The Relationship between Recruitment, Affective Commitment, Relational Contract and Productivity in Organizations in Lusaka-Zambia

Yıl 2019, , 29 - 47, 26.06.2019

Sylvia Atoko , Thomas Taylor , Chanda Sichinsambwe

https://doi.org/10.19148/ijhbs.482373

Cited By: 1

Öz

The aim of this research was to empirically establish
the relationship between recruitment, affective commitment, relational contract
and productivity in selected Lusaka based organizations in Zambia. The
Organizational Commitment Theory, Relational Theory of Contract, and Social
Exchange Theory guided the conceptualization of the research on the assumption
that, recruitment or engagement of employees encapsulates in a perceived
relational trust between the employer and the employee; In other words, each
party to the contractual agreement on employment engagement know their
respective roles. From the conceptual postulation, the following hypotheses
emerged: there is a relationship between recruitment and productivity; there is
a relationship between recruitment and affective commitment; there is a
relationship between recruitment and relational contract, there is a
relationship between affective commitment and productivity; and finally, there
is a relationship between relational contract and productivity. The methodology
was a cross-sectional descriptive survey. A Structural Equation Modeling (SEM)
utilizing latent variables and partial least-squares (LVPLS) was employed for
the analysis. The results indicated that, there is a relationship between
recruitment and productivity, affective commitment and relational contract.
Contrary, there is no relationship between relational contract and affective
commitment on productivity. The conclusion was that, there is a relationship between
recruitment, affective commitment and relational contract.

