Digitalization for supply chain resilience and robustness: The roles of collaboration and formal contracts

doi:10.1007/s42524-022-0229-x

Front. Eng

2023, Vol. 10

Issue (1) : 5-19 https://doi.org/10.1007/s42524-022-0229-x

RESEARCH ARTICLE

Digitalization for supply chain resilience and robustness: The roles of collaboration and formal contracts

Ying LI¹, Dakun LI¹, Yuyang LIU¹, Yongyi SHOU²(

)

¹. School of Management, Shandong University, Jinan 250100, China
². School of Management, Zhejiang University, Hangzhou 310058, China

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Abstract

Black swan events such as the coronavirus (COVID-19) outbreak cause substantial supply chain disruption risks to modern companies. In today’s turbulent and complex business environment, supply chain resilience and robustness as two critical capabilities for firms to cope with disruptions have won substantial attention from both the academia and industry. Accordingly, this study intends to explore how digitalization helps build supply chain resilience and robustness. Adopting organizational information processing theory, it proposes the mediating effect of supply chain collaboration and the moderating effect of formal contracts. Using survey data of Chinese manufacturing firms, the study applied structural equation modelling to test the research model. Results show that digitalization has a direct effect on supply chain resilience, and supply chain collaboration can directly facilitate both resilience and robustness. Our study also indicates a complementary mediating effect of supply chain collaboration on the relationship between digitalization and supply chain resilience and an indirect-only mediation effect on the relationship between digitalization and supply chain robustness. Findings reveal the differential roles of digitalization as a technical factor and supply chain collaboration as an organizational factor in managing supply chain disruptions. Paradoxically, formal contracts enhance the relationship between digitalization and supply chain resilience but weaken the relationship between supply chain collaboration and supply chain resilience. The validation of moderating effects determines the boundary conditions of digitalization and supply chain collaboration and provides insights into governing supply chain partners’ behavior. Overall, this study enhances the understanding on how to build a resilient and robust supply chain.

Keywords digitalization supply chain resilience robustness collaboration formal contract

Corresponding Author(s): Yongyi SHOU

About author:

Changjian Wang and Zhiying Yang contributed equally to this work.

Just Accepted Date: 21 December 2022 Online First Date: 09 February 2023 Issue Date: 02 March 2023

Cite this article:

Ying LI,Dakun LI,Yuyang LIU, et al. Digitalization for supply chain resilience and robustness: The roles of collaboration and formal contracts[J]. Front. Eng, 2023, 10(1): 5-19.

URL:

https://academic.hep.com.cn/fem/EN/10.1007/s42524-022-0229-x
https://academic.hep.com.cn/fem/EN/Y2023/V10/I1/5

Fig.1 Conceptual model.

Tab.1 Sample profile

Constructs and items		Factor loadings	SD	T-statistics
Digitalization (DT) (Cronbach’s α = 0.753; CR = 0.835; AVE = 0.503)
DT1	Our firm adopts digital technologies to collect data from different sources	0.687	0.048	14.278
DT2	Our firm adopts digital technologies to connect business processes	0.668	0.043	15.623
DT3	Our firm adopts digital technologies to promote information exchange	0.684	0.045	15.268
DT4	Our firm adopts digital technologies to build customer interface	0.747	0.033	22.678
DT5	Our firm adopts digital technologies to connect supply chain partners	0.756	0.035	21.752
Supply chain collaboration (SCC) (Cronbach’s α = 0.753; CR = 0.835; AVE = 0.503)
SCC1	Our firm sets common goals with supply chain partners	0.706	0.041	17.288
SCC2	Our firm shows mutual support with supply chain partners	0.681	0.044	15.640
SCC3	Our firm engages in joint problem solving with supply chain partners	0.697	0.033	21.260
SCC4	Our firm shows understanding of supply chain partners’ strengths and weaknesses	0.695	0.037	18.865
SCC5	Our firm engages in regular and collaborative communication with supply chain partners	0.765	0.032	23.705
Supply chain resilience (SCRES) (Cronbach’s α = 0.805; CR = 0.865; AVE = 0.561)
SCRES1	Our firm can predict supply chain disruption risk occurrence	0.759	0.029	26.166
SCRES2	Our firm develops contingency plans to prepare for potential supply chain disruptions	0.752	0.033	22.974
SCRES3	Our firm can prevent disruptions through forecasting and planning	0.717	0.035	20.684
SCRES4	Our firm can adapt to supply chain disruptions by quickly re-engineering the processes	0.761	0.029	26.033
SCRES5	Our firm can respond quickly to SC disruptions	0.754	0.031	24.276
Supply chain robustness (SCROB) (Cronbach’s α = 0.674; CR = 0.799; AVE = 0.501)
SCROB1	Operations would be able to continue	0.812	0.027	30.467
SCROB2	We would still be able to meet customer demand	0.696	0.038	18.136
SCROB3	Our firm can avoid losses caused by supply chain risks	0.633	0.053	11.857
SCROB4	Performance would not deviate significantly	0.677	0.055	12.393
Formal contracts (FC) (Cronbach’s α = 0.767; CR = 0.843; AVE = 0.519)
FC1	Our firm has specific and detailed contractual agreements with supply chain partners	0.742	0.037	19.967
FC2	The contract specifies and details the roles and responsibilities of supply chain partners	0.745	0.033	22.540
FC3	The contract specifies and details how to deal with unexpected events	0.689	0.045	15.286
FC4	The contract specifies and details the penalties for under-performance	0.781	0.028	28.181
FC5	The contract specifies and details how to deal with disputes and conflicts	0.638	0.043	14.750

Tab.2 Reliability and validity

Tab.3 Correlations, square root of the AVE values, and the HTMT values

Tab.4 Cross loadings

Fig.2 Structural model results for direct effects.

Tab.5 Quality of the structural model

Tab.6 Direct effect testing results

Tab.7 Mediating effect testing results

Fig.3 Structural model results for moderating effects.

Tab.8 Moderating effect testing results

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