Exploring factors influencing supply chain performance: Role of supply chain resilience with mixed method approach empirical evidence from the Chinese healthcare Sector

Figures & data

Figure 1. Industry-wise application of SCR.

Source: Singh and Parida (2022)

Figure 2. Relationship between supply chain management and logistics.

Source: Sweeney et al. (2018)

Figure 3. Typical HCSC and the sequence of interviews.

Source: Authors’ Elaboration

Table 1. Supply chain firm summary information

Item	Healthcare supply chain (Tier)	Information’s Title	Years of supply chain experience
Firm 1	Manufacturer (The focal firm)	Purchasing Manager	12
		Materials Manager	10
		Logistics Manager	18
		Sales Service Manager	10
		Sales Manager	15
Firm 2	Supplier 1	Purchasing Director	18
Firm 3	Supplier 2	Purchasing Manager	12
Firm 4	Supplier 3	Purchasing Manager	5
Firm 5	Supplier 4	Purchasing Manager	10
Firm 6	Supplier 5	Logistics Manager	10
Firm 7	Supplier 6	Logistics Manager	18
Firm 8	Supplier 7	Supply Chain Director	16
Firm 9	Supplier 8	Purchasing Manager	10
Firm 10	Supplier 9	Sourcing Manager	10
Firm 11	Supplier 10	Purchasing Manager	6
Firm 12	Supplier 11	Purchasing Manager	15
Firm 13	Supplier 12	Purchasing Manager	7
Firm 14	Supplier 13	Director of operations	5
Firm 15	Supplier 14	Purchasing Manager	6
Firm 16	Supplier 15	Logistics Manager	15
Firm 17	Supplier 16	Purchasing Manager	5
Firm 18	Supplier 17	Purchasing Manager	8
Firm 19	Supplier 18	Supply Chain Manager	15
Firm 20	Supplier 19	Logistics Manager	10
Firm 21	Customer 1	Purchasing Manager	25
Firm 22	Customer 2	Purchasing Manager	20
Firm 23	Customer 3	Supply Chain Manager	14
Firm 24	Customer 4	Purchasing Manager	25
Firm 25	Customer 5	Purchasing Manager	15
Firm 26	Customer 6	Purchasing Manager	16
Firm 27	Customer 7	Equipment section chief	25
Firm 28	Logistics provider 1	Logistics Manager	20
Firm 29	Logistics provider 2	Sales Manager	5
Firm 30	Logistics provider 3	Logistics Manager	25
Firm 31	Logistics provider 4	Logistics Manager	7
Firm 32	Logistics provider 5	Logistics Manager	25
		Average	13.56

Figure 4. Causes of supply chain disruption and supply chain risk.

Figure 5. Mind map of COM.

Source: Authors’ data analysis by NVIVO

Figure 6. Keywords related to TMS.

Source: Authors’ data analysis by NVIVO

Figure 7. The ways to reduce PC and influencing factors of PC.

Source: Authors’ data analysis

Figure 8. Keywords of the SCP.

Source: Authors’ data analysis by NVIVO

Table 2. The code of the impact of SCR on SCP

Item	Influence factor	Firm 1 Manufacturer	Firm 2–20 Suppliers	Firm 21–27 Customers	Firm 28–32 Logistics providers
1	Customer’s delivery	Yes	Yes	Yes	Yes
2	Production plan	Yes	Yes	No	No
3	Reputation of enterprises	Yes	Yes	Yes	Yes
4	Performance of supply chain department	Yes	Yes	Yes	Yes
5	Affect the treatment of patients	Yes	No	Yes	No
6	Hospital operation	Yes	No	Yes	No
7	Logistics cost	Yes	Yes	Yes	Yes
8	Purchasing cost	Yes	Yes	Yes	No

Figure 9. Theoretical framework of SCR.

Table 3. The questionnaire was adapted from the following authors

Variables	Author/Authors
Communication (COM)	Yamin (2021)
Top Management Support (TMS)	Mandal (2020); Lee et al. (2016)
Product complexity(PC)	Eckstein et al. (2015)
Organization culture (OC)	Mandal (2020); Dubey et al. (2017)
SC Resilience (SCR)	Mandal (2020); Mandal et al. (2016)
Supply chain performance(SCP)	Gu et al. (2021)

Table 4. Designation profile

No. of employees	Frequency	(%)
51–100	51	31.48
101–250	35	21.6
251–500	25	15.43
501–1,000	18	11.11
Above 1,000	33	20.37
Total	162	100
Work experience	Frequency	(%)
Less than 5 years	11	6.79
5–10 years	41	25.31
11–15 years	61	37.65
Above 16 years	49	30.25
Total	162	100
Gender	Frequency	(%)
Male	88	54.32
Female	74	45.68
Total	162	100
Designation	Frequency	(%)
Purchase Manager	51	31.48
Supply Chain Manager	23	14.2
Sales Manager	45	27.78
R&D Manager	22	13.58
Production Manager	5	3.09
PMC Manager	5	3.09
Logistics manager	3	1.85
Others	8	4.94
Total	162	100

