996 resultados para Business records


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This series of research vignettes is aimed at sharing current and interesting research findings from our team of international Entrepreneurship researchers. This vignette, written by Professor Beth Webster at Swinburne University of Technology, examines how innovation in small and medium size businesses affect their productivity.

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This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

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Big data analysis in healthcare sector is still in its early stages when comparing with that of other business sectors due to numerous reasons. Accommodating the volume, velocity and variety of healthcare data Identifying platforms that examine data from multiple sources, such as clinical records, genomic data, financial systems, and administrative systems Electronic Health Record (EHR) is a key information resource for big data analysis and is also composed of varied co-created values. Successful integration and crossing of different subfields of healthcare data such as biomedical informatics and health informatics could lead to huge improvement for the end users of the health care system, i.e. the patients.

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Australia is a leading user of collaborative procurement methods, which are used to deliver large and complex infrastructure projects. Project alliances, Early Contractor Involvement (ECI), and partnering are typical examples of collaborative procurement models. In order to increase procurement effectiveness and value for money (VfM), clients have adopted various learning strategies for new contract development. However client learning strategies and behaviours have not been systematically analysed before. Therefore, the current paper undertakes a literature review addressing the research question “How can client learning capabilities be effectively understood?”. From the resource-based and dynamic capability perspectives, this paper proposes that the collaborative learning capability (CLC) of clients drives procurement model evolution. Learning routines underpinning CLC carry out exploratory, transformative and exploitative learning phases associated with collaborative project delivery. This learning improves operating routines, and ultimately performance. The conceptualization of CLC and the three sequential learning phases is used to analyse the evidence in the construction management literature. The main contribution of this study is the presentation of a theoretical foundation for future empirical studies to unveil effective learning strategies, which help clients to improve the performance of collaborative projects in the dynamic infrastructure market.

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The concept of big data has already outperformed traditional data management efforts in almost all industries. Other instances it has succeeded in obtaining promising results that provide value from large-scale integration and analysis of heterogeneous data sources for example Genomic and proteomic information. Big data analytics have become increasingly important in describing the data sets and analytical techniques in software applications that are so large and complex due to its significant advantages including better business decisions, cost reduction and delivery of new product and services [1]. In a similar context, the health community has experienced not only more complex and large data content, but also information systems that contain a large number of data sources with interrelated and interconnected data attributes. That have resulted in challenging, and highly dynamic environments leading to creation of big data with its enumerate complexities, for instant sharing of information with the expected security requirements of stakeholders. When comparing big data analysis with other sectors, the health sector is still in its early stages. Key challenges include accommodating the volume, velocity and variety of healthcare data with the current deluge of exponential growth. Given the complexity of big data, it is understood that while data storage and accessibility are technically manageable, the implementation of Information Accountability measures to healthcare big data might be a practical solution in support of information security, privacy and traceability measures. Transparency is one important measure that can demonstrate integrity which is a vital factor in the healthcare service. Clarity about performance expectations is considered to be another Information Accountability measure which is necessary to avoid data ambiguity and controversy about interpretation and finally, liability [2]. According to current studies [3] Electronic Health Records (EHR) are key information resources for big data analysis and is also composed of varied co-created values [3]. Common healthcare information originates from and is used by different actors and groups that facilitate understanding of the relationship for other data sources. Consequently, healthcare services often serve as an integrated service bundle. Although a critical requirement in healthcare services and analytics, it is difficult to find a comprehensive set of guidelines to adopt EHR to fulfil the big data analysis requirements. Therefore as a remedy, this research work focus on a systematic approach containing comprehensive guidelines with the accurate data that must be provided to apply and evaluate big data analysis until the necessary decision making requirements are fulfilled to improve quality of healthcare services. Hence, we believe that this approach would subsequently improve quality of life.

