@inproceedings{5590,
  abstract     = {{Nowadays, providing employees with failure-free access to various systems, applications and services is a crucial factor for organizations? success as disturbances potentially inhibit smooth workflows and thereby harm productivity. However, it is a challenging task to assign access rights to employees? accounts within a satisfying time frame. In addition, the management of multiple accounts and identities can be very onerous and time consuming for the responsible administrator and therefore expensive for the organization. In order to meet these challenges, firms decide to invest in introducing an Identity and Access Management System (IAMS) that supports the organization by using policies to assign permissions to accounts, groups, and roles. In practice, since various versions of IAMSs exist, it is a challenging task to decide upon introduction of an IAMS. The following study proposes a first attempt of a decision support model for practitioners which considers four alternatives: Introduction of an IAMS with Role-based Access Control RBAC) or without and no introduction of IAMS again with or without RBAC. To underpin the practical applicability of the proposed model, we parametrize and operationalize it based on a real world use case using input from an expert interview.}},
  author       = {{Weishäupl, Eva and Kunz, Michael and Yasasin, Emrah and Wagner, Gerit and Prester, Julian and Schryen, Guido and Pernul, Günther}},
  booktitle    = {{2nd International Workshop on Security in highly connected IT Systems (SHCIS?15)}},
  keywords     = {{Identity and Access Management, Economic Decision Making, Information Systems, Information Security Investment, Decision Theory}},
  title        = {{{Towards an Economic Approach to Identity and Access Management Systems Using Decision Theory}}},
  year         = {{2015}},
}

@inproceedings{11716,
  abstract     = {{The accuracy of automatic speech recognition systems in noisy and reverberant environments can be improved notably by exploiting the uncertainty of the estimated speech features using so-called uncertainty-of-observation techniques. In this paper, we introduce a new Bayesian decision rule that can serve as a mathematical framework from which both known and new uncertainty-of-observation techniques can be either derived or approximated. The new decision rule in its direct form leads to the new significance decoding approach for Gaussian mixture models, which results in better performance compared to standard uncertainty-of-observation techniques in different additive and convolutive noise scenarios.}},
  author       = {{Abdelaziz, Ahmed H. and Zeiler, Steffen and Kolossa, Dorothea and Leutnant, Volker and Haeb-Umbach, Reinhold}},
  booktitle    = {{Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on}},
  issn         = {{1520-6149}},
  keywords     = {{Bayes methods, Gaussian processes, convolution, decision theory, decoding, noise, reverberation, speech coding, speech recognition, Bayesian decision rule, GMM, Gaussian mixture models, additive noise scenarios, automatic speech recognition systems, convolutive noise scenarios, decoding approach, mathematical framework, reverberant environments, significance decoding, speech feature estimation, uncertainty-of-observation techniques, Hidden Markov models, Maximum likelihood decoding, Noise, Speech, Speech recognition, Uncertainty, Uncertainty-of-observation, modified imputation, noise robust speech recognition, significance decoding, uncertainty decoding}},
  pages        = {{6827--6831}},
  title        = {{{GMM-based significance decoding}}},
  doi          = {{10.1109/ICASSP.2013.6638984}},
  year         = {{2013}},
}

@inproceedings{5632,
  abstract     = {{Enduring doubts about the value of IS investments reveal that IS researchers have not fully managed to identify and to explain the economic benefits of IS. Three research tasks are essential requisites on the path towards addressing this criticism: the synthesis of knowledge, the identification of lack of knowledge, and the proposition of paths for closing knowledge gaps. This paper considers each of these tasks by a) synthesizing key research findings based on a comprehensive literature review, b) identifying and unfolding key limitations of current research, and c) applying a decision-theoretic perspective, which opens new horizons to IS business value research and shows paths for overcoming the limitations. The adoption of this perspective results in a decision-theoretic foundation of IS business value research and includes the proposition of a consistent terminology and a research model that frames further research.}},
  author       = {{Schryen, Guido and Bodenstein, Christian}},
  booktitle    = {{Proceedings of the 18th European Conference on Information Systems (ECIS 2010)}},
  keywords     = {{Decision theory, IT value, IS assessment, IS evaluation}},
  title        = {{{A decision-theoretic foundation of IS business value research}}},
  year         = {{2010}},
}