Assimilation of Compliance Software in Highly Regulated Industries: An Empirical Multitheoretical Investigation

In this paper we follow a theory-based approach to study the assimilation of compliance software in highly regulated multinational enterprises. These relatively new software products support the automation of controls which are associated with mandatory compliance requirements. We use institutional and success factor theories to explain the assimilation of compliance software. A framework for analyzing the assimilation of Access Control Systems (ACS), a special type of compliance software, is developed and used to reflect the experiences obtained in four in-depth case studies. One result is that coercive, mimetic, and normative pressures significantly effect ACS assimilation. On the other hand, quality aspects have only a moderate impact at the beginning of the assimilation process, in later phases the impact may increase if performance and improvement objectives become more relevant. In addition, it turns out that position of the enterprises and compatibility heavily influence the assimilation process.

A Process Model of Complementarity and Substitution of Contractual and Relational Governance in IS Outsourcing

This paper develops a process model of how and why complementarity and substitution form over time between contractual and relational governance in the context of information systems outsourcing. Our analysis identifies four distinct process patterns that explain this formation as the outcome of interaction processes between key elements of both contractual and relational governance. These patterns unveil the dynamic nature of complementarity and substitution. In particular, we show that the relationship between contractual and relational governance oscillates between complementarity and substitution. Those oscillations are triggered mainly by three types of contextual events (goal fuzziness, goal conflict, and goal misalignment). Surprisingly, substitution of informal control did not occur as an immediate reaction to external events but emerged as a consequence of preceding complementarity. Thus, our study challenges the prevailing view of an either/or dichotomy of complementarity and substitution by showing that they are causally connected over time.

Early follicular testosterone level predicts preference for masculinity in male faces — But not for women taking hormonal contraception

It has been shown that women’s preference for masculinity in male faces changes across the menstrual cycle. Preference for masculinity is stronger when conception probability is high than when it is low. These findings have been linked to cyclic fluctuations of hormone levels. The purpose of the present study is to further investigate the link between gonadal steroids (i.e. testosterone, estradiol, and progesterone) and masculinity preference in women, while holding the cycle phase constant. Sixty-two female participants were tested in their early follicular cycle phase, when conception probability is low. Participants were shown face pairs and where asked to choose the more attractive face. Face pairs consisted of a masculinized and feminized version of the same face. For naturally cycling women we found a positive relationship between saliva testosterone levels and masculinity preference, but there was no link between any hormones and masculinity preference for women taking hormonal contraception. We conclude that in naturally cycling women early follicular testosterone levels are associated with masculinity preference. However, these hormonal links were not found for women with artificially modified hormonal levels, that is, for women taking hormonal contraception.

Development of a Rasch homogenous short form of the Pathological Narcissism Inventory

During the last decades, the narcissistic personality inventory (npi) was the most widely used questionnaire to measure narcissism as a personality trait. But the npi assesses grandiose narcissism only, while recent discussions emphasize the existence of vulnerable narcissism. The pathological narcissism inventory (pni, pincus et al., 2009) is a new questionnaire assessing these different aspects of narcissism. However, with 54 items on seven subscales, the pni is quite long to serve as a screening tool for narcissistic traits. We therefore developed a short form to facilitate its application in research and practice. Even though the pni covers different symptoms of narcissism, they are all expressions of the same underlying construct. We therefore used the rasch model to guide the item selection. Method and results: a sample of 1837 participants (67.5% female, mean age 26.8 years) was used to choose the items for the short form. Two criteria were adopted: all aspects, represented by the seven subscales in the original, should be retained, and items should be rasch homogenous. In a step-by-step procedure we excluded items successively until reaching a homogenous pool of 22 items. All remaining items had satisfactory fit indices and fitstatistics for the model were good. characteristics of the resulting short form were tested using a new independent validation sample (n=104, mean age = 32.8, 45% female). Correlations of the short pni with different validation measures were comparable to the correlations obtained with the original form, indicating that the two forms were equivalent. Conclusion: the resulting one-dimensional measure can be used as a screening questionnaire for pathological narcissism. The rasch homogeneity facilitates the comparison of narcissism scores among a variety of samples.

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Privacy Panel: Usable and Quantifiable Mobile Privacy

The ever increasing popularity of apps stems from their ability to provide highly customized services to the user. The flip side is that in order to provide such services, apps need access to very sensitive private information about the user. This leads to malicious apps that collect personal user information in the background and exploit it in various ways. Studies have shown that current app vetting processes which are mainly restricted to install time verification mechanisms are incapable of detecting and preventing such attacks. We argue that the missing fundamental aspect here is a comprehensive and usable mobile privacy solution, one that not only protects the user's location information, but also other equally sensitive user data such as the user's contacts and documents. A solution that is usable by the average user who does not understand or care about the low level technical details. To bridge this gap, we propose privacy metrics that quantify low-level app accesses in terms of privacy impact and transforms them to high-level user understandable ratings. We also provide the design and architecture of our Privacy Panel app that represents the computed ratings in a graphical user-friendly format and allows the user to define policies based on them. Finally, experimental results are given to validate the scalability of the proposed solution.

Canonical proof nets for classical logic

Proof nets provide abstract counterparts to sequent proofs modulo rule permutations; the idea being that if two proofs have the same underlying proof-net, they are in essence the same proof. Providing a convincing proof-net counterpart to proofs in the classical sequent calculus is thus an important step in understanding classical sequent calculus proofs. By convincing, we mean that (a) there should be a canonical function from sequent proofs to proof nets, (b) it should be possible to check the correctness of a net in polynomial time, (c) every correct net should be obtainable from a sequent calculus proof, and (d) there should be a cut-elimination procedure which preserves correctness. Previous attempts to give proof-net-like objects for propositional classical logic have failed at least one of the above conditions. In Richard McKinley (2010) [22], the author presented a calculus of proof nets (expansion nets) satisfying (a) and (b); the paper defined a sequent calculus corresponding to expansion nets but gave no explicit demonstration of (c). That sequent calculus, called LK∗ in this paper, is a novel one-sided sequent calculus with both additively and multiplicatively formulated disjunction rules. In this paper (a self-contained extended version of Richard McKinley (2010) [22]), we give a full proof of (c) for expansion nets with respect to LK∗, and in addition give a cut-elimination procedure internal to expansion nets – this makes expansion nets the first notion of proof-net for classical logic satisfying all four criteria.

Update as Evidence: Belief Expansion

We introduce a justification logic with a novel constructor for evidence terms, according to which the new information itself serves as evidence for believing it. We provide a sound and complete axiomatization for belief expansion and minimal change and explain how the minimality can be graded according to the strength of reasoning. We also provide an evidential analog of the Ramsey axiom.

Robust Denoising using Feature and Color Information

We propose a method that robustly combines color and feature buffers to denoise Monte Carlo renderings. On one hand, feature buffers, such as per pixel normals, textures, or depth, are effective in determining denoising filters because features are highly correlated with rendered images. Filters based solely on features, however, are prone to blurring image details that are not well represented by the features. On the other hand, color buffers represent all details, but they may be less effective to determine filters because they are contaminated by the noise that is supposed to be removed. We propose to obtain filters using a combination of color and feature buffers in an NL-means and cross-bilateral filtering framework. We determine a robust weighting of colors and features using a SURE-based error estimate. We show significant improvements in subjective and quantitative errors compared to the previous state-of-the-art. We also demonstrate adaptive sampling and space-time filtering for animations.