APPLICATION OF ANALYTIC HIERARCHY PROCESS INDECISION MAKING OF PROCESSED BANANA PRODUCTS FOR COMMUNITY ENTERPRISES

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Oct 4, 2023
Natanaree Sooksaksun Sunarin Chanta

Abstract

 

Bananas are one of the most produced and consumed fruit crops in the world. However, producers, especially farmers and small businesses, are currently facing many challenges in the market, particularly competitiveness. This article aims to analyze factors that influence the decision-making process of processing banana products for community enterprises. The selection of the best-processed banana products according to the different criteria uses the Analytic Hierarchy Process (AHP) as a multi-criteria decision-making support tool. A case study of community enterprises that process banana products in Prachinburi Province, Thailand is presented. The criteria and priorities are considered based on the opinions of the community enterprises. There are five main factors: main raw materials, readiness for production, profitability and marketing channels, storage conditions, and environmental and societal impacts. The alternatives were divided into two cases: unripe and ripe bananas. The results show that the main factor with the highest priority in processing banana products is the readiness for production. For overall results, the banana chip is the best choice to produce if the supply is unripe bananas. If the supply is ripe bananas, the dried banana is the best choice to produce. These results provide a guideline for decision-making in banana product processing, which helps determine the best option for complex problems.

How to Cite

Sooksaksun, N., & Chanta, S. (2023). APPLICATION OF ANALYTIC HIERARCHY PROCESS INDECISION MAKING OF PROCESSED BANANA PRODUCTS FOR COMMUNITY ENTERPRISES. International Journal of the Analytic Hierarchy Process, 15(2). https://doi.org/10.13033/ijahp.v15i2.1091

Downloads

Download data is not yet available.
Abstract 292 | PDF Downloads 304

##plugins.themes.bootstrap3.article.details##

Keywords

AHP, agricultural processing, multi-criteria decision making

References
Achatbi, I., Amechnoue, K., Haddadi, T.E., & Allouch, S.A. (2020). Advanced system based on ontology and multi agent technology to handle upstream supply chain: intelligent negotiation protocol for supplier and transportation provider selection. Decision Science Letters, 9, 337–354. Doi: https://doi.org/10.5267/j.dsl.2020.5.002

Akıncı, H., Özalp, A.Y., & Turgut, B. (2013). Agricultural land use suitability analysis
using GIS and AHP technique. Computers and Electronics in Agriculture, 97, 71–82. Doi: https://doi.org/10.1016/j.compag.2013.07.006

Akman, G., Boyaci, A.I., & Turkiye, S. (2022). Selecting the suitable e-commerce marketplace with neutrosophic fuzzy AHP and EDAS methods from the seller’s perspective in the context of COVID-19. International Journal of the Analytic Hierarchy Process, 14(3), 1–36. Doi: https://doi.org/10.13033/ijahp.v14i3.994

Anderson, D.P., & Hanselka, D. (2009). Adding value to agricultural products.
https://hdl.handle.net /1969.1/86940.

Anggani, P.C., & Anggrahini, I.B.D. (2017). Supplier selection using Analytical Hierarchy Process at PT. Indolakto. Jurnal Sains dan Seni ITS, 6(1), 27–31. Doi: https://doi.org/10.12962/j23373520.v6i1.21479

Barata, F.A. (2021). Performance measurement of supply chains and distribution industry using balanced scorecard and fuzzy analysis network process. Decision Science Letters, 10, 401–414. Doi: https://doi.org/10.5267/j.dsl.2021.1.004

Barati, A.A., Azadi, H., Pour, M.D., Lebailly, P. & Qafori, M. (2019). Determining key agricultural strategic factors using AHP-MICMAC. Sustainability, 11(14), 3947. Doi: https://doi.org/10.3390/su11143947

Cheng, E.W.L. & Li, H. (2001). Analytic Hierarchy Process: An approach to determine
measures for business performance. Measuring Business Excellence, 5(3), 30–37. Doi: https://doi.org/10.1108/eum0000000005864

Costa, J.F.S., Borges, A.R., & Machado, T.S. (2016). Analytic Hierarchy Process applied to industrial location: A Brazilian perspective on jeans manufacturing. International Journal of the Analytic Hierarchy Process, 8(1), 77–91. Doi: https://doi.org/10.13033/ijahp.v8i1.210

Din, G.Y., & Yunusova, A.B. (2016). Using AHP for evaluation of criteria for agro-industrial projects. International Journal Horticulture and Agriculture, 1(1), 1–6. Doi: https://doi.org/10.15226/2572-3154/1/1/00104

FAO (2021). Banana Statistical Compendium 2020. Rome, Italy: Food and Agriculture
Organization of the United Nations.

