A Call for Qualitative Power Analyses

The purpose of this paper is to emphasize the importance of sampling and sample size considerations in all qualitative research. Such considerations would help qualitative researchers to select sample sizes and sampling designs that are most compatible with their research purposes. First, we discuss the importance of sampling in qualitative research. Next, we outline 24 designs for selecting a sample in qualitative research. We then discuss the importance of selecting a sample size that yields data that have a realistic chance of reaching data saturation, theoretical saturation, or informational redundancy. Based on the literature, we then provide sample size guidelines for several qualitative research designs. As such, we provide a framework for making sampling and sample size considerations in interpretive research. An earlier version of this article received the 2004 Southwest Educational Research Association (SERA) Outstanding Paper Award.     

Inference with dependent data using cluster covariance estimators

This paper presents an inference approach for dependent data in time series, spatial, and panel data applications. The method involves constructing t and Wald statistics using a cluster covariance matrix estimator (CCE). We use an approximation that takes the number of clusters/groups as fixed and the number of observations per group to be large. The resulting limiting distributions of the t and Wald statistics are standard t and F distributions where the number of groups plays the role of sample size. Using a small number of groups is analogous to ‘fixed-b’ asymptotics of [Kiefer and Vogelsang, 2002] and [Kiefer and Vogelsang, 2005] (KV) for heteroskedasticity and autocorrelation consistent inference. We provide simulation evidence that demonstrates that the procedure substantially outperforms conventional inference procedures.     

Robustness of statistical inferences using linear models with meta-analytic correlation matrices

To examine complex relationships among variables, researchers in human resource management, industrial-organizational psychology, organizational behavior, and related fields have increasingly used meta-analytic procedures to aggregate effect sizes across primary studies to form meta-analytic correlation matrices, which are then subjected to further analyses using linear models (e.g., multiple linear regression). Because missing effect sizes (i.e., correlation coefficients) and different sample sizes across primary studies can occur when constructing meta-analytic correlation matrices, the present study examined the effects of missingness under realistic conditions and various methods for estimating sample size (e.g., minimum sample size, arithmetic mean, harmonic mean, and geometric mean) on the estimated squared multiple correlation coefficient (R²) and the power of the significance test on the overall R² in linear regression. Simulation results suggest that missing data had a more detrimental effect as the number of primary studies decreased and the number of predictor variables increased. It appears that using second-order sample sizes of at least 10 (i.e., independent effect sizes) can improve both statistical power and estimation of the overall R² considerably. Results also suggest that although the minimum sample size should not be used to estimate sample size, the other sample size estimates appear to perform similarly.     

The power of using video data

Most data for qualitative research studies in the management field are collected through observations and interviews. Written words and photographs are too static to accurately portray the depth of the given event or interview. We advocate the application of video data. The advantages of video data are its ability to capture the interaction of the participant with the environment, capturing of nonverbal cues, and establishing a permanent record. We recommend the use of Patten’s (Qualitative Evaluation and Research Methods, Sage, Newborn, 1990) process of analysis as a basis for an analytical procedure. To code video data research, software such as Vivo or ATLAS.ti can be used. The four standards to examine the validity and reliability of qualitative research studies (credibility, transferability, dependability and conformability) should also apply to video data analysis. The only outcome and true goal for the use of video data in management research can only be the provision of richer knowledge for academic development.     

Validity and Qualitative Research: An Oxymoron?

Although the importance of validity has long been accepted among quantitative researchers, this concept has been an issue of contention among qualitative researchers. Thus, the first purpose of the present paper is to introduce the Qualitative Legitimation Model, which attempts to integrate many of the types of validity identified by qualitative researchers. The second purpose of this article is to describe 24 methods for assessing the truth value of qualitative research. Utilizing and documenting such techniques should prevent validity and qualitative research from being seen as an oxymoron.     

