Factors Affecting Labor Productivity in the Coconut Oil Industry in Kekeran Hamlet, Batu Layar Village, West Lombok Regency

Wawan Turmuzi Baedowi; Helmy Fuadi; Ahmad Zaenal Wafik

doi:10.59535/pv475n29

Authors

Wawan Turmuzi Baedowi Development Studies Economics Study Program, Faculty of Economics and Business, University of Mataram, Indonesia Author
Helmy Fuadi Development Studies Economics Study Program, Faculty of Economics and Business, University of Mataram, Indonesia Author
Ahmad Zaenal Wafik Development Studies Economics Study Program, Faculty of Economics and Business, University of Mataram, Indonesia Author

DOI:

https://doi.org/10.59535/pv475n29

Keywords:

Wages, Age, Gender, Experience, Productivity

Abstract

This study investigates the factors influencing labor productivity in the coconut oil industry in Kekeran Hamlet, Batu Layar Village, West Lombok Regency. Utilizing a quantitative approach, the research focuses on four independent variables—wages, age, work experience, and gender—while labor productivity serves as the dependent variable. Data were collected through surveys, interviews, and documentation involving 52 randomly selected respondents from a population of 108 workers. The analysis employed Confirmatory Factor Analysis (CFA) and Principal Component Analysis (PCA) to assess the significance and contribution of each factor. The results show that wages are the most dominant factor affecting productivity, followed by gender differences. The study highlights the importance of adequate compensation and gender-sensitive approaches to enhance productivity in local resource-based industries. Recommendations for future research include the use of Common Factor Analysis for deeper exploration and comparison.

References

[1] N. P. Hariram, K. B. Mekha, V. Suganthan, and K. Sudhakar, “Sustainalism: An Integrated Socio-Economic-Environmental Model to Address Sustainable Development and Sustainability,” Sustainability, vol. 15, no. 13, Art. no. 13, Jan. 2023, doi: 10.3390/su151310682.

[2] S. Bai, B. Zhang, Y. Ning, and Y. Wang, “Comprehensive analysis of carbon emissions, economic growth, and employment from the perspective of industrial restructuring: a case study of China,” Environ Sci Pollut Res, vol. 28, no. 36, pp. 50767–50789, Sep. 2021, doi: 10.1007/s11356-021-14040-z.

[3] X. Yu, A. Dilanchiev, and S. Bibi, “Enhancing labor productivity as a key strategy for fostering green economic growth and resource efficiency,” Heliyon, vol. 10, no. 3, Feb. 2024, doi: 10.1016/j.heliyon.2024.e24640.

[4] P. García-Gómez, H.-M. von Gaudecker, and M. Lindeboom, “Health, disability and work: patterns for the working age population,” Int Tax Public Finance, vol. 18, no. 2, pp. 146–165, Apr. 2011, doi: 10.1007/s10797-010-9150-z.

[5] C. M. van Praag and P. H. Versloot, “What is the value of entrepreneurship? A review of recent research,” Small Bus Econ, vol. 29, no. 4, pp. 351–382, Dec. 2007, doi: 10.1007/s11187-007-9074-x.

[6] L. A. Downey, P. J. Johnston, K. Hansen, J. Birney, and C. Stough, “Investigating the mediating effects of emotional intelligence and coping on problem behaviours in adolescents,” Australian Journal of Psychology, vol. 62, no. 1, pp. 20–29, 2010, doi: 10.1080/00049530903312873.

[7] C. S. Dewa, D. McDaid, and S. L. Ettner, “An International Perspective on Worker Mental Health Problems: Who Bears the Burden and How are Costs Addressed?,” Can J Psychiatry, vol. 52, no. 6, pp. 346–356, Jun. 2007, doi: 10.1177/070674370705200603.

[8] C. Maslach and M. P. Leiter, “Understanding the burnout experience: recent research and its implications for psychiatry,” World Psychiatry, vol. 15, no. 2, pp. 103–111, 2016, doi: 10.1002/wps.20311.

