Employer Size and Success in Manpower Training Programs for the Disadvantaged : A Dual Labor Market Analysis

Quoique le gouvernement des États-Unis ait accordé beaucoup d'importance au programme de formation en atelier pour les défavorisés, ces programmes ne se sont pas révélés pour autant une panacée dans la lutte au chômage chronique. Même s'il est difficile de préciser ce qu'on peut entendre par « succès », il est apparent que, au mieux, ces programmes n'ont eu qu'un succès relatif. D'ailleurs, tout étonnant que cela puisse sembler, on en sait bien peu concernant les caractéristiques des entreprises qui permettraient de juger si l'expérience a été une réussite ou un échec.La taille de l'entreprise est une variable qui a quelque chose à voir avec le succès parce qu'elle signifie que l'entreprise est prospère, qu'elle est installée en milieu urbain et à proximité d'un marché du travail de base tel que le définissent Doeringer et Piore. La présente étude analyse un programme connu sous le nom de J.E.T. (Job, éducation, training - emploi, éducation, formation professionnelle)dans l'ouest de la ville de New York. L'échantillon est formé de 149 employeurs qui y participent et qui se répartissent ainsi : 56 appartenant à la petite entreprise (0-49 employés); 33, à la moyenne entreprise (50-199 employés); 60 à la grande entreprise (200 employés et plus). En outre, on y scrute l'expérience en milieu de travail de 223 stagiaires.Voici ce qui a été constaté :1. la grande entreprise est plus en mesure que la petite de s'engager dans de tels programmes ;2. la grande entreprise réussit mieux que la petite à retenir les stagiaires ;3. la grande entreprise a tendance plus que la petite à considérer ces programmes efficaces et compte davantage y participer dans l'avenir ;4. la grande entreprise est encline plus que la petite à apprécier les aspects positifs de ces programmes.Bien des raisons expliquent donc pourquoi la grande entreprise réussit mieux que la petite dans l'application des programmes de formation pour les défavorisés. Puisque ces facteurs présentent un caractère de stabilité, il serait, en conséquence, plus profitable pour les gouvernements, compte tenu du coût-efficacité, de concentrer leurs efforts sur la grande entreprise en ce qui touche le développement de l'emploi.Manpower training programs for the disadvantaged in the United States have been shifting in emphasis over time from institutional to on-the-job training. As a result, it has become increasingly important for program administrators to place trainees in the private sector. Yet little is known about employer characteristics whish are conducive or not conducive to a successful experience. The data presented here indicates that larger compagnies are significantly more successful in these programs than are smaller compagnies

White collar unionization in the United States

Thesis (M.B.A.)--Boston Universit

Multidimensionality of Entrepreneurial Firm-level Processes: Do the Dimensions Covary?

Covariance (or not) among the first-order dimensions of firm-level entrepreneurial processes underpins a fundamental and non-trivial difference between the entrepreneurial orientation and entrepreneurial posture constructs. Utilizing a typology developed for multi-dimensional constructs, we operationalized each construct according to its specific conceptualization (relationships among the dimensions) and compared and contrasted each construct in an identical nomological network. Although we found support for both theories, the entrepreneurial orientation construct was more robust in explaining additional variance in growth. Additionally, our findings suggest that the means through which the first-order dimensions are operationalized—latent vs. summates— significantly affect the analysis

Improving nurse staffing measures: Discharge day measurement in adjusted patient days of care

Previous research cannot account for the discrepancy between registered nurse (RN) reports of understaffing and studies showing slight improvement. One reason may be that adjusted patient days of care (APDC) underestimates patient load. Using data from all Pennsylvania acute care general hospitals for the years 1994 through 1997, we found that APDC is underestimated by two hours. After adjusting APDC, we examined the difference in nurse staffing over the period 1991-2000 before and after the adjustment. We found a significant difference between unadjusted and adjusted measures. However, when applied to the changes in nurse staffing between 1991 and 2000, the difference was not enough to account for the discrepancy between reports and data. Other measurement and conceptual problems may exist in terms of patients\u27 increasing acuity levels, patients\u27 declining lengths of stay and the associated greater proportion of nurse time devoted to admission and discharge, and lack of recent data in some empirical studies

Strategic Cognitive Maps of Small Business Leaders

Cognitive maps influence organizational strategic behaviors by guiding the perceptions of key decisions makers. This paper empirically examines these maps in small business leaders who have the ability to strongly influence an organization's attributes and actions. Results demonstrate that two distinct and polar orientations develop from small business leaders' self-identity with their organization, overall assessments of external stakeholders, and general perceptions of the environment. The strategic implications of these findings suggest that small business leaders should be mindful of their own viewpoints and biases since they can greatly influence organizational behaviors and subsequent performance

The impact of demographic and perceptual variables on a young adult\u27s decision to be covered by private health insurance

