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.     

The capital structure implications of pursuing a strategy of innovation

In this paper, we argue that consideration of firm strategy can help illuminate the choices managers make between debt and equity financing. Within an industry, the form of competition that each firm chooses will determine the strategic value to the firm of maintaining financial slack. Our empirical analysis yields strong support for the proposition that financial slack should be a particularly critical strategic imperative for firms pursuing a competitive strategy premised on innovation. We also demonstrate that firms pursuing such a strategy that fail to recognize the value of financial slack are likely to perform poorly. Copyright © 2003 John Wiley & Sons, Ltd.     

Why Press Coverage of a Client Influences the Audit Opinion

In this study I use an experiment to examine why auditors are more likely to issue going–concern opinions when the client has been the subject of negative press coverage prior to the date of the audit opinion. I find no evidence that negative press coverage increases auditors' perceptions of legal liability, as was suggested in the prior literature. I do find, however, that negative press coverage increases auditors' perception of a client's bankruptcy probability and this, in turn, leads auditors to modify the audit opinion. Because the press coverage presented in this study provides no new information, the results suggest that auditors react too strongly to redundant information. This over–reaction can result in inefficient allocation of audit resources and can have deleterious affects on clients. Accordingly, policy makers, auditors and their clients might be interested in how auditors' reliance on redundant information can be reduced.     

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.