Analytical Hierarchy Process

Nowadays, urban planners are encountered with Urban sprawl in the large cities, especially in the developing countries. In order to control this condition they have taken different policies, one of these policies are increase density. The aim of this research is to determine the optimal building density in Isfahan's fifth district. To analyze this subject, firstly the selected district was divided into several quarters (neighborhoods), the indicators in each quarter were studied and weighted according to their suitability for the proposed density, then the weight of each index was established by the use of comparison matrix and eventually the suitability of each quarter was determined to propose the increase of density. The findings of the presented research indicate that because of the specific qualifications of the district, such as the existence of the valuable historic fabric of Jolfa and its neighborhood with Zayande-Rood, the historical center of the ChaharBagh-e-Bala and width of the passages and …, it`s better to avoid the increase of density in this district; and finally some suggestions is presented in order to determine an optimal density for this region.

Corporate Social Responsibility (CSR) is a general concept where companies voluntarily decide to adopt social, economic and environmental responsibilities for a better society and environment. Researchers in the management field have created various CSR models and theories. Moreover, enterprises are working out to strength its competitiveness performance though adopting CSR approaches. For that, decision makers in an enterprise have to target the most appropriate CSR approach that fit with the environment and the nature of their enterprise. The Analytical Hierarchy Process (AHP) has been presented through the article in order to help an organization take decision toward the most convenient CSR method according to many characteristics and criteria.

The Central Statistics Agency (BPS) is a government institution that has the authority to carry out statistical activities in the form of censuses and surveys, to produce statistical data needed by the government, the private sector and the general public, as a reference in planning, monitoring, and evaluation of development results. Therefore, providing quality statistical data is very decisive because it will have an impact on the effectiveness of decision making. This paper aims to develop a framework to determine priority of solutions in overcoming data quality problems using the Analytic Hierarchy Process (AHP). The framework is built by conducting interviews and Focus Group Discussion (FGD) on experts to get the interrelationship between problems and solutions. The model that has been built is then tested in a case study, namely the Central Jakarta Central Bureau of Statistics (BPS). The results of the study indicate that the proposed model can be used to formulate solutions to data problems in BPS.

Nowadays, most of Businesses have faced a great challenge for entering a new market. The existence conditions have forced the managers to apply the innovative methods for simultaneous analyzing of various factors for arrival to special markets. This paper prioritizes a few target markets using two methods. First, the problem is solved by the combined method of hierarchical analysis and Monte Carlo simulation, and then by the method of fuzzy hierarchical analysis and finally the results of both methods are compared. The considered problem in this study relates to a factory of prefabricated building components that is looking for establishing the sale agencies in appropriate towns in order to introduce and distribute the new products. In order to prioritize cities, desired criteria are determined through interviews with experts and investigating the previous studies. The research findings have shown that based on the four main criteria and seven related sub-criteria, the prioritization of selected cities as markets has been A-D-C-B respectively. In the end, it is concluded that based on the findings of this study, managers and stakeholders should pay attention to these priorities in choosing the target market. In this research, for the first time, the combined Monte Carlo technique and hierarchical analysis have been used to select the market. Market selection is one of the issues that has always been a concern of managers and has been associated with a lot of risk. Using Monte Carlo simulation algorithm and hierarchical analysis, by considering different decision intervals, greatly reduces the risk of selection, so this technique is recommended to managers of organizations as a practical method in market selection.