The current study examines the impact that technological innovation, foreign direct investment, economic growth, and globalization have on tourism in top 10 most popular tourist destinations in the world. The information on the number of tourists, foreign direct investment, growth in gross domestic product, GFCF, use of FFE, and total energy consumption were extracted from the World Development Indicators. The United Nations Conference on Trade and Development (UNCTAD) database was used for collecting the statistics about technological innovation.  The source ETH Zurich has been utilized to gather panel data for the time period 2008 to 2022 to calculate the KOF Index of Globalization. Theoretically, FDI and Economic growth are the endogenous variables for the Tourism model. Whereas, TI, Glob, Energy Consumption, and GFCF are the exogenous variables. Hence, the analysis is based on the System Equation—Simultaneous equations, after checking identification that confirms the problem of simultaneity in system of 3 equations. The empirical outcomes suggest that TI, FDI, globalization index, GDP growth, and energy consumption are the most important factors that contribute to an increase in tourism. Likewise FDI as the endogenous variable is favorably impacted by globalization, technological innovation, fossil fuel energy consumption, gross fixed capital formation, and tourism. Nevertheless, the coefficient of GFCF is only insignificant in the study. While, globalization, TI, and FFE are also favorably affecting the FDI. GDP growth is the second endogenous variable in this research, and it is positively influenced by globalization, FDI, and tourism in the case of the top 10 nations that are most frequently visited by tourists.

Reusable bags have been introduced as an alternative to single-use plastic bags (SUPB). While beneficial, this alternative is economically and environmentally viable only if utilized multiple times. This study aims to identify the determinants influencing the use of reusable bags (RB) over single-use plastic bags (SUPB) within the framework of ecological impact reduction, employing the Theory of Planned Behavior (TPB). The focus is on understanding how attitudes (AT), subjective norms (SN), and perceived behavioral control (PBC) collectively guide consumers towards adopting reusable bags as a pro-environmental choice. The focus is on understanding how attitudes (AT), subjective norms (SN), and perceived behavioral control (PBC) collectively guide consumers towards the adoption of reusable bags as a pro-environmental choice. Data were collected through a survey administered to 814 consumers in Lahore, employing both regression analysis and Structural Equation Modeling (SEM) to assess the impact of AT, SN, and PBC on reusable bag consumption (RBC). The TPB framework underpins the hypothesis that these three psychological factors significantly influence the decision to use RBs. Both regression and SEM analyses demonstrated that AT, SN, and PBC positively affect RBC, with significant estimates indicating the strength of each predictor. Specifically, PBC emerged as the strongest predictor of RBC (PBC2, β = 0.533, p < 0.001), highlighting the paramount importance of control perceptions in influencing bag use. This was followed by AT (β = 0.211, p < 0.001) and SN (β = 0.173, p < 0.001), confirming the hypothesized positive relationships. The congruence of findings from both analytical approaches underlines the robustness of these techniques in validating the TPB within the context of sustainable consumer behaviors. The investigation corroborates the TPB’s applicability in predicting RBC, with a clear hierarchy of influence among the model’s constructs. PBC’s prominence underscores the necessity of enhancing consumers’ control over using RBs to foster sustainable consumption patterns. Practical implications include the development of policies and marketing strategies that target the identified determinants, especially emphasizing the critical role of PBC, to promote broader adoption of RBs and contribute to significant reductions in plastic waste.

The article reveals the problems of the transition to a “green” economy based on sustainable technological changes, which are caused by global ecological pollution of the ecosystem, which leads to warming and ecological changes and the insufficiency of the natural resource potential to meet the needs of the population of the planet, which does not contribute to development. The essence of the study is to determine the impact of a green economy on economic growth and development, in which natural assets continue to provide resources and environmental services. It is shown that the green economy provides a practical and flexible approach to achieving concrete, measurable progress in all its economic and environmental principles, while at the same time fully taking into account the social consequences of greening the dynamics of economic growth. Green economy strategies aim to ensure that natural assets can fully realize their economic potential in a sustainable manner. This potential includes the provision of vital life support services—clean air and water, as well as the sustainable biodiversity needed to support food production and human health. Natural assets cannot be replaced indefinitely, so the policy of the green economy should take this into account. It is characterized that the green economy provides a practical and flexible approach to achieving concrete, measurable progress in all its economic and environmental principles, while at the same time fully taking into account the social consequences of greening the dynamics of economic growth. The problems of the post-war revival of Ukraine’s economy are systematized and proposals for their solution are substantiated, which is the scientific contribution of the authors to the coverage of this problem. The global problems of the transition to a green economy, which are closely related to Ukrainian realities, are revealed. The practical content is determined by the fact that the theoretical and methodological provisions, conclusions and scientific and practical recommendations constitute the scientific basis for the development of a new holistic concept of the development of the green economy of Ukraine. The conclusions that it is the “green” economy that is able to most closely link the ecological and economic aspects of the national economy, acting as a key direction for ensuring the sustainable “green” development of the region and the state as a whole, actualize the prospects of creating a green economy in Ukraine and become necessary and quite achievable in the post-war period.

