E-Journals and the Big Deal: A Review of the Literature

Faced with shrinking budgets and increased subscription prices, many academic libraries are seeking ways to reduce the cost of e-journal access. A common target for cuts is the “Big Deal,” or large bundled subscription model, a term coined by Kenneth Frazier in a 2001 paper criticizing the effects of the Big Deal on the academic community. The purpose of this literature review is to examine issues related to reducing e-journal costs, including criteria for subscription retention or cancellation, decision-making strategies, impacts of cancellations, and other options for e-journal content provision. Commonly used criteria for decision-making include usage statistics, overlap analysis, and input from subject specialists. The most commonly used strategy for guiding the process and aggregating data is the rubric or decision grid. While the e-journal landscape supports several access models, such as Pay-Per-View, cloud access, and interlibrary loan, the Big Deal continues to dominate. Trends over the past several years point to dwindling support for the Big Deal however, due largely to significant annual rate increases and loss of content control

Investigating Decision Support Techniques for Automating Cloud Service Selection

The compass of Cloud infrastructure services advances steadily leaving users in the agony of choice. To be able to select the best mix of service offering from an abundance of possibilities, users must consider complex dependencies and heterogeneous sets of criteria. Therefore, we present a PhD thesis proposal on investigating an intelligent decision support system for selecting Cloud based infrastructure services (e.g. storage, network, CPU).Comment: Accepted by IEEE Cloudcom 2012 - PhD consortium trac

Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics

The accurate and efficient solution of Maxwell's equation is the problem addressed by the scientific discipline called Computational ElectroMagnetics (CEM). Many macroscopic phenomena in a great number of fields are governed by this set of differential equations: electronic, geophysics, medical and biomedical technologies, virtual EM prototyping, besides the traditional antenna and propagation applications. Therefore, many efforts are focussed on the development of new and more efficient approach to solve Maxwell's equation. The interest in CEM applications is growing on. Several problems, hard to figure out few years ago, can now be easily addressed thanks to the reliability and flexibility of new technologies, together with the increased computational power. This technology evolution opens the possibility to address large and complex tasks. Many of these applications aim to simulate the electromagnetic behavior, for example in terms of input impedance and radiation pattern in antenna problems, or Radar Cross Section for scattering applications. Instead, problems, which solution requires high accuracy, need to implement full wave analysis techniques, e.g., virtual prototyping context, where the objective is to obtain reliable simulations in order to minimize measurement number, and as consequence their cost. Besides, other tasks require the analysis of complete structures (that include an high number of details) by directly simulating a CAD Model. This approach allows to relieve researcher of the burden of removing useless details, while maintaining the original complexity and taking into account all details. Unfortunately, this reduction implies: (a) high computational effort, due to the increased number of degrees of freedom, and (b) worsening of spectral properties of the linear system during complex analysis. The above considerations underline the needs to identify appropriate information technologies that ease solution achievement and fasten required elaborations. The authors analysis and expertise infer that Grid Computing techniques can be very useful to these purposes. Grids appear mainly in high performance computing environments. In this context, hundreds of off-the-shelf nodes are linked together and work in parallel to solve problems, that, previously, could be addressed sequentially or by using supercomputers. Grid Computing is a technique developed to elaborate enormous amounts of data and enables large-scale resource sharing to solve problem by exploiting distributed scenarios. The main advantage of Grid is due to parallel computing, indeed if a problem can be split in smaller tasks, that can be executed independently, its solution calculation fasten up considerably. To exploit this advantage, it is necessary to identify a technique able to split original electromagnetic task into a set of smaller subproblems. The Domain Decomposition (DD) technique, based on the block generation algorithm introduced in Matekovits et al. (2007) and Francavilla et al. (2011), perfectly addresses our requirements (see Section 3.4 for details). In this chapter, a Grid Computing infrastructure is presented. This architecture allows parallel block execution by distributing tasks to nodes that belong to the Grid. The set of nodes is composed by physical machines and virtualized ones. This feature enables great flexibility and increase available computational power. Furthermore, the presence of virtual nodes allows a full and efficient Grid usage, indeed the presented architecture can be used by different users that run different applications

