Search results

Public management researchers commonly model dichotomous dependent variables with parametric methods despite their relatively strong assumptions about the data generating process. Without testing for those assumptions and consideration of semiparametric alternatives, such as maximum score, estimates might be biased, or predictions might not be as accurate as possible.

To guide researchers, this paper provides an evaluative framework for comparing parametric estimators with semiparametric and nonparametric estimators for dichotomous dependent variables. To illustrate the framework, the article estimates the factors associated with the passage of school district bond referenda in all Texas school districts from 1998 to 2015.

Estimates show that the correct prediction of a bond passing increases from 77.2 to 78%, with maximum score estimation relative to a commonly used parametric alternative. While this is a small increase, it is meaningful in comparison to the random prediction base model.

Future research modeling any dichotomous dependent variable can use the framework to identify the most appropriate estimator and relevant statistical programs.

To review and address current approaches and limitations to modeling change over time in social entrepreneurship research.

The article provides a narrative review of different practices used to assess change over time. It also shows how different research questions require different methodologies for assessing changes over time. Finally, it presents worked examples for modeling these changes.

Our review suggests that there is a lack of research in social entrepreneurship that takes into account the many different considerations for addressing how time influences outcomes.

This chapter introduces an analytic technique to social entrepreneurship that effectively models changes in predictors and outcomes even when data are non-normal or nested across time or levels of analysis.

We sought to identify codes and themes in the mission statements of Kentucky's school districts and examine the relationship between district characteristics and the mission statements.

We undertook a mixed methods design, specifically, a sequential transformative strategy with a theoretical lens overlaying the sequential procedures and guiding the analysis.

Analysis revealed a range of 1–7 codes per mission statement and a mean of 3.05. Generic student success and individual attention represented the most frequently occurring codes in the mission statements. Chi-square tests of bivariate association yielded no significant differences between districts by locale. Logistic regression analysis revealed that the percentage of students in the district scoring proficient or distinguished in both reading and mathematics was associated significantly (p < 0.05) with the theme of student support.

Although we cannot establish causation between mission statements content and student outcomes or vice-versa, district mission statement remain a visible and public expression of why an organization exists that should guide actions and decision-making, whether instructional, financial or otherwise.

Our study revealed shared institutional language within mission statements across Kentucky's school district, largely without regard to local context. Our analysis suggests that federal and state policy makers are influencing mission statements more so than those at the local level.

Our analysis provides further evidence that suggests that federal and state policy makers are influencing mission statements more so than those at the local level.

On the theoretical level, this chapter examines the mechanisms through which cultural and financial capital affects educational outcomes in different institutional contexts. On the methodological level, the central question in this chapter is how to resolve concerns in comparative analyses of educational attainment, such as variations in enrolment rates and study program duration across institutional settings. On the empirical level, the chapter asks whether family background predicts educational attainment in similar ways in two diametrically opposed welfare states: the United States and Norway. Differences in dropout from higher education were compared using nationally representative longitudinal data from the United States and Norway and event history and multilevel modelling techniques. The chapter also makes use of the standardized sheaf coefficient to summarize central background variables for more direct comparison of effect sizes. The findings show that whereas parents’ education level has strikingly similar effects on students’ dropout probabilities in the two countries, the effect of parents’ income varies substantially according to the institutional context. The chapter concludes that in comparative analyses of inequality in education the value of different types of family resources must be understood in light of the concrete, practical constraints of the national institutional contexts.

Studies for online designer clothing purchases and also online purchases of numerous types of designer clothing are so far unknown. This study seeks to analyze variables influencing intentions to purchase designer clothing online and also online purchases of different types of designer clothing over three months.

Cross‐sectional and longitudinal analyses were performed with linear and logistic regression (n=527). The theoretical framework was the Theory of Planned Behavior. Independent variables also included the Boredom Proneness Scale, and the Consumer Decision Making Styles Inventory. Clothing types were intimate apparel, underwear, swimwear, pants, jeans, skirts/dresses, T‐shirts, shoes, sneakers, sweaters, jackets/coats, socks, hosiery, and hats.

The cross‐sectional analysis for intentions substantiated the Theory of Planned Behavior. Boredom was associated with intentions and some of the specific types purchased. In the longitudinal analysis, increased internet information search was associated with purchases for all the specific clothing types. The most common purchases were T‐shirts, shoes, and skirts/dresses.

Participants were allowed to interpret what was perceived as designer clothing.

As information search is associated with purchases of many types of designer clothing, companies should focus on increasing the likelihood of their web pages being searched. Useful strategies can include purchase of sponsored links and efforts to improve page rank.

This is the first study to analyze predictors for purchasing numerous specific types of designer clothing online. Also, it is believed to be the first longitudinal study to use the Theory of Planned Behavior as the framework to analyze online apparel purchases.

