35 resultados para Social BI, Social Business Intelligence, Sentiment Analysis, Opinion Mining.
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Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: j.s.edwards@aston.ac.uk 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.
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Editorial
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We introduce a type of 2-tier convolutional neural network model for learning distributed paragraph representations for a special task (e.g. paragraph or short document level sentiment analysis and text topic categorization). We decompose the paragraph semantics into 3 cascaded constitutes: word representation, sentence composition and document composition. Specifically, we learn distributed word representations by a continuous bag-of-words model from a large unstructured text corpus. Then, using these word representations as pre-trained vectors, distributed task specific sentence representations are learned from a sentence level corpus with task-specific labels by the first tier of our model. Using these sentence representations as distributed paragraph representation vectors, distributed paragraph representations are learned from a paragraph-level corpus by the second tier of our model. It is evaluated on DBpedia ontology classification dataset and Amazon review dataset. Empirical results show the effectiveness of our proposed learning model for generating distributed paragraph representations.
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Corporate Social Responsibility (CSR) is a multi-disciplinary subject and definitions vary with regard to the perceived scope or boundaries of the corporation’s responsibility. In this paper, corporate motives for CSR are explored, along with the notion of an altruistic ethical impulse among business leaders or managers, perhaps motivated by religious beliefs. It is suggested that the formal adoption of CSR by corporations could be associated with the changing personal values of managers and that there may be an association between different industries, the personal values of the managers who work in them and their commitment to CSR. This paper is preparatory to an empirical investigation that will address how corporate social responsibility (CSR) is interpreted and institutionalised by organisations, including an analysis of firms’ perceptions of the boundaries regarding where and to whom their corporate social responsibilities lie.
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This research paper focuses on the self-declared initiatives of the four largest chocolate companies to tackle social problems within the context of establishing a sustainable supply chain. After the literature review of sustainability, supply chain management, and cocoa farming, this paper gives an assessment of the extant practices of the chocolatiers and makes a comparative analysis based on Corporate Social Responsibility (CSR) and Sustainability Reports. This paper uses a case study approach based on secondary-data. A roadmap and benchmarking of social sustainability initiatives were conducted for the supply chain management activities of the world's four largest chocolatiers. This paper analyses the extant sustainability practices of the chocolatiers and offers a model framework for comparison of the measures taken. This paper is based on self-declared secondary data. There is a chance that some practices were not documented by the case companies; or that companies claim what they don't actually do. This paper provides a framework for agricultural businesses to compare their sustainability efforts and improve the performance of their supply chains. Originality and value of this research reside in terms of both literature and methodology. The framework for analysing the social sustainability aspects of agricultural supply chains is original and gives an up-to-date view of sustainability practices. The use of secondary data to compare self-declared initiatives is also a novel approach to business sustainability research.