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The building sector contributes one-third of the energy-related carbon dioxide globally. Therefore, framing appropriate energy-related policies for the next decades becomes essential in this scenario to realize the global net-zero goals. The purpose of the proposed study is to evaluate the impact of the widespread adoption of such guidelines in a building community in the context of mixed-mode buildings.

This study decentralizes the theme of improving the energy efficiency of the national building stock in parcels by proposing a community-based hybrid bottom-up modelling approach using urban building energy modelling (UBEM) techniques to analyze the effectiveness of the community-wide implementation of energy conservation guidelines.

In this study, the UBEM is developed and validated for the 14-building residential community in Mumbai, India, adopting the framework. Employing Energy Conservation Building Code (ECBC) compliance on the UBEM shows an energy use reduction potential of up to 15%. The results also reveal that ECBC compliance is more advantageous considering the effects of climate change.

In developing countries where the availability of existing building stock information is minimal, the proposed study formulates a holistic framework for developing a detailed UBEM for the residential building stock from scratch. A unique method of assessing the actual cooling load of the developed UBEM is presented. A thorough sensitivity analysis approach to investigate the effect of cooling space fraction on the energy consumption of the building stock is presented, which would assist in choosing the appropriate retrofit strategies. The proposed study's outcomes can significantly transform the formulation and validation of appropriate energy policies.

In order to solve the problems of difficulty in lending to family farms and the lack of credit products, it is necessary to classify the credit rating of family farms and determine the credit risk level of different family farms, so that agriculture-related financial institutions can implement different credit strategies.

A method based on BP neural network model is proposed to measure the weights of credit evaluation indicators of family farms and the linear weighting method and the fuzzy comprehensive evaluation method are used to establish the final credit rating system for family farms.

The empirical results show that the majority of the 246 family farms in Inner Mongolia have a low CC rating.

By constructing a sound and reasonable credit rating system for family farms, thus providing an objective evaluation of the credit rating of family farms, the credit granting status of agriculture-related financial institutions will be adapted to the reasonable loan demand status of family farm owners, and the quality and level of their credit approval will be continuously enhanced.

The purpose of this paper is to evaluate undergraduate student perceptions about the application of immersive technologies for enhancing the student learning experience. This study assesses the viewpoints of students from varying multidisciplinary backgrounds about whether immersive technologies can enhance their learning experience and increase their level of engagement in the context of higher educational delivery.

The research used a case study methodology adopting a questionnaire-based research mixed methods approach. In total, 83 participants completed the questionnaire. The purpose of the research was to evaluate and interpret students’ perspectives at higher educational level about the use of immersive technologies towards enhancing their learning experience. There was also a focus on remote educational delivery due to the legacy of COVID-19.

The findings suggest that there is still more empirical work to be undertaken regarding the application of immersive technologies in higher education. The study revealed that there are immersive benefits though preference for face-to-face teaching remains popular. The negative connotations associated with immersive technology use in higher education, (e.g. virtual reality), such as cost of equipment and motion sickness, substantiates the themes identified in the academic literature.

The study explores a diversity of immersive technologies and their application in higher education (HE) contexts. Findings indicate that although there are acknowledged pedagogical benefits of immersive technology use in HE prevalent barriers remain that require further empirical research if immersive technology use is to be universally used in the sector.

The study analysed the aerospace industry, a traditionally important sector for the topic of risk management, from three complementary perspectives: the supply chain risks present in the sector, the mitigation strategies adopted to face them, and the characteristics (dimensions) observed in the SCRM process of aerospace companies.

The research employed a quali–quantitative method: a survey was carried out, followed by interviews with professionals from companies belonging to different tiers of aerospace supply chains. Interviews helped to interpret the survey data and understand in more detail risk management in aerospace companies.

