interpretive-structural modeling

Price is one of the most significant factors in competing in the retail market. This study aims to present the interpretive-structural modeling of elements affecting store price image, considering local and situational variables. Having analyzed KIOSERT analysis and been sure of accuracy in variables choice, the interpretive-structural modeling was used at the level of categories. The outcome of interpretive-structural modeling was a two-level model, in which the first one consisted of ‘services’, ‘enthralling factors’, ‘store factors’, and ‘social responsibility’, and in the second level, the variables consisted of ‘competitors’, ‘buyer factors’, ‘price and promotions’, and ‘sale policies’. In addition to the mentioned model, another finding of the study is depicting driving-dependency power, in which research variables are divided into four groups: autonomous, dependent, independent, and linkage. Accordingly, the ‘competitors’, ‘buyer factors,’ ‘price and promotions’, ‘sale policies’, ‘enthralling factors’, ‘store factors’, and ‘social responsibility’ belong to linkage variables and ‘service’ variable, by itself, belong to independent variables. 

Spatial justice as a new term focuses more on cities, so it is important to address the national scale. Spatial injustice refers to the imbalanced distribution of valuable political, social and economic power, wealth, infrastructures and opportunity resources. From a political geography point of view, spatial injustice can be a threat to the national integrity, national & domestic security and creation of critical areas in the state. The main goal of this paper is Identification and categorization of factors affecting the spatial injustice in Iran. This paper tries to find an answer to the research main question: What are the most important factors affecting spatial injustice in Iran? This study is practical regarding its purpose and in terms of data collection is survey descriptive. Moreover, its data collection is from the questionnaire. First, the dimensions and spatial injustice indicators are distinguished based on the review of the literature, content and comparative analysis of related researches, and interviews with experts. Then using the methodology of modern analytical-interpretive structural modeling (ISM), the relationship between the indicators is determined and analyzed. Finally, the type of variables according to their influence and reception on other variables was identified using MICMAC analysis. Results show that the most important foundations of spatial injustice in Iran based on Interpretive-Structural Modeling Are Inequality in the distribution of power, wealth and opportunities and Theoretical weakness about the spatial justice domain of knowledge

Improving the competitiveness of businesses through investment in industrial parks is one of the challenges that managers face for economic development. This study has been done with the aim of identifying, determining relationships and providing a structural model of investment to competitive advantage in industrial parks. The data have been analyzed in two parts, qualitative and quantitative. In the qualitative part, the variables of the model were extracted using the method of content analysis and coding and confirmed by the fuzzy Delphi method, and in the quantitative part, the hierarchical structure model was presented. The statistical population of the research is 25 experts who were selected by non-probability purposeful and snowball sampling and answered the pairwise comparison questionnaire. The findings of the qualitative section showed that the model has eight variables including "infrastructure investment", "motivational investment", "economical investment", "institutional investment", "environmental investment", "support investment", "Political investment" and "competitiveness". The findings of the quantitative section showed that the structural model has six levels, that "political investment" and "infrastructure investment" have the most influence in the model and are in the first priority. We conclude that in order to competitive advantage, managers should pay more attention to technical and informational infrastructure, as well as appropriate policies and providing regulations.