Anahtar Kelimeler

Recruitment, Affective Commitment, Relational Contract, Productivity, Lusaka

Kaynakça

• References
• Adebola Y. B. and Banjo K. A. (2017) Recruitment and Selection Procedures and their Relative Effectiveness on Employees’ Performance in the Hospitality Industry in Ogun State, International Journal of the Guild of Contemporary Academic Researchers (IJGCAR). ISSN 2449 – 1527 2 (2) pp.55 – 62
• Allen, N. J., & Meyer, J. P. (1990) The measurement and antecedents of affective, continuance and normative commitment to the organization, Journal of Occupational Psychology, 63(1), 1-18.
• Anderson, J.C., & Gerbing, D.W. (1988) Structural equation modeling in practice: a review and recommended two-step approach,. Psychological Bulletin, 103(3), 411–423.
• Armstrong M. (2006) Human Resource Management Practice (10th edition) Kogan Page limited Publishers, London
• Armstrong, J. S., & Overton, T. S. (1977) Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14, 396-402.
• Ary, D., Jacobs, L. C., & Razavieh, A. (2002) Introduction to research in education. Belmont, CA: Wadsworth.
• Bacon, L. D. (1999). Using LISREL and PLS to Measure Customer Satisfaction, Sawtooth Software Conference Proceedings, La Jolla, California, Feb 2-5, 305-306.
• Bagozzi, R.P., & Yi, Y. (1988) On the evaluation of structural equation models. Academy of Marketing Science, 6 (1), 74–93.
• Bird, R.C. (2005) Employment as a Relational Contract, Journal of Labor and Employment Law, Vol. 8, https://ssrn.colm/abstaract=732645
• Brewster, C. and Mayrhofer, W. (2012) Handbook of Research on Comparative Human Resources Management, Edward Elgar Publishing, Northampton, MA
• Carmody, P. (2009): “An Asian – Driven Economic Recovery in Africa? The Zambian Case”, World Development, Vol. 37, Issue 7, pp 1197 – 1207
• Catano, V. W., Wiesner, W. H., Hackett, R. D and Methot, L. (2010) Recruitment and selection in Canada (4th ed.) Nelson Education, Toronto.
• Central Statistical Office (2013) Zambia Labour Force Survey 2012, Ministry of Labour and Social Security
• Central Statistical Office (2016) Zambia Labour Force Survey 2014, Ministry of Labour and Social Security
• Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (295–336). Mahwah, New Jersey: Lawrence Erlbaum Associates.
• Chin, W. W., Marcolin, B. L., & Newsted, P. R. (1996). A partial least squares latent variable modelling approach for measuring interaction effects: Results from a Monte Carlo simulation study and voice mail emotion/adoption study. Paper presented at the 17th International
• Coyle-Shapiro, J. A. M., & Conway, N. (2005) Perceived organizational support and employee diligence, commitment, and innovation, Journal of Applied Psychology, 90, 774-781
• Dahie, M. A. (2017). Human Resource Management Practices and Organizational Performance: Case Study from Hormuud Telecom in Mogadishu-Somalia. Academic Publishing House, European Researcher Series A. 78–87
• Derchert-Hampe Consulting [DHC](n.d) http://www.dechert-hampe.com/index.php/what-we-do/areas-of-focus/39-services/blog-option-content/103-organisation-productivity-model [Accessed 29th October 2018]
• Edgar, F., & Geare, A. (2005) HRM practice and employee attitudes: Different measures different results, Personnel Review, 34(5), 534-549
• Ekwoaba J. O., Ikeije U. U. and Ufoma N. (2015) The Impact of Recruitment and Selecation Criteria on Organizational Performance, Global Journal of Human Resource Management, Vol. 3, No. 2, pp. 22 – 33
• Esposito Vinzi, V., Trinchera, L., & Amato, S. (2010). PLS Path Modeling: From Foundations to Recent Developments and Open Issues for Model Assessment and Improvement. In. V. Esposito Vinzi, W.W. Chin, J. Henseler & H. Wang (Eds) Handbook of Partial Least Squares: Concepts, Methods and Applications (47-82) Berlin, Germany: Springer Berlin Heidelberg Frank, B. & Hennig-Thurau, T. (2008) Identifying hidden structures in marketing’s structural models through Universal Structure Modeling: An explorative Bayesian Neural Network complement to LISREL and PLS', Marketing, Journal of Research and Management, 4(2), 47-66
• Fornell, C., & Larcker, D.F., (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1), 39-50.
• Haenlein, M. & Kaplan, A. M. (2004) A beginner’s guide to partial least squares analysis, Understanding Statistics, 3(4), 283–297. Hafiz A.Z (2017) Relationship between Organizational Commitment and Employees’ Performance Evidence from Banking Sector of Lahore, Arabian Journal of Business and Management Review. ISSN: 2223-5833 Vol. 7, Issue 2. pp.1 – 7
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010) Multivariate data analysis (7th ed.). Englewood Cliffs: Prentice Hall
• Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2013) A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks: Sage.
• Hair, J. F., Ringle, C. M., &Sarstedt, M. (2011) PLS-SEM: Indeed a silver bullet, Journal of Marketing Theory and Practice, 19(2), 139–151.
• Hair, J.F., Sarstedt, M., Ringle, C.M. & Mena, J.A., (2012) An assessment of the use of partial least squares structural equation modeling in marketing research, Journal of the Academy of Marketing Science, 40(3), 414-433.
• Henseler, J. (2010). On the convergence of the partial least squares path modeling algorithm. Computational Statistics, 25(1), 107–120.
• Henseler. J. and Sarstedt, M. (2013) Goodness-of-fit indices for partial least squares path modeling, Computational Statistics, 28 (2), 565-580
• Henseler, J., Ringle, C., & Sinkovics, R. (2009) The use of partial least squares path modeling in international marketing, Advances in International Marketing, 20 (2009), 277–320.
• Hoyle, R. H. (ed.) (1995) Structural Equation Modeling. Thousand Oaks, CA.: SAGE Publications, Inc. Page 31 of 32 http://marketing-bulletin.massey.ac.nz Marketing Bulletin, 2013, 24, Technical Note 1
• Hulland, J. (1999) Use of partial least squares (PLS) in strategic management research: a review of four recent studies, Strategic Management Journal, 20(2), 195–204.
• Hwang, H., Malhotra, N. K., Kim, Y., Tomiuk, M. A., & Hong, S. (2010) A comparative study on parameter recovery of three approaches to structural equation modeling, Journal of Marketing Research, 47 (Aug), 699-712.
• Igharia, M. & Greenhaus, J. H. (1992) Determinants of MIS employees’ turnover intentions: A structural equation model, Association for Computing Machinery. Communications of the ACM, 35(2), 34-49.
• Jansen, D. (1988) “Trade, Exchange Rate and Agricultural Pricing Policies in Zambia”, Washington, D.C.: The World Bank.
• Kanyemba, M., Iwu, C. G., Allen-Ile, C. O. K. (2015), Impact of Recruitment and Selection on Organization Productivity. Evidence from Staff of a University in South Africa, Corporate Ownership of Control, Volume 12, Issue 2, Winter 2015
• Karia, O.A., Omari, S., Mwanaongoro, S., and Ondieki, A. (2016) Impact of Recruitment and Selection on Performance of the Public Water Utilities in Tanzania African Journal of Education and Human Development. Vol. 2 (1) pp.39 -45, ISSN:2518 – 0304.
• Kline, R. B. (2005) Principles and practice of structural equation modeling (2nd ed.). New York, NY: Guilford
• Kothari, C R (2004): Research Methodology: Methods and Techniques, India: New
• Lambert, D.M., & Harrington, T.C. (1990) Measuring nonresponse bias in customer service mail surveys, Journal of Business Logistics, 11(2), 5–25
• Macneil, I. (1978) Contracts: Adjustments of Long Term Economic Relations under Classical, Neoclassical and Relational Contract Law 72, Nw,U.L. Rev. 854, 857 (1978)
• Mercurio, Z. A. (2015) An Integrative Literature Review, Human Resources Development Review, Vol. 14(4) 389-414
• Meyer, J. P. and Allen, N. J. (1991) A Three Component Conceptualization of Organizational Commitment, Human Resource Management Review, 1, 61-89
• Mohammed, A., Lina, S., & Phillip, M., (2017) Herzberg’s Two-Factor Theory, Life Science Journal, pp. 12 – 16.
• Mowday, R. T., Steers, R. M., & Porter, L. W. (1979), The measurement of organizational commitment. Journal of Vocational Behavior, 14, 224-247.
• Muslim A. &. Wan K. W. (2014) The Impact of Human Resource Management Practices on Organizational Performance Evidence from a Public University. TQM Journal 26(2) pg 125 – 142
• Muslim A. &. Wan K. W. (2014) The Impact of Human Resource Management Practices on Organizational Performance Evidence from a Public University, TQM Journal 26(2) pg 125 – 142.
• Musonda, A. (2017) The Current Labour and Employment Laws in Zambia. Zambia Educational Publishing House: Lusaka, Zambia.
• Niles, N. J. (2013) Basic Concepts of Health Care: Human Resources Management, Jones & Bartlett Learning, Burlington, M.A.
• Oaya, Z. C.T.O., Ogbu, J. O. and Remilekun, O. G. (2017), Impact of Recruitment and Selection Strategy on Employees’ Performance: A Study of Three Selected Manufacturing Companies in Nigeria, International Journal of Innovation and Economic Development, Volume 3, Issue 3, August, pp. 32 – 43.
• Obeidat B. Y., Masa’deh R., and Abdallah A. B. (2014) The Relationship Among Human Resource Management Practices, Organizational Commitment and Knowledge Management Processes: A Structural Equation Modeling Approach, International Journal of Business and Management. ISSN: 1833 – 8119, E-ISSN 1833-8119. Vol. 9 No. 3
• Ofobruku S. A., & Iheabunike O. B., (2013) Assessment of Recruitment Practice on Organization Performance: Empirical Study of Hospitality Business in Abuja, European Scientific Journal. ISSN: 1857 – 7881, ISSN: 1857 – 7431, Vol. 9, No. 29, pp.294 – 305
• Ofori, D. and Aryeetey, M. (2011) Recruitment and Selection Practices in Small and Medium Enterprises in Ghana, International Journal of Business Administration, Vol. 2, No. 3, pp.45-60
• Opatha, H. H. D. N. P. (2010) Human Resources Management. Author Published. Colombo
• Petter, S., Straub, D., and Rai, A. (2007) Specifying formative constructs in information systems research, MIS Quarterly, 31 (4), 623-656.
• Pushpendra S., Garima M., Monika J., & Albert S., (2017) Recruitment & Selection and its Impact on Organizational Productivity, International Journal of Core Engineering & Management. Vol. 4, ISSN 2348 – 9510. pp. 26 -35
• Reinartz, W. J., Haenlein, M. & Henseler, J. (2009) An empirical comparison of the efficacy of covariance-based and variance-based SEM”, International Journal of Market Research, 26 (4), 332–344
• Remenyi, D., Williams, B., Money, A. and Swartz, E. (1998): Doing research in business and Management. London: Sage Publications.
• Ringle, C., Wende, S., & Will, A. (2005) SmartPLS 2.0 (Beta), Hamburg (www.smartpls.de)
• Sangeetha, K. (2010) Effective Recruitment: A framework, IUP Journal of Business Strategy, 7 (1/2), pp. 93-107, Business Source Complete, EBSCOhost [Accessed 29th October 2018)
• Seeck, H. and Parzefall, M. (2010) From HRM to Psychological Contracting – the Case of Finnish Mobile Content Producing Companies, The International Journal of Human Resource Management, 21 (15). pp. 2677-2693. ISSN 0958-5192
• Sosik, J., Kahai, S, Piovoso, M. J. (2009), Silver bullet or voodoo statistics? A primer for using the partial least squares data analytic technique in group and organization research. Emerald Management Reviews: Group & Organization Management, 34(1), 5-36
• Speidel, R. E. (2000) The Characteristics and Challenges of Relational Contract, 94 Nw. UL Rev, 823,823, 828
• Statsoft (2013) Structural Equation Modeling: Statsoft Electronic Statistics Textbook. http://www.statsoft.com/textbook/structural-equation-modeling
• Stefania, D. S. (2015) Expectancy Value Theory: Motivating Healthcare Workers, American International Journal of Contemporary Research., Vol. 5. No. 2 pp. 19-23.
• Syverson, C. (2010), “What determines Productivity?” (No.W15712) National Bureau of Economic Research
• Wold, H. (1973) Nonlinear Iterative Partial Least Squares (NIPALS) Modeling: Some Current Developments, in Paruchuri R. Krishnaiah (Ed.), Multivariate Analysis (Vol. 3, pp. 383-407). New York: Academic Press.
• Wold, H. (1985) Partial Least Squares. In S. Kotz& N. L. Johnson (Eds.), Encyclopedia of Statistical Sciences, (Vol. 6, pp. 581–591). New York: John Wiley & Sons.
• Wong, C., Hui, C., & Law, K. S. (1995) Causal relationship between attitudinal antecedents to turnover, Academy of Management Journal, 4, 342-346
• Wong, K. K. (2010). Handling small survey sample size and skewed dataset with partial least square path modeling, Vue: The Magazine of the Marketing Research and Intelligence Association, November, 20-23.
• Wong, K. K. (2011). Review of the Handbook of Partial Least Squares: Concepts, Methods and Applications, by V. Esposito Vinzi, W.W. Chin, J. Henseler & H. Wang
• Yesufu, L (2016) The Effect of Human Resource Practices on the Psychological Contract of Academics. Doctor of Business Administration (DBA)