Adopt Big-Data Analytics to Explore and Exploit the New Value for Service Innovation

Nopsaran Thuethongchai, Tatri Taiphapoon, Achara Chandrachai and Sipat Triukose
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Nopsaran Thuethongchai: Technopreneurship and Innovation Management Program, Chulalongkorn University, Bangkok 10330, Thailand
Tatri Taiphapoon: Faculty of Communication Arts, Chulalongkorn University, Bangkok 10330, Thailand
Achara Chandrachai: Chulalongkorn Business School, Chulalongkorn University, Bangkok 10330, Thailand
Sipat Triukose: Research Group on Applied Computer Engineering Technology for Medicine and Healthcare, Big-data Analytics and IoT Center (CUBIC), Chulalongkorn University, Bangkok 10330, Thailand

Social Sciences, 2020, vol. 9, issue 3, 1-17

Abstract: Big-data analytics is gaining substantial attention due to its contribution to the process of determining business strategy and providing valuable information for the design and development of service innovation. The principal objective of this research is to study the adoption of big-data analytics for service innovation. The focus will be on leveraging features of data analytics to capture genuine customer’s requirements from the communication data through the digital service channel. This study used mixed methods research of documentary research, with supplementary semi-structured interviews. The interviews were conducted with 11 executive managements who have more than ten years of experience in data analytics or service development. The result of the research found that organizations in the services industry are using big data analytics to build capabilities to gain competitive advantages as well as the ability to rapidly and accurately respond to the market’s demands. The process of adopting big-data analytics for service innovation described in this article consists of seven essential procedural steps that impact the success of the development of service innovation, and also considered with the objective of increasing effectiveness in opportunity identification and reduce complexity in the fuzzy frond-end service innovation development theory.

Keywords: opportunity identification; service innovation; new service development; big-data analytics; data analytics (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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