Opportunities and challenges to improve accounting and accountability of Corporate Social Responsibility with artificial intelligence: insights from scientific mapping: Oportunidades y desafíos para mejorar con inteligencia artificial la contabilidad y los reportes de Responsabilidad Social Empresarial: perspectivas desde el mapeo científico

Taoer Yang

doi:10.6018/rcsar.584771

Autores/as

Taoer Yang Xiamen University, Xiamen, Fujian-P.R. CHINA https://orcid.org/0009-0008-7498-941X

DOI: https://doi.org/10.6018/rcsar.584771

Palabras clave: Inteligencia artificial, Mapeo científico, Bibliometría, Responsabilidad social empresarial, Contabilidad, Reportes de cuentas

Agencias de apoyo

National Social Science Foundation of China (20VHJ007)

Resumen

Este artículo aplica bibliometría como marco analítico para explorar las potenciales aplicaciones de las herramientas emergentes de inteligencia artificial (IA) para mejorar la contabilidad y los reportes de responsabilidad social empresarial (RSE). El análisis bibliométrico mapeó tendencias científicas e identificó temas emergentes relacionados con la IA, la contabilidad/reportes de cuentas y la RSE. Las oportunidades y desafíos de la IA para promover la transparencia, la toma de decisiones informadas y la participación de las partes interesadas se analizan en el contexto de redes temáticas y diagramas estratégicos que ilustran los hallazgos de la investigación. Los resultados indican que las tecnologías de IA emergentes todavía son especializadas y periféricas a la investigación central en RSE, pero existen oportunidades para mejorar la contabilidad de la RSE generando informes de RSE automáticos y más confiables con modelos de lenguaje grandes (LLM) y mediante la aplicación de IA inspirada en procesos biológicos para una toma de decisiones óptima. El aprendizaje automático y el aprendizaje profundo, a su vez, se pueden aplicar para comprender las actitudes de las partes interesadas y para la auditoría algorítmica, promoviendo así el compromiso de las partes interesadas y aumentando la responsabilidad de la RSE. El estudio también analiza los posibles riesgos y sesgos que pueden surgir al implementar tecnologías de IA para la contabilidad/reportes de cuentas de la RSE.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

Abu Zayyad, H. M., Obeidat, Z. M., Alshurideh, M. T., Abuhashesh, M., Maqableh, M., & Masa’deh, R. E. (2021). Corporate social responsibility and patronage intentions: The mediating effect of brand credibility. Journal of Marketing Communications, 27(5), 510-533. https://doi.org/10.1080/13527266.2020.1728565

Agarwal, A., Beygelzimer, A., Dudík, M., Langford, J., & Wallach, H. (2018). A reductions approach to fair classification. In International Conference on Machine Learning (pp. 60-69). Stockholm, Sweden, PMLR 80.

Amran, A., Lee, S. P., & Devi, S. S. (2014). The influence of governance structure and strategic corporate social responsibility toward sustainability reporting quality. Business Strategy and the environment, 23(4), 217-235. https://doi.org/10.1002/bse.1767

Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping. analysis. Journal of informetrics, 11(4), 959-975. https://doi.org/10.1016/j.joi.2017.08.007

Barauskaite, G., & Streimikiene, D. (2021). Corporate social responsibility and financial performance of companies: The puzzle of concepts, definitions and assessment methods. Corporate Social Responsibility and Environmental Management, 28(1), 278-287. https://doi.org/10.1002/csr.2048

Benton, M. C., Radziwill, N. M., Purritano, A. W., & Gerhart, C. J. (2018). Blockchain for supply chain: Improving transparency and efficiency simultaneously. Software Quality Professional, 20(3), 28-38.

