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The contemporary world is marked by generation and consumption of vast volume, high velocity, and considerable diverse data, leading us to the concept of big data. In this study, a system design thinking approach was employed to identify the requirements of Iran's public sector big data system. National big data systems would help governments to support their decisions by data and answer to national problems faster. Given the complexity and time-intensive nature of traditional system requirement analysis methods, their practical application in the industry has been declined. Therefore, in this research, system design thinking as an agile alternative for identifying system requirements has been discussed. To accomplish this, the LDA machine learning method has been utilized to analyze approximately 88,000 articles, a thematic analysis on around 600 Instagram and Twitter posts has been conducted, and six experts representing targeted problem persona were interviewed. The objective of this research is to extract insights to serve as a foundation for formulating big data policies in Iran. Findings reveal that Iran big data system requirements can be classified into four categories which indicate on increasing managed access to data while considering security and privacy, encouraging private and public sectors cooperation, transformation to smart governance, and establishing national data organization which would be responsible of data ID documents. [ABSTRACT FROM AUTHOR]

The continuous and round-the-clock operation of cryptocurrency mining devices generates significant heat that requires powerful cooling systems. Therefore, the main problem of mining is its high electricity consumption and energy usage. Unfortunately, due to the lack of planning by the country's officials, we are facing the problem of electricity shortage, which the growing digital currencies have exacerbated. Since decision-making in the real world (including the electricity shortage problem caused by mining) is complex and uncertain due to various influential factors, this research aims to apply a strategic selection approach to decision-making and provide solutions to solve the electricity shortage problem caused by cryptocurrency mining in Iran. In this study, the Strategic Choice Approach (SCA), one of the soft operational research methods, has been used for analysis, structuring, and decision tree development. For this purpose, four methods (styles) of SCA, which include ten steps, have been implemented. A working group consisting of twelve experts and stakeholders in digital currencies, facilitated by the researchers of this study, has been formed, and specific flowcharts and labels have been used. According to the SCA method, decision-making areas, decision options, areas of uncertainty, exploratory options, and decision trees have been designed. Finally, a "commitment package" ("improvement package") has been proposed to provide practical solutions. This article provides solutions for solving the electricity shortage problem caused by cryptocurrency mining through the SCA. For this purpose, specific tasks have been assigned to the Islamic Consultative Assembly, the Ministry of Economy, the Ministry of Energy and Foreign Affairs, and the government, excluding the mentioned ministries and some key players in digital currencies, which should be carried out in the present and future. By structuring the research problem through the SCA method as one of the soft operations research methods, the readers and users of this research will learn more details and dimensions of the mentioned method, contributing to expanding their knowledge of soft operations research. Although the SCA method has been implemented in Iran and other countries for a long time in various social and organizational issues, the diagrams, shapes, and tables used to implement SCA in this research contribute more to the readers' knowledge. It also helps to localize this method and other research done in the country. [ABSTRACT FROM AUTHOR]

The management of solid waste in Lebanon has evolved into a complex issue, marked by its deleterious environmental, economic, and public health ramifications for both civilians and the state exchequer. Despite the longstanding nature of Lebanon's municipal waste predicament, it escalated to catastrophic proportions in 2015 following the closure of Naameh, the nation's largest landfill. The persisting crisis from 2015 endures due to the government's inadequate and poorly conceived solutions, with the potential to rekindle at any juncture. This paper addresses two fundamental concerns. Initially, a comprehensive portrayal of the municipal solid waste scenario in Lebanon is provided, encompassing its diverse facets. Subsequently, the researchers advocate an integrative approach amalgamating centralized and decentralized systems. Pioneering a strategic proposal to address Lebanon's solid waste predicament, the researchers employ a Journey-Making (JM) methodology to discern direct and indirect actors. Subsequently, a game theory approach, facilitated by the Graph Model for Conflict Resolution (GMCR+) software, is utilized to derive solutions that cater to the satisfaction of all involved parties. The selection of the optimal scenario is contingent upon the available options for the primary stakeholders, factoring in the political, sectarian, economic, and environmental landscape of Lebanon. [ABSTRACT FROM AUTHOR]