202,599 research outputs found

    Event Management for Sensing Enterprises with Decision Support Systems

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s40745-015-0034-z[EN] Sensing enterprises make use of new technologies to capture real-time information and fed constantly the decision making process. Decision support systems (DSS) are exposed to these real-time events and it is possible to start the decision process from scratch in case any unexpected internal and external events take place. Thus, an event monitoring and management system should interact with the DSS to manage events that might affect their decisions. It should act as a supra-system to identify when decisions made are still valid or need to be reanalysed. The traditional configuration of DSS (where they collect internal and external information of the organization and the decision-maker is involved in the decision-making process) should be extended to treat event management using a monitoring and management system, which monitors internal and external information and facilitate the introduction of no monitored events. This monitor and manager systems become more and more necessary due to the incessant incorporation of new technologies that enables the companies to be more context-sensitive. Furthermore, this new and/or more accurate information, which is obtained for the organization, requires a proper management.This research has been carried out in the framework of the project PAID-06-21Universitat Politècnica de València (Sistema de ayuda a la toma de decisiones ante decisiones no programadas en la planificación jerárquica de la producción) and GV/2014/010 Generalitat Valenciana (Identificación de la información proporcionada por los nuevos sistemas de detección accesibles mediante internet en el ámbito de las “sensing enterprises” para la mejora de la toma de decisiones en la planificación de la producción).Boza, A.; Alemany Díaz, MDM.; Cuenca, L.; Ortiz Bas, Á. (2015). Event Management for Sensing Enterprises with Decision Support Systems. Annals of Data Science. 2(1):103-109. https://doi.org/10.1007/s40745-015-0034-zS10310921Estupinyà P (2010) El ladrón de cerebros: Compartiendo el conocimiento científico de las mentes más brillantes. Penguin Random House Grupo Editorial EspañaVicens E, Alemany ME, Andrés C, Guarch JJ (2001) A design and application methodology for hierarchical production planning decision support systems in an enterprise integration context. Int J Prod Econ 74:5–20. doi: 10.1016/S0925-5273(01)00103-7Van Wezel W, Van Donk DP, Gaalman G (2006) The planning flexibility bottleneck in food processing industries. J Oper Manag 24:287–300. doi: 10.1016/j.jom.2004.11.001Winter R (1994) Multi-stage production controlling based on continuous, flexible abstraction hierarchies. IEPMÖzdamar L, Bozyel MA, Birbil SI (1998) A hierarchical decision support system for production planning (with case study). Eur J Oper Res 104:403–422. doi: 10.1016/S0377-2217(97)00016-7FInES FIESC (2012) FInES Research Roadmap 2025Shamsuzzoha Ah, Rintala S, Cunha PF, Ferreira PS, Kankaanpää T, Maia Carneiro L (2013) Event monitoring and management process in a non-hierarchical business network. In: Poler R, Carneiro L, Jasinski T, Zolghadri rc, Pedrazzoli P (eds) Intelligent non-hierarchical manufacturing networks. Wiley, New York, pp 349–374Committee of Sponsoring Organizations of the Treadway Commission (2004) COSO enterprise risk management-integrated framework: application techniques. Committee of Sponsoring Organizations of the Treadway CommissionSantucci G, Martinez C, Vlad-Câlcic D (2012) The sensing enterprise. FInES workshop at FIA 2012Vargas A, Cuenca L, Boza A, Sacala I, Moisescu M (2014) Towards the development of the framework for inter sensing enterprise architecture, J Intell Manuf, 1–18Anthony RN (1965) Planning and control systems: a framework for analysis. Harvard University, CambridgeSimon HA (1960) The new science of management decision. Harper & Brothers, New YorkShim JP, Warkentin M, Courtney JF, Power DJ, Sharda R, Carlsson C (2002) Past, present, and future of decision support technology. Decis Support Syst 33:111–126. doi: 10.1016/S0167-9236(01)00139-7Peng Y, Kou G, Shi Y, Chen ZA (2008) Descriptive framework for the field of data mining and knowledge discovery. Int J Inf Technol Decis Mak 7:639–682. doi: 10.1142/S0219622008003204Alarcón F, Alemany MME, Lario FC, Oltra RF (2011) La falta de homogeneidad del producto (FHP) en las empresas cerámicas y su impacto en la reasignación del inventario. Boletín de la Sociedad Española de Cerámica y Vidrio 50:49–58. doi: 10.3989/cyv.072011Cegarra J, van Wezel W (2011) A comparison of task analysis methods for planning and scheduling. In: Fransoo JC, Waefler T, Wilson JR (eds) Behavioral operations in planning and scheduling. Springer, Berlin Heidelberg, pp 323–338FP7-ICT (2012) ICT: Information and Communication Technologies: work programme 2013Barash G, Bartolini C, Wu L (2007) Measuring and improving the performance of an IT support organization in managing service incidents. In: 2nd IEEE/IFIP international workshop on business-driven IT management, BDIM ’07, pp 11–18Bartolini C, Stefanelli C, Tortonesi M (2010) SYMIAN: analysis and performance improvement of the IT incident management process. IEEE Trans Netw Serv Manag 7:132–144. doi: 10.1109/TNSM.2010.1009.I9P0321Boza A, Alemany MME, Alarcón F, Cuenca L (2013) A model-driven DSS architecture for delivery management in collaborative supply chains with lack of homogeneity in products. Prod Plan Control 25:650–661. doi: 10.1080/09537287.2013.798085Boza A, Ortiz A, Vicens E, Poler R (2009) A framework for a decision support system in a hierarchical extended enterprise decision context. In: Poler R, van Sinderen M, Sanchis R (eds) Enterprise interoperability. Springer, Berlin Heidelberg, pp 113–124Grefen P, Dijkman R (2013) Hybrid control of supply chains: a structured exploration from a systems perspective. Int J Prod Manag Eng 1:39–5

