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Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
Purpose
In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset.
Design/methodology/approach
In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments.
Findings
Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model.
Originality/value
For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future.
Explorer CEOs: The effect of CEO career variety on large firms’ relative exploration orientation
(2018)
Prior studies demonstrate that firms need to make smart trade-off decisions between exploration and exploitation activities in order to increase performance. Chief executive officers (CEOs) are principal decision makers of a firm’s strategic posture. In this study, we theorize and empirically examine how relative exploration orientation of large publicly listed firms varies based on the career variety of their CEOs – that is, how diverse the professional experiences of executives were prior to them becoming CEOs. We further argue that the heterogeneity and structure of the top management team moderates the impact of CEO career variety on firms’ relative exploration orientation. Based on multisource secondary data for 318 S&P 500 firms from 2005 to 2015, we find that CEO career variety is positively associated with relative exploration orientation.
Interestingly, CEOs with high career varieties appear to be less effective in pursuing exploration, when they work with highly heterogeneous and structurally interdependent top management teams.
Enterprise SOA Roadmap
(2008)
Working paper distributed at 2nd Annual Next Generation Telecommunications Conference 2009, 13th – 14th October 2009, Brussels 14 pages Abstract Governments all over Europe are in the process of adopting new broadband strategies. The objective is to create modern telecommunications networks based on powerful broadband infrastructures". In doing so, they aim for innovative and investment-friendly concepts. For instance, in a recently published consultation paper on the subject the German regulator BNetzA declared that it will take “greater account of … reducing risks, securing the investment and innovation power, providing planning certainty and transparency – in order to support and advance broadband rollout in Germany”. It further states that when regulating wholesale rates it has to be ensured that “… adequate incentives for network rollout are provided on the one hand, while sustainable and fair competition is ensured on the other”. Also an EC draft recommendation on regulated network access is about to set new standards for the regulation of next generation access networks. According to the recommendation the prices of new assets shall be based on costs plus a projectspecific risk premium to be included in the costs of capital for the investment risk incurred by the operator. This approach has been criticised from various sides. In particular it has been questioned whether such an approach is adequate to meet the objectives of encouraging both competition and investment into next generation access networks. Against this background, the concept of “long term risk sharing contracts” has been proposed recently as an approach which does not only incorporate the various additional risks involved in the deployment of NGA infrastructure, but has several other advantages. This paper will demonstrate that the concept allows for competition to evolve at both the retail and wholesale level on fair, objective, non-discriminatory and transparent terms and conditions. Moreover, it ensures the highest possible investment incentive in line with socially desirable outcome. The paper is organised as follows: The next section will briefly outline the importance of encouraging competition and investment in an NGA-environment. The third section will specify the design of long term risk sharing contracts in view of achieving these objectives. The fourth section will examine potential problems associated with the concept. In doing so a way of how to deal with them will be elaborated. The last section will look at arguments against long term risk sharing contracts. It will be shown that these arguments are not strong enough to build a case against introducing such contracts.