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Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

Goat milk yoghurt differs from cow milk yoghurt in that it has a different casein composition and content, which presents several technical challenges, including consistency with an appropriate flavor.

In this study, the antioxidant potential and phytochemical profiling of the fruits (pineapple and papaya) and vegetable (carrot) extracts was evaluated and the effect of their purees on the quality and stability of stirred goat milk yoghurt (GMY) were investigated. The qualities of stirred GMY with carrot (CrY), pineapple (PaY) and papaya (PpY) purees were assessed against the product without puree (CY).

The carrot puree had the highest moisture, ash contents and pH value. The carrot extract had the highest DPPH radical scavenging activity, while the pineapple extract had the highest total phenolic value (1.59 µg GAE/g) and flavonoids content (0.203 µg CE/g). The scanning of all the puree extracts in GC-MS indicated that 5-hydroxymethylfurfural was a major component. The phytochemical quantification of the extracts through multiple reaction monitoring (MRM) against 16 compounds showed the presence of sinapic acid, cinnamic acid, pthalic acid, ferulic acid, 4-OH-benzoic acid, 3-OH-benzoic acid, p-coumaric acid, caffeic acid and vanillic acid in different quantities. The addition of purees and storage period had a significant (p < 0.05) effect on the moisture, pH, titratable acidity, syneresis, viscosity, color values and sensory properties of the products. In all the samples after 15 days of storage, Streptococcus thermophilus and Lactobacillus bulgaricus counts remained above the recommended level of 106CFU/g. Stirred GMY sample produced with pineapple puree showed a higher syneresis and viscosity, but the CrY sample demonstrated the highest antioxidant activity. The developed formulations remained stable with minimum changes in quality and sensory attribute during refrigerated storage for 10 days.

This study suggests that addition of fruit and vegetable improve the viscosity and sensory perception of the product with minimal use of synthetic flavor and preservatives.