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This paper aims to find the effects of mothers’ schooling on child schooling.

This paper uses Bangladesh's Household Income and Expenditure Survey (HIES), which is a nationally representative survey. It employs the instrumental variable technique to estimate the intergenerational model.

Interestingly, the results show that the intergenerational transmission of schooling from mothers is slightly higher than that of fathers in Bangladesh.

Estimating the intergenerational model is challenging due to the endogeneity issue. The methodology used in this paper may help to find similar evidence from other countries.

The findings of the study may help to design and evaluate the educational policies in Bangladesh or a country like Bangladesh. For instance, the results of this paper suggest that the female stipend program (FSP) in Bangladesh is effective for the next generation’s schooling.

This paper is among the first to analyze the effect of mother’s schooling on the child’s schooling, controlling the father’s education and other household characteristics. In addition, it controls for endogeneity bias due to genetic transmission.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-06-2023-0491

Indian railways (IR) is one of the largest railway networks in the world. As a part of its strategic development initiative, demand forecasting can be one of the indispensable activities, as it may provide basic inputs for planning and control of various activities such as coach production, planning new trains, coach augmentation and quota redistribution. The purpose of this study is to suggest an approach to demand forecasting for IR management.

A case study is carried out, wherein several models i.e. automated autoregressive integrated moving average (auto-ARIMA), trigonometric regressors (TBATS), Holt–Winters additive model, Holt–Winters multiplicative model, simple exponential smoothing and simple moving average methods have been tested. As per requirements of IR management, the adopted research methodology is predominantly discursive, and the passenger reservation patterns over a five-year period covering a most representative train service for the past five years have been employed. The relative error matrix and the Akaike information criterion have been used to compare the performance of various models. The Diebold–Mariano test was conducted to examine the accuracy of models.

The coach production strategy has been proposed on the most suitable auto-ARIMA model. Around 6,000 railway coaches per year have been produced in the past 3 years by IR. As per the coach production plan for the year 2023–2024, a tentative 6551 coaches of various types have been planned for production. The insights gained from this paper may facilitate need-based coach manufacturing and optimum utilization of the inventory.

This study contributes to the literature on rail ticket demand forecasting and adds value to the process of rolling stock management. The proposed model can be a comprehensive decision-making tool to plan for new train services and assess the rolling stock production requirement on any railway system. The analysis may help in making demand predictions for the busy season, and the management can make important decisions about the pricing of services.

The purpose of this paper is to clarify the relationship between the use of different polymer matrices for the preparation of composite materials, namely, polyethylene terephthalate-glycol (PET-G) and polyamide (PA), using Composite Fiber Co-Extrusion technology with the application of two types of carbon fibers, short and continuous. The aim of the study is also to extend the knowledge of the production of composite materials with a defined structure from the point of view of their influence on the microstructure and their physical-mechanical properties.

As part of the experiment, four types of samples were prepared, namely, two types of samples with PA polymer matrix and two types with PET-G polymer matrix. All types contained short carbon fibers and always one set from each polymer matrix in addition to continuous carbon fibers. All types were prepared using the same 3D printing parameters to avoid any further influence. The samples were then tested for microstructure using microCT, mechanical properties using a tensile test and dilatation characteristics from the point of view of aerospace applications. Finally, the raw materials themselves were tested.

The paper provides insight into the influence of polymer matrix types on the physico-mechanical properties of 3D printed composites. The analysis confirmed that the physico-mechanical results varied with respect to the interface between the polymer matrix and the carbon fiber. The implications of the conclusions can be extended to the development of products in the aerospace and automotive sectors.

This study provides information for composite applications in the aerospace industry, focusing on evaluating dilatation characteristics within very low temperatures (−60 °C) when using carbon fibers (continuous carbon fibers, short carbon fibers and a combination of both) in two types of thermoplastic matrices. This perspective on materials characterisation for aerospace applications is a very important and unpublished approach within the 3D printing of composites. These characteristics are important parameters in the design of prototypes and functional samples with regard to the resulting behaviour in real conditions.

This study focused on exploring the performance factors (PFs) that impact Infrastructure Sanitation Projects (ISSPs) in the construction sector. The aim was twofold: firstly, to identify these crucial PFs and secondly, to develop a robust performance model capable of effectively measuring and assessing the intricate interdependencies and correlations within ISSPs. By achieving these objectives, the study aimed to provide valuable insights into and tools for enhancing the efficiency and effectiveness of sanitation projects in the construction industry.

