Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

A big data framework for facilitating product innovation processes

Zhan, Y. Z., Tan, K. H., Ji, G., Chung, Leanne and Tseng, M. L. 2017. A big data framework for facilitating product innovation processes. Business Process Management Journal 23 (3) , pp. 518-536. 10.1108/BPMJ-11-2015-0157

Full text not available from this repository.

Abstract

Purpose The purpose of this paper is to suggest how firms could use big data to facilitate product innovation processes, by shortening the time to market, improving customers’ product adoption and reducing costs. Design/methodology/approach The research is based on a two-step approach. First, this research identifies four potential key success factors for organisations to integrate big data in accelerating their product innovation processes. The proposed factors are further examined and developed by conducting interviews with different organisation experts and academic researchers. Then a framework is developed based on the interview outputs. The framework sets out the key success factors involved in leveraging big data to reduce lead times and costs in product innovation processes. Findings The three determined key success factors are: accelerated innovation process; customer connection; and an ecosystem of innovation. The authors believe that the developed framework based on big data represents a paradigm shift. It can help firms to make new product development dramatically faster and less costly. Research limitations/implications The proposed accelerated innovation processes demand a shift in traditional organisational culture and practices. It is, though, meaningful only for products and services with short life cycles. Moreover, the framework has not yet been widely tested. Practical implications This paper points to the vital role of big data in helping firms to accelerate product innovation processes. First of all, it allows organisations to launch new products to market as quickly as possible. Second, it helps organisations to determine the weaknesses of the product earlier in the development cycle. Third, it allows functionalities to be added to a product that customers are willing to pay a premium for, while eliminating features they do not want. Last, but not least, it identifies and then prioritises customer needs for specific markets. Originality/value The research shows that firms could harvest external knowledge and import ideas across organisational boundaries. An accelerated innovation process based on big data is characterised by a multidimensional process involving intelligence efforts, relentless data collection and flexible working relationships with team members.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HD Industries. Land use. Labor
Uncontrolled Keywords: Big data, Accelerated innovation, Key success factors, Product innovation processes, Rapid innovation
Publisher: Emerald
ISSN: 1463-7154
Date of Acceptance: 25 November 2015
Last Modified: 03 Jul 2017 13:12
URI: http://orca.cf.ac.uk/id/eprint/86691

Citation Data

Cited 17 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item