Sustainable food consumption and production (SFCP) has become increasingly significant for creating new value, reducing costs, and reducing greenhouse gas emissions. However, there are some challenges and barriers to implementing SFCP in practice. Moreover, current methods for prioritizing barriers to SFCP seldom consider the behavioral preference of experts and interactions among factors, especially with q-Rung orthopair fuzzy set (q-ROFS)-based information. Thus, this study aims to construct a hybrid q-ROFS-based framework for ranking these barriers. First, the q-ROFS is introduced to express the experts’ uncertain information. Then, the q-ROF- CRITIC (CRiteria importance through intercriteria correlation) method is utilized to determine criteria weights considering the interrelations among barriers. Next, the q-ROF generalized TODIM method is built to rank the barriers to SFCP by considering the impact of experts’ behavioral preferences. Finally, a numerical case of barriers analysis for SFCP is organized to display the application procedures of the constructed ranking method. The result indicates that the top-priority set is education and culture (a4), with the most significant overall dominance value (0.839). Further, a comparison exploration is given to demonstrate the preponderances of the present barriers ranking method. The outcomes demonstrate that the proposed ranking method can provide a synthetic and reliable framework to handle the prioritizing issue for the barriers to SFCP within a complex and uncertain context.
XueL., LiuX., LuS., ChengG., HuY., LiuJ., DouZ., ChengS. and LiuG., China’s food loss and waste embodies increasing environmental impacts, Nature Food2 (2021), 519–528.
2.
CorradoS. and SalaS., Food waste accounting along global and European food supply chains: State of the art and outlook, Waste Management79 (2018), 120–131.
3.
BiS., HongX., YangH., YuX., FangS., BaiY., LiuJ., GaoY., YanL., WangW. and WangY., Effect of hydraulic retention time on anaerobic co-digestion of cattle manure and food waste, Renewable Energy150 (2020), 213–220.
4.
HafidH.S., RahmanN.A.A., ShahU.K.M., BaharuddinA.S. and AriffA.B., Feasibility of using kitchen waste as future substrate for bioethanol production: A review, Renewable and Sustainable Energy Reviews74 (2017), 671–686.
5.
ArdraS. and BaruaM.K., Halving food waste generation by: The challenges and strategies of monitoring UN sustainable development goal target 12.3, Journal of Cleaner Production380 (2022), 135042.
6.
LiuY., WoodL.C., VenkateshV.G., ZhangA. and FarooqueM., Barriers to sustainable food consumption and production in China: A fuzzy DEMATEL analysis from a circular economy perspective, Sustainable Production and Consumption28 (2021), 1114–1129.
7.
YuanH., Barriers and countermeasures for managing construction and demolition waste: A case of Shenzhen in China, Journal of Cleaner Production157 (2017), 84–93.
8.
RantaV., Aarikka-StenroosL., RitalaP. and MäkinenS.J., Exploring institutional drivers and barriers of the circular economy: A cross-regional comparison of China, the US, and Europe, Resources, Conservation and Recycling135 (2018), 70–82.
9.
YangY., GaiT., CaoM., ZhangZ., ZhangH. and WuJ., Application of group decision making in shipping industry 4.0: Bibliometric analysis, trends, and future directions, Systems11 (2023), 69.
10.
WangW., HanX., DingW., WuQ., ChenX. and DeveciM., A Fermatean fuzzy Fine–Kinney for occupational risk evaluation using extensible MARCOS with prospect theory, Engineering Applications of Artificial Intelligence117 (2023), 105518.
11.
KaswanM.S., RathiR., ReyesJ.A.G. and AntonyJ., Exploration and investigation of green lean six sigma adoption barriers for manufacturing sustainability, IEEE Transactions on Engineering Management (2021). http://doi.org/10.1109/TEM.2021.3108171
12.
SumritD., Prioritization of policy initiatives to overcome Industry 4.0 transformation barriers based on a Pythagorean fuzzy multi-criteria decision making approach, Cogent Engineering8 (2021), 1979712.
13.
ErolI., MuratI., Ar, I. Peker and SearcyC., 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 Engineering165 (2022), 107962.
14.