Bibri, S. E., & Krogstie, J. (2018). The big data deluge for transforming the knowledge of smart sustainable cities: A data mining framework for urban analytics. In Proceedings of the 3rd International Conference on Smart City Applications (pp. 1-10). Tetouan, Morocco. https://doi.org/10.1145/3286606.3286788

Bollipelly, S. C. G., Sevugan, P., Venkatesan, R., & Sharmila, L. (2023). Blockchain-based messaging system for secure and private communication: Using blockchain and double AES encryption. In P. Swarnalatha & S. Prabu (Eds.), Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT (pp. 354-365). Pennsylvania: IGI Global. https://doi.org/10.4018/978-1-6684-8098-4.ch021

Boons, F., & Lüdeke-Freund, F. (2013). Business models for sustainable innovation: state-of-the-art and steps towards a research agenda. Journal of Cleaner production, 45, 9-19. https://doi.org/10.1016/j.jclepro.2012.07.007

Bouslah, K., Hmaittane, A., Kryzanowski, L., & M’Zali, B. (2023). CSR structures: Evidence, drivers, and firm value implications. Journal of Business Ethics, 185(1), 115-145. https://doi.org/10.1007/s10551-022-05219-6

Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry. Scientometrics, 22, 155-205. https://doi.org/10.1007/BF02019280

Camilleri, M. A. (2023). Artificial intelligence governance: Ethical considerations and implications for social responsibility. Expert Systems. July. https://doi.org/10.1111/exsy.13406

Carroll, A. B. (2015). Corporate social responsibility: The centerpiece of competing and complementary frameworks. Organizational dynamics, 44(2), 87–96. https://doi.org/10.1016/j.orgdyn.2015.02.002

Carroll, A. B. (2016). Carroll’s pyramid of CSR: taking another look. International Journal of Corporate Social Responsibility, 1(1), 1-8. https://doi.org/10.1186/s40991-016-0004-6

Claydon, J. (2011). A new direction for CSR: the shortcomings of previous CSR models and the rationale for a new model. Social Responsibility Journal, 7(3), 405-420. https://doi.org/10.1108/17471111111154545

Chang, S. E., Chen, Y. C., & Lu, M. F. (2019). Supply chain re-engineering using blockchain technology: A case of smart contract-based tracking process. Technological Forecasting and Social Change, 144, 1-11. https://doi.org/10.1016/j.techfore.2019.03.015

Cheng, C. L., & Kung, F. H. (2016). The effects of mandatory corporate social responsibility policy on accounting conservatism. Review of Accounting and Finance, 15(1), 2-20. https://doi.org/10.1108/RAF-12-2014-0135

Cheng, Y., Wang, Y., Zhao, W., Zhang, K., Cai, X., & Jiang, H. (2022). Virtually enhancing public engagement during the pandemic: Measuring the impact of virtual reality powered immersive videos on corporate social responsibility communication. Social Science Computer Review. July. https://doi.org/10.1177/08944393221111482

Choi, T. M., & Ouyang, X. (2021). Initial coin offerings for blockchain based product provenance authentication platforms. International Journal of Production Economics, 233, 1-14. https://doi.org/10.1016/j.ijpe.2020.107995

Coelho, R., Jayantilal, S., & Ferreira, J. J. (2023). The impact of social responsibility on corporate financial performance: A systematic literature review. Corporate Social Responsibility and Environmental Management, 26(3):155-188. https://doi.org/10.1002/csr.2446

Cobo, M. J., López‐Herrera, A. G., Herrera‐Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for information Science and Technology, 62(7), 1382-1402. https://doi.org/10.1002/asi.21525

Cowgill, B., & Tucker, C. E. (2020). Algorithmic fairness and economics. Columbia Business School Research Paper. September. http://dx.doi.org/10.2139/ssrn.3361280

Coulter, N., Monarch, I., & Konda, S. (1998). Software engineering as seen through its research literature: A study in co‐word analysis. Journal of the American Society for Information Science, 49(13), 1206-1223. https://doi.org/10.1002/(SICI)1097-4571(1998)49:13<1206::AID-ASI7>3.0.CO;2-F

