اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدERP projects Internal Stakeholder network and how it influences the projects outcome
88
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
So far little effort has been put into researching the importance of internal ERP project stakeholders mutual interactions,realizing the projects complexity,influence on the whole organization, and high risk for a useful final outcome. This research analyzes the stakeholders interactions and positions in the project network, their criticality, potential bottlenecks and conflicts. The main methods used are Social Network Analysis, and the elicitation of drivers for the individual players. Information was collected from several stakeholders from three large ERP projects all in global companies headquartered in Finland, together with representatives from two different ERP vendors, and with two experienced ERP consultants. The analysis gives quantitative as well as qualitative characterization of stakeholder criticality (mostly the Project Manager(s), the Business Owner(s) and the Process Owner(s)), degree of centrality, closeness, mediating or bottleneck roles, relational ties and conflicts (individual, besides those between business and project organizations), and clique formations. A generic internal stakeholder network model is established as well as the criticality of the project phases. The results are summarized in the form of a list of recommendations for future ERP projects to address the internal stakeholder impacts .Project management should utilize the latest technology to provide tools to increase the interaction between the stakeholders and to monitor the strength of these relations. Social network analysis tools could be used in the projects to visualize the stakeholder relations in order to better understand the possible risks related to the relations (or lack of them).
قيم البحث
اقرأ أيضاً
To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers
to the idea that funds come from a network of people on the Internet who are passionate about supporting others projects. One of the most popular crowdfunding sites is Kickstarter. In it, creators post descriptions of their projects and advertise them on social media sites (mainly Twitter), while investors look for projects to support. The most common reason for project failure is the inability of founders to connect with a sufficient number of investors, and that is mainly because hitherto there has not been any automatic way of matching creators and investors. We thus set out to propose different ways of recommending investors found on Twitter for specific Kickstarter projects. We do so by conducting hypothesis-driven analyses of pledging behavior and translate the corresponding findings into different recommendation strategies. The best strategy achieves, on average, 84% of accuracy in predicting a list of potential investors Twitter accounts for any given project. Our findings also produced key insights about the whys and wherefores of investors deciding to support innovative efforts.
We propose a funding scheme for theoretical research that does not rely on project proposals, but on recent past scientific productivity. Given a quantitative figure of merit on the latter and the total research budget, we introduce a number of polic
ies to decide the allocation of funds in each grant call. Under some assumptions on scientific productivity, some of such policies are shown to converge, in the limit of many grant calls, to a funding configuration that is close to the maximum total productivity of the whole scientific community. We present numerical simulations showing evidence that these schemes would also perform well in the presence of statistical noise in the scientific productivity and/or its evaluation. Finally, we prove that one of our policies cannot be cheated by individual research units. Our work must be understood as a first step towards a mathematical theory of the research activity.
A review is presented of several projects under development which aim to be third generation solar neutrino detectors.
Background: Open source software has an increasing importance in modern software development. However, there is also a growing concern on the sustainability of such projects, which are usually managed by a small number of developers, frequently worki
ng as volunteers. Aims: In this paper, we propose an approach to identify GitHub projects that are not actively maintained. Our goal is to alert users about the risks of using these projects and possibly motivate other developers to assume the maintenance of the projects. Method: We train machine learning models to identify unmaintained or sparsely maintained projects, based on a set of features about project activity (commits, forks, issues, etc). We empirically validate the model with the best performance with the principal developers of 129 GitHub projects. Results: The proposed machine learning approach has a precision of 80%, based on the feedback of real open source developers; and a recall of 96%. We also show that our approach can be used to assess the risks of projects becoming unmaintained. Conclusions: The model proposed in this paper can be used by open source users and developers to identify GitHub projects that are not actively maintained anymore.
New results from Super-Kamiokande, K2K and SNO not only have spurred on the interest in neutrino oscillation physics, but also have started to shift the interest from discovery to precision measurements. Future projects focusing on atmospheric neutri
nos are reviewed in this context. Important contributions could be made in the precision determination of the oscillation parameters, in the observation of matter effects and in the determination of the neutrino mass hierarchy. Unfortunately, the probability that the projects discussed in this review will be running in the next ten years is rather small. The only project with a shorter time scale has not been funded.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
