Identifying Service Opportunities Based on Outcome-Driven Innovation Framework and Deep Learning: A Case Study of Hotel Service

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초록

This research proposes a data-driven systematic method to discover service opportunities in a specific service sector. Specifically, the method quantitatively identifies the important but unsatisfied customer needs by analyzing online review data. To represent customer needs in a structured form, the job-to-be-done-based customer outcomes are adopted from the outcome-driven innovation (ODI) framework. Therefore, job-to-be-done information is extracted from the review data and is transformed into customer outcomes. The outcomes having high service opportunities are selected by metrics for quantifying the importance and satisfaction score of the outcomes. This paper conducted an empirical study for hotel service using relevant review data. The results show that the method can identify customer needs in hotel service-e.g., maximizing safety to pay price/deposit, and maximizing possibility to avoid waiting at lobby-and objectively prioritize strategic directions for service innovation. Therefore, the proposed method can be used as an intelligent tool for the effective development of a business strategy.

키워드

customer needs identificationjob-to-be-doneservice job mapsubject-action-object (SAO)natural language processing (NLP)bidirectional encoder representations from transformers (BERT)attention networkREVIEWSIDENTIFICATIONTECHNOLOGY
제목
Identifying Service Opportunities Based on Outcome-Driven Innovation Framework and Deep Learning: A Case Study of Hotel Service
저자
Nam, SunghyunYoon, SejunRaghavan, NagarajanPark, Hyunseok
DOI
10.3390/su13010391
발행일
2021-01
유형
Article
저널명
Sustainability
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