45,775 research outputs found

    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

    Developing an agent-based simulation model of software evolution

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    Context In attempt to simulate the factors that affect the software evolution behaviour and possibly predict it, several simulation models have been developed recently. The current system dynamic (SD) simulation model of software evolution process was built based on actor-network theory (ANT) of software evolution by using system dynamic environment, which is not a suitable environment to reflect the complexity of ANT theory. In addition the SD model has not been investigated for its ability to represent the real-world process of software evolution. Objectives This paper aims to re-implements the current SD model to an agent-based simulation environment ‘Repast’ and checks the behaviour of the new model compared to the existing SD model. It also aims to investigate the ability of the new Repast model to represent the real-world process of software evolution. Methods a new agent-based simulation model is developed based on the current SD model's specifications and then tests similar to the previous model tests are conducted in order to perform a comparative evaluation between of these two results. In addition an investigation is carried out through an interview with an expert in software development area to investigate the model's ability to represent real-world process of software evolution. Results The Repast model shows more stable behaviour compared with the SD model. Results also found that the evolution health of the software can be calibrated quantitatively and that the new Repast model does have the ability to represent real-world processes of software evolution. Conclusion It is concluded that by applying a more suitable simulation environment (agent-based) to represent ANT theory of software evolution, that this new simulation model will show more stable bahaviour compared with the previous SD model; And it will also shows the ability to represent (at least quantatively) the real-world aspect of software evolution.Peer reviewedFinal Accepted Versio

    Evolution of Supply Chain Collaboration: Implications for the Role of Knowledge

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    Increasingly, research across many disciplines has recognized the shortcomings of the traditional “integration prescription” for inter-organizational knowledge management. This research conducts several simulation experiments to study the effects of different rates of product change, different demand environments, and different economies of scale on the level of integration between firms at different levels in the supply chain. The underlying paradigm shifts from a static, steady state view to a dynamic, complex adaptive systems and knowledge-based view of supply chain networks. Several research propositions are presented that use the role of knowledge in the supply chain to provide predictive power for how supply chain collaborations or integration should evolve. Suggestions and implications are suggested for managerial and research purposes

    AGRICULTURE AS A MANAGED ECOSYSTEM: POLICY IMPLICATIONS

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    One of the greatest challenges facing agriculture for the foreseeable future is to resolve conflicts caused by a growing competition for the services of the soil, water, and other natural resources on which agriculture depends-driven by growing demands for food, fiber, and for nonagricultural services these resources provide. To meet this challenge, research is needed which is integrated across the relevant sciences to better understand and predict the properties of agricultural production systems in all of the dimensions that have come to be represented by the concept of sustainability. If we were to achieve this capability to analyze agriculture as a managed ecosystem, it would be possible to move beyond the current regime of agricultural policies, driven largely by interest-group politics, toward science-based policies that recognize the tradeoffs associated with competing uses of natural resources.Environmental Economics and Policy,

    Integrated Assessment Modelling of Complexity in the New Zealand Farming Industry

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    As New Zealand farming industry pursues more productivity this has implication for environment and makes land use and agricultural policy decision processes more complex for which integrated assessment modeling (IAM) can support. The purpose of this review paper is to propose means through which IAM can be improved specifically to minimize uncertainties and increase relevance, reliability, and utility of outputs of different models. Literature suggests that the general motivation for land use change is that farmers do consider the environment, but need to maintain profitability. There are handful decision support tools for land use and land policy decisions but one common feature of most of the models is that each seems suitable for only a part of the complexity. An appropriate framework for linking different models in an integrated assessment is still needed. As integrated assessment often goes beyond an individual researcher‘s role, research institutions need to align their research portfolio across the dimensions of the complexity by creating an appropriate mechanism to integrate individual research into integrated assessments while individual researchers need to present modelling results in a compatible format for integration into another model‘s application.integrated assessment, modeling, complexity, farming industry, New Zealand, Agribusiness, Land Economics/Use,
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