Purpose
In the past decades, artificial intelligence (AI)-based hybrid methods have been increasingly applied in construction risk management practices. The purpose of this paper is to review and ...compile the current AI methods used for cost-risk assessment in the construction management domain in order to capture complexity and risk interdependencies under high uncertainty.
Design/methodology/approach
This paper makes a content analysis, based on a comprehensive literature review of articles published in high-quality journals from the years 2008 to 2018. Fuzzy hybrid methods, such as fuzzy-analytical network processing, fuzzy-artificial neural network and fuzzy-simulation, have been widely used and dominated in the literature due to their ability to measure the complexity and uncertainty of the system.
Findings
The findings of this review article suggest that due to the limitation of subjective risk data and complex computation, the applications of these AI methods are limited in order to address cost overrun issues under high uncertainty. It is suggested that a hybrid approach of fuzzy logic and extended form of Bayesian belief network (BBN) can be applied in cost-risk assessment to better capture complexity-risk interdependencies under uncertainty.
Research limitations/implications
This study only focuses on the subjective risk assessment methods applied in construction management to overcome cost overrun problem. Therefore, future research can be extended to interpret the input data required to deal with uncertainties, rather than relying solely on subjective judgments in risk assessment analysis.
Practical implications
These results may assist in the management of cost overrun while addressing complexity and uncertainty to avoid chaos in a project. In addition, project managers, experts and practitioners should address the interrelationship between key complexity and risk factors in order to plan risk impact on project cost. The proposed hybrid method of fuzzy logic and BBN can better support the management implications in recent construction risk management practice.
Originality/value
This study addresses the applications of AI-based methods in complex construction projects. A proposed hybrid approach could better address the complexity-risk interdependencies which increase cost uncertainty in project.
Purpose
Cost overrun is inherent to project chaos, which is one of the key drivers of project failure. The purpose of this paper is to explore the critical elements of complexity-risk interdependency ...for cost-chaos in the construction management domain by utilizing a multi-criteria decision model.
Design/methodology/approach
A total of 12 complexity and 60 risk attributes are initially identified from the literature and using expert’s judgements. For the development of a structured hierarchy of key complexity and risk drivers, a real-time Delphi process is adopted for recording and evaluating the responses from experts. Afterwards, a pair-wise comparison using analytical network processing is performed to measure complexity-risk interdependencies against cost alternatives.
Findings
The findings of the integrated priority decision index (IPDI) suggest that uncertainties related to contingency and escalation costs are the main sources of cost overrun in project drift, along with the key elements such as “the use of innovative technology,” “multiple contracts,” “low advance payment,” “change in design,” “unclear specifications” and “the lack of experience” appear to be more significant to chaos in complexity-risk interdependency network.
Research limitations/implications
This study did not address the uncertainty and vulnerability exit in the judgment process, therefore, this framework can be extended using fuzzy logic to better evaluate the significance of cost-chaos drivers.
Practical implications
These results may assist the management of cost overrun to avoid chaos in a project. The proposed model can be applied within project risk management practices to make better-informed technical decisions in the early phases of the project life cycle where uncertainty is high.
Originality/value
This research addresses the importance of cost overruns as a source of project chaos in dynamic systems where projects reach the edge of chaos and progress stops. A new IPDI index contributes toward evaluating the severity of complexity and risk and their interdependencies which create cost-chaos in infrastructure transport projects.
Waste management has become a pressing environmental, social, and economic issue. In Ghana, the government has decentralized the waste management system to include private sector actors as key ...players to improve the collection, disposal, and recycling of waste. With this development, a heterogeneous population of entrepreneurs has engaged in waste recycling, achieving mixed results in terms of performance. The aim of this paper is to identify shared personality traits and characteristics of entrepreneurs that make certain firms engage in waste recycling more innovatively than others. An extensive literature review was used to identify these personality traits and characteristics, which were then modeled using upper echelon theory (UET) to investigate their impact on innovation performance. A regression analysis approach was adopted based on the data collected from 157 entrepreneurs’ founders, co-founders, and shareholders among the waste recycling firms in Ghana selected for the annual Supporting Entrepreneurs for Environment and Development (SEED) Award competition. The key contribution of this research is to better understand the relationship between entrepreneur traits and innovation performance. Given the fact that in small start-ups, the founder plays the most important role, this paper serves as a foundation for defining individual-level factors critical in sustaining sustainable innovation performance in the waste recycling sector. The results of this study will help shareholders and policymakers better understand and implement strategies for determining and selecting innovative waste recycling entrepreneurs.
