Ishikawa Diagram, Gray Numbers and Pareto Principle for the Analysis of the Causes of WEEE Production in Cameroon: Case of SMEs Implementing ISO 14001:2015


  • Gilson Tekendo Djoukoue

    School of Management, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China

  • Moses Olabhele Esangbedo

    School of Management Engineering, Xuzhou University of Technology, Xuzhou, Jiangsu, 221018, China

  • Sijun Bai

    School of Management, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China



The issue of Waste from Electrical and Electronic Equipment (WEEE) in Africa lacks a concrete answer at present. This study aimed to provide an integrated approach using qualitative and quantitative research methods based on the 80/20 principle and the grey system theory, in order to address the uncertainty in the existing literature. First, through a qualitative approach, the authors analysed the environment for the management of WEEE by eight companies in Cameroon, through a literature review and observations made in the field under the framework of the ISO 14001:2015 standard. Then, the weights of the selected cause of the WEEE using grey system theory were proposed and applied, combining the findings from both the qualitative and quantitative methods. Based on the data obtained through the analysis, the research results indicate that the assessed Cameroonian companies dealing with WEEE management can implement measures to reduce WEEE.


Waste from Electrical and Electronic Equipment (WEEE), Grey Relational Analysis (GRA), Pareto principle, Decision-making, Pairwise comparison, Cameroon


[1] Where are WEEE in Africa? [Internet]. Electronics Goes Green 2012+ (EGG). Available from:

[2] Recycling of Waste Electronic and Electrical Equipment (WEEE) [Internet]. Climate Technology Centre and Network [cited 2022 Jan 20]. Available from:

[3] DEee in Africa: State of Play-Results of the Basel Convention’s e-waste Africa Programme [Internet]. Secretariat of the Basel Convention. Available from: (in French).

[4] Order N°002/MINEPDED of 15 October 2012 Setting the Specific Conditions for the Management of Industrial Waste (Toxic and/or Dangerous) [Internet]. Available from: (in French).

[5] Directive 2012/19/EU of the European Parliament and of the Council of 4 July 2012 on Waste Electrical and Electronic Equipment (WEEE) [Internet]. Available from:

[6] List of Codes. Environmental Code [Internet] [cited 2022 Feb 2]. Available from: (in French).

[7] Bertolini, G., 2003. Regulation of transboundary movements of wastes. A plan to strengthen. Géographie Économie Société. 5(1), 91–105. (in French). DOI:

[8] Law No. 96/12 of August 5, 1996 on the Framework Law on Environmental Management [Internet]. Available from: (in French).

[9] El-Ghamrawy, S.M., Eldesouky, A.I., 2012. An agent decision support module based on granular rough model. International Journal of Information Technology & Decision Making. 11(4), 793–820. DOI:

[10] Aydın, S., 2021. A fuzzy MCDM method based on new Fermatean fuzzy theories. International Journal of Information Technology & Decision Making. 20(3), 881–902. DOI:

[11] Xu, D.L., 2009. Assessment of nuclear waste repository options using the ER approach. International Journal of Information Technology & Decision Making. 8(3), 581–607. DOI:

[12] Tervonen, T., Figueira, J.R., Lahdelma, R., et al., 2009. A stochastic method for robustness analysis in sorting problems. European Journal of Operational Research. 192(1), 236–242. DOI:

[13] Ikhlayel, M., 2016. Differences of methods to estimate generation of waste electrical and electronic equipment for developing countries: Jordan as a case study. Resources, Conservation and Recycling. 108, 134–139. DOI:

[14] Forti, V., Baldé, K., Kuehr, R., 2018. E-waste statistics: Guidelines on classifications, reporting and indicators, second edition. United Nations University: Tokyo.

[15] Mahmoudi, S., Huda, N., Behnia, M., 2019. Photovoltaic waste assessment: Forecasting and screening of emerging waste in Australia. Resources, Conservation and Recycling. 146, 192–205. DOI:

[16] Mahmoudi, S., Huda, N., Behnia, M., 2021. Critical assessment of renewable energy waste generation in OECD countries: Decommissioned PV panels. Resources, Conservation and Recycling. 164, 105145. DOI:

[17] Zhang, S., Gu, Y., Tang, A., et al., 2021. Forecast of future yield for printed circuit board resin waste generated from major household electrical and electronic equipment in China. Journal of Cleaner Production. 283, 124575. DOI:

[18] Zhilyaev, D., Cimpan, C., Cao, Z., et al., 2021. The living, the dead, and the obsolete: A characterization of lifetime and stock of ICT products in Denmark. Resources, Conservation and Recycling. 164, 105117. DOI:

[19] He, P., Hu, G., Wang, C., et al., 2021. Analyzing present and future availability of critical high-tech minerals in waste cellphones: A case study of India. Waste Management. 119, 275–284. DOI:

