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Positive experiences with working from home (WFH) during the Corona pandemic (COVID-19) have motivated many employees to continue WFH after the pandemic. However, factors influencing employees' WFH intentions against the backdrop of experiences during pandemic-induced enforced working from home (EWFH) are heterogeneous. This study investigates factors linked to information technology (IT) professionals' WFH intentions.

This mixed-methods study with 92 IT professionals examines the effects of seven predictors for IT professionals' WFH intentions. The predictors are categorized according to the trichotomy of (1) characteristics of the worker, (2) characteristics of the workspace and (3) the work context. Structural equation modeling is used to analyze the quantitative survey data. In addition, IT professionals' responses to six open questions in which they reflect on past experiences and envision future work are examined.

Quantitative results suggest that characteristics of the worker, such as segmentation preference, are influencing WFH intentions stronger than characteristics of the workspace or the work context. Furthermore, perceived productivity during EWFH and gender significantly predict WFH intentions. Contextualizing these quantitative insights, the qualitative data provides a rich yet heterogeneous list of factors why IT professionals prefer (not) to work from home.

Reasons influencing WFH intentions vary due to individual preferences and constraints. Therefore, a differentiated organizational approach is recommended for designing future work arrangements. In addition, the findings suggest that team contracts to formalize working patterns, e.g. to agree on the needed number of physical meetings, can be helpful levers to reduce the complexity of future work that is most likely a mix of WFH and office arrangements.

This study extends literature reflecting on COVID-19-induced changes, specifically the emerging debate about why employees want to continue WFH. It is crucial for researchers and practitioners to understand which factors influence IT professionals' WFH intentions and how they impact the design and implementation of future hybrid work arrangements.

This review paper seeks to enhance knowledge of how pre-loading affects reinforced concrete (RC) beams under fire. It investigates key factors like deflection and load capacity to understand pre-loading's role in replicating RC beams' actual responses to fire, aiming to improve fire testing protocols and structural fire engineering design.

This review systematically aggregates data from existing literature on the fire response of RC beams, comparing scenarios with (WP) and without pre-loading (WOP). Through statistical tools like the two-tailed t-test and Mann–Whitney U-test, it assesses deflection extremes. The study further examines structural responses, including flexural and shear behavior, ultimate load capacity, post-yield behavior, stiffness degradation and failure modes. The approach concludes with a statistical forecast of ideal pre-load levels to elevate experimental precision and enhance fire safety standards.

The review concludes that pre-loading profoundly affects the fire response of RC beams, suggesting a 35%–65% structural capacity range for realistic simulations. The review also recommended the initial crack load as an alternative metric for determining the pre-loading impact. Crucially, it highlights that pre-loading not only influences the fire response but also significantly alters the overall structural behavior of the RC beams.

The review advances structural fire engineering with an in-depth analysis of pre-loading's impact on RC beams during fire exposure, establishing a validated pre-load range through thorough statistical analysis and examination of previous research. It refines experimental methodologies and structural design accuracy, ultimately bolstering fire safety protocols.

The study aims to identify Green Lean Six Sigma (GLSS) barriers in the context of Higher Education Institutions (HEIs) and prioritize them for executing the GLSS approach.

A systematic literature review (SLR) was used to identify a total of 14 barriers, which were then verified for greater relevance by the professional judgments of industrial personnel. Moreover, many removal measures strategies are also recommended in this study. Furthermore, this work also utilizes Gray Relational Analysis (GRA) to prioritize the identified GLSS barriers.

The study reveals that training and education, continuous assessment of SDG, organizational culture, resources and skills to facilitate implementation, and assessment of satisfaction and welfare of the employee are the most significant barriers to implementing this approach.

The present study provides an impetus for practitioners and managers to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers. In this case, the outcomes of this research, and in particular the GRA technique presented by this work, can be used by managers and professionals to rank the GLSS barriers and take appropriate action to eliminate them.

The ranking of GLSS barriers gives top officials of HEIs a very clear view to effectively and efficiently implementing GLSS initiatives. The outcomes also show training and education, sustainable development goals and organizational culture as critical barriers. The findings of this study provide an impetus for managers, policymakers and consultants to embrace the GLSS strategy through a wide-ranging understanding and exploring these barriers.

