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The purpose of the study is to mainstream the disaster risk reduction (DRR) and disaster resilience measures into the GreenSL® building rating system in Sri Lanka to demonstrate a more holistic approach in achieving sustainability with resilience.

First, a comprehensive literature review was carried out on green building practices and rating tools, natural hazards and DRR and global and local frameworks. Next, criteria were developed incorporating the disaster resilience aspects through eight expert committee meetings and included the rating tool in three levels. Finally, 11 green-certified buildings from the Green Building Council of Sri Lanka were reevaluated using the new disaster resilient GREENSL® rating system for built environment as a validation for the new tool and to analyze the new certification levels.

All the green-certified buildings in hazard-prone areas dropped their certification by one level while the buildings in nonhazard-prone areas remained in the certification after being evaluated by the new DRR-incorporated rating system, which recommends the use of new tool for the buildings in hazard-prone areas. But due to the rapid changes in climate and the unpredictable trends of natural hazards, the use of new DRR incorporated GREENSL® rating system for built environment for the certification of buildings is highly endorsed.

This is the first research study based on the GREENSL rating system. And it is the first effort to incorporate DRR aspects to any rating tool in Sri Lanka. The projects that were evaluated for the validation of the new tool are the actual projects which obtained green building certification. Also, it is apparent that this study has gone some way towards enhancing the understanding of blending the sustainability and resilience in rating systems for built environment.

With the increasing demand for sustainable developments, higher education should focus on teaching both sustainable buildings and infrastructure systems. This study aims to investigate the existing sustainable infrastructure (SI) teaching efforts in sustainability courses; identify best practices to integrate SI throughout bachelor’s and master’s programs under the construction management (CM) curricula; and propose guidelines for students to obtain Envision sustainability professional (ENV SP) credential during sustainability education.

This study conducted keywords search within the sustainability course descriptions under the American Council for Construction Education accredited CM curricula to locate SI topics. Additionally, this research collected inputs from the Envision Academic Committee members to develop a matrix representing the best practices for integrating SI in higher education and provided a guide with a step-by-step procedure to obtain ENV SP credentials.

This study identified a gap regarding the availability of SI education and offered best practices on how CM curricula might nurture such knowledge. Phase I highlighted that only two CM programs taught infrastructure sustainability, and three programs offered sustainability credentialing processes under a bachelor’s degree. Phase II developed a framework that offered a variety of pedagogical approaches and outlined the process for obtaining the ENV SP certificate for CM students in the freshman, sophomore, junior and senior years.

The findings of this study can facilitate CM education to create awareness among the future workforce and encourage them to establish skills pertaining to the economic, social and environmental implications while designing SI.

BE2ST-In-Highways is a framework for assessing the social impact of reusing materials in pavement building, using the Pavement Life-Cycle Assessment Tool for Environmental and Economic Impacts (PaLATE) and life-cycle cost analysis (LCCA). ENVISION is a two-stage assessment method with four levels of certification: bronze award, silver award, gold award, and platinum award. Stantec published the Green Guide for Roads in 2008 as a marketing tool to highlight its commitment to sustainable development (SD), and the certification policy was created using the Leadership in Energy and Environmental Design (LEED) certification policy. As part of their first-year requirements, Stantec and a team of Worcester Polytechnic Institute students created another ‘Green Guide for Roads’ in 2009 to integrate previously missing components of the certification guidelines. GreenPave was developed by the Ontario Ministry of Transportation as an SD certification framework based on the Greenroads and GreenLITES SD certification frameworks. Specifications are classified into three types: repair activities, new development projects, and credit for evident and clear criteria. The Greenroads SD certification process reintroduces SD ideas into highway building by awarding points to projects that effectively integrate SD objectives. I-LAST is a tool developed by the Illinois Department of Transportation, American Consulting Engineers Council (ACEC), and Illinois Road and Transportation Builders Association (IRTBA) to analyse SD principles in road infrastructure building. INVEST (Infrastructure Voluntary Assessment Sustainability Tool) is designed to be simple to use and includes four stages of a project. Scorecards for pavement, basic rural, basic urban, extended rural, extended urban, and custom are included. CEEQUAL (Sustainability Assessment and Awards for Civil Engineering, Infrastructure, Landscaping, and the Public Realm) was established to improve infrastructure sustainability and award projects to organizations that address environmental concerns in a productive and effective manner. It is managed by CEEQUAL Ltd. and is based on three SD principles: environment, economics, and labelling the social component of SD with access. Customized scorecards may be used when a project does not fit into one of the pre-defined scorecards. The framework was initially created for the United Kingdom (UK) but has now been revised to be worldwide relevant and includes two categories of projects: domestic (UK and Ireland) projects and foreign initiatives. It also offers six project awards. This chapter reviewed frameworks, models, and guidelines for sustainable infrastructure projects, emphasizing the Be²st-In-Highway rating system, ENVISION certification policies, green guide for road rating systems, greenlights certification system or policy, Greenpaves rating system, Greenroads rating system, I-LAST certification tools, invest rating tools, CEEQUAL certification system, and stars rating tools.

