A Knowledge Management and Decision Support Model for Enterprises

We propose a novel knowledge management system (KMS) for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty

An Evolution of Corporate Software Support Systems

This paper is a brief literature survey on Software Support Systems (SSSs) and Knowledge Management (KM). This paper aims to evaluate strategic decision making perspective where enterprise information and knowledge management plays a vital role. For this evaluation, Software Support Systems (SSSs) and Knowledge Management (KM) which helps in selecting different types of support systems and human factors that affect adoption of such computer based systems in organizations are reviewed. This paper helps to analyze different types of the software support systems and system adoption concepts for the enterprises. This paper also includes concepts related to the Knowledge Management, which helps organizations to learn. Organizations knowledge and the support systems help the enterprises to take strategic decisions. Concerned literature describes Software Support Systems (SSSs) as Corporate Portals (CPs), Decision Support Systems (DSSs), Group Decision Support Systems (GDSSs), Computerized Decision Support Systems, and Adaptive Decision Support System (ADSSs). In addition, Technology Acceptance Model (TAM) that analyzes factors which would affect peoples in the enterprises is included. The factors, such as individual perception, ease of use and usefulness are analyzed. Keywords: Software Support Systems, Knowledge Management, Technology Acceptance Models

Multifaceted modelling of complex business enterprises

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control

Data driven decision support systems as a critical success factor for IT-Governance: an application in the financial sector

IT-Governance has a major impact not only on IT management but also and foremost in the Enterprises performance and control. Business uses IT agility, flexibility and innovation to pursue its objectives and to sustain its strategy. However being it more critical to the business, compliance forces IT on the opposite way of predictability, stability and regulations. Adding the current economical environment and the fact that most of the times IT departments are considered cost centres, IT-Governance decisions become more important and critical. Current IT-Governance research and practise is mainly based on management techniques and principles, leaving a gap for the contribution of information systems to IT-Governance enhancement. This research intends to provide an answer to IT-Governance requirements using Data Driven Decision Support Systems based on dimensional models. This seems a key factor to improve the IT-Governance decision making process. To address this research opportunity we have considered IT-Governance research (Peter Weill), best practises (ITIL), Body of Knowledge (PMBOK) and frameworks (COBIT). Key IT-Governance processes (Change Management, Incident Management, Project Development and Service Desk Management) were studied and key process stakeholders were interviewed. Based on the facts gathered, dimensional models (data marts) were modelled and developed to answer to key improvement requirements on each IT-Governance process. A Unified Dimensional Model (IT-Governance Data warehouse) was materialized. To assess the Unified Dimensional Model, the model was applied in a bank in real working conditions. The resulting model implementation was them assessed against Peter Weill‘s Governance IT Principles.Assessment results revealed that the model satisfies all the IT-Governance Principles. The research project enables to conclude that the success of IT-Governance implementation may be fostered by Data Driven Decision Support Systems implemented using Unified Dimensional Model concepts and based on best practises, frameworks and body of knowledge that enable process oriented, data driven decision support

Mathematics as a Supporting Tool for Technological Management

The necessity of production involving the applicability of mathematics in the management decision-making process stimulates the elaboration of this article. This approach seeks to develop under a new profile of Mathematical Science, now as another tool of technological management, while it allows to understand the diverse deductive paradigms of this knowledge of support to the administrative process. In this way, the general objective is to deal with the application of mathematics as a tool in technological management; (1), to evaluate the applicability of these tools in the management of small and medium enterprises (2), to propose a mathematical model that contributes to the innovation of the business enterprise (3). The theoretical foundation is in the Taxonomy of Bloom, prescribed for the development of abilities and cognitive attitudes of the individual. There will be no doubt that mathematical problem-solving procedures advance significantly, especially to the demands of complex solutions. The Content Analysis Method and related procedures apply to this task. As a result .... Therefore, the study of mathematical and statistical application, in addition to computer resources to identify the possible trend in the index of technological management, the present article states that mathematics as a tool has its widespread applicability within the most diverse types of technological management, regardless of their size and showing how mathematics is associated in different areas of knowledge as a trend for technological management, since it is still considered for some as a difficult element among managers