The GLSS barriers in HEIs may significantly affect the society. HEIs can lessen their environmental effect by using GLSS practices, which can support sustainability initiatives and foster social responsibility. Taking steps to reduce environmental effect can benefit society as a whole. GLSS techniques in HEIs can also result in increased operational effectiveness and cost savings, which can free up resources to be employed in other areas, like boosting student services and improving educational programs. However, failing to implement GLSS procedures in HEIs could have societal repercussions as well. As a result, it is critical for HEIs to identify and remove GLSS barriers in order to advance sustainability, social responsibility and operational effectiveness.

GLSS is a comprehensive methodology that facilitates the optimum utilization of resources, reduces waste and provides the pathway for sustainable development so, the novelty of this study stands in the inclusion of its barriers and HEIs to prioritize them for effective implementation.

This study analyzes the impact of COVID-19 on agricultural production in South India by evaluating the influence of market channels and socioeconomic conditions on the production decisions of farmers during two key cropping seasons. We base our analysis on primary data from 200 marginal, small and medium farmers, primarily focusing on the key seasonal crops, namely paddy and black gram.

We studied the downstream supply chains of paddy and black gram crops in the district of Villupuram, situated in the South Indian state of Tamil Nadu. Using a Bi-Probit model, we analyzed the production decisions of marginal, small and medium farmers engaged in paddy and black gram cultivation. Various factors are considered, including farmers’ socioeconomic characteristics, gender, market channels accessed and the coping strategies employed.

After the easing of lockdown measures in June 2020, our research revealed substantial disruptions in agricultural production during the critical Kharif and Rabi seasons. Most farmers refrained from returning to their fields during the Kharif season; those who did produced millet as the main crop. Factors such as choice of market channels in previous seasons, economic status, access to all-weather roads, labor availability, gender and coping strategies played an important role in the return to production in the subsequent Kharif and Rabi seasons.

Our data revealed several interesting threads related to price volatility, irrigation and access to markets and their impact on food security. The role of intermediaries and market channels in providing liquidity emerges as an important aspect of farmers' choice of markets. The pandemic impacted all these factors, but a detailed analysis was beyond the scope of this study.

We also find that resilience to economic shocks varies not only by economic status but also by gender and social groups. Farmers with female members are more likely to be resilient, and marginal and small farmers primarily belong to social groups that are economically less developed.

This study contributes to the literature on factors influencing farmer choice and decision-making and provides nuances to discussions by analyzing crop-specific supply chains, highlighting the critical role of socioeconomic factors. It also highlights the role of demographics and infrastructural factors like access to all-weather roads and access to markets that influence farmers’ production decisions.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.

The purpose of this study is to investigate the effects of entropy generation of some embedded thermophysical properties on heat and mass transfer of pulsatile flow of non-Newtonian nanofluid flows between two porous parallel plates in the presence of Lorentz force are taken into account in this research.

The governing partial differential equations (PDEs) were nondimensionalized using suitable nondimensional quantities to transform the PDEs into a system of coupled nonlinear PDEs. The resulting equations are solved using the spectral relaxation method due to the effectiveness and accuracy of the method. The obtained velocity and temperature profiles are used to compute the entropy generation rate and Bejan number. The influence of various flow parameters on the velocity, temperature, entropy generation rate and Bejan number are discussed graphically.

The results indicate that the energy losses can be minimized in the system by choosing appropriate values for pertinent parameters; when thermal conductivity is increasing, this leads to the depreciation of entropy generation, and while this increment in thermal conductivity appreciates the Bejan number, the Eckert number on entropy generation and Bejan number, the graph shows that each time of increase in Eckert will lead to rising of entropy generation while this increase shows a reduction in Bejan number. To shed more light, these results were further demonstrated graphically. The current research was very well supported by prior literature works.

All results are presented graphically, and the results in this article are anticipated to be helpful in the area of engineering.

This study aims to determine experimentally factors affecting the satisfaction of retail stock investors with various investor protection regulatory measures implemented by the Government of India and Securities and Exchange Board of India (SEBI). Also, an effort has been made to gauge the level of satisfaction of retail equities investors with the laws and guidelines developed by the Indian Government and SEBI for their invested funds.

To accomplish the study’s goals, a well-structured questionnaire was created with the help of a literature review, and copies of it were filled by Punjabi retail equities investors with the aid of stockbrokers, i.e. intermediaries. Amritsar, Jalandhar, Ludhiana and Mohali-area intermediaries were chosen using a random selection procedure. Xerox copies of the questionnaire were given to the intermediaries, who were then asked to collect responses from their clients. Some intermediaries requested the researcher to sit in their offices to collect responses from their clients. Only 373 questionnaires out of 1,000 questionnaires that were provided had been received back. Only 328 copies were correctly filled by the equity investors. To conduct the analysis, 328 copies, which were fully completed, were used as data. The appropriate approaches, such as descriptives, factor analysis and ordinal regression analysis, were used to study the data.

