KnE Social Sciences

Published date: Sep 16 2025

Journal Title: KnE Social Sciences

Issue title: The Mercu Buana Ecobiz Energy International Conference: Sustainability and ESG Reporting in the Energy Sector

Pages: 83 - 91

DOI: 10.18502/kss.v10i21.19693

Swarmilah Harianiswarmilah@mercubuana.ac.idFaculty of Economics and Business, Universitas Mercu Buana, Jakarta

Hafiz Abdul Samee MalikSchool of International Studies, Universiti Utara Malaysia, Kedah Darul Aman

This research aims to identify the influence of expert systems (ES) on the efficiency of accounting information systems (AIS), which ultimately contributes to decision making sustainability (DMS) in the energy sector, such as saving energy and reducing carbon emissions. Using a quantitative approach, this research involved 127 decision-makers familiar with the efficient use of AIS. Data was collected through a self-completed questionnaire and validated using structural equation modelling (SEM) - PLS. The research results show that expert systems positively and significantly influence AIS efficiency in industrial companies in Indonesia, which in turn can impact DMS in the energy sector. However, technological vigilance did not moderate the relationship between expert systems and AIS efficiency. This study contributes to the AIS efficiency literature by identifying factors influencing AIS network efficiency and its benefits and validating the proposed model in the context of industrial companies. The results of this research serve as a guide to explain the importance of AIS efficiency, provide practical implications, and identify opportunities for future research in energy and sustainability.

Keywords: expert system, accounting information system, sustainable decisionmaking, energy efficiency, sustainability

[1] Yang X, Zhu C. Industrial Expert Systems Review: A Comprehensive Analysis of Typical Applications. IEEE Access. 2024;12:88558–84.

[2] Ioshchikhes B, Frank M, Elserafi G, Magin J, Weigold M. Developing Expert Systems for Improving Energy Efficiency in Manufacturing: A Case Study on Parts Cleaning. Energies. 2024;17(14):3417.

[3] Pawanr S, Gupta K. A Review on Recent Advances in the Energy Efficiency of Machining Processes for Sustainability. Energies. 2024;17(15):3659.

[4] Balcιoglu YS, Celik AA, Altιndag E. Artificial Intelligence Integration in Sustainable Business Practices: A Text Mining Analysis of USA Firms. Sustainability (Basel). 2024;16(15):6334.

[5] Masudin I, Restuputri DP, Amalia F, Oktiarso T. The role of smart technology, managerial initiatives and human factors on sustainable manufacturing: a case study of Indonesian oil and gas workers. Ergonomics. 2024 Dec;67(12):1884–908.

[6] Dolšak J, Hrovatin N, Zorić J. What Impacts the strength of perceived barriers to and drivers of energy efficiency in manufacturing SMEs? Heliyon. 2024 Jan;10(1):e24020.

[7] Miller DE, Eggleston B. Moral Theory and Climate Change. New York: Routledge; 2020. https://doi.org/10.4324/9781315205069.

[8] Qatawneh AM, Al-Okaily M. The mediating role of technological vigilance between IT infrastructure and AIS efficiency. J Open Innov. 2024;10(1):100212.

[9] Kaur R, Gabrijelčič D, Klobučar T. Artificial intelligence for cybersecurity: literature review and future research directions. Inf Fusion. 2023;97:101804.

[10] Qasaimeh G, Al-Gasaymeh A, Kaddumi T, Kilani Q. Expert Systems and Neural Networks and their Impact on the Relevance of Financial Information in the Jordanian Commercial Banks. In: IEEE (eds.) 2022 International Conference on Business Analytics for Technology and Security (ICBATS), pp. 1–7. USA: IEEE; 2022.

[11] Lutfi A, Al-Okaily M, Alsyouf A, Alrawad M. Evaluating the D&M IS Success Model in the Context of Accounting Information System and Sustainable Decision Making. Sustainability (Basel). 2022;14(13):8120.

[12] Hair J, Hult GM, Ringle MC, Sarstedt M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd ed. Los Angeles: Sage; 2017.

[13] O’brien RM. A Caution Regarding Rules of Thumb for Variance Inflation Factors. Qual Quant. 2007;41(5):673–90.

[14] Woolston A, Tu YK, Baxter PD, Gilthorpe MS. P65 A new index to assess the impact of collinearity in epidemiological research. J Epidemiol Community Health. 2010;64 Suppl 1:A59–59.

[15] Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate Data Analysis. 7th ed. Harlow: Pearson Education; 2013.

[16] Piepho H. An adjusted coefficient of determination (R2) for generalized linear mixed models in one go. Biometrical J. 2023;65(7).

[17] Chin WW, Newsted PR. Structural equation modeling analysis with small samples using Partial Least Squares. In: Hoyle R, editor. Statistical Strategies for Small Sample Research. Thousand Oaks: Sage; 1999. pp. 307–41.

[18] Li C, Chen Y, Shang Y. A review of industrial big data for decision making in intelligent manufacturing. Eng Sci Technol Int J. 2022;29:101021.

[19] Shaikh PH, Nor NB, Nallagownden P, Elamvazuthi I, Ibrahim T. A review on optimized control systems for building energy and comfort management of smart sustainable buildings. Renew Sustain Energy Rev. 2014;34:409–29.

[20] Lu X. Influence of financial accounting information transparency on supply chain financial decision-making. Heliyon. 2024 Jun;10(13):e33113.

[21] Nguyen HT, T R, Kweh QL, Tran PT, Tran Duong Minh H. Determinants of accounting information system effectiveness and moderating role of external consultants: Empirical research in the Ben Tre Province of Vietnam. Heliyon. 2024 Mar;10(7):e28847.

[22] Zhao J, Gómez Fari nas B. Artificial Intelligence and Sustainable Decisions. Eur Bus Organ Law Rev. 2023;24(1):1–39.

[23] Bressane A, Fengler FH, Medeiros LC, Urban RC, Negri RG. Enhancing energy sustainability of building projects through nature-based solutions: A fuzzy-based decision support system. Nat Based Solut. 2024;5:100107.

[24] Mondejar ME, Avtar R, Diaz HL, Dubey RK, Esteban J, Gómez-Morales A, et al. Digitalization to achieve sustainable development goals: Steps towards a Smart Green Planet. Sci Total Environ. 2021 Nov;794:148539.

[25] Handoyo S, Suharman H, Ghani EK, Soedarsono S. A business strategy, operational efficiency, ownership structure, and manufacturing performance: the moderating role of market uncertainty and competition intensity and its implication on open innovation. J Open Innov. 2023;9(2):100039.