Grant: Discovery Launch Supplement
University of Regina
$12,500.00
Knowledge-based decision support system for overall supply chain resilience performance evaluation
EF 2024-25
Résumé
Have you ever experienced delays in your orders or encountered empty shelves at grocery stores such as Walmart or Canadian superstore? If so, then it is because of supply chain (SC) disruptions. Resilient SC enhances the ability of any organization in minimizing disruption impact across SC functions and facilitates effective recovery through SC resilience capacity which includes resistance and recovery. Over the last decade, SC resilience has been a contemporary topic of research among academics and practitioners. Studies that focus on an integrated system for SC resilience performance evaluation and improvement are still in their early stages. Unfortunately, neither reactive nor proactive decision support systems exist at the firm level to help organizations enhance their SC resilient capabilities. For this reason, the vision and objective of this research program is to develop a data-driven integrated knowledge-based decision support system (KBDSS) and to facilitate Canadian industries to cope with the disruption impact such as COVID-19 outbreak.
In order to achieve the objectives of this research program, I will employ both qualitative and quantitative approaches. Qualitative approaches facilitate the acquisition of in-depth knowledge of the research topic, as they tend to be more flexible and inductive. A qualitative approach such as the focus group technique, Delphi technique, and content analysis, will be used in this research. In parallel, quantitative approaches will be used to analyze and validate construct-based groups of identified SC resilience indicators of business dimensions, and the development of KBDSS. Quantitative methods are based on deductive logic and are widely employed in natural sciences and engineering. The purposive sampling technique, exploratory factors analysis, confirmatory factor analysis, and multi-criteria decision making (MCDM) methods will be used to analyze, and validate the constructs-based group of the identified SC resilience indicators of business dimensions and resilience strategies, and eventually the development of KBDSS.
To the best of my knowledge, this endeavor is a pioneering attempt that provides several practical answers to managers and policymakers who are keen to evaluate and improve the organizational level of overall SC resilience performance. It can provide decision support, models, and a collaborative platform to enhance overall SC resilience, enabling real time monitoring of SC performance and disruptions, data management, risk assessment, and can address several challenges within this domain. Moreover, the proposed research program strongly aligns with the visions and priorities of the Federal Government of Canada, Provincial Government of Saskatchewan, World Vision Canada, and Innovation, Science and Economic Development Canada. This research program will also contribute to the training of a diverse team of highly qualified personnel of various backgrounds and identities.
Programme
Discovery Launch Supplement
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
DGECR-2024-00084
Name nom
Khan, Sharfuddin
Department département
Industrial Systems Engineering
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
12500
Program id
DGECR
Program name en
Discovery Launch Supplement
Program name fr
Supplément Tremplin vers la découverte
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1509
Committee name en
Civil, Industrial and Systems Engineering
Committee name fr
Génie civil, industriel et des systèmes
Area of application code
520
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Production and operations management
Area of application fr
Production et gestion des opérations
Research subject code
1606
Research subject group en
Industrial engineering
Research subject group fr
Génie industriel
Research subject en
Operations management
Research subject fr
Gestion de la production
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Knowledge-based decision support system for overall supply chain resilience performance evaluation
Keywords
operations management; supply chain management; supply chain resilience; organizational resources; business dimensions; resilience strategies; knowledge-based systems
Application summary
Have you ever experienced delays in your orders or encountered empty shelves at grocery stores such as Walmart or Canadian superstore? If so, then it is because of supply chain (SC) disruptions. Resilient SC enhances the ability of any organization in minimizing disruption impact across SC functions and facilitates effective recovery through SC resilience capacity which includes resistance and recovery. Over the last decade, SC resilience has been a contemporary topic of research among academics and practitioners. Studies that focus on an integrated system for SC resilience performance evaluation and improvement are still in their early stages. Unfortunately, neither reactive nor proactive decision support systems exist at the firm level to help organizations enhance their SC resilient capabilities. For this reason, the vision and objective of this research program is to develop a data-driven integrated knowledge-based decision support system (KBDSS) and to facilitate Canadian industries to cope with the disruption impact such as COVID-19 outbreak.
In order to achieve the objectives of this research program, I will employ both qualitative and quantitative approaches. Qualitative approaches facilitate the acquisition of in-depth knowledge of the research topic, as they tend to be more flexible and inductive. A qualitative approach such as the focus group technique, Delphi technique, and content analysis, will be used in this research. In parallel, quantitative approaches will be used to analyze and validate construct-based groups of identified SC resilience indicators of business dimensions, and the development of KBDSS. Quantitative methods are based on deductive logic and are widely employed in natural sciences and engineering. The purposive sampling technique, exploratory factors analysis, confirmatory factor analysis, and multi-criteria decision making (MCDM) methods will be used to analyze, and validate the constructs-based group of the identified SC resilience indicators of business dimensions and resilience strategies, and eventually the development of KBDSS.
To the best of my knowledge, this endeavor is a pioneering attempt that provides several practical answers to managers and policymakers who are keen to evaluate and improve the organizational level of overall SC resilience performance. It can provide decision support, models, and a collaborative platform to enhance overall SC resilience, enabling real time monitoring of SC performance and disruptions, data management, risk assessment, and can address several challenges within this domain. Moreover, the proposed research program strongly aligns with the visions and priorities of the Federal Government of Canada, Provincial Government of Saskatchewan, World Vision Canada, and Innovation, Science and Economic Development Canada. This research program will also contribute to the training of a diverse team of highly qualified personnel of various backgrounds and identities.