Significance and Role of Industrial Inputs in Productivity of Large-scale Manufacturing in Karachi: A Correlation Analysis

M. Iqbal, G. Mahar
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Abstract

In an industrial process, productivity is a basic concern. A combination of production input, namely employment, labour cost, energy and raw material cost, result in value addition expressed as value- added. The effective role of each input in the manufacturing process can be assessed through the influence of variables involved. Pearson's correlation coefficients show various degrees of effects through interrelationships of variables and bring out the outstanding or relatively more important role of one or more variables (inputs) in specific combinations in the manufacturing process. The paper in hand analyses the interrelationship of structuring variables in the major groups of manufacturing in Karachi using Pearson's correlation measurement techniques. The role of the variables has been assessed through sets of ten correlations in each of the six major industrial categories. The results of the analyses show the leading or the dominant contribution of the variables towards value addition and productivity. In the case of the textile industry, strong correlations are indicated between Value Added (VA) and 'Other Cost' (OC) and Average Daily Employment (ADE) and Employment Cost (EC) and also VA and ADE. For chemical and chemical products strong correlation exist between VA and OC, OC and IC (industrial cost) and ADE and EC. In respect of the wearing apparel category, a strong correlation occur between OC and IC, VA and OC, ADE and EC. Basic metal industry shows strong correlation in all ten sets of relationships, thus every variable exercising an equal influence. The food and beverage group has only two strong correlations that are VA and OC, IC, and OC. In the case of motor vehicles and trailers, strong relationships are indicated by all sets of correlation ship.  
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工业投入对卡拉奇大规模制造业生产率的意义与作用:一个相关分析
在工业生产过程中,生产率是一个基本问题。生产投入,即劳动力成本、劳动力成本、能源成本和原材料成本的组合,产生增加值,表示为增加值。每个输入在制造过程中的有效作用可以通过所涉及的变量的影响来评估。皮尔逊相关系数通过变量之间的相互关系表现出不同程度的影响,并揭示出一个或多个变量(输入)在制造过程中特定组合中的突出或相对更重要的作用。本文利用Pearson的相关测量技术分析了卡拉奇主要制造业群体中结构变量的相互关系。通过六个主要工业类别中每一个的十组相关性来评估变量的作用。分析结果显示了变量对附加值和生产率的主导或主导贡献。就纺织行业而言,增加值(VA)和“其他成本”(OC)、平均每日就业(ADE)和就业成本(EC)以及VA和ADE之间存在很强的相关性。对于化工产品而言,VA与OC、OC与IC(工业成本)、ADE与EC之间存在很强的相关性。就穿着服装类别而言,OC与IC、VA与OC、ADE与EC之间存在很强的相关性。基础金属工业在所有十组关系中都表现出很强的相关性,因此每个变量的影响都是相等的。食品和饮料组只有两个强相关性,即VA和OC, IC和OC。在机动车和挂车的情况下,强关系由所有相关船的集合表示。
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