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The short/fast-food and perishable food supply chains (PFSC) have similar characteristics of lower lifespan and variable demand, leading to significant waste. However, the global population surge and increased health awareness make it impossible to continue wasting food because it is responsible for the loss of economy, resources, and biodiversity. A sustainable transition in short and PFSC is necessary; thus, addressing challenges is critical to explore the best strategy for redesigning PFSC.

An extensive literature review helped to identify 40 challenges, while a Delphi study highlighted 21 critical challenges. The fuzzy decision-making trial and evaluation laboratory method establishes a causal relationship between sustainable development (SD) challenges to help redesign PFSC.

From a strategic development perspective, frequent transportation disruption is the main critical challenge. Lack of supplier reliability is the most substantial cause of independence, with a causal value of 2.878. Overhead costs and lack of green maintenance strategies are part of the performance-oriented challenges. As it belongs to the driving zone, the second quadrant requires control while transforming PFSC for better sustainable development.

The study has several implications, such as lack of supplier reliability and frequent transportation disruption, which have the most robust causal value used as short-term strategy development. For short- and fast-food supply chains, it is necessary to study market and consumer behavior patterns to optimize inventory and customer service. Combating transportation disruption and supplier reliability challenges is vital in both PFSC and short and fast-food supply chains to reduce waste and promote sustainability.

The study’s findings are unique and put value toward the sustainable transition of PFSC by revealing critical challenges and their impact.

Blockchain is a nascent technology that has the ability to revolutionize the workings of the educational landscape. However, there are several barriers to the adoption of blockchain technology (BCT). So, this paper aims to determine, rank and analyse the interdependent contextual relationship among the BCT adoption barriers within the education management system (EMS) of higher education institutes.

The present research principally uses the technology-organization-environment model for the classification of BCT adoption barriers in the EMS. An integrated dual phase best-worst method and interpretive structural modelling – cross-impact matrix multiplication applied to classification (BWM-ISM-MICMAC) analysis is used for the identification, prioritization and analysis of the contextual relationships among the BCT barriers.

The findings of the research show that the environmental barrier among the primary barriers and the lack of government initiatives among the sub-barriers are crucial barriers to BCT adoption in the EMS.

Certain barriers might not be selected during the literature review and expert opinions might be biased. Future studies should use structural equation modelling to validate the relationships between BCT barriers and conduct similar research across other business sectors to provide valuable insights for scholars and practitioners alike.

The study facilitates a better perspective of BCT barriers and explores possible solutions more comprehensively for policymakers and field managers. Consequently, it offers viable suggestions for the successful and effective implementation of BCT within the EMS.

The concept of using the blockchain in academics is a novel one. This study establishes a crucial research base for the smooth adoption of BCT in EMS.

This study aims to examine the factors that impact the choice of paddy marketing channels in India at the farm level and household contingencies.

Employing multinomial logistic regression, the analysis utilizes the National Sample Survey Office (NSSO) 77th round Situation Assessment Survey (SAS) data from the 2018 to 2019 period, specifically for the paddy Kharif season, to determine the factors determining the choice of marketing channels. The significant independent variables include minimum support price (MSP) awareness, access to and adoption of technical advice, input agency, social group, farm size of farmers, region, age and education of the household head.

Awareness of MSP and adoption of technical advice from experts can enhance the probability of selecting government channels for paddy. The reliance on government input agencies has a favourable impact on the choice of government channels. Government channels are more likely preferred by higher social groups and those with higher land-holdings. There has been a state-wise variation in access to regulated marketing channels for paddy.

Transaction cost associated with marketing channel choice is an important factor, not incorporated in this study due to the unavailability in the NSS data.

The research uses the latest unit-level data of the NSSO 77th round, published by the Ministry of Statistics and Programme Implementation (MoSPI), the Government of India.

This paper aims to provide a conceptual framework containing SERVQUAL original dimensions and add two additional dimensions: patient satisfaction and loyalty in the hospital SQ model that demonstrates the relationship between hospital service quality, patient satisfaction and loyalty from patients’ perspective.

This research conducted a thorough literature review using specific keywords and electronic databases, adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Through analysis, the key dimensions of service quality in Indian hospitals were identified, with the addition of patient satisfaction and loyalty as variables. Of 1,000 initially downloaded papers, 497 were included.

While many researchers rely on the SERVQUAL model, some introduce new or modified dimensions, often renaming existing ones. This study identifies the RATER factors as the main dimensions patients use to evaluate hospital services. This study finds a positive relationship between service quality, patient satisfaction and loyalty.

An understanding of how health-care service quality dimensions, directly and indirectly, affect patient satisfaction and loyalty is important for hospital marketing managers. This study helps them take action to improve patient satisfaction, which encourages patients to be loyal.

