Product Service Systems Research Articles

A comprehensive framework for circular product-service systems in infrastructure: Enhancing customer-contractor collaboration

Product-service systems (PSS) represent a business model that increases material decoupling and decreases environmental risks while providing customer value. PSS can help realize a more sustainable construction industry, which remains among the largest polluting and waste-generating sectors. Systemic change in the infrastructure sector requires client involvement, which is represented by the government. However, establishing circular PSS is challenging due to the complexities, which need to combine the lifecycle approach, customer-client aspects, new contracting, knowledge transfer, technology, and PSS-specific aspects. It requires ex-ante evaluation of real case studies to increase knowledge and understanding. This article presents a first-of-its-kind framework for infrastructure based on the current literature and analysis of five infrastructure pilots in the Netherlands (bridge deck, digital road lights, guide rails, roads). The final multistakeholder integrated circular PSS framework includes i) lifecycle perspective and circularity, a) materials and b) management, ii) customer-contractor relationship including a) customer-perspective b) co-creation aspects, c) client-customer hierarchy, iii) technology perspective (functions and resources) iv) business aspects such as a) network and b) value creation and retention. The framework allows customer-contractor communication and can serve as decision support. It is applicable to circular PSS where the customer has more involvement in the formulation of PSS.

Smart Product-Service System for Parking Furniture—Sale of Storage Space in Parking Places

Growing competition, changing customer needs, and growing environmental protection requirements mean companies are forced to change their approach to business. Traditional product sales are being replaced by systemic solutions focused on meeting specific customer requirements while reducing negative impacts on the environment. One such solution is the Product-Service System (PSS). This allows manufacturers to offer their products’ functionalities and features through related services. By extending the life of products, promoting the reuse of materials, and reducing the amount of waste, the implementation of PSS strongly supports sustainable development. The paper focuses on a new product group—garage boxes (GB). It discusses a new PSS business model that responds to the needs of people living in blocks of flats with no tenant storage lockers or rooms in the basement. The new business model sells the function (storing various possessions) and eliminates problems faced by tenants due to the lack of sufficient storage space. It provides customers with high-quality GB for as long as they need them. Customers can pick and choose equipment with additional services depending on their needs. The idea of the model is the outcome of a nationwide study carried out in Poland on a group of 500 residents of blocks of flats and consultations with manufacturers, homeowner associations, wholesale and retail traders, and the financial sector. The study provided us with information and data that provided a comprehensive picture of the problem of the absence of storage lockers or rooms for residents and the needs connected with GB. The results of the conducted research indicate that the developed business model responds to the diverse requirements of residents and supports sustainable solutions. It is an alternative to the lack of a storage unit assigned to each apartment. The business model developed in the paper is highly innovative and comprehensive. This makes it an attractive solution for residents of apartment blocks, and its implementation can significantly reduce the environmental impact.

Holistic Approach to the Indian Higher Education System in Design and Sustainability

Sustainability is a need of the hour as we have very limited resources that are to be restored or utilized carefully. One way toward sustainability is through higher education, with awareness, possible ways of using it, and a change in thought process which will lead to minimal wastage of resources. Design decisions based on sustainability are more than using natural resources that are biodegradable. One of the main strategies of green design is to follow the ‘waste hierarchy’. Green materials are designed to be reusable and recyclable, and they degrade naturally at the end of their life, reducing the environmental footprint of the product. In point of fact, design has the power to stoke and encourage innovation. It can also contribute to the shaping of the world on a variety of levels, from materials to products, product service systems, social organizations, and socio-technical systems. Eco-design is a comprehensive and holistic approach to planning activities that emphasizes the welfare of people and the environment as the final design. ‘It focuses on resource efficiency and the use of environmentally friendly materials to develop products and processes’ (Manzini, 2020, Design, When Everybody Designs). Sustainability for design is sometimes referred to as a lifetime configuration approach since it gathers data on the full life cycles of products and their effects on the environment and living beings. The aim of the paper is to be unambiguous as to why sustainable systems should be included in higher education. An endeavor, additionally, had been to summarize the government policies in order to raise awareness for the next generation. Further, data is collected from respondents who belong to the education system for understanding the importance of sustainability in education. From the gathered information, it was observed that every person unconsciously considers sustainability in their day-to-day lives. However, with mindfulness and plan training there will be an impact on the general public for a better future.

