Steering socially sustainable behaviour: how digital platforms can drive sustainable mobility

Road transport is vital to modern economies, enabling the movement of people and goods, but it also accounts for 1.19 million deaths annually, ranking among the top global causes of mortality. The World Health Organization (2023) reports that 92% of road traffic deaths occur in low- and middle-income countries, revealing a disproportionate burden despite lower vehicle ownership.

Traditional enforcement methods like fines and legal restrictions are often ineffective, as they are context-dependent, difficult to monitor and can provoke defensiveness (White et al., 2019). Although road safety is central to social sustainability (SS) (Vallance et al., 2011), enforcement models frequently rarely address the behavioural and psychological factors influencing mobility choices. This paper conceptualises SS as cultivating inclusive, equitable societies that enable intergenerational thriving. It focuses on human rights, social justice, safety and well-being through fair resource access and participatory governance. Beyond reducing inequality, it promotes cultural diversity, community resilience and adaptability, integrating collective agency, policy and innovation for systemic, lasting societal transformation (Vallance et al., 2011). Achieving this vision requires a shift from top-down regulation to user-centred engagement strategies that embed sustainability into everyday actions. SS, as focused on in this paper, is also a core priority under the Sustainable Development Goals (SDGs) (United Nations, 2009), centring on SDG 3 (good health and well-being), SDG 10 (reduced inequalities), SDG 11 (sustainable cities and communities) and SDG 16 (peaceful and inclusive societies).

Digital platforms (DPs) increasingly act as socio-technical actors capable of influencing behaviour at scale. By coordinating users, enabling data-driven interactions and supporting value co-creation, they are well-suited to address distributed challenges such as sustainable mobility (Kolk and Ciulli, 2020). As platforms increasingly foster value co-creation across user networks (Chen et al., 2022), their role in sustainability transitions is gaining scholarly attention (Kolk and Ciulli, 2020).

At this juncture, it is also important to recognise the growing body of scholarship cautioning against their potential harms. Research shows that DPs may reproduce social inequalities (Yan et al., 2021), facilitate surveillance and data misuse and amplify misinformation (Allcott and Gentzkow, 2017). Scholars critique that DPs´ extensive data extraction and opaque algorithmic systems may marginalise certain users and shape behaviour in ways that limit autonomy (van Dijck et al., 2018; Zuboff, 2019). Acknowledging these risks situates DPs within a broader socio-technical context and urges the need for understanding the positive role DPs play in shaping user-level SS behaviours (Kolk and Ciulli, 2020).

Given the behavioural complexity of road safety and sustainable mobility, this research draws on established psychological frameworks, the Theory of Planned Behaviour (TPB) (Ajzen, 1991), the Technological Acceptance Model (TAM) (Davis, 1989) and the Equity Theory (Adams, 1965) to build and test a behavioural model for SS, in the context of sustainable mobility. These theoretical lenses enable a nuanced understanding of how intention, perceived fairness and usability interact within the DP environment. Applying these insights to the DP landscape, the study investigates how user engagement and user-centred strategies can drive meaningful impact, positioning DPs as catalysts for SS initiatives in the context of sustainable mobility.

The study positions sustainable mobility as an integral part of SS, grounded in principles of equity, safety, accessibility and collective well-being. It focuses on the case of SmartTraffic (a Pseudonym for confidentiality), a DP designed to encourage socially responsible transport behaviours through incentives, rewards and active user engagement. By targeting habits such as traffic rule adherence and safer driving practices, the platform contributes to creating more equitable and socially sustainable mobility systems.

Although DPs have been widely studied, most research focuses on economic or environmental outcomes, leaving the behavioural foundations of SS underexamined. Existing work rarely integrates intention-based models with fairness perceptions, nor does it explore how DPs influence socially sustainable mobility. This study addresses these gaps by offering an integrated behavioural framework that explains how perceptions, usability and fairness shape socially sustainable mobility behaviour, positioning DPs as intermediaries that can advance equity and collective well-being.

The research contributes to three key areas. First, it advances sustainability literature by integrating behavioural insights into the study of DP as systemic enablers of SS. Second, it builds and tests a behavioural model for SS by demonstrating how platform-based incentive structures can shape user decision-making, thus bridging the divide between behavioural psychology and DPs for SS. Third, it offers actionable implications for both policymakers and platform designers, showing how user-centred strategies and fairness-oriented mechanisms can encourage behavioural shifts, using sustainable mobility as a lens for broader SS challenges.

