Problem: Partial least squares (PLS), a form of structural equation modeling (SEM), can provide much value for causal inquiry in communication-related and behavioral research fields. Despite the wide availability of technical information on PLS, many behavioral and communication researchers often do not use PLS in situations in which it could provide unique theoretical insights. Moreover, complex models comprising formative (causal) and reflective (consequent) constructs are now common in behavioral research, but they are often misspecified in statistical models, resulting in erroneous tests. Key concepts: First-generation (1G) techniques, such as correlations, regressions, or difference of means tests (such as ANOVA or <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">${\rm t}$</tex></formula> -tests), offer limited modeling capabilities, particularly in terms of causal modeling. In contrast, second-generation techniques (such as covariance-based SEM or PLS) offer extensive, scalable, and flexible causal-modeling capabilities. Second-generation (2G) techniques do not invalidate the need for 1G techniques however. The key point of 2G techniques is that they are superior for the complex causal modeling that dominates recent communication and behavioral research. Key lessons: For exploratory work, or for studies that include formative constructs, PLS should be selected. For confirmatory work, either covariance-based SEM or PLS may be used. Despite claims that lower sampling requirements exist for PLS, inadequate sample sizes result in the same problems for either technique. Implications: SEM's strength is in modeling. In particular, SEM allows for complex models that include latent (unobserved) variables, formative variables, chains of effects (mediation), and multiple group comparisons of these more complex relationships.

In this paper we present, from an academic perspective, the perceived quality ratings of business and technical communication journals. Through a survey of academic experts, we asked respondents to rate the top overall journals, business communication journals, technical communication journals, and the top journals from a technology perspective. In addition, we asked respondents to list the journals that they read most frequently. We analyzed the results by breaking down the rankings into world regions and academic departments. The top-three overall journals for all regions are Journal of Business and Technical Communication, Journal of Business Communication, and IEEE Transactions on Professional Communication. Importantly, differences by world region and academic department type were found in all these rankings. These results can support researchers worldwide by helping them target their publishing efforts to journals that have the best fit with their business and technical communication discipline, world region, and academic home.