Abstract
Service innovativeness is a key sustainable competitive advantage that increases sustainability of enterprise development. Literature suggests that big data and big data analytics capability (BDAC) enhance sustainable performance. Yet, no studies have examined how big data and BDAC affect service innovativeness. To fill this research gap, based on the information processing theory (IPT), we examine how fits and misfits between big data and BDAC affect service innovativeness. To increase cross-national generalizability of the study results, we collected data from 1403 new service development (NSD) projects in the United States, China and Singapore. Dummy regression method was used to test the model. The results indicate that for all three countries, high big data and high BDAC has the greatest effect on sustainable innovativeness. In China, fits are always better than misfits for creating sustainable innovativeness. In the U.S., high big data is always better for increasing sustainable innovativeness than low big data is. In contrast, in Singapore, high BDAC is always better for enhancing sustainable innovativeness than low BDAC is. This study extends the IPT and enriches cross-national research of big data and BDAC. We conclude the article with suggestions of research limitations and future research directions.
Highlights
The explosive growth of big data has brought opportunities and challenges for firms to rapidly develop and improve their competitiveness and sustainability of the enterprise development [1,2]
When there is a fit between big data and big data analytics capability (BDAC), new service development (NSD) projects can achieve higher sustainable innovativeness
Consistent with Hypothesis 2 (H2), the effect of high-high fit (b = 0.688; p < 0.01) on sustainable innovativeness is higher than that of low-low fit (b = 0.427; p < 0.01), indicating that NSD projects with high levels of both big data and BDAC can achieve higher sustainable innovativeness
Summary
The explosive growth of big data has brought opportunities and challenges for firms to rapidly develop and improve their competitiveness and sustainability of the enterprise development [1,2]. Studies have demonstrated that big data is an invaluable resource in the development of service innovation [2,3,4], and places great demands on the information processing capability of firms [5]. IPT predicts that when there is a fit between a firm’s demands for information and its information processing capability, the firm will gain greater sustainable competitive advantage. Firms need to use advanced technologies and tools, such as deep learning [5,9] and essential analytics capability [10,11], to identify market trends and evolution patterns contained in big data. A lack of big data analytics capability (BDAC) can leave firms with unharnessed big data, resulting in increased data storage costs and greater difficulty in converting data into useful, timely information [12,13]
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