The remainder of the paper is structured as follows. Section 2 reviews the relevant literature on SS, DPs and user behaviour. Section 3 introduces the conceptual model and presents the hypotheses. Section 4 outlines the research methodology, including data collection and analysis techniques. Section 5 presents the findings, and Section 6 offers a critical discussion of their theoretical and practical implications. Section 7 concludes with a summary of key contributions, limitations and avenues for future research.

SS (World Commission on Environment and Development, 1987) centres human well-being, equity and community resilience, and remains underexplored compared to environmental and economic sustainability (Vallance et al., 2011). Its conceptual ambiguity and measurement challenges have contributed to its marginalisation in sustainability research (Colantonio, 2009). Growing social inequalities and fragile labour conditions indicate the urgency of integrating SS into mainstream sustainability debates (Missimer et al., 2017). It is ingrained in community dynamics, hence requiring systemic interventions rather than isolated initiatives. However, dispersed regulations and short-term business priorities continue to hinder progress (Weingaertner and Moberg, 2014).

In practice, organisations and governments often prioritise measurable environmental targets, overlooking the complexity of social issues. Fragmented policies and weak accountability mechanisms further undermine the progress of SS initiatives (Weingaertner and Moberg, 2014). Recent scholarship reframes SS as a systemic issue requiring collaborative solutions (Ballet et al., 2020). This broader framing is especially relevant in sectors like mobility, where issues of accessibility and safety intersect with people's everyday lives.

Sustainable mobility refers to transport systems that promote equitable access while advancing societal and economic development in balance with human and environmental well-being (Berger et al., 2014; Holden et al., 2020). Current mobility systems contribute to environmental degradation (Holden et al., 2020) and inequalities in access to essential services (World Health Organization, 2023). Travel behaviour has thus emerged as a critical site of intervention, reflecting broader systemic challenges (Berger et al., 2014). Recent scholarship calls for greater attention to the role of actors, particularly drivers, as agents of behavioural change within these sustainability transitions, especially in the context of mobility (Holden et al., 2020).

Sustainable mobility supports public health and urban liveability by reducing air pollution, traffic-related fatalities and sedentary lifestyles (Holden et al., 2020). There is a strong interconnection between SS and sustainable mobility, where both concepts influence equity, social inclusion, public health and community resilience. A socially sustainable mobility system ensures that all individuals, regardless of income, ability, or geographic location, have fair and reliable access to transportation, enabling them to participate in economic, social and cultural activities (Berger et al., 2014). Addressing disparities related to unsustainable mobility through accessible, affordable and safe transport solutions is essential for fostering social cohesion and well-being (Holden et al., 2020), both critical SS concepts. We therefore treat sustainable mobility as a core expression of SS.

DPs have been studied through various lenses due to their cross-disciplinary nature, spanning B2B contexts, governance, design mechanisms (Chen et al., 2022), platform competition (Rietveld and Schilling, 2021), network effects (McIntyre and Srinivasan, 2017) and for their development and characterisation (Bonina et al., 2021). Drawing from the prior literature, we define DPs as technology-enabled entities that facilitate interactions among multiple user groups, enabling transactions, information exchange and value co-creation across diverse sectors (McIntyre and Srinivasan, 2017; Stallkamp and Schotter, 2021). Although the themes researched in the past remain crucial to understanding the working DPs and their future, the role of DPs in promoting, facilitating and integrating sustainability is yet to be seen.

The concept of SS is either explicitly or implicitly referenced in the DP literature, where platforms serve as tools for mobilizing collective action (Chamakiotis et al., 2021) and facilitating peer-to-peer collaboration and user-generated knowledge. For instance, platforms like MedicineAfrica demonstrate how DPs can enhance equitable access to resources by dismantling institutional barriers in healthcare. Similarly, platforms leveraging electronic word-of-mouth (e-WOM) (Suk Choi et al., 2019) illustrate how sustainability narratives are no longer dictated solely by corporations or institutions, users actively shape discussions, influence public perception and drive organizations toward more ethical practices.

