Social Structural Inquiries – Part 2: Statistical Methods and Process Models

A tightened linkage between theory and data would enhance cumulative sociological knowledge. Toward that end this article selectivity reviews and develops social structural theories – theories that explain data. It focuses on statistical methods and process models because both approaches advance cumulative social science, and the tension between their advocates works against disciplinary solidarity. Boudon’s structural schematics cover all of the examples, suggesting a common perspective that can lessen the friction among practitioners of these forms of quantitative analysis and refocus much of the diversity of current sociology. An erratum to this article is available at .     

Nonlinear Structural Equation Models with the Theory of Planned Behavior: Comparison of Multiple Group and Latent Product Term Analyses

Nonlinear relationships in structural equation analysis became moreinteresting for applied researchers since the implementation of nonlinearconstraints in software programs (i.e., LISREL). This article provides acomprehensive application of the expectancy × value part of the Theory of Planned Behavior (Ajzen, 1991) including interactions of latent variables.The main purpose of the study is to overcome limitations of similarprevious analyses of Baumgartner and Bagozzi (1995) and Yang Jonsson (1997,1998) with an empirical example from representative survey data. Nonlinearrelationships of the theories' constructs (Attitude toward the behavior, subjectivenorm and perceived behavioral control) are analyzed one upon another withmultiple group comparisons and latent interaction models. Results confirmthe strategy to use multiple group techniques for preliminary analyses(i.e., detection of an interaction effect). With latent interaction models thestrength and the significance of the interaction is estimated under controlfor random measurement error. Parameters, standard errors, andgoodness-of-fit statistics are compared between three estimationtechniques (ML, GLS and WLS). Multiple group analyses and latentinteraction modeling detect a significant interaction for perceivedbehavioral control but not for attitude toward the behavior and subjective norm. Variations of the estimators of the perceived behavioral controlsubmodel is proved by bootstrapping. Further model improvements andalternative model techniques are discussed in the final chapter.     

Sustainable development of small‐ and medium‐sized enterprises in the European Union: A taxonomy of circular economy practices

This paper focuses on the implementation of circular economy (CE) practices in small‐ and medium‐sized firms in all 28 European Union (EU) countries. The analyses take into account the hierarchical nature of the collected data as firms are nested within EU countries, that is, the heterogeneity between different types of firms and countries according to practices and attitudes towards CE. The multilevel latent class model identifies groups of firms and groups of EU countries that are homogeneous in terms of CE, that is, how the homogeneous groups of small‐ and medium‐sized enterprises (SMEs) are distributed across the groups of EU countries. These results, together with the fact that firms with similar CE attitudes and practices have different demographic and business profiles across groups of countries, shed further light on the topic of green behavior in the EU with implications for businesses' environmental policies. Moreover, indications emerge that European policies favoring the implementation of CE practices should be targeted at least for subgroups of European countries, considering the different composition by typology of SMEs operating in their territories and that, at the same time, policies should be defined within each group of countries to account for the specific features of each of the four classes of SMEs.