Iran has one of the oldest civilizations in the world, and many elements of today’s urban planning and design have their origins in the country. However, mass country-city migration from the 1960s onwards brought enormous challenges for the country’s main cities in the provision of adequate housing and associated services, resulting in a range of sub-standard housing solutions, particularly in Tehran, the capital city. At the same time, and notably in the past decade, Iran’s main cities have had significant involvement in the smart city movement. The Smart Tehran Program is currently underway, attempting to transition the capital towards a smart city by 2025. This study adopts a qualitative, inductive approach based on secondary sources and interview evidence to explore the current housing problems in Tehran and their relationship with the Smart Tehran Program. It explores how housing has evolved in Tehran and identifies key aspects of the current provision, and then assesses the main components of the Smart Tehran Program and their potential contribution to remedying the housing problems in the city. The article concludes that although housing related issues are at least being raised via the new smart city technology infrastructure, any meaningful change in housing provision is hampered by the over centralized and bureaucratic political system, an out of date planning process, lack of integration of planning and housing initiatives, and the limited scope for real citizen participation.

The main purpose of this paper was to examine the impact of generative artificial intelligence (AI) on employee well-being and work dynamics. Using qualitative methodology, three semi-structured interviews were conducted to investigate the implications of generative AI on employee outcomes such as efficiency, job satisfaction, ethical considerations, and work-life balance. The findings highlighted the potential benefits and risks associated with generative AI implementation in the workplace. The study contributed to the literature by adopting a qualitative approach, allowing in-depth exploration of individual experiences with generative AI in the workplace. The study discussed the implications for employers, employees, and society.

Although much bibliometric research has been conducted to analyze publications on energy policy, a systematic investigation of the sustainability of nuclear energy use after the Fukushima nuclear accident is still lacking. Therefore, this study conducted a comprehensive bibliometric review of the sustainability of nuclear energy policy (NEP). This study discusses NEPs, highlighting their disadvantages; emerging research themes; and networks of the most productive authors, countries, journals, and institutions over the last 20 years (2002–2022). This timeframe was selected because of the Fukushima nuclear accident, which has been one of the largest environmental disasters in recent years. Bibliometric analysis was carried out by reviewing 1146 documents from the Scopus database using the keywords “energy policy” and “nuclear energy.” The OpenRefine software was used to deep-clean keywords with the same meaning, and VOSviewer was used to visualize them. The results show that over the past two decades, future research themes and trends in the study of NEP have focused on nuclear fuel, the Fukushima nuclear accident, risk perception, energy transition, and renewable energy. Bibliometric analysis has positively affected the development of NEP in countries that do not yet have nuclear power plants, such as Indonesia.

Vegetable production is an important sector of economy for farmers in Nepal. The analysis was carried out to explore the trends in vegetable production sector in Nepal along with the recent trend of some major vegetables in terms of area, production and yield. The time series data from 1977/78 to 2016/17 (40 years) of vegetables production and 5 years data (2011/12 - 2015/16) of major vegetables were collected from reliable source and analysis was done through Microsoft Excel. The results show that between 1977/78 and 2016/17 the area under vegetables cultivation has jumped by 222.8% while production is increased by 728.21% and productivity is increased by 156.6% during this course. The result also reveals that during the period of 5 years (2011/12 - 2015/16), solanaceous and cruciferous vegetables has an increasing trend in area, production and yield except for the area under cultivation for eggplant (declined by 5.2%) and for radish (declined by 6.0%) respectively while cucurbitaceous vegetables has increasing trend in area and production but an declining trend in yield except for the yield of cucumber (increased by 15.8%). However, the trend of other major vegetables is seen highly fluctuating over the years. 

India’s economic growth is of significant interest due to its expanding Gross Domestic Product (GDP) and global market influence. This study investigates the interplay between production, trade, carbon dioxide (CO₂) emissions, and economic growth in India using Granger causality analysis. Also, the data from 1994 to 2023 were analyzed to explore the relationships among these variables. The results reveal strong positive correlations among production, trade, CO₂ emissions, and GDP, with production showing significant associations with export, import, and GDP. Co-integration tests confirm the presence of a long-term relationship among the variables, suggesting their interconnectedness in shaping India’s economic landscape. Regression analysis indicates that production, export, import, United States (US)-India trade, manufacturing cost of energy, and CO₂ emissions significantly impact GDP. Moreover, the Vector Error Correction Model (VECM) estimation reveals both short-term and long-term dynamics, highlighting the importance of understanding equilibrium and deviations in economic variables. Overall, this study contributes to a better understanding of the complex interactions driving India’s economic growth and sustainability.