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The paper aims to raise awareness in the industry of design automation tools, especially in early design phases, by demonstrating along a case study the seamless integration of a prototypically implemented optimization, supporting design space exploration in the early design phase and an in operational use product configurator, supporting the drafting and detailing of the solution predominantly in the later design phase.

Based on the comparison of modeled as-is and to-be processes of ascent assembly designs with and without design automation tools, an automation roadmap is developed. Using qualitative and quantitative assessments, the potentials and benefits, as well as acceptance and usage aspects, are evaluated.

Engineers tend to consider design automation for routine tasks. Yet, prototypical implementations support the communication and identification of the potential for the early stages of the design process to explore solution spaces. In this context, choosing from and interactively working with automatically generated alternative solutions emerged as a particular focus. Translators, enabling automatic downstream propagation of changes and thus ensuring consistency as to change management were also evaluated to be of major value.

A systematic validation of design automation in design practice is presented. For generalization, more case studies are needed. Further, the derivation of appropriate metrics needs to be investigated to normalize validation of design automation in future research.

Integration of design automation in early design phases has great potential for reducing costs in the market launch. Prototypical implementations are an important ingredient for potential evaluation of actual usage and acceptance before implementing a live system.

There is a lack of systematic validation of design automation tools supporting early design phases. In this context, this work contributes a systematically validated industrial case study. Early design-phases-support technology transfer is important because of high leverage potential.

We propose that group affective tone may be dysfunctional for teams faced with complex, equivocal, and dynamically changing tasks and environments. Group affective tone (and in particular, a positive affective tone) may exacerbate pre-existing tendencies of teams to develop a single-shared reality that team members confidently believe to be valid and to be prone to group-centrism. Alternatively, heterogeneity in member mood states within teams may lead to the development of multiple-shared realities that reflect the equivocality of the teams’ tasks and circumstances and other functional outcomes (e.g., multiple perspectives and minority dissent), which ultimately may enhance team effectiveness.

In this chapter, we theorize that metaperceptions (beliefs about how one is viewed by others) derived from social identity categories will influence intrapersonal processing and resultant member interaction patterns in diverse work groups. In turn, such patterns of interactions will affect the quality of emergent states within diverse groups, ultimately impacting group-level outcomes. We will extend previous work in this area by examining the formation, nature, and consequences of metaperceptions in workgroups within which individuals vary with regard to social identities. In addition, we will describe the implications of metaperceptions for the effective leadership of diverse groups.

This paper seeks to be a thought experiment. If the field of futures were invented today, it asks, what would it look like? What would be its intellectual foundations? Who would it serve and influence? And how would its ideas and insights be put into practice?

It reviews the literatures on experimental psychology and neuroscience to identify biases that affect people's ability to think about and act upon the future, studies of expertise that map the limits of professional judgment, and recent work on the nature of critical challenges of the twenty‐first century.

It argues that futurists could develop social software tools, prediction markets, and other technologies to improve the individual and collective accuracy and impact of work. Choice architectures and nudges to lengthen “the shadow of the future” of everyday choices made by ordinary people could also be used.

The paper argues for new directions in the practice of futures, to make the field better‐suited to deal with the challenges confronting an increasingly complex, chaotic, and contingent world.

The development of tools to augment professional activity, and adoption of choice architectures and nudges as media for communicating about the future, could improve futures work and its impact, but lay the foundation for other methodological innovations.

The paper contributes to the ongoing discussion about where futures should go.

This paper aims to address the coating and compound analysis of diamond-like carbon (DLC) on steel, to understand the frictional behavior in tribological gear systems presented in paper Part I. Here, the Ti and Zr modified DLC coating architectures are analyzed regarding their chemical, mechanical and thermophysical properties. The results represent a systematic analysis of the thermal insulating effect in tribological contact of DLC coated gears.

The approach was to evaluate the effect of the substitution of Zr through Ti at the reference coating ZrCg to TiCg and the effect on thermophysical properties. Furthermore, the influence of different carbon and hydrogen contents on the coating and compound properties was analyzed. Therefore, different discrete Ti or Zr containing DLC coatings were deposited on an industrial coating machine. Thereby the understanding of the microstructure and chemical composition of the reference coatings is increased.

