42 resultados para business intelligence


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This thesis addressed the problem of data quality, reliability and energy consumption of networked Radio Frequency Identification systems for business intelligence applications decision making processes. The outcome of the research substantially improved the accuracy and reliability of RFID generated data as well as energy depletion thus prolonging RFID system lifetime.

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Business intelligence (BI) can help support decision-making processes and so contribute to improved BI assimilation and organisational performance. However, a BI undertaking may be effective and profitable for some organisations but not others. How can these differing outcomes be explained for those firms that have adopted BI systems? Drawing on the literature pertaining to absorptive capacity theory, IT competency, and BI assimilation we develop a conceptual framework to investigate the relationships between BI competency, absorptive capacity, and BI assimilation. This research provides insights for BI stakeholders in understanding the mediating role of organisational absorptive capacity within a complex BI environment, enabling many organisations that have implemented BI to leverage the benefits from their costly investments. The conceptual framework provides a sound basis for further research to shed light on the effects of BI competency and organisational absorptive capacity on BI assimilation. Contributions to research and practice are discussed.

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Business intelligence (BI) offers opportunities for managers to master vast data resources for operational and strategic gains, and allows BI-based organizations to generate significant business value. While several researchers emphasized the importance of BI to assist making quality decisions, no study explored the use of BI for improved understanding of business before such decisions are made and assessing the impact of the actions derived from these decisions. To fill this gap we use the theory of organizational sensemaking. The presented research uses hermeneutic phenomenology to study the experiences of decision-makers in using BI-generated insights to guide their actions while altering business processes, structures and information. The study emphasizes the necessity of using BI in the creation and maintenance of individual and organizational identity, as well as, enactment of this identity on the business and its environment, which need to be molded in response to changing circumstances.

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With emerging trends for Internet of Things (IoT) and Smart Cities, complex data transformation, aggregation and visualization problems are becoming increasingly common. These tasks support improved business intelligence, analytics and enduser access to data. However, in most cases developers of these tasks are presented with challenging problems including noisy data, diverse data formats, data modeling and increasing demand for sophisticated visualization support. This paper describes our experiences with just such problems in the context of Household Travel Surveys data integration and harmonization. We describe a common approach for addressing these harmonizations. We then discuss a set of lessons that we have learned from our experience that we hope will be useful for others embarking on similar problems. We also identify several key directions and needs for future research and practical support in this area.

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This paper is the result of a "Rip Van Winkle" experience I had concerning the teaching of Business Communication. The paper focuses on the remarkable expansion in the curriculum of the traditional "Business Communication" or "Business Writing" course offered by many tertiary institutions around the world. Based on 25 years of personal observation and experience in a number of educational settings, the paper will trace the increasing sophistication and complexity of the study of business communication from one that covered little more than lessons in the design of hardcopy memos, letters, and reports to one that now covers a broad spectrum of topics such as "emotional intelligence," "intercultural communication," "effective public speaking," as well as the effects of purpose and audience on the design of a wide variety of business communications.

An example of an effective task that involves a number of on the job activities is provided in the form of a ready to use assignment that is applicable in a number of contexts.

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Recent work on the distinctive features of emotions appraised as either negative or positive has links to the investigation of differences in levels of emotional intelligence. In a study with experienced teachers as participants, it was found that emotional reactions to positive or negative situations was moderated by level of emotional intelligence. The reactions to positively charged emotional situations involving students and peers were similar for teachers with high and low levels of emotional intelligence, although the low level group showed somewhat lower likelihood of making an “emotionally intelligent” response compared to the high level group. A much sharper contrast in response likelihood was found for negatively charged emotional situations involving students and peers. Teachers with high levels of emotional intelligence responded quite differently to those with low levels of emotional intelligence. The results indicate the prospect of clarifying a neglected area of exploration of differences in the likely behaviour of teachers differing in levels of emotional intelligence.

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The Financial Intelligence Centre Act 38 of 2001 (FICA) compels certain persons and institutions (defined as "accountable institutions'') to identify and verify the identity of a new client before any transaction may be concluded or any business relationship is established.1 Accountable institutions are listed in schedule 1 to FICA and include banks, brokers, financial advisers, insurance companies, attorneys and estate agents. This duty to identify new clients came into effect on 30 June 2003. However, FICA also requires a similar procedure to be followed in respect of all current clients. Current clients are those with whom an accountable institution had business relationships on 30 June 2003.2 After 30 June 2004 an institution may not conclude a transaction in the course of its business relationship with an unidentified current client, until it has established and verified that client's identity as prescribed. An institution that concludes any transaction in contravention of this prohibition, commits an offence and is liable to a fine not exceeding R10 million or to imprisonment of up to 15 years.3

The majority of accountable institutions and their clients failed to meet the June 2004 current client identification deadline.4 This failure posed serious economic and legal risks. With a few days to spare, the minister of finance granted a partial and temporary exemption in respect of these requirements. This article explores the statutory scheme for identification and re-identification of clients and some of the practical problems that were encountered. The June 2004 exemptions from these requirements are also considered and proposals for law reform are made.

