Psychologists, psycholinguists, and other researchers using language stimuli have been struggling for more than 30 years with the problem of how to analyze experimental data that contain two crossed random effects (items and participants). The classical analysis of variance does not apply; alternatives have been proposed but have failed to catch on, and a statistically unsatisfactory procedure of using two approximations (known as F 1 and F 2) has become the standard. A simple and elegant solution using mixed model analysis has been available for 15 years, and recent improvements in statistical software have made mixed models analysis widely available. The aim of this article is to increase the use of mixed models by giving a concise practical introduction and by giving clear directions for undertaking the analysis in the most popular statistical packages. The article also introduces the djmixed add-on package for SPSS, which makes entering the models and reporting their results as straightforward as possible.
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Financially vulnerable consumers are often associated with suboptimal financial behaviors. Evaluated financial education programs so far show difficulties to effectively reach this target population. In our attempt to solve this problem, we built a behaviorally informed financial education program incorporating insights from both motivational and behavioral change theories. In a quasi-experimental field study among Dutch financially vulnerable people, we compared this program with both a control group and a traditional program group. In comparison with the control group, we found robust positive effects of the behaviorally informed program on financial skills and knowledge and self-reported financial behavior, but not on other outcomes. Additionally, we did not find evidence that the behaviorally informed program performed better than the traditional program. Finally, we discuss the findings and limitations of this study in light of the financial education literature and provide implications for policymaking and directions for future research.
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Lean Production (LP) can be regarded as a design approach in search of a theoretical foundation. In this paper we show that Lowlands’ Sociotechnical Design Theory (STSL) could function as such a foundation. To reach this goal, we first describe STSL as a system theoretical reformulation of Original Sociotechnical Theory (OSTS). Then, we introduce the Toyota Production System as the origin of LP and the challenge it poses for the academic field of organization design. This academic field should (1) assess LP’s success, (2) generalize it by embedding it in more abstract concepts and theories in order to be able to (3) re-specify it for different manufacturing and non-manufacturing contexts. Next, we give an exposition of STSL as a structural design approach based on developments in system theory. At last, we reformulate lean production in STSL terms and so show that LP is a subcase within the more general theory of STSL. We discuss the merits of both approaches and clarify some misunderstandings of lean both outside and inside the lean community. Embedding LP in the more general language of STSL should enable us to discover similarities and differences, to start a process of mutual learning, to integrate diverse design approaches in a theory of organizational design and to add content to redesign proposals of for example the health care system as proposed by Porter and Teisberg (2006) and Christensen et al. (2009). We quote extensively from the lean literature (to convince our sociotechnical friends) and embed both STSL and LP in the broader literature on organization design. We hope this adds a new perspective to the one given in the Operations Management literature on LP. Again, mutual learning is the goal.
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