The product-mix planning and the lot size decisions are some of the most fundamental research themes for the operations research community. The fact that markets have become more unpredictable has increaed the importance of these issues, rapidly. Currently, directors need to work with product-mix planning and lot size decision models by introducing stochastic variables related to the demands, lead times, etc. However, some real mathematical models involving stochastic variables are not capable of obtaining good solutions within short commuting times. Several heuristics and metaheuristics have been developed to deal with lot decisions problems, in order to obtain high quality results within short commuting times. Nevertheless, the search for an efficient model by considering product mix and deal size with stochastic demand is a prominent research area. This paper aims to develop a general model for the product-mix, and lot size decision within a stochastic demand environment, by introducing the Economic Value Added (EVA) as the objective function of a product portfolio selection. The proposed stochastic model has been solved by using a Sample Average Approximation (SAA) scheme. The proposed model obtains high quality results within acceptable computing times.

The adoption of EVA as a compensation and management plan, generally, impacts positively the performance of companies adopting this method. However, this paper examines whether the adoption of the EVA framework enhances the firm’s performance and gauge the long-term effects of such an adoption on the firm’s value. It also assesses whether the market reacts to the announcement of the adoption of EVA as a compensation system. Moreover, the paper fills this gap in research literature by showing whether or not EVA adoption leads to a significant increase in firm value as reflected by its market prices on the long run. Growing evidence in research indicates that the stock market does not incorporate all firm information into the stock price quickly and completely (REF). Therefore, the critique that contemporaneous association between price and EVA does not reflect reality is likely to be correct. However, this paper takes a different action. The basic contention is that although prices adjust slowly to information, long horizons are sufficiently long for markets to incorporate almost all relevant information into prices. The study sample consists of 89 US firms adopted EVA as a compensation system. It compares the performance of adopting firms to that of selected matching firms and to the market indexes, particularly, the S&P500 portfolio. Then it uses two common aggregating methods to test the event of adopting EVA by different US firms namely the CAR and BHAR methods. The results obtained, however, showed a slight improvement in the performance of companies adopting EVA within five years from the date of adoption.

There is no doubt that traditional accounting does not provide actual value of assets since they only measure tangible assets. Intellectual capital provides a new concept for measuring actual value of the assets and we can calculate future values of the firm. In this paper, we first calculate intellectual capital based on the ratio of market value/book value for three years period. Then we investigate the relationship between intellectual capital and growth rate of intellectual capital as well as financial performance of some publicly traded petrochemical and pharmaceutical firms. The results of our survey indicate that there is a positive relationship between intellectual capital and equity growth with EVA and return of assets. However, there is no meaningful relationship between intellectual assets with net earnings.