Trust but verify: a Verification-as-a-Service framework for sustainable infrastructure governance—An integrative conceptual review

1 Introduction

The robust, reliable backbone for modern urban society increasingly depends on the continuous development, maintenance, and upgrading of physical infrastructure across mission-critical sectors such as public works, municipal utilities, telecommunications, and urban construction (Carpenter and Poon, 2023; Kifokeris and Koch, 2020). As these sectors scale to meet escalating global demands and Environmental, Social, and Governance (ESG) targets, project execution relies heavily on an extensive, distributed network of third-party contractors and subcontractors whose collective effort underpins complex infrastructure programs across multiple sectors (Zhang et al., 2022). However, while this contractual decentralization provides essential specialized skills and scalable labor (Dakhli et al., 2019), it simultaneously creates a pronounced visibility gap between municipal project owners and field execution. Project owners and managers often struggle to monitor work performed far from the point of execution, resulting in limited, hard-to-verify evidence that field-based work was completed at the correct location, at the intended time, and to the required specifications (Çelik et al., 2021; Scott et al., 2021; Singh and Kumar, 2021; Soto et al., 2022).

Historically, decentralized oversight has relied on administrative trust reinforced through periodic inspections and manual documentation (Salin and Lundgren, 2023). Organizations have commonly assumed that contracted work is performed to specification, supplementing these assumptions with reactive, physical checks primarily when issues become apparent (Halder et al., 2024). Rooted in Principal-Agent Theory and Information Asymmetry (Ivić and Cerić, 2023), this structural gap creates a “trust deficit,” where information asymmetry between principal project owners and agent contractors creates perverse incentives for opportunistic behavior and costly agency costs. However, as projects become more complex and geographically dispersed, this trust-based paradigm introduces systemic vulnerabilities (Ali et al., 2022). Inadequate, non-standardized verification fosters costly rework, unnecessary site visits that inflate municipal Scope 3 emissions, and payment delays, while missing, inconsistent, or easily manipulated documentation exacerbates vulnerabilities to fraud and misrepresentation (Fix, 2008; Soto et al., 2022; Stone, 2013). The cumulative effect of these failures inflates project costs, erodes trust between public and private project stakeholders, and elevates compliance risk across the project lifecycle (Abdelghany, 2024; Singh and Kumar, 2021). Despite the accelerating breadth of digital transformation across infrastructure sectors, quality-control practices have remained comparatively static, leaving a persistent methodological gap between modern project complexity and legacy verification tools.

To address these challenges, recent research and practice trends converge on the need to close this execution gap using verifiable, integrity-secured records. Blockchain and distributed ledger technologies (DLT) are increasingly proposed as enablers of transparent, accountable workflows that trace activities, materials, and payments from ordering through handover (Abdelghany, 2024; Barenji and Montreuil, 2022; Dakhli et al., 2019). Frameworks that integrate these technologies with Building Information Modeling (BIM), digital twins, and smart contracts offer the potential to automate verification, link payments to milestones, and provide immutable records without sole reliance on trusted middlemen (Çelik et al., 2021; Scott et al., 2021; Zhang et al., 2022). Crucially, however, DLT and BIM alone do not resolve the physical-to-digital validation bottleneck, commonly known as the “Oracle Problem,” wherein immutability guarantees only data record stability, not real-world truth. Without hardware-level cryptographic signatures and anti-spoofing multi-factor geofencing to prevent geolocation forgery at the point of capture, digitized ledgers risk immutably recording fraudulent or flawed field data. Furthermore, Verification-as-a-Service (VaaS) must be conceptualized not as a replacement for foundational tools like BIM or blockchain, but as an overarching, high-level governance layer that orchestrates real-time evidence validation across disparate digital assets. Navigating these practical hurdles also requires addressing urban spatial data governance, field-worker privacy considerations in public spaces by balancing audit integrity with GDPR/CCPA compliance through event-triggered data capture rather than invasive continuous worker tracking, cross-organizational interoperability, and the risk of over-relying on automated attestations without robust field verification (Caldarelli, 2020; Msawil et al., 2022; Stouffer et al., 2022). These limitations underscore the critical need for an operational framework that integrates digital provenance with field-level evidence capture.

Against this backdrop, this integrative conceptual review advances a VaaS framework tailored to operationalize verifiable, field-based oversight at scale for sustainable urban infrastructure governance. Rather than employing a restrictive systematic protocol like PRISMA, which is designed for homogeneous empirical trial aggregation, an integrative review methodology was deliberately selected to synthesize heterogeneous, cross-disciplinary literature across computer science, urban planning, and construction management. To resolve the persistent “trust deficit” in decentralized operations, we propose a fundamental shift in quality control methodology. We define the trust deficit as the inability of project stakeholders to objectively verify that contracted work has been completed according to agreed specifications despite formal contractual relationships. To avoid over-generalization, we explicitly establish the boundary conditions of VaaS: while highly effective for objective, quantifiable, and location-bound physical tasks, VaaS is explicitly unsuitable for subjective aesthetic evaluations or highly unstandardized design decisions requiring nuanced human judgment. By synthesizing design principles and architectural considerations from the broader literature on cybersecurity, distributed ledgers, smart city governance, and construction traceability, we outline a pragmatic pathway for implementing VaaS. Rather than presenting an isolated empirical case study, this integrative conceptual review synthesizes multidisciplinary literature to establish a category-defining architecture and an empirically testable theoretical foundation for a proactive, digitized, and remote verification process.

A robust VaaS regime delivers real-time, integrity-secured records of site activities by utilizing standardized, geotagged, and automated metadata verification. Furthermore, it integrates with BIM and digital twins while leveraging programmable workflows to enforce auditability, support municipal decarbonization goals by reducing physical inspector dispatches (“truck rolls”), and streamline verification and payment cycles (Gould et al., 2016; Stone, 2013). In contextualizing these operational gains, reported outcomes such as 50–70% inspection cost reductions and 30–60% accelerated payment cycles are positioned as external industry benchmarks and empirical reference points rather than deterministic outputs generated by this conceptual model (Kim et al., 2025; Lin et al., 2022). We propose modular, interoperable components for VaaS that prioritize decision-grade transparency, privacy-preserving robust data governance, and incremental adoption across the infrastructure ecosystem. In doing so, the framework positions verification not as a downstream administrative task but as an integrated, data-driven control embedded throughout the project lifecycle. To ensure scientific rigor and empirical falsifiability, this framework formalizes a Theory of Change paired with three explicit, testable hypotheses regarding audit velocity, dispute mitigation, and compliance costs for future empirical validation. Consequently, this framework not only promises to mitigate the costly bottlenecks of legacy inspection methods, but also provides a structured theoretical foundation and explicit hypotheses for future empirical validation, paving the way for a more transparent, efficient, and environmentally sustainable future for smart city and global infrastructure development.

2 Methodology: integrative conceptual review strategy

This integrative conceptual review employs the framework established by Torraco (2016) to develop the proposed Verification-as-a-Service (VaaS) framework for sustainable urban infrastructural governance. An integrative review is particularly appropriate as it enables the synthesis of diverse methodologies, empirical studies, and theoretical perspectives to formulate novel frameworks and reframe systemic challenges across complex, multi-stakeholder ecosystems (Torraco, 2016). Unlike standardized systematic review protocols (e.g., PRISMA), which primarily focus on aggregating homogeneous empirical trials or conducting meta-analyses within narrow domain boundaries, an integrative conceptual review provides the necessary qualitative synthesis logic to connect disparate, highly heterogeneous literature across civil engineering, cybersecurity, urban planning, and public administration. Our methodology was designed to systematically source, filter, and analyze multidisciplinary literature spanning construction traceability, DLT, cybersecurity, smart city governance, environmental sustainability, and operations management.

