A fuzzy multicriteria group decision approach for circular business models prioritization

according to the number of alternatives (Saaty, 2008Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83-98. http://dx.doi.org/10.1504/IJSSCI.2008.017590.
http://dx.doi.org/10.1504/IJSSCI.2008.01... ).

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Table 6
Fuzzy linguistic terms for the pairwise comparisons.

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Table 7
Fuzzy linguistic terms to represent the intensity level of the relationship.

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Table 8
Expert’s pairwise comparisons between CE principles.

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Table 9
Aggregated decision matrix of the CE principles pairwise comparisons.

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Table 10
Circular Business Models closeness coefficient

C C_{i}

and rank.

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Table 11
Performance of each CBM when isolating each dimension of indicators.

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Table 12
Performance of each CBM when with integral weight in each criterion.

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

(19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27)

(28)

(29)

(30)

(31)

(32)

(33)

	Systems Thinking	Strong	Strong	Strong	Strong	Strong	Strong	Strong	Strong	Strong
Principles	Innovation	Weak	Strong	Strong	Weak	Weak	Strong	Strong	Strong	Strong
	Stewardship	Strong	Strong	Strong	Strong	Strong	Strong	Strong	Strong	Strong
	Collaboration	Medium	Medium	Strong	Medium	Strong	Weak	Weak	Weak	Strong
	Value Optimization	Strong	Strong	Strong	Strong	Strong	Strong	Strong	Strong	Weak
	Transparency	Medium	Medium	Medium	Medium	Medium	Medium	Medium	Medium	Strong
	Indicators	Dimension	Material
Control Variables	Indicators	*Reduction of raw materials*	*Renewability*	*Reciclability*	*Reduction of toxic substances*	*Reuse*	*Remanufacturing*	*Refurbishment*	*Product Longevity*	*Stakeholder structure and diversity*
Circular Business Models	Product as a Service	Strong	Weak	Weak	Weak	Strong	Weak	Strong	Strong	Strong
	Sharing Economy	Strong	Medium	Medium	Medium	Strong	Medium	Medium	Medium	Medium
	Product life extension	Strong	Weak	Strong	Strong	Strong	Strong	Strong	Strong	Strong
	On-demand	Strong	Weak	Weak	Weak	Medium	Medium	Medium	Medium	Medium
	Recovery by-products	Strong	Medium	Strong	Strong	Strong	Strong	Strong	Strong	Strong
	Dematerialization	Strong	Medium	Medium	Medium	Medium	Medium	Medium	Medium	Medium

	Systems Thinking	Weak	Weak	Medium
Principles	Innovation	Weak	Weak	Strong
	Stewardship	Strong	Weak	Medium
	Collaboration	Weak	Strong	Medium
	Value Optimization	Strong	Weak	Strong
	Transparency	Weak	Medium	Medium
	Indicators	Dimension	Economic
Control Variables	Indicators	*Financial results*	*Taxation or regulatory milestones*	*Circular investment*
Circular Business Models	Product as a Service	Strong	Strong	Strong
	Sharing Economy	Strong	Medium	Strong
	Product life extension	Strong	Medium	Strong
	On-demand	Strong	Weak	Weak
	Recovery by-products	Strong	Strong	Strong
	Dematerialization	Strong	Medium	Strong

	Systems Thinking	Strong	Strong	Strong	Strong	Strong	Strong
Principles	Innovation	Strong	Weak	Medium	Medium	Strong	Strong
	Stewardship	Weak	Strong	Medium	Strong	Strong	Weak
	Collaboration	Strong	Weak	Strong	Weak	Strong	Strong
	Value Optimization	Weak	Strong	Strong	Weak	Weak	Strong
	Transparency	Medium	Medium	Strong	Medium	Strong	Strong
	Indicators	Dimension
Control Variables	Indicators	Job creation	Income generated by jobs	Employee participation in the circular business model	Market characterization	Involvement of stakeholders in decision-making processes	Mindset / cultural change
Circular Business Models	Product as a Service	Strong	Strong	Strong	Strong	Strong	Strong
	Sharing Economy	Medium	Medium	Medium	Strong	Strong	Weak
	Product life extension	Strong	Strong	Strong	Strong	Strong	Weak
	On-demand	Strong	Strong	Weak	Strong	Strong	Strong
	Recovery by-products	Strong	Strong	Strong	Strong	Strong	Weak
	Dematerialization	Medium	Medium	Strong	Strong	Strong	Weak

