CoChat
Sign Up
Cited by 16Knowledge Management and SharingAI and HR TechnologiesManagement and Organizational Practices

Human Resource Analytics in the Era of Artificial Intelligence: Leveraging Knowledge towards Organizational Success in Pakistan

Open access
Muhammad Haroon Rasheed, Jamshed Khalid, Aasir Ali, Muhammad Shahid Rasheed, Kamran Ali·2024·Journal of Chinese Human Resources Management
DOI 10.47297/wspchrmwsp2040-800501.20241503
Open this paper in CoChat — free account

Abstract

Given the sudden rise of artificial intelligence and declining standardization, the study focuses on the link between contextualized workplace coordination and administrative performance by preserving knowledge and utilizing generative AI models. The study employed a survey questionnaire design to collect data from project employees working at software houses in Islamabad. Hypothesis testing is done by utilizing partial least square regression through SMART-PLS. The findings indicate that the mandatory implicit and explicit coordination practices through accountability at organizational levels lead to increased knowledge sharing and administrative performance in Pakistan. The study concluded that knowledge-sharing acts as a mediator, hence implicit and explicit knowledge coordination is only fruitful in the occurrence of effective knowledge-sharing systems in the organization. The infusion of generative AI models by organizational employees is found to act as a moderator. It has significant potential to reduce the drawbacks associated with a lack of knowledge-sharing systems. Aside from being a pioneer study in this contextualized setting of HR analytics, these findings also have practical significance for HR managers, employees, and other stakeholders. The findings can be utilized to better ensure effectiveness and efficiency in organizational settings while managers can overcome any shortcomings in the system through the infusion of artificial intelligence in their HR analytics practices.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.47297/wspchrmwsp2040-800501.20241503

