148 resultados para Empirical analysis


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Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

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In recent years, the value of business planning for new business ventures and small firms has been the subject of debate amongst entrepreneurship researchers (Brinckmann et al 2010: 24). Drawing on institutional theory, a number of writers suggest that business planning is primarily used to confer symbolic legitimacy on businesses seeking investment and engagement from external stakeholders ( Karlsson & Honig 2009; Zimmerman & Zeitz 2002; Delmar & Shane 2004). In this sense, business planning may not have any significant effects on firm learning, but may be used as evidence of good business operations in order to attract external resources. Meta-evaluation of the available empirical literature contests this proposition, finding that both the symbolic and organisational learning effects of business planning influence small firm performance (Brinckmann et al 2010: 36) While social enterprise – which we define as organisations that exist for a public or community benefit and trade to fulfill their mission - the study of social enterprise is a nascent and pre-paradigmatic area of inquiry (Nicholls 2010). As a consequence, there has been relatively little empirical analysis of the nature or effects of business planning amongst social enterprises (for two exceptions, see exploratory studies by Hynes 2009 and Bull & Crompton 2006). In this paper, we examine business planning practices amongst Australian social enterprises. Drawing on a survey of 365 social enterprises conducted in 2010 and in-depth interviews with 11 social entrepreneurs and managers from eight social enterprises, we find that social enterprises report being more actively engaged in business planning activities than their mainstream business counterparts. Our exploratory research suggests that both legitimacy and learning drive business planning amongst social enterprises, although legitimacy is the stronger driver. Our results also suggest that, as multi-stakeholder businesses led by mission, business planning can serve unique communicative and relational functions for this business type.

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Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

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Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

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Nowadays, everyone can effortlessly access a range of information on the World Wide Web (WWW). As information resources on the web continue to grow tremendously, it becomes progressively more difficult to meet high expectations of users and find relevant information. Although existing search engine technologies can find valuable information, however, they suffer from the problems of information overload and information mismatch. This paper presents a hybrid Web Information Retrieval approach allowing personalised search using ontology, user profile and collaborative filtering. This approach finds the context of user query with least user’s involvement, using ontology. Simultaneously, this approach uses time-based automatic user profile updating with user’s changing behaviour. Subsequently, this approach uses recommendations from similar users using collaborative filtering technique. The proposed method is evaluated with the FIRE 2010 dataset and manually generated dataset. Empirical analysis reveals that Precision, Recall and F-Score of most of the queries for many users are improved with proposed method.

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The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.

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In response to international awareness of environmental issues and the inadequacies of common law actions, legislation has been enacted by Australian governments to facilitate environmental protection. The Environmental Protection Act 1994 (Qld) and accompanying Environmental Protection (Interim) Regulation 1995 (Qld) is one example of government response to mounting public pressure to legislate for the environment. Investigation into the operation of the legislation exposes the costs faced by Australian firms in its application. The legislation identifies a number of environmentally relevant activities and imposes licensing and reporting requirements on firms undertaking such activities. In view of these legislative requirements and the increasing public awareness of environmental issues over the last decade in Australia, it could be expected that firms undertaking environmentally sensitive activities will place greater importance on the management of environmental issues. If so, the greater prominence placed on environmental management may be reflected in disclosures made by the firm to its shareholders and other interested parties. This article investigates the type and extent of costs currently imposed by the body of environmental laws in Australia with the discussion primarily focusing upon costs imposed due to the operation of environmental legislation in Queensland. Further, the article reports empirical analysis of management response to environmental issues where firms are undertaking environmentally sensitive activities.

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Micro and small businesses contribute the majority of business activity in most developed economies. They are typically embedded in local communities and therefore well placed to influence community wellbeing. While there has been considerable theoretical and empirical analysis of corporate citizenship and corporate social responsibility (CSR), the nature of micro-business community responsibility (mBCR) remains relatively under-explored. This article presents findings from an exploratory study of mBCR that examined the approaches, motivations and barriers of this phenomenon. Analysis of data from 36 semi structured interviews with micro-business owner-operators in the Australian city of Brisbane revealed three mBCR approaches, suggesting an observable mBCR typology. Each mBCR type was at least partly driven by enlightened self interest (ESI). In addition to a pure ESI approach, findings revealed ESI combined with philanthropic approaches and ESI combined with social entrepreneurial approaches. The combination of doing business and doing good found amongst participants in this study suggests that many micro-business owner-operators are supporters of their local communities, and therefore driven by more than profit. This study provides a fine-grained understanding of micro-business involvement in community wellbeing through a lens of responsible business behaviour.

