This dissertation employs both design science and behavioral science research paradigms to investigate an emerging form of technology-enabled human collective intelligence known as information markets. This work establishes a conceptual foundation for the study of organizational information markets and the design and use processes of information markets inside organizations. This research conceptualizes markets from an information systems perspective and presents an information systems research framework for organizational information markets. This work develops a systems theory of information markets to facilitate investigation of the relationships and interactions between markets as systems and their context of use. It proposes a structuration model for design and use of IT artifacts in organizations and applies it to the study of information markets. A framework of market users is developed to guide market design to satisfy the different motivational and informational needs of market users. A design based solution is proposed to an important open question in the information markets literature; how to generate sufficient uninformed trades. This research extends structuration theory by developing the structuration model of technology-induced organization development. A well-designed information market can generate several benefits to organizations that contribute to their growth and development. Due to the importance of software in everyday life, and the high costs and percentages of failure in software projects, this dissertation proposes an information market solution to help organizations better manage the risks facing software projects. It also develops a theoretical framework for the determinants of software project risk assessment accuracy and evaluates the market‘s efficacy in improving assessment accuracy via the use of controlled laboratory experiments. The results of the experiments demonstrate the market‘s efficacy in improving assessment accuracy by increasing the currency, accuracy and completeness of reported status information about project main objectives such as cost, schedule, performance and functionality. The results also demonstrate the market‘s efficacy in increasing individual willingness to report negative status information by decreasing their perception of information asymmetry between them and management/clients, and by increasing their perception of both the anonymity of the reporting mechanism and their perceived self-interest in reporting negative status information.

In this dissertation, I examine how IT can support individuals, and in turn their organizations, in learning about and knowing their external environment on the Web. Specifically, I examine novel-knowledge discovery in the context of the multi-level organizational learning process, focusing on cognitive developments and changes to mental models. Novel knowledge is defined as knowledge that is potentially strategically important to the organization, not currently known to the organization, indirectly relevant and therefore difficult to find. Novel knowledge is proposed to be one of three different types of knowledge that organizations seek to discover in their environment. A theoretical framework is developed to identify the sets of tool characteristics, collectively referred to as levels, which are proposed to support the discovery of different types of knowledge, as well as different modes of learning and learning processes. In addition, extensions to the 4I organizational learning process model are proposed, specific to searching and learning on the Web: 1) adding a fifth process – information foraging and search-term development, and 2) adding a fourth level to the learning process – the machine-level. A competing theories approach is used to develop a rich understanding of knowledge discovery and learning on the Web. Understanding which types of tools are useful in different learning contexts has implications for learning effectiveness and may help firms understand how to “manage” their learning. Tools for the discovery of highly novel knowledge are less prevalent than tools to support the other levels of knowledge discovery. Accordingly, a design theory for novel-knowledge discovery tools is proposed based on organizational learning theories. An instantiation of the design theory, a novel-knowledge discovery tool, is developed and tested within the organizational learning process and compared to tools at the other two levels of knowledge discovery. In addition, different processes involved in using a novel-knowledge discovery tool at the group level are examined. Three separate studies were conducted, including a lab and field experiment, and case study. The results are proposed to demonstrate how novel-knowledge discovery tools can support organizational learning. / Thesis (Ph.D, Management) -- Queen's University, 2008-08-26 09:25:31.367

The purpose of business-IT alignment is to optimise the relation between business and IT in order to maximise the business value of IT. Successful business-IT alignment can be enabled by business processes and e-processes functioning as adaptive mediators between business and IT systems. Business processes are the ways actors work in enterprises and collaborate in value networks, while e-processes support a flexible flow of information between IT systems and business processes. The overall goal of this thesis is to propose methods for business process and e-process design and evaluation for achieving alignment between enterprise goals and IT systems. The methods are based on model-driven approaches, using enterprise and software models. More precisely, the proposed methods can be used for designing models of business processes supporting the fulfilment of enterprise goals in the setting of a value network; for designing models of generic and reusable business processes that support the fulfilment of enterprise goals; for designing models of e-processes that support a flexible alignment of IT systems with business processes; and for evaluating the extent to which business processes are aligned with enterprise goals and IT systems. The result of the thesis can be used to support business and system designers with practical knowledge on how to align business and IT systems in order to create efficient, high-quality, flexible and innovative organisations. The research presented in this thesis has been carried out following the design science paradigm. This paradigm is characterised by the creation of new and innovative artefacts for solving general problems, and the evaluation of their benefits and drawbacks.

