Employment Decisions Research Articles

Exploring ‘Employee Voice’ of Informal Female Workers of the Textiles Industry in Pakistan: A Grounded Theory Approach

Firm restructuring and labour subcontracting has paved the way for the rise of informalisation in the female-dominated textiles industry of Pakistan after the expiry of the Agreement on Textiles and Clothing (ATC). Despite the emergence of low quality of employment available for women in the informal economy, there is a dearth of knowledge on their position at the workplace, namely ‘employee voice.’ This study therefore explores the employee voice of informal female workers of the stitching and ginning sections of the textiles industry in Pakistan in the post ATC period. A grounded theory approach, involving 25 in-depth interviews with informal female workers and employers, is used to explore employer-employee interactions. The findings reveal that the core requirements of the ‘capability for voice’ of informal female workers centre on ‘decisions of employers’, ‘bearing of tradition’ and ‘worker performance’. The grounded theory clarifies the procedure and identifies the interaction of the above categories to form the contextual conditions that direct the expectations of employers and female workers in the informal labour market. The expectations of a ‘perfect fit’ of informal female workers, within the hierarchy of the textiles industry, gives rise to a situation of ‘tolerance/no voice’, despite the negative workplace culture. The findings indicate that strategies to advance gender equality in Pakistan must consider informalisation of the labour market through a gender perspective.

Health status, life expectancy and early claiming of pension

Prior to 2011, individual life expectancy played no role in the Norwegian old-age pension system. However, after the 2011 reform, life expectancy became a central factor for early pension take-up. Asymmetric information is crucial in most insurance markets, including the new pension system, where employees can flexible claim a public pension from the age of 62. Individuals who expect to live longer than the average for their birth cohort can maximize their pension wealth by deferring pension claiming, while those with a shorter life expectancy should draw their pension as early as possible. This raises concerns that adverse selection may pose a risk to the sustainability of the new pension system. To investigate this issue, we use chronic disease as a proxy for life expectancy and examine its relationship with employment and pension decisions. Our findings show that individuals with a chronic health condition are more likely to draw a pension and continue working when they reach 62 years of age compared to those without a chronic health condition. This suggests potential adverse selection issues in the pension system, although our results suggest small effects after adjusting for unobservables.

Modeling the employment decisions of young men and women in nine European countries: An application of random utility theory and revealed preference

In this paper we examine the decisions of over 15,000 young adults aged 18–35 from nine European countries to choose employment over unemployment or remaining in education. Instead of focusing only on who makes those decisions as is typically done, we attempt to answer the question of why a particular decision is made. Using data from the Cultural Pathways to Economic Self-sufficiency and Entrepreneurship (CUPESSE) project, we estimate a series of country and gender-specific conditional logit (CLGT) models adjusted for individual work values, soft skills, demographic characteristics and local labor markets. We find that young women in Czechia, Germany, Greece, Hungary and Italy and both men and women in Spain and the United Kingdom, respond to exogenous wage offers providing some evidence for job search theory and for the reservation wage hypothesis. Our uptake rate simulations show that a 10% increase in wages have the potential to increase employment by as little as 2 percentage points in the UK and by as much as 14 percentage points in Czechia and Spain. Further, if unemployment benefits are also simultaneously reduced by 10% employment increases in these latter countries by 20 and 17 percentage points. We demonstrate the ways that revealed preference (RP) analysis can aid policy makers through strength of preference, uptake rate and willingness-to-pay applications.

