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.

Purpose: This study investigates the mediating effect of Environmental Attachment (EA) among consumers in an emerging market, concentrating on the impact of two key factors: Green Environmental Awareness (GEA) and Sense of Responsibility (SOR) on Sustainable Product Consumption (SPC). Design/methodology/approach: A thorough online survey was carried out with Google Docs and distributed to 304 Pakistani consumers who now use or are considering purchasing sustainable or green products. Structural Equation Modeling (SEM) was used to rigorously test the suggested model utilizing a non-probability sampling technique, specifically the stratified purposive sampling approach. Findings: Green environmental awareness (GEA) and a sense of responsibility (SOR) have been shown to have a substantial impact on creating environmental attachment (EA) in both existing and potential customers of sustainable products. The findings of this study also revealed that environmental attachment (EA) plays an important role as a mediator in the links between green environmental awareness (GEA) and the consumption of sustainable goods (SPC), as well as between a sense of responsibility (SOR) and SPC. Despite this, it is crucial to note that the projected direct effect of GEA on SPC was shown to be statistically insignificant. This conclusion implies that additional factors outside the scope of this study may influence the relationship between GEA and SPC. Research limitations/implications: It is vital to highlight that the focus of this study is on an online sample of consumers near Punjab, Pakistan. Future studies should look at other parts of Pakistan to acquire a more complete picture of sustainable consumption trends. Furthermore, our findings suggest that characteristics impacting sustainable consumption, such as Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), may differ among countries. As a result, performing a comparison analysis involving two or more countries could provide valuable insights into projecting sustainable product consumption among current and potential sustainable product customers. Originality/Value: This study contributes to the literature by investigating the factors of sustainable consumption using the lens of the Norm Activation Model theory (NAM), notably Green Environmental Awareness (GEA) and Sense of Responsibility (SOR), to predict sustainable product consumption. The findings are important for promoting long-term goals in Pakistan and provide a framework that can be applied in other emerging markets.

India has experienced notable advancements in trade liberalization, innovation tactics, urbanization, financial expansion, and sophisticated economic development. Researchers are focusing more on how much energy consumption of both renewable and non-renewable accounts for overall system energy consumption in light of these dynamics. In order to gain an understanding of this important and contentious issue, we aim to examine the impact of trade openness, inventions, urbanization, financial expansion, economic development, and carbon emissions affected the usage of renewable and non-renewable energy (REU and N-REU) in India between 1980 and 2020. We apply the econometric approach involving unit root tests, FE-OLS, D-OLS, and FM-OLS, and a new Quantile Regression approach (QR). The empirical results demonstrate that trade openness, urbanization and CO₂ emissions are statistically significant and negatively linked with renewable energy utilization. In contrast, technological innovations, financial development, and economic development in India have become a source of increase in renewable energy utilization. Technological innovations were considered negatively and statistically significant in connection with non-renewable energy utilization, whereas the trade, urbanization, financial growth, economic growth, and carbon emissions have been established that positively and statistically significant influence non-renewable energy utilization. The empirical results of this study offer some policy recommendations. For instance, as financial markets are the primary drivers of economic growth and the renewable energy sector in India, they should be supported in order to reduce CO₂ emissions.

The increase in world carbon emissions is always in line with national economic growth programs, which create negative environmental externalities. To understand the effectiveness of related factors in mitigating CO₂ emissions, this study investigates the intricate relationship among macro-pillars such as economic growth, foreign investment, trade and finance, energy, and renewable energy with CO₂ emissions of the high gross domestic product economies in East Asia Pacific, such as China, Japan, Korea, Australia and Indonesia (EAP-5). Through the application of the Vector Error Correction Model (VECM), this research reveals the long-term equilibrium and short-term dynamics between CO₂ emissions and selected factors from 1991 to 2020. The long-term cointegration vector test results show that economic growth and foreign investment contribute to carbon reduction. Meanwhile, the short-term Granger causality test shows that economic growth has a two-way causality towards carbon emissions, while energy consumption and renewable energy consumption have a one-way causality towards carbon emissions. In contrast, the variables trade, foreign direct investment, and domestic credit to the private sector do not have two-way causality towards CO₂ emissions. The findings reveal that economic growth and foreign investment play significant roles in carbon reduction, which are observed in long-term causality relationships, while energy consumption and renewable energy are notable factors. Thus, the study offers implications for mitigating environmental concerns on national economic growth agendas by scrutinizing and examining the efficacy of related factors.

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.

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.