(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Technology and Engineering Exploration (IJATEE)

ISSN (Print):2394-5443    ISSN (Online):2394-7454
Volume-8 Issue-80 July-2021
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Paper Title : The mediating role of big data analytics in enhancing firms’ commitment to sustainability
Author Name : Wail El Hilali, Abdellah El Manouar and Mohammed Abdou Janati Idrissi
Abstract :

The era of big data has overturned the classical model of how businesses work. Companies are now dealing with data as one of their most valuable assets that fuels their digital strategies to overcome the competition. As the potential of big data analytics is endless, looking for any impact from this cutting-edge technology on sustainability could lead to new insights about this paradigm. This paper represents a quantitative study that included 41 Moroccan firms from diverse industries. By using a Partial Least Squares-Structural Equation Modeling (PLS-SEM) approach, the results showed that big data analytics may enhance companies’ commitment to sustainability (p-value =0) if the firm crafted the right digital strategy fuelled by data (p-value=0), established a data-driven decision-making culture (p-value =0.008), and acquired the right talents with soft skills (p-value = 0.029). Against all expectations, the results showed that technical skills do not play a significant role and do not boost the mediating role of big data regarding sustainability (p-value=0.124).

Keywords : Sustainability, Big data, Digital transformation, Digital capabilities.
Cite this article : Hilali WE, Manouar AE, Idrissi MA. The mediating role of big data analytics in enhancing firms’ commitment to sustainability. International Journal of Advanced Technology and Engineering Exploration. 2021; 8(80):932-944. DOI:10.19101/IJATEE.2021.874114.
References :
[1]https://www.ibm.com/cloud/blog/structured-vs-unstructured-data. Accessed 11 April 2021.
[2]Economist T. Data is giving rise to a new economy. The Economist. 2017.
[Google Scholar]
[3]Schmarzo B. Big data MBA: driving business strategies with data science. John Wiley & Sons; 2015.
[Google Scholar]
[4]https://www.forbes.com/sites/steveolenski/2015/03/19/big-data-solving-big-problems/?sh=2584f2cb5b8e. Accessed 11 April 2021.
[5]Howie T. The big bang: how the big data explosion is changing the world. The Microsoft Enterprise Insight Blog. [Internet]. 2013.
[Google Scholar]
[6]https://www.technologyreview.com/2013/10/03/82990/the-big-data-conundrum-how-to-define-it/. Accessed 11 April 2021.
[7]Gudivada VN, Baeza-yates R, Raghavan VV. Big data: promises and problems. Computer. 2015; 48(3):20-3.
[Google Scholar]
[8]https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/#components-of-a-big-data-architecture. Accessed 11 April 2021.
[9]https://www.wiley.com/en-us/Big+Data%3A+Concepts%2C+Technology%2C+and+Architecture-p-9781119701828. Accessed 11 April 2021.
[10]Gorelik A. The enterprise big data lake: delivering the promise of big data and data science. OReilly Media; 2019.
[Google Scholar]
[11]Walker R. From big data to big profits: success with data and analytics. Oxford University Press; 2015.
[Google Scholar]
[12]Idrissi MA. Big data for sustainability: a qualitative analysis. In 5th international conference on cloud computing and artificial intelligence: technologies and applications 2020 (pp. 1-4). IEEE.
[Crossref] [Google Scholar]
[13]Raut RD, Mangla SK, Narwane VS, Gardas BB, Priyadarshinee P, Narkhede BE. Linking big data analytics and operational sustainability practices for sustainable business management. Journal of Cleaner Production. 2019; 224:10-24.
[Crossref] [Google Scholar]
[14]Ali Q, Salman A, Yaacob H, Zaini Z, Abdullah R. Does big data analytics enhance sustainability and financial performance? the case of ASEAN banks. The Journal of Asian Finance, Economics, and Business. 2020; 7(7):1-13.
[Crossref] [Google Scholar]
[15]Dubey R, Gunasekaran A, Childe SJ, Papadopoulos T, Luo Z, Wamba SF, Roubaud D. Can big data and predictive analytics improve social and environmental sustainability? Technological Forecasting and Social Change. 2019; 144:534-45.
[Crossref] [Google Scholar]
[16]Lucivero F. Big data, big waste? a reflection on the environmental sustainability of big data initiatives. Science and Engineering Ethics. 2020; 26(2):1009-30.
