Reverse Logistics and Performance of Plastic Bottling Firms in Mombasa County, Kenya

Naima Siyad Kuno () and Dr. Wycliffe Arani ()

International Journal of Supply Chain Management, 2024, vol. 9, issue 4, 23 - 31

Abstract: Purpose: The purpose of this study was to determine the relationship between reverse logistics and the performance of plastic bottling firms in Mombasa County, Kenya. Methodology: Cross-sectional research design was employed in the study. The study considered all 27 plastic bottling firms registered by Mombasa County Department of Trade. Stratified random sampling techniques was used to select sample size and Slovin’s formula was adopted to get the sample size for the study. Primary data was collected by use of structured questionnaires. Collected data was analyzed by employing descriptive and inferential statistics as the data analysis techniques. Descriptive statistics gives the profile of the respondents, that is, the frequencies and their percentages; whereas inferential statistics adopts a hierarchical, moderated, multiple regression analysis model in order to determine the effect of the explanatory variable. Statistical Package for Social Science was used as the data analysis tool. Data was presented in frequency and descriptive tables. Findings: The study established that there is a correlation of 0.748 between reverse logistics and performance of plastic bottling firms in Mombasa County. Reverse logistics accounted for 56.0% of the variation in the performance of plastic bottling firms in Mombasa County. Unique Contribution to Theory, Practice and Policy: Systems theory was adopted and validated. By incorporating linking the entire supply chain, Systems theory could assist plastic bottling firms in developing a seamless sustainable reverse logistics. The study revealed that successfully implementing reverse logistics; minimize unnecessary costs, protect the environment and increase firm returns.

Keywords: Reverse Logistics; Plastic Bottling Firms; Performance (search for similar items in EconPapers)
Date: 2024
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