Qaisar ALI, Asma SALMAN, Hakimah YAACOB, Zaki ZAINI, Rose ABDULLAH /
Journal of Asian Finance, Economics and Business Vol 7 No 7 (2020) 001 – 013 1
Print ISSN: 2288-4637 / Online ISSN 2288-4645
doi:10.13106/jafeb.2020.vol7.no7.001
1
First Author. Faculty of Islamic Economics and Finance,
University Islam Sultan Sharif Ali, Brunei Darussalam.
Email: aliqaisar21@gmail.com
2
Corresponding Author. Department of Accounting, Finance
and Economics, College of Business Administration, American
University in the Emirates (AUE) [Postal Address: Dubai
International Academic City, Block 6 & 7, United Arab Emirates]
Email: asma.salman@aue.ae
3
Faculty of Islamic Economics and Finance, university Islam Sultan
Sharif Ali, Brunei Darussalam. Email: hakimahunissa@gmail.com
4
Faculty of Islamic Economics and Finance, university Islam Sultan
Sharif Ali, Brunei Darussalam. Email: zaki.zaini@unissa.edu.bn
5
Faculty of Islamic Economics and Finance, university Islam Sultan
Sharif Ali, Brunei Darussalam. Email: rose.abdullah@unissa.edu.bn
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Does Big Data Analytics Enhance Sustainability and Financial
Performance? The Case of ASEAN Banks
Qaisar ALI
1
, Asma SALMAN
2
, Hakimah YAACOB
3
, Zaki ZAINI
4
, Rose ABDULLAH
5
Received: April 07, 2020 Revised: May 10, 2020 Accepted: June 08, 2020
Abstract
This study analyzes the key drivers (commitment, integration of big data, green supply chain management, and green human resource
practices) of sustainable capabilities and the infuence to which these sustainable capabilities impact the banks’ environmental and fnancial
performance. Additionally, this study analyzes the impact of green management practices on the integration of big data technology with
operations. The theory of dynamic capability was deployed to propose and empirically test the conceptual model. Data was collected
through a self-administrated survey questionnaire from 319 participants employed at 35 banks located in six ASEAN countries. The fndings
indicate that big data analytics strategies have an impact on internal processes and banks’ sustainable and fnancial performance. This
study indicates that banks committed towards proper data monitoring of its clients achieve operational efciency and sustainability goals.
Moreover, our results confrm that banks practising green innovation strategies experience better environmental and economic performance
as the employees of these banks have received advance green human resource training. Finally, our study found that internal and external
green supply chain management practices have a positive impact on banks’ environmental and fnancial performance, which confrms that
ASEAN banks contributing in reduction of environmental impact through its operations will ultimately experience increased fnancial
performance.
Key Words: Sustainability, ASEAN, Banks, Big Data Analytics, Financial Performance, Green Management
JEL Classifcation Code: E58, G21, Q5
1. Introduction
United Nations’ 2030 Agenda for sustainable development
and the global commitment to leave no one behind requires
collecting, processing, and disseminating an unprecedented
amount of data, including disaggregated data, for effective
policy design, monitoring, and evaluation of progress
(United Nations Report, 2019). The advent of big data (BD)
has brought solace for humans and societies in numerous
ways; especially, modern-day uncertainties confronted by
human beings can effectively be reduced using BD (Allam,
2020). BD is going to stay, however, its environmental and
social (E&S) consequences and the sustainability of BD
needs further investigation. Corbett (2018) contends that the
revelation of BD revolution has created new opportunities
by increasing the awareness of E&S impacts on supply
chain and the concomitant potential to improve along these
dimensions.
BD potentially impacts the businesses that warrant
an analysis of the implications vis-à-vis organizational
response, prospects, and challenges of environmentally-
sustainable business operations (Seles, de Sousa Jabbour,
Jabbour, de Camargo Fiorini, Mohd- Yusoff, & Thome,
2018). The traditional methods to acquire, access and analyze
BD have become obsolete as these methods do not fit with