The study presents a panorama of the aerospace industry in terms of risk management. The sector’s turbulent environment is described as well as the strategies to prevent, minimise or postpone the impact of supply chain risks. In particular, ten dimensions that have been identified in the SCRM process of aerospace firms are discussed. These characteristics influence the objectives of this process and are related to resources, roles and responsibilities, incentives, development of competences and skills, scope (internal and external) and approaches to integrate decisions and actions in the context of the supply chain.

Articles that address the SCRM process usually focus on the process steps, whereas this study investigated dimensions that transcend these steps but whose discussion in the literature is still fragmented. It also analysed a reference sector for the topic from a broader perspective than others available in the literature (supply chain risks, mitigation strategies and characteristics of the SCRM process). Supply chain members with relationships with each other were investigated, a desirable approach for SCRM but still under-explored. The study also answers calls for industry-specific studies and research on emerging countries.

The purpose of this paper is to investigate and review the impact of the use of statistical quality control (SQC) development and analytical and numerical methods on average run length for econometric applications.

This study used several academic databases to survey and analyze the literature on SQC tools, their characteristics and applications. The surveys covered both parametric and nonparametric SQC.

This survey paper reviews the literature both control charts and methodology to evaluate an average run length (ARL) which the SQC charts can be applied to any data. Because of the nonparametric control chart is an alternative effective to standard control charts. The mixed nonparametric control chart can overcome the assumption of normality and independence. In addition, there are several analytical and numerical methods for determining the ARL, those of methods; Markov Chain, Martingales, Numerical Integral Equation and Explicit formulas which use less time consuming but accuracy. New ideas of mixed parametric and nonparametric control charts are effective alternatives for econometric applications.

In terms of mixed nonparametric control charts, this can be applied to all data which no limitation in using of the proposed control chart. In particular, the data consist of volatility and fluctuation usually occurred in econometric solutions. Furthermore, to find the ARL as a performance measure, an explicit formula for the ARL of time series data can be derived using the integral equation and its accuracy can be verified using the numerical integral equation.

It is no news that Chinese construction companies are highly motivated to invest in Africa in terms of infrastructure and construction. This influx from the beginning of the millennium marked a game-changer for infrastructural development in most African countries. This study, therefore, explores how the partnership between China and Africa has impacted the construction industry in Africa with a focus on Nigeria.

A quantitative approach was adapted for the study, which is descriptive in nature, and the primary participants of the study were core construction professionals within the Nigerian construction industry. Data was collected via a structured questionnaire, and multivariate statistics was used to analyse the data.

The study results revealed that the benefits accrued from Chinese participation in the African construction industry can be classified into three distinct categories: socio-economic development through construction, land transportation system development and construction industry development. The study further revealed that Chinese involvement has been most beneficial to the development of the land transportation system in Nigeria with more investment in the construction and maintenance of roads and railways.

The study will serve as a basis for making informed future decisions on Chinese participation in the Nigerian construction industry as it exposes the impacts of the relationship within the current system. The outcome of this study can be used to refocus the partnership to ensure the optimum development of the local construction industry. The government and other relevant agencies can use the findings from this study to ensure that there is sustainable growth in the local construction industry through Chinese participation.

This research aims to examine the time-varying behavior of the Weekend, Turn-of-the-Month, January, and Halloween effects in eight foreign exchange rates against the U.S. dollar from the Adaptive Market Hypothesis (AMH) perspective. It also explores whether these anomalies can generate excess returns compared to a buy-and-hold strategy.

Using daily return data from January 2004 to December 2023 in a rolling-window framework, the study employs the Concordance Coefficient test and AR-GARCH models to assess the time-varying behavior of four calendar anomalies. It also assesses the statistical significance of the trading strategies implied by these anomalies using t-tests and applies F-tests for subperiod analysis.

The results reveal a generalized time-varying presence of calendar anomalies in emerging currencies and, to a lesser extent, developed currencies. However, the trading strategies implied by these anomalies generally did not show statistical significance, except for the Turn-of-the-Month effect, which exhibited statistically significant unprofitability.

