JournalTOCs

Engineering, Construction and Architectural Management
Journal Prestige (SJR): 0.653

Citation Impact (citeScore): 2
Number of Followers: 10

Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0969-9988
Published by Emerald

[341 journals]

Publisher’s note
- Pages: 478 - 478
  Abstract: Engineering, Construction and Architectural Management, Volume 25, Issue 4, Page 478-478, May 2018.
  
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-06-25T07:50:49Z
  DOI: 10.1108/ECAM-05-2018-269
Improving contractor social networking on IBS infrastructure maintenance
projects: a review
- Pages: 479 - 496
  Abstract: Engineering, Construction and Architectural Management, Volume 25, Issue 4, Page 479-496, May 2018.
  Purpose A key factor adversely affecting contractor social networking performance is the improper handling and information management of contractor’s services delivery on websites. Contractor social networking is particularly problematic on industrialised building system (IBS) infrastructure maintenance projects where contractor’s certified quality product and firms are not matched with maintenance specialisation services. The paper aims to discuss this issue. Design/methodology/approach This paper reports on the early stages of research which is developing a new information and communications technology (ICT)-based approach to managing contractor social networking on IBS infrastructure maintenance schemes. As a precursor to this work, the paper reviews current contractor social networking websites practices on IBS infrastructure maintenance projects and explores the ICT tools and techniques currently being employed on such projects. Findings The findings reveal the need for more sophisticated contractor social networking websites solutions which accord with the needs of IBS infrastructure maintenance schemes. Originality/value The paper concludes by presenting a research framework for developing such a system in the future.
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-06-25T07:50:54Z
  DOI: 10.1108/ECAM-08-2016-0180
Causes of delays in construction industry and comparative delay analysis
techniques with SCL protocol
- Pages: 497 - 533
  Abstract: Engineering, Construction and Architectural Management, Volume 25, Issue 4, Page 497-533, May 2018.
  Purpose The purpose of this paper is to reveal the main causes of delays in the projects are from the client (relative importance index (RII)=0.716), labor and equipment (RII=0.701) and contractor (RII=0.698). Hence determining the contractual responsibility of delay is the most likely source of dispute in construction projects and many techniques have been used in the courts to demonstrate the criticalities of a delay event on the project schedule. Therefore, authors try to investigate all process-based techniques of delay claims and evaluated and conformed them with principles by Society of Construction Law (SCL) protocol and Association for the Advancement of Cost Engineering International (AACEI) in order to choose the best techniques based on the specific circumstances of each project. Design/methodology/approach This section is divided into two distinct parts: refers to the methods used to assess the perceptions of clients, consultants, and contractors on the relative importance of causes of delay in construction industry; and refers to advantages and disadvantages of various techniques used to analyze delays and their conform with SCL protocol. A questionnaire was developed to assess the perceptions of clients, consultants, and contractors on the relative importance of causes of delay in Iranian construction industry. The respondents were asked to indicate their response category on 78 well-recognized construction delay factors identified by authors. Findings In total, 78 causes of delay were identified through research. The identified causes are combined into seven groups. The field survey included 58 contractors, 55 consultants, and 62 client. Data collected were analyzed by RII and Statistical Package for Social Sciences (SPSS). The authors identified main causes of delay and ten most important causes, according to Table AII, from the perspective of three major groups of participants (clients, consultants and contractors). The ranking of categories of causes of delay, according to Table I, were: client-related causes (RII=0.716); labor and equipment category causes (RII=0.701); contractor-related causes (RII=0.698); material-related causes (RII=0.690); design-related causes (RII=0.666); external causes (RII=0.662); and consultant-related causes (RII=0.662). But according to the discussions and given that determining the contractual responsibility of delay is the most likely source of dispute in construction industry and many techniques have been used in the courts to demonstrate the criticalities of a delay event on the project schedule. Originality/value All process-based techniques of delay analysis have been present in this paper and categorized in 11 groups. In order to understand the advantages and disadvantages of them by clients, contractor and consultant, a thorough review conducted to reveal the nature of techniques. In the next step, given that selecting the most appropriate technique based on constraints and specific conditions of each project is one of the most important steps to carry out a successful delay analysis. The authors conformed, all process-based techniques of delay analysis, by SCL protocol and AACEI principles. Finally, the result of this match was brought in order to choose the best technique based on the specific circumstances of each project.
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-06-25T07:50:51Z
  DOI: 10.1108/ECAM-10-2016-0220
