Executive Information Systems' Multidimensional Models

Executive Information Systems are design to improve the quality of strategic level of management in organization through a new type of technology and several techniques for extracting, transforming, processing, integrating and presenting data in such a way that the organizational knowledge filters can easily associate with this data and turn it into information for the organization. These technologies are known as Business Intelligence Tools. But in order to build analytic reports for Executive Information Systems (EIS) in an organization we need to design a multidimensional model based on the business model from the organization. This paper presents some multidimensional models that can be used in EIS development and propose a new model that is suitable for strategic business requests.Executive Information Systems (EIS), Decision Support Systems (DSS), multidimensional models, Business Intelligence tools, On-Line Analytical Processing (OLAP)

Allocative and Informational Externalities in Auctions and Related Mechanisms

We study the effects of allocative and informational externalities in (multi-object) auctions and related mechanisms. Such externalities naturally arise in models that embed auctions in larger economic contexts. In particular, they appear when there is downstream interaction among bidders after the auction has closed. The endogeneity of valuations is the main driving force behind many new, specific phenomena with allocative externalities: even in complete information settings, traditional auction formats need not be efficient, and they may give rise to multiple equilibria and strategic non-participation. But, in the absence of informational externalities, welfare maximization can be achieved by Vickrey-Clarke- Groves mechanisms. Welfare-maximizing Bayes-Nash implementation is, however, impossible in multi-object settings with informational externalities, unless the allocation problem is separable across objects (e.g. there are no allocative externalities nor complementarities) or signals are one-dimensional. Moreover, implementation of any choice function via ex-post equilibrium is generically impossible with informational externalities and multidimensional types. A theory of information constraints with multidimensional signals is rather complex, but indispensable for our study

Allocative and Informational Externalities in Auctions and Related Mechanisms

We study the effects of allocative and informational externalities in (multi-object) auctions and related mechanisms. Such externalities naturally arise in models that embed auctions in larger economic contexts. In particular, they appear when there is downstream interaction among bidders after the auction has closed. The endogeneity of valuations is the main driving force behind many new, specific phenomena with allocative externalities: even in complete information settings, traditional auction formats need not be efficient, and they may give rise to multiple equilibria and strategic non-participation. But, in the absence of informational externalities, welfare maximization can be achieved by Vickrey-Clarke- Groves mechanisms. Welfare-maximizing Bayes-Nash implementation is, however, impossible in multi-object settings with informational externalities, unless the allocation problem is separable across objects (e.g. there are no allocative externalities nor complementarities) or signals are one-dimensional. Moreover, implementation of any choice function via ex-post equilibrium is generically impossible with informational externalities and multidimensional types. A theory of information constraints with multidimensional signals is rather complex, but indispensable for our study.

Enriched elderly virtual profiles by means of a multidimensional integrated assessment platform

The pressure over Healthcare systems is increasing in most developed countries. The generalized aging of the population is one of the main causes. This situation is even worse in underdeveloped, sparsely populated regions like Extremadura in Spain or Alentejo in Portugal. The authors propose to use the Situational-Context, a technique to seamlessly adapt Internet of Things systems to the needs and preferences of their users, for virtually modeling the elderly. These models could be used to enhance the elderly experience when using those kind of systems without raising the need for technical skills or the costs of implementing such systems by the regional healthcare systems. In this paper, the integration of a multidimensional integrated assessment platform with such virtual profiles is presented. The assessment platform provides and additional source of information for the virtual profiles that is used to better adapt existing systems to the elders needs

A top-down appraoch to patent mapping

Patent mapping [1] is an attempt to present competitive patent information in graphical form for strategic decision-making purposes. Currently, patent mapping is a bottom-up process, starting from the structured data recorded in patents, through data mining, and ending at multidimensional graphs. A problem is that, as databases expand and consequently mining methods become complicated, the resultant increase in dimensions of visualisations make interpretations more difficult. In fact patent mapping need not be a bottom-up process, as we propose a new top-down approach that is based upon the widely accepted Theory of Innovative Problem Solving (TRIZ) [2]. In order to avoid statistical analysis of many patents, this TRIZ-led patent mapping, first, begins with comprehension of patent competition rules using simple gaming models before visualising competitive environments and technical correlations; then key patents are probed for relevant techniques finally reaching an analysis of technical innovation (Figure 1 below). The research addresses: (i) a critical review of current patent mapping; (ii) explanation of how TRIZ can inform a new patent mapping method; and (iii) application of this new method to a case study in aluminium beverage can manufacturing. The conclusion is that a TRIZ-led mapping method reveals synergistic relationships between patents that are not identified by current method

25 Years of CIO and IT Leadership – Revisiting Managerial Roles in Information Systems Research

Knowledge-intensive organizations are challenged by the digitization of business models and the need for IT knowledge throughout entire organizations. This changes the role of CIOs from a central IT leader towards a digitization ambassador for the whole organization. In this research, we develop and validate a multidimensional IT leadership roles construct, theoretically grounded on Mintzberg’s managerial roles. We empirically evolve the construct based on a quantitative survey among 228 CIOs in the U.S., where we assess the management roles of prior information systems research. Based on the empirical analysis, we add a new role definition. The result is an updated, comprehensive, and modernized IT leadership construct, taking the role of the CIO not only as IT leader, but as central agency for developing a digital mindset in the top management team but also throughout the whole organization. Thus, we contribute to 25 years of information systems research in that field

Efficient spectrum occupancy prediction exploiting multidimensional correlations through composite 2D-LSTM models

In cognitive radio systems, identifying spectrum opportunities is fundamental to efficiently use the spectrum. Spectrum occupancy prediction is a convenient way of revealing opportunities based on previous occupancies. Studies have demonstrated that usage of the spectrum has a high correlation over multidimensions, which includes time, frequency, and space. Accordingly, recent literature uses tensor-based methods to exploit the multidimensional spectrum correlation. However, these methods share two main drawbacks. First, they are computationally complex. Second, they need to re-train the overall model when no information is received from any base station for any reason. Different than the existing works, this paper proposes a method for dividing the multidimensional correlation exploitation problem into a set of smaller sub-problems. This division is achieved through composite two-dimensional (2D)-long short-term memory (LSTM) models. Extensive experimental results reveal a high detection performance with more robustness and less complexity attained by the proposed method. The real-world measurements provided by one of the leading mobile network operators in Turkey validate these results

Cloud/web mapping and geoprocessing services - Intelligently linking geoinformation

We live in a world that is alive with information and geographies. ‘‘Everything happens somewhere” (Tosta, 2001). This reality is being exposed in the digital earth technologies providing a multidimensional, multi-temporal and multi-resolution model of the planet, based on the needs of diverse actors: from scientists to decision makers, communities and citizens (Brovelli et al., 2015). We are building up a geospatial information infrastructure updated in real time thanks to mobile, positioning and sensor observations. Users can navigate, not only through space but also through time, to access historical data and future predictions based on social and/or environmental models. But how do we find the information about certain geographic locations or localities when it is scattered in the cloud and across the web of data behind a diversity of databases, web services and hyperlinked pages? We need to be able to link geoinformation together in order to integrate it, make sense of it, and use it appropriately for managing the world and making decisions