D’Cruz, P., Du, S., Noronha, E., Parboteeah, K. P., Trittin-Ulbrich, H., & Whelan, G. (2022). Technology, megatrends and work: Thoughts on the future of business ethics. Journal of Business Ethics, 180(3), 879-902. https://doi.org/10.1007/s10551-022-05240-9

Dawkins, J., & Lewis, S. (2003). CSR in stakeholde expectations: And their implication for company strategy. Journal of Business Ethics, 44, 185-193. https://doi.org/10.1023/A:1023399732720

De Bakker, F. G., Groenewegen, P., & Den Hond, F. (2005). A bibliometric analysis of 30 years of research and theory on corporate social responsibility and corporate social performance. Business & society, 44(3), 283-317. https://doi.org/10.1177/0007650305278086

Dubbink, W., Graafland, J., & Van Liedekerke, L. (2008). CSR, transparency and the role of intermediate organisations. Journal of business ethics, 82, 391-406. https://doi.org/10.1007/s10551-008-9893-y

Dawkins, J., & Lewis, S. (2003). CSR in stakeholde expectations: And their implication for company strategy. Journal of Business Ethics, 44, 185-193. https://doi.org/10.1023/A:1023399732720

Dong, X., Wen, X., Wang, K., & Cai, C. (2022). Can negative media coverage be positive? When negative news coverage improves firm financial performance. Journal of Business & Industrial Marketing, 37(6), 1338-1355. https://doi.org/10.1108/JBIM-01-2021-0038

Ezzi, F., Jarboui, A., & Mouakhar, K. (2023). Exploring the relationship between blockchain technology and corporate social responsibility performance: Empirical evidence from European firms. Journal of the Knowledge Economy, 14(2), 1227-1248. https://doi.org/10.1007/s13132-022-00946-7

Etter, M., Morsing, M., & Castello, I. (2011, October). Barriers to dialogue-organizational challenges for CSR communication in social media. In CSR Communication Conference (pp. 1-14). Amsterdam, Netherlands.

Ebinger, F., & Omondi, B. (2020). Leveraging digital approaches for transparency in sustainable supply chains: A conceptual paper. Sustainability, 12(15), 6129. https://doi.org/10.3390/su12156129

Fan, B., Lv, L., & Han, G. (2022). Online platform’s corporate social responsibility for mitigating traffic risk: Dynamic games and governmental regulations in O2O food delivery industry. Computers & Industrial Engineering, 169, 108188. https://doi.org/10.1016/j.cie.2022.108188

Francisco, K., & Swanson, D. (2018). The supply chain has no clothes: Technology adoption of blockchain for supply chain transparency. Logistics, 2(1), 2. https://doi.org/10.3390/logistics2010002

Feng, Y., Zhu, Q., & Lai, K. H. (2017). Corporate social responsibility for supply chain management: A literature review and bibliometric analysis. Journal of Cleaner Production, 158, 296-307. https://doi.org/10.1016/j.jclepro.2017.05.018

Galiano-Coronil, A., Aguirre Montero, A., López Sánchez, J. A., & Díaz Ortega, R. (2024). Exploring social responsibility, social marketing and happiness using artificial intelligence, automated text analysis and correspondence analysis. Management Decision, 62(2), 549-574. https://doi.org/10.1108/MD-01-2023-0099

García-Sánchez, I.-M. (2021). Corporate social reporting and assurance: The state of the art: Información social corporativa y aseguramiento: el estado de la cuestión. Revista de Contabilidad - Spanish Accounting Review, 24(2), 241–269. https://doi.org/10.6018/rcsar.409441

Garvey, A. M., Kim, T., & Duhachek, A. (2023). Bad news? Send an AI. Good news? Send a human. Journal of Marketing, 87(1), 10-25. https://doi.org/10.1177/00222429211066972