Lessons from The Cultural and Political Economy of Recovery

This essay reviews four of the central themes in Emily Chamily‐Wright's The Cultural and Political Economy of Recovery. These themes include: (1) the cultural toolkit, (2) the use of qualitative methods in social science research, (3) polycentricism and disaster recovery, and (4) entrepreneurship in non‐priced environments. Our purpose is twofold. First, to make clear Chamlee‐Wright's contributions to our understanding of disaster recovery. Second, to demonstrate how these themes provide an opportunity for interdisciplinary exchange by blending insights from across the social sciences.     

TACKLING FALSE POSITIVES IN BUSINESS RESEARCH: A STATISTICAL TOOLBOX WITH APPLICATIONS

Serious concerns have been raised that false positive findings are widespread in empirical research in business disciplines. This is largely because researchers almost exclusively adopt the ‘p‐value less than 0.05’ criterion for statistical significance; and they are often not fully aware of large‐sample biases which can potentially mislead their research outcomes. This paper proposes that a statistical toolbox (rather than a single hammer) be used in empirical research, which offers researchers a range of statistical instruments, including a range of alternatives to the p‐value criterion such as the Bayesian methods, optimal significance level, sample size selection, equivalence testing and exploratory data analyses. It is found that the positive results obtained under the p‐value criterion cannot stand, when the toolbox is applied to three notable studies in finance.     

More than mere fragments? The use of the Workplace Employment Relations Survey data in HRM research

This paper explores the use of the British Workplace Employment Relations (WERS) survey data in HRM research. While the WERS surveys contain much material of relevance to key debates in the HRM area, there is a prima facie case that there has not been as much WERS-based research in the HRM area as might have been consequently expected. This paper examines why this might be the case, and considers the prospects for the further use of WERS data by HRM researchers. While noting the limits of survey data to address key questions in the area, it suggests that there is a need for a programme of research that builds upon the valuable insights that can be obtained from WERS-based research by the complementary generation of more context-rich information via focused case studies and associated qualitative research.     

Critical Areas and Entry Points for Sustainability‐Related Strategies in the Sugarcane‐Based Ethanol Industry of Brazil

This study reveals five critical areas that Brazil's sugarcane‐based ethanol industry could capitalize on to incorporate sustainability into their firms' strategies. The emergent theoretical framework represents a starting point for further investigations aimed at integrating the sustainability construct and strategies for the industry. A growing body of literature calls for strategic management to adapt to complex and ever‐changing environments and sustainability trends. For many firms in developing economies, sustainability remains isolated from mainstream strategy, resulting in reactive approaches on the part of management. A qualitative research method – grounded theory – was used to induct from data. Five themes emerged from the analysis providing guidance on where sustainability‐related strategies ought to begin. This research posits that existing sectoral innovation systems could be used to channel sustainability‐driven innovations. In addition, a combination of public and private efforts to foster innovations based on the emergent themes could increase the value of industry under study, while lessening its social and environmental footprint. Copyright © 2012 John Wiley & Sons, Ltd and ERP Environment.     

Localised Estimates of Dynamics of Multi‐dimensional Disadvantage: An Application of the Small Area Estimation Technique Using Australian Survey and Census Data

Deep and persistent disadvantage is an important, but statistically rare, phenomenon in the population, and sample sizes are usually not large enough to provide reliable estimates for disaggregated analysis. Survey samples are typically designed to produce estimates of population characteristics of planned areas. The sample sizes are calculated so that the survey estimator for each of the planned areas is of a desired level of precision. However, in many instances, estimators are required for areas of the population for which the survey providing the data was unplanned. Then, for areas with small sample sizes, direct estimation of population characteristics based only on the data available from the particular area tends to be unreliable. This has led to the development of a class of indirect estimators that make use of information from related areas through modelling. A model is used to link similar areas to enhance the estimation of unplanned areas; in other words, they borrow strength from the other areas. Doing so improves the precision of estimated characteristics in the small area, especially in areas with smaller sample sizes. Social science researchers have increasingly employed small area estimation to provide localised estimates of population characteristics from surveys. We explore how to extend this approach within the context of deep and persistent disadvantage in Australia. We find that because of the unique circumstances of the Australian population distribution, direct estimates of disadvantage have substantial variation, but by applying small area estimation, there are significant improvements in precision of estimates.     