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

The citation lists haven’t been fetched yet

References 89 · Cited by 16

Research works printed but not linked: 107

  1. Vol. 15, Issue 3, Pages: 3-20(2024)
  2. Rasheed, M. H., Khalid, J., Ali, A., Rasheed, M. S., & Ali, K. (2024). Human resource analytics in the era of artificial intelligence: Leveraging knowledge towards organizational success in Pakistan[J]. Journal of Chinese Human Resources Management, 15(03):3-20.
  3. Rasheed, M. H., Khalid, J., Ali, A., Rasheed, M. S., & Ali, K. (2024). Human resource analytics in the era of artificial intelligence: Leveraging knowledge towards organizational success in Pakistan[J]. Journal of Chinese Human Resources Management, 15(03):3-20. DOI： 10.47297/wspchrmWSP2040-800501.20241503.
  4. The methodological approach of the study is based on research onion as illustrated by Saunders et al. (2009). If we consider the aim of the study, it aligns with the objectivism. Furthermore, The reason the study is focused on identifying factors that ensure optimal performance making the impact of these variables an independent objective reality (
  5. Alavi, M., & Leidner, D. E. (2001a). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136. [Baidu Scholar]
  6. Campbell, D., & Fiske, D. (1998). Convergent and discriminant validation by the multitrait-multimethods matrix'. Personality, 56(2), 162. [Baidu Scholar]
  7. Fitz-Enz, J. (2010). The new HR analytics. American Management Association. https://www.academia.edu/download/48388687/_Dr._Jac_Fitzenz__The_New_HR_Analytics_PredictinBook4You.pdf [Baidu Scholar]
  8. Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage. [Baidu Scholar]
  9. Nagesh, Ds., & Thomas, S. (2015). Success factors of public funded R&D projects. Current Science, 108(3), 357–363. [Baidu Scholar]
  10. Ngoc-Tan, N., & Gregar, A. (2018). Impacts of knowledge management on innovations in higher education institutions: An empirical evidence from Vietnam. Economics and Sociology, 11(3), 301-320. https://publikace.k.utb.cz/handle/10563/1008257 [Baidu Scholar]
  11. Nonaka, I. (2009). The knowledge-creating company. In The economic impact of knowledge (pp. 175–187). Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9780080505022-16/knowledge-creating-company-ikujiro-nonaka [Baidu Scholar] · DOI
  12. Saunders, M., Lewis, P., & Thornhill, A. (2009). Understanding research philosophies and approaches. In Research methods for business students (Vol. 4). Pearson Education. [Baidu Scholar]
  13. Zack, M. H. (2002). Epilogue: Developing a knowledge strategy. In The strategic management of intellectual capital and organizational knowledge: A collection of readings (pp. 268–276). [Baidu Scholar]
  14. Abdillah, A., Widianingsih, I., Buchari, R. A., & Nurasa, H. (2023). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Learning: Research and Practice, 10(1), 1–3. https://doi.org/10.1080/23735082.2023.2272611 · DOI
  15. Adler, P. S., & Kwon, S.-W. (2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1), 17–40. https://doi.org/10.5465/amr.2002.5922314 · DOI · Paper page
  16. Agbim, K. C., Zever, T. A., & Oriarewo, G. O. (2014). Assessing the effect of knowledge acquisition on competitive advantage: A knowledge-based and resource-based study. Information and Knowledge Management, 4(11), 131–142. https://core.ac.uk/download/pdf/234671861.pdf
  17. Ajmal, M. M., Kekäle, T., & Takala, J. (2009). Cultural impacts on knowledge management and learning in project‐based firms. VINE, 39(4), 339–352. https://doi.org/10.1108/03055720911013634 · DOI
  18. Alavi, M., & Leidner, D. E. (2001a). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136.
  19. Argote, L., Ingram, P., Levine, J. M., & Moreland, R. L. (2000). Knowledge transfer in organizations: Learning from the experience of others. Organizational Behavior and Human Decision Processes, 82(1), 1–8.
  20. Aydiner, A. S., Tatoglu, E., Bayraktar, E., & Zaim, S. (2019). Information system capabilities and firm performance: Opening the black box through decision-making performance and business-process performance. International Journal of Information Management, 47, 168–182. https://doi.org/10.1016/j.ijinfomgt.2018.12.015 · DOI
  21. Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173.
