Accounting Information Systems and Influencing Factors: A Research Review Using Bibliometric Method

1. Introduction

Accounting is an essential component of economic and financial management systems, playing a proactive role in managing, operating, and controlling the production and business activities of organizations and enterprises. Corporate accounting is crucial in providing accounting information that supports managerial and financial operations, serving as the foundation for financial decision-making and strategic direction by business owners, government agencies, business partners, investors, and other stakeholders.

The Accounting Information System (AIS) maintains and generates accounting information used by organizations to analyze, evaluate, plan, and diagnose activities and financial conditions (Romney, Steinbart, Mula, McNamara, & Tonkin, 2012). Several studies have analyzed factors affecting information quality, such as the research by DeLone and McLean (1992), which indicates that AIS quality heavily depends on input quality. However, research findings on factors affecting AIS quality differ. Ismail (2009) identified three influencing factors: managerial accounting knowledge, effectiveness of software provider consultation, and the effectiveness of consultancy from accounting firms. Conversely, research by Hajiha (2011) highlighted three additional factors: managers' knowledge of IT and accounting, the use of experts, and organizational size. Anggraeni and Winarningsih (2021) conducted research involving 72 participants, including general managers, accounting and finance directors, and accounting and finance staff from a four-star hotel in Bandung, Indonesia, demonstrated that the organization's institutional framework significantly impacts the quality of AIS implementation, directly and indirectly supporting the production of quality accounting information.

In Vietnam, several studies have examined factors influencing AIS quality. Research by Liên (2012) identified 13 detailed influencing factors, including human resource policies, the supervisory environment, corporate culture, quality control, change management, ERP process quality, equipment, infrastructure, system testing, training, employee participation, data quality, project team capabilities, and top management commitment. Hạnh (2014) identified three factors: employee participation, technological knowledge, and executive commitment. Meanwhile, Thuyên (2017) highlighted organizational structure, culture, and commitment, indicating AIS quality positively influences the quality of accounting information. Research by Nguyệt (2019) pointed out two primary influencing factors: organizational culture and transformational leadership. Huy and Phuc (2021) investigated the relationship between Emotional Intelligence (EI), Blockchain Technology application (BLO), and AIS effectiveness using Structural Equation Modeling on survey data from 412 participants, confirming the significance of blockchain technology application in AIS effectiveness. NGO, LUU, and TRUONG (2021) analyzed the impact of internal control on accounting information quality in Vietnamese paper manufacturing enterprises, with data collected via emails and interviews with managers, staff, and accountants from 56 companies. Their results indicate that the control of the environment positively affects accounting information quality, including AIS and internal control processes.

In summary, previous research identified multiple factors influencing AIS quality, including managerial commitment, managerial accounting knowledge, data quality, and the effectiveness of external consultant advice. This study aims to comprehensively review factors influencing AIS based on the Scopus database using the PRISMA method for systematic information synthesis. Key questions addressed include identifying prominent publishing countries, journals, leading authors in quantity and influence, and determining the most prominent keywords in evaluating factors affecting management information systems.

2. Data source and Methodology

2.1. Search Strategy

In this study, publications on accounting information systems (AIS) were initially examined using bibliometric analysis. Bibliometric analysis involves examining characteristics of scientific research on a specific topic, such as authors, author affiliations, countries, and citation networks. In the initial stage, a search was conducted using the keyword "accounting information systems" in journals indexed by the Scopus database, and relevant publications were compiled. The data collected from this search were categorized and analyzed using Vosviewer software, a widely used tool designed for visual mapping analysis, allowing for systematic visual presentation of scientific literature.

For comprehensive coverage, the AIS literature search was performed without field restrictions ("All fields") in March 2024, using articles visible in the Scopus database. The literature search specifically targeted journal articles within accounting-related research fields, including accounting information systems, management accounting, accounting information quality, and accounting information. Journal articles were selected as they are considered more credible, concise, and thorough compared to other information sources (Ramos‐Rodríguez & Ruíz‐Navarro, 2004). The specific search terms utilized were "Accounting information systems" AND ("Determination" OR "Impact"). Publications containing these search terms in their titles, abstracts, and keywords were identified. The research period covered thirty years, from 1996 to February 2025, to capture current trends and factors influencing AIS quality.

A literature review methodology was preferred for this study. The Scopus database was selected due to its ease of data compilation, comprehensive journal coverage, and extensive usage in academic research. Additionally, Scopus includes numerous accounting-related journals, ensuring sufficient data availability. Identifying research areas through bibliometric analysis helps in tracking the scientific development, structure, and evolution within the field.

