Achieving Data Driven Decision-Making Quality Through Digital Leadership and Organizational Optimization.
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F23%3A63559578" target="_blank" >RIV/70883521:28120/23:63559578 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Achieving Data Driven Decision-Making Quality Through Digital Leadership and Organizational Optimization.
Original language description
Study purpose is to provide a mechanism for overcoming the barrierstowards implementation of big data solutions in true sense for the organizations, which are not ready for future industrial demands. Interrelated theoretical lens of contextual leadership theory and strategic alignment model along with data analysis of 279 top manager from FMCG sector in Pakistan representing south Asian region provide support in favor of presented mechanism. Result analysis shows that organizational optimizations including top management commitment, strategic planning and departmental collaboration mediates the relationship between digital leadership and big data analytics. Furthermore, big data analytics has direct positive effect of data driven decision-making. Study has important managerial and theoretical implication that no matter how strong is the leadership, means through which the desire outcome could be achieve should not be ignore.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the International Conference on Industrial Engineering and Operations Management
ISBN
979-8-3507-0542-3
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
1-10
Publisher name
IEOM Society International
Place of publication
Canton
Event location
Sydney
Event date
Dec 20, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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