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The purpose of this paper is to explore the relationship among risk aversion, brand trust, brand affect, attitudinal loyalty and behavioral loyalty for low involvement day-to-day use of personal care products.

To achieve the above-stated objective, a theoretical model was tested using structural equation modeling. Before undertaking the analysis, preliminary analysis techniques such as the common method bias social desirability bias reliability and validity analysis were also assessed.

The results indicate that, for low involvement products, risk adverse consumers do not purchase a brand based only on trust. Risk aversion is also positively associated with attitudinal loyalty. When it comes to the relationship between brand trust and brand affect, it has been concluded that brand trust has had an important impact on brand affect. In this study, it has been found that attitudinal loyalty has a positive and strong impact on behavioral loyalty. This paper explains that due to the lack of trust, certain risk adverse customers are sticking with a particular brand.

Most of the brand loyalty research has been performed on high involvement products, whereas very limited research is available on low involvement day-to-day use products (i.e. personal care products), in particular where the consumption period of the product is less than a month. This kind of research is very rare, and this study has been done to fill this gap using rigorous data analysis.

The purpose of this paper is to identify the challenges surrounding the implementation of digital technology (DT) agri-food supply chain (AFSC) and explore how these challenges relate to the various sustainability dimensions. Additionally, it aims to assess how these challenges are interconnected in relation to achieving sustainable development goals (SDGs).

The study employs a mixed-method approach utilizing the EFA-ISM-Fuzzy DEMATEL technique. To support and validate the findings, exploratory factor analysis (EFA) categorized 12 critical challenges in sustainable dimensions from 141 participants' responses. Furthermore, interpretive structural modeling (ISM) and decision-making trial and evaluation (DEMATEL) methods were used to obtain the interrelationship and hierarchical structure of the challenges.

The study identified 12 critical challenges while adopting DT in AFSC. These challenges were categorized into four sustainable dimensions: technological, economic, environmental and social. These challenges hinder the achievement of SDGs as well. Lack of regulatory and policy framework with security and privacy issues were the key challenges faced while adopting DT. These observations emphasize the necessity for government and policymakers to prioritize tackling the identified challenges to successfully endorse and execute DT initiatives in AFSC while also fulfilling the SDGs.

The implication underscores the need for collaboration among various stakeholders, such as governments, policymakers, businesses and researchers. By collectively addressing these challenges, DT can be leveraged optimally, fostering sustainable practices and making progress toward achieving the SDGs within the AFSC.

The study uses a combination technique of EFA and ISM-DEMATEL to identify the challenges faced in Indian AFSC while adopting DT and categorizes the interrelation between the challenges along with fulfilling the SDGs.

This study aims to empirically analyze the significance of various knowledge management (KM) elements to the environment in a military organization and establish the efficacy of performance indicators of civil organizations for a military organization.

The research methodology includes the development of a research model based on a comprehensive literature review. A sample of 454 Indian Air Force Veterans was obtained and structural equation modeling (SEM) analysis using statistical package for the social sciences (SPSS) analysis of moment structures (AMOS) was conducted to test the hypotheses. The study first employed exploratory factor analysis (EFA) for redefining the theoretical constructs and then confirmatory factor analysis (CFA) to test the hypotheses.

The study empirically establishes the significance of various KM elements on the knowledge environment that creates, stores, transfers and applies knowledge to achieve military objectives. Findings indicate the complexity of KM in a military setup while applying the performance measures used in the civil organization.

The study expects to expand the scope of the KM literature to the militaries of developing countries and provide a methodology to the leaders and practitioners in the military organizations, and to study the available KM practices, models and tools in the civil world.

To the best of the authors’ knowledge, the present research is one of the first to generate empirical insights into a knowledge environment in military organizations and test its relation with parameters used in civil organizations. The paper would significantly contribute to the underexplored area of KM in military organizations and infuse a theoretical rigor into the KM literature.

The circular economy (CE) represents an industry-wide transition from linear to circular processes. There has been a proliferation of literature on CE in the last decade. However, the existing studies on the adaption of CE in small and medium-sized enterprises (SMEs) are scarce. This study aims to develop a research agenda and the way forward for future researchers focusing on the adoption of CE.

