Body Worn Camera (BWC) is an Information Technology (IT) artefact that has begun to be used in law enforcement. In this paper, we develop a research model that focuses on law enforcement agents’ perspective about the ethical use of BWC, by extending rational choice theory (RCT) from the standpoint of cost/benefit of using BWC, contextual factors, as well as organisational justice. The paper tests the relationship between three factors: a) work motivation, b) cost of using BWC, and c) benefit of using BWC and police perceptions of ethical use of BWC. In addition, we test the moderating effects of work-related uncertainty on the above three relationships. The associations between organisational justice factors and work motivation are also discussed. Further, in collaboration with the National White Collar Crime Center (NW3C), we develop three grey BWC scenarios that are not clearly ethical nor clearly unethical. We apply a survey methodology to test the model in the context of grey scenarios. The results show that work motivation and the risk of using BWC are negatively related with the law enforcement agents’ perceptions about ethical use of BWC and these relationships are negatively moderated by work-related uncertainty, while justice constructs are positively associated with perceived work motivation.

Phishing is an attempt to acquire sensitive information from an unsuspecting victim by malicious means. Recent studies have shown that phishers often use persuasion techniques to get positive responses from the recipients. Still missing from this literature are studies assessing effectiveness of persuasion cues in phishing email detection. Specifically focusing on gain and loss persuasion cues, we address the following research questions: In detecting phishing emails, (1) how effective are the gain persuasion cues, (2) how effective are the loss persuasion cues, and (3) how effective is an integrated model of gain and loss persuasion In order to address the research questions, we create three machine learning models, with relevant gain persuasion cues, loss persuasion cues, and combined gain and loss persuasion cues respectively, and compare the estimates with a baseline model that does not account for the persuasion cues. The results show that the three phishing detection models with relevant persuasion cues significantly outperform the baseline model by approximately 5% to 20% percent in terms of F-score, thus representing reliable methods for phishing email detection.

Rooted in theories of competitiveness and social comparison, we model the effects of users’ structural and trait competitiveness on their engagement and performance growth in an informal learning environment. We hypothesise that game elements of points and leaderboards stimulate users’ structural competitiveness, which affects users’ engagement and has an inverted-U effect on performance growth. We further hypothesise that these effects are stronger among individuals with higher trait competitiveness. We tested our hypotheses using data from a natural experiment conducted over 300 days on 88,310 unique users who made 215,920 game interactions within the Cyber Detectives exhibit at the Tech Interactive museum in California. Our results are based on two objective measures of trait-competitiveness as both behaviour and outcome (percentile ranking on total time spent and number of badges earned, respectively), multiple objective measures of user engagement (time spent per attempt, number of reattempts, and daily user attempts), and an objective measure of performance growth (points). Results provide overall support to our hypotheses. We contribute to the gamification literature by providing strong causal evidence of points and leaderboards triggering structural and trait competitiveness, which interact to affect both engagement and performance growth in informal learning contexts.

During humanitarian crises, there is a need for a large amount of information in a short period of time. Such need creates the base for misinformation such as rumors, fake news or hoaxes to spread within and outside the affected community. This results in (mis)information harms that can generate serious short term or long-term consequences. In such situations, there is a need for a joint human-machine effort to mitigate such harms. Computational scientists have created misinformation detection systems and algorithms, while social scientists have examined the roles of involved parties, examined the way misinformation spreads and convinces people. However, there has been no work, to our knowledge, in examining situations when the machine and human interact with each other in the context of misinformation. In order to systematically examine the harms from misinformation, we draw on Activity Theory to suggest a suitable framework. Such a framework enables interactions among the human and machines and their respective loops for the purpose of mitigation of misinformation harms

Trust is considered as a critical enabler in reducing consumer concerns regarding e-commerce transactions. Another enabler that helps reduce consumers’ concerns is Web Assurance Seal Services (WASS). We suggest that both factors help in the reduction of a critical hindrance to e-commerce, namely consumer concerns, and foster e-commerce transactions. Prior research has focused on trust in e-commerce, and separately, on the effectiveness of WASS within certain nations or cultures. However, given that e-commerce is now a global phenomenon we contend that the national or cultural characteristics of consumers are important to understand. This comparative national research attempts to fill this gap. This study makes the following contributions: It identifies a hindrance (i.e., consumers’ concerns), and two enablers (i.e., effectiveness of WASS and trust) in e-commerce technologies as a shopping channel (i.e., trust in e-Channel). It proposes consumers’ concerns for e-commerce as a second-order three-dimensional construct (i.e., security, privacy, and business integrity concern) and compares the effects of trust in e-Channel and WASS on consumers’ e-commerce transaction intention in two different national/cultural contexts (i.e., the U.S.A. and South Korea). The results of the study indicate that the perceived effectiveness of WASS of the U.S. consumers has a strong positive impact on their transaction intention and has a strong negative influence on their concerns for e-commerce. In contrast, Korean consumers’ perceived effectiveness of WASS does not significantly influence their transaction intention and their concerns for e-commerce. The results of group comparison analysis confirm that the strength of perceived effectiveness of WASS of the U.S. consumers is significantly stronger than that of Korean consumers. Interpretations from a cross-national perspective, theoretical and practical implications as well as limitations are discussed.