To execute this review, the literature search was conducted across primary academic databases, including Scopus, Web of Science, IEEE Xplore, and Google Scholar, to ensure comprehensive coverage across engineering, urban planning, environmental management, and business management disciplines. Search strings systematically combined keywords across three core thematic pillars: (1) decentralized and urban infrastructure operations (e.g., “smart city” AND “quality control,” “public works” AND “contractor oversight”), (2) verification, compliance, and governance challenges (e.g., “trust deficit” AND “field inspection”, “ESG compliance” AND “infrastructure verification”), and (3) digital technologies supporting traceability and verification (e.g., “remote verification” AND “sustainable infrastructure,” “blockchain” AND “digital twin” AND “field operations”). This systematic initial query generated a total yield of approximately 1,420 candidate records across all indexed databases.

To ensure academic rigor and relevance during this search process, explicit inclusion and exclusion and a multi-stage screening workflow were established. Following the removal of 531 duplicate records, 889 unique titles and abstracts were screened, reducing the pool to 232 studies selected for full-text review. Included works were restricted to peer-reviewed journal articles, high-impact conference proceedings, and authoritative industry reports published between 2010 and 2025. This timeframe was selected to capture recent, rapid technological evolution in digital traceability, spatial computing, urban digital twins, and decentralized governance. Studies were excluded if they did not address physical field-based operations, or if they discussed digital ledgers and quality control strictly within the context of software development or financial technologies (FinTech) rather than physical infrastructure and municipal asset management. Furthermore, candidate studies were subjected to an explicit quality and suitability assessment based on three core criteria: (a) methodological rigor and theoretical clarity, (b) direct relevance to physical infrastructure field operations or digital provenance, and (c) publication in peer-reviewed venues or authoritative institutional outlets. Applying these quality filters yielded a final synthesized sample of 116 core reference studies.

Following the initial screening based on these criteria, the selected literature underwent a qualitative thematic analysis to identify recurring operational bottlenecks and proposed technological solutions. Data synthesis was structured around a rigorous three-phase coding process consisting of open, axial, and selective coding. Initial open coding extracted raw concepts, operational bottlenecks, and technology enablers from the literature. Axial coding then clustered these concepts into higher-order theoretical categories, such as structural information asymmetry, evidence manipulation risks, and physical inspection inefficiencies, which directly informed the operationalization of the “trust deficit” construct. Finally, selective coding integrated these validated themes into the architectural components of the proposed VaaS model, linking cybersecurity protocols, spatial metadata tracking, and decarbonization mechanisms. Emerging themes were then compared across disciplines to identify complementary governance mechanisms, decarbonization pathways, and recurring design principles. These synthesized themes were organized into the conceptual components of the proposed framework. Subsequently, we extracted and synthesized core design principles from cybersecurity (e.g., data immutability, zero-trust architectures, privacy-preserving metadata masking), construction technology (e.g., geotagging, BIM integration), and urban sustainability (e.g., emission reduction via optimized remote inspection dispatches). This cross-disciplinary synthesis guided the architectural development of the five-phase VaaS lifecycle, the ESG-aligned Value Proposition Pyramid, and the systemic Theory of Change. By triangulating these multidisciplinary insights, the methodology ensures that the proposed VaaS framework is grounded in established empirical research while offering a novel, structured approach to remote field governance. Consistent with the objectives of an integrative review (Torraco, 2016), the purpose of this methodology was not to evaluate the effectiveness of individual technologies, but rather to synthesize complementary concepts into a coherent operational governance framework capable of advancing sustainable urban development.

3 The problem landscape: conceptualizing the “trust deficit” in field work

This section presents a theoretical synthesis based on an integrative review of existing literature rather than original empirical field findings.

3.1 Verification challenges, theoretical foundations, and documentation breakdowns

Decentralized municipal and utility field operations increasingly depend on accurate, verifiable evidence to confirm that work was completed to standard, at the intended location, and on schedule within complex urban environments (Domínguez Monferrer et al., 2022). However, as smart city initiatives and public works projects scale and teams disperse across wide metropolitan areas, municipal agency leaders and project managers struggle to reliably capture these signals (Hu et al., 2021; Hussain and Hinrichsen, 2019). Rooted in classical economic and organizational scholarship, this operational friction can be conceptualized through Principal-Agent Theory, Information Asymmetry Theory, and Trust Theory (Eisenhardt, 1989; Ivić and Cerić, 2023; Jensen and Meckling, 1976). In infrastructure governance, municipal project owners (principals) delegate physical execution to specialized third-party contractors and subcontractors (agents). Because field work occurs far from central offices, agents possess superior real-time information regarding actual site conditions, work quality, and material usage, creating severe information asymmetry (Ceric, 2014; Xiang et al., 2012). This information imbalance creates moral hazard and adverse selection incentives, enabling opportunistic behavior such as cutting corners or submitting inflated claims (Arrow, 1985).

In the absence of robust, real-time oversight, the literature on distributed labor indicates that project managers are often forced to rely on a “blind trust” model (Chen et al., 2022), creating what this paper conceptualizes as the “trust deficit.” While Information Asymmetry describes the state of unequal knowledge and Principal-Agent Theory explains goal divergence, the “trust deficit” specifically operationalizes the downstream verifiability gap, the systematic inability of the principal to convert agent-asserted claims into decision-grade, audit-proof physical evidence without incurring prohibitive transaction costs (Ceric, 2014; Ivić and Cerić, 2023). Unlike classical relational or institutional trust, which relies on long-term reputation or periodic physical audits (Mayer et al., 1995; Zaheer et al., 1998), the trust deficit arises because modern project dispersion degrades relational oversight while legacy administrative controls fail to provide timely verification (Chen et al., 2022; Salin and Lundgren, 2023).

This reliance on informal or subjective assessments undermines real-time validation, thereby increasing the likelihood that errors, omissions, and substandard workmanship will go undetected until much later in the project lifecycle (Wang, 2020). Consequently, this lack of empirical verification at the point of action directly drives avoidable rework, material waste, and costly schedule slippage (Casati et al., 2008; Salcedo et al., 2019). These dynamics illustrate a structural mismatch between the spatial distribution of modern urban field work and the limited verification tools available to city supervisors, creating a persistent latency between the execution and detection of quality issues.

This verification gap is further compounded by deficiencies in evidentiary integrity in the built environment (de Oliveira Dantas et al., 2020; Kan et al., 2019). Prior construction-sector research has actively explored digital tools for remote inspection, including photo-based site monitoring, laser scanning, and computer-vision progress tracking (Samsami, 2024). However, these existing built-environment approaches predominantly focus on isolated point solutions, such as automated image classification or localized BIM updates, without establishing an end-to-end governance architecture that binds physical evidence capture directly to automated contractual and financial workflows (Çelik et al., 2021; Li and Kassem, 2021). Incremental to prior research, VaaS provides this missing overarching governance layer, transforming isolated digital capture tools into legally defensible, tamper-resistant evidence chains (Abdelghany, 2024).