In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

Construction education rarely addressed the importance of disseminating knowledge on infrastructure equity, thus impeding progress toward creating equitable and sustainable developments. This study aims to investigate the existing sustainability courses under the American Council for Construction Education (ACCE) accredited construction management (CM) programs to examine the integration of infrastructure equity topics and assess improvement in CM students’ knowledge and awareness to address this issue through an intervention.

To achieve these objectives, this research reviewed the sustainability course descriptions of the ACCE-accredited undergraduate and graduate CM curricula. Furthermore, the study implemented a workshop within a CM sustainability course that taught the students about the key concepts of infrastructure equity as well as how to address this issue by leveraging the Envision infrastructure rating system.

The course review results showed that most sustainability courses lack topics such as infrastructure equity and social sustainability. Moreover, the analysis of pre- and postworkshop surveys indicated that guided training could improve the students’ understanding as well as boost their confidence to address and mitigate infrastructure inequity issues.

The findings of the study are valuable for increasing awareness of infrastructure equity and facilitating the future construction workforce with the required expertise to develop equitable infrastructure systems.

The hygiene factor is always imperative when customers consider a certain restaurant, and the information contained in customer reviews can be an efficient approach to gauge a restaurant's hygiene during gaps in the official inspection. Therefore, the purpose of this study was to investigate whether information obtained from online reviews could predict the upcoming hygiene rating, specifically, evaluating the impact of both qualitative and quantitative content of reviews on the restaurant hygiene rating.

The quantitative research method with big data analytic techniques was applied in this study. In total, 127,656 pieces of data collected from 1,710 restaurants in four major cities in the USA were used in the analysis. Both quantitative factors (i.e. reviewer's numerical rating, days to review, readability, useful/funny/cool) and qualitative factors (i.e. eight emotional dimensions of textual reviews) were analyzed from the online customer reviews and considered in predicting the restaurant's hygiene rating.

Six out of eight emotional dimensions including anger, disgust, fear, sadness, surprise and trust were identified as having significant influences on the restaurant hygiene ratings. While three quantitative variables including days to review, readability and usefulness were identified with significant impacts on the dependent variable of restaurant hygiene rating.

This study opens an avenue for innovative research that establishes a connection between customers' reviews and restaurants' inspection systems. The results allow restaurants to predict an impending hygiene inspection rating upon dynamic assessment of review content and aid in adjusting hygiene measures accordingly.

The existing concept in the building rating scheme especially in developing countries was more focused on the environment, economic, social and culture. The new approach of the classroom condition index (CCI) assessment scheme has its uniqueness in environmental and social aspects because of high building performance in secondary school buildings. The requirements set by the Ministry of Education Malaysia include providing a conducive learning environment, especially for students who are considered as the main users of classrooms in school buildings. Currently, the school administration needs to manually record the condition of the classroom to increase its comfort level. The lack of a structured scheme for classroom assessment makes it difficult for school administration to focus on the overall classroom condition (physical environmental aspect) in the school building. The purpose of this study is to develop a framework for classroom conditions by proposing a CCI assessment scheme for a secondary school building in Malaysia.

Mixed methods were used to carry out the study. The first stage of this study concentrates on developing a system for CCI that relates to physical elements in the classroom. This is done by reviewing the literature on the classroom physical performance, as well as a comparison between several building rating systems locally and abroad. The structure of the proposed CCI scheme is grouped into four main themes, namely, space management quality (SMQ), building condition (BC), indoor environmental quality (IEQ) and teaching and learning quality (TLQ). In addition, there are 12 categories and 23 indicators listed under this theme. The second stage focuses on formulating assessment categories with their relevant performance indicators. This phase undergoes a validation process by conducting a survey (questionnaire) toward the classroom’s main users, which are students and teachers. This is to ensure the accuracy of classroom conditions in the school building. A semi-structured interview was also conducted among building experts. They are building surveyors, building engineers, building designers and building performance experts to support the main findings in the second stage. Relative importance (RI) index approach has been applied to show the indicators weighting and ranking are used as data collections method by using Statistical Package of Social Science software to examine the RI of each category and indicator, respectively.

The findings show that prominent RI and balanced weights are formed from these four main themes. They are SMQ (19.9%), BC (26.6%), IEQ (33.2%) and TLQ (20.3%). The outcome of this study will contribute to a detailed assessment scheme for CCI at the secondary school building. The contribution of the CCI Assessment Scheme is more comprehensive and holistic than the conventional assessment process for BCs. It focuses specifically on classroom space as it is the most important area to achieve a high level of comfort comparing to other spaces in the school building. This holistic approach encompasses all types of classrooms. The concept of one tool fits all is seen as no longer a relevant adaptation in this context. This proposed tool is to be used only for the classroom (as the name CCI implies) and it cannot be used for the other types of spaces, for instance, teacher room, library, meeting room, toilet, canteen and, etc. This is because different spaces represent different physical indicators to be classified. This, in turn, contributes to a conducive learning environment for students in the school.

