Four-pronged decision support framework for implementing industrialized construction projects

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ibrahim Yahaya Wuni ◽  
Geoffrey Qiping Shen ◽  
Adedayo Johnson Ogungbile ◽  
Jonathan Zinzi Ayitey
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Construction Projects ◽  
Organizational Factors ◽  
Construction Time ◽  
Stringent Requirement ◽  
Data Set ◽  
Content Type ◽  
Decision Support Framework ◽  
Decision Making Factors

Purpose Industrialized construction (IC) is promoted to address some of the ills associated with the processes and products of the traditional construction approach. With several successful projects, IC is progressively becoming a preferred alternative construction approach and spurred the interest of contractors, developers and housing authorities in the technology. Increasingly, these stakeholders are keen to ascertain the compatibility and feasibility of using IC in their projects. This paper aims to develop a knowledge-based decision support framework for implementing industrialized construction projects (ICPs) that can facilitate better and informed decision-making when deciding to implement ICPs. Design/methodology/approach A comprehensive literature review was implemented to recruit 40 decision support factors (DSFs) and grouped into project requirements, location and site attribute, labour considerations and organizational factors. A 3-member expert panel validated the relevance of 35 DSFs, which became candidates for a structured questionnaire survey of experts in 18 countries. Statistical techniques are used to evaluate and prioritize the DSFs, leading to the development of a conceptual framework. Findings Statistical analysis revealed 33 significant DSFs. The top five most significant factors that could influence the decision to implement IC in a project include a stringent requirement for project quality control, suitability of the design for IC, organizational readiness and competencies in ICPs, client receptivity to IC and the need to minimize field construction time. A framework of project requirements, location and site attributes, labour considerations and organizational factors was proposed as decision support. Practical implications The proposed framework may help to inform decision-making regarding the implementation of IC in a project. It has wider applicability because it includes technical, managerial and operational aspects of and the required competencies for IC, which are shared between project types and territories. The prioritized DSFs could be used as a guide when implementing IC, especially in countries where bespoke decision support systems cannot be developed. Originality/value The paper delineated the most important DSFs that are shared between IC project types and territories and can be used to investigate the compatibility of using IC in a proposed project. This research constitutes the first exclusive attempt at delineating, quantifying and ranking the sets of decision-making factors, drawing on international data set and contributes to the empirical checklist of DSFs for ICPs.

Making decision toward overseas construction projects

2019 ◽  
Vol 26 (2) ◽  
pp. 285-302 ◽  
Author(s):  
Wahyudi P. Utama ◽  
Albert P.C. Chan ◽  
Hafiz Zahoor ◽  
Ran Gao ◽  
Dwifitra Y. Jumas
Keyword(s):  
Decision Support ◽  
Construction Projects ◽  
Fuzzy Inference ◽  
Optimization Method ◽  
Preliminary Assessment ◽  
Anfis Model ◽  
Data Set ◽  
Inference System ◽  
Content Type ◽  
Neuro Fuzzy

Purpose The purpose of this paper is to introduce a decision support aid for deciding an overseas construction project (OCP) using an adaptive neuro fuzzy inference system (ANFIS). Design/methodology/approach This study presents an ANFIS approach as a decision support aid for assessment of OCPs. The processing data were derived from 110 simulation cases of OCPs. In total, 21 international factors observed from a Delphi survey were determined as assessment variables to examine the cases. The experts were involved to evaluate and judge whether the company should Go or Not Go for an OCP, based on the different parameter scenarios given. To measure the performance of the ANFIS model, root mean square error (RMSE) and coefficient of correlation (R) were employed. Findings The result shows that optimum ANFIS model indicating RMSE and R scores adequately near between 0 and 1, respectively, was obtained from parameter set of network algorithm with two input membership functions, Gaussian type of membership function and hybrid optimization method. When the model tested to nine real OCPs data, the result indicates 88.89 percent accurate. Research limitations/implications The use of simulation cases as data set in development the model has several advantages. This technique can be replicated to generate other case scenarios which are not available publicly or limited in terms of quantity. Originality/value This study evidences that the developed ANFIS model can predict the decision satisfactorily. Therefore, it can help companies’ management to make preliminary assessment of an OCP.

