How do personality traits influence Open Government Data (OGD) adoption and usage? Investigating the indirect and moderating effects

Open Government Data (OGD) research has focused for a long on the adoption and usage from the perspectives of users across different contexts. The underlying rationale for this specific focus is that OGD initiatives are undertaken to further citizen engagement with OGD for value generation and innovation purposes. Conceding that usage propensity is different across individuals, it is important to understand the influence of personality traits vis-à-vis OGD adoption and usage. Given that OGD has been regarded as a sophisticated “technology” and the role of personality traits has been considered as important in the adoption and usage of “technologies” in general, therefore, the present study contributes to the extant OGD-focused literature from a novel dimension. The study invokes the adapted model of the Unified Theory of Technology Adoption and Use (UTAUT) alongside the HEXACO-100 inventory constructs for studying the relationships between the constructs with a sample of 530 respondents. The results demonstrate that higher user Openness to Experience contributes to their higher Effort and Performance Expectancy; exposure to Social Influence; an increased level of Trust; and a more positive perception of Facilitating Conditions and Information Quality. Agreeable people are more likely to voluntarily use OGD. An individual's conscientiousness improves their perception of factors related to OGD quality. Excessive emotionality leads to a more critical perception of systems and information quality issues. Our findings also attest to the moderating impact of Honesty-Humility across Information Quality-Behavioral Intention positively; Extraversion across Information Quality-Behavioral Intention negatively and Extraversion across Trust-Behavioral Intention positively. Honesty turns out to be important for considering Information Quality vis-à-vis OGD adoption and usage but whilst extroverts are concerned about Information Quality, i.e. flawless information retrieval via OGD sources, Introverts are concerned about OGD trustworthiness, i.e. credible OGD for its adoption and usage and Extroverts find the OGD reliable and credible. With pointers for further research across the personality traits-OGD adoption and usage theme, the study closes with practitioner implications.

[1]  Nachiketa Tripathi,et al.  Forced transition to technology: role of self-efficacy and big five personality variables in the adoption of technology , 2022, International Journal of Educational Management.

[2]  Vinh Phu Nguyen The perceptions of social media users of digital detox apps considering personality traits , 2022, Education and Information Technologies.

[3]  Jan C. Weyerer,et al.  Open Government: Development, Concept, and Future Research Directions , 2022, International Journal of Public Administration.

[4]  Stuti Saxena,et al.  Investigation into the adoption of open government data among students: the behavioural intention-based comparative analysis of three countries , 2022, Aslib J. Inf. Manag..

[5]  Md. Shamim Talukder,et al.  Exploring continuance usage intention toward open government data technologies: an integrated approach , 2021, VINE Journal of Information and Knowledge Management Systems.

[6]  Koen Ponnet,et al.  The role of HEXACO personality traits in different kinds of sexting:A cross-cultural study in 10 countries , 2020, Computers in Human Behavior.

[7]  Stefan Pfattheicher,et al.  The Beautiful Complexity of Human Prosociality: On the Interplay of Honesty-Humility, Intuition, and a Reward System , 2020 .

[8]  R. Molarius,et al.  Open government data policy and value added - Evidence on transport safety agency case , 2020, Technology in Society.

[9]  Marijn Janssen,et al.  Citizens’ Trust in Open Government Data: A Quantitative Study about the Effects of Data Quality, System Quality and Service Quality , 2020, DG.O.

[10]  Matt C. Howard Using the HEXACO-100 to measure Individual Entrepreneurial Orientation: Introducing the HEXACO-IEO , 2020 .

[11]  H. Hlavacs,et al.  Personality differences between videogame vs. non-videogame consumers using the HEXACO model , 2020, Current Psychology.

[12]  Zhenbin Yang,et al.  What drives public agencies to participate in open government data initiatives? an innovation resource perspective , 2020, Inf. Manag..

[13]  Zhaoli Zhang,et al.  Identifying key factors affecting college students’ adoption of the e-learning system in mandatory blended learning environments , 2020, Interact. Learn. Environ..

[14]  M. Janssen,et al.  A Systematic Literature Study to Unravel Transparency Enabled by Open Government Data: The Window Theory , 2019, Public Performance & Management Review.

[15]  E. Avram,et al.  Exploring the relationship between personality structure and smartphone usage , 2019, Current Psychology.

[16]  Jorge L. Alfaro-Perez,et al.  Personality Types as Moderators of the Acceptance of Information Technologies in Organizations: A Multi-Group Analysis in PLS-SEM , 2019, Sustainability.

[17]  Yukun Bao,et al.  Determinants of user acceptance and use of open government data (OGD): An empirical investigation in Bangladesh , 2019, Technology in Society.

[18]  Joseph F. Hair,et al.  When to use and how to report the results of PLS-SEM , 2019, European Business Review.

[19]  Yannis Charalabidis,et al.  Analysing the Characteristics of Open Government Data Sources in Greece , 2018 .

[20]  S. Roberts,et al.  HEXACO Personality Factors and their Associations with Facebook use and Facebook Network Characteristics. , 2018, Psychological reports.

[21]  Jeromy Anglim,et al.  Personality and problematic smartphone use: A facet-level analysis using the Five Factor Model and HEXACO frameworks , 2018, Comput. Hum. Behav..

[22]  M. Ashton,et al.  Psychometric Properties of the HEXACO-100 , 2018, Assessment.

[23]  Pascal J. Kieslich,et al.  Lead Us (Not) into Temptation: Testing the Motivational Mechanisms Linking Honesty–Humility to Cooperation , 2018 .

[24]  S. Buono,et al.  Personality factors and acceptability of socially assistive robotics in teachers with and without specialized training for children with disability , 2017 .