MODERN LABOR LAW: A REVIEW OF CURRENT TRENDS IN EMPLOYEE RIGHTS AND ORGANIZATIONAL DUTIES

This review delves into the dynamic landscape of contemporary labor laws governing the relationship between employers and employees, and encapsulates the evolving facets of labor rights and organizational responsibilities in the current milieu. The shifting paradigm of labor law reflects a growing emphasis on safeguarding employee rights. Recent trends indicate a heightened focus on inclusivity, non-discrimination, and diversity in the workplace. Legislative reforms and judicial interpretations have sought to fortify the rights of marginalized groups, encompassing gender, race, sexual orientation, and disability. Concurrently, the emergence of remote work and the gig economy has prompted reevaluations of traditional employment classifications, engendering debates on the extension of protections to freelancers and independent contractors. Moreover, organizational duties have undergone transformation, aligning with the evolving societal expectations. Compliance frameworks have adapted to address ethical considerations, sustainability, and corporate social responsibility, amplifying the obligations of employers beyond profit-centric objectives. This evolution extends to the duty of care owed to employees, encompassing mental health support, workplace safety, and accommodation for work-life balance. The review also analyzes the interplay between statutory regulations, judicial precedents, and societal shifts, charting their impact on the employer-employee relationship. It examines the complexities arising from the globalization of labor markets, addressing the challenges of harmonizing diverse legal frameworks and cross-border employment dynamics. It also scrutinizes the implications of technological advancements, such as AI-driven employment decisions, on labor rights. It probes the legal and ethical quandaries arising from the proliferation of surveillance technologies in the workplace, balancing the interests of productivity and privacy rights of employees. The insight presented in this review provides a comprehensive overview of the multifaceted landscape of modern labor law, capturing its intricate tapestry of rights, obligations, and the evolving contours of the employer-employee nexus amidst contemporary socio-economic dynamics.
 Keywords: Labour Law, Employee Right, Compliance, Organizational Duties, Review.

INTISARI ANALISIS PERSIAPAN PELAKSANAAN PATIENT SAFETY DI RUANG RAWAT INAP (STUDY KASUS DI RSUD KABUPATEN BIMA)

The era of globalization impact very rapidly, in the development of advanced medical technology. These conditions have an impact on medical services is very complex and it is potentially causing the error, so that the necessary improvement of health care quality. Patient safety is one important component in the quality of health care. Improved patient safety is a necessary step to prevent and minimize unwanted incident (KTD). Nurses are one of the health workers who are at the forefront of health care and have a very important role in improving patient safety. To determine attitudes on the analysis of patient safety in the inpatient unit nurse Bima district hospital and in particular to identify the components of patient safety attitudes include climate of team work, working conditions, employment decisions, and some factors that support and hinder patient safety attitudes. The research is descriptive qualitative. Subjects were 3 nurses and 3 patients with interview techniques. Data collection techniques in this study used the analysis of qualitative data. A qualitative data analysis technique is using descriptive analysis techniques to describe the data in the field which were analyzed and concluded. Components of the patient safety attitudes is climate of teamwork that showed lower patient safety attitudes, job satisfaction showed high patient safety attitudes, working conditions showed lower patient safety attitudes, for logistical support in the form of medical equipment are laboratory equipments that still lacking. Components of the patient safety attitudes were high that consist job satisfaction, and the low patient safety attitudes components were the teamwork climate and conditions of employment, because they needed additional medical equipment such as laboratory equipments.

Bargaining in mobile app supply chain considering members’ fairness concern attitudes

The fast-developing mobile app industry has brought challenges to service pricing and profit allocation problems. This study constructs a four-stage game model consisting of a brand mobile app supplier as well as a distributor and takes members’ distributional fairness concern into consideration. We analyze the equilibrium revenue retaining ratio bargaining result, service price as well as the investigation and regulation (I&R) level in different fairness concern models and explore the managers’ employment decisions of supply chain members at equilibrium. Through analysis, we obtain several theoretical contributions and managerial insights. Firstly, while the supplier’s distributional fairness concern drops down both the service price and I&R level, the distributor’s fairness concern exerts no effect on both decisions. Secondly, we show that at equilibrium, the supply chain members would sink into prisoner’s dilemma when the cost coefficient of I&R activity is relatively low. When the cost coefficient is relatively high, the supplier would obtain higher profit while the distributor would suffer profit loss compared with fairness neutral situation and unfortunately the profit gain of the supplier is overwhelmed by the profit loss of the distributor, resulting profit loss of the whole supply chain. Thirdly, we suggest the distributor in mobile app supply chain to control I&R cost for the purpose of attracting the supplier to sign fairness neutral commitment contract, which can avoid supply chain inefficiency. Besides, the government is advised to take intervention measures when the I&R cost coefficient is relatively high.

Predicting Everyday Critical Thinking: A Review of Critical Thinking Assessments.

