William H. Money

Big Data: Issues and Challenges Moving Forward

Big data refers to data volumes in the range of exabytes (1018) and beyond. Such volumes exceed the capacity of current on-line storage systems and processing systems. Data, information, and knowledge are being created and collected at a rate that is rapidly approaching the exabyte/year range. But, its creation and aggregation are accelerating and will approach the zettabyte/year range within a few years. Volume is only one aspect of big data; other attributes are variety, velocity, value, and complexity. Storage and data transport are technology issues, which seem to be solvable in the near-term, but represent longterm challenges that require research and new paradigms. We analyze the issues and challenges as we begin a collaborative research program into methodologies for big data analysis and design.

Impact of organizational and project factors on acceptance and usage of project management software and perceived project success

This study surveyed 497 participants to determine the factors that affect project professionals’ acceptance of project management software and the perceived impact of software usage on their performance. The study finds that greater information quality and higher project complexity are the dominant factors explaining higher levels of system utilization, that greater system functionality and ease of use have a significant positive relationship with increased software usage, and that a strong positive relationship exists between higher usage of project management software and perceived project managers’ improved performance. Inconsistent with prior research, more training was not found to be associated with project management software usage. The study explains more than 40% of the variation in project management software acceptance and adds project management software usage to project success factors by empirically confirming for the first time that project management software enhances project professionals’ perceived performance and provides a positive impact on the results of their projects. The study provides practical implications for project professionals, their organizations, senior management, decision makers, software developers, and vendors. These findings support the call for further research that investigates the diffusion of information technologies in the project management field and their impact on project success and competitive position.

Assessing Knowledge Management System User Acceptance with the Technology Acceptance Model

This article presents the results of a study investigating the applicability of Davis’ Technology Acceptance Model (TAM) to user acceptance of a knowledge management system (KMS) in a modern organizational environment. The study endeavors to expand empirical research of two important and complex research questions: (1) What are the important factors, conditions, and mechanisms that affect people’s acceptance and usage of collaborative and interdependent KMS in the modern organizational environment?, and (2) How applicable is the TAM, and the substantial body of information technology (IT) research around this model, to user acceptance and usage of a KMS in a modern organizational environment where collaboration, knowledge sharing, and role based system usage is necessary for the organization to function competitively? The study provides preliminary evidence suggesting previous TAM research may serve as a foundation for research of KMS user acceptance. Relationships among primary TAM constructs found in this study are in substantive agreement with those of previous research. These findings are significant because they suggest that the considerable body of previous TAM related IT research may be usefully applied to the knowledge management (KM) domain where interdependent social processes that require knowledge creation, storage and retrieval, transfer, and application are required for effective organizational functioning.

A Decision Framework for Cloud Computing

Cloud computing technology is garnering success and wisdom-like stories of savings, ease of use, and increased flexibility in controlling how resources are used at any given time to deliver computing capability. This paper develops a preliminary decision framework to assist managers who are determining which cloud solution matches their specific requirements and evaluating the numerous commercial claims (in many cases unsubstantiated) of a clouds value. This decision framework and research helps managers allocate investments and assess cloud alternatives that now compete with in-house data centers that previously stored, accessed, and processed data or with another companys (outsourced) data center resources. The hypothetically newly captured corporate value (from cloud) is that resources are no longer idle most of the time, and are now much more fully utilized (with lower unit costs). This reduces high ownership and support costs, improves capital leverage, and delivers increased flexibility in the use of resources.

Service Migration in a Cloud Architecture

This paper examines service migration in a new computing paradigm, the cloud computing environment (CCE), by examining security and integration issues associated with service implementation. We postulate that a cloud architecture will evolve to be both more flexible and heterogeneous in resources because of the services complexity demanded by organizations. This introduces additional, but tractable, complications when considering the service migration concept within three support areas; acquisition, implementation, and security that present significant challenges to service migration in the cloud. From the consumer perspective, these support areas present the slowest and most costly components of the migration problem for small to medium size organizations. We hypothesize that several mechanisms including CCE platform standards and a computational virtual machine will need to be developed (or will emerge and achieve dominance in the cloud market domain) to facilitate service migration and the resolution of the issues identified.

