Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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    Automating Systematic Literature Reviews with Retrieval-Augmented Generation: A Comprehensive Overview
    (MDPI (Basel, Switzerland), 2024-10-09) Han B; Susnjak T; Mathrani A; Garcia Villalba LJ
    This study examines Retrieval-Augmented Generation (RAG) in large language models (LLMs) and their significant application for undertaking systematic literature reviews (SLRs). RAG-based LLMs can potentially automate tasks like data extraction, summarization, and trend identification. However, while LLMs are exceptionally proficient in generating human-like text and interpreting complex linguistic nuances, their dependence on static, pre-trained knowledge can result in inaccuracies and hallucinations. RAG mitigates these limitations by integrating LLMs’ generative capabilities with the precision of real-time information retrieval. We review in detail the three key processes of the RAG framework—retrieval, augmentation, and generation. We then discuss applications of RAG-based LLMs to SLR automation and highlight future research topics, including integration of domain-specific LLMs, multimodal data processing and generation, and utilization of multiple retrieval sources. We propose a framework of RAG-based LLMs for automating SRLs, which covers four stages of SLR process: literature search, literature screening, data extraction, and information synthesis. Future research aims to optimize the interaction between LLM selection, training strategies, RAG techniques, and prompt engineering to implement the proposed framework, with particular emphasis on the retrieval of information from individual scientific papers and the integration of these data to produce outputs addressing various aspects such as current status, existing gaps, and emerging trends.
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    An analysis of the literature on construction employee turnover: drivers, consequences, and future direction
    (Taylor and Francis Group, 2024-04-22) Abdolmaleki G; Naismith N; Ghodrati N; Poshdar M; Babaeian Jelodar M
    Employee turnover is a critical factor affecting organizational effectiveness. It is particularly important in the construction sector due to its knowledge and labor-intensive characteristics. Therefore, it is necessary to understand why qualified employees would leave their employers so that effective measures can be taken to retain them. Despite the growing body of knowledge on employee turnover, there is a lack of comprehensive review of this topic in the construction literature. This study adopts a systematic literature review approach to synthesize domain knowledge on employee turnover from two perspectives: its investigated causes, and consequences. In total, 77 relevant papers are extracted. A total of 51 drivers of construction employee turnover are identified and categorized into personal, job-related, organizational, and external influencers. Findings also suggest three major outcomes caused by employee turnover, including individual, project, and organization-related consequences. This review contributes to understanding the turnover phenomenon in construction literature and highlights potential areas for future empirical studies to move forward. By understanding the main factors influencing turnover decisions, construction organizations can develop and implement effective means for managing employee turnover. This study further contributes to construction employee turnover research by emphasizing the importance of studying the consequences of the turnover phenomenon.
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    Investigating the theoretical constructs of a green lean six sigma approach towards environmental sustainability: A systematic literature review and future directions
    (MDPI (Basel, Switzerland), 7/10/2020) Farrukh A; Mathrani S; Taskin N
    Green lean six sigma (GLSS) is an emerging approach towards environmental sustainability in conjunction with operational achievements. The success of this approach is premised on an understanding of the different components of a GLSS program; being the determinants for its outcomes. The aim of this paper is to investigate the various constructs of GLSS that play an essential role in achieving environmental sustainability. For this purpose, a systematic review of available literature has been conducted to evaluate the drivers, enablers (tools), and outcomes of a GLSS strategy as well as its critical success factors and barriers. Findings reveal that these constructs of GLSS as a holistic approach can facilitate an organization to better accomplish environmental objectives such as waste minimization, emission reduction, and resource conservation as compared to constructs of only one or any two of these strategies. Based on the analysis, an integrated GLSS framework is developed for environmental sustainability in addition to identifying vital research gaps and future directions.