Qualitative Research in the Service of Understanding Learners and Users of Statistics

This paper seeks to add to a scholarly dialogue regarding the role and value of qualitative techniques in research on learning and using statistics. The paper briefly outlines some of the core assumptions of qualitative research methods, and presents four examples to illustrate selected qualitative methods that are used by educational researchers and service organizations. The discussion emphasizes the need to integrate quantitative and qualitative approaches in research on learners and users of statistics, and suggests that such integration may be needed to study emerging web-based communities of learners and users of statistics.     

Tracking precursors of entrepreneurial intention: the case of researchers involved in eco-label industry

This article is based on the adaptation of Ajzen’s theory of planned behavior (TPB) to build an entrepreneurial intention framework tailored to the specific context of researchers involved in eco-label industry, who can be perceived as nascent entrepreneurs. The entrepreneurial intention model is tested on a convenience sample of researchers involved in eco-label industry from a wide range of countries. The configurational effect of research experience, personal attitude, funding instruments and entrepreneurial education level is tested for causal condition related to entrepreneurial intention of 25 eco-label researchers. The qualitative approach of data reveals that research experience and personal attitude relate positively to entrepreneurial career intentions and that these relationships are mediated by entrepreneurial education level. A multi-sided online platform connecting innovators and potential investors is considered a suitable solution for funding respondents’ results of research and innovation activities. Stimulating entrepreneurial motivations and intentions may help researchers to better adapt to alternative career perspectives. Results of this study suggest several ways to stimulate entrepreneurial career choices among researchers involved in eco-label industry.

     

Foundational Value of Statistics Education for Management Curriculum

The purpose of this paper is to propose a unique and distinct value of statistics education for management. The 1986 inaugural conference on Making Statistics More Effective in Schools of Business (MSMESB) proposed valuable guidelines for reforming statistics education in schools of business. However, a survey conducted by McAlevey & Everett (2001) identified that their impact has been minimal, and argued that structural problems many business schools have are the potential cause. We argue these structural problems exist because the value of the body of statistical tools for management is ambiguous and has not been made explicit. The unique and distinct value of statistics for management can be identified as the body of tools necessary to meet the inherent needs of a manager charged with making predictive judgments facing data. The need arises because human information‐processing capacity is quite limited, as the findings of researchers in cognitive psychology testify. These findings also affirm that the basic statistical concepts needed for processing data cannot be learned from management experiences. The model of a manager faced with data, while considering the evidence of inherent limitations of human information‐processing capacity, establishes the foundational value of statistics training in the management curriculum. Statistics education in business schools will be made more effective when management educators recognize such value of the discipline, lend their support and reward the ownership commitment for continuous improvement and innovations of the business statistics curriculum.     

Social integration and the role of student societies in higher education: an exploratory study in the UK

• This paper reports the research findings of an exploratory study designed to examine the role that planned efforts to establish and cultivate a student society play in the social integration of undergraduate students in higher education institutions (HEIs) in the UK. It identifies and explores the potential positive and negative benefits and outcomes that the operation of such a society can provide. The study aimed to achieve a better understanding of the role that a student society can play in the social integration of students. A qualitative methodology using 12 in‐depth interviews was employed. Data were analysed in relation to the key theme of the study, that is, student‐peer and student‐staff interactions. In addition, emergent themes were recorded and evaluated. The findings demonstrated that involvement in a student society did contribute to the social integration of students, it was found to be a key factor in reducing student attrition and dropout rates. The findings also demonstrate that a student society can make a meaningful and positive contribution to the management and administration of HEIs in terms of the perceived employability of students and the potential for student recruitment. It would appear that perhaps the value of a student society is currently under‐realised. Student societies could be viewed as a resource that with proper attention and development and could provide real benefits for both students and institutions across the entire HEI environment of the UK. Although there is a danger of student marginality occurring, there are ways to address this potential drawback.