Building a rough sets-based prediction model for classifying large-scale
construction projects based on sustainable success index
- Pages: 534 - 558
  Abstract: Engineering, Construction and Architectural Management, Volume 25, Issue 4, Page 534-558, May 2018.
  Purpose To address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly on large-scale construction projects, has been a controversial issue, especially in developing countries. Hence, in this paper, after introducing a sustainable success index (SSI), a novel method called “rough set approach” had been adopted to induce decision rules and to classify construction projects. The paper aims to discuss these issues. Design/methodology/approach At first, 20 effective success factors and 15 success criteria based on three pillars of sustainability of economy, society and environment had been categorized. The research data used for analysis had been collected from 26 large-scale construction projects in Iran and five other countries. After collecting data collection, observations had been analyzed and 51 decision rules were generated, and the projects were classified. Eventually, in order to evaluate the performance of the generated rules, confusion matrix was applied, and the model was validated. Findings The results of the present study show that rough set theory (RST) can be an effective and valuable tool for building expert systems. Practical applications of these results along with limitations and future research are described. Originality/value Perhaps for the first time, in the present study, a number of large-scale construction projects are classified based on SSI. Applying RST for building rule-based system and classifying projects in construction project area are novel attempts undertaken in this paper. The rules induced in this study can be applied to develop a sustainable success prediction model in the future studies.
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-06-25T07:50:56Z
  DOI: 10.1108/ECAM-05-2016-0110
Modeling of workers’ learning behavior in construction projects
using agent-based approach
- Pages: 559 - 573
  Abstract: Engineering, Construction and Architectural Management, Volume 25, Issue 4, Page 559-573, May 2018.
  Purpose Learning as the way in which labor acquire new knowledge and skills has important strategic implications for the competitive advantage of an organization. The purpose of this paper is to present an agent-based modeling (ABM) approach to investigate the learning behavior of workers. The effect of interactions among different workers as well as the factors affecting the workers’ learning behavior is assessed using the proposed ABM approach. Design/methodology/approach For this purpose, the processes through which the competency value of worker is changed are understood and the workers’ learning behavior is modeled, taking account of various influencing factors such as knowledge flow, social ability to teach and forgetting factor. Findings The proposed model is implemented on a real steel structure project to evaluate its applicability and performance. The variation in the competency value of different workers involved in the project is simulated over time taking account of all the influencing factors using the proposed ABM approach. Practical implications In order to assess the effect of interactions among welders as well as the welders’ characteristics on their learning behavior, the competence value of different welders is evaluated. Originality/value This research presents an ABM approach to investigate the workers’ learning behavior. To evaluate the performance of the proposed ABM approach, it was implemented on a real steel structure project. The learning behavior of different welders (agents) was simulated taking account of their interactions as well as the factors affecting the welders’ learning behavior. The project involved the welding of a 240-ton steel structure. The initial project duration was estimated as 100 days. In this project, it has been planned to execute the welding process using three different welders namely welder A, B and C.
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-06-25T07:50:42Z
  DOI: 10.1108/ECAM-07-2016-0166
A taxonomy of performance shaping factors for shield tunnel construction
- Pages: 574 - 596
  Abstract: Engineering, Construction and Architectural Management, Volume 25, Issue 4, Page 574-596, May 2018.
  Purpose On shield tunnel construction (STC) site, human error is widely recognized as essential to accident. It is necessary to explain which factors lead to human error and how these factors can influence human performance. Human reliability analysis supports such necessity through modeling the performance shaping factors (PSFs). The purpose of this paper is to establish and validate a PSF taxonomy for the STC context. Design/methodology/approach The approach taken in this study mainly consists of three steps. First, a description of the STC context is proposed through the analysis of the STC context. Second, the literature which stretch across the PSF methodologies, cognitive psychology and human factors of STC and other construction industries are reviewed to develop an initial set of PSFs. Finally, a final PSF set is modified and validated based on STC task analysis and STC accidents cases. Findings The PSF taxonomy constituted by 4 main components, 4 hierarchies and 85 PSFs is established for human behavior modeling and simulation under the STC context. Furthermore, by comparing and evaluating the performance of STC PSF and existing PSF studies, the proposed PSF taxonomy meets the requirement for qualitative and quantitative analysis. Practical implications The PSF taxonomy can provide a basis and support for human behavior modeling and simulation under the STC context. Integrating PSFs into a behavior simulation model provides a more realistic and integrated assessment of human error by manifesting the influence of each PSFs on the cognitive processes. The simulation results can suggest concrete points for the improvement of STC safety management. Originality/value This paper develops a taxonomy of PSFs that addresses the various unique influences of the STC context on human behaviors. The harsh underground working conditions and diverse resources of system information are identified as key characteristics of the STC context. Furthermore, the PSF taxonomy can be integrated into a human cognitive behavior model to predict the worker’s behavior on STC site in future work.