  22. Bierly, P. E., & Chakrabarti, A. K. (1996). Technological learning, strategic flexibility, and new product development in the pharmaceutical industry. IEEE Transactions on Engineering Management, 43(4), 368–380.
  23. Boamah, F. A., Zhang, J., Shehzad, M. U., & Ahmad, M. (2023). The mediating role of social dynamics in the influence of absorptive capacity and tacit knowledge sharing on project performance. Business Process Management Journal, 29(1), 240–261.
  24. Bollen, K. A. (1989). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303–316.
  25. Bresnen, M., Edelman, L., Newell, S., Scarbrough, H., & Swan, J. (2003). Social practices and the management of knowledge in project environments. International Journal of Project Management, 21(3), 157–166.
  26. Bryman, A., & Bell, E. (2015). Business research methods. Oxford University Press.
  27. Cabrera, E. F., & Cabrera, A. (2005). Fostering knowledge sharing through people management practices. The International Journal of Human Resource Management, 16(5), 720–735. https://doi.org/10.1080/09585190500083020 · DOI · Paper page
  28. Caimo, A., & Lomi, A. (2015). Knowledge sharing in organizations: A Bayesian analysis of the role of reciprocity and formal structure. Journal of Management, 41(2), 665–691. https://doi.org/10.1177/0149206314552192 · DOI
  29. Campbell, D., & Fiske, D. (1998). Convergent and discriminant validation by the multitrait-multimethods matrix'. Personality, 56(2), 162.
  30. Castellani, P., Rossato, C., Giaretta, E., & Davide, R. (2021). Tacit knowledge sharing in knowledge-intensive firms: The perceptions of team members and team leaders. Review of Managerial Science, 15(1), 125–155. https://doi.org/10.1007/s11846-019-00368-x · DOI
  31. Chang, H.-T., Lin, C.-C., Chen, C.-H., & Ho, Y.-H. (2017). Explicit and implicit team coordination: Development of a multidimensional scale. Social Behavior and Personality: An International Journal, 45(6), 915–929.
  32. Child, J., & McGrath, R. G. (2001). Organizations unfettered: Organizational form in an information-intensive economy. Academy of Management Journal, 44(6), 1135–1148. https://doi.org/10.5465/3069393 · DOI
  33. Chin, W. W. (2010). How to write up and report PLS analyses. In Handbook of partial least squares (pp. 655–690). Springer.
  34. Connelly, C. E., & Kevin Kelloway, E. (2003). Predictors of employees' perceptions of knowledge sharing cultures. Leadership & Organization Development Journal, 24(5), 294–301. https://doi.org/10.1108/01437730310485815 · DOI
  35. Cooper, C., Pereira, V., Vrontis, D., & Liu, Y. (2023). Extending the resource and knowledge based view: Insights from new contexts of analysis. Journal of Business Research, 156, 113523. https://www.sciencedirect.com/science/article/pii/S0148296322009882
  36. Darroch, J. (2005). Knowledge management, innovation and firm performance. Journal of Knowledge Management, 9(3), 101–115. https://doi.org/10.1108/13673270510602809 · DOI
  37. Davenport, T. H., De Long, D. W., & Beers, M. C. (1998). Successful knowledge management projects. MIT Sloan Management Review, 39(2), 43–57.
  38. Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Harvard Business Press.
  39. Dawson, J. F. (2014). Moderation in management research: What, why, when, and how. Journal of Business and Psychology, 29(1), 1–19. https://doi.org/10.1007/s10869-013-9308-7 · DOI
  40. De Long, D. W., & Fahey, L. (2000). Diagnosing cultural barriers to knowledge management. Academy of Management Perspectives, 14(4), 113–127. https://doi.org/10.5465/ame.2000.3979820 · DOI
  41. Deng, H., Duan, S. X., & Wibowo, S. (2023). Digital technology driven knowledge sharing for job performance. Journal of Knowledge Management, 27(2), 404–425.
  42. Duffield, S., & Whitty, S. J. (2016). How to apply the Systemic Lessons Learned Knowledge model to wire an organisation for the capability of storytelling. International Journal of Project Management, 34(3), 429–443. https://doi.org/10.1016/j.ijproman.2015.11.004 · DOI
  43. Edmondson, A. C. (2003). Speaking up in the operating room: How team leaders promote learning in interdisciplinary action teams. Journal of Management Studies, 40(6), 1419–1452. https://doi.org/10.1111/1467-6486.00386 · DOI · Paper page
  44. Ellis, N. C. (2005). At the interface: Dynamic interactions of explicit and implicit language knowledge. Studies in Second Language Acquisition, 27(2), 305–352.
