Understanding fear of opportunism in global prize-based science contests: Evidence for gender and age differences

Global prize-based science contests have great potential for tapping into diverse knowledge on a global scale and overcoming important scientific challenges. A necessary step for knowledge to be utilized in these contests is for that knowledge to be disclosed. Knowledge disclosure, however, is paradoxical in nature: in order for the value of knowledge to be assessed, inventors must disclose their knowledge, but then the person who receives that knowledge does so at no cost and may use it opportunistically. This risk of potential opportunistic behavior in turn makes the inventor fearful of disclosing knowledge, and this is a major psychological barrier to knowledge disclosure. In this project, we investigated this fear of opportunism in global prize-based science contests by surveying 630 contest participants in the InnoCentive online platform for science contests. We found that participants in these science contests experience fear of opportunism to varying degrees, and that women and older participants have significantly less fear of disclosing their scientific knowledge. Our findings highlight the importance of taking differences in such fears into account when designing global prize-based contests so that the potential of the contests for reaching solutions to important and challenging problems can be used more effectively

An Active Temporal Model for Network Management Databases

The purpose of a network management system is to provide smooth functioning of a large heterogeneous network through monitoring and controlling of network behavior. ISO/OSI has defined six management functionalities that aid in overall management of a network: configuration, fault, performance, security, directory and accounting management. These management functionalities provide tools for overall graceful functioning of the network on both day-to-day and long-term basis. All of the functionalities entail dealing with huge volumes of data. So network management in a sense is management of data, like a DBMS is used to manage data. This is precisely our purpose in this paper to show that by viewing the network as a conceptual global database the six management functionalities can be performed in a declarative fashion through specification of management functionalities as data manipulation statements. But to be able to do so we need a model that incorporates the unique properties of netw..

The Effect of Using Artificial Intelligence on Performance of Appraisal System: A Case Study for University of Jeddah Staff in Saudi Arabia

The final authenticated version is available online at https://doi.org/10.1007/978-3-030-55180-3_11.© 2021, Springer Nature Switzerland AG. Despite the interest of developed countries in relying on artificial intelligence in the performance of their work, developing countries are at the beginning of this path. The researcher has noted that the use of modern technologies, especially artificial intelligence, did not give the necessary attention in government business and many private sector companies, so it was necessary to draw attention to the importance of using it to develop all businesses. This study focuses on clarifying the importance of using artificial intelligence (AI) technology in the process of evaluating the employee’s performance to increase the effectiveness of performance appraisal for all organisational levels to make strategic decisions which affect the objectives of the organisation. This study has used a questionnaire that looked at participants’ views and attitudes towards technology and its usefulness in the appraisal process. Knowing the opinions of employees and their supervisors will enable to demonstrate the need to use AI to raise the efficiency of the performance appraisal system and develop its processes for the employee’s benefits and the general interest at the organisation. Most of the answers were between agree and strongly agree, and on the other side, there was a very small percentage that did not believe the importance of using artificial intelligence in works, and this may be due to their feeling of resisting change and the desire to work a way they used to. This paper begins by providing demographic details and background information on the participants, followed by an examination of the reliability of the extracted factors/metrics. The extracted factors will then be described individually using general descriptive statistics (such as repetition percentages) to look at their respective elements and see the level of the agreement created by the participant. Following this descriptive part of the analysis, this paper seeks to conduct an in-depth analysis of the results using various inferential statistics to test group differences using demographic and background details of the participants (e.g. age, gender, education). This study investigates the impact of the use of AI on the performance appraisal model, and to examine the effect of AI on the technology adoption