Cognitive computing on unstructured data for customer co-innovation. (19th December 2019)

• Record Type: Journal Article
• Authors: Chen, Sixing; Kang, Jun; Liu, Suchi; Sun, Yifan
• Is Part Of: European journal of marketing. Volume 54:Number 3(2020)
• Page Start: 570
• Page End: 593
• Publication Date: 2019-12-19
• Subjects: Complexity theory -- Co-innovation -- Cognitive computing -- Unstructured data; Marketing -- Periodicals; Consumer behavior -- Periodicals; 658.8
• DOI: 10.1108/EJM-01-2019-0092
• Languages: English
• ISSNs: 0309-0566

Abstract

Abstract : Purpose: This paper aims to build on the latest advances in cognitive computing techniques to systematically illustrate how unstructured data from users can offer significant value for co-innovation. Design/methodology/approach: The paper adopts a general overview approach to understand how unstructured data from users can be analyzed with cognitive computing techniques for innovation. The paper links the computerized techniques with marketing innovation problems with an integrated framework using dynamic capabilities and complexity theory. Findings: The paper identifies a suite of methodologies for facilitating company co-innovation via engaging with customers and external data with cognitive computing technologies. It helps to expand marketing researchers and practitioners' understanding of using unstructured data. Research limitations/implications: This paper provides a conceptual framework that divides co-innovation process into three stages, ideas generation, ideas integration and ideas evaluation, and maps cognitive computing methodologies and technologies to each stage. This paper makes the theoretical contributions by developing propositions from both customer and firm perspectives. Practical implications: This paper can be used for companies to engage consumers and external data for co-innovation activities by strategically select appropriate cognitive computing techniques to analyze unstructured data for better insights. Originality/value: Given the lack of systematic discussion regarding what is possible from using cognitive computing to analyze unstructured data for co-innovation. This paper makes first attempt to summarize how unstructured data can be analyzed with cognitive computing techniques. This paper also integrates complexity theory to the framework from a novel perspective.