Please wait a minute...
Shopping Cart Email List Chinese
Advanced Search Fig/Tab
Frontiers of Engineering Management

ISSN 2095-7513

ISSN 2096-0255(Online)

CN 10-1205/N

Postal Subscription Code 80-905

Featured Articles  |  Most Downloaded  |  Most Reading
Online Submission Subscribe to Our RSS Content Feed
Front. Eng    2019, Vol. 6 Issue (2) : 221-238    https://doi.org/10.1007/s42524-019-0026-3
RESEARCH ARTICLE
Common biases in client involved decision-making in the AEC industry
Sujesh F. SUJAN1(), Arto KIVINIEMI2, Steve W. JONES1, Jacqueline M. WHEATHCROFT3, Eilif HJELSETH4
1. School of Engineering, University of Liverpool, Liverpool L69 3BX, UK
2. School of Architecture, University of Liverpool, Liverpool L69 3BX, UK
3. School of Psychological Sciences, University of Liverpool, Liverpool L69 3BX, UK
4. Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, NO-7491 Trondheim, Norway
 Download: PDF(703 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

Understanding of the constitution of client involved decisions is important for future improvements of the processes. Significant decisions in construction projects are reliant on heuristic processes where assumptions are developed from past experience. The paper presents a methodology to collect empirical data in an unstructured manner utilizing participant intuition and experience regarding project level collaboration, a term easily understood by practitioners. Empirical data collected from 6 focus group discussions in Norway and 18 individual interviews in Finland is associated with biases in decision making aimed at bridging the gap of understanding and literature’s insufficient coverage. An analytic framework was developed to suit the diverse emergence of concepts to allow application of psychological principles in a structured manner to empirical data. The paper contributes by identifying types of cognitive and motivational biases in client involved decisions. The biases are found to be alleviated by one another depending on the particular application of the decision. Findings suggest that normative beliefs exist developed from past experience and habitual thinking. A number of emerged biases in this domain are alleviated from normative beliefs which are discussed in this paper.
Keywords collaboration      construction industry      social science      decision-making      client      cognitive bias      motivational bias      holistic analysis      human factor     
Corresponding Author(s): Sujesh F. SUJAN   
Just Accepted Date: 20 March 2019   Online First Date: 22 April 2019    Issue Date: 17 May 2019
 Cite this article:   
Sujesh F. SUJAN,Arto KIVINIEMI,Steve W. JONES, et al. Common biases in client involved decision-making in the AEC industry[J]. Front. Eng, 2019, 6(2): 221-238.
 URL:  
https://academic.hep.com.cn/fem/EN/10.1007/s42524-019-0026-3
https://academic.hep.com.cn/fem/EN/Y2019/V6/I2/221
Fig.1  Client associated thematic interactions
Location Study 1: Finland Study 2: Norway
Level of Digital Technology Commonly Used Level 2 to 3 Level 2 to 3
Approach End to End, One Firm Perspective End to End perspective Multiple Firms
Duration 5 Days 5 Days
Method Focus Groups Nil 5 (14 participants)
Semi-Structured Interviews 18 individual interviews Nil
Qualitative Analysis Thematic Analysis
Participant Classification End-to-End Project Management (Design and Production Managers) 2 Contractors, 1 Project Management, 1 Public Client, 1 Consultant, 1 Industry Organisation
Tab.1  Overview of studies
Fig.2  Overview of participants
Role Frequency Description of role
Site engineer 2 Works with the site manager on site in being the lead team on site. Assists in managing the subcontractors and daily operations on site. Involved in motivating the subcontractors and dealing with design changes. Partially involved in procurement of sub-contractors
Service engineer 1 Pipe renovations from start to finish, design to production. Direct link to client and managing the designs and subcontractors
Site manager 4 The leader of production on site. Assisted by site engineers and holds a role to manage subcontractors and resources used on site. Also involved on site originating design changes
Design manager 3 The leader of the design teams; controls collaboration between design teams by the use of digital tools and big room discussions. Also involved in some circumstances in the procurement of design teams. Involved in 3 to 4 projects at the same time
IT development 2 A strategic organisational role involving process management to ensure that projects follow the strategy of the firm. Developing the process of construction continuously
