Aberrant Riding Behavior of Food Delivery Riders – Model

Abstract

The Aberrant Riding Behavior of Food Delivery Riders—Model (Qian, He, & Shi, 2024) is a psychological instrument designed to quantify the prevalence and nature of unsafe riding behaviors among food delivery personnel. This comprehensive model specifically investigates how safety knowledge influences actual riding behaviors, while simultaneously examining the critical mediating roles played by safety attitudes and risk perceptions in this relationship. The 31-item instrument, validated on a sample of Chinese adults, incorporates items adapted from established studies in traffic psychology to ensure robust psychometric properties, including factor structure, reliability, and validity.

The scale is highly relevant for understanding occupational safety risks in the growing gig economy, particularly concerning two-wheeled vehicle usage. It provides a structured mechanism for evaluating psychological factors that predispose riders to engage in Aberrant Riding Behavior, such as aggressive riding, general violations, and distracted behaviors.

Keywords

Aberrant Riding Behavior, Aggressive Riding, Distraction and Mistakes, Electronic Bikes, Food Delivery Bikes, General Violations, Risk Perception, Safety Attitudes toward Laws, Safety Attitudes toward Responsibility, Safety Knowledge.

Authors

Qian, Qian, He, Junyi, Shi, Jing

Purpose

The primary purpose of the model is to systematically assess and quantify the aberrant riding behavior exhibited by food delivery riders. The instrument is specifically designed not just to measure the behavior itself, but also the underlying cognitive and attitudinal factors—namely, safety knowledge, safety attitudes, and risk perception—that contribute to or mitigate these unsafe actions in a high-pressure delivery context.

The results derived from this model are intended to inform targeted interventions, training programs, and policy changes aimed at enhancing road safety for both riders and the general public, particularly in urban environments where two-wheeled electronic vehicles are prevalent for commercial delivery.

Construct

The Aberrant Riding Behavior of Food Delivery Riders—Model measures a complex set of interrelated psychological and behavioral constructs relevant to traffic safety:

• Aberrant Riding Behavior: The core outcome variable, encompassing self-reported unsafe driving acts, categorized into general violations, distraction and mistakes, and aggressive riding tendencies.
• Safety Knowledge (SK): The rider’s understanding of traffic laws, safety protocols, and accident prevention strategies pertinent to operating an e-bike.
• Safety Attitudes and Risk Perceptions (SA & RP): This crucial mediating layer includes Safety Attitudes toward Responsibility (SA-r), Safety Attitudes toward Laws (SA-l), and Risk Perception (RP), which gauges the rider’s subjective assessment of the likelihood and severity of negative outcomes resulting from unsafe behaviors.

Validity

The validation process confirmed both the convergent and discriminant validity of the scale components. Convergent validity was established by confirming that the Average Variance Extracted (AVE) for all factors exceeded the recommended threshold of 0.5. This result indicates that the items designed to measure a specific construct share a high proportion of variance in common.

Discriminant validity was rigorously confirmed using the Fornell-Larcker method. This analysis showed that the square root of the AVE for each factor was greater than the highest correlation coefficients between that factor and all other factors in the model. This statistical evidence ensures that each latent construct measures a unique concept distinct from the others.

Reliability

The scale demonstrated strong internal consistency and acceptable stability across its various subscales. For internal consistency reliability, the Cronbach’s alpha (Cronbach’s α) coefficients ranged from 0.706 to 0.944, and the Composite Reliability (CR) values spanned from 0.836 to 0.934. These values are well above the conventional acceptance criteria, confirming the reliability of the measurements.

Furthermore, the study assessed split-half reliability. The Spearman-Brown coefficients were reported as 0.804 for the Safety Attitudes toward Laws (SA-l) scale and 0.821 for the Risk Perception (RP-p) scale, further supporting the robust consistency of the instrument components.

Factor Analysis

Both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized to confirm the underlying factor structure of the 31-item model. The EFA results indicated a sound structure, with the total cumulative variance contribution exceeding 60%, suggesting the factors account for a substantial portion of the variance in the items. The Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy were high (0.821 and 0.912), confirming the data’s suitability for factor analysis.

The subsequent CFA provided strong evidence for the model’s fit to the observed data. Key fitness indices were reported as: Chi-square/DF = 1.929 (indicating good fit below the threshold of 3.0), RMSEA = 0.064 (meeting the standard for acceptable fit), CFI = 0.916, IFI = 0.917, and TLI = 0.904. These indices collectively confirm the structural integrity and validity of the proposed theoretical model linking safety knowledge, attitudes, risk perception, and aberrant behavior.

Instrument

Test Type: Inventory/Questionnaire

Format: Items are primarily rated on 5-point Likert-type scales, ranging from “Totally Uninformed” to “Very Well-Informed” (for knowledge) or “Never” to “Always” (for behavior frequency).

