Journal of Systems Thinking in Practice
Volume:3 Issue: 2, Spring 2024

Presently, the tourism industry confronts a multitude of challenges, such as the mismatch between the quality of services provided and tourists' expectations and the management of tourist identity and security. These challenges can be addressed with the emergence of advanced technologies, including blockchain technology. This research uses the system dynamics approach to investigate the implementation and application of blockchain technology in the tourism supply chain of travel agencies in Isfahan. This research has a practical purpose, aiming to address real-world issues. Additionally, the nature and methodology of the study are descriptive-causal, and the data collection method employed in this research is a survey. At first, based on the existing research literature, the factors influencing the implementation and application of blockchain technology in the tourism supply chain of Isfahan travel agencies were identified. Subsequently, using a judgmental sampling method and gathering opinions from 45 experts, managers, and university tourism professionals, the relationships between the identified factors were determined, and a causal loop diagram was drawn. Then, employing a convenience sampling method and gathering information from 15 selected travel agencies in Isfahan, mathematical relationships between the identified factors were determined, and a stock and flow diagram was designed. The simulation results of this research indicated that the quality of using blockchain technology in the early years of its implementation was not favorable, but it would improve over time. Furthermore, the findings demonstrated a positive correlation between the quality of using blockchain technology with service quality and the level of tourist attraction. The scenarios designed in this research showed that by allocating more resources to employee training and enhancing information technology infrastructure, the quality of using blockchain technology and the quality of the services could significantly improve during the initial years of implementation of blockchain technology.

In this paper, we propose using a mixed genetic-floyd-warshall algorithm in combination with a Floyd-warshall algorithm to model the satisficing behaviour of consumers across spatially differentiated stores. Consumer agents can pick a basket of goods from different stores to either maximize their utility or to “satisfice” by selecting the first basket with a utility that is higher than their satisfaction threshold. The Floyd-warshall algorithm is used to find the shortest path between two chosen stores by considering travel cost. Factors such as price, quality of goods, the cost of travel to the store, consumers' decision-making preferences, and store locations play significant roles in the decision-making process of consumer agents. The model is tested based on mechanisms at the individual level to show how the model works and at the macro-level to reproduce foundational theories in economics.

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.

Chaos theory offers a unique lens to understand the intricate relationships between economic growth and energy supply pricing. Existing economic theories often emphasize energy prices' inherent randomness, unpredictability, and economic growth. A deeper comprehension can be achieved by applying chaos theory to this complex system. Developing a dynamic model that captures the causal relationships among the various variables impacting economic growth, energy supply, and pricing is crucial for unraveling this complexity. This study aims to delve into the chaotic nature of the energy economy system within the context of economic growth. The research methodology is rooted in a fundamental-applied approach. By employing numerical simulation techniques, specifically utilizing the Simulink MATLAB toolbox, the study seeks to explore and potentially control chaos within the system. The findings highlight the system's nonlinear dynamics, showcasing its sensitivity to initial conditions and exhibiting chaotic behavior, limit cycles, and stable equilibrium points across varying initial values. This research endeavor contributes to a more nuanced understanding of the interplay between energy economics, economic growth, and pricing dynamics.

Resilience is one of the most crucial parameters in the electricity supply chain, and the absence of this concept can lead to various issues in service provision. One perspective that can greatly contribute to resilience is utilizing the Industry 4.0 approach. This study examines the challenges and strategies for the flexibility of the electricity supply chain in the Industry 4.0 era. A descriptive-analytical method employing library research and field studies has been employed. Subsequently, using the factors and criteria obtained from Value-Focused Thinking (VFT) from Soft Operational Research and verification by literature, a fuzzy IVIF-WASPAS-based analysis was conducted. The decision-making team comprised internal experts in the electricity supply chain in Iran, focusing on the principles of resilience in the Industry 4.0 era to analyze key issues. A case study was also conducted within the electricity supply chain, incorporating insights from academic experts and the team's experiences. Strategies like smart network systems, blockchain technology, cybersecurity, and education are fundamental to enhancing the supply chain's flexibility. This study's findings indicate a long journey in developing Industry 4.0 in Iran's electricity supply chain. However, relying on the proposed strategies can minimize existing issues and propel the system toward growth.

As one of the emerging research fields of sustainability management, Organizational Citizenship Behavior (OCB), especially its influence on employee performance, has drawn increased attention in the academic and industrial areas. Nevertheless, existing studies mainly examine the static relationship between OCB and employee performance. Therefore, this paper aims to evaluate the dynamic impacts of OCB on employee performance in Yasuj Municipality with the assistance of a system dynamics model. Four causal feedback loops and a stock-flow diagram were developed to illustrate the dynamic influencing mechanism. Three distinct policies quantitatively simulated the possible impacts of OCB changes on the whole system and, specifically, on employee performance. The results show that increasing the Actual Increasing Rate of Project Culture (AIROC) significantly influences OCB and employee performance improvement. The higher the AIRPP (actual increasing rate of potential promotion) in the multi-policy scenario, the higher the OCB and the performance. One major contribution is that this study is one of the first to explore the potential use of system dynamics to model organizational behavior and its performance, which has implications for the practical and cultural promotion of OCB.