This article analyses the CE concepts through a Systematic Literature Review (SLR). Coding and content analysis are performed to generate emergent themes with the help of “Atlas.ti” software.

The authors uncovered the contemporary significance of adopting CE and the state-of-the-art literature on CE. The study's findings fall into four broad themes: Technical know-how, resource and process optimization, reverse practices and technology and innovation. Ten thought-provoking questions were identified in the four themes that researchers can explore further in embracing CE to achieve sustainability in SMEs.

The study has highlighted the importance of CE adoption and CE's benefits to stakeholders across all three dimensions, i.e. social, economic and ecological. Practitioners can use the agenda in four themes to strengthen the practitioners' existing practices in SMEs to promote CE.

The study's uniqueness is the supply of current knowledge from diverse literature and practical consequences for SMEs. This study opens new lines of inquiry to adopt CE in SMEs, streamlining the existing literature into four themes to focus future research.

This paper aims to explore the underlying intention behind using blockchain technology (BLCT) in the agri-food supply chain (AFSC). This is achieved by using a conceptual framework based on technology acceptance models that considers various factors influencing user behavior toward implementing this technology in their practices.

The conceptual framework developed is empirically validated using structural equation modeling (SEM). A total of 258 respondents from agri-food domain in India were involved in this survey, and their responses were analyzed through SEM to validate our conceptual framework.

The findings state that food safety and security, traceability, transparency and cost highly influence the intention to use BLCT. Decision-makers of the AFSCs are more inclined to embrace BLCT if they perceive the usefulness of the technology as valuable and believe it will enhance their productivity.

This study contributes to the existing literature by providing thorough examination of the variables that influence the intention to adopt BLCT within the AFSC. The insights aim to benefit industry decision-makers, supply chain practitioners and policymakers in their decision-making processes regarding BLCT adoption in the AFSC.

This study investigates how decision-makers’ perceptions of BLCT influence their intention to use it in AFSCs, as well as the impact of the different underlying factors deemed valuable in the adoption process of this technology.

This paper aims to provide a detailed study on the influence of slip flow and thermal jump over mixed convection flow along an exponentially stretching surface. Also, impacts of suction/blowing, volumetric heat source/sink and velocity ratio parameter will be studied in this analysis.

The modeled governing equations for the assumed problem are dimensional nonlinear partial differential equations in nature. To reduce these equations, non-similar transformations are used to get the dimensionless nonlinear partial differential equations. Then, quasi-linearization technique is used to linearize these non-dimensional nonlinear partial differential equations. Finally, an implicit finite difference scheme is used to discretize the resulting equations.

The physical explanations are provided for the variations of various non-dimensional governing parameters over the velocity and temperature profiles. Also, the effects of these dimensionless parameters on skin friction coefficient and heat transfer rate are scrutinized in a manner which highlights their physical interpretation. The detailed discussion exhibits the fact that the streamwise co-ordinate velocity ratio parameter, partial slip parameter and the thermal jump parameter have significant influence over the flow and thermal fields.

This work has not been reported in the literature to the authors’ best of knowledge.

Improving work engagement can have significant implications for performance at individual, team and organisational level. The purpose of this paper is to investigate the effects of occupational self efficacy and human resource development (HRD) climate on work engagement among business executives of select business organisations in India. In addition, it aims to attempt to examine the mediating effect of HRD climate on self efficacy and work engagement relationship.

The sample consisted of 150 business executives from both public and private sector manufacturing and service organisations in India. Data were collected through both personal visits and online questionnaires. Correlation and regression analyses were used to test the research hypotheses. Specifically, Baron and Kenny's method was used for testing the hypotheses of mediation.

A significant relationship was found between all variables in the study. All the study hypotheses were supported. HRD climate was found to partially mediate the relationship between occupational self‐efficacy and work engagement. Interestingly, both HRD climate and self‐efficacy affect work engagement both directly and indirectly through influencing the other.

Work engagement requires the workforce that is endorsed with self‐efficacy as dispositional trait. In addition, improving the HRD climate can have significant implications for enhancing the work engagement among Indian business executives.

By investigating the relationship between self‐efficacy, HRD climate and work engagement the present study made an effort to fulfil the gap in academic literature where there is a significant dearth of academic literature on work engagement from developing economies.

