How and when do big data investments pay off? The role of marketing affordances and service innovation

Big data technologies and analytics enable new digital services and are often associated with superior performance. However, firms investing in big data often fail to attain those advantages. To answer the questions of how and when big data pay off, marketing scholars need new theoretical approaches and empirical tools that account for the digitized world. Building on affordance theory, the authors develop a novel, conceptually rigorous, and practice-oriented framework of the impact of big data investments on service innovation and performance. Affordances representaction possibilities, namely what individuals or organizations with certain goals and capabilities can do with a technology. The authors conceptualize and operationalize three important big data marketing affordances: customer behavior pattern spotting, real-time market responsiveness, and data-driven market ambidexterity. The empirical analysis establishes construct validity and offers a preliminary nomological test of direct, indirect, and conditional effects of big data marketing affordances on perceived big data performance.

Automated summary

Big data technologies and analytics have the potential to offer new digital services and lead to superior performance, but many firms fail to effectively leverage their investments in big data. Researchers have developed a framework based on affordance theory to analyze the impact of big data investments on service innovation and performance, focusing on customer behavior pattern spotting, real-time market responsiveness, and data-driven market ambidexterity. The empirical analysis validates the constructs and examines the direct, indirect, and conditional effects of big data marketing affordances on perceived big data performance.