DETERMINANTS OF NATURAL RESOURCES BASED MICROENTERPRISES PERFORMANCE IN INDIA’S WESTERN HIMALAYAN REGION: A NAÏVE BAYES CLASSIFIER ANALYSIS

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Abstract

The natural resources-based Microenterprises are the major part of the economy of the western Himalayan region of Uttara hand, India, as the region is predominantly covered with reserved forests. The present study evaluates the performance of Microenterprises and the factors affecting it in the region using the primary data enumerated from 110 microenterprises sampled under four major categories of microenterprises, viz, agro and allied, Animal and allied, handicrafts and handlooms, and miscellaneous. The Naïve Bayes classifier approach has been applied to evaluate the performances (Loss-making, breakeven, profit-making, or high-profit making) of these microenterprises based on their performance determining factors such as ease of raw material availability, level of training received, technological advancement, and the extent of market knowledge, and also on the type of ownership and the employee's number. The Naïve Bayes classification accuracy on the training dataset was 100%, while accuracy on the test dataset ranged from 93% to 100%. The results revealed that agro-based microenterprises have a greater probability (0.67) of making a profit/high profit, while animal product-based microenterprises have a high probability of running into losses. A higher level of Market Knowledge contributes to a high probability (0.89) of making high profits. The higher level of technology and training provides greater chances/probability (0.72, 0.72) of making high profits. Self-help groups (SHGs) have shown a better probability of making profits. The study suggests promoting SHGs in the region, wider dissemination of the market knowledge (marketing strategy), and leveling up the training/technology of the microenterprise.
印度西喜马拉雅地区基于自然资源的微型企业绩效的决定因素:naÏve贝叶斯分类器分析
以自然资源为基础的微型企业是印度北塔拉邦西喜马拉雅地区经济的主要部分,因为该地区主要覆盖着保留森林。本研究利用110家微型企业的原始数据,对该地区微型企业的绩效及其影响因素进行了评估,这些微型企业分为农业及相关企业、动物及相关企业、手工业及手工织布机企业和杂项企业四大类。Naïve贝叶斯分类器方法已被应用于评估这些微型企业的业绩(亏损,盈亏平衡,盈利或高利润)基于他们的业绩决定因素,如原材料的易用性,接受的培训水平,技术进步,市场知识的程度,以及所有权的类型和员工的数量。Naïve在训练数据集上的贝叶斯分类准确率为100%,而在测试数据集上的准确率为93%到100%。结果显示,农业微企业盈利/高利润的概率更高(0.67),而畜产品微企业亏损的概率更高。较高的市场知识水平有助于获得高利润的高概率(0.89)。技术和培训水平越高,获得高利润的机会/概率(0.72,0.72)越大。自助小组(shg)盈利的可能性更大。该研究建议在该地区推广微型企业,更广泛地传播市场知识(营销战略),并提高微型企业的培训/技术水平。
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