Mustafa Nal, Erhan Dag and Yasar Demir
The first aim of this study is to determine the effect of lean leadership on the workload and job satisfaction of healthcare workers, and the second aim is to reveal the…
Abstract
Purpose
The first aim of this study is to determine the effect of lean leadership on the workload and job satisfaction of healthcare workers, and the second aim is to reveal the moderating role of workload and employee gender in this relationship.
Design/methodology/approach
In this study, we created a comprehensive model to determine the effect of lean leadership on the workload and job satisfaction of healthcare employees and to reveal the moderating role of workload and employee gender in this relationship. We collected 1,207 valid questionnaires among Turkish health workers.
Findings
The results indicate that: (1) Lean leadership reduces perceived workload, (2) Lean leadership increases job satisfaction, (3) Workload moderates the effect of lean leadership on job satisfaction and (4) Employee gender moderates the effect of lean leadership on job satisfaction and workload. These findings have provided theoretical and practical suggestions for reducing the workload and increasing the job satisfaction of healthcare employees. Finally, we will make some suggestions for the future.
Research limitations/implications
As with other studies, there are some limitations in this study. The data used in this study were collected in Turkey. Turkish culture has a more collectivist culture than Western countries (Koksal 2011). In addition, the research was carried out with the participation of health employees. Due to Turkish cultural characteristics and the characteristics of health services, the generalization of research results may be limited. Therefore, it is recommended that the research be repeated across different cultures and different sectors to determine whether our results are culture-specific, sector-specific or generalized.
Practical implications
Healthcare managers can reduce the perception of employees’ workload by showing lean leadership behavior. Healthcare managers can increase their job satisfaction by valuing employees, inviting them to participate in business processes and providing them with the resources they need.
Social implications
In order to maintain and increase health workers’ job satisfaction, we recommend that health managers should ensure fair job sharing. In addition, health managers should take into account that female employees are more sensitive about the workload.
Originality/value
This research is the first study to examine the effect of lean leadership behavior on healthcare professionals’ workload perception and job satisfaction. Therefore, it offers important theoretical and practical implications.
Details
Keywords
Marzia Hoque Tania, M. Shamim Kaiser, Kamal Abu-Hassan and M. A. Hossain
The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals have created a demand for intelligent systems with the…
Abstract
Purpose
The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals have created a demand for intelligent systems with the least error-prone diagnosis results to be used by less medically trained persons and save clinical time. This paper aims at investigating the development of image-based colourimetric analysis. The purpose of recognising such tests is to support wider users to begin a colourimetric test to be used at homecare settings, telepathology and so on.
Design/methodology/approach
The concept of an automatic colourimetric assay detection is delivered by utilising two cases. Training deep learning (DL) models on thousands of images of these tests using transfer learning, this paper (1) classifies the type of the assay and (2) classifies the colourimetric results.
Findings
This paper demonstrated that the assay type can be recognised using DL techniques with 100% accuracy within a fraction of a second. Some of the advantages of the pre-trained model over the calibration-based approach are robustness, readiness and suitability to deploy for similar applications within a shorter period of time.
Originality/value
To the best of the authors’ knowledge, this is the first attempt to provide colourimetric assay type classification (CATC) using DL. Humans are capable to learn thousands of visual classifications in their life. Object recognition may be a trivial task for humans, due to photometric and geometric variabilities along with the high degree of intra-class variabilities, it can be a challenging task for machines. However, transforming visual knowledge into machines, as proposed, can support non-experts to better manage their health and reduce some of the burdens on experts.