  45. Faraj, S., & Sproull, L. (2000). Coordinating expertise in software development teams. Management Science, 46(12), 1554–1568. https://doi.org/10.1287/mnsc.46.12.1554.12072 · DOI · Paper page
  46. Fernie, S., Green, S. D., Weller, S. J., & Newcombe, R. (2003). Knowledge sharing: Context, confusion and controversy. International Journal of Project Management, 21(3), 177–187. https://doi.org/10.1016/S0263-7863(02)00092-3 · DOI
  47. Fisher, C., & Buglear, J. (2010). Researching and writing a dissertation: An essential guide for business students. Pearson Education.
  48. Fitz-Enz, J. (2010). The new HR analytics. American Management Association. https://www.academia.edu/download/48388687/_Dr._Jac_Fitzenz__The_New_HR_Analytics_PredictinBook4You.pdf
  49. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
  50. Gao, J., & Bernard, A. (2018). An overview of knowledge sharing in new product development. The International Journal of Advanced Manufacturing Technology, 94(5–8), 1545–1550. https://doi.org/10.1007/s00170-017-0140-5 · DOI
  51. Ghauri, P. N., & Grønhaug, K. (2005). Research methods in business studies: A practical guide. Pearson Education.
  52. Grant, R. M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(S2), 109–122. https://doi.org/10.1002/smj.4250171110 · DOI · Paper page
  53. Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Sage.
  54. Hansen, M. T., Mors, M. L., & Løvås, B. (2005). Knowledge sharing in organizations: Multiple networks, multiple phases. Academy of Management Journal, 48(5), 776–793. https://doi.org/10.5465/amj.2005.18803922 · DOI
  55. Hassandoust, F., Techatassanasoontorn, A. A., & Tan, F. B. (2016). Factors influencing the infusion of information systems: A literature review. Pacific Asia Journal of the Association for Information Systems, 8(1), 2.
  56. Hislop, D., Bosua, R., & Helms, R. (2018). Knowledge management in organizations: A critical introduction. Oxford university press.
  57. Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1), 88–115. https://doi.org/10.1287/orsc.2.1.88 · DOI · Paper page
  58. Husain, S. N., & Husain, Y. S. (2016). Mediating effect of OCB on relationship between job attitudes and knowledge sharing behavior. International Journal of Science and Research (IJSR), 5(1), 1008–1015.
  59. Husted, K., & Michailova, S. (2002). Diagnosing and fighting knowledge-sharing hostility. Organizational Dynamics - ORGAN DYN, 31(1), 60–73. https://doi.org/10.1016/S0090-2616(02)00072-4 · DOI
  60. Jennex, M. E., & Olfman, L. (2006). A model of knowledge management success. International Journal of Knowledge Management (IJKM), 2(3), 51–68. https://doi.org/10.4018/jkm.2006070104 · DOI
  61. Jiao, W., Wang, W., Huang, J., Wang, X., & Tu, Z. (2023). Is ChatGPT a good translator? A preliminary study. arXiv Preprint arXiv:2301.08745, 1(10). https://www.researchgate.net/publication/367359399_Is_ChatGPT_A_Good_Translator_A_Preliminary_Study · arXiv
  62. Jiménez-Jiménez, D., & Sanz-Valle, R. (2011). Innovation, organizational learning, and performance. Journal of Business Research, 64(4), 408–417. https://doi.org/10.1016/j.jbusres.2010.09.010 · DOI
  63. KALLEBERG, A. L., & MOODY, J. W. (1994). Human resource management and organizational performance. American Behavioral Scientist, 37(7), 948–962. https://doi.org/10.1177/0002764294037007007 · DOI
  64. Kamara, J. M., Augenbroe, G., Anumba, C. J., & Carrillo, P. M. (2002). Knowledge management in the architecture, engineering and construction industry. Construction Innovation, 2(1), 53–67.
  65. Kamaşak, R., & Bulutlar, F. (2010). The influence of knowledge sharing on innovation. European Business Review, 22(3), 306–317.
  66. Kareem, H. M., Aziz, K. A., Maelah, R., Yunus, Y. M., & Dauwed, M. (2019). Organizational performance in Iraqi SMEs: Validity and reliability questionnaire. Academy of Accounting and Financial Studies Journal, 23(6), 1–16.
  67. Kenny, J. (2003). Effective project management for strategic innovation and change in an organizational context. Project Management Journal, 34(1), 43–53. https://doi.org/10.1177/875697280303400106 · DOI
  68. Kianto, A., Vanhala, M., & Heilmann, P. (2016). The impact of knowledge management on job satisfaction. Journal of Knowledge Management, 20(4), 621–636.
  69. Kim, H.-W., & Gupta, S. (2014). A user empowerment approach to information systems infusion. IEEE Transactions on Engineering Management, 61(4), 656–668.