2.2. Literature identification process

The relevant literature for this study was systematically identified through inclusion and exclusion criteria, applying a structured methodology consisting of four distinct stages as illustrated in Figure 1. This methodological framework is adapted from the Preferred Reporting Items for Systematic Literature Review and Meta-Analysis (PRISMA) guidelines developed by Moher, Liberati, Tetzlaff, and Altman (2009). As depicted in Stage One of Figure 1, the initial search conducted within the Scopus database retrieved 549 documents from peer-reviewed journals and conference proceedings. The subsequent phase, Stage Two, focused on removing duplicate records. This screening process was efficiently managed using the duplicate removal feature available in Microsoft Excel, resulting in the identification and removal of 62 duplicate documents, thus reducing the total from 549 to 487 records. In Stage Three, these 487 documents underwent further screening based on a detailed examination of their titles and abstracts. The purpose of this stage was to retain articles directly related to factors influencing the effectiveness and quality of Accounting Information Systems. Publications written in languages other than English, or not clearly aligned with the research theme, were excluded. Consequently, 76 documents did not satisfy these criteria and were removed, leaving 411 articles eligible for further analysis. Stage Four involved a comprehensive assessment of the full text of these 411 articles to confirm their eligibility based on predefined inclusion criteria. In this thorough review, 49 documents did not meet the necessary criteria and were subsequently excluded. Ultimately, after the full-text review, a final total of 348 articles remained, forming the basis for the in-depth analysis conducted in this study.

Figure 1: Literature search process

Source: Author’s own

3. Bibliometric Analysis, Results, and Discussion

The systematic literature search from the Scopus database, spanning from 1996 to February  2025, identified a total of 348 scientific publications specifically related to the topic of "Accounting Information Systems" (AIS). Figure 2 presents a detailed annual distribution of these publications, demonstrating a clear upward trend over the period analyzed. The highest number of publications occurred in both 2019 and 2020, each with 45 articles. These years represent a peak in research activity within the domain of accounting information systems. As figure 2, a notable increase in publication activity was observed in recent years, specifically with 42 publications in 2024, 41 in 2023, and 36 in 2022, highlighting continued interest and steady growth in the field in recent years. From 2017 onwards, the publication rate accelerated significantly, consistently exceeding 15 articles per year. This momentum reflects a growing academic interest and increasing research activities in AIS. Prior to 2015, the annual number of publications was relatively limited, indicating that AIS research gained substantial academic attention and expansion primarily after 2015. The relatively lower count of publications in 2025, currently at only 6, is likely because this study was conducted in February 2025, thus the data for the year is not yet fully available.

Figure 2: Distribution of 348 scientific publications from 1996 to February 2025

Source: Author’s analysis

3.1. Analysis of Countries Involved in Research

Table 1 presents the top 10 countries ranked by the quantity of published articles related to the Accounting Information System (AIS), alongside their total citations and citations per article (TC/Art). Indonesia leads with the highest number of publications (123 articles), followed by Jordan (39 articles) and Malaysia (29 articles). Although Indonesia has the highest article output, the average citation per article (7.11) is lower compared to other countries on the list. Although the United States produced fewer articles (19 publications) compared to Indonesia, Jordan, and Malaysia, its research achieved higher citation impacts (26.32 citations per article), reflecting greater international influence and recognition. Australia, although ranked last in terms of quantity with only 8 articles, possesses the highest average citation rate per article at 44.00, indicating substantial influence and research quality. Vietnam appears fourth in terms of article quantity, contributing 22 publications with an average citation rate of 8.09, suggesting moderate influence in the field. Countries like Jordan and Malaysia exhibit strong research productivity and notable citation rates (15.51 and 14.45 citations per article, respectively), underscoring their significant academic contributions to AIS studies.

Table 1: Top 10 ranking of countries by articles, and citations

*TC/Art: Total citations per article.

Source: Author’s analysis

3.2. Institute Distribution of Institutions

Table 2 lists the top 10 most influential institutions based on their research output in Accounting Information Systems (AIS). These institutions collectively account for a significant portion of the total publications in this field. Universitas Padjadjaran from Indonesia ranks first, contributing the highest number of publications (46 articles). It is followed by another Indonesian institution, Bina Nusantara University, with 20 publications, and Jadara University from Jordan, which contributed 13 publications. Malaysia's Universiti Teknologi MARA ranks fourth with 9 publications. Universitas Sumatera Utara from Indonesia occupies the fifth position, contributing 8 publications. Other notable institutions include Al-Zaytoonah University of Jordan with 7 publications and Instituto Politécnico do Porto from Portugal, Amman Arab University from Jordan, University of Economics Ho Chi Minh City from Vietnam, and Politeknik Negeri Medan from Indonesia, each contributing 6 publications.