Value-driven partner search for <i>Energy from Waste</i> projects

Energy from Waste (EfW) projects require complex value chains to operate effectively. To identify business partners, plant operators need to network with organisations whose strategic objectives are aligned with their own. Supplier organisations need to work out where they fit in the value chain. Our aim is to support people in identifying potential business partners, based on their organisation’s interpretation of value. Value for an organisation should reflect its strategy and may be interpreted using key priorities and KPIs (key performance indicators). KPIs may comprise any or all of knowledge, operational, economic, social and convenience indicators. This paper presents an ontology for modelling and prioritising connections within the business environment, and in the process provides means for defining value and mapping these to corresponding KPIs. The ontology is used to guide the design of a visual representation of the environment to aid partner search

Giving the customer a voice: A study of market research methods and their perceived effectiveness in NPD

There is a widely held view that a lack of, “…customer understanding,” is one of the main reasons for product failure (Eliashberg et al., 1997, p. 219). This is despite the fact that new product development (NPD) is a crucial business process for many companies. The importance of integrating the voice of the customer (VoC) through market research is well documented (Davis, 1993; Mullins and Sutherland, 1998; Cooper et al., 2002; Flint, 2002; Davilla et al., 2006; Cooper and Edgett, 2008; Cooper and Dreher, 2010; Goffin and Mitchell, 2010). However, not all research methods are well received, for example there are studies that have strongly criticized focus groups, interviews and surveys (e.g. Ulwick, 2002; Goffin et al, 2010; Sandberg, 2002). In particular, a point is made that, “…traditional market research and development approaches proved to be particularly ill-suited to breakthrough products” (Deszca et al, 2010, p613). Therefore, in situations where traditional techniques—interviews and focus groups—are ineffective, the question is which market research techniques are appropriate, particularly for developing breakthrough products? To investigate this, an attempt was made to access the knowledge of market research practitioners from agencies with a reputation for their work on breakthrough NPD. We were surprised to find that this research had not been conducted previously. In order to make it possible for the sample of 24 market research experts identified for this study to share their knowledge, repertory grid technique was used. This psychology based method particularly seeks out tacit knowledge by using indepth interviews. In this case the interviews were conducted with professionals from leading market research agencies in two countries. The resulting data provided two unique insights: they highlighted the attributes of market research methods which made them effective at identifying customers’ needs and they showed how different methods were perceived against these attributes. This article starts with a review of the literature on different methods for conducting market research to identify customer needs. The conclusions from the literature are then used to define the research question. We explain our choice of methodology, including the data collection and analysis approach. Next the key results are presented. Finally, the discussion section identifies the key insights, clarifies the limitations of the research, suggests areas for future research, and draws implications for managers. We conclude that existing research is not aligned with regard to which methods (or combination of methods) are best suited to the various stages of the NPD process. We have set out the challenges and our own intended work in this regard in our section on ‘further research’. Also, the existing literature does not explicitly seek the perceptions of practitioner experts based in market research agencies. This we have started to address, and we acknowledge that further work is required. Although our research in ongoing, it has already yielded the first view of a model of the perceptions of 24 expert market researchers in the UK and Denmark. Based on the explanation of these experts, the model situates a derived set of categories in a manner that reflects the way in which they are inter-linked. We believe that our model begins to deal with the gaps and anomalies in the existing research into VoC methods

E-finance-lab at the House of Finance : about us

The financial services industry is believed to be on the verge of a dramatic [r]evolution. A substantial redesign of its value chains aimed at reducing costs, providing more efficient and flexible services and enabling new products and revenue streams is imminent. But there seems to be no clear migration path nor goal which can cast light on the question where the finance industry and its various players will be and should be in a decade from now. The mission of the E-Finance Lab is the development and application of research methodologies in the financial industry that promote and assess how business strategies and structures are shared and supported by strategies and structures of information systems. Important challenges include the design of smart production infrastructures, the development and evaluation of advantageous sourcing strategies and smart selling concepts to enable new revenue streams for financial service providers in the future. Overall, our goal is to contribute methods and views to the realignment of the E-Finance value chain. ..