    The necessities for building a model to evaluate Business Intelligence projects- Literature Review

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    In recent years Business Intelligence (BI) systems have consistently been rated as one of the highest priorities of Information Systems (IS) and business leaders. BI allows firms to apply information for supporting their processes and decisions by combining its capabilities in both of organizational and technical issues. Many of companies are being spent a significant portion of its IT budgets on business intelligence and related technology. Evaluation of BI readiness is vital because it serves two important goals. First, it shows gaps areas where company is not ready to proceed with its BI efforts. By identifying BI readiness gaps, we can avoid wasting time and resources. Second, the evaluation guides us what we need to close the gaps and implement BI with a high probability of success. This paper proposes to present an overview of BI and necessities for evaluation of readiness. Key words: Business intelligence, Evaluation, Success, ReadinessComment: International Journal of Computer Science & Engineering Survey (IJCSES) Vol.3, No.2, April 201

    Goals/questions/metrics method and SAP implementation projects

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    During the last years some researchers have studied the critical success factors (CSFs) in ERP implementations. However, until now, no one has studied how these CSFs should be put in practice to help organizations achieve success in ERP implementations. This technical research report attempts to define the usage of Goals/Questions/Metrics (GQM) approach in the definition of a measurement system for ERP implementation projects. GQM approach is a mechanism for defining and interpreting operational, measurable goals. Lately, because of its intuitive nature the approach has gained widespread appeal. We present a metrics overview and a description of GQM approach. Then we provide an example of GQM application for monitoring sustained management support in ERP implementations. Sustained management support is the most cited critical success factor in ERP implementation projects.Postprint (published version

    Community Development Evaluation Storymap and Legend

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    Community based organizations, funders, and intermediary organizations working in the community development field have a shared interest in building stronger organizations and stronger communities. Through evaluation these organizations can learn how their programs and activities contribute to the achievement of these goals, and how to improve their effectiveness and the well-being of their communities. Yet, evaluation is rarely seen as part of a non-judgemental organizational learning process. Instead, the term "evaluation" has often generated anxiety and confusion. The Community Development Storymap project is a response to those concerns.Illustrations found in this document were produced by Grove Consultants

    Performance measurement : challenges for tomorrow

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    This paper demonstrates that the context within which performance measurement is used is changing. The key questions posed are: Is performance measurement ready for the emerging context? What are the gaps in our knowledge? and Which lines of enquiry do we need to pursue? A literature synthesis conducted by a team of multidisciplinary researchers charts the evolution of the performance-measurement literature and identifies that the literature largely follows the emerging business and global trends. The ensuing discussion introduces the currently emerging and predicted future trends and explores how current knowledge on performance measurement may deal with the emerging context. This results in identification of specific challenges for performance measurement within a holistic systems-based framework. The principle limitation of the paper is that it covers a broad literature base without in-depth analysis of a particular aspect of performance measurement. However, this weakness is also the strength of the paper. What is perhaps most significant is that there is a need for rethinking how we research the field of performance measurement by taking a holistic systems-based approach, recognizing the integrated and concurrent nature of challenges that the practitioners, and consequently the field, face