Gafuma, S., Byarugaba-Bazirake, G.W., & Mugampoza, E. (2018). Textural hardness of selected Ugandan banana cultivars under different processing treatments. Journal of Food Research, 7(5), 98–111. Doi: https://doi.org/10.5539/jfr.v7n5p98

Ganguly, A., & Merino, D. An integrated AHP-QFD approach for evaluating completing technological process. International Journal of the Analytic Hierarchy Process, 7(3), 539–559. Doi: https://doi.org/10.13033/ijahp.v7i3.315

Hiranyalawan, T., & Ractham, V.V. (2021). Knowledge sharing from famer/processor and the perceived benefits of processed banana consumers. Kasetsart Journal of Social Sciences, 42, 249–254. Doi: https://doi.org/10.34044/j.kjss.2021.42.2.05

Huynh, T.T.G., Luu, T.D., & Phung, T.T. (2021). A fuzzy-set approach for multiple criteria decision making in sustainable consumption of organic food. Decision Science Letters, 10, 291–300. Doi: https://doi.org/10.5267/j.dsl.2021.3.001

Jayant, A., Gupta, P., & Garg, S.K. (2011). An application of the analytic network process to evaluate supply chain logistics strategies. International Journal of the Analytic Hierarchy Process, 3(2), 149–171. Doi: https://doi.org/10.13033/ijahp.v3i2.76

Jayasinghe, S.L., Ranawana, C.J.K., Liyanage, I.C., & Kaliyadasa, P.E. (2022). Growth and yield estimation of banana through mathematical modelling: A systematic review. The Journal of Agricultural Science, 160(3-4), 1–16. Doi: https://doi.org/10.1017/s0021859622000259

Khodadadzadeh, T., & Sadjadi, S.J. (2013). A state-of-art review on supplier selection problem. Decision Science Letters, 2, 59–70. Doi: https://doi.org/10.5267/j.dsl.2013.03.001

Koul, S., & Verma, R. (2012). Dynamic vendor selection: Fuzzy AHP approach. International Journal of the Analytic Hierarchy Process, 4(2), 118–136. Doi: https://doi.org/10.13033/ijahp.v4i2.25

Kumar, A., & Pant, S. (2023). Analytical hierarchy process for sustainable agriculture: An overview. MethodsX, 10, 101954. Doi: https://doi.org/10.1016/j.mex.2022.101954

Kumar, D. (2019). Buyer-supplier relationship selection for a sustainable supply chain: A case of the Indian automobile industry. International Journal of the Analytic Hierarchy Process, 11(2), 215–227. Doi: https://doi.org/10.13033/ijahp.v11i2.605

Kumar, G.V.A., Ramaa, A., Shilpa, M. (2022). Parametric analysis of dry machining process using a novel integrated multi-attribute decision making approach. Decision Science Letters, 11, 193–202. Doi: https://doi.org/10.5267/j.dsl.2021.11.001

Marinis, P.D., & Sali, G. (2020). Participatory analytic hierarchy process for resource allocation in agricultural development projects. Evaluation and Program Planning, 80, 101793. Doi: https://doi.org/10.1016/j.evalprogplan.2020.101793

Miškolci, S. (2008). Multifunctional agriculture: evaluation of non-production benefits
using the Analytical Hierarchy Process. Agricultural Economics–Czech, 54(7), 322–332. Doi: https://doi.org/10.17221/2709-agricecon

Nyaoga, R., Magutu, P., & Wang, M. (2016). Application of Grey-TOPSIS approach to evaluate value chain performance of tea processing chains. Decision Science Letters, 5, 431–446. Doi: https://doi.org/10.5267/j.dsl.2016.1.002

Nybom, J., Hunter, E., Micheels, E., & Melin, M. (2021). Farmers’ strategic responses to
competitive intensity and the impact on perceived performance. SN Business and Economics, 1(74), 1–22. Doi: https://doi.org/10.1007/s43546-021-00078-1

Nyombi, K. (2010). Understanding growth of East Africa highland banana: experiments and simulation (Ph.D. Dissertation), Wageningen University and Research.

