ACHIEVING BIG DATA DECISION-MAKING QUALITY THROUGH DIGITAL LEADERSHIP AND KNOWLEDGE SHARING AT TRANSFER POINT IN BIG DATA CHAIN.

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F22%3A63551578" target="_blank" >RIV/70883521:28120/22:63551578 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

ACHIEVING BIG DATA DECISION-MAKING QUALITY THROUGH DIGITAL LEADERSHIP AND KNOWLEDGE SHARING AT TRANSFER POINT IN BIG DATA CHAIN.

Original language description

Providing a mechanism to boost quality data-based decision making through big data analytics which is among the objectives of industry 4.0 by optimizing human or employee capabilities is the main purpose of current study. Interrelated theoretical lens of dynamic capability view andstrategic alignment model is used. Data from 305 top manager related to FMCG sector in Pakistan representing south Asian region is analyse by applying structural equation modelling through SMRTPLS. Results provide support in favour of presented mechanism that knowledge sharing mediates the relationship among digital leadership and big data analytics positively which shows positive impact on data-based decision-making quality. Results show that human or employee factors are crucial for achieving big data analytics and big data decision making quality. Without addressing these human or employee factors, big data analytics and big data decision-making quality will not be achieved and implementation of big data solutions in its true sense will remains a dream. Current study contributes towards dynamic capability view and strategic alignment model. Organizations can build alignment among strategic, operational and technical level through its dynamic capabilities at strategic, operational and technical level. Organization has to focus on enhancing their capabilities at all level so that organization may have strategic alignment at all level. Once the organizations have alignment in them at all level their big data decision making quality will improve to great extent and that has been proof by current study data analysis.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

50204 - Business and management

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

DOKBAT 2022 - 18th International Bata Conference for Ph.D. Students and Young Researchers

ISBN

978-80-7678-101-6

ISSN

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e-ISSN

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Number of pages

11

Pages from-to

388-398

Publisher name

Fakulta managementu a ekonomiky, UTB ve Zlíně

Place of publication

Zlín

Event location

Zlín

Event date

Sep 14, 2022

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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