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This paper integrates research on quiet quitting (a mindset where employees restrict their efforts to their job description) and organizational learning (OL) to illustrate how quiet quitting challenges the sub-processes of OL.

By integrating the existing literature on quiet quitting and OL, this paper identifies and maps the challenges of quiet quitting to the sub-processes of OL, namely, intuiting, interpreting, integrating, and institutionalizing within the 4I framework of Crossan et al. (1999).

This paper conceptually establishes that quiet quitting undermines employees’ cognitive efforts and weakens employees’ contribution to team discussions. Further, quiet quitting undermines suggestion sharing and creates a reluctance to share knowledge, undermining OL.

The paper provides actionable strategies for managers to tackle the challenges of quiet quitting on OL.

To the best of the authors' knowledge, this study is amongst the first to illustrate the challenges of quiet quitting on OL.

Recent research highlights the growing use of anthropomorphizing voice commerce, attributing human-like traits to shopping assistants. However, scant research examines the influence of anthropomorphism on the behavioral intention of shoppers. Therefore, the study examines the mediating role of anthropomorphism and privacy concerns in the relationship between utilitarian and hedonic factors with the behavioral intention of voice-commerce shoppers.

The study employs structural equation modeling (SEM) to analyze responses from 279 voice-commerce shoppers.

Results indicate that anthropomorphizing voice commerce fosters adoption for hedonic factors but not for utilitarian factors. Paradoxically, anthropomorphism decreases shoppers’ behavioral intentions and heightens their privacy concerns.

The cross-sectional survey design serves as a notable limitation of the study. Future researchers can rely on longitudinal designs for additional insights.

Marketers should anthropomorphize voice commerce for hedonic shoppers, not for utilitarian shoppers, and consider implementing customized privacy settings tailored to individual preferences.

The study contributes to academia and management by emphasizing the need to customize anthropomorphic features according to utilitarian and hedonic factors. Furthermore, it highlights the adverse effects of anthropomorphizing voice commerce on shoppers’ behavior, offering policymakers guidance for appropriate regulations.

This study aims to develop a framework for evaluating environmental, social and governance (ESG) factors in the context of commercial banks, addressing the need for a more robust and transparent assessment of ESG subfactors.

Using an integrated multi-criteria decision-making approach, this study uses rough stepwise weight assessment ratio analysis (R-SWARA) to determine the weights of ESG factors, followed by the combined compromise solution (CoCoSo) method to assess the sustainability performance of five major commercial banks. This study involves insights from 15 experts in the banking sector, ensuring a comprehensive understanding of ESG integration.

The research reveals that governance is the most significant ESG factor in the banking sector, followed by social and environmental factors. The CoCoSo method’s results, aligning with the R-SWARA findings, identify the top-performing banks regarding ESG practices, highlighting the importance of robust governance structures for sustainable banking operations.

This study provides a strategic framework for banks to prioritize and implement ESG initiatives effectively. It provides insights into allocating resources toward areas with the most significant impact on ESG performance, thereby enhancing operational efficiency and stakeholder trust.

This study contributes to the existing literature by offering a unique, integrated approach to ESG evaluation in the banking sector, combining the qualitative and quantitative aspects of ESG factors. It addresses the subjectivity issue inherent in ESG evaluation and provides a comprehensive ranking system for ESG factors in commercial banks.

Historically, global events have always provided a setback to the existing mechanism of any business operation. The magnitude of such variation may be different from industry to industry but sustainable outlook afterwards any global crisis calls for a re-look into strategies. Similar experience persisted when sudden drop of brick-and-mortar stores during corona crisis came into picture. Post corona, the entire working style of supply chain companies revisited a virtual set-up. The delivery partners like Dunzo, Blinkit, Zypp, Delhivery, Ecomexpress have transformed the way logistics used to work before COVID-19. On the other hand, recent Russia–Ukraine war has posed further global challenges like that of food shortage, supply challenges, global inflation, recessionary trends worldwide. An investor earlier confident of exponential wealth creation in supply chain companies may have to rethink about resilient strategies while creating a portfolio with companies from supply chain industry. In the present study, a comparative analysis has been made by use of exponential Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) model to explore the impact of both these crisis on returns from supply chain companies. The output of this chapter shall be beneficial for investors, asset management companies, investment brokers and other portfolio managers.

This paper aims to focus on the selection of an appropriate nature-inspired texture pattern for cutting tool tribological surface. The selection process uses the recognized skin textures of different snakes scrolling on highly rough and projected surface conditions to analyze suitability of texture based on the texture geometry and machining conditions. The work also aims to propose a texture pattern selection process to incorporate on cutting tool tribological surface.

The selection of alternative nature-inspired texture patterns based on the texture pattern geometry and machining properties leads to a multi-criteria decision-making problem. Thirteen criteria are considered for selecting an appropriate texture pattern among 14 alternatives, i.e. nature-inspired texture patterns. In the present work, an integrated analytical hierarchy process (AHP)-TOPSIS, AHP-multi-objective optimization on the basis of ratio analysis (MOORA) and AHP-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approaches have been proposed for the selection of an appropriate nature-inspired texture pattern. AHP is used for the formulation of decision-making matrix and criteria weight calculations and ranking of alternatives is done by three methods. Spearman’s correlation compared and found positive relations between rank assigned by methods. Experimental validation is done in Lathe for selected texture effects.

The texture parameters C-1 (Width of texture) and C-2 (Depth of texture) are found significant, while T-2 (Blended Krait) and T-6 (Banded Racer-1) texture is found optimal to generate on cutting tool surface.

Only some nature-inspired texture patterns have been recognized before the selection; an infinite number of textures are available in nature. The size of the texture pattern is difficult to identify by the selection process because each texture pattern may have different effects on tribological surfaces.

The proposed selection methodology of nature-inspired texture patterns will help identify optimal texture geometry for specific tribological applications. The nature-inspired texture patterned tool has a significant impact on the cutting force and temperature due to its tribological effect on the cutting tool surface; it decreases the power required for machining. The machining characteristics like roughness are found to decrease by using nature-inspired texture patterned tools.

Various nature-inspire texture studies to generate specific effects on the tribological surfaces may be started study for the surface of aircraft, ships, bearings, etc. Small and big fabrication industries may benefit by decreasing the cost of machining using nature-inspired texture-patterned tools. Research society will pay attention to nature’s inspiration.

Novel snake-skin-inspired texture patterns are recognized and hybrid MCDM methods are proposed to select optimal texture pattern. Proposed method used single time normalization to effectively rank the alternatives. The insights gained from this research can be extrapolated to address similar challenges in selecting nature-inspired textures for various applications.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0163/

The purpose of this study is to systematically review the existing literature on the concept of consumer sovereignty.

By leveraging a systematic literature review using a data-driven approach and quantitative methodology, this study provides an overview of the intellectual structure of consumer sovereignty research.

We explored the main topics that researchers tackled in consumer sovereignty research. Furthermore, we identified the theoretical lenses used in these studies. Finally, we proposed a research agenda to advance the scholarly debate on consumer sovereignty.

Some limitations should be acknowledged. First, the study only studied and analyzed consumer sovereignty articles that were published in peer-reviewed academic journals. Second, our review comprised journals identified in Scopus. Third, in this study, we have taken into account only articles written in English.

The authors expect the current review to significantly impact the identification of theories for the main trends in the academic analysis of consumer sovereignty and consumer behavior.

This study is the first to provide an integrated view of the body of consumer sovereignty. This review provides a strong contribution to consumer sovereignty literature by recommending a new research agenda for the concept of consumer sovereignty.