Information organisation behaviours within everyday life : an exploration using the diary method

This paper presents the results from a study of information behaviours (IB), with specific focus on information- organisation-related behaviours conducted as part of a larger daily diary study with 40 participants. The findings indicate that organisation of information in everyday life is problematic due to various factors, specifically temporal and spatial ones, i.e., the passage of time, along with the difference in the physical environment between when the information was organised and when the information is retrieved. These have implications for information organisation schemas, and point toward the need for a context-sensitive model of information organisation that reflects the relation between information objects, information representation, and information users.

User expertise in contemporary information systems : conceptualization, measurement and application

This research proposes a method for identifying user expertise in contemporary Information Systems (IS). It also proposes and develops a model for evaluating expertise. The aim of this study was to offer a common instrument that addresses the requirements of a contemporary Information System in a holistic way. This study demonstrates the application of the expertise construct in Information System evaluations, and shows that users of different expertise levels evaluate systems differently.

Vision-based estimation of airborne target pseudobearing rate using hidden Markov model filters

The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information.

Can emotion provide a new approach to business model innovation?

Companies require new strategies to drive growth and survival, as the fast pace of change has created the need for greater business flexibility. Therefore, industry leaders are looking to business innovation as a principle source of differentiation and competitive advantage. However, most companies rely heavily on either technology or products to provide business innovation, yet competitors can easily and rapidly surpass these forms of innovation. Business model innovation expands beyond innovation in isolated areas, such as product innovation, to create strategies that incorporate many business avenues to work together to create and deliver value to its customers. Existing literature highlights that a business model’s central role is ‘customer value’. However, the emotional underpinnings of customer value within a business model are not well understood. The integration of customer emotion into business model design and value chain can be viewed as a way to innovate beyond just products, services and processes. This paper investigates the emotional avenues within business strategy and operations, business model innovation and customer engagement. Three propositions are outlined and explored as future research. The significance of this research is to provide companies with a new approach to innovation through a deeper understanding and integration of their customers’ emotions.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Storyboard augmentation of process model grammars for stakeholder communication

Process models are often used to visualize and communicate workflows to involved stakeholders. Unfortunately, process modeling notations can be complex and need specific knowledge to be understood. Storyboards, as a visual language to illustrate workflows as sequences of images, provide natural visualization features that allow for better communication, to provide insight to people from non-process modelling expert domains. This paper proposes a visualization approach using a 3D virtual world environment to visualize storyboards for business process models. A prototype was built to present its applicability via generating output with examples of five major process model patterns and two non-trivial use cases. Illustrative results for the approach show the promise of using a 3D virtual world to visualize complex process models in an unambiguous and intuitive manner.

Understanding and measuring information security culture in developing countries : case of Saudi Arabia

The purpose of the current study was to develop a measurement of information security culture in developing countries such as Saudi Arabia. In order to achieve this goal, the study commenced with a comprehensive review of the literature, the outcome being the development of a conceptual model as a reference base. The literature review revealed a lack of academic and professional research into information security culture in developing countries and more specifically in Saudi Arabia. Given the increasing importance and significant investment developing countries are making in information technology, there is a clear need to investigate information security culture from developing countries perspective such as Saudi Arabia. Furthermore, our analysis indicated a lack of clear conceptualization and distinction between factors that constitute information security culture and factors that influence information security culture. Our research aims to fill this gap by developing and validating a measurement model of information security culture, as well as developing initial understanding of factors that influence security culture. A sequential mixed method consisting of a qualitative phase to explore the conceptualisation of information security culture, and a quantitative phase to validate the model is adopted for this research. In the qualitative phase, eight interviews with information security experts in eight different Saudi organisations were conducted, revealing that security culture can be constituted as reflection of security awareness, security compliance and security ownership. Additionally, the qualitative interviews have revealed that factors that influence security culture are top management involvement, policy enforcement, policy maintenance, training and ethical conduct policies. These factors were confirmed by the literature review as being critical and important for the creation of security culture and formed the basis for our initial information security culture model, which was operationalised and tested in different Saudi Arabian organisations. Using data from two hundred and fifty-four valid responses, we demonstrated the validity and reliability of the information security culture model through Exploratory Factor Analysis (EFA), followed by Confirmatory Factor Analysis (CFA.) In addition, using Structural Equation Modelling (SEM) we were further able to demonstrate the validity of the model in a nomological net, as well as provide some preliminary findings on the factors that influence information security culture. The current study contributes to the existing body of knowledge in two major ways: firstly, it develops an information security culture measurement model; secondly, it presents empirical evidence for the nomological validity for the security culture measurement model and discovery of factors that influence information security culture. The current study also indicates possible future related research needs.

"You’ve modelled and now what?" : Exploring determinants of process model re-use

Business process modelling as a practice and research field has received great attention over recent years. Organizations invest significantly into process modelling in terms of training, tools, capabilities and resources. The return on this investment is a function of process model re-use, which we define as the recurring use of process models to support organizational work tasks. While prior research has examined re-use as a design principle, we explore re-use as a behaviour, because evidence suggest that analysts’ re-use of process models is indeed limited. In this paper we develop a two-stage conceptualization of the key object-, behaviour- and socioorganization-centric factors explaining process model re-use behaviour. We propose a theoretical model and detail implications for its operationalization and measurement. Our study can provide significant benefits to our understanding of process modelling and process model use as key practices in analysis and design.

