Drivers of Urban Public Transportation Adoption in the Post-COVID-19 Era–Model Inventory

Abstract

The Drivers of Urban Public Transportation Adoption in the Post-COVID-19 Era–Model Inventory (DUPTA-M) is an advanced psychometric instrument developed by Anwar et al. (2023) to evaluate urban commuters’ behavioral intentions to transition from private vehicles back to mass transit systems following the disruption of the global pandemic. Grounded in an integrated synthesis of the Push-Pull-Mooring (PPM) framework of human migration and institutional theory, the inventory operationalizes seven key latent dimensions: Regulative Environment (REG), Affordability (AFF), Hygiene Concern (HC), Choice Uncertainty (CU), Green Self-Identity (GSI), Normative Environment (NOE), and Switching Intentions Towards Public Transport (SWI). Comprising 24 self-report items administered on a 5-point Likert scale ranging from 1 (Strongly disagree) to 5 (Strongly agree), the instrument captures the complex trade-offs individuals navigate between environmental stewardship and personal health preservation.

The psychometric integrity of the DUPTA-M was established using structural equation modeling (SEM) and confirmatory factor analysis (CFA) across a representative sample of adult urban transit consumers within metropolitan regions of the United States. Empirical validation demonstrated exceptional internal consistency, with composite reliability (CR) coefficients spanning from 0.72 to 0.95 across all latent constructs. Convergent validity was substantiated by average variance extracted (AVE) values ranging between 0.51 and 0.84, satisfying standard psychometric thresholds. Discriminant validity was rigorously corroborated through both the Fornell-Larcker criterion and the Heterotrait-Monotrait ratio of correlations (HTMT), with all values resting strictly below the conservative cut-off of 0.85. The measurement model exhibited exemplary goodness-of-fit indices (χ²/df = 1.60, CFI = 0.98, TLI = 0.98, RMSEA = 0.03), and Harman’s single-factor test confirmed the absence of common method bias (17.91% maximum variance explained). The DUPTA-M provides urban planners, municipal policymakers, and behavioral researchers with an empirically robust diagnostic tool for designing sustainable transit interventions.

Keywords

Affordability, Choice Uncertainty, Green Self-Identity, Hygiene Concern, Normative Environment, Post-COVID-19 Era, Regulative Environment, Switching Intentions Towards Public Transport, Push-Pull-Mooring, Institutional Theory

Authors

The DUPTA-M inventory was developed and validated by an international research consortium specializing in consumer behavior, sustainable supply chain management, and applied environmental psychology:

• Muhammad Azfar Anwar — College of Management, Research Institute of Business Analytics and Supply Chain Management, Shenzhen University, Shenzhen, China. Email: [email protected]
• Amandeep Dhir — Norwegian School of Hotel Management, Faculty of Social Sciences, University of Stavanger, Stavanger, Norway; Department of Management, School of Business & Law, University of Agder, Kristiansand, Norway. ORCID: 0000-0002-6006-6058. Email: [email protected]
• Fauzia Jabeen — College of Business, Abu Dhabi University, Abu Dhabi, United Arab Emirates. Email: [email protected]
• Qingyu Zhang (Corresponding Author) — College of Management, Research Institute of Business Analytics and Supply Chain Management, Shenzhen University, Shenzhen, China. Email: [email protected]
• Ahmad Nabeel Siddiquei — Bond Business School, Bond University, Robina, Queensland, Australia. Email: [email protected]

Purpose

The overarching purpose of the Drivers of Urban Public Transportation Adoption in the Post-COVID-19 Era–Model Inventory is to decipher and quantify the psychological mechanisms, perceived structural barriers, and social-institutional forces governing commuters’ modal shifts back toward public transportation. The COVID-19 pandemic catalyzed unprecedented disruptions in global mobility patterns, inducing widespread transit avoidance due to heightened contagion fear, physical distancing mandates, and the proliferation of remote work arrangements. As urban ecosystems transition into an endemic or post-pandemic phase, municipal authorities face critical challenges regarding vehicle congestion, carbon emissions, and declining fare revenues. The DUPTA-M was constructed to illuminate why commuters hesitate or decide to resume transit usage, focusing specifically on the trade-offs between prosocial environmental motivations and self-protective health orientations.