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The paper hand-held record (PHR) has been used extensively in general practice (GP) shared care management of pregnant women, and recently, the first Mater Shared Electronic Health Record (MSEHR) was introduced. The aim of this qualitative study was to examine women’s experiences using the records and the contribution of the records to integrate care. At the 36-week antenatal visit in a maternity tertiary centre clinic, women were identified as a user of either the PHR or the MSEHR and organised into Phase 1 and Phase 2 studies respectively. Fifteen women were interviewed in Phase 1 and 12 women in Phase 2. Semi-structured interviews were used for data collection, and analysed using qualitative content analysis. Four main themes were identified: (1) purpose of the record; (2) perceptions of the record; (3) content of the record, and; (4) sharing the record. Findings indicate that the PHR is a well-liked maternity tool. The findings also indicate there is under-usage of the MSEHR due to health-care providers failing to follow up and discuss the option of using the electronic health record option or if a woman has completed the log-in process. This paper adds to an already favourable body of knowledge about the use of the PHR. It is recommended that continued implementation of the MSEHR be undertaken to facilitate its use.

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Designers have become aware of the importance of creating strong emotional experiences intertwined with new tangible products for the past decade, however an increased interest from firms has emerged in developing new service and business models as complimentary forms of emotion-driven innovation. This interdisciplinary study draws from the psychological sciences – theory of emotion – and the management sciences – business model literature to introduce this new innovation agenda. The term visceral hedonic rhetoric (VHR) is defined as the properties of a product, (and in this paper service and business model extensions) that persuasively induce the pursuit of pleasure at an instinctual level of cognition. This research paper lays the foundation for VHR beyond a product setting, presenting the results from an empirical study where organizations explored the possibilities for VHR in the context of their business. The results found that firms currently believe VHR is perceived in either their product and/or services they provide. Implications suggest shifting perspective surrounding the use of VHR across a firm’s business model design in order to influence the outcomes of their product and/or service design, resulting in an overall stronger emotional connection with the customer.

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The rapid increase in migration into host countries and the growth of immigrant-owned business enterprises has revitalized research on ethnic business. Does micro (individual)-level social capital, or meso (group)-level location within the ethnic enclave lead to immigrant business growth? Or do you need both? We analyze quantitative data collected from 110 Chinese restaurants in Australia, a major host country. At the micro level we find that coethnic (same ethnic group) networks are critical to the growth of an immigrant entrepreneur's business, particularly in the early years. But non-coethnic (different ethnic group) social capital only has a positive impact on business growth for immigrant businesses outside the ethnic enclave. Our findings are relevant, not only to host-country policymakers, but also for future immigrant business owners and ethnic community leaders trying to better understand how to promote healthy communities and sustainable economic growth.

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The business value of IT (BVIT) has been a prominent and central research topic in the IS discipline. Due to continuous and unpredictable technology and business changes, a more dynamic perspective on IT business value that includes organizational learning is required. We suggest that simple rules heuristics can address this challenge. The simple rules heuristics approach has been introduced by Eisenhardt and co-authors (Bingham & Eisenhardt, 2011; Bingham, Eisenhardt, & Furr, 2007; Eisenhardt & Sull, 2001) to better understand strategic decision making for capturing superabundant, heterogeneous, fastmoving opportunities. They argue that explicit organizational learning can translate accumulated experience into increasingly effective heuristics for strategic processes in highvelocity environments. We make three main contributions by exploring the suitability of a simple rules heuristics approach for the creation of IT business value: (1) we propose six types of simple rules heuristics for capturing IT-based opportunities in dynamic environments, including synergy heuristics as specifically relevant in an IT context, (2) we show how a simple rules heuristics approach can advance our understanding of dynamics and organizational learning for BVIT, and; (3) we introduce the strategic logic of opportunity to BVIT.

