Abbott, M., Barraket, J., Erin, I., Castellas, P., Hiruy, K., Suchowerska, R., & Ward-Christie, L. (2019). “Evaluating the labour productivity of social enterprises in comparison to SMEs in Australia”, Social Enterprise Journal. Vol. 15 No. 2, pp. 179-194.
Adeyeye, O. J., Adeniji, A. A., Osinbanjo, A. O., & Oludayo, O. O. (2015). Effects of workplace ethics on employees and organisational productivity in Nigeria. In: 2nd Covenant University Conference on African Development Issues (CU-ICADI), 11th - 13th May, 2015, Africa Leadership Development Center, Covenant University, Ota, Nigeria
Bildstein, I., Gueldenberg, S. and Tjitra, H. (2013), "Effective leadership of knowledge workers: results of an intercultural business study", Management Research Review, Vol. 36 No. 8, pp. 788-804.
Butt, M. A., Nawaz, F., Hussain, S., Sousa, M. J., Wang, M., Sumbal, M. S., & Shujahat, M. (2019). “Individual knowledge management engagement, knowledge-worker productivity, and innovation performance in knowledge-based organizations: the implications for knowledge processes and knowledge-based systems”, Computational and Mathematical Organization Theory, 25 (3), pp. 336-356.
Chang, T. Y., Graff Zivin, J., Gross, T., & Neidell, M. (2019). “The effect of pollution on worker productivity: evidence from call center workers in China”, American Economic Journal: Applied Economics, 11 (1), pp. 72-151.
Cheng, C. H. & Lin, Y. (2002). “Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation”, European journal of operational research, 142 (1), pp. 174-186.
Drucker, P. F. (1999). “Knowledge-worker productivity: The biggest challenge”, California management review, 41 (2), pp. 79-94.
Escorpizo, R., Burghardt, E., & Richards, C. (2019). “Type of job, personal factors, and disease status are important contextual factors when measuring worker productivity in people with arthritis: a Delphi study”, Disability and Rehabilitation, pp. 1-8.
Ghorbanizadeh, V., Kheirandish, M., & Adnan Rad, A. (2017). “The main factors affecting the retention of knowledge staff with the aim of developing quality of work life programs in the Institute of International Energy Studies”, Quarterly Journal of Human Resource Management in the Oil Industry, No. 32. (in Persian)
Glock, C. H., Grosse, E. H., Jaber, M. Y., & Smunt, T. L. (2019). “Applications of learning curves in production and operations management: A systematic literature review”, Computers & Industrial Engineering, 131, pp. 422-441.
Hatam, N., Kavosi, Z., Lotfi, M., Zarifi, M., Tavakoli, A., Rahimi, M. (2014). Localization of the Knowledge Workers’ Productivity Questionnaire and Evaluation of the Productivity of Knowledge Workers of the Central Field of Shiraz University of Medical Sciences. International Journal of Travel Medicine and Global Health, 2(2), 51-60.
Hiyassat, M. A., Hiyari, M. A., & Sweis, G. J. (2016). “Factors affecting construction labour productivity: a case study of Jordan”, International Journal of Construction Management, 16 (2), pp. 138-149.
Huang, Y., Aimin, Y. A. N., & Smith, R. (2019). “Methodology for the development of knowledge management on organizational performance based on employees’ professional competence”, Revista De Cercetare Si Interventie Sociala, 64, pp. 85-96.
Kao, C. & Hwang, S. N. (2010). “Efficiency measurement for network systems: IT impact on firm performance”, Decision Support Systems, 48 (3), pp. 437-446.
Khaksar, S. M. S., Chu, M. T., Rozario, S., & Slade, B. (2020). “Knowledge-based dynamic capabilities and knowledge worker productivity in professional service firms The moderating role of organisational culture”, Knowledge Management Research & Practice, pp. 1-18.
Kianto, A., Shujahat, M., Hussain, S., Nawaz, F. and Ali, M. (2019), "The impact of knowledge management on knowledge worker productivity", Baltic Journal of Management, Vol. 14 No. 2, pp. 178-197
Kim, T. W., Lee, H. S., Park, M., & Yu, J. H. (2011). “Productivity management methodology using productivity achievement ratio”, KSCE Journal of Civil Engineering, 15 (1), pp. 23-31.
