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Assessing the Critical Failure Factors of AI Chatbots for Research Using ISM Approach

Catherine Camiguing Gabia et al.

International Journal of Intelligent Information Technologies2026https://doi.org/10.4018/ijiit.402395article
ABDC C
Weight
0.50

What the paper says

Despite the potential of artificial intelligence chatbots in overcoming the tedious tasks of research, scholars have considered critical failure factors before fully integrating such tool into the research process. While extensive works have comprehensively described these factors, none have explored their interrelationships in depth. Therefore, this paper applies interpretive structural modeling analyses to an actual case study of a university in the Philippines to understand the structural relationships among factors. It is found that the authors' lack of knowledge in the research field is the most influential factor. This implies that artificial intelligence chatbots must remain an auxiliary tool in research writing and authors must still possess the firsthand, necessary knowledge to serve as the main contributor of new knowledge in the field.

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https://doi.org/https://doi.org/10.4018/ijiit.402395

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@article{catherine2026,
  title        = {{Assessing the Critical Failure Factors of AI Chatbots for Research Using ISM Approach}},
  author       = {Catherine Camiguing Gabia et al.},
  journal      = {International Journal of Intelligent Information Technologies},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/ijiit.402395},
}

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Assessing the Critical Failure Factors of AI Chatbots for Research Using ISM Approach

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.