Efficiency Of Human Resources Research Articles

Virtual Visit Evaluation from the Perspectives of Physicians and Patients: A Qualitative Study in a Developing Country

Introduction: Many patients, especially in rural and remote areas, face the problem of unavailability of specialists. Today, virtual visit technology is used by the public as a solution to solve the problem of lack of access to specialists and reduce unnecessary costs. Therefore, the purpose of this study is to identify the strengths, weaknesses, opportunities and threats (SWOT) of the virtual visit system from the point of view of physicians and patients.Material and Methods: This cross-sectional qualitative study was conducted from June to August 2023 in Kermanshah. Semi-structured and in-depth interviews were conducted face-to-face with five physicians and ten patients. All interviews were transcribed verbatim. Data analysis utilized the SWOT framework and the software Atlas.ti8.Results: The results of this study revealed that virtual visits have strengths such as minimal infrastructure requirements, cost reduction, and human resource efficiency. Weaknesses include the absence of physical examination, reduced quality of examinations, and limitations for certain patients. Opportunities include quick visits in remote areas and a decrease in health disparities, while threats encompass potential privacy breaches, violation of patient information confidentiality, lack of motivation among health users, and limited access to technology.Conclusion: Based on the study findings, in healthcare crises, telemedicine technology proves effective in providing primary healthcare services. Telemedicine plays a crucial role in health by enhancing access and reducing costs. To optimize this process, a comprehensive strategy in digital health, involving infrastructure investment and stakeholder feedback, is evident. Sharing experiences and addressing challenges empower managers to enhance healthcare services through virtual visits, adapting to the prevailing conditions.

Fairness, AI & recruitment

The ever-increasing adoption of AI technologies in the hiring landscape to enhance human resources efficiency raises questions about algorithmic decision-making's implications in employment, especially for job applicants, including those at higher risk of social discrimination. Among other concepts, such as transparency and accountability, fairness has become crucial in AI recruitment debates due to the potential reproduction of bias and discrimination that can disproportionately affect certain vulnerable groups. However, the ideals and ambitions of fairness may signify different meanings to various stakeholders. Conceptualizing fairness is critical because it may provide a clear benchmark for evaluating and mitigating biases, ensuring that AI systems do not perpetuate existing imbalances and promote, in this case, equitable opportunities for all candidates in the job market. To this end, in this article, we conduct a scoping literature review on fairness in AI applications for recruitment and selection purposes, with special emphasis on its definition, categorization, and practical implementation. We start by explaining how AI applications have been increasingly used in the hiring process, especially to increase the efficiency of the HR team. We then move to the limitations of this technological innovation, which is known to be at high risk of privacy violations and social discrimination. Against this backdrop, we focus on defining and operationalizing fairness in AI applications for recruitment and selection purposes through cross-disciplinary lenses. Although the applicable legal frameworks and some research currently address the issue piecemeal, we observe and welcome the emergence of some cross-disciplinary efforts aimed at tackling this multifaceted challenge. We conclude the article with some brief recommendations to guide and shape future research and action on the fairness of AI applications in the hiring process for the better.

Pengaruh Tingkat Efisiensi dan Produktivitas SDM dalam Menjalankan Operasional Guna Meningkatkan Mutu Layanan Jaminan Kesehatan Nasional (JKN)

In the era of globalization and digital, innovation is one thing that is discussed a lot by humans in order to try to create a form or thing or object that can make an activity more effective and efficient. The challenge to continue to innovate does not only come to individual people but also extends to the organizational scope. This research aims to look at the dynamics that occur in the innovation process carried out by BPJS Health by taking a case study on the SDM performance management system. Data was obtained through interviews and observations, research sources used a qualitative approach. With the aim of knowing the influence of the level of efficiency and productivity of human resources in carrying out operations in order to improve the quality of national health insurance services (JKN) . The innovation of the performance management system at BPJS Health is a concrete form that the organization sees employees as talents and as the main competitive asset and key factor for the organization's success in the future.

