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Organizational Behavior Attributes and Sustainable Construction Adoption: An Econometric Analysis Using Data from Qatar
Abstract
Despite the efforts of governments to promote sustainable construction practices, the decision to adopt sustainability practices largely falls upon the firms involved in construction projects. This paper presents an econometric model that describes the relationship between the level of sustainability experience a firm possesses and its characteristics and behavioral attributes. Data for this research were collected in Qatar by means of a survey as part of a study that aimed to analyze the triggers of sustainability adoption in the Qatari construction market. The presented model showed that a number of behavioral attributes of firms, besides their origin and the average size of projects they undertake, determine the level of sustainability experience these firms might have. Examples include firms' risk-taking tendencies, their claimed competitive advantages, and their previous history of introducing changes to their modus operandi. This research adds to the body of knowledge on sustainable construction by studying its adoption from an organizational behavior perspective that focuses on factors internal to the firms. This complements existing literature that studies external triggers such as governmental policies.
... They are however also one of the major contributors to greenhouse gas emissions and other environmental pollutants in both industrialized and developing countries (Kientzel and Kok, 2011). As such, sustainable construction practices have attracted significant interest in developed countries and more so in some developing countries (Hassan et al., 2016). Indeed, a recent report revealed that emerging economies have experienced a strong green building (GB) growth, expecting to grow two to six times over current levels in the next three years (Dodge Data & Analytics, 2016). ...
... Among the various practitioner-related factors -related knowledge has been consistently identified by many researchers as critical. This criticality stems from the fact that, in spite of the governmental efforts, the decision to implement sustainable practices majorly depended on project parties, including owners, designers, and contractors (Hassan et al., 2016). Thus, their GB-related knowledge can significantly shape the practices and outcome of GB projects. ...
Unlike it is in the developed world, green buildings (GBs) have been a relatively new concept in emerging markets. In Vietnam for example, local green building rating systems, such as LOTUS was first released in 2010 by Vietnam Green Building Council (VGBC); and Excellence in Design for Greater Efficiencies (EDGE) was introduced in 2015 is still limited. Given this slow development in GBs, uncertified regular buildings are still dominant in Vietnam, contributing to substantial energy use and pollution. To reduce emissions and improve energy efficiency, it is thus essential to embed sustainable design and construction practices in uncertified regular buildings. As the first step sustainable practices in regular building projects. In particular, a questionnaire survey was conducted to-related knowledge and project roles affect the extent to which various sustainable practices were implemented in building projects in Vietnam. Statistical analysis showed that the degree of-related knowledge. moderated the relationships between their GB-related knowledge and the application of sustainable practices. Specifically, this relationship was most significant for owner representatives, followed by designers and constructors. These findings imply that practitioners, especially those working for owners and designers, should be equipped with adequate GB knowledge to advance sustainable building practices in fast-growing emerging economies.
... Buildings also consume 30-40% of all primary energy and account for 16% of annual water usage worldwide (Lippiatt 1999;Robichaud and Anantatmula 2011). As such, many governments have become focused on ways to embed sustainable building (SB) practices during construction, particularly in developing countries (Hassan et al. 2016). For example, most emerging economies are currently experiencing significant green building (GB) growth, and this trend is expected to increase by two to six times in the next 3 years (Dodge Data and Analytics 2016). ...
... Second, it is well established in the literature that participants' roles (such as project owners, project managers, and project team members) will have various levels of influence over project practices (Wu et al. 2015). Decisions regarding whether and how to implement SB practices lie heavily with project owners and designers, as opposed to project team members (Hassan et al. 2016). However, despite this role-dependent influence over project practices, the literature has largely not explored how different participants' roles may moderate the relationship between their personal characteristics (prior experience and GB-related knowledge) and SB practices. ...
The slow development of green building (GB) practices in emerging economies has resulted in these countries remaining dominated by uncertified conventional buildings, which has caused negative environmental impacts (e.g., energy consumption and pollution). Using a mixed-research method, this study examined the interactive effect of participants’ characteristics (experience, knowledge, and roles) on sustainable building (SB) practices in conventional buildings in Vietnam—a fast-growing emerging market. Empirical data collected from qualitative (Study 1) and quantitative (Study 2) studies revealed that participants’ GB-related knowledge—especially owner representatives’ and designers’ knowledge—positively affected the extent of SB practices. However, participants’ industry experience was found to be a hindrance, which may be due to lack of motivation (e.g., weighting the benefits and extra effort required) for behavioral changes. These findings suggest the need to provide GB-related training to experienced practitioners and owner and designer representatives to enhance their knowledge and willingness to adopt SB practices. This study contributes to the sustainable construction literature by providing empirical evidence of the influence of project participants’ characteristics on SB practices.
... Recently, the number of GBs grown significantly worldwide owing to governments having implemented measures to improve sustainable development, especially not only in developed countries but also in developing countries (Hassan et al., 2016). The benefits of GBs are gaining attention from both industry practitioners and academics in developing countries (Chua and Oh, 2011). ...
