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*Corresponding Author: Sogand Mohammad Hasanzadeh M.S Student in Project Management and Construction, Shahid Beheshti University, Tehran, Iran. E-mail: [email protected]
Assessing the Applicability of Collaborative Procurement in Iranian Construction Industry
Mojtaba Hoseilalipour1, Sogand Mohammadhasanzadeh2, Mohammadreza Hafezi3
1Ph.D.in Project Management and Construction , Shahid Beheshti University, Tehran, Iran
2M.S Student in Project Management and Construction, Shahid Beheshti University, Tehran, Iran
1Ph.D.in Architecture, Shahid Beheshti University, Tehran, Iran
Received: June 24 2013 Accepted: September 23 2013
ABSTRACT
Since some of the recent prominent change faced by the construction industry, collaborative procurement has been prosperous in recent years. This new approach has been proved widely applicable within construction projects of United States, the United Kingdom, Australia, South Africa, Turkey, Sweden, Malaysia, Hong Kong and Japan;
however, Application and generalization of construction partnering in Iran is still in its inception. Through extensive literature review and data collected via semi-structured interviews and questionnaire in large contractor firms in construction industry, presented conceptual framework for assessing applicability of partnering in Iran’s construction industry. The essential context for overall assessment is summarized in two categories. First one is motivator elements –such as benefits, positive effects of partnering on project performance and technical and economic needs of organization- that encourage firms to participate in collaborative approach. On the other hand the expectations of a rapid movement toward integrated and collaborative systems were unrealistic, since this shift would need major modification of current conditions. Unfortunately like any new process, there are lots of challenges to implementing collaborative delivery method. These obstacles categorized in six distinct perspectives - organizational, cultural, economical, juridical/political, technical and individual barriers-.
The main purpose of this paper is to identify main barriers in implementing collaborative procurement in Iranian construction industry. This study uses a hybrid MCDM model based on analytic network process(FANP) and FDEMATEL technique to prioritize barriers. To this end, designing a fuzzy DEMATEL and fuzzy ANP questionnaire sent to twenty experts at partnering field in the construction industry. With using DEMATEL mathematical model, causal relations and their effects on each other are determined. Research results indicate that on one hand social barriers and on other hand political/juridical barriers are the most influence and the strongest connection to other criteria. Then based on these causal relations, factors are prioritized with using pairwise comparison logic and fuzzy group ANP method and the relative importance of each factor on application of partnering determined. The findings show that the collaborative approach could counter some of the requirements associated with the Iranian construction sector, although the implementation of this method face complications, mainly in terms of cultural change requirements , organizational barriers and political/juridical barriers. Also, using the calculation results, strategies were suggested separately for barriers in order to reduce their effect and facilitate movement toward more collaborative approach in the region.
KEYWORDS: Collaborative procurement, Partnering, Applicability, Construction industry, Iran, Fuzzy DEMATEL, Fuzzy ANP.
1.INTRODUCTION
The construction industry is one of the backbones of the economy in many countries (Ngai, S., Drew, D., Lo, H. P. and Skitmore, M. 2002).Furthermore, construction products have a large impact on safety, health, and environmental aspects (Bayliss, R., Cheung, S., Suen, H. and Wong, S.-P. 2004). For these reasons all human beings in modern societies are directly affected by the processes and/or the products of the construction industry (Ngai, S., Drew, D., Lo, H. P. and Skitmore, M. 2002). Due to the fragmented nature of construction, communication and coordination problems are common and affect project performance and productivity ( Li, Heng, Eddie WL Cheng, and Peter ED Love 2000). Because of differences in professional background, technology, knowledge and
perspective among participants, problems in communications and cooperation are commonplace, often compromising project performance and results (Chen T.T., and Wu F.y. 2010). Construction is a project-based industry, in which time and scope are seen in a narrow perspective ( Dubois, A. and Gadde, L.-E. 2000). Thus, relationships focus on the short-term, with actors attempting to lever what they can out of the existing contract, leading to opportunism. In many countries the construction industry has, over a long period, attracted criticism for its relationships, with conflicts and disputes, lack of trust and cooperation, poor customer focus and end-user involvement cited as significant amongst its shortcomings (Latham 1994); (Egan, Sir John and the Construction Task Force 1998); ( Ng, T., Rose, T., Mak, M. and Chen, S.E. 2002); (Chan, A., Chan, D. and Ho, K. 2003).Four essential differences between the traditional adversarial approach and the more recent trend towards partnering, namely: (1) an emphasis on cost rather than price, (2) a long-term rather than a short-term focus, (3) defect prevention in place of quality checks, and (4) single, rather than multiple sourcing (Black, C., A. Akintoye, et al.
2000); (V. S. 2009).
Some of the recent prominent changes faced by the construction industry are the increased competition, higher standards for competitive success, limited resources, existence of a global market/economy, need for more flexibility and faster response time, and the increased risk in construction projects (Dikmen, I, Birgonul, M T, Ozorhon, B and Eren, K . 2008), escalated conflicts and adversarial client–contractor relationships ( Bresnen M, Marshall N. 2000), increased complexity, uncertainty and time pressure that characterize construction projects (Erik 2007); (Pietroforte 1997), Partnering has been acknowledged by many researchers and practitioners for the last two decades as an innovative approach for the procurement of construction services effectively and it has become a primary management strategy for improving project performance and organizational relations(Dikmen, I, Birgonul, M T, Ozorhon, B and Eren, K . 2008). Coordination is an important process complementing collaboration. It defines working rules for a fruitful collaboration including conflicts identification, decision making process and follow-up traceability. In this climate of trust, decisions should be possible taken more rapidly and with a higher level of certainty (C. Dumoulin, P. Benning, Bouygues; J. Tulke, Hochtief; T. Laine, Granlund; M. Nour, Bauhaus; S.
