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Organic food consumption has received great attention due to the increase in consumer environmental and health concerns. This study intends to analyse how customers' green purchasing intentions for organic food are affected by internal factors of attitude and health consciousness and external factors of social norms and environmental concern, as well as how green trust operates as a moderator between green purchase intention and actual purchase.

A quantitative research methodology was employed in this study. The data (n = 323) were gathered via a self-administered questionnaire. The respondents, who were current purchasers of organic food, were chosen through a purposive sampling technique. Data were analysed using exploratory factor analysis and structural equation modelling with the aid of IBM SPSS 25.0 and AMOS 25.

The results reveal that customers' green purchase intention for organic products is positively influenced by internal factors (attitude and health consciousness) and external factors (social norms and environmental concern). This study also shows the moderating effect of green trust on intention and action, demonstrating the necessity of building green trust among customers to diminish green purchasing inconsistency.

The study's results have ramifications for producers of organic goods, merchants and market oversight organizations. Establishing a viable strategy while considering customers' concerns about health and the environment is necessary. The formulated strategy must target specific customer niches, therefore strengthening customers' trust in and understanding of organic food items, which will in turn diminish green purchasing inconsistency in the organic industry.

This study contributes to the existing literature by extending the Theory of Planned Behaviour model to organic food consumption and by visualizing how various factors (internal, external and green trust) affect a consumer's inclination to make organic food purchases. The authors added to the empirical evidence that green trust plays a crucial role in stimulating green buying intentions into behaviour and ultimately diminishing green purchasing inconsistency.

With corporate social responsibility (CSR) becoming mandatory, several firms in India have been compelled into spending resources on CSR while their business strategy and processes were unprepared to take up CSR activities, effectively. In this light, the CSR relationship with other business functions would be altered. Using Thomson Reuters data from 2010 to 2018 (pre-mandate to post-mandate) this study aims to re-examine the relationship between CSR and financial performance.

The current study is rooted in the bandwagon-bias effect theory and uses a long-term data (2010–2018) of Indian firms. It uses Refinitiv Thomson Reuters ESG rating to measure CSR and accounting measures for financial performance (FP) to make a pre-post analysis of the impact that mandatory CSR regime has had on firms performance. The study uses the weighted panel regression method.

The relationship between CSR and FP is different when CSR was voluntary than when it has been mandated by Law. CSR has a positive effect over the FP during the voluntary phase but this positive relationship weakens during the mandatory phase. The waning effect of CSR over FP substantiates the presence of bandwagon bias effect which can be explained by the crowding-in of several companies engaged in CSR activities because of the mandatory CSR law.

Few countries have made CSR mandatory therefore CSR literature is limited. But mandating CSR is a growing phenomenon so this study augments to the body of knowledge. Until now literature generally converged on a positive relationship between CSR performance and FP but the current study shows altering directions to this relationship in a changing CSR environment. The use of the bandwagon-bias theory contributes to the theoretical approaches. Theoretically, the findings add to the body CSR literature and offer impetus to the evolving domain of impact measurement and reporting.

Results of the study offer a clear indication to managers that they need to re-strategise their CSR activities during the mandatory CSR environment if they wish to draw instrumental benefits of a positive impact on the FP of their firms. CSR expenditure is now a leveller so managers may either exceed the mandatory 2% expenditure as some firms did during the voluntary CSR phase or else design their CSR implementation plans to bring about a more impactful positive change. Communicating the impact of CSR to influential and powerful stakeholders beyond the mandatory reporting to the government is yet another way through which managers can draw benefits of CSR activities. Additionally to draw positive results from CSR activities firms may consider adopting international reporting and benchmarking standards such as the GRI and ISO 26000. Finally, the results of the study can be used by policymakers to make a note that the CSR law is causing a weakening of the financial benefits and therefore.

The results of the study can be used by policymakers also need to make a note that the CSR law is causing a weakening of the financial benefits and therefore firms are adopting shortcuts, by donating the required amount of funds. But donation of funds defeats the real purpose of mandatory CSR which is social impact, therefore the regulators may want to make the necessary changes unplug the gaps in the CSR law to ensure better adherence to the law in spirit and a real impact on the ground activities.

While CSR–FP relationship has been extensively explored but limited studies have explored this relationship in a mandatory CSR environment and no other work presents a comparative view of the CSR–FP relationship, namely, before and after the mandatory CSR policy. The current study is one of the limited few studying the impact of mandatory CSR policy on FP, and the only one that uses the bandwagon-bias effect to explain the phenomenon of weakening impact of CSR on FP of firms. Bandwagon-bias effect has been used in studying consumer behaviour, where group effect impacts behaviour of individuals and with mandatory CSR policy, firms following the other firms leading to crowding in. Using the bandwagon-bias effect has found limited attention from the CSR scholars, the current study uses this theoretical basis and therefore augments the CSR literature.

Nanosized honeycomb-configured materials are used in modern technology, thermal science and chemical engineering due to their high ultra thermic relevance. This study aims to scrutinize the heat transmission features of magnetohydrodynamic (MHD) honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts.

