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Green consumption is fundamental to sustainable development, as it involves adopting practices and technologies that reduce the environmental impact of human activities. This study aims to analyze the influence of consumers’ green orientation on their environmental concerns and green purchase decisions. Furthermore, the study investigates the mediating role of consumers’ environmental concerns in the relationship between pro-sustainable orientation and green purchase decisions.

This study uses a quantitative methodology, applying the partial least squares method to a sample of 927 Portuguese consumers of green products. The sample was collected through an online survey.

Perceived benefits and perceived quality of products play a positive and significant role in influencing green behavior, especially when consumers are endowed with greater environmental concerns. In addition, consumers’ awareness of the prices of green products and their expectations regarding the future benefits of sustainable consumption positively impact green consumption behavior, further intensifying their environmental concerns.

According to the present findings, companies should adopt a holistic and integrated approach to promote green consumption. This means creating premium eco-friendly products, communicating their benefits, addressing the cost factor, emphasizing the future impact of eco-friendly options and raising consumers’ environmental awareness.

It is critical that environmental education is a priority in schools and that there are political incentives for green behaviors. In addition, media campaigns can be an important tool to raise awareness in society.

The results of this study provide important insights for companies on consumer engagement in the circular economy. Deepening knowledge of the antecedents of consumers’ environmental concerns contributes to a deeper understanding of green purchasing decision behavior, allowing companies to support new business strategies.

The purpose of this paper is to reduce the post-harvest loss occurring through respiration and CO₂ emission produce by the selected produces, during logistics. This paper proposes a supply chain (SC) structure for the Indian traditional agriculture SC planning model to reduce post-harvest loss and mixed closed transportation to reduce CO₂ emission.

The Indian agriculture SC structure is modeled and solved by genetic algorithm using a MATLAB Optimization toolbox. The respiration rate is measured by a static method. These values are applied in an SC planning model and the post-harvest loss and its corresponding CO₂ emission are estimated.

This paper proposes a supply structure for the Indian traditional agriculture SC to reduce the post-harvest loss; the experiments measured the respiration rate to estimate the CO₂ emission. The mixed closed transportation method is found to be suitable for short-purpose domestic transportation.

The optimized supply structure leads to unemployment through eliminating the intermediaries. Therefore, further research encourages the conversion of intermediaries into hub instead of eliminating them.

This paper includes implications for the development of Indian traditional agriculture SC by an optimized supply structure and novel transportation method for the selected agriculture produces based on compatibility.

This paper identified that the agriculture produces respiration can also emit the CO₂. The closed transportation method can reduce the CO₂ emission of produces respiration than traditional open transportation.

Online shopping around the world is growing exponentially, especially during the COVID-19 pandemic. This study aims to examine how an online customer's purchasing experience influences his/her buying intention and willingness to believe in fraud news, as well as the ripple impact of satisfaction and trust, with gender as a moderator in an emerging economy during COVID-19.

Based on the underpinning of the stimulus-organism-behavior-consequence (SOBC) theory, the research model was developed, and collected data from 259 respondents using convenience samples technique. Next, the data were analyzed using partial least squares-based structural equation modeling (PLS-SEM), SPSS (Statistical Package for the Social Sciences) and Hayes Process Macro.

The study results confirmed that the online shopping experience (OSE) has positive impact on customers' satisfaction (CS), purchase intention (PI) and customer trust (CT); CS has positive effects on trust toward online shopping and their future product PI; future product PI significantly affects customers' propensity to believe and act on fraud news (PBAFN). The finding also states that gender moderates the relationships of CS to PI, OSE to PI and PI to PBAFN, but doesn't moderate the CT to PI relationship.

The study findings will assist policymakers and online vendors to win customers' hearts and minds' through confirming satisfaction, trust and a negative attitude toward fake news, which will lead to customer loyalty and the sustainable development of the industry. Finally, the limitations and future research directions are discussed.