Understanding after-market service channel selection for complex product-services supply chains: A game-theoretical approach

Today, cooperation between an OEM (Original Equipment Manufacturer) of Complex Products and Systems (CoPS) and her multiple Key Component Suppliers (KCSs) is characterized by a strategic partnership where long-term benefits are sought for both parties. Since CoPS after-market service can be provided by the KCS, the OEM, or an MRO (Maintenance, Repair, and Overhaul) party, different after-market service channels can be established. In this paper, we model each of these channels using game theory, compare their main features, and discuss the selection of the optimal after-market service channel. We show that the duration of the after-market service is not influenced by the service channel if the service cost remains constant. If the after-market service costs are equal for all parties, each party would prefer the other to perform the service. In the case of different costs, both the cost of the service and potential market size have the same effect on the OEM’s preference for the after-market service channel as on the CoPS ordered quantities. Furthermore, OEM and KCS after-market service channel preferences depend on market size, and “win-win” situations are discussed for the different channels, along with their impact on the long-term stability of the strategic partnership between KCS and OEM. Finally, a sensitivity analysis is carried out to examine the impact of several key parameters. The results presented in the paper serve to deepen the understanding of complex product-service systems and offer a number of managerial insights to select an appropriate after-market service channel for KCSs.

How to deploy the PSS towards a circular economy in housing? A multiple-case study

Transitioning to a circular housing economy necessitates innovative business models informed by Circular Economy (CE) principles. Yet, a business viewpoint is almost absent from the current circular housing discourse. Of various applicable business approaches, the Product-Service System (PSS) has frequently been put forward due to its resource reduction capacity. Nonetheless, its practical application within the realm of circular housing remains an uncharted territory. To address this knowledge gap, this study employed a multiple-case study, investigating the practices of five frontrunners in the field through interviews and document analysis. The findings informed an empirically grounded framework of 14 guiding principles that provide actionable knowledge for deploying the PSS for a CE in housing across the value proposition, value creation and delivery, and value capture components of the business model concept. Additionally, the findings highlighted the role of intermediary-led collaborative value networks as catalysts for PSS and CE implementation in housing. Beyond these theoretical contributions, the findings and framework presented herein can serve as a dependable point of reference for practitioners in their quest to explore and capture the potential of the PSS towards a CE in housing.

Servitization and product service system: A literature review on value creation

In recent years, the concept of servitization has been widely applied in the management of enterprises. However, changing customer demands and competitive pressures of the market have compelled enterprises to seek innovation. Simultaneously, in the context of the Industry 4.0 trend, the rapid development of digital technologies has led to an increasing number of studies on the integration of servitization and digitization. Therefore, this study, based on VOSviewer, Gephi, Scimago Graphica, and Histcite, analyzes the current state and development trends of research on servitization and product service system innovation from the perspective of value creation. Initially, basic statistical characteristics such as the influential author, geographical cooperation, and highly cited papers are presented by collecting relevant data from the Web of Science core collection database. Subsequently, this study explores the research hotspots and evolutionary trends in servitization and product service system innovation through keyword co-occurrence analysis and cluster analysis. Lastly, from a literature analysis perspective, the application of advanced technologies in servitization, digital servitization from an ecosystem perspective, and the innovative use of microservices architecture in product service systems are summarized and forecasted as research directions, providing theoretical guidance for future research in servitization.

