Identifying Service Opportunities Based on Outcome-Driven Innovation Framework and Deep Learning: A Case Study of Hotel Service
Identifying Service Opportunities Based on Outcome-Driven Innovation Framework and Deep Learning: A Case Study of Hotel Service
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DOI：
10.3390/su13010391
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发表时间：
2021-01
期刊：
影响因子：
3.9
通讯作者：
Sunghyun Nam;Sejun Yoon;N. Raghavan;Hyunseok Park
中科院分区：
文献类型：
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作者：
Sunghyun Nam;Sejun Yoon;N. Raghavan;Hyunseok Park
本研究提出了一种数据驱动的系统化方法来发现特定服务行业的服务机会。具体而言，该方法通过分析在线评论数据来定量识别重要但未满足的客户需求。为了以结构化的形式表示客户需求，基于工作要完成的客户成果采用了成果驱动创新（ODI）框架。因此，要完成的工作信息从审查数据中提取出来，并转换为客户成果。具有高服务机会的结果通过用于量化结果的重要性和满意度得分的度量来选择。本文利用相关评论数据对酒店服务进行了实证研究。结果表明，该方法可以识别酒店服务中的客户需求，最大化支付价格/存款的安全性，以及最大化避免在大厅等待的可能性-并且客观地优先考虑服务创新的战略方向。因此，所提出的方法可以作为一种智能工具，有效地制定业务战略。
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.