Business model innovations emerge over time and are influenced by managerial interaction with stakeholders. Especially with regard to business model innovation for sustainability, manager-stakeholder interaction can radically change a company’s business model and underlying logic. However, the majority of the literature shows how manager–stakeholder interaction may limit business model innovation when stakeholders reinforce existing managerial cognitions. In this chapter we study how stakeholders can also stimulate business model innovation by affecting managerial cognitive change. Through three case studies, we find that this can occur through three shaping processes: market approach shaping, product/service offering shaping, and credibility shaping. We also find that the impact of new or latent stakeholders is greater than that of existing stakeholders. We end the chapter by sketching a research agenda to further unravel the role of stakeholders affecting managerial cognition around business model innovation for sustainability.
OBJECTIVE: The prevalence of multimorbidity has risen considerably because of the increase in longevity and the rapidly growing number of older individuals. Today, only little is known about the influence of multimorbidity on cognition in a normal healthy aging population. The primary aim of the present study was to investigate the effect of multimorbidity on cognition over a 12-year period in an adult population with a large age range. METHODS: Data were collected as part of the Maastricht Aging Study (MAAS), a prospective study into the determinants of cognitive aging. Eligible MAAS participants (N = 1763), 24-81 years older, were recruited from the Registration Network Family Practices (RNH) which enabled the use of medical records. The association between 96 chronic diseases, grouped into 23 disease clusters, and cognition on baseline, at 6 and 12 years of follow-up, were analyzed. Cognitive performance was measured in two main domains: verbal memory and psychomotor speed. A multilevel statistical analysis, a method that respects the hierarchical data structure, was used. RESULTS: Multiple disease clusters were associated with cognition during a 12-year follow-up period in a healthy adult population. The disease combination malignancies and movement disorders multimorbidity also appeared to significantly affect cognition. CONCLUSIONS: The current results indicate that a variety of medical conditions adversely affects cognition. However, these effects appear to be small in a normal healthy aging population.
Player behavior during game play can be used to construct player models that help adapt the game and make it more fun for the player involved. Similarly in-game behavior could help model personality traits that describe people's attitudes in a fashion that can be stable over time and over different domains, e.g., to support health coaching, or other behavior change approaches. This paper demonstrates the feasibility of this approach by relating Need for Cognition (NfC) a personality trait that can predict the effectiveness of different persuasion strategies upon users to a commonly used game mechanic - hints. An experiment with N=188 participants confirmed our hypothesis that NfC has a negative correlation with the number of hints players follow during the game. Future work should confirm if adherence to hints can be used as a predictor of behavior in different games, and to find other game mechanics than hints, that help predict user traits.
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
Onderzocht wordt in hoeverre embodied cognition activiteiten bij meetkundeonderwijs in de bovenbouw van de basisschool leerlingen aanzetten tot wiskundig denken (abstraheren) en op welke manier leerkrachten dit proces kunnen begeleiden. Looptijd 01 september 2019 - 31 augustus 2023
Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology which uses strong electric fields to manipulate liquid atomization. Among many other areas, electrospray is currently used as an important tool for biomedical applications (droplet encapsulation), water technology (thermal desalination and metal recovery) and material sciences (nanofibers and nano spheres fabrication, metal recovery, selective membranes and batteries). A complete review about the particularities of this technology and its applications was recently published in a special edition of the Journal of Aerosol Sciences [1]. Even though EHDA is already applied in many different industrial processes, there are not many controlling tools commercially available which can be used to remotely operate the system as well as identify some spray characteristics, e.g. droplet size, operational mode, droplet production ratio. The AECTion project proposes the development of an innovative controlling system based on the electrospray current, signal processing & control and artificial intelligence to build a non-visual tool to control and characterize EHDA processes.