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Smart Product-Service Design for Sustainability

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Products and Services".

Deadline for manuscript submissions: 16 September 2024 | Viewed by 3137

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Special Issue Editors

Prof. Dr. Dun Liu

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Guest Editor

School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China
Interests: product development and improvement; decision analysis based on big data; information management and decision support system; business intelligence, e-commerce and behavior decisions

Prof. Dr. Decui Liang

E-Mail Website
Guest Editor

School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 610054, China
Interests: decision analysis based on big data; information management and business intelligence; risk evaluation and management
Special Issues, Collections and Topics in MDPI journals

Dr. Yinfeng Du

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Guest Editor

Faculty of Management and Economics, Kunming University of Science and Technology, Kunming 650093, China
Interests: product development and improvement; decision analysis based on big data; preference and behavior analysis for users

Special Issue Information

Dear Colleagues,

Owing to the fierce competition in modern manufacturing and service, smart production and service which enable manufacturers to gradually meet more and more personalized needs of users are critical to achieve sustainable success in the connected era. New information technologies, such as machine learning, artificial intelligence, big data, etc., bring numerous opportunities for continuous improvements and innovations. Meanwhile, many challenges emerge in the specific studies, such as product design based on user needs, user preference mining, customer requirements analysis, feature analysis, performance analysis and optimization, quality evaluation and improvement, and user satisfaction analysis. Therefore, this Special Issue aims to publish original, significant, and visionary works on the abovementioned aspects. Rigorous quantitative methods and real-world practice in smart production and service systems are welcome.

Research areas may include (but are not limited to) the following:

Data-driven sustainable smart product–service system design;
Data-driven sustainable smart product development;
User preference analysis based on online reviews;
Customer requirements analysis for smart product and/or service based on online reviews;
Feature analysis for smart product and/or service based on online reviews;
Multiple-attribute decision making in sustainable smart product;
Sustainability performance evaluation for smart product–service system;
Performance analysis and optimization for smart product–service system;
Sustainable practices in smart product–service system;
Sustainable product design based on user needs;
Product and service quality evaluation and improvement for sustainability;
User satisfaction analysis for smart products and services from online reviews.

We look forward to receiving your contributions.

Prof. Dr. Dun Liu
Prof. Dr. Decui Liang
Dr. Yinfeng Du
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

smart product–service systems
sustainability
online reviews
data-driven
customer needs analysis
feature analysis
performance analysis
quality evaluation and improvement
multiple-attribute decision making

Published Papers (3 papers)

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Research

18 pages, 1281 KiB

Open AccessArticle

Online Review Analysis from a Customer Behavior Observation Perspective for Product Development

by Yeong Un Lee, Seung Hyun Chung and Joon Young Park

Sustainability 2024, 16(9), 3550; https://doi.org/10.3390/su16093550 - 24 Apr 2024

Viewed by 331

Abstract

Observing customers is one of the methods to uncover their needs. By closely observing how customers use products, we can indirectly experience their interactions and gain a deep understanding of their feelings and preferences. Through this process, companies can design new products that have the potential to succeed on the market. However, traditional methods of customer observation are time-consuming and labor-intensive. In this study, we propose a method that leverages the analysis of online customer reviews as a substitute for direct customer observations. By correlating a customer journey map (CJM) with online reviews, this research establishes a verb-centric analysis that produces a CJM based on online review data. Various text analysis techniques were utilized in this process. When applying online retail site review data, our method of customer observation required one week. This proved to be more efficient in comparison with traditional customer observation methods, which typically need at least one month to complete. Additionally, we observed that the customer behavior-based VOC (voice of customer) identified during the CJM mapping process offers broad insights that are distinct from traditional product feature-centric review analyses. This behavior VOC can be effectively utilized for product improvement, new product development, and product marketing. To verify the usefulness of the behavior VOC, we asked product development experts to evaluate the quantitative analysis results of the same reviews. The experts evaluated the CJM as useful for product conceptualization and selecting technology priorities. Full article

(This article belongs to the Special Issue Smart Product-Service Design for Sustainability)

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21 pages, 3084 KiB

Open AccessArticle

Construction of Product Appearance Kansei Evaluation Model Based on Online Reviews and FAHP: A Case Study of Household Portable Air Conditioners

by Yuanjian Du, Meng Zhang, Mobing Cai and Kyungjin Park

Sustainability 2024, 16(8), 3132; https://doi.org/10.3390/su16083132 - 09 Apr 2024

Viewed by 515

Abstract

Meeting the personalized needs of users is the key to achieving the sustainable success of a product. It depends not only on the product’s functionality but also on satisfying users’ emotional needs for the product’s appearance. Therefore, researchers have been conducting research focusing on Kansei engineering theory to determine users’ emotional needs effectively. The initial process involves accurately extracting and filtering emotional data and Kansei words from consumers. Thus, we propose an evaluation model to efficiently obtain, screen, and sort these Kansei words based on Kansei engineering, using household portable air conditioners as research subjects. By integrating techniques for online user comment mining methods, users’ Kansei terms related to the product’s appearance can be gathered efficiently. These terms are then combined with image samples and filtered to determine a final set of 16 Kansei word pairs. Subsequently, the fuzzy analytic hierarchy process (FAHP) is utilized to prioritize these terms, and the fuzzy comprehensive evaluation (FCE) method is used to validate the results and determine the applicability of the evaluation model. The results showed that Kansei words could be quickly and objectively acquired using existing text mining techniques on online reviews. Moreover, the weights of different Kansei terms of the product’s appearance in the consumer’s perception are accurately produced through the FAHP. This evaluation model marks a significant advancement in accurately obtaining users’ emotional data in Kansei engineering. It offers valuable guidance for designing products that meet users’ personalized needs, enhancing design efficiency and reducing resource wastage at the early stages of designing, and improving the sustainability development of Kansei engineering. Full article

(This article belongs to the Special Issue Smart Product-Service Design for Sustainability)

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12 pages, 1227 KiB

Open AccessArticle

User Interface Characteristics Influencing Medical Self-Service Terminals Behavioral Intention and Acceptance by Chinese Elderly: An Empirical Examination Based on an Extended UTAUT Model

by Qun Wu, Lan Huang and Jiecong Zong

Sustainability 2023, 15(19), 14252; https://doi.org/10.3390/su151914252 - 27 Sep 2023

Viewed by 1283

Abstract

Medical self-service terminals (MSTs) offer potential advantages for optimizing workflows and enhancing patient experience in hospitals, particularly for the elderly. Despite this, the uptake of MSTs among older adults in China remains a challenge. This research aims to identify the key factors influencing behavioral intention (BI) to adopt MSTs in this age group, with a particular emphasis on user interface (UI) attributes. We extend the Unified Technology Acceptance and Use Theory (UTAUT) model to include these UI elements. Our empirical analysis examines seven variables, which include three critical UI attributes and four core UTAUT elements. The results highlight the importance of performance expectancy (β = 0.40, p < 0.001), effort expectancy (β = 0.50, p < 0.001), and social influence (β = 0.25, p < 0.05) in shaping BI. Importantly, the design of the user interface shows a strong positive correlation with both performance expectancy (β = 0.89, p < 0.001) and effort expectancy (β = 0.81, p < 0.001). These findings illuminate the complex relationship between objective UI features and subjective UTAUT factors. Our study enriches the understanding of how UI design affects the willingness and acceptance of MSTs, especially among China’s elderly population, emphasizing the need to incorporate their viewpoints for successful technology integration in healthcare. Full article

(This article belongs to the Special Issue Smart Product-Service Design for Sustainability)

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