In applied research, the inventory serves as an operational instrument to evaluate the direct influence of personal hygiene concerns on behavioral switching intentions. Crucially, the scale is designed to examine the moderating and mediating effects that health anxieties exert on established push factors (e.g., negative perceptions of private vehicle costs or transit affordability hurdles), pull factors (e.g., green self-identity and institutional incentives), and mooring dimensions (e.g., situational choice uncertainty and social support). For urban transportation authorities and transportation psychologists, the DUPTA-M provides actionable diagnostic intelligence to identify which factors impede transit recovery: whether non-adoption is primarily driven by institutional distrust, biological health apprehension, financial misalignments, or ambiguous modal choices.

From a theoretical standpoint, the DUPTA-M bridges the gap between individual-level rational choice models and macro-level socio-environmental frameworks. Traditional behavioral models such as the Theory of Planned Behavior (TPB) often fail to account for exogenous biological crises or the dual pressures of institutional governance and self-identity. By providing standardized metrics across institutional, economic, psychological, and normative domains, the scale facilitates cross-regional comparisons and allows municipal agencies to design targeted behavioral interventions, infrastructure sanitization policies, and subsidized fare structures grounded in psychometrically verified evidence.

Psychological Construct

The DUPTA-M conceptualizes modal switching behavior as a multidimensional construct emerging from the interplay of individual cognitions, affective health anxieties, and systemic institutional signals. It operationalizes seven distinct dimensions:

1. Regulative Environment (REG)

Grounded in institutional theory, this dimension measures an individual’s perception of the formal rules, enforcement mechanisms, sanitization mandates, and supportive safety infrastructure deployed by municipal transit authorities and national governments. Rather than evaluating generic governmental trust, REG explicitly assesses whether transit operators provide active health safeguards, such as dedicated supervisory personnel, hand sanitizing infrastructure, and free distribution of personal protective equipment (PPE). High scores reflect a strong cognitive appraisal that the public transit environment is governed by stringent, protective regulatory mechanisms.

2. Affordability (AFF)

Affordability assesses the commuter’s cognitive appraisal of the financial costs associated with mass transit usage relative to their perceived economic utility. Framed through the lens of economic friction, this construct reflects the perceived expense of daily transit passes, baseline ticket fares, and routine travel costs. In modal switching paradigms, heightened perceptions of unaffordability function as economic push or mooring constraints that discourage consumers from abandoning private automotive transport.

3. Hygiene Concern (HC)

This subscale captures the behavioral and affective vigilance exercised by commuters regarding pathogen exposure, microbial contamination, and surface cleanliness within crowded transit micro-environments. It measures active physical avoidance behaviors, such as refraining from touching grab rails and surfaces, alongside self-regulatory hygienic practices such as immediate hand washing and respiratory etiquette. Hygiene concern serves as the pivotal psychological anchor in the post-pandemic context, operating as an inhibitor that can override green consumer tendencies.

4. Choice Uncertainty (CU)

Choice uncertainty measures cognitive ambiguity, decision paralysis, and situational unpredictability concerning travel arrangements. It encompasses instability regarding mode selection (e.g., choosing between shared micro-mobility, buses, or rail systems), scheduling dilemmas (e.g., peak versus off-peak commuting), and difficulty in forecasting passenger density to avoid overcrowded vehicles. CU operationalizes a state of bounded rationality wherein prospective passengers experience information overload or risk aversion when attempting to reintegrate into public transportation networks.