DPs are transforming how businesses and societies operate, but their role in sustainability is a double-edged sword, like they reinforce social inequalities (Allcott and Gentzkow, 2017; Yan et al., 2021). The governance challenges associated with DPs, particularly issues of platform accountability and value distribution, remain unresolved, making their role in sustainability transitions highly contested (Hellemans et al., 2022).

Beyond ethical concerns, DPs also shape user beliefs and behaviours, amplifying polarisation and misinformation, particularly in political contexts (Yan et al., 2021). With their vast reach and influence, DPs have the power to reinforce social divides or serve as tools for positive societal change, making their governance and ethical oversight more critical than ever. The paradoxical role of DPs in the literature likely stems from their inherent (Hellemans et al., 2022). While they are often celebrated for their ability to connect users and facilitate innovation, their negative impacts cannot be overlooked.

Despite this, DPs are not going anywhere. The question is no longer whether DPs will influence sustainability efforts, but how they will do so, and whether their impact will be positive or negative (Hellemans et al., 2022). Achieving real progress requires rethinking user engagement models, ensuring fair value distribution (Hellemans et al., 2022) and aligning user values (Khalek and Chakraborty, 2023) with long-term sustainability goals rather than short-term profitability.

Understanding user behaviour in DPs is essential for advancing SS, particularly in sustainable mobility. A user-level approach helps uncover how individuals´ perceptions, attitudes and decision-making processes influence platform engagement. Nudges guide consumption and sustainability decisions in digital environments (Thaler and Sunstein, 2008; Hettler et al., 2024; Lehner et al., 2016). Gamification extends these decision-making effects by embedding motivational elements such as points, rewards and challenges into platform experiences, helping habit formation and sustainable consumption (Hamari et al., 2014; Pegan et al., 2025). This highlights the relevance of gamified design for sustainability mobility platforms like SmartTraffic, where rewards can encourage responsible driving.

Research on DPs spans domains such as collaborative consumption, sharing economy and environmental sustainability (Khalek and Chakraborty, 2023; Sutherland and Jarrahi, 2018), yet much of the work focuses on economic or environmental outcomes, leaving the behavioural dynamics underlying SS underexplored. While systemic change is often framed through institutional or policy lenses (Ballet et al., 2020), DPs offer a unique micro-level lens, one rooted in the everyday actions of users.

To examine such behaviours, researchers rely on established frameworks in the behavioural psychology literature that integrate attitudes, values and motivation. The TPB (Ajzen, 1991) remains a dominant framework to understand intention formation and has shown continued empirical relevance as demonstrated by a recent bibliometric study (Naskar et al., 2025). Extensions of TPB are seen with other value-based models like Schwartz's Value Theory and the Value-Belief-Norm (VBN) theory to explain pro-sustainability behaviours (Ahmad et al., 2020; Stern et al., 1999).

The TAM model (Davis, 1989) offers a complementary lens by focusing on perceived usefulness and ease of use for technology adoption. It is widely applied in mobility and sustainability contexts, explaining the adoption of technology for environmental consciousness and sustainable consumer behaviours (Kordrostami et al., 2025; Nakandala et al., 2024). However, its application at the intersection of DPs, SS and behaviour remains limited.

The equity theory (Adams, 1965) explores the effort required in behavioural decision-making. Fairness has been shown to influence sustainable actions across domains, including green innovation in supply chains (Zhou et al., 2021), value-based judgments in sustainable innovation (Muñoz, 2025) and sustainable consumption, where perceived equity increases willingness to act responsibly (Carvalho et al., 2017).

Drawing mainly on the TPB (Ajzen, 1991), TAM (Davis, 1989) and Equity Theory (Adams, 1965), this study develops a behavioural model that explain SS behaviour on DPs in the sustainable mobility context. TPB offers a structured approach to understanding the formation of intention through attitudes and norms. TAM provides insight into how usability and technological ease influence adoption. Equity Theory adds the dimension of fairness, capturing how users assess whether their contributions are equitably matched with rewards. Bringing these perspectives together, this study views DPs as more than just technological entities, but as intermediaries that can be leveraged to promote SS behaviours in individuals, particularly within the context of sustainable mobility.

Attitude remains a foundational construct in behavioural research and is a key predictor of intention within TPB (Ajzen, 1991). In this study, we conceptualise attitude as a second-order reflective construct comprising both belief-based evaluations (“responsible driving is beneficial”) and affective evaluations (“I feel positive when I follow traffic rules”) toward perceived responsibility. Belief refers to the cognitive evaluation of one’s role in promoting SS, while affect captures the emotional weight of that responsibility, such as guilt, pride, or moral obligation.