Green Buildings (GB) have been continuing to grow in line with the sustainability trend worldwide. However, GB projects frequently involve more risks than conventional projects due to their adoption of innovative sustainability technology. Consequently, risk management (RM) is more complicated and necessary for GB projects compared with conventional projects, especially in developing countries with few GB risk studies. As a first effort, this research aimed to explore risk factors that GB projects frequently confront in Vietnam. First, the 53 risk factors were identified by reviewing previous studies and interviewing industry professionals. A questionnaire was then developed to collect data from 207 construction professionals to assess the importance of GB risk factors. The result provided a ranking list of GB risks and their corresponding evaluations. Next, exploratory factor analysis was conducted and revealed the six most influential risk components: (1) human resource and technical risk in the construction phase, (2) performance risk in the operation phase, (3) human resource risk in the design phase, (4) financial risk, (5) regulation and complexity risk, and (6) material risk. Also, this research found no differences in risk preferences among various roles in GB projects. These findings provided insight into GB risks that can be useful for practitioners and future research. The final contribution included discussions on critical risks and suggestions for further research directions.
... Recently, there has been noteworthy development of GBs worldwide. Notably, GBs have also received attention in emerging economies [4]. According to the previous research, several developing countries had a significant GB development recently, and this was anticipated to grow quicker in the near future [5]. ...
In line with the sustainable trend in the construction industry worldwide, there have been a number of studies that examined risks in Green Building (GB) projects recently. This study aimed to assess risk factors that GB projects often face through a questionnaire survey with 69 GB practitioners in Vietnam. Notably, this study evaluated GB risk factors according to three features: likelihood occurrence, the magnitude of impact, and risk controllability. The results indicated the top five crucial risks are “Owners lacks determination”; “Lack of experience of designers about GB”; “Project managers lack experience in GB projects”; “Underestimation of initial investment cost”; and “Project managers lack design management experience”. This paper could be a helpful reference for the construction industry by providing a profoundly assessing GB projects’ risks. Additionally, this study contributes empirical research of risk assessment in GB projects in Vietnam. Therefore, this study may contribute to the development of sustainable trends in the construction industry worldwide.
... The last several years have witnessed significant growth in the development of GBs over the world. As such, sustainable construction practices have attracted considerable interest over the world and, more so in some developing countries [4]. A recent report also revealed that emerging economies experienced a strong GB growth, and this was expected to grow faster in the forthcoming years [5]. ...
In recent years there has been significant interest in investigating risks linked to the implementation of Green Building (GB) projects that are in line with the developing trend of sustainable construction over the world. In an attempt to contribute to GB risks literature, this study explored risk factors that GB projects frequently confront in Vietnam. This study firstly conducted a comprehensive literature review to generate a preliminary list of risk factors. These risk factors were then confirmed and complemented by interviewing ten experts in the field. After that, the research assessed the risk factors by surveying 119 construction professionals to discover the most critical GB risks. Notably, this paper considered the effect on the risk assessment process of GB experience and project roles. Results showed that “The owner lacks determination,” “Late involvement of GB consultants,” and “Project evaluation result did not reach the expected GB standard” were the top three critical risks in GB projects. The statistical analysis also revealed that the assessment of GB risk negatively correlated with participants’ GB practical experience. Furthermore, hierarchical moderated regression analysis exposed differences in the risk assessment between various project roles, though these differences were relatively small and not statistically significant. By investigating GB projects’ main risks, this paper may become a useful reference guide within the construction sector. This research also enriches the literature by contributing empirical evidence of risk assessment in GB projects in a developing country.
... sebagaimana ditunjukkan pada Gambar 4 menunjukkan bahwa kegiatan sosialisasi dan pendampingan penyusunan desain bangunan yang menerapkan konsep dan kriteria green building memberikan peningkatan pemahaman yang cukup signifikan bagi para pesertanya. Peserta sosialisasi dan pendampingan penyusunan desain bangunan secara umum memiliki peningkatan pemahaman terhadap konsep dan kriteria green building, yang meliputi (1) kriteria pemilihan tapak bangunan, (2) kriteria konservasi energi, (3) konservasi air,(4) ...