Decision making in highway construction: a systematic review and future directions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Afiqah R. Radzi ◽  
Rahimi A. Rahman ◽  
Shu Ing Doh
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Decision Support ◽  
Construction Projects ◽  
Highway Construction ◽  
The Body ◽  
Decision Criteria ◽  
Future Directions ◽  
Content Type ◽  
Decision Making Models

Purpose Various approaches have emerged to assist practitioners in making more informed decisions in highway construction projects. However, industry practitioners are still using subjective ways to make decisions. Also, researchers have developed tools and techniques with similar objectives. Lack of information on what has been developed might lead to those issues. Therefore, this paper aims to review trends of evolution, pinpoint strengths and gaps in the literature and identifies potential future directions for decision-making research in highway construction projects. Design/methodology/approach A systematic review was conducted on published articles on decision-making in highway construction projects using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) technique. Findings The analysis of 101 articles revealed that existing decision-making research in highway construction projects targets improvements in four areas: feasibility, conceptual, detailed scope and detailed design. The four areas consist of sixteen subthemes that are detailed in this study. In addition, most research involved developing decision support tools and systems as well as decision-making models, techniques and frameworks. Lastly, several research areas have emerged, such as adding more decision criteria including those with uncertainties, expanding existing decision-making models into decision support systems, benchmarking decision criteria between different sample populations and exploring inter-and intra-relationships between decision criteria. Originality/value This paper provides an overview of existing research on decision-making in highway construction projects. Also, it reveals research gaps in the body of knowledge to point out directions for future research. Finally, industry practitioners can use the findings to develop strategies for effective decision-making processes.

Extension of PROMETHEE for robot selection decision making

2016 ◽  
Vol 23 (4) ◽  
pp. 983-1014 ◽  
Author(s):  
Dilip Kumar Sen ◽  
Saurav Datta ◽  
S.S. Mahapatra
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Decision Support ◽  
Selection Process ◽  
Subjective Evaluation ◽  
Preference Ranking ◽  
Data Set ◽  
Subjective Data ◽  
Content Type ◽  
Robot Selection

Purpose – Robot selection is basically a task of choosing appropriate robot among available alternatives with respect to some evaluation criteria. The task becomes much more complicated since apart from objective criteria a number of subjective criteria need to be evaluated simultaneously. Plenty of decision support systems have been well documented in existing literature which considers either objective or subjective data set; however, decision support module with simultaneous consideration of objective as well as subjective data has rarely been attempted before. The paper aims to discuss these issues. Design/methodology/approach – Motivated by this, present work exhibits application potential of preference ranking organization method for enrichment evaluations (extended to operate under fuzzy environment) to solve decision-making problems which encounter both objective as well as subjective evaluation data. Findings – An empirical case study has been demonstrated in the context of robot selection problem. Finally, a sensitivity analysis has been performed to make the robot selection process more robust. A trade-off between objective criteria measure and subjective criteria measure has been shown using sensitivity analysis. Originality/value – Robot selection has long been viewed as an important decision-making scenario in the industrial context. Appropriate robot selection helps in enhancing value of the product and thereby, results in increased profitability for the manufacturing industries. The proposed decision support system considering simultaneous exploration of subjective as well as objective database is rarely attempted before.

