Do environmental knowledge and green trust matter for purchase intention of eco-friendly home appliances? An application of extended theory of planned behavior

Achieving environmentally responsible production through green managerial awareness, human resource management and employee behavior

In the current context of increasing global environmental challenges, sustainable production and development have become strategically important for companies. This study explores the impact of green managerial awareness on environmentally responsible production, both direct and indirect, through the mediating role of green human resource management and environmentally friendly employee behavior. Utilizing a quantitative research approach, data were collected from 207 wine companies, and PLS-SEM technique was employed to analyze the relationships between the variables. The findings reveal that green managerial awareness significantly influences environmentally responsible production, both directly and indirectly, being found that green human resource management is a vital mechanism for translating managerial awareness into effective sustainable practices, while environmentally friendly employee behavior played a crucial role in embedding sustainability into daily operations. It is concluded that organizations can reduce the environmental impact of business operations and integrate sustainability into their culture by promoting environmental awareness among managers, and designing and implementing strategies that link human resource management with environmentally responsible employee behavior and sustainable production. This research has interesting theoretical, managerial, and policy implications, emphasizing the need for a coordinated approach that aligns organizational practices, leadership, and public policy to reduce the environmental impact of the business activities on the natural environment and advance sustainable development goals.

How do perceptions of information usefulness and green trust influence intentions toward eco-friendly purchases in a social media context?

Drawing upon the stimulus-organism-response framework and incorporating green trust and perceptions of information usefulness, we formulated a model to explore how marketing on social media impacts consumers' intentions towards eco-friendly purchases, using eastern Chinese cities as a case study. The findings indicate that: (1) marketing on social media significantly boosts intentions for eco-friendly purchases, and green trust positively affects the perceptions of information usefulness. (2) Green trust and perceptions of information usefulness jointly act as mediators between social media marketing and eco-friendly purchase intentions, with green trust exhibiting a stronger effect (0.306 > 0.122). The multi-group analysis findings indicate significant disparities in several potential pathways as a result of moderating factors such as educational attainment, etc. The benefits are especially apparent in women, people with middle to high incomes, people with intermediate to high levels of education, and people who engage with social media for over three hours per day. Through the effect analysis between marketing on social media, green trust, and perceptions of information usefulness on consumers' intentions towards eco-friendly purchases, this study offers insights to social media platforms, businesses, and policymakers, enabling them to enhance strategies for fostering eco-friendly consumer behavior through social media channels.

Mitigating environmental pollution in China: Unlocking the potential for high-quality innovation

The nexus between environmental pollution (EP) and technological innovation is crucial for achieving sustainable development. However, existing literature has paid less attention to the new form of high-quality innovation (HI) in environmental management. This paper uses panel data from 31 Chinese provinces from 2008 to 2020, employing the two-stage least squares method to investigate the relationship between HI and EP. The empirical results reveal that HI can effectively reduce the EP, which holds after multiple robustness tests, and this effect is more obvious in southern China. Meanwhile, HI drives clean and efficient energy transition and decreases EP. Moreover, increased environmental regulation weakens the influence of HI on EP. The major contributions of this study are constructing an HI index including innovation, human capital, and government support and examining its influence on EP in China. The findings encourage government to implement policies of innovation-driven transformation, energy conservation and emissions reduction.

Eco-consciousness to eco-consumption: unraveling the drivers of sustainable consumption behavior under the mediated-moderated Model

