Big data affordances and market performance: The moderating role of servitization

Many service-oriented manufacturers (SOMers) aggressively engage with big data to stay ahead of the competition, but not all have achieved the anticipated market returns. To unravel this puzzle, we draw on affordance theory and the resource-based view to investigate the combined effects of two big data affordances (i.e., customer behavior pattern spotting and real-time market responsiveness) and two service categorizations (i.e., basic and advanced services) on market performance. Analyzing data from 223 SOMers in China, we reveal that while customer behavior pattern spotting is positively associated with market performance, real-time market responsiveness has a U-shaped association with market performance. More interestingly, basic services enhance the positive association between customer behavior pattern spotting and market performance, whereas SOMers with a high (vs. low) level of advanced services better use real-time market responsiveness to enhance market performance. We contribute to the big data literature by offering a new theoretical explanation for the inconsistent big data–performance relationship. Our findings also have managerial implications by guiding SOMers on how to reorient their big data usage.