With the aid of factor analysis, four factors have been identified that influence investors’ satisfaction with various investor protection regulatory measures implemented by government and SEBI regulations, including regulations addressing primary and secondary market dealings, rules for investor awareness and protection, rules to prevent company malpractices and laws for corporate governance and investor protection. The impact of these four components on investor satisfaction has been investigated using ordinal regression analysis. The pseudo-R-square statistics for the ordinal regression model demonstrated the model’s capacity for the explanation. The findings suggested that a significant amount of the overall satisfaction score about the various investor protection measures implemented by the government/SEBI has been explained by the regression model.

A study could be conducted to analyse the perspective of various stakeholders towards the disclosures made and norms followed by corporate houses. The current study may be expanded to cover the entire nation because it is only at the state level currently. It might be conceivable to examine how investments made in the retail capital market affect investors in rural areas. The influence of reforms on the functioning of stock markets could potentially be examined through another study. It could be possible to undertake a study on female investors’ knowledge about retail investment trends. The effect of digital stock trading could be examined in India. The effect of technological innovations on capital markets can be studied.

This research would be extremely useful to regulators in developing policies to protect retail equities investors. Investors are required to be safeguarded and protected to deal freely in the securities market, so they should be given more freedom in terms of investor protection measures. Stock exchanges should have the potential to bring about technological advancements in trading to protect investors from any kind of financial loss. Since the government has the power to create rules and regulations to strengthen investor protection. So, this research will be extremely useful to the government.

This work has societal ramifications. Because when adequate rules and regulations are in place to safeguard investors, they will be able to invest freely. Companies will use capital wisely and profitably. Companies should undertake tasks towards corporate social responsibility out of profits because corporate houses are part and parcel of society only.

Many investors may lack the necessary expertise to make sound financial judgments. They might not be aware of the entire risk-reward profile of various investment options. However, they must know various investor protection measures taken by the Government of India & Securities and Exchange Board of India (SEBI) to safeguard their interests. Investors must be well-informed on the precautions to take while dealing with market intermediaries, as well as in the stock market.

In the backdrop of an increase in market-based banking activities, this paper aims to study operational efficiency of Indian banking sector during 2009–2010 through 2017–2018 considering Capital Gain and Gain from Forex Market (as desirable outputs) and Slippage (as undesirable byproducts) simultaneously, along with Advances – a desirable output considered in the traditional banking performance assessment literature. This enables to have an assessment of performance (as captured by the measured efficiency scores) of Indian Banks following an alternative viewpoint about the banking activities. The authors also explain such efficiency scores in terms of bank-specific factors, banking industry competition scenario and interest rate channel.

Using data envelopment analysis (DEA) method, the authors estimate six alternatives but interlinked operational efficiency scores (TES) of the Indian domestic commercial banks. In the second stage, they explain such TES in terms of bank-specific factors, banking industry competition scenario and interest rate channel.

The authors observe that the private sector banks as a group outperform those under public ownership. Moreover, although the private sector banks could maintain somewhat consistency in their operational efficiency performance over the sample period, public sector banks clearly show a declining tendency. The second stage econometric estimation results show that the priority sector lending has a negative effect on efficiency. Interestingly, the authors get varying results for the relationship between maturity and efficiency score depending on banks’ strategies on stressed assets management. Furthermore, the analyses result that banks are not so efficient in managing relatively larger-volume loans. It is also observed that banks’ efficiency positively depends on the Credit-to-Deposit (CD) ratio. It is found that the overall operational efficiency of the banks to manage their credit risk portfolio improves with a reduction in the lending rate (LR). However, the interaction of lending activities and capital market shows that with the increase in LR, corporate borrowers may switch to capital market to explore for desired funds, which may induce the banking sector to investment in capital markets and create a positive market sentiment.

Literature, although scanty, is there dealing stressed assets of a bank as some undesirable byproducts of its operational and business activities. However, such literature mostly done within the traditional framework of banking business activities and modern market-based business activities are almost absent in the literature. The authors have done it in the present study.

There is a strong inducement to develop new inorganic materials to substitute the current industrial pigments, which are known for their poor ultraviolet absorbent and low photoluminescence (PL) properties. The purpose of this paper is to invent a better rare-earth-based pigment material as a spectral modifier with good luminescence properties to enhance the spectral response for photovoltaic panel application.

