Smart Product-service Systems Research Articles

Integrating object detection and natural language processing models to build a personalized attraction recommendation agent in a smart product service system

Product Service System (PSS) is a new business model that integrates tangible products and intangible services to better meet customer needs and expectations. In recent years, scholars had some efforts to enhance the capability of PSS with the support of artificial intelligence (AI) which is known as Smart PSS(SPSS). So far, most previous studies adopted a single model which cannot handle multiple tasks simultaneously that results in unsatisfactory services to customers. In addition, customer preference cannot be fully addressed to achieve personalization. Therefore, this study proposes a method that integrates multiple models into an SPSS with three steps: (1) Collect data and construct an appropriate object detection model. (2) Develop smart PSS solutions. Then, (3) Optimize the system based on feedback through Natural Language Processing (NLP) to provide customers with personalized services. An attraction recommendation case study with experiment is designed to verify the proposed method. The results show that proposed SPSS can optimize the system in time according to the feedback of users, and provide better personalized services. This research is the first research that utilizes applied both text and image data to extract customer characteristics to better capture the voice of customers.

Dynamic user profile construction and its application to smart product-service system design: A maternity-oriented case study

The human-centric philosophy is considered a crucial development direction for smart Product-Service Systems (smart PSS). Smart PSS has effectively advanced the circular economy by enhancing user experience, incorporating servitization and digital servitization, and extending product lifecycle, among other key aspects of sustainable development. However, there is currently a lack of a reasonable, accurate, and actionable framework and methodology to express the human element, namely user profiling, within this philosophy. To address this gap, this paper utilizes statistical methods such as factor analysis, cluster analysis, and regression analysis, building upon the concept of traditional user profiling. The aim is to integrate the three prominent approaches of goal-oriented, scenario-based, and data-driven user profiling, with the goal of complementing each other and designing a top-level user profiling framework for smart PSS. Furthermore, Industry 4.0 technologies and text mining techniques are employed to collect data on users' product and service usage. As these data contain real-time information about user needs, behaviors and goals at different time periods, they can be used to construct dynamic features of user profiling, and ultimately achieve the construction of dynamic user profiling for smart PSS. To validate the proposed user profiling framework and dynamic user features of smart PSS, this paper presents a case study focusing on the user group of maternal women. This case study promotes the in-depth exploration of smart PSS research in expressing the human element.

Optimized Attention Enhanced Temporal Graph Convolutional Network Espoused Research of Intelligent Customer Service System based on Natural Language Processing Technology

ABSTRACT Consumers have begun to move their attention away from product functioning and toward value probably extracted from items. Companies have begun to use customer service systems (CSS) in response to this trend, which are business models that give clients with not solitary tangible items as well as intangible facilities. Even with substantial investigation on Smart CSS frameworks, rare of this frameworks considered customers active data producers actively creating data for the Smart CSS. Furthermore, the majority of them offered a generic remedy rather than a personalized one. To classify customer service systems, performance metrics, such as precision, accuracy, F1-score, Recall (Sensitivity), Specificity, Error rate, Computation time, and RoC are considered. The performance of AETGCN-NGOA-CSS approach attains 19.11%, 24.12% and 28.13% high specificity, 24.93%, 23.04%, and 9.51% lower computation time, 15.2%, 25.45% and 13.91% higher ROC and 8.45%, 20.98%, and 27.55% higher accuracy compared with existing methods, such as developing personalized recommendation system in smart product service system depend on unsupervised learning model (CSS-BERT), Cognitive Decision-Making approaches in Data-driven Retail Intelligence: Consumer Sentiments, Choices, Shopping Behaviors (CSS-CDMA), e-Commerce Online Intelligent Customer Service System under Fuzzy Control (CSS-FFNN), respectively.

Evaluating Technicians' Workload and Performance in Diagnosis for Corrective Maintenance.

The advancement in digital technology is transforming the world. It enables smart product-service systems that improve productivity by changing tasks, processes, and the ways we work. There are great opportunities in maintenance because many tasks require physical and cognitive work, but are still carried out manually. However, the interaction between a human and a smart system is inevitable, since not all tasks in maintenance can be fully automated. Therefore, we conducted a controlled laboratory experiment to investigate the impact on technicians' workload and performance due to the introduction of smart technology. Especially, we focused on the effects of different diagnosis support systems on technicians during maintenance activity. We experimented with a model that replicates the key components of a computer numerical control (CNC) machine with a proximity sensor, a component that requires frequent maintenance. Forty-five participants were evenly assigned to three groups: a group that used a Fault-Tree diagnosis support system (FTd-system), a group that used an artificial intelligence diagnosis support system (AId-system), and a group that used neither of the diagnosis support systems. The results show that the group that used the FTd-system completed the task 15% faster than the group that used the AId-system. There was no significant difference in the workload between groups. Further analysis using the NGOMSL model implied that the difference in time to complete was probably due to the difference in system interfaces. In summary, the experimental results and further analysis imply that adopting the new diagnosis support system may improve maintenance productivity by reducing the number of diagnosis attempts without burdening technicians with new workloads. Estimates indicate that the maintenance time and the cognitive load can be reduced by 8.4 s and 15% if only two options are shown in the user interface.