Ghadge, A., Bourlakis, M., Kamble, S., & Seuring, S. (2023). Blockchain implementation in pharmaceutical supply chains: A review and conceptual framework. International Journal of Production Research, 61(19), 6633-6651. https://doi.org/10.1080/00207543.2022.2125595

Global Reporting Initiative (2020). Sustainability Disclosure Database. Working Paper. https://www.globalreporting.org/media/m22dl3o0/gri-data-legend-sustainability-disclosure-database-profiling.pdf

Govindan, K., Jafarian, A., & Nourbakhsh, V. (2019). Designing a sustainable supply chain network integrated with vehicle routing: A comparison of hybrid swarm intelligence metaheuristics. Computers & Operations Research, 110, 220-235. https://doi.org/10.1016/j.cor.2018.11.013

Guandalini, I. (2022). Sustainability through digital transformation: A systematic literature review for research guidance. Journal of Business Research, 148, 456-471. https://doi.org/10.1016/j.jbusres.2022.05.003

Gupta, M., Parra, C. M., & Dennehy, D. (2021). Questioning racial and gender bias in AI-based recommendations: Do espoused national cultural values matter?. Information Systems Frontiers, 24(5), 1-17. https://doi.org/10.1007/s10796-021-10156-2

Gutierrez-Bustamante, M., & Espinosa-Leal, L. (2022). Natural language processing methods for scoring sustainability reports—A study of Nordic listed companies. Sustainability, 14(15), 9165. https://doi.org/10.3390/su14159165

Harrer, S. (2023). Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine. EBioMedicine, 90, 1-12. https://doi.org/10.1016/j.ebiom.2023.104512

Hira, A., & Busumtwi-Sam, J. (2021). Improving mining community benefits through better monitoring and evaluation. Resources Policy, 73, 1-11. https://doi.org/10.1016/j.resourpol.2021.102138

Hongdao, Q., Bibi, S., Khan, A., Ardito, L., & Nurunnabi, M. (2019). Does what goes around really comes around? The mediating effect of CSR on the relationship between transformational leadership and employee’s job performance in law firms. Sustainability, 11(12), 1-19. https://doi.org/10.3390/su11123366

Ho, M. T., & Nguyen, H. K. T. (2023). From the eco-calypse to the infocalypse: the importance of building a new culture for protecting the infosphere. AI & Society, August, 1-3. https://doi.org/10.1007/s00146-023-01737-7

Iansiti, M., & Lakhani, K. R. (2017). The truth about blockchain. Harvard business review, 95(1), 118-127. https://hbr.org/2017/01/the-truth-about-blockchain

Jenkins, H. (2009). A ‘business opportunity’model of corporate social responsibility for small‐and medium‐sized enterprises. Business Ethics: A European Review, 18(1), 21-36. https://doi.org/10.1111/j.1467-8608.2009.01546.x

Kaab, A., Sharifi, M., Mobli, H., Nabavi-Pelesaraei, A., & Chau, K. W. (2019). Combined life cycle assessment and artificial intelligence for prediction of output energy and environmental impacts of sugarcane production. Science of the Total Environment, 664, 1005-1019. https://doi.org/10.1016/j.scitotenv.2019.02.004

Kazim, I., Wang, F., Nie, D., & Jameel Hussain, M. (2025). Can more able CEOs reduce the gap between internal and external CSR disclosures? Pueden los consejeros delegados más capaces reducir la brecha entre la información interna y externa sobre RSE?. Revista de Contabilidad - Spanish Accounting Review, 28(1), 84–95. https://doi.org/10.6018/rcsar.557871

Khan, M. T., Khan, N. A., Ahmed, S., & Ali, M. (2012). Corporate social responsibility (CSR)–definition, concepts and scope. Universal Journal of Management and Social Sciences, 2(7), 41-52.

