Due to a rising interest in empirical ‘respect’ research but at the same time a somewhat fuzzy use of the term and its semantically close neighbors, we introduce a conceptual framework. The framework draws on existing philosophical traditions and empirical psychological works alike. It is pointed out that respect, acceptance, and tolerance are all attitudes of a subject towards an object which are not aligned on one dimension, but are concerned with quite different issues. Moreover, we propose that research needs to differentiate between two very different kinds of respect. Whereas appraisal respect, acceptance, and tolerance are attitudinal reflections of a subject’s decisions on certain issues (i.e., on influence, membership, and presence), recognition respect is proposed to be an overarching processing mode, i.e., a general attitude on how to confront others.

Systematically combining quantitative and qualitative research approaches offers the potential for a more comprehensive and nuanced understanding of social scientific phenomena. With their strong opportunities for building, qualifying, and testing social scientific theories, methodological integrations thus enable researchers to make substantive contributions that would not have been possible with one method alone. In this article we demonstrate how the integration of Qualitative Comparative Analysis (QCA) and conventional statistical analysis offers researchers new opportunities for contributing to the social sciences. Whereas statistical analysis is variable-oriented and relies on correlational analysis to make comparisons across cases, QCA is based on set theory, is case oriented, and relies on Boolean algebra to make comparisons between cases. Drawing on the literature on the interdependency between theoretical contribution and methodology, we review studies that integrate QCA and statistical analysis to explain how the specific combination of these two approaches allows researchers to strengthen the theoretical contribution of their research. From our review we identify common challenges and provide solutions for integrating QCA and statistical analysis.

Previous research indicated that leader moral identity (MI; i.e., leaders’ self-definition in terms of moral attributes) predicts to what extent followers perceive their leader as ethical (i.e., demonstrating and promoting ethical conduct in the organization). Leadership, however, is a relational process that involves leaders and followers. Building on this understanding, we hypothesized that follower and leader MI (a) interact in predicting whether followers will perceive their leaders as ethical and, as a result, (b) influence followers’ perceptions of leader–follower relationship quality. A dyadic field study (N = 101) shows that leader MI is a stronger predictor of followers’ perceptions of ethical leadership for followers who are high (vs. low) in MI. Perceptions of ethical leadership in turn predict how the quality of the relationship will be perceived. Hence, whether leader MI translates to perceptions of ethical leadership and of better relationship quality depends on the MI of followers.

The forecasting of road freight traffic has relied heavily on the close correlation between GDP and road tonne-kilometers. It has not been rooted in an understanding of the causes of freight traffic growth. The research reported in this paper has investigated this process of traffic growth in two ways: first, by analysing official data on the production, consumption and movement of food and drink products, and second, by conducting a survey of the changing freight transport requirements of 88 large British-based manufacturers.
The analysis of secondary data shows how, in the food and drink sector, the relationship between the real value of output and road vehicle-kms hinges on four key parameters: value density, handling factor, average length of haul and consignment size. An attempt is made to explain variations in these parameters.
The survey of manufacturers suggests that the growth of lorry traffic is the net result of a complex interaction between factors operating at four levels of logistical management: strategic planning of logistical systems, choice of suppliers and distributors, scheduling of product flow and the management of transport resources. Changes in the frequency and scheduling of freight deliveries in response to tightening customer service requirements and just-in-time management appear to have become a more prevalent cause of freight traffic growth than the physical restructuring of logistical systems. Manufacturers anticipate that their road freight demand will broadly increase in line with sales and be largely unaffected by road transport cost increases at the levels currently proposed. The paper concludes by examining their likely reactions to a much sharper increase in the cost of road freight movement.