This dual perspective aligns with prior research suggesting that attitudes are shaped by both rational assessment and emotional engagement (Bodur et al., 2000). In DPs like SmartTraffic, where behavioural outcomes (e.g. traffic compliance) are directly linked to SS goals, this framing is particularly relevant. Integrating belief and affect offers a comprehensive understanding of attitude formation and user engagement. Prior studies show that perceived responsibility, both in cognition and feeling, significantly influences pro-social intentions (Gifford and Nilsson, 2014). Accordingly, it is hypothesised that.

Social norms, especially injunctive norms, reflect individuals’ perceptions of which behaviours are socially approved, shaping moral obligations and reinforcing acceptable conduct (Schultz et al., 2007). Unlike descriptive norms, which stem from observed actions, injunctive norms are rooted in perceived social expectations, what people believe they ought to do to align with collective values. In sustainable mobility, such norms act as a moral guide, signalling that behaviours like traffic rule compliance or platform participation are socially endorsed.

When users perceive approval from relevant others, such as family, peers or institutions, their sense of social legitimacy and accountability increases. Research shows that social approval can significantly influence behaviour (Khalek and Chakraborty, 2023). In DPs, this effect can be amplified through visibility, feedback and institutional alignment. Thus, injunctive norms contribute to a normative environment that supports pro-social behaviour. Based on this, it is hypothesised that.

Perceived Ease of Use, central to the TAM (Davis, 1989), refers to the extent to which users believe a system is effortless to use. In DPs for sustainable mobility, ease of use is critical for lowering adoption barriers and fostering continued engagement. Research shows that intuitive, user-friendly platforms that require minimal cognitive effort positively shape user attitudes and intentions (Venkatesh and Davis, 2000). This is especially relevant for platforms like SmartTraffic, where streamlined interaction supports socially sustainable behaviours. Given that perceived complexity often hinders the uptake of digital solutions, it is hypothesised that:

Intention is a central construct in the TPB (Ajzen, 1991) and extended TAM models (Venkatesh and Davis, 2000). It reflects an individual's motivational readiness to perform a behaviour and links attitudinal, normative and control factors and actual usage. In the context of DPs like SmartTraffic, intention determines whether individuals actively engage with digital sustainability solutions and integrate them into their mobility choices. Accordingly, it is hypothesised that.

Effort fairness is introduced as a moderating variable in our behavioural model to explain variations in the link between intention and socially sustainable behaviour. Grounded in Equity Theory (Adams, 1965), it refers to users’ perception of balance between the effort invested (e.g. time, cognitive load) and the value received (e.g. rewards, ease of access Perceived fairness encourages consistent engagement, whereas disproportionate effort may lead to disengagement.

Drawing from service fairness literature (Ting, 2013), effort fairness incorporates both procedural and distributive fairness, emphasising both how intuitively a platform operates and whether participation feels worthwhile. This construct is especially relevant in DPs, where user trust and perceived reciprocity (Kim and Yoon, 2021) are key. When effort fairness is high, it strengthens user commitment and enhances the influence of other behavioural drivers. Accordingly, it is hypothesised that.

In this study, SS behaviour refers to individual actions that advance collective well-being, fairness and participatory social processes. While SS is a broad concept encompassing dimensions such as human rights, social cohesion, cultural diversity, safety and community resilience (Colantonio, 2009; Vallance et al., 2011), scholars consistently identify two foundational principles of SS: democratic participation, which gives individuals agency in shaping shared outcomes, and equity and justice, which promote fairness and inclusive access to opportunities (Ballet et al., 2020; Lyons et al., 2001). These principles are highly relevant in mobility systems where user behaviour directly influences community safety and equitable access. Accordingly, this study operationalises SS behaviour through these two dimensions and integrates them into the behavioural model to examine how individual platform engagement contributes to sustainable mobility (Vallance et al., 2011; Weingaertner and Moberg, 2014).

The conceptual model for this study (see Figure 1) illustrates the hypothesized relationships between social norms, perceived ease-of-use of the DP, attitudes toward SS, the intention to use DPs for SS and the SS behaviour. Figure 1 presents the proposed research model, including five hypotheses (H1–H5).