The discussion of the FICA identification scheme necessitates the following brief overview of the international and South African money laundering control framework.

1 s 21(1) of FICA.
2 s 21(2) of FICA. See also s 82(2)(b).
3 s 46(2) of FICA read with s 68(1) of FICA.

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Investigation of the role of hypothesis formation in complex (business) problem solving has resulted in a new approach to hypothesis generation. A prototypical hypothesis generation paradigm for management intelligence has been developed, reflecting a widespread need to support management in such areas as fraud detection and intelligent decision analysis. This dissertation presents this new paradigm and its application to goal directed problem solving methodologies, including case based reasoning. The hypothesis generation model, which is supported by a dynamic hypothesis space, consists of three components, namely, Anomaly Detection, Abductive Reasoning, and Conflict Resolution models. Anomaly detection activates the hypothesis generation model by scanning anomalous data and relations in its working environment. The respective heuristics are activated by initial indications of anomalous behaviour based on evidence from historical patterns, linkages with other cases, inconsistencies, etc. Abductive reasoning, as implemented in this paradigm, is based on joining conceptual graphs, and provides an inference process that can incorporate a new observation into a world model by determining what assumptions should be added to the world, so that it can explain new observations. Abductive inference is a weak mechanism for generating explanation and hypothesis. Although a practical conclusion cannot be guaranteed, the cues provided by the inference are very beneficial. Conflict resolution is crucial for the evaluation of explanations, especially those generated by a weak (abduction) mechanism.The measurements developed in this research for explanation and hypothesis provide an indirect way of estimating the ‘quality’ of an explanation for given evidence. Such methods are realistic for complex domains such as fraud detection, where the prevailing hypothesis may not always be relevant to the new evidence. In order to survive in rapidly changing environments, it is necessary to bridge the gap that exists between the system’s view of the world and reality.Our research has demonstrated the value of Case-Based Interaction, which utilises an hypothesis structure for the representation of relevant planning and strategic knowledge. Under, the guidance of case based interaction, users are active agents empowered by system knowledge, and the system acquires its auxiliary information/knowledge from this external source. Case studies using the new paradigm and drawn from the insurance industry have attracted wide interest. A prototypical system of fraud detection for motor vehicle insurance based on an hypothesis guided problem solving mechanism is now under commercial development. The initial feedback from claims managers is promising.

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The last 25 years have seen rapid increases in the number and sophistication of technological and process innovations in large manufacturers, producing dramatic improvements in productivity and efficiency. However, smaller manufacturers’ adoption of such innovations has been uneven. Ambient Intelligence (AmI) technologies are being positioned as the next performance and productivity enhancing purchase for manufacturers. This paper defines and gives examples of AmI technologies in current use, summarises AmI technologies of potential interest to small and medium enterprise (SME) manufacturers, and identifies potential impacts of restricted absorptive capacity in SMEs on the adoption of AmI technologies. Comparing two SME manufacturers, one from Germany and one from Australia illustrates a potential application of generic AmI technology based business solutions to a range of SME manufacturers.

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Social media data are becoming increasingly critical for businesses to capture, analyse, and utilise in a timely manner. However, the unstructured and distributed nature and volume of this information makes the task of extracting useful and practical information challenging. Given the dynamic evolution of social media and social media monitoring, our current understanding of how social media monitoring can help organisations to create business value is inadequate. As a result, there is a need to study how organisations can (a) extract and analyse social media data related to their business (Sensing), and (b) utilise external intelligence gained from social media monitoring for specific business initiatives (Seizing). This study uses a qualitative approach with a multiple embedded case study design to understand the phenomenon of social media monitoring and its outcome for organisations. Anticipated contributions are presented.

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This paper identifies which immersion program activities are most important in developing cross-cultural skills, and identifies the cultural intelligence (CQ) factors that Master of Business Administration (MBA) students gain by their participation in a cultural immersion program. Twenty students were surveyed, and it was found that the most important immersion program activities to develop cross-cultural skills were “visits to Indonesian companies” and “cultural activities”, as opposed to lectures by academics/industry guest speakers or working in cross-cultural teams. Motivational CQ was found to be the highest scoring CQ factor, followed by behavioural, then metacognitive and finally cognitive CQ. Students may have developed less cognitive CQ competencies because they had less opportunity to learn about knowledge aspects of CQ and had more opportunity to put into practice their motivational and behavioural CQ through immersion program activities.