Choi, Jaewoong Jeong, Byeongki Yoon, Janghyeok 2024-01-19T11:30:50Z 2024-01-19T11:30:50Z 2022-06-17 2022-09 0166-3615 https://pubs.kist.re.kr/handle/201004/114759 Emerging business areas are early indicators of potential business opportunities, which are considered key to formulating new business strategies and envisioning near-future business environments. However, existing methods for analysing business opportunities solely depend on the opinion and knowledge of experts, which are time-consuming and labour-intensive. In academia, recent years have witnessed a significant increase in attempts to identify emerging business areas as near-future business opportunities with data-driven approaches. Although successful innovation requires sources of novelty, how to measure the novelty of business areas has barely been investigated in the literature. As a solution, we propose an approach to identifying emerging business areas with high novelty with a systematic process and quantitative outcomes. At the heart of the proposed approach is the composite use of the language model and local outlier factor (LOF). The meaning of business opportunities become more explicit by identifying emerging business areas composed of novel goods and services, with implications for the business operation stage. Finally, business opportunity maps are developed based on recency and visibility values, thereby investigating the implications as business opportunities. A case study of the trademarks related to scientific apparatus is presented to illustrate the proposed approach. The systematic process and quantitative results are expected to be employed in practice as a complementary tool, serving as a cornerstone for analysing business opportunities using trademarks. (c) 2022 Elsevier B.V. English Elsevier BV Identification of emerging business areas for business opportunity analysis: An approach based on language model and local outlier factor Article 10.1016/j.compind.2022.103677 1 Computers in Industry, v.140 Computers in Industry 140 N scie scopus 000807519600003 Computer Science, Interdisciplinary Applications Computer Science Article CREATION DISCOVERY IDENTIFY Business opportunity Designated goods and services Novelty indicator Language model Local outlier factor