Abstract
A persistent question for information technology researchers and practitioners is how big data analytics (BDA) can improve sales performance. Therefore, this study proposed a research model to investigate the impact of BDA on perceived sales performance in accordance with the resource-based view (RBV) and dynamic capability theory. The 416 valid responses collected from the employees of pharmaceutical organizations were analyzed using structural equation modelling to test the proposed research model. Results indicated that the BDA and customer relationship management (CRM) capabilities shared a strong positive impact on perceived sales performance. BDA, as organizational resources, creates organizational dynamic capabilities, such as CRM capabilities. BDA and CRM capabilities can influence perceived sales performance. Furthermore, CRM capabilities have a significant mediating impact on the relationships between BDA and perceived sales performance. This study also highlighted the practical and theoretical implications of the proposed model, the research limitations, and the future research directions.
Highlights
Big data analytics (BDA) has received special attention due to its dynamic decision-making capabilities [1]
A recent study explored the important of BDA in services personalization in multisector organizations such as insurance, banking, telecommunication, and e-commerce and suggested the need of more empirical studies on it especially in healthcare sector [74]. ese studies suggested that personalization should be empirically investigated in the context of BDA. erefore, the present study proposes personalization as a BDA benefit that will influence perceived sales performance (PSP) and customer relationship management (CRM) capabilities (CIMC, customer relationship upgrading capabilities (CRUCs), and customer win-back capabilities (CWBCs))
AMOS is an appropriate tool for confirmatory factor analysis (CFA) and structural equation modelling (SEM) [92] and a powerful tool for estimating specific indirect effects [93]. e demographical information presented through SPSS is shown in Table 4. e results indicated that the respondents were diverse in gender, with 53.6% males and 46.4% females
Summary
Big data analytics (BDA) has received special attention due to its dynamic decision-making capabilities [1]. Today’s technology-oriented world brings numerous unprecedented opportunities and novel complexities that contribute to improving decision-making capabilities and obtaining competitive advantages [2, 3]. BDA refers to the complex process of obtaining information like the hidden patterns, unidentified correlations, users’ preferences, and market trends from the massive amount of structured and unstructured data that assist organizations for efficient decision-making [4]. The research on the potential of BDA is still at the fundamental stage and generally fails to consider the mechanisms through which the investments in BDA are converted into competitive performance [7, 8]. The research on the potential of BDA is still at the fundamental stage and generally fails to consider the mechanisms through which the investments in BDA are converted into competitive performance [7, 8]. e literature provides vital knowledge on the challenges, benefits, and outcomes of BDA, but little is known about how the practice of BDA in organizations creates value for organizations, becomes the competitive edge of organizations, and enhances organizational or sales performance [9, 10]. e proponents of BDA application in the USA claim that the proper application of BDA in healthcare organizations, including pharmaceutical
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