Background: The large number of uninsured individuals in the United States creates negative consequences for those who are uninsured and for those who are covered by health insurance plans. Young adults between the ages of 18 and 24 are the largest uninsured population subgroup. This subgroup warrants analysis. The major aim of this study is to determine why young adults between the ages of 18 and 24 are the largest uninsured population subgroup. Methods: The present study seeks to determine why young adults between the ages of 18 and 24 are the largest population subgroup that is not covered by private health insurance. Data on perceived health status, perceived need, perceived value, socioeconomic status, gender, and race was obtained from a national sample of 1,340 young adults from the 2005 Medical Expenditure Panel Survey and examined for possible explanatory variables, as well as data on the same variables from a national sample of 1,463 from the 2008 Medical Expenditure Panel Survey. Results: Results of the structural equation model analysis indicate that insurance coverage in the 2005 sample was largely a function of higher socioeconomic status and being a non-minority. Perceived health status, perceived need, perceived value, and gender were not significant predictors of private health insurance coverage in the 2005 sample. However, in the 2008 sample, these indicators changed. Socioeconomic status, minority status, perceived health, perceived need, and perceived value were significant predictors of private health insurance coverage. Conclusions: The results of this study show that coverage by a private health insurance plan in the 2005 sample was largely a matter of having a higher socioeconomic status and having a non-minority status. In 2008 each of the attitudinal variables (perceived health, perceived value, and perceived need) predicted whether subjects carried private insurance. Our findings suggest that among those sampled, the young adult subgroup between the ages of 18 and 24 does not necessarily represent a unique segment of the population, with behaviors differing from the rest of the sample

The impact of demographic and perceptual variables on a young adult\u27s decision to be covered by private health insurance

Background: The large number of uninsured individuals in the United States creates negative consequences for those who are uninsured and for those who are covered by health insurance plans. Young adults between the ages of 18 and 24 are the largest uninsured population subgroup. This subgroup warrants analysis. The major aim of this study is to determine why young adults between the ages of 18 and 24 are the largest uninsured population subgroup. Methods: The present study seeks to determine why young adults between the ages of 18 and 24 are the largest population subgroup that is not covered by private health insurance. Data on perceived health status, perceived need, perceived value, socioeconomic status, gender, and race was obtained from a national sample of 1,340 young adults from the 2005 Medical Expenditure Panel Survey and examined for possible explanatory variables, as well as data on the same variables from a national sample of 1,463 from the 2008 Medical Expenditure Panel Survey. Results: Results of the structural equation model analysis indicate that insurance coverage in the 2005 sample was largely a function of higher socioeconomic status and being a non-minority. Perceived health status, perceived need, perceived value, and gender were not significant predictors of private health insurance coverage in the 2005 sample. However, in the 2008 sample, these indicators changed. Socioeconomic status, minority status, perceived health, perceived need, and perceived value were significant predictors of private health insurance coverage. Conclusions: The results of this study show that coverage by a private health insurance plan in the 2005 sample was largely a matter of having a higher socioeconomic status and having a non-minority status. In 2008 each of the attitudinal variables (perceived health, perceived value, and perceived need) predicted whether subjects carried private insurance. Our findings suggest that among those sampled, the young adult subgroup between the ages of 18 and 24 does not necessarily represent a unique segment of the population, with behaviors differing from the rest of the sample

Re-Prioritizing Doctoral Education In Health Administration And Policy.

Among health administration programs, doctoral education has been a low priority for decades. Programs which are profitable from an economic perspective tend to be maintained or expanded while less profitable programs tend to be reduced. For a variety of reasons, doctoral programs tend to be viewed as less profitable than other programs. This paper analyses why doctoral programs are a low priority, the symptoms of this low priority, implications for the future of health administration education, and recommendations for enhancing that future

The Retail Revolution In Health Care: Who Will Win And Who Will Lose?

Retailers are expected to profoundly affect health care delivery by providing an alternative site for basic medical care. Retail health services are described together with their potential impacts on patient\u27s health care providers and payors. This article concludes with implications for health care executives. © 2006 Lippincott Williams & Wilkins, Inc

Customer Service

Management of customer service in healthcare requires addressing the service strategy, service staffing, and service systems. All are important contributors to the ultimate goal of meeting and exceeding the needs, wants, and expectations of internal and external customers. Key internal customers include physicians and staff. Key external customers include patients, families, third-party payers, and vendors. Discussion of the service strategy involves looking at the current market reality and consumer expectations. The strategic planning process as it relates to service requires assessment of the external environment, developing appropriate action plans, forecasting the future, enhancing the healing environment, and creating a customer-focused culture. Staffing addresses the human resource activities which provide the professional and non-professional staff who develop, implement, improve, and monitor the service strategy. Such activities or functions include job analysis, recruitment, selection, leader and staff development, employee motivation, and patient co-production of services. Systems refer to the processes, standards, and other practices that support staff including information systems, various systems techniques, systems to reduce wait times, feedback systems, and service failure recovery systems