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The deployment of solar photovoltaic (PV) in higher education institutions is beneficial and critical for attaining sustainable campus goals. However, various barriers hamper the adoption of the technology, and unless these challenges are identified, formulating tailor made solutions to boost deployment will be challenging. Thus, this study aimed to identify the barriers to the deployment of PV in the public university sector in South Africa.

A critical review of the literature was conducted to identify the factors that negatively impact PV deployment. By screening the barriers identified from the literature using a conceptual framework, the barriers that were considered relevant to deployment within a university context were selected. Thereafter, the selected barriers and additional barriers recommended by panellists were verified through a three-round Delphi survey. The factors were either accepted or rejected as barriers in the sector based on the factors' mean score and interquartile range values.

The study observed that 12 barriers hamper PV deployment in the public university sector. The findings indicated that the top five barriers were the lack of incentives, lack of green building targets, lack of financial resources, high initial cost, and lack of clear policy direction. However, the study found that deployment was not hindered because there was resistance to change or uncertainty of recouping investment costs. The deployment was also not hindered because there was a lack of demand from electricity end-users or a lack of suitable installation space.

Given the lack of empirical studies on the subject in the region, the present study contributes to the body of knowledge by identifying the significant barriers that impede PV deployment in the public university sector. Furthermore, insight is provided on measures that relevant stakeholders can take to motivate and support universities to deploy the technology further.

This study aims to test the effect of cause-related marketing (CRM), campaign-related marketing and consumer-related antecedents on consumers’ behavioral responses in a developing-country context.

A descriptive cross-sectional research design was used. An online questionnaire was distributed, and a sample of 738 Egyptians was obtained. Both the SPSS25 and Smart PLS software were used to report the results.

Results revealed that campaign-related antecedents had stronger effects on consumer attitudes than consumer-related antecedents. The most important campaign-related antecedents were brand function fit and hedonic product type. Extrinsic religiosity affected brand attitude and was also the most important predictor of purchase intention. Other predictors of purchase intention were brand attitude, hedonic product type and brand function fit. Furthermore, the effect of brand attitude on purchase intention was positive and significant. Cause involvement and others’ – centered attribution of corporate motives positively moderated the relationship between attitudes and purchase intention. Conversely, skepticism and self-centered attribution of corporate motives negatively moderated brand attitudes and purchase intention relationships. Research implications and suggestions for future research were also presented.

The study contributes to the existing academic literature by providing a better understanding of the effect of consumer and campaign-related variables on consumer attitudes and purchase intentions in a CRM context. It also helps understand the role of the two dimensions of religiosity in forming attitudes and purchase intentions for CRM campaigns. Furthermore, the research examines two possible moderators of the attitude–behavior gap through the lenses of signaling theory, prosocial behavior theory, theory of reasoned action and attribution theory.

Despite the digital penetration in the larger consumer market, the adoption of e-pharmacy services is reported to be very low in emerging economies like India. In this context, the purpose of the current study is to examine the influence of consumers’ risk perception on their intention to purchase medicines/pharmaceuticals through online pharmacies. Furthermore, the study seeks to understand to what extent the perceived usefulness of online pharmacy mediates the relationship between different dimensions of perceived risk and purchase intention.

The study was conducted among a sample of 800 consumers in India who are familiar with online e-commerce. To ensure the homogeneity of the sample and hence the generalizations of results, inclusion criteria were set as not to include respondents who have made a prior purchase through e-pharmacy services. Self-reporting questionnaires were administered among the respondents, who were selected through a purposive and convenience sampling method. Measurement modeling and path analysis were done using IBM SPSS 23.0 and AMOS 24.0 to test the hypotheses and draw inferences.

Results revealed that consumers’ risk perceptions, such as financial, product, source and privacy risks, had a significant direct and indirect effect on their intention to purchase medicines through online pharmacies. India is the major universal provider of generic medicines. The insights gained from this study can help policymakers, corporates, consumers, distributors, retailers and marketing managers to frame effective strategies for improved usage of online platforms for procuring medications.

