امینی، علیرضا.، فتاحی، حمیدرضا.، و دولتشاه، پیمان. (1398). استراتژی‌های نوآوری، موفقیت کارآفرینانه و نقش میانجی ظرفیت جذب دانش. پژوهش‌های مدیریت منابع سازمانی، 9 (4)، 1-21.
بسطامی، رجب، منظری توکلی، حمداله و سلاجقه، سنجر. (1396). بررسی فناوری اطلاعات و ارتباطات و رابطه آن با جلوه‌های بهره‌وری سازمانی مبتنیبر برویکرد اجتماعی توسعه پایدار. مدیریت شهری و روستایی، 47 (18)، 207-224.
حشمدار، اکرم و کردی، مراد. (1401). بررسی اثربخشی سیستم‌های هوشمصنوعی در کارکردهای منابع انسانی. پژوهش‌های معاصر در علوم مدیریت و حسابداری، 12 (4)، 1-6.
خیاطیان، محمد صادق.، الیاسی، مهدی.، و طباطباییان، سید حبیب اله. (1395). الگوی پایداری شرکت‌های دانش‌بنیان در ایران. سیاست علم و فناوری، 9 (2)، 49-62.
روشن، سید علیقلی.، یعقوبی، نورمحمد.، و مومنی، امیررضا. (1400). کاربست هوشمصنوعی در بخش دولتی (مطالعه ای فرا ترکیب). فصلنامه انجمن علوم مدیریت ایران، 16 (61)، 117-145.
صفری، احرام، و انصاری، علی اصغر. (1401). شناسایی و رتبه‌بندی عوامل مؤثر بر پذیرش هوشمصنوعی در بخش دولتی و خصوصی.
مطالعات مدیریت کسب‌وکار هوشمند،
41 (11)، 222-254. (DOI):
10.22054/IMS.2022.66402.2131
محمدیان، محمود و رونقی، محمدحسین (1390) استراتژی‌ها و تکنیک‌های ارتقای برند: 50 روش کاربردی در برندینگ، تهران، نشر مهربان.
Acemoglu, D., & Restrepo, P. (2018).
Artificial intelligence, automation, and work. In The economics of artificial intelligence: An agenda (pp. 197-236). University of Chicago Press. Acemoglu, Daron and Restrepo, Pascual, Artificial Intelligence, Automation and Work (January 2018). NBER Working Paper No. w24196, Available at SSRN:
https://ssrn.com/abstract=3101994
Agarwal, R. (2020). Digital transformation: A path to economic and societal value.
Revista CEA,
6 (12), 9-12. DOI:
10.22430/24223182.1700
Agarwal, V., Mathiyazhagan, K., Malhotra, S., & Saikouk, T. (2022). Analysis of challenges in sustainable human resource management due to disruptions by Industry 4.0: an emerging economy perspective.
International Journal of Manpower,
43 (2), 513-541. DOI:
10.1108/IJM-03-2021-0192
Ahmadi, H. B., Kusi-Sarpong, S., & Rezaei, J. (2017). Assessing the social sustainability of supply chains using Best Worst Method.
Resources, Conservation and Recycling,
126 (8), 99-106. DOI:
10.1016/j.resconrec.2017.07.020
Alam, M. S., Dhar, S. S., & Munira, K. S. (2020). HR Professionals’ intention to adopt and use of artificial intelligence in recruiting talents.
Business Perspective Review,
2 (2), 15-30. DOI:
10.38157/business-perspective-review.v2i2.122
Alnamrouti, A., Rjoub, H., & Ozgit, H. (2022). Do strategic human resources and artificial intelligence help to make organisations more sustainable? evidence from non-governmental organisations.
Sustainability,
14 (12), 7327. DOI:
10.3390/su14127327
Amini, A., & Alimohammadlou, M. (2021). Toward equation structural modeling an integration of interpretive structural modeling and structural equation modeling.
