2020
DOI: 10.1016/j.aei.2020.101042
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How sustainable is smart PSS? An integrated evaluation approach based on rough BWM and TODIM

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Cited by 47 publications
(35 citation statements)
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“…There are, thus, both pros and cons with smart PSS, e.g., pros: reduced energy consumption by responses to customer behavior in real time; cons: privacy loss, or social discrepancies. Liu et al [68] therefore propose a method to particularly evaluate the sustainability of smart PSS and suggest how to weight the different sustainability criteria in such a method. Kwok et al [69] also discuss how to give weighting to different sustainability criteria in support tools for sustainability assessment in early design phases.…”
Section: Number Of Articlesmentioning
confidence: 99%
See 3 more Smart Citations
“…There are, thus, both pros and cons with smart PSS, e.g., pros: reduced energy consumption by responses to customer behavior in real time; cons: privacy loss, or social discrepancies. Liu et al [68] therefore propose a method to particularly evaluate the sustainability of smart PSS and suggest how to weight the different sustainability criteria in such a method. Kwok et al [69] also discuss how to give weighting to different sustainability criteria in support tools for sustainability assessment in early design phases.…”
Section: Number Of Articlesmentioning
confidence: 99%
“…However, which of and how the sustainability criteria are selected in the first place is even more important as the evaluation will be of less value or even misleading if the correct sustainability criteria are not selected. There are different approaches between the method suggested by Liu et al [68] and the method proposed by Kwok et al [69]. Liu et al [68] use a few criteria covering The literature also states that digitalization and servitization work best together [48] and PSS are rarely implemented without ICT, according to Belvedere et al [61].…”
Section: Number Of Articlesmentioning
confidence: 99%
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“…following that, Zhai et al (2008) introduced the rough number concept. Since then, rough set theory has been incorporated into many decision-making techniques, such as TOPSIS (Stevic et al 2018, Shojaei & Bolvardizadeh., 2020, AHP (Pamučar et al, 2018), ANP (Li and Wang, 2018), DEMATEL (Song et al, 2020), and BWM (Liu et al, 2020). By aggregating group information, rough set theory can overcome the vagueness and subjectivity that arise from diverging judgments in a group decision-making process (Mao et al, 2020).…”
Section: Rough Set Theorymentioning
confidence: 99%