Big data (BD) analytics has been increasingly gaining attraction in both practice and theory in light of its opportunities, barriers and expected benefits. In particular, emerging economics view big ...data analytics as having great importance despite the fact that it has been in a constant struggle with the barriers that prevent its adoption. Thus, this study primarily attempted to determine the drivers of big data analytics in the context of a developing economy, Jordan. The study examined the influence of technological, organizational and environmental factors on big data adoption in the Jordanian SMEs context, using PLS-SEM for the analysis. The empirical results revealed that the relative advantage, complexity, security, top management support, organizational readiness and government support influence the adoption of BD, whilst pressure of competition and compatibility appeared to be of insignificant influence. The findings are expected to contribute to enterprise management and strategic use of data analytics in the present dynamic market environment, for both researcher and practitioner circles concerned with the adoption of big data in developing countries.
This study argues that.•BDA capability and BI&A are positively related to data driven insights, decision-making quality.•BDA capability and BI&A are positively related to circular economy ...performance.•Data driven insights are positively related to decision-making quality.•Decision making quality influences circular economy performance.•Data driven insights mediates the relationship of BI&A and decision-making quality.
Big data analytics (BDA) is a revolutionary approach for sound decision-making in organizations that can lead to remarkable changes in transforming and supporting the circular economy (CE). However, extant literature on BDA capability has paid limited attention to understanding the enabling role of data-driven insights for supporting decision-making and, consequently, enhancing CE performance. We argue that firms drive decision-making quality through data-driven insights, business intelligence and analytics (BI&A), and BDA capability. In this study, we empirically investigated the association of BDA capability with CE performance and examined the mediating role of data-driven insights in the relationship between BDA capability and decision-making. Data were collected from 109 Czech manufacturing firms, and partial least squares structural equation modeling was applied to analyze the data. The results reveal that BDA capability and BI&A are positively associated with decision-making quality. This effect is stronger when the manufacturer utilizes data-driven insights. The results demonstrate that BDA capability drives decision-making quality in organizations, and data-driven insights do not mediate this relationship. BI&A is associated with decision-making quality through data-driven insights. These findings offer important insights to managers, as they can act as a reference point for developing data-driven insights with the CE paradigm in organizations.
•Novel framework to align activities across information systems and the circular economy.•Digital circular economy research agenda and implications for practitioners.•Guidance for aligning digital ...and sustainable strategies.•Knowledge base of 100 theorized and real-world smart circular strategies.•Digital circular economy as a cornerstone of a sustainable society.
Digital technologies (DTs), such as the Internet of Things (IoT), big data, and data analytics, are considered essential enablers of the circular economy (CE). However, as both CE and DTs are emerging fields, there exists little systematic guidance on how DTs can be applied to capture the full potential of circular strategies for improving resource efficiency and productivity. Furthermore, there is little insight into the supporting business analytics (BA) capabilities required to accomplish this. To address this gap, this paper conducts a theory- and practice-based review, resulting in the Smart CE framework that supports translating the circular strategies central to the goals of manufacturing companies in contributing the United Nation’s (UN) 12th Sustainable Development Goal, that is, “sustainable consumption and production,” into the BA requirements of DTs. Both scholars and practitioners may find the framework useful to (1) create a common language for aligning activities across the boundaries of disciplines such as information systems and the CE body of knowledge, and (2) identify the gap between the current and entailed BA requirements and identify the strategic initiatives needed to close it. Additionally, the framework is used to organize a database of case examples to identify some best practices related to specific smart circular strategies.
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