Marzieh Abbaszadeh, Hadi Shirouyehzad and Milad Asadpour
The purpose of this paper is to present a fuzzy Quality Function Deployment (QFD)-based approach for identifying and prioritizing organizational agility (OA) capabilities and…
Abstract
Purpose
The purpose of this paper is to present a fuzzy Quality Function Deployment (QFD)-based approach for identifying and prioritizing organizational agility (OA) capabilities and enablers based on its drivers.
Design/methodology/approach
First, several models for agility drivers (ADs), agility capabilities (ACs) and agility enablers (AEs) are reviewed and ranked, and the best for each one is selected. Second, ADs’ indexes are weighted by using experts’ comments and fuzzy numbers. Finally, by using a proposed fuzzy QFD approach, ACs and AEs are prioritized. In addition, the proposed approach has been examined within a real case study, Golnoor Company in Esfahan, Iran.
Findings
Results reveal that among ADs’ criteria, “Changes in competition criteria” have the highest weights for the case study. In addition, “Leadership in the use of current technology” and “Knowledge management” have been ranked as the first place among ACs and AEs, respectively.
Originality/value
After conducting a comprehensive literature review, the authors did not find any particular framework, which consider AEs and ACs based on ADs simultaneously. Accordingly, the authors’ main novelty is proposing a fuzzy QFD to prioritize the OA capabilities and enablers based on its drivers.
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Fatemeh Narenji Thani and Seyed Mohammad Mirkamali
Knowledge is recognized as a valuable asset and universities are in search of a new strategy that allows them to build their knowledge and experience. To achieve this goal, it…
Abstract
Purpose
Knowledge is recognized as a valuable asset and universities are in search of a new strategy that allows them to build their knowledge and experience. To achieve this goal, it seems essential to find the factors associated with knowledge creation (KC) in universities. There is currently no comprehensive model that delineates the relationships between personal, institutional and support-related factors of KC. The purpose of this paper is to gain a better understanding of the factors that affect KC in higher education institutions.
Design/methodology/approach
This is an explanatory mixed methods approach that consists of qualitative and quantitative stages. In the qualitative phase, 14 authorities on KC were interviewed and the data yielded were subjected to content analysis. A model and hypotheses were then formulated and a questionnaire was developed to test these. The questionnaire was submitted to faculty members of Tehran University. Questionnaire data were was analyzed using structural equation and partial least squares with the aid of SmartPLS.
Findings
The results showed three main categories of KC factors: institutional, personal and support. A total of 19 sub-factors were identified within these main categories. According to the results, social capital (path coefficient=0.84) had the strongest correlation with the institutional; basic skills for KC (path coefficient=0.92) had the strongest correlation with the personal, and information and library resources (path coefficient=0.95) had the highest correlation with the support aspect of KC.
Originality/value
The study uses a multidimensional approach to test the effect of factors on KC, and can contribute to organizations (especially universities) through developing a more comprehensive model of KC. This research may lead to guidelines for universities, using Tehran University as a case study, which give more attention to the main factors of KC and improve and develop the KC process.