PurposeRisk analysis plays a vital role in controlling and managing cost overruns in complex construction projects, particularly where uncertainty is high. This study attempts to address an important ...issue of cost overrun that encountered by metropolitan rapid transit projects in relation to the significance of risk involved under high uncertainty.Design/methodology/approachIn order to solve cost overrun problems in metropolitan transit projects and facilitate the decision-makers for effective future budgeting, a cost-risk contingency framework has been designed using fuzzy logic, analytical hierarchy process and Monte Carlo simulation.FindingsInitially, a hierarchical breakdown structure of important complexity-driven risk factors has been conceptualized herein using relative importance index. Later, a proposed cost-risk contingency framework has investigated the expected total construction cost in order to consider the additional budgeted cost required to mitigate the risk consequences for particular project activity. The results of cost-risk analysis imply that poor design issues, an increase in material prices and delays in relocating facilities show higher dependency and increase the risk of cost overrun in metropolitan transit projects.Practical implicationsThe findings and implication for project managers could possibly be achieved by assuming the proposed cost-risk contingency framework under high uncertainty of cost found in this research. Furthermore, this procedure may be used by experts from other engineering domains by replacing and considering the complex relationship between complexity-risk factors.Originality/valueThis study contributes to the body of knowledge by providing a practical contingency model to identify and evaluate the additional risk cost required to compute total construction cost for getting stability in future budgeting.
Researchers and practitioners have spent much time on and given a great deal of attention to the practical characteristics of professional development and its delivery in an attempt to understand the ...training transfer problem at the workplace. However, when we consider the individual employee as the primary agent of the transfer process, we cannot and should not ignore their perceived self‐rated attributes, motivation and expectations of learning and transfer at the pre‐training stage. In this study, it is hypothesized that, trainees’ answers to the questions ‘can I do this task?’ and ‘do I want to do this task?’ are positively associated with the level of transfer effort performance expectancy. The Learning Transfer System Inventory questionnaire was completed by 213 teachers in high schools and vocational schools in Thailand during their training on cloud computing tools. The findings reveal that a teacher’s personal characteristics (learning readiness, personal transfer efficacy, motivation to transfer, personal capacity and perceived content validity) at the pre‐training stage are significant predictors of transfer effort performance expectancy at the post‐training stage. This study can help training practitioners and managers to enhance learner characteristics prior to training with a view to increasing training transfer.
The mining industries' contribution to economies has been limited to the boomtown's impact of short-term initiatives. However, the bane of mining on resource management has been a recurring theme. ...This study recognizes the need to investigate the interrelationship among legitimate pressure, resource dependence, and green practices in the quest for sustainable resource management. The study categorized legitimate pressure into three distinct groups (coercive, normative, and mimetic pressure) and resource dependence into intra and inter-organizational resource dependence to assess the interrelationship among these constructs. We use both the structural model and the fuzzy set qualitative comparative analysis (fsQCA) approach and 320 respondents from the Ghanaian mining industry.
According to our findings, normative pressure does not influence the implementation of green mining policies without the two groups of resource dependencies acting as mediators.The findings from the fSQCA have shown that the combination of coercive pressure, normative pressure, inter-organizational resource dependencies, and intra-organizational resource dependencies is the best path toward sustainable resource management. The study contributes to the global efforts toward sustainable resource management. Policy and managerial implications are discussed.
•Relationship among legitimate pressure, resource dependence, and green practices is investigated.•Both direct and configuration path analysis using fsQCA is conducted.•The best combination to achieve higher SRM is determined.•Mining firms should prioritize inter-organizational collaboration.
