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Obtaining building permit certificate is an essential component of construction endeavors, but it can be cumbersome sometimes. The process is frequently beset with obstacles, including bureaucratic impediments, red-tapism, prolonged authorization protocols and insufficient inter-agency collaboration which result in project timeline extension, cost escalation and applicant dissatisfaction. Therefore, this study aims to examine customer satisfaction with the assessment of building construction permit certificates in Lalitpur, Nepal.

Following the notion of evaluation model theory, this study adopts an explanatory research design to determine the causal relationship between latent and observed variables. People who have recently completed the construction of their building and those people whose construction work is pending make up the population for the study. A total of 198 samples were collected by following the convenience sampling method from Lalitpur, Nepal. The primary data are collected by using the structured questionnaire with the interview process where the data are statistically evaluated using descriptive and inferential analysis using the KOBO toolbox, SPSS and AMOS. The connection between variables was examined using structural equation modeling (SEM).

Results indicate that the negligence of the employees, the attitude of the employees, the need for additional costs and the hiring of the agent are the most significant obstacles encountered by customers during the process of getting construction permit. Regarding the whole assessment system, the general population expresses displeasure. SEM results indicate that environment and quality are significantly related to customer satisfaction.

This paper's novelty lies in its Nepal-specific inquiry into the relationship between building permit acquisition procedures and customer contentment. The study provides a distinctive viewpoint on this context by combining evaluation model theory and SEM. The localized approach emphasizes the importance of customized strategies to improve customer satisfaction, adding to the current literature on the subject. The study's use of SEM as a quantitative analysis tool enhances its methodological rigor. This interdisciplinary research offers valuable insights for academics, practitioners and policymakers in Nepal and contributes to the wider field of construction and customer satisfaction.

Despite enormous progress in health globally, primary healthcare services in many developing countries are facing different challenges. Many studies have documented that decentralisation could be useful in supporting and developing health services closer to citizens. The purpose of this paper is to assess the effect of decentralisation on health services, and to draw general lessons which might help to develop appropriate strategies to improve health services in Nepal.

A mixed method was used, consisting of reviews of current literatures relevant to decentralisation and health performance, engaging with health service inputs‐outputs data between 2001 and 2007, and assessing the range of choices (management, finance and governance) available to local authorities using Bossert's “decision‐space approach”.

Decentralisation in many countries, including Nepal, suggests a new form of service delivery.

Review of the selected studies in triangulation with health services data has revealed that decentralisation in many cases has improved access to, utilisation of, and management of health services. The effects on other performance dimensions such as policy, equity, quality and service effectiveness are poorly investigated topics in the literature. The findings suggest that the successful implementation of decentralisation requires a broader context of institutional capacity building and resource management, and underlines the need for their consideration during implementation processes, and further investigation.

Grassroots innovations, developed by local people using locally available resources, have shown the potential to provide low-cost technological solutions to the problems faced by underserved consumers in the global south. This paper aims to link the concept of grassroots innovations to energy use in the context of India.

The paper takes three case studies from the list of technologies scouted and nurtured by the National Innovation Foundation to critically discuss the potential of grassroots innovations for the dissemination and diffusion of urban sustainable energy uses. The data for this study has been collected from various secondary sources. It discusses the opportunities and challenges in promoting grassroots innovations for sustainable energy uses in urban settings.

The paper discusses the opportunities and challenges in promoting grassroots innovations for sustainable energy uses in urban settings.

Although the concept and understanding of grassroots innovations have well developed, its linkages with sustainable energy use in urban settings have received scarce or no attention in the literature.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

The purpose of this paper is to examine the factors that significantly affect the prediction of fake news from the virality theory perspective. The paper looks at a mix of emotion-driven content, sentimental resonance, topic modeling and linguistic features of news articles to predict the probability of fake news.