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Baron von Richthofen (the Red Baron) arguably the most famous fighter pilot of all time painted his plane the vividest of red hues, making it visible and identifiable at great distance, showing an aggressive pronouncement of dominance to other pilots. Can colour affect aggression and performance and if so is it observable within team sports? This study explores the effect of red on sporting performances within a team sports arena, through empirical analysis of match results from the Australian Rugby League spanning a period of 30 years. Both the descriptive analysis and the multivariate analysis report a positive relationship. Nevertheless, more evidence is required to better understand whether teams in red do enjoy greater success controlling explicitly in a multivariate analysis for many factors that simultaneously affect performance.

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Entity-oriented search has become an essential component of modern search engines. It focuses on retrieving a list of entities or information about the specific entities instead of documents. In this paper, we study the problem of finding entity related information, referred to as attribute-value pairs, that play a significant role in searching target entities. We propose a novel decomposition framework combining reduced relations and the discriminative model, Conditional Random Field (CRF), for automatically finding entity-related attribute-value pairs from free text documents. This decomposition framework allows us to locate potential text fragments and identify the hidden semantics, in the form of attribute-value pairs for user queries. Empirical analysis shows that the decomposition framework outperforms pattern-based approaches due to its capability of effective integration of syntactic and semantic features.

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Online social networks can be modelled as graphs; in this paper, we analyze the use of graph metrics for identifying users with anomalous relationships to other users. A framework is proposed for analyzing the effectiveness of various graph theoretic properties such as the number of neighbouring nodes and edges, betweenness centrality, and community cohesiveness in detecting anomalous users. Experimental results on real-world data collected from online social networks show that the majority of users typically have friends who are friends themselves, whereas anomalous users’ graphs typically do not follow this common rule. Empirical analysis also shows that the relationship between average betweenness centrality and edges identifies anomalies more accurately than other approaches.

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Purpose – Integrated supplier management (ISM), new product development (NPD) and knowledge sharing (KS) practices are three primary business activities utilised to enhance manufacturers' business performance (BP). The purpose of this paper is to empirically investigate the relationships between these three business activities (i.e. ISM, NPD, KS) and BP in a Taiwanese electronics manufacturing context. Design/methodology/approach – A questionnaire survey is first administered to a sample of electronic manufacturing companies operating in Taiwan to elicit the opinions of technical and managerial professionals regarding business activities and BP within their companies. A total of 170 respondents from 83 companies respond to the survey. Factor, correlation and path analysis are undertaken on this quantitative data set to derive the key factors which leverage business outcomes in these companies. Following empirical analysis, six semi-structured interviews are undertaken with manufacturing executives to provide qualitative insights into the underlying reasons why certain business activity factors are the strongest predictors of BP. Findings – The investigation shows that the ISM, NPD and KS constructs all play an important role in the success of company operations and creating business outcomes. Specifically, the key factors within these constructs which influenced BP are: supplier evaluation and selection; design simplification and modular design; information technology infrastructure and systems and open communication. Accordingly, sufficient financial and human resources should be allocated to these important activities to derive accelerated rates of improved BP. These findings are supported by the qualitative interviews with manufacturing executives. Originality/value – The paper depicts the pathways to improved manufacturing BP, through targeting efforts into the above-mentioned factors within the ISM, NPD and KS constructs. Based on the empirical path model, and the specific insights derived from the explanatory interviews with manufacturing executives, the paper also provides a number of practical implications for manufacturing companies seeking to enhance their BP through improved operational activities.

