Numerical Representations of Acceptance

Accepting a proposition means that our confidence in this proposition is strictly greater than the confidence in its negation. This paper investigates the subclass of uncertainty measures, expressing confidence, that capture the idea of acceptance, what we call acceptance functions. Due to the monotonicity property of confidence measures, the acceptance of a proposition entails the acceptance of any of its logical consequences. In agreement with the idea that a belief set (in the sense of Gardenfors) must be closed under logical consequence, it is also required that the separate acceptance o two propositions entail the acceptance of their conjunction. Necessity (and possibility) measures agree with this view of acceptance while probability and belief functions generally do not. General properties of acceptance functions are estabilished. The motivation behind this work is the investigation of a setting for belief revision more general than the one proposed by Alchourron, Gardenfors and Makinson, in connection with the notion of conditioning.Comment: Appears in Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence (UAI1995

Acceptance practice

Acceptances

Deductive Cogency, understanding, and acceptance

Deductive Cogency holds that the set of propositions towards which one has, or is prepared to have, a given type of propositional attitude should be consistent and closed under logical consequence. While there are many propositional attitudes that are not subject to this requirement, e.g. hoping and imagining, it is at least prima facie plausible that Deductive Cogency applies to the doxastic attitude involved in propositional knowledge, viz. belief. However, this thought is undermined by the well-known preface paradox, leading a number of philosophers to conclude that Deductive Cogency has at best a very limited role to play in our epistemic lives. I argue here that Deductive Cogency is still an important epistemic requirement, albeit not as a requirement on belief. Instead, building on a distinction between belief and acceptance introduced by Jonathan Cohen and recent developments in the epistemology of understanding, I propose that Deductive Cogency applies to the attitude of treating propositions as given in the context of attempting to understand a given phenomenon. I then argue that this simultaneously accounts for the plausibility of the considerations in favor of Deductive Cogency and avoids the problematic consequences of the preface paradox

The influence of technology, environment and user acceptance on the effectiveness of information system project selection using SEM

The selection of the present information system project is difficult because of the many factors that influence it. Information system project should pay attention to the user acceptance, technology and the environment in terms of their influence on the information system project selection.The purpose of this paper is to determine how much influence user acceptance, technology and the environment have on the information system project selection.This research uses data obtained from several ministries and analyzed using SEM (Structural Equation Models).The results found that the technology and the environment affects user acceptance. Moreover, technology and environment affect the effectiveness of the information systems project selection through the mediating effect of user acceptance. User acceptance, tested by the incorporation of usefulness and ease of use, the results are more modest and in line with previous theories. Furthermore, the external environment highly impacts the information system project selection

Towards the integration of culture into the Unified Theory of Acceptance and Use of Technology

Educational technology is increasingly used in multicultural contexts and across national cultures. Educational technology users with different national and professional backgrounds may, however, exhibit different attitudes towards technology. Previous research provides isolated evidence of the relationship between learning technology acceptance and culture, and so an overall picture is missing. Therefore, this study attempts to integrate culture (sensu Hofstede, 2001) into an established technology acceptance model (ie. the Unified Theory of Acceptance and Use of Technology, UTAUT, Venkatesh, Morris, Davis & Davis, 2003). Examining a large sample (N = 2866) of learning technology users from Germany and Romania by means of questionnaire survey, we investigate the differences in culture and technology acceptance between sample subgroups. The collected data reveal the presence of cultural differences both between countries and between professions. In line with previous research, these differences are associated with dissimilar acceptance profiles, ie. different values of acceptance variables and of path coefficients between them. Based on the findings, this study makes headway in cross-cultural research by proposing an extended model of UTAUT – one which integrates three of Hofstede’s culture dimensions. As a practical implication, national and professional culture may shape computer-based learning environments

A study into user acceptance of new technology: British Airways ground transport department Heathrow Terminal 5

