Technology Roadmapping Using Text Mining: A Foresight Study for the Retail Industry

Özcan S., Homayounfard A., Simms C., Wasim J.

IEEE Transactions on Engineering Management, vol.69, no.1, pp.228-244, 2022 (SCI-Expanded, SSCI, Scopus) identifier

  • Nəşrin Növü: Article / Article
  • Cild: 69 Say: 1
  • Nəşr tarixi: 2022
  • Doi nömrəsi: 10.1109/tem.2021.3068310
  • jurnalın adı: IEEE Transactions on Engineering Management
  • Jurnalın baxıldığı indekslər: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Public Affairs Index, Civil Engineering Abstracts
  • Səhifə sayı: pp.228-244
  • Açar sözlər: Emerging technologies, foresight, patent analysis, retail technologies, technology roadmapping, text mining
  • Açıq Arxiv Kolleksiyası: Məqalə
  • Adres: Bəli

Qısa məlumat

Technology roadmapping is a widely accepted method for offering industry foresight as it supports strategic innovation management and identifies the potential application of emerging technologies. While roadmapping applications have been implemented across different technologies and industries, prior studies have not addressed the potential application of emerging technologies in the retail industry. Furthermore, few studies have examined service-oriented technologies by a roadmapping method. Methodologically, there are limited roadmapping studies that implement both quantitative and qualitative approaches. Hence, this article aims to offer a foresight for future technologies in the retailing industry using an integrated roadmapping method. To achieve this, we used a sequential method that consisted of both text mining and an expert review process. Our results show clear directions for the future of emerging technologies as the industry moves toward unmanned retail operations. We generate eight clusters of technologies and integrate them into a roadmapping model, illustrating their links to the market and business requirements. Our study has a number of implications and identifies potential bottlenecks between the integration of front- and back-end solutions for the future of unmanned retailing.