This research provides a comprehensive framework for measuring health-care service quality, combining SERVQUAL dimensions and new variables. This study offers useful insights for academics and health-care professionals, promoting more accurate measurement and enhancement of service quality. The use of PRISMA in this context is also innovative, as it is less common in administrative health-care research.

The successful completion of linear infrastructure construction projects such as railroads, roads, tunnels, and pipelines relies heavily on decision-making processes during planning phase. Professionals in the construction industry emphasize that determining the starting point of a linear infrastructure construction project is one of the most important decisions to be made in the planning phase. However, the existing literature does not specifically focus on selection of the starting point of the segments to be constructed. Therefore, it is of utmost importance to develop a multi-criteria decision-making (MCDM) model to support selection of the starting point of the segments to be constructed in linear infrastructure construction projects.

Based on the characteristics of the railroad projects and insights gathered from expert interviews, the appropriate criteria for the model were determined. Once the criteria were determined, a decision hierarchy was developed and the weights of the criteria (w_i) were calculated using DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method. Then, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), COmplex PRoportional Assessment (COPRAS), and evaluation based on distance from average solution (EDAS) methods were used. The alternatives were ranked in terms of their priority with TOPSIS method based on relative closeness (Ci) of each alternative to the ideal solution, COPRAS method based on quantitative utility (Ui) for each alternative and EDAS method based on evaluation score (ASi) for all alternatives. The results were compared with each other.

The study reveals the effects of all criteria on the proposed model. The results of DEMATEL method indicated that quantity of aggregate (w_i = 0.075), ballast (w_i = 0.071), and sub-ballast (w_i = 0.069) are the most important criteria in starting location selection for railroads, where earthquake (w_i = 0.046), excavation cost (w_i = 0.054), and longest distance from borrow pit (w_i = 0.055) were found to be less important criteria. The starting location alternatives were ranked based on TOPSIS, COPRAS and EDAS methods. The A-1 alternative was selected as the most appropriate alternative (Ci = 0.64; Ui = 100%; ASi = 0.81), followed by A-6 alternative (Ci = 0.61; Ui = 97%; ASi = 0.73) and A-7 alternative (Ci = 0.59; Ui = 94%; ASi = 0.60). Even tough different methods were used, they provided compatible results where the same ranking was achieved except three alternatives.

This study identifies novel criteria for the starting location selection of railroad construction based on the data of a railroad project. This study uses different methods for selecting the starting location. Considering the project type and its scope, the model can be used by decision-makers in linear infrastructure projects for which efficient planning and effective location selection are critical for successful operations.

This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice.

A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare.

The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI’s role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology.

This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

This paper aims to identify and provide a theoretical explanation for the barriers that hinder the adoption of emerging technologies in the architecture, engineering and construction industry, irrespective of the company’s size, specialization or geographical location. In addition, the paper proposes potential areas for future research in this domain.

A list of barriers hindering the adoption of emerging technologies was identified and clarified using a systematic literature review of various scientific sources.

Twenty-five barriers were recognized and explained and some suggestions for future research studies were provided.

The barriers related to a specific country or region or to a specific technology were excluded.

By providing a deeper comprehension of the barriers hindering the adoption of emerging technologies, this review is expected to encourage their adoption in the industry. Furthermore, it could prove valuable in devising effective strategies for the successful implementation of these technologies.

This study aims to understand the impact of the Covid-19 pandemic disruptive event on delivery of the built environment degree apprentice programme in higher education in the UK and identify the key strategies to minimise the effect.

A qualitative approach was used to collect and analyse data from a sample set of built environment degree apprenticeship stakeholders. Semi-structured interviews were conducted with 17 key stakeholders to collate emerging themes on their perceptions of the impacts of the pandemic and strategies to adopted to minimise it.

The investigation reveals that the core impacts of Covid-19 on the apprentices training programme are lack of access to the site, furlough, limited access to off the job training, limited interaction with tutors and peers, too much time on the screen, limited pastoral care and lack of contact with a mentor. The census from the research participants is that despite the development and gain with the various virtual platform used during pandemic physical meetings with their mentor remain pivotal to the built environment apprentices learning and training.

The results provide relevant stakeholders and actors supporting degree apprentices training programmes (training providers and employers, among others) with the information needed to improve the delivery of built environment degree apprenticeship training programmes during a disruptive event Covid-19. The study identifies various strategies to minimise the impact of disruptive events on the apprentices training, including technology, regular meeting with mentors online, and personal and pastoral care.

The study is the first to document the impact of the Covid-19 pandemic on degree apprenticeship programs in the built environment. This study provides an in-depth understanding of how these programs have been affected and offers potential solutions to reduce or mitigate potential damage. The research will inform future policy decisions related to degree apprenticeship programs in the built environment.