender Differences in Binge-Watching by Teenagers: A Uses and Gratification Analysis. Journal of Peace, Development, and Communication.

Quinn, M., Hiebl, M. R., Moores, K., & Craig, J. B. (2018). Future research on management accounting and control in family firms: suggestions linked to architecture, governance, entrepreneurship and stewardship. Journal of Management Control, 28, 529-546.

Ranjan, J., & Foropon, C. (2021). Big data analytics in building the competitive intelligence of organizations. International Journal of Information Management, 56, 102231.

Rialti, R., Marzi, G., Silic, M., & Ciappei, C. (2018). Ambidextrous organization and agility in big data era: The role of business process management systems. Business process management journal, 24(5), 1091-1109.

Raza, H., Raza., M. R (2021). A study of blockchain technology, bitcoin, and other cryptocurrencies as means of money laundering, frauds, and scams. Global Media and Social Sciences Research Journal (GMSSRJ).

Saunders, M. N. (2012). Choosing research participants. Qualitative organizational research: Core methods and current challenges, 35-52.

Schlegelmilch, B. B., Diamantopoulos, A., & Kreuz, P. (2003). Strategic innovation: the construct, its drivers and its strategic outcomes. Journal of strategic marketing, 11(2), 117-132.

Sheng, V. S., & Zhang, J. (2019, July). Machine learning with crowdsourcing: A brief summary of the past research and future directions. In Proceedings of the AAAI conference on artificial intelligence (Vol. 33, No. 01, pp. 9837-9843).

Sirmon, D. G., & Hitt, M. A. (2003). Managing resources: Linking unique resources, management, and wealth creation in family firms. Entrepreneurship theory and practice, 27(4), 339-358.

Sun, Y., Li, L., Chen, Y., & Kataev, M. Y. (2021). An empirical study on innovation ecosystem, technological trajectory transition, and innovation performance. Journal of Global Information Management (JGIM), 29(4), 148-171.

Tahir, S. H., & Sabir, H. M. (2014). Impact of family ownership on market value of a firm: A comparative analysis of family and non-family companies listed at karachi stock exchange (Pakistan). International Journal of Management and Sustainability, 3(12), 673-683.

Teece, D. J. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strategic management journal, 28(13), 1319-1350.

Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of business research, 70, 356-365.

Wang, Y., Yuan, C., Zhang, S., & Wang, R. (2022). Moderation in all things: Industry-university- research alliance portfolio configuration and SMEs’ innovation performance in China. Journal of Small Business Management, 60(6), 1516-1544.

Xu, N., Price, B., Cohen, S., & Huang, T. (2017). Deep image matting. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 2970-2979).

Yousaf, I., Ali, S., & Hassan, A. (2019). Effect of family control on corporate dividend policy of firms in Pakistan. Financial Innovation, 5(1), 42.

Zattoni, A., Gnan, L., & Huse, M. (2015). Does family involvement influence firm performance? Exploring the mediating effects of board processes and tasks. Journal of Management, 41(4), 1214-1243.

Zellweger, T. (2017). Managing the family business: Theory and practice. Edward Elgar Publishing.

Zeng, J., & Khan, Z. (2019). Value creation through big data in emerging economies: The role of resource orchestration and entrepreneurial orientation. Management Decision, 57(8), 1818-1838.

Downloads

Published

30.11.2024

How to Cite

Embracing the Big Data Analytics Capabilities on Firm’s Performance in the Digital Transformation Era of Family-Owned Businesses: A Study of the Fashion Industry of Pakistan. (2024). PAKISTAN JOURNAL OF LAW, ANALYSIS AND WISDOM, 3(11), 83-98. https://pjlaw.com.pk/index.php/Journal/article/view/v3i11-83-98

Similar Articles

1-10 of 203

You may also start an advanced similarity search for this article.