Late payment, and indeed no payment, is a rampant and chronic problem that has plagued the global construction industry for too long. Recent development in blockchain technology, particularly its smart contract, seems to provide a new opportunity to improve this old problem. However, this opportunity is largely unexploited. This study aims to develop a blockchain-based smart contract (BBSC) system for smart payment in the construction industry by focusing on the fundamental cycle of payment freezing (sometimes also synonymously called payment guarantees) and disbursement application. Firstly, a BBSC framework, containing three processes of (a) initiation and configuration, (b) payment freezing, and (c) disbursement application, is developed. Next, based on the framework, the system architecture of the BBSC system, containing three layers of (1) Infrastructure as a Service (IaaS), (2) Blockchain as a Service (BaaS), and (3) Software as a Service (SaaS) is proposed and elabora-ted. Finally, based on the system architecture, a BBSC prototype system is developed using a real-life modular construction project as a case study. It was found that the prototype system can improve the certainty and efficiency of the progress payment, thereby enabling smart payment in construction transactions. Without advocating radical changes (e.g., the contractual relationships or the intermediate role of banks in modern construction projects), the prototype can be developed into a real-life BBSC system that can work compatibly with current advancements in the field. Future works are recommended to fine-tune the findings and translate and implement them in real-life applications.
The development of digital transformation in the construction industry has led to the increasing adoption of smart contracts. As programmable applications to automatically write, verify, and enforce transaction conditions, smart contracts can be used in different areas mainly to improve automation level, information security, and built digital environment enhancement. However, the smart contract is commonly mentioned as a blockchain appendage, while its unique connotation and value in the construction industry have not been recognized. Therefore, this study carries out a systematic review based on 81 research articles published from 2014 to 2021 on smart contract applications in construction to explore and highlight their potentials under domain-specific requirements. Results are analyzed according to research type categorization and domain codification. Eight research domains are identified, where the three most highly explored domains are contract and payment, supply chain and logistics, and information management. The integration of smart contracts with other innovative concepts and advanced technologies is analyzed. The applicability, benefits, and challenges of smart contract applications regarding different research domains are discussed.
In the majority of the previous works on discrete-event stochastic systems, they have been assumed to have independent input processes. However, in many applications, these input processes can be highly correlated. Furthermore, the performance measures of the systems with correlated inputs can be significantly different from those with independent inputs. In this paper, we provide an overview on some commonly used methods for modeling correlated input processes, and we discuss the difficulties and possible future research topics in the study of discrete-event stochastic systems with correlated inputs.
A project is a specific effort to create a unique product, so it is a favorable place for knowledge creation and development. Knowledge can be transferred inside and outside projects and their parent project-based organizations, thus affecting project performance and organizational competitiveness. However, the current research on the elements and outcomes of knowledge transfer (KT) in the project environment lacks completeness and clarity, and that on the different levels of KT is fragmented. This study aims to conduct comprehensive research to determine and link the elements and outcomes of KT in the project environment. The authors systematically analyzed the relevant literature from 2000 to 2021, which showed an increasing publication trend. They divided KT in the project environment into three levels according to the transfer scenario: Intra-project, cross-project, and cross-organizational KT. Five-dimensional transfer elements and two-dimensional transfer outcomes were then identified and analyzed from previous literature. Lastly, the relationships between the transfer elements and outcomes were gathered to create a comprehensive model. Importantly, the knowledge gap in the current literature was highlighted, and future research directions were put forward. This study builds a theoretical framework linking transfer elements to outcomes that can serve as a basis for scholars and practitioners to develop effective strategies for KT in the project environment.
Over the past two decades, machine learning (ML) has elicited increasing attention in building energy management (BEM) research. However, the boundary of the ML-BEM research has not been clearly defined, and no thorough review of ML applications in BEM during the whole building life-cycle has been published. This study aims to address this gap by reviewing the ML-BEM papers to ascertain the status of this research area and identify future research directions. An integrated framework of ML-BEM, composed of four layers and a series of driving factors, is proposed. Then, based on the hype cycle model, this paper analyzes the current development status of ML-BEM and tries to predict its future development trend. Finally, five research directions are discussed: (1) the behavioral impact on BEM, (2) the integration management of renewable energy, (3) security concerns of ML-BEM, (4) extension to other building life-cycle phases, and (5) the focus on fault detection and diagnosis. The findings of this study are believed to provide useful references for future research on ML-BEM.
Due to uncertainties in water supply, there is growing demand for water resource management in enterprises. In this study, we evaluated the effects of companies’ water-saving reconstruction projects. We used Hina Advanced Materials Company as a case to construct an investment decision model to (1) calculate the internal and external costs of water resources based on circular economic value analysis theory, and (2) locate the level of water resources circulation. We adopted gray situation decision analysis to identify the typical problems that occur in water resource utilization. Moreover, we demonstrated optimization plans for different potential improvements, thereby providing guidance and references for water resource cost management and the comprehensive optimization of environmental benefits. We concluded that the circulation economic value analysis model can effectively display the flow and amount of value derived from water resource flows, thereby providing guidance and suggestions for optimizing water resource flows.
