Despite increased interest in experience and experience design in hospitality, tourism, and leisure, the field remains emergent. For experience design to mature in research and practice, clear consensus conceptualization of key constructs, like memorable, meaningful, and transformative experiences, is needed. While existing research identifies emotions as the key to memorable experiences, more conceptual work is needed to understand the unique impact and process behind meaningful experiences. This paper proposes an expanded conceptualization of the impact and process associated with meaningful experiences. We suggest that as individuals reflect on existing experiential (i.e., autobiographical) memories, they can extract insight from those memories. If any of the extracted insights connect with core sources of meaning, then the individuals perceive their experience as meaningful. Suggestions for potential strategies to design for meaningful experiences are also shared.
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Within large service organizations there are currently two trends visible. These trends seem to be diametrically opposed. On the one hand organizations face increasing price pressure and thus a pressure to cut costs. One of the consequences of this trend is that organizations are increasingly encouraging customers to make more use of digital communication channels. At the same time, companies find it important to know their customers in order to respond adequately to their needs. To do this, organizations must have a certain degree of personal involvement to their customers and they must have regular personal contact. It is assumed that both trends – digitisation and personalisation – will have a strong impact on customer experience and (perhaps) on the relational models customers use. If it is true that relational models - so the way in which people perceive and assess a relationship - play a role in the perception of the customer, it is also interesting to know if it is possible to influence these relational models. During the last fifty years much research has been done into the possibilities to influence customers by using subliminal priming techniques. In these techniques thoughts and feelings are unconsciously activated by showing people certain words or images (eg Bargh, Chen & Burrows, 1996; Dijksterhuis, 2005). In recent years a number of experiments were performed in which customers were unconsciously primed at some type of relationship (eg Aggarwal, 2004; McGraw & Tetlock, 2005; Tuk, Verlegh, Smidts & Wigboldus, 2009). These experiments showed that it is possible to activate a certain type of relationship. The experiments however the researchers used scenario’s based on an interpersonal relationship, and often to a fictitious relationship. The question is whether priming techniques also work for an already existing and more complex relationship between an organization and its customers. From 2010-2013 we conducted research for six large service providers in banking, insurance, utilities and social welfare to discover what the customer experience of these organisations, what role relational models played in customer experience and whether it was possible to influence these relational models. The research project has provided answers to the following questions: - Which relational models are used by customers and what is the influence of these models on customer experience? - What is the influence of digitisation in customer communication on relational models and customer experience? - What is the influence of personalisation in customer communication on relational models and customer experience? And finally, - Is it possible to influence relational models (and customer experience) by using specific words and images that are associated with relational models (relational framing)?
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This article describes the relation between mental health and academic performance during the start of college and how AI-enhanced chatbot interventions could prevent both study problems and mental health problems.
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The SPRONG-collaboration “Collective process development for an innovative chemical industry” (CONNECT) aims to accelerate the chemical industry’s climate/sustainability transition by process development of innovative chemical processes. The CONNECT SPRONG-group integrates the expertise of the research groups “Material Sciences” (Zuyd Hogeschool), “Making Industry Sustainable” (Hogeschool Rotterdam), “Innovative Testing in Life Sciences & Chemistry” and “Circular Water” (both Hogeschool Utrecht) and affiliated knowledge centres (Centres of Expertise CHILL [affiliated to Zuyd] and HRTech, and Utrecht Science Park InnovationLab). The combined CONNECT-expertise generates critical mass to facilitate process development of necessary energy-/material-efficient processes for the 2050 goals of the Knowledge and Innovation Agenda (KIA) Climate and Energy (mission C) using Chemical Key Technologies. CONNECT focuses on process development/chemical engineering. We will collaborate with SPRONG-groups centred on chemistry and other non-SPRONG initiatives. The CONNECT-consortium will generate a Learning Community of the core group (universities of applied science and knowledge centres), companies (high-tech equipment, engineering and chemical end-users), secondary vocational training, universities, sustainability institutes and regional network organizations that will facilitate research, demand articulation and professionalization of students and professionals. In the CONNECT-trajectory, four field labs will be integrated and strengthened with necessary coordination, organisation, expertise and equipment to facilitate chemical innovations to bridge the innovation valley-of-death between feasibility studies and high technology-readiness-level pilot plant infrastructure. The CONNECT-field labs will combine experimental and theoretical approaches to generate high-quality data that can be used for modelling and predict the impact of flow chemical technologies. The CONNECT-trajectory will optimize research quality systems (e.g. PDCA, data management, impact). At the end of the CONNECT-trajectory, the SPRONG-group will have become the process development/chemical engineering SPRONG-group in the Netherlands. We can then meaningfully contribute to further integrate the (inter)national research ecosystem to valorise innovative chemical processes for the KIA Climate and Energy.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
The IMPULS-2020 project DIGIREAL (BUas, 2021) aims to significantly strengthen BUAS’ Research and Development (R&D) on Digital Realities for the benefit of innovation in our sectoral industries. The project will furthermore help BUas to position itself in the emerging innovation ecosystems on Human Interaction, AI and Interactive Technologies. The pandemic has had a tremendous negative impact on BUas industrial sectors of research: Tourism, Leisure and Events, Hospitality and Facility, Built Environment and Logistics. Our partner industries are in great need of innovative responses to the crises. Data, AI combined with Interactive and Immersive Technologies (Games, VR/AR) can provide a partial solution, in line with the key-enabling technologies of the Smart Industry agenda. DIGIREAL builds upon our well-established expertise and capacity in entertainment and serious games and digital media (VR/AR). It furthermore strengthens our initial plans to venture into Data and Applied AI. Digital Realities offer great opportunities for sectoral industry research and innovation, such as experience measurement in Leisure and Hospitality, data-driven decision-making for (sustainable) tourism, geo-data simulations for Logistics and Digital Twins for Spatial Planning. Although BUas already has successful R&D projects in these areas, the synergy can and should significantly be improved. We propose a coherent one-year Impuls funded package to develop (in 2021): 1. A multi-year R&D program on Digital Realities, that leads to, 2. Strategic R&D proposals, in particular a SPRONG/sleuteltechnologie proposal; 3. Partnerships in the regional and national innovation ecosystem, in particular Mind Labs and Data Development Lab (DDL); 4. A shared Digital Realities Lab infrastructure, in particular hardware/software/peopleware for Augmented and Mixed Reality; 5. Leadership, support and operational capacity to achieve and support the above. The proposal presents a work program and management structure, with external partners in an advisory role.
