Enhancing RFID data quality and reliability

This thesis addressed the problem of data quality, reliability and energy consumption of networked Radio Frequency Identification systems for business intelligence applications decision making processes. The outcome of the research substantially improved the accuracy and reliability of RFID generated data as well as energy depletion thus prolonging RFID system lifetime.

Linking BI competency and assimilation through absorptive capacity: a conceptual framework

Business intelligence (BI) can help support decision-making processes and so contribute to improved BI assimilation and organisational performance. However, a BI undertaking may be effective and profitable for some organisations but not others. How can these differing outcomes be explained for those firms that have adopted BI systems? Drawing on the literature pertaining to absorptive capacity theory, IT competency, and BI assimilation we develop a conceptual framework to investigate the relationships between BI competency, absorptive capacity, and BI assimilation. This research provides insights for BI stakeholders in understanding the mediating role of organisational absorptive capacity within a complex BI environment, enabling many organisations that have implemented BI to leverage the benefits from their costly investments. The conceptual framework provides a sound basis for further research to shed light on the effects of BI competency and organisational absorptive capacity on BI assimilation. Contributions to research and practice are discussed.

BI-based organizations : a sensemaking perspective

Business intelligence (BI) offers opportunities for managers to master vast data resources for operational and strategic gains, and allows BI-based organizations to generate significant business value. While several researchers emphasized the importance of BI to assist making quality decisions, no study explored the use of BI for improved understanding of business before such decisions are made and assessing the impact of the actions derived from these decisions. To fill this gap we use the theory of organizational sensemaking. The presented research uses hermeneutic phenomenology to study the experiences of decision-makers in using BI-generated insights to guide their actions while altering business processes, structures and information. The study emphasizes the necessity of using BI in the creation and maintenance of individual and organizational identity, as well as, enactment of this identity on the business and its environment, which need to be molded in response to changing circumstances.

Enhancing RFID tag resistance against cloning attack

In its current form, RFID system are susceptible to a range of malevolent attacks. With the rich business intelligence that RFID infrastructure could possibly carry, security is of paramount importance. In this paper, we formalise various threat models due tag cloning on the RFID system. We also present a simple but efficient and cost effect technique that strengthens the resistance of RFID tags to cloning attacks. Our techniques can even strengthen tags against cloning in environments with untrusted reading devices.

Customer analytics managers' views about market research

Data based on survey responses from online questionaire directed at Customer Analytics managers in the United States. Respondents recruited were mainly in CRM, customer data warehouse or CA roles.

Success was measured on several items asking respondents to compare the success of their organisation with others in their industry on measures such as profitability and new product development. Items about the integration of MR and CA were included. These talked about effectively combining CA and MR for the purpose of identifying new markets and new segments as well as reducing churn.

Survey of market research managers' views about customer analytics

Data based on survey responses from an online questionnaire directed at market research managers in the US.

Using an online questionnaire 435 market research managers in the United States were surveyed about their views on using customer analytics to provide reliable customer information to gain market edge.

Using SPSS AMOS software, the resulting data identifies new trends in the business intelligence industry in transition and particularly the usage by market relations managers of customer analytics information.

An empirical study of BI-based corporate performance management in North America and East Asia

Managing corporate performance is an important yet challenging process. Recently, many enterprises have adopted business intelligence (BI) tools to facilitate more effective corporate performance management. Based on a survey with 290 organizations across North America and East Asia, this paper presents empirical evidence on the key benefits of and barriers to BI-based corporate performance management (CPM). The study reveals that the implementation of BI-based CPM faces multi-dimensional challenges. Organizations in East Asia perceived higher CPM benefits as well as higher CPM barriers than their counterparts in North America. Cultural, economic and environmental differences between the two regions explain these issues. The research findings offer important insights for multinational organizations that are planning or are in the process of implementing or reviewing their BI-based CPM, as well as for consulting companies that are assisting with CPM implementation in different countries.

Becoming an analytics-based organisation : strategic agency in the change process in a retail organisation

The paper examines how the upward and downward strategic influences of the head of the BI unit in the case organization have evolved over time and the BI perspective became legitimate in the organization. The analysis covers a decade long period of time. We engaged in an Action Research (AR) inquiry where the change process was explored through the first-hand experiences of one of the co-authors. The model of the strategic agency of middle managers was applied in the analysis. We analyse the evolution as well as the enablers and constraints of the strategic agency of the head of the BI unit in the case organisation and identify the type of strategic agency exhibited in the case.