Journal of Management Analytics,
8 (4), 693-714. DOI:
10.1080/23270012.2021.1881927
Amini A., Fatahi, H. & Dolatshah, P. (2020). Innovation strategies, entrepreneurial success and the role of absorption knowledge capacity, Researches of Management Organizational Resources, 9 (4), 1-21. (In Persian)
Ajmal, M. M., Khan, M., Hussain, M., & Helo, P. (2018). Conceptualizing and incorporating social sustainability in the business world.
International Journal of Sustainable Development & World Ecology,
25 (4), 327-339. DOI:
10.1080/13504509.2017.1408714
Babina, T., Fedyk, A., He, A., & Hodson, J. (2024). Artificial intelligence, firm growth, and product innovation.
Journal of Financial Economics,
151, 103745. DOI:
10.1016/j.jfineco.2023.103745
Babkin, A. V., Lipatnikov, V. S., & Muraveva, S. V. (2015). Assessing the impact of innovation strategies and R&D costs on the performance of IT companies.
Procedia-Social and Behavioral Sciences,
207, 749-758. DOI:
10.1016/j.sbspro.2015.10.153
Bag, S., Pretorius, J. H. C., Gupta, S., & Dwivedi, Y. K. (2021). Role of institutional pressures and resources in the adoption of big data analytics powered artificial intelligence, sustainable manufacturing practices and circular economy capabilities.
Technological Forecasting and Social Change,
163 (5), 120420. DOI:
10.1016/j.techfore.2020.120420
Banihashemi, T. A., Fei, J., & Chen, P. S. L. (2019). Exploring the relationship between reverse logistics and sustainability performance: A literature review.
Modern Supply Chain Research and Applications,
1 (1), 2-27. DOI:
10.1108/MSCRA-03-2019-0009
Baskentli, S., Sen, S., Du, S., & Bhattacharya, C. B. (2019). Consumer reactions to corporate social responsibility: The role of CSR domains.
Journal of Business Research,
95 (1), 502-513. DOI:
10.1016/j.jbusres.2018.07.046
Bastami, R., Manzari, H. & Salajeghe S. (2017). Review of ICT and Its Relation to Organizational Productivity Effects Based on Sustainable Development Social Approach, Urban Management, 16 (47), 201-218. (In Persian)
Bergstein, B. (2019). From intelligent systems to intelligent organizations.
Research-Technology Management,
62 (3), 31-37. DOI:
10.1080/08956308.2019.1587300
Boudreau, J. (2016). Work in the future will fall into these 4 categories. Harvard Business Review.
Brynjolfsson, E., & McAffee, A. (2017). What it can–and cannot–do for your organization. Harvard Business Review.
Buser, M., & Koch, C. (2014). Is this none of the contractor’s business? Social sustainability challenges informed by literary accounts.
Construction management and economics,
32 (7-8), 749-759. DOI:
10.1080/01446193.2014.927898
Byrne, B.M. (2010).
Structural Equation Modeling with AMOS Basic Concepts, Applications, and Programming, New York: Taylor and Francis Group.
DOI: 10.4324/9781315757421
Cao, G., Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2021). Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation, 106 (5), 102312. DOI:
10.1016/j.technovation.2021.102312
Carroll, A. B., & Shabana, K. M. (2010). The business case for corporate social responsibility: A review of concepts, research and practice.
International journal of management reviews,
12 (1), 85-105. DOI:
10.1111/j.1468-2370.2009.00275.x
Chatterjee, S., Rana, N. P., Khorana, S., Mikalef, P., & Sharma, A. (2021). Assessing organizational users’ intentions and behavior to AI integrated CRM systems: A meta-UTAUT approach.
Information Systems Frontiers,
25 (4), 1299-1313. DOI:
10.1007/s10796-021-10181-1
Chen, H. (2019).
Success factors impacting artificial intelligence adoption: Perspective from the telecom industry in China. Doctoral dissertation, Old Dominion University.
DOI: 10.25777/a8q8-gm13
Chen, Y., & Lin, Z. (2021). Business intelligence capabilities and firm performance: A study in China.