Pekerjaan konstruksi memiliki dampak yang signifikan terhadap aspek lingkungan. Dibutuhkan upaya untuk meminimalkan dampak negatif dari pekerjaan konstruksi terhadap penurunan kondisi lingkungan secara global. Salah satu upaya adalah dengan menerapkan desain bangunan yang memenuhi kriteria green building. Konsep green building bertujuan untuk mengurangi atau menghilangkan dampak negatif serta memberikan dampak positif bagi iklim dan lingkungan, baik dalam fase desain, konstruksi, maupun operasional bangunan. Hingga saat ini, pelaksanaan pekerjaan konstruksi bangunan pada umumnya masih belum sepenuhnya menerapkan konsep green building, karena pemilik proyek, perencana, dan pelaksana konstruksi masih belum memahami konsep green building secara komprehensif, sehingga upaya mencapai pembangunan bangunan ramah lingkungan sulit untuk dicapai. Mengingat pekerjaan konstruksi bangunan gedung dan fasilitas infrastruktur yang terus meningkat secara global, maka penyuluhan dan sosialisasi mengenai konsep green building kepada pihak-pihak yang terlibat di dalam proyek konstruksi sangat dibutuhkan. Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan pemahaman developer, konsultan, dan kontraktor terhadap konsep desain bangunan yang menerapkan kriteria green building. Kegiatan pengabdian ini dilaksanakan dalam bentuk sosialisasi dan pendampingan penyusunan desain bangunan. Melalui kegiatan ini, terdapat peningkatan pemahaman dari perwakilan developer, konsultan, dan kontraktor terhadap konsep green building. Kegiatan ini diharapkan berkontribusi positif terhadap praktek konstruksi berkelanjutan
... This objective can be achieved by having a rating system with specific criteria as a measurement tool for an operational road. However, most rating systems are widely utilized to assess the sustainability of vertical development, such as buildings [6,7]. Although many agencies have established their very own rating system for infrastructure development, particularly in road facilities, it still lacks in the operation and maintenance phase. ...
Green Rating System is utilized as tools to analyze the sustainability of buildings or infrastructures. Improvising green rating system is a continuous effort due to the needs of local implementation of a country. In Malaysia, there are two established rating systems for roads; MyGHI for highways and pHJKR (Roads) for non-tolled roads. Preliminary study on pHJKR (Roads) identified this rating tool assess road sustainability performance only at planning, design & construction stages. This study foresees, it is essential to sustain its engineering and sustainability performance, including carbon assessment under Operation and Maintenance (O&M). Therefore, this paper highlights the relevance and applicability of pHJKR (Roads) in comparison to other establish green road rating tools. The assessment criteria and elements during (O&M) phase are proposed for score development, which extensive research will lead to the establishment of O&M pHJKR (Roads). The data was gathered and analysed from a comprehensive review of current pHJKR (Roads) with a comparison other green road rating index. The expert panel discussion also was utilized to determine suitable sustainability factors. This study, in conclusion providing an opportunity to the enhancement of pHJKR (Roads), which offer a complete cycle of assessment in road project development of road Green Rating System
... The ordered probit modeling framework was selected due to the ordinal nature of the response data (Washington et al. 2010). The probit model has been successfully applied to survey data (Kaiser and Spitz 2000;Senik 2005;Anastasopoulos et al. 2012;Hassan et al. 2016;Anderson et al. 2018), as well as to other forms of ordinal data related to transportation safety (Al-Bdairi and Hernandez 2017; Islam and Hernandez 2013). ...
The construction industry in the United States employs thousands of workers in various jobs and accounted for over $645 billion of the US Gross Domestic Product in 2017. Given the reported labor shortage, it has never been more important for the construction industry to have a qualified and motivated workforce. To do so, the industry needs to understand the current status of occupational rewards and how they are being perceived by construction workers. This paper describes research that aims to address this issue by investigating workers' perspectives of occupational rewards in the construction industry. The study utilizes responses from 176 construction workers across different states, different job responsibilities, and different work conditions. The research contributes to the construction industry by providing a unique perspective on occupational rewards through the lens of construction workers. The study identifies the rewards that are available to workers, rewards that are needed by workers, and factors that impact workers' reward satisfaction. By understanding these three aspects of occupational rewards, the industry will have a better chance of attracting and retaining the right workers for the job and motivating the available workforce for the allocated tasks. The study also contributes to the body of knowledge by facilitating a new and holistic view of rewards and the factors influencing rewards in construction. Findings from the research indicate that workers in general, are satisfied with the rewards that they are receiving, where job responsibility was found to be the reward that is received the most. However, workers' needs showed a commonality of financial importance. Furthermore, reward satisfaction was found to be influenced by 11 factors, 8 of which are occupational, and 3 sociodemographic factors.
... Gonzalez and Navarro (2006) affirmed that the suitable selection of materials can mitigate CO2 emission. Hassan et al. (2016) argued that governments need to focus on ways to embed sustainable practices during construction, particularly in developing countries. Vietnam, an emerging economy, has experienced the fastest economic development since 1990s (World Bank 2016), meaning that in the last decades, there was a significant growth of new projects. ...
In the construction industry of developing countries, the term sustainability has still not been adequately perceived. These countries are trying to overcome barriers to sustainable construction. In this study, managerial perceptions at various levels on main barriers to sustainable construction: firm level and project level, will be analysed. A questionnaire was developed and distributed to respondents in Vietnam to collect data. First, barriers are ranked based on their mean. Kendall test affirmed that a consistency of responses given by both directors and project managers significantly exists regarding the barriers. Moreover, Mann–Whitney U test proved there are no statistically significant differences among these two groups responding to the five main barriers. Through statistical analyses, the study identified the five most significant barriers, namely incompetence of project managers, limited sustainable materials and technologies, maintaining the current practice and resisting the change towards sustainability, lack of government incentives, and low implementation level of sustainable practices. From the findings, measures are also given to help stakeholders, especially directors and project managers, initially overcome the most significant barriers as well as gradually acquaint with the sustainable construction concept in developing countries.