YangK., DuanT., FengJ. and MishraA.R., Internet of things challenges of sustainable supply chain management in the manufacturing sector using an integrated q-Rung Orthopair Fuzzy-CRITIC-VIKOR method, Journal of Enterprise Information Management35 (2022), 1011–1039.
15.
GüneriB. and DeveciM., Evaluation of supplier selection in the defense industry using q-rung orthopair fuzzy set based EDAS approach, Expert Systems with Applications222 (2023), 119846.
16.
DeveciM., GokasarI., PamucarD., CoffmanD.M. and PapadonikolakiE., Safe E-scooter operation alternative prioritization using a q-rung orthopair Fuzzy Einstein based WASPAS approach, Journal of Cleaner Production347 (2022), 131239.
17.
KrishankumarR., NimmagaddaS.S., RaniP., MishraA.R., RavichandranK.S. and GandomiA.H., Solving renewable energy source selection problems using a q-rung orthopair fuzzy-based integrated decision-making approach, Journal of Cleaner Production279 (2021), 123329.
18.
AlbahriA.S., AlbahriO.S., ZaidanA.A., AlnoorA., AlsattarH.A., MohammedR., AlamoodiA.H., ZaidanB.B., AickelinU., AlazabM., GarfanS., AhmaroI.Y.Y. and AhmedM.A., Integration of fuzzy-weighted zero-inconsistency and fuzzy decision by opinion score methods under a q-rung orthopair environment: A distribution case study of COVID-19 vaccine doses, Computer Standards & Interfaces80 (2022), 103572.
19.
KrishankumarR. and EcerF., Selection of IoT service provider for sustainable transport using q-rung orthopair fuzzy CRADIS and unknown weights, Applied Soft Computing132 (2023), 109870.
20.
EcerF., Ögelİ.Y., KrishankumarR. and TirkolaeeE.B., The q-rung fuzzy LOPCOW-VIKOR model to assess the role of unmanned aerial vehicles for precision agriculture realization in the Agri-Food 4.0 era, Artificial Intelligence Review (2023). https://doi.org/10.1007/s10462-10023-10476-10466
21.
HuY., Al-BarakatiA. and RaniP., Investigating the Internet-of-Things (Iot) risks for supply chain management using Q-rung orthopair fuzzy-SWARA-ARAS Framework, Technological and Economic Development of Economy (2022). https://doi.org/10.3846/tede.2022.16583
22.
TangG., YangY., GuX., ChiclanaF., LiuP. and WangF., A new integrated multi-attribute decision-making approach for mobile medical app evaluation under q-rung orthopair fuzzy environment, Expert Systems with Applications200 (2022), 117034.
23.
AlkanN. and KahramanC., Evaluation of government strategies against COVID-19 pandemic using q-rung orthopair fuzzy TOPSIS method, Applied Soft Computing110 (2021), 107653.
24.
DeveciM., GokasarI. and Brito-ParadaP.R., A comprehensive model for socially responsible rehabilitation of mining sites using Q-rung orthopair fuzzy sets and combinative distance-based assessment, Expert Systems with Applications200 (2022), 117155.
25.
MishraA.R., RaniP., PamucarD., HezamI.M. and SahaA., Entropy and discrimination measures based q-rung orthopair fuzzy MULTIMOORA framework for selecting solid waste disposal method, Environmental Science and Pollution Research30 (2023), 12988–13011.
26.
MishraA.R., RaniP., SahaA., PamucarD. and HezamI.M., A q-rung orthopair fuzzy combined compromise solution approach for selecting sustainable third-party reverse logistics provider, Management Decision61 (2023), 1816–1853.
27.
FarooqueM., ZhangA. and LiuY., Barriers to circular food supply chains in China, Supply Chain Management: An International Journal24 (2019), 677–696.
28.
FeilA.A., CyrneC.C.d.S., SindelarF.C.W., BardenJ.E. and DalmoroM., Profiles of sustainable food consumption: Consumer behavior toward organic food in southern region of Brazil, Journal of Cleaner Production258 (2020), 120690.
29.
HoekA.C., MalekpourS., RavenR., CourtE. and ByrneE., Towards environmentally sustainable food systems: decision-making factors in sustainable food production and consumption, Sustainable Production and Consumption26 (2021), 610–626.
30.
