TY - JOUR
T1 - Hidden fuzzy information
T2 - Requirement specification and measurement of project provider performance using the best worst method
AU - Asadabadi, Mehdi Rajabi
AU - Chang, Elizabeth
AU - Zwikael, Ofer
AU - Saberi, Morteza
AU - Sharpe, Keiran
N1 - Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2020/3/15
Y1 - 2020/3/15
N2 - The requirement specification process is an important part of a project and has the potential to prevent problems that may last for years after a project is delivered. Previous studies on the requirement specification process have focused on clarifying stated fuzzy terms in software requirement engineering. However, in many projects there is information that is not stated, but it is implied and can be inferred. This hidden information is usually ignored due to the assumption that ‘the provider understands what they mean/need’. This assumption is not always true. Such information, if extracted, may include fuzzy terms, namely hidden fuzzy terms (HFTs), which need specification. Therefore, these fuzzy terms have to be identified and then specified to avoid potential future consequences. This study proposes an algorithm to extract the hidden fuzzy terms, utilises a fuzzy inference system (FIS) to specify them, and applies the best worst multi-criteria decision making method (BWM) to evaluate the delivered product and measure the performance of the provider. The model is then used to examine a case from Defence Housing Australia. Such evaluation and measurement enable the project owner/manager to have a transparent basis to support decisions later in different phases of the project, and to ultimately reduce the likelihood of conflict and the receipt of an unsatisfactory product.
AB - The requirement specification process is an important part of a project and has the potential to prevent problems that may last for years after a project is delivered. Previous studies on the requirement specification process have focused on clarifying stated fuzzy terms in software requirement engineering. However, in many projects there is information that is not stated, but it is implied and can be inferred. This hidden information is usually ignored due to the assumption that ‘the provider understands what they mean/need’. This assumption is not always true. Such information, if extracted, may include fuzzy terms, namely hidden fuzzy terms (HFTs), which need specification. Therefore, these fuzzy terms have to be identified and then specified to avoid potential future consequences. This study proposes an algorithm to extract the hidden fuzzy terms, utilises a fuzzy inference system (FIS) to specify them, and applies the best worst multi-criteria decision making method (BWM) to evaluate the delivered product and measure the performance of the provider. The model is then used to examine a case from Defence Housing Australia. Such evaluation and measurement enable the project owner/manager to have a transparent basis to support decisions later in different phases of the project, and to ultimately reduce the likelihood of conflict and the receipt of an unsatisfactory product.
KW - BWM
KW - Fuzzy inference system
KW - Hidden fuzzy
KW - MCDM
KW - Requirement specification
UR - http://www.scopus.com/inward/record.url?scp=85068454165&partnerID=8YFLogxK
U2 - 10.1016/j.fss.2019.06.017
DO - 10.1016/j.fss.2019.06.017
M3 - Article
SN - 0165-0114
VL - 383
SP - 127
EP - 145
JO - Fuzzy Sets and Systems
JF - Fuzzy Sets and Systems
ER -