Okfalisa, O., Anggraini, W., Nawanir, G., Saktioto, & Wong, K.Y. (2021). Measuring the effects of different factors influencing on the readiness of SMEs towards digitalization: A multiple perspectives design of decision support system. Decision Science Letters, 10, 425–442. Doi: https://doi.org/10.5267/j.dsl.2021.1.002

Saaty, T.L. (1980). The Analytical Hierarchy Process. New York: McGraw-Hill. Doi: https://doi.org/10.1287/mnsc.36.3.259

Saaty, T.L. (1990). An exposition of the AHP in reply to the paper: remarks on the Analytic Hierarchy Process. Management Science, 36(3), 259–268. Doi: https://doi.org/10.1287/mnsc.36.3.259

Sevkli, M., Koh, S.C.L., Zaim, S., Demirbag, E., & Tatoglu, E. (2008). Hybrid analytical hierarchy process model for supplier selection. Industrial Management & Data Systems, 108(1), 122–142. Doi: https://doi.org/10.1108/02635570810844124

Siregar, H., Suroso, A.I., Siregar, H., & Djohar, S. (2022). Development of efficient strategies to optimize production efficiency: Evidence from Pine chemical industry. Decision Science Letters, 11, 419–430. Doi: https://doi.org/10.5267/j.dsl.2022.7.003

Teniwut, W.A., & Marimin, Djatna T. (2019). GIS-based multi-criteria decision making model for site selection of seaweed farming information centre: A lesson from small islands, Indonesia. Decision Science Letters, 8, 137–150. Doi: https://doi.org/10.5267/j.dsl.2018.8.001

Toloi, R.C., Teis, J.G.M., Toloi, M.N.V., Vendrametto, O., & Cabral, J.A.S.P. (2022). Applying Analytic Hierarchy Process (AHP) to identify decision-making in soybean supply chains: a case of Mato Grosso production. Revista de Economia e Sociologia Rural, 60(2), e229595. Doi: https://doi.org/10.1590/1806-9479.2021.229595

Tošovi´c-Stevanovi´c, A., Ristanovi´c, V., Calovi´c, D., Lali´c, G., Žuža, M., & Cvijanovi´c, G. (2020). Small farm business analysis using the AHP model
for efficient assessment of distribution channels. Sustainability, 12, 10479. Doi: https://doi.org/10.3390/su122410479

Tuan, N.H., & Canh, T.T. Integral SWOT-AHP-TOWS model for strategic agricultural development in the context of drought: A case study in Ninh Thuan, Vietnam. International Journal of the Analytic Hierarchy Process, 14(1), 1–30. Doi: https://doi.org/10.13033/ijahp.v14i1.890

Wang, L., Qi, C., Jiang, P., & Xiang, S. (2022). The impact of blockchain application
on the qualification rate and circulation efficiency of agricultural products: A simulation analysis with agent-based modelling. International Journal of Environmental Research and Public Health, 19(13), 7686. Doi: https://doi.org/10.3390/ijerph19137686

Wardhan, H., Das, S., & Gulati, A. (2022). Banana and mango value chains. In: Gulati, A., Ganguly, K., Wardhan, H. (eds) Agricultural Value Chains in India. India Studies in Business and Economics. Singapore: Springer. Doi: https://doi.org/10.1007/978-981-33-4268-2_4

Zhao, S., Li, P., Xiong, Y., Zhang, X., & Chai, L. (2012). Complex agricultural system evolution basing on fourth thermodynamic law. In Proceedings of the 2012 Eighth International Conference on Natural Computation (ICNC), Chongqing, China, 29–31 May, 20–24. Doi: https://doi.org/10.1109/icnc.2012.6234740

Section
Articles