Schedule Management 2 Managing the schedules of projects, at least 10 projects at a time. Developing a master schedule and then adding more detail as the process evolves
Procurement 1 Selection and controlling subcontractors. Development of subcontractor contracts
Development Manager 2 Manages developments that the company partially have a stake in from beginning to end mainly in residential developments
Research and Development 1 Involved in developing innovative ideas to improve productivity in the firm. Highly involved in developing an organization wide learning system
Tab.2  Study 1 participant role description
Category of firm Number of participants Description of firm and participants
Contractor 2 Involved in building and civil projects. Primarily running projects in Norway and have begun to work in Sweden. Privately owned firm and approximately 65% of shares are owned by employees. Participants are innovation managers in the firm
Contractor 3 Involved in civil and building construction in Norway. One of the largest contractors in Norway regarding building construction. Participants involved were involved in BIM driven innovation in teaching staff and developing process management
Design and Management Firm 4 Primarily a design firm who has the ability to manage the end-to-end construction process. One of Norway's top six design firms. Participants involved were an innovation manager, project design manager and a BIM coordinator/manager
Public Client 2 A Norwegian government funded client who is involved in the development, management and facilities management of buildings. The participants were involved at the strategic level in developing the use of innovative technologies e.g. BIM and developing client requirements
Professional Organisation 2 Participants were involved in the national development of standards and innovation development
Project Management Firm 3 A firm that controls the end-to-end process of construction projects similar to the firm in Study 1. The participants were involved in developing organisational strategies and innovations
Tab.3  Description of firms and participants in study 2
Fig.3  Analysis of empirical data overview
Tasks Method
1 Empirical Analysis Critical factor emergence from perception of researchers and participants a Thematic analysis A commonly used methodology in psychology to sort information collected qualitatively in a widely accepted manner
b Thematic structure interactions Interactions between themes are plotted in network diagrams which represents a visual tool that the researcher utilizes to understand the underlying processes
c Collation of critical factors Critical factors associated with a particular topic are selected based on empirical evidence from thematic analysis
2 Theoretical Analysis Association of bias from psychology a Literature review Keywords emerged from thematic analysis and the researcher's holistic understanding driven by data collected was used to associate psychological theories with bias in decision making
b Association of critical factors with psychological theories Understanding of biases are applied in client driven decisions by relating empirical evidence from critical factors to generalized definitions of phenomena found in psychology
Tab.4  Summary of analytic framework
Empirical critical factor Success characteristic Control-lability Failure characteristic Effect on information latency (IL) Possible reasoning How it can be controlled Strength of triangulation Key literature associated
Client Technical Knowledge (EC1) Client Representative is able to understand information in the manner that it is produced Medium Client Representative requires a different form of information to enable complete understanding Equivocality influencing client driven decisions negatively. If the client requires a simplified form of information, this adds more pressure on the teams; higher technical latency Not incentivised and lack of awareness of importance in client firms The involvement of an independent consultant bridging the gap of technical competency High Hedgren and Stehn (2014); Engström and Hedgren (2012); Neill and Rose (2007); Rachel Dinur (2011); Levander et al. (2011);Daft and Weick (1984);
Client Perception of Industry Culture (EC2) Client does not think the players are solely driven by individual profits Low Client decision is affected based on assumptions such as firms are driven by capitalistic and opportunistic goals which creates lack of trust between teams and client Negative influence on client decision making driven by heuristic based assumptions stemming from local industrial culture or past experience. Poor decision-making results in higher probability of technical latency Long-term traditional values running culturally in client firms; internal policies of client firms which are set to make the Client Representative think about cost control in a fixed manner resulting in lack of client trust Leadership strategies to make openness of finance critical in the contract, develop trust from the beginning of the project; rewards to teams that reduce cost drastically Medium Boukendour (2007), Van Duren and Voordijk (2015)