SmartTraffic (see Supplementary File), launched in June 2023, is India's first DP designed to extrinsically motivate safe driving through incentive-based mechanisms. As a pilot initiative, it exemplifies a public-private partnership aimed at addressing traffic regulation challenges while fostering a collective commitment to road safety.

Users register on the app and receive an RFID (Radio Frequency Identification) tag, which tracks compliance with SmartTraffic-enabled signals. Each correct stop earns redeemable points, which can be exchanged for rewards across partner brands. The platform also builds a digital driving record, potentially benefiting users through reduced insurance costs. SmartTraffic was chosen as the study's case because it uniquely advances SS by aligning behavioural incentives with public-sector safety goals and private-sector engagement.

Unlike traditional top-down sustainability interventions, which rely on taxation and penalties, SmartTraffic employs real-time incentives to directly engage users, making a behavioural analysis essential (Hamari et al., 2016). It provides a real-world example of a DP explicitly targeting SS by linking incentives with safety objectives. Because sustainability transitions depend on long-term behavioural shifts, it is crucial to examine whether users develop habitual pro-sustainability behaviours beyond immediate rewards (Kim and Yoon, 2021). This case offers empirical insights into how individual agency interacts with DPs, providing a novel theoretical contribution to the literature on SS, sustainable mobility and DPs.

An a priori power analysis with an α = 0.05, power level = 95% and a small effect size of Cohen's f² = 0.05 (Cohen, 2013) indicated that a total sample size of N = 402 was required to examine an interaction effect (df = 5) between variables of interest. As such, the included number of SmartTraffic users, n = 406, was appropriate to detect a small effect size using regression analysis with f² deviation fixed from zero.

This study was approved by the low-risk human research ethics committee of [retained for blind review] (Approval Number: 26,741). A time-lagged online survey with a 2-week interval was carried out in early 2024 via Qualtrics to SmartTraffic users. A total of 406 valid responses were obtained. The questionnaire was divided into two parts – Part A (t = baseline), including demographic and predictor variable items, moderator and criterion questions (51 questions). Part B was administered at t+2 weeks, with the rest of the predictor questions (40 questions). Participants were asked to submit their email addresses to be contacted for Part B of the survey.

Both Part A and Part B of the survey consisted of additional questions on user preferences outside the scope of this study. The full survey took an average of 35 min to complete (see Supplementary file).

Before data collection, a pilot study was conducted with research scholars (n = 22), minor wording amendments were incorporated to improve clarity.

All constructs were measured using seven-point Likert scales, with higher scores indicating stronger agreement or endorsement.

SS behaviour was operationalised using two dimensions: democratic participation and empowerment (Lyons et al., 2001) and social equity and justice (Ballet et al., 2020). A sample item was “Using the platform, I am more involved in the collective goal to enhance road safety”.

Attitude was measured using belief and affect components toward perceived responsibility (Bodur et al., 2000). A sample item for attitude was “I believe that it is our responsibility to care for our society/community” (reverse scored).

Social norms were operationalised using seven injunctive norm items (Schultz et al., 2007). A sample item is: “Community would ________ of my socially sustainable behaviour through the use of digital platforms” (reverse scored), with higher scores indicating stronger perceived social approval.

Perceived ease of use was operationalised using four TAM-based items (Davis, 1989), such as: “I find it easy to get the digital platform to do what I want it to do”.

Intention was assessed using three items adapted from the TPB (Ajzen, 1991). A sample item is: “I expect to adopt socially sustainable practices through a digital platform”.

Effort fairness was assessed using four items from the service fairness scale (Ting, 2013). A sample item is: “The digital platform provides reasonable incentives”.

Participants reported biological sex, age, education, employment sector, household income (INR), duration of SmartTraffic use and whether they use other DPs supporting social issues.

We tested our measurement model with confirmatory factor analyses (CFA) in JASP v 0.18.3. The hypothesised, six-factor model demonstrated a fair fit to the data based on sample size adjusted (n = 406) equation-based CFI cut-off value of 0.90, χ²(480) = 1119.76, p < 0.001, CFI = 0.91, TLI = 0.90, RMSEA = 0.06, SRMR = 0.04. These indices meet established thresholds (CFI/TLI ≥0.90, RMSEA ≤0.06, SRMR ≤0.08), indicating that the model adequately captures the underlying factor structure in the sample (n = 406).

