Freight Demand and Supply Assessment for Implementation of Crowdsourcing Technology: A Case Study in Bratislava, Slovakia

• Main Authors: Andrii Galkin, Tibor Schlosser, Ivan Cardenas, Dominika Hodakova, Silvia Capayova
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Sustainability
• Subjects: crowd shipping; regression; questionnaire; freight; goods; gender
• Online Access: https://www.mdpi.com/2071-1050/13/7/3865

The article studies the development of crowd shipping technologies in the Old Town of Bratislava. The paper aims to assess the potential for implementation of the crowdsourcing technology in the transport system of Bratislava. Methodology: An interview with the entrepreneurs in this area was conducted to assess the potential demand. In the survey, we collected information about type of goods; operations, quantities, and frequency of delivery; willingness to pay for one delivery among others. Based on the results, the freight demand, and its characteristics were assessed. The second part of the paper is devoted to assessing the supply of logistics to meet the demand. A survey of the willingness of ordinary travelers to work as an occasional courier was conducted. In the end, the equilibrium of demand and supply in the crowd shipping market in Bratislava is presented. The regression and correlation analysis were performed to understand the relationship between parameters of demand and delivery quantities in the first part of the research, sociodemographic characteristics of nonprofessional couriers, and the maximum weight of the parcel nonprofessional couriers agree to delivery. The willingness to pay per delivery was determined for respondents of different genders. Key findings: The results of the survey allowed us to estimate the freight demand for the Old Town of Bratislava, as well as to understand the needs of potential demand for crowd shipping services. The results of the second questionnaire show the sociodemographic characteristics of nonprofessional couriers (age, gender, gender, income, travel time) significantly influence the decision to participate in the delivery market.