Different phosphor samples made of nano-calcium carbonate (CaCO₃) with varied wt.% of the dopant Dysprosium doped calcium borophosphate (CBP/Dy) as (W0 – 0%, W1 – 3,85%, W2 – 7.41%, W3 –10.71% and W4 –13.79%) were prepared via the solid-state diffusion method at 600 °C for 6 h using a muffle furnace. The structural, morphological and luminescence properties of the CaCO₃:CBP/Dy powder samples were examined using scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and PL test.

The XRD, SEM and FTIR results verified the crystalline formation, morphological behaviour and vibration bonds of synthesized CBP/Dy-doped CaCO₃ powder samples. XRD pattern revealed that the synthesized powder samples exhibit crystalline structured materials, and SEM results showed irregular shape and porous-like structured morphologies. FTIR spectrum shows prominent bands at 712, 874 and 1,404 cm⁻¹, corresponding to asymmetric stretching vibrations of CO3²⁻ groups and out-of-plane bending. PL characterization of CBP/Dy-doped CaCO₃ (sample W) shows emission at 427 nm (λmax) under the excitation of 358 nm. The intensity of PL emission spectra drops due to the concentration quenching effect, while the maximum PL intensity is observed in the W3 phosphor powder system.

This phosphor powder is expected to find out the potential application such as a spectral modifier which is applied to match the energy of photons with solar cell bandgap to improve spectral absorption and lead to better efficiency.

The introduction of a nano-CaCO₃:CBP/Dy hybrid powder system with good luminescence properties to be used as spectral modifiers for solar cell application has been synthesized in the lab, which is a novel attempt.

Competencies are significant predictors of employee outcome. Nowadays, new technologies are changing maintenance processes and workflow. The role of employees and their competencies will therefore undergo decisive changes in the future. Therefore, a well-designed competency model for maintenance departments is important. The purpose of this paper is to develop a maintenance 4.0 competency model applicable to all industrial sectors by adapting it to the specificities of each sector.

The research methods consist of a comprehensive literature review on the main characteristics of the competency model and the individual competencies needed for the maintenance 4.0 employees. Interviews were conducted in order to validate and prioritize the required competencies for maintenance 4.0 employees identified in the literature.

The maintenance 4.0 competency model combines the required competencies in maintenance 4.0 and crosses the three hierarchical levels: managers, engineers and technicians. These competencies are organized in terms of four categories: technical, personal, social and methodological. In addition, a degree of importance for each competency is assigned as very important, moderately important and slightly important. As a result, this study identified the essential competencies for maintenance 4.0 stakeholders, where 12 competencies are considered very important for maintenance 4.0 technicians, 19 for engineers and 18 for managers.

This work has some limitations. First, although the articles related to competencies and their classification were selected very carefully, it is difficult to eliminate the probability of overlooking publications. Second, the limitation of the study is based on the difficulty of implementing the model in a case study, given that a minority of industrial companies have implemented maintenance 4.0 technologies in Morocco.

This work has practical implications for both individuals and institutions (companies and academies) to cope with new competency requirements in maintenance 4.0. Organizations can use the model in the recruitment process and for the identification of training needs. The results of the research will also contribute to identifying the scope of competencies of the maintenance 4.0 actors (engineer, manager and technician), which, in practice, contributes to the creation of requirements for the candidates applying for a job in the maintenance department. Additionally, educational institutions should make the necessary changes to their curricula to suitably prepare students for the required maintenance 4.0 competencies.

The social implications of the article result from the contribution to the development of maintenance competencies. Individuals can use this model for their own personal development. Furthermore, companies can use this model to define job profiles for vacancies in M4.0. Therefore, using the model for training program implementation has a positive effect on employee job satisfaction and employees ’morale.

This research develops a novel maintenance 4.0 competency model by categorizing the maintenance workforce into three hierarchical levels: managers, engineers and technicians. In addition, the competency requirement is prioritized to three degrees: very important, moderately important and slightly important. According to the previous studies conducted on maintenance 4.0 and employees' competencies, this study revealed that no research has developed a competency model for maintenance 4.0. Hence, this model is unique, generic and integrative since it presents the most relevant competencies for the three hierarchical levels. Moreover, this work combines the results of the literature review and the experts' returns. This model can be useful in the recruitment of new maintenance employees, the evaluation of their performance and the identification of training needs to cope with new changes in maintenance competencies.