Hierarchy of Client Organisation Culture (EC3) Hierarchy in the client organization does not influence Client Representative; sufficient freedom to make decisions Low Long process in decision making as decisions are passed up the hierarchy Judgement/response selection delay as Decision making is slowed down, therefore creating a breakage in the flow of information The Client Representative is contracted to the client organization in a way that inflicts personal liability, Client Representative is in a position where faults can be traced back and made public Awareness to client organisations High Schneeweiß (1995); Kometa et al. (1996);Simon (1965)
Client involvement in contract development (EC4) Trusting the project management enough to give them leverage over teams Medium Client wants to be in the position of power, which puts the project management in a decentralised role When the leader has lower leverage to other teams, teams are prone to deliver information not on time or lacking in quality. If the contracts are direct to the client, there is risk of the client not having sufficient knowledge to make decisions. Financial leverage to the project management firm allows for control over the other teams Open dialog between the client and the project management when developing contracts early in the project progress Medium Che Ibrahim et al. (2015)
Client perception of own role (EC5) Client understands that there is need for high involvement and interaction with teams Medium Client only considerate to financial issues If the client is not involved optimally, cognitive latency can emerge from delayed/poor decision making Client's involvement is vital to the team's motivation and their own understanding of processes that teams utilize to interoperate Project management to raise awareness to the client of the need for consistent involvement throughout the project High Loosemore and Richard (2015); Thompson (1991); Rajakallio et al. (2017);
Client knowledge of own needs (EC6) Client's needs do not change through the process of design and construction Low Client needs constantly evolved putting pressure on teams to provide solutions systemically, bringing uncertainty of extra work claims in accordance to the contract More information flow due to extra work, repetition of tasks reduces motivation, therefore higher probability of latent information The client needs affect the client requirements that teams are developing a product for, therefore, if the requirements consistently change, this brings inefficiency Client to use forms of virtual reality to understand what is needed High Loosemore and Richard (2015); Kometa et al. (1996);
Clients influence on team selection (EC7) Client oversees team selection in a transparent manner with the project management Medium Client selects teams without consulting project management The non-optimal selection of teams can bring about lacking trust and motivation, teams do not have the skills and characteristics to interoperate; Team selection is critical in ensuring that teams can interoperate efficiently with the skills, personality and experience they have Client to trust the project management to enable a open procurement strategy not only based on skills but previous experiences High Che Ibrahim et al. (2015); Briscoe et al. (2004); De Araújo et al. (2017); Kometa et al. (1996); Loosemore and Richard (2015)
Client Financial Stability and Flexibility (EC8) Client is able to finance major changes to the budget mainly due to changing client requirements Low Client changes requirements with insufficient financial flexibility Lack of motivation as the finance is not flexible enough to take on the changes requested; susceptibility to IL The lack of financial flexibility can bring about less motivation to teams when the client requirements change as they question whether they can be paid as agreed. Extra works claims can be rejected Leadership to plan the financial part of the project with more contingency if client needs will change and if the client is less financially flexible Medium Kometa et al. (1996)