The Integration of Digital Transformation with Human Resource Management – A Theoretical Point of View

Virtual transformation changes HRM practices by introducing new strategic skills, control, and operational performance. Virtual tools and technology have made hiring, training, and managing employees easier, broadening the talent pool and increasing job satisfaction. HR analytics software has also helped HR professionals make more informed decisions about workforce planning and skill development. Virtual transformation has also enabled more flexible work policies and virtual education programs, improving operational performance and worker engagement. To be successful, HR professionals must now possess virtual literacy and a strategic mindset. The digital revolution has positioned human resource management as a critical driver of organizational success, emphasizing the role of digital tools and technology in shaping the future of work and talent management. Keywords: Digital Transformation, Human Resource Management and Efficiency

The Effect of Effort and Result-Oriented Contracts on Human Resource Productivity: An Important Component of Sustainable Development Study of Dairy Farm in Iran

Human resource productivity is one of the essential components of the sustainable development of human resources. Human resource efficiency means the optimal use of people's capabilities, skills, knowledge, and experiences in society or organization. The sustainable development of human resources can be aided by raising productivity levels. The management of human resources systems and performance evaluation techniques may need help in evaluating the performance of employees under the influence of its complexities, which can cause inaccurate evaluation results. As a result, the organization will need help achieving the predetermined goals with proper productivity. Therefore, The present study examines the effect of effort and result-oriented contracts on the productivity of human resources in a 20,000-head state cattle farm in Iran. A comparative approach was used to investigate the effect of effort-based and result-based payments on human resource productivity. It analyzed ten projects in a set, where five were used for effort-based contracts and five similar projects used for results-based contracts. The findings of the study show that result-based contracts have a substantial impact on the productivity of labor in terms of effectiveness and efficiency. The study likewise discussed the implications of its results.

The Importance of e-Recruitment within a Smart Government Framework

This literary review examines the current state of research in the field of e-recruitment within the framework of smart government and its implementation in the context of modern public services. We elucidate the concepts of “smart government” as a concept of efficient, technologically supported public administration, and “electronic recruitment” as a process utilizing digital tools in the search and acquisition of suitable candidates for job vacancies. The objective of this review is to provide a brief overview of the current state of smart government, e-HRM (electronic human resource management), and e-recruitment, and analyze their interconnection. The selection of relevant sources followed the PRISMA method. In the context of defining the key functional module of e-HRM, the Grounded Theory Method (GTM) was employed. The final part of the methodological approach involved designing a research problem for future research. Specifically, the review focuses on defining the key functional module of e-HRM and proposes an orientation for future research that should concentrate on the impacts of e-recruitment on the efficiency of human resources within public services. The results of this study can serve as a foundation for future research aimed at optimizing and utilizing e-recruitment in the specific field of smart government.

Process Mining Organization (PMO) Based on Machine Learning Decision Making for Prevention of Chronic Diseases

This paper discusses a methodology to improve the prevention processes of chronic diseases such as diabetes and strokes. The research motivation is to find a new methodological approach to design advanced Diagnostic and Therapeutic Care Pathways (PDTAs) based on the prediction of chronic disease using telemedicine technologies and machine learning (ML) data processing techniques. The aim is to decrease health risk and avoid hospitalizations through prevention. The proposed method defines a Process Mining Organization (PMO) model, managing risks using a PDTA structured to prevent chronic risk. Specifically, the data analysis is focused on stroke risk. First, we applied and compared the Random Forest (RF) and Gradient Boosted Trees (GBT) supervised algorithms to predict stroke risk, and then, the Fuzzy c-Means unsupervised algorithm to cluster information on the predicted results. The application of the proposed approach is able to increase the efficiency of healthcare human resources and drastically decrease care costs.

The influence of job satisfaction on retention of primary healthcare professionals in Tamil Nadu

Stability among healthcare professionals is considered critical to providing excellent care. Job satisfaction has a significant impact on the productivity and efficiency of human resources in the healthcare industry. This cross-sectional study examined the job satisfaction and retention intentions of healthcare professionals in primary healthcare centers in Tamil Nadu. Convenience sampling was used to collect data from 334 respondents using a validated structured questionnaire. The empirical research revealed that their work values were the most significant predictor of job satisfaction among PHC employees. On the other hand, time pressure had the least significant relationship with PHC employee satisfaction. The findings indicate that targeted interventions to enhance health workers' job satisfaction, reduce stress, and increase positive work values are essential to creating a positive work environment and increasing job satisfaction. This study adds to the literature on job satisfaction and retention of primary healthcare workers in Tamil Nadu. We recommend that healthcare managers promote and enforce PHC workers' work values to keep them positive. Work values and PHC workers' satisfaction and intention to stay have received little research attention. One of the first studies to empirically examine quality improvement, time pressure, commitment, compensation, and work values as dimensions of job satisfaction among health professionals in Tamil Nadu Primary Health Care Centers.

