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Doukari, O, Kassem, M, Scoditti, E, Aguejdad, R and Greenwood, D (2024) A BIM based tool for evaluating building renovation strategies: the case of three demonstration sites in different European countries. Construction Innovation, 24(01), 365-83.
Faraji, A, Homayoon Arya, S, Ghasemi, E, Rashidi, M, Perera, S, Tam, V and Rahnamayiezekavat, P (2024) A conceptual framework of decentralized blockchain integrated system based on building information modeling to steering digital administration of disputes in the IPD contracts. Construction Innovation, 24(01), 384-406.
Garip, S B, Güzelci, O Z, Garip, E and Kocabay, S (2024) A genetic algorithm-based design model to provide reduced risk areas for housing interiors. Construction Innovation, 24(01), 49-66.
Gledson, B, Zulu, S L, Saad, A M and Ponton, H (2024) Digital leadership framework to support firm-level digital transformations for Construction 4.0. Construction Innovation, 24(01), 341-64.
Jowett, B, Edwards, D J and Kassem, M (2024) Field BIM and mobile BIM technologies: a requirements taxonomy and its interactions with construction management functions. Construction Innovation, 24(01), 134-63.
Likita, A J, Jelodar, M B, Vishnupriya, V and Rotimi, J O B (2024) Lean and BIM integration benefits construction management practices in New Zealand. Construction Innovation, 24(01), 106-33.
Lisco, M and Aulin, R (2024) Taxonomy supporting design strategies for reuse of building parts in timber-based construction. Construction Innovation, 24(01), 221-41.
Mahamedi, E, Wonders, M, Gerami Seresht, N, Woo, W L and Kassem, M (2024) A reinforcing transfer learning approach to predict buildings energy performance. Construction Innovation, 24(01), 242-55.
Matoseiro Dinis, F, Rodrigues, R and Pedro da Silva Poças Martins, J (2024) Development and validation of natural user interfaces for semantic enrichment of BIM models using open formats. Construction Innovation, 24(01), 196-220.
Parisi, F, Sangiorgio, V, Parisi, N, Mangini, A M, Fanti, M P and Adam, J M (2024) A new concept for large additive manufacturing in construction: tower crane-based 3D printing controlled by deep reinforcement learning. Construction Innovation, 24(01), 8-32.
Philip, B and AlJassmi, H (2024) Time-series forecasting of road distress parameters using dynamic Bayesian belief networks. Construction Innovation, 24(01), 317-40.
Rampini, L and Re Cecconi, F (2024) Synthetic images generation for semantic understanding in facility management. Construction Innovation, 24(01), 33-48.
Saif, W and Alshibani, A (2024) A close-range photogrammetric model for tracking and performance-based forecasting earthmoving operations. Construction Innovation, 24(01), 164-95.
Sati, A and Al-Tabtabai, H (2024) A paradigm shift toward the application of blockchain in enhancing quality information management. Construction Innovation, 24(01), 407-24.
Singh, A, Kumar, V, Mittal, A and Verma, P (2024) Identifying critical challenges to lean construction adoption. Construction Innovation, 24(01), 67-105.
- Type: Journal Article
- Keywords: barriers; construction management; implementation; Indian construction industry; lean construction
- ISBN/ISSN:
- URL: https://doi.org/10.1108/CI-09-2022-0229
- Abstract:
Purpose: This study aims to set out to identify and evaluate potential obstacles to successfully implementing lean construction (LC) as a result. Design/methodology/approach: Several indicators were recognized as major obstacles following an exhaustive assessment of the literature and a multicriteria decision analysis based on the analytic hierarchy process (AHP) of information obtained from a questionnaire survey that was directed to practitioners in the Indian construction industry. Findings: The results of this AHP model suggest that “Managerial” and “Inadequate resources” categories with a priority weight of “0.361” and “0.309” have the highest levels of influence, respectively, while “Inadequate knowledge” and “just in time (JIT)” categories with a priority weight of “0.053” and “0.034” have the lowest levels of influence, respectively. Research limitations/implications: Construction companies can use the study’s findings as a guide to determine whether they are ready to embrace LC, learn more about the components needed for implementation or investigate any challenges that may arise. These businesses can then create plans to promote the adoption and application of the lean philosophy. Originality/value: The Indian construction industry may see great success with LC management initiatives. LC concepts have been adopted by many nations, but during the past 20 years, there has only appeared to be a limited amount of lean implementation in the Indian construction industry. It seems that several structural and cultural barriers are preventing its effective implementation. Organizations will not be able to determine what improvement efforts are required, where these efforts should be directed or which initiatives could provide the best outcomes if they are unaware of the elements that influence the effective implementation of LC. © 2023, Emerald Publishing Limited.
Yu, J, Zhong, H and Bolpagni, M (2024) Integrating blockchain with building information modelling (BIM): a systematic review based on a sociotechnical system perspective. Construction Innovation, 24(01), 280-316.
Zani, A, Speroni, A, Mainini, A G, Zinzi, M, Caldas, L and Poli, T (2024) Customized shading solutions for complex building façades: the potential of an innovative cement-textile composite material through a performance-based generative design. Construction Innovation, 24(01), 256-79.