Critical success factors and architecture of innovation services models in data industry

Tsung Yi Chen, Hsiu Fang Chang

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Big data can be used by enterprises to discover their operating rules and make a forecast of their future operation. To successfully realize the benefits of big data analytics (BDA), an enterprise must rely on external heterogeneous information that is effectively combined and integrated. Enterprises, their upstream and downstream organizations, that utilize big data together form a data industry chain. This study discussed the potential bottlenecks and obstacles of big data-based business model innovation and data transaction platform construction in the business environment. It also explored the successful influencing factors in the big data industry, and applied the analytic hierarchy process to collect opinions from information technology professionals. Regarding the critical factors associated with BDA success, this study found that the experts attached the greatest importance to the maintenance of personal and business privacy and security during the data used with data de-identification being of utmost concern. Based on the results, this study proposed three innovative services models for the data industry. It further analyzed a role model based on the three proposed service models, and defined the rights and obligations of each role holder. Based on decentralization of the blockchain, a multi-layer cloud-based services platform architecture was designed to support data transactions, thereby ensuring the fairness and transparency of big data transactions.

Original languageEnglish
Article number119014
JournalExpert Systems With Applications
Volume213
DOIs
Publication statusPublished - 2023 Mar 1

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Critical success factors and architecture of innovation services models in data industry'. Together they form a unique fingerprint.

Cite this