A framework for capturing and evaluating value propositions of smart products considering users’ experiences

ABSTRACT The personalised value propositions in smart product-service systems have created new business opportunities for manufacturing enterprises. However, a few users can’t deeply recognise or exploit every one of them to solve pain points in real experiences. From the user-driven perspective, based on DEMATEL and group consensus, we construct an integrated framework for capturing and evaluating value propositions of smart products considering users’ experiences. A case study of the sweeping robot and method comparisons verify the rationality and validity of the proposed model. The present work can help enterprises redesign smart products to satisfy user needs and gain competitive advantages.

A user-centred collective system design approach for Smart Product-Service Systems: A case study on fitness product design

Emerging technologies have significantly contributed to the evolution of traditional product-service systems (PSS) into smart PSS. This transformation demands a fresh perspective and a more inventive design approach. In response, this study proposes a new User-Centred Collective System Design (CSD) framework and process for Smart PSS design, aiming to enhance stakeholder engagement during the entire design process, thus promoting highly effective and creative design solutions. A case study, titled ‘Next-G Smart Fitness PSS Design’, was carried out to test and implement this approach, contrasting the results of the CSD method with a designer-centred method. The outcomes showed a marked improvement in product novelty and user desirability of the design outcomes when using the proposed design framework. The proposed CSD framework could offer beneficial insights and user-centric viewpoints for practitioners dealing with complex challenges linked to smart PSS design.

Sustainable value creation through customization for smart PSS models: a multi-industry case study

PurposeThis study is a reference for manufacturers who are promoting their product-service system (PSS) development. Currently, improvements in both digital customization and sustainability for various smart PSS categories have been considered rarely. This paper addresses this research gap by developing relevant models.Design/methodology/approachThe development trends of customization-oriented PSS are described in a literature review. An in-depth multiple-case study methodology is adopted, and seven manufacturing companies are sampled. The goal is to identify digital customization measures that can be employed on representative smart PSS models and to explore how these models can create sustainable value.FindingsThis study provides valuable insights by uncovering a synthesis framework for achieving customization of the product/use/result-oriented smart PSSs, and the relevant representative smart functions are summarized. This identifies how digital customization capabilities can improve sustainability, including direct economic value for customers as well as additional social benefits and environmental improvements during customization.Originality/valueCurrently, the influence of digitalization on customized offerings and the relevant impact on sustainability development have not been fully addressed to date. This study provides comprehensive information with a reference value for digital customization transformation among the three main types of smart PSS.

Design and engineering of value-driven Smart PSS for manufacturing companies: Design risk anticipation with sPS2Risk Framework

Digital servitization has emerged over the last years, at the convergence between digital- and service-oriented business strategies, leading manufacturing companies to transform their business models through the adoption of so-called Smart PSS (Smart Product-Service-Systems). As a contribution to the relatively recent scientific literature on Smart PSS design, this paper presents a framework for the design and engineering of Smart PSS offers, based on a value-driven approach. The added-value of the framework is notably to integrate (i) a smart PSS prototyping approach associated with (ii) a risk management process, all along the design process. When a manufacturing company has to shift from a ‘product-centric’ to a ‘Smart PSS’ business model, sPS2Risk Framework helps decision-makers anticipating and mitigating key innovation risks. The paper presents the generic framework and its experimentation for an industrial case study, in the heating appliance sector.

The impact of the internet of things on the perceived quality and customer involvement of smart product-service systems

Despite emerging business trends reshaping the business strategies through disruptive digitalization technologies, there is a notable lack of research evaluating the customer's experience and quality attributes in Smart Product-Service Systems (SPSS) and their connection with the Internet of Things (IoT) technologies. To address these challenges, this paper proposes and tests through six application cases, and eight use cases a novel methodology supporting firms to (i) assess the impact of IoT technologies on the perceived quality of SPSSs and (ii) assess the intensity of customer engagement through the IoT in the SPSS lifecycle to enhance the perceived quality of customers and stakeholders. A mixed-methods approach was used as the research design of the study. Overall, our findings show that the methodology supports SPSS scholars and practitioners in enhancing customer experience, prioritizing investments in adopting cutting-edge technologies, identifying the main quality determinants affected by the IoT in SPSS business and the critical technical factors related to the perceived quality of customers. The study bridges the current knowledge gap between quality determinants and emerging IoT technologies in SPSS business, proposing a methodology to assess the perceived quality determinants in SPSS enabled by IoT technologies.

