Modeling a Logistics Hub Using the Digital Footprint Method—The Implication for Open Innovation Engineering
Abstract
1. Introduction
2. Theoretical Foundations and Methodology
2.1. Literature Review
2.2. Problem Statement
2.3. Method of Research
2.4. Mathematical Modeling of Goods and Cargo Flows
3. Results
3.1. Experience-Oriented Solutions. Huawei History
3.2. Huawei Business Status
3.3. Huawei Perspective, Mission and Strategy
3.4. Company Management System
- constant innovations, consumer-oriented and based on their needs and technological leadership, for creation of sure-fire ecosystem;
- risk control for business continuity;
- maintaining corporate social responsibility and achieving sustainable social development.
3.5. Mathematical Model of DC Operation
3.6. Calculation Example
3.7. Practical Calculation on a Computer Using Mathematical Modeling
4. Discussion
4.1. Discussion: A logistics Hub Using the Digital Footprint Method
4.2. Discussion: Open Innovation Engineering from the Digital Footprint Method
- -
- Open innovation engineering: Preliminary study on new entrance of technology to market;
- -
- Open R&D and open innovation: exploring the phenomenon;
- -
- Open innovation and serial entrepreneurs;
- -
- The fit between firms’ open innovation and business model for new product development speed: a contingency perspective;
- -
- Bringing open innovation to services;
- -
- Open innovation in value networks.
- (a)
- how central firms choose between different governance modes when they establish relations with partners;
- (b)
- studying value constellations being a nexus for the integration of different theoretical perspectives since they are a nexus where value creation, non-arm’s-length transactions, external resource sourcing and inter-organizational networking are welded together;
- (c)
- analyzing Open Innovation at different levels and that interorganizational networks.
5. Conclusions
- -
- Formalize the characteristics of the stochastic flow of goods and cargo through the logistics hub.
- -
- Assess the parameters of the two main cross-docking and pick-by-line technologies in cargo handling.
5.1. Advantages of the Enterprise
5.2. Disadvantages of the Enterprise
5.3. Model Implementation
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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2014 | 2015 | 2016 | 2017 | 2018 | |
---|---|---|---|---|---|
Sales revenue | 239,025 | 288,197 | 395,009 | 521,574 | 609,621 |
Operating revenue | 239,025 | 288,197 | 395,009 | 47,515 | 5638 |
Operating margin | 12.2% | 11.9% | 11.6% | 9.1% | 9.3% |
Margin of profit | 21,003 | 27,866 | 36,910 | 37,052 | 47,455 |
Operating cash flow | 22,554 | 41,755 | 52,300 | 49,218 | 96,336 |
Financial resources and short-range investments | 81,944 | 106,036 | 125,208 | 145,653 | 199,943 |
Operative expenses | 75,180 | 78,566 | 89,019 | 116,231 | 137,576 |
Total assets | 244,091 | 309,773 | 372,155 | 443,634 | 505,225 |
Total borrowings | 23,033 | 28,108 | 28,986 | 44,799 | 39,925 |
Owned capital | 86,266 | 99,985 | 119,069 | 140,133 | 175,616 |
Assets and liabilities | 64.7% | 67.7% | 68.0% | 68.4% | 65.2% |
Penalty | A1 | A2 | A3 | A4 | A5 | |
---|---|---|---|---|---|---|
Limitation on stocks held in DC | r = 0 | 0 | 27.5 | 55 | 110 | 137.5 |
r = 1 | 0.42 | 23.3 | 46.2 | 92.1 | 115.1 | |
r = 2 | 1.2 | 20 | 38.7 | 76.2 | 95.2 | |
r = 3 | 2.5 | 17.55 | 32.51 | 62.53 | 77.6 | |
r = 4 | 4.19 | 15.8 | 27.51 | 50.83 | 62.55 | |
r = 5 | 6.25 | 15.3 | 23.75 | 41.25 | 50.1 | |
r = 6 | 8.75 | 15.1 | 21.29 | 33.71 | 40.3 | |
r = 7 | 11.67 | 15.83 | 20.21 | 28.33 | 32.50 | |
r = 8 | 15 | 17.5 | 20.7 | 25.3 | 27.51 | |
r = 9 | 18.75 | 20.1 | 21.2 | 23.7 | 25.4 | |
r = 10 | 22.92 | 23.33 | 23.75 | 24.58 | 25.02 | |
r = 11 | 27.51 | 27.51 | 27.51 | 27.51 | 27.51 | |
r = 12 | 32.54 | 32.54 | 32.54 | 32.54 | 32.54 | |
min expenses | 0 | 14.2 | 18.6 | 21.1 | 22.3 |
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Shmatko, A.; Barykin, S.; Sergeev, S.; Thirakulwanich, A. Modeling a Logistics Hub Using the Digital Footprint Method—The Implication for Open Innovation Engineering. J. Open Innov. Technol. Mark. Complex. 2021, 7, 59. https://doi.org/10.3390/joitmc7010059
Shmatko A, Barykin S, Sergeev S, Thirakulwanich A. Modeling a Logistics Hub Using the Digital Footprint Method—The Implication for Open Innovation Engineering. Journal of Open Innovation: Technology, Market, and Complexity. 2021; 7(1):59. https://doi.org/10.3390/joitmc7010059
Chicago/Turabian StyleShmatko, Alexey, Sergey Barykin, Sergey Sergeev, and Anuphat Thirakulwanich. 2021. "Modeling a Logistics Hub Using the Digital Footprint Method—The Implication for Open Innovation Engineering" Journal of Open Innovation: Technology, Market, and Complexity 7, no. 1: 59. https://doi.org/10.3390/joitmc7010059
APA StyleShmatko, A., Barykin, S., Sergeev, S., & Thirakulwanich, A. (2021). Modeling a Logistics Hub Using the Digital Footprint Method—The Implication for Open Innovation Engineering. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 59. https://doi.org/10.3390/joitmc7010059