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Akbari, S, Pour Rahimian, F, Sheikhkhoshkar, M, Banihashemi, S and Khanzadi, M (2020) Dynamic sustainable success prediction model for infrastructure projects: a rough set based fuzzy inference system. Construction Innovation , 20(04), 545–67.

Lavikka, R , Seppänen, O, Peltokorpi, A and Lehtovaara, J (2020) Fostering process innovations in construction through industry–university consortium. Construction Innovation , 20(04), 569–86.

Marzouk, M and Zaher, M (2020) Artificial intelligence exploitation in facility management using deep learning. Construction Innovation , 20(04), 609–24.

O'Connor, J T and Mock, B (2020) Responsibilities and accountabilities for industrial facility commissioning and startup activities. Construction Innovation , 20(04), 625–45.

Suresh, M and Arun Ram Nathan, R (2020) Readiness for lean procurement in construction projects. Construction Innovation , 20(04), 587–608.

  • Type: Journal Article
  • Keywords: Construction projects; Lean readiness; Total interpretive structural modelling; Lean procurement; Procurement readiness; Purchase factors;
  • ISBN/ISSN: 1471-4175
  • URL: https://doi.org/10.1108/CI-07-2019-0067
  • Abstract:
    The purpose of this paper is to identify, analyse and categorize the major factors affecting lean procurement (LP) in a construction project of a company in India using total interpretive structural modelling (TISM) approach. The readiness factors identified help the managers to recognize the areas that lack, i.e. purchase, stocks and receipts, and provide importance to the successful implementation of LP in those areas. This study further intends to examine the hierarchical interrelationships among the factors identified using dependence and driving power. Design/methodology/approach Ten factors were identified from literature review, and expert opinions were collected from the organization which is in construction phase in India. Scheduled interviews were conducted based on questionnaire survey in the organizations to identify the relevance of the relations among the factors. Matrix impact cross-multiplication applied to classification analysis uses dependence and driving power to understand the hierarchical relationship among the factors identified. Findings Results indicate that supplier selection is the key readiness factor for LP. The manager needs to concentrate more on readiness factors to formulate execution process of LP for the betterment of the construction project undergoing organization in India. The readiness factors help the manager to identify the target area for LP execution. Practical implications This study would be useful for researchers and practitioners to understand the readiness factors before starting the implementation process of LP in construction projects. The managers of companies undergoing construction project can use the outcome of the present study to implement LP in a competent way. Basing the priorities of attention on the ten readiness LP factors in the appropriate order of importance, as suggested by this study, can give project managers a more scientific basis in which to specify the level of attention required for each of the factors to implement readiness in LP. Originality/value The present study identifies the readiness factors related to LP, especially for construction project. None of the researchers have studied readiness factors of LP for organizations undergoing construction projects. This is the first attempt made to analyze the relationship between LP readiness factors and TISM approach in construction project organization.

van den Berg, M, Voordijk, H and Adriaanse, A (2020) Information processing for end-of-life coordination: a multiple-case study. Construction Innovation , 20(04), 647–71.