... A recent research analyzing econometric data from Qatar identified characteristics and organizational behavior attributes for Sustainable Construction Adoption. The factors internal to the firms like their risk taking tendencies, claimed competitive advantages or history of changes in modus operandi etc were reflected (Hassan, Kandil, Senouci, & Al-Derham, 2016). The problem of CM selection for sustainability involves Economic, Environmental and Social criteria out of which, some can be measured quantitatively and some can be estimated qualitatively. ...
A big challenge in sustainable projects is selection of appropriate construction method and is considered to be the decisive factor for its success. Many environment friendly prefabricated elements are entering into the market at an increasing pace. This has increased the workload and inquisitiveness of the stakeholders who will need information about their environmental, technical and aesthetic aspects. The use of Prefabrication in Sustainable Construction is advantageous but appropriate decision criteria and their weightage for applicability assessments for a project from every stakeholder’s perspective is found to be deficient. Decisions to use prefabricated elements are still largely based on anecdotal evidence or cost-based evaluation rather than holistic sustainable performance. But authenticated information is seldom available and suitability within the project requirements is always debatable. Environmental decisions, being closely coupled with society’s built-in uncertainties and risks, are uncertain since ecological systems as well as social systems change in the future. Thus the selection of a suitable Construction Method has been perceived as a multi-criteria decision-making problem highly intensive in knowledge with partial information and uncertainty. This knowledge or perception base from the minds of experts has to be collected and processed for a decision. Fuzzy synthetic evaluation method using Analytic Hierarchy Process by Saaty has been adopted to provide an analytical tool to evaluate the applicability of Prefabricated or on-site Construction Method.
Purpose
Risks in implementing green building (GB) projects have emerged as a significant obstacle for GB development, especially in developing countries. In recent years, both academics and construction practitioners have paid considerable attention to the risks associated with GB. In this study, the authors aimed to create a comprehensive risk assessment model that considers three crucial risk features: impact level, probability of occurrence and risk manageability.
Design/methodology/approach
In the research, authors adopted the mean scoring and fuzzy synthetic evaluation method to assess GB risks. Based on expert assessments, this model can determine the significance of risk factors, risk groups and overall risk. Notably, this research applied the proposed model to assess GB risks in Vietnam by surveying 58 GB experienced professionals.
Findings
The findings revealed that GB risks are relatively high in Vietnam, implying that risk management is essential for GB projects to succeed. The results also showed that “lack of experience of GB designers” is the most critical factor, and “human resources risk in the design phase” is the top crucial risk group.
Originality/value
This study contributes a novel and practical model to help practitioners assess risks in GB projects. In addition, this research offers detailed GB risk evaluations in Vietnam and thus could be a valuable reference for construction practitioners and future studies.
Purpose: This paper seeks to explore the effect of emotions on sustainable purchasing in Arab countries, mainly Qatar and Egypt. Design/methodology/approach: The current investigation will empirically examine the effects of self-conscious emotions (private and public) on consumers' ‗green' purchasing behavior and test whether these actions are mediated by the following emotions: empathy, pride, and guilt. An online self-report survey was employed to collect data from 234 students and faculty members who are affiliated with Qatar University (Qatar) and Tanta University (Egypt). A Confirmatory Factor Analysis (CFA) was used to determine what factors directly and indirectly influence one's Willingness To Pay (WTP) for sustainable products. Findings: The results showed that private self-consciousness was significantly related to feelings of pride, while public self-consciousness was more closely associated with empathy. Feelings of guilt and pride were more likely to encourage participants to pay greater for sustainable products and services. Originality/value: The link between emotions and sustainable purchasing remains novel in Arab countries. Previous research has found that having ethical awareness toward sustainable purchasing does not amount to purchasing ‗green' products. This will be the first study to explore the impact emotions can have on sustainable purchasing.
This paper examines the factors that affect carbon emissions based on the panel data for 9 western provinces in China over the period 1990–2009. Our empirical results show that the output size, industrial structure and energy consumption structure are the main factors affecting carbon emissions, and the income level has a negative effect to carbon emissions. Some policy implications of the empirical results have finally been proposed
This paper analyzed the econometric relationship between the urbanization and energy consumption from 1990 to 2010 in China with the co-integration theory and the error correction model. The results show that there is a long-term equilibrium relationship between urbanization and the total energy consumption, which has an effect of short-term adjustment. Urbanization has different effects on the consumption of coal, natural gas and electricity. Besides, the improvement of the urbanization level can lead to the increase of energy consumption in the short term. However, the energy efficiency can be improved in the long term due to the readjustment of the industrial structure and the promotion of energy-saving technologies. Therefore, the establishment of resource-saving urbanization model will help to reduce energy consumption under the current condition.
