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The purpose of this paper is to investigate the impact of risk on the project delivery selection process of three primary methods in use in the USA, including design-bid-build (DBB); design-build (DB); and construction manager/general contractor (CMGC).

The review of empirical studies, national survey questionnaire, multivariate analysis, and cross-validating discussion are adopted for this research. The risk factors were identified through an exhaustive literature review and empirical studies that included more than $10 billion of transportation projects. Experts with an average of 25 years of professional experience related to risk and project delivery methods in the transportation industry were invited to participate in the survey.

There were six critical risk factors for DBB, seven for DB, and six for CMGC. These critical risk factors are ranked differently from each delivery method. The most critical risk factor for DBB is construction risk, for DB is scope risk, and for CMGC is constructability and documentation risk.

Knowledge of the risk factors will allow researchers to better understand the impact of risk on DBB, DB, and CMGC projects. The chief limitation of this research is that the primary data were mostly opinions from experts although several empirical data were collected for cross-validation. The future research may take into account the role of participant's risk aversion in project delivery decision frameworks.

Transportation agencies and other practitioners can use these risk factors to make more effective and defensible decisions on which delivery method is the most suitable for their projects. The result from this study provides a foundation for decision makers to use a risk-based approach in the project delivery decision.

This research is the first attempt to examine the impact of risk on the project delivery selection process.

The purpose of this paper is to present a framework to devise a system for ranking of traditional project delivery methods, regarding their suitability, against the varying levels of mega project attributes.

The proposed system employs input and output interfaces and a granular (fuzzy rule base) component for estimating the subjective levels of risks, opportunities, and constraints and then mapping them to a decision matrix. A questionnaire has been designed (using the SurveyGizmo® platform) to collect the perceptions of the various project stakeholders and use them. A total of 127 stakeholders completed the survey form in full.

The survey data were used to calibrate the fuzzy logic model of the granular component. The envisioned system computes, for each possible delivery method, an index that reflects the suitability (of the corresponding delivery method) on an ordinal scale.

The devised decision support system is likely to lessen the dependency of “accurate decision” on “the experience of the decision-makers.” It will also enable ranking the various project delivery methods based on the various project and stakeholder attributes that are likely to affect the project risks, opportunities and constraints.

The purpose of this paper is to identify key project delivery method selection factors to assist water industry decision-makers in selecting the most appropriate delivery method for their water treatment plant projects.

The selection factors were identified by compiling and validating key project delivery selection factors across various industries through an extensive literature review and two industry expert workshops. This resulted in the development of a web-based decision-support tool to facilitate project delivery method selection within the water industry.

The research effort led to the identification of 13 key project delivery method selection factors (seven primary factors and six secondary factors) for water treatment plant projects. These factors were utilized to develop EXPRSS-TP, a pioneering web-based project delivery method decision-support tool for the water industry.

A project delivery method selection process is typically an informal process that may range from days to weeks at a time. Based on this work, the assessment can now be completed in about one hour and provides decision-makers with the most favorable delivery method for their project. And with the new tool that encompasses the new knowledge, not only is the decision reached at an accelerated pace, EXPRSS-TP also documents the entire selection process, allowing for a written and retained record of this key decision and its procedure.

This paper contributes to the exisiting body of knowledge by identifying key project delivery selection factors across numerous industries, assessing and combining them, and finally incorporating them into one comprehensive process. EXPRSS-TP improves the traditional project delivery method selection process and provides evidence-based project delivery method selection recommendations.

The purpose of this paper is to reduce the waiting time on webcast for selective contents, by proposing a scheduling method called the “contents prefetched broadcasting considering user participation” (CPB‐CP) method.

The authors analyze and evaluate the performance of the proposed CPB‐CP method.

It is confirmed that the proposed method gives shorter average waiting time than the conventional methods.

A future direction of this study will involve making a scheduling method in the case where the playing time of each content item is different.

In selective contents delivery, users may wait for the next bit of content to start playing after watching the previous one. In quiz programs, users may wait to receive the content data for their selected answer after they select their answer.

In the CPB‐CP method, when a provider node pulls out of the network while delivering contents, waiting time is reduced effectively by reconstructing a delivery schedule that considers the available bandwidth of each provider node.

Increasing academic communities and practitioners begin to explore a novel method to reduce environmental pollution and realize green logistics delivery. Additionally, China's Statistical Yearbook shows that the number of private cars has reached 165 million in China. Under this background, this study proposes a green delivery method by the combination of sharing vehicle (private cars) and IoT (Internet of things) from the perspective of vehicle energy efficiency and aims to improve the energy efficiency of social vehicles and provides more convenient delivery services.

This study builds an IoT architecture consisting of customer data layer, information collection layer, cloud optimization layer and delivery task execution layer. Especially in the IoT architecture, a clustering analysis method is used to determine the critical value of customers' classification and shared delivery, a routing optimization method is used to solve the initial solution in could layer and shared technology is used in the implementation of shared delivery.

The results show that the delivery method considering shared vehicles has a positive effect on improving the energy utilization of vehicles. But if all of delivery tasks are performed by the shared vehicle, the application effect may be counterproductive, such as delivery cost increases and energy efficiency decreases. This study provides a good reference for the implementation of green intelligent delivery business, which has a positive effect on the improvement of logistics operation efficiency.

