The DOI matches its Crossref record; 116 of the 116 references it cites were found in a registry or an index.
The impact of information technology usage on supply chain resilience and performance: An ambidexterous view
Open accessAbstract
Scholars and practitioners have recognized the importance of supply chain (SC) resilience. However, it remains unclear how to build SC resilience and whether SC resilience can enhance firm performance and bring values to customers. By analyzing data collected from 206 manufacturers in China, this study empirically examines how firms implement different information technology (IT) patterns (exploitative versus explorative) with SC partners to achieve supplier and customer resilience from information processing theory, and examines the performance implications of these two dimensions of SC resilience. In addition, this study also investigates how IT ambidexterity reconciles the paradox between IT exploitation and IT exploration in enhancing SC resilience. The results show that both supplier and customer resilience could improve SC performance. To achieve the two aspects of SC resilience, only explorative use of IT with suppliers and customers have significant effects. The results also show that the ambidextrous use of IT on the customer side takes effect. The exploitative and explorative use of IT complement each other to improve customer resilience. The findings of this study contribute to IT and SC resilience literature.
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Cites
Evaluating structural equation models with unobservable variables and measurement error
Fornell, C., & Larcker, D. F. (1981) · Journal of Marketing Research · doi:10.1177/002224378101800104 · Cited by 109,190
Hu, L., & Bentler, P. M. (1999) · Structural Equation Modeling A Multidisciplinary Journal · doi:10.1080/10705519909540118 · Cited by 108,788
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003) · Journal of Applied Psychology · doi:10.1037/0021-9010.88.5.879 · Cited by 82,194
Principles and Practice of Structural Equation Modeling
Tabri, N., & Elliott, C. M. (2012) · Canadian Graduate Journal of Sociology and Criminology · doi:10.15353/cgjsc-rcessc.v1i1.25 · Cited by 38,891
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-014-0403-8 · Cited by 38,459
(1998) · Cited by 36,049
Exploration and Exploitation in Organizational Learning
March, J. G. (1991) · Organization Science · doi:10.1287/orsc.2.1.71 · Cited by 21,942 · cited 2×
“It can be achieved through reassessment of current solution with variance-seek and novel solutions development (Andriopoulos and Lewis, 2009; Chiu, 2014; March, 1991; Sanders, 2008; Subramani, 2004).”
Self-Reports in Organizational Research: Problems and Prospects
Podsakoff, P. M., & Organ, D. W. (1986) · Journal of Management · doi:10.1177/014920638601200408 · Cited by 17,102
Multivariate data analysis : a global perspective
Hair, J. F. (2010) · Cited by 12,255
Estimating Nonresponse Bias in Mail Surveys
Armstrong, J. S., & Overton, T. S. (1977) · Journal of Marketing Research · doi:10.2307/3150783 · Cited by 12,222
Cited by
Ivanov, D. (2024) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2021.3095193 · Cited by 336
How does digital transformation improve organizational resilience?—findings from PLS-SEM and fsQCA
Zhang, J., Long, J., & von Schaewen, A. M. E. (2021) · Sustainability · doi:10.3390/su132011487 · Cited by 245
Supply chain resilience: new challenges and opportunities
Shi, X., Liu, W., & Lim, M. K. (2024) · International Journal of Logistics Research and Applications · doi:10.1080/13675567.2023.2262396 · Cited by 39
Metadata
- Authors
- Gu, M., Yang, L., & Huo, B.
- Venue
- International Journal of Production Economics
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 232
- Pages
- 107956
- ISSN
- 0925-5273 (ISSN-L)
- OpenAlex
- W3092666012
- Cited by
- 409
- References
- 116
- FWCI
- 44.79
- Type
- journal article
- Language
- en
- Open access
- green
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- Gu, M., Yang, L., & Huo, B. (2021). The impact of information technology usage on supply chain resilience and performance: An ambidexterous view. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2020.107956
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