Dehlin, N. Outters, NCC; MV. Salo, YIT; M. Pfitzner, Max Bögl 2011).Generally, greater cooperation relationships are argued to be a suitable antidote for many of the industry’s problems. In order to enhance a change towards increased cooperation, it seems suitable to first reflect upon the question: What are the main reasons for the lack of cooperation in construction projects (Erik 2007)?
1-1.Partnering in construction industry
“You have to partner today or you will miss the next wave. You cannot possibly acquire the technology fast enough, so partnering is essential.” ( Inkpen, A. C. and Ross, J. 2001) (Inkpen&Ross ,2001)
Partnering at its most basic level is a non-adversarial approach to procuring and engaging in construction projects.
It may be viewed in a number of different ways; an ethical framework (Wood, G., McDermott, P. and Swan, W 2002), a procurement approach (Cox, A. and Townsend, M. 1998), or a “bag of tools” to manage relationships (Barlow 1996);(Abdelnasr Omran, DRUICA E. 2011). The first broad application of this project partnering in construction industry was by the United States of America Army Corps of Engineers in the late 80s. In United Kingdom, it was first applied on the North Sea oil and gas industries in the early 1990s (Bennett 2000). In 1994 Sir Michael Latham came out with a reviewed partnering notion and it was commissioned by the UK government. It used in other countries in the early days including the United States, the United Kingdom, South Africa , Hong Kong, Turkey, Sweden, Malaysia, Australia; as well as Japan, where it deemed the “normal way of working in the local construction industry” ( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (Awodele, O.A., Ogunsemi, D.R. 2010). Through exploration into the State Procurement Law (SPL), new developments in Turkey, anticipated changes and the public construction process, (Koraltan, S.B.
and Dikbas, A. 2002) assessed the applicability of partnering in the Turkish construction sector (Lu SH., Yan H.
2007)proposed a framework for assessing the applicability of partnering, where management mechanism, organizations involved and project dimensions can be evaluated for determining partnering use. Although there is conformity over the general concept of partnering there is considerable variation of definition:
‘‘A long-term commitment by two or more organizations for the purpose of achieving specific business objectives by maximizing the effectiveness of each participant’s resources. This requires changing traditional relationships to a shared culture without regard to organization boundaries. The relationship is based upon trust, dedication to common goals, and an understanding of each other’s individual expectations and values. Expected benefits include improved efficiency and cost-effectiveness, increased opportunity for innovation, and the continuous improvement of quality products and services(Construction Industry Institute (CII) 1991).”
“A structured management approach to facilitate team working across contractual boundaries…it should not be confused with other good project management practice, or with longstanding relationships, negotiated contracts, or preferred supplier arrangement, all of which lack the structure and objective measures that must support a partnering relationship ((CIB) 1997).”
“Partnering is a set of strategic actions that deliver marked improvements in construction performance. It is driven by a clear understanding of mutual objectives and co-operative decision-making by multiple firms all focused on using feedback to continuously improve their joint performance(Bennet 1998).”
“A voluntary organized process by which multiple stake-holders having shared interests perform as a team to achieve mutually beneficial goals. It is based on establishing these goals early in the project lifecycle, building trusting relationships, and engaging in collaborative relationships. It requires empowering team members to solve problems at the lowest organizational level possible (Engineers 2010).”
Implementing cooperative relationships is however not an easy and straightforward task (Chan, A., Chan, D. and Ho, K. 2003); it should therefore be done in a proper way and for the proper reasons in suitable projects ( Bresnen M, Marshall N. 2000); ( Ng, T., Rose, T., Mak, M. and Chen, S.E. 2002). Partnering is best starting of course in an early stage of project’s age. Even though, starting partnering in late stage is better than not starting it at all at least to avoid disputes, so better late than never. But, it works better when starting as soon as the concept for the project is well known. (Benedict D. Ilozor and David J. Kelly 2012).
This paper reviews partnering related articles, since it was introduced to the international construction industry in the 1980s, to document motivator elements, possible barriers and critical failure factors to partnering implementation and coupled with expert interviews and Questionnaire survey, to assess the applicability and adaptability of construction partnering in the construction industry of Iran.
2.FRAMEWORK FOR ASSESSING APPLICABILITY OF PARTNERING IN CONSTRUCTION INDUSTRY
The following conceptual framework is presented through extensive literature review of collaborative procurement and employing semi-structured interviews with academic experts and active project managers in partnering projects.
The framework shows it is essential to analyze motivator elements and potential barriers of partnering application which may infer the feasibility of partnering implementation in the region(Figure 1).
Figure 1:Framework for assessing applicability of partnering in construction industry 2-1.Motivator elements involve:
-Benefits of partnering: Partnering offers many potential advantages over a traditional design-bid-build delivery model, but each team needs to determine why partnering is appropriate for them. In partnering evaluation, there are two types of benefits: direct and indirect benefits. The first one is measurable and quantifiable such as cost saving (Hong Yuming, Chan, M.ASCE D.W. M.; C., Chan Albert P.; and. Yeung John F. Y 2012); (AIA 2011); (Abdelnasr Omran, DRUICA E. 2011); (Skeggs 2010); (Awodele, O.A., Ogunsemi, D.R. 2010); ( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (Lu SH., Yan H. 2007); (M. 2005); (Beach R., Webster M. , Campbell K.M. 2005); (B. 2001);
(Haksever AM, Demir IH, Giran O. 2001); (Black, C., A. Akintoye, et al. 2000); (J. 2007); (Egan, Sir John and the Construction Task Force 1998); ((CIIA) 1996), time saving (Hong Yuming, Chan, M.ASCE D.W. M.; C., Chan Albert P.; and. Yeung John F. Y 2012); (AIA 2011); (A.-A. S. 2011); (Abdelnasr Omran, DRUICA E.