Authors	Proposition	Technique	Criteria
Kharola et al. (2022)Kharola, S., Ram, M., Kumar Mangla, S., Goyal, N., Nautiyal, O. P., Pant, D., & Kazancoglu, Y. (2022). Exploring the green waste management problem in food supply chains: a circular economy context. Journal of Cleaner Production, 351, 131355. http://dx.doi.org/10.1016/j.jclepro.2022.131355. http://dx.doi.org/10.1016/j.jclepro.2022...	Rank the best preferred and least preferred criteria as key practices for Food Supply Chain that contribute to food waste reduction to ensure green waste management.	Best-Worst Method (BWM)	Enhancing productivity in practices
			Protection and infrastructure
			Skill and training
			Exposure and capacity building
			Environmental and circular economy involving practices
Govindan et al. (2022)Govindan, K., Nasr, A. K., Karimi, F., & Mina, H. (2022). Circular economy adoption barriers: An extended fuzzy best–worst method using fuzzy DEMATEL and Supermatrix structure. Business Strategy and the Environment, 31(4), 1566-1586. http://dx.doi.org/10.1002/bse.2970. http://dx.doi.org/10.1002/bse.2970...	Raking CE adoption barriers in the cable and wire industry. Adoption barriers are weighted using BWM, the interdependencies among components are calculated by DEMATEL and barriers are ranked using Supermatrix Structure.	Best-Worst Method (BWM), fuzzy decision-making trial and evaluation laboratory (DEMATEL), and Supermatrix structure	Customer
			Financial
			Learning and growth
			Internal process
Khan & Ali (2022a)Khan, F., & Ali, Y. (2022a). A facilitating framework for a developing country to adopt smart waste management in the context of circular economy. Environmental Science and Pollution Research International, 29(18), 26336-26351. http://dx.doi.org/10.1007/s11356-021-17573-5. PMid:34850345. http://dx.doi.org/10.1007/s11356-021-175...	A framework for the adoption of smart waste management in the context of CE for Pakistan. SWARA was used for allocating weights to the determined criteria; whereas, fuzzy VIKOR to rank the critical facilitators adopted from the secondary literature.	Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) and the fuzzy VIšekriterijumsko kompromisno rangiranje (VIKOR)	Environmental
			Social
			Economic
			Technical
			Regulatory perspectives
Kazancoglu et al. (2022)Kazancoglu, Y., Ozkan-Ozen, Y. D., Mangla, S. K., & Ram, M. (2022). Risk assessment for sustainability in e-waste recycling in circular economy. Clean Technologies and Environmental Policy, 24(4), 1145-1157. http://dx.doi.org/10.1007/s10098-020-01901-3. http://dx.doi.org/10.1007/s10098-020-019...	A decision tool under uncertain and risky conditions for achieving sustainability in electronic waste (e-waste) recycling in circular economy. TODIM was used to evaluate the irrationality and risk attitudes of decision makers in a risky and uncertain environment.	TODIM	Revenue generated
			Part demand
			Disposal cost
			Quality risks
			Ergonomic risk
			Accident risk
			Crush
			Lifting/moving hazard
			Flammable
			Solid waste
			Oxidation
			Energy consumption
