TY - CHAP
T1 - The Influence of Customer Involvement in Data Analytics on Innovation
T2 - An Abstract
AU - Zhang, Haisu
AU - Xiao, Yazhen
N1 - Publisher Copyright:
© 2020, The Academy of Marketing Science.
PY - 2020
Y1 - 2020
N2 - This research suggests that customer engagement goes beyond the task of providing data for new product development (NPD), and that customers may play a more active role in data analytics. We view customer involvement in data analytics as consisting of two aspects: Customer as Data Provider (CDP), defined as customers (passively) providing data through different channels; and Customer as Data Analyst (CDA), defined as customers (actively) participating in data analytics, such as acquisition and implementation, to co-develop innovative outputs. While CDP is consistent with the mainstream research on data analytics, CDA introduces a new aspect of customer involvement in data analytics practice. Big data is often used to understand customer needs. Thus, we further explore how customer needs characteristics moderate the proposed effects of customer involvement in data analytics on new product performance. We examine two characteristics, tacitness and diversity, and suggest that they both moderate the main effects, but their moderating mechanisms are opposite. We collected survey data of Business-to-Business (B2B) innovation projects. All 148 respondents held management-related positions at the time of data collection. Data quality was satisfactory based on reliability, confirmatory factor analysis, discriminant validity, and common method bias tests. Results showed that both CDP and CDA were positively related to new product performance. In addition, it was found that while customer need tacitness negatively moderated the effect of CDP on new product performance, it positively moderated that of CDA. Meanwhile, customer need diversity positively moderated the effect of CDP. To our knowledge, we are the first to empirically test CDA. Extant literature is dominated by a conventional view of CDP. However, as big data prevails, we challenge the assumption that customers always serve as a data source; instead, they can participate more in data analytics for NPD. As a result, this research contributes a new insight into the literature of data analytics.
AB - This research suggests that customer engagement goes beyond the task of providing data for new product development (NPD), and that customers may play a more active role in data analytics. We view customer involvement in data analytics as consisting of two aspects: Customer as Data Provider (CDP), defined as customers (passively) providing data through different channels; and Customer as Data Analyst (CDA), defined as customers (actively) participating in data analytics, such as acquisition and implementation, to co-develop innovative outputs. While CDP is consistent with the mainstream research on data analytics, CDA introduces a new aspect of customer involvement in data analytics practice. Big data is often used to understand customer needs. Thus, we further explore how customer needs characteristics moderate the proposed effects of customer involvement in data analytics on new product performance. We examine two characteristics, tacitness and diversity, and suggest that they both moderate the main effects, but their moderating mechanisms are opposite. We collected survey data of Business-to-Business (B2B) innovation projects. All 148 respondents held management-related positions at the time of data collection. Data quality was satisfactory based on reliability, confirmatory factor analysis, discriminant validity, and common method bias tests. Results showed that both CDP and CDA were positively related to new product performance. In addition, it was found that while customer need tacitness negatively moderated the effect of CDP on new product performance, it positively moderated that of CDA. Meanwhile, customer need diversity positively moderated the effect of CDP. To our knowledge, we are the first to empirically test CDA. Extant literature is dominated by a conventional view of CDP. However, as big data prevails, we challenge the assumption that customers always serve as a data source; instead, they can participate more in data analytics for NPD. As a result, this research contributes a new insight into the literature of data analytics.
KW - Big data
KW - Customer involvement
KW - Customer needs
KW - Innovation
UR - http://www.scopus.com/inward/record.url?scp=85125173942&partnerID=8YFLogxK
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U2 - 10.1007/978-3-030-42545-6_84
DO - 10.1007/978-3-030-42545-6_84
M3 - Chapter
AN - SCOPUS:85125173942
T3 - Developments in Marketing Science: Proceedings of the Academy of Marketing Science
SP - 279
EP - 280
BT - Developments in Marketing Science
PB - Springer Nature
ER -