Purpose – Successful future has inspired organizations to measure long-term and non-financial measurements and key performance indicators (KPIs). Kaplan and Norton proposed balanced scorecard (BSC) for this issue and have extended it to one of the most preferred strategic management system’s tools. However, available planning tools like BSC have some limitations, like dependency to the developer, weakness in showing time delays, and also mathematical relationships between lead and lag indicators. In this paper, the authors would present a new methodology for developing BSCs, which would be able to overcome these limitations. Therefore, the purpose of this paper is to develop an integrated framework for developing BSC with system dynamics approach (a dynamic BSC (DBSC)) which has lower limitation in compare with traditional BSC. The other purpose of this paper is developing a DBSC for an Iranian public transportation company. Design/methodology/approach – Based on this purpose, related literature was thoroughly reviewed and the proposed methodology designed using the system dynamics and BSC concepts. This methodology is a composition of original BSC development methodology and system dynamics principles. An assumed organization has been used for showing methodology’s capability and procedure. Furthermore, a case study has been accomplished in this paper. This case study is a DBSC which has been developed for an Iranian public transportation company. The purpose of this case study is to ensure about proposed methodology implication in action. Findings – The authors proposed a methodology which can be applied for developing BSCs. This methodology consists of six different steps which are: developing a system for organization, selecting stakeholders’ most important objectives and target, identifying organization’s objectives and their KPIs for different BSC aspects, developing strategy map, targeting, and selecting initiatives. In the proceeding of this paper, the proposed methodology and its steps would be explained in detail. Originality/value – The system dynamic approach has precedents in business studies; however, this research makes this approach operational in BSC designing and analysis. BSCs, which developed by this methodology can show time delays between an organization’s objectives, its KPIs’ relationship and also planning for it. Selecting achievable and rational vision and objectives’ targets, change management, scenario planning and policy analysis are other values which can be achieved by DBSC deployment which need further researches. In summary, this research has shown an integrated framework for developing DBSC and then applies it to an Iranian public transportation company. Therefore, another contribution of this paper is the application of this method for an Iranian public transportation company.

Abstract:Marketing policies and strategies have long term effects on firm's financial indicators. Measuring these longterm effects is somehow difficult and it could be important from managers' viewpoint as well. Up to now a lot of researches have been done to disclose these effects, but the previous studies have limitation in demonstration of these long-term effects. In this article, we applied system dynamics for developing a dynamic marketing system and analyzing different marketing policies and strategies on firm's financial measurements. For this purpose, we proposed a dynamic marketing system model. The conceptual framework for dynamic model has been extracted by analyzing literature. In this regard, we studied related papers and determined the boundaries of marketing system by realizing important variables. Furthermore literatures have been analyzed for identifying relationships between marketing factors in a dynamic marketing system. As a result, most important positive reinforcement and negative balancing loops in this marketing system have been described in a comprehensive manner. In fact, the proposed marketing system can be applied in different industries and firms by customization for the firm's conditions and developing a quantitative dynamic marketing system.

Abstract:One of the major challenges in decision making is selection among MCDM (multi criteria decision making) methods. These methods do not provide same answer to decision maker. Therefore selecting the best answer is an important dilemma. To solve this problem, methods like Borda and Copeland compilation have been proposed. However, applying these methods leads to a hybrid solution which is not necessarily the best answer. In this paper a new approach is proposed to rank different MCDM methods. This approach is AUROC (area under receiver operating characteristic) which is a data mining tool for ranking classification models. The results would show great potential of applying AUROC for ranking MCDM methods in an immense selection problem with historical outcome.

Understanding of the long term effects of marketing mix policies on firm's financial outcomes is counted as an essential issue in marketing studies. Managers really need to know the efficiency of their decisions in marketing efforts. A large number of researches have been already conducted so as to disclose these consequences, although all of them have got some limitations. In the present paper, the authors have made use of system dynamics to develop a dynamic marketing system and analyze the effect of different marketing mix policies on firm's financial indicators. For this purpose, they have introduced two dynamic marketing models based on the related literature review. The first one, that is a qualitative model, represents the logic of marketing efforts based on system dynamic rules and the second one is a quantitative model which is based on five important loops of the qualitative model. The quantitative model has been manipulated in order to analyze several marketing mix policies (scenarios). The results indicate that decision making for selecting appropriate marketing mix is a complicated process usually leading to nonlinear and complex results. Considering this point, the authors' study suggests the utilization of dynamic simulation in order to predict and analyze the effects of marketing policies on firm's financial indicators. Finally, the findings clearly show the ability of system dynamics in measuring and anticipating firm's marketing initiatives and adapting the most effective policy for its success.

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