It is a common practice for organisation to carry out assessment exercises regarding performance of their organisational activities and processes. This paper assesses the market performance of five agro-processed crops at Sustainable Agriculture Tanzania (SAT) against some criteria. Experts at SAT supplied useful information by responding through a questionnaire. The fuzzy TOPSIS model was applied in the methodology to rank the processed products. For the sake of comparing results, the fuzzy analytical hierarchy process (AHP) model was also applied to rank the products. It was found that three products maintained their positions in the two models while the other two products (alternatives) exchanged their positions. It was further suggested that more efforts have to go for lower market performing products by looking upon means to improve on their corresponding low weight criteria/sub-criteria.
JahanshahlooG.R., Extension of TOPSIS method for decision making with fuzzy data, Applied Mathematics and Computation, (2006), 1544–1551.
2.
TanT., MillsG., PapadonikolakiE. and LiuZ., Combining multi-criteria decision making (MCDM) methods with building information modelling (BIM): A review, Automation in Construction121, 2021.
3.
ErdinC. and AkbasH.E., A comparative analysis of fuzzy TOPSIS and geographic information system (GIS) for the location selection of shopping malls: A case study from Turkey, Sustainability MDPI11(3837) (2019), 1–22.
4.
BaliotiV., TzimopoulosC. and EvangelidesC., Multi-criteria decision making using TOPSIS method under fuzzy environment: Application in spillway selection, Proceedings MDPI2(637) (2018), pp. 1–8.
5.
GebreS.L., CattrysseD. and Van OrshovenJ., Multi-criteria decision-making methods to address water allocation problems: A systematic review, Water13 (2021), 125.
6.
RoghanianE., SheykhanA. and AbendankashiE.S., A application of fuzzy TOPSIS to improve the process of supply chain management in the food industries: a case study of protein products manufacturing company, Growing Science, Decision Science Letters3(2014) (2014), 17–26.
7.
SufiyanM., HaleemA., KhanS. and KhanM.I., Evaluating food supply chain performance using hybrid fuzzy MCDM technique, Elsevier20 (2019), 40–57.
8.
GadeP.K. and OsuriM., Evaluation of multi-criteria decision making methods for potential use in application security, Blekinge Institute of Technology, 2014.
9.
SrisawatC. and PayakpateJ., Comparison of MCDM methods for intercrop selection in rubber plantations, Journal of ICT15(1) (2016), 165–182.
10.
HuangW., HossainG.S. and SultanaA., Rasel and S. Rahman, Applying fuzzy technique for order preference by similarity to ideal solution (TOPSIS) in the selection of best candidate: a case study on interview performance, British Journal of Economis, Finance and Management Sciences17(1) (2020), pp. 36–49, February, 2020.
11.
YavuzM., Equipment selection by using fuzzy TOPSIS method, World multidisciplinary earth sciences symposium (WMESS)44 (2016), 1–5.
12.
NadabanS., DzitacS. and DzitacI., Fuzzy TOPSIS: a general view, Elsevier Science Direct, Procedia computer science91 (2016), 823–831.
13.
KusumawardaniR.P. and AgintiaraM., Application of fuzzy AHP-TOPSIS method for decision making in human resource manager selection process, Elsevier, Procedia Computer Science72 (2015), 638–646.
14.
SevkliM., ZaimS., TurkyilmazA. and SatirM., An application of fuzzy TOPSIS method for supplier selection, IEEE world congress on computational intelligence, WCCI, Barcelona, 2010.
15.
YaylaA.Y., YildizA. and OzbekA., Fuzzy TOPSIS method in supplier selection and application in garment industry, Eastern Europe4(93) (2012), 20–23.
16.
VelasquezM. and HesterP.T., An analysis of multi-criteria decision making methods, International Journal of Operations Research10(2) (2013), 56–66.
17.
SantosF.J.J. and CamargoH.A., Fuzzy systems for multi-criteria decision making, Electronic Journal13(3) (2010), 1–8.
18.
AriapourA., VeisanlooF. and AsgariM., Application of fuzzy TOPSIS method for plant selection in rangeland improvement (Case study: Boroujerd rangeland, Lorestan province, Iran), Journal of Rangeland Science4(3) (2014), 183–193.
19.
AshrafzadehM., RafieiF.M., IsfahaniN.M. and ZareZ., Application of fuzzy TOPSIS method for the selection of warehouse location: A case study, Interdisciplinary Journal of Contemporary Research in Business3(9) (2012), 655–671.
20.
SuderA. and KahramanC., Multi-attribute evaluation of organic and inorganic agricultural food investments using fuzzy TOPSIS, Technological and Economic Development of Economy24(3) (2015), 844–885.
21.
KoreN.B., RaviK. and PatilS.B., A simplified description of fuzzy TOPSIS method for multi-criteria decision making, International Research Journal of Engineering and Technology (IRJET)5(4) (2017), 1–4.
22.