An analysis is made of private sector construction demand (quarterly new orders) grouped into housing, commercial and industrial construction respectively, and their relationship with a priori selected leading indicators of GNP, price level, real interest rate, unemployment and manufacturing profitability over the period 1974 to 1988. The results indicate that different variables explain the trends in these private sector construction demand sub-sectors. While construction price appeared to be an important elastic influence in housing investment, it was not found to be an important factor in respect to commercial and industrial construction. Trends in commercial and industrial constructions are explained by manufacturing profitability and economic conditions. The level of unemployment influences commercial construction only and with a negative inelastic relationship. Lead indicator forecasts of the groupings of private sector investment are above 10 percent of accuracy due to the unusual deep cut in private construction as a result of the recession although the models except increasing trends in these series. The implication of this level of accuracy is the need to investigate further variables for inclusion in the models to track the cut in private sectorial construction demand. This work is currently being undertaken at the University of Salford through the financial support of the Science and Engineering Research Council.
This textbook provides an introduction to econometrics through a grounding in probability theory and statistical inference. The emphasis is on the concepts and ideas underlying probability theory and statistical inference, and on motivating the learning of them both at a formal and an intuitive level. It encourages the mastering of fundamental concepts and theoretical perspectives which guide the formulation and solution of problems in econometric modelling. This makes it an ideal introduction to empirical econometric modelling and the more advanced econometric literature. It is recommended for use on courses giving students a thorough grounding in econometrics at undergraduate or graduate level.
Modern buildings rival automobiles and factories as sources of harm to the environment today, contributing to deforestation, air and water pollution, stratospheric ozone depletion, and the risk of global warming. Many also make their occupants ill through "sick building syndrome'. This paper documents how a variety of traditional design solutions and advanced technologies - from earthen materials to efficient lights - can cost-effectively eliminate almost all of the damage done by modern buildings, while preserving the comfort and amenities that people expect from them. It also explains how structures with fewer environmental and health problems make better places to work and live, translating into higher worker productivity and home values. The large gap between cost-effective potential and current reality suggests that the biggest challenge in improving buildings lies in changing how the building industry itself works. -from Authors
The construction cost index (CCI), which has been published monthly in the United States by Engineering News-Record (ENR), is subject to significant variations. These variations are problematic for cost estimation, bid preparation, and investment planning. The accurate prediction of CCI can be invaluable for cost estimation and budgeting of capital projects, and can result in accurate bids. The research objective of this paper is to create appropriate multivariate time series models for forecasting CCI based on a group of explanatory variables that are identified by using Granger causality tests. The results of cointegration tests recommend vector error correction (VEC) models as the proper type of multivariate time series models to forecast CCI. Several VEC models are created and compared with existing univariate time series models for forecasting CCI. It is shown that the CCI predicted by these VEC models is more accurate than that predicted by the previously proposed univariate models (i.e.,seasonal autoregressive integrated mean-average and Holt-Winters exponential smoothing). The comparisons are based on two typical error measures: mean absolute prediction error and mean squared error. The primary contribution of this research to the body of knowledge is the creation of multivariate time series models that are more accurate than the current univariate time series models for forecasting CCI. It is expected that this work will contribute to the construction engineering and management community by helping cost engineers and capital planners prepare more accurate bids, cost estimates, and budgets for capital projects.
In the wake of sustainable construction entering the mainstream, many developing countries are either currently pursuing green building guidelines or are planning to pursue them in the near future. This research attempts to formulate an implementation strategy for the rapid adoption of these guidelines for the developing nations. This implementation strategy is based on the detailed review of the major green building guidelines globally and contextual information of Indian society collected through a survey questionnaire. The proposed strategy shows that it is important for green building initiatives to identify: the organizations that accelerate the adoption of green building guidelines in a society, the incentives and barriers associated with the green building guidelines, and the necessary motivations for the adopter organizations. An informed approach in the form of this implementation strategy might potentially contribute to the acceleration of green building guidelines' adoption in developing countries.
The Building for Environmental and Economic Sustainability (BEES) tool implements a rational, systematic technique for selecting cost-effective green building products. The technique is based on consensus standards and designed to be practical, flexible, and transparent. The Windows-based decision support software, aimed at designers, builders, and product manufacturers, includes actual environmental and economic performance data for 24 building products across a range of functional applications. BEES measures the environmental performance of building products using the environmental life-cycle assessment approach specified in the latest versions of ISO 14000 draft standards. The approach is based on the belief that all stages in the life of a product generate environmental impacts and must be analyzed. The stages include raw material acquisition, manufacture, transportation, installation, use, and waste management. Economic performance is measured using the ASTM standard life-cycle cost method. The technique includes the costs over a given study period of initial investment, replacement, operation, maintenance and repair, and disposal. Environmental and economic performance are combined into an overall performance measure using the ASTM standard for multiattribute decision analysis.