The impact of climate change has malformed the world's ecosystem, thus making humans call for environmental protection. Climate change, the biggest trauma of the twenty-first century, has made humans switch towards natural consumption. In this regard, the growing phenomenon of industrialization has spurred consumers to invest more in ecological products. Consuming eco-friendly products has several benefits; however, countries are still unable to satisfy the consumer's concern for the environment. The current study presents literature on environmental concerns, psychological well-being, willingness to pay for pro-environmental products, pro-environmental self-identity, and pro-environmental consumer behavior, which are required to ensure the consumer's organic behavior. The research used a questionnaire-driven methodology to gather data from 379 participants. Data analysis was conducted using statistical software packages, specifically SPSS (Version: 4.1.0.0). The suitability of the measurement model was evaluated through structural equation modeling (SEM), which was performed utilizing the SmartPLS. According to the research findings, there is a positive relationship between variables in the study, and individuals with greater levels of psychological well-being are more likely to engage in behaviors that promote sustainable consumption. In order to foster more sustainable consumption patterns in society, policymakers, marketers, and educators may find these findings to be valuable insights. As a result of its empirical exploration of these relationships, the study contributes to the growing body of literature on environmental psychology and sustainable marketing, emphasizing the important role psychological factors play in promoting a greener environment.

Energy markets restructure beyond 2022 and its implications on Qatar LNG sales strategy: Business forecasting and trend analysis

The emergence of new suppliers and energy resources has reshaped the energy market in terms of contractual structures and pricing systems. The market shifts were accelerated in response to the latest Russian-Ukraine crisis, impacting natural gas supply chains from financing projects to contracting volumes. The increased demand for liquified natural gas volumes intensified the need to switch from long-term oil-indexed contracts to short-term gas-indexed contracts. Those shifts were anticipated to influence the selling strategies for the expected added 49 MTPA of Qatari LNG, wherein increasing the share of spot selling would be reflected in higher economic performance. This study used forecasted prices to investigate potential Qatari LNG selling strategies. Initially, projections of the most dominant pricing systems used for pricing Qatari LNG (i.e., brent, Henry Hub, Title Transfer Facility, and Japan Korea Marker) were estimated between 2023 and 2040. While Qatar has been relying on long-term oil-indexed contracts, the second step estimated annual LNG revenues under different combinations of selling strategies (i.e., long-term and spot sales). Finally, the influence of varying brent slopes on the estimated revenues was measured. Due to data limitations and non-stationarity, the double exponential smoothing model was selected among the different tested models. Considering current market dynamics, forecasts of the double exponential smoothing model showed an upward price trend until 2040. An annual average increase of 1.24% for the studied pricing systems was reported. Reducing the share of long-term brent-indexed contracts to 70% and dedicating the remaining 30% of volumes to spot sales yielded the highest premiums for revenue estimates. An average annual revenue of $62 bn was reported for the 70/30 strategy, around 6% higher than the 100% brent-indexed contracts strategy. The findings revealed that diversifying the selling approach and introducing spot sales can enhance revenues. From the buyers' perspective, the outcomes support policymakers in understanding the implications of escalated prices driven by a lack of liquidity investments.

Less-advanced regions in EU innovation networks: Could nanotechnology represent a possible trigger for path upgrading?

This paper examines whether nanotechnology projects funded under the European Union (EU) Framework Programmes (FPs) are a possible trigger for path upgrading (i.e., infusion of new technologies in existing traditional sectors) in less-advanced regions. First, the adoption of cluster analysis and a set of key indicators (i.e., technological intensity, scientific excellence, human capital, and research and development expenditure) allowed us to distinguish between 79 more-advanced and 127 less-advanced EU regions. Subsequently, through social network analysis and nonparametric testing we were able to demonstrate how the less-advanced EU regions (average degree centrality: 40.5) play a marginal role compared with the more-advanced ones (average degree centrality: 98.5) in the nanotechnology network created within Horizon 2020-i.e., the EU programming cycle implemented in the 2014-2020 period. Despite this, we observed that a few less-advanced regions (33 out of 127) were able to score higher than the EU median in terms of participation in the targeted nanotechnology network, thus benefiting from relevant knowledge flows potentially leading to re-industrialization processes. The adoption of qualitative comparative analysis allowed us to determine which combinations of key innovation, scientific and socioeconomic factors could facilitate such beneficial interregional interactions and related knowledge exchange in these types of regions (i.e., primarily what we defined as "relative innovativeness," excellence in nanotechnology research and a comparatively high level of gross domestic product per capita). Our empirical results provided some clear policy implications. For instance, the necessity to I) remove the barriers impeding a more balanced participation to promote a widespread renewal of traditional industries in less-advanced regions and II) implement coordinated EU and domestic actions designed to encourage the involvement of the great majority of the less-advanced regions, which remain marginal in the periodically launched FPs.