Erol et al. (2022)Erol, I., Murat Ar, I., Peker, I., & Searcy, C. (2022). Alleviating the impact of the barriers to circular economy adoption through blockchain: an investigation using an integrated MCDM-based QFD with hesitant fuzzy linguistic term sets. Computers & Industrial Engineering, 165, 107962. http://dx.doi.org/10.1016/j.cie.2022.107962. http://dx.doi.org/10.1016/j.cie.2022.107...	An integrated decision framework to investigate the true potential of blockchain to address the CE adoption barriers.	Hesistant Fuzzy Linguistic Term Sets (HFLTS)	Transparent traceability management
			Improved collaboration and coordination
			Robust supply chain ecosystem
			Improved quality of life
			Higher level of trust
			Coopetition and prosumerism
			Sustainable behavior
Govindan (2022)Govindan, K. (2022). Tunneling the barriers of blockchain technology in remanufacturing for achieving sustainable development goals: a circular manufacturing perspective. Business Strategy and the Environment, bse.3031. http://dx.doi.org/10.1002/bse.3031. http://dx.doi.org/10.1002/bse.3031...	Identifies the barriers that exist with the implementation of blockchain technology in the application of the remanufacturing sector. DEMATEL is used to identify the effective and most influential barriers among common barriers.	DEMATEL	CE barriers
Shahidzadeh & Shokouhyar (2022)Shahidzadeh, M. H., & Shokouhyar, S. (2022). Toward the closed-loop sustainability development model: a reverse logistics multi-criteria decision-making analysis. Environment, Development and Sustainability, 1-93. http://dx.doi.org/10.1007/s10668-022-02216-7. http://dx.doi.org/10.1007/s10668-022-022...	Conceptual model of sustainability was proposed, discussed and analyzed to determine the relationship between reverse logistics performance and sustainability.	Hesitant fuzzy DEMATEL	Economics
			Environmental
			Social
			Consumer
Amiri et al. (2022)Amiri, M., Hashemi-Tabatabaei, M., Ghahremanloo, M., Keshavarz-Ghorabaee, M., Zavadskas, E. K., & Salimi-Zavieh, S. G. (2022). Evaluating barriers and challenges of circular supply chains using a decision-making model based on rough sets. International Journal of Environmental Science and Technology, 1-22. http://dx.doi.org/10.1007/s13762-021-03899-7. http://dx.doi.org/10.1007/s13762-021-038...	Find the main issues and prioritize the challenges related to the adoption of circular supply chain management.	BWM and rough set	Financial and economic
			Rules and regulations
			Technology
			Behavioral-social
			Supply chain management
			Product specifications
			Market and competition
Khan & Ali (2022b)Khan, F., & Ali, Y. (2022b). Implementation of the circular supply chain management in the pharmaceutical industry. Environment, Development and Sustainability, 1-27. http://dx.doi.org/10.1007/s10668-021-02007-6. PMid:35035276. http://dx.doi.org/10.1007/s10668-021-020...	A model to guide pharmaceutical industries to adopt circular supply chain management. F-FUCOM was used to allocating weights and prioritizing the barriers and FQFD was used to rank the enablers.	Fuzzy full consistency method (F-FUCOM) and Fuzzy quality function deployment (FQFD)	CE Barriers
			CE Enablers
Bertassini et al. (2022b)	An approach to assess the readiness of companies to implement a CE-oriented culture. FDM was used to identify CE culture elements and FIS was used to classify organizations in levels of readiness.	Fuzzy Delphi Methodlogy (FDM) and Fuzzy Inference Systems (FIS)	CE-oriented culture elements
Bertassini et al. (2022b)			CE-oriented culture building blocks