This study designs a novel method to solve the green and shared delivery issues under the IoT environment, which integrates the IoT architecture. The proposed methodology is applied in a real case in China.

Delivering a building project on time and under budget is still an increasingly complex and risky business. A host of new project delivery methods and management techniques have been promoted to help achieve this. Developing a project delivery strategy and contractual relationships is a particularly complex and large problem domain that requires diverse, highly sophisticated skills, expertise and knowledge. Expert knowledge and lessons learned in the construction phase of a building project hold a wealth of knowledge and expertise that can be often taken for granted. However, this body of knowledge is not systematically incorporated into the procurement phase of subsequent projects. Case‐based reasoning is a technology for problem solving based on recall and reuse of specific experiences; it offers techniques for acquiring, representing and managing the knowledge gained from previous experiences and augmenting a set of specific experiences with generalised knowledge. Outlines how current case‐based reasoning techniques support project delivery method decisions. Presents a case‐based framework for project delivery method selection. Finally, reports the findings of the first phase of the system development cycle.

Over the last three decades, construction projects have increasingly been delivered through alternative delivery methods. As a result, many owners have a range of delivery methods to choose from and aim to use the right one for each of their projects. Researchers have developed several tools and decision-support processes to facilitate this selection procedure. The purpose of this study is to review and discuss differences and common themes across selection tools developed by academic researchers and project owners.

The study reviews prominent selection processes and tools used for infrastructure projects by conducting an in-depth literature review and using the content analysis method to elicit findings on the methodologies and criteria presented in the literature.

This study presents three principal findings. First, findings show three common themes emerge within the selection criteria—characteristics, goals and risks. Second, while academic studies most commonly suggest employing multi-attribute analysis, this study reveals that, in practice, selection tools most frequently employ a staged or gated evaluation based on the type of criteria and their importance to the decision. Finally, this review further highlights the importance of institutional context in decision-making.

This work contributes to the body of knowledge by providing guidance to practitioners and opening new directions for researchers around the way selection criteria are categorized in the relevant literature and the institutional context considerations when structuring or evaluating a selection process or tool.

The purpose of this paper is to propose an automated machine learning (AutoML) and multi-agent system approach to improve overall product delivery satisfaction under limited resources.

An AutoML method is purposed to model delivery satisfaction of individual customer, and a heuristic method and multi-agent system are proposed to improve overall satisfaction under limited processing capability. A series of simulation experiments have been conducted to illustrate the effectiveness of the proposed methodology.

The simulated results show that the proposed method can effectively improve overall delivery satisfaction, especially when the demand of customer orders is highly fluctuating and when the customer satisfaction models are highly diversified.

The proposed framework provides a more dynamic and continuously improving way to model delivery satisfaction of individual customer, thereby supports companies to provide personalized services and develop scalable and flexible business at a lower cost, and ultimately improves the overall quality, efficiency and effectiveness of delivery services.

The proposed methodology utilizes AutoML and multi-agent system to model individual customer delivery satisfaction and improve the overall satisfaction. It can cooperate with the existing delivery resource planning methods to further improve customer delivery satisfaction. The authors propose an AutoML approach to model individual customer delivery satisfaction, which enables continuous update and improvements. The authors propose multi-agent system and a heuristic method to improve overall delivery satisfaction. The numerical results show that the proposed method can improve overall delivery satisfaction with limited processing capability.

To achieve the shift towards sustainable construction the industry must change the project delivery methods used. Therefore, this paper reports on a high-performance building project that implemented a collaborative project delivery method through the examination of the following research questions: RQ1: What were the most important contractual, cultural and organisational elements studied in the collaborative project delivery method? RQ2: What were the effects of the studied elements?

A longitudinal case study approach was adopted. As for means of data collection, a document review, semi-structured interviews, and observations was conducted. A total of 20 observations (App. 80 h, 175 pages of notes) and 12 interviews (App. 20 h, 100 pages of notes) with project participants was conducted.

The analysis indicates that if attention is paid to task, team and individual needs through contractual, cultural and organisational elements, this will affect the development of an integrated team.

We demonstrate that the effects of the elements are shown through their achievement in creating and sustaining an integrated team of inter-organisational participants working in a collaborative environment.

It provides a better understanding of how a collaborative project delivery method for the design phase emphasises team integration. We demonstrate that while the principal sets the contractual boundaries by deciding the contractual elements, the agent should be intentional in the selection and use of organizational and cultural elements.

The paper suggests that it is not enough to just have contractual elements implemented. Consequently, this insight suggests that managers should be attentive to the untapped potential that lies within organisational and cultural elements.

This paper is one of seven in this volume elaborating different approaches to quality improvement in education. This paper aims to delineate a methodology called Deliverology.

The paper presents the origins, theoretical foundations, core principles and a case study showing an application of Deliverology in the Kentucky Department of Education in the USA.

The core principles underlying the approach are embodied in its guiding questions: What is our system trying to do? How are we planning to do it? At any given moment, how will we know whether we are on track to succeed? and If we are not on track, what are we going to do about it?

Few theoretical treatments and demonstration cases are currently available on commonly used models of quality improvement in other fields that might have potential value in improving education systems internationally. This paper fills this gap by elucidating one promising approach. The paper also derives value, as it permits a comparison of the Deliverology approach with other quality improvement approaches treated in this volume.