Influence of environmental awareness on the willingness to pay for green products: an analysis under the application of the theory of planned behavior in the Peruvian market

Introduction

This paper aimed to build a predictive model through an empirical study to examine the influence of environmental awareness (EA) on attitude (ATT) and perceived behavioral control (PBC), as well as to determine the influence of the three variables of the theory of planned behavior (TPB) on willingness to pay (WP) for green products in the Peruvian market.

Methods

A total of 405 Peruvian consumers were surveyed. Most of them were between the ages of 18 and 30 and single. To test the hypotheses, partial least squares (PLS-SEM) were used using the SamrtPls4 software. The results show the significant positive effect of EA on ATT and PBC. The positive and significant effect of ATT, SN, and PBC on WP was also tested A total of 405 Peruvian consumers were surveyed. Most of them were between 18 and 30 years old and single. To test the hypotheses, partial least squares (PLS-SEM) was used using SamrtPls4 software.

Results

The results show the positive and significant effect of AD on ATT and PBC. The positive and significant effect of ATT, SN and PBC on WP was also tested.

Discussion

The research provides antecedents that allow evaluation of the possibility that companies and governments adjust the dissemination strategies and related public policies regarding the impact of environmentally responsible behavior in order to contribute to the development of environmental awareness as a variable that promotes the disposition of consumers to pay for environmentally friendly products.

Impact of green factors on undergraduate students' green behavioral intentions: A hybrid two-stage modeling approach

Consumers' unsustainable behavior contributes to environmental degradation and impedes sustainability. Using green products is one way to reduce this effect and promote environmental growth. Therefore, this study aims to investigate the green factors that impact young customers' behavioral intentions regarding green products. For this purpose, the researcher designed a research model based on the expanded theory of planned behavior (TPB). The study adopted a two-stage, hybrid model using partial least square-structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) to evaluate and validate the results. A sample of 382 undergraduate students was gathered using a convenience sampling approach. The results reveal that green TPB perception (GTP), green price sensitivity (GPS), green product trust (GPT), and green product value (GPV) are significantly and positively correlated with green behavioral intention (GBI). This study's main contribution is adding a brand-new higher-order construct, GTP, in the environmental and marketing literature and validating its effect on GBI. Again, environmental awareness moderates the association between GPS and GBI. Furthermore, the NCA's findings indicated that these variables are necessary to various degrees for students' GBI. Decision-makers may use the study's insights to create successful regulations to better understand young customers and develop appropriate green initiatives for sustainable development.

Smart city pilots, marketization processes, and substantive green innovation: A quasi-natural experiment from China

The world's major economies are striving to control carbon emissions and avoid irreversible impacts on the natural environment. Therefore, innovative green technologies are crucial for both government departments and the private sector as an important way to address carbon emissions. This study aims to investigate the link between the government's smart city construction and corporate green innovation and optimize the policy guidelines that drive green innovation in enterprises. This study analyzes 6,104 panels of Chinese listed companies from 2007-2019. An approach called the Differences-in-Differences model was applied to evaluate hypotheses. The empirical results suggest that smart city pilots drove substantial green innovation in businesses. The marketization process has a moderating effect on the impact of smart city pilots on substantive green innovation in enterprises. Moreover, marketization process has a threshold effect in smart city pilots influencing the substantive green innovation of enterprises, and the effect of smart city drivers influencing the substantive green innovation of enterprises increases significantly when regional marketization process reaches a certain level. The findings of this study provide valuable guidance for policy designers to promote corporate green innovation at both the hardware facility level and the market system level of cities when developing policies related to green innovation.