Khalid, Z. M., & Zeebaree, S. R. (2021). Big data analysis for data visualization: A review. International Journal of Science and Business, 5(2), 64-75. https://doi.org/10.1109/ICRITO51393.2021.9596423

Kirst, R. W., Borchardt, M., de Carvalho, M. N. M., & Pereira, G. M. (2021). Best of the world or better for the world? A systematic literature review on benefit corporations and certified B corporations contribution to sustainable development. Corporate Social Responsibility and Environmental Management, 28(6), 1822-1839. https://doi.org/10.1002/csr.2160

Kong, D., & Liu, B. (2023). Digital technology and corporate social responsibility: evidence from China. Emerging Markets Finance and Trade, 59(9), 2967-2993. https://doi.org/10.1080/1540496X.2023.2199122

Luyet, V., Schlaepfer, R., Parlange, M. B., & Buttler, A. (2012). A framework to implement stakeholder participation in environmental projects. Journal of Environmental Management, 111, 213-219. https://doi.org/10.1016/j.jenvman.2012.06.026

Lennard, J. B., & Roberts, R. W. (2023). The accounting profession, corporate social responsibility, and ethics. In Marion B. & Charles H. C.(Eds.), Research Handbook on Accounting and Ethics (pp. 35-49). Massachusetts: Edward Elgar Publishing. https://doi.org/10.1002/9781119512356

Lindell, J. (2020). Analytics and big data for accountants. New York: John Wiley & Sons. https://doi.org/10.1002/9781119512356

Lima, F., De Carvalho, C. N., Acardi, M. B., Dos Santos, E. G., De Miranda, G. B., Maia, R. F., & Massote, A. A. (2019). Digital manufacturing tools in the simulation of collaborative robots: Towards industry 4.0. Brazilian Journal of Operations & Production Management, 16(2), 261-280. https://doi.org/10.14488/BJOPM.2019.v16.n2.a8

López, B., & Monfort, A. (2017). Creating shared value in the context of sustainability: The communication strategy of MNCs. In Okechukwu L. E. (Eds.), Corporate governance and strategic decision making (pp. 119-135). ‎London: Intechopen. https://doi.org/10.5772/intechopen.70177

Lu, A., Zhang, H., Zhang, Y., Wang, X., & Yang, D. (2023). Bounding the capabilities of large language models in open text generation with prompt constraints. In Findings of the Association for Computational Linguistics: EACL 2023 (pp. 1982-2008). Dubrovnik: Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-eacl.148

McCoy, R. T., Smolensky, P., Linzen, T., Gao, J., & Celikyilmaz, A. (2023). How much do language models copy from their training data? evaluating linguistic novelty in text generation using raven. Transactions of the Association for Computational Linguistics, 11, 652-670. https://doi.org/10.1162/tacl_a_00567

Mok, K. Y., Shen, G. Q., & Yang, J. (2015). Stakeholder management studies in mega construction projects: A review and future directions. International Journal of Project Management, 33(2), 446-457. https://doi.org/10.1016/j.ijproman.2014.08.007

Maccarrone, P., & Contri, A. M. (2021). Integrating corporate social responsibility into corporate strategy: The role of formal tools. Sustainability, 13(22), 12551. https://doi.org/10.3390/su132212551

Martínez-Ríos, F. O., Marmolejo-Saucedo, J. A., & Abascal-Olascoaga, G. (2020). A new protocol based on blockchain technology for transparent operation of corporate social responsibility. In García-Álvarez S. and Atristain-Suárez C. (Eds.), Strategy, Power and CSR: Practices and Challenges in Organizational Management (pp. 205-233). Leeds: Emerald Publishing Limited. https://doi.org/10.1108/978-1-83867-973-620201012

Meseguer-Sánchez, V., Gálvez-Sánchez, F. J., López-Martínez, G., & Molina-Moreno, V. (2021). Corporate social responsibility and sustainability. A bibliometric analysis of their interrelations. Sustainability, 13(4), 1-18. https://doi.org/10.3390/su13041636

Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics and firm performance: Findings from a mixed-method approach. Journal of Business Research, 98, 261-276. https://doi.org/10.1016/j.jbusres.2019.01.044

Milano, S., Taddeo, M., & Floridi, L. (2020). Recommender systems and their ethical challenges. AI & Society, 35, 957-967. https://doi.org/10.1007/s00146-020-00950-y

Minkkinen, M., Niukkanen, A., & Mäntymäki, M. (2022). What about investors? ESG analyses as tools for ethics-based AI auditing. AI & society, 1-15. https://doi.org/10.1007/s00146-022-01415-0

Muñoz-Leiva, F., Viedma-del-Jesús, M. I., Sánchez-Fernández, J., & López-Herrera, A. G. (2012). An application of co-word analysis and bibliometric maps for detecting the most highlighting themes in the consumer behaviour research from a longi-tudinal perspective. Quality & Quantity, 46, 1077-1095. https://doi.org/10.1007/s11135-011-9565-3

Narayan, R., & Tidström, A. (2019). Blockchains for accelerating open innovation systems for sustainability transitions. In M. Swan & J. Potts(Eds.), Blockchain Economics: Implications of Distributed Ledgers (pp. 85-101). London: World Scientific Publishing Europe Ltd. https://doi.org/10.1142/9781786346391_0005

Nguyen, T. H., Vu, Q. T., Nguyen, D. M., & Le, H. L. (2021). Factors influencing corporate social responsibility disclosure and its impact on financial performance: The case of Vietnam. Sustainability, 13(15), 8197. https://doi.org/10.3390/su13158197

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041

Ndayizigamiye, P., & Dube, S. (2019). Potential adoption of blockchain technology to enhance transparency and accountability in the public healthcare system in South Africa. In 2019 International Multidisciplinary Information Technology and Engineering Conference (IMITEC) (pp. 1-5). Vanderbijlpark, South Africa. https://doi.org/10.1109/IMITEC45504.2019.9015920

Ntoutsi, E., Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. E., ... & Staab, S. (2020). Bias in data‐driven artificial intelligence systems—An introductory survey. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 10(3), 1356. https://doi.org/10.1002/widm.1356

Ozdemir, S. (2023). Quick start guide to large language models: Strategies and best practices for using ChatGPT and other LLMs (pp. 56-68). Chicago: Addison-Wesley Professional.

Pai, V., & Chandra, S. (2022). Exploring factors influencing organizational adoption of artificial intelligence (AI) in corporate social responsibility (CSR) initiatives. Pacific Asia Journal of the Association for Information Systems, 14(5), 82-115. https://doi.org/10.17705/1pais.14504

Powell, L. M., Schwartz, J., & Hendon, M. (2021). The mobility open blockchain initiative: Identity, members, technologies, and future trends. In Surjit S., Anca D. J. (Eds.), Revolutionary applications of blockchain-enabled privacy and access control (pp. 99-118). Pennsylvania: IGI Global. https://doi.org/10.4018/978-1-7998-7589-5.ch005

Poláková-Kersten, M., Khanagha, S., van den Hooff, B., & Khapova, S. N. (2023). Digital transformation in high-reliability organizations: A longitudinal study of the micro-foundations of failure. The Journal of Strategic Information Systems, 32(1), 1-18. https://doi.org/10.1016/j.jsis.2023.101756

Popescu, C. R., & Banța, V. C. (2019). Performance evaluation of the implementation of the 2013/34/EU directive in Romania on the basis of corporate social responsibility reports. Sustainability, 11(9), 1-16. https://doi.org/10.3390/su11092531

Ratican, J., Hutson, J., & Wright, A. (2023). A Proposed Meta-Reality Immersive Development Pipeline: Generative AI Models and Extended Reality (XR) Content for the Metaverse. Journal of Intelligent Learning Systems and Applications, 15(1), 24-35. https://doi.org/10.4236/jilsa.2023.151002

