Why cognitive absorption is not enough: The role of knowledge absorption capacity and technological opportunity for individual learning

Main Article Content

Ahmad Adeel
Samreen Batool
Daisy Mui Hung Kee
Zain-ul-Abdeen Madni

Abstract

The purpose of this paper is to address the basic question why does high absorptive training programmes are not always beneficial for individual level learning? Thus, we seek to understand when and how cognitive absorption is beneficial for individual learning. The proposed model was tested using data obtained in a field study (N = 371) and in an experiment (N = 119). For field study, data was obtained at two points in time from three data sources (co-workers, subordinates, supervisors) working at a private commercial bank operating in Pakistan. For laboratory experiment, data was collected from the business students of a private sector university in Pakistan. The obtained data for both studies were analysed for random coefficient models with Mplus. Based on the motivation-ability-opportunity theory of behaviour, we proposed a model. It was found that cognitive absorption and highest individual learning was contingent upon the individual level knowledge absorption capacity. It was further found that training programmes with high cognitive absorption are likely to produce high levels of individual learning when the participants also have both high level of knowledge absorption capacity and technological opportunity. With this research, we inform practitioners that in these learner-focused trainings, personal characteristics of the participants and technology play vital role in determining effectiveness for high level of individual learning. The research findings will help practitioners understand what they need to add in training programmes for high level individual learning experience. Doing so will bring best value in form of higher learning to the cost of trainings. 

Article Details

How to Cite
Ahmad Adeel, Samreen Batool, Daisy Mui Hung Kee, & Zain-ul-Abdeen Madni. (2023). Why cognitive absorption is not enough: The role of knowledge absorption capacity and technological opportunity for individual learning. Asian Academy of Management Journal, 28(2), 239–274. https://doi.org/10.21315/aamj2023.28.2.9
Section
Original Articles

References

Addison, T. (2003). E-commerce project development risks: Evidence from a Delphi survey. International Journal of Information Management, 23(1), 25–40. https://doi.org/10.1016/S0268-4012(02)00066-X

Adeel, A., Batool, S., Daisy, K. M. H., & Khan, M. K. (2022). LMX and creative idea validation: The role of helping and bullying. Asian Academy of Management Journal, 27(2), 107−134. https://doi.org/10.21315/aamj2022.27.2.6

Adeel, A., Pengcheng, Z., Saleem, F., Ali, R., & Batool, S. (2019). Conflicts and creative idea endorsement: Do subordinates’ political skills and implementation instrumentality matter? International Journal of Conflict Management, 30(5), 637−656. https://doi.org/10.1108/IJCMA-02-2019-0033

Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694. https://doi.org/10.2307/3250951

Agarwal, R., Sambamurthy, V., & Stair, R. M. (1997). Cognitive absorption and the adoption of new information technologies. Academy of Management Proceedings, 1997(1). https://doi.org/10.5465/ambpp.1997.4983719

Aiken, L. S., West, S. G., & Reno, R. R. (1991). Multiple regression: Testing and interpreting interactions. SAGE Publications.

Al-Taweel, F. B., Abdulkareem, A. A., Gul, S. S., & Alshami, M. L. (2021). Evaluation of technology: Based learning by dental students during the pandemic outbreak of coronavirus disease 2019. European Journal of Dental Education, 25(1), 183–190. https://doi.org/10.1111/eje.12589

Alketbi, S., Akmal, S., Al-Shami, S., & Hamid, R. (2021). Conceptual framework: The role of cognitive absorption in Delone and McLean success model in online learning in United Arab Emirates. Academy of Strategic Management Journal, 20, 1–9. https://www.abacademies.org/articles/conceptual-framework-the-role-of- cognitive-absorption-in-delone-and-mclean-success-model-in-online-learning- in-united-arab-emirate-11046.html

Almuraqab, N. A. S. (2020). Shall universities at the UAE continue distance learning after the COVID-19 pandemic? Revealing students’ perspective. Social Science Research Network. https://pubmed.ncbi.nlm.nih.gov/32714122

Amabile, T., & Mueller, J. (2007). Psychometric approaches to the study of human creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 35–61). Cambridge University Press.

