Partnering relationships in construction: A literature review

Bygballe, Lena E.; Jahre, Marianne; Swärd, Anna

doi:10.1016/j.pursup.2010.08.002

Cited by 197 publications

(210 citation statements)

References 98 publications

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“…In another similar research, the same researchers developed a model for design and construction contracts through application of regression (Lam et al, 2008). In another research, Cheung et al (2008) On the other hand, several methods have been used for anticipation as follows,  Time series (Hwang, 2011;Wong et al, 2007)  Various regression methods (Cheung et al, 2010;Hwang, 2008;Wang & Gibson, 2010)  Neural networks (Cheung et al, 2006;Chua et al 1997;Ko & Cheng, 2007;Wang & Gibson, 2010)  Fuzzy logics (Ko & Cheng, 2007;Li et al, 2006;Young & Poon, 2013) In previous researches, most researchers and authors have recommended future researchers to provide their anticipator models with respect to things like localization in other countries, application of more precise and simple methods and a model for different phases of a project (Bygballe et al, 2010;Chang et al, 2013;davis, 2013;Eigbe et al, 2014;Han et al, 2007;Han et al , 2007;Petro & Gardiner, 2015).…”

Section: Anticipation Of Project Successmentioning

confidence: 99%

Diagnosing the success of the construction projects during the initial phases

Ghazimoradi¹,

Kheyroddin²,

Rezayfar³

2016

10.5267/j.dsl

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As construction projects are becoming more deployed and more complicated at the same time, having an instrument for anticipation of success has become a primary requirement for every stakeholder. On this basis, several models have been introduced which implement different methods for anticipation of the entire goals or a series of goals of projects. In this research, at the first step, 16 criteria as instruments of anticipation of success and 33 factors as required instruments for obtaining success were extracted through library studies, semi-structured interviews and the Delphi method. At the next step, by having 169 questionnaires filled by senior managers of construction projects, the importance and priority of each of these 16 criteria and 33 factors for the initial phases of projects were determined according to Iran's local conditions. Ultimately, through modeling of data by a propagation neural network including 35 hidden layers, the anticipator model for success of construction projects during their initial phases was developed with Performance and Regression. This model is able to anticipate the level of realization of projects' success criteria according to the level of realization of success factors at the initial phase.

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Section: Anticipation Of Project Successmentioning

confidence: 99%

Diagnosing the success of the construction projects during the initial phases

Ghazimoradi¹,

Kheyroddin²,

Rezayfar³

2016

10.5267/j.dsl

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“…There are several traits of suppliers' relationships. Firstly, their relationships are different from owner-contractor and contractorsubcontractor relationships that have been analyzed earlier [11]. The difference is that the relationships between suppliers are noncontractual relationships, while general relationships in project networks are contractual ones [12].…”

Section: Introductionmentioning

confidence: 96%

Cooperative Evolutionary Game and Applications in Construction Supplier Tendency

Shi

Zhu

2018

Complexity

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Major construction projects have a great influence on the national economy and society, wherein cooperative relationship between construction suppliers plays an increasingly significant role in the overall supply chain system. However, the relationships between suppliers are noncontractual, multistage, dynamic, and complicated. To gain a deeper insight into the suppliers' cooperative relationships, an evolutionary game model is developed to explore the cooperation tendency of multisuppliers. A replicator dynamic system is further formulated to investigate the evolutionary stable strategies of multisuppliers. Then, fourteen "when-then" type scenarios are concluded and classified into six different evolutionary tracks. Meanwhile, the critical influencing factors are identified. The results show that the suppliers' production capacity, owner-supplier contract, and the owner's incentive mechanism influence the cooperation tendency of suppliers directly. The managerial implications contribute to insightful references for a more stable cooperative relationship between the owner and suppliers.

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“…In a well working supply chain the coordination of all participants of the overall house project is an important aspect to delivering the house on time, with low costs and high quality standards (Lessing, 2006;Grundke & Wildemann,to the delivery of the house (Bygballe;Jahre & Swärd, 2010). The high number of companies involved in the process as well as the transportation and the construction/assembly of the modules on-site are some of the complexity drivers for the supply chain management (Arantes;Ferreira & Costa, 2015;Cheng;Law;Bjornsson;Jones & Sriram, 2010).…”

Section: Introductionmentioning

confidence: 99%

Impact Analysis of Complexity Drivers in the Supply Chain of Prefabricated Houses

Stroebele¹,

Kießling²

2017

JMS

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The lack of living space has recently increased particularly in urban centers. This deficiency cannot be remedied with the productivity status quo in the construction industry. One opportunity to significantly increase the productivity of the construction industry is the industrial modular construction. In order to achieve increased productivity, the value chain must act across the entire organization. A supply chain management is required to exploit the potential of the prefabricated construction. In order to develop a specific supply chain management, the corresponding complexity factors along the value chain must be known. The aim of the study is to quantify the essential factors which influence the value chain for prefabricated houses and form a basis for the future development of a supply chain management. The results of this scientific work clearly show that although an industrial modular production is carried out, the highest complexity drivers are still found on the construction site as well as in the logistics from the module production to the construction site. In addition, it is also apparent that special requirements as well as the size of the modules are decisive factors and as such need to be considered during the future development of the supply chain management concept.

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Partnering relationships in construction: A literature review

Cited by 197 publications

References 98 publications

Diagnosing the success of the construction projects during the initial phases

Diagnosing the success of the construction projects during the initial phases

Cooperative Evolutionary Game and Applications in Construction Supplier Tendency

Impact Analysis of Complexity Drivers in the Supply Chain of Prefabricated Houses

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