Moda Endüstrisinde Akıllı Ürün-Hizmet Sistemleri: Sürdürülebilirlik Sonuçları Üzerine Sistematik Bir Derleme

Purpose: This review paper provides an inductive analysis on "Smart product service systems" in fashion industry by explaining how servitization as a form of service innovation is critical for sustainability, and the promise of digital technologies for smart fashion industry based on analysing current challenges, opportunities, and digital technologies for the implementation of Smart PSS in the fashion industry.
 Methodology: The study employed an inductive analysis approach to identify the servitization domains, respective Smart PSS applications and the environmental sustainability results. The environmental sustainability results matched with the services were derived from the extensive literature by inductive coding of all identified Smart PSS applications through systematic literature review.
 Findings: Fashion industry applications of Smart PSS were matched with the respective servitization domain, and the discussion were extended with the possible environmental sustainability results based on the literature content. Further research questions have been proposed.
 Originality: Recent research calls for contributions about the effects of digitalization on different outcomes of servitization beyond financial performance and draws attention to the small number of studies addressing the environmental benefits of digital servitization to the circular economy. This study addresses the research gap for a scholarly discussion about the environmental sustainability results of digital servitization in fashion industry and provides a comprehensive future research agenda.

Exploring the Influence of Smart Product Service Systems on Enterprise Competitive Advantage from the Perspective of Value Creation

With the continuous development of information and communication technology, the development of smart product service systems (smart PSS) has become a crucial approach for enterprises to establish a competitive advantage. However, there is still a lack of clarity regarding the impact process of smart PSS on competitive advantage. This paper aims to explore the impact mechanism of smart PSS on competitive advantage from the perspective of value creation, using an intelligent connected vehicle supplier as a case study. The findings reveal that the composition of smart PSS, including smart technology, smart products, and smart services, influences competitive advantage through the value creation process, which involves relationship construction, relationship operation, and value release. Under the smart PSS environment, changes occur in subject relationships, resources, and key elements. In the context of smart PSS, deep cooperation between enterprises and partners focuses on ecological advantages, while general cooperation emphasizes benefit advantages. This research provides valuable insights into the impact of smart PSS composition on competitive advantage and offers reference values for organizations to establish competitive advantage objectives.

A context-aware smart product-service system development approach and application case

With advancements in information and communication technologies (ICTs), one of the epitomes of ICTs are smart product-service systems (SPSSs), which have attracted much research attention in recent years. The capture and analysis of users' dynamic situations are crucial for generating personalized services. Thus the context awareness ability with better self-adaptation and capability to mine information on implicit needs appears to be promising to cope with this issue. However, approaches for the development of a model that integrates context analysis and SPSS have not been fully explored. Therefore, this study presents a new perspective with the incorporation of context awareness, and then proposes a conceptual framework for an SPSS with context awareness (CA-SPSS) and the approach to develop this system. Specifically, the approach consists of four steps. The first step is context acquisition to create a wireless sensor network with wearable devices to acquire the physiological data of users. Second, context modeling procedures are set up on a cloud platform, such as for data collection, storage, and analysis. Moreover, machine learning datasets with information obtained through multiple channels, such as user, physical, sensed and inferred contexts, are generated. Afterwards, neural network models are used for context reasoning to determine the modalities for the users. To produce the appropriate service contents for each user modality level, a multi-criteria decision making process is employed to form customized service strategies for context distribution. To implement the proposed approach, an SPSS case for supporting non-professional sports competitions is developed and assessed in terms of the model performance and user satisfaction. The results show that the model deployed in the system has a better performance than traditional machine learning models. According to the findings from the user experiments, the subjects are very satisfied with the personalized service bundles and intelligence, but find that the reliability is suffering. The case study shows that the proposed CA-SPSS approach contributes to extending the available definitions of context in the literature and effectively guides the further development of SPSSs, especially in sports and mobile health.

