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VibrantFENG2050500

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Vibrant@FENG - Issue 1 (May 2021)

 Cover Story

A scenario-based product-service system for servitization of gerontechnology for ageing in place

The unprecedented increase in the ageing population brings great impact to business strategies and product development, since potential opportunities in the silver-hair market are emerging at the same time as a result of researchers’ and practitioners’ efforts. The elderly people trend is for ‘ageing in place’, which means that the elderly are more willing to stay in their own home rather than living in a nursing home during their retirement life due to the feeling of comfort and convenience when living in a familiar environment. Many researchers and practitioners are paying attention to the technology for ageing and its matching services in their market and technology activities. Gerontechnology, combining gerontology with technology, is usually coupled with the product-service system which is a mix of products and services for satisfying customer needs and aspirations. However, the existing product-service system mainly focuses on the product features and functions, and the development of service components is usually neglected by gerontechnology manufacturers.

Consequently, the research team led by Professor Benny Cheung of the Department of Industrial and Systems Engineering (ISE) has undertaken a project entitled “a scenario-based product-service system for servitization of gerontechnology for ageing in place” which attempts to investigate the design rationales of gerontechnology product-service systems for ageing in place. To determine a product-service design rationale, a survey of a substantial number of young-old senior age groups has been conducted, as shown in Figure 1. The results show that confidence to use, independence to use, emotional enjoyment, and social support are the key factors influencing their technology adoption. Hence, a Customer-centric Product-Service System is developed based on statistical analysis and text mining of online customer comments, as shown in Figure 2. This enables product-service providers to better understand elderly people’s expectations of gerontechnology for ageing in place, their common practices and interesting patterns of ageing in place, as well as acquiring product and service design rationales in terms of user needs, requirements and value. This study selects online customer comments on smartphones as a case study, and is conducted through six steps: data collection and acquisition, data storage and processing, emotion analysis, information validation, statistical analysis, and design rationale generation. 1,000 datasets were selected as the initial datasets from online customer comment databases and finally 696 qualified datasets have been selected for analysis. Through the keywords extraction and clustering, specific features of products and services to which customers pay close attention have emerged, such as product-related issues about battery life, screen, and camera and service-related issues of replacement, product delivery, and system updating. Through analysing customers’ comments, their needs, expectations and preferences are captured, which can help product-services providers to generate design rationales. For instance, it was found that customers prefer cameras with 16-megapixels and f/1.9 lens, and the current online technical support is insufficient and needs to be improved. This research method allows product-service providers to generate user-centric design rationales and build user-oriented scenarios responding to real user needs in practice for developing integrated product-service solutions with effective action plans.

Figure 1 Classification of the Senior Age Group – Definition of Young-Old Senior Age Group
Classification of Senior Age Group – Definition of Young-Old Senior Age Group

 

Figure 2 Framework of Customer-centric Product-Service System
Framework of Customer-centric Product-Service System

 

Project Information:
Principal Investigator: Professor Benny C.F. Cheung (ISE)
Co-Investigator: Professor Kelvin Willoughby, Skolkovo Institute of Science and Technology, Moscow, Russia
Funding Source: Departmental General Research Fund (DGRF) from ISE
Project Code: G-UABL

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