Husain et al. (2021)Husain, Z., Maqbool, A., Haleem, A., Pathak, R. D., & Samson, D. (2021). Analyzing the business models for circular economy implementation: a fuzzy TOPSIS approach. Operations Management Research, 14(3), 256-271. http://dx.doi.org/10.1007/s12063-021-00197-w. http://dx.doi.org/10.1007/s12063-021-001...	Rank the business models for the successful adoption of the circular economy.	Fuzzy for Order of Preference by Similarity to Ideal Solution (TOPSIS)	Partnership
			Activities
			Resources
			Value proposition
			Customer relationships
			Distribution Channels
			Client segments
			Cost structure
			Revenue flows
Pamucar et al. (2021)Pamucar, D., Deveci, M., Gokasar, I., Işık, M., & Zizovic, M. (2021). Circular economy concepts in urban mobility alternatives using integrated DIBR method and fuzzy Dombi CoCoSo model. Journal of Cleaner Production, 323, 129096. http://dx.doi.org/10.1016/j.jclepro.2021.129096. http://dx.doi.org/10.1016/j.jclepro.2021...	A decision-making model to prioritize the possible CE concepts for the planning of urban mobility in a big city.	Fuzzy Dombi based Combined Compromise Solution (D’CoCoSo)	Economic productivity aspects
			Health and environment aspects
			Social infrastructure and cultural aspects
			Policy aspects
			Transportation aspects
Nag et al. (2021)Nag, U., Sharma, S. K., & Govindan, K. (2021). Investigating drivers of circular supply chain with product-service system in automotive firms of an emerging economy. Journal of Cleaner Production, 319, 128629. http://dx.doi.org/10.1016/j.jclepro.2021.128629. http://dx.doi.org/10.1016/j.jclepro.2021...	A theoretical framework that identifies and evaluates drivers and sub-drivers that are needed for the adoption of circular principles in product-service system business model.	Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL)	Circular Value Marketing
			Circular Services
			Circular product manufacturing
			Reverse flow
Karuppiah et al. (2021)Karuppiah, K., Sankaranarayanan, B., Ali, S. M., Jabbour, C. J. C., & Bhalaji, R. K. A. (2021). Inhibitors to circular economy practices in the leather industry using an integrated approach: implications for sustainable development goals in emerging economies. Sustainable Production and Consumption, 27, 1554-1568. http://dx.doi.org/10.1016/j.spc.2021.03.015. http://dx.doi.org/10.1016/j.spc.2021.03....	A methodological framework for evaluating the inhibitors to circular economy practices in the leather industry.	Grey-decision making trial and evaluation laboratory (DEMATEL) and fuzzy complex proportional assessment method	Organisational issues
			Regulatory issues
			Market issues
			Technological issues
			Economic issues
			Social issues
Gupta et al. (2021)Gupta, H., Kumar, A., & Wasan, P. (2021). Industry 4.0, cleaner production and circular economy: An integrative framework for evaluating ethical and sustainable business performance of manufacturing organizations. Journal of Cleaner Production, 295, 126253. http://dx.doi.org/10.1016/j.jclepro.2021.126253. http://dx.doi.org/10.1016/j.jclepro.2021...	A framework to assess sustainability performance of manufacturing companies and to guide them in prioritizing investment in potential solutions for enhancing performance on sustainability.	BWM and CoCoSo	Industry 4.0
			Sustainable and cleaner production
			Circular Economy
