972 resultados para Business Groups


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Remote networked collaboration with business model documentation has many communication problems. The aim of this project is to solve some of these communication problems by using digital 3D representations of human visual cues. Results from this project increased our understanding of the role and effects of visual cues in remote collaboration, specifically for validating business process models. Technology designs to support such cues across a distance have been proposed in this thesis with qualitative and quantitative methods of analysis being combined to analyse the impact of these cues on the communication, coordination and performance of a team collaborating remotely.

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Purpose The purpose of this paper is to explore the contribution of global business services to improved productivity and economic growth of the world economy, which has gone largely unnoticed in service research. Design/methodology/approach The authors draw on macroeconomic data and industry reports, and link them to the non-ownership-concept in service research and theories of the firm. Findings Business services explain a large share of the growth of the global service economy. The fast growth of business services coincides with shifts from domestic production towards global outsourcing of services. A new wave of global business services are traded across borders and have emerged as important drivers of growth in the world’s service sector. Research limitations/implications This paper advances the understanding of non-ownership services in an increasingly global and specialized post-industrial economy. The paper makes a conceptual contribution supported by descriptive data, but without empirical testing. Originality/value The authors integrate the non-ownership concept and three related economic theories of the firm to explain the role of global business services in driving business performance and the international transformation of service economies.

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This paper outlines an approach for teaching Marketing Principles in an MBA course through service-learning to enable adult learners to connect the lectures’ marketing content to a real-world marketing project. During the course, 40 students in groups of four to five individuals were involved in eight different client-sponsored marketing projects executed simultaneously. The rationale, planning and management of this approach utilised current research on service-learning, living cases and client-sponsored projects in marketing education. The experimental curriculum design is presented in a timeline that mirrors the preparation and management of the group projects and the considerations to be taken into account when initiating and facilitating the projects. Reflections from this iteration of the service-learning design suggest the importance of: detailed project planning, the involvement of students in choosing the projects, the introduction of forms and feedback loops, the role of the instructor in facilitating the students and managing expectations, and the role of the company representative in supporting the groups.

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Purpose The purpose of this paper is to explore the concept of service quality for settings where several customers are involved in the joint creation and consumption of a service. The approach is to provide first insights into the implications of a simultaneous multi‐customer integration on service quality. Design/methodology/approach This conceptual paper undertakes a thorough review of the relevant literature before developing a conceptual model regarding service co‐creation and service quality in customer groups. Findings Group service encounters must be set up carefully to account for the dynamics (social activity) in a customer group and skill set and capabilities (task activity) of each of the individual participants involved in a group service experience. Research limitations/implications Future research should undertake empirical studies to validate and/or modify the suggested model presented in this contribution. Practical implications Managers of service firms should be made aware of the implications and the underlying factors of group services in order to create and manage a group experience successfully. Particular attention should be given to those factors that can be influenced by service providers in managing encounters with multiple customers. Originality/value This article introduces a new conceptual approach for service encounters with groups of customers in a proposed service quality model. In particular, the paper focuses on integrating the impact of customers' co‐creation activities on service quality in a multiple‐actor model.

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Although Human papillomavirus (HPV) is a common sexually transmitted infection, there is limited knowledge of HPV with ethnic/racial minorities experiencing the greatest disparities. This cross-sectional study used the most recent available data from the California Health Interview Survey to assess disparities in awareness and knowledge of HPV among ethnically/racially diverse women varying in generation status (N = 19,928). Generation status emerged as a significant predictor of HPV awareness across ethnic/racial groups, with 1st generation Asian-Americans and 1st and 2nd generation Latinas reporting the least awareness when compared to same-generation White counterparts. Also, generation status was a significant predictor of HPV knowledge, but only for Asian-Americans. Regardless of ethnicity/race, 1st generation women reported lowest HPV knowledge when compared to 2nd and 3rd generation women. These findings underscore the importance of looking at differences within and across ethnic/racial groups to identify subgroups at greatest risk for poor health outcomes. In particular, we found generation status to be an important yet often overlooked factor in the identification of health disparities.