Qu, L., Wu, S., Fei, H., Nie, L., & Chua, T. S. (2023). Layoutllm-t2i: Eliciting layout guidance from llm for text-to-image generation. In Proceedings of the 31st ACM International Conference on Multimedia (pp. 643-654). Ottawa, Canada. https://doi.org/10.1145/3581783.3612012

Roszkowska, P. (2021). Fintech in financial reporting and audit for fraud prevention and safeguarding equity investments. Journal of Accounting & Organizational Change, 17(2), 164-196. https://doi.org/10.1108/JAOC-09-2019-0098

Sahar, E., & Aripin, N. (2023). A Review of Global Reporting Initiative (GRI) Research with Sustainability Reporting: 1999-2020 dataset: Una revisión de la investigación de Global Reporting Initiative (GRI) con informes de sostenibilidad: conjunto de datos 1999-2020. Revista de Contabilidad-Spanish Accounting Review, 26(2), 274-290. https://orcid.org/0000-0001-5197-4751

Saveliev, A., & Zhurenkov, D. (2021). Artificial intelligence and social responsibility: the case of the artificial intelligence strategies in the United States, Russia, and China. Kybernetes, 50(3), 656-675. https://doi.org/10.1108/K-01-2020-0060

Sætra, H. S. (2021). A Framework for Evaluating and Disclosing the ESG Related Impacts of AI with the SDGs. Sustainability, 13(15), 1-16. https://doi.org/10.3390/su13158503

Şimşek, T., Öner, M. A., Kunday, Ö., & Olcay, G. A. (2022). A journey towards a digital platform business model: A case study in a global tech-company. Technological Forecasting and Social Change, 175, 1-17. https://doi.org/10.1016/j.techfore.2021.121372

Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of Big Data challenges and analytical methods. Journal of business research, 70, 263-286. https://doi.org/10.1016/j.jbusres.2016.08.001

Shum, H. Y., He, X. D., & Li, D. (2018). From Eliza to XiaoIce: challenges and opportunities with social chatbots. Frontiers of Information Technology & Electronic Engineering, 19, 10-26. https://doi.org/10.1631/FITEE.1700826

Smuha, N. A. (2019). The EU approach to ethics guidelines for trustworthy artificial intelligence. Computer Law Review International, 20(4), 97-106. https://doi.org/10.9785/cri-2019-200402

Srivastava, S., Vergin Raja Sarobin, M., Anbarasi, J., & Sankaran, N. (2021). Text sentiment analysis using artificial intelligence techniques. In Thampi, S.M., Gelenbe, E., Atiquzzaman, M., Chaudhary, V., & Li, KC. (Eds.), Advances in Computing and Network Communications (pp. 491-502). Singapore: Springer. https://doi.org/10.1007/978-981-33-6987-0_40

Stubbs, W., & Higgins, C. (2018). Stakeholders’ perspectives on the role of regulatory reform in integrated reporting. Journal of Business Ethics, 147, 489-508. https://doi.org/10.1007/s10551-015-2954-0

Stahl, B. C., Antoniou, J., Bhalla, N., Brooks, L., Jansen, P., Lindqvist, B., Wright, D. (2023). A systematic review of artificial intelligence impact assessments. Artificial Intelligence Review, 56(11), 12799-12831. https://doi.org/10.1007/s10462-023-10420-8

Suchacka, M. (2020). Corporate digital responsibility-A new dimension of the human-Technology relations. System Safety: Human-Technical Facility-Environment, 2(1), 1-8. https://doi.org/10.2478/czoto-2020-0001

Svanberg, J., Ardeshiri, T., Samsten, I., Öhman, P., Neidermeyer, P. E., Rana, T., Semenova, N. & Danielson, M. (2022). Corporate governance performance ratings with machine learning. Intelligent Systems in Accounting, Finance and Management, 29(1), 50-68. https://doi.org/10.1002/isaf.1505

