This study conceptualizes how artificial intelligence (AI)-based customer engagement strategies can shape consumers’ green purchasing intentions, focusing on the theorized roles of attitude and perceived risk toward green products as articulated in prior literature. Building on contemporary research in sustainable marketing and consumer psychology, the article proposes a conceptual framework in which AI-enabled engagement influences green purchase intention via attitudes, with perceived risk operating as a boundary condition that moderates these effects. To qualitatively substantiate the salience and practical relevance of these constructs, an exploratory sentiment analysis of Amazon reviews for green products was conducted to surface emotional responses, perceived value drivers, and behavioral cues. The review corpus predominantly reflects positive sentiment alongside mixed subjectivity and factual commentary, highlighting recurring decision factors such as product quality, packaging, sustainability claims, and price sensitivity. Consistent with literature, the evidence aligns with the view that personalization and transparency can bolster trust and more favorable attitudes, while perceived risks—spanning greenwashing concerns, cost, and performance doubts—remain obstacles to adoption. Crucially, the sentiment analysis is presented as illustrative and does not statistically test the proposed mediation or moderation pathways; rather, it offers qualitative support that complements the literature-based conceptual model. The study contributes by integrating insights from digital technologies, consumer psychology, and sustainable marketing to guide authentic, strategic engagement practices that can encourage eco-conscious behavior.

In the evolving digital marketplace, consumer behaviour is increasingly shaped by green marketing strategies, particularly in the context of sustainable consumption. This study aims to examine the mechanisms through which green content marketing and green affiliate marketing influence green variety-seeking shopping behaviours, with particular attention to the role of green shopping motives and the effectiveness of marketing strategies. As traditional retail methods face limitations, digital marketing channels provide new avenues to engage consumers through personalized and dynamic content. Using the Theory–Context–Characteristics–Methodology (TCCM) framework, this research systematically examines the existing literature to identify key theories, contexts, characteristics, and methodologies relevant to variety-seeking behaviours towards green products. The study explores the psychological and behavioural drivers behind shopping choices, offering insights into why consumers exhibit variety-seeking behaviour when purchasing green products. The results indicate that effective green content and affiliate marketing drive variety-seeking behaviour in green shopping, with consumer motives serving as a key mediating factor. The conceptual model developed in this study provides a structured understanding of how modern marketing strategies shape consumer preferences and engagement with green products. This study offers a future research agenda and practical implications for marketers and retailers. By understanding these influences, businesses can refine their marketing strategies to strengthen green shopping motives, encourage sustainable consumption over traditional consumption, and adapt to the dynamic retail landscape.

It is eminent to understand, be aware of and encourage domestic retail investors towards investment in the capital market in a developing economy such as India for tackling the situation of capital insufficiency and financial instability. Therefore, the study was purposed to find out the different dimensions of cognition that affect investment attitude and the different characteristics of risk absorption affecting the investment decision making. The study also intended to find the direct and the mediating impact of investors’ cognition directly and through risk-absorption scenarios on the level of interest on investment. The study used the causative research design and by using stratified random sampling, received 392 responses from investors with risk-absorption characteristics from four strata of Odisha (a state of India) through a self-constructed questionnaire. Factor analysis was used to find out the factor of cognition and risk absorption. Multiple linear regression was used to find out the effect of both factors of cognition and risk absorption on the intensity of purchase financial product or level of interest in investment. Mediation analysis was used to find the mediating impact showing the direct and indirect impact of cognition on interest in investment and through the factors risk absorption. The study found that the dimensions of cognition (hot, cold, social and meta) have a significant impact on the level of interest towards investment, so financial product sellers must use these dimensions and sources of cognition to bring up interest from the domestic investor to invest in the domestic capital market. It has also been found that the risk-absorption characteristics play a mediating and vital role in the relation between investors’ cognition and level of interest in investment. Therefore, it is imperative to uplift the risk-absorption capacity through different dimensions of cognition and sources of information, which can reflect in a better understanding of the market and investment scenarios.

The present study aimed at the detection of suitable Lactobacillus species from dogs for usage as probiotic. A total of 67 rectal swabs from healthy pups were analyzed and 49 (73.1%) Lactobacillus isolates were identified based on morphological, biochemical characteristics and confirmed by genus specific PCR targeting 16S rRNA gene. A total of 20 isolates that showed strong aggregation, high cell surface hydrophobicity, acid and bile tolerance were screened for in-vitro antibacterial activity by agar well diffusion assay, where prominent inhibitory zones were observed against majority of the test pathogens. Reduction in antibacterial activity was noticed after neutralization, proteinase K and heat treatment of supernatants. Partial 16S rRNA nucleotide sequence analysis of seven Lactobacillus isolates that showed prominent in-vitro antibacterial activity revealed maximum sequence homology with Lactobacillus fermentum (for six isolates) and Lactobacillus agilis (for one isolate). The in-vitro antibacterial activity results highlighted the need for in-vivo studies in India to establish probiotic potential of canine faecal Lactobacillus species in the near future.