Efficiency Analysis of the Food and Beverage Industry in Tanzania: A Comparative Analysis

Veneranda Lufano, Gabriel Kirori, Rose Mugiira
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 Methodology: The study used secondary data to achieve its objectives. The study employed a Panel data analysis technique using 40 companies in the manufacturing sector over a period of three years, 2018-2020. A stochastic frontier production model was applied using a linearized Translog production function to determine the performance elasticity coefficients of inputs and technical efficiency. The study used production theory advanced by Koutsoyiannis (1979) to explain the relatonship between input and output factors.
 Findings: One of the key findings was that the level and trend of efficiency in food and beverage industry demonstrated an upward trend for the period between 2018 and 2020 as evidenced by the changes in average in both food and beverage sub-sector which grew from 0.776 in 2018 to 0.7557 in 2019 and finally to 0.7746 in 2020. Another finding of the study was that, the individual productive efficiency distribution between food and beverage sub-sector revealed that beverage sub-sector performs much better than food sub-sectors, with an average technical efficiency of 77.85% and 81.36% for both food and beverage sub-sectors, respectively.
 Unique Contribution to Theory, Practice and Policy: The study’s unique contributions to theory include its assessment of efficiency levels, analysis of efficiency trends, and exploration of sector-specific variations. Its practical contributions encompass policy recommendations, guidance on modernization and technology adoption, and the importance of skills development and export promotion. These insights have direct implications for policymakers, industry stakeholders, and practitioners in Tanzania's food and beverage sector, aiding in the formulation of effective strategies to enhance efficiency and competitiveness.
 The study recommends that the government and other stakeholders comes up with policy reforms to address the underlying factors contributing to the underutilization of each firm’s production capacity. This includes reforming the input market in the manufacturing sector in order to increase the level of efficiency to 100%. There should be establishment of an efficient marketing mechanism that reduces the involvement of many parties in the supply chain and hence high transaction costs.","PeriodicalId":42721,"journal":{"name":"International Journal of Economics Management and Accounting","volume":null,"pages":null},"PeriodicalIF":0.4000,"publicationDate":"2023-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Economics Management and Accounting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47604/ijecon.2119","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ECONOMICS","Score":null,"Total":0}
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Abstract

Purpose: This study examined the performance of food and beverage industries in Tanzania in terms of productive and technical efficiency. The specific objectives of the study were to evaluate the productive efficiency performance of food and beverage industries in Tanzania, to determine the level and trend of efficiency of food and beverage of food and beverage industry in Tanzania, and to assess the levels of productive efficiency performance in the food and beverage subsectors in Tanzania Methodology: The study used secondary data to achieve its objectives. The study employed a Panel data analysis technique using 40 companies in the manufacturing sector over a period of three years, 2018-2020. A stochastic frontier production model was applied using a linearized Translog production function to determine the performance elasticity coefficients of inputs and technical efficiency. The study used production theory advanced by Koutsoyiannis (1979) to explain the relatonship between input and output factors. Findings: One of the key findings was that the level and trend of efficiency in food and beverage industry demonstrated an upward trend for the period between 2018 and 2020 as evidenced by the changes in average in both food and beverage sub-sector which grew from 0.776 in 2018 to 0.7557 in 2019 and finally to 0.7746 in 2020. Another finding of the study was that, the individual productive efficiency distribution between food and beverage sub-sector revealed that beverage sub-sector performs much better than food sub-sectors, with an average technical efficiency of 77.85% and 81.36% for both food and beverage sub-sectors, respectively. Unique Contribution to Theory, Practice and Policy: The study’s unique contributions to theory include its assessment of efficiency levels, analysis of efficiency trends, and exploration of sector-specific variations. Its practical contributions encompass policy recommendations, guidance on modernization and technology adoption, and the importance of skills development and export promotion. These insights have direct implications for policymakers, industry stakeholders, and practitioners in Tanzania's food and beverage sector, aiding in the formulation of effective strategies to enhance efficiency and competitiveness. The study recommends that the government and other stakeholders comes up with policy reforms to address the underlying factors contributing to the underutilization of each firm’s production capacity. This includes reforming the input market in the manufacturing sector in order to increase the level of efficiency to 100%. There should be establishment of an efficient marketing mechanism that reduces the involvement of many parties in the supply chain and hence high transaction costs.
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坦桑尼亚食品和饮料工业的效率分析:一个比较分析
目的:本研究考察了坦桑尼亚食品和饮料行业在生产和技术效率方面的表现。本研究的具体目标是评估坦桑尼亚食品和饮料行业的生产效率绩效,确定坦桑尼亚食品和饮料行业的食品和饮料效率水平和趋势,并评估坦桑尼亚食品和饮料分行业的生产效率绩效水平 方法:本研究使用二手数据来实现其目的。该研究采用了面板数据分析技术,在2018年至2020年的三年时间里,研究了制造业的40家公司。采用线性化的超对数生产函数,建立了随机前沿生产模型,确定了投入物的性能弹性系数和技术效率。本研究采用Koutsoyiannis(1979)的生产理论来解释投入与产出要素之间的关系。 研究结果:其中一个重要发现是,2018年至2020年期间,食品和饮料行业的效率水平和趋势呈上升趋势,食品和饮料子行业的平均水平从2018年的0.776增长到2019年的0.7557,最终增长到2020年的0.7746。研究的另一个发现是,食品和饮料子行业之间的个别生产效率分布显示,饮料子行业的表现远好于食品子行业,食品和饮料子行业的平均技术效率分别为77.85%和81.36%。 对理论、实践和政策的独特贡献:该研究对理论的独特贡献包括对效率水平的评估、效率趋势的分析和对部门具体变化的探索。它的实际贡献包括政策建议、现代化和技术采用方面的指导以及技能发展和促进出口的重要性。这些见解对坦桑尼亚食品和饮料行业的政策制定者、行业利益相关者和从业人员有直接影响,有助于制定有效战略,提高效率和竞争力。该研究建议政府和其他利益相关者提出政策改革,以解决导致每家企业产能利用率不足的潜在因素。这包括改革制造业的投入市场,以便将效率水平提高到100%。应该建立有效的营销机制,减少供应链中多方的参与,从而降低交易成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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