Preface
Introduction
Transportation is integral to developed societies. It is responsible for personal mobility which includes access to services, goods, and leisure. It is also a key element in the delivery of consumer goods. Regional, state, national, and the world economy rely upon the efficient and safe functioning of transportation facilities.
In addition to the sweeping influence transportation has on economic and social aspects of modern society, transportation issues pose challenges to professionals across a wide range of disciplines including transportation engineers, urban and regional planners, economists, logisticians, systems and safety engineers, social scientists, law enforcement and security professionals, and consumer theorists. Where to place and expand transportation infrastructure, how to safely and efficiently operate and maintain infrastructure, and how to spend valuable resources to improve mobility, access to goods, services and healthcare, are among the decisions made routinely by transportation-related professionals.
Many transportation-related problems and challenges involve stochastic processes that are influenced by observed and unobserved factors in unknown ways. The stochastic nature of these problems is largely a result of the role that people play in transportation. Transportation-system users are routinely faced with decisions in contexts such as what transportation mode to use, which vehicle to purchase, whether or not to participate in a vanpool or telecommute, where to relocate a business, whether or not to support a proposed light-rail project and whether to utilize traveler information before or during a trip. These decisions involve various degrees of uncertainty. Transportation-system managers and governmental agencies face similar stochastic problems in determining how to measure and compare system measures of performance, where to invest in safety improvements, how to efficiently operate transportation systems and how to estimate transportation demand. As a result of the complexity, diversity, and stochastic nature of transportation problems, the methodological toolbox required of the transportation analyst must be broad.
Approach
The third edition of Statistical and Econometric Methods offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics, to address reader and reviewer comments on the first and second editions, and to provide an increasing range of examples and corresponding data sets.
This book describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. Every book must strike an appropriate balance between depth and breadth of theory and applications, given the intended audience. This book targets two general audiences. First, it can serve as a textbook for advanced undergraduate, Masters, and Ph.D. students in transportation-related disciplines including engineering, economics, urban and regional planning, and sociology. There is sufficient material to cover two 3-unit semester courses in statistical and econometric methods. Alternatively, a one semester course could consist of a subset of topics covered in this book. The publisher’s web-site contains the numerous datasets used to develop the examples in this book so that readers can use them to reinforce the modeling techniques discussed throughout the text. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems. It provides a wide breadth of examples and case studies, covering applications in various aspects of transportation planning, engineering, safety, and economics. Sufficient analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications.
Data-Driven Methods vs. Statistical and Econometric Methods
In the analysis of transportation data, four general methodological approaches have become widely applied: data-driven methods, traditional statistical methods, heterogeneity models, and causal inference models (the latter three of which fall into the category of statistical and econometric methods and are covered in this text). Each of these methods have an implicit trade-off between practical prediction accuracy and their ability to uncover underlying causality. Data-driven methods include a wide range of techniques including those relating to data mining, artificial intelligence, machine learning, neural networks, support vector machines, and others. Such methods have the potential to handle extremely large amounts of data and provide a high level of prediction accuracy. On the down side, such methods may not necessarily provide insights into underlying causality (truly understanding the effects of specific factors on accident likelihoods and their resulting injury probabilities). Traditional statistical methods provide reasonable predictive capability and some insight into causality, but they are eclipsed in both prediction and providing causal insights by other approaches Heterogeneity models extend traditional statistical and econometric methods to account for potential unobserved heterogeneity (unobserved factors that may be influencing the process of interest). Causal-inference models use statistical and econometric methods to focus on underlying causality, often sacrificing predictive capability to do so.
Even though data-driven methods are often a viable alternative to the analysis of transportation data if one is interested solely in prediction and not interested in uncovering causal effects, because the focus of this book is uncovering issues of causality using statistical and econometric methods, data-driven methods are not covered.
Chapter topics and organization
Part I of the book provides statistical fundamentals (Chapters 1 and 2). This portion of the book is useful for refreshing fundamentals and sufficiently preparing students for the following sections. This portion of the book is targeted for students who have taken a basic statistics course but have since forgotten many of the fundamentals and need a review.
Part II of the book presents continuous dependent variable models. The chapter on linear regression (Chapter 3) devotes additional pages to introduce common modeling practice—examining residuals, creating indicator variables, and building statistical models—and thus serves as a logical starting chapter for readers new to statistical modeling. The subsection on Tobit and censored regressions is new to the second edition. Chapter 4 discusses the impacts of failing to meet linear regression assumptions and presents corresponding solutions. Chapter 5 deals with simultaneous equation models and presents modeling methods appropriate when studying two or more interrelated dependent variables. Chapter 6 presents methods for analyzing panel data—data obtained from repeated observations on sampling units over time, such as household surveys conducted several times to a sample of households. When data are collected continuously over time, such as hourly, daily, weekly, or yearly, time series methods and models are often needed and are discussed in Chapters 7 and 8. New to the 2nd edition is explicit treatment of frequency domain time series analysis including Fourier and Wavelets analysis methods. Latent variable models, discussed in Chapter 9, are used when the dependent variable is not directly observable and is approximated with one or more surrogate variables. The final chapter in this section, Chapter 10, presents duration models, which are used to model time-until-event data as survival, hazard, and decay processes.