Fidan et al. (2021)Fidan, F. Ş., Aydoğan, E. K., & Uzal, N. (2021). An integrated life cycle assessment approach for denim fabric production using recycled cotton fibers and combined heat and power plant. Journal of Cleaner Production, 287, 125439. http://dx.doi.org/10.1016/j.jclepro.2020.125439. http://dx.doi.org/10.1016/j.jclepro.2020...	Investigate the contribution of using mechanically recycled cotton fiber instead of virgin cotton fiber.	TODIM	Washed weight
			Tear
			Tensile
			Cost-saving
Lee et al. (2021)Lee, Y., Hu, J., & Lim, M. K. (2021). Maximising the circular economy and sustainability outcomes: an end-of-life tyre recycling outlets selection model. International Journal of Production Economics, 232, 107965. http://dx.doi.org/10.1016/j.ijpe.2020.107965. http://dx.doi.org/10.1016/j.ijpe.2020.10...	A list of evaluation criteria to rank recycling outlets, and develop and end-of-life tyre outlets selection matrix.	Fuzzy AHP and fuzzy TOPSIS	Economy
			Environment
			Social
Ali et al. (2021)Ali, Y., Jokhio, D. H., Dojki, A. A., Rehman, O. U., Khan, F., & Salman, A. (2021). Adoption of circular economy for food waste management in the context of a developing country. Waste Management & Research, 40(6), 734242X211038198. https://doi.org/10.1177/0734242X211038198.	Identify and prioritize CE barriers in order of their significance.	TOPSIS	CE Barriers
Agrawal et al. (2021)Agrawal, R., Wankhede, V. A., Kumar, A., & Luthra, S. (2021). Analysing the roadblocks of circular economy adoption in the automobile sector: reducing waste and environmental perspectives. Business Strategy and the Environment, 30(2), 1051-1066. http://dx.doi.org/10.1002/bse.2669. http://dx.doi.org/10.1002/bse.2669...	Analysis and prioritization of roadblocks for the implementation of CE in the Indian automobile industry.	TOPSIS	Technical
			Economic
			Cultural
Lahane & Kant (2021)Lahane, S., & Kant, R. (2021). Evaluation and ranking of solutions to mitigate circular supply chain risks. Sustainable Production and Consumption, 27, 753-773. https://doi.org/10.1016/j.spc.2021.01.034. https://doi.org/10.1016/j.spc.2021.01.03...	A framework to rank solutions for mitigating the risks of circular supply chain implementation.	Fuzzy AHP and fuzzy VIKOR	Operational and technological risks
			Product recovery risk
			Supply risks
			Demand risks
			Environmental risks
			Economical risks
			Social risks
Padilla-Rivera et al. (2021)Padilla-Rivera, A., do Carmo, B. B. T., Arcese, G., & Merveille, N. (2021). Social circular economy indicators: Selection through fuzzy delphi method. Sustainable Production and Consumption, 26, 101-110. http://dx.doi.org/10.1016/j.spc.2020.09.015. http://dx.doi.org/10.1016/j.spc.2020.09....	An approach to identify key social indicators of CE.	Fuzzy Delphi	CE indicators
Tariq et al. (2021)Tariq, H., Ali, Y., Khan, A. U., Petrillo, A., & De Felice, F. (2021). Sustainable production of diapers and their potential outputs for the Pakistani market in the circular economy perspective. The Science of the Total Environment, 769, 145084. http://dx.doi.org/10.1016/j.scitotenv.2021.145084. PMid:33486174. http://dx.doi.org/10.1016/j.scitotenv.20...	Evaluate how multiple alternatives for disposal of diapers can provide sustainable advantages in the Pakistan scenario.	TOPSIS	Emissions
			Socio-culture
			Technology
			Cost
