Forecasting techniques, operating environment and accuracy of performance forecasting for large manufacturing companies in Kenya
Chindia, Elijah W
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This study explored the relationship among forecasting techniques, operating environment and APF in LMFs. Study objectives were to compare forecasting techniques in APF, identify performance measures influenced by the operating environment, assess moderating effects of the operating environment on the relationship between a method and APF and to examine the relationships among forecasting methods, operating environment and APF. A model and framework were formed on the basis of previous research, an empirical testing of the model was done after collecting data using a structured questionnaire, From a sample frame of 487 LMFs proportionate stratified random sampling was used to select a sample of 217 firms. Response rate was 81 percent. Data analysis used descriptive statistics, factor analysis, ANOV A, correlation and linear regression. Hypotheses were tested by analyzing independent effects of selected variables on APF. Results indicated there was empirical evidence that the effect of objective and combined forecasting techniques, and external operating. environment on APF was strong. Conversely, empirical evidence indicated the effect of variables of the internal operating environment on APF was not strong. Further, the effect of variables of the external operating environment accounted for more variation in APF compared to variables of the internal operating environment. There was statistical evidence that competitors and external customers influence APF. For objective one the hypothesis on the influence between a forecasting method and accuracy of performance forecasting was tested using objective, judgmental and combined forecasting methods. Measures of accuracy of performance forecasting used were EV, ROS, ROA and growth in market share. Results provided statistical evidence that the three forecasting methods yielded APF against expected value and ROS. It was concluded that the three forecasting methods could be used to accurately forecast expected value and ROS. Objective two was to identify performance measures that were influenced by the operating environment in LMFs. The above performance measures were tested against leadership, strategy, structure and culture as elements of the internal operating environment and customers, competitors, suppliers, substitute products and demographic characteristics as parameters of the external operating environment. There was statistically significant evidence that, except for EV and ROS, external operating environment had an influence on APF. Objective three assessed moderating effect of external and internal operating environments on the relationship between a forecasting method and APF. Using regression analysis, results indicated that external operating environment had a partial moderating effect on the relationship between each of the forecasting methods and APF, with respect to ROS and ROA for the objective method and ROA for both combined and judgmental methods. Conversely, the internal operating environment had a moderating effect on the relationship between objective forecasting method and APF with respect to ROS. Objective four examined relationships among forecasting techniques, operating environment and APF. Using regression analysis, results showed that the joint effect of the operating environments had a partial moderating effect on the relationship between objective and combined forecasting methods and APF, with respect to EV and ROS. Study findings indicated that objective and combined forecasting yielded APF in a competitive environment. For APF a forecasting method should not ignore the effects of the operating environment. The study contributes by developing an exploratory model to link LMFs APF with variables of the operating environment.