Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management

Abstract

Purpose Based on previous literature on big data analytics (BDA) and supply chain (SC) management, the purpose of this paper is to address the factors determining firms’ intention to adopt BDA in their daily operations. Specifically, this study classifies potential factors into four categories: technological, organizational, environmental factors, and SC characteristics. Design/methodology/approach Drawing on the innovation diffusion theory, a model consisted of direct technological and organizational factors as well as moderators was proposed. Subsequently, survey data was collected from 210 organizations. Then we used SPSS and SmartPLS to analyze the collected data. Findings The empirical results revealed that perceived benefits and top management support can significantly influence the adoption intention. And environmental factors, such as competitors’ adoption, government policy, and SC connectivity, can significantly moderate the direct relationships between driving factors and the adoption intention. Research limitations/implications Given the fact that big data (BD) usage in logistics and SC management is still in the start-up stage, the interpretations toward BDA might vary from different perspectives, thus causing some ambiguity in understanding the meaning and potential BD has. In addition, we collected data through questionnaires completed by IT managers, whose viewpoint may not fully represent that of an organization. Practical implications This paper tests the organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously. Social implications This research helps top managers assess the benefits of BDA as well as how to adjust their business strategy along the changes of environment and SC maturity. Originality/value This paper contributes to the literature of organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.

Deliberate storytelling in big data analytics adoption

“…The study suggests that deliberately told stories facilitate individual-level BDA usage due to the distinct focus of each story on resolving the BDA adoption challenges identified in the prior literature (Bose, 2009;Sivarajah et al, 2017;Verma et al, 2018;Wamba et al, 2015) by improving technology ease of use, data visualization, and interpretation and by ensuring data quality, data privacy, and security. Congruent with prior research on the enabling factors of BDA adoption in organizations (Caesarius & Hohenthal, 2018;Lai et al, 2018), this study demonstrates the importance of communicating stories about the benefits of BDA for both an organization and its customers, top management commitment, and competitive pressure in an organization to facilitate internal BDA adoption.…”

“…First, whereas existing BDA studies have paid considerable attention to organization-level BDA adoption (Caesarius & Hohenthal, 2018;Dremel et al, 2017;Gunasekaran et al, 2017;Lai et al, 2018;Obal, 2017;Venkatesh et al, 2003), this study extends the individual-level adoption research (Verma et al, 2018) by suggesting a new behavioural perspective that focuses on the facilitating role of storytelling in BDA adoption at the individual level. As a result, this study increases the research field's attention to the factors enabling individual BDA adoption, and it encourages future research to explore human behaviour with BDA.…”

“…Drawing on the achievement of competitive advantage, scholars have shed light on how the acceptance, routinization, and assimilation of BDA improve organizational performance (Gunasekaran et al, ). The extant literature has provided evidence for the relationship between technological (perceived benefits) and organizational (top management support) factors with the intention to adopt BDA (Lai et al, ). Additionally, prior research has demonstrated that satisfaction with the postadoption usage of disruptive technologies is positively correlated with the time and effort invested in searching for the most appropriate technology (Obal, ).…”

“…Aiming to advance our understanding of individual-level BDA use, Verma et al (2018) demonstrated how the system and information quality have both direct and indirect effects on BDA adoption. Despite the emergence of research emphasizing BDA adoption, existing studies have primarily focused on examining the impact of BDA adoption on organizational-level digital transformation (Dremel et al, 2017) and firm performance , which are determinants of organizational BDA adoption intention (Caesarius & Hohenthal, 2018;Lai et al, 2018), as well as antecedents of disruptive technology adoption at the firm level (Obal, 2017). Given that this research stream lacks studies exploring the drivers of individual-level BDA adoption (Verma et al, 2018), this study endeavours both to provide richer insights into the underlying mechanisms of human behaviour and to fill the abovementioned research gap.…”

“…To unlock the full potential of digitization and BDA, it is crucial for organizations to support employees in adopting new technology and in addressing BDA challenges (McAfee & Brynjolfsson, ; Sivarajah et al, ). Although researchers have recently explored the antecedents of organizational BDA adoption intention (Caesarius & Hohenthal, ; Lai, Sun, & Ren, ) and postadoption usage (Obal, ), the impact of BDA adoption on firm performance (Gunasekaran et al, ), and organizational digital transformation (Dremel, Wulf, Herterich, Waizmann, & Brenner, ), the prior research has neglected the factors underlying the individual‐level adoption of BDA (Verma, Bhattacharyya, & Kumar, ). This remains an obstacle and a relevant topic for organizations aiming to understand individual behaviour and increase individual‐level BDA usage.…”