Does Big Data Drive Innovation In E-Commerce: A Global Perspective?

Abstract

Objective: Literature indicates big data is a competitive edge, which boasts a firm’s overall performance. With the rise of big data (BD), e-commerce firms are using the tools to engage more with customers, offer better products, and innovate more to gain a competitive advantage. Nevertheless, past empirical studies have shown conflicting results. Design: Building on the capital-based perspective and the firm’s inertia concept, we created a model to explore how BD and BD analytics capability impact innovation results in e-commerce businesses. We carried out a two-year empirical investigation project to secure empirical data on 1703 data-driven innovation tasks from USA and Asia. Findings: We showed that there is a tradeoff between BD and BD analytics capability, in which the optimum balance of BD depends on the amount of BD analytics ability. BD analytics ability exerts a good moderating impact, that is, the better this capability is, the higher the effect of BD on gross margin and sales growth. For U.S. innovation tasks, BD has an inverted U-shaped relationship with sales innovation. For Asian innovation tasks, when major data capital is minimal, promoting big data analytics capability improves sales innovation and disgusting margin up to a specific point. Policy Implications: Establishing BD analytics capability over that time could prevent innovation efficiency. Our findings offer guidance to e-commerce firms on producing strategic choices about source allocations for BD and BD analytics ability. Originality: A limited research has been carried out to show the impact of using BD analytics tools to drive innovation. This is one of the first articles that dive into using BD to foster innovation in the e-commerce business.