Without standardized, technology-enforced reporting protocols, field documentation is frequently inconsistent, incomplete, or missing altogether (Kan et al., 2019). Furthermore, in the absence of stringent on-site oversight, field-submitted evidence records are particularly susceptible to manipulation, such as the submission of recycled or digitally altered photographs (Nirmala, 2024). When the evidence of completed work is highly subjective or susceptible to exploitation, it fosters an environment prone to contractual disputes (Zhao et al., 2016). Ultimately, these deadlocks deteriorate relationships between public asset owners and private contractors, fostering misaligned perceptions of progress and driving protracted negotiations (de Oliveira Dantas et al., 2020). The absence of a defensible evidence chain also limits the ability of municipalities to perform root-cause analyses or establish accountability, further entrenching systemic inefficiencies.

3.2 Operational, financial, and compliance consequences

The trust deficit produces operational, financial, environmental, and regulatory consequences that extend well beyond project execution (Dithebe et al., 2021; Rao et al., 2024). To compensate for subjective or missing data, organizations frequently deploy internal quality control personnel to perform manual site inspections. From an organizational efficiency and sustainability standpoint, these physical site visits, commonly referred to as “truck rolls,” consume substantial amounts of fossil fuel, labor hours, and administrative overhead, while directly inflating municipal Scope 3 greenhouse gas emissions (Shash and Habash, 2021; Thusini et al., 2025).

Beyond this immediate logistical and environmental waste, ambiguous or disputed evidence severely disrupts the financial ecosystem of a project (Dithebe et al., 2021; Keim, 2023). Invoices and payment cycles stall as they await manual reconciliation and verification, straining contractor cash flows and exacerbating friction between public owners and their decentralized workforces (de Oliveira Dantas et al., 2020; Hu et al., 2021). These cascading delays illustrate how verification failures propagate beyond operational inefficiency to directly influence financial liquidity, contract performance, urban carbon footprints, and workforce stability.

Furthermore, in highly regulated sectors such as telecommunications, municipal utilities, and public infrastructure, the burden of proof for completed work is intensified by strict compliance standards and emerging ESG disclosure mandates (Henriques et al., 2024). Regulatory and oversight bodies demand auditable, defensible records to demonstrate safety, environmental compliance, and adherence to specifications (Longo et al., 2021; Latorre et al., 2023). Fragmented and non-standardized paperwork fundamentally undermines chain-of-custody assurances and ESG reporting accuracy (Batista et al., 2023). Theoretically, this opacity leaves municipalities and enterprise asset owners highly vulnerable to failed audits, substantial financial penalties, and weakened legal standing should project records be contested (de Oliveira Dantas et al., 2020). As regulatory regimes increasingly emphasize digital traceability, carbon accounting, and accountability, legacy verification practices become progressively misaligned with compliance expectations, heightening institutional exposure.

3.3 The boundary conditions, the oracle problem, and VaaS conceptualization

To establish a rigorous theoretical foundation, the boundary conditions of VaaS must be explicitly defined (Torraco, 2016). VaaS is uniquely suited for objective, quantifiable, physical, and location-bound infrastructure tasks, such as verifying trenching depth, pipe installation, cable laying, asset tagging, and structural rebar placement, where completion can be empirically validated through spatial metadata and digital evidence (Gould et al., 2016; Samsami, 2024). Conversely, VaaS is explicitly unsuitable for subjective aesthetic evaluations, highly artistic masonry, complex design negotiations, or novel qualitative structural assessments that require nuanced human engineering judgment and contextual arbitration (Markman, 2006).

Furthermore, a fundamental distinction must be drawn between VaaS as a high-level governance layer and its underlying enabling technologies (Çelik et al., 2021; Jaskula and Papadonikolaki, 2021). DLT and blockchain provide immutable ledger storage; Smart Contracts execute automated programmatic rules; BIM offers spatial digital twin models; and mobile sensors capture raw field data (Abdelghany, 2024; Li and Kassem, 2021). VaaS does not replace these systems; rather, it operates as an overarching governance framework that orchestrates evidence validation, standardizes cross-organizational data schemas, and enforces verification protocols before data is written to ledgers or triggers smart contract payments (Stouffer et al., 2022).

Addressing this layer distinction highlights a key vulnerability in decentralized governance known as the “Oracle Problem” (Caldarelli, 2020). DLT and blockchain immutability guarantees only data record stability, meaning data cannot be altered once written, not real-world truth (Abdou et al., 2017). If a field worker uploads spoofed GPS coordinates, recycled photographs, or fraudulent measurements, a blockchain will merely record that fraudulent data immutably (Fargas and Petersen, 2017). To solve the Oracle Problem, VaaS incorporates multi-factor physical-to-digital validation protocols at the point of capture (Mustafa et al., 2025). This includes hardware-level cryptographic attestation (Trusted Execution Environments), anti-spoofing multi-factor geofencing (combining GPS, cell tower triangulation, and Wi-Fi SSID mapping) (Abdou et al., 2017; Fargas and Petersen, 2017), cryptographic time-stamping, and automated metadata integrity checks. By validating the authenticity of physical data before ledger entry, VaaS bridges the physical-digital divide and closes the Oracle vulnerability (Caldarelli, 2020; Mustafa et al., 2025).

Taken together, the dynamics of the trust deficit, documentation integrity challenges, ESG compliance mandates, and vehicle overhead create a compelling case for a formal VaaS framework (Hajipour et al., 2020; Shoker and Yactine, 2021). VaaS operationalizes cloud-based, automated verification workflows that can be invoked on demand to confirm field-reported outcomes, dramatically reducing the reliance on manual site visits and vehicle dispatches (de Oliveira Dantas et al., 2017, 2020). By providing real-time, integrity-secured logging, privacy-preserving spatial metadata, and unchallengeable audit trails, VaaS mitigates the need for subjective interpretation (Hu et al., 2021; Zhang et al., 2022). The literature confirms that embedding such standardized, technology-enabled reporting protocols significantly reduces post hoc rework, carbon intensity, and financial disruption (Kan et al., 2019). Conceptually, VaaS establishes the minimum conditions for trustworthy field oversight, standardized evidence capture, verifiable provenance, and automated validation, thereby defining the boundary at which decentralized urban operations can transition from assumption-based to evidence-based smart city governance.

Because persistent operational bottlenecks in field-based industries are largely symptoms of an outdated, manual quality control process, Figure 1 provides a comparative visualization between the traditional ‘Trust Deficit' workflow and the proposed VaaS framework. While the legacy model relies on assumed trust, manual site visits, and disjointed documentation which routinely produce costly rework, excess vehicle emissions, and delayed payments, the VaaS model replaces these vulnerabilities with a continuous, digitized evidence trail. This contrast highlights how shifting from physical inspections to structured digital evidence fundamentally streamlines project delivery models and advances urban decarbonization. It also illustrates the point at which verification becomes a proactive, data-driven control rather than a reactive administrative burden.

4 The Verification-as-a-Service framework

To operationalize the shift from reactive inspections to proactive verification across smart cities and public infrastructure networks, we propose the theoretical VaaS lifecycle framework. As illustrated in Figure 2, this conceptual framework organizes the quality control process into five distinct, sequential phases: Task Assignment and Standardization (Defined Expectations), Remote Work Documentation (Defensible Evidence), Quality Validation (Approval Workflow), Payment Readiness (Completion Plan), and Performance Tracking (Performance Insights). These stages range from initial task standardization to post-completion performance analytics and urban ESG impact evaluation (Muralidharan et al., 2022). By embedding defensible evidence and approval gateways at each step, the framework theorizes a system where trust is continuously validated through data rather than assumption (de Oliveira Dantas et al., 2017). Ultimately, this closes the operational loop with automated payment triggers and actionable insights, aligning with broader research on verifiable, contract-driven processes in distributed urban environments (Shoker and Yactine, 2021).