In recent years businesses around the world have been facing the challenges of a rapidly changing business and technology environment. As a result, organisations are paying more attention to supporting business process management by adapting to the dynamic environment. With the increased complexity and uncertainty in business operations, adaptive and collaborative business process and exception management (EM) are gaining attention. In the logistics industry, the growing importance of logistics worldwide as well as the increasing complexity of logistics networks and the service requirement of customers has become a challenge. The current logistics exceptions are managed using human brain power together with the traditional workflow technology-based supply-chain management or other logistics tools. The traditional workflow technology models and manages business processes and anticipated exceptions based on predefined logical procedures of activities from a centralised perspective. This situation offers inadequate decision support for flexibility and adaptability in logistics EM. The traditional workflow technology is also limited to monitoring the logistics activities in real-time to detect and resolve exceptions in a timely manner. To mitigate these problems, an intelligent agent incorporating business activity monitoring (BAM) decision support approach in logistics EM has been proposed and investigated in this research. This research creates and evaluates two IT designed artefacts (conceptual framework and prototype) intended to efficiently and automatically monitor and handle logistics exceptions. It follows a design science research strategy. The design, development, and evaluation adhere to the principles enunciated in the design science literature. The aim of this research is to solve the important logistics EM problem in a more effective and efficient manner. Two designed artefacts were strictly informed by, and incorporated with, three different theories. An exploratory case study and a later confirmatory case study assisted in the rigorous derivation of the design and framework. The results of the confirmatory case study were used in particular to refine the designed artefacts. Such a build-and-evaluate loop iterated several times before the final designed artefacts were generated. The designed artefacts were then evaluated empirically via a field experiment. The research included both a technical presentation and a practical framing in terms of application in the logistics exception monitoring and handling domain. In this study, there were three interrelated research phases. In the first research phase, a decision-making conceptual framework (an artefact) for design and development of real-time logistics EM system was developed. To enable more efficient decision support practices for logistics EM, the characteristics of logistics exceptions were first examined and identified. The logistics exception analysis was conducted through a comprehensive literature review and an exploratory case study conducted in a major logistics company in Australia. The logistics exceptions were then classified into known and knowable categories, based on the Cynefin sense-making framework (Snowden, 2002). On the basis of the logistics analysis, informed by Gartner’s three-layer BAM architecture (Dresner, 2003), the Cynefin sense-making framework decision models (Snowden, 2002), and Simon’s (1977) decision-making/problem-solving process, the real-time logistics EM conceptual framework was depicted. The BAM architecture provided the real-time decision support. Based on Cynefin’s decision model, adaptive business process flow was chosen for known and knowable logistics exceptions to speed up the decision-making process. In addition, Simon’s process theory was deployed to model the diagnosing process for known and knowable logistics exceptions. This conceptual model guided the analysis, design, and development for real-time logistics EM systems. In the second research phase, based on the logistics EM conceptual framework, a Web-service-multi-agent-based real-time logistics EM system (an artefact) was designed and developed. Intelligent agent technology was applied to deal with the complex, dynamic, and distributed logistics EM processes. Web-services techniques were proposed for more interoperability and scalability in network-based business environment. By integrating agent technology with Web-services to make use of the advantages from both, this approach provided a more intelligent, flexible, autonomous, and comprehensive solution to real-time logistics EM. In the third research phase, two designed artefacts were evaluated via a confirmatory case study and a field experiment. The confirmatory case study was conducted to collect feedback on the two designed artefacts (i.e., conceptual framework and prototype system) to refine them. The field experiment was then conducted to investigate the proposed logistics EM prototype system decision support effectiveness and efficiency by comparing the human decision-making performance with/without the logistics EM decision support facility. The evaluation results indicated that the proposed logistics EM prototype outperformed the one without logistics EM decision support in terms of more efficient decision process, higher decision outcome quality, and better user perception. The two designed artefacts were the major contributions of this research. They add knowledge to decision theory and practice. The artefacts are the real-time extension for Simon’s (1977) classic decision-making/problem-solving process model in logistics EM by incorporating BAM (Dresner, 2003). In addition, by adding the Cynefin sense-making framework (Snowden, 2002), the artefacts provide a more efficient decision-making routine for logistics EM. This research provides the first attempt (to the best of the researcher’s knowledge) to design a real-time logistics EM decision support mechanism based on decision science theories. To demonstrate the usability of the proposed conceptual framework, a logistics EM decision support prototype was designed, developed, and evaluated. For practice, the logistics exceptions classification, logistics EM conceptual framework, and incorporating agent technologies into logistics EM all will assist logistics companies to develop their logistics exception handling decision-making strategies and solutions.

