Abstract
The purpose of this paper is to examine the relationship between logistics activities and business performance in the Covid-19’ impact. A literature review on supply chain and logistics was conducted to integrate the existing knowledge of supply chain management, logistics activities and critical element for the success of business process. A set of logistics activities, business performance based on balance score card, and a conceptual framework are presented. The model was validated through a survey of 212 survey samples at textile enterprises. Partial least squares structural equation modeling (PLS-SEM) was conducted to assess the status of the impact of logistics activities on business performance of textile enterprises in Binh Tri Thien area in the context of the global economic crisis current Covid-19 pandemic.
According to the findings, the logistics activities had impact on the business performance. Especially, the moderator variable “Covid” showed a negative impact on logistics activities and business performance. Finally, based on the current situation, the study has proposed policy implications to improve Logistics activities, thereby contributing to the future business performance of textile enterprises in Binh Tri Thien.
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Appendix 1
Appendix 1
Cost-Log | Covid | Out-Log | In-Log | Sup-Log | INTCovid_Log-act | Inter-Log | BP | Log-act | |
|---|---|---|---|---|---|---|---|---|---|
Cost-Log2 | 0.889 | ||||||||
Cost-Log2 | 0.767 | ||||||||
Cost-Log3 | 0.827 | ||||||||
Cost-Log3 | 0.726 | ||||||||
Cost-Log4 | 0.852 | ||||||||
Cost-Log4 | 0.736 | ||||||||
Cost-Log5 | 0.872 | ||||||||
Cost-Log5 | 0.754 | ||||||||
Cost-Log6 | 0.834 | ||||||||
Cost-Log6 | 0.758 | ||||||||
Out-Log1 | 0.931 | ||||||||
Out-Log1 | 0.79 | ||||||||
Out-Log2 | 0.833 | ||||||||
Out-Log2 | 0.728 | ||||||||
Out-Log3 | 0.856 | ||||||||
Out-Log3 | 0.754 | ||||||||
Out-Log4 | 0.846 | ||||||||
Out-Log4 | 0.771 | ||||||||
Out-Log5 | 0.862 | ||||||||
Out-Log5 | 0.749 | ||||||||
covid | 1 | ||||||||
In-Log1 | 0.799 | ||||||||
In-Log1 | 0.727 | ||||||||
In-Log2 | 0.736 | ||||||||
In-Log2 | 0.723 | ||||||||
In-Log3 | 0.77 | ||||||||
In-Log3 | 0.736 | ||||||||
In-Log4 | 0.807 | ||||||||
In-Log4 | 0.73 | ||||||||
In-Log5 | 0.882 | ||||||||
In-Log5 | 0.792 | ||||||||
In-Log6 | 0.862 | ||||||||
In-Log6 | 0.774 | ||||||||
BP1 | 0.811 | ||||||||
BP2 | 0.813 | ||||||||
BP3 | 0.851 | ||||||||
BP4 | 0.872 | ||||||||
Sup-Log1 | 0.879 | ||||||||
Sup-Log1 | 0.729 | ||||||||
Sup-Log2 | 0.817 | ||||||||
Sup-Log2 | 0.707 | ||||||||
Sup-Log3 | 0.848 | ||||||||
Sup-Log3 | 0.745 | ||||||||
Sup-Log4 | 0.854 | ||||||||
Sup-Log4 | 0.74 | ||||||||
Sup-Log5 | 0.829 | ||||||||
Sup-Log5 | 0.738 | ||||||||
Sup-Log6 | 0.858 | ||||||||
Sup-Log6 | 0.721 | ||||||||
Log-act * Covid | 1.397 | ||||||||
Inter-Log1 | 0.876 | ||||||||
Inter-Log1 | 0.719 | ||||||||
Inter-Log2 | 0.865 | ||||||||
Inter-Log2 | 0.724 | ||||||||
Inter-Log3 | 0.896 | ||||||||
Inter-Log3 | 0.721 | ||||||||
Cost-Log | 0.837 | ||||||||
Cost-Log | 0.731 | ||||||||
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Thanh, L.T.P., Thao, L.T.P., Hoang, T.V.B. (2024). Predicting the Impact of Covid Pandemic on the Relationship Between Logistics Activities and Business Performance: A PLS-SEM Approach. In: Ngoc Thach, N., Kreinovich, V., Ha, D.T., Trung, N.D. (eds) Optimal Transport Statistics for Economics and Related Topics. Studies in Systems, Decision and Control, vol 483. Springer, Cham. https://doi.org/10.1007/978-3-031-35763-3_23
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