Embracing Big Data Capabilities: Toward Achieving Green E-Procurement in Public Sector
Bader K. AlNuaimi
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Public procurements can be instrumental in enhancing sustainable development worldwide by advancing green procurement, as they are a substantial element in many countries‘ national economies. Due to the recent development of e-procurement (EP) platforms, governments and suppliers can now easily and transparently interact with each other to construct, disseminate, and pilot green public procurement (GPP) policies and improve environmental performance (ENP). However, there are many types of EP platforms, and not all of them provide the flexibility necessary for the efficient integration of GPP. For this reason, recent studies suggest that the next set of improvements in EP systems should enable the integration of operational data and the adoption of big data technology. The emerging big data technology and concepts can offer public procurement with a range of benefits—such as simplifying life cycle assessment, spend analysis, and transparency. Recent studies in big data analytics capabilities (BDAC) have shown that it has the potential to transform and innovate the traditional EP system into green EP. Although big data technology has become more available for organizations, big data can be of limited value if the decision maker and employees within an organization are unable to understand the big data analysis. Hence, the aim of this study was to contribute to the literature related to resource-based view (RBV) theory, natural-resource-based view (NRBV) theory, and the dynamic capability (DC) framework, particularly regarding the adoption of big data technology to achieve GPP. Drawing upon this theoretical foundation, the purpose of this study was twofold: (1) to examine the relationships among the BDAC, specifically technological v capabilities (TC) and human capabilities (HC) and EP under the moderating effect of a data driven culture (DDC); and (2) to identify what, if any, direct and indirect effects the TC and HC have on ENP under the mediation influence of EP. The study used a constructive positivism quantitative research method by sending out a carefully developed questionnaire survey to a sample group consisting of procurement professionals from the United Arab Emirates (UAE) government sector. After a promising pilot study was completed, the data was then collected from 216 participants. IBM SPSS was used to perform regression analysis of the relationship between the variables to test and verify the research hypotheses. In addition, Hayes PROCESS SPSS macro was used for moderation and mediation testing. The primary results determined that TC and HC have a significant influence on EP. However, DDC does not have a significant moderation effect on the relationship between both big data capabilities (TC and HC) and EP. The findings also determined that EP has a positive influence on ENP, and when EP was introduced as a mediator between the relationship of TC and ENP, ENP improved even further. However, EP has no mediation effect on the relationship between TC and ENP. This study has several theoretical implications. Most importantly, it is among the first studies to assess the impact of big data capabilities (TC and HC) on ENP and EP and to evaluate the moderation impact of DDC on the relationship between big data capabilities and EP. In addition, the study utilized the DC framework to view the construct of big data capabilities as vi multidimensional, which integrates the technical, human, and cultural perspectives instead of viewing big data capabilities as a technical construct. Lastly, it contributes to the emerging literature on big data by advancing the theoretical understanding of BDAC in relation to ICT based procurement and environmental science via the DC framework. This study offers many practical contributions. Public organizations that aim to implement big data in their procurement function must focus on assuring the interoperability of data infrastructure with other systems and applications and the availability of accessible data for analysis. At the same time, organizations must focus on training management and employees on data technology, analysis, and developing technical and relational knowledge to develop skilled procurement analysts. Overall, this study‘s findings offer a more advanced understanding of the impact of big data capabilities on EP, thereby addressing the crucial questions of how and when these capabilities can enhance environmental sustainability in procurement and supply chains. The study limitations were linked to four major areas associated with the limited sample size and scope of the study in terms of constructs and country setting, in addition to the limitation due to the use of a cross-sectional research design for data collection.