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-06-25T07:50:46Z
  DOI: 10.1108/ECAM-06-2016-0155
Human resource management practices to improve project managers’ job
satisfaction
- Abstract: Engineering, Construction and Architectural Management, Ahead of Print.
  Purpose More attention should be paid to project managers’ (PMs) job satisfaction as they play an important role in ensuring projects are completed successfully. The purpose of this paper is to identify human resource management (HRM) policies and practices that lead to higher PMs’ job satisfaction. Design/methodology/approach A questionnaire survey was conducted on PMs who are working in construction firms and project management consultancy firms. Data were collected via random, convenience and snowball sampling. The data collected were analysed using partial least square-structural equation modelling, independent samples t-test and Pearson’s correlation. Findings The findings show that PMs who are satisfied with their firms’ HRM practices and job rewards also have higher job satisfaction. Several HRM strategies that give rise to higher job satisfaction are identified, e.g. a system to recognise and develop talent, and taking active steps to identify and develop backups in case of emergency. Unfortunately, some practices are not implemented to a significant extent, and these include: systematically recruiting and retaining talented PMs, encouraging PMs to plan for their careers, offering performance and development coaching, and appraising employees. Research limitations/implications The limitations include the low response rate and the relatively small sample size of 81. The profile of respondents is largely from construction companies with more than 150 staff, and, therefore, the findings are more applicable to medium- to large-sized construction firms. Practical implications The study identified many HRM practices and policies that are significantly associated with PMs’ job satisfaction, yet many of these are not implemented to a significant extent by the employers. The practical implication is that employers of PMs should systematically implement these in order that their PMs have higher job satisfaction which is important for a project’s success. Originality/value The originality of this research is that the HRM practices and policies that are associated with job satisfaction of PMs are uncovered. Its value is in showing that PMs derive greater job satisfaction when HRM policies encompass talent development, career coaching and a personalised management style. Among these important practices, those that have been neglected were also identified. The study offers recommendations on the HRM practices that firms should be put in place for their PMs to experience higher job satisfaction.
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-07-12T10:24:38Z
  DOI: 10.1108/ECAM-02-2017-0030
Resource levelling optimization model considering float loss impact
- Abstract: Engineering, Construction and Architectural Management, Ahead of Print.
  Purpose The purpose of this paper is to propose a Non-Linear Integer Programming (NLIP) model that solves the resource leveling problem while reducing the negative effect of the total float loss on risk. Design/methodology/approach An NLIP model is formulated to solve the resource leveling optimization problem incorporating float loss cost (FLC). The proposed model is implemented using “What’s Best solver” for Excel. The FLC is calculated using the float commodity approach. An example is solved using the proposed model in order to illustrate its applicability. Sensitivity analysis is also performed. Findings The results confirmed that resource leveling reduces the available float of non-critical activities; decreases schedule flexibility and reduces the probability of project completion. The probability of timely completion dropped from 50 percent (for the normal schedule with 32 resource fluctuations) to 13.5 percent for leveled resources with zero fluctuations. Using the proposed method, the number of resource fluctuations is 8 but the probability of completing the project on time improved to 20 percent. Practical implications The proposed model allows project managers to exercise new trade-offs between resource leveling and schedule flexibility which will ultimately improve the chances of successful project delivery. Originality/value Resource leveling techniques result in reducing the available total float for the non-critical activities. Existing methods focus on moving noncritical activities within their available float and ignore the impact of the resulting float loss. This reduces the schedule flexibility and increase the risk of project delays. The proposed model incorporates the FLC into the resource leveling optimization problem resulting in more efficient schedules with improved resource utilization while keeping some schedule flexibility.
  Citation: Engineering, Construction and Architectural Management
  PubDate: 2018-07-04T10:54:05Z
  DOI: 10.1108/ECAM-10-2016-0229