2011); (Skeggs 2010); (Awodele, O.A., Ogunsemi, D.R. 2010); ( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (Lu SH., Yan H. 2007); (M. 2005); (Beach R., Webster M. , Campbell K.M. 2005); (B. 2001); (Haksever AM, Demir IH, Giran O. 2001); (Black, C., A.
Akintoye, et al. 2000); (Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P. 1999); (Egan, Sir John and the Construction Task Force 1998); ((CIIA) 1996),reduced litigation (Hong Yuming, Chan, M.ASCE D.W.
M.; C., Chan Albert P.; and. Yeung John F. Y 2012); (Abdelnasr Omran, DRUICA E. 2011); (Skeggs 2010);
(Awodele, O.A., Ogunsemi, D.R. 2010);( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (Chan, A., Chan, D., Fan, L., Lam, P., and Yeung, J. 2008); (J. 2007);
(Lu SH., Yan H. 2007); (M. 2005); (Beach R., Webster M. , Campbell K.M. 2005); (B. 2001); (Haksever AM, Demir IH, Giran O. 2001); (Black, C., A. Akintoye, et al. 2000); (Egan, Sir John and the Construction Task Force 1998); ((CIIA) 1996),quality improvement (Hong Yuming, Daniel W.M. Chan, Albert P.C. Chan 2012);
(Abdelnasr Omran, DRUICA E. 2011); (Skeggs 2010); (Awodele, O.A., Ogunsemi, D.R. 2010);( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (J. 2007); (Lu SH., Yan H. 2007); (Beach R., Webster M. , Campbell K.M. 2005); (Law 2004); (B. 2001); (Haksever AM, Demir IH, Giran O. 2001); (Black, C., A. Akintoye, et al. 2000); (Egan, Sir John and the Construction Task Force 1998); ((CIIA) 1996),minimizing claims and disputes (A.-A. S. 2011); (Awodele, O.A., Ogunsemi, D.R.
2010);( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (Chan, A., Chan, D., Fan, L., Lam, P., and Yeung, J. 2008); (J. 2007); (M. 2005); (Beach R., Webster M.
, Campbell K.M. 2005); (B. 2001); (Haksever AM, Demir IH, Giran O. 2001); (Black, C., A. Akintoye, et al.
2000); (Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P. 1999); (Egan, Sir John and the Construction Task Force 1998),market advantage (AIA 2011); (Ruuska, I. and R. Teigland 2008); (Lu SH., Yan H. 2007); (Beach R., Webster M. , Campbell K.M. 2005); (B. 2001); (Haksever AM, Demir IH, Giran O. 2001);
(Black, C., A. Akintoye, et al. 2000); (Egan, Sir John and the Construction Task Force 1998)and etc..
Thesecond one is not easy to be measured but it comes as a result of partnering. It focuses on qualities such as improved long-term competitive advantages (Ruuska, I. and R. Teigland 2008); (Lu SH., Yan H. 2007); (Beach R., Webster M. , Campbell K.M. 2005); (B. 2001); (Haksever AM, Demir IH, Giran O. 2001); (Black, C., A.
Akintoye, et al. 2000); (Egan, Sir John and the Construction Task Force 1998), overcome design complexity (AIA 2011);(Awodele, O.A., Ogunsemi, D.R. 2010); (Beach R., Webster M. , Campbell K.M. 2005); (B. 2001);
(Haksever AM, Demir IH, Giran O. 2001); (Black, C., A. Akintoye, et al. 2000); (Egan, Sir John and the Construction Task Force 1998), Better communication and decision making ( Azlan-Shah Ali, Zuraidah Mohd- Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (Chan, A.P.C., Chan, D.W.M., Fan, L.C.N., Lam, P.T.I. and Yeung, J.F.Y. 2008); (M. 2005); (Beach R., Webster M. , Campbell K.M. 2005); (Law 2004), increasing customer satisfaction (A.-A. S. 2011); (Awodele, O.A., Ogunsemi, D.R. 2010); ( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul-Nizam Kamaruzzaman and Michael Pitt 2010); (Lu SH., Yan H. 2007); (Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P. 1999), innovation (Hong Yuming, Daniel W.M. Chan, Albert P.C. Chan 2012); ( Azlan-Shah Ali, Zuraidah Mohd-Don, Anuar Alias, Syahrul- Nizam Kamaruzzaman and Michael Pitt 2010); (Lu SH., Yan H. 2007); (Law 2004), enhancing the good reputation of the firms (A.-A. S. 2011); (Ruuska, I. and R. Teigland 2008); (Lu SH., Yan H. 2007); (Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P. 1999)and etc.
