Urban Sharing Logistics Strategies against Epidemic Outbreaks: Its Feasibility and Sustainability
Abstract
:1. Introduction
1.1. Background and Motivation
1.2. Research Questions and Key Findings
- (1)
- When the cost (small batch), efficiency (convenience), and disruption risk (continuity) factors are considered together, what type of sharing mechanism is feasible and can achieve Pareto improvements?
- (2)
- How can the best sharing decision be made for intercity logistics companies under different conditions?
- (3)
- What type of sharing mechanism of urban distribution is sustainable (in terms of load ratio, low-carbon, and low-disruption dimensions), especially when fighting against epidemic outbreaks (e.g., COVID-19)?
- (1)
- When logistics sharing for cost reduction and efficiency improvement, the load ratio, and the disruption risk factor are considered together, the sharing logistics mechanisms based on revenue sharing and equity investment proposed in this paper are feasible and can achieve Pareto improvements for any given load ratio. In contrast, the first sharing logistics mechanism only based on the wholesale price contract is not optimal for some load ratios. In the majority of scenarios, the sharing logistics mechanism based on equity investment is better than that based on revenue-sharing contracts, but, sometimes, the opposite is the case.
- (2)
- Regarding practices, it is necessary to scientifically design the load ratio of trucks to delivery vehicles, as it plays an important role in the performance of the sharing logistics implementation.
- (3)
- For any given load ratio of trucks to delivery vehicles, compared with the BM, all of the sharing mechanisms generally increase the load ratio and significantly reduce the unit carbon emission rate, as well as the unit disruption risk.
1.3. Contribution Statements and Structure of This Paper
2. Literature Review
2.1. Supply Chain Disruptions and Resilience
2.2. Urban Sharing Logistics in the Logistics Supply Chain
2.3. Sharing Mechanisms in Operations Management
2.3.1. Sharing Economics in Operations Management
2.3.2. Sharing Contracts
2.4. Emergency and Humanitarian Logistics
3. Problem Descriptions and Hypotheses
- (1)
- Optimal Pareto improvement:i. ii. .
- (2)
- Suboptimal Pareto improvement:i. ii. .
4. Equilibrium Analysis
4.1. The Benchmark Model (BM)
- (1)
- While , the optimal decisions are , and the optimal utilities are , ;
- (2)
- While , where , the optimal decisions and utilities are
- (i)
- if , then , , , ;
- (ii)
- If , then , .
4.2. Sharing Mechanism 1: SM1
- (1)
- While , the optimal decisions are , and the optimal utility are , ;
- (2)
- While , where , the optimal decisions and utility are
- (i)
- if , then , ;
- (ii)
- if , then , .
4.3. Sharing Mechanism 2: SM2
- (1)
- While , the optimal decisions are , and the optimal utility are , ;
- (2)
- While , where , the optimal decisions and utility are
- (i)
- if , then , , , ;
- (ii)
- if , then , , .
4.4. Sharing Mechanism 3: SM3
- (1)
- if , the optimal decisions and utility are , ;
- (2)
- if , the optimal decisions and utility are , .
5. Comparative Analyses
5.1. Feasibility Analysis
- (1)
- . When falls into region I in Figure 5a, the relationship among the sharing mechanisms satisfies SM3 > SM2 > SM1. When falls into region II in Figure 5a, the relationship among the sharing mechanisms satisfies SM2 > SM3 > SM1. When falls into region III in Figure 5a, the relationship among the sharing mechanisms satisfies SM2 > SM1, and SM3 is not better than the BM. See Figure 5a and Table 6a below for details.
- (2)
- . When falls into region I in Figure 5b, the relationship among the sharing mechanisms satisfies SM3 > SM2 > SM1. When falls into region II in Figure 5b, the relationship among the sharing mechanisms satisfies SM3 > SM1, and SM2 is not better than the BM. When falls into regions III and IV in Figure 5b, the relationship among the sharing mechanisms satisfies SM3 > SM2, and SM1 is not better than the BM. When falls into regions V and VI in Figure 5b, the sharing mechanism SM2 is better, but SM1 and SM3 are not better than the benchmark model (BM). When falls into regions VII and VIII in Figure 5b, the sharing mechanism SM3 is better, but SM1 and SM2 are not better than the BM. When falls into the other regions in in Figure 5b, none of the sharing mechanisms—SM1, SM2, or SM3—is better than the BM. See Figure 5b and Table 6b below for details.
- (3)
- . When falls into region I in Figure 5c, the relationship among the sharing mechanisms satisfies SM3 > SM2 > SM1. When falls into region II in Figure 5c, the relationship among the sharing mechanisms satisfies SM3 > SM1, and SM2 is not better than the BM. When falls into regions III and IV in Figure 5c, the relationship among the sharing mechanisms satisfies SM3 > SM2, and SM1 is not better than the BM. When falls into regions V and VI in Figure 5c, the sharing mechanism SM2 is better, but SM1 and SM3 are not better than the BM. When falls into regions VII and VIII in Figure 5c, the sharing mechanism SM3 is better, but SM1 and SM2 are not better than the BM. When falls into the other regions in in Figure 5c, none of the sharing mechanisms—SM1, SM2, or SM3—is better than the BM. See Figure 5c and Table 6c below for details.