Towards facing uncertainties in biofuel supply chain networks: a systematic literature review

Biofuel supply chains (BSCs) face diverse uncertainties that pose serious challenges. This has led to an expanding body of research focused on studying these challenges. Hence, there is a growing need for a comprehensive review that summarizes the current studies, identifies their limitations, and provides essential advancements to support scholars in the field. To overcome these limitations, this research aims to provide insights into managing uncertainties in BSCs. The review utilizes the Systematic Reviews and Meta-Analyses (PRISMA) method, identifying 205 papers for analysis. This study encompasses three key tasks: first, it analyses the general information of the shortlisted papers. Second, it discusses existing methodologies and their limitations in addressing uncertainties. Lastly, it identifies critical research gaps and potential future directions. One notable gap involves the underutilization of machine learning techniques, which show potential for risk identification, resilient planning, demand prediction, and parameter estimations in BSCs but have received limited attention. Another area for investigation is the potential of agent-based simulation, which can contribute to analysing resilient policies, evaluating resilience, predicting parameters, and assessing the impact of emerging technologies on BSC resilience in the twenty-first century. Additionally, the study identifies the omission of various realistic assumptions, such as backward flow, lateral transshipments, and ripple effects in BSC. This study highlights the complexity of managing uncertainties in BSCs and emphasizes the need for further research and attention. It contributes to policymakers' understanding of uncertain sources and suitable approaches while inspiring researchers to address limitations and generate breakthrough ideas in managing BSC uncertainties.

Adopting e-government to monitor public infrastructure projects execution in Nigeria: The public perspective

Public infrastructure projects (PIPs) are critical to the socioeconomic development of any country and similar to most public activities, their governance requires effective public participation to be successful. Information and communication technology adoption in government-public engagements (i.e., e-government) has improved public participation in governance in developed countries. This study utilizes the unified theory of acceptance and use of technology to investigate determining factors for the Nigerian public to adopt e-government tools to promote public participation in monitoring PIPs execution. It adopts questionnaire survey and structural equation modelling techniques to show that performance expectancy, facilitating conditions, social influence, and effort expectancy significantly and positively affect behavioral intention to adopt e-government tools to monitor PIPs execution in Nigeria. This study provides scholars with an exploratory baseline for extension of e-government adoption to public infrastructure project management. This study also provides recommendations to policy makers, government technocrats, and project engineers on the need for policy changes, creation of interactive and up-to-date project websites for PIPs in Nigeria.

Modelling the mass adoption potential of food waste composting among rural Chinese farmers

As a safe alternative to hazardous agrochemicals, food waste compost could prevent human health hazards and environmental degradation. Food waste composting has not garnered much popularity among farmers given their sole dependence on synthetic fertilizers for high yields and commercial returns. Hence, this study aimed to identify the factors influencing farmers' adoption of food waste composting for regular use. Empirical data were collected from 399 farmers residing in different second-tier cities in China through face-to-face interviews using a structured questionnaire. The partial least squares-structural equation modelling was used to statistically examine the models and construct correlations. Based on the study outcomes, the perceived usefulness of food waste compost, awareness of the consequences, social influence, anticipated guilt, and attitude towards food waste composting substantially impacted food waste composting intention. Intriguingly, the perceived value of sustainability and ascription of responsibility did not have a significant impact on food waste composting intention, whereas food waste composting intention substantially influenced food waste composting behavior. The results of the multi-group analysis revealed differences in the relationship between awareness of consequences and food waste composting intention across genders and educational levels. This intriguing finding provides new avenues for future research and offers novel insights into the practical applications and promotion of food waste composting. These results will improve the relevant aspects among farmers for eco-friendly farming practices, innovate food waste management strategies, and mitigate environmental deterioration resulting from hazardous agrochemicals. This study expands the current body of literature by providing government regulators and other social enterprises with effective laws, policies, and strategy development guidelines for adopting natural composting on a large scale and enhancing the nutritional value of food to prevent unforeseen health risks caused by toxic chemicals.

