We study the emergence and evolution of trust in larger societies. We focus on the thin notion of trust, that is the trust needed for interacting with hitherto unknown individuals encountered for just a single interaction. Our model builds upon well-established theoretical knowledge of the determinants of trust. These works identify parameters such as the existence of networks, the level of mobility or the percentage of trust-abusing agents in a society. While the influence of each of these factors individually is well-established by empirical work, a precise account of the interplay of these factors is lacking. To bridge this gap, we devise a multi agent computer simulation that allows a fine grained analysis of the dynamic processes governing the emergence of trust and its dependencies upon these parameters. We model agents using a bayesian learning framework about the value of trust, taking both individual and social information into account.
Green information systems have been shown to contribute to environmental sustainability and help to prevent associated problems. Private households account for 25% of primary energy consumption in western countries, and therefore hold a great potential to curb the use of fossil fuels and prevent cli-mate change. As such, green information systems should not focus solely on the organizational con-text, but also target a single individual’s behaviour in their home. Personal information systems (e.g., web portals) can achieve this focus, however, need to be actively used to produce effects. System us-age can be effectively motivated through incentives, and therewith contribute to positive outcomes. Incentives are either monetary or non-monetary and can be implemented in different scales. In a large field experiment (n= 2,355), with real energy customers of a utility company, we tested the effective-ness of different types and sizes of incentive in motivating active system usage. We show that incen-tives significantly increased system usage of participants, and additionally increased energy savings. However, monetary incentives were not necessarily superior to non-monetary incentives.
Enterprise architecture (EA) network analysis has been attracting researchers' attention lately. The main source of information is the structural components, including the relations among them and how they might be structurally arranged. These relations are studied to generate valuable information for EA professionals. However, to the best of our knowledge, ours is the first attempt to combine structural information with a second source of information: expert's tacit knowledge. We believe combining these sources employing two new methods - what we call cognitive-structural diagnosis analysis and attribute check analysis - can refine the expert's knowledge about the architecture. To demonstrate these methods' feasibility, we apply them with two application architecture datasets collected in two different organizations. We also offer a classification schema for enterprise architecture network analysis at the component level, our focus. Our conclusions indicate that the cognitive- structural diagnosis analysis method minimizes analysis subjectivity while validating important components and also suggesting important structural ones to be further analyzed by experts. The attribute check analysis offers further contributions by helping in the investigation of particular attributes of applications in important architectural positions.
Recent terrorist attacks and several terror alerts have increased the need to investigate the behavioral consequences of these threats. This research-in-progress paper focuses on the motivational factors determining usage behavior of social network sites (SNS) in the aftermath of terrorist attacks. Based on terror management theory (TMT) and uses and gratifications theory (U&G), this paper argues that people reminded of their mortality by terrorist attacks are motivated to seek information and communicate about the attacks on SNS to defend their cultural worldviews and maintain their self-esteem. The paper contributes to the understanding of factors driving people’s usage behavior of SNS in the aftermath of terrorist attacks.
As the complexity of malware grows, so does the necessity of employing program structuring mechanisms during development. While control flow structuring is often obfuscated, the dynamic data structures employed by the program are typically untouched. We report on work in progress that exploits this weakness to identify dynamic data structures present in malware samples for the purposes of aiding reverse engineering and constructing malware signatures, which may be employed for malware classification. Using a prototype implementation, which combines the type recovery tool Howard and the identification tool Data Structure Investigator (DSI), we analyze data structures in Carberp and AgoBot malware. Identifying their data structures illustrates a challenging problem. To tackle this, we propose a new type recovery for binaries based on machine learning, which uses Howard's types to guide the search and DSI's memory abstraction for hypothesis evaluation.
Communication between and within crisis response organizations (i.e., fire and rescue services, medical assistance, government agencies, public organizations, police) and the public (i.e., victims, volunteers, people affected by the attacks) is essential for coping with natural or man-made crises such as Hurri-cane Katrina or the terror attacks of 9/11. Research, however, emphasizes that effective communication is difficult to establish because multiple communication-related barriers arise during crisis management that impede enhanced mitigation, preparedness, response, and recovery. Although research in crisis management and crisis communication gains more and more practical and scientific notice, it still lacks a comprehensive overview. Hence, we conducted a systematic literature review to examine how com-munication between and within crisis response organizations and the public takes place during the mit-igation, preparedness, response, and recovery phases of a crisis. The results show that several techno-logical, organizational, and social barriers hinder communication between all involved. The purpose of this review is to provide a foundation based on the current literature and suggest future research direc-tions to advance knowledge on communication and barriers in communication between and within crisis response organizations and the public during crisis management.