Hierarchical cluster classification of Iranian food manufacturing and processing industries
Abstract
Clustering is a recognized data mining practice, which comprises the devising of a set of objects into a suitable classification of compatible cases. Current cluster study of Iranian food manufacturing industries encompassed food manufacturing and processing practices regarding the number of employees, energy consumed, input and output materials streams, flow-diagram of processes and also the land area used individually. It was used SPSS Software along with Delphi Fuzzy set theory (incorporated with simple additive weighting) to classify about 57 Food Manufacturing and Processing Industries (FMPI) as a hierarchical cluster. According to the t-test analysis, there is no significant difference among 57 FMPI and their criteria such as employees, power, water, land, and fuel. The obtained results were revealed the ranks values (weights) around 2.17, 3.95, 1.64, 2.26 and 4.98 for employees, power, water, fuel, and land criteria extracted from both Kendall's W and Friedman tests respectively. Also, it was found values around 180.749 and 0.793 for Chi-square and Kendall's Coefficient of Concordance in the Friedman and Kendall's W tests respectively. Mean Cronbach's Alpha based on the mean Eigenvalue was acquired about α=1. Pearson correlation analysis had shown the highest correlation between both factors of land and employees about 0.798. Finally, a hierarchical cluster classification was developed for the 57 FMPI.
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2.Ruth SMV, Huisman W, Luning PA. Food fraud vulnerability and its key factors. Trends in Food Sci &Technol 2017; 67:70-75.
3.Compton M, Willis S, Rezaie B, et al. Food processing industry energy and water consumption in the Pacific northwest. Innov Food Sci & Emerg Technol 2018; 47: 371–83.
4.Jonidi JA, Hassanpour M, Nemati S. Nanotechnology and Environmental Health. 1thed. Ebadi Far Publication. Tehran; 2013.
5.Ghorabaee MK, Amiri M, Zavadskas EK, et al. A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Arch Civil & Mech Engin 2018; 18:32- 49.
6.Halim Lim SA, Antony J, Albliwi NAS. A systematic review of statistical process control implementation in the food manufacturing industry. J Total Qual Manage& Busin Excell 2017; 28:1-14.
7.Hoffmann J. Identification of spatial agglomerations in the German food processing industry. The 116th EAAEseminar "spatial dynamics in AGRI-food systems: implications for sustainability and consumer welfare".Parma, Italy, 2010.
8.Rahimi I, Behmanesh R, Yusuff RM. A hybrid method for prediction and assessment efficiency of decision-making Units (Real case study: Iranian poultry farms). Int J Dec Supp Sys Technol 2013; 5:1-14.
9.Banaeian N, Mobli H, Fahimnia B, et al. Green supplier selection using fuzzy group decision making methods: Acase study from the agri-food industry. Comput &Operat Res 2018; 89:337-47.
10.Eisinga R, Heskes T, Pelzer B, et al. Exact p-values for pairwise comparison of Friedman rank sums, with application to comparing classifiers. BMC Bioinform.2017; 18:2-18.
11.Shirazia F, Kazemipoor H, Tavakkoli-Moghaddam R.Fuzzy decision analysis for project scope change management. Dec Sci Lett 2017; 6:395-06.
12.Hassanpour M. Projects Management Addressed to Iranian Government (A case study). J Proceed Busin & Econom Stud 2018; 1:1-15.
13.Hassanpour M. Evaluation of Iranian recycling industries. J Wast Recycl 2017; 2:1-7.
14.Tash MNS, Nasrabadi H. Ranking Iran's MonopolisticIndustry Based on Fuzzy TOPSIS Method. Iran JEconom Stud 2013; 2:103-22.
15.Shaverdi M, Heshmati MR, Eskandaripour E, et al. Developing sustainable SCM evaluation model using fuzzy AHP in publishing industry. Proced Comput Sci 2013; 17:340-49.
16.Shaverdi M, Heshmati MR, Ramezani I. Application of Fuzzy AHP Approach for Financial Performance Evaluation of Iranian Petrochemical Sector. Proced Comput Sci 2014; 31:995-1004.
17.Hourali M, Fathian M, Montazeri A, et al. A Model forE-Readiness Assessment of Iranian Small and MediumEnterprises. J Facul Engin 2008; 41:969-85.
18.Hosseininia G, Ramezani A. Factors influencing sustainable Entrepreneurship in Small and Medium-Sized Enterprises in Iran: A Case Study of FoodIndustry. Sustain 2016; 8:1-20.
19.Behrouzi F, Wong KY, Behrouzi F. A Study on LeanSupply Chain Performance Measures of SMEs in the Automotive Industry. Proceedings of the IEEE IEEM.Singapore, Singapore. 2011.
20.Dadashpoor H, Allan A. Industrial Clustering, Innovation and Competitive Advantage in theMetropolitan Regions: Evidence from the Auto-partsCluster within the Tehran Metropolitan Region. Int JHuman 2010; 17:19-46.
21.Salehi M, Hematfar M. Comparing linear and non-linear relationships between accounting variables and dividend: Evidence of Iranian chemical industries. Afric J Busin Manage 2012; 6:2143-51.
22.Kavousi S, Salamzadeh Y. Identifying and PrioritizingFactors Influencing Success of a Strategic PlanningProcess: A Study on National Iranian Copper industries company. 2016; 12:230-44.
23.Yunus MFM, Taib CA, Iteng R. A Preliminary Study on the Application of Statistical Process Control (SPC)
Towards Process Efficiency: Case Study in Food Industries. Rosman Iteng/ Sains Human 2016; 8:25-31.
24.Radfar R, Ebrahimi L. Fuzzy Multi-Criteria DecisionMaking Model for Prioritizing the Investment Methods in Technology Transfer in Shipping Industries.Proceedings of the 2012 International Conference on Industrial Engineering and Operations ManagementIstanbul, Turkey, July 3-6, 2012.
25.Moghimi R, Anvari A, Amoozesh N, et al. An integrated fuzzy MCDM approach, and analysis, to the evaluation of the financial performance of Iranian cement companies. Int J Adv Manufac Technol 2014; 71:685-98.
26.Fekri R, Aliahmadi A, Fathian M. Predicting a model for agile NPD process with fuzzy cognitive map: the case of Iranian manufacturing enterprises. Int J Adv Manufac Technol 2009; 41:1240-60.
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| Issue | Vol 4 No 1/2 (2018): Winter/Spring | |
| Section | Original Article(s) | |
| Keywords | ||
| Hierarchical cluster Food manufacturing Industries | ||
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How to Cite
1.
Hassanpour M. Hierarchical cluster classification of Iranian food manufacturing and processing industries. J Food Safe & Hyg. 2019;4(1/2):27-40.
