How big data-driven organizational capabilities shape innovation performance? An empirical study from small and medium manufacturing enterprises

Тип публикацииJournal Article
Дата публикации2023-10-11
scimago Q1
wos Q2
white level БС1
SJR0.606
CiteScore6.1
Impact factor2.9
ISSN0368492X, 17587883
Computer Science (miscellaneous)
Social Sciences (miscellaneous)
Control and Systems Engineering
Theoretical Computer Science
Engineering (miscellaneous)
Краткое описание
Purpose

This study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation performance (IP), then explore the indirect effect of SCIC and also test the moderating effects for both internal supply chain integration (ISCI) and external supply chain integration (ESCI) into the relationship between BDDOC and SCIC.

Design/methodology/approach

In order to test the conceptual model and the hypothesized relationships between all the constructs, the data were collected using a self-reported questionnaire by workers in Jordanian small and medium manufacturing enterprises. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the model.

Findings

The paper reached a set of interesting results where it was confirmed that there is a positive and statistically significant relationship between BDDOC, SCIC and IP in addition to confirming the indirect effect of SCIC between BDDOC and IP. The results also showed that there is a moderating role for both ESCI and ISCI.

Originality/value

This study can be considered the first study in the current literature that investigates these constructs as shown in the research model. Therefore, the paper presents an interesting set of theoretical and managerial contributions that may contribute to covering part of the research gap in the literature.

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Топ-30

Журналы

1
Industrial Management and Data Systems
1 публикация, 20%
Journal of Manufacturing Technology Management
1 публикация, 20%
Information Development
1 публикация, 20%
Production Planning and Control
1 публикация, 20%
Revista de Gestão
1 публикация, 20%
1

Издатели

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Emerald
3 публикации, 60%
SAGE
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Taylor & Francis
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ГОСТ |
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Al-Khatib A. W. How big data-driven organizational capabilities shape innovation performance? An empirical study from small and medium manufacturing enterprises // Kybernetes. 2023.
ГОСТ со всеми авторами (до 50) Скопировать
Al-Khatib A. W. How big data-driven organizational capabilities shape innovation performance? An empirical study from small and medium manufacturing enterprises // Kybernetes. 2023.
RIS |
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TY - JOUR
DO - 10.1108/k-06-2023-1070
UR - https://doi.org/10.1108/k-06-2023-1070
TI - How big data-driven organizational capabilities shape innovation performance? An empirical study from small and medium manufacturing enterprises
T2 - Kybernetes
AU - Al-Khatib, Ayman Wael
PY - 2023
DA - 2023/10/11
PB - Emerald
SN - 0368-492X
SN - 1758-7883
ER -
BibTex
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BibTex (до 50 авторов) Скопировать
@article{2023_Al-Khatib,
author = {Ayman Wael Al-Khatib},
title = {How big data-driven organizational capabilities shape innovation performance? An empirical study from small and medium manufacturing enterprises},
journal = {Kybernetes},
year = {2023},
publisher = {Emerald},
month = {oct},
url = {https://doi.org/10.1108/k-06-2023-1070},
doi = {10.1108/k-06-2023-1070}
}
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