Eco-friendly digital marketing strategies are crucial for Jordanian companies that want to meet environmental standards. This covers eco-friendly pricing, goods, and online cooperation. In contrast, customer concern and action are not connected, requiring true green marketing tactics. Jordan’s “Go Green” programme and the EU-EBRD’s Green Financing Facility show that sustainability boosts digital marketing. Eco-friendly branding goes beyond sustainable goods and strategic collaborations to support green causes. Consumer awareness is rising globally, especially in Asia-Pacific. Eco-friendly methods are being used to improve sustainability, employee wellbeing, and operational effectiveness. Email, social media, content, influencers, and SEO are effective digital marketing methods that increase customer involvement and reduce environmental impact. The environmental efforts of Patagonia, IKEA, Tesla, and Google are notable in Jordan. Jordanian economic modernization relies on sectoral strategies that integrate sustainability and diversity. The government is making headway in green projects, notably in energy, to meet Agenda 2030 and the Sustainable Development Goals. Environmentally responsible firms use content development, social media, and influencer marketing to create real stories and engage communities. Content marketing requires understanding the target audience, creating instructional resources, and effective distribution. Influencer marketing boosts brand awareness and engagement. Jordan suffers from resource limitations and the need for ongoing education, yet urbanisation and cultural growth are promising. Investments and government projects in green initiatives are enabling this change. Jordanians are increasingly buying eco-friendly items, which affects brand loyalty. Eco-friendly branding boosts customer views and brand awareness in Jordan, emphasising the significance of environmental responsibility in business.

This research delves into the urgent requirement for innovative agricultural methodologies amid growing concerns over sustainable development and food security. By employing machine learning strategies, particularly focusing on non-parametric learning algorithms, we explore the assessment of soil suitability for agricultural use under conditions of drought stress. Through the detailed examination of varied datasets, which include parameters like soil toxicity, terrain characteristics, and quality scores, our study offers new insights into the complexities of predicting soil suitability for crops. Our findings underline the effectiveness of various machine learning models, with the decision tree approach standing out for its accuracy, despite the need for comprehensive data gathering. Moreover, the research emphasizes the promise of merging machine learning techniques with conventional practices in soil science, paving the way for novel contributions to agricultural studies and practical implementations.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.

Technology development in the agricultural sector is important in the development of Thailand’s economy. The purpose of this research was to study the approach of guidelines for future agricultural technology development to increase productivity in the Agricultural sector in order to develop a structural equation model. The research applied mixed-methodology. Qualitative research by in depth interview from 9 experts and focus group with 11 successful businesspersons for approve this model. The quantitative data gather from firm, in the 500 of agricultural sector by using questionnaire, using statistical tests of descriptive analysis, inferential analysis, and multivariate analysis. The research found guidelines for future agricultural technology development to increase productivity in the Agricultural sector composed of 4 latent. The most important item of each latent were as following: 1) Agrobiology Technology (= 4.41), in important item as choose seeds that for disease resistance and tolerate the environment to suit the cultivation area, 2) Environmental Assessment (= 4.37),, in important item as survey of cultivated areas according to topography with geographic information system, 3) Agricultural Innovation (= 4.30), in important item as technology reduces operational procedures, reduce the workforce and can reduce operating costs, and 4) Modern Management Systems (= 4.13), in important item as grouping and manage as a cooperative to mega farms. In addition, the hypothesis test found that the difference in manufacturing firm sizes. Medium and Small size and large size revealed overall aspects that were significantly different at the level of 0.05. The analysis of the developed structural equation model found that there was in accordance and fit with the empirical data and passed the evaluation criteria. Its Chi-square probability level, relative Chi-square, the goodness of fit index, and root mean square error of approximation were 0.062, 1.165, 0.961, and 0.018, respectively.

The recent crisis-filled period has placed a significant burden on various businesses, including in the tourism sector. As a result, the concept of resilience, the flexible ability to resist, has become more and more tangible. This study aims to update the quantitative organizational resilience assessment scale of Orchiston, Prayag and Brown. The paper analyses a sample of 87 tourism service providers managing attractions, and factor analysis was carried out to identify the factors in order to be able to measure the resilience of tourism service providers. Four factors could be identified: Leadership and Organization, Strategy, Independence, and Internal Identity. These identified factors and the included 14 items mean the key contribution, as a new, updated assessment system.

This paper presents an assessment approach to fostering socioeconomic re-development and resilience in Iraqi regions emerging from the destruction and instability, in the aftermath of the war conflict in Iraq. Focusing on the intricate interplay of logistics infrastructure and economic recovery, the present study proposes a novel framework that integrates general resilience insights, data analytics, infrastructure systems, and decision support from Data Envelopment Analysis (DEA). We draw inspiration also from historical cases on “creative destruction” or “Blessing in Disguise” (BiD) phenomena, like the post-WWII reconstruction of Rotterdam, so as to develop the notion of stepwise or cascadic prosilience, analyzing how innovative logistics systems may in various stages contribute to economic rejuvenation. Our approach recognizes the multifaceted nature of regional resilience capacity, encompassing both static (conserving resources, rerouting, etc.) and dynamic (accelerating recovery through innovative strategies) dimensions. The logistics aspect spans both the supply side (new infrastructure, ICT facilities) and the demand side (changing transportation flows and product demands), culminating in an integrated perspective for sustainable growth of Iraqi regions. In our study, we explore several forward-looking strategic future options (scenarios) for recovery and reconstruction policy factors in the context of regional development in Iraq, regarding them as crucial strategic elements for effective post-conflict rebuilding and regeneration. Given that such assets and infrastructures typically extend beyond a single city or area, their geographic scope is broader, calling for a multi-region approach. By leveraging the extended DEA approach by an incorporation of a super-efficiency (SE) DEA approach so as to better discriminate among efficient Decision-Making Units (DMUs)—in this case, regions in Iraq—our research aims to present actionable and effective insights for infrastructure investment strategies at regional-governorate scale in Iraq, that optimize efficiency, sustainability and resilience. This approach may ultimately foster prosperous and stable post-conflict regional economies that display—by means of a cascadic change—a new balanced prosilient future.