Effect Sizes in Qualitative Research: A Prolegomenon

The American Psychological Association Task Force recommended that researchers always report and interpret effect sizes for quantitative data. However, no such recommendation was made for qualitative data. Thus, the first objective of the present paper is to provide a rationale for reporting and interpreting effect sizes in qualitative research. Arguments are presented that effect sizes enhance the process of verstehen/hermeneutics advocated by interpretive researchers. The second objective of this paper is to provide a typology of effect sizes in qualitative research. Examples are given illustrating various applications of effect sizes. For instance, when conducting typological analyses, qualitative analysts only identify emergent themes; yet, these themes can be quantitized to ascertain the hierarchical structure of emergent themes. The final objective is to illustrate how inferential statistics can be utilized in qualitative data analyses. This can be accomplished by treating words arising from individuals, or observations emerging from a particular setting, as sample units of data that represent the total number of words/observations existing from that sample member/context. Heuristic examples are provided to demonstrate how inferential statistics can be used to provide more complex levels of verstehen than is presently undertaken in qualitative research.     

Density estimation in the uniform deconvolution model

We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estimate based on the empirical distribution function of the observable data. The second is a kernel density estimate based on the MLE of the distribution function of the unobservable (uncorrupted) data.     

数据管理:电子商务数据的存储问题

许多情况说明，用于组织中数据存储的消费已经成爆炸状态。产生这种情况的主要因素是电子邮件和电子商务对数据的质量和数量的要求提高了，并且这种数据大部分是分散的、非结构性的，这就增加了对组织中数据管理的要求。本文是在澳大利亚进行的一次调查的基础上做出的，该调查是关于组织中如何处理数据增长和由于数据增长所带来的问题。调查的结果显示人们对该问题表现出高度的关注，同时显示出一种乐观的趋势，即技术将对未来出现的各种各样的问题提供解决方案。     

FDI facilitated by agglomeration economies: evidence from manufacturing and services joint ventures in China

The open door policy of China’s economic reform since the 1980s has attracted heavy foreign direct investment (FDI) flows into China and especially to Guangdong (particularly the Pearl River Delta region, PRD) and induced significant economic growth during the past two decades. While there exist various classical theories of FDI in attempting to identify the determinants of FDI inflow and to explain the behavior of FDI flows, limited attention has been given from the perspective of agglomeration effects generated by a core-periphery (CP) relation.This paper intends to study the impacts of agglomerations on FDI inflows in the context of Krugman’s CP relation (1991) by investigating (1) the formation of a CP relation via gravity model analysis; (2) whether different types of industry FDI flows will respond differently in the CP-system, given agglomeration effects; and (3) whether FDI origin and firm scale matter in affecting FDI flows.A database consisting of a population frame of 37,742 firm-level manufacturing and services joint ventures investing in Guangdong in 1998 was used. Empirical results show that the agglomerations of the CP relation have affected FDI flow patterns. While both manufacturing and services FDI and sources of investment responded differently to the impacts, smaller firms were found more responsive to the CP-agglomeration settings regardless of FDI by industry type and by source. The significance and implications of the CP-system to further facilitate FDI in the region are discussed.     

Identifying “best” applicants in recruiting using data envelopment analysis

Selecting the most promising candidates to fill an open position can be a difficult task when there are many applicants. Each applicant achieves certain performance levels in various categories and the resulting information can be overwhelming. We demonstrate how data envelopment analysis (DEA) can be used as a fair screening and sorting tool to support the candidate selection and decision-making process. Each applicant is viewed as an entity with multiple achievements. Without any a priori preference or information on the multiple achievements, DEA identifies the non-dominated solutions, which, in our case, represent the “best” candidates. A DEA-aided recruiting process was developed that (1) determines the performance levels of the “best” candidates relative to other applicants; (2) evaluates the degree of excellence of “best” candidates’ performance; (3) forms consistent tradeoff information on multiple recruiting criteria among search committee members, and, then, (4) clusters the applicants.     

TAX COMPETITION

In the modern world, capital enterprise and skilled labour are increasingly mobile, and naturally attracted to countries with low taxes. Indeed tax competition can be healthy, and far preferable to a 'tax collectors' cartel.' The right of the fiscally oppressed to move themselves and their capital elsewhere is a great defender of economic freedom.     

Evidence on agglomeration economies,diseconomies, and growth

Conventional urban economic analysis suggests that a local economy's size is closely related to a number of features, including levels of human capital and the availability of specialized inputs, which are likely to influence positively the rate at which it accumulates further economic activity. At the same time, urban theory also suggests that once cities reach a certain level of size, these agglomeration benefits begin to peter out, while diseconomies rise rapidly. Consequently, we should see an ‘inverted U‐shaped’ pattern of growth with respect to economic size—rates of growth first rise, then fall as size increases. This paper shows that, while such a pattern is largely absent from recent data on growth in metropolitan area population and employment, it emerges strikingly in county‐level data. Copyright © 2002 John Wiley & Sons, Ltd.     

Changes in food provision in Russian households experiencing perestroika

The purpose of this article is to describe how households in Novgorod the Great, Russia, deal with food provision in everyday life. The study focuses on changes experienced in food provision and consumption in Russian society, in order to illustrate how households respond to the transformation towards a market economy. The study reflects women's perspective on food provision. Students from Novgorod the Great visited 105 households and asked the women in the household to answer a questionnaire. Results from the study show that in order to cope with changes in society related to economic reforms, Russian households had changed both their food consumption and food production patterns. There was no big difference between urban and rural households. Nearly all of the households were self‐sufficient in the provision of vegetables and potatoes. Many households had a ‘dacha’ (plot), where they produced most of what they needed. Among the changes experienced during recent years (i.e. during the end of the 1990s), a decade after perestroika was initiated, households mentioned the rise in food prices and the decrease of income. Households reported that they consumed less fruit and/or meat. Some households also mentioned that the quality of nourishment had decreased, thereby indicating lower general quality, lower nutrition value, or less healthy foodstuffs.