Reverse logistics practices and profitability of large scale manufacturing firms in Nairobi, Kenya

Abstract

Reverse Logistics is an issue that has received growing attention, above all, in the last decade, given the confluence of several situations. Reverse logistics is becoming a key initiative today, this is due to a number of factors for example, of all the products sold, an average of eight to twelve percent is returned. Among the key players in reverse logistics are manufacturing firms, NEMA, UNEP and the Council for Logistics who play an integral role in fostering reverse logistics practices. With this understanding, the objectives of this study were: to determine reverse logistics practices used by large scale manufacturing firms in Nairobi, Kenya and to establish the relationship between reverse logistics practices and profitability of large scale manufacturing firms in Nairobi, Kenya. The study used a descriptive survey design; the population of the study included all large scale manufacturing firms in Nairobi, Kenya. The study considered Nairobi because this is where most of the large scale manufacturing firms in various sectors are concentrated and thus providing a population where a proportionate sample could be derived. The sample size for this study involved 46 respondents. This was arrived at through a formula developed by Kelley and Maxwell (2003) as shown below: 0.101=Sample Size/Total population (0.101*455) =46.This formula was derived from a series of samples assuming non zero probability. The study used primary and secondary data that was collected through a self-administered questionnaire designed to elicit specific responses for qualitative and quantitative analysis respectively. The results of the regression analysis revealed that there was a direct relationship between reverse logistics practices and profitability of large scale manufacturing firms. From the results, 52.4 % explains the variance on the effect of reverse logistics practices on profitability of large scale manufacturing firms. The variables in the regression model contribute to (R=72.4), 72% level of explanation. From the tests, there was statistically significant relationship between the variables since the p-values of all the independent variables from the table above are less than 5%.The study concluded that the most popular reverse logistics activities conducted most firms is receiving returned product from customers, while the number of manufacturers that conducted the other activities such as remanufacturing, reconditioning, landfill practices and repackaging and even recycling was quite high. The study recommends that it would be a good idea to investigate the influences of various factors such as government regulations, environmental awareness or any other factors either as independent or moderating mediating variables that can influence manufacturer‟s decision in adopting reverse logistics activities. The limitation of this study was that the respondents were not willing to commit their time to respond to the questionnaires. Most of the respondents agreed to participate only on condition that the information will not be divulged to any other party other than for academic purposes only