A data set of over 12,000 articles was chosen to develop a model for fake news detection. Machine learning algorithms and natural language processing techniques were used to handle big data with efficiency. Lexicon-based emotion analysis provided eight kinds of emotions used in the article text. The cluster of topics was extracted using topic modeling (five topics), while sentiment analysis provided the resonance between the title and the text. Linguistic features were added to the coding outcomes to develop a logistic regression predictive model for testing the significant variables. Other machine learning algorithms were also executed and compared.

The results revealed that positive emotions in a text lower the probability of news being fake. It was also found that sensational content like illegal activities and crime-related content were associated with fake news. The news title and the text exhibiting similar sentiments were found to be having lower chances of being fake. News titles with more words and content with fewer words were found to impact fake news detection significantly.

Several systems and social media platforms today are trying to implement fake news detection methods to filter the content. This research provides exciting parameters from a viral theory perspective that could help develop automated fake news detectors.

While several studies have explored fake news detection, this study uses a new perspective on viral theory. It also introduces new parameters like sentimental resonance that could help predict fake news. This study deals with an extensive data set and uses advanced natural language processing to automate the coding techniques in developing the prediction model.

In Nepal, not much is known about the adoption of improved vegetable varieties. Also, there are reasons to expect that the determinants of adoption may vary between subsistence and commercial farmers, given their different production/market orientations. Therefore, the paper aims to examine the adoption intentions of commercial and subsistence vegetable farmers.

A logistic regression model was used to empirically test the determinants of the intention to adopt and recommend improved vegetable varieties. The paper also uses propensity score matching (PSM) to assess the causal effects of production/market orientation on household dietary patterns. Cross-sectional data of 600 Nepalese vegetable farmers are analyzed.

Compared to subsistence farmers, commercial vegetable farmers obtain seeds mainly from formal sources and use hybrid seeds. The most consistent covariates of vegetable adoption intentions were risk preferences and experience growing vegetables. Overall, adoption intentions were higher among commercial farmers, and commercial vegetable households tend to consume more vegetables.

Considering that vegetable farming provides an important supplementary food production system for the household, adopting improved vegetable varieties is pivotal to increasing productivity and improving household level dietary diversity in developing countries. Actions to promote wider adoption of vegetable varieties and encourage healthier dietary patterns could be successful if these efforts also focus on subsistence farmers. The findings in this paper will be useful to policymakers to better prioritize dissemination strategies.

The paper highlights the differences in characteristics and adoption intention towards new vegetable varieties between subsistence and commercial farmers. The impact of commercial production on healthier household dietary patterns is accentuated.

The purpose of this paper is to present a road map to implement Lean-Kaizen concept using value stream mapping (VSM) to identify hidden continuous improvement opportunities in a small and medium-sized enterprise (SME) located at the non-capital region of India.

From the collected data, a current state map was prepared that indicated the current operating situation of selected SME. The takt time was calculated and those processes which attained higher cycle time (C/T) than takt time were identified. The continuous flow processing was achieved by adjusting C/T of each process and supermarket pull system was developed to control the production at the workstations. Finally, a future state map was developed that served as a guide for future lean activities. Few problems were identified to realize the future state. The “5-why” analysis was used for identifying root causes of these problems and Kaizen events were proposed as solutions. In this case study, one Kaizen event was identified in which brainstorming technique was used to control the variation caused by unorthodox fixture design for clamping and de-clamping of case product and thus eliminated non-value-added activities performed by the operator on a milling machine.

Before and after implementation of value stream map, the data obtained were analyzed and eliminated rework time, reduced inventory level, reduced lead time and C/T, improved productivity and product quality are presented as finding. Lean-Kaizen provides a better chance for every individual of the industry to have a hand in achieving organization’s goals to attain continuous progress in productivity and quality of the product. Even good understanding of the concept of lean tools and techniques by SMEs, the employee willingness and motivation to identify and eliminate wastes are found feeble.

This study is among best practices to identify hidden improvement opportunities in the regular production of the product to increase productivity and improve quality using value stream map. The research paper gives useful understandings to the lean implementers, Kaizen identifiers, consultants and researchers.