Emergency management systems are a critical factor in successful mitigation of natural and man-made disasters, facilitating responder decision making in complex situations. Based on socio-technical systems, have which four components (people, technology, structure and task), this study develops a research framework of factors affecting effective emergency management. People factors include psychological factors such as responders' self-efficacy, support from family, peers and community, and training. Technology factors are task technology and information sharing. The structure factors are leadership, labour and logistics. Finally, the task factor refers to effective emergency management. This study empirically tests this framework by collecting surveys from emergency responders who participated in the 2006 Buffalo October Storm. The research results demonstrate that training and support positively affect emergency management self-efficacy which, in turn, has a positive significant relationship with effective emergency management. Task technology and information sharing also have a positive impact on effective emergency management. However, findings suggest that the structure factors do not show a significant relationship with effective emergency management. This research presents that human factors in emergency management are essential to conduct effective operations. More importantly, investing in technology to assist responders in performing their jobs during the emergency is crucial during the emergency operations.

On December 26th, 2004, the largest natural disaster in recent recorded history took the lives of over 225,000 people from over 40 different nations and displaced millions more. In an increasingly global environment, these disasters are no longer isolated phenomena and must be responded to with a global perspective. The number of casualties from Indian Ocean Tsunami is a testament to the failure of humans in mitigating large scale emergency incidents and it is the consequence of ineffective information sharing and communication among key stakeholders. Using Activity Theory as the theoretical lens, we explore the communication phenomena in emergency response and we identify the major challenge facing communication practices. The paper further explores the design, implementation, and management of advanced information technologies to address the communication challenges.

Enterprises establish computer security policies to ensure the security of information resources; however, if employees and end-users of organisational information systems (IS) are not keen or are unwilling to follow security policies, then these efforts are in vain. Our study is informed by the literature on IS adoption, protection-motivation theory, deterrence theory, and organisational behaviour, and is motivated by the fundamental premise that the adoption of information security practices and policies is affected by organisational, environmental, and behavioural factors. We develop an Integrated Protection Motivation and Deterrence model of security policy compliance under the umbrella of Taylor-Todd's Decomposed Theory of Planned Behaviour. Furthermore, we evaluate the effect of organisational commitment on employee security compliance intentions. Finally, we empirically test the theoretical model with a data set representing the survey responses of 312 employees from 78 organisations. Our results suggest that (a) threat perceptions about the severity of breaches and response perceptions of response efficacy, self-efficacy, and response costs are likely to affect policy attitudes; (b) organisational commitment and social influence have a significant impact on compliance intentions; and (c) resource availability is a significant factor in enhancing self-efficacy, which in turn, is a significant predictor of policy compliance intentions. We find that employees in our sample underestimate the probability of security breaches.

As organizations increasingly operate, compete, and cooperate in a global context, business processes are also becoming global to propagate the benefits from coordination and standardization across geographical boundaries. In this context, security has gained significance due to increased threats, as well as legislation and compliance issues. This article presents a framework for assessing the security of Internet technology components that support a globally distributed workplace. Four distinct information flow and design architectures are identified based on location sensitivities and placements of the infrastructure components. Using a combination of scenarios, architectures, and technologies, the article presents the framework of a development tool for information security officers to evaluate the security posture of an information system. To aid managers in better understanding their options to improve security of the system, we also propose a three-dimensional representation, based on the framework, for embedding solution alternatives. To demonstrate its use in a real-world context, the article also applies the framework to assess a globally distributed workforce application at a northeast financial institution.

Using IT applications is essential for the productive, safe and reliable transportation service. However, there are concerns regarding the cybersecurity vulnerability of IT applications. In this study, we investigate the role of IT in the surface transportation security based on responses from mid and high level managers in transportation industries. Our survey results indicate that managers of the transportation industry think IT applications are fundamental components in the surface transportation operation and security. However, they are highly concern about cybersecurity threats on IT applications. Our research findings contribute to provide the understating of the sate of IT application on surface transportation systems and cybersecurity threats. Our research results and analysis are discussed in this paper.