To achieve the study's aim, the methodology for identifying the PFs for ISSPs involved several steps: extensive literature review, interviews with Egyptian industry experts, a questionnaire survey targeting industry practitioners and an analysis using the Relative Importance Index (RII), Pareto principle and analytic network process (ANP). The RII ranked factor importance,  and Pareto identified the top 20% for ANP, which determined connections and interdependencies among these factors.

The literature review identified 36 PFs, and an additional 13 were uncovered during interviews. The highest-ranked PF is PF5, while PF19 is the lowest-ranked. Pareto principle selected 11 PFs, representing the top 20% of factors. The ANP model produced an application for measuring ISSP effectiveness, validated through two case studies. Application results were 92.25% and 91.48%, compared to actual results of 95.77% and 97.37%, indicating its effectiveness and accuracy, respectively.

This study addresses a significant knowledge gap by identifying the critical PFs that influence ISSPs within the construction industry. Subsequently, it constructs a novel performance model, resulting in the development of a practical computer application aimed at measuring and evaluating the performance of these projects.

The purpose of this paper is to investigate the social acceptance of renewable and non-renewable energies in Iran using the social acceptance pyramid.

Today, social acceptance is considered a very important phenomenon in the development, implementation and achievement of energy policy goals. Low acceptance will make it difficult to achieve energy development goals; therefore, social acceptance must be taken into account when making policy. Firstly, the model criteria, using data obtained from questionnaires, are weighted by the Shannon entropy method and, finally, four sources of fossil, nuclear, wind and solar energy were ranked by means of VIKOR, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

The results show that, in Iran, the social acceptance criterion and trust sub-criterion are the most important criteria for energy acceptance. The results of the ranking of options based on multiple-criteria decision-making (MCDM) techniques show that, given Iran's specific energy requirements, social acceptance of fossil energy is higher than wind, solar and nuclear, and wind, solar and nuclear energy come later in the rankings.

This research contributes to the literature in two ways: Firstly, social acceptance is considered a very important phenomenon in the development, implementation and achievement of energy policy goals; thus social acceptance must be taken into account when making policy. The results of the ranking of options based on MCDM techniques show that, given Iran's specific energy requirements, social acceptance of fossil energy is higher than wind, solar and nuclear, and wind, solar and nuclear energy come later in the rankings. Also, the social acceptance criterion and trust sub-criterion are the most important criteria for energy acceptance in Iran.

The purpose of the study is to examine the obstacle in doing business and determinants of credit adoption by the textile enterprises in India.

The study is based on World Bank’s Enterprises Survey, there are 571 enterprises involved in textile business. The enterprises survey has response on wide range of business obstacles which are categorized under three broad categories, namely, access to resource, business regulations and market externalities. Chi-square test and analysis of variance (ANOVA) have been used to examine the significant difference among firm’s profile and perceived business obstacles across the firm size. Furthermore, binary logistic regression model has been applied to explore the determinants of credit adoption by textile enterprises.

A statistically significant difference has been found in size of firms and legal status nature of establishment, gender of top manager, main product market and credit adoption from financial institutions. Majority of small- and medium-sized enterprises (SMEs) are sole proprietorship firm while large enterprises are limited partnership firms. Similarly, large enterprises have relatively more female as a top manager and international market for their product. ANOVA reveals equal degree of obstacles in doing textile business across the firm size. The logistic regression coefficient and marginal effects reveal that firm size, main market,gender of owner, number of establishment in the firms positive and significantly affects the credit adoption by 3 textile enterprises.

The study has some policy implications for various stakeholders such as textile business managers and promoters, government, investors and bankers for entrepreneurship development in textile sector. The study suggests that the government should incentivize small- and medium-sized businesses to increase their exports. The results show that despite government efforts to finance SMEs, fewer SMEs are receiving both short- and long-term credit. To help SMEs in the textile industry overcome financial difficulties and expand their main product market to both domestic and international levels, a soft loan should be provided based on the characteristics of textile enterprises.

The present study suggests the evidence-based understanding of textile business environment. The value and uniqueness of this study is to explore an ease of business textile sector using comprehensive enterprises survey data of World Bank.

Using coconut shell aggregates (CSA) in concrete benefits agricultural waste management and reduces the demand for mineral resources. Several studies have found that concrete containing CSA can achieve strengths that are comparable to regular concrete. The purpose of the present work is to evaluate the concrete’s durability-related properties to supplement these earlier findings.