A Longitudinal History-Based Review of the Product-Service System: Past, Present, and Future

The research field of product-service systems (PSS) has experienced rapid growth since it emerged at the end of the 80s. Consequently, the conceptual structure of the PSS research field has expanded, and this phenomenon has driven novel research topics and future trends. This study analyzes the evolution and conceptual structure of the PSS research field since its emergence. A systematic literature review based on a bibliometric analysis was conducted, followed by a co-keyword analysis and content analysis, aiming to develop a historical overview of the nature of the research. The dataset involved 868 studies published between 1988 and 2022. The results present an analysis of the evolution of the literature in the following periods: (i) from 1988 to 2015, referred to in this study as the ‘past’, and (ii) from 2016 to 2022 (the ‘present’). A comparative analysis of the two periods is carried out, and the main topics and research trends and perspectives for future studies are identified (the ‘future’). Some of the main research topics include digitalization and sustainability, for which discussions on smart PSS, life-cycle management, ecodesign, knowledge management, development of assessment tools, simulation, and modeling technologies, have appeared. Research opportunities for future studies aligned with those topics are also identified, e.g., map key success factors to positive implementation of proposals that reconcile PSS with digitalization.

Adaptability evaluation of conceptual design for smart product-service system: An integrated rough DEMATEL and Bayesian network model

Smart product service system (PSS) design evaluation plays a crucial role in the early design stage of Smart PSS development. It aims at considering the user's value proposition for Smart PSS in the dimensions of intelligence, sustainability, and society, while also ranking Smart PSS to support delivery risk management under uncertainty. However, related Smart PSS evaluation models advocate the use of multi-criteria decision models for obtaining the intrinsic value of PSS by ignoring the influence of the causality of criteria on Smart PSS design, which results in an unstable evaluation process. Additionally, the adaptiveness of Smart PSS has not been thoroughly explored, and determining the adoption intentions of Smart PSS can be challenging. To fill these gaps, a Smart PSS evaluation model that integrates a rough decision-making trial and evaluation laboratory (DEMATEL) and a Bayesian network (BN) is proposed to support probabilistic reasoning for Smart PSS adaptiveness and reduce the risk of Smart PSS development. First, a set of 17 evaluation criteria is identified, and their causal relationships and weights of the criteria were identified using a rough DEMATEL under uncertainty. Second, a BN-based reasoning model for Smart PSS criteria is developed to evaluate the adaptability of smart PSS by constructing a conditional probability calculation model based on criterion weights. Finally, a multifunctional smart cooking center (MFSCC) case study is presented to demonstrate the applicability of the proposed approach. The belief propagation analysis results revealed the key criteria affecting the MFSCC service system development and provided design strategies to improve the adaptiveness of the Smart PSS.

UNISON framework for user requirement elicitation and classification of smart product-service system

Smart product-service system (smart PSS) has become the manufacturers’ new revenue and sustainable competitiveness sources with the rise of digital servitization. To configure a customer-tailored smart PSS effectively, requirement analysis plays a significant role. Till now, the heterogeneity feature of smart PSS requirements, the usage of user-generated data, and data-driven paradigm have not been considered sufficiently. Hence, this study develops a UNISON framework based on the integration of deep learning approaches for eliciting and evaluating the user requirements for smart PSS with a systematic process, data-driven manner, and quantitative results. Adopting the user-centric perspective, this study employed massive user online reviews as the niche for requirement analysis. The bidirectional long short-term memory (Bi-LSTM) neural network and bi-term topic model (BTM) were employed to extract and elicit the smart PSS requirements in both product and service aspects. Further, a multi-dimensional and automatic requirement evaluation method integrating the sentiment analysis, IPA-Kano model, and opportunity algorithm was proposed for assessing, classifying, and prioritizing the identified requirement items. A smart PSS requirement landscape map was also developed to present the analysis results visually and guide decision-making. An empirical study has been conducted for the smart cleaning robot service system to prove the feasibility of the suggested approach. Enabled by the hybrid application of big data analytics and deep learning techniques, this study can empower the smart PSS provider to understand the user requirements comprehensively and upgrade the smart PSS design effectively.

REQUIREMENTS FOR A SMART PRODUCT-SERVICE SYSTEM DEVELOPMENT FRAMEWORK

AbstractNowadays, companies operate in increasingly competitive and dynamic markets with fast-changing customer needs. Simultaneously, major advances are being made in information and communication technologies, and the digitization of products is progressing. Based on these economic and technological trends, smart product-service systems (PSS) are emerging as a new form of business model. Recent studies show that the transition to developing smart PSS is a major challenge for companies and that they require methodological support, as their internal structures are undergoing significant changes.In order to provide a sound basis for support, we have undertaken a comprehensive study to identify requirements for a smart PSS development framework. 24 interviews and 5 workshops with companies that have recently focused on the development of smart PSS provide a rich set of empirical data to explore the challenges faced by companies today. We systematically analyzed the data and evaluated the results with our respondents. To increase the robustness and generalizability of our findings, we performed a contextual literature review and analyzed additional cases. This led us to a set of 17 requirements for a smart PSS development framework.