			Feasibility
			Energy recovery
Haleem et al. (2021)Haleem, A., Khan, S., Luthra, S., Varshney, H., Alam, M., & Khan, M. I. (2021). Supplier evaluation in the context of circular economy: a forward step for resilient business and environment concern. Business Strategy and the Environment, 30(4), 2119-2146. http://dx.doi.org/10.1002/bse.2736. http://dx.doi.org/10.1002/bse.2736...	A framework for evaluating suppliers concerning the CE implementation.	Fuzzy CRITIC and TOPSIS	Technological capability and energy consumption
			Economic
			Environment
			Social and regulatory support/requirement
			Logistics
			Management’s respect towards CE
Bertassini et al. (2021a)Bertassini, A. C., Zanon, L. G., Azarias, J. G., Gerolam, M. C., & Omettoo, A. R. (2021a). Circular business ecosystem innovation: a guide for mapping stakeholders, capturing values, and finding new opportunities. Sustainable Production and Consumption, 27, 436-448. https://doi.org/10.1016/j.spc.2020.12.004. https://doi.org/10.1016/j.spc.2020.12.00...	A guide for mapping stakeholders, capturing circular values and finding new CE implementation opportunities. FCM to assess the relations between captured values and CE principles	Fuzzy Cognitive Maps (FCM)	Circular captured values
		Fuzzy Cognitive Maps (FCM)	CE principles
Gue et al., 2020Gue, I. H. V., Promentilla, M. A. B., Tan, R. R., & Ubando, A. T. (2020). Sector perception of circular economy driver interrelationships. Journal of Cleaner Production, 276, 123204. http://dx.doi.org/10.1016/j.jclepro.2020.123204. http://dx.doi.org/10.1016/j.jclepro.2020...	A methodological framework for mapping causality networks for macro-level transition towards circular economy based on sector perceptions.	DEMATEL	Government support
			Company culture
			Consumer demand
			Social recognition
			Economic attractiveness
			Information to practitioners
Khan & Haleem (2020)Khan, S., & Haleem, A. (2020). Strategies to implement circular economy practices: a fuzzy DEMATEL approach. Journal of Industrial Integration and Management, 5(2), 253-269. http://dx.doi.org/10.1142/S2424862220500050. http://dx.doi.org/10.1142/S2424862220500...	Evaluate the key strategies to accomplish CE and to develop a causal relationship among these strategies.	DEMATEL	CE strategies
Mahpour (2018)Mahpour, A. (2018). Prioritizing barriers to adopt circular economy in construction and demolition waste management. Resources, Conservation and Recycling, 134, 216-227. http://dx.doi.org/10.1016/j.resconrec.2018.01.026. http://dx.doi.org/10.1016/j.resconrec.20...	Prioritize the potential barriers to adopt circular economy in construction and demolition waste management from behavioral, technical, and legal perspectives and aggregately.	TOPSIS	Behavioral
			Technical
			Legal
Zhao et al. (2017)Zhao, H., Zhao, H., & Guo, S. (2017). Evaluating the comprehensive benefit of eco-industrial parks by employing multi-criteria decision making approach for circular economy. Journal of Cleaner Production, 142, 2262-2276. http://dx.doi.org/10.1016/j.jclepro.2016.11.041. http://dx.doi.org/10.1016/j.jclepro.2016...	A hybrid framework for evaluating the comprehensive benefit of eco-industrial parks from the perspective of circular economy.	Grey-Delphi and fuzzy-VIKOR	Economic
			Social
			Environmental
			Ecology industry construction
			Management