Advanced Analytics -- Issues and Challenges in a Global Environment

Modern businesses require a suite of appropriate analytical tools - both quantitative and qualitative - that go beyond data mining, because of issues with scalability, parallelizability, and numeric vs. symbolic representation that may well affect analytic utility and the results of an analytic. However, there is limited formal or structured guidance for new and complex problem spaces providing criteria for what analytics to use and how they are to be cascaded or integrated to obtain useful results and generate a range of alternate explanations of what is happening now, what is likely to happen soon, and what could happen in the long term. In this paper, we describe sixteen classes of analytics in which we extend previous work by Kaisler and Cioffi-Revilla [7]. We examine some issues and implementation challenges for analytics in the global business environment. We suggest several applications of these analytics to modern business problems and draw several conclusions that lead to further research.

Effects of Computer Self Efficacy on the Use and Adoption of Online Social Networking

Online Social Networking (OSN) systems such as Ning, MySpace, Facebook and Friendster have achieved tremendous popularity. However, little research has been conducted to determine factors motivating users with varying capabilities to use and adopt OSN systems addressing target tasks, with varying system capabilities and characteristics. The relationships between user characteristics and use/performance have not been adequately addressed. This study used a cross-sectional survey of 262 graduate and undergraduate students to examine how end user Computer Self-Efficacy (CSE) affects performance and use of OSN systems and how A¢â‚¬A“fitA¢â‚¬Â determines whether there are user, task and/or systems characteristics associated with the best performance and usage levels. Significant direct and indirect relationships were found between CSE, task and system characteristics as measured by performance and use, and these relationships were further significantly strengthened when there was good A¢â‚¬A“fitA¢â‚¬Â between the variables. Results indicate that users having high self-efficacy A¢â‚¬A“fitA¢â‚¬Â with task or systems characteristics produce higher performance and use.

Improving Integration and Insight in Smart Cities with Policy and Trust

This paper examines the issues of policy and trust in the context of IT infrastructures for Smart Cities. This paper proposes that trusted Smart city policies can lead to the development of trusted foundational service underlying all smart city solutions. Such a set services are critical for architectural choices of data integration and use within smart city domains, and will lead to the development of a marketplace where service providers and consumers engage in a free and fully informed exchange to choose worthy and reliable experiences to address everything from reporting street light outage to identifying economic advantages during city planning. It argues that two usually mutually exclusive architectural meta-models; Centralization and Federation, are required to achieve a set of trusted foundational services. It reviews the large array of options for implementing the marketplace component of the foundational services to support scenarios varying from fully isolated well known analytics to the anonymous access that allows potential users to browse for services without any controls. It concludes that Trusted Policies are highly important as successful ingredients in the development of foundational services and the following developmental stage, and in the operations and maintenance stages for integrated Smart city systems. It is critical that Smart cities systems implement city-wide policies that improve and sustain trust that in turn help Smart cities manage across the multitude of systems that are in both developmental and operational stages simultaneously, and will be so for many decades to come.

Data Systems Fault Coping for Real-time Big Data Analytics Required Architectural Crucibles

This paper analyzes the properties and characteristics of unknown and unexpected faults introduced into information systems while processing Big Data in real-time. The authors hypothesize that there are new faults, and requirements for fault handling and propose an analytic model and architectural framework to assess and manage the faults and mitigate the risks of correlating or integrating otherwise uncorrelated Big Data, and to ensure the source pedigree, quality, set integrity, freshness, and validity of data being consumed. We argue that new architectures, methods, and tools for handling and analyzing Big Data systems functioning in real-time must design systems that address and mitigate concerns for faults resulting from real-time streaming processes while ensuring that variables such as synchronization, redundancy, and latency are addressed. This paper concludes that with improved designs, real-time Big Data systems may continuously deliver the value and benefits of streaming Big Data.

Developing Applications and Methodologies for Electronically Facilitated Project Planning: a Coast Guard Case Study

This paper reports on development of an electronic project planning application and process designed to quickly and easily generate plans. The literature suggests that collaboration, planning and follow-up are major obstacles to project success. During the 1990s, the authors developed a formatting application providing GroupSystems output in MS Project format, and successfully tested it by developing a treaty implementation plan for the coast guard. The application worked, but languished because it was cumbersome and constrained by 1990s technology. In 2004, authors were asked to expand the earlier coast guard plan. Determined to improve upon their legacy system, they developed a completely new application specifically designed to collaboratively develop project plans, and tested it in development of a new long range plan for the coast guard. The opportunity to develop an application without legacy artifacts was an exciting experience. This paper discusses the authors experiences in application and collaborative process development