Dynamic elicitation and forecasting innovation requirement of smart product-service system via user-manufacturer value co-creation perspective using multi-source data

Achieving greater efficiency and lower resource consumption is a constant pursuit for successfully developing smart product-service system (PSS). Conducting dynamic requirements analysis is increasingly important in the process while the value co-creation of smart PSS stakeholders has not been sufficiently considered. This study adopts a user-manufacturer value co-creation perspective to explore smart PSS dynamic requirement elicitation and forecasting. Using multi-source data of user online reviews, historical descriptive texts and patent abstracts, this study dynamically elicits the smart PSS innovation requirements using dynamic topic model (DTM) and bidirectional encoder representation from transformers (BERT). Furthermore, the key innovation requirements of smart PSS are identified by integrating their importance and satisfaction values into a dynamic importance-performance analysis (DIPA). Then, the trend of smart PSS key innovation requirements is predicted by the grey forecasting model to determine the smart PSS improvement direction. An empirical study of smartwatch service system is conducted to validate the proposed approach. By blending both user and manufacturer requirements, this study provides a novel framework for dynamic requirement elicitation and forecasting of smart PSS based on multi-source data. It contributes to facilitating the value co-creation during smart PSS development to optimize manufacturer’s R&D resource allocation and enhance user experience.

Self-X heterogeneous attributed graph embedding-based product configuration framework for cognitive mass personalization

Cognitive mass personalization (CMP) is a promising manufacturing paradigm; equipped with cognitive capabilities like reasoning, CMP satisfies changeable needs via configuring personalized products at scale. In CMP, knowledge graphs (KGs) are exploited by smart product-service systems (SPSS) to support cognitive configuration/reconfiguration processes. However, the extant KG-enabled SPSSs are built upon fixed configurations and hybrid frameworks due to lacking a graph embedding (GE) model to render cognitive configuration decisions. In fact, GE is scarcely used in SPSS configuration, because it is not only compromised by the heterogeneity of KGs entailed by content-related specifications and complex structures but also influenced by the feature randomness and feature drift problems, which are triggered by accumulative errors and inconsistent objectives due to noisy assignments and different configuration tasks, separately. To address these limitations, a Self-X Heterogeneous Attributed Graph Embedding (SXHAGE) model is proposed in a Self-X architecture, which includes 1) self-attention graph attention networks, 2) a self-adaptive autoencoder, and 3) self-optimizing training objectives, to present heterogeneous data through jointly optimizing heterogeneous attributed entities and relations. A systematic SXHAGE-based configuration framework, in which product family design and configuration recommending are enabled by graph clustering and link prediction, is developed as a continuous updating loop to proactively configure personalized products. A real-world case study, i.e., configure personalized electric clippers via a web-based sustainable configuration platform, is performed to validate the applicability of the proposed framework in the CMP context. Moreover, extensive experiments on the case study dataset demonstrate the superiority of SXHAGE over the state-of-the-art algorithms, e.g., surpassing Deep Neighbor-Aware Embedding (DNENC) by 18 % in F1-score for graph clustering and by 5 % in ROC-AUC for link prediction.

Building information modeling-based production process optimization model

In the current manufacturing process of enterprises, there are some problems such as poor predictability and low level of intelligence, which lead to high product error rate and affect production efficiency. Therefore, this paper introduces the building information model in the field of engineering construction, and proposes a big data predictive manufacturing model based on the building information model, which divides the production process into production service system, resource planning system, production control system and after-sales service system, and realizes the overall process optimization of planning-production-sales on the basis of the close combination of each system and virtual model system. Finally, the application of error correction process in production line is verified from an empirical point of view, which provides a reference method and path for reducing production error rate and improving work efficiency.

AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems

AbstractSmart Product–Service Systems (S-PSS) represent an innovative business model that integrates intelligent products with advanced digital capabilities and corresponding e-services. The user experience (UX) within an S-PSS is heavily influenced by the customization of services and customer empowerment. However, conventional UX analysis primarily focuses on the design stage and may not adequately respond to the evolving user needs during the usage stage and how to exploit the data surrounding the use of S-PSS. To overcome these limitations, this article introduces a practical framework for developing Adaptive User Interfaces within S-PSS. This framework integrates ontologies and Context-aware recommendation systems, with user interactions serving as the primary data source, facilitating the development of adaptive user interfaces. One of the main contributions of this work lies on the integration of various components to achieve the creation of Adaptive User Interfaces for digital services. A case study of a smart device app is presented, to demonstrate the practical implementation of the framework, with a hands-on development approach, considering technological aspects and utilizing appropriate tools. The results of the evaluation of the recommendation engine show that using a context-aware approach improves the precision of recommendations. Furthermore, pragmatic aspects of UX, such as usefulness and system efficiency, are evaluated with participants with an overall positive impact on the use of the smart device.

Managing the Emergence of AI-Enabled Product-Service Systems in Autonomous Solutions

Managing the Emergence of AI-Enabled Product-Service Systems in Autonomous Solutions

Overview on Application of Operation Research in Various fields

Abstract: In any area of human endeavour, whether it is a production system, business system or service system where an objective is to be optimized. Operation research as coined by Europeans or operations Research by Americans is relatively a new discipline that deals with the application of analytical methods to gain a better decision. Operation research finds a solution to a problem is by breaking down the problem into basic components and then solving it in defined steps by mathematical analysis.

Leveraging digital data to facilitate circular control in the aftermarket – experiences from an international manufacturing firm

PurposeGrowing research attention has been given to both the circular economy and digitalisation in accounting research in recent years, but there are few studies exploring how digital tools are used to develop, analyse and respond to information for circular decision-making in industrial organisations. Therefore, this paper addresses how the data from digital technologies are leveraged in the aftermarket of an industrial firm for circular control.Design/methodology/approachThe paper develops an analytical framework that is then used to frame the findings through a single case study of an international heavy equipment manufacturer for circular control.FindingsThe case provides examples of how digital technologies are used for circular control, framed within the analytical model as the key contribution. The study illustrates the different ways through which the accounting information from such technologies supports the service marketing function through circular control and the types of controls needed for this.Practical implicationsManagers in large industrial organisations should ensure customer-facing staff have adequate digital competences and knowledge of circular products and services for marketing, product design improvements and material recovery that can help decrease costs and improve customer satisfaction. The digital systems need to be integrated with upstream and downstream partners.Social implicationsUnderstanding the transition towards increasingly circular product-service systems in industrial firms is important for current and future generations.Originality/valueThe originality lies in providing an empirical example of how digital technologies can be used to facilitate circular control and support the service marketing function in the aftermarket of an industrial firm.

Design intervention strategies for revitalizing the traditional craft industry through distributed manufacturing

This study explores how design intervention can promote the transformation of the traditional craft industry into the distributed manufacturing model. First, theories relevant to distributed manufacturing and product-service system (PSS) are analyzed. Subsequently, design intervention strategies aimed at revitalizing specific traditional crafts are proposed. Finally, these strategies are explained comprehensively by combining Gourd Play design practice case. The proposed design intervention strategies can help specific traditional crafts achieve distributed manufacturing and improve their sustainability.

A novel requirement elicitation and evaluation framework for product-service systems based on contextual matching and hybrid decision-making

Most studies concerning requirement elicitation and evaluation for product-service systems (PSSs) disregard the importance of completeness and the preferences of different stakeholders. In order to address these issues, a novel requirement elicitation and evaluation framework for PSSs is proposed. First, a new requirement elicitation method based on contextual matching is introduced to capture the complete PSS requirements. Second, a hybrid decision-making method that considers the preferences of users and enterprise experts, as well as the uncertainty and stochasticity during the decision-making process, is proposed to determine the prioritization of PSS requirements. Finally, an illustrative case study of an automatic guided vehicle PSS (AGV-PSS) is demonstrated to examine and justify the proposed framework and methods.

