This booklet Critical issues in sustainability Part II represents a continuation of the work we have embarked on some years ago. It contains a selection of opinion pieces that we have written over the past year and which were published in national and regional newspapers. These opinion pieces allow us to share our thinking and ideas with the broader public and support the exchange of them through discussion and debate, while they support debates through media that we think are critical to realizing the goals of exposing, debunking, and eliciting
Inleiding:De online leefwereld speelt in toenemende mate een centrale rol in het leven en de ontwikkeling van jongeren. De online leefwereld biedt jongeren veel mogelijkheden om bijvoorbeeld hun talenten te ontdekken en te ontwikkelen, andere jongeren te ontmoeten en vriendschappen op te bouwen, te experimenteren met verschillende aspecten van hun identiteit, nieuwe vaardigheden aan te leren en ondersteuning voor hun vragen en problemen makkelijker te zoeken en te vinden. Niet alle jongeren profiteren van deze mogelijkheden. Sommige jongeren ervaren ook de negatieve kanten van de online leefwereld (zoals cyberpesten, grooming, exposing, uitsluiting, etc.), zijn betrokken bij online fraude en cybercrime, hebben moeite bij bepaalde stappen in hun ontwikkeling en vertonen risicogedrag in de online leefwereld. Vooral deze jongeren hebben ondersteuning nodig in de online leefwereld. Maar wie moet dat doen en hoe kun je precies jongeren in deze omgeving ondersteunen? Terwijl scholen en ouders vaak achter de feiten aan hollen en nauwelijks toegang hebben tot de online leefwereld van jongeren, werken jongerenwerkers al een aantal jaar intensiever in die leefwereld.
Social networks and news outlets use recommender systems to distribute information and suggest news to their users. These algorithms are an attractive solution to deal with the massive amount of content on the web [6]. However, some organisations prioritise retention and maximisation of the number of access, which can be incompatible with values like the diversity of content and transparency. In recent years critics have warned of the dangers of algorithmic curation. The term filter bubbles, coined by the internet activist Eli Pariser [1], describes the outcome of pre-selected personalisation, where users are trapped in a bubble of similar contents. Pariser warns that it is not the user but the algorithm that curates and selects interesting topics to watch or read. Still, there is disagreement about the consequences for individuals and society. Research on the existence of filter bubbles is inconclusive. Fletcher in [5], claims that the term filter bubbles is an oversimplification of a much more complex system involving cognitive processes and social and technological interactions. And most of the empirical studies indicate that algorithmic recommendations have not locked large segments of the audience into bubbles [3] [6]. We built an agent-based simulation tool to study the dynamic and complex interplay between individual choices and social and technological interaction. The model includes different recommendation algorithms and a range of cognitive filters that can simulate different social network dynamics. The cognitive filters are based on the triple-filter bubble model [2]. The tool can be used to understand under which circumstances algorithmic filtering and social network dynamics affect users' innate opinions and which interventions on recommender systems can mitigate adverse side effects like the presence of filter bubbles. The resulting tool is an open-source interactive web interface, allowing the simulation with different parameters such as users' characteristics, social networks and recommender system settings (see Fig. 1). The ABM model, implemented in Python Mesa [4], allows users to visualise, compare and analyse the consequence of combining various factors. Experiment results are similar to the ones published in the Triple Filter Bubble paper [2]. The novelty is the option to use a real collaborative-filter recommendation system and a new metric to measure the distance between users' innate and final opinions. We observed that slight modifications in the recommendation system, exposing items within the boundaries of users' latitude of acceptance, could increase content diversity.References 1. Pariser, E.: The filter bubble: What the internet is hiding from you. Penguin, New York, NY (2011) 2. Geschke, D., Lorenz, J., Holtz, P.: The triple-filter bubble: Using agent-based modelling to test a meta-theoretical framework for the emergence of filter bubbles and echo chambers. British Journal of Social Psychology (2019), 58, 129–149 3. Möller, J., Trilling, D., Helberger, N. , and van Es, B.: Do Not Blame It on the Algorithm: An Empirical Assessment of Multiple Recommender Systems and Their Impact on Content Diversity. Information, Communication and Society 21, no. 7 (2018): 959–77 4. Mesa: Agent-based modeling in Python, https://mesa.readthedocs.io/. Last accessed 2 Sep 2022 5. Fletcher, R.: The truth behind filter bubbles: Bursting some myths. Digital News Report - Reuters Institute (2020). https://reutersinstitute.politics.ox.ac.uk/news/truth-behind-filter-bubblesbursting-some-myths. Last accessed 2 Sep 2022 6. Haim, M., Graefe, A, Brosius, H: Burst of the Filter Bubble?: Effects of Personalization on the Diversity of Google News. Digital Journalism 6, no. 3 (2018): 330–43.
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Despite Dutch Hospitality industry’s significant economic value, employers struggle to attract and retain early career professionals at a time when tourism is forecasted to grow exponentially (Ruël, 2018). Universally, hospitality management graduates are shunning hospitality careers preferring other career paths; stimulating the Dutch Hospitality to find innovative ways of attracting and retaining early career professionals. Following calls from the Human Resource Management (HRM) community (Ehnert, 2009), we attribute this trend to personnel being depicted as rentable resources, driving profit’’ often at personal expense. For example, hotels primarily employ immigrants and students for a minimum wage suppressing salaries of local talent (Kusluvan, et al 2010, O’Relly and Pfeffer, 2010). Similarly, flattening organizational structures have eliminated management positions, placing responsibility on inexperienced shoulders, with vacancies commonly filled by pressured employees accepting unpaid overtime jeopardizing their work life balance (Davidson, et al 2010,). These HRM practices fuel attrition by exposing early career professionals to burnout (Baum et al, 2016, Goh et al, 2015, Deery and Jog, 2009). Collectively this has eroded the industry’s employer brand, now characterized by unsocial working hours, poor compensation, limited career opportunities, low professional standing, high turnover and substance abuse (Mooney et al, 2016, Gehrels and de Looij, 2011). In contrast, Sustainable HRM “enables an organizational goal achievement while simultaneously reproducing the human resource base over a long-lasting calendar time (Ehnert, 2009, p. 74).” Hence, to overcome this barrier we suggest embracing the ROC framework (Prins et al, 2014), which (R)espects internal stakeholders, embraces an (O)pen HRM approach while ensuring (C)ontinuity of economic and societal sustainability which could overcome this barrier. Accordingly, we will employ field research, narrative discourse, survey analysis and quarterly workshops with industry partners, employees, union representatives, hotel school students to develop sustainable HRM practices attracting and retaining career professionals to pursue Dutch hospitality careers.
