| Literature DB >> 34070535 |
José Moleiro Martins1,2, Hira Aftab3, Mário Nuno Mata1,4, Muhammad Ussama Majeed3, Sumaira Aslam3, Anabela Batista Correia1, Pedro Neves Mata5.
Abstract
The global need to preserve ecology has propelled the green movement across the globe. An emerging managerial challenge for all organizations is to protect natural resources by reducing their negative impact on the environment and increase sustainable performance. Greening is the need of the age to conserve natural resources. This study investigates the impact of green human resource management practice-i.e., green hiring-on the sustainable performance of public and private healthcare organizations. A quantitative research approach was used for data collection. Scale survey of 160 responses was gathered from public and private healthcare organizations. Partial least square-structural equation modeling was used for data analysis. The study results suggest that green recruitment has a positive and significant impact on environmental performance, economic performance, and social performance. Path coefficients test also revealed that green performance management and compensation significantly mediate the relationship between green hiring and sustainable performance of public and private healthcare organizations. This study is helpful for organizations in adapting GHRM practices that will benefit the organizations in all ways. This study also provides a better understanding to policymakers on how to promote GHRM practices and increase sustainability in organizations.Entities:
Keywords: and compensation; environmental performance; green hiring; green human resource management; green performance management; sustainability
Year: 2021 PMID: 34070535 PMCID: PMC8198420 DOI: 10.3390/ijerph18115654
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Conceptual framework.
Demographic profile of the respondents.
| Items | Category | Distribution | |
|---|---|---|---|
| Frequency | Percentage | ||
| Gender | Male | 72 | 45% |
| Female | 88 | 55% | |
| Sector | Public | 72 | 45% |
| Private | 88 | 55% | |
| Family Origin | Urban | 110 | 68.8% |
| Rural | 50 | 31.3% | |
| Age Bracket | 20–30 | 78 | 48.8% |
| 30–40 | 62 | 38.8% | |
| 40–50 | 18 | 11.3% | |
| 50 above | 2 | 1.3% | |
| Job Designation | HR position | 62 | 38.8% |
| Non-HR position | 98 | 61.3% | |
| Level of Corporate Hierarchy | Top Level | 45 | 28.1% |
| Middle Level | 87 | 54.4% | |
| Operational Level | 28 | 17.5% | |
References of questionnaire distributed and collected.
| Hospitals | Questionnaires Collected | Questionnaires Distributed |
|---|---|---|
| General Hospital, Lahore | 25 | 50 |
| Children’s Hospital, Lahore | 15 | 50 |
| Farooq Hospital, Lahore | 50 | 75 |
| Sheikh Zahid Hospital, Lahore | 50 | 75 |
| National Hospital, Lahore | 20 | 50 |
| Total | 160 | 300 |
Construct reliability and validity.
| Constructs | Cronbach’s Alpha | Composite Reliability | Average Variance Extracted (AVE) |
|---|---|---|---|
| ECP | 0.797 | 0.791 | 0.526 |
| EP | 0.816 | 0.866 | 0.519 |
| GH | 0.895 | 0.920 | 0.657 |
| GPMC | 0.906 | 0.924 | 0.605 |
| SP | 0.814 | 0.860 | 0.623 |
Fornell–Larker criterion.
| Constructs | ECP | EP | GH | GPMC | SP |
|---|---|---|---|---|---|
| ECP | 0.703 | ||||
| EP | 0.678 | 0.720 | |||
| GH | 0.440 | 0.510 | 0.778 | ||
| GPMC | 0.343 | 0.428 | 0.840 | 0.811 | |
| SP | 0.385 | 0.483 | 0.907 | 0.828 | 0.727 |
Figure 2SEM model of the study.
Significance of path coefficients.
| Suggested Paths | Original Sample (O) | Mean (M) | Standard Deviation (STDEV) | T Statistics | |
|---|---|---|---|---|---|
| GH → ECP | 0.347 | 0.356 | 0.070 | 4.928 | 0.000 |
| GH → EP | 0.430 | 0.438 | 0.061 | 7.006 | 0.000 |
| GH → SP | 0.326 | 0.337 | 0.062 | 5.221 | 0.000 |
Coefficient of determination (R2 Value).
| Endogenous Construct | R Square | R Square Adjusted |
|---|---|---|
| ECP | 0.456 | 0.448 |
| EP | 0.710 | 0.708 |
| SP | 0.569 | 0.557 |
Specific indirect effect.
| Suggested Paths | Original Sample (O) | Mean (M) | Standard Deviation (STDEV) | T Statistics | |
|---|---|---|---|---|---|
| GH → GPMC → ECP | 0.457 | 0.468 | 0.130 | 3.522 | 0.000 |
| GH → GPMC → EP | 0.478 | 0.485 | 0.129 | 3.698 | 0.000 |
| GH → GPMC → SP | 0.429 | 0.446 | 0.116 | 3.688 | 0.000 |