This study is pioneering in conceptualizing and testing a theoretical model linking consumers’ risk perceptions, perceived usefulness and intention to purchase through online pharmacies, particularly in the context of an emerging economy like India. Implications regarding facilitating and nurturing a conducive platform for online purchasing medicines and its outcomes are elaborated, thus striving to fill a gap in the existing literature. By examining the proposed framework through the lens of the technology acceptance model and theory of risk perception, this study seeks to add to the emergent literature on online pharmacies, especially in emerging economies with huge market potential.

Drawing upon social exchange theory, this study investigates how witnessed incivility is related to psychological distress for employees. In addition, scholars dug deep into the potential moderating effect of self-esteem that links witnessed incivility, employee silence and psychological distress.

In data were obtained from 292 bankers at family-owned banks. In this work, data analysis was performed using Smart-PLS covariance-based SEM version 4.

The study results indicate that employee silence mediates witnessed incivility and psychological distress. Findings also suggest that high self-esteem can mitigate the harmful effects of witnessed incivility, indirectly causing silence and psychological distress among employees.

Family-owned bank management should encourage employees to speak up, demonstrate self-esteem and share their concerns. Thus, reducing witnessed incivility increases well-being, stress, and mental health in Pakistani family-owned enterprises which operate in diverse industries.

In the context of family-owned banks, our study adds context and theory to the existing body of knowledge by illuminating the underlying process that relates incivility with psychological distress By exploring the use of social exchange theory.

Research on solar energy adoption offers a multidimensional scope and warrants exploration from multiple perspectives, including political, economic, management, behavioral, policy and innovation aspects. The aim of this paper is to comprehensively consolidate major research findings on the premise of solar energy adoption and to disclose gaps in the existing literature.

A bibliometric analysis of the vast literature is conducted on 1,009 meticulously shortlisted articles following the semi-systematic literature review methodology. A text analytics tool named BibExcel is used for synthesizing the literature, and the results are visualized using Gephi, Pajek and a spreadsheet application.

This paper reports the evolution of research in the selected domain. It is noted that research in this domain was primarily concentrated on four broad themes, namely, peer effects and spatial patterns, public perceptions, policies and economics and technological evolution. The analysis further reveals the merging of two of these themes as a result of transdisciplinary research and also projects future research trends emphasizing political interventions in technological evolution and diffusion.

Research trends and future research scope are identified and discussed in detail. The information revealed from the analysis, along with the research implications, will assist policymakers in noting the flaws in the current doctrines and practices, entrepreneurs in understanding potential enablers and barriers influencing solar energy adoption and budding scholars in comprehending the current research status and framing promising research objectives to close the existing research gaps.

This study aims to explore entropy evaluation in the bi-directional flow of Casson hybrid nanofluids within a stagnated domain, a topic of significant importance for optimizing thermal systems. The aim is to investigate the behavior of unsteady, magnetized and laminar flow using a parametric model based on the thermo-physical properties of alumina and copper nanoparticles.

The research uses boundary layer approximations and the Keller-box method to solve the derived ordinary differential equations, ensuring numerical accuracy through convergence and stability analysis. A comparison benchmark has been used to authenticate the accuracy of the numerical outcomes.

Results indicate that increasing the Casson fluid parameter (ranging from 0.1 to 1.0) reduces velocity, the Bejan number decreases with higher bidirectional flow parameter (ranging from 0.1 to 0.9) and the Nusselt number increases with higher nanoparticle concentrations (ranging from 1% to 4%).

This study has limitations, including the assumption of laminar flow and the neglect of possible turbulent effects, which could be significant in practical applications.

The findings offer insights for optimizing thermal management systems, particularly in industries where precise control of heat transfer is crucial. The Keller-box simulation method proves to be effective in accurately predicting the behavior of such complex systems, and the entropy evaluation aids in assessing thermodynamic irreversibilities, which can enhance the efficiency of engineering designs.

These findings provide valuable insights into the thermal management of hybrid nanofluid systems, marking a novel contribution to the field.

In the apparel industry, suppliers play a significant role, directly affecting customer service levels and business profits. Integrating sustainable requirements into supplier selection not only aligns with global environmental goals but also enhances business performance, social responsibility and overall industry well-being. This study aims to design a multi-criteria model to evaluate and select the most sustainable suppliers in the fashion industry, trying to balance the conflicts in the set of sustainable development criteria.

