Bicycle Usage Intention Survey Analysis for Puerto Madryn

Leo Ordínez created a dataset containing a table of multinomial logistic regression results. The analysis models the potential increase in bicycle use over the next 12 months in Puerto Madryn, with difficulties in cycling as explanatory factors. The dependent variable is the intention to increase bike use, and the model explains the relationship between these factors and the outcome.

Use Cases

• Modeling transportation mode shift intentions based on perceived cycling difficulties.
• Analyzing the relative effect of different barriers on future bicycle adoption.
• Predicting the likelihood of increased bicycle use for new survey respondents based on their reported difficulties.

Strengths

• The dataset is derived from a specific multinomial logistic regression analysis, providing a structured statistical model.
• The analysis focuses on a concrete dependent variable: the potential increment in bicycle use within a 12-month timeframe.
• The dataset is associated with a specific geographical context, Puerto Madryn.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to the survey conducted in Puerto Madryn.

Provenance

Source

Leo Ordínez via paperswithcode

Collection Method

Likely derived from a survey or experiment analyzing cycling difficulties and future usage intentions.

Geography

Puerto Madryn