Companies’ E-waste Estimation Based on General Equilibrium The­ory Context and Random Forest Regression Algorithm in Cameroon: Case Study of SMEs Implementing ISO 14001:2015  

作　　者：Gilson Tekendo Djoukoue Idriss Djiofack Teledjieu Sijun Bai 

机构地区：[1]School of Management,Northwestern Polytechnical University,Xi’an,Shaanxi,710072,China [2]School of Artificial Intelligence,Xidian University,Xi’an,Shaanxi,710071,China

出　　处：《Journal of Management Science & Engineering Research》2023年第2期60-81,共22页管理科学与工程研究（英文）

摘　　要：Given the challenge of estimating or calculating quantities of waste electrical and electronic equipment(WEEE)in developing countries,this article focuses on predicting the WEEE generated by Cameroonian small and medium enterprises(SMEs)that are engaged in ISO 14001:2015 initiatives and consume electrical and electronic equipment(EEE)to enhance their performance and profitability.The methodology employed an exploratory approach involving the application of general equilibrium theory(GET)to contextualize the study and generate relevant parameters for deploying the random forest regression learning algorithm for predictions.Machine learning was applied to 80%of the samples for training,while simulation was conducted on the remaining 20%of samples based on quantities of EEE utilized over a specific period,utilization rates,repair rates,and average lifespans.The results demonstrate that the model’s predicted values are significantly close to the actual quantities of generated WEEE,and the model’s performance was evaluated using the mean squared error(MSE)and yielding satisfactory results.Based on this model,both companies and stakeholders can set realistic objectives for managing companies’WEEE,fostering sustainable socio-environmental practices.

关 键 词：Electrical and electronic equipment(EEE) Waste from electrical and electronic equipment(WEEE) General equilibrium theory Random forest regression algorithm DECISION-MAKING Cameroon 

分 类 号：F42[经济管理—产业经济]