| Title | Most Successful Business Models In Logistics Innovations - The Review Of Crowd Logistics Solutions |
|---|---|
| ID_Doc | 71208 |
| Authors | Szmelter-Jarosz, A; Chmiel, B; Sledzik, K |
| Title | Most Successful Business Models In Logistics Innovations - The Review Of Crowd Logistics Solutions |
| Year | 2023 |
| Published | Logforum, 19.0, 3 |
| Abstract | Background: Crowd logistics is a relatively new phenomenon that has emerged due to the growing demand for flexible, efficient, and sustainable delivery solutions. This paper presents an empirical study of crowd logistics initiatives by collecting a comprehensive dataset of companies operating in this field. Our research aims to identify the elements of the most successful crowd logistics business models and identifies the causes for their failures. Materials and methods: To achieve these goals, we conduct a systematic screening of the world market, which allows us to identify a diverse set of crowd logistics initiatives, ranging from small startups to well-established companies. We then classify these initiatives based on their business models, main business areas, and services. We also review the EU-funded projects related to the development of crowd logistics. Finally, we analyze the main business areas of each initiative, such as urban logistics, last-mile delivery, and transportation of goods. Results: We present the full view of crowd logistics solutions worldwide, their main characteristics, and models to build a complete picture of those solutions and assess them as being successful or unsuccessful by providing the list of the features identified as success factors and failure factors. Conclusions: Finally, we conclude that crowd logistics, despite many failures observed worldwide, can be a successful solution for urban logistics if it meets the requirements mentioned in the results section. Our findings provide insights into the emerging landscape of crowd logistics and offer practical implications for managers, policymakers, and researchers. |
| https://doi.org/10.17270/j.log.2023.840 |
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