[Crossref] [Google Scholar]
[17]Stahl BC, Wright D. Ethics and privacy in AI and big data: implementing responsible research and innovation. IEEE Security & Privacy. 2018; 16(3):26-33.
[Crossref] [Google Scholar]
[18]Cuquet M, Vega-gorgojo G, Lammerant H, Finn R. Societal impacts of big data: challenges and opportunities in Europe. arXiv preprint arXiv:1704.03361. 2017.
[Google Scholar]
[19]Marr B. Data strategy: how to profit from a world of big data, analytics and the internet of things. Kogan Page Publishers; 2017.
[Google Scholar]
[20]Missbach M, Staerk T, Gardiner C, Mccloud J, Madl R, Tempes M, et al. SAP and the internet of things. In SAP on the cloud 2016 (pp. 139-51). Springer, Berlin, Heidelberg.
[Crossref] [Google Scholar]
[21]Gardiner A, Aasheim C, Rutner P, Williams S. Skill requirements in big data: a content analysis of job advertisements. Journal of Computer Information Systems. 2018; 58(4):374-84.
[Crossref] [Google Scholar]
[22]CEPAL N. Big data and open data as sustainability tools: a working paper prepared by the economic commission for Latin America and the Caribbean. Economic Commission for Latin America and the Caribbean.2014.
[Google Scholar]
[23]Mckay E, Mohamad MB. Big data management skills: accurate measurement. Research and Practice in Technology Enhanced Learning. 2018; 13(1):1-24.
[Crossref] [Google Scholar]
[24]Etzion D, Aragon-correa JA. Big data, management, and sustainability: strategic opportunities ahead. Organization & Environment. 2016; 29(2): 147-55.
[Crossref] [Google Scholar]
[25]Singh SK, El-kassar AN. Role of big data analytics in developing sustainable capabilities. Journal of Cleaner Production. 2019; 213:1264-73.
[Crossref] [Google Scholar]
[26]https://www.cio.com/article/3571792/how-to-create-a-data-driven-culture.html. Accessed 11 April 2021.
[27]Bertels S, Papania L, Papania D. Embedding sustainability in organizational culture. a systematic review of the body of knowledge. London, Canada: Network for Business Sustainability. 2010.
[Google Scholar]
[28]Hilali WE, Manouar AE. Unlocking digitalizations possibilities: reaching sustainability by adopting the right digital strategy. International conference on wireless technologies, embedded and intelligent systems 2019 (pp. 1-74)
[29]Lacroux A. The advantages and limitations of the “partial least square” (PLS) method: an empirical illustration in the field of HRM. Human Resources Management Review. 2011; 2(80): 45-64.
[Google Scholar]
[30]Hair JJF, Sarstedt M, Hopkins L, Kuppelwieser VG. Partial least squares structural equation modeling (PLS-SEM): an emerging tool in business research. European Business Review. 2014; 26(2):106-21.
[Crossref] [Google Scholar]
[31]Richter NF, Sinkovics RR, Ringle CM, Schlägel C. A critical look at the use of SEM in international business research. International Marketing Review. 2016; 33(3):376-404.
[Crossref] [Google Scholar]
[32]Hair JF, Risher JJ, Sarstedt M, Ringle CM. When to use and how to report the results of PLS-SEM. European Business Review. 2019; 31(1):2-24.
[Google Scholar]
[33]Garson GD. Partial least squares. Regression and structural equation models.2016.
[Google Scholar]
[34]Gefen D, Straub D. A practical guide to factorial validity using PLS-graph: tutorial and annotated example. Communications of the Association for Information Systems. 2005; 16:91-109.
[Google Scholar]
[35]Hair JF, Ringle CM, Sarstedt M. Partial least squares structural equation modeling: rigorous applications, better results and higher acceptance. Long Range Planning. 2013; 46(1-2):1-12.
[Google Scholar]
[36]Henseler J, Ringle CM, Sarstedt M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science. 2015; 43(1):115-35.
[Crossref] [Google Scholar]
[37]Henseler J, Sarstedt M. Goodness-of-fit indices for partial least squares path modeling. Computational Statistics. 2013; 28(2):565-80.
[Crossref] [Google Scholar]
[38]Wetzels M, Odekerken-schröder G, Van OC. Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration. MIS Quarterly. 2009; 33(1):177-95.
[Crossref] [Google Scholar]
[39]Falk RF, Miller NB. A primer for soft modeling University of Akron Press. Akron, Ohio. 1992.
[Google Scholar]
[40]Cohen J. Statistical power analysis for the behavioral sciences. Academic Press; 2013.
[Google Scholar]