[20] Perkins, D.N., Drisse, M.N.B., Nxele, T., et al., 2014. E-waste: A global hazard. Annals of Global Health. 80(4), 286–295. DOI:

[21] Jiang, B., Adebayo, A., Jia, J., et al., 2019. Impacts of heavy metals and soil properties at a Nigerian e-waste site on soil microbial community. Journal of Hazardous Materials. 362, 187–195. DOI:

[22] Isimekhai, K.A., Garelick, H., Watt, J., et al., 2017. Heavy metals distribution and risk assessment in soil from an informal E-waste recycling site in Lagos State, Nigeria. Environmental Science and Pollution Research. 24, 17206–17219. DOI:

[23] Rautela, R., Arya, S., Vishwakarma, S., et al., 2021. E-waste management and its effects on the environment and human health. Science of the Total Environment. 773, 145623. DOI:

[24] Dai, Q., Xu, X., Eskenazi, B., et al., 2020. Severe dioxin-like compound (DLC) contamination in e-waste recycling areas: An under-recognized threat to local health. Environment International. 139, 105731. DOI:

[25] Peluola, A., 2016. Investigation of the implementation and effectiveness of electronic waste management in Nigeria. Modeling Earth Systems and Environment. 2, 1–6. DOI:

[26] Maphosa, V., Maphosa, M., 2020. E-waste management in Sub-Saharan Africa: A systematic literature review. Cogent Business & Management. 7(1), 1814503. DOI:

[27] Grant, R.J., Oteng-Ababio, M., 2016. The global transformation of materials and the emergence of informal urban mining in Accra, Ghana. Africa Today. 62(4), 3–20. DOI:

[28] Yu, E.A., Akormedi, M., Asampong, E., et al., 2017. Informal processing of electronic waste at Agbogbloshie, Ghana: Workers’ knowledge about associated health hazards and alternative livelihoods. Global Health Promotion. 24(4), 90–98. DOI:

[29] Mmereki, D., Li, B., Li’ao, W., 2015. Waste electrical and electronic equipment management in Botswana: Prospects and challenges. Journal of the Air & Waste Management Association. 65(1), 11–26. DOI:

[30] Nwagwu, W., Okuneye, M., 2016. Awareness and attitudes of small-scale information technology business operators in Lagos, Nigeria toward E-waste hazards. Journal of Global Information Technology Management. 19(4), 267–282. DOI:

[31] Tetteh, D., Lengel, L., 2017. The urgent need for health impact assessment: Proposing a transdisciplinary approach to the e-waste crisis in sub-Saharan Africa. Global Health Promotion. 24(2), 35–42. DOI:

[32] Oteng-Ababio, M., van der Velden, M., Taylor, M.B., 2020. Building policy coherence for sound waste electrical and electronic equipment management in a developing country. The Journal of Environment & Development. 29(3), 306–328. DOI:

[33] Globalization, Urbanization and Municipal Solid Waste Management in Africa [Internet]. Available from:

[34] Kakeu, R.C., 2008. Management of municipal solid waste the proof of the public-private partnership Bafoussam, Cameroon: An analysis of the in environmental equality in a medium-sized city in Sub-Saharan Africa [Ph.D. thesis]. Lausanne: University of Lausanne. (in French).

[35] Dieng, D., Diop, C., Sonko, E.h.M., et al., 2018. Waste management of electrical and electronic equipment (WEEE) in Senegal: Actors and organizational strategy of the sector. International Journal of Biological and Chemical Sciences. 11(5), 2393–2407. (in French). DOI:

[36] Xinping, X., Jianghui, W., Ming, X., 2010. Grey relational analysis and forecast of demand for scrap steel. Journal of Grey System. 22(1), 73–80.

[37] Jing, C., Jianmin, Z., Zhongyu, W., et al., 2007. Application of grey relational analysis in water quality evaluation. Journal of Grey System. 19(1), 99–106.

[38] Yuan, Y., Jian, W., 2017. Advanced grey relational analysis method and its application in water quality evaluation of the lake-type wetland. Journal of Landscape Research. 9(4), 81–87.

[39] Chin-Tsai, L., Wen-Hsiang, W., Hsin-Chuan, P., 2010. Using grey control charts in surface mounting technology. Journal of Grey System. 22(2), 167–176.

[40] Chung-Chih, C., Che-Wei, C., 2010. Check quality of recycled building materials via GRA and AHP. Journal of Grey System. 22(1), 63–72.

[41] Tao, M., Li, H., Xu, H., 2011. Influencing factor analysis of the investment efficiency of the environmental governance: A case of Shandong Province in China. Grey Systems: Theory and Application. 1(3), 240–249. DOI:

[42] Wei, F., Liu, S., Yin, L., et al., 2014. Research on performance evaluation system for green supply chain management based on the context of recycled economy—taking Guangxi’s manufacturing industry as example. Journal of Grey System. 26(2), 177–187.