Copyright © 2013 John Wiley & Sons, Ltd.     

Qualitative methodology and its pitfalls in educational research

There is considerable controversy in educational research with respect to the use of qualitative and quantitative data and as to what constitutes scientific research. The objective of this study is to explore the degree to which in-service teachers understand the difference between qualitative/quantitative data and methods, validity/authenticity, generalization and how these can be used to solve problems faced by the teachers. The study is based on 84 participants who had registered for a 10-week course on Methodology of Investigation in Education, as part of their Master’s degree program. The course is based on 11 readings drawing on a history and philosophy of science perspective (positivism, constructivism, Popper, Kuhn, Lakatos). Course activities included written reports, class room discussions based on participants’ presentations, and written exams. Based on the results obtained it is concluded: (a) Most participants understood that the problem to be investigated precedes the method and determines the methodology to be used; (b) As all observations are theory-laden, it is preferable that interpretations based on both qualitative and quantitative data be allowed to compete in order to provide validity to our research findings; (c) The difference between validity and authenticity was controversial and most participants considered the need for interpreting data and hence favored authenticity; (d) Discussions led to the idea of ‘degrees of validity’ as both validity in the quantitative sense and authenticity in the qualitative sense, ultimately depend on critical appraisals of the community; (e) Generalizability of results obtained from qualitative studies was a controversial topic and most participants agreed that it is not desirable to generalize; (f) Discussions suggested an alternative: In both qualitative and quantitative research generalizability is possible, provided we are willing to grant that our conceptions/theories are not entirely grounded in empirical evidence but rather on the degree to which the community can uphold such a consensus; (g) Most teachers considered the use of participant observation in qualitative research as non-controversial. Class discussions led to the understanding that emphasizing observations may lead us to the Aristotelian ideal of empirical science; (h) Formulation of hypotheses, manipulation of variables, and the quest for causal variables was considered by many teachers to be equivalent to the scientific method. Discussions facilitated the understanding that this led to idealization and thus helped to reduce the complexity of a problem.     

Generalization practices in qualitative research: a mixed methods case study

The purpose of this mixed methods case study was to examine the generalization practices in qualitative research published in a reputable qualitative journal. In order to accomplish this, all qualitative research articles published in Qualitative Report since its inception in 1990 (n =  273) were examined. A quantitative analysis of the all 125 empirical qualitative research articles revealed that a significant proportion (i.e., 29.6%) of studies involved generalizations beyond the underlying sample that were made inappropriately by the author(s). A qualitative analysis identified the types of over-generalizations that occurred, which included making general recommendations for future practice and providing general policy implications based only on a few cases. Thus, a significant proportion of articles published in Qualitative Report lack what we call interpretive consistency.     

Exploring the moderating effect of gender in the relationship between individuals' aspirations and career success among engineers in Peru

Purpose: The aim of this paper is to analyse the relationship between career success and individual career aspirations for engineers, and to test whether this differs according to gender. The primary hypothesis in this research is that gender does make a significant difference.

Design/methodological/approach: The sample consists of 1011 engineers who graduated from a prestigious Peruvian college between 1998 and 2005. Female graduates constituted only 4% of the sample, which is similar to the national statistics for engineers in Peru during this period. The relationships were primarily tested using multiple regression and structural equation modelling analyses.

Findings: Findings show a positive relationship between individual career aspirations and career success for men, but not necessarily for women; this supports the hypothesis that gender moderates this relationship. Females seek more secure career orientation than their male counterparts. In addition, females have shown that their career success is more related to feminine themes such as achieving ‘work–family balance’. The findings are in line with previously published results in other countries in which female engineers have career orientations with a preference for a balance between work and family as well as work stability.