Nigeria’s palm oil processing industry poses significant environmental pollution risks, jeopardizing the country’s ability to meet the UN’s 17 Sustainable Development Goals (SDGs) by 2030. Traditional processing methods generate palm oil mill effluent (POME), contaminating soil and shallow wells. This study investigated water samples from five locations (Edo, Akwa-Ibom, Cross River, Delta, and Imo states) with high effluent release. While some parameters met international and national standards (WHO guidelines, ASCE, NIS, and NSDWQ) others exceeded acceptable limits, detrimental to improved water quality. Results showed, pH values within acceptable ranges (6.5–8.5), high total conductivity and salinity (800–1150 µS/cm), acceptable hardness values (200–300 mg/L), nitrite concentrations (10–45 mg/L), excessive magnesium absorption (> 50 mg/L), biochemical oxygen demand (BOD) indicating significant pollution (75–290 mg/L), total dissolved solids (TDS) exceeding safe limits in four locations, total solids (TS) exceeding allowable limits for drinking water (310–845 mg/L), water quality index (WQI) values ranged from “poor” to “very poor”. POME contamination by metals like magnesium, nitrite, chloride, and sodium compromised shallow well water quality. Correlation analysis confirmed robust results, indicating strong positive correlations between conductivity and TDS (r = 0.85, p < 0.01) and pH and total hardness (r = 0.65, p < 0.05). The study emphasizes the need for environmentally friendly palm oil processing methods to mitigate pollution, ensure safe drinking water, and achieve Nigeria’s SDGs. Implementation of sustainable practices is crucial to protect public health and the environment.

The increasing demand for electricity and the need to reduce carbon emissions have made optimizing energy usage and promoting sustainability critical in the modern economy. This research paper explores the design and implementation of an Intelligent-Electricity Consumption and Billing Information System (IEBCIS), focusing on its role in addressing electricity sustainability challenges. Using the Design Science Research (DSR) methodology, the system’s architecture collects, analyses, and visualizes electricity usage data, providing users with valuable insights into their consumption patterns. The research involved developing and validating the IEBCIS prototype, with results demonstrating enhanced real-time monitoring, load shedding schedules, and billing information. These results were validated through user testing and feedback, contributing to the scientific knowledge of intelligent energy management systems. The contributions of this research include the development of a framework for intelligent energy management and the integration of data-driven insights to optimize electricity consumption, reduce costs, and promote sustainable energy use. This research was conducted over a time scope of two years (24 months) and entails design, development, pilot test implementation and validation phases.

In the era of artificial intelligence, smart clothing, as a product of the interaction between fashion clothing and intelligent technology, has increasingly attracted the attention and affection of enterprises and consumers. However, to date, there is a lack of focus on the demand of silver-haired population’s consumers for smart clothing. To adapt to the rapidly aging modern society, this paper explores the influencing factors of silver-haired population’s demand for smart clothing and proposes a corresponding consumer-consumption-need theoretical model (CCNTM) to further promote the development of the smart clothing industry. Based on literature and theoretical research, using the technology acceptance model (TAM) and functional-expressive-aesthetic consumer needs model (FEAM) as the foundation, and introducing interactivity and risk perception as new external variables, a consumer-consumption-need theoretical model containing nine variables including perceived usefulness, perceived ease of use, functionality, expressiveness, aesthetics, interactivity, risk perception, purchase attitude, and purchase intention was constructed. A questionnaire survey was conducted among the Chinese silver-haired population aged 55–65 using the Questionnaire Star platform, with a total of 560 questionnaires issued. The results show that the functionality, expressiveness, interactivity, and perceived ease of use of smart clothing significantly positively affect perceived usefulness (P < 0.01); perceived usefulness, perceived ease of use, aesthetics, and interactivity significantly positively affect the purchase attitude of the silver-haired population (P < 0.01); perceived usefulness, aesthetics, interactivity, and purchase attitude significantly positively affect the purchase intention of the silver-haired population (P < 0.01); functionality and expressiveness significantly positively affect perceived ease of use (P < 0.01); risk perception significantly negatively affects purchase attitude (P < 0.01). Through the construction and empirical study of the smart clothing consumer-consumption-need theoretical model, this paper hopes to stimulate the purchasing behavior of silver-haired population’s consumers towards smart clothing and enable them to enjoy the benefits brought by scientific and technological advancements, which to live out their golden years in comfort, also, promote the rapid development of the smart clothing industry.