Managing Trust in Online Social Networks

In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

Call for action : investigating the role of business process management in green IS

Sustainable practices are more than ever on the radar screen of organizations, triggered by a growing demand of the wider population towards approaches and practices that can be considered "green" or "sustainable". Our specific intent with this call for action is to immerse deeper into the role of business processes, and specifically the contributions that the management of these processes can play in leveraging the transformative power of information systems (IS) in order to create environmentally sustainable organizations. Our key premise is that business and information technology (IT) managers need to engage in a process-focused discussion to enable a common, comprehensive understanding of process, and the process-centered opportunities for making these processes, and ultimately the organization as a process-centric entity, "green". Based on a business process lifecycle model, we propose possible avenues for future research.

An example of developing a business model for information and communication technologies (ICT) adoption on construction projects – the National Museum of Australia project

Effective use of information and communication technologies (ICT) is necessary for delivering efficiency and improved project delivery in the construction industry. Convincing clients or contracting organisations to embrace ICT is a difficult task, there are few templates of an ICT business model for the industry to use. ICT application in the construction industry is relatively low compared to automotive and aerospace industries. The National Museum of Australia project provides a unique opportunity for investigating and reporting on this deficiency in publicly available knowledge. Concentrates on the business model content and objectives, briefly indicates the evaluation framework that was used to evaluate ICT effectiveness.

Fragment-based version management for repositories of business process models

As organizations reach higher levels of Business Process Management maturity, they tend to accumulate large collections of process models. These repositories may contain thousands of activities and be managed by different stakeholders with varying skills and responsibilities. However, while being of great value, these repositories induce high management costs. Thus, it becomes essential to keep track of the various model versions as they may mutually overlap, supersede one another and evolve over time. We propose an innovative versioning model, and associated storage structure, specifically designed to maximize sharing across process models and process model versions, reduce conflicts in concurrent edits and automatically handle controlled change propagation. The focal point of this technique is to version single process model fragments, rather than entire process models. Indeed empirical evidence shows that real-life process model repositories have numerous duplicate fragments. Experiments on two industrial datasets confirm the usefulness of our technique.

The effectiveness of literalism-symbolism in business-to-business advertising

A basic element in advertising strategy is the choice of an appeal. In business-to-business (B2B) marketing communication, a long-standing approach relies on literal and factual, benefit-laden messages. Given the highly complex, costly and involved processes of business purchases, such approaches are certainly understandable. This project challenges the traditional B2B approach and asks if an alternative approach—using symbolic messages that operate at a more intrinsic or emotional level—is effective in the B2B arena. As an alternative to literal (factual) messages, there is an emerging body of literature that asserts stronger, more enduring results can be achieved through symbolic messages (imagery or text) in an advertisement. The present study contributes to this stream of research. From a theoretical standpoint, the study explores differences in literal-symbolic message content in B2B advertisements. There has been much discussion—mainly in the consumer literature—on the ability of symbolic messages to motivate a prospect to process advertising information by necessitating more elaborate processing and comprehension. Business buyers are regarded as less receptive to indirect or implicit appeals because their purchase decisions are based on direct evidence of product superiority. It is argued here, that these same buyers may be equally influenced by advertising that stimulates internally-directed motivation, feelings and cognitions about the brand. Thus far, studies on the effect of literalism and symbolism are fragmented, and few focus on the B2B market. While there have been many studies about the effects of symbolism no adequate scale exists to measure the continuum of literalism-symbolism. Therefore, a first task for this study was to develop such a scale. Following scale development, content analysis of 748 B2B print advertisements was undertaken to investigate whether differences in literalism-symbolism led to higher advertising performance. Variations of time and industry were also measured. From a practical perspective, the results challenge the prevailing B2B practice of relying on literal messages. While definitive support was not established for the use of symbolic message content, literal messages also failed to predict advertising performance. If the ‘fact, benefit laden’ assumption within B2B advertising cannot be supported, then other approaches used in the business-to-consumer (B2C) sector, such as symbolic messages may be also appropriate in business markets. Further research will need to test the potential effects of such messages, thereby building a revised foundation that can help drive advances in B2B advertising. Finally, the study offers a contribution to the growing body of knowledge on symbolism in advertising. While the specific focus of the study relates to B2B advertising, the Literalism-Symbolism scale developed here provides a reliable measure to evaluate literal and symbolic message content in all print advertisements. The value of this scale to advance our understanding about message strategy may be significant in future consumer and business advertising research.

