De meest gebruikte opbouw in business intelligence, predictive analitics en analytics modellen is de moeilijkheidsgraad: 1) descriptive, 2) diagnostic, 3) predictive en 4) prescriptive. Deze schaal vertelt iets over de volwassenheid van het gebruik van data door de organisatie. Een model dat niet op zichzelf staat en een achterliggende methode kent is de data driehoek van EDM (Figuur 1), welke in dit artikel zal worden toegelicht.
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In the course of our supervisory work over the years, we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called frequently asked questions (FAQs). This series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By ‘novice’ we mean Master’s students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of qualitative research papers. The second article focused on context, research questions and designs, and referred to publications for further reading. This third article addresses FAQs about sampling, data collection and analysis. The data collection plan needs to be broadly defined and open at first, and become flexible during data collection. Sampling strategies should be chosen in such a way that they yield rich information and are consistent with the methodological approach used. Data saturation determines sample size and will be different for each study. The most commonly used data collection methods are participant observation, face-to-face in-depth interviews and focus group discussions. Analyses in ethnographic, phenomenological, grounded theory, and content analysis studies yield different narrative findings: a detailed description of a culture, the essence of the lived experience, a theory, and a descriptive summary, respectively. The fourth and final article will focus on trustworthiness and publishing qualitative research.
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Generation Z (Gen Z) will account for a growing proportion of the global workforce in the coming years. Therefore, it is vitally important to understand this generation’s unique perspectives and preferences regarding work. This exploratory study examines the prioritisation and desirability of Gen Z work values according to respondents’ nationality. Data for this study was collected through a survey among 1188 undergraduate students enrolled in one university each in China, Germany, the Netherlands and Thailand. ANOVA test and Tukey post-hoc analysis were used to find out the difference between the groups based on nationality. Findings indicate nationality serves as a key differentiator in work value preferences. The findings challenge the concept of a global Generation Z as only two of the measured values, learning and visible results, were found to have universal appeal across the nationality groups. Despite increased levels of global interconnectedness and accompanying crossvergence of values, the results show significant statistical differences in work values based on the respondents’ nationality. Due to the scope and explorative design of the present study, it cannot be certain that the findings are exclusively from Gen Z characteristics or influenced by other, non-cultural, variables. This study suggests there is a need for study programmes at a tertiary level to embed experiential learning components and individual study pathways in their curricula to enable students to develop realistic expectations about the workplace and their place in it. In turn, these programmes will be able to develop a competitive advantage in HE landscape. The insights gained can be leveraged by internationally oriented study programmes, such as International Business (IB), to better address Gen Z needs and expectations.
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