Multifaceted Modelling of Complex Business Enterprises

We formalise and present a new generic multifaceted complex system approach for modelling complex business enterprises. Our method has a strong focus on integrating the various data types available in an enterprise which represent the diverse perspectives of various stakeholders. We explain the challenges faced and define a novel approach to converting diverse data types into usable Bayesian probability forms. The data types that can be integrated include historic data, survey data, and management planning data, expert knowledge and incomplete data. The structural complexities of the complex system modelling process, based on various decision contexts, are also explained along with a solution. This new application of complex system models as a management tool for decision making is demonstrated using a railway transport case study. The case study demonstrates how the new approach can be utilised to develop a customised decision support model for a specific enterprise. Various decision scenarios are also provided to illustrate the versatility of the decision model at different phases of enterprise operations such as planning and control

Asset Management in Electricity Transmission Utilities: Investigation into Factors Affecting and their Impact on the Network

This thesis draws on techniques from Management Science and Artificial Intelligence to explore asset management in electricity transmission enterprises. In this research, factors that influence policies and practices of asset management within electricity transmission enterprises have been identified, in order to examine their interaction and how they impact the policies, practices and performance of transmission businesses. It has been found that, while there is extensive literature on the economics of transmission regulation and pricing, there is little published research linking the engineering and financial aspects of transmission asset management at a management policy level. To remedy this situation, this investigation has drawn on a wide range of literature, together with expert interviews and personal knowledge of the electricity industry, to construct a conceptual model of asset management with broad applicability across transmission enterprises in different parts of the world. A concise representation of the model has been formulated using a Causal Loop Diagram (CLD). To investigate the interactions between factors of influence it is necessary to implement the model and validate it against known outcomes. However, because of the nature of the data (a mix of numeric and non-numeric data, imprecise, incomplete and often approximate) and complexity and imprecision in the definition of relationships between elements, this problem is intractable to modelling by traditional engineering methodologies. The solution has been to utilise techniques from other disciplines. Two implementations have been explored: a multi-level fuzzy rule-based model and a system dynamics model; they offer different but complementary insights into transmission asset management. Each model shows potential to be used by transmission businesses for strategic-level decision support. The research demonstrates the key impact of routine maintenance effectiveness on the condition and performance of transmission system assets. However, performance of the transmission network, is not only related to equipment performance, but is a function of system design and operational aspects, such as loading and load factor. Type and supportiveness of regulation, together with the objectives and corporate culture of the transmission organisation also play roles in promoting various strategies for asset management. The cumulative effect of all these drivers is to produce differences in asset management policies and practices, discernable between individual companies and at a regional level, where similar conditions have applied historically and today

Применение метода аналитических сетей для оптимизации процесса выбора стратегии развития пассажирского автотранспортного предприятия

В статье обозначена проблема снижения рентабельности пассажирских автотранспортных предприятий и связанные с этим сложности по реализации процедуры стратегического прогнозирования и управления предприятием. Обосновано использование метода аналитических сетей в модели поддержки принятия решений при управлении стратегией автотранспортного предприятия, представленной в работе [1], в качестве инструмента, позволяющего формализовать экспертные знания на основных этапах оценки и выбора проектов стратегического развития. Описаны основные шаги и приведены результаты расчета алгоритма метода аналитических сетей в рамках данной модели.The article outlines the problem of reducing the profitability of passenger motor transport enterprises and the associated difficulties in implementing the procedure of strategic forecasting and enterprise management. The use of the method of analytical networks in the model of decision support in managing the strategy of a trucking enterprise presented in [1] is substantiated as a tool that allows to formalize expert knowledge at the main stages of evaluation and selection of projects for strategic development. The main steps and calculations of the algorithm algorithm for analytical networks within the framework of this model are described

Применение метода аналитических сетей для оптимизации процесса выбора стратегии развития пассажирского автотранспортного предприятия

В статье обозначена проблема снижения рентабельности пассажирских автотранспортных предприятий и связанные с этим сложности по реализации процедуры стратегического прогнозирования и управления предприятием. Обосновано использование метода аналитических сетей в модели поддержки принятия решений при управлении стратегией автотранспортного предприятия, представленной в работе [1], в качестве инструмента, позволяющего формализовать экспертные знания на основных этапах оценки и выбора проектов стратегического развития. Описаны основные шаги и приведены результаты расчета алгоритма метода аналитических сетей в рамках данной модели.The article outlines the problem of reducing the profitability of passenger motor transport enterprises and the associated difficulties in implementing the procedure of strategic forecasting and enterprise management. The use of the method of analytical networks in the model of decision support in managing the strategy of a trucking enterprise presented in [1] is substantiated as a tool that allows to formalize expert knowledge at the main stages of evaluation and selection of projects for strategic development. The main steps and calculations of the algorithm algorithm for analytical networks within the framework of this model are described