When asked by the editors to contribute a chapter to their book on how I position family business research in targeting different types of journals, I thought that this would be a simple task. Codifying intangible knowledge, however, is easier said than done. Thus, I searched my memory to find where this intangible knowledge comes from and how I have established my publication pattern.
Edited by Pietro Mazzola and Franz W. Kellermanns
Franz W. Kellermanns and Kimberly A. Eddleston
Franz W. Kellermanns and Laura J. Stanley
Frederik J. Riar and Franz W. Kellermanns
Family firms are essential to both emerging and advanced economies. Nearly 90 percent of all firms worldwide are family firms (Aldrich and Cliff, 2003); they outnumber nonfamily firms in terms of their contribution to global economic activity and employment (De Massis et al., 2015; Gedajlovic et al., 2012). Although many family firms are small, a sizable number are represented among medium and large corporations (La Porta et al., 1999), such as ALDI Group, BMW, Cargill and Walmart. Owing to the high relevance of family firms for the worldwide economy, scholars have recognized family business as a research field (Debicki et al., 2009). The theory of family firm conferences (see Chrisman et al., 2003; Chua et al., 2003), the highly visible publications on family business (for example, Schulze et al., 2001, 2003), and the establishment of family-firm specific conferences (for example, the International Family Enterprise Research Academy, IFERA, and the Federal Energy Regulatory Commission, FERC) have helped to start and fuel the growth of the field.
Curtis F. Matherne, Bart J. Debicki, Franz W. Kellermanns and James J. Chrisman
Melissa Medaugh, Laura Stanley, Franz W. Kellermanns and Thomas M. Zellweger
In this chapter, we review person-centered mixture modeling and longitudinal research methods capable of advancing family firm and entrepreneurship theory. The modeling techniques we discuss (i.e., Latent Profile Analysis, latent growth modeling, multilevel growth modeling, and latent class growth modeling) complement more traditional variable-centered methods and allow researchers to examine the complex interplay between variables, as well as how these relationships change over time. We provide illustrations from extant research and offer suggestions for future research employing these techniques.