-Effect of partnering on the project performance: A more collaborative spirit among project members have been found to improve cost performance, such as elimination of cost overruns, controlling overall costs, and reducing administration costs ( Bresnen M, Marshall N. 2000); (Naoum 2003); (Chen W. T., Chen T. 2007);
(Keil 2007); (Löfgren, P. and Eriksson, P.E. 2009). Furthermore, construction projects with emphasis on collaboration rather than price and authority are more likely to eliminate time overruns (Larson, E. and Drexter, J.A. 1997), (Naoum 2003). Collaboration among project actors has also been found to improve quality by replacing the more traditional adversarial relationship with an atmosphere that fosters teamwork to achieve joint objectives (Chan, A., Chan, D. and Ho, K. 2003). Hence, in construction projects with great uncertainty high levels of trust and collaboration could lead to increased efficiency (Kadefors 2004); (Löfgren, P. and Eriksson, P.E. 2009).
-Organization needs(Technical / Economical):Five interviewed experts noticed that these needs will encourage organization to implement project in collaborative methods: lack of financial and technical skills to perform commitments, number of ongoing projects and not having enough time and resources, reduction in number of bidders and incensement of the chances of winning, implementing similar projects by partner, requirement to have expertise or a special certificate given owner, economically justified and increased competitiveness and requires collaboration to increase synergy.
2-2.Potential Barriers: On the other hand, partnering barriers and challenges could be categorized in six distinct perspectives :
organizational barriers include: dealing with large bureaucratic organizations, fear of Cooperation, internal Conflict, lack of general top management commitment and support, suspicious, risk-taking, organizational culture, climate and structure, failure to attain documented mutual understanding in the work environment, lack of strong institutional partnering norms in the industry (Hong Yuming, Daniel W.M. Chan, Albert P.C. Chan 2012);
(Lazar 1997); (Eriksson, P.E. and Nilsson, T. 2008); (A.-A. S. 2011); (Anvuur A.,Kumaraswamy M. 2007);
(Mahmud S. H. and Zhi Y. L. 2009); (Koraltan, S.B. and Dikbas, A. 2002); (Larson, E. and Drexter, J.A. 1997);
(Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P. 1999); (Post, J. and Altman, B. 1994);
(Childerhouse, P., Hermiz, R., Mason-Jones, R., Popp, A. and Towill, D. 2003);(Chan, A.P.C., Chan, D.W.M., Fan, L.C.N., Lam, P.T.I. and Yeung, J.F.Y. 2008);(M. 2005);(Chan, A.P.C., Chan, D.W.M., Chiang, Y.H., Tang, B.S., Chan, E.H.W. and Ho, K.S.K. 2004);( Ng, T., Rose, T., Mak, M. and Chen, S.E. 2002);(Kumaraswamy, M.; Ling, Florence Yean Yng; M., Rahman; and Siew Ting Phng. 2005);(Cheung, S.O., Suen, H.C.H, and Cheung, K.K.W.
2003);(H. 2010);(Gadde, L-E., Dubois 2010).
Cultural barriers include: Stakeholders who don’t develop a ”win-win” attitude, Potential for corruption induced by closer relationship, Lack of continuous open and honest communication, Stakeholders who don’t commit to the partnering arrangement, Relationship problems – adversarial relationship, distrust; partnering requires a mindset change for it to be successfully utilized, unwillingness to change (Hong Yuming, Daniel W.M. Chan, Albert P.C. Chan 2012); (Lazar 1997); (Eriksson, P.E. and Nilsson, T. 2008); (Mahmud S. H. and Zhi Y. L. 2009);
(Koraltan, S.B. and Dikbas, A. 2002); (Larson, E. and Drexter, J.A. 1997); (Matthews 1999); (Newcombe 1997);
(Liu, A.M.M. and Fellows, R.F. 1999); (Naaranoja M., Haapalainen, P. and Lonka, H. 2008); (Xu, T., Tiong, R.L.K., Chew, D.A.S. and Smith, N.J. 2005); (Ling, F.Y.Y., Ang, A.M.H. and Lim, S.S.Y. 2007); (Chan, A., Chan, D., Fan, L., Lam, P., and Yeung, J. 2008);(H. 2010);(M. 2005);(Chan, A.P.C., Chan, D.W.M., Chiang, Y.H., Tang, B.S., Chan, E.H.W. and Ho, K.S.K. 2004);( Ng, T., Rose, T., Mak, M. and Chen, S.E. 2002);(Kumaraswamy, M.;
Ling, Florence Yean Yng; M., Rahman; and Siew Ting Phng. 2005);(Cheung, S.O., Suen, H.C.H, and Cheung, K.K.W. 2003).
Economical barriers include: The current competitive tendering strategy for procuring construction projects is well-developed compared with other procurement strategies because the contracting parties have been accustomed to it for long, concerning significantly the costs arising from the implementation of partnering before the benefits are reaped through its practice, disruption of the prevailing gain-share /pain-share mechanism, risks or rewards were not shared directly, Difficulties in the financing and delivery of currency in terms of sanctions, difficulties in paying taxes (Hong Yuming, Daniel W.M. Chan, Albert P.C. Chan 2012); (Lazar 1997); (Mahmud S.
H. and Zhi Y. L. 2009); (Chan, A., Chan, D., Fan, L., Lam, P., and Yeung, J. 2008);(Erik 2007);(M. 2005);(Chan, A.P.C., Chan, D.W.M., Chiang, Y.H., Tang, B.S., Chan, E.H.W. and Ho, K.S.K. 2004);(Kumaraswamy, M.; Ling, Florence Yean Yng; M., Rahman; and Siew Ting Phng. 2005).