5. Green Self-Identity (GSI)

Rooted in identity theory, GSI assesses the extent to which an individual views themselves as an environmentally ethical and socially responsible consumer. Commuters with an entrenched green self-identity align their consumer behaviors with planetary welfare, viewing public transit adoption as an expressive manifestation of their moral values and ecological responsibility. Within the DUPTA-M, GSI represents an intrinsic motivational pull driving sustainable mobility.

6. Normative Environment (NOE)

The normative environment evaluates the perceived presence of relational social support, emotional validation, and collective solidarity experienced by the commuter during periods of crisis or behavioral transition. Composed of relational appraisals regarding having people who listen, encourage, and show concern for one’s physical and psychological wellbeing, NOE reflects the informal social fabric that bolsters individual resilience and facilitates adaptive behavioral decisions amidst external environmental stressors.

7. Switching Intentions Towards Public Transport (SWI)

Serving as the primary behavioral outcome construct, SWI measures the commuter’s conscious, planned readiness and subjective probability of replacing private automotive commuting with urban public transit in the near future. It operationalizes high-order behavioral commitment across intentionality, strategic planning, desire, and self-predicted likelihood of modal transition.

Theoretical Framework

The conceptual architecture of the DUPTA-M synthesizes two foundational social science theories: the Push-Pull-Mooring (PPM) Model of Migration and Institutional Theory.

The Push-Pull-Mooring (PPM) Framework

Originally formulated in geographical demography by Everett S. Lee and subsequently adapted for consumer switching behavior by Bansal et al., the PPM framework posits that switching decisions are governed by three interacting forces:

• Push Factors: Negative external conditions or structural frictions that motivate an individual to depart from an incumbent status quo (e.g., high private vehicle maintenance costs, traffic congestion, or perceived transit price distortions captured via Affordability).
• Pull Factors: Positive attributes, ethical appeals, or situational advantages exerted by the alternative destination (e.g., the ecological benefits of mass transit captured via Green Self-Identity, alongside robust institutional safeguards).
• Mooring Factors: Personal, cultural, situational, or psychological variables that either facilitate or impede the switching trajectory, acting as moderating catalysts or structural anchors. In the DUPTA-M, Hygiene Concern and Choice Uncertainty operate as quintessential mooring variables. Even when a commuter acknowledges the ecological pull of public transit, pervasive pathogen apprehension (HC) and temporal-spatial ambiguity (CU) create cognitive friction, mooring the commuter to private vehicular transport.

Institutional Theory

To augment the individualistic assumptions of standard consumer decision models, Anwar et al. integrated the regulative pillar of institutional theory, famously articulated by W. Richard Scott. Institutional theory asserts that human behavior is fundamentally bounded and legitimized by external social structures, including formal legal regulations, surveillance, enforcement, and cultural-cognitive expectations.

In the wake of COVID-19, personal health cannot be disentangled from the macro-institutional environment. Commuters require structural assurance that transit authorities are exercising collective guardianship through sanitization mandates, volunteer deployment, and the provision of protective equipment. The regulative environment provides an institutional scaffolding that lowers perceived personal risk, mitigating the inhibitory friction generated by hygiene concerns and enabling intrinsic green values to translate into actionable switching intentions.

Validity

The DUPTA-M underwent extensive psychometric validation following rigorous empirical protocols to establish content, convergent, and discriminant validity.

Content and Face Validity

The initial generation of items was adapted from established psychometric literature, including validated scales from Sajjad et al. (2020) for regulative and normative environments, Zhang et al. (2014) for transit affordability, Shiu et al. (2011) for hygiene concerns, Tung et al. (2017) for green self-identity, and Jung et al. (2017) for switching intentions. To ensure content and face validity, the preliminary instrument was evaluated by an expert panel comprising three senior academics specializing in marketing, public health, and environmental psychology. The panel assessed item relevance, syntactic clarity, conceptual alignment, and contextual suitability for post-pandemic transit dynamics, leading to minor iterative refinements.

