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How sustainable is smart PSS? An integrated evaluation approach based on rough BWM and TODIM

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Abstract

Smart Product-Service Systems (PSS) integrates smart products and e-services into a total solution with Information and Communication Technology (ICT). It is necessary to assess the Smart PSS from the perspective of sustainability in the early design phase to reduce potential failure to meet the environmental and social requirements in delivery stage. However, the existing PSS evaluation frameworks consider less about characteristics of digitalization and smartness. Moreover, the previous criteria weighting methods for PSS evaluation becomes time consuming and frustrating when comparing too many criteria to determine the weights for criteria. In addition, the existing PSS evaluation methods often omit decision makers’ bounded rationality and vagueness of judgements. To solve these problems, a novel method is proposed by integrating the merit of Best Worst Method (BWM) in reducing the decision makers’ burden of pairwise comparisons of criteria importance, the strengths of TODIM (an acronym in Portuguese of Interactive and Multi-Criteria Decision Making) in dealing with decision makers’ bounded rationality and the flexibility of Rough Set Theory (RST) in handling vagueness without prior information. Finally, a case study of sustainability evaluation for smart air-conditioner PSS is used to validate the effectiveness and efficiency of the proposed method.

Introduction

With the rapid development of information and communication technology (ICT), product service systems (PSS) providers are going to serve customers with an integration of smart products and e-services [1], [2]. This type of PSS, viz. Smart PSS, follows the fundamental principles of traditional PSS as an effective business model with sustainability concerns [3], which is less harmful to environment and achieves a win-win situation for the stakeholders [4], [5]. It can help companies to achieve sustainability by upgrading products and services with ICT [6].

It is widely believed that Smart PSS has positive impacts on sustainability. The embedding ICT enables companies collecting customers’ behavioral data in real time, responding immediately with remotely controlled devices, and reducing costs of energy consumption [7]. For example, Schindler Co. uses instant data, which are collected from the app FieldLink installed on customers’ iPhone or iPad, to predict maintenance requirements. While the growth of a Smart PSS may increase productivity and benefit customers, it also raises potential sustainability challenges, including the cybersecurity vulnerabilities [8], privacy loss [9], [10], CO2 emissions associated with increased electricity generation demand [11], and social discrepancies caused by the widening gap derived from automation of information processing and delivery of services, commonly referred to as the “digital divide” between those who benefit from Smart PSS, and those who may lose jobs, economic resources, or other social benefits [12]. Thus, it is necessary to evaluate the sustainability of conceptual Smart PSS solutions in the early concept design phase based on the principles of the triple bottom line (TBL), which helps to select more sustainable alternatives to reduce potential damage to economy, environment and society in the later stages of the holistic life cycle of PSS [13], [14].

Considering the multiple criteria based on the principles of the TBL, sustainability evaluation of Smart PSS solutions is a typical multi-criteria decision making (MCDM) problem. It’s difficult for the conventional approaches (e.g. analytical hierarchy process, AHP) to solve such problems especially when the number of criteria increases [15]. Additionally, it is difficult for the designers to obtain accurate and quantitative sustainability information of Smart PSS during the early design stage because of the interactions of product and service as well as the complexity of performance [16]. In this respect, some evaluation approaches requiring accurate inputs and outputs (e.g. life cycle assessment, LCA) are not suitable to solve the problem of concept sustainability assessment in the early design stage [17]. Moreover, due to the complexity of PSS business mode, traditional environmental assessment methods, such as LCA, can hardly handle the sustainability assessment problem of smart hybrid solutions including tangible products and intangible services [18], [19], [20]. Although green criteria for conventional PSS are studied a lot by researchers, there is a lack of discussion about the sustainability of Smart PSS [4], [21].

When deal with the MCDM problem under the concerns of sustainability, hybrid decision methods are in the highlighted position. Commonly, a group of experts are invited to evaluate the sustainability of alternative Smart PSS offerings. However, inconsistency may occur in group decisions due to subjectivity and vagueness of judgments [22]. Thus the decision method should be developed to reduce decision maker’s uncertainty of assessments [23]. To meet such concerns, a novel method integrating rough set theory (RST), the best worst method (BWM) and TODIM (an acronym in Portuguese of Interactive and Multi-Criteria Decision Making) is proposed in this paper. RST can effectively reduce inconsistency among group members under uncertainty [22]; TODIM deals with decision makers’ uncertainty (either opportunity or risk) with prospect theory (PT) [24]; the latest MCDM method BWM is integrated to reduce inconsistency of deciding criteria weights with less pairwise comparison data [15].

The structure of this paper is shown as following: Section 1 introduces the background of evaluating sustainability of Smart PSS and the origins of the proposed decision making methods. Section 2 reviews related literatures of Smart PSS, sustainability criteria of Smart PSS and basic knowledge about RST, BWM and TODIM. Section 3 proposes the integrated rough BWM-TODIM (RBT) method, followed by Section 4, in which the proposed sustainability evaluation method is applied to the evaluating of smart air-conditioner PSS alternatives. The comparisons between the proposed approach and other methods are also given in Section 4. The paper closes with the conclusion of highlights of the proposed RBT method and the directions for future research.

Section snippets

Smart PSS

PSS is firstly proposed by Goedkoop [25] to address the sustainability issues in economic growth. It enhances companies’ competitiveness by satisfying customer requirements with high value-added solutions [23], [25], [26], [27].

The fast development of ICT triggers an innovation with smart, connected products (SCP) [3], [8]. Smart PSS is an upgradation of general PSS [28], [29] that integrates SCP and e-services into single solution [2]. It is a connected and value co-creation network that

The proposed method

To manipulate the complexity of criteria weights determination and experts’ bounded rationality in smart PSS sustainability evaluation, a hybrid MCGDM method is developed in this section. The detailed process of the novel MCGDM method is proposed in this section. The method is named as RBT method. ‘R’ stands for RST, ‘B’ stands for BWM and ‘T’ stands for TODIM. The framework of RBT method is depicted in Fig. 1.

Phase 1: Calculate the weights of criteria with rough BWM from each expert.

Step 1.1:

Case background

With the improvement of living standards, people pay more and more attention to comfortable living environment, especially good air condition. However, air conditioners consume plenty power in commercial buildings and homes [45], [64]. Unlike conventional air-conditioners, smart air-conditioner PSS automatically sense environment and proactively react, which can reduce power consumption and greenhouse gas emissions. For example, Song et al. proposed an IoT-based smart controlling system for

Conclusion

Sustainability evaluation is critical in the design and development of conceptual Smart PSS offerings. The evaluation criteria set is generated by extracting related principles following TBL and the life cycle of Smart PSS. Afterward, a novel hybrid MCGDM method integrating RST, BWM and TODIM is proposed. The case study on prioritization of smart air-conditioner PSSs validates the effectiveness of the proposed model.

In summary, the proposed method contributes to the sustainability evaluation of

Acknowledgement

This research is supported by the National Natural Science Foundation of China (No. 71971012, 71501006, 71332003) and the support of China Scholarship Council (Student No. 201706020084). Grateful appreciates also go to the editor and the anonymous reviewers, whose comments are valuable to improve our manuscript.

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