The authors propose the use of experience sampling methodology (ESM) as an innovative methodological approach to address critical questions in entrepreneurship research. ESM requires participants to provide reports of their thoughts, feelings, and behaviors at multiple times across situations as they happen in the natural environment. Thus, ESM allows researchers to capture dynamic person-by-situation interactions as well as between- and within-person processes, improve the ecological validity of results, and minimize retrospective biases. The authors provide a step-by-step description of how to design and implement ESM studies beginning with research design and ending with data analysis, and including issues of implementation such as time and resources needed, participant recruitment and orientation, signaling procedures, and the use of computerized devices and wireless technologies. The authors also describe a cell phone ESM protocol that enables researchers to monitor and interact with participants in real time, reduces costs, expedites data entry, and increases convenience. Finally, the authors discuss implications of ESM-based research for entrepreneurs, business incubators, and entrepreneurship educators.

In response to the ongoing concern regarding a science-practice gap, we propose a customer-centric approach to reporting significant research results that involves a sequence of three interdependent steps. The first step involves setting an alpha level (i.e., a priori Type I error rate) that considers the relative seriousness of falsely rejecting a null hypothesis of no effect or relationship (i.e., Type I error) relative to not detecting an existing effect or relationship (i.e., Type II error) and reporting the actual observed p value (i.e., probability that the data would be obtained if the null hypothesis is true). The second step involves reporting estimates of the size of the effect or relationship, which indicate the extent to which an outcome is explained or predicted. The third step includes reporting results of a qualitative study to gather evidence regarding the practical significance of the effect or relationship. Our proposal to report research results with rigor, relevance, and practical impact involves important changes in how we report research results with the goal to bridge the science-practice gap.

This essay tries to be true to a podium talk I presented at a conference in March, 2008. But, of necessity, certain consolidation liberties are taken. Beginning with a brief and broad treatment of ethnography as a paired written representation of and lengthy personal experience in a particular social world, I move to consider why the former, the text, has been so infrequently examined in lieu of the latter, the so-called method. I then move to ethnographic texts themselves and look at what I take to be some broad changes the seem apparent – particularly within the organizational ethnography domain – over the past 20 or so years. Alongside these changes comes the emergence of several distinct genres treated only lightly (or not at all) in Tales of the Field. I end by considering what seems to have stayed the course in ethnography and why.

We review conjoint analysis (CA) usage in recent entrepreneurship research to assess how researchers have used the method to study entrepreneurial decision making. We first provide a brief overview of the method and present an exemplar study. We next examine how 16 studies published in leading entrepreneurship journals from 1999 to 2008 used CA, highlight topics these studies have investigated most frequently, and suggest reasons why studies, in general, have not used the method with greater frequency, despite its many advantages in studying decision making. We conclude by suggesting potential future research applications in an attempt to encourage greater CA usage in entrepreneurship research.

Techniques such as dominance analysis and relative weight analysis have been proposed recently to evaluate more accurately predictor importance in ordinary least squares (OLS) regression. Similar questions of predictor importance also arise in instances where logistic regression is the primary mode of analysis. This article presents an extension of relative weight analysis that can be applied in logistic regression and thus aids in the determination of predictor importance. We briefly review relative importance techniques and then discuss a new procedure for calculating relative importance estimates in logistic regression. Finally, we present a substantive example applying this new approach to an example data set.

Ethnography plays a partial role in organizational development in ways that call out for a kind of "tale of the field" that represents what Geertz calls a "blurred genre." It is blurred by a mixture of ethnographic epistemology based on abductive logic and context/meaning questions, together with ideas from organizational intervention from work by such figures as Argyris, Schein and Stacey. This article defines and exemplifies the blend with two case studies from a state court and a cancer treatment center. The conclusion is that the tale, blurred genre though it is, is in fact clear and it works. The problem is that political and implementation issues typically block a trial run of the proposed solutions that it generates.

Construct validity continues to pose challenges in the organizational sciences. To capture difficult-to-measure constructs of interest, researchers have often relied on content analysis. One content analysis technique, computer-aided text analysis (CATA), is particularly attractive because of the ability to process large samples with high speeds and reliabilities. Unfortunately, inconsistent guidance exists to guide researchers through the use of this tool in a manner compatible with accepted methods used to validate constructs in a rigorous manner. The authors review research using content analysis to examine the extent to which such studies integrate methods for assessing content, external, discriminant, and predictive validity. To provide direction for organizational researchers interested in using CATA to measure theoretically based constructs relevant to the management field, they suggest a number of possible procedures to enhance construct validity. They illustrate these procedures using the construct of entrepreneurial orientation.