Convergent Validity

Convergent validity was evaluated via confirmatory factor analysis utilizing two primary criteria: standardized factor loadings and the Average Variance Extracted (AVE). In accordance with the classical benchmarks formulated by Fornell and Larcker (1981):

• Standardized item factor loadings across all seven constructs demonstrated high statistical significance (p < 0.001) and exceeded the desirable threshold of 0.60, with the vast majority surpassing 0.70.
• The calculated Average Variance Extracted (AVE) for each construct fell between 0.51 and 0.84, consistently exceeding the mandated minimum benchmark of 0.50. This confirms that the latent constructs account for more than 50% of the variance observed across their respective manifest indicators.

Discriminant Validity

Discriminant validity was established using two complementary analytical approaches:

• Fornell-Larcker Criterion: The square root of the AVE for each latent construct was strictly greater than the inter-construct correlations between that construct and all other latent variables in the model.
• Heterotrait-Monotrait Ratio of Correlations (HTMT): Recognizing the conservative nature of traditional methods, the authors conducted HTMT analysis. All estimated HTMT ratios remained well beneath the stringent 0.85 cut-off threshold, empirically verifying that the seven dimensions represent statistically distinct theoretical entities.

Reliability

The reliability of the DUPTA-M was rigorously examined to ensure exceptional internal consistency across all latent measurement subscales. In structural equation modeling, traditional Cronbach’s alpha coefficients are often supplemented or superseded by Composite Reliability (CR), which accounts for unequal factor loadings across indicators and avoids the systemic underestimation of scale reliability associated with tau-equivalence assumptions.

Across the seven validated constructs, the Composite Reliability (CR) values yielded the following results:

• Composite Reliability Range: 0.72 to 0.95 across all constructs.
• Benchmark Comparison: All values comfortably exceed the generally recommended cut-off threshold of 0.70 established by Hair et al. (2010), demonstrating robust scale reliability and minimal measurement error.
• Construct-Specific Performance: High-loading constructs such as Switching Intentions (SWI) and Regulative Environment (REG) exhibited CR coefficients exceeding 0.90, reflecting high internal consistency suitable for predictive and structural path modeling.

Factor Analysis

The latent factor structure of the DUPTA-M was scrutinized using both diagnostic common method bias testing and rigorous Confirmatory Factor Analysis (CFA).

Assessment of Common Method Bias

Because self-report surveys administered concurrently can introduce common method variance, the authors conducted Harman’s single-factor test in accordance with the methodological guidance of Podsakoff et al. (2003). When all 24 manifest items were constrained to load onto a single unrotated exploratory factor, the maximum variance extracted by that solitary construct was only 17.91%. Because this figure falls well below the conservative threshold of 50%, common method bias was ruled out as a threat to the study’s validity.

Confirmatory Factor Analysis (CFA) Fit Indices

A maximum-likelihood confirmatory factor analysis was conducted to establish structural dimensionality. The hypothesized seven-factor measurement model demonstrated exceptional goodness-of-fit to the empirical data:

• Chi-Square to Degrees of Freedom Ratio (χ²/df): 1.60 (Threshold: ≤ 3.0 represents excellent fit; ≤ 5.0 represents acceptable fit).
• Comparative Fit Index (CFI): 0.98 (Threshold: ≥ 0.95 indicates superior model fit).
• Tucker-Lewis Index (TLI): 0.98 (Threshold: ≥ 0.95 indicates superior model fit).
• Root Mean Square Error of Approximation (RMSEA): 0.03 with a 90% confidence interval falling well below 0.05 (Threshold: ≤ 0.06 reflects close fit).

These fit metrics substantiate that the empirical data fit the theoretical seven-factor model, confirming that each item functions as an indicator of its designated construct without unacceptable cross-loadings.

