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Implementing enterprise resource planning for lean waste minimisation: challenges and proposed strategies

Author(s): ORCID
ORCID
ORCID
ORCID
Medium: journal article
Language(s): English
Published in: Smart and Sustainable Built Environment
DOI: 10.1108/sasbe-04-2022-0068
Abstract:

Purpose

In a conventional sense, information technology has frequently been considered a source of Lean waste management. However, as the corporate world evolves, new models that provide a competitive edge by merging technical breakthroughs with the Lean paradigm must be developed. Enterprise resource planning (ERP), which is such technological advancement, is found to be highly influential for Lean implementation. However, there is a dearth of literature on the adaptability of ERP to minimise Lean waste in the construction industry. This paper, therefore, aims to investigate the possibility of applying ERP to minimise Lean waste in the construction industry.

Design/methodology/approach

The study used a qualitative approach, consisting of fifteen (15) expert interviews and code-based content analysis was used to analyse the empirical data.

Findings

The findings revealed the challenges faced when applying ERP with the Lean concept and the strategies that would help overcome the challenges. Most of the challenges could be overcome through training and awareness programmes and proper team management. The study also found that ERP could be applied with Lean to eliminate waste generation in the construction industry.

Originality/value

This paper contributes to the theory by providing an evaluation of the possibility of adopting ERP to eliminate Lean waste in the construction industry. The study will contribute to new knowledge related to strategies for proper use of ERP for Lean waste minimisation, which will be useful for future researchers in the area.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1108/sasbe-04-2022-0068.
  • About this
    data sheet
  • Reference-ID
    10779680
  • Published on:
    12/05/2024
  • Last updated on:
    12/05/2024
 
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