Research limitations/implications: The sample is limited to graduates from a single Peruvian college of engineering. Although the sample has similar demographic characteristic to a national population, a more heterogeneous sample is called for in a future research. Moreover, additional moderators should be incorporated, such as family background, residency (large urban cities vs. small villages) and perhaps other variables.

Practical implications: Results can help Human Resource Managers to design better career plans, which consider gender in defining policies for the attraction and retention of competent female engineers.     

Guidance for deciding upon use of primary mixed methods studies in research synthesis: lessons learned in childhood trauma

When reviewing literature, mixed methods studies (MMS) are increasingly retrieved, yet it is unclear how they should be dealt with in a research synthesis. In this article we examine the inclusion of primary MMS in research synthesis, based on experiences with a meta-analysis (MA) and a qualitative evidence synthesis (QES) in childhood trauma. The aim is to offer guidance for reviewers in deciding upon the use of MMS. This review article examines (1) the qualitative component, (2) the quantitative component, as well as (3) the third component of combined yield for use in a MA, a QES or a mixed studies review. A systematic search for MMS in the field of childhood trauma from January 1980 to October 2011 resulted in twelve MMS. Eight qualitative components, six quantitative components and one combined yield could have been included in a MA or QES. Exclusion of qualitative components was due to insufficient quality. Quantitative components were excluded because sample sizes were too small, different outcome measures than ours were used or no adequate statistics were provided. Yield could not be included because it was absent, outside the scope or otherwise unspecified. Finally, we offer flow charts with clear steps to assist researchers in deciding upon the use of components of MMS. Our study demonstrates that MMS can cover new areas and therefore cannot be neglected in a research synthesis.     

Building IASB Research Capacity: A Commentary

This Commentary summarizes and remarks on several discussions of the link between academic accounting research and financial reporting standard setting. Our Commentary is prompted by references to building the International Accounting Standards Board's (IASB) research capacity, included in three due process documents: Report of the Trustees' Strategy Review, IFRSs as the Global Standard: Setting a Strategy for the Foundation's Second Decade; Agenda Consultation 2011; and Feedback Statement: Agenda Consultation 2011. Pursuant to its mission, the International Association for Accounting Education and Research (IAAER) has undertaken activities, including hosting two roundtables, related to the link between academic accounting research (and researchers) and the IASB's standard‐setting activities. We discuss the main issues addressed and themes emerging from the IAAER roundtables including whether academic research is relevant to standard setters; types of academic research, and areas of inquiry, that would be most relevant to accounting standard setters; perceptions on why academic research is not more useful to standard setters and challenges to academic researcher's engagement in standard setting. We summarize the IAAER Committee response to the consultation paper, Status of Trustees' Strategy Review. Finally, we identify areas where we believe academia can assist in building a dedicated research capacity at the IASB and note specific areas where future academic research is needed to inform the IASB.     

On selecting the best ofk lognormal distributions

Summary Fork lognormal populations, which differ only in one certain parameter Ϙ, the problem of finding the population with the largest value ofϑ is considered. For two-parameter lognormal families, several natural choices ofϑ are treated, where the problem can be solved, through logarithmic transformation of the observations, within the framework of estimating parameters ink, possibly restricted, normal populations. For three-parameter lognormal families, this standard approach of selecting in terms of natural estimators fails to work ifϑ is the “guaranteed lifetime”. For this case, a selection procedure is derived which is based on anL-statistic which has the smallest asymptotic variance. Of importance here is that it is location equivariant, whereas it does not matter what it actually estimates. Comparisons are made with other suitable selection rules, through the asymptotic relative efficiencies, as well as in an example of intermediate sample sizes. It is shown that only in the latter, the selection rule, which is based on the sample minima, compares favorably. The research of this author was supported by the Office of Naval Research Contract N00014-88-K-0170 and NSF Grant Number DMS-8606964 at Purdue University. Reproduction in whole or in part is permitted for any purpose of the United States Government. The research of this author was supported by the Air Force Office of Scientific Research Grant 85-0347 at the University of Illinois at Chicago.