Table 2: Top 10 Influential Institutions

Source: Author’s analysis

3.3. Most Influential Source Title

The retrieved 348 papers were published in 200 distinct journals and institutes, of which 10 had only a single publication throughout the examined period. Only journals with at least four publications related to Accounting Information Systems are displayed in Table 3. The Journal of Engineering and Applied Sciences (Asian Research Publishing Network) ranks first with 14 articles. This is followed by the International Journal of Accounting Information Systems published by Elsevier Inc, contributing 11 documents and holding a high H-Index of 65. The Journal of Theoretical and Applied Information Technology, published by Little Lion Scientific, has 9 documents and an H-Index of 44, highlighting its significant presence in the field. Notably, the journal Sustainability, despite having fewer articles (5 documents), possesses the highest H-Index (169), indicating a substantial impact on academic research. Other influential sources include Cogent Business and Management (7 articles), International Journal of Applied Business and Economic Research (6 articles, H-Index 24), and International Journal of Supply Chain Management (6 articles, H-Index 25). The Journal of Asian Finance, Economics, and Business (6 articles, H-Index 35) also contributes notably to this domain. 

Table 3: Top 15 sources ranked according to documents and h-Index

Source: Author’s analysis

3.4. Most cited publications of articles

To thoroughly understand research related to Accounting Information Systems (AIS) and influencing factors, it is essential to analyze the most cited documents, focusing on their methodologies and key findings. Nicolaou (2000) using quantitative empirical methods based on contingency theory, highlighted that organizational coordination and control significantly enhance the perceived effectiveness of AIS. Rom and Rohde (2007)conducted an extensive literature review, concluding that integrated AIS significantly improve management accounting practices, decision-making effectiveness, and overall organizational performance. Choe (1996) utilized quantitative analysis through surveys and regression methods, revealing managerial support and the maturity of the AIS as crucial factors influencing its performance. Similarly, M. Al-Okaily (2024) employed Structural Equation Modeling (SEM), based on the DeLone and McLean model, emphasizing that system quality, information quality, and user satisfaction are essential for AIS success.

Table 4: Top 10 most cited articles

Source: Author’s analysis

3.5. The most productive authors

Regarding the analysis of the most productive authors, the dataset revealed 317 distinct authors contributing to the 348 selected documents on Accounting Information Systems and their influencing factors. Table 5 identifies the ten authors with the highest number of publications and citations within the Scopus database. Susanto A. stands out as the most prolific author, contributing a total of 29 publications and accumulating 257 citations. Meiryani follows with 18 publications and a total of 172 citations. Both authors notably focus on the relationship between organizational factors, technological infrastructure, and the quality and effectiveness of AIS. Other prominent authors include Mulyani S. with 9 documents cited 76 times, and Napitupulu I.H. contributing 8 publications cited 72 times. Authors like Muda I. and Erlina, despite fewer publications (6 and 5, respectively), achieved relatively high citation impacts (98 and 77 citations, respectively). These findings suggest significant academic influence through their targeted studies on AIS-related influencing factors such as organizational control, internal control effectiveness, management support, and technological capability.

Table 5: Top 10 most productive authors with their h-Index

Source: Author’s analysis

3.6. Co-word analysis

According to Su and Lee (2010), keyword analysis is essential as keywords succinctly represent and summarize the core focus of research topics. Additionally, Van Eck and Waltman (2010) emphasized that keyword networks can visually illustrate conceptual connections, facilitating the understanding of knowledge structures within research domains. Over time, research themes often merge, evolve, and expand, highlighting the dynamic trends and boundaries within various academic disciplines. One effective approach for understanding these evolving themes is co-word analysis, a common bibliometric technique described (Callon, Courtial, & Laville, 1991). Co-word analysis involves counting the frequency with which pairs of keywords co-occur across publications. This method enables researchers to visually analyze and interpret interactions among frequently used terms, thereby identifying emerging patterns, relationships, and trends in specific research areas. Keywords selected by authors reveal central themes and research directions within a discipline. In this study, keyword co-occurrences derived from titles, abstracts, and author-provided keywords were analyzed. A total of 1,251 keywords were processed using VOSviewer software, with the 20 most frequently occurring keywords presented in Table 6. This analysis highlights the primary research themes and prominent topics within literature.