This project was conducted with the help and encouragement of British Airways (BA) management. It was carried out at Heathrow Airport, Terminal 5 (T5) where a new Resource Management System (RMS) that is based upon Internet Protocol (IP) has been implemented. RMS has replaced traditional pen and paper and radio systems for allocating work tasks to 4,000 airport operational staff. This research project studied one application of the RMS system; the allocation of tasks to the coach drivers in the Ground Transport Services (GTS) department. The user acceptance of the RMS system by the drivers was evaluated. In the previous 20 years, user acceptance theories have been developed which have shown that increased user acceptance of new Information Technology (IT) projects significantly reduces costs and improves efficiency (Davis, 1980). The most comprehensive theory is that of Sun and Zhang (2006) who identify critical factors regarding individual user acceptance (gender, age, experience, cultural background and intellectual capability). This research project used a case study methodology: three days were spent airside at T5 observing and interviewing a sample of drivers. The project research question was: 'Can the degree of RMS acceptance by the GTS end-users be determined by factors identified in user acceptance theories?' Essentially, it was not possible to answer this question because of two reasons. First there was little difference in level of user acceptance; it was very high for all users. Second there was also very little difference in the sample and population. The drivers were all male, over 90% between 42 and 65 years of age, with similar levels of experience regarding the RMS technology and computers in general. In addition, it was not possible to measure any difference between the intellectual capabilities of the participants. A difference in the cultural background was identified; there were two ethnic groups, Asian and Caucasian. However, detailed analysis of the responses to the questionnaire demonstrated that there was no evidence of different levels of user acceptance of these groups. Recommendations to improve the testing of user acceptance theories are included in this report

The Effect of Acceptance Training on Psychological and Physical Health Outcomes in Elders with Chronic Conditions

This pilot trial investigated the short and long-term effects of Acceptance Training (ACT) intervention on acceptance, perceived health, functional status, anxiety, and depression in elders with chronic conditions living in retirement communities (RCs). The ACT intervention combined Rational Emotive Behavior Therapy with music, relaxation, and guided imagery during six weekly 2-hour sessions. Face-to-face interviews were conducted with 16 African-American and 46 White elders across four data collection points in six randomly selected RCs using well-established measures of perceived health, functional status, anxiety, and depression, and a measure of acceptance of chronic conditions adapted from a previous measure of acceptance of diabetes. While changes were found in perceived health, functional status, anxiety, and depression, the most significant changes occurred in the elders\u27 acceptance of chronic conditions immediately after the intervention (t = -2.62, P \u3c .02), and these changes persisted for 6 and 12 weeks (t\u27s = -2.74, -3.32, p\u27s \u3c .01), respectively. Although a 40% attrition rate reduced the sample size from 62 (N = 62) to 37 (N = 37), the significant increases in acceptance over time provide initial evidence for the fidelity of the ACT intervention

Acceptance conditions in automated negotiation

In every negotiation with a deadline, one of the negotiating parties has to accept an offer to avoid a break off. A break off is usually an undesirable outcome for both parties, therefore it is important that a negotiator employs a proficient mechanism to decide under which conditions to accept. When designing such conditions one is faced with the acceptance dilemma: accepting the current offer may be suboptimal, as better offers may still be presented. On the other hand, accepting too late may prevent an agreement from being reached, resulting in a break off with no gain for either party. Motivated by the challenges of bilateral negotiations between automated agents and by the results and insights of the automated negotiating agents competition (ANAC), we classify and compare state-of-the-art generic acceptance conditions. We focus on decoupled acceptance conditions, i.e. conditions that do not depend on the bidding strategy that is used. We performed extensive experiments to compare the performance of acceptance conditions in combination with a broad range of bidding strategies and negotiation domains. Furthermore we propose new acceptance conditions and we demonstrate that they outperform the other conditions that we study. In particular, it is shown that they outperform the standard acceptance condition of comparing the current offer with the offer the agent is ready to send out. We also provide insight in to why some conditions work better than others and investigate correlations between the properties of the negotiation environment and the efficacy of acceptance condition