The impact of taxi drivers’ characteristics on the propensity to do business: Case study from a sharing economy

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This paper aims to quantify the impact of selected demographic, financial, and economic factors on the propensity to do business in the taxi sector of the sharing economy. The sample comprised 375 taxi drivers from the Czech Republic and Slovak Republic. Data were collected using the query method via a questionnaire in April 2022. The structure of the respondents is divided into shared taxi service providers (N = 294) and traditional taxi service providers (N = 69). The study selected 14 factors: demographic (4), financial (7), and economic (3). The SEM approach was applied to evaluate the hypotheses. Shared taxi providers have a stronger propensity to do business than traditional taxi drivers. Demographic characteristics of a traditional taxi driver are the most significant factors with a strong influence on the propensity to do business (βS = 0.525 > βT = 0.425). On the other hand, the financial and economic characteristics of shared taxi drivers strongly influence the propensity to do business (βT = 0.565 > βS = 0.212). The characteristics of the enterprise are on the verge of significance in relation to the tendency to do business with shared taxi drivers, as opposed to traditional taxi drivers. For traditional taxi drivers, there is a strong influence of the characteristics of the enterprise on the propensity to do business (βT = 0.476 > βS = 0.026). This study contributes to understanding how participating in sharing economy may stimulate the propensity to do business.

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    • Figure 1. Visualization of final models (S)
    • Figure 2. Visualization of final models (T)
    • Table 1. Selected characteristics of shared and traditional taxi service providers
    • Table 2. Results of descriptive characteristics and internal consistency (CI-TC) (S/T)
    • Table 3. Reliability, validity, KMO test, and Bartlett‘s test (S/T)
    • Table 4. Evaluation of statistics hypotheses with testing path coefficients
    • Table 5. Summary fit model (S/T)
    • Table 6. Representation of respondents with a positive attitude toward the propensity to do business
    • Conceptualization
      Zoltan Rozsa, Aknur Zhidebekkyzy
    • Formal Analysis
      Zoltan Rozsa, Aknur Zhidebekkyzy
    • Methodology
      Zoltan Rozsa
    • Supervision
      Zoltan Rozsa
    • Resources
      Aknur Zhidebekkyzy
    • Software
      Aknur Zhidebekkyzy
    • Funding acquisition
      Yuriy Bilan
    • Project administration
      Yuriy Bilan
    • Validation
      Yuriy Bilan
    • Writing – review & editing
      Yuriy Bilan
    • Data curation
      Jana Drahosova
    • Investigation
      Jana Drahosova
    • Visualization
      Jana Drahosova
    • Writing – original draft
      Jana Drahosova