Under what conditions is end-user training (EUT) as part of the implementation of a business process management (BPM) system successful? This question is addressed in this paper. Based on the literature on EUT and implementation success, we first argue that user involvement with, and attitude towards, a BPM system, both have a conditional effect on the relationship between EUT and the implementation success of the system. Secondly, we investigated this expectation empirically, by measuring the practice of EUT as perceived by end-users. Using a mixed method approach, survey data was collected from 143 end-users of a BPM system in a large Dutch social insurance organisation, and by 49 additional semi-structured interviews. Regression analysis of the survey data shows that attitude variables indeed have a significant moderating influence on implementation success. In addition, the interviews revealed that specific attention must be paid to the arrangements for EUT when deploying BPM systems in this type of organisations. Arguments are given for a more comprehensive way of measuring and optimising EUT during the implementation of information systems/information technology in organisations.
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This article delves into the acceptance of autonomous driving within society and its implications for the automotive insurance sector. The research encompasses two different studies conducted with meticulous analysis. The first study involves over 600 participants involved with the automotive industry who have not yet had the opportunity to experience autonomous driving technology. It primarily centers on the adaptation of insurance products to align with the imminent implementation of this technology. The second study is directed at individuals who have had the opportunity to test an autonomous driving platform first-hand. Specifically, it examines users’ experiences after conducting test drives on public roads using an autonomous research platform jointly developed by MAPFRE, Universidad Carlos III de Madrid, and Universidad Politécnica de Madrid. The study conducted demonstrates that the user acceptance of autonomous driving technology significantly increases after firsthand experience with a real autonomous car. This finding underscores the importance of bringing autonomous driving technology closer to end-users in order to improve societal perception. Furthermore, the results provide valuable insights for industry stakeholders seeking to navigate the market as autonomous driving technology slowly becomes an integral part of commercial vehicles. The findings reveal that a substantial majority (96% of the surveyed individuals) believe that autonomous vehicles will still require insurance. Additionally, 90% of respondents express the opinion that policies for autonomous vehicles should be as affordable or even cheaper than those for traditional vehicles. This suggests that people may not be fully aware of the significant costs associated with the systems enabling autonomous driving when considering their insurance needs, which puts the spotlight back on the importance of bringing this technology closer to the general public.
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Accurate modeling of end-users’ decision-making behavior is crucial for validating demand response (DR) policies. However, existing models usually represent the decision-making behavior as an optimization problem, neglecting the impact of human psychology on decisions. In this paper, we propose a Belief-Desire-Intention (BDI) agent model to model end-users’ decision-making under DR. This model has the ability to perceive environmental information, generate different power scheduling plans, and make decisions that align with its own interests. The key modeling capabilities of the proposed model have been validated in a household end-user with flexible loads
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