In comparison, the findings in Table 1 demonstrate a consistent decline in model fit with fewer factors, supporting the superiority of the hypothesised six-factor solution.

Absolute factor loadings ranged from 0.96 to 1.42, above the cutoff of 0.5 (Hair et al., 2010). Average Variance Extracted (AVE) ranged from 0.46 to 0.56, which were in the close acceptable range when interpreted with reliability coefficient Cronbach's Alpha (α) (Hair et al., 2010), revealing fair convergent validity.

To further establish the discriminant validity of the construct, the square root of the AVE measures was compared to the correlations among each pair of the construct (Fornell and Larcker, 1981; Podsakoff et al., 2012). The modest discriminant validity was partially acceptable (Hair et al., 2010), with square roots of AVE close to or greater than 0.5 which were greater than the Pearson correlation (r) for Social Norms and Perceived Ease of Use, but not for Attitude, Intention and Effort Fairness. However, Cronbach's alpha (α) was greater than 0.7 for all constructs, indicating that the latent constructs consistently measured what was intended (Hair et al., 2010).

To check for multicollinearity, the variance inflation factors (VIFs) of all constructs were tested, which were found to be below the threshold of 10 (Mason and Perreault, 1991). Attitude (3.84), Social Norms (1.92), Perceived Ease of Use (2.49), but not for Intention (36.18), Effort Fairness (29.51) and the interaction term Intention*Effort Fairness (116.46). Because these inflated values could destabilise coefficient estimates, we employed ridge regression as a regularisation technique. Ridge regression introduces an L2 penalty term (λ = 0.02) to shrink overly large coefficients and improve estimation stability in the presence of correlated predictors (Hoerl and Kennard, 1970). Importantly, ridge does not lower VIF values or remove multicollinearity; instead, it mitigates the adverse effects of predictor correlation by balancing the bias–variance trade-off. This trade-off is acceptable in our context, as the goal is to obtain robust estimates rather than to make unbiased predictions of individual coefficients. The penalty parameter (λ = 0.02) was selected after exploratory checks to ensure that the coefficients remained theoretically interpretable while improving estimation stability (Saleh and Shalabh, 2014).

To minimise common method bias, a time-lagged survey design was employed with a minimum two-week interval between data collection phases (Jordan and Troth, 2020). Several ex ante procedural remedies were also implemented: (1) participants were assured of anonymity and that there were no right or wrong answers (Podsakoff et al., 2012); (2) validated instruments and pilot testing ensured clarity; (3) items included both positively and negatively worded questions; and (4) both binary and Likert-scale formats were used (Chandler et al., 2015). Additionally, Harman's single-factor test indicated that a single factor accounted for only 41% of the total variance—below the 50% threshold (Harman, 1976). The poor fit of the single-factor model (χ² (495) = 1781.88, p < 0.001, CFI = 0.81, TLI = 0.80, RMSEA = 0.08, SRMR = 0.06) further suggested that common method bias was not a major concern (see Table 2).

A total of 429 commenced the survey; 23 were excluded due to incomplete responses or uniform answering, leaving a dataset of n = 406. Analysis was carried out using JASP v 0.18.3 and RStudio v 4.3.

Table 3 presents the demographic characteristics of the survey respondents from whom the data were collected.

Ridge regression results are shown in Table 4, several hypotheses were supported. Attitude significantly predicted (β = 0.21, 95% CI [0.13, 0.29], p < 0.001), supporting H1. Social norms were not significant (β = −0.03, 95% CI [–0.08, 0.01], p = 0.90), and H2 was not supported. Perceived ease of use significantly predicted intention (β = 0.07, 95% CI [–0.00, 0.15], p = 0.03), supporting H3. Intention significantly predicted SS behaviour (β = 0.11, 95% CI [0.02, 0.20], p = 0.01), supporting H4. Effort fairness was also a strong positive predictor of behaviour (β = 0.29, 95% CI [0.21, 0.38], p < 0.001). The interaction between intention and effort fairness was significant (β = 0.12, 95% CI [0.10, 0.15], p < 0.001), supporting H5.

The study provides key insights into how DPs that use incentives and rewards contribute to SS efforts. The findings suggest that attitudinal and usability-related perceptions strongly shape intention, while effort fairness enhances the translation of intention into sustainable action.