[43] Liu, W., Zhang, J., Wu, C., et al., 2016. Identifying key industry factors of remanufacturing industry using grey incidence analysis: A case of Jiangsu province. Grey Systems: Theory and Application. 6(3), 398–414. DOI:

[44] Chang, A.Y., Cheng, Y.T., 2019. Analysis model of the sustainability development of manufacturing small and medium-sized enterprises in Taiwan. Journal of Cleaner Production. 207, 458–473. DOI:

[45] Javanmardi, E., Liu, S., Xie, N., 2020. Exploring grey systems theory-based methods and applications in sustainability studies: A systematic review approach. Sustainability. 12(11), 4437. DOI:

[46] Zhao, R., Su, H., Chen, X., et al., 2016. Commercially available materials selection in sustainable design: An integrated multi-attribute decision making approach. Sustainability. 8(1), 79. DOI:

[47] Zhang, H., Peng, Y., Tian, G., et al., 2017. Green material selection for sustainability: A hybrid MCDM approach. PloS One. 12(5), e0177578. DOI:

[48] Luthra, S., Mangla, S.K., Shankar, R., et al., 2018. Modelling critical success factors for sustainability initiatives in supply chains in Indian context using Grey-DEMATEL. Production Planning & Control. 29(9), 705–728. DOI:

[49] Esangbedo, M.O., Bai, S., Mirjalili, S., et al., 2021. Evaluation of human resource information systems using grey ordinal pairwise comparison MCDM methods. Expert Systems with Applications. 182, 115151. DOI:

[50] Liu, J., Liu, S., Fang, Z., 2015. Fractional-order reverse accumulation generation gm (1, 1) model and its applications. Journal of Grey System. 27(4), 52–62.

[51] Duman, G.M., Kongar, E., Gupta, S.M., 2019. Estimation of electronic waste using optimized multivariate grey models. Waste Management. 95, 241–249. DOI:

[52] Sahu, A.K., Narang, H.K., Rajput, M.S., 2018. A Grey-DEMATEL approach for implicating e-waste management practice: Modeling in context of Indian scenario. Grey Systems: Theory and Application. 8(1), 84–99. DOI:

[53] Agrawal, R., 2020. Sustainability evaluation of additive manufacturing processes using grey-based approach. Grey Systems: Theory and Application. 10(4), 393–412. DOI:

[54] Esangbedo, M.O., Che, A., 2016. Evaluating business environment in Africa using grey number weights. Journal of Grey System. 28(3), 26–47.

[55] Diba, S., Xie, N., 2019. Sustainable supplier selection for Satrec Vitalait Milk Company in Senegal using the novel grey relational analysis method. Grey Systems: Theory and Application. 9(3), 262–294. DOI:

[56] Cao, Q., Esangbedo, M.O., Bai, S., et al., 2019. Grey SWARA-FUCOM weighting method for contractor selection MCDM problem: A case study of floating solar panel energy system installation. Energies. 12(13), 2481. DOI:

[57] Angela, F., Angelina, A., 2021. Grey relational evaluation of the supplier selection criteria in Indonesian hospitality industry. International Journal of Grey Systems. 1(2), 47–59. DOI:

[58] Directory and Emography of Modern Businesses in 2016 [Internet]. Available from: (in French).

[59] Esangbedo, M.O., Bai, S., 2019. Grey regulatory focus theory weighting method for the multi-criteria decision-making problem in evaluating university reputation. Symmetry. 11(2), 230. DOI:

[60] Liu, S.F., Lin, Y., 2006. Grey information: Theory and practical applications. Springer: London. DOI:

[61] Islam, S., 2021. Evaluation of low-carbon sustainable technologies in agriculture sector through grey ordinal priority approach. International Journal of Grey Systems. 1(1), 5–26. DOI:

[62] Darvishi, D., Forrest, J., Liu, S., 2019. A comparative analysis of grey ranking approaches. Grey Systems: Theory and Application. 9(4), 472–487. DOI:

[63] Li, G.D., Yamaguchi, D., Nagai, M., 2007. A grey-based decision-making approach to the supplier selection problem. Mathematical and Computer Modelling. 46(3–4), 573–581. DOI:

[64] Shi, J.R., 2005. A new solution for interval number linear programming. Journal of Systems Engineering Theory and Practice. 2, 101–106.


How to Cite

Tekendo Djoukoue, G., Olabhele Esangbedo, M., & Bai, S. (2024). Ishikawa Diagram, Gray Numbers and Pareto Principle for the Analysis of the Causes of WEEE Production in Cameroon: Case of SMEs Implementing ISO 14001:2015. Journal of Management Science & Engineering Research, 7(1), 22–42.