Business service management : understanding business models

One of the prominent topics in Business Service Management is business models for (new) services. Business models are useful for service management and engineering as they provide a broader and more holistic perspective on services. Business models are particularly relevant for service innovation as this requires paying attention to the business models that make new services viable and business model innovation can drive the innovation of new and established services. Before we can have a look at business models for services, we first need to understand what business models are. This is not straight-forward as business models are still not well comprehended and the knowledge about business models is fragmented over different disciplines, such as information systems, strategy, innovation, and entrepreneurship. This whitepaper, ‘Understanding business models,’ introduces readers to business models. This whitepaper contributes to enhancing the understanding of business models, in particular the conceptualisation of business models by discussing and integrating business model definitions, frameworks and archetypes from different disciplines. After reading this whitepaper, the reader will have a well-developed understanding about what business models are and how the concept is sometimes interpreted and used in different ways. It will help the reader in assessing their own understanding of business models and that and of others. This will contribute to a better and more beneficial use of business models, an increase in shared understanding, and making it easier to work with business model techniques and tools.

Characterisation of public mobile data networks for aeronautical telemetry purposes

This paper describes the characterisation for airborne uses of the public mobile data communication systems known broadly as 3G. The motivation for this study was to explore how this mature public communication systems could be used for aviation purposes. An experimental system was fitted to a light aircraft to record communication latency, line speed, RF level, packet loss and cell tower identifier. Communications was established using internet protocols and connection was made to a local server. The aircraft was flown in both remote and populous areas at altitudes up to 8500ft in a region located in South East Queensland, Australia. Results show that the average airborne RF levels are better than those on the ground by 21% and in the order of -77 dbm. Latencies were in the order of 500 ms (1/2 the latency of Iridium), an average download speed of 0.48 Mb/s, average uplink speed of 0.85 Mb/s, a packet of information loss of 6.5%. The maximum communication range was also observed to be 70km from a single cell station. The paper also describes possible limitations and utility of using such a communications architecture for both manned and unmanned aircraft systems.

Challenges of tracking topical discussion networks online

Attempts to map online networks, representing relationships between people and sites, have covered sites including Facebook, Twitter, and blogs. However, the predominant approach of static network visualization, treating months of data as a single case rather than depicting changes over time or between topics, remains a flawed process. As different events and themes provoke varying interactions and conversations, it is proposed that case-by-case analysis would aid studies of online social networks by further examining the dynamics of links and information flows. This study uses hyperlink analysis of a population of French political blogs to compare connections between sites from January to August 2009. Themes discussed in this period were identified for subsequent analysis of topic-oriented networks. By comparing static blogrolls with topical citations within posts, this research addresses challenges and methods in mapping online networks, providing new information on temporal aspects of linking behaviors and information flows within these systems.

For the better or the worse? The impact of business idea changes on new venture performance and novelty

Should new ventures stick to their knitting once they start commercialising or should they engage in frequent changes of their business idea? In this paper we argue that new ventures still need to learn their way in the early phases of commercialisation and that changes are good, but subject to two important contingencies. First is that changes should be aimed at enhancing uniqueness, which in turn enhances new venture performance. Second is that our results show that changes have limited affect on uniqueness and performance for entrepreneurs aiming at maximising opportunities, but that changing the business idea has a significant positive impact for entrepreneurs focusing on minimising losses. Our findings indicate that entrepreneurs aiming at minimising losses may offset their initial disadvantages by engaging in a series of adaptations of the business idea to gain higher performance and a more unique product offering.