I want to discuss a version of collaborative action research oriented toward exploring, and verbally articulating, the real possibilities for making an innovative next step in a specific situation in a particular organization. There are many situations in organizational life in which people express, either very general concerns—for example, a need for people to be more innovative, to trust each other more, and so on—or simply feelings of disquiet, of "something being not quite right" needing to be changed ... although they do not know what that "something" is! The research we are often asked to do is precisely to make these vague concerns sufficiently determinate to inform new (or at least modified) practices. But this task, as I see it, following Wittgenstein (1980), entails resolving a difficulty of orientation or of relating rather than solving a problem. Below, the author discusses a dialogically structured action research practice precisely tailored to these orientational needs, along with the theoretical-concepts needed to guide participants in it toward the activities relevant both to its conduct and toward the realization of the possibilities it discloses.

John Van Maanen’s account of the evolution of ethnographic narratives provided far more than insight about classic anthropological and sociological texts. By encouraging qualitative researchers to focus on the rhetorical and political qualities of voice, style, authority, and representations of selves and others, he exposed the often hidden assumptions built into fieldwork and scholarship. It is not too much to say that no other single text has so forcefully shaped and inspired our understanding of qualitative research and narrative writing across the social sciences. Van Maanen’s work inspired two cross-disciplinary projects. One charted the cultural, rhetorical, and narrative influences that constructed classic ethnographic texts; the other created a common cultural code for new explorations of organizations and cultures. One result of those projects is that those of us doing qualitative became more comfortable in our textual diversity if at times challenged to find the appropriate evaluative standards to determine its worth and contribution. We have also embraced, if not fully acted upon, a perceived need to make our scholarship more relevant to diverse publics inside and outside of the academy.

In quantitative research, analyses are generally made using a geographically defined population as the study area. In this context, the relationships between predictor and response variables can differ within the study area, a feature that is known as spatial heterogeneity. Without analyzing spatial heterogeneity, a global model may not be correct, and there may be unclear spatial boundaries in the generalizability of the findings. The authors discuss how the method of geographically weighted regression (GWR) can be used to identify the study area, and illustrate the utility of GWR for empirical analyses in entrepreneurship research. Future entrepreneurship research can benefit from analyzing whether conflicting evidence may be due to spatial heterogeneity and from applying GWR in an exploratory way.

This article deals with interviewing reluctant respondents. The analysis is used to construct a process-oriented model of respondent rapport and empathy. By assessing respondent rapport in a reflective way, the article contributes to the sociology of knowledge generation and the construction of respondent reality of complex social phenomena. Using the authors' reflective experiences of a particular interview episode, the stages of rapport building in the researcher–respondent relationship are assessed, providing guidance and lessons for future researchers. The limitations of the approach are considered and suggestions for future research are made.

The authors develop, illustrate, and validate an experimental approach to further empirical research on opportunity recognition. The approach emphasizes the use of recognition exercises that provide direct observations of participants’ efforts to think about ex-ante uncertain opportunities. To facilitate future uses of this approach, the authors develop a measure of opportunity-recognition beliefs and conduct three related studies to validate this measure. The authors conclude by offering concrete practical recommendations for future studies. Doing so, the authors contribute an integrated method to address conceptual and methodological issues that have hindered prior research on opportunity recognition, and thereby enable more rigorous investigations of this important activity.

The current study provides an exposition of artificial neural network (ANN) methodology in the context of research on personality and work performance. We demonstrate some of the benefits and limitations of this methodology relative to multiple regression (MR) for conducting exploratory research. Using three data sets that each contained personality scores and measures of work performance, we compared the predictive accuracy of ANNs to both simple and complex MR equations. Across the three data sets, the neural networks performed as well or better than the MR equations on a relational measure of predictive accuracy but performed no better than the simplest regression equations on an absolute measure of predictive accuracy. Furthermore, through a combination of sensitivity analysis and graphical representations, we were able to identify the specific configural and nonlinear relationships that accounted for the superior performance of the neural networks with respect to the relational measure. The implications of the findings for researchers interested in applying ANNs to study organizational behavior are discussed.

Research design is a central element of empirical research, and thus, an important consideration for entrepreneurship researchers and anyone interested in entrepreneurship-related research findings. Yet, many years have past since the last thorough review of research design and construct measurement practices. Thus, it is unknown whether there is a gap between what is currently being done versus what needs to be done. In this article, authors use a two-study approach involving a content analysis of published empirical research and a survey of experts within the field to assess the current state of practices. Their findings indicate that, in general, research design and construct measurement practices continue to improve; however, there are some issues that still need to be resolved. Authors lay out key implications and provide several suggestions to help resolve these issues.

Measures used in entrepreneurship research are often subject to spatial dependence. Spatial dependence renders ordinary least squares (OLS) estimation inappropriate because the estimates will be biased, inconsistent, and/or inefficient. The aims of this article are (a) to demonstrate how spatial dependence is especially problematic for entrepreneurship research and (b) to arm researchers with spatial modeling techniques that are more appropriate for such analysis. As such, not only will this article illustrate how to incorporate spatial dependence explicitly into the linear regression model, it also discusses how these techniques make it possible to explore and locate areas with particularly high levels of spatial dependence (i.e., hot spots). These techniques, although new to the management literature, are well known in both the regional science and geography literatures and are rapidly diffusing to economics, sociology, and related social sciences.