A FRAMEWORK FOR SMART EXPERIENCE DESIGN BASED ON ZERO-PARTY CUSTOMER EXPERIENCE DATA

AbstractData about customer experiences would be critical in smart product-service systems. Research is desired on how to establish a framework for Smart Experience Design based on customer experience data so that determining what kinds of customer data are needed and how these data are acquired effectively can be supported. This paper presents a framework and a method to design customer experience personalization services based on customer experience evaluation data obtained in real time and accumulated together with context data. Two illustrative cases are provided to demonstrate the validity of the framework of smart experience design based on customer experience data.

The research landscape around the physical internet – a bibliometric analysis

The concept of the Physical Internet (PI) has been introduced as a vision for globally efficient and sustainable logistics. Examining the activities of the PI since its foundation, enormous efforts can be recognised in the political and business spheres. Furthermore, the topic has received considerable attention from logistics and supply chain management scientists. In this context, a wide variety of dimensions of the PI concept has been investigated. In contrast to some existing qualitative literature reviews, this study focuses on a quantitative review methodology to provide a holistic overview of the PI concept and its underlying dimensions and interrelations. Based on bibliometric performance analysis and science mapping, this research maps and connects the extant PI literature landscape. In doing so, the most important journals, researchers, and institutions in the PI field are identified. Furthermore, eight research topics are grouped thematically, including PI benefits and the challenge of its operationalisation, carriers and shippers in the PI network, PI foundations, smart product-service systems and services, hyperconnected city logistics, information and communication technology requirements, modular PI containers, and organisation and control of PI hubs. Based on the clustering of existing research, the study concludes by providing directions for future research.

Sustainable smart product-service systems: a causal logic framework for impact design

Digital technologies can elevate product-service systems (PSS) to smart PSS, which focus on performance rather than ownership and are considered a means for dematerialization. However, transitioning to smart PSS does not guarantee sustainability. To understand the impact of smart PSS holistically, we take a two-pronged approach. First, we use the theory of change to conceptualize the causal link between sustainable smart PSS and their ultimate impact. We develop a three-step causal logic framework consisting of design, causation, and impact. Within this framework, we identify the business model properties of sustainable smart PSS as design characteristics and categorize the eventual impacts based on the triple bottom line. We introduce the term multi-causal pathway to describe the causation processes underlining the possibility of non-linearity and multi-causality. Second, we conduct a systematic literature review to investigate the mechanisms linking design and impact. Based on an analysis of 63 publications, we identify 17 specific mechanisms and group them into four types: information, resource, empowerment, and adverse mechanisms. Visualizing our results, we develop a morphological box as a toolkit for managers to develop their own impact-oriented logic model by identifying and activating the multi-causal pathway that fosters the desired sustainability effects. Moreover, discussing our framework, we develop research propositions and managerial questions for impact design. By linking the theory of change with the business model impact, we contribute toward a conceptual synthesis for understanding the impact of (sustainable) smart PSS.

Smart experience-oriented customer requirement analysis for smart product service system: A novel hesitant fuzzy linguistic cloud DEMATEL method

Smart product service system (PSS) has become an essential strategy to transform towards digital servitization for manufacturing companies. By leveraging smart capabilities, smart PSS aims to create superior user experience in a smart context. To develop a successful smart PSS, customer requirement management from smart experience perspective is necessary. However, it is a challenging task to identify and evaluate diverse, implicit and interrelated smart experience-oriented customer requirement (SEO-CR) in smart PSS context. Hence, this paper proposes an effective methodology to elicit and analyze SEO-CRs. At first, a generic, two-dimensional SEO-CR system is presented as a basis to derive the tailored SEO-CRs for various smart PSS applications. Second, a novel HFLC-DEMATEL (hesitant fuzzy linguistic cloud-based Decision-making and trial evaluation laboratory) method is proposed to accurately evaluate the priority and complicated interaction of SEO-CRs, considering the hesitancy, fuzziness and randomness under uncertain decision environment. Some new operations (e.g., cloud total-relation matrix and weight determination method) and a cloud influence relation map are developed to fully take advantage of cloud model in DEMATEL implementation. Finally, a real case of smart vehicle service system (SVSS) is presented. The 18 SEO-CRs of the SVSS are derived based on the generalized SEO-CRs. By using HFLC-DEMATEL, some important SEO-CRs in context of SVSS are identified, such as autonomous and convenience. The finding of results can help designers make proper decisions in design and development of SVSS with a superior smart experience. The effectiveness and reliability of the proposed method are validated by conducting some comparative analyses.