Smart product service resources composition optimization for smart product service system in context of industrial IoT platform

Smart product service resources composition (SPS-RC) is a core issue of smart product service system (PSS) development in the emerging context of industrial internet of things (IIoT) platform, aiming to organize distributed resources for smart product service operation tasks. Existing research mainly focuses on the traditional physical PSS, while contains scant exploration of the new features emerging in context of IIoT platform, leading to an urgent updating need for SPS-RC approaches. Therefore, this study proposes a systematic framework for SPS-RC in context of IIoT platform based on cyber physical system (CPS)-based SPS blueprint, graph theory and adaptive genetic algorithm. In the proposed framework, the SPS-RC problem is formulated in accordance with the realistic smart product service operation process using the CPS-based SPS blueprint. The graph theory and depth-first search algorithm are employed to calculate the composition performance under the environment of heterogenous connection structures between SPS tasks. In addition, an optimization model considering heterogenous composition structures is established with aggregating various quality of service into one comprehensive objective and solved by an adaptive genetic algorithm. Finally, an application of this systematic framework for smart port container crane service demonstrates the feasibility and effectiveness of the proposed approach.

Achieving supply chain agility through product-service systems offering

Achieving supply chain agility through product-service systems offering

Semantic differences and psychological behavior in multi-criteria group decision-making: Do they need consideration?

In Multi-Criteria Group Decision-Making (MCGDM), linguistic evaluation is widely used due to its flexibility. In particular, Personalized Individual Semantics (PIS), namely decision-makers hold heterogeneous understandings of the same word, has been extensively studied to elicit numeric meaning to the linguistic scale. However, few studies consider the need to tailor linguistics to the different indicators used, as well as the semantic difference in the same level linguistic that experts use when situations change. The traditional PIS models overlook the psychological aspect of the decision makers. To solve these problems, this paper proposes a method that considers semantic differences arising from the decision-makers and the indicators and incorporates the experts' psychological behavior. We apply this method to assess the alternatives for a smart refrigerator product service system. The results suggest that a large semantic difference, when evaluating the linguistic indicators, can influence the final outcome. We validate the flexibility and the effectiveness of the method by comparing against the base case of no semantic difference, using the Euclidean and Manhattan distance measures.

A simulation-based approach for investigating the dynamics of rebound effects in the circular economy: A case of use-oriented product/service system

Current research in Circular Economy (CE) fails to address the occurrence of Rebound Effects (RE), which are systemic and behavioural responses to the implementation of interventions hindering the potential sustainability benefits. This paper aims to advance the academic discussion and the practical consideration of RE by exploring the potential of using System Dynamics (SD) to enable the ex-ante identification of potential RE of CE initiatives. A five-stage simulation-based approach for the identification and mitigation of potential rebound effects (AIMRE) is proposed. Its application is demonstrated in a use-oriented product/service system (PSS) case focused on a high-end dress rental service. The AIMRE enables the representation of the magnitude and reasons for RE occurrence through 14 scenarios. The finding highlights the importance of considering the interplay between consumers' and companies’ decision-making processes in quantifying, understanding, and mitigating RE occurrence.

Cognitive intelligence-enabled requirements elicitation for design optimisation of smart product-service system

The rapid development of advanced technologies provides futuristic option to enhance product value with digital services, which the concept of Smart Product-Service System (SPSS) was proposed. SPSS focuses on usage data, the whole lifecycle, and the iterative optimisation. A large amount of data and context information can be collected during the usage stage, which can be used to elicit requirements to guide further design. How to realise the requirement elicitation with cognitive intelligence based on usage data is the key step for design optimisation. Therefore, this research proposes a cognitive intelligence-enabled requirements elicitation framework to help designers promote the design optimisation process. First, the digital twin-driven data collection architecture of SPSS is proposed by considering multi-sources and multi-stages. Second, the behaviour of SPSS is modelled based on Auto-Encoder which is constructed using deep learning to cognise SPSS performance. Third, the corresponding behaviour model is interpreted based on Shapley Addictive exPlanations (SHAP) to discover key factors with cognitive intelligence. Finally, the domain knowledge graph is used to generate the optimisation requirements for further design. To demonstrate the feasibility and advantages of the proposed framework, this study adopts the case study of wind turbines for illustration and verification.