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In this paper we illustrate a set of features of the Apromore process model repository for analyzing business process variants. Two types of analysis are provided: one is static and based on differences on the process control flow, the other is dynamic and based on differences in the process behavior between the variants. These features combine techniques for the management of large process model collections with those for mining process knowledge from process execution logs. The tool demonstration will be useful for researchers and practitioners working on large process model collections and process execution logs, and specifically for those with an interest in understanding, managing and consolidating business process variants both within and across organizational boundaries.

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BPM 2015 was the 13th International Conference on Business Process Management. It provided a global forum for researchers to meet and exchange views over research topics and outcomes in business process management. BPM 2015 was hosted by the University of Innsbruck and took place August 31 to September 3.

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Social enterprise is important. Yet, there has been diverse understanding of the phenomenon in the literature. This paper attempts to make sense of the social enterprise phenomenon in the literature from a two-layer framework of two-by-two matrices. The first layer juxtaposes social enterprise against other organizations (a typology of organizations) and the second layer classifies different types of social enterprises (a typology of social enterprise). This framework may provide researchers with tools to develop a clear and comprehensive definition of social enterprise. For practitioners, the ability to recognize structures of different types of social enterprises may offer them guideline to design the appropriate business model to serve their purposes.

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Exposure to polycyclic aromatic hydrocarbons (PAHs) has been associated with adverse health outcomes. Concentrations of urinary PAH metabolites (OH-PAHs) provide an integrated measure of human exposure to PAHs but measurement of urinary OH-PAHs has not been done in Australia and rarely in Vietnam, where air pollution is of concern. In this study, we assessed exposure to PAHs in 16 participants living in Brisbane, Australia and Hanoi, Vietnam, with 4 participants travelling between the two cities during the monitoring period. A total of 312 first morning urine samples were collected over 10 weeks and were analysed for nine OH-PAHs. Concentrations of the urinary OH-PAHs were 2–10 times higher in participants from Hanoi than those from Brisbane. For example, the median concentrations of 1-hydroxypyrene were 292 pg/mL in Hanoi, compared to 64 pg/mL in Brisbane. For participants travelling from Brisbane to Hanoi and back, differences in exposure to PAHs in these two cities resulted in corresponding changes of urinary OH-PAH concentrations, demonstrating that the more polluted environment in Hanoi was likely the source for higher PAH exposure there.

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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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The Korean black scraper, Thamnaconus modestus, is one of the most economically important maricultural fish species in Korea. However, the annual catch of this fish has been continuously declining over the past several decades. In this study, the genetic diversity and relationships among four wild populations and two hatchery stocks of Korean black scraper were assessed based on 16 microsatellite (MS) markers. A total of 319 different alleles were detected over all loci with an average of 19.94 alleles per locus. The hatchery stocks [mean number of alleles (N A) = 12, allelic richness (A R) = 12, expected heterozygosity (He) = 0.834] showed a slight reduction (P > 0.05) in genetic variability in comparison with wild populations (mean N A = 13.86, A R = 12.35, He = 0.844), suggesting a sufficient level of genetic variation in the hatchery populations. Similarly low levels of inbreeding and significant Hardy–Weinberg equilibrium deviations were detected in both wild and hatchery populations. The genetic subdivision among all six populations was low but significant (overall F ST = 0.008, P < 0.01). Pairwise F ST, a phylogenetic tree, and multidimensional scaling analysis suggested the existence of three geographically structured populations based on different sea basin origins, although the isolation-by-distance model was rejected. This result was corroborated by an analysis of molecular variance. This genetic differentiation may result from the co-effects of various factors, such as historical dispersal, local environment and ocean currents. These three geographical groups can be considered as independent management units. Our results show that MS markers may be suitable not only for the genetic monitoring of hatchery stocks but also for revealing the population structure of Korean black scraper populations. These results will provide critical information for breeding programs, the management of cultured stocks and the conservation of this species.

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Analysing the engagement of students in university-based Facebook groups can shed light on the nature of their learning experience and highlight leverage points to build on student success. While post-semester surveys and demographic participation data can highlight who was involved and how they subsequently felt about the experience, these techniques do not necessarily reflect real-time engagement. One way to gain insight into in-situ student experiences is by categorising the original posts and comments into predetermined frameworks of learning. This paper offers a systematic method of coding Facebook contributions within various engagement categories: motivation, discourse, cognition and emotive responses.

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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.