Time does not go backward. A negative duration, such as “time period” at first sight is difficult to interpret. Previous network techniques (CPM/PERT/PDM) did not support negative parameters and/or loops (potentially necessitating recursive calculations) in the model because of the limited computing and data storage capabilities of early computers. Monsieur Roy and John Fondahl implicitly introduced negative weights into network techniques to represent activities with fixed or estimated durations (MPM/PDM). Subsequently, the introduction of negative lead and/or lag times by software developers (IBM) apparently overcome the limitation of not allowing negative time parameters in time model. Referring to general digraph (Event on Node) representation where activities are represented by pairs of nodes and pairwise relative time restrictions are represented by weighted arrows, we can release most restraints in constructing the graph structure (incorporating the dynamic model of the inner logic of time plan), and a surprisingly flexible and handy network model can be developed that provides all the advantages of the abovementioned techniques. This paper aims to review the theoretical possibilities and technical interpretations (and use) of negative weights in network time models and discuss approximately 20 types of time-based restrictions among the activities of construction projects. We focus on pure relative time models, without considering other restrictions (such as calendar data, time-cost trade-off, resource allocation or other constraints).
The new mode for managing construction projects with information technology (IT) has attracted worldwide attention because it can help managers and workers perform tasks and bring potential benefits, such as high-quality products and accident-free production, effectively. However, the application of IT in site have not achieved expected results because it is faced with many constraints caused by internal factors from enterprises and projects and external factors from the government and environment. Although many relevant studies have discussed the constraints of implementing different IT and devices in the construction industry or site, few articles have specifically focused on identifying and analyzing the indicator system. In this work, we took China as the background, scientifically identified 23 influential factors that affect the implementation of IT in construction management through literature review and expert interviews. Subsequently, questionnaires were issued, and Delphi method was used to obtain empirical data that aimed at four different management fields. Then, an efficient and convenient method called DEMATEL was used to deal with these data. Afterward, the factors were divided into four categories, namely, core, diving, independent, and impact factors. Finally, the similarities and differences of the analysis results from the four fields were compared, and the key factors were identified. Results show that the cross-domain talent ability, concept and value cognition, and organization structure are core factors in all management fields that should be managed first along with the IT innovation ability in the enterprise. The formulation of technical standards and related device and training input are also critical in specific fields. Strategic planning plays a role in macro control and promotion. Data management and application, platform construction, solution, and collaboration have direct impacts on information management. The research results provide suggestions not only for the government to formulate effective policies for IT application and promotion in construction industry, but also for enterprises to take measures in improving management efficiency in the construction site and realizing its substantial benefits.
Carbon emission reduction is the only way to alleviate environmental problems, such as global warming. Effective evaluation of carbon performance can help enterprises to carry out energy saving and emission reduction activities to a certain extent and promote sustainable development. This paper constructs a carbon performance evaluation index system that includes the four dimensions of carbon resource (energy) input, cycle, output, and carbon management by incorporating the principles of circular economy and the theory of resource value circulation from the perspective of the flow trajectory of carbon-containing resources in the circulation of enterprises combined with the production characteristics of thermoelectric enterprises. Subsequently, combined with the case study, this paper discusses the scientific and practical nature of the system and provides another way of thinking for carbon performance evaluation of micro-enterprises in other industries. This paper expands the application boundary of matter–element model and supplements the literature of carbon performance, which has certain theoretical and practical significance.
This paper examines the current state of project cultures in the German turnkey construction industry and the ideal project cultures in terms of partnering from the perspective of various key stakeholders (i.e., Investors, General Contractors, (Sub-)Contractors and Designers). To investigate the current and ideal cultures, data were gathered among the key stakeholders by means of a survey study with 72 respondents divided over 12 companies. The respondents rated the current and desired cultures by using the Organizational Culture Assessment Instrument, which belongs to the Competing Values Framework. The investigations show many similarities and differences between the stakeholder perspectives of the current and the idealized partnering project cultures. Mainly, the General Contractors desire more cooperative behaviors than the (Sub-)Contractors, and the Investors desire more pronounced flexibility than the General Contractors. All stakeholders desire a cultural change from highly competitive behaviors toward more cooperation. Changes in terms of clear procedures or more flexibility are only desired by the Designers. Defining both the current and an ideal partnering project culture enables academics and project managers to compare their actual project cultures to an ideal situation. With such an approach, academics and project managers could measure whether new tools or changes in resources affect their project cultures toward a partnering project culture.
The mechanism of risk allocation is designed to protect all stakeholders, and it is vital to project success. Qualitative and quantitative ways of optimizing risk allocation have been well documented in extant literature (e.g., allocation principles, models, and solutions), and the foci of existing research are usually the maximization of rational utility. Few research has focused on partners’ social preferences affecting the output of risk allocation. This study presents a quantitative approach based on modeling alliance member (AM)’s inequity aversion (IA) to analyze risk-sharing arrangements in an alliance project. Fehr and Schmidt’s inequity-aversion model is integrated into modeling partner’s utility. This paper derives results for an alliance leader (AL)’s optimal risk-sharing ratio and AM’s optimal risk-management effort simultaneously. The derivation is based on solving a restrained optimization problem using the conception and methods from Stackelberg game theory. Results show that an AM’s IA significantly affects risk allocation between AL and AM. Specifically, envious preference is positively related to AL’s optimal risk-sharing ratio, whereas guilty preference negatively affects AL’s optimal risk-sharing ratio. These findings will be of interest to academics and practitioners involved in designing alliance negotiations.