Client Attitude (EC9) A more consulting attitude Low An enforcing attitude A client with a consulting attitude can utilize teams to make suitable decisions to reduce risk of IL The client's attitude makes the consultants fear to be open about innovative solutions Awareness to client organisations High Kometa et al. (1996)
Client perception of early investment on processes (EC10) Client accepts early investment on processes understanding that information delivery can be streamlined for future benefit in the project Low Client does not see the value in early investment on processes More streamlined processes allows for faster generation of information and therefore less technical latency Processes like scripting of repetitive tasks can be done to reduce the time taken and human resources allocated Client to improve understanding of technical aspects in the end to end construction process Low Hedgren and Stehn (2014); Simon (1965); Collins et al. (2017); Luo et al. (2016); Chang and Chiu (2005); Loosemore and Richard (2015); Briscoe et al. (2004); Pesämaa et al. (2018);
Client's criteria for success (EC11) Client promotes collaboration as part of their criteria for successful projects Low Client focuses on financial criteria for success Positive collaboration can improve information flow in numeral ways both cognitively and technically, enabled by increased openness Client demands are treated seriously by teams employed and therefore would make collaboration important Awareness to client organisations Medium Karen and Le (2015); Babaeian Jelodar et al. (2016); Pesämaa et al. (2018); Kometa et al. (1996); Loosemore and Richard (2015); Briscoe et al. (2004);
Tab.5  Empirical Findings
Fig.4  Conceptual overview of findings and existing knowledge
Observed problem Examples of emersion Name of biases associated
Psychophysically based errors Association based errors
O1: The definition of client needs (EC6) The clients do not know what they want to achieve so it is hard to set goals Gain-loss Myopic problem representation
Omission of important variables
O2: Lack of client knowledge (EC1, EC7, EC10) Not enough skill in the clients to move to value-based procurement Gain-loss Overconfidence
Myopic problem representation
Omission of important variables
Confirmation
O3: Perception of teams having strong financial goals (EC2) Clients feel that there is catch but you cannot see it, they think the building industry is all about making money out of the client Gain-loss Availability/Ease of recall
O4: Openness about finance (EC8) Blind spot in extra work, it can be looked as a modification or not, it brings arguments Anchoring Confirmation
Overconfidence
O5: Inefficient financial model to foster collaboration (EC4, EC6) Penalties for scheduling, we are trying to adopt reward based system Anchoring Overconfidence
O6: Lack of flexibility in client needs (EC6) The BIM manual that the client provides is high in detail, no-one uses it, they are too detailed Equalising bias Myopic problem representation
O7: Lack of use of new contractual models (EC4) Reluctance from clients to use new contracts Gain-loss
O8: Enforcing client attitude (EC2, EC5, EC7, EC9, EC11) The client didn’t try to promote and create a cooperative environment and made controlling decisions based on a fixed budget' which made teams stuck Confirmation
O9: Personal liability (EC3) Counting every cent' as the decision maker is personally liable and not made to feel protected Affect influenced
Tab.6  Association of bias with observed problem from empirical evidence
1 IAjzen (1985). From intentions to actions: A theory of planned behavior. Action Control, Springer, 11–39
2 IAjzen (2002). Residual effects of past on later behavior: Habituation and reasoned action perspectives. Personality and Social Psychology Review, 6(2): 107–122
https://doi.org/10.1207/S15327957PSPR0602_02
4 M BBabaeian Jelodar, T WYiu, SWilkinson (2016). Assessing contractual relationship quality: Study of judgment trends among construction industry participants. Journal of Management Engineering, 33(1): 04016028
https://doi.org/10.1061/(ASCE)ME.1943-5479.0000461
5 M HBazerman, D A Moore (2008). Judgment in Managerial Decision Making. Hoboken, New Jersey: John Wiley & Sons, Inc.
6 SBoukendour (2007). Preventing post-contractual opportunism by an option to switch from one contract to another. Construction Management and Economics, 25(7): 723–727
https://doi.org/10.1080/01446190701392994
7 VBraun, V Clarke (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2): 77–101
https://doi.org/10.1191/1478088706qp063oa
8 G HBriscoe, A R J Dainty, S J Millett, R H Neale (2004). Client-led strategies for construction supply chain improvement. Construction Management and Economics, 22(2): 193–201