It has been suggested that parallel processing helps in the solution of difficult discrete optimization problems, in particular, those problems that exhibit combinatorial search and require large-scale computations. By using a number of processors that are connected, coordinated and operating simultaneously, the solutions to such problems can be obtained much more quickly. The purpose of this paper is to propose an efficient parallel hypercube algorithm for the discrete resource allocation problem (DRAP). A sequential divide-and-conquer algorithm is first proposed. The algorithm is then modified for a parallel hypercube machine by exploiting its inherent parallelism. To allocate N units of discrete resources to n agents using a d-dimensional hypercube of p=2/sup d/ nodes, this parallel algorithm solves the DRAP in O((n/p+log/sub 2/p)N/sup 2/) time. A simulation study is conducted on a 32-node nCUBE/2 hypercube computer to present the experimental results. The speedup factor of the parallel hypercube algorithm is found to be more significant when the number of agents in the DRAP is much greater than the number of processing nodes on the hypercube. Some issues related to load balancing, routing, scalability, and mappings of the parallel hypercube algorithm are also discussed.

An important dimension of mobile computing is the ubiquitous and location-independent availability of data. Aggregation is the ability to electronically access and display personal account information from disparate sources through a single identity. The client financial data is assembled in an organized format providing meaningful summarization and analysis. The prevalent methods of aggregation pose issues in information security and assurance. Utilizing advances in Internet technology such as web services and SOAP coupled with the best of the present approaches to aggregation we can arrive at better solutions to securing the identity and data of aggregation customers. The paper puts forth conceptual solutions to address issues regarding security of user profile and identifying aggregators masquerading as users through processes such as screen scraping.

This study proposes a framework regarding the relationship between consumer trust, satisfaction, and expectation in the context of electronic commerce. In particular, the framework draws together two theories: expectation-confirmation theory and social exchange theory. Following the longitudinal pre-purchase and post-purchase stages, this study provides a theoretical framework combining trust, expectation and satisfaction, and tests the proposed models empirically using Internet consumer behavior data collected via two rounds of Web surveys conducted in two major Korean universities. In accordance with existing literature of traditional commerce, the empirical findings suggest that both consumer's trust and expectation have positive influences on consumer's satisfaction. The study also provides a framework explaining the subsequent relationships of trust and satisfaction (trust → satisfaction → post-trust → long-term trust) following the pre-purchase and post-purchase stages. In addition, a significant and positive relationship is detected between consumer's trust and expectation.

Discrete resource allocation problems (RAPs) deal with making decisions that result in an optimal deployment of indivisible scarce resources among a group of agents so as to achieve the maximum aggregate utility. One prerequisite for solving the discrete RAP is that the decision maker be cognizant of the individual utility functions for the agents involved. When an agent's preference information is not available, the decision maker needs to gather such information through an inquiry process. The information acquisition process entails its own costs such as communication costs and computation costs. In this paper, three different information inference mechanisms merging, ranking, and entropy - are proposed and compared for the information acquisition process in the discrete RAP. It is found that the merging mechanism results in the least computation costs for the decision maker while the entropy mechanism incurs the least communication costs.

Research in the area of information acquisition has been based on two key assumptions, namely, nonsatiety (implying more is preferable to less) and transitivity (implying that if A is preferred to B and B to C then A will be preferred to C). While at first glance these assumptions do not seem altogether unjustifiable, they do, in practice, constrain the empirical application of the research models. The primary purpose of the paper is to test the validity of these two key assumptions underlying most theoretical research in information acquisition and resource allocation. We begin by introducing four partial order structures and highlight the assumptions upon which they have been based. We then discuss how these structures could be used in estimating consumer preferences. We also provide a statistical methodology to implement such estimation. In later sections, we implement the empirical model on two data sets and discuss the results and propose generalizations.

Explores a multi-agent resource allocation problem in an environment of incomplete information. The paper posits the existence of a central policy maker who integrates information acquisition with decision making, in order to optimally allocate resources among multiple agents. The study focuses on three salient aspects: first, the policy maker uses a nonparametric revealed preference approach for the elicitation of each agent's preference profiles. This allows the policy maker to avoid distorting the allocation decision and emerging with suboptimal allocations. Second, the process of information gathering and decision making is a challenging task in view of the extremely large numbers of possible profiles for each agent, even for problems of modest size. To find an optimal allocation, the policy maker can use schemes that utilize partial preference information to handle the complexity of the problem. Third, the incorporation of costs into the information process and the minimal assumptions made about the problem environment allow the policy maker to realistically analyze the resource allocation problem.>

The theory of questionnaires deals with the design of experiments for eliciting information with a view to making a decision. The need for eliciting information arises in the problem of allocation of discrete and indivisible scarce resources among consumers by a coordinator. Resource allocation is carried out based on consumer preference information about the discrete resources. This information is acquired by the coordinator by administering a questionnaire, a sequential experimental process that allows the mapping of consumer preference profiles. Questionnaires are comprised of paired comparison experiments. The research questions posed in the paper are akin to those asked in the marketing literature of tailored interviewing: which experiment should be conducted first, and given the answer to the first, which experiment should be conducted next. The focus of this paper is the analysis of the process of preference information acquisition in a choice set-sensitive scenario. A general nonparametric measure of entropy is used for the analysis.>