Decision support in a fieldable laboratory management during an epidemic outbreak of disease

2016 ◽  
Vol 6 (3) ◽  
pp. 264-295 ◽  
Author(s):  
Olga Vybornova ◽  
Jean-Luc Gala
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Making Process ◽  
Information Flows ◽  
Content Type ◽  
Related Information ◽  
Decision Support Framework ◽  
Operational Improvement ◽  
Cultural Origins ◽  
Definition Of

Purpose The purpose of this paper is to analyze the decision-making process and provide a decision support framework for deployment of an on-site analytical capacity (a fieldable laboratory (FL)) to contain an expanding outbreak and protect public health. Design/methodology/approach The FL mission cycle consists of five successive interlinked phases with a set of operational functions (OFs) performed during the mission. The list of phases, OFs and their contents were iteratively developed during and after FL missions and validated with operational partners. Findings The well-defined structure of the FL domain appears as the best functional basis for tracking the decision-making process across the whole mission cycle. Description of all the FL elements and information flows addresses the major issue of interoperability of resources used by similar international capacities (inter-)acting as operational partners in global response to the crisis. Originality/value The work presents the first attempt in this field to systematically describe and chronologically organize the decisions taken by a FL manager and staff during all phases of the FL mission cycle. Definition of OFs with all the related information flows allows for comparison of procedures, their better planning and refining, validation of protocols, mutual training and operational improvement between FLs from different geographical, organizational and cultural origins.

Re-examining the effects of supplier integration on operations performance: a relational view

2017 ◽  
Vol 37 (12) ◽  
pp. 1702-1721 ◽  
Author(s):  
Yuanqiong He ◽  
Hongyi Sun ◽  
Wenbin Ni ◽  
Stephen C.H. Ng
Keyword(s):  
Decision Making ◽  
Product Complexity ◽  
Relational View ◽  
Competition Intensity ◽  
Data Set ◽  
Joint Decision ◽  
Competitive Intensity ◽  
Content Type ◽  
Supplier Integration ◽  
Operations Performance

Purpose The importance of supplier integration (SI) in improving firms’ performance has been previously identified but the effects of SI are complicated, as the relationship between supplier and buyer is full of uncertainty. The purpose of this paper is to re-examine the effects of SI on operations performance from a relational view. Design/methodology/approach Two strategies of integrating suppliers are theoretically presented: information sharing and joint decision making. Hypotheses are then developed on when SI influences operations performance, using product complexity and competitive intensity as moderating factors. The hypotheses are tested using a global survey data set, made up of 763 manufacturing firms from 22 countries. Findings The results indicate a positive relationship between SI and operations performance and that the moderating roles of product complexity and competition intensity are significant, but product complexity does not have significant moderation effects on the relationships between joint decision making and product quality/cost reduction. Research limitations/implications The moderators of product complexity and competitive intensity are not comprehensive. Future study into how and under what circumstances SI has the greatest effect will be of benefit. Originality/value This study makes theoretical contributions by exploring the strategies of SI through a relational view, and examining the effects of SI through the moderating roles of product complexity and competition intensity.

Causal ascription of rework in building and civil engineering projects

2014 ◽  
Vol 21 (1) ◽  
pp. 111-126 ◽  
Author(s):  
Palaneeswaran Ekambaram ◽  
Peter E.D. Love ◽  
Mohan M. Kumaraswamy ◽  
Thomas S.T. Ng
Keyword(s):  
Construction Projects ◽  
Civil Engineering ◽  
Small Data ◽  
Data Set ◽  
Content Type ◽  
Management Measures ◽  
Significant Difference ◽  
Quantitative Impact ◽  
Engineering Projects

Purpose – Rework is an endemic problem in construction projects and has been identified as being a significant factor contributing cost and schedule overruns. Causal ascription is necessary to obtain knowledge about the underlying nature of rework so that appropriate prevention mechanisms can be put in place. The paper aims to discuss these issues. Design/methodology/approach – Using a supervised questionnaire survey and case-study interviews, data from 112 building and engineering projects about the sources and causes of rework in projects were obtained. A multivariate exploration was conducted to examine the underlying relationships between rework variables. Findings – The analysis revealed that there was a significant difference between rework causes for building and civil engineering projects. The set of associations explored in the analyses will be useful to develop a generic causal model to examine the quantitative impact of rework on project performance so that appropriate prevention strategies can be identified and developed. Research limitations/implications – The limitations include: small data set (112 projects), which include 75 from building and 37 from civil engineering projects. Practical implications – Meaningful insights into the rework occurrences in construction projects will pave pathways for rational mitigation and effective management measures. Originality/value – To date there has been limited empirical research that has sought to determine the causal ascription of rework, particularly in Hong Kong.