The study explores the perspectives of college students on the pedagogical shift as well as frequent transitions between online and offline learning modes during the COVID-19 pandemic in Kerala, the most literate state in India.

A descriptive cross-sectional study was conducted among 1,366 college students in Kerala during December 2021. A pre-tested questionnaire was sent using Google Forms to students of arts and science colleges. The authors analyzed quantitative data using descriptive statistics and qualitative data using thematic content analysis.

The reported advantages of online learning were increased technical skill, flexibility in study time, effectiveness in bridging the gap of the missed academic period and provision of attending more educational webinars. Students expressed concerns of increased workload, difficulty in concentration due to family circumstances, academic incompetency, uncleared doubts and addiction to mobile phones and social media during the online classes. The main advantages reported for switching to an offline learning mode were enhanced social interaction, effective learning, better concentration and reduced stress. The reported challenges of offline classes were fear of getting the disease, concern of maintaining social distancing and difficulty in wearing masks during the classes. The shift in offline to online learning and vice versa was perceived as a difficult process for the students as it took a considerable time for them to adjust to the switching process of learning.

Students' concerns regarding transition between different learning modes provide important information to educators to better understand and support the needs of students during the pandemic situations.

Disruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable dimensions and disruptive technologies implementation in the supply chain of the petroleum industry. The authors used content analysis in the literature and experts input to explore the sustainable dimensions and disruptive technologies in the supply chain.

This study used a hybrid method of hesitant fuzzy set and regret theory to identify the prominent sustainability dimensions and prominent disruptive technologies. This method emphasizes the decision-makers psychological characteristics under uncertain environments.

The result indicates that social responsibility, labor practices, safety and technical standards hold the most prominent sustainable dimensions in the petroleum supply chain. Further, the result also depicts that when consider an equal degree of regret and rejoice, artificial intelligence and big data could significantly enhance operations sustainability in the petroleum industry.

This study considers only 11 sustainable dimensions and 43 sustainable factors, whereas other dimensions and factors could also be considered in future research. The research uses hesitant fussy set and regret set theory to identify the prominent sustainable dimensions and disruptive technologies, whereas other multiple-criteria decision-making (MCDM) techniques can also be used.

To the best of the authors’ knowledge, this is the first paper to explore the sustainable dimensions (environmental, social and economic) and disruptive technologies in the supply chain of the petroleum industry. This research intended to guide the practitioners, policymakers and academicians to emphasize their effort toward sustainable operations supply chain management.

The study aims to determine the the optimal value of output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The output parameters of a variable compression ratio (CR) diesel engine are investigated at different loads, CR and fuel modes of operation experimentally. The performance parameters like brake thermal efficiency (BTE) and brake specific energy consumption (BSEC), whereas CO emission, HC emission, CO₂ emission, NO_x emission, exhaust gas temperature (EGT) and opacity are the emission parameters measured during the test. Tests are conducted for 2, 6 and 10 kg of load, 16.5 and 17.5 of CR.

In this investigation, the first engine was fueled with 100% diesel and 100% Calophyllum inophyllum oil in single-fuel mode. Then Calophyllum inophyllum oil with producer gas was fed to the engine. Calophyllum inophyllum oil offers lower BTE, CO and HC emissions, opacity and higher EGT, BSEC, CO₂ emission and NO_x emissions compared to diesel fuel in both fuel modes of operation observed. The performance optimization using the Taguchi approach is carried out to determine the optimal input parameters for maximum performance and minimum emissions for the test engine. The optimized value of the input parameters is then fed into the prediction techniques, such as the artificial neural network (ANN).

From multiple response optimization, the minimum emissions of 0.58% of CO, 42% of HC, 191 ppm NO_x and maximum BTE of 21.56% for 16.5 CR, 10 kg load and dual fuel mode of operation are determined. Based on generated errors, the ANN is also ranked for precision. The proposed ANN model provides better prediction with minimum experimental data sets. The values of the R² correlation coefficient are 1, 0.95552, 0.94367 and 0.97789 for training, validation, testing and all, respectively. The said biodiesel may be used as a substitute for conventional diesel fuel.

The blend of Calophyllum inophyllum oil-producer gas is used to run the diesel engine. Performance and emission analysis has been carried out, compared, optimized and validated.