In recent years businesses around the world have been facing the challenges of a rapidly changing business and technology environment. As a result, organisations are paying more attention to supporting business process management by adapting to the dynamic environment. With the increased complexity and uncertainty in business operations, adaptive and collaborative business process and exception management (EM) are gaining attention. In the logistics industry, the growing importance of logistics worldwide as well as the increasing complexity of logistics networks and the service requirement of customers has become a challenge. The current logistics exceptions are managed using human brain power together with the traditional workflow technology-based supply-chain management or other logistics tools. The traditional workflow technology models and manages business processes and anticipated exceptions based on predefined logical procedures of activities from a centralised perspective. This situation offers inadequate decision support for flexibility and adaptability in logistics EM. The traditional workflow technology is also limited to monitoring the logistics activities in real-time to detect and resolve exceptions in a timely manner. To mitigate these problems, an intelligent agent incorporating business activity monitoring (BAM) decision support approach in logistics EM has been proposed and investigated in this research. This research creates and evaluates two IT designed artefacts (conceptual framework and prototype) intended to efficiently and automatically monitor and handle logistics exceptions. It follows a design science research strategy. The design, development, and evaluation adhere to the principles enunciated in the design science literature. The aim of this research is to solve the important logistics EM problem in a more effective and efficient manner. Two designed artefacts were strictly informed by, and incorporated with, three different theories. An exploratory case study and a later confirmatory case study assisted in the rigorous derivation of the design and framework. The results of the confirmatory case study were used in particular to refine the designed artefacts. Such a build-and-evaluate loop iterated several times before the final designed artefacts were generated. The designed artefacts were then evaluated empirically via a field experiment. The research included both a technical presentation and a practical framing in terms of application in the logistics exception monitoring and handling domain. In this study, there were three interrelated research phases. In the first research phase, a decision-making conceptual framework (an artefact) for design and development of real-time logistics EM system was developed. To enable more efficient decision support practices for logistics EM, the characteristics of logistics exceptions were first examined and identified. The logistics exception analysis was conducted through a comprehensive literature review and an exploratory case study conducted in a major logistics company in Australia. The logistics exceptions were then classified into known and knowable categories, based on the Cynefin sense-making framework (Snowden, 2002). On the basis of the logistics analysis, informed by Gartner’s three-layer BAM architecture (Dresner, 2003), the Cynefin sense-making framework decision models (Snowden, 2002), and Simon’s (1977) decision-making/problem-solving process, the real-time logistics EM conceptual framework was depicted. The BAM architecture provided the real-time decision support. Based on Cynefin’s decision model, adaptive business process flow was chosen for known and knowable logistics exceptions to speed up the decision-making process. In addition, Simon’s process theory was deployed to model the diagnosing process for known and knowable logistics exceptions. This conceptual model guided the analysis, design, and development for real-time logistics EM systems. In the second research phase, based on the logistics EM conceptual framework, a Web-service-multi-agent-based real-time logistics EM system (an artefact) was designed and developed. Intelligent agent technology was applied to deal with the complex, dynamic, and distributed logistics EM processes. Web-services techniques were proposed for more interoperability and scalability in network-based business environment. By integrating agent technology with Web-services to make use of the advantages from both, this approach provided a more intelligent, flexible, autonomous, and comprehensive solution to real-time logistics EM. In the third research phase, two designed artefacts were evaluated via a confirmatory case study and a field experiment. The confirmatory case study was conducted to collect feedback on the two designed artefacts (i.e., conceptual framework and prototype system) to refine them. The field experiment was then conducted to investigate the proposed logistics EM prototype system decision support effectiveness and efficiency by comparing the human decision-making performance with/without the logistics EM decision support facility. The evaluation results indicated that the proposed logistics EM prototype outperformed the one without logistics EM decision support in terms of more efficient decision process, higher decision outcome quality, and better user perception. The two designed artefacts were the major contributions of this research. They add knowledge to decision theory and practice. The artefacts are the real-time extension for Simon’s (1977) classic decision-making/problem-solving process model in logistics EM by incorporating BAM (Dresner, 2003). In addition, by adding the Cynefin sense-making framework (Snowden, 2002), the artefacts provide a more efficient decision-making routine for logistics EM. This research provides the first attempt (to the best of the researcher’s knowledge) to design a real-time logistics EM decision support mechanism based on decision science theories. To demonstrate the usability of the proposed conceptual framework, a logistics EM decision support prototype was designed, developed, and evaluated. For practice, the logistics exceptions classification, logistics EM conceptual framework, and incorporating agent technologies into logistics EM all will assist logistics companies to develop their logistics exception handling decision-making strategies and solutions.