WangW., LiuX., ChenX. and QinY., Risk assessment based on hybrid FMEA framework by considering decision maker’s psychological behavior character, Computers & Industrial Engineering136 (2019), 516–527.
31.
SuY., ZhaoM., WeiC. and ChenX., PT-TODIM method for probabilistic linguistic MAGDM and application to industrial control system security supplier selection, International Journal of Fuzzy Systems24 (2022), 202–215.
32.
DivsalarM., AhmadiM., EbrahimiE. and IshizakaA., A probabilistic hesitant fuzzy Choquet integral-based TODIM method for multi-attribute group decision-making, Expert Systems with Applications191 (2022), 116266.
33.
DingN., YuS.-H., ChuJ.-J., ChenC. and ShuX.-Y., A decision framework for cultural and creative products based on IF-TODIM method and group consensus reaching model, Advanced Engineering Informatics55 (2023), 101891.
34.
NieR.-X., TianZ.-P., SangC. Kwai and WangJ.-Q., Implementing healthcare service quality enhancement using a cloud-support QFD model integrated with TODIM method and linguistic distribution assessments, Journal of the Operational Research Society73 (2022), 207–229.
35.
WuQ., LiuX., QinJ., WangW. and ZhouL., A linguistic distribution behavioral multi-criteria group decision making model integrating extended generalized TODIM and quantum decision theory, Applied Soft Computing98 (2021).
36.
WangW., LiuX., QinJ. and LiuS., An extended generalized TODIM for risk evaluation and prioritization of failure modes considering risk indicators interaction, IISE Transactions51 (2019), 1236–1250.
37.
LlamazaresB., An analysis of the generalized TODIM method, European Journal of Operational Research269 (2018), 1041–1049.
38.
AlattasK. and WuQ., A framework to evaluate the barriers for adopting the internet of medical things using the extended generalized TODIM method under the hesitant fuzzy environment, Applied Intelligence52 (2022), 13345–13363.
39.
WuQ., LiuX., QinJ., ZhouL., MardaniA. and DeveciM., An integrated generalized TODIM model for portfolio selection based on financial performance of firms, Knowledge-Based Systems249 (2022), 108794.
40.
XiaoL., HuangG. and ZhangG., An integrated risk assessment method using Z-fuzzy clouds and generalized TODIM, Quality and Reliability Engineering International38 (2022), 1909–1943.
41.
ManglaS.K., GovindanK. and LuthraS., Prioritizing the barriers to achieve sustainable consumption and production trends in supply chains using fuzzy Analytical Hierarchy Process, Journal of Cleaner Production151 (2017), 509–525.
42.
TangJ., LiuX. and WangW., A hybrid risk prioritization method based on generalized TODIM and BWM for Fine-Kinney under interval type-2 fuzzy environment, Human and Ecological Risk Assessment27 (2021), 954–979.
43.
WangW., LiuX., QinY. and FuY., A risk evaluation and prioritization method for FMEA with prospect theory and Choquet integral, Safety Science110 (2018), 152–163.
44.
WangW., WangY., FanS., HanX., WuQ. and PamucarD., A complex spherical fuzzy CRADIS method based Fine-Kinney framework for occupational risk evaluation in natural gas pipeline construction, Journal of Petroleum Science and Engineering220 (2023), 111246.
45.
ChengS., JianfuS., AlrasheediM., SaeidiP., MishraA.R. and RaniP., A new extended VIKOR approach using q-Rung Orthopair fuzzy sets for sustainable enterprise risk management assessment in manufacturing small and medium-sized enterprises, International Journal of Fuzzy Systems23 (2021), 1347–1369.
46.
ChenL., LuoN. and GouX., A novel q-rung orthopair fuzzy TODIM approach for multi-criteria group decision making based on Shapley value and relative entropy, Journal of Intelligent & Fuzzy Systems40 (2021), 235–250.
47.
ZhangZ. and LiZ., Consensus-based TOPSIS-Sort-B for multi-criteria sorting in the context of group decision-making, Annals of Operations Research (2022). https://doi.org/10.1007/s10479-10022-04985-w
48.
LiZ., ZhangZ. and YuW., Consensus reaching for ordinal classification-based group decision making with heterogeneous preference information, Journal of the Operational Research Society (2023). https://doi.org/10.1080/01605682.01602023.02186806
