Letizia Lorusso, Miran Mosmondor, Andrej Grguric, Lara Toccafondi, Grazia D'Onofrio, Sergio Russo, Jure Lampe, Tarmo Pihl, Nicolas Mayer, Gianna Vignani, Isabelle Lesterpt, Lucie Vaamonde, Francesco Giuliani, Manuele Bonaccorsi, Carlo La Viola, Erika Rovini, Filippo Cavallo, Laura Fiorini
Design and Evaluation of Personalized Services to Foster Active Aging: The Experience of Technology Pre-Validation in Italian Pilots
Sensors (Basel, Switzerland)
development potential chinas medical insurance market huge research medical insurance demand always focus academic discussions result discipline behavioral economics derived aims explain decisionmaking behavior individual insurance consumption among focus study investigate influence individual psychological characteristics cognitive level insurance behavior difference reference points paper combined behavioral insurance actuarial mathematics econometrics knowledge system comprehensive theoretical analysis empirical tests analyzed impact mechanism individual frame effect medical insurance demand different reference points multiple levels time based risk selfassessment outdoor sports artificial intelligence insurance psychology analyzed based correlation vector machine algorithm theoretical basis combined dual perspective insurance products expected utility model established guarantee framework prospect theoretical model established profit loss framework framing effect used measure relative size guarantee utility profit loss utility highinsurancerate model lowinsurancerate model established theoretical model analysis found high insurance rate profit loss utility positive size individual frame effect positively correlated willingness insure low insurance rate profit loss utility negative size individual frame effect negatively correlated willingness insure research results paper show insurance important beginning insurance consumption behavior includes complex mentality emotion consumers insurance activities insurance demand policyholders formed joint action external internal incentives many factors income level education level play important role insurance consumption decision making