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Previous qualitative research has highlighted that temporality plays an important role in relevance for clinical records search. In this study, an investigation is undertaken to determine the effect that the timespan of events within a patient record has on relevance in a retrieval scenario. In addition, based on the standard practise of document length normalisation, a document timespan normalisation model that specifically accounts for timespans is proposed. Initial analysis revealed that in general relevant patient records tended to cover a longer timespan of events than non-relevant patient records. However, an empirical evaluation using the TREC Medical Records track supports the opposite view that shorter documents (in terms of timespan) are better for retrieval. These findings highlight that the role of temporality in relevance is complex and how to effectively deal with temporality within a retrieval scenario remains an open question.

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Since their inception in 1962, Petri nets have been used in a wide variety of application domains. Although Petri nets are graphical and easy to understand, they have formal semantics and allow for analysis techniques ranging from model checking and structural analysis to process mining and performance analysis. Over time Petri nets emerged as a solid foundation for Business Process Management (BPM) research. The BPM discipline develops methods, techniques, and tools to support the design, enactment, management, and analysis of operational business processes. Mainstream business process modeling notations and workflow management systems are using token-based semantics borrowed from Petri nets. Moreover, state-of-the-art BPM analysis techniques are using Petri nets as an internal representation. Users of BPM methods and tools are often not aware of this. This paper aims to unveil the seminal role of Petri nets in BPM.

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This thesis provides two main contributions. The first one is BP-TRBAC, a unified authorisation model that can support legacy systems as well as business process systems. BP-TRBAC supports specific features that are required by business process environments. BP-TRBAC is designed to be used as an independent enterprise-wide authorisation model, rather than having it as part of the workflow system. It is designed to be the main authorisation model for an organisation. The second contribution is BP-XACML, an authorisation policy language that is designed to represent BPM authorisation policies for business processes. The contribution also includes a policy model for BP-XACML. Using BP-TRBAC as an authorisation model together with BP-XACML as an authorisation policy language will allow an organisation to manage and control authorisation requests from workflow systems and other legacy systems.

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In this chapter, we explore the 'darker' faces of international business (IB). Over a decade ago, Eden and Len way (2001) raised the need for examining both the 'bright' and the 'dark' side of globalization in order to achieve a better understanding of the concept and of its impact on IB activities. In doing this, they posited the multinational enterprise (MNE) as the 'key agent' and 'f.1ee' of globalization and discussed, primarily, the relationship between MNEs and nation-states as the central interf.1ce of its impact. Additionally, they posited that, by and large, the community of IB scholars positioned themselves at the bright end of the globalization spectrum, seeing it as essentially positive, whilst most non-governmental organizations (NGOs) and international political economy (IPE) academics set themselves at the dark end. Whilst they acknowledged their own 'bright side' tendencies, they called for a more nuanced consideration of MNEs as what they referred to as the Janus bee' of globalization.

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Over the past fifteen years the music industry has experienced a disruptive process of digital transformation that has reshaped most aspects of the industry; in 2015 the contours of a “new music economy” have begun to emerge. The structure and mechanics of these evolutionary processes vary considerably between continents, and this book examines these processes within Europe, America and Asia. The contributors offer a range of theoretical perspectives, as well as empirical findings from the social sciences and business, as well as the media industries. They offer a holistic understanding of the forces shaping the new music economy, and shed some light on the impact of these forces on the ways in which music is created, aggregated and distributed, and on the economic and social consequences for industry producers and consumers.

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This paper explores consumer behavioural patterns on a magazine website. By using a unique dataset of real-life click stream data from 295 magazine website visitors, interesting behavioural patterns are noted: most importantly, 86 % of all sessions only visit the blogs hosted by the magazine. This means that the visitors short-circuit the start page and are not exposed to any editorial content at all, and consequently not to any commercial content on those pages. Sessions visiting editorial content, commercial content or social media links actually represent only one (1) per cent or less of all sessions recorded. Consequently, the online platform gives very limited support for the business model. Our data questions the general assumption that online platforms are key components of a contemporary magazine’s business model.