Our ability to think critically and our disposition to do so can have major implications for our everyday lives. Research across the globe has shown the impact of critical thinking on decisions about our health, politics, relationships, finances, consumer purchases, education, work, and more. This chapter will review some of that research. Given the importance of critical thinking to our everyday lives, the fair and unbiased assessment of critical thinking is useful for guiding educators in their classrooms, for the sake of self-improvement, and in employment decisions. This chapter will also review the psychometric properties of several critical thinking assessments, with a special emphasis on the everyday behaviors predicted by these assessments. The practical challenges faced by test adopters and future directions in the assessment of critical thinking will be discussed.

Signal, error, or bias? exploring the uses of scores from observation systems

AbstractScores from observational measures of teaching have recently been put to many uses within school systems, including communicating a standard of practice and providing teacher feedback, identifying teachers for professional development, monitoring system equity, and making employment decisions. In each of these uses, observation scores are interpreted as representing some aspect of the enacted instruction or teachers’ capacity to enact instruction, as seen through the observation systems lens for understanding teaching quality. The quality of these interpretations, or the extent to which observation scores are composed of a signal that accurately reflects the interpretation, has important implications for the overall validity of uses of observation systems. Starting from an explicit conceptualization of instruction, this paper combines generalizability theory and hierarchical linear modelling approaches to decompose observation scores to explore the extent to which scores from observation systems are composed of signal, error, and bias across four different uses (i.e., teacher feedback, professional development, monitoring system equity, and employment decisions) of scores. We show that the quality of observation scores may depend more on what scores are interpreted as representing (i.e., the proposed use) than on the specific observation rubric being used. Further, we show that rater errors and biases are a major threat to any attempt to interpret observation scores as capturing the observation system’s understanding of teaching quality. We discuss implications for using scores from observation systems.

The influence of micro-influencers and content marketing through customer engagement on purchasing decisions

Technology has had a huge impact on the marketing field. In today's digital era, technology has completely changed the way we interact and communicate with customers. Instagram is the object of research because this platform has become one of the largest and most popular social media in the world. This research aims to determine the influence of micro-influencers and content marketing through customer engagement on product purchasing decisions on Instagram. The data obtained by this research is through a questionnaire from 100 respondents. Instagram users. This research data was processed using SEM (Structural Equation Modeling) using the SmartPLS4 application. The results of this research show the positive influence of Micro-influencers on Customer engagement, Content marketing on Customer engagement, Micro-influencers on purchasing decisions, Content marketing on purchasing decisions, Customer engagement on purchasing decisions, and Micro influencers on work decisions through customer engagement. Content marketing on employment decisions through customer engagement. Implementation for companies that market their products via Instagram is expected to use Micro-Influencers and Content Marketing to attract buyers and good customer engagement, resulting in purchasing decisions on the Instagram application.

Does Trade Secrets Protection Affect Human Capital Investment? Evidence From the Inevitable Disclosure Doctrine

This study investigates the impact of trade secrets protection on corporate employment decisions. By exploiting the staggered adoption of the Inevitable Disclosure Doctrine (IDD) by the U.S. state courts as an exogenous shock that significantly reduces employee mobility, we employ a difference-in-differences (DiD) approach and find that the adoption of the IDD, on average, leads to higher deviation from the optimal employment level explained by the underlying economics (i.e., lower labor investment efficiency) for firms headquartered in that state, whilst the rejection of the previously adopted IDD results in lower deviation from the optimal employment level (i.e., higher labor investment efficiency). Further analyses show that the impact of the IDD adoption on corporate employment decisions is primarily driven by firms’ overinvestment in labor, suggesting that firms strategically engage in precautionary human capital hoarding in response to the reduced talent supply in the labor market and consequently higher labor adjustment costs. Our cross-sectional analyses show that the impact of the IDD adoptions on corporate employment decisions is more pronounced for (1) firms in high-skill industries and (2) firms facing high levels of product market competition. Overall, our findings indicate that the trade secrets protection environment can be an influential determinant for labor investment practices and have implications for both policymakers and industry practitioners.

