The role accounting plays in decision-making in business is a broad topic that has driven academics. This paper is grounded on decision and utility theories. It investigates the Certified Accountants' perception of financial information (FI) usefulness and the company's performance. Based on data collected through a survey applied to certified accountants, this study develops and evaluates an original theoretical model using the Structural Equations Model (SEM). The results reveal that manager's gender and academic qualifications influence the perception of FI utility. Non-owner managers and older companies also attach more significance to FI in decision making. The managers who attribute the most usefulness to FI in decision-making are those of companies with higher performance. Additionally, the results show that the FI usefulness is a mediator variable in the relationship between the characteristics above and company performance. This research helps all stakeholders improve decision-making, studying past events with FI to predict future results and consequently increase the company's success.

Optimization of a multi-response dynamic system aims at finding out a setting combination of input controllable factors that would result in optimum values for all response variables at all signal levels. In real life situation, often the multiple responses are found to be correlated. The main advantage of PCA-based approaches is that it takes into account the correlation among the multiple responses. Two PCA-based approaches that are commonly used for optimization of multiple responses in dynamic system are PCA-based technique for order preference by similarity to ideal solution (TOPSIS) and PCA-based multiple criteria evaluation of the grey relational model (MCE-GRM). This paper presents a new PCA-based approach, called PCA-based utility theory (UT) approach, for optimization of multiple dynamic responses and compares its optimization performance with other existing PCA-based approaches. The results show that the proposed PCA-based UT method is superior to the other PCA-based approaches.

Selecting from a pool of interdependent projects under certainty, when faced with resource constraints, has been studied well in the literature of project selection problem. After briefly reviewing and discussing popular modeling approaches for dealing with uncertainty, this paper proposes an approach based on chance constrained programming and utility theory for a certain range of problems and under some practical assumptions. Expected Utility Programming, as the proposed modeling approach, will be compared with other well-known methods and its meaningfulness and usefulness will be illustrated via two numerical examples and one real case.

When aiming on improving efficiency and reducing cost in manufacturing environments, production scheduling can play an important role. Although a common workshop is full of uncertainties, when using mathematical programs researchers have mainly focused on deterministic problems. After briefly reviewing and discussing popular modeling approaches in the field of stochastic programming, this paper proposes a new approach based on utility theory for a certain range of problems and under some practical assumptions. Expected utility programming, as the proposed approach, will be compared with the other well-known methods and its meaningfulness and usefulness will be illustrated via a numerical examples and a real case.

Providing insurance contract with “deductible” is beneficial for both insurer and insured. In this paper, we provide a utility modeling approach to handle insurance pricing and evaluate the tradeoff between discount benefit and deductible level. We analyze four different pricing problems of no insurance, full insurance coverage, insurance with β% deductible and insurance with D-dollar deductible based on a given utility function. A numerical example is also used to illustrate some interesting results.