TY - CHAP A1 - Barnat, Miriam A1 - Bosse, Elke A1 - Tight, Malcolm T1 - The Guiding Role of Theory in Mixed-Methods Research: Combining Individual and Institutional Perspectives on the Transition to Higher Education T2 - Theory and Method in Higher Education Research. Vol 3 N2 - The methodological discourse of mixed-methods research offers general procedures to combine quantitative and qualitative methods for investigating complex fields of research such as higher education. However, integrating different methods still poses considerable challenges. To move beyond general recommendations for mixed-methods research, this chapter proposes to discuss methodological issues with respect to a particular research domain. Taking current studies on the transition to higher education as an example, the authors first provide an overview of the potentials and limitations of quantitative and qualitative methods in the research domain. Second, they show the need for a conceptual framework grounded in the theory of the research object to guide the integration of different methods and findings. Finally, an example study that investigates transition with regard to the interplay of the individual student and the institutional context serves to illustrate the guiding role of theory. The framework integrates different theoretical perspectives on transition, informs the selection of the research methods, and defines the nexus of the two strands that constitute the mixed-methods design. As the interplay of individual and context is of concern for teaching and learning in general, the example presented may be fruitful for the wider field of higher education research. KW - Quantitative research KW - Mixed-Methods Research KW - Transition KW - Students KW - Higher education Y1 - 2017 SN - 978-1-78743-222-2 U6 - http://dx.doi.org/10.1108/S2056-375220170000003001 SP - 1 EP - 19 PB - Emerald Publishing Limited ER - TY - CHAP A1 - Steuer-Dankert, Linda A1 - Leicht-Scholten, Carmen T1 - Perceiving diversity : an explorative approach in a complex research organization. T2 - Diversity and discrimination in research organizations N2 - Diversity management is seen as a decisive factor for ensuring the development of socially responsible innovations (Beacham and Shambaugh, 2011; Sonntag, 2014; López, 2015; Uebernickel et al., 2015). However, many diversity management approaches fail due to a one-sided consideration of diversity (Thomas and Ely, 2019) and a lacking linkage between the prevailing organizational culture and the perception of diversity in the respective organization. Reflecting the importance of diverse perspectives, research institutions have a special responsibility to actively deal with diversity, as they are publicly funded institutions that drive socially relevant development and educate future generations of developers, leaders and decision-makers. Nevertheless, only a few studies have so far dealt with the influence of the special framework conditions of the science system on diversity management. Focusing on the interdependency of the organizational culture and diversity management especially in a university research environment, this chapter aims in a first step to provide a theoretical perspective on the framework conditions of a complex research organization in Germany in order to understand the system-specific factors influencing diversity management. In a second step, an exploratory cluster analysis is presented, investigating the perception of diversity and possible influencing factors moderating this perception in a scientific organization. Combining both steps, the results show specific mechanisms and structures of the university research environment that have an impact on diversity management and rigidify structural barriers preventing an increase of diversity. The quantitative study also points out that the management level takes on a special role model function in the scientific system and thus has an influence on the perception of diversity. Consequently, when developing diversity management approaches in research organizations, it is necessary to consider the top-down direction of action, the special nature of organizational structures in the university research environment as well as the special role of the professorial level as role model for the scientific staff. KW - Diversity management KW - Organizational culture KW - Change management KW - Psychological concepts KW - Perception Y1 - 2022 SN - 978-1-80117-959-1 (Print) SN - 978-1-80117-956-0 (Online) U6 - http://dx.doi.org/10.1108/978-1-80117-956-020221010 SP - 365 EP - 392 PB - Emerald Publishing Limited CY - Bingley ER - TY - CHAP A1 - Striebing, Clemens A1 - Müller, Jörg A1 - Schraudner, Martina A1 - Gewinner, Irina Valerie A1 - Guerrero Morales, Patricia A1 - Hochfeld, Katharina A1 - Hoffman, Shekinah A1 - Kmec, Julie A. A1 - Nguyen, Huu Minh A1 - Schneider, Jannick A1 - Sheridan, Jennifer A1 - Steuer-Dankert, Linda A1 - Trimble O'Connor, Lindsey A1 - Vandevelde-Rougale, Agnès T1 - Promoting diversity and combatting discrimination in research organizations: a practitioner’s guide T2 - Diversity and discrimination in research organizations N2 - The essay is addressed to practitioners in research management and from academic leadership. It describes which measures can contribute to creating an inclusive climate for research teams and preventing and effectively dealing with discrimination. The practical recommendations consider the policy and organizational levels, as well as the individual perspective of research managers. Following a series of basic recommendations, six lessons learned are formulated, derived from the contributions to the edited collection on “Diversity and Discrimination in Research Organizations.” KW - Inclusive work climate KW - lessons learned KW - policy recommendations KW - recommendations for actions KW - bullying Y1 - 2022 SN - 978-1-80117-959-1 (Print) SN - 978-1-80117-956-0 (Online) U6 - http://dx.doi.org/10.1108/978-1-80117-956-020221012 SP - 421 EP - 442 PB - Emerald Publishing Limited CY - Bingley ER - TY - JOUR A1 - Mueller, Tobias A1 - Segin, Alexander A1 - Weigand, Christoph A1 - Schmitt, Robert H. T1 - Feature selection for measurement models JF - International journal of quality & reliability management N2 - Purpose In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset. Design/methodology/approach In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments. Findings Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model. Originality/value For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future. KW - Feature selection KW - Modelling KW - Measurement models KW - Measurement uncertainty Y1 - 2022 U6 - http://dx.doi.org/10.1108/IJQRM-07-2021-0245 SN - 0265-671X IS - Vol. ahead-of-print, No. ahead-of-print. PB - Emerald Group Publishing Limited CY - Bingley ER -