The significant effect of attitude on intention (H1) aligns with TPB (Ajzen, 1991), indicating that DPs can positively shape user perceptions through positive interactions and reward-based engagement (Hamari et al., 2016). This suggests that platforms can move beyond facilitating transactions to influencing how users relate to socially responsible behaviours.

The non-significant effect of social norms (H2) is notable given the expectations of strong normative influence in collectivist cultures (Hofstede, 2001). A likely explanation lies in India's traffic environment, where the weak enforcement and minimal penalties associated with traffic laws dilute normative expectations. Existing research suggests that lax enforcement and low perceived risk of apprehension lead drivers to prioritise their convenience over normative expectations (Dong et al., 2021). Consequently, in environments where traffic laws are rarely enforced, social norms lose their potency, prompting drivers to dissociate their driving behaviour from their social identities or community expectations. Moreover, cultural theory argues that collectivism alone does not guarantee normative influence, especially when individual incentives or situational cues dominate behaviour (Oyserman et al., 2002; Triandis, 2005). SmartTraffic´s individualised incentives and reward structures may therefore shift attention from social approval to self-focused engagement.

Perceived ease of use (H3) emerged as a significant predictor, consistent with TAM (Davis, 1989). In DPs for SS, simplicity functions as a behavioural enabler, reducing friction makes pro-social engagement feel less effortful and increases the likelihood of repeated use (White et al., 2019). By lowering the cognitive and procedural barriers, ease of use may allow other behavioural drivers to exert greater influence.

Effort fairness (H4) provides one of the most compelling insights. Users were more likely to participate when they perceived a reasonable balance between their effort and the rewards offered. This aligns with Equity Theory (Adams, 1965) and work on technology fairness (Kim and Yoon, 2021; Ting, 2013), showing that fairness is a functional part of platform engagement. When users sense an imbalance, high effort and low reward, disengagement becomes more likely; when effort and reward align, intention increases. In contexts where institutional systems often fail to offer consistent enforcement or recognition, platforms can step in and fill that void through fairness-based design.

Finally, the significant relationship between intention and SS behaviour (H5) reinforces the idea that DPs can meaningfully contribute to SS goals. While much of the DP literature on sustainability focuses on environmental outcomes (Khalek and Chakraborty, 2023), this study highlights the importance of the social dimension, with its principles like empowerment, social equity, justice, the well-being of humans and democratic participation, in mobility systems. Through platforms like SmartTraffic, they are not just making safer or more efficient choices; they are participating in a system that bridges the intention-behaviour nexus towards sustainable mobility.

This study examined how incentives embedded in a DP can shape SS behaviour in the context of traffic regulation. By developing and validating a behavioural model, it offers insights into how platform design features influence sustainable mobility outcomes.

The research extends behavioural frameworks such as the TPB (Ajzen, 1991), TAM (Davis, 1989) and Equity Theory (Adams, 1965), into the SS, domain, demonstrating their relevance for understanding mobility-related behaviour on DPs. thereby adding new value and relevance to these traditional models. To our knowledge, this integration has not been previously addressed. We call on the academic community to prioritise SS as a core component of the broader sustainability agenda, recognising that sustainable development must be approached holistically (Ballet et al., 2020; Colantonio, 2009). By conceptualizing sustainable mobility as a subset of SS, due to its links to public safety, well-being and equitable access, this research offers a novel lens through which to view everyday mobility challenges (Ballet et al., 2020; Berger et al., 2014; Holden et al., 2020).

More broadly, this study extends platform research by showing that DPs are not only economic or efficiency-driven systems but socio-technical actors capable of shaping collective behaviour (Chamakiotis et al., 2021; Kolk and Ciulli, 2020). Our findings demonstrate that thoughtfully designed incentives can make sustainable actions feel meaningful, fair and socially reinforced, shifting engagement from compliance or consumption toward participatory and transformative behaviours (Toşa et al., 2024).

In doing so, this work responds to calls to understand users not merely as consumers or data points but as active contributors to socially sustainable futures. DPs signal values and shape what behaviours users perceive as meaningful; this requires intentionality in how sustainable behaviours are presented, modelled and rewarded (Hellemans et al., 2022). Our study introduces a novel intersection between platform design, SS and mobility behaviour, offering a foundation for further empirical and theoretical exploration.