Pengaruh Modal Intelektual terhadap Performa Perusahaan dengan Manajemen Keluarga sebagai Variabel Moderasi

This research uses family management as a moderating variable to explore the influence of intellectual capital determinants on firm performance. Intangible asset such as intellectual capital is very important in supporting firm performance. Intellectual capital with the Modified Intellectual Value Added Coefficient (MVAIC) model consists of Human Resource Efficiency (HCE), Structural Capital Efficiency (SCE), Capital Employed Efficiency (CEE), and Relational Capital Efficiency (RCE). The sample for this research is companies from all industries that are recorded on the Indonesia Stock Exchange (IDX) which is provide comprehensive company financial reports and annual reports for the 2018–2022 period. This research was applied using a quantitative approach method. Panel data regression and moderated regression analysis are the data analysis method used in this research. The findings of this research indicate that MVAIC has a significant positive effect on firm performance and family management does not moderate the relationship between intellectual capital and firm performance. The higher the intellectual capital assets owned by a company, the greater the company's performance.

АНАЛИЗ БИЗНЕС-ПРОЦЕССОВ НЕФТЕДОБЫВАЮЩЕЙ КОМПАНИИ

In this article business processes of an oil producing company are considered. The research included the analysis of current business processes, identification of problem areas, as well as recommendations for their improvement. SWOT analysis and process design methods were used to identify key aspects of the company’s efficiency and competitiveness. The results of the study emphasised the need to implement automation of certain processes, improve the quality control system and increase the efficiency of human resources. This study was conducted to improve the operations and increase the competitive advantage of an oil production company in today’s industry.

Talent Management for Enhancing the Efficiency of Human Resources in the Public Sector of Sri Lanka: A Comparative Study

The Sri Lankan Public Sector has often been criticized for being overstaffed, inefficient and a burden to the economy. This has partly been attributed to the deficiencies in employee talents management. This study attempts to find the direction for augmenting human resource in public sector in Sri Lanka through Talent Management (TM), by benchmarking against standards from Japan, Singapore, and Norway. This study adopts a qualitative research approach. One-on-one interviews were conducted with the Executive Officers of Public Service of Sri Lanka. Also, data on TM practices in Public Sector in Japan were gathered through a questionnaire. There was also an extensive review of relevant literature on the study concept from the Public Service of Japan, Singapore and Norway, which rank top in Government Efficiency Indicator. Using the Case study approach, the data obtained was analysed by comparative analysis to compare TM policies and activities of these countries. The study revealed several drawbacks concerning TM in Public Service of Sri Lanka. Analysing various TM models of countries having high standards, the benchmark study proposes an effective Talent Management Model for the Public Sector in Sri Lanka, including Talent Gap analysis, Talent Acquisition and Augmenting, development, assessment, measurement, retention, and transition.

Dedication of Machine Learning for Trend of Digital HRM

The digital world has inevitably entered various fields of human life in carrying out their duties as world leaders. Technology is an important tool to ease the human workload, including in this discourse is human resource management. Machine Learning is a technology that allows machines to learn and adapt quickly from given data without having to be explicitly programmed. Machine Learning has found its place in many industries and has great potential to improve the efficiency of human resources within organizations. This research is a literature review of several articles related to machine learning. The review was conducted from some of the recent research efforts that utilize machine learning. Furthermore, this review is derived from multiple literacies and includes an attempt at problem solving efforts that are divided into section areas from the perspective of each machine learning category. Machine learning can change the way the human resource management domain functions in an organization. It is making changes in all aspects of human resource management starting from human resource planning. Enormous data is available in human resource information systems (HRIS) available in organizations.

Burnout syndrome and related factors among health team employees.

Burnout is not only related to mental health but also to efficiency. Thus, recognizing effective coping strategies has a significant role in improving mental health, the efficiency and productivity of human resources, and making better the level of quality of service. To determine burnout syndrome and examine related factors among the employees of Mashhad University of Medical Sciences. This cross-sectional study was conducted among 600 employees at Mashhad University of Medical Sciences. They were selected by a stratified sampling method. The data collection tool was the demographic information and the Burnout Self-Test Maslach Burnout Inventory (MBI) questionnaire. Data were analyzed through SPSS software version 20, using descriptive statistics and independent samples t-tests, one-way ANOVA, and Pearson and Spearman regression. The findings showed that emotional exhaustion (EE) and depersonalization (DP) in the majority of employees were high and personal accomplishment (PA) was low at 88.33% of cases. All participants presented burnout. However, participants aged 35-40 years, those with professional and Ph.D. degrees, and research staff reported higher burnout levels. Job burnout and its subscale levels among the employees were high. Job burnout is associated with socioeconomic status that can be affected by individual, organizational, management, and environmental factors. Therefore, this study suggests that employees need to get out of EE and DP conditions for higher job performance. Additionally, further research is required to examine the long-term effects of workplace burnout.