In the search to reduce the various divides between the developed and the developing world, Information and Communication Technology (ICT) is seen as an enabler in resource-constrained environments. However, the impact of ICT for Development (ICT4D) implementations is contested, and the ability to facilitate sustained change remains elusive. Sustainability emerged as a key lesson from the failure of early ICT4D projects, and has served as a focal point in facilitating ICT4D success. However, interpretation of the concepts of sustainability and sustainable development seems to be multiple and disconnected from practice, and is rarely translated into a useful construct for guiding project-level actions. The focus of international development is gradually shifting from donated aid towards capability and choice, empowerment, and per-poor initiatives. However, the reality remains that multiple organisations with varying levels of power, resources, and influence determine the outcomes and the sustainability of benefits from a development intervention. This research investigates mechanisms to sustain benefit by exploring the interface between various role players through the lens of decision-making. It builds on the view that the value created by the virtual ‘organisation’ of stakeholders in an ICT4D implementation results from the sum of its decisions, and develops a framework for decision-making with a view on sustaining benefits. The work follows a Design Science Research methodology, comprising an iterative process for the development, testing, and improvement of the framework based on three literature reviews, two case studies, and an expert review. The research answers the primary research question, namely: What are the elements of a framework that support strategic decision-making for the design and implementation of ICT4D interventions in resource-constrained environments, in support of sustained benefit? The knowledge contribution is primarily at the concept and methodological level. In addition to framework development, the decision problem in ICT4D is defined, andthe concept of sustained benefit is proposed as a means of operationalizing sustainability. This research illustrates the role of decision concepts in structuring the complexity of ICT4D problems. It introduces an alternative perspective into the debate on sustainability in ICT4D, and provides a basis for the future development of theory. / Information Systems / D. Litt. et Phil. (Information Systems)

The continuing financial losses incurred by individuals and companies due to identity information being phished are necessitating more innovative approaches to solving the problem of phishing attacks at the company level. Security standards are developed by respected experts in the profession and are widely accepted in the industry. The purpose of this study was to investigate whether a standard can be adapted to develop a framework that may guide companies in determining how to protect themselves against phishing attacks. A qualitative approach using design research as the methodology was used during the research. The data collection took place by means of a literature survey and semi-structured interviews. The artefact developed was a phishing-prevention framework based on the ISO/IEC 17799 standard, and the evaluation thereof took place through test cases. The findings communicated to the managerial audience was a set of recommendations as a further investment in their security protection against phishing attacks; the findings communicated to the technical audience was the successful adaptation of an existing security standard to produce a usable framework. Further research initiatives should extend the types of test cases that the phishing-prevention framework was evaluated against, and explore the use of tools for determining compliance with the framework. / Theoretical Computing / M. Sc. (Information Systems)