Mass, energy and momentum preservation laws are assumed to find the mathematical model. A set of unified ordinary differential equations with nonlinear behavior is used to express the correlated partial differential equations of the established models, adopting a reasonable similarity adjustment. An approximate convergent numerical solution to these equations is evaluated by the shooting scheme with the Runge–Kutta–Fehlberg (RKF45) technique.

The impression of pertinent evolving parameters on the temperature, fluid velocity, entropy generation, skin friction coefficients and the heat transference rate is explored. Further, the significance of the irreversibility nature of heat transfer due to evolving flow parameters are evaluated. It is noted that the heat transference rate performance is improved due to the imposition of the allied magnetic field, Joule dissipation, heat absorption, squeezing and thermal buoyancy parameters. The entropy generation upsurges due to rising magnetic field strength while its intensification is declined by enhancing the porosity parameter.

The uniqueness of this research work is the numerical evaluation of MHD honeycomb-structured graphene nanofluid flow within two squeezed parallel plates under Joule dissipation and solar thermal radiation impacts. Furthermore, regression models are devised to forecast the correlation between the rate of thermal heat transmission and persistent flow parameters.

To develop and examine an efficient and reliable jujube grading model with reduced computational time, which could be utilized in the food processing and packaging industries to perform quick grading and pricing of jujube as well as for the other similar types of fruits.

The whole process begins with manual analysis and collection of four jujube grades from the jujube tree, in addition to this jujube image acquisition was performed utilizing MVS which is further followed by image pre-processing and augmentation tasks. Eventually, classification models (i.e. proposed model, from scratch and pre-trained VGG16 and AlexNet) were trained and validated over the original and augmented datasets to discriminate the jujube into maturity grades.

The highest success rates reported over the original and augmented datasets were 97.53% (i.e. error of 2.47%) and 99.44% (i.e. error of 0.56%) respectively using Adam optimizer and a learning rate of 0.003.

The investigation relies upon a single view of the jujube image and the outer appearance of the jujube. In the future, multi-view image capturing system could be employed for the model training/validation.

Due to the vast functional derivatives of jujube, the identification of maturity grades of jujube is paramount in the fruit industry, functional food production industries and pharmaceutical industry. Therefore, the proposed model which is practically feasible and easy to implement could be utilized in such industries.

This research examines the performance of proposed CNN models for selected optimizer and learning rates for the grading of jujube maturity into four classes and compares them with the classical models to depict the sublime model in terms of accuracy, the number of parameters, epochs and computational time. After a thorough investigation of the models, it was discovered that the proposed model transcends both classical models in all aspects for both the original and augmented datasets utilizing Adam optimizer with learning rate of 0.003.

The catastrophic effects of the COVID-19 pandemic have considerably impacted the labour market and increased job insecurity among workers. This study systematically reviews the literature on job insecurity conducted in the context of the COVID-19 pandemic with three key objectives. First, to identify the key antecedents of job insecurity during the pandemic. Second, to identify the outcomes associated with job insecurity during the pandemic. Third, to identify the underlying boundary conditions that strengthened or alleviated the association between the antecedents of job insecurity and its associated outcomes.

The study followed PRISMA 2020 guidelines for the selection and inclusion of scientific literature by systematically searching five electronic databases, namely, Scopus, ScienceDirect, PubMed, Web of Science and Psych Info.

A perception of health-related risks, negative economic consequences and organizational restructuring during the pandemic were the primary factors contributing to job insecurity among workers. The consequences encompassed detrimental impacts on health and well-being, proactive measures undertaken by employees to alleviate the threat of job loss, and a variety of tactics employed to cope with stress arising from job insecurity. The boundary conditions elucidate the factors that alleviated job insecurity among workers and influenced both their work and non-work outcomes.

This is the first systematic review summarizing the literature on employees' experiences with job insecurity amid the COVID-19 pandemic. Based on a systematic review, this study provides doable steps that HR managers can take to effectively manage job insecurity among workers, particularly during a crisis.

The purpose of this study is to identify and analyze the barriers associated with the adoption of Industry 4.0 technologies in agricultural supply chains.

The study initially identified thirteen barriers by conducting a literature review and semi-structured interviews with key stakeholders. Subsequently, these barriers were validated and modeled using an integrated Fuzzy Delphi-ISM approach. Finally, MICMAC analysis was employed to categorize the barriers into distinct clusters.

The results provide considerable insights into the hierarchical structure and complex interrelationships between the barriers as well the driving and dependence power of barriers. Lack of information about technologies and lack of compatibility with traditional methods emerged as the two main barriers which directly and indirectly influence the other ones.

The robust hybrid Fuzzy Delphi and ISM techniques used in this study can serve as a useful model and benchmark for similar studies probing the barriers to Industry 4.0 adoption. From a theoretical standpoint, this study expands the scope of institutional theory in explaining Industry 4.0 adoption barriers.

The study is timely for the post-COVID-19 recovery and growth of the agricultural sector. The findings are helpful for policymakers and agriculture supply chain stakeholders in devising new strategies and policy interventions to prioritize and address Industry 4.0 adoption barriers.

It is the first comprehensive, multi-country and multi-method empirical study to comprehensively identify and model barriers to Industry 4.0 adoption in agricultural supply chains in emerging economies.