Andersén, J., & Kask, J. (2012). Asymmetrically realized absorptive capacity and relationship durability. Management Decision, 50(1), 43–57. https://doi. org/10.1108/00251741211194868

Arbaugh, J. B. (2008). Does the community of inquiry framework predict outcomes in online MBA courses? The International Review of Research in Open and Distributed Learning, 9(2), 1–21. https://doi.org/10.19173/irrodl.v9i2.490

Armin, M. H., & Roslin, V. P. (2021). The effect of nonverbal communication training on Iranian EFL learners’ perception of communicative competence and communication apprehension. KURMANJ; The Journal of Culture, Humanities and Social Science, 3(1), 1–11. https://doi.org/10.47176/kurmanj.3.1.1

Ashford, S. J. (1986). Feedback-seeking in individual adaptation: A resource perspective. Academy of Management Journal, 29(3), 465–487. https://doi.org/10.2307/256219

Austin, J. R. (2003). Transactive memory in organizational groups: The effects of content, consensus, specialization, and accuracy on group performance. Journal of Applied Psychology, 88(5), 866−878. https://doi.org/10.1037/0021-9010.88.5.866

Balakrishnan, J., & Dwivedi, Y. K. (2021). Role of cognitive absorption in building user trust and experience. Psychology & Marketing, 38(4), 643–668. https://doi. org/10.1002/mar.21462

Barnes, S. J., Pressey, A. D., & Scornavacca, E. (2019). Mobile ubiquity: Understanding the relationship between cognitive absorption, smartphone addiction and social network services. Computers in Human Behavior, 90, 246–258. https://doi.org/10.1016/j.chb.2018.09.013

Basaglia, S., Caporarello, L., Magni, M., & Pennarola, F. (2010). IT knowledge integration capability and team performance: The role of team climate. International Journal of Information Management, 30(6), 542–551. https://doi.org/10.1016/j.ijinfomgt.2010.04.003

Bell, B. S., & Kozlowski, S. W. (2008). Active learning: Effects of core training design elements on self-regulatory processes, learning, and adaptability. Journal of Applied Psychology, 93(2), 296. https://doi.org/10.1037/0021-9010.93.2.296

Benbunan-Fich, R., & Hiltz, S. R. (2003). Mediators of the effectiveness of online courses. IEEE Transactions on Professional Communication, 46(4), 298–312. https://doi.org/10.1109/TPC.2003.819639

Bergdahl, N., Nouri, J., & Fors, U. (2020). Disengagement, engagement and digital skills in technology-enhanced learning. Education and Information Technologies, 25(2), 957–983. https://doi.org/10.1007/s10639-019-09998-w

Blumberg, M., & Pringle, C. D. (1982). The missing opportunity in organizational research: Some implications for a theory of work performance. Academy of Management Review, 7(4), 560–569. https://doi.org/10.5465/amr.1982.4285240

Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equation perspective (vol. 467). John Wiley & Sons.

Bresman, H. (2010). External learning activities and team performance: A multimethod field study. Organization Science, 21(1), 81–96. https://doi.org/10.1287/orsc.1080.0413

Bunderson, J. S. (2003). Recognizing and utilizing expertise in work groups: A status characteristics perspective. Administrative Science Quarterly, 48(4), 557–591. https://doi.org/10.2307/3556637

Burton-Jones, A., & Straub Jr, D. W. (2006). Reconceptualizing system usage: An approach and empirical test. Information Systems Research, 17(3), 228–246. https://doi.org/10.1287/isre.1060.0096

Cannella Jr, A. A., & McFadyen, M. A. (2016). Changing the exchange: The dynamics of knowledge worker ego networks. Journal of Management, 42(4), 1005–1029. https://doi.org/10.1177/0149206313511114

Casillas, J. C., Barbero, J. L., & Sapienza, H. J. (2015). Knowledge acquisition, learning, and the initial pace of internationalization. International Business Review, 24(1), 102–114. https://doi.org/10.1016/j.ibusrev.2014.06.005

Chang, J. J., Lin, W. S., & Chen, H. R. (2019). How attention level and cognitive style affect learning in a MOOC environment? Based on the perspective of brainwave analysis. Computers in Human Behavior, 100, 209–217. https://doi.org/10.1016/j.chb.2018.08.016

Chen, S. Y., & Chang, L. P. (2016). The influences of cognitive styles on individual learning and collaborative learning. Innovations in Education and Teaching International, 53(4), 458–471. https://doi.org/10.1080/14703297.2014.931242

Choi, S. Y., Lee, H., & Yoo, Y. (2010). The impact of information technology and transactive memory systems on knowledge sharing, application, and team performance: A field study. MIS Quarterly, 34(4), 855–870. https://doi.org/10.2307/25750708

Cohen, W., & Levinthal, D. (1990). Tacit knowledge and scientific networks. Administrative Science Quarterly, 35(1), 128–152. https://www.jstor.org/stable/284473

Comeig, I., Mas-Tur, A., & Viglia, G. (2018). Introduction to the special issue on innovation, knowledge absorption, judgement and decision-making processes. European Journal of Management and Business Economics, 27(2), 126–128. https://doi.org/10.1108/EJMBE-07-2018-067

Daouk, L., & Aldalaien, M. (2019). The usage of e-learning instructional technologies in higher education institutions in the United Arab Emirates (UAE). TOJET: The Turkish Online Journal of Educational Technology, 18(3), 97–109. https://files.eric.ed.gov/fulltext/EJ1223782.pdf

Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin, 125(6), 627. https://doi.org/10.1037/0033-2909.125.6.627

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

Denison, D. R., Hart, S. L., & Kahn, J. A. (1996). From chimneys to cross-functional teams: Developing and validating a diagnostic model. Academy of Management Journal, 39(4), 1005–1023. https://doi.org/10.2307/256721

Dewett, T. (2003). Understanding the relationship between information technology and creativity in organizations. Creativity Research Journal, 15(2–3), 167–182. https://doi.org/10.1080/10400419.2003.9651410

Druskat, V. U., & Kayes, D. C. (2000). Learning versus performance in short- term project teams. Small Group Research, 31(3), 328–353. https://doi.org/10.1177/104649640003100304

Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. https://doi.org/10.2307/2666999

Edmondson, A. C., Winslow, A. B., Bohmer, R. M., & Pisano, G. P. (2003). Learning how and learning what: Effects of tacit and codified knowledge on performance improvement following technology adoption. Decision Sciences, 34(2), 197–224. https://doi.org/10.1111/1540-5915.02316

Elsbach, K. D., & Hargadon, A. B. (2006). Enhancing creativity through “mindless” work: A framework of workday design. Organization Science, 17(4), 470–483. https://doi.org/10.1287/orsc.1060.0193

Erdogan, B., Bauer, T. N., & Walter, J. (2015). Deeds that help and words that hurt: Helping and gossip as moderators of the relationship between leader–member exchange and advice network centrality. Personnel Psychology, 68(1), 185–214. https://doi.org/10.1111/peps.12075

Gajendran, R. S., & Harrison, D. A. (2007). The good, the bad, and the unknown about telecommuting: Meta-analysis of psychological mediators and individual consequences. Journal of Applied Psychology, 92(6), 1524−1541. https://doi. org/10.1037/0021-9010.92.6.1524

Gardner, H. K., Gino, F., & Staats, B. R. (2012). Dynamically integrating knowledge in teams: Transforming resources into performance. Academy of Management Journal, 55(4), 998–1022. https://doi.org/10.5465/amj.2010.0604

Garud, R., & Kumaraswamy, A. (2005). Vicious and virtuous circles in the management of knowledge: The case of Infosys Technologies. MIS Quarterly, 19(1), 9–33. https://doi.org/10.2307/25148666

Goasduff, L., & Pettey, C. (2011). Gartner Enterprise Architecture Summit Report. https://www.gartner.com/imagesrv/summits/docs/na/enterprise-architecture/EA_Recommended_AAAG_flier.pdf

Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214. https://doi.org/10.1080/07421222.2001.11045669

Grant, A. M. (2008). Does intrinsic motivation fuel the prosocial fire? Motivational synergy in predicting persistence, performance, and productivity. Journal of Applied Psychology, 93(1), 48. https://doi.org/10.1037/0021-9010.93.1.48

Grant, A. M., & Berry, J. W. (2011). The necessity of others is the mother of invention: Intrinsic and prosocial motivations, perspective taking, and creativity. Academy of Management Journal, 54(1), 73–96. https://doi.org/10.5465/amj.2011.59215085

Guo, Y. M., & Ro, Y. K. (2008). Capturing flow in the business classroom. Decision Sciences Journal of Innovative Education, 6(2), 437–462. https://doi.org/10.1111/ j.1540-4609.2008.00185.x

Hackman, J. R., Pearce, J. L., & Wolfe, J. C. (1978). Effects of changes in job characteristics on work attitudes and behaviors: A naturally occurring quasi-experiment. Organizational Behavior and Human Performance, 21(3), 289–304. https://doi. org/10.1016/0030-5073(78)90055-7

Hamilton, D., McFarland, D., & Mirchandani, D. (2000). A decision model for integration across the business curriculum in the 21st century. Journal of Management Education, 24(1), 102–126. https://doi.org/10.1177/105256290002400107

Hoegl, M., & Gemuenden, H. G. (2001). Teamwork quality and the success of innovative projects: A theoretical concept and empirical evidence. Organization Science, 12(4), 435–449. https://doi.org/10.1287/orsc.12.4.435.10635

Huang, S.-Y., Kuo, Y.-H., & Chen, H.-C. (2020). Applying digital escape rooms infused with science teaching in elementary school: Learning performance, learning motivation, and problem-solving ability. Thinking Skills and Creativity, 37, 100681. https://doi.org/10.1016/j.tsc.2020.100681

Humphrey, S. E., Nahrgang, J. D., & Morgeson, F. P. (2007). Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. Journal of Applied Psychology, 92(5), 1332. https://doi.org/10.1037/0021-9010.92.5.1332

Jansen, J. J., Van Den Bosch, F. A., & Volberda, H. W. (2005). Managing potential and realized absorptive capacity: How do organizational antecedents matter? Academy of Management Journal, 48(6), 999–1015. https://doi.org/10.5465/ AMJ.2005.19573106

Jiang, X., & Li, Y. (2008). The relationship between organizational learning and firms’ financial performance in strategic alliances: A contingency approach. Journal of World Business, 43(3), 365–379. https://doi.org/10.1016/j.jwb.2007.11.003

Jiang, Z., Chan, J., Tan, B. C., & Chua, W. S. (2010). Effects of interactivity on website involvement and purchase intention. Journal of the Association for Information Systems, 11(1), 34–59. https://doi.org/10.17705/1jais.00218

Kahwajy, J., Kemanian, V., Keys, T., & Strebel, P. (2005). Emotional highs. Mastering executive education: How to combine content with context and emotion. The IMD Guide (pp. 13–20). Pearson Education.

Kaizer, B. M., Silva, C. E. S., de Pavia, A. P., & Zerbini, T. (2020). E-learning training in work corporations: A review on instructional planning. European Journal of Training and Development, 44(6/7), 615−636. https://doi.org/10.1108/EJTD-08- 2019-0149

Keys, B., & Wolfe, J. (1990). The role of management games and simulations in education and research. Journal of Management, 16(2), 307–336. https://doi.org/10.1177/014920639001600205

Kim, E.-J., Park, S., & Kang, H.-S. T. (2019). Support, training readiness and learning motivation in determining intention to transfer. European Journal of Training and Development, 43(3/4), 306−321. https://doi.org/10.1108/EJTD-08-2018-0075

Kirschner, P. A., Sweller, J., Kirschner, F., & Zambrano, J. (2018). From cognitive load theory to collaborative cognitive load theory. International Journal of Computer- Supported Collaborative Learning, 13(2), 213–233. https://doi.org/10.1007/s11412-018-9277-y

Kuhfeld, M., Soland, J., Tarasawa, B., Johnson, A., Ruzek, E., & Liu, J. (2020). Projecting the potential impact of COVID-19 school closures on academic achievement. Educational Researcher, 49(8), 549–565. https://doi.org/10.3102/0013189X20965918

Larson, J. R., Christensen, C., Abbott, A. S., & Franz, T. M. (1996). Diagnosing groups: Charting the flow of information in medical decision-making teams. Journal of Personality and Social Psychology, 71(2), 315. https://doi.org/10.1037//0022-3514.71.2.315

Lewis, M. (2004). Moneyball: The art of winning an unfair game. WW Norton & Company.

Lischewski, J., Seeber, S., Wuttke, E., & Rosemann, T. (2020). What influences participation in non-formal and informal modes of continuous vocational education and training? An analysis of individual and institutional influencing factors. Frontiers in Psychology, 11, 2821. https://doi.org/10.3389/fpsyg.2020.534485

Little, R. J., & Rubin, D. B. (2002). Bayes and multiple imputation. Statistical analysis with missing data (pp. 200–220). John Wiley & Sons, Inc. https://doi.org/10.1002/9781119013563.ch10

Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to parcel: Exploring the question, weighing the merits. Structural Equation Modeling, 9(2), 151–173. https://doi.org/10.1207/S15328007SEM0902_1

Loderer, K., Pekrun, R., & Lester, J. C. (2020). Beyond cold technology: A systematic review and meta-analysis on emotions in technology-based learning environments. Learning and Instruction, 70, 101162. https://doi.org/10.1016/j. learninstruc.2018.08.002

Magni, M., Paolino, C., Cappetta, R., & Proserpio, L. (2013). Diving too deep: How cognitive absorption and group learning behavior affect individual learning. Academy of Management Learning & Education, 12(1), 51–69. https://doi. org/10.5465/amle.2011.0096

Martin, X., & Salomon, R. (2003). Knowledge transfer capacity and its implications for the theory of the multinational corporation. Journal of International Business Studies, 34(4), 356–373. https://doi.org/10.1057/palgrave.jibs.8400037

Masrek, M. N., & Gaskin, J. E. (2016). Assessing users satisfaction with web digital library: The case of Universiti Teknologi MARA. The International Journal of Information and Learning Technology, 33(1), 36−56. https://doi.org/10.1108/IJILT-06-2015-0019

Mathieu, J. E., & Martineau, J. W. (1997). Individual and situational influences in training motivation. In J. K. Ford, S. W. J. Kozlowski, K. Kraiger, E. Salas, & M. S. Teachout (Eds.), Improving training effectiveness in work organizations (pp. 193−221). Psychology Press.

McCarthy, G., & Milner, J. (2020). Ability, motivation and opportunity: Managerial coaching in practice. Asia Pacific Journal of Human Resources, 58(1), 149–170. https://doi.org/10.1111/1744-7941.12219

Meyer, J. P. (2003). Four territories of experience: A developmental action inquiry approach to outdoor-adventure experiential learning. Academy of Management Learning & Education, 2(4), 352–363. https://doi.org/10.5465/amle.2003.11901956

Miller-Rososhansky, L., & Bryan, V. C. (2018). Use of technology-enabled informal learning in a learning organization. In V. C. Bryan, A. T. Musgrove, & J. R. Powers (Eds.), Handbook of research on human development in the digital age (pp. 33–42). IGI Global. https://doi.org/10.4018/978-1-5225-2838-8.ch002

Moreno, V., Cavazotte, F., & Alves, I. (2017). Explaining university students’ effective use of e-learning platforms. British Journal of Educational Technology, 48(4), 995–1009. https://doi.org/10.1111/bjet.12469

Morgeson, F. P., & Humphrey, S. E. (2006). The Work Design Questionnaire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of work. Journal of Applied Psychology, 91(6), 1321−1339. https://doi. org/10.1037/0021-9010.91.6.1321

Mpofu, M., & Hlatywayo, C. K. (2015). Training and development as a tool for improving basic service delivery: The case of a selected municipality. Journal of Economics, Finance and Administrative Science, 20(39), 133–136. https://doi.org/10.1016/j.jefas.2015.10.004

Muthén, L. K., & Muthén, B. O. (2010). Mplus: Statistical analysis with latent variables user’s guide (Version 6). Muthén & Muthén.

Olanipekun, T., Effoe, V., Bakinde, N., Bradley, C., Ivonye, C., & Harris, R. (2020). Learning styles of internal medicine residents and association with the in-training examination performance. Journal of the National Medical Association, 112(1), 44–51. https://doi.org/10.1016/j.jnma.2019.12.002

Oldham, G. R., & Da Silva, N. (2015). The impact of digital technology on the generation and implementation of creative ideas in the workplace. Computers in Human Behavior, 42, 5–11. https://doi.org/10.1016/j.chb.2013.10.041

Oldham, G. R., & Hackman, J. R. (2010). Not what it was and not what it will be: The future of job design research. Journal of Organizational Behavior, 31(2–3), 463–479. https://doi.org/10.1002/job.678

Ozkara, B. Y., Ozmen, M., & Kim, J. W. (2017). Examining the effect of flow experience on online purchase: A novel approach to the flow theory based on hedonic and utilitarian value. Journal of Retailing and Consumer Services, 37, 119–131. https://doi.org/10.1016/j.jretconser.2017.04.001

Pallud, J. (2017). Impact of interactive technologies on stimulating learning experiences in a museum. Information & Management, 54(4), 465–478. https://doi.org/10.1016/j.im.2016.10.004

Parboteeah, K. P., Hoegl, M., & Muethel, M. (2015). Team characteristics and employees’ individual learning: A cross-level investigation. European Management Journal, 33(4), 287–295. https://doi.org/10.1016/j.emj.2015.02.004

Park, C. W., & Mittal, B. (1985). A theory of involvement in consumer behavior: Problems and issues. In J. N. Sheth (Ed.), Research in consumer behavior 1 (pp. 201– 231). JAI Press.

Pearson, S. (2020). Anatomy: Beyond the COVID-19 pandemic. Academic Medicine, 95(11), e1. https://doi.org/10.1097/acm.0000000000003567

Ranganathan, R., Ghosh, A., & Rosenkopf, L. (2018). Competition–cooperation interplay during multifirm technology coordination: The effect of firm heterogeneity on conflict and consensus in a technology standards organization. Strategic Management Journal, 39(12), 3193−3221. https://doi.org/10.1002/smj.2786

Reinholt, M., Pedersen, T., & Foss, N. J. (2011). Why a central network position isn’t enough: The role of motivation and ability for knowledge sharing in employee networks. Academy of Management Journal, 54(6), 1277–1297. https://doi.org/10.5465/amj.2009.0007

Reychav, I., & Wu, D. (2015). Are your users actively involved? A cognitive absorption perspective in mobile training. Computers in Human Behavior, 44, 335–346. https://doi.org/10.1016/j.chb.2014.09.021

Ryan, R. M., & Connell, J. P. (1989). Perceived locus of causality and internalization: Examining reasons for acting in two domains. Journal of Personality and Social Psychology, 57(5), 749. https://doi.org/10.1037//0022-3514.57.5.749

Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68. https://doi.org/10.1037/0003-066X.55.1.68

Salas, E., & Cannon-Bowers, J. (2000). The anatomy of team training. In S. Tobias & J. D. Fletcher (Eds.), Training and retraining: A handbook for business, industry, goverment, and the military (pp. 312–335). Macmillan Library Reference.

Salas, E., Wildman, J. L., & Piccolo, R. F. (2009). Using simulation-based training to enhance management education. Academy of Management Learning & Education, 8(4), 559–573. https://www.jstor.org/stable/27759193

Salimon, M. G., Sanuri, S. M. M., Aliyu, O. A., Perumal, S., & Yusr, M. M. (2021). E-learning satisfaction and retention: A concurrent perspective of cognitive absorption, perceived social presence and technology acceptance model. Journal of Systems and Information Technology, 23(1), 109−129. https://doi.org/10.1108/ JSIT-02-2020-0029

Sarin, S., & McDermott, C. (2003). The effect of team leader characteristics on learning, knowledge application, and performance of cross-functional new product development teams. Decision Sciences, 34(4), 707–739. https://doi.org/10.1111/j.1540-5414.2003.02350.x

Scherbaum, C. A., & Ferreter, J. M. (2009). Estimating statistical power and required sample sizes for organizational research using multilevel modeling. Organizational Research Methods, 12(2), 347–367. https://doi.org/10.1177/1094428107308906

Seo, Y. W., Chae, S. W., & Lee, K. C. (2015). The impact of absorptive capacity, exploration, and exploitation on individual creativity: Moderating effect of subjective well-being. Computers in Human Behavior, 42, 68–82. https://doi.org/10.1016/j.chb.2014.03.031

Shen, C. W., & Ho, J. T. (2020). Technology-enhanced learning in higher education: A bibliometric analysis with latent semantic approach. Computers in Human Behavior, 104, 106177. https://doi.org/10.1016/j.chb.2019.106177

Stewart, D. D., & Stasser, G. (1995). Expert role assignment and information sampling during collective recall and decision making. Journal of Personality and Social Psychology, 69(4), 619−628. https://doi.org/10.1037//0022-3514.69.4.619

Tan, H. H., & Zhao, B. (2003). Individual-and perceived contextual-level antecedents of individual technical information inquiry in organizations. The Journal of Psychology, 137(6), 597–621. https://doi.org/10.1080/00223980309600637

Tang, C., Zhang, Y., & Reiter-Palmon, R. (2020). Network centrality, knowledge searching and creativity: The role of domain. Creativity and Innovation Management, 29(1), 72–84. https://doi.org/10.1111/caim.12351

Tannenbaum, S. I., & Yukl, G. (1992). Training and development in work organizations. Annual Review of Psychology, 43(1), 399–441. https://doi.org/10.1146/annurev.ps.43.020192.002151

Thabet, R., Hill, C., & Gaad, E. (2021). Perceptions and barriers to the adoption of blended learning at a research-based university in the United Arab Emirates. In M. Al- Emran, K. Shaalan, & A. Hassanien (Eds.), Recent advances in intelligent systems and smart applications (pp. 277–294). Springer. https://doi.org/10.1007/978-3-030-47411-9_16

Tharenou, P. (2001). The relationship of training motivation to participation in training and development. Journal of Occupational and Organizational Psychology, 74(5), 599–621. https://doi.org/10.1348/096317901167541

Tseng, C.-Y., Chang Pai, D., & Hung, C.-H. (2011). Knowledge absorptive capacity and innovation performance in KIBS. Journal of Knowledge Management, 15(6), 971–983. https://doi.org/10.1108/13673271111179316

Tucker, A. L., Nembhard, I. M., & Edmondson, A. C. (2007). Implementing new practices: An empirical study of organizational learning in hospital intensive care units. Management Science, 53(6), 894–907. https://doi.org/10.1287/mnsc.1060.0692

Turvey, K., & Pachler, N. (2020). Design principles for fostering pedagogical provenance through research in technology supported learning. Computers & Education, 146, 103736. https://doi.org/10.1016/j.compedu.2019.103736

Van de Ven, A., Bechara, J. P., & Sun, K. (2017). How outcome agreement and power balance among parties influence processes of organizational learning and non-learning. Journal of Management, 45(3), 1252–1283. https://doi.org/10.1177/0149206317698021

Vătămănescu, E. M., Cegarra-Navarro, J. G., Andrei, A. G., Dincă, V. M., & Alexandru, V. A. (2020). SMEs strategic networks and innovative performance: A relational design and methodology for knowledge sharing. Journal of Knowledge Management, 24(6), 1369–1392. https://doi.org/10.1108/JKM-01-2020-0010

Virick, M., DaSilva, N., & Arrington, K. (2010). Moderators of the curvilinear relation between extent of telecommuting and job and life satisfaction: The role of performance outcome orientation and worker type. Human Relations, 63(1), 137–154. https://doi.org/10.1177/0018726709349198

Wang, E. T., Tai, J. C., & Grover, V. (2013). Examining the relational benefits of improved interfirm information processing capability in buyer-supplier dyads. MIS Quarterly, 37(1), 149–173. https://www.jstor.org/stable/43825941

Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1), 35–57. https://doi.org/10.2307/25148667

Yildiz, H. E., Murtic, A., Zander, U., & Richtnér, A. (2019). What fosters individual- level absorptive capacity in MNCs? An extended motivation–ability–opportunity framework. Management International Review, 59(1), 93–129. https://doi.org/10.1007/s11575-018-0367-x

Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of Consumer Research, 12(3), 341–352. https://doi.org/10.1086/208520

Zalesny, M. D., & Ford, J. K. (1990). Extending the social information processing perspective: New links to attitudes, behaviors, and perceptions. Organizational Behavior and Human Decision Processes, 47(2), 205–246. https://doi.org/10.1016/0749-5978(90)90037-A

Zambrano, J., Kirschner, F., Sweller, J., & Kirschner, P. A. (2019). Effects of prior knowledge on collaborative and individual learning. Learning and Instruction, 63, 101214. https://doi.org/10.1016/j.learninstruc.2019.05.011

Zhang, P., Jiang, M., Adeel, A., & Yaseen, A. (2018). The effects of social relationships and the justice environment on creative idea endorsement. IEEE Access, 6, 44340–44350. https://doi.org/10.1109/ACCESS.2018.2840099