This paper provides the current information, knowledge and findings related to the classroom physical indicators in developing the assessment scheme for the classroom environment. It will assist both technical and non-technical experts to clarify the current condition of classroom physical performance that ideally may affect the students’ learning environment. The novelty of CCI development is not only on the adopted method but it also includes the ideas on next generation model of rating system that ideally need specific indicators and weighting to be generated into an intelligent computerized system.

Over the years, public sector reforms in emerging economies have focused on improving national budget systems and financial management practices to promote sustainable development. In the context of the COVID-19 crisis, this article examines whether the strength or effectiveness of national budget systems and related financial management practices moderates the impact of fiscal policy measures on economic recovery and resilience.

The article uses bivariate correlations and difference-in-difference analyses to examine the relationship between budget system effectiveness, government stimulus measures and forecasts of economic recovery and resilience. The analysis uses data from the Public Expenditure and Financial Accountability (PEFA) program, International Monetary Fund (IMF) and World Bank.

The article finds that estimates of economic recovery and resilience are higher in countries with more reliable budget processes and more transparent public finances. Also, the strength or effectiveness of the budget system before the pandemic appears to moderate the impact of government stimulus measures on economic recovery and resilience over a medium-term forecast horizon.

This is a prospective analysis based on economic forecasts from the IMF, which are subject to change in the coming years. In addition, the analysis uses subjective budget system indicators, which present measurement challenges that often influence this area of research. Better comparative data in the future, for example, large administrative datasets, will enable researchers to explore these issues with less estimation bias.

The findings are relevant for policymakers and budget officials in developing countries in Africa who are engaged in plans to improve national budget systems and enhance resilience to crises, such as the COVID-19-induced economic crisis. The findings also have implications for developing countries beyond Africa with similar economic and fiscal conditions.

The findings have implications for economic and budgetary planning for the social sector as well as the efficient delivery of public services in developing countries. Public managers have a critical role to play in adapting national budget systems and financial management reforms within complex and evolving economic circumstances even after the coronavirus pandemic.

The authors use novel and latest data on country responses to the COVID-19 pandemic as well as medium-term economic forecasts to examine the relationship between national budget systems and post-pandemic economic recovery and resilience in the African context. Previous research has only addressed these issues in the context of industrialized countries, and a limited number of empirical studies examine these relationships. The findings also have significant value for policymakers outside Africa who are facing similar challenges related to the coronavirus pandemic.

The researchers analyzed factors affecting the adoption of the Leadership in Energy and Environmental Design (LEED) green-building certification system in Jordan, including financial performance of certified projects along with broader barriers that may impact developers’ interest in LEED.

The authors first reviewed online data for all LEED registered and certified projects in Jordan, recruited LEED-certified project stakeholders, collected documents related to LEED projects and conducted LEED category credit summaries, financial cost-benefit analyses and spot-checking reported values in local markets. The authors then visited projects sites and interviewed various project stakeholders to understand better stakeholders' decision-making processes concerning LEED and relevant factors (financial, branding, cultural, political, etc.).

Obtaining LEED certification in Jordan was financially feasible as evinced in both the quantitative analysis and interviews. However, the authors found that there was very limited interest in LEED among Jordanian developers. Barriers included widespread cynicism toward green building concepts as well as a lack of local expertise in installing and maintaining green technologies. To overcome these barriers, the authors recommend that green building initiatives place a greater emphasis on education and public-promotion activities.

The research data were limited to projects that had successfully achieved LEED certification. Broader qualitative research conducted across the Jordanian building community could provide additional insights, but such an investigation is beyond the scope of the current study.

The complexity of adapting a Western green building standard (LEED) to a non-Western context is discussed in detail. The findings suggest that understanding regional development challenges, local markets and cultural differences is vital for successfully implementing green building certification systems.

Given the importance of credit rating agencies’ (CRAs) assessment in affecting international financial markets, it is useful for policymakers and investors to be able to forecast it properly. Therefore, this study aims to forecast sovereign risk perception of the main agencies related to Brazilian bonds through the application of different machine learning (ML) techniques and evaluate their predictive accuracy in order to find out which one is best for this task.

Based on monthly data from January 1996 to November 2018, we perform different forecast analyses using the K-Nearest Neighbors, the Gradient Boosted Random Trees and the Multilayer Perceptron methods.

The results of this study suggest the Multilayer Perceptron technique is the most reliable one. Its predictive accuracy is relatively high if compared to the other two methods. Its forecast errors are the lowest in both the out-of-sample and in-sample forecasts’ exercises. These results hold if we consider the CRAs classification structure as linear or logarithmic. Moreover, its forecast errors are not statistically associated with periods of changes in CRAs’ opinion of any sort.

To the best of the authors’ knowledge, this study is the first to evaluate the performance of ML methods in the task of predicting sovereign credit news, including not only the sovereign ratings but also the outlook and credit watch status. In addition, the authors investigate whether the forecasts errors are statistically associated with periods of changes in sovereign risk perception.