The influence of meaningful work on the mental health of SME employees in the COVID-19 era: can coping strategies mediate the relationship?

BackgroundStress, depression, and anxiety are prevalent issues among SME employees during the COVID-19 pandemic. Even while having meaningful work that expressively contributes to individual growth has been related to improving mental health, employees’ work may also need to adopt coping strategies to increase outcomes. The purpose of this study was to examine the relationship between meaningful work (positive meaning, meaning-making, and greater good motivations) and mental health, as well as coping strategies (problem-focused and emotion-focused) as a mediator of this relationship.MethodsMeaningful work, coping strategies, and mental health were evaluated in empirical research based on a sample of 462 SME employees working in Malaysia. Structured questionnaires were used to collect the data and analyze it through Structural Equation Modelling (SEM) using AMOS 21.0.ResultsThe findings of the study show the importance of meaningful work in influencing the mental health of SME employees, particularly during a crisis like the COVID-19 pandemic. This suggests that the more they value and see their work as meaningful, the more capable they are of dealing with limitations and mental health problems associated with crises. The study also discovered a partial mediating role for coping strategies between employees’ mental health and meaningful work.ConclusionThis study encourages employees to constantly feel connected and discover continued possibilities to work and learn even during crisis situations. In order to improve human resource efficiency in emerging markets, managers and owners of SMEs must implement the model developed by the researchers.

Burnout and turnover intention of primary health care providers during the COVID-19 pandemic in China

ObjectivesThis study explored the changes and new characteristics of burnout and turnover intention of primary health care (PHC) providers during the COVID-19 pandemic in China. Study designThis was a cross-sectional study. MethodsThis study investigated 1326 PHC providers during the COVID-19 outbreak in 2022 in one district of Shanghai, China. Independent t-test or one-way analysis of variance (ANOVA) test were used to analyse the between-group variation of variables associated to burnout and turnover intention. Then, hierarchical regression analysis was used to further determine the impact of certain variables on burnout and turnover intention, the relationship of burnout on turnover intention and the possible moderating effect. ResultsThe results showed that there was no significant change in the prevalence of overall burnout of PHC providers compared to the pre-epidemic period; however, there was a significant increase in high-level burnout. No significant change in turnover intention at the moderate level and above was observed. During the COVID-19 pandemic, PHC providers who were older, married, local and had a higher skill level had higher burnout, while PHC providers who were male, unmarried, non-local and separated from their family had a higher turnover intention. It was shown that burnout, with its three sub-dimensions, was a good predictor of turnover intention. The impact of burnout on turnover intention was shown to be alleviated by certain variables, including being married, living locally and receiving benefit packages, including the preferential education policy for children and talent incentive policies. ConclusionsResults from this study have highlighted the importance of paying attention to vulnerable groups of PHC providers, for example those who are separated from their families, during emergency situations. Various incentive tools could be comprehensively used to ensure the stability and efficiency of PHC human resources.

Natural resources lineage, high technology exports and economic performance: RCEP economies perspective of human capital and energy resources efficiency

Natural resources play a crucial role in economic growth and development. The presence of abundant natural resources can provide countries with opportunities for economic expansion, job creation, and increased export revenues. However, the utilization of natural resources also carries significant risks and challenges that can affect macroeconomic and environmental outcomes. This paper examines the impact of natural resource rents, high technology exports, human capital, and energy efficiency on economic growth of five RCEP nations over the period of 1989–2021. We use quantile regression method, which is useful for analyzing the relationship between two variables, especially when the effect of one variable on the other is anticipated to vary across various parts of the response variable's distribution. We find that natural resource rents are harmful for economic growth. However, high technology exports, human capital and energy efficiency positively affect economic growth. The findings also suggest that policies intended to promote growth should be tailored to the unique requirements and characteristics of countries at various stages of economic development.