Table 6: Top 20 frequent keywords

*TLS: Total Link Strength

Source: Author’s analysis of Scopus

This research generated network maps displaying keyword co-occurrences across 348 articles. A minimum occurrence threshold of five was established, resulting in 51 keywords that met the criteria for analysis. The analysis identified four distinct clusters, which are illustrated in Figure 3. The total connection strength among these keyword nodes is 711. Figure 3 visualizes these 51 keywords in six clusters, each represented by distinct colors: red, green, blue, purple, aquamarine, and yellow, corresponding to clusters 1 through 6, respectively. Curved lines between nodes indicate the strength of relationships among keywords.

Figure 3: Network visualization map for co-occurring keywords

Source: Author’s analysis

Cluster 1 – Managerial Support and User Satisfaction: The red cluster is the largest and prominently features keywords such as "user satisfaction," "information quality," "top management support," and "systems quality." These keywords underline the central role managerial commitment and user perception play in shaping AIS effectiveness. Nicolaou (2000) provided empirical evidence that strong organizational coordination and top management involvement significantly enhance AIS success by improving both user satisfaction and the overall quality of information produced. Additionally, Choe (1996); (Muda, Asrina Waty, Roesli, & Nuradi, 2020) found that active managerial support and mature system implementation positively influence AIS performance outcomes. Furthermore, Ismail (2009) highlighted how effective consultation and support from senior management considerably impact the successful implementation and ongoing effectiveness of AIS, emphasizing that managerial commitment directly affects user acceptance and satisfaction levels. Thus, this cluster underscores the necessity of sustained managerial support and the critical importance of meeting user expectations to ensure optimal functionality and performance of accounting information systems.

Cluster 2 – Business Processes and Information Management: The green cluster focuses primarily on "business process," "enterprise resource planning (ERP)," and "information management." These keywords emphasize the crucial role of streamlined business processes and ERP systems integration in shaping AIS effectiveness. Rom and Rohde (2007) reviewed literature extensively, concluding that integrated AIS positively impacts managerial accounting, supports strategic decision-making, and enhances operational efficiency. Similarly, Grande et al. (2011)empirically supported the argument that effective AIS implementation significantly improves both financial and non-financial performance metrics in small and medium-sized enterprises (SMEs).

Cluster 3 – Internal Controls and Firm Performance: The blue cluster emphasizes keywords such as "internal control" and "firm performance," underscoring their critical role in determining AIS effectiveness. A. Al-Okaily et al. (2020) applied Structural Equation Modeling to highlight how effective internal control systems directly contribute to AIS success.

Cluster 4 – Technological Advancements and Decision-Making: Represented by the yellow cluster, this area highlights significant keywords including "AI," "software," "performance," and "supply chain." Prasad and Green (2015) emphasized the critical role of advanced technology integration in decision-making processes, significantly improving overall organizational performance through enhanced AIS.

Cluster 5 – Institutional Frameworks and Organizational Knowledge: The purple cluster focuses on keywords like "organizational performance" and "knowledge," highlighting organizational factors as influential determinants of AIS quality. Anggraeni and Winarningsih (2021)empirically showed the substantial impact of institutional frameworks and internal organizational knowledge on AIS quality.

Cluster 6 – Information Quality and Technology Infrastructure: Highlighted by the aquamarine cluster, this group prominently features keywords like "information quality," "data quality," and "information technology," emphasizing the foundational importance of technology infrastructure and data integrity in determining AIS outcomes. Xu (2003) provided empirical evidence that data quality directly impacts the reliability and usefulness of accounting information systems, confirming that accurate and reliable data are fundamental for effective decision-making within AIS contexts.

4. Discussion

In this paper, we applied systematic mapping using bibliometric analysis to address the main research question: What are the current publication trends and influencing factors in research on Accounting Information Systems (AIS)? To answer this, we analyzed bibliographic coupling of countries, institutions, and journals, examined authorship and citations, and performed keyword co-occurrence analysis using VOSviewer based on Scopus database sources. The key findings of this analysis are summarized as follows:

(1) The bibliographic coupling analysis by country indicated that Indonesia emerged as the leading country in AIS research, with the highest volume of publications. Jordan and Malaysia followed in terms of publication numbers. Interestingly, while Indonesia had the most publications, Australia and the United States exhibited significantly higher citation rates per article, reflecting their substantial influence within AIS research. Vietnam also emerged as a notable contributor in terms of the number of publications, indicating its active engagement in this field. . Connections among these countries indicate active international collaboration in AIS research, particularly between Indonesia, Jordan, and Malaysia.