Broadband technologies, techno-optimism and the "hopeful" citizen

Using the internet to promote or facilitate learning has a relatively long history. As early as the mid-1980s, at a time when the internet itself was relatively experimental, a few early pioneers such as Hiltz were exploring the possibilities that networked computer communications technology could provide for education. Not only were universities the birthplace of the internet as a research network, they also had both staff with interests in using technology for learning as well as the critical infrastructure which might permit early development and adoption. But, with the widespread public uptake of the internet from 1994 onwards, online learning has become much more widespread-through traditional institutions of learning (schools, colleges, and universities), and also through the auto-didactic qualities of both the internet itself and many who use it; and finally through the opportunities which commercial “providers” of education and training imagine might be embedded in this new technology to deinstitutionalize learning.

Biomedical signal filtering for noisy environments

 Luke's work addresses issue of robustly attenuating multi-source noise from surface EEG signals using a novel Adaptive-Multiple-Reference Least-Means-Squares filter (AMR-LMS). In practice, the filter successfully removes electrical interference and muscle noise generated during movement which contaminates EEG, allowing subjects to maintain maximum mobility throughout signal acquisition and during the use of a Brain Computer Interface.

Extension of bivariate means to weighted means of several arguments by using binary trees

ABSTRACTAveraging aggregation functions are valuable in building decision making and fuzzy logic systems and in handling uncertainty. Some interesting classes of averages are bivariate and not easily extended to the multivariate case. We propose a generic method for extending bivariate symmetric means to n-variate weighted means by recursively applying the specified bivariate mean in a binary tree construction. We prove that the resulting extension inherits many desirable properties of the base mean and design an efficient numerical algorithm by pruning the binary tree. We show that the proposed method is numerically competitive to the explicit analytical formulas and hence can be used in various computational intelligence systems which rely on aggregation functions.

An effective energy testing framework for cloud workflow activities

Cloud computing as the latest computing paradigm has shown its promising future in business workflow systems facing massive concurrent user requests and complicated computing tasks. With the fast growth of cloud data centers, energy management especially energy monitoring and saving in cloud workflow systems has been attracting increasing attention. It is obvious that the energy for running a cloud workflow instance is mainly dependent on the energy for executing its workflow activities. However, existing energy management strategies mainly monitor the virtual machines instead of the workflow activities running on them, and hence it is difficult to directly monitor and optimize the energy consumption of cloud workflows. To address such an issue, in this paper, we propose an effective energy testing framework for cloud workflow activities. This framework can help to accurately test and analyze the baseline energy of physical and virtual machines in the cloud environment, and then obtain the energy consumption data of cloud workflow activities. Based on these data, we can further produce the energy consumption model and apply energy prediction strategies. Our experiments are conducted in an OpenStack based cloud computing environment. The effectiveness of our framework has been successfully verified through a detailed case study and a set of energy modelling and prediction experiments based on representative time-series models.

V for variety: Lessons learned from complex smart cities data harmonization and integration

With emerging trends for Internet of Things (IoT) and Smart Cities, complex data transformation, aggregation and visualization problems are becoming increasingly common. These tasks support improved business intelligence, analytics and enduser access to data. However, in most cases developers of these tasks are presented with challenging problems including noisy data, diverse data formats, data modeling and increasing demand for sophisticated visualization support. This paper describes our experiences with just such problems in the context of Household Travel Surveys data integration and harmonization. We describe a common approach for addressing these harmonizations. We then discuss a set of lessons that we have learned from our experience that we hope will be useful for others embarking on similar problems. We also identify several key directions and needs for future research and practical support in this area.

Information systems and business informatics: an Australian German comparison

At last year's ACIS conference in Melbourne a panel titled 'IS: A discipline in crisis' discussed issues relating to be in disability of IS in Australia. It is not, however, just the Australian IS discipline that must deal with problems such as the need for better organisational structures and greater visibility in universities. This paper presents a comparison between the German Business Informatics discipline and the Australian Information Systems discipline. The objective is to provide another perspective on the IS discipline to raise new ideas and stimulate discussion with reference to the organisational structure of our discipline in universities.