Evaluation and Design of Employment Decision Analysis System Based on Artificial Intelligence

Evaluation and Design of Employment Decision Analysis System Based on Artificial Intelligence

Research on the construction of accurate counseling path for students with employment difficulties in colleges and universities based on RFM model analysis

Abstract The widespread adoption of higher education has led to a continuous increase in the number of college graduates. Concurrently, the challenge of graduate unemployment is escalating, highlighting a critical need for precise career planning and guidance. Addressing the challenges faced by college graduates, this study employs the RFM model in conjunction with the fuzzy C-means clustering technique to categorize student data into distinct attributes. Subsequently, a GM(1,1) model is developed based on these attributes to forecast the future employment decisions of the students in the sample. The analysis reveals that the student data can be segmented into six distinct attributes. Of these, academic performance, English proficiency, and attributes related to physical and mental development, as well as cultural, sports, and artistic engagement, are identified as having greater significance. Notably, academic performance holds the highest importance, with a weight of 7.2. The GM(1,1) model demonstrates over 85% accuracy in predicting the future career choices of students. Despite minor discrepancies in certain areas of the model, its effectiveness is substantiated. The classification of attributes and the prediction of employment directions are poised to significantly enhance the development of targeted counseling strategies for college graduates facing employment difficulties. This approach not only aids in addressing immediate employment challenges but also contributes to the broader discourse on enhancing graduate employability through tailored guidance and support.

Taking Action Against Clinician Burnout Through Reducing the Documentation Burden With an Operating Room Supply Scanning Approach.

Documenting surgical supply items in the operating room can be a burdensome task for circulating nurses because of manual input within the electronic medical record. This can lead to documentation fatigue and contribute to nursing burnout. The aim of this quality improvement project was to design and implement a supply item scanning process and evaluate the effect on intraoperative documentation completion time, room turnover time, picklist documentation accuracy, nurse satisfaction, and burnout. The sample included nine acute care hospitals throughout the United States, with 189 total circulating nurses and 31 718 procedures occurring during the study timeframe of 8 months. Results indicated that nurses were able to complete documentation on average 37.33 minutes sooner, and the operating room turnover time decreased by 1.88 minutes. Although nurses reported that their perceived picklist documentation accuracy did not improve, and the presence of new scanning technology did not influence their hospital employment decision, subjective feedback was mostly positive, with most responses citing the helpfulness of scanning for documentation. This study shows that an interdisciplinary team can effectively work to optimize documentation efficiency and performance improvement using a scanning intervention. Lessons learned through this process can translate into optimizations elsewhere in the electronic medical record.

Will the use of AI in human resources create a digital Frankenstein?

Organizations are increasingly using artificial intelligence (AI) and machine learning (ML) to manage human resource processes and practices (e.g., recruitment, selection, performance management, and compensation). However, it has long been known that these new systems create several ethical problems and dilemmas in organizations. As a result, the primary purposes of this paper were to review the major ethical and moral issues associated with using AI and ML for human resource management. In particular, we considered the potential for these new systems to violate ethical standards, and reviewed the degree to which AL and ML models affect (a) perceptions of invasion of privacy, (b) biases and unfair discrimination in employment decision making, and (c) the harm that may come to individuals and organizations from the erroneous data generated by AI and ML. We also offered strategies that organizations might use to overcome these critical ethical problems.

Is it All About the Money? Motivations and Preferences for Work Across Emirati and Non-Emirati Youth in the UAE

This policy paper examines the values and preferences of United Arab Emirates’ (UAE) youth regarding work and the workplace. Drawing on interviews with non-Emirati and Emirati youth, the study reveals key factors influencing their employment decisions. Flexibility in the workplace, opportunities for growth, and a supportive environment emerge as critical considerations. Additionally, the desire for meaningful, purposeful work transcends financial compensation. Emirati and non-Emirati youth exhibit nuanced differences in their priorities for work and the work environment. While both value supportive environments, the study finds that Emirati youth are more likely to prefer work closer to home and work environments where there is lenience and flexibility in terms of management style compared to their non-Emirati counterparts. It also finds that non-Emirati youth value supportive environments for goals of career advancement and financial stability as opposed to Emirati youth who value nurturing environments for reasons of personal development and purposeful work. Understanding these distinct motivators is essential for organizations seeking to attract, engage, and retain young talent in the UAE's rapidly growing economy.