Juridical/ Political barriers include: including the environmental policy and legislation, government policy in partnering legislation, Issues being allowed to be escalated and assigned to separate contractors, the requirement to use competitive bidding because of regulations and sanctions condition (Hong Yuming, Daniel W.M. Chan, Albert P.C. Chan 2012); (Lazar 1997); (Eriksson, P.E. and Nilsson, T. 2008); (Wang, D.S., Hadavi, A. and Krizek, R.J. 2006); (Koraltan, S.B. and Dikbas, A. 2002); (Erik 2007);( Ng, T., Rose, T., Mak, M. and Chen, S.E. 2002).
Technical barriers include: In view of the current status of infertile practice of partnering, it could be easily perceived that lack of understanding of partnering concepts and process could be a critical problem which preventing its adoption within the construction industry. Technical barriers including Lack of training and guidance in the project partnering, incomprehension of the concept of partnering by participants, little experience with the partnering approach, unsuitability of Partnering for a particular project, absence of joint project database ( BIM ,IT- tools, PNet), lack of technical knowledge, problems with drawings and specifications (Hong Yuming, Daniel W.M.
Chan, Albert P.C. Chan 2012); (Larson, E. and Drexter, J.A. 1997); (Zhao, Z.Y., Liu, Y.S. and Wu, Y.N. 2005);
(Jiang 2008)); (Koraltan, S.B. and Dikbas, A. 2002); (Chan, A., Chan, D., Fan, L., Lam, P., and Yeung, J. 2008);(M.
2005);(Chan, A.P.C., Chan, D.W.M., Chiang, Y.H., Tang, B.S., Chan, E.H.W. and Ho, K.S.K. 2004);(Eriksson, P.E.
and Nilsson, T. 2008);(Cheung, S.O., Suen, H.C.H, and Cheung, K.K.W. 2003);( Ng, T., Rose, T., Mak, M. and Chen, S.E. 2002);(Kumaraswamy, M.; Ling, Florence Yean Yng; M., Rahman; and Siew Ting Phng. 2005).
Individual barriers include: Self attitude, lack of Empowerment, disinterest, indecision, doubt in partnering performance, misconception, unwillingness to change, unwillingness to compromise and reconciliation (A.-A. S. 2011); (Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P. 1999); ( Ng, T., Rose, T., Mak, M. and Chen, S.E. 2002).
3.METHODOLOGY
Application and generalization of construction partnering in Iran is still in its inception. There is no project clearly labeled as partnering projects, although the key elements of partnering can be observed in many projects.
Many of partnering projects are not officially called so, but instead they are called joint-ventures, joint-ownerships, consortiums, various forms of joint production and selling and so on(V. S. 2009).There are some projects in the field of Thermal and hydro-electric power plants construction that have used collaborative approach such as joint- Venture/consortium. Since these are only collaborative systems used in Iran, this research goes through the senior managements and project managements in these projects, interviewing and asking them to fill the questionnaire. The specific focus of this article will be investigating partnering affairs of large contractor firms which are active in construction sector and in Middle East especially in Iran. Since there is no evidence in the literature indicating that partnering is a management approach suitable for some countries but not the others (Koraltan, S.B. and Dikbas, A.
2002), exploring partnering applicability in Iran is conducive in order to unveil the main barriers of construction partnering which are Prevented from moving toward more integrated approaches in the region.
3-1. Fuzzy ANP and Fuzzy DEMATEL questionnaire design
This study uses 6 evaluation criteria and symbols as follows: (A1) organizational barriers, (A2) Cultural barriers, (A3) Economical barriers, (A4) Juridical/ External barriers, (A5) Technical barriers, (A6) Individual barriers. The fuzzy DEMATEL method is also used to evaluate the influence of each barrier in application of partnering. This research first designed a questionnaire for fuzzy DEMATEL and fuzzy ANP composed of three parts. The first part outlines each criteria definition for easy understanding and response. Using such pairwise comparison to collect the judgments of decision makers has important advantages. The relative importance or preference of the decision criteria are determined in a pairwise qualitatively comparison manner-using linguistic scale-Table 1&Table 2(Larimian T., Zarabadi Z. S. S. , Sadeghi A. 2013). This process allows the decision maker to concentrate on the comparison of just two objects, which makes the observation to a large extent independent from irrelevant effects. The third part is a pair-wise comparison to evaluate the influence of each barrier on the others, where scores of 0, 1, 2, 3 and 4 represent ‘‘no influence’’, ‘‘low influence”, ”normal influence”, ‘‘high influence’’, and ‘‘very high influence’’, respectively(Larimian T., Zarabadi Z. S. S. , Sadeghi A. 2013).
Linguistic terms Influence
score Triangular fuzzy numbers
l m u
No influence (No) 0
0.0
0.1 0.3
Very low influence (VL) 1
0.1
0.3 0.5
Low influence (L) 2
0.3
0.5 0.7
High influence (H) 3
0.5
0.7 0.9
Very high influence (VH) 4
0.7
0.9 1
Linguistic scale for importance Triangular fuzzy scale
Triangular fuzzy reciprocal scale
l m u
l m
u
Equally Preferred 1
1 1
1 1
1
Moderately Preferred 2
3 4
0.25 0.333
0.5
Strongly Preferred 4
5 6
0.166 0.2
0.25
very strongly Preferred 6
7 8
0.125 0.142
0.166
Extremely Preferred 9
9 9
0.111 0.111
0.111
Table 1: Linguistic scales for the importance weight of criteria (Fuzzy
DEMATEL)
Table 2 :Linguistic scale for importance(Fuzzy AHP)
4.MODEL PROPOSED
4-1. The calculation process of fuzzy DEMATEL method
The DEMATEL method was first conducted by The Battelle Memorial Institute through its Geneva Research Centre in 1973 .DEMATEL is an extended method for building and analyzing a structural model for analyzing the influence relation among complex criteria. However, making decisions is very difficult in fuzzy environment to segment complex factors. The current study uses the fuzzy DEMATEL method to obtain a more accurate analysis.