Results prove comparable mechanical properties of metal modified DLC independent of differences in chemical compositions. Moreover, the compound adhesion between TiC_g/16MnCr5E was improved compared to ZrC_g/16MnCr5E. The effect of hydrogen content Ψ and carbon content x_c on the thermophysical properties is limited by Ψ = 18 at.% and x_c = 90 at.%.

The findings of the combined papers Part I and II show a high potential for industrial application of DLC on gears. Based on the results DLC coatings and gears can be tailored to each other.

Systematic analysis of DLC coatings were conducted to evaluate the effect of titanium, carbon and hydrogen on thermophysical properties.

Investors frequently make judgments and decisions in the presence of affect (i.e., mood or emotion). Investors' moods may influence the extent to which they incorporate available financial information in their investment judgments. I propose that investors interpret their moods as signals of the extent to which financial information should be processed to make investment judgments, but only when other, more direct signals regarding the need for in-depth processing are unavailable. Consistent with research in psychology, my experimental results suggest that investors experiencing positive mood exert less effort to process available financial information than investors experiencing negative mood. Consequently, positive mood results in lower-quality financial judgments in my setting. However, when investors receive cues suggesting that initially received information is subjective, the effect of mood on effort to process financial information is mitigated. Overall, my results suggest that factors associated with positive investor mood (e.g., positive market sentiment) reduce the depth of investor analysis and lower judgment quality absent signals regarding the subjectivity of financial information.

Design thinking (DT) is still a relatively new methodology in the context of entrepreneurial education, which presents itself as an important tool for the development of entrepreneurial skills when inserted into the educational system. This research aimed to analyze studies about DT related to the entrepreneurial mindset in international journals over a period of ten years (2009–2019). Entrepreneurial education has been a constant in academic debates as well as practices and methodologies to apply this education, and such context has moved educational institutions to adopt practices and initiatives focused on the theme.

The tool used in the present study was the bibliometric database of the Web of Science through the words “Design Thinking” (DT) and “Entrepreneurial Education”. The research is characterized as descriptive and quantitative, and 146 publications were investigated in the period from 2009 to 2019, in the respective database.

The study also highlighted the new generation of young students forcing a change in education with an approach centered on the individual. Speech does not prevail in the teachers but in the students, and the teacher educator starts to collaborate for this new educational demand with didactics relevant to the world in this way preparing these young people and delivering society to critical, proactive and participatory individuals.

In the course of the study, we observed practices and examples of schools and universities that have adapted ways to allow new interactions in the school environment by promoting and encouraging innovative education.

Standard estimation of ARMA models in which the AR and MA roots nearly cancel, so that individual coefficients are only weakly identified, often produces inferential ranges for individual coefficients that give a spurious appearance of accuracy. We remedy this problem with a model that uses a simple mixture prior. The posterior mixing probability is derived using Bayesian methods, but we show that the method works well in both Bayesian and frequentist setups. In particular, we show that our mixture procedure weights standard results heavily when given data from a well-identified ARMA model (which does not exhibit near root cancellation) and weights heavily an uninformative inferential region when given data from a weakly-identified ARMA model (with near root cancellation). When our procedure is applied to a well-identified process the investigator gets the “usual results,” so there is no important statistical cost to using our procedure. On the other hand, when our procedure is applied to a weakly identified process, the investigator learns that the data tell us little about the parameters – and is thus protected against making spurious inferences. We recommend that mixture models be computed routinely when inference about ARMA coefficients is of interest.

In this chapter, we seek to resolve the long-running controversy as to whether moods foster or inhibit creativity. We base our arguments on a new theory, which we refer to as “creativity-as-mood-regulation,” where employees experiencing moods are envisaged to engage in creative behavior in the hope of regulating their moods. We further suggest that employees with different goal orientations will have different likelihoods of choosing creative activities to regulate their moods. Finally, we identify the specific goal-orientation conditions under which positive and negative moods may facilitate or depress creativity, and develop and discuss six related propositions.