A novel method for finding similarities between unordered trees using matrix data model

Trees are capable of portraying the semi-structured data which is common in web domain. Finding similarities between trees is mandatory for several applications that deal with semi-structured data. Existing similarity methods examine a pair of trees by comparing through nodes and paths of two trees, and find the similarity between them. However, these methods provide unfavorable results for unordered tree data and result in yielding NP-hard or MAX-SNP hard complexity. In this paper, we present a novel method that encodes a tree with an optimal traversing approach first, and then, utilizes it to model the tree with its equivalent matrix representation for finding similarity between unordered trees efficiently. Empirical analysis shows that the proposed method is able to achieve high accuracy even on the large data sets.

A biological staging model for operable non-small cell lung cancer

Background Currently the best prognostic index for operable non-small cell lung cancer (NSCLC) is the TNM staging system. Molecular biology holds the promise of predicting outcome for the individual patient and identifying novel therapeutic targets. Angiogenesis, matrix metalloproteinases (MMP)-2 and -9, and the erb/HER type I tyrosine kinase receptors are all implicated in the pathogenesis of NSCLC. Methods A retrospective analysis of 167 patients with resected stage I-IIIa NSCLC and >60 days postoperative survival with a minimum follow up of 2 years was undertaken. Immunohistochemical analysis was performed on paraffin embedded sections for the microvessel marker CD34, MMP-2 and MMP-9, EGFR, and c-erbB-2 to evaluate the relationships between and impact on survival of these molecular markers. Results Tumour cell MMP-9 (HR 1.91 (1.23-2.97)), a high microvessel count (HR 1.97 (1.28-3.03)), and stage (stage II HR 1.44 (0.87-2.40), stage IIIa HR 2.21 (1.31-3.74)) were independent prognostic factors. Patients with a high microvessel count and tumour cell MMP-9 expression had a worse outcome than cases with only one (HR 1.68 (1.04-2.73)) or neither (HR 4.43 (2.29-8.57)) of these markers. EGFR expression correlated with tumour cell MMP-9 expression (p<0.001). Immunoreactivity for both of these factors within the same tumour was associated with a poor prognosis (HR 2.22 (1.45-3.41)). Conclusion Angiogenesis, EGFR, and MMP-9 expression provide prognostic information independent of TNM stage, allowing a more accurate outcome prediction for the individual patient. The development of novel anti-angiogenic agents, EGFR targeted therapies, and MMP inhibitors suggests that target specific adjuvant treatments may become a therapeutic option in patients with resected NSCLC.

A Procedural Model for Ontological Analyses

In recent years, there has been a significant increase in the popularity of ontological analysis of conceptual modelling techniques. To date, related research explores the ontological deficiencies of classical techniques such as ER or UML modelling, as well as business process modelling techniques such as ARIS or even Web Services standards such as BPEL4WS, BPML, ebXML, BPSS and WSCI. While the ontologies that form the basis of these analyses are reasonably mature, it is the actual process of an ontological analysis that still lacks rigour. The current procedure is prone to individual interpretations and is one reason for criticism of the entire ontological analysis. This paper presents a procedural model for ontological analysis based on the use of meta models, multiple coders and metrics. The model is supported by examples from various ontological analyses.

Enterprise social networks : a business model perspective

Enterprise Social Networks continue to be adopted by organisations looking to increase collaboration between employees, customers and industry partners. Offering a varied range of features and functionality, this technology can be distinguished by the underlying business models that providers of this software deploy. This study identifies and describes the different business models through an analysis of leading Enterprise Social Networks: Yammer, Chatter, SharePoint, Connections, Jive, Facebook and Twitter. A key contribution of this research is the identification of consumer and corporate models as extreme approaches. These findings align well with research on the adoption of Enterprise Social Networks that has discussed bottom-up and top-down approaches. Of specific interest are hybrid models that wrap a corporate model within a consumer model and may, therefore, provide synergies on both models. From a broader perspective, this can be seen as the merging of the corporate and consumer markets for IT products and services.

Service-oriented architecture integration within enterprise architecture : a-priori model

This paper proposes that critical realism can provide a useful theoretical foundation to study enterprise architecture (EA) evolution. Specifically it will investigate the practically relevant and academically challenging question of how EAs integrate the Service-oriented Architecture (SOA). Archer’s Morphogenetic theory is used as an analytical approach to distinguish the architectural conditions under which SOA is introduced, to study the relationships between these conditions and SOA introduction, and to reflect on EA evolution (elaborations) that then take place. The focus lies on the reasons why EA evolution takes place (or not) and what architectural changes happen. This paper uses the findings of a literature review to build an a-priori model informed by Archer’s theory to understand EA evolution in a field that often lacks a solid theoretical groundwork. The findings are threefold. First, EA can evolve on different levels (different integration outcomes). Second, the integration outcomes are classified into three levels: business architecture, information systems architecture and technology architecture. Third, the analytical separation using Archer’s theory is helpful in order to understand how these different integration outcomes are generated.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

Process model comprehension : the effects of cognitive abilities, learning style, and strategy

Process models are used to convey semantics about business operations that are to be supported by an information system. A wide variety of professionals is targeted to use such models, including people who have little modeling or domain expertise. We identify important user characteristics that influence the comprehension of process models. Through a free simulation experiment, we provide evidence that selected cognitive abilities, learning style, and learning strategy influence the development of process model comprehension. These insights draw attention to the importance of research that views process model comprehension as an emergent learning process rather than as an attribute of the models as objects. Based on our findings, we identify a set of organizational intervention strategies that can lead to more successful process modeling workshops.