Identifying the electricity-saving driving behaviors of electric bus based on trip-level electricity consumption: a machine learning approach

Electric buses (EBs) are gaining popularity worldwide as a more sustainable and eco-friendly alternative to diesel buses (DBs). Electricity-saving driving plays a crucial role in minimizing an EB's energy consumption, subsequently leading to an extended driving range. This study proposes a machine learning-based framework for identifying electricity-saving EB driving behaviors during various driving stages, including running on road segments, entering bus stops/intersections, and exiting bus stops/intersections. The proposed random forest (RF) model effectively evaluates the energy consumption level using EB drivers' historical driving data under different scenarios. Specifically, the electricity consumption factor (ECF), as the evaluation index, is divided into three categories to determine the implicit relationship between driving behavior and energy consumption. The results indicate that the classification accuracy of RF models surpasses 90%, which highlights the effectiveness in accurately identifying energy-efficient EB driving behaviors. In addition, the Shapley additive explanations (SHAP) and partial dependency plots (PDPs) are utilized to visualize and interpret the results of RF models. A speed interval of 30-40 km/h is identified as the most energy-efficient range for EB running on a road segment. Findings from this study can be applied to targeted optimization of electricity-saving driving strategies in different driving scenarios to improve the overall efficiency and sustainability of the transportation system.

Are economic growth and environmental pollution a dilemma?

For the first time, this study introduces-proposes using the Armey curve hypothesis (ACH) for testing the environmental Kuznets curve hypothesis (EKCH) in the relevant literature. The rationale for this new proposed methodology is that both hypotheses are expected to have similar inverted U-shaped curves. Hence, we combine the aforementioned hypotheses to obtain a single composite model. This single model may allow us to calculate a maximum (optimum) level of government expenditures that will increase or decrease CO₂ emissions for USMCA (the USA-Mexico-Canada Agreement) countries. To this end, our study employs an augmented mean group (AMG) estimator. The results demonstrate that the EKCH is verified by way of the AC model only for Mexico. Additionally, with the advantage of this approach, we calculated the optimal government spending level, which will increase both per capita real GDP (RGDPPC) and CO₂ emissions in this country by around 26.4% of RGDPPC. This level of spending will be a kind of threshold point for the Mexican government's policymakers. Hence, they will know that if they continue to spend more than this level, both the RGDPPC and CO₂ emissions will decrease, implying either a lower RGDPPC or a cleaner environment. The primary purpose of the proposed methodology in this study is to reveal the possible effects of the government's economic growth-oriented increased public expenditures on the environment in a single composite model. In other words, the relationship between economic growth and the environment is approached from the perspective of public spending, and it is reminded that governments should have harmonious and sustainable public spending policies for both economic growth and a cleaner environment.

Determining the influencing factors of consumers' attitude toward renewable energy adoption in developing countries: a roadmap toward environmental sustainability and green energy technologies

The energy sector is a crucial pillar of the economic development of every nation. In developing countries, renewable energy deployment is scarce; consequently, the government and private sectors are exploring efficient energy resources. This research aims to scrutinize the linkages among value orientation, utilitarian benefits, collectivism, the reason for adoption, attitude toward renewable energy (RE), and adoption intention in the renewable energy context. The study analyzes survey data from 359 Pakistani consumers using solar panels for households. An approach called structural equation modeling is applied to evaluate hypotheses. Empirical findings suggest that value orientation positively and significantly influences the reason for the adoption of RE and attitude toward RE. Similarly, the utilitarian benefit positively and substantially affects attitude toward RE. Moreover, collectivism and reason for adoption are substantially and favorably related to attitude toward RE. The study's findings also show that customer intentions to use renewable energy are favorably and substantially influenced by RE attitudes. The research has contributed to the enhancement of future avenues for scholars and professionals are provided by the literature on renewable practice.