This study offers several implications for platform designers, policymakers and practitioners working at the intersection of DPs and sustainability. The strong effect of attitude, shaped by belief in personal responsibility and emotional engagement, is a key driver of intention. This demands a need to frame sustainable behaviours such as responsible driving as meaningful social contributions rather than mere rule compliance. Incentive structures should therefore balance external rewards with users' internal beliefs, creating value-driven and emotionally resonant engagement. airness is equally critical: users must perceive that their time and effort are proportionately rewarded, as fairness-based design fosters trust, accountability and continued participation.

This highlights the need for platforms to move beyond transactional engagement and create value-driven, emotionally resonant experiences. Sustainable behaviours such as responsible driving should be framed not merely as compliance but as meaningful social contributions. Platform owners must build incentive structures that balance external rewards with the internal beliefs of users, acknowledging their actions as socially relevant. Evolving behavioural targets and public recognition of contributions, when tied to authentic societal value, can help position these behaviours within a broader collective effort. Additionally, effort fairness is essential; users must perceive that their investment of time and energy is equitably rewarded. When fairness is embedded into platform design, it fosters trust, accountability and continued engagement.

Equally, the strong influence of perceived ease of use emphasises that intuitive, user-friendly design is a behavioural enabler. When users can engage with minimal friction, the likelihood of sustained participation increases. DPs, therefore, should be viewed not just as service providers but as behavioural infrastructures with the potential to complement or substitute weak formal systems. In settings where institutional enforcement is limited, platforms can offer decentralised mechanisms for promoting SS. Drawing from the learnings of SmartTraffic, Policymakers and urban mobility planners should collaborate with platform developers to integrate behavioural insights into transport systems, embedding behavioural nudges and positive reinforcements into everyday mobility practices. Ultimately, choices signal what behaviours are valued. When thoughtfully implemented, platforms can shape both individual action and broader cultural norms, supporting long-term transitions toward socially sustainable systems.

More broadly, this study extends practical implications for the DP domain. Platforms are often designed and evaluated through economic or efficiency logics like scaling, optimisation and competition, yet our findings show that they also operate as socio-technical actors capable of catalysing collective behavioural shifts. Because DPs signal values and influence what users perceive as meaningful, sustainable behaviours must be intentionally presented, modelled and rewarded through design choices.

This study has several limitations that offer opportunities for future research. First, the findings are based on a single platform within a specific mobility context, limiting generalisability. Behavioural responses to incentives and fairness may vary across institutional, cultural and infrastructural settings; comparative studies across diverse DPs and governance environments would strengthen external validity. Second, although the time-lagged design improves causal inference, it cannot capture how habits evolve as platform features change. Longitudinal designs are needed to examine how sustainable behaviours are sustained or replaced over time.

The non-significant effect of social norms may reflect the distal framing of measurement items rather than a true absence of normative influence. Proximal, context-specific measures typically yield stronger predictive validity (Armitage and Conner, 1999); future studies should refine measurement strategies accordingly. Additional psychological perspectives, such as Self-Determination Theory (Deci and Ryan, 2004), or the Value-Belief-Norm framework (Stern et al., 1999), could further illuminate how intrinsic motivations and moral values shape long-term engagement.

Although the sample is skewed toward young adults, this reflects SmartTraffic's early adopters and national patterns of mobile Internet use in India (IAMAI and Kantar, 2023). Because we aimed to examine behaviours within this high-usage segment, the demographic skew does not compromise internal validity, though future studies should test the model with a more diverse user base.

In conclusion, this study shows that DPs can encourage socially sustainable mobility behaviours by drawing on users' attitudes, fairness perceptions and ease of use. By focusing on the social pillar of sustainability, our findings connect directly to global priorities such as SDG 3, SDG 10, SDG 11 and SDG 16. As platforms become more embedded in everyday civic life, future research should explore how these behavioural insights apply in marginalised or resource-limited settings and how platforms can be shaped in partnership with the communities they aim to serve.

The author acknowledges the guidance and support of colleagues at LUT University and RMIT University. The author also thanks the research participants from SmartTraffic and the Finnish Foundation for Economic Education, which made the data collection possible. Appreciation is further extended to the reviewers for their valuable insights, which helped strengthen the manuscript.

The supplementary material for this article can be found online.