4.1 The five-phase VaaS lifecycle

The lifecycle begins with Phase 1: Task Assignment and Standardization (Defined Expectations). Conceptually, this phase lays the essential groundwork for the VaaS lifecycle before field personnel arrive on site. The core objective is to minimize ambiguity in traditional work orders by specifying precise task requirements, environmental compliance checklists, and enumerating the required visual evidence needed for completion (Sanderson et al., 2018). This proactive standardization functions as a theoretical early-stage quality control mechanism, reducing misunderstandings and operational deviations before execution begins (Li and Kassem, 2021). Furthermore, explicit evidence definitions serve as the foundation for subsequent remote validation, ESG reporting, and contract-level assurances (Jaskula and Papadonikolaki, 2021). From a governance perspective, by anchoring expectations in codified criteria, Phase 1 supports consistent measurement of deliverables and facilitates downstream automation when evidence is submitted for review (Castillo et al., 2026). This phase effectively transforms work orders into structured data schemas, enabling machine-readable verification and reducing interpretive variability across decentralized teams.

Following this preparation, Phase 2: Remote Work Documentation (Defensible Evidence). During this phase, field activities transition into structured, remote data capture. The framework shifts from informal communication to rigorous documentation of before, during, and after states, incorporating geotagged photos, high-resolution videos, and secure timestamps (Bamodu et al., 2013). Crucially, embedding GPS metadata directly from field devices creates a digital evidence trail while adhering to spatial data minimization standards in public spaces (George and Al-Ansari, 2023). This anchors evidence to the exact project location, thereby ensuring authenticity and contextual accuracy (Mustafa et al., 2025). This phase serves as the conceptual core for operationalizing data provenance and authenticated evidence reliability, allowing for remote validation without the need for physical site visits, while maintaining the verifiable traceability required for audit-defensible invoicing and decarbonization logging (Mavračić, 2025; de Oliveira Dantas et al., 2020). By converting field actions into standardized, verifiable digital evidence records, Phase 2 establishes the empirical foundation upon which all subsequent validation and automation depend.

Once data is captured, it flows into Phase 3: Quality Validation (Approval Workflow), which enables structured, defensible remote reviews of submitted field data. Project managers and quality assurance teams analyze location accuracy, technical compliance, and overall workmanship via a centralized digital dashboard (Becker et al., 2024). This remote validation model reduces the need for costly and time-consuming on-site visits, thereby accelerating inspection cycles and reducing overhead, and significantly curbing Scope 3 transport emissions caused by unnecessary physical inspector dispatches (“truck rolls”) (Fisher et al., 2021). The theoretical emphasis is placed on defensible evidence and traceable decision rationales, aiming to achieve consensus on acceptance criteria based on verifiable data rather than subjective assertions (Markman, 2006). Where applicable, complementary model compliance-checking approaches or urban digital twins can be leveraged to corroborate observed outcomes against initial contract specifications (de Oliveira Dantas et al., 2017). This phase formalizes decision-making logic, enabling organizations to transition from discretionary decision-making to standardized, evidence-driven acceptance workflows.

Upon successful validation, the system advances to Phase 4: Payment Readiness (Completion Plan), where the VaaS model bridges the agency gap between verified work outcomes and financial execution. Once a remote submission is validated and approved, the system establishes immediate payment readiness, automatically queuing the invoice or generating an audit-verified payment trigger (Rahman et al., 2020). This structured readiness tightens the link between verifiable proof of work and contractor compensation, significantly reducing invoice disputes and administrative burdens (Chandran et al., 2023). Additionally, it accelerates cash flow for field personnel by eliminating manual reconciliation bottlenecks (Li and Kassem, 2021). The payment readiness gate functions as a contract-level control, recording attestations and timestamps that support traceable financial transactions, consistent with blockchain-enabled payment architectures (Stavrou et al., 2025). By embedding readiness verification directly into the verification workflow, Phase 4 operationalizes a form of programmable compliance, ensuring that financial actions are formally authorized only when supported by validated field evidence.

Finally, Phase 5: Performance Tracking (Performance Insights) theorizes the transformation of operational evidence into strategic business intelligence and civic governance insights. By leveraging aggregate data collected from the documentation and validation cycles, organizations can generate objective contractor performance assessments, portfolio-level carbon reduction metrics, and detailed productivity analytics (Jarquín et al., 2015). This continuous, data-driven feedback loop empowers municipal and enterprise project owners to evaluate their decentralized workforce based on verified empirical metrics, effectively mitigating the traditional principal-agent problem found in decentralized labor (Sanderson et al., 2018). Ultimately, this supports an ecosystem of accountability, evidence-based competition, and continuous improvement across all projects and teams (Becker et al., 2024; Mavračić, 2025). Phase 5 thus elevates verification data from operational utility to strategic governance, enabling portfolio-level optimization, municipal ESG benchmarking, and long-term performance benchmarking.

Illustrative case scenario: municipal water main replacement

To illustrate the operational progression across the five phases, consider a hypothetical municipal infrastructure project involving the underground replacement of a 500-meter water distribution pipe:

• Phase 1 (Defined Expectations): The municipal public works authority issues a digital task package specifying exact trenching depth (1.5m), bedding compaction density, pipe joint alignment criteria, and required camera angles for visual evidence.
• Phase 2 (Defensible Evidence): Prior to backfilling, the field contractor captures encrypted, geotagged, and cryptographically time-stamped visual evidence of the laid pipe and depth gauge using a mobile VaaS application.
• Phase 3 (Approval Workflow): Quality assurance engineers inspect the submitted spatial metadata and high-resolution images via a central digital twin dashboard, cross-referencing spatial coordinates against underground utility maps to confirm specification compliance without dispatching an inspector vehicle.
• Phase 4 (Completion Plan): Upon remote QA sign-off, an automated payment readiness gateway validates milestone completion, instantly generating an audit-certified invoice trigger for contractor disbursement.
• Phase 5 (Performance Insights): Completed job data is aggregated into the municipality's master database, updating contractor reliability scorecards and logging calculated Scope 3 emission savings resulting from the eliminated inspector site visit.

4.2 Cross-industry adaptability

The VaaS framework derives its principal theoretical strength from its operational versatility and evidence integrity, and alignment with urban sustainability goals. Central to this is its core operational model, whose fundamental mechanisms, standardized evidence capture, geolocation verification, and automated approval workflows are fundamentally agnostic to specific labor domains (Ceric, 2014; Ivić and Cerić, 2023). This agnosticism enables seamless adaptation across a broad range of field-based industries, directly addressing the universal challenge of decentralized quality control in smart cities and regional infrastructure (Samsami, 2024). The specific operational challenges, applied VaaS solutions, and key outcomes across diverse sectors are summarized in Table 1 and further detailed below.

Table 1. cross-industry applications and governance of the VaaS framework.

In public infrastructure programs and smart city developments, from municipal road repairs to urban green infrastructure, projects are funded with taxpayer dollars and require highly transparent governance, carbon footprint reductions, and rigorous civic accountability (Santoni and Rufat, 2021). The VaaS framework theorizes a model that replaces subjective reporting with auditable, structured digital evidence, ensuring that publicly funded work meets strict contract specifications while minimizing physical vehicle dispatches (Spasenovic et al., 2019). By providing this verifiable chain of custody and emissions-conscious verification pipeline, public agencies can assure stakeholders, regulators, and citizens that funds are applied effectively, thereby supporting ongoing public trust, municipal ESG compliance, and civic accountability (Xiang et al., 2012). This transparency is particularly critical in public-sector procurement, where evidentiary rigor directly influences legitimacy and long-term institutional trust.

In the utilities and municipal infrastructure sector, distribution networks for power, water, and gas are mission-critical and subject to stringent safety, reliability, and sustainability demands (Samsami, 2024). Utilities must maintain comprehensive, immutable records of field work to demonstrate compliance and audit readiness. The VaaS framework delivers location-verified evidence for each task, producing granular documentation that supports safety assurances, carbon accounting, and regulatory oversight (Lovelace et al., 2015).

Similarly, large-scale telecommunications deployments produce geographically dispersed field activities, ranging from fiber trenching to cellular tower installations. The sheer scale and travel requirements render traditional on-site quality control highly cost-prohibitive and fuel-intensive, presenting a severe spatial distribution constraint (Xiang et al., 2012). VaaS remedies this by enabling instant field verification through geotagged, time-stamped media, delivering rapid, remote confirmation of adherence to engineering standards (Spasenovic et al., 2019).

In fragmented commercial and residential construction ecosystems, miscommunication and conflicting claims among multi-tier subcontractors frequently derail projects due to extreme information asymmetry (Lovelace et al., 2015). The VaaS approach conceptually mitigates these bottlenecks by enforcing standardized evidence records and structured visual evidence for every completed task (Xiang et al., 2012). Digitized punch-list validation enables general contractors to verify that subcontractors have met contractual specifications before authorizing payment. This granular level of digital evidence accelerates project closeouts, reduces material waste, and minimizes delays caused by undocumented rework (Samsami, 2024).

4.3 Implementation nuances, standards integration, and privacy governance

While core VaaS mechanisms are universally applicable, successful cross-industry deployment requires navigating domain-specific constraints, urban privacy regulations, worker dynamics, and technical standardization (Gosálvez-White et al., 2025; Samsami, 2024). To ensure technical interoperability and rigorous governance, VaaS implementation must align with established international standards (Stouffer et al., 2022). Information management across the VaaS lifecycle should align with the ISO 19650 framework for Building Information Modeling (BIM), establishing standardized data containers and common data environments (CDE) (International Organization for Standardization, 2018). For spatial and geolocation metadata, data structures must follow Open Geospatial Consortium (OGC) standards and ISO 19115 to ensure cross-system GIS interoperability (International Organization for Standardization, 2014). Security governance, identity management, and evidence access control should be anchored in ISO/IEC 27001 standards and NIST SP 800-53 control frameworks International Organization for Standardization / International Electrotechnical Commission (2022; National Institute of Standards Technology, 2020), utilizing W3C Verifiable Credentials and Decentralized Identifiers (DIDs) to cryptographically authenticate field workers and devices without exposing personal identification data (W3C, 2022a,b).

Addressing labor relations requires deep engagement with privacy hazards and worker-surveillance concerns (Escobar and Demeritt, 2016). Continuous GPS tracking and invasive worker monitoring introduce severe psychological stress, worker resistance, and potential legal non-compliance under privacy frameworks like GDPR and CCPA (Chandran et al., 2023; Lardo et al., 2022). There is a fundamental trade-off between strict auditability requirements, evidence integrity, and labor-protection considerations (Pedreño et al., 2021). To resolve this tension, VaaS rejects continuous background tracking in favor of strict event-triggered data capture (Chandran et al., 2023). Under this privacy-by-design policy, aligned with GDPR Article 5(1)(c) data minimization principles, spatial and personal metadata are recorded exclusively at the precise instant a worker manually submits a task verification photo or measurement (Pineda et al., 2024). Spatial metadata masking and blur filters automatically redact facial features and non-essential background details in public spaces, ensuring robust evidence integrity while safeguarding worker dignity and citizen spatial privacy (Shashidhara et al., 2024).

However, as the literature highlights, there is an inherent tension between data integrity and operational practicality in areas with poor field connectivity; integrating offline-capable capture modes ensures that evidence remains intact without sacrificing on-site efficiency (Samsami, 2024). Additionally, while some sources highlight substantial efficiency gains from fully remote validation (Fisher et al., 2021), highly regulated or complex contexts may still require physical verification to supplement remote evidence (Markman, 2006). The VaaS framework explicitly accommodates this variable by design, allowing phased remote validation with physical fallback pathways. Field operators must also manage the trade-off between rapid automated verification and the thoroughness of the evidence, ensuring critical quality signals are not inadvertently overlooked in the pursuit of operational speed (Ceric, 2014; Ivić and Cerić, 2023). Ultimately, this holistic, data-driven conceptual model aligns with established practices in verification and data provenance, providing a scalable solution to the unique demands of decentralized field operations (Pasupuleti, 2024).

5 Value proposition and long-term implications

The adoption of an evidence-based verification framework is theorized to yield compounding benefits that extend far beyond simple field-level data collection to advance municipal ESG objectives and smart city governance. Figure 3 illustrates the Value Proposition Pyramid, a conceptual model that categorizes these impacts across four ascending layers. Foundational technical capabilities at the Functional Layer enable immediate cost, time and emissions savings at the Operational Layer. These, in turn, structurally drive high-level business outcomes at the Strategic Layer, culminating in the Ecosystem Layer, where increasing operational trust, civic transparency, and accountability are established across decentralized project networks. This theoretical progression aligns with existing research demonstrating that automated, auditable verification serves as the foundation for efficiency, environmental sustainability, and compliance across distributed portfolios (Ernest et al., 2023; Merlec et al., 2022). Together, these layers articulate how micro-level data capture scales into macro-level governance improvements, forming a coherent theory of change for VaaS adoption in sustainable urban environments.

5.1 The value proposition pyramid

At the base of the pyramid lies the Functional Layer, which establishes the foundational, machine-enforceable technical mechanisms required to digitize field oversight. This layer enforces the structured capture of field-generated evidence records, including precise GPS geolocation, high-resolution media, privacy-preserving metadata, and secure timestamps (Abdou et al., 2017; Fargas and Petersen, 2017; Zadegan et al., 2024). By standardizing these inputs, the data inherently assumes theoretical qualities of reliability, integrity-secured permanence, and contextual accuracy, significantly reducing ambiguity regarding task execution (Sanabria et al., 2024). Beyond initial capture, this layer implements automated routing and evaluation logic that minimizes subjective human intervention (Bidry et al., 2023). Anchoring data integrity in these concrete rules ensures that all subsequent project records remain protected and traceable throughout the verification lifecycle (Chen et al., 2023). In essence, the Functional Layer provides the technical preconditions without which higher-order operational, environmental, and strategic benefits cannot materialize.

Resting upon this technical foundation, the Operational Layer translates raw field data into immediate, day-to-day business efficiencies and measurable decarbonization outcomes. Standardizing field documentation across disparate teams directly reduces administrative variance and limits reliance on manual, error-prone paperwork (Escobar and Demeritt, 2016; Latina et al., 2020). A central pillar of this layer is empowering project managers and municipal inspectors to conduct remote reviews, effectively substituting costly physical site visits with digital verification (Li et al., 2024). It is important to clarify that this conceptual review does not generate original empirical cost data; rather, external industry literature reports substantiate potential savings. Benchmark studies in related digitized workflow domains observe quality control cost reductions often ranging between 50 and 70% (Lin et al., 2022). These figures serve as external contextual indicators of potential impact rather than empirical outputs generated by the VaaS framework itself. Crucially, from an urban sustainability perspective, eliminating non-essential physical inspections directly curtails fleet fuel consumption, drastically reducing municipal Scope 3 greenhouse gas emissions produced by vehicle “truck rolls.” These gains reflect a significant reduction in field-to-office cycle times, lower urban carbon footprints, and vastly improved consistency in data capture (Kareem and Shakir, 2023). The Operational Layer, therefore, represents the first observable organizational benefits, where technical capabilities translate into measurable organizational efficiencies and environmental savings.

As operational efficiencies scale across a portfolio of projects, they structurally drive organizational outcomes at the Strategic Layer that focus on financial flow efficiency and risk mitigation, and municipal ESG alignment. By linking proof of work directly to automated approval workflows, organizations gain stronger controls over invoicing and contractor payments (Kabashi et al., 2024). This verifiable evidence replaces contested claims, leading to a notable reduction in invoice disputes and an acceleration of payment timelines. External empirical studies across decentralized settings observe potential payment timeline improvements benchmarked between 30 and 60% (Kim et al., 2025). Furthermore, the real-time nature of proactive verification catches errors at the moment of submission, drastically curtailing the compounding costs and material waste of rework (Jaafar and Alsaad, 2023). From an executive and municipal leadership standpoint, the creation of verifiable, timestamped records provides the audit-ready defensibility required by oversight bodies and ESG compliance auditors, thereby strengthening the organization's regulatory compliance posture (Bidry et al., 2023). At this layer, verification becomes not merely an operational function but a strategic asset that enhances financial governance, environmental accountability, and institutional resilience.

At the pinnacle of the pyramid, the Ecosystem Layer represents a theorized fundamental transformation in how decentralized project networks and smart cities operate. The core premise of this layer is structurally ensuring that every job is definitively verified before any downstream action or payment is triggered (Akindotei et al., 2024). This approach bridges the persistent “trust deficit” across suppliers, contractors, public asset owners, and citizens. By establishing an integrity-protected, shared record of verification events, the framework fosters alignment among multiple actors and significantly reduces information asymmetries (An et al., 2024; Bikos and Kumar, 2022; Theodouli et al., 2020). Ultimately, trust is established through the verifiable provenance of field evidence rather than historical reputation or subjective assurances (Ali et al., 2022; Lai et al., 2023). This layer thus conceptualizes VaaS not only as a technical system but as an institutional mechanism capable of reshaping norms of accountability and sustainable governance across entire project ecosystems.

However, while the Value Proposition Pyramid offers a clear theoretical progression of impact, realizing these benefits requires careful navigation of systemic trade-offs and cost overheads. From an economic perspective, decision-makers must evaluate the capital and operational expenditures of establishing VaaS digital infrastructure, such as cloud architecture, device integration, API maintenance, and software licensing, against the chronic costs of trust-deficit failures, including unbudgeted rework, payment litigation, delayed municipal milestones, and excessive fuel expenditure. Deepening the analysis of privacy hazards and labor relations reveals that continuous digital oversight introduces severe risks of perceived workforce surveillance, monitoring fatigue, and worker resistance. The magnitude of hypothesized operational and strategic gains relies heavily on disciplined data capture at the Functional Layer; inconsistent adoption can quickly diminish the system's value (Sanabria et al., 2024).

To navigate the inherent tension between strict auditability, evidence integrity, and labor protections, organizations must enforce privacy-by-design principles, such as event-triggered metadata logging (GDPR Article 5(1)(c)), automated background blurring, and cryptographic pseudonymization (Lardo et al., 2022; Pedreño et al., 2021). Techniques such as selective disclosure, spatial metadata masking, or privacy-preserving smart contracts offer viable pathways to maintain confidentiality while preserving total auditability (Kim et al., 2025; Shashidhara et al., 2024). Deliberate architectural choices regarding access controls and data minimization are essential to sustaining this ecosystem-wide trust without overexposing sensitive operational data or creating invasive workforce surveillance (Halder et al., 2024; Pineda et al., 2024). These tensions highlight that the pyramid's upper layers are contingent rather than guaranteed; their realization depends on sustained organizational commitment, governance capability, and cross-stakeholder coordination.

5.2 Theory of change and regulatory standardization

Theorizing the diffusion of the VaaS framework across field-based operations reveals that its long-term implications extend far beyond immediate, project-level cost savings. Drawing on prior work regarding audits, evidence-based governance, and trust in regulation, a systematic, digitized approach to verification is theorized to create the conditions for broader institutional change (Chechik et al., 2019). To establish methodological rigor, our analytical framework grounds this progression in classic Theory of Change evaluation literature (Weiss, 1995), mapping explicit causal linkages from technological inputs to systemic societal impacts. By articulating a clear, conceptual Theory of Change, we can map how the widespread integration of VaaS is projected to reconfigure regulatory standards, competitive procurement dynamics, and urban decarbonization pathways across decentralized infrastructure networks (Munar et al., 2018). This section, therefore, positions VaaS not merely as a technical intervention but as a catalyst for structural transformation across institutional, market, and environmental domains.

Within this conceptual model, the adoption of structured digital verification is posited to transition from a voluntary operational advantage to a regulated baseline expectation for municipal asset management. Industry trajectories suggest that, over time, a digital provenance trail will become a non-negotiable prerequisite for major infrastructure programs (Niu et al., 2019). This theoretical trajectory mirrors how historical safety protocols evolved from optional best practices to strict statutory requirements (Kessides, 2005). Based on governance literature, given the magnitude of public investment and the escalation of ESG expectations in smart cities, government agencies and large infrastructure funds are increasingly likely to mandate VaaS-like protocols (Bertelli, 2018; Gupta, 2025).

This standardization is theorized to drive a clear delineation between field execution, verification, and auditing functions, elevating the role of independent verifiers and trusted data custodians (Falco et al., 2021; Neumeier, 2016). Furthermore, the consolidation of VaaS-generated data into standardized formats enables regulators and municipal compliance officers to assess compliance with greater transparency, providing an auditable trail for complex, multi-stakeholder collaborations (Hu et al., 2021; Neumeier, 2011). Such shared evidence can reduce the informational disparities that normally arise when asset owners, contractors, verifiers, and regulators possess different accounts of whether, when, where, and to what standard work was completed (Ali et al., 2022; Hu et al., 2021). When verification records are authenticated, time-stamped, and protected against unauthorized alteration, the common evidence base can also reduce disagreement regarding the validity of reported performance (An et al., 2024). In turn, a mutually accessible and trusted verification record should reduce the scope for conflicting claims while increasing confidence in governance decisions (Lai et al., 2023).

Accordingly, the following hypothesis is proposed:

H1 (Ecosystem Information Asymmetry): A shared, authenticated verification ledger decreases multi-stakeholder dispute rates and increases institutional trust among public asset owners, contractors, and municipal oversight bodies.

However, technological transparency alone does not guarantee stakeholder acceptance. To prevent overreach or misalignment between regulatory criteria and on-the-ground realities, participatory design and transparent governance of these standards are essential to maintain stakeholder legitimacy (Liou et al., 2020; Stoustrup, 2022). This consideration is particularly important where VaaS incorporates spatial or location-related metadata (Chandran et al., 2023). Continuous location surveillance may collect substantially more information about field personnel than is necessary to verify a particular work event, potentially generating privacy concerns and resistance to adoption (Escobar and Demeritt, 2016). By contrast, an event-triggered model limits data collection to the time, location, and verification event necessary to document work completion (Chandran et al., 2023). When combined with privacy-preserving mechanisms such as background redaction, data minimization, controlled retention, and restricted access, such architecture separates verification of the work from continuous monitoring of the worker (Lardo et al., 2022; Shashidhara et al., 2024). The Theory of Change therefore suggests that privacy-preserving verification should increase the legitimacy and acceptability of digital oversight relative to continuous tracking approaches (Weiss, 1995).

This reasoning leads to the following hypothesis:

H2 (Privacy-Preserving Workforce Acceptance): Event-triggered spatial metadata capture combined with privacy-preserving redaction is associated with higher worker adoption and lower perceived surveillance stress than continuous location-tracking approaches.

In this sense, regulatory adoption is both an outcome of VaaS diffusion and a reinforcing mechanism that accelerates its institutionalization.

As standardized VaaS data accumulates, it is modeled to catalyze a shift in evidence-based competition and public sector procurement reform. Municipal project owners and funding bodies will increasingly be positioned to base procurement decisions on objective, verifiable performance metrics rather than relying solely on opaque reporting, historical relationships, or lowest-bid pricing (Puddicombe, 2009). Digital evidence allows for reliable comparisons across bidders using precise metrics such as first-time quality, defect rates, verified carbon reduction compliance, and schedule adherence (Chen, 2020; Vilhushynskyi and Chornous, 2019). Consequently, within this framework, firms that consistently deliver verifiable, high-quality, and low-emission results will command stronger competitive positioning (Kenny, 2009). Conversely, contractors who remain dependent on subjective reporting will face increasing competitive disadvantages in a data-driven marketplace (Noell et al., 2018).

The same evidentiary architecture has implications beyond contractor selection. Conventional multi-tier contractor payment systems frequently separate evidence of work completion from approval and financial disbursement (Dithebe et al., 2021). Documentation must pass through multiple organizational layers before an invoice can be validated, creating opportunities for information loss, duplicate checking, disagreement over completion status, and payment delay (de Oliveira Dantas et al., 2020; Shash and Habash, 2021). VaaS conceptually reduces this separation by linking verified work events to auditable records of task completion. When acceptance criteria are defined in advance and successful verification creates an authenticated evidence event, that event can serve as an objective trigger for subsequent approval and payment processes (Rahman et al., 2020). The resulting linkage between verified performance and financial workflow reduces dependence on retrospective reconciliation and provides asset owners, prime contractors, subcontractors, and finance functions with a common evidentiary basis for payment authorization (Li and Kassem, 2021). Under this logic, verification becomes not only a quality-control mechanism but also an information infrastructure for improving financial coordination across contractor networks (Kifokeris and Koch, 2020).

Accordingly:

H3 (Strategic Financial Flow): Integrating event-triggered, auditable digital evidence into payment workflows reduces the frequency of invoice disputes and accelerates disbursement cycles across multi-tier contractor networks.

Some scholars caution, however, that rapid shifts toward data-driven procurement can exacerbate market disparities if small firms lack access to digital verification tooling; therefore, transitional support and open verification standards may be necessary to ensure equitable market evolution (Cheelo and Liebenthal, 2018). Crucially, the credibility of this new competitive landscape hinges on data governance and privacy protections to maintain trust in the verification outcomes (Chen et al., 2025). Over time, these dynamics are theorized to reshape competitive norms, shifting the basis of market advantage from relational capital to empirically demonstrated performance.

In addition to market dynamics, the theoretical environmental rationale for adopting digitized verification is robust and aligns directly with global ESG commitments and municipal carbon neutrality goals. By shifting to remote verification, the literature indicates that organizations can reduce the need for on-site travel, thereby lowering vehicular emissions associated with physical “truck rolls” (Bynum et al., 2018; Moskalik et al., 2018). Remote evidence transmission also changes the temporal structure of verification (Fisher et al., 2021). Instead of waiting for an inspector to travel to a work location, digital evidence can be transmitted from the field to an authorized reviewer shortly after completion (Moskalik et al., 2018). This reduces the elapsed time between work execution, evidence review, correction, and acceptance (Kan et al., 2019). Where deficiencies are identified, contractors can receive feedback while crews, equipment, and contextual knowledge remain available, thereby reducing both verification delays and avoidable remobilization (Ingemarsdotter et al., 2021).

By optimizing remote inspection dispatches across metropolitan areas, public works departments can achieve quantifiable reductions in Scope 3 greenhouse gas emissions. Furthermore, because proactive VaaS protocols enable near real-time error detection, they significantly decrease the material waste and resource consumption typically associated with tearing down and re-executing flawed work (Ingemarsdotter et al., 2021). These effects suggest that operational efficiency and decarbonization are not independent outcomes of verification digitization. Rather, they arise from a shared mechanism: reducing the temporal and geographic separation between field execution and verification.

Accordingly, the following hypothesis is proposed:

H4 (Operational Efficiency and Decarbonization): The implementation of standardized remote VaaS digital-verification protocols reduces field-to-office verification cycle times and Scope 3 inspector-transit emissions relative to traditional physical-inspection workflows.

These environmental advantages can compound to create systemic improvements in the ecological footprint of infrastructure development (Puddicombe, 2009). To fully realize these sustainability benefits, however, organizations must apply a holistic lifecycle perspective. This includes accounting for the environmental impact of the digital infrastructure itself, such as data centers and cloud servers, alongside the material efficiencies gained in the field (Long and Steel, 2020). Ultimately, improved environmental outcomes and transparent reporting bolster community trust and facilitate responsible investment decisions (Gilardi, 2022). Thus, VaaS aligns operational efficiency with environmental stewardship, reinforcing ESG integration across the infrastructural lifecycle.

The successful realization of these long-term implications can be modeled through a classic Theory of Change framework, which relies on a structured sequence of inputs, activities, outputs, and impacts (Weiss, 1995). The foundational inputs are conceptualized as requiring scalable digital architectures, privacy-compliant spatial data layers, and interoperability with existing urban digital twins and municipal data ecosystems (Hu et al., 2021). Core activities would involve deploying VaaS protocols across smart city pilot programs while maintaining transparency audits and engaging stakeholders to sustain legitimacy (Duberry et al., 2021). These activities are projected to generate outputs such as interoperable verification records and auditable evidence-traceability frameworks, which directly facilitate near-term outcomes like reduced rework, lower fleet fuel consumption, and lower mobilization costs (Neumeier, 2011). Ultimately, these outcomes theoretically cascade into macro-level impacts: greater transparency in infrastructure governance, highly resilient supply chains, substantially lowered municipal emissions, and a paradigm shift toward performance-based funding (Puddicombe, 2009).

To visually map this causal sequence from foundational technological prerequisites up to systemic macro-level shifts, Figure 4 outlines the explicit developmental pathways embedded within the VaaS framework. This causal logic demonstrates how discrete operational mechanisms (evidence capture, verification, privacy protection, decision integration, and data interoperability) can produce immediate organizational outcomes that accumulate into longer-term institutional, economic, and environmental change.

The hypothesized trajectory of the VaaS framework points to a definitive transition from optional project optimization to standardized industry responsibility. As digital verification becomes deeply embedded in governance, procurement, and ESG reporting, the competitive landscape will shift to focus on data-driven performance. While the potential operational and environmental benefits are substantial, this adoption path requires deliberate attention to interoperability, urban data privacy, workforce change management, and stakeholder engagement (Gilardi, 2022). By ensuring that verification outputs remain interpretable and aligned with societal values, industries can fully realize the benefits of VaaS while preserving trust and accountability across diverse jurisdictions (Puddicombe, 2009; Chen et al., 2025). In sum, the Theory of Change positions VaaS as a foundational enabler for transparent, resilient, and sustainability-aligned infrastructure systems.

5.3 Future research directions: guidelines for empirical validation

While this paper establishes the theoretical and structural foundation for the VaaS framework, its conceptual models necessitate rigorous empirical validation. Because the current synthesis provides a category-defining architecture rather than an isolated empirical case study, future research should prioritize translating these theoretical propositions into empirically testable hypotheses suited for urban sustainability and smart city literature. Researchers are encouraged to deploy longitudinal case studies, comparative pilot programs in municipal public works, and mixed-methods approaches to test the core hypotheses embedded within the Value Proposition Pyramid.

To maximize practical value and provide clear guidance for subsequent researchers, empirical testing should proceed in a phased priority order:

Priority 1 (Functional and Operational Layer Validation): Researchers should first evaluate baseline technical data integrity, reductions in field-to-office cycle times, and direct fleet vehicle Scope 3 emissions reductions through quasi-experimental field trials comparing traditional inspections with VaaS workflows.

Priority 2 (Strategic Layer Validation): Once operational reliability is validated, empirical efforts should evaluate financial performance metrics, specifically testing whether automated proof-of-work validation reduces invoice-to-cash turnaround times and dispute frequencies (H₂).

Priority 3 (Ecosystem and Governance Layer Validation): Long-term longitudinal studies should evaluate multi-stakeholder trust metrics, procurement policy shifts, and systemic municipal ESG performance across smart city networks (H₃).

To validate the projected efficiencies at the Operational and Strategic Layers, quantitative studies should focus on testing the underlying causal relationship between VaaS adoption and operational performance, rather than evaluating adherence to rigid numerical ranges. Instead of treating specific empirical literature benchmarks, such as 50% to 70% quality control cost savings, as strict theoretical pass/fail thresholds, future research should hypothesize and measure directional improvements across key performance metrics. Future research could design quasi-experimental field trials comparing traditional, manual inspection workflows against fully integrated VaaS deployments within the same municipal utility or public works agency. Key performance indicators (KPIs) for these studies should include the relative magnitude of reduction in field-to-office cycle times, the frequency and cost of rework, the reduction in fleet vehicle travel kilometers and associated Scope 3 transport emissions, and the percentage acceleration in payment processing (invoice-to-cash cycles). Furthermore, comparative financial analyses should empirically measure the net return on investment (ROI) by contrasting the ongoing software and digital infrastructure overhead of VaaS against the avoided expenses of physical travel, rework, and compliance litigation. Additionally, researchers can utilize digital audit logs or system logs to empirically audit the integrity and immutability of the remote evidence trails.

Beyond quantitative financial and environmental metrics, validating the Ecosystem Layer requires qualitative exploration of human factors, urban privacy compliance, and organizational behavior. The transition from implicit trust to continuous, data-driven digital oversight introduces distinct management change challenges, including potential workforce resistance, monitoring fatigue, and fears of invasive surveillance. Future studies should utilize surveys, semi-structured interviews, and ethnographic field research to assess how frontline workers, subcontractors, and site managers perceive and adapt to VaaS-enforced oversight while testing the effectiveness of privacy-preserving metadata masking and event-triggered data collection under municipal data protection standards (e.g., GDPR/CCPA). Investigating these human dynamics is critical for refining the governance mechanisms outlined in this framework, identifying potential barriers to technological adoption, and ensuring that VaaS implementations are both operationally effective, privacy-compliant, and socially sustainable across the decentralized labor force.

6 Conclusion

Reliance on implicit trust and reactive, manual inspections within decentralized field operations and smart city asset management has long been identified in the literature as a source of systemic friction. This paper argues that the trust deficit is not fundamentally a problem of interpersonal trust but of insufficient objective verification. As demonstrated, this pervasive trust deficit generates financial waste, compliance vulnerabilities, elevated Scope 3 transport emissions, and protracted stakeholder disputes. By synthesizing insights across built-environment scholarship, this study's primary theoretical contribution lies in conceptualizing Verification-as-a-Service (VaaS) as an overarching governance framework. Crucially, VaaS is logically distinguished from underlying enabling technologies, such as Building Information Modeling (BIM), digital twins, blockchain, and smart contracts, by serving as the high-level operational and managerial layer that orchestrates these tools into a standardized, evidence-based verification lifecycle. Replacing subjective assumptions with the structured VaaS framework provides a theoretical model to resolve persistent principal-agent information asymmetries. By operationalizing a continuous, five-phase digital evidence-traceability lifecycle, ranging from standardized task assignment to data-driven performance tracking and urban ESG evaluation, organizations and municipal agencies can substantially reduce the evidentiary ambiguity that drives costly rework, unnecessary physical site visits, and delayed payment cycles. In doing so, VaaS reframes verification not as a downstream administrative task but as an integrated, data-centric control embedded throughout the project lifecycle.

The projected impacts of this transition extend far beyond immediate field-level efficiencies. As articulated through the theoretical model of the Value Proposition Pyramid, the VaaS framework builds upon a technological foundation of geotagged, time-stamped evidence and privacy-preserving spatial metadata to drive compounding strategic benefits, culminating in ecosystem-wide operational trust and municipal decarbonization. This provides a significant incremental contribution over prior built-environment scholarship by explicitly connecting remote inspection workflows to measurable Scope 3 fleet emission reductions and municipal ESG compliance. Furthermore, because its core mechanisms are inherently domain-agnostic, the framework offers broad conceptual adaptability across mission-critical sectors, including public works and smart cities, utilities, telecommunications, and construction. By structurally ensuring that every task is objectively verified before financial compensation is released, VaaS theoretically bridges the persistent visibility gap between project owners and their distributed workforces. This shift establishes a shared evidentiary language across stakeholders, reducing information asymmetries that have historically undermined coordination and accountability.

Ultimately, the VaaS framework represents more than an operational upgrade; it is a fundamental conceptual redefinition of accountability in the field. Looking forward, guided by the proposed Theory of Change, this evidence-driven approach is hypothesized to transition from a voluntary competitive advantage to a standardized regulatory baseline in public procurement and municipal asset governance. As industries and public sector entities increasingly shift toward evidence-based procurement and prioritize the environmental sustainability of remote verification, drastically reducing fleet emissions through eliminated “truck rolls,” the widespread adoption of VaaS will do more than optimize individual project margins. It establishes a new, transparent standard for excellence, paving the way for a future where global infrastructure development and urban asset management are fundamentally faster, safer, more sustainable, and more reliable. However, several key limitations of this study must be acknowledged. As an integrative conceptual review, this work delivers a theoretical framework that lacks direct empirical field testing. Furthermore, the framework's boundary conditions depend heavily on resolving the “oracle problem,” ensuring data veracity at the point of capture, and navigating complex trade-offs regarding worker surveillance risks, urban spatial privacy (CDPR/CCPA), and software infrastructure overhead. Realizing this trajectory, however, will require deliberate attention to implementation governance, interoperability, spatial privacy safeguards (e.g., GDPR/CCPA), worker surveillance mitigation, and realistic evaluations of software overhead costs vs. net ROI, ensuring that the benefits of VaaS are distributed widely rather than reinforcing existing disparities.

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Footnotes

Edited by: Ehsan Noroozinejad Farsangi, Western Sydney University, Australia

Reviewed by: Yasser Nassar, University of Kufa, Iraq

Lin Liu, Beijing Jiaotong University, China