Examining the needs to adopt big data analytics in B2B organizations: development of propositions and model of needs. Issue 4 (27th July 2021)

• Record Type: Journal Article
• Authors: Ram, Jiwat; Zhang, Zeyang
• Is Part Of: Journal of business & industrial marketing. Volume 37:Issue 4(2022)
• Page Start: 790
• Page End: 809
• Publication Date: 2021-07-27
• Subjects: Decision-making -- Electronic commerce -- Information management -- Data analysis -- Communication technologies -- Business-to-business marketing -- Business-to-business (B2B) -- Technology adoption needs -- Big data analytics -- Theory of organizational motivation; Industrial marketing -- Periodicals; 658.804
• DOI: 10.1108/JBIM-10-2020-0464
• Languages: English
• ISSNs: 0885-8624

Abstract

Abstract : Purpose: Big data analytics (BDA) is becoming a strategic tool to harness data to achieve business efficiencies. While business-to-customer organizations have adopted BDA, its adoption in business-to-business (B2B) has been slow, raising concerns about the lack of understanding of the need to adopt BDA. Little knowledge exists on the subject and the purpose of this study is to examine BDA adoption needs among B2B organizations. Design/methodology/approach: A systematic literature review (SLR) following the six-step SLR guidelines of Templier and Paré (2015) involved 1, 051 articles, which were content analyzed. Findings: The authors offer two-pronged findings. First, on the basis of the SLR, the authors develop a new four-category classification scheme of needs to adopt BDA and present a consolidated review of the current knowledge base along with these categories (i.e. innovation, operational efficiency, customer satisfaction and digital transformation). Second, underpinned by the theory of organizational motivation and literature evidence, the authors develop propositions and a corresponding model of BDA adoption needs. The authors show that BDA adoption among B2B organizations is driven by the need to augment customer lifetime value, champion the change, improve managerial decision cycle-time, tap into social media benefits and align with market transformation. Research limitations/implications: The results facilitate theory development as the study creates a new classification scheme of needs and a model of needs to adopt BDA in large B2B organizations. Practical implications: The findings will serve as a guideline framework for managers to examine their BDA adoption needs and strategize its adoption. Originality/value: The study develops a new four-category classification scheme for understanding B2B organizations' needs to adopt big data analytics. The study also develops a new model of needs which will serve as a stepping stone for the development of a theory of needs of technology adoption.