This study presents an in-depth investigation of watermelon cultivation in Bangladesh, focusing on the assessment of production levels, costs, influential factors, and the application of Fuzzy Cognitive Map (FCM) technology for precision agriculture. Utilizing degree centrality and closeness centrality measures, the FCM model is employed to systematically examine the interplay among various elements involved in watermelon cultivation in Bangladesh and to elucidate the impacts of these factors on production yield. The findings contribute to the advancement of precision agriculture practices and provide valuable insights for optimizing watermelon production management in Bangladesh.

This study addresses the challenge of selecting appropriate electric vehicles for urban logistics, with a specific focus on the impact of various multi-criteria analysis methods on this complex decision-making process. The investigation utilizes a mixed methodology, combining objective weight determination methods, such as Entropy, CRITIC (Criteria through the Inter-Criteria Correlation), and MEREC (Method Based on the Removal Effects of Criteria), alongside standard deviation and a modified version of the standard deviation method. The Simple Additive Weighting (SAW) method was further employed for alternative ranking. Application of these methods across nine diverse Small Van vehicles, assessed according to 12 criteria, highlighted the paramountcy of Charge Time and Cargo Volume as factors bearing the most significant weight in decision-making. The Toyota Proace City Verso Electric L2 emerged as a superior choice under most conditions. Yet, the results varied when applying weights deduced through the MEREC method, leading to the ascendency of the Renault Kangoo E-Tech.

In decision-making scenarios, challenges often arise from closely knitted criteria or inherent uncertainties. Such uncertainties prominently pervade the realm of sustainable energy, particularly concerning hydrogen generation systems. A critical need is identified to elucidate the efficiency, costs, and environmental implications of these technologies as a shift towards a low-carbon economy is pursued. In this study, the interdependencies among decision-making variables were examined, revealing their collective influence and correlations. By utilizing the framework of Intuitionistic Hypersoft Sets (IHSSs), uncertainties were addressed, multi-criteria decision-making (MCDM) was harnessed, technological selection was facilitated, resource allocation was optimized, and environmental ramifications were assessed. The primary objective of this research was to decipher the conundrum of choosing among multiple hydrogen production methodologies. Such an approach fosters the adoption of environmentally conducive hydrogen production methods, heralding a shift towards a greener energy future. Notably, further research could probe into methodologies like AHP and TOPSIS in a neutrosophic context, offering tantalizing avenues for exploration.

Disruptive technologies such as the big data analytics, blockchain, Internet of Things, and artificial intelligence have each impacted how businesses operate. The most recent example of disruptive technology is artificial intelligence (AI), which has the most potential to revolutionize marketing completely. Practitioners worldwide are searching for artificial intelligence (AI) solutions most suited for their marketing functions. Artificial intelligence can provide marketers with assistance in a variety of ways to boost client satisfaction. This article looks at the exciting new developments in artificial intelligence (AI) and marketing that have been occurring recently, it examines the latest developments in marketing using artificial intelligence (AI). These breakthroughs encompass predictive analytics for analyzing customer behaviour, integrating chatbots to enhance customer support, and implementing AI-driven content personalization tactics. This article also covers the horizons and problems of artificial intelligence and marketing, the precise applications of AI in a range of marketing segments, and their impact on marketing sectors. Additionally, this article examines the particular applications of AI in marketing.

Advancements in technology have revolutionized communication, socialization, and work paradigms. The surges in globalization, the permeation of digital culture, and the expansion of online communication tools have prompted organizations globally to adopt virtual teams. These virtual environments, while beneficial, present a myriad of challenges that necessitate the application of system dynamics to optimize performance. A systematic review was conducted to analyze previous studies focusing on the leadership of virtual teams within the context of systems thinking. Seven databases, including Sage Online, Springer, JSTOR, Taylor and Wiley Online Library, Francis Online, Google Scholar, and Semantic Scholar, were utilized. From an initial pool of 5,070 studies, 30 were meticulously screened, summarized, and synthesized based on pre-established inclusion and exclusion criteria. The review highlighted the recurrent emphasis on factors such as communication technology, trust, intra-team relationships, and leadership strategies as pivotal for enhancing virtual team performance. This synthesis aims to present a comprehensive overview of current research trajectories in the field, delineating existing research gaps, limitations, and challenges.