https://doi.org/10.1080/0144619042000201394
9 A SChang, S H Chiu (2005). Nature of engineering consulting projects. Journal of Management Engineering, 21(4): 179–188
https://doi.org/10.1061/(ASCE)0742-597X(2005)21:4(179)
10 C K IChe Ibrahim, S BCostello, SWilkinson (2015). Key indicators influencing the management of team integration in construction projects. International Journal of Managing Projects in Business, 8(2): 300–323
https://doi.org/10.1108/IJMPB-04-2014-0028
11 PCheckland (2000). The emergent properties of SSM in use: A symposium by reflective practitioners. Systemic Practice and Action Research, 13(6): 799–823
https://doi.org/10.1023/A:1026431613200
65 WCollins, K Parrish, G EGibson Jr (2017). Development of a project scope definition and assessment tool for small industrial construction projects Journal of Management in Engineering, 33(4): 4017015
https://doi.org/10.5465/amr.1984.4277657
12 R LDaft, K E Weick (1984). Toward a model of organizations as interpretation systems. Academy of Management Review, 9(2): 284–295
https://doi.org/10.5465/amr.1984.4277657
66 M C BDe Araújo, L HAlencar, C MDe Miranda Mota (2017). Project procurement management: A structured literature review. International Journal of Project Management, 35(3): 353–377
https://doi.org/10.5465/amr.1984.4277657
13 CDietrich (2010). Decision making: Factors that influence decision making, heuristics used, and decision outcomes. Inquiries Journal/Student Pulse
14 Z,Dörnyei D T Griffee (2010). Research methods in applied linguistics. tesol journal (tj), 1(1): 181–183
https://doi.org/10.5054/tj.2010.215611
15 JDu, Z Zou, YShi, DZhao (2018). Zero latency: Real-time synchronization of BIM data in virtual reality for collaborative decision-making. Automation in Construction, 85: 51–64
https://doi.org/10.1016/j.autcon.2017.10.009
16 H JEinhorn, R M Hogarth (1981). Behavioral decision theory: Processes of judgement and choice. Annual Review of Psychology, 32(1): 53–88
https://doi.org/10.1146/annurev.ps.32.020181.000413
17 SEngström, E Hedgren (2012). Sustaining inertia? Construction clients’ decision-making and information-processing approach to industrialized building innovations. Construction Innovation, 12(4): 393–413
https://doi.org/10.1108/14714171211272180
18 M LFinucane, A Alhakami, PSlovic, S MJohnson (2000). The affect heuristic in judgments of risks and benefits. Journal of Behavioral Decision Making, 13(1): 1–17
https://doi.org/10.1002/(SICI)1099-0771(200001/03)13:1<1::AID-BDM333>3.0.CO;2-S
19 C RFox, D Bardolet, DLieb (2005). Partition dependence in decision analysis, resource allocation, and consumer choice. In: Zwick R, Rapoport A, eds. Experimental Business Research. Springer, 229–251
20 C RFox, R T Clemen (2005). Subjective probability assessment in decision analysis: Partition dependence and bias toward the ignorance prior. Management Science, 51(9): 1417–1432
https://doi.org/10.1287/mnsc.1050.0409
21 TGilovich, D Griffin, DKahneman (2002). Heuristics and Biases: The Psychology of Intuitive Judgment. Cambridge: Cambridge University Press
22 EHedgren, L Stehn (2014). The impact of clients’ decision-making on their adoption of industrialized building. Construction Management and Economics, 32(1–2): 126–145
https://doi.org/10.1080/01446193.2013.833340
23 S KJacobi, B F Hobbs (2007). Quantifying and mitigating the splitting bias and other value tree-induced weighting biases. Decision Analysis, 4(4): 194–210
https://doi.org/10.1287/deca.1070.0100
24 P AJargowsky (2005). Omitted Variable Bias. In: Kempf-Leonard K, ed. Encyclopedia of Social Measurement. New York: Elsevier, 919–924
25 DKahneman, A Tversky (1979). On the interpretation of intuitive probability: A reply to Jonathan Cohen. Cognition, 7(4): 409–411
https://doi.org/10.1016/0010-0277(79)90024-6
26 MKaren, C Le (2015). Collaborative learning model of infrastructure construction: A capability perspective. Construction Innovation, 15(3): 355–377
https://doi.org/10.1108/CI-05-2014-0031
27 HKerzner (2017). Project Management: A Systems Approach to Planning, Scheduling, and Controlling. Hoboken, New Jersey: John Wiley & Sons
28 S TKometa, P O Olomolaiye, F C Harris (1996). A review of client-generated risks to project consultants. International Journal of Project Management, 14(5): 273–279
https://doi.org/10.1016/0263-7863(96)84510-8
29 PLegrenzi, V Girotto (1996). Mental models in reasoning and decision making processes. Mental Models in Cognitive Science, 95–118
30 PLegrenzi, V Girotto, P NJohnson-Laird (1993). Focussing in reasoning and decision making. Cognition, 49(1–2): 37–66
https://doi.org/10.1016/0010-0277(93)90035-T pmid: 8287674