Part III in the book presents count and discrete dependent variable models. Count models (Chapter 11) arise when the data of interest are non-negative integers. Examples of such data include vehicles in a queue and the number of vehicle crashes per unit time. Zero inflation—a phenomenon observed frequently with count data—is discussed in detail and a new example and corresponding data set have been added in this 2nd edition. Logistic Regression is commonly used to model probabilities of binary outcomes, is presented in Chapter 12, and is unique to the 2nd edition. Discrete outcome models are extremely useful in many study applications, and are described in detail in Chapter 13. A unique feature of the book is that discrete outcome models are first considered statistically, and then later related to economic theories of consumer choice. Ordered probability models (a new chapter for the second edition) are presented in Chapter 14. Discrete-continuous models are presented in Chapter 15 and demonstrate that interrelated discrete and continuous data need to be modeled as a system rather than individually, such as the choice of which vehicle to drive and how far it will be driven.
Finally, Part IV of the book contains massively expanded chapter on random parameters models (Chapter 16), a new chapter on latent class models (Chapter 17), a new chapter on bivariate and multivariate dependent variable models (Chapter 18) and an expanded chapter on Bayesian statistical modeling (Chapter 19). Models that deal with unobserved heterogeneity (random parameters models and latent class models) have become the standard statistical approach in many transportation sub-disciplines and Chapters 16 and 17 provide an important introduction to these methods. Bivariate and multivariate dependent variable models are encountered in many transportation data analyses. Although the inter-relation among dependent variables has often been ignored in transportation research, the methodologies presented in Chapter 18 show how such inter-dependencies can be accurately modeled. The chapter on Bayesian statistical models (Chapter 19) arises as a result of the increasing prevalence of Bayesian inference and Markov Chain Monte Carlo Methods (an analytically convenient method for estimating complex Bayes’ models). This chapter presents the basic theory of Bayesian models, of Markov Chain Monte Carlo methods of sampling, and presents two separate examples of Bayes’ models.
The appendices are complementary to the remainder of the book. Appendix A presents fundamental concepts in statistics which support analytical methods discussed. Appendix B provides tables of probability distributions used in the book, while Appendix C describes typical uses of data transformations common to many statistical methods.
While the book covers a wide variety of analytical tools for improving the quality of research, it does not attempt to teach all elements of the research process. Specifically, the development and selection of research hypotheses, alternative experimental design methodologies, the virtues and drawbacks of experimental versus observational studies, and issues involved with the collection of data are not discussed. These issues are critical elements in the conduct of research, and can drastically impact the overall results and quality of the research endeavor. It is considered a prerequisite that readers of this book are educated and informed on these critical research elements in order to appropriately apply the analytical tools presented herein.
Simon P. Washnington
Mathew G. Karlaftis
Fred L. Mannering
Panigiotis Ch. Anastasopoulos
Engineering News-Record (ENR) publishes its Construction Cost Index (CCI) monthly. CCI is the weighted average price of construction activities in 20 United States (US) cities. CCI has widely been used for cost estimation, bid preparation and investment planning. Cost estimators and investment planners are not only interested in the current CCI, but also are interested in forecasting changes in CCI trends. However, CCI is subject to significant variations that are difficult to predict. An important step towards forecasting CCI trends is to identify its leading indicators. The research objective is to identify the leading indicators of CCI using empirical tests. The results of Granger causality tests show that consumer price index, crude oil price, producer price index, GDP, employment levels in construction, number of building permits, number of housing starts and money supply are the leading indicators of CCI. The results of Johansen’s cointegration tests show that money supply and crude oil price are the leading indicators with long-term relationships with CCI. These findings contribute to the body of knowledge in CCI forecasting. CCI can be predicted more accurately using its leading indicators. Cost estimators and capital project planners can benefit from better forecasting through reduction in uncertainty about future construction costs.
This paper investigates the likelihood of occurrence and quantifies the magnitude and rate of discrepancies in highway project final costs with respect to their contract award amounts. Using data from Indiana, we develop a multistep econometric approach that can be used to estimate the effects of factors associated with the contract bidding process, project type, and the project physical environment on cost discrepancies in highway contracts. Estimation findings indicate that for a given project type and project year, contracts of larger size or longer duration are generally more likely to incur cost overruns. In addition, for contracts that incur cost overruns, the cost overrun rate decreases nonlinearly with increasing contract size up to a certain point after which the cost overrun rate increases with increasing contract size. Our approach allows for the possibility that cost overrun amounts are not linearly related to contract award amounts (contract size), and shows that greater analytical flexibility needs to be incorporated into any investigation of contract cost overruns. Agencies interested in improving their financial forecasts can replicate our proposed methodology using local contract data.