- (4)
- . When falls into region I in Figure 5d, the relationship among the sharing mechanisms satisfies SM3 > SM2 > SM1. When falls into region II in Figure 5d, the relationship among the sharing mechanisms satisfies SM3 > SM1, and SM2 is not better than the BM. When falls into regions III and V in Figure 5d, the relationship among the sharing mechanisms satisfies SM2 > SM1, and SM3 is not better than the BM. When falls into region IV in Figure 5d, the sharing mechanism SM2 is better, but SM1 and SM3 are not better than the BM. When falls into regions VI and VII in Figure 5d, the sharing mechanism SM1 is better, but SM2 and SM3 are not better than the BM. When falls into the other regions in in Figure 5d, none of the sharing mechanisms—SM1, SM2, or SM3—is better than the BM. See Figure 5d and Table 6d below for details.
5.2. Sustainability Analysis: Load Ratio, Low-Carbon, and Low-Disruption Dimensions
6. Conclusions
6.1. Summary of Findings
6.2. Managerial Implications
6.2.1. Vertical Integration Based on the Sharing Mechanism
6.2.2. Standardization of Logistics Technology and Equipment
6.2.3. Coordination and Sharing of the Handling Mechanisms during Emergencies
Public Incident
6.3. Limitations and Future Studies
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Notation | Description |
---|---|
Parameters | |
load ratio of trucks to delivery vehicles | |
disruption risk per delivery vehicle | |
non-disruption risk preference coefficient | |
non-disruption risk preference in the benchmark model (BM) | |
non-disruption risk preference in sharing mechanism (SMi; ) | |
number of dispatched delivery vehicles for urban logistics company in BM | |
number of dispatched delivery vehicles in SMi () | |
operational cost of one delivery vehicle | |
feasible regions of the lemmas | |
increase rate of load ratio | |
reduction rate of carbon emissions per unit product | |
reduction rate of the risk of disruption per unit product | |
Decision variables | |
logistics service price | |
market demands | |
distribution service price in BM | |
distribution service price in SMi () | |
revenue-sharing factor in SM2 | |
Utility functions | |
utility function of the intercity logistics companies in BM | |
utility function of the urban logistics distribution companies in BM | |
utility function of the intercity logistics companies in SM1 | |
utility function of the urban sharing logistics distribution company in SM1 | |
utility function of the intercity logistics companies in SM2 | |
utility function of the urban sharing logistics distribution company in SM2 | |
utility function of the intercity logistics companies in SM3 | |
utility function of the urban sharing logistics distribution company in SM3 |
Optimal or Suboptimal | Pros and Cons | Related Parameter Conditions | |
---|---|---|---|
2 | Optimal | ||
3 | Suboptimal | ||
4 | Suboptimal | ||
5 | Optimal | ||
Optimal | |||
Suboptimal | |||
6 | Optimal | ||
Optimal | |||
Suboptimal | |||
7 | Optimal | ||
Optimal | |||
Suboptimal |
Optimal or Suboptimal | Pros and Cons | Related Parameter Conditions | |
---|---|---|---|
2 | Optimal | ||
3 | Optimal | ||
Suboptimal | |||
4 | Optimal | ||
Suboptimal | |||
5 | Optimal | ||
Optimal | |||
Optimal | |||
Suboptimal |
Optimal or Suboptimal | Pros and Cons | Related Parameter Conditions | |
---|---|---|---|
2,3,4 | Optimal | ||
, | Optimal | ||
Optimal |
For any given and SMi =>BM: N() =>SMi : M() =>Lemma 0, Lemma i, min {, } => Feasible region =>BM(, N ):, =>SMi (, M ):, =>Compare the and the ; =>According to Definition i, decide the optimal or suboptimal Pareto improvement End |
(a) | |
Conditions | Mathematical Expression of the Conditions |
Condition (1) | |
Condition (2) | |
(b) | |
Conditions | Mathematical Expression of the Conditions |
Condition (1) | |
Condition (2) | |
Condition (3) | |
(c) | |
Conditions | Mathematical Expression of the Conditions |
Condition (1) | |
Condition (2) | |
Condition (3) | |
(d) | |
Conditions | Mathematical Expression of the Conditions |
Condition (1) | |
Condition (2) | |
Condition (3) | |
Condition (4) | |
Condition (5) | |
Condition (6) |
SM1 | SM2 | SM3 | SM1 | SM2 | SM3 | SM1 | SM2 | SM3 | |
---|---|---|---|---|---|---|---|---|---|
2 | 100% | 100% | 100% | −50% | −50% | −50% | −50% | ||
3 | 0 | 33.3% 0 | 33.3% | 0 | −25% 0 | −25% | 0 | 0 | |
4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | |
5 | 33.3% −16.7% | −16.7% 60% 33.3% 0 | 0 60% | −25% 20% | 20% −37.5% −25% 0 | 0 −37.5% | 0 |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wei, Q.; Gou, X.; Zhang, B. Urban Sharing Logistics Strategies against Epidemic Outbreaks: Its Feasibility and Sustainability. Sustainability 2024, 16, 7628. https://doi.org/10.3390/su16177628
Wei Q, Gou X, Zhang B. Urban Sharing Logistics Strategies against Epidemic Outbreaks: Its Feasibility and Sustainability. Sustainability. 2024; 16(17):7628. https://doi.org/10.3390/su16177628
Chicago/Turabian StyleWei, Qiang, Xinyu Gou, and Baiyang Zhang. 2024. "Urban Sharing Logistics Strategies against Epidemic Outbreaks: Its Feasibility and Sustainability" Sustainability 16, no. 17: 7628. https://doi.org/10.3390/su16177628