Language Available: Chinese (Initial validation)

Population Group: Human; Male; Female.

Age Group: Adulthood (18+), spanning Young Adulthood (18-29 yrs), Thirties (30-39 yrs), and Middle Age (40-64 yrs).

Population Details: Respondents were adult food delivery riders recruited from various regions in China.

Test Methodology: Electronic administration was used for data collection.

Keywords

Aberrant Riding Behavior, Electronic Bikes, Food Delivery Riders, Safety Knowledge, Risk Perception, Safety Attitudes, Traffic Psychology, Questionnaire.

Authors

Author ORCID Identifier: Not provided in source content.

Affiliation Email addresses: Not provided in source content.

Correspondence Address: Not provided in source content.

Permissions & Fee and Test Year

Permissions and Fees: Information regarding permissions, licensing, and associated fees is not provided in the source material. Researchers should contact the corresponding author, Qian Qian, for usage rights.

Test Year: 2024

Reference’s

Qian, Q., He, J., & Shi, J. (2024). Analysis of factors influencing aberrant riding behavior of food delivery riders: A perspective on safety attitude and risk perception. Transportation Research Part F: Traffic Psychology and Behaviour, 100, 273–288. The official academic reference can be accessed via the DOI: https://doi.org/10.1016/j.trf.2023.12.007

The instrument development also drew upon previous studies:

• Wang et al., 2010
• Wang et al., 2021
• Nguyen-Phuoc et al., 2020
• Jamil et al., 2021
• Zhao et al., 2021
• Shi et al., 2010

Items of the Aberrant Riding Behavior of Food Delivery Riders – Model

IMPORTANT: The following scale items must be preserved in their original language and must not be changed in any way.

I. Scale Components and Items

The model is composed of three main sections: Safety Knowledge (SK), Safety Attitudes and Risk Perception (RP), and Aberrant Riding Behaviors.

A. Safety Knowledge (SK)

This section assesses the rider’s understanding of safety-related information. Items are rated on a five-point Likert scale ranging from 1 (Totally Uninformed) to 5 (Very Well-Informed).

• A1. Exposure to safety training or awareness education

• A2. Understanding of e-bike traffic-related codes or laws

• A3. Understanding of rider accident insurance

B. Safety Attitudes and Risk Perception (RP)

This section examines riders’ attitudes toward safety and their perception of risk. Items are rated on a five-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree).

• A4. I will be responsible for the safety of others during the delivery process.

• A5. I will do my best to prevent crashes during the delivery process.

• A6. I will feel guilty if a crash occurs due to my own fault.

• A7. I think every delivery rider should be responsible for his or her own behavior.

• A8. If a crash occurs, it will seriously affect the family’s life. (Note: Items in this factor are reverse-scored in subsequent analysis)

• A9. I think it is okay to violate traffic rules to pursue faster delivery while ensuring safety.

• A10. Sometimes it is possible to violate traffic rules to ensure the goods are delivered on time.

• RP-s G1. How risky do you think running a red light on an e-bike is?

• RP-s G2. How risky do you think drunk-riding is?

• RP-s G3. How risky do you think riding in the opposite direction because the vehicle in front of you is blocking the traffic is?

• RP-s G4. How risky do you think pulling into a motor lane when the non-motor lane is congested is?

• RP-s G5. How risky do you think traveling at a higher speed than the surrounding traffic is?

• RP-p G6. Possibility of being injured in a crash in the next 12 months

• RP-p G7. Possibility of being involved in a crash in the next 12 months.

C. Aberrant Riding Behaviors

This section assesses the frequency of specific unsafe riding behaviors. Items are rated on a five-point Likert scale with numbers 1-5 indicating Never, Rarely, Occasionally, Sometimes, and Always, respectively.

• F1. Speeding (over 25 km/h)

• F2. Running a red light

• F3. Running a yellow light

• F4. Riding in the opposite direction

• F5. Occupying a motor lane

• F6. Changing lanes at your own discretion

• F7. Making/receiving phone calls

• F8. Not using a turn signal when making a turn

• F9. Turning too fast and making the e-bike difficult to control

• F10. Inattention and almost colliding with pedestrians or objects

• F11. Forcibly approaching or cutting through when the vehicle in front of you is turning right

• F12. Not slowing down before an intersection

• F13. Not slowing down to give way when entering or leaving a pedestrian area (e.g., a school or a bus stop)

• F14. Scrambling when merging with other vehicles

• F15. Checking delivery routes (using cell phones) during the delivery process

• F16. Drinking or eating in the delivery process

• F17. Not slowing down when passing vehicles

• F18. Not slowing down on rainy roads

Note: The last four items (F15-F18) were excluded from the final measure.