Virtual reality-based decision support model for interior design and decoration of an office building

2019 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Kai Juan ◽  
Hao-Yun Chi ◽  
Hsing-Hung Chen
Keyword(s):  
Decision Making ◽  
Virtual Reality ◽  
Decision Support ◽  
Decision Support System ◽  
Interior Design ◽  
Support System ◽  
Decision Makers ◽  
Office Building ◽  
Design Decision ◽  
Content Type

Purpose The purpose of this paper is to develop a virtual reality (VR)-based and user-oriented decision support system for interior design and decoration. The four-phase decision-making process of the system is verified through a case study of an office building. Design/methodology/approach Different “spatial layouts” are presented by VR for users to decide their preference (Phase 1). According to the selected spatial layout, a “spatial scene” is constructed by VR and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to determine the spatial scene preference (Phase 2). Based on the binary integer programming method, the system provides the optimal preliminary solution under a limited decoration budget (Phase 3). Finally, the consistency between the overall color scheme and pattern is fine-tuned by VR in order to obtain the final solution (Phase 4). Findings The questionnaire survey results show that decision makers generally affirm the operation and application of VR, and especially recognize the advantages in the improvement of VR-based interior design feasibility, communication efficiency and design decision-making speed. The optimization of the costs and benefits enables decision makers to effectively evaluate the impact of design decisions on subsequent project implementation during the preliminary design process. Originality/value The VR-based decision support system for interior design retains the original immersive experience of VR, and offers a systematic multiple criteria decision- making and operations research optimization method, thus, providing more complete decision-making assistance. Compared with traditional design communication, it can significantly reduce cognitive differences and improve decision-making quality and speed.

Resource co-specialization in outsourcing of enterprise systems software

2019 ◽  
Vol 10 (5) ◽  
pp. 1015-1046 ◽  
Author(s):  
Sung Min Kim ◽  
Gopesh Anand ◽  
Eric C. Larson ◽  
Joseph Mahoney
Keyword(s):  
Firm Growth ◽  
Empirical Test ◽  
Enterprise Systems ◽  
Organizational Factors ◽  
Enterprise Software ◽  
Implementation Success ◽  
Data Set ◽  
Planning And Scheduling ◽  
Content Type ◽  
Advanced Planning

Purpose Enterprise systems are commonly implemented by firms through outsourcing arrangements with software vendors. However, deriving benefits from these implementations has proved to be a challenge, and a great deal of variation has been observed in the extent of value generated for client and vendor firms. This research examines the role of co-specialization as a strategy to make the most out of outsourced enterprise systems. The authors develop hypotheses relating resource co-specialization with two indicators of success for implementation of enterprise software: (1) exchange success and (2) firm growth. Design/methodology/approach The hypotheses are tested using a unique panel data set of 175 firms adopting Advanced Planning and Scheduling (APS) software, a type of enterprise system used for managing manufacturing and logistics. The authors identify organizational factors that support co-specialization and then examine how co-specialization is associated with enterprise software implementation success, controlling for the endogenous choice to co-specialize. Findings The empirical results suggest that resource co-specialization is positively associated with implementation success and that the two resource co-specialization pathways that are examined complement each other in providing performance benefits. Originality/value This paper contributes to the research literature on outsourcing. The study also provides a new empirical test using a unique data set of 175 firms adopting APS Software.