Specifically, the DEMATEL method is based on digraphs, which separate involved factors into cause group and effect group. Directed graphs, known as digraphs, are more useful than directionless graphs because digraphs demonstrate the directed relationships of sub-systems. The digraph may portray a basic concept of contextual relation among elements of a system, in which the values represent the strength of influence. Hence, The DEMATEL can convert the relationship between cause and effect factors into an intelligible structural model of the system. The DEMATEL can propose the most important criterion which affects other criteria(Chang B.; , Chang C.- W.; Wu, C.-H. 2011).
Step 1. Set up Direct-Relation Matrix T:The first step of the fuzzy DEMATEL analysis sets up a direct-relation matrix T from the data collected.
Step 2. Design the fuzzy linguistic variables: The study addresses response to the human logic variable, according to the linguistic variable (Table 1): no influence, very low influence, low influence, high influence and very high influence(Li 1999), and shows positive triangular fuzzy numbers (l, m, r)
As Table 1. The study transforms direct-relation matrix T into triangular fuzzy numbers as Table 3.
Zadeh proposed the fuzzy set theory and introduced the concept of membership function (Zadeh 1965). Fuzzy numbers refer to the fuzzy set on real line R and their membership function is µx(y) : R[0, 1],
A6
A2
A1
A5
A3
A4 A6
0.00
0.40
1.20
1.00
1.80
2.60
2.40
3.20
3.80
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20 A2
1.30
2.00
2.80
0.00
0.40
1.20
2.40
3.20
3.80
0.00
0.40
1.20
0.40
1.00
1.80
0.00
0.40
1.20 A10.60
1.20
2.00
0.30
0.80
1.60
0.00
0.40
1.20
1.00
1.80
2.60
0.00
0.40
1.20
0.00
0.40
1.20 A5
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20 A3
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20
0.10
0.60
1.40
0.00
0.40
1.20
0.00
0.40
1.20 A4
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20
0.00
0.40
1.20
1.40
2.20
3.00
0.00
0.40
1.20
Table 3: Direct-relation matrix F.
Step 3. Transform triangular fuzzy numbers into the initialdirect-relation matrix M: This study applies the triangular fuzzy number to obtain ideal solutions from group decision-making. Fuzzy linguistic variables are parts of human languages. Therefore, fuzzy numbers are used when dealing with human response. Fuzzy aggregation processes must include a defuzzification step. The CFCS (Converting Fuzzy data into Crisp Scores) defuzzification method is suitable for the fuzzy aggregation process. The CFCS method obtains a better crisp value. The questionnaires are defuzzified as a crisp value which obtains the Zij.The logistic formula computes the initial direct- relation matrixF according to CFCS method, thereby obtaining the initial direct-relation matrix M as Table 4.
Step 4. Obtain average value: The study obtains the average value of initial direct-relationmatrixes M from the total amount of all initial direct-relation matrixesM divided by 20 (the number of respondents).
Step 5. Set up the generalized direct-relation matrix N: The study obtains a generalized direct-relation matrix Nthrough the formula in which all principal diagonal elements are between 1 to zero. The generalized direct-relation matrix is shown as Table 5.
0121 . 24 0 . 8
1 max
1
1
nj
aij
k
N = 0.0121*M
14
M A6 A2
A1 A5
A3 A4
A 0.51 6 1.76
3.12 0.51
0.51 0.49
A 1.97 2 0.51
3.12 0.55
1.07 0.49
A 1.25 1 0.89
0.50 1.89
0.51 0.49
A 0.51 5 0.51
0.50 0.55
0.51 0.49
A 0.51 3 0.51
0.50 0.75
0.51 0.49
A 0.51 4 0.51
0.50 0.55
2.15 0.49
N A6 A2 A1
A5 A3
A4
A 0.06 6 0.21 0.38
0.06 0.06
0.06
A 0.24 2 0.06 0.38
0.07 0.13
0.06
A 0.15 1 0.11 0.06
0.23 0.06
0.06
A 0.06 5 0.06 0.06
0.07 0.06
0.06
A 0.06 3 0.06 0.06
0.09 0.06
0.06
A 0.06 4 0.06 0.06
0.07 0.26
0.06
Table 4:Initial direct-relation matrix M. Table 5:The generalized direct-relation matrix N.
Step 6. Set up the total-relation matrix T: The total-relation matrix T is acquired using Eq. bellow from the generalized direct-relation matrix. The total-relation matrix is shown as Table 6.
1T N I N
Step 7. Obtain the sum of rows and columns: The sum of rows and the sum of columns are separately denoted as D and R within the total-relation matrix T (Table 7).
Step 8. Set up degrees of central role and relation: The first calculation obtains amount from MATLAB. Second, in this step, we calculate these direct/indirect matrix T values. The results are showed inTable 7.
T A6 A2
A1 A5
A3 A4
A 0.37 6 0.46
0.79 0.36
0.29 0.20
A 0.54 2 0.35
0.82 0.39
0.36 0.22
A 0.35 1 0.29
0.38 0.42
0.23 0.17
A 0.17 5 0.16
0.23 0.18
0.16 0.12
A 0.18 3 0.17
0.24 0.20
0.16 0.12
A 0.21 4 0.20
0.28 0.22
0.39 0.14
D T R
D+R D-R
1.828 A1 2.731
4.558 -
0.903
2.673 A2 1.619
4.292 1.054
1.071 A3 1.589
2.660 -
0.518
1.434 A4 0.974
2.408 0.460
1.022 A5 1.758
2.780 -
0.735
2.463 A6 1.821
4.285 0.642
Table 6: Total-relation matrix T. Table 7: The degree of central role (D + R).
