Understanding Challenges of Applying Enterprise Architecture in Public Sectors: A Technology Acceptance Perspective

Guo, Hong; Li, Jingyue; Gao, Shang

doi:10.1109/edocw.2019.00020

Cited by 12 publications

(10 citation statements)

References 20 publications

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“…Technology has become indispensable, as it is involved in strategy implementation, varied system integration and development of business processes (Hafsi and Assar, 2016). In developed countries such as the USA, Denmark, Norway, Ireland and Finland, the implementation of EA has been on the rise (Dang and Pekkola, 2017a; Guo et al , 2019; Seppänen, 2014; Syynimaa, 2017; Jnr and Petersen, 2022). In fact, EA is mandatory for public sector organizations in Finland and the USA, while in Korea, EA is institutionalized by the Enactment of Efficient Introduction and Operation of Information System Act 2005 (Lemmetti and Pekkola, 2012).…”

Section: Introductionmentioning

confidence: 99%

Factors of organizational adoption of enterprise architecture in Malaysian public sector: a multi group analysis

Ahmad

Drus

Kasim

2022

JSIT

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Purpose The relevant importance of enterprise architecture (EA) to an organization has gained the attention of the public sector. However, its adoption rate remains slow on the uptake. Thus, this study aims to investigate the various factors associated with adoption intention based on the technological, organizational and environmental framework for federal and state types of public organizations to provide greater predictive accuracy and relevance of EA adoption in Malaysia’s public sector (MPS) context. Design/methodology/approach An empirical study was conducted through an online survey in Malaysia. Based on 255 samples from public organizations throughout Malaysia, a multigroup analysis with partial least square structural equation modeling was performed to identify the respective influencing factors for adopting EA by federal and state organizations in the Malaysian public sector. Findings Five organizational factors (clear communication, normative pressure, expected benefit, good governance and organization size) and two environmental factors (coercive pressure and mimetic pressure) were found to be significant factors influencing adoption intention for EA. Additionally, clear communication and coercive pressure were noted to be significant factors influencing adoption for both federal and state organizations. Other significant factors for federal organizations include expected benefit and normative pressure, whereas for state organizations, another significant influencing factor was good governance. The predictive accuracy for federal organizations was slightly higher at 74.6% than that of state organizations, that is, at 65%. Research limitations/implications These findings imply that federal and state organizations respond to different factors that motivate their intention to adopt EA. These findings guide future intentional practice and ensure greater motivation for EA adoption. Practical implications The identification of specific factors that matter to the federal and state public organizations in driving intention to adopt EA in this study has provided significant information that could help in effective decision-making process for these organizations. Common strategies that emphasize on clear communication and coercive pressure can be applied to address EA adoption processes for both federal and state public organizations. Further to that, more specified strategies such as highlighting expected EA benefits and instilling good governance work more effectively for federal and state, respectively. Originality/value This study has provided a more extensive view of EA adoption in MPS by differentiating the discerning factors based on the technological–organizational–environmental framework significant for federal and state types of organizations. Hence, this could help in formulating strategies specified to the organization type and ensure greater success in EA adoption in both federal and state organizations.

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Section: Introductionmentioning

confidence: 99%

Factors of organizational adoption of enterprise architecture in Malaysian public sector: a multi group analysis

Ahmad

Drus

Kasim

2022

JSIT

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“…TAM was developed from the Theory of Reasoned Action (TRA) by Ajzen and Fishbein (1980) by Davis (1989) to investigate users' acceptance of deployed IS. In EA context TAM has been employed to examine EA acceptance in organizations (Guo et al, 2019;Jonnagaddala et al, 2020;Lee et al, 2015;Närman et al, 2012). Thus, this study employed TAM as seen in Fig.…”

Section: Research Model and Hypotheses Developmentmentioning

confidence: 99%

Validation of a Developed Enterprise Architecture Framework for Digitalisation of Smart Cities: a Mixed-Mode Approach

Anthony

Petersen

2022

J Knowl Econ

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To support smart cities in aligning information technology (IT) and business strategies to achieve urban digitalization, this study aims to present an Enterprise Architecture Framework (EAF) to facilitate the digitalization of urban environments. Technology Acceptance Model (TAM) was employed to design a research model, and a mixed-mode methodology was employed. Quantitative data from survey questionnaires was used to gather data from practitioners in enterprises within Norway and Ireland that currently adopt Enterprise Architecture (EA) in a smart city project to empirically validate the developed EAF. Additionally, the developed EAF layers were validated through a qualitative focus group workshop with participants that utilize the developed EAF to provide digital services in smart cities. The findings suggest that the developed EAF can aid enterprises that provided digital services in identifying and assessing their digitalization initiatives and how EA benefits can be realized. Drawing on the TAM, the developed research model presents factors that influence practitioner’s adoption of EA towards the digitalization of urban environments. More importantly, this study provides empirically validated research on EAF adoption which is scarce.

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“…TAM was introduced by Davis (1989) as an adoption of technology model for predicting user acceptance of technology grounded on two variables, perceived ease of use and perceived usefulness which are theorized to be fundamental factors of user acceptance. Also, TAM is an adaptation of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA) which are other widely employed social psychology model that focuses on the factors that influences user behavior (Guo et al, 2019). According to TAM users incline to use or not utilize an application to the degree, they believe it will aid them to achieve their job better (Bernaert et al, 2014).…”

Section: Prior Enterprise Adoption Theories Employed In Ea Researchmentioning

confidence: 99%

“…One of such models is the Technology Acceptance Model (TAM), which is employed to evaluate user's acceptance of new technology. TAM has previously been employed to assess the adoption of EA in different domains such as application usage (Närman et al, 2012), building information modeling (Lee et al, 2015), security policy, e-government (Guo et al, 2019), e-health (Jonnagaddala et al, 2020), etc. TAM is grounded based on two constructs perceived usefulness and perceived ease of use (Närman et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Using an extended technology acceptance model to predict enterprise architecture adoption in making cities smarter

Anthony

Petersen

2022

Environ Syst Decis

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Presently cities are undergoing changes and transformations due to the adoption of information and communications technology. Enterprise Architecture (EA) is one of the approaches adopted by practitioners and researchers to facilitate smart city development as it can enhance the effectiveness of cities’ digital resources and sustainability capabilities. But, despite several literature on EA, studies on the adoption of EA to improve the sustainability of cities are still at the early stage. Besides, there are fewer studies that provided evidence on the adoption of EA to make cities sustainable grounded on established theoretical models and quantitative data. Therefore, this study aims to provide an understanding on the adoption of EA by different practitioners involved in a smart city project. Knowledge transfer and support services are integrated as new external variables needed to improve practitioners’ behavior intention and actual adoption of EA in making cities smarter. A model is developed grounded on an extension of Technology Acceptance Model (TAM), and data were collected via a cross-country survey. Partial least squares-structural equation modeling was employed to analyze the data. Findings from this study offer implications for research and practice and provide opportunities for future research.

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Understanding Challenges of Applying Enterprise Architecture in Public Sectors: A Technology Acceptance Perspective

Cited by 12 publications

References 20 publications

Factors of organizational adoption of enterprise architecture in Malaysian public sector: a multi group analysis

Factors of organizational adoption of enterprise architecture in Malaysian public sector: a multi group analysis

Validation of a Developed Enterprise Architecture Framework for Digitalisation of Smart Cities: a Mixed-Mode Approach

Using an extended technology acceptance model to predict enterprise architecture adoption in making cities smarter

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