KahramanC., CebeciU. and RuanD., Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey, International Journal of Production Economics87 (2004), 171–184.
23.
AyhanM.B., A fuzzy AHP approach for supplier selection problem: A case study in a gear motor company, International Journal of Managing Value and Supply Chain4(3) (2013), 11–23.
24.
JovcicS., PrusaP., SamsonJ. and LazarevicD., A fuzzy-AHP approach to evaluate the criteria of third-party logistics (3PL) service provider, in 4th Logistics International Conference, Belgrade, 2019.
25.
CebiA. and KaralH., An application of fuzzy analytic hierarchy process (FAHP) for evaluating students’ project, Educational Research and Reviews, Academic Journals12(3) (2017), 120–132.
YadavS.K., BabuS., YadavM.K., SinghK., YadavG.S. and PalS., A Review of Organic Farming for Sustainable Agriculture in Northern India, International Journal of Agronomy (2013), pp. 1–8.
28.
SAT, Sustainable Agriculture Tanzania An IPEN Case StudyLush Spring Prize 2017: Established Project, Sustainable Agriculture Tanzania (SAT), Morogoro, 2017.
29.
EkblomM., Challenges facing food processing MSEs in Tanzania: Aqualitative case study of the sunflower oil industry in Babati, Manyara, Soldertorn University, Stockholm, 2016.
30.
FAO, Territorial tools for agro-industry development: a sourcebook, Food and Agriculture Organization of the United Nations (FAO), Rome, 2017.
31.
FAO and UNIDO, Agro-industry for development, CAB International FAO and UNIDO, Rome, 2009.
32.
BaykasogluA., GolcukI. and AkyolD.E., A fuzzy multi-attribute decision making model to evaluate new product pricing strategies, Springer Science + Business Media, New York, 2015.
33.
ChernatonyL.D., Brand building, in M.J. Baker, The Marketing Book, Oxford: Butterworth Heinemann, (2003), pp. 372–394.
34.
JukićD. and DunkovićB., Creating Brand Relationship in Service Marketing, in Trade Perspectives 2019: Business Model Innovations in Domestic and InternationalTrade Conference, (2019), pp. 255–274.
35.
HoC.-Y, TsaiB.-H., ChenC.-S. and LuM.-T., Exploring green marketing orientations toward sustainability the hospitality industry in the COVID-19 pandemic, Sustainability13 (2021), pp. 4348.
36.
SwaiM.I., Factors affecting growth of small scale and medium agro-processing firms in Tanzania: A case of sunflower oil processing in Dodoma, 2017.
37.
NkwabiJ.M., MboyaL.B., NkwabiJ.M. and NkwabiJ.M., a review of the challenges affecting the agro-processing sector in Tanzania, Asian Journal of Business Research1(1) (2019), 60–77.
38.
AlinezhadA., MakuiA., MaviR.K. and ZohrehbandianM., An MCDM-DEA approach for technology selection, J Ind Eng7(12), 2011.
39.
CamilleriM.A., Understanding customer needs and wants. in travel marketing, tourism economics and the airline product, chapter 2, Cham, Switzerland: Springer Nature (2018), pp. 29–50.
40.
AghdaieM.H., ZolfaniS.H., RezaeiniaN. and Mehri-TekmehJ., A hybrid fuzzy MCDM approach for market segments evaluation and selection, inManagement and Service Science (MASS) Conference, 2011.
AsogwaB.C. and OkwocheV.A., Marketing of agricultural produce among rural farm households in Nigeria: The case of sorghum marketing in Benue state, International Journal of Business and Social Sciences3(13) (2012), 269–277.
43.
KawemamaW.B., Knowledge and perceptions of consumers on safety of organic vegetables in Tanzania: A case study of Morogoro and Kinondoni municipalities, Sokoine University of Agriculture, Morogoro, 2017.
44.
VafaeiN., RibeiroR.A. and Camarinha-MatosL.M., Data normalisation techniques in decision making: Case study with TOPSIS method, Int J Information and Decision Science10(1) (2018), 19–38.
45.
SaghafianS., Multi-criteria group decision making using a modified fuzzy TOPSIS procedure, in International Conference on Computational Intelligence for Modelling, control and automation, and international conference intelligent agents, web technologies and Internet Commerce (CIMCA-IAWTIC 05), Tehran, Iran, 2005.
46.
SoufiM.D., GhobadianB., NajafiG., SabzimalekiM.R. and YusafT., TOPSIS Multi-Criteria Decision Modeling Approach for Biolubricant Selection for Two- Stroke Petrol Engines, Energies (2015), pp. 13960–13970.
47.
SeyedmohammadiJ., SarmadianF., JafarzadehA.A., GhorbaniM.A. and ShahbaziF., Application of SAW, TOPSIS and fuzzy TOPSIS model in cultivation priority planning for maize, rapeseed and soybean, Elsevier, Geoderma310 (2018), pp. 178–19.
