درخت حوزه‌های تخصصی

The agricultural sector in developing countries plays an important role in promoting national development and rational policy making and strategic planning to advance the sustainable development of this sector are of main concerns of the relevant institutional actors. In this regard, the current research was conducted with the aim of identifying scenarios of sustainable agricultural development in the catchment area of Zayandeh River in Isfahan province. The present research was applied, of descriptive-survey type. The statistical population was experts related to agricultural development in the province. To collect data, library sources, questionnaires and interviews were used. Delphi method and interviews with elites and executives were used to identify the primary components and drivers effective on the sustainable development of agriculture in the Zayandeh River watershed of Isfahan province. The snowball technique was used to select the experts. Finally, 8 key drivers were identified and separated in order to explain the research variables in a strategic format. Based on this, in the section related to the expression of research priorities in two direct and indirect modes, these 8 key factors have been repeated in different priorities. Questionnaires were distributed among 25 experts. In this study, five plausible scenarios were identified for forecasting the future of sustainable agricultural development by considering potential outcomes based on key factors and their similarities or differences across the categories of favorable, static, and critical scenarios. Based on their total scores, which range from 85 to 109, two scenarios were identified as the most likely: one favorable scenario and one critical scenario.

Housing satisfies crucial needs, as shown in Maslow’s Hierarchy of Needs. Be that as it may, the Sustainable Development Goals evidently have one critical aspect missing in its 17 goals: achieving housing security for all. Goal 11 mentions urban settlement but fails to understand the concept of housing security. Over a billion people reside in slums and other informal settlements across the globe, and the number is expected to increase. However, there is a lack of a comprehensive, multidimensional, and validated instrument for measuring the extent of housing insecurity despite housing significantly impacting household’s health, economic, and psychological well-being. Methods: This study sought to apply and adopt a newly developed multidimensional household housing insecurity index (HHII), consisting of eight dimensions that respond to the lack of universally accepted measures of housing insecurity. This study used primary data with a sample size of 600 South African households collected in four types of areas in two provinces (Gauteng and KwaZulu Natal). Results: The findings indicated that merely 25% of households were deemed housing secure, in stark contrast to 75% facing varying levels of housing insecurity, from mild to severe. This concerning result highlights that, even after more than thirty years of democracy, housing remains a significant problem in South Africa. Conclusions: The study reveals that housing insecurity significantly impacts Black populations, with female heads of households in rural and informal settings facing the most severe challenges.

In the real world, situations frequently occur when we want to allocate a fixed cost between a set of decision-making units (DMUs) such as institutions, organizations. In this paper, we use the data envelopment analysis (DEA) technique to allocate fixed costs among DMUs. First, we introduce semi-additive production technology in DEA and present efficiency evaluation models in this technology. In estimating the frontier of this technology, in addition to the observed DMUs, the set of all aggregations of these DMUs are also used. In the following, we propose an interactive process for fixed cost allocation between DMUs in DEA based on the concept of cross-efficiency. We show that our proposed iterative approach is always feasible, and ensures that all DMUs become efficient after the fixed cost is allocated as an additional input measure. The cross-efficiency scores corresponding to all DMUs are improved at each stage of the interactive process. We also illustrate the proposed approach with a numerical example. The proposed approaches are demonstrated using an application of the fixed cost allocation problem for branches of commercial banks. Finally, we bring the results of the research.

The development of knowledge and advancement in technology has created a wide-ranging transformation in societies and has led to changes in the per-formance of companies in order to respond to environmental turmoil and social expectations. In this way, they tried to gain a significant competitive advantage over other competitors. The purpose of this study was to investi-gate the moderating role of managerial fortification in relation to the impact of technology-based capabilities on the product market competition of knowledge-based companies in the capital market: a source-based capabili-ties (DEA). This research is applied in terms of purpose and in terms of data envelopment analysis is a quasi-experimental and post-event research in the field of positive accounting research. Then, based on multivariate regression, the research hypothesis was tested using Eviews software. The statistical population studied in this study consisted of knowledge-based companies listed on the Tehran Stock Exchange during the years 2015 to 2019 and 79 companies were selected and reviewed based on systematic screening. The result of testing the research hypothesis is that the technological capabilities have a positive and significant effect on the product market competition of knowledge-based companies in the capital market. This result demonstrates that the resource-based technology capability based on the source-based capabilities is seen as a resource against stagnation in a competitive environ-ment and helps the company, to maintain flexibility in the face of environ-mental change in order to respond faster, at the same time to develop the company's competitive capacity to create new resources or new and innova-tive products, and to make the company's future more attractive to stake-holders with greater returns and potential risk control.

The existence of bubbles in the market, especially the capital market, can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country. On the other hand, due to the goal of investors in achieving a portfolio of high returns with the least amount of risk, the need to pay attention to these markets increases. In this research, with the aim of maximizing return and minimizing investment risk, an attempt has been made to form an optimal portfolio in conditions where the capital market has a price bubble. According to the purpose, the research is of applied type, and in terms of data, quantitative and post-event, and in terms of type of analysis, it is of descriptive-correlation type. In order to identify the months with bubbles in the period from 2015 to 2021 in the Tehran Stock Exchange market, sequence tests and skewness and kurtosis tests were used. After identifying periods with bubbles, the meta-heuristic algorithms were used to optimize the portfolio. The results indicate the identification of 14 periods with price bubbles in the period under study. Also, in portfolio optimization, selected stock portfolios with maximum returns and minimum risk are formed. This research will be a guide for investors in identifying bubble courses and how to form an optimal portfolio in these conditions.

The real interest rate is a key and important economic variable in policymaking, economic stability, and economic growth. Current advanced economies are heavily influenced by interest rates and react quickly to changes in them. In fact, interest rates act as a powerful control tool in managing and directing the market. In this regard, the main goal of this study is to investigate the convergence of the economic performance of the provinces and to investigate the effect of the real interest rate on the convergence speed of the economic performance of Iran's provinces.The results obtained from estimating models using spatial econometrics in the period of 2011 – 2022 showed that the real interest rate has a significant negative impact on economic performance convergence among provinces. Annually, 3.86% of the economic gap between provinces is reduced in the case of absolute convergence, and 4.55% and 4.175% in the case of conditional convergence, moving toward a stable state. Other results revealed that the individuals using the internet in provinces as an indicator of information and Communication Technology (ICT), and the real capital stock in provinces have a positive and significant effect on economic performance convergence. However, the number of university graduates per capita in provinces, as a measure of human capital, does not have a significant impact on the convergence of economic performance across provinces. This contrasts with the expectation that human capital would have a significant effect on the convergence of economic performance across provinces.