The central goal of this study is to clarify to what degree former education and students' personal characteristics (the 'Big Five personality characteristics', personal orientations on learning and students' study approach) may predict study outcome (required credits and study continuance). Analysis of the data gathered through questionnaires of 1,471 Universities of Applied Sciences students make clear that former Education did not come forth as a powerful predictor for Credits or Study Continuance. Significant predictors are Conscientiousness and Ambivalence and Lack of Regulation. The higher the scores on Conscientiousness the more credits students are bound to obtain and the more likely they will continue their education. On the other hand students with high scores on Ambivalence and Lack of Regulation will most likely obtain fewer Credits or drop out more easily. The question arises what these results mean for the present knowledge economy which demands an increase of inhabitants with an advanced level of education. Finally, implications and recommendations for future research are suggested.
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Digitalization enables public organizations to personalize their services, tuning them to the specific situation, abilities, and preferences of the citizens. At the same time, digital services can be experienced as being less personal than face-to-face contact by citizens. The large existing volume of academic literature on personalization mainly represents the service provider perspective. In contrast, in this paper we investigate what makes citizens experience a service as personal. The result are eight dimensions that capture the full range of individual experiences and expectations that citizens expressed in focus groups. These dimensions can serve as a framework for public sector organizations to explore the expectations of citizens of their own services and identify the areas in which they can improve the personal experiences they offer.
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As people age, physiological changes affect their thermal perception, sensitivity and regulation. The ability to respond effectively to temperature fluctuations is compromised with physiological ageing, upsetting the homeostatic balance of health in some. As a result, older people can become vulnerable at extremes of thermal conditions in their environment. With population ageing worldwide, it is an imperative that there is a better understanding of older people’s thermal needs and preferences so that their comfort and wellbeing in their living environment can be optimised and healthy ageing achieved. However, the complex changes affecting the physiological layers of the individual during the ageing process, although largely inevitable, cannot be considered linear. They can happen in different stages, speeds and intensities throughout the ageing process, resulting in an older population with a great level of heterogeneity and risk. Therefore, predicting older people’s thermal requirements in an accurate way requires an in-depth investigation of their individual intrinsic differences. This paper discusses an exploratory study that collected data from 71 participants, aged 65 or above, from 57 households in South Australia, over a period of 9 months in 2019. The paper includes a preliminary evaluation of the effects of individual intrinsic characteristics such as sex, body composition, frailty and other factors, on thermal comfort. It is expected that understanding older people’s thermal comfort from the lens of these diversity-causing parameters could lead to the development of individualised thermal comfort models that fully capture the heterogeneity observed and respond directly to older people’s needs in an effective way. (article starts at page 13)
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In our increasingly global society, organizations face many opportunities in innovation, improved productivity and easy access to talent. At the same time, one of the greatest challenges, businesses experience nowadays, is the importance of social and/or human capital for their effectiveness and success (Backhaus and Tikoo, 2004; Mosley, 2007; Theurer et al., 2018; Tumasjan et al., 2020). High-quality employees are crucial to the competitive strength of an organization in the global economy, as these employees have a major influence on organizational reputation (Dowling at al., 2012). An important question is how, under these global circumstances, organizations and companies in the Netherlands can best be stimulated to attract and preserve social capital.Several studies have suggested the scarcity of talent and the crucial importance of gaining competitive advantage with recruitment communication to find the fit between personal and fundamental organizational characteristics and values for employees (Cable and Edwards, 2004; Bhatnagar and Srivastava, 2008; ManPower Group, 2014; European Communication Monitor (ECM), 2018). In order to become an employer of choice, organizations have to not only stand out from the crowd during the recruitment process but work on developing loyalty and a culture of trust in their relationship with employees (ECM, 2018). Employer Branding focuses on the process of promoting an organization, as the “employer of choice” to a desired target group, which an organization aims to attract and retain. This process encompasses building an identifiable and unique employer identity or, more specifically, “the promotion of a unique and attractive image” as an employer (Backhaus 2004, p. 117; Backhaus and Tikoo 2004, p. 502).One of the biggest challenges in the North of the Netherlands at the moment is the urgent need for qualified labor in the IT, energy and healthcare sectors and the excess supply of international graduates who are able to find a job in the North of the Netherlands (AWVN, 2019). Talent development, as part of the regional labor market and education policy, has been an important part of government programs and strategies in the region (VNO-NCW Noord, 2018). For instance, North Netherlands Alliance (SNN) signed a Northern Innovation Agenda for the 2014-2020 period. SNN encourages, facilitates and connects ambitions focused on the development of the Northern Netherlands. Also, the Social Economic council North Netherlands issued an advice on the labour market in the North Netherlands (SER Noord Nederland, 2017). Knowledge institutions also contribute through employability programs. Another example is the Regional Talent Agreement (Talent Akkoord) framework issued by the Groningen educational institutions, employers and employees’ organizations and regional authorities in which they jointly commit to recruiting, training, retaining and developing talent for the Northern labor market. Most of the hires with a maximum of five year of experience at companies are represented by millennials. To learn what values make an attractive brand for employees in the of the North of the Netherlands, we conducted a first study. When ranking the most important values of corporate culture which matter to young employees, they mention creative freedom, purposeful work, flexibility, work-life balance as well as personal development. Whereas attractive workplace and job security do not matter to such a degree. A positive work environment and a good relationship with colleagues are valued highly (Hein, 2019).To date, as far as we know, no other employer branding studies have been carried out for the North of the Netherlands. Further insight is needed into the role of employer branding as a powerful tool to retain talent in Northern industry in particular.The goal of this study is to provide a detailed analysis of the regional industry in the Northern Netherlands and contribute to: 1) the scientific body of knowledge about whether and how employer branding can strengthen the attractiveness of a regional industry in the labor market; 2) the application of this knowledge and insights by companies and governments in local policy development in the North of the Netherlands.
The focal point of the research will be to find an answer to the following research question:Is it possible to optimise the selection and tuning of the machine learning algorithm on the basis of the characteristics of a dataset, and in particular human datasets?
Lack of physical activity in urban contexts is an increasing health risk in The Netherlands and Brazil. Exercise applications (apps) are seen as potential ways of increasing physical activity. However, physical activity apps in app stores commonly lack a scientific base. Consequently, it remains unknown what specific content messages should contain and how messages can be personalized to the individual. Moreover, it is unknown how their effects depend on the physical urban environment in which people live and on personal characteristics and attitudes. The current project aims to get insight in how mobile personalized technology can motivate urban residents to become physically active. More specifically, we aim to gain insight into the effectiveness of elements within an exercise app (motivational feedback, goal setting, individualized messages, gaming elements (gamification) for making people more physically active, and how the effectiveness depends on characteristics of the individual and the urban setting. This results in a flexible exercise app for inactive citizens based on theories in data mining, machine learning, exercise psychology, behavioral change and gamification. The sensors on the mobile phone, together with sensors (beacons) in public spaces, combined with sociodemographic and land use information will generate a massive amount of data. The project involves analysis in two ways. First, a unique feature of our project is that we apply machine learning/data mining techniques to optimize the app specification for each individual in a dynamic and iterative research design (Sequential Multiple Assignment Randomised Trial (SMART)), by testing the effectiveness of specific messages given personal and urban characteristics. Second, the implementation of the app in Sao Paolo and Amsterdam will provide us with (big) data on use of functionalities, physical activity, motivation etc. allowing us to investigate in detail the effects of personalized technology on lifestyle in different geographical and cultural contexts.