Step 9. Set up the causal diagram: The causal diagram was built by the horizontal axis (D + R) which is the degree of central role and vertical axis (D _ R) which is the degree of relation (Figure 2).
A1 A2 A3 A4 A5 A6
A1 -
- - - 0.39 0.35
A2 0.82
- 0.36 -
0.42 0.54
A3 -
- - - - -
A4 -
- 0.39 -
- -
A5 -
- - - - -
A6 0.79
0.46 -
- 0.36 -
Figure 2: The causal diagram.: (A1) organizational barriers, (A2) Cultural barriers, (A3) Economical barriers, (A4) Juridical/ External barriers, (A5) Technical barriers, (A6) Individual barriers
Table 8:The significant pattern of the main criteria
Degree of central role (D + R) in DEMATEL represents the strength of influences both dispatched and received. On the other hand, if (D _ R) > 0, then the evaluation criterion x dispatches the influence to other evaluation criteria more than it receives. If (D _ R) < 0, the evaluation criterion x receives the influence from other evaluation criteria more than it dispatched. The strategy map is an organizational strategy showing the relation between the cause and effect model. The study finds evaluation criteria of causal relationships from the fuzzy DEMATEL method to set up
A6 A2
A1 A5
A3 A4
-1.500 -1.000 -0.500 0.000 0.500 1.000 1.500
a strategy map. Based on the results of the total- relation matrix in Table 6, the causal relationships among partnering barriers are depicted as the strategy map (Figure 3).
Figure 3: Strategy map. (A1) organizational barriers, (A2) Cultural barriers, (A3) Economical barriers, (A4) Juridical/ External barriers, (A5) Technical barriers, (A6) Individual barriers
Figure 4: Structural difference between a hierarchy and a network.(a) a hierarchy (b) a network.
4-2. Analytic Network Process (ANP)
Analytic Network Process (ANP) is another MCDM method developed by Saaty in 1996, which is a generalization of AHP. In addition to hierarchical problems, ANP also supports problems which are modeled as a network instead of a hierarchy. In an ANP network, the criteria are collected in clusters and the influences between clusters are displayed by arrows. With these arrows, the method uses feedback and inner dependencies in problem, so the result becomes more reasonable and accurateFigure 4(YANAR L., Tozan H, Hloch S. 2012).
4-3. The calculation process of fuzzy ANP method
Fuzzy ANP technique uses both interdependence of criteria and inner dependence of criteria with pairwise comparison matrix. Chang’s extent analysis method is used to evaluate fuzzy pairwise comparisons. Chang’s (1996) extent analysis approach is explained in details.
Let X={ , … , } be an object sets, and G={ , … , } be a goal set. According to the method of Chang’s (1996) extent analysis, each object is taken and extent analysis for each goal is performed respectively. Therefore, m extent analysis values for each object can be obtained, with the following signs:
, , … , = 1,2, … ,
Where = 1,2, … , are triangular fuzzy numbers (TFNs)-Figure 5.The linguistic expression between criteria in paire-rise comparisons are rewrited by using fuzzy numbers and fuzzy average given in Table 9.
Fi = (li, mi, ui)
n
u u u n
m m m n
l l ge l
fuzzyavera n n ... n
... ,
... , 1 2 1 2
2 1
A1
A2
A3
A4
A5
A6 A11112.254
2.820
3.400
2.385
2.790
3.197
2.902
3.517
4.146
1.765
2.130
2.508
2.060
2.577
3.108 A20.294
0.355
0.444
1
1
1
3.035
3.744
4.458
3.983
4.593
5.213
2.354
2.920
3.500
2.588
3.247
3.913 A30.313
0.358
0.419
0.224
0.267
0.329
1
1
1
2.983
3.593
4.213
2.631
3.237
3.846
2.796
3.560
4.338 A40.241
0.284
0.345
0.192
0.218
0.251
0.237
0.278
0.335
1
1
1
0.638
0.869
1.124
0.546
0.688
0.867 A50.399
0.469
0.567
0.286
0.342
0.425
0.260
0.309
0.380
0.890
1.150
1.567
1
1
1
2.338
3.000
3.675 A60.322
0.388
0.485
0.256
0.308
0.386
0.231
0.281
0.358
1.154
1.454
1.832
0.272
0.333
0.428
1
1
1
Table 9: Fuzzy average of partnering barriers
A6
A4 A3
A1 A5
A2
16
= (1,1,1)⨁(2.254, 2.820, 3.400)⨁(2.385, 2.790, 3.197)⨁(2.902, 3.517, 4.146)⨁(1.765, 2.130, 2.508) (2.060, 2.577, 3.108) = (12.366, 14.835, 17.360)
M =
(12.366,14.835,17.360) M = (9.947, 12.016, 14.145) M = (5.172, 6.271, 7.613) M = (13.255, 15.858,