31 ELevander, S Engström, YSardén, LStehn (2011). Construction clients’ ability to manage uncertainty and equivocality. Construction Management and Economics, 29(7): 753–764
https://doi.org/10.1080/01446193.2011.595423
32 I PLevin, S L Schneider, G J Gaeth (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76(2): 149–188
https://doi.org/10.1006/obhd.1998.2804 pmid: 9831520
33 SLichtenstein, B Fischhoff (1977). Do those who know more also know more about how much they know. Organizational Behavior and Human Performance, 20(2): 159–183
https://doi.org/10.1016/0030-5073(77)90001-0
34 MLoosemore, J Richard (2015). Valuing innovation in construction and infrastructure: Getting clients past a lowest price mentality. Engineering, Construction, and Architectural Management, 22(1): 38–53
https://doi.org/10.1108/ECAM-02-2014-0031
67 LLuo, Q H Ge, J XXie, D LYang (2016). Investigating the relationship between project complexity and success in complex construction projects. Journal of Management in Engineering, 33(2): 4016036
https://doi.org/10.1108/ECAM-02-2014-0031
35 KManley (2006). The innovation competence of repeat public sector clients in the Australian construction industry. Construction Management and Economics, 24(12): 1295–1304
https://doi.org/10.1080/01446190600934953
36 GMontibeller, D von Winterfeldt (2015). Cognitive and motivational biases in decision and risk analysis. Risk Analysis. International Journal (Toronto, Ont.), 35(7): 1230–1251
https://doi.org/10.1111/risa.12360 pmid: 25873355
37 D AMoore, P J Healy (2008). The trouble with overconfidence. Psychological Review, 115(2): 502–517
https://doi.org/10.1037/0033-295X.115.2.502 pmid: 18426301
38 AMurray (2013). Information Technology Law: The Law and Society. Oxford: Oxford University Press
39 SNeill, G M Rose (2007). Achieving adaptive ends through equivocality: A study of organizational antecedents and consequences. Journal of Business Research, 60(4): 305–313
https://doi.org/10.1016/j.jbusres.2006.10.020
40 R SNickerson (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2): 175–220
https://doi.org/10.1037/1089-2680.2.2.175
41 J WPayne, J R Bettman, D A Schkade, N Schwarz, RGregory (1999). Measuring constructed preferences: Towards a building code. Elicitation of Preferences. Springer, 243–275
42 OPesämaa, J Larsson, PErik Eriksson (2018). Role of performance feedback on process performance in construction projects: Client and contractor perspectives. Journal of Management Engineering, 34(4): 04018023
https://doi.org/10.1061/(ASCE)ME.1943-5479.0000619
43 S EPhelan (2001). What is complexity science, really? Emergence, A Journal of Complexity Issues in Organizations and Management, 3: 120–136
44 ARachel Dinur (2011). Common and un-common sense in managerial decision making under task uncertainty. Management Decision, 49(5): 694–709
https://doi.org/10.1108/00251741111130797
45 KRajakallio, M Ristimäki, MAndelin, SJunnila (2017). Business model renewal in context of integrated solutions delivery: A network perspective. International Journal of Strategic Property Management, 21(1): 72–86
https://doi.org/10.3846/1648715X.2016.1249533
46 R WRieber, D K Robinson (2001). Wilhelm Wundt in History: The Making of a Scientific Psychology. Berlin: Springer Science & Business Media
47 CRuppert-Winkel, R Arlinghaus, SDeppisch, KEisenack, DGottschlich, BHirschl, BMatzdorf, TMölders, MPadmanabhan, KSelbmann, RZiegler, TPlieninger (2015). Characteristics, emerging needs, and challenges of transdisciplinary sustainability science: Experiences from the German Social-Ecological Research Program. Ecology and Society, 20(3): 20
https://doi.org/10.5751/ES-07739-200313
68 CSchneeweiβ (1995). Hierarchical structures in organisations: A conceptual framework. European Journal of Operational Research, 86(1): 4–31
https://doi.org/10.5751/ES-07739-200313
48 R RSenescu, G Aranda-Mena, J RHaymaker (2012). Relationships between project complexity and communication. Journal of Management Engineering, 29(2): 183–197
https://doi.org/10.1061/(ASCE)ME.1943-5479.0000121
49 A KShah, D M Oppenheimer (2008). Heuristics made easy: An effort-reduction framework. Psychological Bulletin, 134(2): 207–222
https://doi.org/10.1037/0033-2909.134.2.207 pmid: 18298269
50 H ASimon (1965). Administrative Behavior: A Study of Decision-making Process in Administrative Organisation. Burlington: Free Press
51 PSlovic, M L Finucane, E Peters, D GMacGregor (2004). Risk as analysis and risk as feelings: Some thoughts about affect, reason, risk, and rationality. Risk Analysis, 24(2): 311–322
https://doi.org/10.1111/j.0272-4332.2004.00433.x pmid: 15078302
52 PThompson (1991). The client role in project management. International Journal of Project Management, 9(2): 90–92
