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The purpose of this study is to empirically examine how the seven human resource management (HRM) practises, namely, leadership development, professional investment, egalitarian practises, developmental appraisals, family-friendly practises, engagement practises and generous benefits, are associated with perceived organisational support (POS) and destructive deviance in the context of Indian organisational culture.

In total, 265 middle-level IT personnel provided the study's data. To test the suggested study hypotheses, confirmatory factor analysis and PROCESS Macros were used.

Results show that putting in place leadership development, professional investment, egalitarian practises, developmental appraisal, family-friendly practises, engagement practises and generous benefits generates POS that, in turn, significantly contributes to reducing destructive deviance. Additionally, POS was found to partially mediate the relationship between perceived HRM practises and destructive deviance.

The results would help firms reduce detrimental employee deviation. To do this, managers must develop and put into effect the seven HRM practises, which demonstrate to workers that the organisation appreciates their contributions and cares about their well-being, thereby lowering disruptive deviance. In essence, IT businesses should carefully plan and implement the HRM practises they expressly want to use rather than mindlessly copying those of rival organisations. Furthermore, to adapt to the workforce's evolving needs, these HRM practises must be properly matched with both individual and organisational goals.

By including destructive deviance as a result of POS, this study adds to the body of research on organisational support theory. The literature on POS and negative behaviours will take a new turn with such a focus on destructive deviance. Additionally, this study encourages academics to investigate an underlying mechanism that accounts for how HRM practises affect employees' conduct. This study also adds to the sparse body of knowledge on POS for non-Western workers. The study's findings confirm that POS is a crucial concept for both Asian and Western workers.

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.