The integration of analytic hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) offers advantages in sustainable supplier selection within the apparel industry. The AHP plays a crucial role in engaging multiple decision-makers with conflicting criteria to reach a consensus during the decision-making process. Conversely, the TOPSIS is used to compute alternative ratings. By simultaneously determining criteria weights and incorporating stakeholder preferences, hybrid models enhance decision-making strength and overcome limitations observed in classical multi-criteria decision-making techniques.

This research identified and classified 16 critical criteria impacting the selection of apparel industry suppliers, focusing on sustainable development. The criteria were weighted, providing a robust statistical foundation for the selection model. The results indicated that the most influential criteria were staff training, production capability, flexibility and practice of recycling. The proposed sustainable supplier selection model explains to decision-makers how criteria influence supplier ranking results compared to traditional models, supporting managers in making informed and sustainable supply chain decisions through continuous updates and enhancements.

This research provides new insight into the weighted impact of factors related to sustainable supplier selection in the apparel industry. The combination of a precise process and scientific knowledge will improve the quality of sustainable supplier selection.

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.

Agile new product development (ANPD) attracts researchers and practitioners by its ability to rapidly reconfigure products and related processes to meet the needs of emerging markets. To increase ANPD adoption, this study aims to identify ANPD enablers (ANPDEs) and create a structural framework that practitioners can use as a quick reference.

Initially, a comprehensive literature review is conducted to identify ANPDEs, and a structural framework is developed in consultation with an expert panel using a hybrid robust best–worst method interpretive structural modeling (ISM). During the ISM process, the interactions between the ANPDEs are investigated. The ISM result is used as input for fuzzy Matrice d’Impacts croises-multiplication appliqúean classment means cross-impact matrix multiplication applied to classification (MICMAC) analysis to investigate enablers that are both strong drivers and highly dependent.

The study’s findings show that four ANPDEs are in the low-intensity cluster and thus are excluded during the structural frame development. ISM output shows that “Strong commitment to NPD/top management support,” “Availability of resources,” “Supplier commitment/capability” and “Systematic project planning” are the important ANPDEs. Based on their driving and dependence power, the clusters formed during the fuzzy MICMAC approach show that 16 ANPDEs appear in the dependent zone, one ANPDE in the linkage zone and 14 ANPDEs in the driving zone.

This research has intense functional consequences for researchers and practitioners within the industry. Industry professionals require a conservative focus on the established ANPDEs during ANPD adoption. Management has to carefully prepare a course of action to avoid any flop during ANPD adoption.

The framework established is a one-of-a-kind study that provides an integrated impression of important ANPDEs. The authors hope that the suggested structural framework will serve as a blueprint for scholars working in the ANPD domain and will aid in its adoption.

This investigation delves into the rationale behind the preferential applicability of the non-Newtonian nanofluid model over alternative frameworks, particularly those incorporating porous medium considerations. The study focuses on analyzing the mass and heat transfer characteristics inherent in the Williamson nanofluid’s non-Newtonian flow over a stretched sheet, accounting for influences such as chemical reactions, viscous dissipation, magnetic field and slip velocity. Emphasis is placed on scenarios where the properties of the Williamson nanofluid, including thermal conductivity and viscosity, exhibit temperature-dependent variations.

Following the use of the OHAM approach, an analytical resolution to the proposed issue is provided. The findings are elucidated through the construction of graphical representations, illustrating the impact of diverse physical parameters on temperature, velocity and concentration profiles.

Remarkably, it is discerned that the magnetic field, viscous dissipation phenomena and slip velocity assumption significantly influence the heat and mass transmission processes. Numerical and theoretical outcomes exhibit a noteworthy level of qualitative concurrence, underscoring the robustness and reliability of the non-Newtonian nanofluid model in capturing the intricacies of the studied phenomena.

Available studies show that no work on the Williamson model is conducted by considering viscous dissipation and the MHD effect past over an exponentially stretched porous sheet. This contribution fills this gap.