This study aims to examine the relationship between top‐performing US furniture manufacturers and industry's best manufacturing practices.

In the past studies, best manufacturing practices were mostly determined using qualitative methods. In this paper, a quantitative evaluating method to determine best manufacturing practices was designed by taking into consideration qualitative criterions. A sample of 122 manufacturing practices was observed in six US furniture companies, two of them considered world‐class performers and the other four considered average. A logistic regression was used to examine the relationship between best manufacturing practices and top‐performing companies.

Statistical analyses showed a positive relationship between top‐performing companies and use of best manufacturing practices by these companies. A database of best manufacturing practices was created and shared with the participant companies.

One limitation of this study is that the causal relationship between performance and best practices was not considered. Future studies could employ statistical methods such as structural equation model to better understand this causality. Other methods could possibly be developed to audit and classify manufacturing practices.

It is believed that the database of best manufacturing practices will help average or below‐average performing companies to identify and adopt best manufacturing practices. It will also help top‐performing companies in the cycle of continuous improvement.

The purpose of this paper is to assess the vulnerability of communities prone to earthquake hazards in Baluchistan at the community and household levels and identify the determinants accounting for the vulnerability of the communities. Baluchistan is vulnerable to potential seismic risk and has recently suffered huge economic and property losses due to the October 2008 earthquake.

The study is based on household surveys, field observations, key informant interviews and focus-group discussions for the assessment of community vulnerability to earthquakes.

The analysis revealed that the community is vulnerable to earthquake hazards both at the community and household levels. The logistic regression model identified three variables, namely, ownership of residential unit, family size and household income, as the most important factors in influencing community vulnerability to earthquake hazards.

The paper may help emergency managers, policymakers and local government authorities to implement building codes, urban planning by-laws and projects and activities to empower communities for disaster preparedness and disaster risk reduction.

The paper concludes that for earthquake safety, building regulations and spatial planning by-laws should be implemented and monitored rigorously. Community preparedness is essential for enhancing people’s awareness against future earthquake hazards in the area.

The purpose of this paper is to measure the potential role of the field of education and the fact of having worked during studies on the employability of the higher educated (ISCED 5-6) cohort targeted by the ET2020 graduates’ employability benchmark.

Using the same data source as the benchmark (i.e. the annual LFS microdata from 2004 to 2010), and exploring the additional transition questions collected in the LFS 2009 ad hoc module, the authors define and test four hypotheses using a probit approach on each EU country.

The degree plays a significant role in the employability of young graduates across countries and time. In terms of probability of employment, the leading field is health and welfare. In terms of type of contracts, the leading fields are social sciences and engineering. Moreover, what labour markets seem to value the most is the capacity of higher educated students to combine high-level studies and work, i.e. a high workload capacity and intellectual flexibility.

Reaching the new European target of a minimum of 82 per cent of employment of young graduates will require countries to invest wisely in the most “employable” fields of education. This analysis will help policy makers in their future orientations towards that target.

The originality of this work lies in its exploration of the exact same extraction of microdata used for the computation of the ET2020 Benchmark indictor and in its immediate political implications for the monitoring of this benchmark.

This article investigates the effectiveness of pepper spray as a means of aiding arrest. The authors aim to provide a more rigorous study than has previously been achieved. Data from the Baltimore County Police Department have been used in this analysis. The evaluation undertaken has taken into account the “effective‐ineffective” dichotomy of the incapacitating effects of pepper spray as well as whether those being arrested were drunk, under the influence of drugs or mentally disturbed. Five variables of age, weight, height, race and sex were also recorded, the latter three having little or no effect. The overall conclusion which is drawn is that using pepper spray eases arrest in the majority of instances. The conclusions drawn leave the way open for further detailed analysis of the use of the spray to ease arrest.

Although the use of data from different levels is very common in international marketing research, the practice of employing multi‐level analysis techniques is relatively new. The paper aims to provide an application of a specific case of multi‐level modelling – where the dependent variable is dichotomous, which is often the case in marketing research (e.g. whether a consumer buys the brand or not, whether he/she is aware of the brand or not, etc.)

A hierarchical generalized linear model is employed.

Since this is a technical paper, the authors would like to emphasize the process rather than the empirical findings. In summary, the paper: provides a brief theoretical overview of Hierarchical Linear Modeling and Hierarchical Generalized Linear Modeling; illustrates the application of the method using the domains of consumers within countries and a dichotomous dependent variable; focuses on interpretation of log‐odds results; and concludes with practical issues and research implications.

The main value of this research is to demonstrate how to employ multi‐level models when the dependent variable is dichotomous. Multi‐level techniques are quite new in international marketing research, although nested data structures are relatively common in our field. This is a technical paper that guides the researchers as to how to apply and interpret the results when modeling such data with a dichotomous dependent variable.