$n$	3	4	5	6	7	8	9	10
$R I_{n}$	0.58	0.9	1.12	1.24	1.32	1.41	1.45	1.49

Fuzzy Linguistic Terms	Triangular Fuzzy Number
Extremely more important (EI)	(7, 9, 9)
Much more important (MMI)	(3, 5, 7)
More important (MI)	(1, 3, 5)
A little more important (LMI)	(1, 1, 3)
Equally important (EI)	(1, 1, 1)

Fuzzy Linguistic Terms	Triangular Fuzzy Number
Strong	(5, 9, 9)
Medium	(1, 5, 9)
Weak	(1, 1, 5)

	System Thinking	Innovation	Stewardship	Collaboration	Value Optimization	Transparency
DM1
System Thinking	EI	EI	EI	LMI	LMI	MI
Innovation	1 / EI	EI	EI	LMI	LMI	MI
Stewardship	1 / EI	1 / EI	EI	LMI	LMI	MI
Collaboration	1 / LMI	1 / LMI	1 / LMI	EI	EI	LMI
Value Optimization	1 / LMI	1 / LMI	1 / LMI	1 / EI	EI	LMI
Transparency	1 / MI	1 / MI	1 / MI	1 / LMI	1 / LMI	EI
DM2
System Thinking	EI	EI	EI	LMI	LMI	MI
Innovation	1 / EI	EI	EI	LMI	LMI	MI
Stewardship	1 / EI	1 / EI	EI	EI	MI	LMI
Collaboration	1 / LMI	1 / LMI	1 / EI	EI	EI	LMI
Value Optimization	1 / LMI	1 / LMI	1 / MI	1 / EI	EI	LMI
Transparency	1 / MI	1 / LMI	1 / LMI	1 / LMI	1 / LMI	EI
DM3
System Thinking	EI	EI	EI	EI	LMI	MI
Innovation	1 / EI	EI	LMI	LMI	LMI	MI
Stewardship	1 / EI	1 / LMI	EI	LMI	LMI	MI
Collaboration	1 / EI	1 / LMI	1 / LMI	EI	LMI	LMI
Value Optimization	1 / LMI	1 / LMI	1 / LMI	1 / LMI	EI	EI
Transparency	1 / MI	1 / MI	1 / MI	1 / LMI	1 / EI	EI
DM4
System Thinking	EI	EI	LMI	LMI	LMI	MI
Innovation	1 / EI	EI	EI	LMI	LMI	MI
Stewardship	1 / LMI	1 / EI	EI	EI	EI	MI
Collaboration	1 / LMI	1 / LMI	1 / EI	EI	EI	MI
Value Optimization	1 / LMI	1 / LMI	1 / EI	1 / EI	EI	LMI
Transparency	1 / MI	1 / MI	1 / MI	1 / MI	1 / LMI	EI

	System Thinking	Innovation	Stewardship	Collaboration	Value Optimization	Transparency
System Thinking	(1.0, 1.0, 1.0)	(1.0, 1.0, 1.0)	(1.0, 1.0, 1.5)	(1.0, 1.0, 2.5)	(1.0, 1.0, 3.0)	(1.0, 3.0, 5.0)
Innovation	(1.0, 1.0, 1.0)	(1.0, 1.0, 1.0)	(1.0, 1.0, 1.5)	(1.0, 1.0, 3.0)	(1.0, 1.0, 3.0)	(1.0, 3.0, 5.0)
Stewardship	(0.83, 1.0, 1.0)	(0.83, 1.0, 1.0)	(1.0, 1.0, 1.0)	(1.0, 1.0, 3.0)	(1.0, 1.5, 3.0)	(1.0, 2.5, 4.5)
Collaboration	(0.5, 1.0, 1.0)	(0.33, 1.0, 1.0)	(0.67, 1.0, 1.0)	(1.0, 1.0, 2.0)	(1.0, 1.0, 1.5)	(1.0, 1.5, 3.5)
Value Optimization	(0.33, 1.0, 1.0)	(0.33, 1.0, 1.0)	(0.47, 0.83, 1.0)	(0.83, 1.0, 1.0)	(1.0, 1.0, 1.0)	(1.0, 1.0, 2.5)
Transparency	(0.2, 0.33, 1.0)	(0.2, 0.33, 1.0)	(0.23, 0.50, 1.0)	(0.30, 0.83, 3.0)	(0.5, 1.0, 3.0)	(1.0, 1.0, 1.0)

Circular Business Model	$C C_{i}$	Rank
Recovery by-products	0.6740	$1_{s t}$
Product life extension	0.6489	$2_{n d}$
Product as service	0.5969	$3_{r d}$
Sharing economy	0.5222	$4_{t h}$
Dematerialization	0.5240	$5_{t h}$
On-demand	0.4794	$6_{t h}$

Circular Business Models	Dimension of the analyzed indicators
	Material		Economic		Social
	Coe	Rank	Coe	Rank	Coe	Rank
Product as service	0.4277	5	0.7350	1	0.7070	1
Sharing economy	0.5191	3	0.6152	3	0.4570	6
Product life extension	0.6379	2	0.6152	3	0.5713	2
On-demand	0.4216	6	0.2807	6	0.5713	4
Recovery by-products	0.6859	1	0.7350	1	0.5713	2
Dematerialization	0.5033	4	0.6152	3	0.5220	5