International Journal of Information Management,
57 (3), 102232. DOI:
10.1016/j.ijinfomgt.2020.102232
Chi, O. H., Gursoy, D., & Chi, C. G. (2022). Tourists’ attitudes toward the use of artificially intelligent (AI) devices in tourism service delivery: moderating role of service value seeking.
Journal of Travel Research,
61 (1), 170-185. DOI:
10.1177/0047287520971054
Dabbous, A., Aoun Barakat, K., & Merhej Sayegh, M. (2022). Enabling organizational use of artificial intelligence: an employee perspective.
Journal of Asia Business Studies,
16 (2), 245-266. DOI:
10.1108/JABS-09-2020-0372
Dasoriya, R., Rajpopat, J., Jamar, R., & Maurya, M. (2018).
The Uncertain Future of Artificial Intelligence. 2018 8th International Conference on Cloud Computing, Data Science & Engineering (Confluence). DOI:
10.1109/CONFLUENCE.2018.8442945
Demartini, M., Evans, S., & Tonelli, F. (2019). Digitalization technologies for industrial sustainability.
Procedia manufacturing,
33, 264-271. DOI:
10.1016/j.promfg.2019.04.032
Digalwar, A. K., Dambhare, S., & Saraswat, S. (2020). Social sustainability assessment framework for indian manufacturing industry.
Materials Today: Proceedings,
28 (2), 591-598. DOI:
10.1016/j.matpr.2019.12.226
Di Vaio, A., Palladino, R., Hassan, R., & Escobar, O. (2020). Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review.
Journal of Business Research,
121, 283-314. DOI:
10.1016/j.jbusres.2020.08.019
Dubravská, M., Marchevská, M., Vašaničová, P., & Kotulič, R. (2020). Corporate social responsibility and environmental management linkage: An empirical analysis of the Slovak Republic.
Sustainability,
12 (13), 5431. DOI:
10.3390/su12135431
Dyllick, T., & Hockerts, K. (2002). Beyond the business case for corporate sustainability.
Business Strategy and the Environment, 11 (2), 130-141. DOI:
10.1002/bse.323
Elkington, J. (1994). Towards the sustainable corporation: Win-win-win business strategies for sustainable development.
California management review,
36 (2), 90-100. DOI:
10.2307/41165746
Fan, W., Liu, J., Zhu, S., & Pardalos, P. M. (2020). Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS).
Annals of Operations Research,
294 (1), 567-592. DOI:
10.1007/s10479-018-2818-y
Ferreira, J. J., Lopes, J. M., Gomes, S., & Rammal, H. G. (2023). Industry 4.0 implementation: Environmental and social sustainability in manufacturing multinational enterprises.
Journal of Cleaner Production,
404, 136841. DOI:
10.1016/j.jclepro.2023.136841
Fornell, C. & Larcker, D. (1981) “Structural Equation Models with Unobservable Variables and Measurement Error.”
Journal of Marketing Research,
18 (1), 39-50.
DOI: 10.2307/3151312
Furht, B., Villanustre, F., Najafabadi, M. M., Villanustre, F., Khoshgoftaar, T. M., Seliya, N.,... & Muharemagc, E. (2016). Deep learning techniques in big data analytics.
Big Data Technologies and Applications,
2 (1), 133-156. DOI:
10.1007/978-3-319-44550-2_5
Ghorpade, A. A. G. (2020). Investigating roadblocks to artificial intelligence adoption in enterprises through a systems perspective.Doctoral dissertation, Massachusetts Institute of Technology.
Graham, S. A., Lee, E. E., Jeste, D. V., Van Patten, R., Twamley, E. W., Nebeker, C.,... & Depp, C. A. (2020). Artificial intelligence approaches to predicting and detecting cognitive decline in older adults: A conceptual review.
Psychiatry research,
284, 112732.
DOI: 10.1016/j.psychres.2019.112732
Grover, P., Kar, A. K., & Dwivedi, Y. K. (2022). Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions.