18.527) M = (2.854, 3.337, 3.921) M = (3.234, 3.765, 4.489)
The steps of Chang’s extent analysis can be given as in the following:
Step1: The value of fuzzy synthetic extent with respect to the ith object is defined as
= ∗ ( )
Interdependence of criteria
S1= (0.187, 0.265, 0.371) S3= (0.151, 0.214, 0.302) S5= (0.078, 0.112, 0.163) S2= (0.201, 0.283, 0.396) S4= (0.084, 0.060, 0.043) S6= (0.049, 0.067, 0.096)
Step2: The degree of possibility of = ( , , ) ≥ = ( , , )can be equivalently expressed as follows- Table 10-:
V(S > S ) = hgt(S ∩ S )
V(S ≥ S )
⎩
⎨
⎧ 1 if(m ≥ m ) 0 if(m ≥ m )
l − u
(m − u ) − (m − l ) else
The degree possibility The degree
possibility The degree
possibility
V(S1>S2) 0.903
V(S3>S1) 0.696
V(S5>S1) 0.000
V(S1>S3) 1.000
V(S3>S2) 0.597
V(S5>S2) 0.000
V(S1>S4) 1.000
V(S3>S4) 1.000
V(S5>S3) 0.105
V(S1>S5) 1.000
V(S3>S5) 1.000
V(S5>S4) 1.000
V(S1>S6) 1.000
V(S3>S6) 1.000
V(S5>S6) 1.000
V(S2>S1) 1.000
V(S4>S1) 1.000
V(S6>S1) 0.000
V(S2>S3) 1.000
V(S4>S2) 0.094
V(S6>S2) 0.000
V(S2>S4) 1.000
V(S4>S3) 0.820
V(S6>S3) 0.000
V(S2>S5) 1.000
V(S4>S5) 0.094
V(S6>S4) 1.000
V(S2>S5) 1.000
V(S4>S6) 0.820
V(S6>S5) 0.282
Table 10: Calculate degree of possibility
Step 3: The degree possibility for a convex fuzzy number to be greater than k convex fuzzy numbers ( = 1,2, … , )can be defined by
V(S > S , S , … , S ) = min V (S > S ) Assume that:
d'(Ai)=minV(Si≥Sk)
for k=1,2,…,n ;k ≠i. Then the weight vector is given by W' = (d'(A1), …, d'(An))
Where ( = 1,2, … , )are n elements- Table11.
Step 4: Via normalization, the normalized weight vectors are
=∑
Where W is a non-fuzzy number-Table 12(ERGİNEL, Nihal; ŞENTÜRK, Şevil. 2011).
4-3. Ultimate priority of partnering barriers by Fuzzy ANP & Fuzzy DEMATEL methods
So, for measuring their matrix of importance weights, we only use a total-relation fuzzy DEMATEL technique, introduced in section 5-1, instead of several fuzzy ANP matrices of even comparisons. We can do other stages of the model by using Super Decisions software. Because of the high quantity of the data
V(S1>Sk) 0.903
V(S2>Sk) 1.000
V(S3>Sk) 0.597
V(S4>Sk) 0.094
V(S5>Sk) 0.105
V(S6>Sk) 0.282
Figure 5: Linguistic scale for relative importance (ERGİNEL, Nihal; ŞENTÜRK, Şevil. 2011)
Table11: weight vector of criteria
V(S1>Sk) 0.303
V(S2>Sk) 0.335
V(S3>Sk) 0.200
V(S4>Sk) 0.032
V(S5>Sk) 0.035
V(S6>Sk) 0.095
Table 12:normalized weight vectors of criteria Figure 6: weight vectors of criteria with FAHP method and the conducted measurements, we only summarize the output of different super matrices and the final result of the model.
1Goal 2Criteria
Goal A1
A2 A3
A4 A5
A6
1Goal Goal
0 0
0 0
0 0
0
2Criteria A1
0.3029 0.3757
0.2908 0.2277
0.1670 0.4164
0.3503
A2 0.3355
0.8223 0.3469
0.3612 0.2169
0.3853 0.5403
0.2002 A3 0.2358
0.1663 0.1636
0.1223 0.2038
0.1790
A4 0.0316
0.2772 0.1955
0.3912 0.1437
0.2162 0.2104
A5 0.0352
0.2303 0.1624
0.1598 0.1194
0.1757 0.1748
0.0946 A6 0.7893
0.4570 0.2857
0.2045 0.3602
0.3665
Table 13: Non weight super-matrix of barriers In non-weight super matrixes (
Table 13), those parts that are colored as grey show the importance weight measured by the total-relation matrix in fuzzy DEMATEL technique, and other parts show the importance weights measured by the ANP method. Via normalization, the non-weight super matrixes are changed into weighted super matrix (normalized). The sum of the all columns of the functional super matrix (Table 14) are equal to One. So, with calculating the limit super matrix, final weight of each criterion is calculated with ANP technique (Figure 7).
1Goal 2Criteria
Goal A1
A2 A3
A4 A5
A6
1Goal Goal
0 0
0 0
0 0
0
2Criteria A1
0.3029 0.1376
0.1796 0.1433
0.1715 0.23 9
0.1923
A2 0.3355
0.3011 0.2143
0.2273 0.2227
0.2192 0.2966
0.2002 A3 0.0863
0.1027 0.1029
0.1256 0.1160
0.0983
0.0316 A4 0.1015
0.1208 0.2462
0.1476 0.1230
0.1155
A5 0.0352
0.0843 0.1003
0.1005 0.1226
0.0999 0.0960
A6 0.0946
0.2891 0.2823
0.1798 0.2100
0.2049 0.2012
Table 14: Functional super matrix of barriers 0.303
0.335
0.200
0.032 0.035 0.095
A1 A2 A3 A4 A5 A6