Investigating sponsor decision-making: the role of schema theory, agency conflicts, and signaling theory in the persistence of naming rights agreements

2020 ◽  
Vol 21 (3) ◽  
pp. 467-486 ◽  
Author(s):  
Jonathan A. Jensen ◽  
David Head ◽  
Christopher Mergy
Keyword(s):  
Decision Making ◽  
Schema Theory ◽  
Agency Conflicts ◽  
Data Set ◽  
Content Type ◽  
Naming Rights ◽  
High Level ◽  
Sport Facilities

PurposeNaming rights sponsorships of sport facilities are among the most highly visible marketing agreements in the world. However, factors that may lead one sponsorship to persist for decades, while others end after just a few years, have yet to be investigated. Thus, this study examines the decision-making of brand marketers by investigating the predictors of a sponsoring brand's decision to either continue or dissolve such agreements.Design/methodology/approachUtilizing a global data set of 219 naming rights agreements, an empirical approach is utilized to isolate whether a variety of factors increase or decrease the probability of sponsorship dissolution.FindingsResults indicate that agreements entered into with new, as of yet-unnamed facilities lead to a reduction in the probability of dissolution, with a high level of brand equity also reducing the probability of dissolution. Agency conflicts may also play a role, as the sponsoring firm being headquartered in the same metropolitan area as the facility also contributes to the persistence of such agreements.Originality/valueThese results are intended to assist both sides of what is ideally a long-term relationship in better understanding the factors that may either contribute to or inhibit longer-term partnerships.

Optimizing time–cost in generalized construction projects using multiple-objective social group optimization and multi-criteria decision-making methods

2020 ◽  
Vol 27 (9) ◽  
pp. 2287-2313 ◽  
Author(s):  
Duc Hoc Tran
Keyword(s):  
Decision Making ◽  
Construction Projects ◽  
Project Managers ◽  
Multiple Objective ◽  
Cost Curve ◽  
Multi Criteria Decision Making ◽  
Construction Process ◽  
Time Cost ◽  
Content Type ◽  
Social Group Optimization

PurposeProject managers work to ensure successful project completion within the shortest period and at the lowest cost. One of the main tasks of a project manager in the planning phase is to generate the project time–cost curve, and furthermore, to determine the most appropriate schedule for the construction process. Numerous existing time–cost tradeoff analysis models have focused on solving a simple project representation without regarding for typical activity and project characteristics. This study aims to present a novel approach called “multiple-objective social group optimization” (MOSGO) for optimizing time–cost decisions in generalized construction projects.Design/methodology/approachIn this paper, a novel MOGSO to mimic the time–cost tradeoff problem in generalized construction projects is proposed. The MOSGO has slightly modified the mechanism operation from the original algorithm to be a free-parameter algorithm and to enhance the exploring and exploiting balance in an optimization algorithm. The evidential reasoning technique is used to rank the global optimal obtained non-dominated solutions to help decision makers reach a single compromise solution.FindingsTwo case studies of real construction projects were investigated and the performance of MOSGO was compared to those of widely considered multiple-objective evolutionary algorithms. The comparison results indicated that the MOSGO approach is a powerful, efficient and effective tool in finding the time–cost curve. In addition, the multi-criteria decision-making approaches were applied to identify the best schedule for project implementation.Research limitations/implicationsAccordingly, the first major practical contribution of the present research is that it provides a tool for handling real-world construction projects by considering all types of construction project. The second important implication of this study derives from research finding on the hybridization multiple-objective and multi-criteria techniques to help project managers in facilitating the time–cost tradeoff (TCT) problems easily. The third implication stems from the wide-range application of the proposed model TCT.Practical implicationsThe model can be used in early stages of the construction process to help project managers in selecting an appropriate plan for whole project lifecycle.Social implicationsThe proposal model can be applied to multi-objective contexts in diversified fields. Moreover, the model is also a useful reference for future research.Originality/valueThis paper makes contributions to extant literature by: introducing a method for making TCT models applicable to actual projects by considering general activity precedence relations; developing a novel MOSGO algorithm to solving TCT problems in multi-objective context by a single simulation; and facilitating the TCT problems to project managers by using multi-criteria decision-making approaches.

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