Table 5. Construct reliability and validity

	Cronbach’s Alpha	rho_A	Composite Reliability	Average Variance Extracted (AVE)
Communication(COM)	0.906	0.917	0.934	0.780
Organization culture(OC)	0.933	0.935	0.949	0.789
Product complexity(PC)	0.837	0.841	0.902	0.754
Supply Chain Performance(SCP)	0.956	0.960	0.964	0.792
Supply Chain Resilience(SCR)	0.962	0.964	0.971	0.870
Top management support(TMS)	0.902	0.908	0.927	0.719

Table 6. Discriminant validity (Fornell-Larcker criterion)

	(COM)	(OC)	(PC)	(SCP)	(SCR)	(TMS)
Communication (COM)	0.883
Organization culture (OC)	0.750	0.888
Product Complexity (PC)	0.611	0.691	0.868
Supply Chain Performance (SCP)	0.716	0.759	0.772	0.890
Supply Chain Resilience (SCR)	0.728	0.754	0.738	0.863	0.933
Top management support (TMS)	0.835	0.695	0.595	0.698	0.680	0.848

Figure 10. Outer model assessment.

Figure 11. Inner model assessment.

Figure 12. Importance-performance map analysis (IPMA).

Table 7. Path coefficients mean, STDEV, T-Values, P-Values

	Original Sample (O)	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (|O/STDEV|)	P Values	Supported?
Communication(COM) -> Supply Chain Resilience(SCR)	0.243	0.250	0.119	2.041	0.041	Yes
Organization culture(OC)_ -> Supply Chain Resilience(SCR)	0.275	0.271	0.107	2.560	0.010	Yes
Product complexity(PC) -> Supply Chain Resilience(SCR)	0.355	0.356	0.101	3.513	0.000	Yes
Supply Chain Resilience(SCR) -> Supply Chain Performance(SCP)	0.863	0.866	0.031	27.407	0.000	Yes
Top management support(TMS)_ -> Supply Chain Resilience(SCR)	0.075	0.077	0.120	0.625	0.532	No

Figure 13. SCR matrix.

Source: Adapted from Dharma and Dwi (2017)

Singh, A., & Parida, R. (2022). Decision-making models for healthcare supply chain disruptions: Review and insights for Post-pandemic Era. International Journal of Global Business and Competitiveness, 17(2), 130–141. https://doi.org/10.1007/s42943-021-00045-5

 Google Scholar

Sweeney, E., Grant, D. B., & Mangan, D. J. (2018). Strategic adoption of logistics and supply chain management. International Journal of Operations & Production Management, 38(3), 852–873. https://doi.org/10.1108/IJOPM-05-2016-0258

 Web of Science ®Google Scholar

Yamin, M. A. (2021). Investigating the drivers of supply chain resilience in the wake of the COVID-19 pandemic: Empirical evidence from an emerging economy. Sustainability, 13(21), 11939. Switzerland), 13(21 https://doi.org/10.3390/su132111939

 Web of Science ®Google Scholar

Mandal, S. (2020). Impact of supplier innovativeness, top management support and strategic sourcing on supply chain resilience. International Journal of Productivity & Performance Management, 70(7), 1561–1581. https://doi.org/10.1108/IJPPM-07-2019-0349

 Google Scholar

Lee, J. C., Shiue, Y. C., & Chen, C. Y. (2016). Examining the impacts of organizational culture and top management support of knowledge sharing on the success of software process improvement. Computers in Human Behavior, 54, 462–474. https://doi.org/10.1016/j.chb.2015.08.030

 Web of Science ®Google Scholar

Eckstein, D., Goellner, M., Blome, C., & Henke, M. (2015). The performance impact of supply chain agility and supply chain adaptability: The moderating effect of product complexity. International Journal of Production Research, 53(10), 3028–3046. https://doi.org/10.1080/00207543.2014.970707

 Web of Science ®Google Scholar

Dubey, R., Gunasekaran, A., Helo, P., Papadopoulos, T., Childe, S. J., & Sahay, B. S. (2017). Explaining the impact of reconfigurable manufacturing systems on environmental performance: The role of top management and organizational culture. Journal of Cleaner Production, 141, 56–66. https://doi.org/10.1016/j.jclepro.2016.09.035

 Web of Science ®Google Scholar

Mandal, S., Sarathy, R., Korasiga, V. R., Bhattacharya, S., & Dastidar, S. G. (2016). Achieving supply chain resilience: The contribution of logistics and supply chain capabilities. International Journal of Disaster Resilience in the Built Environment, 7(5), 544–562. https://doi.org/10.1108/IJDRBE-04-2016-0010

 Web of Science ®Google Scholar

Gu, M., Yang, L., & Huo, B. (2021). The impact of information technology usage on supply chain resilience and performance: An ambidextrous view. International Journal of Production Economics, 232(December), 107956. https://doi.org/10.1016/j.ijpe.2020.107956

 PubMedGoogle Scholar

Dharma, H., & Dwi, Y. (2017). The Asian journal of Shipping and Logistics simulating fleet procurement in an Indonesian Logistics company. The Asian Journal of Shipping and Logistics, 33(1), 1–10. https://doi.org/10.1016/j.ajsl.2017.03.001

 Google Scholar