Satisfaction in life and everyday work is important in everyone's life. We spend most of our time working or being involved in some economic activity to make a living. This paper focuses on the relative importance of job satisfaction factors and their impact on the overall job satisfaction of employees. The present study is a cross-sectional type of research performed in 2015. The study population is senior executives of the Asgariyeh and MehrIran Banks in Qazvin and Alborz. The research instruments included two questionnaires based on individual characteristics and proprietary. The Individual characteristics questionnaire consists of 4 questions and the Proprietary questionnaire consists of 70 items, including a dependent variable of Job satisfaction. SPSS software was used for data analysis. One-sample t-Test was used to investigate the condition of each of the dependent and independent variables in the research. In conclusion, it can be said that the colleagues, upgrade, and compensation variables are respectively in the first, second, and third place influencing job satisfaction.

Purpose The purpose of this study is to investigate the optimization of the scheduling of production and transportation systems while considering delay time (DT) and environmental pollution (EP) concurrently. To this, an integrated multi-site manufacturing process using a cumulative transportation system is investigated. Additionally, a novel multi-society genetic algorithm is developed to reach the best answers. Design/methodology/approach A bi-objective model is proposed to optimize the production and transportation process with the objectives of minimizing DT and EP. This is solved by a social dynamic genetic algorithm (SDGA), which is a novel multi-society genetic algorithm, in scenarios of equal and unequal impacts of each objective. The impacts of each objective are calculated by the analytical hierarchical process (AHP) using experts’ opinions. Results are compared by dynamic genetic algorithm and optimum solution results. Findings Results clearly depict the efficiency of the proposed algorithm and model in the scheduling of production and transportation systems with the objectives of minimizing DT and EP concurrently. Although SDGA’s performance is acceptable in all cases, in comparison to other genetic algorithms, it needs more process time which is the cost of reaching better answers. Additionally, SDGA had better performance in variable weights of objectives in comparison to itself and other genetic algorithms. Research limitations/implications This research is an improvement which allows both society and industry to elevate the levels of their satisfaction while their social responsibilities have been glorified through assuaging the concerns of customers on distribution networks’ emission, competing more efficient and effective in the global market and having the ability to make deliberate decisions far from bias. Additionally, implications of the developed genetic algorithm help directly to the organizations engaged with intelligent production and/or transportation planning which society will be merited indirectly from their outcomes. It also could be utilitarian for organizations that are engaged with small, medium and big data analysis in their processes and want to use more effective and more efficient tools. Originality/value Optimization of EP and DT are considered simultaneously in both model and algorithm in this study. Besides, a novel genetic algorithm, SDGA, is proposed. In this multi-society algorithm, each society is focused on a particular objective; however, in one society all the feasible answers will have been integrated and optimization will have been continued.

Main objective of this article is investigating the role of Porter's competitive strategies (differentiation, cost reduction and focus) to increase the competitiveness and eventually gain competitive advantage. This study is a cross-sectional survey that is conducted in 2017. The study population is 221 CEOs (senior managers) in 99 Branches of 4 private banks in IRANs provinces Tehran (Capital of Iran), Qazvin and Isfahan as 3 of the most monetary turnovers. The research tools are a questionnaire containing demographic and specific information. To analyze the data, an SPSS statistical software is used and several statistical tests are used in the testing of the hypothesis and research goals. Finally, the impact of each dimension of the strategy to increase competitiveness is assessed. Also, each dimension is ranked according to influence; respectively differentiation strategy, focus strategy and cost reduction strategies. Considering banks multiplicity and results, special invest on differentiation strategy reaching competitiveness advantages to escape Red-Ocean in this industry is necessary. JEL Classification Codes: M13, G24, G21, F14.

The role of assessment systems in organizational excellence today is well-known in the business world. Performance assessment in organizations to identify strengths and weaknesses to make optimal use of resources has special significance. The changing needs of customers and stakeholders, competition, constant changes in laws and regulations, and reliance on traditional methods will not result in enhanced performance within global hypercompetition. Therefore, it has become necessary to employ models which possess the ability to evaluate organizations' present situation for strategic planning. In this regard, the EFQM Model is known as one of the most comprehensive performance evaluation tools. This study uses a descriptive-analytical survey method to evaluate Mehr Iran Bank's performance based on the EFQM Model. Research instruments in this survey include a personal details questionnaire and a special questionnaire. The SPSS software and the Kolmogrov-Smirnov test have been used to analyze data and check the normality of the variables, respectively.