Factors affecting the implementation rates of energy and productivity recommendations in small and medium sized companies

Abstract

The Industrial Assessment Center (IAC) at the University of Wisconsin-Milwaukee has worked with more than 500 manufacturing companies to identify energy and productivity saving opportunities for small and medium sized companies. The most common saving recommendations are summarized. The implementation rates of the recommendations were only about 40%. The logistic regression analysis is used to investigate the factors that affect the implementation rates of the recommendations in 147 manufacturing plants from seven different types of industries. Six possible factors affecting the implementation rates of the recommendations are investigated; payback period, sales, number of employees, plant area, annual working hours, and the industry type. It is determined that each type of industry deals differently with implementing the recommendations. Furthermore, the recommendation type (energy or productivity) and payback period are the main factors that affect the implementation rates. It was also found that the companies which run on full capacity or work more hours are less likely to implement the recommendations.