The importance of the construction industry for the three elements of sustainable development, namely economic growth, social progress and effective protection of the environment, cannot be disregarded. This paper aims to evolve a conceptual framework for implementing sustainability principles and strategies to the construction industry from a life-cycle perspective to contribute to sustainable development. The framework relies on three basic principles, which are resource management, life-cycle design and design for human and environment. Following a literature review, each principle involving strategies and methods to be applied during the life cycle of construction projects is explained and a few case studies are presented for clarity on the methods. The framework, offering tools for stakeholders of the construction industry, also aims to help to develop the most appropriate assessment tool, which is based on the priorities of critical conditions. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment.
Labour resources are invaluable assets in the construction industry. Nurturing a quality workforce and promoting stable employment for construction personnel have often been advocated as part and parcel of an industrial policy. Yet, the future labour market of the industry is always uncertain, and there is a need for estimating future labour market conditions as an aid to policy formulation and implementation. The Box-Jenkins approach has been applied to develop Autoregressive Integrated Moving Average (ARIMA) models to analyse and forecast five key indicators in the construction labour market of Hong Kong: employment level, productivity, unemployment rate, underemployment rate and real wage. This approach can be adopted in more complex and diverse labour markets subject to the properties of the utilized data series. Quarterly time-series statistics over the period 1983-2002 are used in this study. The predictive adequacy of the models derived is evaluated with out-of-sample forecasts in comparison with actual data, based on the mean absolute percentage error (MAPE) and the Theil's U statistics. The results indicate that except for construction employment, the proposed forecasting models have reasonably good predictive performance. Among the five case studies, the most accurate is the construction real wages model. In addition, we conclude that univariate projection is not an appropriate method for forecasting construction employment in Hong Kong. Multivariate structural forecasting analysis should be adopted in order to obtain more accurate estimates. The developed models can be used to provide benchmark estimates for further analysis of the construction labour market and the projections offer valuable information and early signals to training providers and employment policy makers.
This textbook provides an introduction to econometrics through a grounding in probability theory and statistical inference. The emphasis is on the concepts and ideas underlying probability theory and statistical inference, and on motivating the learning of them both at a formal and an intuitive level. It encourages the mastering of fundamental concepts and theoretical perspectives which guide the formulation and solution of problems in econometric modelling. This makes it an ideal introduction to empirical econometric modelling and the more advanced econometric literature. It is recommended for use on courses giving students a thorough grounding in econometrics at undergraduate or graduate level.
An understanding of future trends in construction prices is likely to influence the construction investment strategy of a variety of interested parties, ranging from private and public clients to construction contractors, property speculators, financial institutions, and construction professionals. This paper derives leading indicators for construction prices in the United Kingdom. These indicators are based on two experimental methods: turning points of the basic indicators in relation to construction price turning points; and predictive power of lags of the basic indicators. It is concluded, based on the analyses, that unemployment level, construction output, industrial production, and ratio of price to cost indices in manufacturing are consistent leading indicators of construction prices. Building cost index and gross national product constitute coincident indicators. 'Popular' macro-economic time series such as nominal interest rate, inflation rate, real interest rate, all share index and money supply produced inconclusive results.
The primary purpose of this paper is to examine dynamic causal relationships between house price and its five determinants, including total household income, short-run interest rates, stock price index, construction costs, and housing completions, in Taipei new dwelling market. Granger causality tests, variance decomposition, impulse response functions based on the vector error-correction model are utilised. All five determinants Granger cause house prices, but only house prices and stock price index have a bilateral feedback effect. The variance decomposition results suggest that disturbances originating from current house prices inflict greatest variability (66 percent of variance) to future prices. The remaining 34 percent of the variance is explained by the five determinants. On the supply side, the construction costs and housing completions together explain about 10 percent of the house price variance. On the demand side, short-run interest rates, total household income and stock price index explain about 24 percent of the variance.
Carbon footprint study of environment and energy research institute in Qatar
- R Chamoun
Chamoun, R. (2013). "Carbon footprint study of environment and energy
research institute in Qatar." Proc., 2nd Int. Conf. on Chemical, Ecology
and Environmental Sciences (ICEES'2013), Planetary Scientific
Research Center (PSRC), 226-229.
Are you on the bench? Insight into the Qatar construction market and opportunities for real estate developers
- Deloitte
Deloitte. (2013). "Are you on the bench? Insight into the Qatar construction
market and opportunities for real estate developers." 〈http://www
.deloitte.com/assets/DcomMiddleEast/Local%20Assets/Documents/
Services/FAS/me_fas_qatar-construction-market_052013.pdf〉 (Apr. 27,
2014).
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UNEP (United Nations Environmental Programme). (2003). " Sustainable
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General Secretariat for Development Planning) Qatar national vision 2030
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