The study pioneers an analysis of five calendar anomalies across various currencies from the standpoint of the AMH and proposes case-specific explanations for their occurrence. It also examines the potential for the anomalies’ implied trading strategies to generate excess returns compared to a straightforward buy-and-hold strategy. Additionally, the study introduces the recently developed Concordance Coefficient test as a valuable alternative to other non-parametric methods.

This study aims to examine whether inmate’s social support network is related to changes in anthropometric data among individuals in Canadian correctional facilities.

Methods: A total of 754 participants in federal correctional facilities who had been incarcerated for at least six months responded to the questionnaire by interview regarding their social support network. Chi-square tests and non-parametric tests for median comparison were used to measure changes in anthropometric data [weight and body mass index (BMI)] between the date of admission into custody and the date of the interview. Subsequently, a multivariate regression analysis for BMI change was conducted to adjust for covariates such as sex, age and ethnicity.

Results: Participants who received more than two visits per month had significantly lower weight gain (2.6 kg) than those who received less than one visit per month (7.1 kg, p = 0.02). Similar results were observed for the average change in BMI (p = 0.01). The influence of an external social support network on BMI change remained significant after adjusting for covariates. Conclusions: An individual's external social support network (outside the prison environment) may protect against weight gain in correctional facilities. Given how social support will vary based on the prison context by country and jurisdiction, individual and organizational strategies should be considered to maintain a healthy social support network and increase the number of visits (at every stage of incarceration) to counteract this weight gain and its adverse health consequences.

The social support network outside the prison environment may protect against weight gain in correctional facilities. Strategies should be considered to maintain a healthy social support network and increase the number of visits to counteract this weight gain and its adverse health consequences.

The paper aims at addressing the following research questions: does institutional quality improve countries' environmental efficiency? And which pillars of institutional quality improve countries' environmental efficiency?

By specifying a directional distance function in the context of stochastic frontier method where GHG emissions are considered as the bad output and the GDP is referred as the desirable one, the work computes the environmental efficiency into the appraisal of a production function for the European countries over three decades.

According to the countries' performance, the findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries. In this environmental context, the role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries.

This article attempts to analyze the role of different dimensions of institutional quality in different European countries' performance – in terms of mitigating GHGs (undesirable output) – while trying to raise their economic performance through their GDP (desirable output).

1. The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

2. We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

3. The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

4. The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

The paper aims at addressing the following research question: does institutional quality improve countries' environmental efficiency?

We adopt a directional distance function in the context of stochastic frontier method, considering 40 European economies over a 30-year time interval.

The findings confirm that high and upper middle-income countries have higher environmental efficiency compared to low middle-income countries.

The role of institutional quality turns out to be really important in improving the environmental efficiency for high income countries, while the performance decreases for the low middle-income countries.

This study examined brand hate within the context of the (German) Bundesliga and (Australian) National Rugby League (NRL). The study pursued two research questions: (1) What types of brand hate were expressed towards the Bundesliga and the NRL? (2) To what extent did hateful comments attract more likes than non-hateful comments?

Brand hate was studied in the context of competition restrictions in 2020 due to the Covid-19 pandemic. We analysed reader comments posted below online articles published in three German (119 articles and 8,975 comments) and three Australian online newspaper articles (116 articles and 4,858 reader comments). The data were analysed deductively.

Non-parametric tests found that all types of brand hate were expressed. Approximately 85% of the hateful comments were mild, or more specifically, cold (n = 445 or approximately 53%), or cool (n = 250 or approximately 30%), or hot (n = 20 or approximately 2%). Hateful comments attracted more likes than non-hateful comments.

This study advances our understanding of how negative brand perceptions underpin an extreme negative emotional reaction in the form of brand hate. The empirical evidence enables brand managers to better address disgusted, angry, or contemptuous consumers (or stakeholders) and consider whether the feeling is enduring, strong or weak, and linked to either aggressive or passive behaviours.