(2) Regarding the most influential institutions, Universitas Padjadjaran (Indonesia) clearly stood out, contributing significantly to the total number of publications. Other notable institutions include Bina Nusantara University (Indonesia), Jadara University (Jordan), and Universiti Teknologi MARA (Malaysia). These institutions have consistently produced impactful research and maintained strong collaborative ties within the global AIS research community. Additionally, the University of Economics Ho Chi Minh City represented Vietnam, highlighting regional academic contributions and influence.

(3) In terms of influential journals, the analysis highlighted journals such as the Journal of Engineering and Applied Sciences, International Journal of Accounting Information Systems, and Sustainability as the leading publication outlets for AIS-related studies. The International Journal of Accounting Information Systems particularly showed strong scholarly impact, having both high publication counts and a significant H-index. Other prominent journals contributing to this field include Cogent Business and Management, Journal of Asian Finance Economics and Business, and International Journal of Supply Chain Management, collectively demonstrating that AIS research spans multiple disciplines, including management, finance, and technology.

(4) The analysis of the most influential publications identified Nicolaou (2000) and Rom and Rohde (2007) as highly cited studies that substantially shaped AIS literature. Nicolaou (2000) empirically demonstrated organizational coordination and managerial support as pivotal factors enhancing AIS effectiveness. Rom and Rohde (2007) provided a comprehensive review underscoring integration, information quality, and managerial accounting impacts as central themes. Other essential studies contributing influential findings included Choe (1996), Grande, Estébanez, and Colomina (2011), and Al-Okaily et al. (2017), who empirically validated factors such as internal controls, ERP systems, and user satisfaction significantly impacting AIS effectiveness.

(5) Keyword co-occurrence analysis provided critical insights into research trends and prominent themes within AIS literature. Recent years have emphasized managerial support, information quality, ERP integration, internal control systems, and technological advancements as core research areas. The emergence of keywords such as "user satisfaction," "information management," "internal control," "organizational knowledge," "artificial intelligence," and "data quality" highlights the evolving interest in exploring diverse yet interconnected influencing factors. These keyword trends suggest a dynamic research focus shifting towards integrating technological advancements and robust organizational practices to enhance AIS effectiveness.

5. Conclusion & Future research direction

This paper presented a systematic literature review on Accounting Information Systems and the influencing factors from the last 30 years (1996-2025). A total of 348 research articles from the Scopus database were screened and analyzed. The primary findings indicated that Susanto A. had the highest number of publications within this research domain. Additionally, the most cited publication was by Nicolaou (2000), highlighting organizational coordination and managerial support as pivotal factors in AIS effectiveness. The journals identified as most productive in AIS research were the Journal of Engineering and Applied Sciences, the International Journal of Accounting Information Systems, and the Journal of Theoretical and Applied Information Technology. Countries leading AIS research included Indonesia, Jordan, Malaysia, the United States, and Vietnam. The study utilized keyword co-occurrence and bibliographic coupling analyses, revealing six distinct clusters that highlighted core influencing factors, including managerial support, user satisfaction, internal control effectiveness, technological infrastructure, organizational processes, and institutional frameworks.

However, the current study also faces certain limitations. Primarily, the study’s results are confined to data extracted solely from the Scopus database. Thus, incorporating additional databases such as Web of Science or DOAJ might yield different findings. The keyword selection used for data extraction may also have influenced the resulting dataset, meaning alternative search queries might provide different outcomes. Moreover, the retrieved data encompassed numerous journals without any single journal emerging as significantly dominant, reflecting scattered publication sources. The study applied specific data mining criteria, including only peer-reviewed journal articles published in English, excluding conference proceedings, books, and review articles. Additionally, although bibliometric analysis provided structural insights, potential biases might arise during thematic identification and the naming of clusters. Furthermore, such methods do not differentiate between high-quality and lower-quality citations. Finally, the analysis primarily emphasized structural network relationships and did not incorporate sentiment analysis.

Author Contributions: All authors contributed to this research.

Funding: Not applicable.

Conflict of Interest: The authors declare no conflict of interest.

Informed Consent Statement/Ethics Approval: Not applicable.

Declaration of Generative AI and AI-assisted Technologies: This study has not used any generative AI tools or technologies in the preparation of this manuscript.