[25]  Gordon W. Cheung,et al.  Current Approaches for Assessing Convergent and Discriminant Validity with SEM: Issues and Solutions , 2017 .

[26]  Hager Khechine,et al.  Relating personality (Big Five) to the core constructs of the Unified Theory of Acceptance and Use of Technology , 2017 .

[27]  Marijn Janssen,et al.  Transparency-by-design as a foundation for open government , 2017 .

[28]  Kuo-Lun Hsiao,et al.  Compulsive mobile application usage and technostress: the role of personality traits , 2017, Online Inf. Rev..

[29]  Nikolaos K. Tselios,et al.  Twitter adoption, students’ perceptions, Big Five personality traits and learning outcome: Lessons learned from 3 case studies , 2017, ArXiv.

[30]  A. Chirumbolo,et al.  How HEXACO Personality Traits Predict Different Selfie-Posting Behaviors among Adolescents and Young Adults , 2017, Front. Psychol..

[31]  W. Boontarig Effect of personality factors on attitude towards the adoption of health information via online social networking , 2016, 2016 International Computer Science and Engineering Conference (ICSEC).

[32]  Boonlert Watjatrakul,et al.  Interactive Technology and Smart Education Online Learning Adoption : Effects of Neuroticism , Openness to Experience , and Perceived Values , 2016 .

[33]  Marco Torchiano,et al.  Open data quality measurement framework: Definition and application to Open Government Data , 2016, Gov. Inf. Q..

[34]  Yannis Charalabidis,et al.  A taxonomy of open government data research areas and topics , 2016, J. Organ. Comput. Electron. Commer..

[35]  Yogesh Kumar Dwivedi,et al.  Acceptance and use predictors of open data technologies: Drawing upon the unified theory of acceptance and use of technology , 2015, Gov. Inf. Q..

[36]  Sören Auer,et al.  A systematic review of open government data initiatives , 2015, Gov. Inf. Q..

[37]  Allison W. Pearson,et al.  Five-factor model personality traits as predictors of perceived and actual usage of technology , 2015, Eur. J. Inf. Syst..

[38]  Jordan Shropshire,et al.  Personality, attitudes, and intentions: Predicting initial adoption of information security behavior , 2015, Comput. Secur..

[39]  B. Wirtz,et al.  Open Government: Origin, Development, and Conceptual Perspectives , 2015 .

[40]  Stefano Taddei,et al.  Privacy, trust and control: Which relationships with online self-disclosure? , 2013, Comput. Hum. Behav..

[41]  Anastasios A. Economides,et al.  How student's personality traits affect Computer Based Assessment Acceptance: Integrating BFI with CBAAM , 2012, Comput. Hum. Behav..

[42]  Efthimios Tambouris,et al.  A classification scheme for open government data: towards linking decentralised data , 2011, Int. J. Web Eng. Technol..

[43]  Xiaojun Zhang,et al.  'Just What the Doctor Ordered': A Revised UTAUT for EMR System Adoption and Use by Doctors , 2011, 2011 44th Hawaii International Conference on System Sciences.

[44]  Dong Hee Shin,et al.  Understanding User Acceptance of DMB in South Korea Using the Modified Technology Acceptance Model , 2009, Int. J. Hum. Comput. Interact..

[45]  A. Parasuraman,et al.  The effects of the dimensions of technology readiness on technology acceptance: An empirical analysis , 2008 .

[46]  Robert F. Easley,et al.  Research Note - How Does Personality Matter? Relating the Five-Factor Model to Technology Acceptance and Use , 2008, Inf. Syst. Res..

[47]  James C. McElroy,et al.  Dispositional Factors in Internet Use: Personality Versus Cognitive Style , 2007, MIS Q..

[48]  Paul M. Brunet,et al.  Is shyness context specific? Relation between shyness and online self-disclosure with and without a live webcam in young adults , 2007 .

[49]  Paul T. Costa,et al.  Personality in Adulthood: A Five-Factor Theory Perspective , 2005 .

[50]  Hengdong Yang,et al.  The Role of Personality Traits in UTAUT Model under Online Stocking , 2005 .

[51]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[52]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[53]  E. Levine,et al.  Personality structure: a culture-specific examination of the five-factor model , 1995 .

[54]  I. Ajzen The theory of planned behavior , 1991 .

[55]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[56]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[57]  H. Eysenck Biological Basis of Personality , 1963, Nature.

[58]  Niels Bjørn-Andersen,et al.  The Sustainable Value of Open Government Data , 2019, J. Assoc. Inf. Syst..

[59]  Stefan Pfattheicher,et al.  Honesty-Humility Under Threat: Self-Uncertainty Destroys Trust Among the Nice Guys , 2018, Journal of personality and social psychology.

[60]  Albert Meijer,et al.  Utilization of open government data: A systematic literature review of types, conditions, effects and users , 2017, Inf. Polity.

[61]  M. S. Hershcovisa,et al.  Organizational Behavior and Human Decision Processes , 2017 .

[62]  Ricardo Buettner,et al.  Personality as a predictor of Business Social Media Usage: an Empirical Investigation of Xing Usage Patterns , 2016, PACIS.

[63]  Augusto Gnisci,et al.  Construct validation of the Use, Abuse and Dependence on the Internet inventory , 2011, Comput. Hum. Behav..

[64]  Stephanie C Payne,et al.  A meta-analytic examination of the goal orientation nomological net. , 2007, The Journal of applied psychology.

[65]  A. Tellegen,et al.  An alternative "description of personality": the big-five factor structure. , 1990, Journal of personality and social psychology.

[66]  L. A. Pervin Personality: Theory and Research , 1984 .

[67]  R. Cattell Personality and mood by questionnaire. , 1973 .