  70. Kulkarni, U. R., Ravindran, S., & Freeze, R. (2006). A knowledge management success model: Theoretical development and empirical validation. Journal of Management Information Systems, 23(3), 309–347. https://doi.org/10.2753/MIS0742-1222230311 · DOI
  71. Lee, M. Y., & Edmondson, A. C. (2017). Self-managing organizations: Exploring the limits of less-hierarchical organizing. Research in Organizational Behavior, 37, 35–58. https://doi.org/10.1016/j.riob.2017.10.002 · DOI · Paper page
  72. Lin, H. (2007). Knowledge sharing and firm innovation capability: An empirical study. International Journal of Manpower, 28(3/4), 315–332. https://doi.org/10.1108/01437720710755272 · DOI
  73. Lüdeke‐Freund, F. (2020). Sustainable entrepreneurship, innovation, and business models: Integrative framework and propositions for future research. Business Strategy and the Environment, 29(2), 665–681. https://doi.org/10.1002/bse.2396 · DOI · Paper page
  74. Mohajan, H. K. (2019). Knowledge sharing among employees in organizations. Journal of Economic Development, Environment and People, 8(1), 52–61.
  75. Nagesh, Ds., & Thomas, S. (2015). Success factors of public funded R&D projects. Current Science, 108(3), 357–363.
  76. Nambisan, S., Agarwal, R., & Tanniru, M. (1999). Organizational mechanisms for enhancing user innovation in information technology. MIS Quarterly, 23(3), 365–395.
  77. Ngoc Thang, N., & Anh Tuan, P. (2020). Knowledge acquisition, knowledge management strategy and innovation: An empirical study of Vietnamese firms. Cogent Business & Management, 7(1), 1786314. https://doi.org/10.1080/23311975.2020.1786314 · DOI
  78. Ngoc-Tan, N., & Gregar, A. (2018). Impacts of knowledge management on innovations in higher education institutions: An empirical evidence from Vietnam. Economics and Sociology, 11(3), 301-320. https://publikace.k.utb.cz/handle/10563/1008257
  79. Ni, G., Cui, Q., Sang, L., Wang, W., & Xia, D. (2018). Knowledge-sharing culture, project-team interaction, and knowledge-sharing performance among project members. Journal of Management in Engineering, 34(2), 04017065. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000590 · DOI
  80. Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. https://doi.org/10.1287/orsc.5.1.14 · DOI · Paper page
  81. Nonaka, I. (2009). The knowledge-creating company. In The economic impact of knowledge (pp. 175–187). Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9780080505022-16/knowledge-creating-company-ikujiro-nonaka · DOI
  82. Olan, F., Liu, S., Neaga, I., Chen, H., & Nakpodia, F. (2019). How cultural impact on knowledge sharing contributes to organizational performance: Using the fsQCA approach. Journal of Business Research, 94, 313–319. https://doi.org/10.1016/j.jbusres.2018.02.027 · DOI
  83. Pérez‐López, S., & Alegre, J. (2012). Information technology competency, knowledge processes and firm performance. Industrial Management & Data Systems, 112(4), 644–662. https://doi.org/10.1108/02635571211225521 · DOI
  84. Pinho, I., Rego, A., & Pina e Cunha, M. (2012). Improving knowledge management processes: A hybrid positive approach. Journal of Knowledge Management, 16(2), 215–242. https://doi.org/10.1108/13673271211218834 · DOI
  85. Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–731. https://doi.org/10.3758/BF03206553 · DOI · Paper page
  86. Raisch, S., & Birkinshaw, J. (2008). Organizational ambidexterity: Antecedents, outcomes, and moderators. Journal of Management, 34(3), 375–409.
  87. Rasheed, M. H., Ali, A., & Khan, N. A. (2023). Technological advancements and noise trading: A case of investors' sentiments at the Pakistan stock exchange. Computers in Human Behavior Reports, 12, 100344. https://doi.org/10.1016/j.chbr.2023.100344 · DOI
  88. Ravichandran, T. (2018). Exploring the relationships between IT competence, innovation capacity and organizational agility. The Journal of Strategic Information Systems, 27(1), 22–42.
  89. Rieger, M. O., & Wang, M. (2006). Cumulative prospect theory and the St. Petersburg paradox. Economic Theory, 28(3), 665–679.
  90. Saarenketo, S., Puumalainen, K., Kuivalainen, O., & Kyläheiko, K. (2009). A knowledge-based view of growth in new ventures. European Business Review, 21(6), 531–546.
  91. Santos, R. F., Oliveira, M., & Curado, C. (2023). The effects of the relational dimension of social capital on tacit and explicit knowledge sharing: A mixed-methods approach. VINE Journal of Information and Knowledge Management Systems, 53(1), 43–63.
  92. Saunders, M., Lewis, P., & Thornhill, A. (2009). Understanding research philosophies and approaches. In Research methods for business students (Vol. 4). Pearson Education.
  93. Subramaniam, M., & Youndt, M. A. (2005). The influence of intellectual capital on the types of innovative capabilities. Academy of Management Journal, 48(3), 450–463.
  94. Suzuki, Y., Jeong, H., Cui, H., Okamoto, K., Kawashima, R., & Sugiura, M. (2023). An fMRI validation study of the word-monitoring task as a measure of implicit knowledge: Exploring the role of explicit and implicit aptitudes in behavioral and neural processing. Studies in Second Language Acquisition, 45(1), 109–136.
  95. Takeuchi, H., & Nonaka, I. (1986). The new new product development game. Harvard Business Review, 64(1), 137–146.
  96. Tams, S., Thatcher, J. B., & Craig, K. (2018). How and why trust matters in post-adoptive usage: The mediating roles of internal and external self-efficacy. The Journal of Strategic Information Systems, 27(2), 170–190.
  97. Tassabehji, R., Mishra, J. L., & Dominguez-Péry, C. (2019). Knowledge sharing for innovation performance improvement in micro/SMEs: An insight from the creative sector. Production Planning & Control, 30(10–12), 935–950. https://doi.org/10.1080/09537287.2019.1582101 · DOI
  98. Tiwana, A. (2002). The knowledge management toolkit: Orchestrating IT, strategy, and knowledge platforms. Pearson Education India.
  99. Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: The role of intrafirm networks. Academy of Management Journal, 41(4), 464–476. https://doi.org/10.2307/257085 · DOI
  100. Wamba, S. F., Queiroz, M. M., Jabbour, C. J. C., & Shi, C. V. (2023). Are both generative AI and ChatGPT game changers for 21st-Century operations and supply chain excellence? International Journal of Production Economics, 265, 109015.
  101. Wamba-Taguimdje, S.-L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924.
  102. Wang, C., Rodan, S., Fruin, M., & Xu, X. (2014). Knowledge networks, collaboration networks, and exploratory innovation. Academy of Management Journal, 57(2), 484–514.
  103. Wang, S., & Noe, R. A. (2010). Knowledge sharing: A review and directions for future research. Human Resource Management Review, 20(2), 115–131.
  104. Wang, Z., & Wang, N. (2012). Knowledge sharing, innovation and firm performance. Expert Systems with Applications, 39(10), 8899–8908.
  105. Wong, L.-W., Tan, G. W.-H., Ooi, K.-B., Lin, B., & Dwivedi, Y. K. (2022). Artificial intelligence-driven risk management for enhancing supply chain agility: A deep-learning-based dual-stage PLS-SEM-ANN analysis. International Journal of Production Research, 1–21. https://doi.org/10.1080/00207543.2022.2063089 · DOI
  106. Zack, M. H. (2002). Epilogue: Developing a knowledge strategy. In The strategic management of intellectual capital and organizational knowledge: A collection of readings (pp. 268–276).
  107. Zhang, J., Raza, M., Khalid, R., Parveen, R., & Ramírez-Asís, E. H. (2023). Impact of team knowledge management, problem solving competence, interpersonal conflicts, organizational trust on project performance, a mediating role of psychological capital. Annals of Operations Research, 326(S1), 41–42. https://doi.org/10.1007/s10479-021-04334-3 · DOI

Authors
Rasheed, M. H., Khalid, J., Ali, A., Rasheed, M. S., & Ali, K.
Affiliations
  • University of Sargodha (PK)
  • University of the Punjab (PK)
ORCID
Venue
Journal of Chinese Human Resources Management
Publisher
World Scientific Publishing House Ltd
Published
2024-05-27
Volume
15
Issue
3
ISSN
  • 2040-8005 (ISSN-L)
  • 2040-8013
DOI
10.47297/wspchrmwsp2040-800501.20241503
OpenAlex
W4399045972
Cited by
16
References
89
Citations by year
2026: 3 · 2025: 9 · 2024: 4
FWCI
13.43
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
Journal of Chinese Human Resource Management (publishedVersion, cc-by)
Topics
  • Social Sciences › Communication › Knowledge Management and Sharing
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Management and Organizational Practices
Keywords
HR analytics, artificial intelligence, generative AI, knowledge sharing, implicit and explicit knowledge, administrative performance, accountability, software companies

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review