Mediating Effect of Job Satisfaction on the Relationship between Work-Life Balance and Job Performance among Academics: Data Screening

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    This paper highlights the data screening for the research on mediating effect of job satisfaction on the relationship between work-life balance and job performance among full-time academics. It had 354 samples from the public universities located in Indonesia-Malaysia-Thailand Growth Triangle (IMT-GT). The data screening procedure was applied to identify problematic patterns within the data set of the study. It analyzed the missing values, outliers, normality test, and multicollinearity test. The results of the data screening showed that the data was ready for further multivariate analysis.

  • References

      [1] Guthrie, J., Evans, E. & Burritt, R. (2014). Australian accounting academics: Challenges and possibilities. Meditari Accountancy Research, 22(1), 20-37.

      [2] Cardoso, S., Rosa, M.J. & Santos, C.S. (2013). Different academics’ characteristics, different perceptions on quality assessment? Quality Assurance in Education, 21(1), 96-117.

      [3] Hayat, M.J., Schmiege, S.J. & Cook, P.F. (2014). Perspectives on statistics education: Observations from statistical consulting in an academic nursing environment. Journal of Nursing Education, 53(4), 185-191.

      [4] Kainth, J.S. & Verma, H.V. (2011). Consumption values: Scale development and validation. Journal in Advances in Management Research, 8(2), 285-300.

      [5] Salem, M.A., Shawtari, F.A., Shamsudin, M.F. & Hussain, H.I. (2016). The relation between stakeholders integration and environmental competitiveness. Social Responsibility Journal, 12(4), 755-769.

      [6] Acock, A.C. (2005). Working with missing values. Journal of Marriage and Family, 67(4), 1012-1028.

      [7] Rhoads, H. (2012). Problems with tests of the missingness mechanism in quantitative policy studies. Statistics, Politics, and Policy, 3(1), 1-23.

      [8] Siddique, J., Harel, O., Crespi, C.M. & Hedeker, D. (2014). Binary variable multiple-model multiple imputation to address missing data mechanism uncertainty: Application to a smoking cessation trail. Statistics in Medicine, 33(17), 3013-3028.

      [9] Zurada, J. (2012). Does removing/replacing missing values improving the model’s classification performance? International Journal of Management & Information Systems, 16(3), 215-220.

      [10] Zhang, S. (2011). Information enhancement for data mining. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(4), 284-295.

      [11] Hair, J.F., Jr., Hult, G.T.M., Ringle, C.M. & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks: SAGE Publications.

      [12] Lujja, S., Mohammad, M.O. & Hassan, R. (2016). Modelling public behavioral intention to adopt Islamic banking in Uganda: The theory of reasoned action. International Journal of Islamic and Middle Eastern Finance and Management, 9(4), 583-600.

      [13] Hair, J.F., Jr., Black, W.C., Babin, B.J. & Anderson, R.E. (2010). Multivariate data analysis – A global perspective (7th ed.). Upper Saddle River: Pearson Education.

      [14] Chan, X.W., Kalliath, T., Brough, P., O’Driscoll, M., Sue, O. & Timms, C. (2017). Self-efficacy and work engagement: Test of a chain model. International Journal of Manpower, 38(6), 819-834.

      [15] Aguinis, H., Gottfredson, R.K. & Joo, H. (2013). Best practice recommendations for defining, identifying, and handling outliers. Organizational Research Methods, 16(2), 270-301.

      [16] Yan, J.H., Rodriguez, W.A. & Thomas, J.R. (2005). Does data distribution change as a function of motor skill practice? Research Quarterly for Exercise and Sport, 76(4), 494-499.

      [17] Siddiqi, A.F. (2014). An observatory note on tests for normality assumptions. Journal of Modelling in Management, 9(3), 290-305.

      [18] Razali, N.M. & Wah, Y.B. (2011). Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests. Journal of Statistical Modeling and Analytics, 2(1), 21-33.

      [19] Anwer, M.A., Esichaikul, V., Rehman, M. & Anjum, M. (2016). E-government services evaluation from citizen satisfaction perspective: A case of Afghanistan. Transforming Government: People, Process and Policy, 10(1), 139-167.

      [20] Farooq, R. (2016). Role of structural equation modeling in scale development. Journal of Advances in Management Research, 13(1), 75-91.

      [21] De Marco, A., Mangano, G. & Zou, X.Y. (2012). Factors influencing the equity share of build-operate-transfer projects. Build Environment Project and Asset Management, 2(1), 70-85.

      [22] Cheung, C. & Law, R. (2001). Determinants of tourism hotel expenditure in Hong Kong. International Journal of Contemporary Hospitality Management, 13(3), 151-158.

      [23] Winston, B. & Fields, D. (2015). Seeking and measuring the essential behaviors of servant leadership. Leadership & Organization Development Journal, 36(4), 413-434.

      [24] Davidson, M.J., Wood, G.J. & Harvey, J.T. (2012). A cross-cultural study in the UK and Australia of pay expectations and entitlements: A case of vanishing differences? Gender in Management: An International Journal, 27(3), 165-185.




Article ID: 22581
DOI: 10.14419/ijet.v7i4.28.22581

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.