[9] C. B. Bhattacharya, S. Sen, and D. Korschun, “Using Corporate Social Responsibility to Win the War for Talent,” 2008, Social Science Research Network, Rochester, NY: 2333549. Accessed: Jul. 22, 2025. [Online]. Available: https://papers.ssrn.com/abstract=2333549

[10] M. L. Ranney, Z. F. Meisel, E. K. Choo, A. C. Garro, C. Sasson, and K. Morrow Guthrie, “Interview-based Qualitative Research in Emergency Care Part II: Data Collection, Analysis and Results Reporting,” Academic Emergency Medicine, vol. 22, no. 9, pp. 1103–1112, 2015, doi: 10.1111/acem.12735.

[11] H. Poorter, Ü. Niinemets, L. Poorter, I. J. Wright, and R. Villar, “Causes and consequences of variation in leaf mass per area (LMA): a meta-analysis,” New Phytologist, vol. 182, no. 3, pp. 565–588, 2009, doi: 10.1111/j.1469-8137.2009.02830.x.

[12] B. Williams, A. Onsman, and T. Brown, “Exploratory Factor Analysis: A Five-Step Guide for Novices,” Australasian Journal of Paramedicine, vol. 8, pp. 1–13, Jan. 2010, doi: 10.33151/ajp.8.3.93.

[13] L. Belkhiri and T. S. Narany, “Using Multivariate Statistical Analysis, Geostatistical Techniques and Structural Equation Modeling to Identify Spatial Variability of Groundwater Quality,” Water Resour Manage, vol. 29, no. 6, pp. 2073–2089, Apr. 2015, doi: 10.1007/s11269-015-0929-7.

[14] A. Teixeira, M. R. Ferreira, A. Correia, and V. Lima, “Students’ perceptions of corporate social responsibility: evidences from a Portuguese higher education institution,” Int Rev Public Nonprofit Mark, vol. 15, no. 2, pp. 235–252, Jun. 2018, doi: 10.1007/s12208-018-0199-1.

[15] T. H. Thien and N. X. Hung, “Intellectual capital and investment efficiency: The mediating role of strategic management accounting practices,” Cogent Business & Management, vol. 10, no. 2, p. 2207879, Dec. 2023, doi: 10.1080/23311975.2023.2207879.

[16] M. J. Peláez Zuberbühler, C. Coo Calcagni, I. M. Martínez, and M. Salanova, “Development and validation of the coaching-based leadership scale and its relationship with psychological capital, work engagement, and performance,” Curr Psychol, vol. 42, no. 1, pp. 648–669, Jan. 2023, doi: 10.1007/s12144-021-01460-w.

[17] R. C. MacCallum, K. F. Widaman, K. J. Preacher, and S. Hong, “Sample Size in Factor Analysis: The Role of Model Error,” Multivariate Behavioral Research, vol. 36, no. 4, pp. 611–637, Oct. 2001, doi: 10.1207/S15327906MBR3604_06.

[18] G. R. Elsworth, A. Beauchamp, and R. H. Osborne, “Measuring health literacy in community agencies: a Bayesian study of the factor structure and measurement invariance of the health literacy questionnaire (HLQ),” BMC Health Serv Res, vol. 16, no. 1, p. 508, Sep. 2016, doi: 10.1186/s12913-016-1754-2.

[19] S. M. Mirbagheri, A. O. Rafiei Atani, and M. Parsanejad, “The Effect of Collective Decision-Making on Productivity: A Structural Equation Modeling,” SAGE Open, vol. 13, no. 4, p. 21582440231219046, Oct. 2023, doi: 10.1177/21582440231219046.

[20] T. Hong, Şe. Purzer, and M. E. Cardella, “A Psychometric Re-Evaluation of the Design, Engineering and Technology (DET) Survey,” Journal of Engineering Education, vol. 100, no. 4, pp. 800–818, 2011, doi: 10.1002/j.2168-9830.2011.tb00037.x.