Instrument / Measurement Tool

The DUPTA-M is structured as a standardized psychological survey instrument. Its technical and operational parameters are detailed below:

• Test Type: Multi-dimensional psychometric rating inventory / self-report survey.
• Administration Format: Standardized paper-and-pencil or digital/computer-assisted questionnaire.
• Target Population: Adult urban commuters and public transit consumers (aged 18 and older, including young adults, thirties, and middle-aged commuters) across metropolitan regions.
• Item Count: 24 operational items distributed across 7 latent subscales:
  • Regulative Environment (REG): 4 items
  • Affordability (AFF): 3 items
  • Hygiene Concern (HC): 3 items
  • Choice Uncertainty (CU): 4 items
  • Green Self-Identity (GSI): 2 items
  • Normative Environment (NOE): 4 items
  • Switching Intentions Towards Public Transport (SWI): 4 items
• Response Scale: 5-point Likert scale formatted as:
  • 1 = Strongly disagree
  • 2 = Disagree
  • 3 = Neutral
  • 4 = Agree
  • 5 = Strongly agree
• Scoring Protocol: Individual subscale scores are computed either by calculating the arithmetic mean or the sum of items within each respective construct. In advanced multivariate and structural equation modeling, latent construct scores should be derived from standardized factor score weights. Higher scores on REG indicate greater perceived institutional safety support; higher AFF reflects stronger perceptions that transit is financially burdensome; higher HC reflects greater microbial vigilance; higher CU indicates greater modal decision ambiguity; higher GSI denotes stronger environmental self-concept; higher NOE reflects greater perceived social support; and higher SWI denotes strong commitment to adopting public transit.

Permissions & Fee and Test Year

The Drivers of Urban Public Transportation Adoption in the Post-COVID-19 Era–Model Inventory was developed and published in 2023 by Muhammad Azfar Anwar, Amandeep Dhir, Fauzia Jabeen, Qingyu Zhang, and Ahmad Nabeel Siddiquei in the Journal of Business Research.

• Academic Permissions: The instrument is open-access under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License. Researchers, educators, and public transportation planners are permitted to copy, distribute, adapt, and use the scale without formal permission, provided appropriate credit is given to the original authors and the source publication.
• Commercial Use: Commercial exploitation, proprietary resale, or packaging into commercial diagnostic suites requires authorization or adherence to relevant institutional and publisher agreements.
• Fee: There is no fee required to administer, adapt, or cite this scale for academic research and educational assessments.

References

• Anwar, M. A., Dhir, A., Jabeen, F., Zhang, Q., & Siddiquei, A. N. (2023). Unconventional green transport innovations in the post-COVID-19 era. A trade-off between green actions and personal health protection. Journal of Business Research, 155(Part A), Article 113442. https://doi.org/10.1016/j.jbusres.2022.113442
• Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). Prentice Hall.
• Jung, J., Han, H., & Oh, M. (2017). Travelers’ switching intentions toward green hotels: An application of the push-pull-mooring model. International Journal of Contemporary Hospitality Management, 29(4), 1146–1166. https://doi.org/10.1108/IJCHM-03-2016-0158
• Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
• Sajjad, A., Chu, J., Anwar, M. A., & Asmi, F. (2020). Between green and resilience: Contemplating the effects of extreme weather events on firms’ green innovations. Journal of Cleaner Production, 265, Article 121930. https://doi.org/10.1016/j.jclepro.2020.121930
• Shiu, J. Y., Dawson, J. A., & Lane, C. W. (2011). Segmenting the market for food safety: A study of UK consumers. Appetite, 57(1), 146–155. https://doi.org/10.1016/j.appet.2011.01.005
• Tung, V. W. S., Ritchie, J. R. B., & Wong, I. A. (2017). The role of identity in sustainable tourism consumption. Tourism Management, 58, 258–266. https://doi.org/10.1016/j.tourman.2016.09.014
• Zhang, H., Xu, F., & Leung, H. H. (2014). An empirical study of commuters’ intention to use public transportation: Integrating the theory of planned behavior and habit. Transportation Research Part D: Transport and Environment, 32, 102–112. https://doi.org/10.1016/j.trd.2014.05.015

Items of the Scale