https://doi.org/10.1016/0263-7863(91)90066-5
53 ATversky, D Kahneman (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2): 207–232
https://doi.org/10.1016/0010-0285(73)90033-9
54 ATversky, D Kahneman (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157): 1124–1131
https://doi.org/10.1126/science.185.4157.1124 pmid: 17835457
3 ATversky, D Kahneman (1981). The framing of decisions and the psychology of choice. Science, 211(4481): 453–458
https://doi.org/10.1126/science.7455683 pmid: 7455683
55 JVan Duren, H Voordijk (2015). Perceptions of success in performance-based procurement. Construction Innovation, 15(1): 107–128
https://doi.org/10.1108/CI-04-2014-0022
56 PVandenbroeck, R Dechenne, KBecher, MEyssen, KVan den Heede (2014). Recommendations for the organization of mental health services for children and adolescents in Belgium: use of the soft systems methodology. Health Policy (Amsterdam), 114(2-3): 263–268
https://doi.org/10.1016/j.healthpol.2013.07.009 pmid: 23932415
57 T OVuori, Q N Huy (2016). Distributed attention and shared emotions in the innovation process: How Nokia lost the smartphone battle. Administrative Science Quarterly, 61(1): 9–51
https://doi.org/10.1177/0001839215606951
58 K EWeick (1979). The Social Psychology of Organizing (Topics in Social Psychology Series). Columbus, OH: McGraw-Hill Humanities
59 J MWheatcroft, L JAlison, DMcGrory (2012). The influence of trust on senior investigating officers’ decision-making in high-profile critical incidents. Police Quarterly, 15(4): 386–413
https://doi.org/10.1177/1098611112447610
60 D VWinterfeldt, WEdwards (1986). Decision Analysis and Behavioral Research. Cambridge: Cambridge University Press
61 C HWong, G D Holt, P A Cooper (2000). Lowest price or value? Investigation of UK construction clients’ tender selection process. Construction Management and Economics, 18(7): 767–774
https://doi.org/10.1080/014461900433050
62 MZolghadri, C Eckert, SZouggar, PGirard (2011). Power-based supplier selection in product development projects. Computers in Industry, 62(5): 487–500
https://doi.org/10.1016/j.compind.2010.12.001
[1] Xiaoxiao XU, Patrick X. W. ZOU. System dynamics analytical modeling approach for construction project management research: A critical review and future directions[J]. Front. Eng, 2021, 8(1): 17-31.
[2] Yanrong LI, Shizhe PENG, Yanting LI, Wei JIANG. A review of condition-based maintenance: Its prognostic and operational aspects[J]. Front. Eng, 2020, 7(3): 323-334.
[3] Veronika BOLSHAKOVA, Annie GUERRIERO, Gilles HALIN. Identifying stakeholders’ roles and relevant project documents for 4D-based collaborative decision making[J]. Front. Eng, 2020, 7(1): 104-118.
[4] Lizzette PÉREZ LESPIER, Suzanna LONG, Tom SHOBERG, Steven CORNS. A model for the evaluation of environmental impact indicators for a sustainable maritime transportation systems[J]. Front. Eng, 2019, 6(3): 368-383.
[5] Jide SUN, Mian ZHENG, Martin SKITMORE, Bo XIA, Xincheng WANG. Industry effect of job hopping: an agent-based simulation of Chinese construction workers[J]. Front. Eng, 2019, 6(2): 249-261.
[6] Zeshui XU, Shen ZHANG. An overview on the applications of the hesitant fuzzy sets in group decision-making: theory, support and methods[J]. Front. Eng, 2019, 6(2): 163-182.
[7] Muhammad Tariq SHAFIQ, Jane MATTHEWS, Steve LOCKLEY, Peter E.D. LOVE. Model server enabled management of collaborative changes in building information models[J]. Front. Eng, 2018, 5(3): 298-306.
[8] Donald KENNEDY, Simon P. PHILBIN. The imperative need to develop guidelines to manage human versus machine intelligence[J]. Front. Eng, 2018, 5(2): 182-194.
[9] Yongling ZHU, Qianqian SHI, Qian LI, Zhimei YIN. Decision-making governance for the Hong Kong-Zhuhai-Macao Bridge in China[J]. Front. Eng, 2018, 5(1): 30-39.
[10] Dongping CAO, Heng LI, Guangbin WANG. Impacts of building information modeling (BIM) implementation on design and construction performance: a resource dependence theory perspective[J]. Front. Eng, 2017, 4(1): 20-34.
[11] Zhen-you Li,Ji-shan He,Meng-jun Wang. Improving Internationally Core Competences Based on the Capabilities of Precise and Accurate Project Management[J]. Front. Eng, 2016, 3(3): 231-238.
[12] Fei Dai,Yoojung Yoon,Hota V. GangaRao. State of Practice of Construction Site Safety in the USA[J]. Front. Eng, 2016, 3(3): 275-282.
[13] Ru-jiang Zhao,Wung Hee Moh. Value Management Practices on Major Construction Projects and Green Building[J]. Front. Eng, 2016, 3(2): 147-157.
[14] Da-yuan Li,Min Huang. Industrial Greening of the Dongting Lake Eco-economic Zone[J]. Front. Eng, 2015, 2(3): 228-233.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed