TRANSPARENCY IN GOVERNANCE: THE INFLUENCE OF OPEN DATA ON PUBLIC TRUST IN PHILIPPINE CONTEXT

Institutional theory

Institutional Theory provides a foundational explanation of why governments adopt transparency initiatives such as open data systems. Institutional Theory posits that organizations operate within a framework of formal rules, norms, and societal expectations that shape their structures and behaviors (Scott, 2014). Institutions adopt reforms not only for efficiency but also to gain legitimacy, credibility, and public acceptance. In the context of public governance, transparency reforms, including open data initiatives, are institutional responses to increasing societal demands for accountability, openness, and democratic governance.

DiMaggio and Powell (1983) argue that institutional change occurs through coercive, normative, and mimetic pressures. Coercive pressures arise from legal mandates, such as transparency laws and freedom of information policies. Normative pressures stem from professional standards and expectations of good governance. Mimetic pressures occur when governments adopt practices implemented by other countries to enhance legitimacy and align with global governance standards. In the Philippine context, transparency reforms such as the Freedom of Information Program and open data portals reflect institutional responses to both domestic and international pressures for transparency and accountability.

Institutional Theory also emphasizes the concept of legitimacy, which refers to the perception that government actions are appropriate, lawful, and aligned with societal expectations (Suchman, 1995). Transparency initiatives enhance institutional legitimacy by demonstrating openness and accountability. When citizens perceive government institutions as legitimate, they are more likely to trust them. Thus, open data initiatives function as institutional mechanisms designed to enhance legitimacy and strengthen public trust.

Furthermore, Institutional Theory explains that transparency reforms become institutionalized over time as part of governance structures. Open data initiatives transition from optional reforms to standard governance practices, reinforcing transparency norms and promoting trust-building relationships between government and citizens.

Transparency theory

Transparency Theory explains how access to government information reduces information asymmetry and strengthens accountability and trust. Transparency refers to the extent to which government actions, decisions, and information are open and accessible to citizens (Meijer, 2013). Transparency reduces uncertainty by providing citizens with reliable information about government activities, thereby enabling public oversight and evaluation.

According to Transparency Theory, transparency enhances accountability by allowing citizens to monitor government performance and hold public officials accountable for their actions (Florini, 2007). Open data initiatives operationalize transparency by providing structured, accessible, and reusable government information. This proactive disclosure enables citizens, civil society organizations, and researchers to analyze government performance and detect inefficiencies or corruption.

Transparency also addresses the principal–agent problem in governance. In democratic systems, citizens act as principals, while government officials act as agents responsible for managing public resources. Information asymmetry occurs when agents possess more information than principals, creating opportunities for opportunistic behavior and corruption (Stiglitz, 2002). Transparency reduces this asymmetry by ensuring that citizens have access to relevant information, thereby improving accountability and reducing opportunities for misconduct.

Grimmelikhuijsen and Meijer (2014) argue that transparency strengthens trust by signaling competence, honesty, and openness. When governments disclose information proactively, citizens perceive them as more accountable and trustworthy. Open data initiatives enhance transparency by enabling citizens to access real-time information about government budgets, procurement, and service delivery. This enhances citizens’ ability to evaluate government performance, thereby strengthening trust.

However, Transparency Theory also recognizes that transparency alone may not automatically increase trust. The effectiveness of transparency depends on factors such as data accessibility, usability, and citizen awareness. If data are difficult to access or understand, transparency initiatives may fail to achieve their intended trust-building effects. Therefore, open data initiatives must ensure not only availability but also usability and accessibility to effectively enhance public trust.

Trust theory

Trust Theory provides the psychological and behavioral explanation for how transparency influences citizens’ trust in government. Trust in government refers to citizens’ belief that government institutions act competently, honestly, and in the public interest (Bouckaert & Van de Walle, 2003). Trust is essential for effective governance because it promotes citizen cooperation, policy compliance, and political stability.

Mayer, Davis, and Schoorman (1995) conceptualize trust as a function of three key factors: ability, benevolence, and integrity. Ability refers to the competence of government institutions to perform their functions effectively. Benevolence refers to the perception that government acts in the public interest. Integrity refers to adherence to ethical standards and transparency. Open data initiatives enhance perceptions of integrity by demonstrating openness and accountability.

Trust Theory also emphasizes the role of information in trust formation. Citizens rely on available information to evaluate government performance. When governments provide accurate, timely, and accessible information, citizens are more likely to develop trust. Conversely, lack of transparency creates uncertainty and suspicion, which undermines trust (Blind, 2007).

Transparency influences trust through cognitive and affective mechanisms. Cognitive trust is based on rational evaluation of government performance and information disclosure. Affective trust is based on emotional perceptions of government honesty and fairness. Open data initiatives contribute to both cognitive and affective trust by providing evidence of government accountability and openness.

Furthermore, trust is essential for governance effectiveness. Citizens who trust government institutions are more likely to comply with laws, participate in civic activities, and support public policies (OECD, 2017). Therefore, enhancing transparency through open data initiatives can contribute to improved governance outcomes by strengthening citizen trust.

Integration of Institutional Theory, Transparency Theory, and Trust Theory.

The integration of Institutional Theory, Transparency Theory, and Trust Theory provides a comprehensive explanation of how open data transparency influences public trust in government. Institutional Theory explains why governments adopt open data initiatives—to enhance legitimacy and respond to societal expectations. Transparency Theory explains how open data reduces information asymmetry and enhances accountability. Trust Theory explains how transparency influences citizens’ perceptions of government competence, integrity, and benevolence, thereby strengthening trust.

In this integrated framework, open data initiatives function as institutional transparency mechanisms that enhance accountability and legitimacy. These transparency mechanisms influence citizens’ perceptions of government openness, competence, and integrity, which in turn shape public trust. Institutional structures enable transparency initiatives, transparency mechanisms provide information disclosure, and trust mechanisms determine citizen confidence in government.

In the Philippine context, open data initiatives such as the Freedom of Information Program, Transparency Seal, and open government data portals represent institutional transparency mechanisms designed to enhance accountability and legitimacy. These initiatives provide citizens with access to government information, thereby reducing information asymmetry and strengthening trust. However, the effectiveness of these initiatives depends on accessibility, usability, and citizen awareness.

Thus, this study adopts an integrated theoretical framework that explains how institutional transparency mechanisms influence trust through transparency processes. This framework provides the theoretical basis for examining the influence of open data transparency on public trust in government.

Research design

This study employed a quantitative explanatory research design to examine the influence of open data transparency on public trust in government within the Philippine context. An explanatory design is appropriate when the objective is to determine causal relationships among variables and to assess the predictive strength of independent variables on a dependent variable (Creswell & Creswell, 2018). The study specifically tested whether open data accessibility, usability, and perceived transparency significantly influence levels of public trust in government institutions. By using a quantitative approach, the study enabled objective measurement of perceptions and allowed statistical testing of hypothesized relationships, thereby strengthening the generalizability and replicability of findings (Bryman, 2016).

A cross-sectional survey method was adopted, wherein data were collected from respondents at a single point in time. Cross-sectional designs are widely used in public administration and governance research to measure citizen attitudes, perceptions, and institutional evaluations (Etikan, Musa, & Alkassim, 2016). This design was considered appropriate because the study sought to capture current perceptions of open data transparency and its relationship to public trust rather than changes over time.

Research locale

The study was conducted in the Philippines, a developing democracy that has institutionalized transparency reforms through open government initiatives. The Philippine context provides a relevant setting for examining the relationship between open data and public trust due to the implementation of the Freedom of Information (FOI) Program, the Open Government Data (OGD) portal, the Transparency Seal policy, and other digital governance initiatives. These reforms aim to enhance transparency, accountability, and citizen engagement through proactive disclosure of government information.

Despite these reforms, concerns regarding public trust, corruption perception, and institutional accountability persist. This makes the Philippines an appropriate empirical case for investigating whether open data transparency contributes to strengthening public trust in governance. The study focused on Filipino citizens who have access to digital platforms and government information systems, as open data initiatives are primarily delivered through online channels.

Population and sampling

The target population consisted of Filipino citizens aged 18 years and above who have access to the internet and have the capacity to access government information through digital platforms. Given that open data initiatives are primarily web-based, it was necessary to include respondents who are capable of interacting with digital transparency tools.

A stratified random sampling technique was employed to ensure representation across key demographic characteristics, including age group, gender, educational attainment, and geographic distribution. Stratified sampling enhances representativeness by ensuring proportional inclusion of relevant subgroups and reducing sampling bias (Lohr, 2019). This approach strengthens the external validity of the findings.

The sample size was determined using Cochran’s (1977) formula for large populations, with a 95% confidence level and a 5% margin of error. The minimum required sample size was calculated at 384 respondents. To ensure adequate statistical power and account for incomplete responses, the final target sample size was set at 400 respondents. This sample size satisfies minimum requirements for multivariate statistical analysis, including multiple regression (Hair et al., 2019).

Research instrument

Data were collected using a structured survey questionnaire composed of five major sections: demographic profile, open data accessibility, open data usability, perceived transparency, and public trust in government. The instrument was designed to measure citizens’ perceptions of open data systems and their level of trust in government institutions.

The demographic section gathered information on age, gender, educational attainment, employment status, and frequency of internet use. These variables were included to control for demographic influences that may affect perceptions of transparency and trust.

The open data accessibility section measured the extent to which respondents perceive government data as available, accessible, and easy to locate. Items assessed the visibility of government portals, availability of datasets, and ease of navigation. The usability section evaluated whether government data are understandable, relevant, and useful for citizen purposes, including clarity of presentation and ease of interpretation.

Perceived transparency was measured by assessing respondents’ views on government openness, disclosure practices, and willingness to share information. Finally, public trust in government was measured through items assessing confidence in government integrity, perceived honesty of public officials, and trust in government decision-making processes.

All items were measured using a five-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The five-point Likert scale was selected because it provides sufficient variability for statistical analysis while maintaining respondent clarity and reliability (Joshi et al., 2015). The survey instrument was adapted from validated measures used in prior studies on transparency, open data, and trust in government (Grimmelikhuijsen et al., 2013; Welch, Hinnant, & Moon, 2005), ensuring theoretical alignment and construct validity.

Statistical treatment of data

Data were analyzed using SPSS. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were computed to summarize respondent characteristics and perception levels.

Pearson correlation analysis was conducted to examine the strength and direction of relationships between open data transparency variables and public trust. To test the predictive influence of independent variables on public trust, multiple regression analysis was performed. The regression model estimated the extent to which open data accessibility, usability, and perceived transparency significantly predict public trust in government.

Hypotheses were tested at a 0.05 level of significance. A p-value less than 0.05 indicated a statistically significant relationship, leading to rejection of the null hypothesis. This analytical approach enabled the study to determine whether open data transparency significantly influences public trust in the Philippine governance context.

Validity and reliability

Content validity was established through expert evaluation by three scholars specializing in public administration, governance, and research methodology. The experts reviewed the questionnaire to assess clarity, relevance, and alignment with the research objectives. Revisions were made based on their recommendations to improve precision and comprehensiveness.

Construct validity was assessed through exploratory factor analysis (EFA), which examined whether survey items loaded appropriately onto their intended constructs. Factor loadings of 0.50 or higher were considered acceptable indicators of construct validity (Hair et al., 2019).

Reliability was assessed using Cronbach’s alpha coefficient to determine internal consistency among scale items. A minimum reliability threshold of 0.70 was adopted, consistent with established psychometric standards (Nunnally & Bernstein, 1994). Reliability testing was conducted after a pilot study involving 30 respondents, and necessary refinements were made prior to full data collection.

Data collection procedure

Data were collected using an online survey platform to ensure accessibility and efficient distribution. The online format was selected due to the digital nature of open data systems and the need to reach respondents who actively use internet-based government platforms.

The data collection process involved pilot testing the instrument, revising items based on feedback, and distributing the survey link through email networks, academic institutions, and social media platforms. Participation was voluntary, and informed consent was obtained electronically prior to survey completion. Data screening was conducted to remove incomplete or inconsistent responses before statistical analysis.

Informed consent

Written informed consent was obtained from all participants prior to their participation in the study. Before accessing the survey questionnaire, respondents were presented with an electronic informed consent form that explained the purpose of the research, the voluntary nature of participation, confidentiality of responses, and the right to withdraw at any time without penalty. Participants indicated their consent by selecting the “I agree to participate” option before proceeding to the survey questionnaire. This process constituted written informed consent in accordance with ethical standards for research involving human participants. Only respondents who provided consent were allowed to complete the survey.

The informed consent process was reviewed and approved by the University Research Ethics Committee of the Polytechnic University of the Philippines as part of the study’s ethical clearance.

Ethical considerations

This study adhered to internationally recognized ethical standards for research involving human participants. All research procedures were conducted in accordance with the ethical principles outlined in the World Medical Association Declaration of Helsinki for research involving human subjects.

Prior to the commencement of data collection, ethical approval for the study was obtained from the University Research Ethics Committee (UREC) of the Polytechnic University of the Philippines, which serves as the institutional review board responsible for evaluating research involving human participants. The ethics review confirmed that the research design, participant recruitment procedures, informed consent process, and data management protocols complied with national and international ethical guidelines for research involving human subjects.

The study received formal ethics approval under UREC Code 2025–4025, issued on April 23, 2025.

Participation in the study was voluntary, and all respondents were informed of the purpose of the research, confidentiality of responses, and their right to withdraw at any time without penalty. All collected data were anonymized and used solely for academic research purposes.

Open data accessibility

Open Data Accessibility was measured through five items assessing availability of government information online, ease of locating datasets, accessibility of open data portals, and visibility of government platforms.

Table I presents the descriptive statistics for the Open Data Accessibility indicators, including the availability of government data online, accessibility of government websites, visibility of open data portals, ease of locating datasets, and frequency of data updates.

The overall mean score of 3.78 indicates that respondents generally perceive open government data as accessible. The highest-rated item was “Government data are available online” (M = 3.92), suggesting that citizens recognize the government’s effort in digitizing and publishing information.

This finding aligns with Institutional Theory (Scott, 2014), which posits that governments adopt transparency reforms to enhance legitimacy. The accessibility of government data reflects institutional compliance with transparency norms and digital governance standards. However, the relatively lower score for “ease of finding datasets” (M = 3.63) suggests that accessibility may still be constrained by navigation complexity or platform design.

Consistent with Janssen et al. (2012), accessibility is a foundational condition for open data effectiveness. Without accessible platforms, transparency reforms cannot meaningfully influence citizen trust.

Open data usability

Table II presents the descriptive statistics for the Open Data Usability indicators, which measure the clarity, interpretability, and usefulness of government data for citizens. Open Data Usability assessed whether government data are understandable, clear, interpretable, and useful to citizens.

The overall usability score (M = 3.65) indicates positive but slightly lower perceptions compared to accessibility. While citizens acknowledge availability of data, interpretability remains an area requiring improvement.

Transparency Theory emphasizes that transparency must go beyond disclosure and include intelligibility (Meijer, 2013). Data that are technically available but difficult to interpret may not effectively reduce information asymmetry. This supports Zuiderwijk and Janssen (2014), who argue that usability determines whether open data can achieve accountability and trust-building outcomes.

The findings suggest that improving user-friendly presentation and data visualization tools may further enhance trust outcomes.

Perceived transparency

Table III summarizes the descriptive statistics for Perceived Transparency, reflecting respondents’ perceptions of government openness, disclosure practices, and accountability. Perceived Transparency measured citizens’ perceptions of government openness, disclosure practices, and willingness to share information.

Perceived transparency received a high overall rating (M = 3.59). The highest-rated item was “Government promotes openness” (M = 3.79), indicating recognition of transparency reforms.

However, lower ratings for decision-making transparency (M = 3.48) suggest that procedural transparency may be less visible than informational transparency. Transparency Theory posits that both informational disclosure and procedural openness are necessary to strengthen trust (Florini, 2007).

These findings suggest that while citizens acknowledge transparency efforts, perceived openness in policymaking processes may require further enhancement.

Public trust in government

Public Trust was measured through five items assessing confidence in integrity, honesty, fairness, and competence. Table IV presents the descriptive statistics for Public Trust in Government, including citizens’ perceptions of institutional competence, honesty, fairness, and commitment to the public interest.

Public trust scored moderately high (M = 3.54). Trust in competence (M = 3.75) was stronger than trust in honesty (M = 3.42), indicating that citizens may perceive government as capable but remain cautious regarding integrity.

Trust Theory (Mayer et al., 1995) emphasizes ability, benevolence, and integrity as core components of trust. The findings suggest relatively stronger perceptions of ability than integrity, indicating that transparency reforms may need to further strengthen perceptions of ethical governance.

Correlation analysis

Table V presents the Pearson correlation matrix examining the relationships among Open Data Accessibility, Usability, Perceived Transparency, and Public Trust in Government.

Perceived transparency showed the strongest correlation with public trust (r = 0.78). This supports Grimmelikhuijsen et al. (2013), who found that transparency positively influences trust.

The moderate-to-strong correlations confirm that accessibility and usability contribute to trust, but transparency perception plays the most decisive role.

Regression analysis

Table VI presents the results of the multiple regression analysis examining the predictive influence of Open Data Accessibility, Usability, and Perceived Transparency on Public Trust in Government.

Model Summary:

R = 0.81.

R² = 0.66.

F = 254.72.

p = 0.000.

The model explains 66% of variance in public trust, indicating strong explanatory power. Perceived transparency is the strongest predictor (β = 0.48), followed by usability (β = 0.26) and accessibility (β = 0.21).

This confirms the integrated theoretical framework:

The findings indicate that transparency must move beyond technical availability to meaningful disclosure and usability to maximize trust outcomes.