The purpose of this study is to investigate the determinants of agricultural insurance adoption by farmers of the state of São Paulo, Brazil.

Primary data from the 2015/2016 crop season was collected from a sample of 175 farmers. Logit econometric models were applied to identify the variables that affect the probability of agricultural insurance adoption.

The empirical results show that the education level, access to technical assistance, use of management tools and farm size positively affect the probability of adopting agricultural insurance. In addition, farmers who produce soybean and/or corn are more likely to use insurance. On the other hand, the higher the farmers’ propensity to take risk the lower the likelihood of using insurance.

The empirical analysis is based on cross-sectional data of a sample of 175 farmers of the state of São Paulo. The use of panel data with a larger sample of farmers, considering a period of years, could provide additional information.

To the best of the knowledge, this is the first empirical analysis about determinants of agricultural insurance adoption by Brazilian farmers, considering behavioral factors. The findings provide useful insights for policymakers in formulating risk management programs in the Brazilian agricultural markets. A better understanding about the determinants of insurance adoption is also relevant for private companies that sell insurance to farmers. Therefore, the paper may contribute with the diffusion of rural insurance as risk management tool in Brazilian agriculture.

This study aims to understand the socio-cultural context of Indian women's high-tech entrepreneurial experience. Despite a small proportion of women entrepreneurs, and the traditional gender dynamics among the educated middle-classes that appears to be antithetical to female entrepreneurship; women-led high-tech start-ups are on the rise.

Semi-structured interviews were conducted with women founders at an academic incubator in an elite Indian Institute of Technology. The study was based on the post-structural feminist approach that women entrepreneurs are embedded in their socio-cultural and institutional context. During data collection, the Coronavirus lockdown provided a natural experiment, highlighting entrepreneurial response to unforeseen obstacles.

It finds that the context is significant in constructing opportunity, and in navigating challenges of gender and entrepreneurship. Further, in the process of construction of an entrepreneurial identity, women innovators not only reproduce, but also modify their context. Also, the experiences with academic incubator indicate positive results both for gender dynamics and enhancing an emergent entrepreneurial culture.

The study highlights that women's high-tech entrepreneurship has considerable potential for enhancing women's status in society through the support of academic incubator. This has certain implications for policy.

It provides an insight in to the hitherto neglected issue of women's high-tech entrepreneurship in India, and argues that a study of “social embeddedness” not only highlights constraints for women entrepreneurs unique to that context, but also the potential of women's entrepreneurship in advancing women's agency and gender equality.

This research intended the utilization of Javanese turmeric (0.4% w/v) as a kombucha substrate and analysis of its hepatoprotective activity, in comparison against nonfermented Javanese turmeric beverage (JTB) and black tea kombucha.

Forty-two healthy male Balb/c mice (two- to three-week-old, 20–30 g) were divided into six groups with seven replicates each. The treatments were normal diet, normal diet + Javanese turmeric kombucha (JTK), normal diet + diethylnitrosamine (DEN), DEN + JTB, DEN + JTK, DEN + black tea kombucha. Kombuchas and JTB were given at 0.3 mL/20 g BW/d. DEN was induced intraperitoneally at a dose of 100 mg/kg. Observed biomarkers were blood serum glutamate pyruvate transaminase (SGPT) and serum glutamate oxaloacetate transaminase (SGOT) activity, serum malonaldehyde (MDA), as well as liver histology. Data were analyzed using analysis of variance.

Among DEN-induced groups, JTK significantly (p < 0.05) diminished the level of blood SGPT, SGOT and serum MDA. JTK also had lower blood SGPT (8.604 ± 2.195 U/L) and serum MDA levels (2.884 ± 0.083 nM/mL) compared to the normal group (8.604 ± 2.195 U/L and 5.050 ± 0.998 nM/mL, respectively). JTK also produced the least damaged liver-cell numbers.

JTK demonstrated better hepatoprotective activity compared to JTB.