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Purpose – Business process management (BPM) requires a holistic perspective that includes managing the culture of an organization to achieve objectives of efficient and effective business processes. Still, the specifics of a BPM-supportive organizational culture have not been examined so far. Thus, the purpose of this paper is to identify the characteristics of a cultural setting supportive of BPM objectives. Design/methodology/approach – The paper examines the constituent values of a BPM-supportive cultural setting through a global Delphi study with BPM experts from academia and practice and explore these values in a cultural value framework. Findings – The paper empirically identifies and defines four key cultural values supporting BPM, viz., customer orientation, excellence, responsibility, and teamwork. The paper discusses the relationships between these values and identifies a particular challenge in managing these seemingly competing values. Research limitations/implications – The identification and definition of these values represents a first step towards the operationalization (and empirical analysis) of what has been identified as the concept of BPM culture, i.e. a culture supportive of achieving BPM objectives. Practical implications – Identifying these cultural values provides the basis for developing an instrument that can measure how far an existing cultural context is supportive of BPM. This, in turn, is fundamental for identifying measures towards achieving a BPM culture as a necessary, yet not sufficient means to obtain BPM success. Originality/value – The paper examines which cultural values create an environment receptive for BPM and, thus, specifies the important theoretical construct BPM culture. In addition, the paper raises awareness for realizing these values in a BPM context.

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Australian airports have emerged as important urban activity centres over the past decade as a result of privatisation. A range of reciprocal airport and regional impacts now pose considerable challenges for both airport operation and the surrounding urban and regional environment. The airport can no longer be managed solely as a specialised transport entity in isolation from the metropolis that it serves. In 2007 a multidisciplinary Australian Research Council Linkage Project (LP 0775225) was funded to investigate the changing role of airports in Australia. This thesis is but one component of this collaborative research effort. Here the issues surrounding the policy and practice of airport and regional land use planning are explored, analysed and detailed. This research, for the first time, assembles a distinct progression of the wider social, economic, technological and environmental roles of the airport within the Australian airport literature from 1914 – 2011. It recognises that while the list of airport and regional impacts has grown through time, treatment within practice and the literature has largely remained highly specialised and contained within disciplinary paradigms. The first publication of the thesis (Chapter 2) acknowledges that the changing role of airports demands the establishment of new models of airport planning and development. It argues that practice and research requires a better understanding of the reciprocal impacts of airports and their urban catchments. The second publication (Chapter 3) highlights that there is ad hoc examination and media attention of high profile airport and regional conflict, but little empirical analysis or understanding of the extent to which all privatised Australian airports are intending to develop. The conceptual and methodological significance of this research is the development of a national land use classification system for on-airport development. This paper establishes the extent of on-airport development in Australia, providing insight into the changing land use and economic roles of privatised airports. The third publication (Chapter 4) details new and significant interdependencies for airport and regional development in consideration of the progression of airports as activity centres. Here the model of an ‘airport metropolis’ is offered as an organising device and theoretical contribution for comprehending the complexity and planning of airport and regional development. It delivers a conceptual framework for both research and policy, which acknowledges the reciprocal impacts of economic development, land use, infrastructure and governance ‘interfaces’. In a timely and significant concurrence with this research the Australian Government announced and delivered a National Aviation Policy Review (2008 – 2009). As such the fourth publication (Chapter 5) focuses on the airport and urban planning aspects of the review. This paper also highlights the overall policy intention of facilitating broader airport and regional collaborative processes. This communicative turn in airport policy is significant in light of the communicative theoretical framework of the thesis. The fifth paper of the thesis (Chapter 6) examines three Australian case studies (Brisbane, Adelaide and Canberra) to detail the context of airport and regional land use planning and to apply the airport metropolis model as a framework for research. Through the use of Land Use Forums, over 120 airport and regional stakeholders are brought together to detail their perspectives and interactions with airport and regional land use planning. An inductive thematic analysis of the results identifies three significant themes which contribute to the fragmentation of airport and regional and land use planning: 1) inadequate coordination and disjointed decision-making; 2) current legislative and policy frameworks; and 3) competing stakeholder priorities and interests. Building on this new knowledge, Chapter 7 details the perceptions of airport and local, state and territory government stakeholders to land use relationships, processes and outcomes. A series of semi-structured interviews are undertaken in each of the case studies to inform this research. The potential implications for ongoing communicative practice are discussed in conclusion. The following thesis represents an incremental and cumulative research process which delivers new knowledge for the practical understanding and research interpretation of airport and regional land use planning practice and policy. It has developed and applied a robust conceptual framework which delivers significant direction for all stakeholders to better comprehend the relevance of airports in the urban character and design of our cities.

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This thesis improves the process of recommending people to people in social networks using new clustering algorithms and ranking methods. The proposed system and methods are evaluated on the data collected from a real life social network. The empirical analysis of this research confirms that the proposed system and methods achieved improvements in the accuracy and efficiency of matching and recommending people, and overcome some of the problems that social matching systems usually suffer.