Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model
Developing a comprehensive data-driven strategy for evaluating the organisational culture in companies to foster digital innovation involves a multi-criteria decision-making (MCDM) problem. This needs to consider various organisational culture characteristics that influence digital innovation succes...
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my.uniten.dspace-339432024-10-14T11:17:29Z Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model Albahri O.S. Alamoodi A.H. Deveci M. Albahri A.S. Mahmoud M.A. Al-Quraishi T. Moslem S. Mohamad Sharaf I. 57201013684 57205435311 55734383000 57201009814 55247787300 57196035672 57203017976 17435789800 Digital transformation Multi criteria decision-making Organizational culture q-Rung fuzzy set Benchmarking Data handling Decision making Reliability analysis Sensitivity analysis Decision-making modeling Digital innovations Digital transformation Multi criteria decision-making Multi-criteria decision-making models Multicriteria decision-making Multicriterion decision makings Organizational cultures Q-rung fuzzy set Weighting model Fuzzy sets Developing a comprehensive data-driven strategy for evaluating the organisational culture in companies to foster digital innovation involves a multi-criteria decision-making (MCDM) problem. This needs to consider various organisational culture characteristics that influence digital innovation success, assign significance weights to each characteristic, and recognise that distinct organisational cultures may excel in different aspects necessitates the proper handling of data variations. Hence, to provide organisations seeking to align cultural practises with digital innovation objectives with valuable insights, this study aims to develop an MCDM model for evaluating and benchmarking organisational culture in companies to foster digital innovation. The benchmarking decision matrix is formulated based on the intersection of evaluation characteristics and a list of organisational culture aspects in companies. The MCDM model is developed in two phases. Firstly, a new weighting model, q-rung picture fuzzy-weighted zero-inconsistency (q-RPFWZIC), is formulated for assessing the evaluation characteristics under the q-rung picture fuzzy sets environment. Secondly, the simple additive weighting (SAW) model is formulated for benchmarking the organisational culture in companies using the extracted weights of the evaluation characteristics. The results indicate that characteristic C6 (corporate entrepreneurship) has the highest weight, with a value of 0.161, while characteristic C3 (employee participation, agility and organizational structures) and C7 (digital awareness and necessity of innovations) has the lowest weight of 0.088. Company A2 secures the top rank with a score of 0.911, satisfying eight evaluation characteristics, whereas company A7 holds the last rank order, satisfying only one evaluation characteristic, obtaining a score of 0.101. In model evaluation, several scenarios were considered in a sensitivity analysis test based on a 100% increment in weight values for each characteristic to validate the reliability of the model results. � 2023 The Author(s) Final 2024-10-14T03:17:29Z 2024-10-14T03:17:29Z 2023 Article 10.1016/j.aei.2023.102191 2-s2.0-85172225374 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172225374&doi=10.1016%2fj.aei.2023.102191&partnerID=40&md5=d0ff0b300544992ed3492595dcad56a7 https://irepository.uniten.edu.my/handle/123456789/33943 58 102191 All Open Access Hybrid Gold Open Access Elsevier Ltd Scopus |
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Digital transformation Multi criteria decision-making Organizational culture q-Rung fuzzy set Benchmarking Data handling Decision making Reliability analysis Sensitivity analysis Decision-making modeling Digital innovations Digital transformation Multi criteria decision-making Multi-criteria decision-making models Multicriteria decision-making Multicriterion decision makings Organizational cultures Q-rung fuzzy set Weighting model Fuzzy sets |
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Digital transformation Multi criteria decision-making Organizational culture q-Rung fuzzy set Benchmarking Data handling Decision making Reliability analysis Sensitivity analysis Decision-making modeling Digital innovations Digital transformation Multi criteria decision-making Multi-criteria decision-making models Multicriteria decision-making Multicriterion decision makings Organizational cultures Q-rung fuzzy set Weighting model Fuzzy sets Albahri O.S. Alamoodi A.H. Deveci M. Albahri A.S. Mahmoud M.A. Al-Quraishi T. Moslem S. Mohamad Sharaf I. Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model |
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Developing a comprehensive data-driven strategy for evaluating the organisational culture in companies to foster digital innovation involves a multi-criteria decision-making (MCDM) problem. This needs to consider various organisational culture characteristics that influence digital innovation success, assign significance weights to each characteristic, and recognise that distinct organisational cultures may excel in different aspects necessitates the proper handling of data variations. Hence, to provide organisations seeking to align cultural practises with digital innovation objectives with valuable insights, this study aims to develop an MCDM model for evaluating and benchmarking organisational culture in companies to foster digital innovation. The benchmarking decision matrix is formulated based on the intersection of evaluation characteristics and a list of organisational culture aspects in companies. The MCDM model is developed in two phases. Firstly, a new weighting model, q-rung picture fuzzy-weighted zero-inconsistency (q-RPFWZIC), is formulated for assessing the evaluation characteristics under the q-rung picture fuzzy sets environment. Secondly, the simple additive weighting (SAW) model is formulated for benchmarking the organisational culture in companies using the extracted weights of the evaluation characteristics. The results indicate that characteristic C6 (corporate entrepreneurship) has the highest weight, with a value of 0.161, while characteristic C3 (employee participation, agility and organizational structures) and C7 (digital awareness and necessity of innovations) has the lowest weight of 0.088. Company A2 secures the top rank with a score of 0.911, satisfying eight evaluation characteristics, whereas company A7 holds the last rank order, satisfying only one evaluation characteristic, obtaining a score of 0.101. In model evaluation, several scenarios were considered in a sensitivity analysis test based on a 100% increment in weight values for each characteristic to validate the reliability of the model results. � 2023 The Author(s) |
author2 |
57201013684 |
author_facet |
57201013684 Albahri O.S. Alamoodi A.H. Deveci M. Albahri A.S. Mahmoud M.A. Al-Quraishi T. Moslem S. Mohamad Sharaf I. |
format |
Article |
author |
Albahri O.S. Alamoodi A.H. Deveci M. Albahri A.S. Mahmoud M.A. Al-Quraishi T. Moslem S. Mohamad Sharaf I. |
author_sort |
Albahri O.S. |
title |
Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model |
title_short |
Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model |
title_full |
Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model |
title_fullStr |
Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model |
title_full_unstemmed |
Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model |
title_sort |
evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model |
publisher |
Elsevier Ltd |
publishDate |
2024 |
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1814061095672872960 |
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13.209306 |