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Assessing Some Important Factors for BDA Project Success

Assessing Some Important Factors for BDA Project Success

Tor Guimaraes (Tennessee Technological University, USA), Ketan Paranjape (Roche Diagnostics, USA), Curtis Armstrong (Tennessee Technological University, USA), and Edwin Baidoo (Tennesse Tech University, USA)
Source Title: International Journal of Applied Logistics (IJAL) 12(1)
Copyright: © 2022 | Pages: 29
DOI: 10.4018/IJAL.309087

Abstract

To be successful, BDA applications must be capable of producing actionable information useful to support managerial decisions throughout the organization. Some authors have proposed that BDA projects differ from IT projects by requiring extra analytical capabilities, special software, and more specialized application developers to enhance decision modelling effectiveness. This study used a two-respondent survey of decision makers using BDA applications fully operational for between 1-3 years and the corresponding CDOs in 282 organizations in various industry sectors. Using stepwise multivariate regression analysis, this convenience sample with a response rate of 32% was used to test hypotheses regarding the importance of some factors proposed in the literature as likely to improve the success of BDA applications. The results corroborate the importance of these factors by explaining a substantial percentage of the variance in decision modelling effectiveness and support several insights on a few success factors corporate managers should focus on.
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Introduction

Increasingly large volumes and a wider variety of data are being generated daily at unprecedented speeds from heterogeneous sources and in many domains (e.g., health, government, social networks, marketing, financial) from business operations and the many technological trends such as the Internet, Social Computing, and Cloud Computing (Botta et al., 2016), as well the widespread use of smart devices. This phenomenon has been called Big Data (BD). As we should expect, it has created opportunities and problems for the use and management of IT in many organizations in various industry sectors. The number and variety of applications of BDA related applications have proliferated wildly as partially shown in Table 1.

Table 1.
Partial list of relevant literature grouped by selected sub-topics
BDA Sub-topics Partial List of Topic Relevant Literature
General descriptions of the BDA phenomenon and its importance. (Raghupathi & Raghupathi, 2014, Watson, 2014
New BDA applications. Jiang et al., 2014; Lotfi, et al. 2022a; Lotfi, et al. 2021a; Lotfi, et al. 2021b; Lotfi, et al. 2022b; Lotfi, et al. 2021c; Lotfi, et al. 2022c; Lotfi, et al. 2021d; Lotfi, et al. 2021e; Lotfi, et al. 2021f; Murdoch & Detsky, 2013; Wang et al., 2015.
Effective BDA tools and methods Jiang et al., 2014; Lotfi, et al. 2022a; Lotfi, et al. 2021a; Lotfi, et al. 2021b; Lotfi, et al. 2022; Lotfi, et al. 2021c; Lotfi, et al. 2022c; Lotfi, et al. 2021d; Lotfi, et al. 2021e; Lotfi, et al. 2021f; Murdoch & Detsky, 2013; Wang et al., 2015.
Some recent BDA studies in Logistics and Supply Chain Management. Albqowr et al., 2022; Hou & Chen,2022; Maheshwari et al., 2021; Parola et al., 2021; Pawar & Paluri, 2022; Seyedan et al., 2020; Wang et al., 2016; Xu et al., 2021.
Consequences of poorly managing BDA projects. Bodenheimer, 2005; Grantmakers In Health, 2012; Herrick et al., 2010; The Kaiser Family Foundation, 2012.
Management of the BDA Function. Constantiou & Kallinikos, 2015; Cortada et al., 2012; Guimaraes & Paranjape, 2021; Jiang et al., 2014; Kelly & Kaskade, 2013; Mikalef et al., 2018; Murdoch & Detsky, 2013; Wang et al., 2015; Rose et al., 2017; Shah & Pathak, 2014; Sharma et al., 2014; Wang et al. 2014.
Empirical tests of integrative model for BDA success factors at the company level. Guimaraes & Paranjape, 2021
Empirical tests of integrative model for BDA success factors at the project level. This study.

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