Annals of Operations Research,
308 (1-2), 177-213. DOI:
10.1007/s10479-020-03683-9
Gupta, M., & Hodges, N. (2012). Corporate social responsibility in the apparel industry: An exploration of Indian consumers’ perceptions and expectations.
Journal of Fashion Marketing and Management: An International Journal,
16 (2), 216-233. DOI:
10.1108/13612021211222833
Gupta, S., Wang, Y., & Czinkota, M. (2023). Reshoring: a road to Industry 4.0 transformation.
British Journal of Management,
34 (3), 1081-1099. DOI:
10.1111/1467-8551.12731
Hasan, M. S., Ebrahim, Z., Mahmood, W. W., & Ab Rahman, M. N. (2017). Sustainable-ERP system: A preliminary study on sustainability indicators. Journal of Advanced Manufacturing Technology (JAMT), 11 (1), 61-74.
Hashmdar, A. & Kordi M. (2021). Investigating effectiveness of artificial intelligence systems in human resource functions, Current researchs in management and accounting science, 4 (12), 1-6. (In Persian)
Hmoud, B. I., & Várallyai, L. (2020). Artificial intelligence in human resources information systems: Investigating its trust and adoption determinants.
International Journal of Engineering and Management Sciences,
5 (1), 749-765. DOI:
10.21791/IJEMS.2020.1.65
Holmström, J. (2022). From AI to digital transformation: The AI readiness framework.
Business Horizons,
65 (3), 329-339. DOI:
10.1016/j.bushor.2021.03.006
Holzmann, P., Schwarz, E. J., & Audretsch, D. B. (2020). Understanding the determinants of novel technology adoption among teachers: the case of 3D printing.
The Journal of Technology Transfer,
45 (1), 259-275. DOI:
10.1007/s10961-018-9693-1
Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service.
Journal of service research,
21 (2), 155-172. DOI:
10.1177/1094670517752459
Jain, R., Garg, N., & Khera, S. N. (2022). Adoption of AI-Enabled Tools in Social Development Organizations in India: An Extension of UTAUT Model.
Frontiers in Psychology,
13, 893691. DOI:
10.3389/fpsyg.2022.893691
Jameel, A. S., Harjan, S. A., & Ahmad, A. R. (2023). Behavioral Intentions to use Artificial Intelligence Among Managers in Small and Medium Enterprises.
AIP Conference Proceedings,
2814 (1), 8. DOI:
10.1063/5.0148676
Jones, S. A., Michelfelder, D., & Nair, I. (2015). Engineering managers and sustainable systems: the need for and challenges of using an ethical framework for transformative leadership.
Journal of Cleaner Production,
1 (8), 1-7. DOI:
10.1016/j.jclepro.2015.02.009
Khakurel, J., Melkas, H., & Porras, J. (2018). Tapping into the wearable device revolution in the work environment: a systematic review.
Information Technology & People,
31 (3), 791-818. DOI:
10.1108/ITP-03-2017-0076
Khalilzadeh, J., Ozturk, A. B., & Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based mobile payment in the restaurant industry.
Computers in human behavior,
70 (2), 460-474. DOI:
10.1016/j.chb.2017.01.001
Lee, C. M. J., Che-Ha, N., & Alwi, S. F. S. (2021). Service customer orientation and social sustainability: The case of small medium enterprises.
Journal of Business Research,
122, 751-760. DOI:
10.1016/j.jbusres.2019.12.048
Lin, C. J., Efranto, R. Y., & Santoso, M. A. (2021). Identification of workplace social sustainability indicators related to employee ergonomics perception in Indonesian industry.
Sustainability,
13 (19), 11069. DOI:
10.3390/su131911069
Lin, H., Chi, O. H., & Gursoy, D. (2020). Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services.
Journal of Hospitality Marketing & Management,
29 (5), 530-549. DOI:
10.1080/19368623.2020.1685053
Lu, L., Cai, R., & Gursoy, D. (2019). Developing and validating a service robot integration willingness scale.