Graph is an important and fundamental data structure that presents in a wide variety of practical scenarios.With the rapid development of the Internet in recent years,there has been a huge increase ...in social network graph data,and the analysis of this data can be of great help in practical scenarios such as public services and advertising and marketing.There are already quite a few graph neural network algorithms that can get good results in such problems,but they still have room for improvement,and in many scenarios where high accuracy is pursued,engineers still want to have algorithms with better performance to choose from.This paper improves personalized propagation of neural predictions and proposes a new graph neural network algorithm called degree of node based personalized propagation of neural predictions(DPPNP)that can be used in social graph networks.Compared to traditional graph neural network algorithms,when the information is propagated between nodes,the proposed algorithm will keep its own infor
Graph is an important and fundamental data structure that presents in a wide variety of practical scenarios.With the rapid development of the Internet in recent years, there has been a huge increase ...in social network graph data, and the analysis of this data can be of great help in practical scenarios such as public services and advertising and marketing.There are already quite a few graph neural network algorithms that can get good results in such problems, but they still have room for improvement, and in many scenarios where high accuracy is pursued, engineers still want to have algorithms with better performance to choose from.This paper improves personalized propagation of neural predictions and proposes a new graph neural network algorithm called degree of node based personalized propagation of neural predictions（DPPNP）that can be used in social graph networks.Compared to traditional graph neural network algorithms, when the information is propagated between nodes, the proposed algorithm will keep its ow
Although prior research on late-career entrepreneurship has explored the effects of financial, human, and social capital on the intentions to engage in entrepreneurial activity within the domains of ...a developed economy, little research has investigated this scholarship in the context of a push perspective within a developing economy. This study endeavors to meet this gap by investigating the effects of financial, social, and human capital and the personal dispositional traits on the entrepreneurial intentions among early retirees in the ICT sector of Pakistan. Based on the collected data from the web-based questionnaire and personally administered surveys and interviews from 345 respondents who face a survival challenge in the aftermath of a job loss, we make use of hierarchical logistic regression to periodically explore the independent and combined effects of the financial, social and human capital and the impact of a stable dispositional trait of fear of failure on the entrepreneurial intention. Being one of the foremost studies to address the late-career entrepreneurship phenomenon in a developing economy, this study has to offer notable contributions to entrepreneurship literature. Consistent with prior research, we observe support for the individual influence of various elements of financial, social, and human capital and the fear of failure on the intentions to engage in an entrepreneurial career. Results also demonstrate considerable evidence for the interaction effects among financial, human, and social capital as well as among different measures of financial capital, human capital, and the fear of failure. Discussion about the results is furnished followed by limitations and future research implications.
Tax collection is an essential activity to boost the economy of all countries. Larger businesses and governments are increasingly relying on Enterprise Resource Planning (ERP) systems, which are ...designed to enhance the collection of revenues among other things. However, the implementation of an ERP system often affects the organizational climate by changing the manner businesses are conducted from the past both internally and externally. These changes have the tendency to impact the actions of workers throughout the transition process. Nevertheless, organization climate which is an essential variable to measure the success of ERPs is mostly underutilized. Thus in this study, we proposed an information system (IS) success model that integrates organizational climate variables namely, role clarity, teamwork and support, and, training and learning into the DeLone and McLean model to evaluate the success of a tax ERP system. The proposed model was based on a quantitative and a mixed-method case study (MM-CS). Data was gathered from a top company with many branches in Ghana through interviews, observation, focus groups, and questionnaires. Partial least squares structural equation modeling was used to examine the 555 data collected from the questionnaire. The result of the study shows that the organizational climate variables (training & learning, teamwork & support, and role clarity) were statistically significant in determining the success of a tax ERP system. Training & learning and teamwork & support also had a positive impact on service quality, user satisfaction, and individual impact.
Enterprise resource planning (ERP) systems, DeLone & McLean IS success model, Information systems, Organizational climate, Structural equation modeling.
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