Is there life after product quality failures? Evidence from employment decisions

Prior literature has documented that product quality failures have negative impacts on the interest of stakeholders, such as consumers and shareholders. We extend this literature by investigating its potential effects on the interest of employees. Using a novel dataset that tracks the recall incidents of Chinese firms in an industry where product quality is crucial (i.e., the drug industry), our empirical results show that the effects on corporate employment decisions are twofold. On the one hand, we show that firms’ employment growth decreases after product recalls. The effect is more pronounced in non-state-owned firms, firms with higher labor costs, firms in regions with weaker labor protection, and during periods when local politicians lack promotion incentives. On the other hand, product recalls mainly induce firms to reduce the employment growth of low-grade employees, consistent with recalling firms relying on high-skilled labor to improve drug quality. Collectively, our study suggests that product quality failures could be a broader issue of corporate social responsibility (CSR) than being documented, and carries implications for policymakers concerning employment as well as product safety.

Research on Spatial Migration Patterns and Influencing Factors of Western Talents: Based on Data from "Double first-class" Universities in China

The western region's talent loss issue has received widespread attention. Promoting the construction of human resources in the west has become key to forming an important high-quality development pole in western China. This study analyzes the graduate migration data of first-class universities in western China between 2016 and 2020 and draws the following conclusions: Overall, the retention rate of college graduates in western China across seven provinces is high, with a relatively higher retention rate observed in the place of study in four southwestern provinces. The retention rate of different provinces' place of study showed different trends during the period of 2016-2020, and the retention rate of different provinces also showed different trends during the same period. In 2020, western college graduates continued to show a preference for employment in popular provinces such as Guangdong, Beijing, and Shanghai, while they showed a greater inclination towards choosing employment opportunities in the South and Central regions of China. The results based on the directed migration model show that economic factors and natural and educational resources in a city have a greater impact on employment decisions. Analysis of heterogeneity found that graduates from areas with a high sticking rate are more susceptible to population size, human resources, and economic factors, and that cultural resources and transportation resources also have a significant impact on talent migration. Policy recommendations include western provinces taking higher education as a key factor to utilizing employment retention advantages to attract and retain high-quality talents.

A linear regression-based study of the relationship between health and labor market performance

This paper uses a linear regression model to study the relationship between health on labor market performance. The paper adds health variables to explore the influencing factors of labor market performance in urban China under the more multidimensional concept of human capital. Using the China Nutrition Survey (CHNS) microdata in recent years, the impact of health on employment decisions is explored in urban China. The paper constructs an endogenous joint equation of health and labor force participation, and employs multiple physical characteristics of disability or frailty as instrumental variables for health indicators, effectively addressing the endogeneity and metric bias of the existence of health.

A good university or a good city?: Double considerations in the employment decisions of STEM doctoral graduates in China

AbstractThis study explores how doctoral graduates weigh considerations of employment sectors and cities in their career decision‐making processes. Guided by Social Cognitive Career Theory and a Four‐quadrant Model, researchers analysed interviews from 40 STEM doctoral graduates in China. Findings demonstrate that self‐efficacy, outcome expectations and goal‐setting were factors in participants' interests and selections of academic careers. Three types of doctoral graduates were identified: (1) highfliers, (2) academic loyalists and (3) city pickers. While participants prioritize employment sectors and cities differently, cities played a significant role in their career choices which intersected with gender and class factors. Female doctoral graduates were more inclined to follow their partners, while those from socioeconomically disadvantaged backgrounds tended to prioritize cost of living factors at the expense of pursuing opportunities in top‐tier cities. Implications suggest that factors undergirding doctoral graduates' career choices rely on the interaction between geographical locations and employment sector opportunities.

Commuting barriers to low-wage employment

Lack of access to affordable transportation has been hypothesized to be a barrier to employment among low-wage workers. We build a structural job search model to investigate how commuting costs influence the employment decisions of low-wage workers in the United States, and whether differences in commuting by race and education can explain observed disparities in employment. We find that commuting itself poses a significant barrier to overall low-wage employment, as the associated costs are high relative to potential wages. However, we find that inter-group differences in commuting costs account for a much smaller fraction of inter-group employment disparities than do differences in other labor market factors such as the wage offer distribution and offer arrival rates.