Swan, M. (2015). Blockchain thinking: The brain as a decentralized autonomous corporation [commentary]. IEEE Technology and Society Magazine, 34(4), 41-52. https://doi.org/10.1109/MTS.2015.2494358

Székely, F., & Knirsch, M. (2005). Responsible leadership and corporate social responsibility: Metrics for sustainable performance. European Management Journal, 23(6), 628-647. https://doi.org/10.1016/j.emj.2005.10.009

Talpur, S., Nadeem, M., & Roberts, H. (2023). Corporate social responsibility decoupling: a systematic literature review and future research agenda. Journal of Applied Accounting Research. January. https://doi.org/10.1108/JAAR-08-2022-0223

Tang, S., & Higgins, C. (2022). Do not forget the “how” along with the “what”: Improving the transparency of sustainability reports. California Management Review, 65(1), 44-63. https://doi.org/10.1177/0008125622109487

Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., ... & Fuso Nerini, F. (2020). The role of artificial intelligence in achieving the Sustainable Development Goals. Nature communications, 11(1), 1-10. https://doi.org/10.1038/s41467-019-14108-y

Wach, K., Duong, C.D., Ejdys, J., Kazlauskaitė, R., Korzynski, P., Mazurek, G., Paliszkiewicz, J., & Ziemba, E. (2023). The dark side of generative artificial intelligence: A critical analysis of controversies and risks of ChatGPT. Entrepreneurial Business and Economics Review, 11(2), 7-24. https://doi.org/10.15678/EBER.2023.110201

Wang, H., Tong, L., Takeuchi, R., & George, G. (2016). Corporate social responsibility: An overview and new research directions: Thematic issue on corporate social responsibility. Academy of Management journal, 59(2), 534-544. https://doi.org/10.5465/amj.2016.5001

Xie, H., Zhang, Y., Wu, Z., & Lv, T. (2020). A bibliometric analysis on land degradation: Current status, development, and future directions. Land, 9(1), 1-37. https://doi.org/10.3390/land9010028

Yao S. and B. Huang (2017). Beyond parity: Fairness objectives for collaborative filtering. In Conference on Neural Information Processing Systems (pp. 2925–2934). California, United States.

Ye, N., Kueh, T. B., Hou, L., Liu, Y., & Yu, H. (2020). A bibliometric analysis of corporate social responsibility in sustainable development. Journal of Cleaner Production, 272, 1-15. https://doi.org/10.1016/j.jclepro.2020.122679

Zhan, Y., Chung, L., Lim, M. K., Ye, F., Kumar, A., & Tan, K. H. (2021). The impact of sustainability on supplier selection: A behavioural study. International Journal of Production Economics, 236, 1-37. https://doi.org/10.1016/j.ijpe.2021.108118

Zhao, L., Yang, M. M., Wang, Z., & Michelson, G. (2023a). Trends in the dynamic evolution of corporate social responsibility and leadership: A literature review and bibliometric analysis. Journal of Business Ethics, 182(1), 135-157. https://doi.org/10.1007/s10551-022-05035-y

Zhao, W., Cheng, Y., & Lee, Y. I. (2023b). Exploring 360-degree virtual reality videos for CSR communication: An integrated model of perceived control, telepresence, and consumer behavioral intentions. Computers in Human Behavior, 144, 1-11. https://doi.org/10.1016/j.chb.2023.107736

Zhukova, G. S., Dolbik-Vorobey, T. A., Ostrovskaya, N. V., Burlankov, P. S., & Sh, K. N. (2020). Digital technologies for implementing corporate social responsibility. Bulletin of the National Academy of Sciences of the republic of Kazakhstan, 2, 99-105. https://doi.org/10.32014/2020.2518-1467.47

Oportunidades y desafíos para mejorar con inteligencia artificial la contabilidad y los reportes de Responsabilidad Social Empresarial: perspectivas desde el mapeo científico