International Journal of Hospitality Management,
80 (1), 36-51. DOI:
10.1016/j.ijhm.2019.01.005
Lukin, E., Krajnović, A., & Bosna, J. (2022). Sustainability strategies and achieving SDGs: A comparative analysis of leading companies in the automotive industry.
Sustainability,
14 (7), 1-15. DOI:
10.3390/su14074000
Malik, N., Tripathi, S. N., Kar, A. K., & Gupta, S. (2022). Impact of artificial intelligence on employees working in industry 4.0 led organizations.
International Journal of Manpower,
43 (2), 334-354. DOI:
10.1108/IJM-03-2021-0173
Mani, V., Gunasekaran, A., & Delgado, C. (2018). Supply chain social sustainability: Standard adoption practices in Portuguese manufacturing firms.
International Journal of Production Economics,
198 (16), 149-164. DOI:
10.1016/j.ijpe.2018.01.032
McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (2006). A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955.
AI magazine,
27 (4), 12-12. DOI:
10.1609/aimag.v27i4.1904
Mohammadian, M., & Ronaghi, M. H. (2010). Brand Promotion Strategies and Techniques: 50 Applied Branding Methods. Tehran: Mehraban Book Institute Publishing. (In Persian)
Moriuchi, E. (2021). An empirical study on anthropomorphism and engagement with disembodied AIs and consumers' re‐use behavior.
Psychology & Marketing,
38 (1), 21-42. DOI:
10.1002/mar.21407
Moodaley, W., & Telukdarie, A. (2023). Greenwashing, Sustainability Reporting, and Artificial Intelligence: A Systematic Literature Review.
Sustainability,
15 (2), 1481-1500. DOI:
10.3390/su15021481
Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda.
International Journal of Information Management,
53, 102104. DOI:
10.1016/j.ijinfomgt.2020.102104
Öberseder, M., Schlegelmilch, B. B., & Murphy, P. E. (2013). CSR practices and consumer perceptions.
Journal of Business Research,
66 (10), 1839-1851. DOI:
10.1016/j.jbusres.2013.02.005
Pang, Q., Fang, M., Wang, L., Mi, K., & Su, M. (2023). Increasing couriers’ job satisfaction through social-sustainability practices: perceived fairness and psychological-safety perspectives.
Behavioral Sciences,
13 (2), 125. DOI:
10.3390/bs13020125
Pfeffer, J. (2010). Building sustainable organizations: The human factor.
Academy of management perspectives,
24 (1), 34-45. DOI:
10.2139/ssrn.1545977
Pullman, M. E., Maloni, M. J., & Carter, C. R. (2009). Food for thought: social versus environmental sustainability practices and performance outcomes.
Journal of supply chain management,
45 (4), 38-54. DOI:
10.1111/j.1745-493X.2009.03175.x
Rahman, M. M., Lesch, M. F., Horrey, W. J., & Strawderman, L. (2017). Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems.
Accident Analysis & Prevention,
108 (2), 361-373. DOI:
10.1016/j.aap.2017.09.011
Rahman, M. S., Bag, S., Gupta, S., & Sivarajah, U. (2023). Technology readiness of B2B firms and AI-based customer relationship management capability for enhancing social sustainability performance.
Journal of Business Research,
156 (1), 113525. DOI:
10.1016/j.jbusres.2022.113525
Rodgers, W. (2020).
Artificial intelligence in a throughput model: Some major algorithms. CRC Press. DOI:
10.1201/9780429266065
Rojas, A., & Tuomi, A. (2022). Reimagining the sustainable social development of AI for the service sector: the role of startups.
Journal of Ethics in Entrepreneurship and Technology,
2 (3), 39-54. DOI:
10.1108/JEET-03-2022-0005
Ronaghi, M. H. (2021). Open-source software migration under sanctions conditions.
International Journal of System Assurance Engineering and Management,
12 (4), 1132-1145. DOI:
10.1007/s13198-021-01329-y
Ronaghi, M. H. (2023). A contextualized study of blockchain technology adoption as a digital currency platform under sanctions.