Do programs to improve business performance in small and medium manufacturing enterprise improve opportunity recognition?

Increasing awareness of the benefits of stimulating entrepreneurial behaviour in small and medium enterprises has fostered strong interest in innovation programs. Recently many western countries have invested in design innovation for better firm performance. This research presents some early findings from a study of companies which participated in an holistic approach to design innovation, where the outcomes include better business performance and better market positioning in global markets. Preliminary findings from in-depth semi-structured interviews indicate the importance of firm openness to new ways of working and developing new processes of strategic entrepreneurship. Implications for theory and practice are discussed.

The role of digressive learning and uniqueness on performance : longitudinal evidence from young firms

The ability to differentiate from competitors through the selection of unique offerings is an important cornerstone of competitive performance. Developing unique products and services to offer in the marketplace is not only important for established firms, but also an important strategic choice for young firms (Baum and Haveman, 1997). Unlike large and established firms, young firms tend to have less access to adequate resources, well-developed sources of information, contact networks, and considerable experience and management know-how. That is, these firms differ significantly in their attributes and performance from larger and well-established firms (c.f. Miller and Chen, 1994). Although young firms are disadvantaged by the paucity of resources in putting together its unique product offering(s), they develop different pathways in advancing their assortment of capabilities that enables them to stay ahead of competitors.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Micro-business community responsibility – approaches, motivations and barriers

Micro-businesses, those with fewer than five employees, have a significant impact on the economy. These very small players represent 89% of all Australian businesses and, collectively, they provide 17% of the nation’s private sector employment. They are ubiquitous in Australia as in many other nations, embedded in local communities and therefore well placed to influence community wellbeing. Surprisingly, very little is known about micro-Business Community Responsibility (mBCR), the micro-business equivalent of Small Business Social Responsibility (SBSR) and Corporate Social Responsibility (CSR). Most national data available on business support for community wellbeing does not separately identify micro-business contributions. In this study an exploratory approach informed by business ethics theory was taken. Data from 36 semi-structured interviews was analysed to examine perceived mBCR approaches, motivations and barriers. The sample for this study was a mix of micro-business owner-operators situated in suburban shopping areas in Brisbane. Three types of mBCR emerged. All types are at least partly driven by enlightened selfinterest (ESI). However of the three mBCR types, two combine ESI with other approaches. One type combines ESI and philanthropic approaches to mBCR, and the other combines ESI with social entrepreneurial approaches to mBCR. The combination of doing business and doing good for many micro-business owneroperators, suggests mBCR may be a significant, yet unrecognised component of the third sector social economy.

Intrusion detection framework for encrypted networks

Network-based Intrusion Detection Systems (NIDSs) monitor network traffic for signs of malicious activities that have the potential to disrupt entire network infrastructures and services. NIDS can only operate when the network traffic is available and can be extracted for analysis. However, with the growing use of encrypted networks such as Virtual Private Networks (VPNs) that encrypt and conceal network traffic, a traditional NIDS can no longer access network traffic for analysis. The goal of this research is to address this problem by proposing a detection framework that allows a commercial off-the-shelf NIDS to function normally in a VPN without any modification. One of the features of the proposed framework is that it does not compromise on the confidentiality afforded by the VPN. Our work uses a combination of Shamir’s secret-sharing scheme and randomised network proxies to securely route network traffic to the NIDS for analysis. The detection framework is effective against two general classes of attacks – attacks targeted at the network hosts or attacks targeted at framework itself. We implement the detection framework as a prototype program and evaluate it. Our evaluation shows that the framework does indeed detect these classes of attacks and does not introduce any additional false positives. Despite the increase in network overhead in doing so, the proposed detection framework is able to consistently detect intrusions through encrypted networks.