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Creating Sustainable Innovativeness through Big Data and Big Data Analytics Capability: From the Perspective of the Information Processing Theory

School of Economics and Management, Xi’an Technological University, Xi’an 720021, China
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Sustainability 2020, 12(5), 1984; https://doi.org/10.3390/su12051984
Received: 9 February 2020 / Revised: 2 March 2020 / Accepted: 2 March 2020 / Published: 5 March 2020
(This article belongs to the Special Issue Big Data and Sustainability)
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. View Full-Text
Keywords: big data; big data analytics capability; innovations and sustainability; information processing theory; sustainable innovativeness big data; big data analytics capability; innovations and sustainability; information processing theory; sustainable innovativeness
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MDPI and ACS Style

Song, M.; Zhang, H.; Heng, J. Creating Sustainable Innovativeness through Big Data and Big Data Analytics Capability: From the Perspective of the Information Processing Theory. Sustainability 2020, 12, 1984. https://doi.org/10.3390/su12051984

AMA Style

Song M, Zhang H, Heng J. Creating Sustainable Innovativeness through Big Data and Big Data Analytics Capability: From the Perspective of the Information Processing Theory. Sustainability. 2020; 12(5):1984. https://doi.org/10.3390/su12051984

Chicago/Turabian Style

Song, Michael, Haili Zhang, and Jinjin Heng. 2020. "Creating Sustainable Innovativeness through Big Data and Big Data Analytics Capability: From the Perspective of the Information Processing Theory" Sustainability 12, no. 5: 1984. https://doi.org/10.3390/su12051984

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