This thesis describes a research investigation into the implementation of the Last Planner System (LPS) in Nigeria, to improve construction processes within the Nigerian construction industry. LPS is known to be the most developed practical use of Lean Construction. It focuses on minimising the negative impacts of variability, uncertainties, buffers, making projects more predictable, creating reliable work plans and convalescing collaborative planning. However, the Nigerian construction industry is associated with a number of challenges which impair its performance. These challenges were grouped and classified into six major barriers: these include: supervision and quality control, fluctuation and variations, subcontractor involvement, resistance to change, cultural issues, and lengthy approvals. Consequently, a Design Science Research (DSR) approach is adopted to evaluate the effectiveness of implementing LPS in construction projects in Nigeria. In order to achieve this aim, an Action Research strategy is adopted and three case studies are reported; two of these cases describe how LPS was successfully implemented in construction projects within Nigeria. While the third case involved an investigation into the state of production plan reliability, of a successful project in Nigeria. These projects were selected based on non-probabilistic sampling from different geographical locations in Nigeria to represent different kinds of construction projects within the country. The first and second cases involved the implementation of LPS within the construction of a prototype student’s hostel and the construction a 4 Kilometre single carriageway road respectively. The third on the other hand involved the construction of a multipurpose hydro-power dam project; where comparisons were made between typical LPS projects and the project management techniques applied within the project. Data was collected through observation site activities, interviews, documentary analysis and questionnaire survey. The data generated was subsequently analysed by means of content analysis and evaluated in terms of its reliability, validity, representativeness, flexibility, rigour and reflexivity. In view of the LPS implementation within the two case studies, six barriers were identified and classified together with the six barriers associated with the Nigerian Construction industry. These barriers were linked, measured and ranked in averages of their degrees of occurrences. It was revealed that the major barriers were cultural issues and resistance to change, while the others include; lengthy approval, subcontractor’s involvement, poor supervision and quality, fluctuations and variations. Hence, a framework was developed to mitigate these barriers, when implementing LPS in construction projects in Nigeria. The main steps of the framework include: the need to identify purpose; the need to identify stakeholders impact; the need to obtain Sponsorship; the need to build a cross functional team; the need to create measurement indices; the need for training on Lean techniques and LPS; and finally the need to create a right working climate. Furthermore a focus group between construction practitioners was organised to test and evaluate the framework developed. It was revealed from the focus group that the framework has the potential to facilitate the implementation process as proposed.

No description available.

Since its beginnings in 1974, the Automated Clearing House (ACH) network has grown into one of the largest, safest, and most efficient payment systems in the world. An ACH transaction is an electronic funds transfer between bank accounts using a batch processing system. Currently, the ACH Network moves almost $43 trillion and 25 billion electronic financial transactions each year. With the increasing movement toward an electronic, interconnected and mobile infrastructure, it is critical that electronic payments work safely and efficiently for all users. ACH transactions carry sensitive data, such as a consumer's name, account number, tax identification number, account holder name, address, or social security number. ACH fraud consists of the theft of funds through the Automated Clearing House financial transaction network (Accounts Receivable & Order-to-Cash Network, 2012). If the transactions are intercepted by fraudulent activities, either during transit or during rest, the sensitive customer data can be used to steal the transferred funds, which can cause financial and reputational damage to ACH network participants and consumers. Even though the National Automated Clearing House Association (NACHA) requires ACH participants to use commercially reasonable encryption and authentication procedures, the risks associated with employee error or negligence, physical theft, and insider theft of data remain substantial. The ACH network that handles 40 billion transactions annually has consumer and corporate financial information. As the ACH network emerges as a prominent payment channel, proactive steps must be taken to guarantee consumer safety. The primary research question “How can opportunities to commit ACH fraud by insiders be inhibited by masking sensitive data in the ACH transactions life cycle?” is addressed employing design science research methodology with special focus on this specific question: Will use of Multi-step tokens in life cycle of ACH transactions lower the risk of sensitive data exposure? To demonstrate the extent to which the Multi-step tokens in the life cycle of ACH transactions lower the risk of sensitive data exposure, the following two sub-questions will be answered: • How to model and simulate sensitive data exposure risk in current ACH transaction life cycle? • How to model and simulate sensitive data exposure risk in the multi-step tokenized ACH transaction life cycle? The research findings through proof of concept simulations confirm that sensitive consumer personal identifiable information shared in ACH network can be made more secure from insider threat opportunities by multi-step tokenization of ACH data. In the to-be system, the real account number will not be used to post the actual financial transaction. Only tokenized account number will be used by RDFI (Receiving Depository Financial Institution) to post the financial transaction. Even if the ODFI (Originating Depository Financial Institution) initiate the financial transaction using real account number, RDFI will reject the transaction back to the originator to resend the transaction using the token value. For the same account number, RDFI will have different token values based on SEC (Standard Entry Class) code, origin, ODFI, transaction type etc. The account token value will be generated only if ODFI sends a token request separately to RDFI in a multi-step manner. The research findings suggest that multi-step tokenization can be used to generate and validate unique transaction path as a function of the transaction origin number, originating depository financial institution, Standard Entry class, Receiving depository financial institution and account number. Even if the account or token value gets misplaced, the data will be of no use to the person having the information. The cipher can be further strengthened by including additional unique ACH data elements. The findings stem from proof of concept development and testing of conceptual, empirical and simulated models of current ACH network, insider breach scenarios, and multi-step tokenized systems. The study findings were augmented by running different model scenarios and comparing the outputs for breaches, network traffic and costs. The study findings conclude with an implementation proposal of the findings in the ACH network and opportunities for further research on the topic.