Cylindrical specimens were prepared with a constant water–cement ratio of 0.50 and CSA content ranging from 0% to 50% (at 10% increment) by volume of the total coarse aggregates. The specimens were cured for 28 days and then tested for density, surface hardness, electrical resistivity and water sorptivity. The surface hardness was measured to describe the concrete resistance to surface wearing, while the resistivity and sorptivity were evaluated to describe the material’s resistance to fluid penetration.

The results showed that the surface hardness of concrete remained on average at 325 Leeb and did not change significantly with CSA addition. The distribution of surface hardness was also similar across all CSA groups, with the interquartile range averaging 59 Leeb. These results suggest that the cement paste and gravel stiffness had a more pronounced influence on the surface hardness than CSA. On the other hand, concrete became lighter by about 9%, had lower resistivity by 80% and had significantly higher initial sorptivity by up to 110%, when 50% of its natural gravel was replaced with CSA. Future work may be done to improve the durability of CSA when used as coarse aggregate.

The present study is the first to show the lack of correlation between CSA content and surface hardness. It would mean that the surface hardness test may not completely capture the porous nature of CSA-added concrete. The paper concludes that without additional treatment prior to mixing, CSA may be limited only to applications where concrete is not in constant contact with water or deleterious substances.

Night lighting reflects the prosperous development of economic and the increasingly rich and colorful cultural life. Currently, various technical standards, protocols and management specifications have been developed to build a safe, comfortable and economical lighting environment. However, prevailing evaluation systems focus on objective indexes of illumination and have ignored environmental characteristics and subjective feelings and lacked consideration of regional culture, economic benefit, management and maintenance. In this context, a lighting evaluation system combining subjective and objective is proposed for the first time in this study to explore approaches to guide the development of a healthy and comfortable urban night-time environment.

Existing research and relevant lighting standards are analyzed and an evaluation model with a logical hierarchy is constructed by combining with the evaluation theory that is set based on people and the environment. The index weights were scientifically determined on the basis of the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation method. The rationality and validity of the proposed evaluation system is verified in accordance with field projects and case studies.

Taking into account traditional and cultural factors, the evaluation model established has an acceptable accuracy. Evaluation based on subjective-objective combination can provide a scientific basis for the management and optimization of night lighting.

The proposed evaluation system can serve as a guiding reference for other areas of cultural identity and esthetic perspective.

The purpose of this research is to present an integrated methodological framework to aid in performance stewardship of management institutions according to their strategies based on a holistic evaluation encompassing social, economic and environmental dimensions.

A Mamdani fuzzy inference system (FIS) approach was adopted to design the quantitative models with respect to balanced scorecard (BSC) perspectives to demonstrate dynamic capability. Individual models were developed for each perspective of BSC using Mamdani FIS. Data was collected from subject matter experts in management education.

The proposed methodology is able to successfully compute the scores for each perspective. Effective placement, teaching learning process, faculty development and systematic feedback from the stakeholders were found to be the key drivers for revenue generation. The model is validated as the results were well accepted by the head of the institution after implementation.

The model resulting from this study will assist the institution to cyclically assess its performance, thus enabling continuous improvement. The strategy map provides the causality of the objectives across the four perspectives to aid the practitioners to better strategize. Also this study contributes to the literature of BSC as well to the applications of multi-criteria decision-making (MCDM) techniques.

Mamdani FIS integrated BSC model is a significant contribution to the academia of management education to quantitatively compute the performance of institutions. This quantified model reduces the ambiguity for practitioners to decide the performance levels for each metric and the priorities of metrics.

This study aims to test the complaints of tourists who visit five-star hotels in Antalya, Turkey, on those same hotels’ websites.

In the study, the data were collected with qualitative methods but analyzed with the mixed analysis method. In this context, the authors collected 1,012 comments on the website between 2016 and 2019.

According to the results of the study, the most intense complaints were found to be concentrated in categories such as ambience, food and staff.

First of all, it is thought that it will make an important contribution to the literature, since different methodologies are adopted in the study. In addition, online shares, evaluations and comments produce positive or negative results for the destination or business in question. It is necessary to closely monitor such activities in electronic environments, as they may have negative consequences, thus revealing the need to take corrective or preventive measures. For this reason, the research is important in terms of not having such a large-scale study in the literature and contributing to the hospitality industry.