Management Decision,
61 (5), 1352-1373.
https://doi.org/10.1108/MD-03-2022-0392
Ronaghi, M. H. (2024). Toward a model for assessing smart hospital readiness within the Industry 4.0 paradigm.
Journal of Science and Technology Policy Management,
15 (2), 353-373. DOI:
10.1108/JSTPM-09-2021-0130
Ronaghi, M. H., & Mahmoudi, J. (2015). The relationship between corporate governance and IT governance in public organizations. Journal of information technology management, 7 (3), 615-634. DOI:
10.22059/jitm.2015.54329
Ronaghi, M. H., & Mosakhani, M. (2022). The effects of blockchain technology adoption on business ethics and social sustainability: evidence from the Middle East.
Environment, Development and Sustainability,
24 (5), 6834-6859. DOI:
10.1007/s10668-021-01729-x
Ronaghi, M. H., Zeinodinzadeh, S., & Alambeladi, S. (2019). Identification and ranking the factors affecting the knowledge management implementation using Metasynthesis Method.
Library and Information Sciences,
22 (3), 112-135. DOI:
10.30481/ijlis.2019.183033.1553
Rosário, A. T., & Dias, J. C. (2022). Sustainability and the Digital transition: A literature review.
Sustainability,
14 (7), 1-15. DOI:
10.3390/su14074072
Faghih, N., Bonyadi, E., Sarreshteari, L. (2020). Entrepreneurship Viability. In: Entrepreneurship Viability Index. Contributions to Management Science. Springer, Cham.
Safari, E. & Ansari, A. (2022). Identifying and Ranking the Factors Affecting the Acceptance of Artificial Intelligence in the Public and Private Sectors,
Quarterly Journal of Bi Management Studies, 11 (41), 221-254. (In Persian)
10.22054/IMS.2022.66402.2131
Saravanan, K., Sreedevi, E., & Subhamathi, V. (2017). A review of Artificial Intelligence systems.
International Journal of Advanced Research in Computer Science,
8 (9), 418-421. DOI:
10.26483/ijarcs.v8i9.5095
Scoville, C., Chapman, M., Amironesei, R., & Boettiger, C. (2021). Algorithmic conservation in a changing climate.
Current Opinion in Environmental Sustainability,
51, 30-35. DOI:
10.1016/j.cosust.2021.01.009
Sharif, A., Afshan, S., & Qureshi, M. A. (2019). Acceptance of learning management system in university students: an integrating framework of modified UTAUT2 and TTF theories.
International Journal of Technology Enhanced Learning, 11 (2), 201-229. DOI:
10.1504/IJTEL.2018.10017608
Spanjol, J., Xiao, Y., & Welzenbach, L. (2018). Successive innovation in digital and physical products: Synthesis, conceptual framework, and research directions.
Innovation and Strategy,
15, 31-62. DOI:
10.1108/S1548-643520180000015004
Vedapradha, R., Hariharan, R., & Shivakami, R. (2019). Artificial intelligence: A technological prototype in recruitment.
Journal of Service Science and Management,
12 (3), 382-390. DOI:
10.4236/jssm.2019.123026
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 27 (3), 425-478.
DOI: 10.2307/30036540
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology.
MIS quarterly,
36 (1), 157-178. DOI:
10.2307/41410412
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), 233-250. DOI:
10.48550/arXiv.1905.00501
Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration.
MIS quarterly,
33 (1), 177-195. DOI:
10.2307/20650284
Wongras, P., & Tanantong, T. (2023). An extended UTAUT model for analyzing users’ Acceptance factors for artificial Intelligence adoption in human resource recruitment: A case study of Thailand.
Education and Information Technologies, 3 (7), 13–27. DOI
:10.20944/preprints202311.1612.v1
Yim, W. W., Yetisgen, M., Harris, W. P., & Kwan, S. W. (2016). Natural language processing in oncology: a review.
JAMA oncology,
2 (6), 797-804. DOI:
10.1001/jamaoncol.2016.0213
)