Artificial Intelligence Model for Human Capital Management

Artificial Intelligence is a technology that allows machines to learn and adapt quickly from given data without having to be explicitly programmed. AI has found its place in many industries and has great potential to improve the efficiency of human resources within organizations. In this article, we will discuss how the use of artificial intelligence can help improve human resource efficiency. This review is a literature search with an elaborative approach. This approach is a methodological effort by organizing the logic flow of the discussion with various compatible literature sources. Reliable literature sources come from journals, books, articles, and other sources relevant to this discourse. The result of the study is that human resource management needs to adjust to the needs of the organization and adjust the culture or corporate culture to the technological culture. Human interaction with machines is an inevitable necessity. The existence of artificial intelligence is very helpful in human resource management, for example in recruitment systems, training, data analysis, performance analysis, and operational duty efficiency.

The impact of talent management on human resources efficiency

The belief that talented people create prosperous organizations contributed to the accomplishment of talent management concepts into reality. Highly capable professionals or talented employees who systematically nurtured the best skills typically demonstrate high performance and serve as one of the key success factors for the organizations. Organizations face challenges attracting and maintaining talented employees more than assets. Researches demonstrate that one of the major challenges an organization experience is the aspect of talent management. The objective of the present study is to examine how talent management functions impact the efficiency of human resources. We conducted a sample survey in the metropolitan branch company of the major shareholding company. SPSS 23.0 and Smart PLS 3.0 are used in data analysis and we conducted several tests like reliability tests, correlation analyses, and structural equation models (SEM) to produce the results. The survey results showed that the practice of talent management improves the efficiency of human resources. Moreover, it proved that proper forecasting of talent management needs that foresee opportunity career development and nurture the work culture which would support the mission and vision of the organization makes it possible to increase the efficiency of the human resources.

The Impact of Functional Competencies on Human Resource Management

Competencies are a contemporary subject of interest for global organizations and have a direct relationship with human resource management. Competency in the workplace is analyzed starting with the individual, directly linked to the job, without any preconceived assumptions about the qualities required for success in the role. Human attributes that correlate with success in the workplace are then identified. The competency approach focuses on how to maximize the utilization of exceptional and creative human resources within the organization, including their selection, development, training, and evaluation.The study aimed to analyze the relationship between intrinsic attributes and human resource management, determine the impact of causal relationships on human resource management, and subsequently understand the connection between the benchmark and human resource management. The study adopted a descriptive-analytical, historical, and statistical approach.One of the study's key findings is that many institutions base their selection on surface-level knowledge and skills competencies, assuming that those hired for new positions possess the underlying motivation and qualities. The practical application of competency concepts contributes to the development of training and education plans for individuals or groups of employees based on the gap between the job-related competencies required and those addressed by the employee. The study recommended several actions, including the need to disseminate practical knowledge of competencies to enhance human resource efficiency and organizational change implementation to meet organizational needs and support employees through the change process.

ANALYSIS OF NURSE UNIT MANAGER SUPERVISION ON THE PERFORMANCE OF NURSES AT X HOSPITAL KEDIRI CITY, INDONESIA: A CROSS-SECTIONAL STUDY

Background: Hospital performance challenges are receiving attention because they concern the efficiency and effectiveness of human resources in accomplishing organizational objectives and visions. Many factors influence performance, including superiors' supervision, which has an impact on the organization's overall performance results. In fact, supervision has not been carried out optimally. Purpose: to analyze how the nurse unit manager's supervision affected nurse performance. Methods: A correlational study methodology was used on 67 nurses from the inpatient room. To obtain 57 individuals, a stratified random sampling procedure was used. The data was analyzed using the Spearman rho statistical test, with a significance threshold of = 0.05. Results: From 67 respondents, 33 respondents (57.9 percent) stated that the nurse unit manager offered acceptable supervision. The 32 respondents (56.1 percent) had adequate performance. Result of the Spearman rho test obtained a p-value = 0.000 which is less than the value of alpha (0.05), so it can be concluded that H0 is rejected, meaning that there is a relationship between the supervision of the head of the room and the performance of nurses at X Hospital Kediri City. Conclusion: It was concluded that there is a link between the nurse unit manager's supervision and the performance of nurses. The study's findings also suggest that supervision can increase nurse performance because, when supervising the nurse unit manager evaluates certain activities directed at nurses, if the evaluation is corrected by the nurse, it can improve the nurse's performance.