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 represent action 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.

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大数据投资如何以及何时获得回报？营销可供性和服务创新的作用

大数据技术和分析支持新的数字服务，并且通常与卓越的性能相关。然而，投资大数据的公司往往无法获得这些优势。为了回答大数据如何以及何时产生回报的问题，营销学者需要新的理论方法和经验工具来解释数字化世界。在可供性理论的基础上，作者开发了一个新颖的、概念严谨的、以实践为导向的大数据投资对服务创新和绩效影响的框架。可供性代表行动的可能性，即具有特定目标和能力的个人或组织可以使用技术做什么。作者对三个重要的大数据营销可供性进行了概念化和操作：客户行为模式发现、实时市场响应、和数据驱动的市场二元性。实证分析建立了结构效度，并提供了大数据营销可供性对感知大数据性能的直接、间接和条件影响的初步规则检验。