    ERP implementation methodologies and frameworks: a literature review

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    Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

    SMEs: ERP or virtual collaboration teams

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    Small firms are indeed the engines of global economic growth. Small and Medium Enterprises (SMEs) play an important role to promote economic development. SMEs in the beginning of implementing new technologies always face capital shortage and need technological assistance. Available ERP systems do not fulfil the specific requirements of Small firms. SMEs has scarce resources and manpower therefore many SMEs don?t have the possessions to buy and operate an ERP System. On the other hand competition and competitiveness of SMEs have to be strengthened. This paper briefly reviews the existing perspectives on virtual teams and their effect on SMEs management. It also discusses the main characteristics of virtual teams and clarifies the differences aspects of virtual team application in SMEs. After outlining some of the main advantages and pitfall of such teams, it concentrates on comparing of ERP and virtual collaborative teams in SMEs. Finally, it provides evidence for the need of ?Software as a Service (SaaS)? where an application is hosted as a service provided to customers across the web for SMEs as an alternative of ERP. It has been widely argued that ERP disadvantage in SMEs such as administrative expenditure and cost, isolated structure, severe lack of software flexibility, insufficient support of SMEs business and high operating cost, lead SMEs to use virtual collaborative team which is net work base solution

    Development of the Integrated Model of the Automotive Product Quality Assessment

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    Issues on building an integrated model of the automotive product quality assessment are studied herein basing on widely applicable methods and models of the quality assessment. A conceptual model of the automotive product quality system meeting customer requirements has been developed. Typical characteristics of modern industrial production are an increase in the production dynamism that determines the product properties; a continuous increase in the volume of information required for decision-making, an increased role of knowledge and high technologies implementing absolutely new scientific and technical ideas. To solve the problem of increasing the automotive product quality, a conceptual structural and hierarchical model is offered to ensure its quality as a closed system with feedback between the regulatory, manufacturing, and information modules, responsible for formation of the product quality at all stages of its life cycle. The three module model of the system of the industrial product quality assurance is considered to be universal and to give the opportunity to explore processes of any complexity while solving theoretical and practical problems of the quality assessment and prediction for products for various purposes, including automotive

    Extending the IS-Impact model into the higher education sector

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    The study addresses known limitations of what may be the most important dependent variable in Information Systems (IS) research; IS-Success or IS-Impact. The study is expected to force a deeper understanding of the broad notions of IS success and impact. The aims of the research are to: (1) enhance the robustness and minimize limitations of the IS-Impact model, and (2) introduce and operationalise a more rigorously validated IS Impact measurement model to Universities, as a reliable model for evaluating different Administrative Systems. In extending and further generalizing the IS-Impact model, the study will address contemporary validation issues

    SMEs e-business behaviour: a demographics and strategic analysis

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    The aim of this research was to understand the strategic uses of e-business systems and technologies by classifying companies and particularly small and medium businesses according to demographics as well as e-business behavior variables.The study was based on data from a large quantitative survey of European E-business W@tch for the period 2007 using questionnaire interviews (N=409). We employed two-step cluster analysis, multinomial logistic regression and stepwise descriminant analysis as the most appropriate methods for our analysis. The findings revealed six clusters associated to e-business adoption. The six groups differ in terms of demographic characteristics as well as e-business applications they use. We found that the following clusters exist: (a) Leaders: large companies that extensively use ebusiness in a strategic manner (b) innovators: use e-business in an way that allows them to innovate and differentiate from other companies (c Beginners: small and medium companies across all sectors that only recently start to use e-business (d) Unready Adopters: micro and small companies that lag behind (e) Late Adopters: small-size companies but larger that the Unready Adopters, that appear not to be interest in the advances of ICTs and (f) Laggards: micro companies with little use of e-business.The results of our survey can positively contribute to managers aiming to take advantage of technological advances in electronic business as well as to any researcher who study e-business management and applications
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