Lu, M. & Zhu, K. (2018). Performance evaluation of the insurance companies based on AHP, in AIP Conference Proceedings (Vol. 1955, No. 1, p. 040002). AIP Publishing.
Mir-Nemati, S.A. & Aniseh, M. (2017). “Study and recognition of factors affecting human resource productivity using fuzzy methods”, Second International Conference on Management and Accounting, Tehran, https://civilica.com/doc/642803. (in
Najafi, A. (2011). “Knowledge Workers Productivity and Stress Management in the Irancell Company”, Australian Journal of Basic and Applied Sciences, 5 (9), pp. 1412-1417.
Najafi, A. (2012). “Knowledge worker productivity measurement using fuzzy analytical network process (FANP)”, Scientific Research and Essays, 7 (31), pp. 2754-2769.
Nappi, I., de Campos Ribeiro, G. and Cochard, N. (2020), "The interplay of stress and workspace attachment on user satisfaction and workspace support to labour productivity", Journal of Corporate Real Estate, Vol. 22 No. 3, pp. 215-237
Palvalin, M., Van der Voordt, T., & Jylhä, T. (2017). “The impact of workplaces and self-management practices on the productivity of knowledge workers”, Journal of Facilities Management, 15 (4), pp. 423-438.
Peter S. WONG & Philip A. NECK, 2010. "A Practitioner’s Approach to Drucker’s Knowledge - Worker Productivity in the 21st Century: A New Model (Part One)," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 11(4), pages 685-695, October.
Ramírez, Y.W. and Nembhard, D.A. (2004), "Measuring knowledge worker productivity: A taxonomy", Journal of Intellectual Capital, Vol. 5 No. 4, pp. 602-628.
Rastgar, AA. & J’afari, T. (2019). “The Effect of Infrastructure Capabilities of Knowledge Management and Business Strategy on Organizational Performance through the Mediating Variable of Knowledge Management Process Capabilities”, Scientific Journal of Strategic Management of Organizational Knowledge, Vol. 2, Issue 5, pp. 173-208. (in Persian)
Sadeghipour, N. (2014). “Factors Affecting Manpower Productivity in Isfahan Province Electricity Distribution Company”, International Conference on Accounting and Management, Tehran, https://civilica.com/doc/392990
. (in Persian)
Sahibzada, U. F., Jianfeng, C., Latif, K. F., Shafait, Z., & Sahibzada, H. F. (2020). “Interpreting the impact of knowledge management processes on organizational performance in Chinese higher education: mediating role of knowledge worker productivity”, Studies in Higher Education, pp. 1-18.
Sayadinejad, R. & Kimia-Gari, A.M. (2019). “A model based on multivariate regression to identify effective factors, measure and improve the productivity of knowledge workers in the field of engineering”, 4th International Conference on Industrial Management, Yazd, https://civilica.com/doc/938063. (in Persian)
Sayed-Naqavi, M.A. & Ismaili, S. (2014). “Prioritize resources for evaluating the performance of knowledge employees”, 6th Knowledge Management Conference, Tehran, Iran. (in Persian)
Sheng, L. K., Khairuddin, S. M. H. S., Tehseen, S., & Yan, Y. H. (2019). “The influence of knowledge-based HRM practices on productivity of knowledge workers: A Study on Malaysian universities”. in 2019 13th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS), pp. 1-7.
Shujahat, M., Ali, B., Nawaz, F., Durst, S., & Kianto, A. (2018). “Translating the impact of knowledge management into knowledge‐based novation:The eglected and mediating role of knowledge‐worker satisfaction”, Human Factors and Ergonomics in Manufacturing & Service Industries, 28 (4), pp. 200-212.
Shujahat, M., Sousa, M. J., Hussain, S., Nawaz, F., Wang, M., & Umer, M. (2019). “Translating the impact of knowledge management processes into knowledge-based innovation: The neglected and mediating role of knowledge-worker productivity”, Journal of Business Research, 94, pp. 442-450.
Sondari, M. C. & Apriyanti, E. (2017). Knowledge Worker Productivity Indicators for Small Consultant Businesses: A Thematic Analysis.
Varmazyar, M., Dehghanbaghi, M., & Afkhami, M. (2016). “A novel hybrid MCDM model for performance evaluation of research and technology organizations based on BSC approach”, Evaluation and program planning, 58, pp. 125-140.