Circular Business Models	System Thinking		Innovation		Stewardship		Collaboration		Value Optimization		Transparency
Circular Business Models	Coe	Rank	Coe	Rank	Coe	Rank	Coe	Rank	Coe	Rank	Coe	Rank
Product as service	0.555	3	0.532	3	0.530	4	0.549	3	0.539	3	0.541	3
Sharing economy	0.518	4	0.510	4	0.534	3	0.517	4	0.523	4	0.511	5
Product life extension	0.643	2	0.634	2	0.653	2	0.611	2	0.636	2	0.622	2
On-demand	0.484	5	0.463	5	0.466	6	0.446	5	0.460	5	0.457	6
Recovery by-products	0.671	1	0.667	1	0.684	1	0.662	1	0.668	1	0.663	1
Dematerialization	0.518	4	0.516	4	0.528	5	0.517	4	0.523	4	0.518	4

μ_{A} (x) = \{\begin{matrix} 0 f o r x < l, \\ \frac{x - 1}{m - 1} f o r a \leq x \leq m, \\ \frac{u - x}{u - m} f o r m \leq x \leq u, \\ 0 f o r x > u . \end{matrix}

F W A = f ({\tilde{A}}_{1}, {\tilde{A}}_{2}, \dots, {\tilde{A}}_{n}, {\tilde{W}}_{1}, {\tilde{W}}_{2}, \dots, {\tilde{W}}_{n}) = \frac{{\tilde{W}}_{1} \times {\tilde{A}}_{1} + {\tilde{W}}_{2} \times {\tilde{A}}_{2} + \dots + {\tilde{W}}_{n} \times {\tilde{A}}_{n}}{{\tilde{W}}_{1} + {\tilde{W}}_{2} + \dots + {\tilde{W}}_{n}}

[\sum_{i = 1}^{n} \sum_{j = 1}^{m} M_{g i}^{i}]^{- 1} = (\frac{1}{\sum_{i = 1}^{n} \sum_{j = 1}^{m} u_{i}}, \frac{1}{\sum_{i = 1}^{n} \sum_{j = 1}^{m} m_{i}}, \frac{1}{\sum_{i = 1}^{n} \sum_{j = 1}^{m} l_{i}})

µ_{S_{2}} (d) = \{\begin{matrix} 1, \\ 0, \\ \frac{l_{1} - u_{2}}{(m_{2} - u_{2}) - (m_{1} - l_{1})}, \end{matrix} \begin{array}{l} i f m_{2} \geq m_{1} \\ i f l_{1} \geq u_{2} \\ o t h e r w i s e \end{array}

\begin{array}{l} \begin{matrix} \begin{matrix} C_{1} & C_{2} & \dots \end{matrix} & C_{m} \end{matrix} \\ \tilde{D} = \begin{matrix} \begin{matrix} A_{1} \\ A_{2} \end{matrix} \\ ⋮ \\ A_{n} \end{matrix} (\begin{matrix} \begin{matrix} \begin{matrix} {\tilde{p}}_{11} & {\tilde{p}}_{12} & \dots \\ {\tilde{p}}_{21} & {\tilde{p}}_{22} & \dots \\ ⋮ & ⋮ & ⋮ \end{matrix} \\ \begin{matrix} {\tilde{p}}_{n 1} & {\tilde{p}}_{n 2} & \dots \end{matrix} \end{matrix} & \begin{matrix} {\tilde{p}}_{1 m} \\ {\tilde{p}}_{2 m} \\ \begin{matrix} ⋮ \\ {\tilde{p}}_{n m} \end{matrix} \end{matrix} \end{matrix}) \end{array}

[1] * rafma92@usp.br

Brasil

Brasil

A fuzzy multicriteria group decision approach for circular business models prioritization

Abstract

Paper aims

Originality

Research method

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Implications for theory and practice