Explaining Endogenous Control Change in Outsourced Software Projects

Given the centrality of control for achieving success in outsourced software projects, past research has identified key exogenous factors that determine the choice of controls. This view of exogenously driven control choice is based on a number of assumptions; particularly, clients and vendors are seen as separate cognitive entities that combat opportunistic threats under environmental uncertainty by one-off choices or infrequent revisions of controls. In this paper we complement this perspective by acknowledging that an outsourced software project may be characterized as a collective, evolving process faced with the challenge of coping with cognitive limitations of both client and vendor through a continuous process of learning. We argue that if viewed in this way, controls are less subject of a deliberate choice but rather are subject of endogenously driven change, i.e. controls evolve in close interaction with the evolving software project. Accordingly, we suggest a complementary model of endogenous control, where controls mediate individual and collective learning processes. Our research contributes to a better understanding of the dynamics in outsourced software projects. It also spells out methodological implications that may help improve cross-section control research.

Justification of Data Warehousing Projects

Project justification is regarded as one of the major methodological deficits in Data Warehousing practice. As reasons for applying inappropriate methods, performing incomplete evaluations, or even entirely omitting justifications, the special nature of Data Warehousing benefits and the large portion of infrastructure-related activities are stated. In this paper, the economic justification of Data Warehousing projects is analyzed, and first results from a large academiaindustry collaboration project in the field of non-technical issues of Data Warehousing are presented. As conceptual foundations, the role of the Data Warehouse system in corporate application architectures is analyzed, and the specific properties of Data Warehousing projects are discussed. Based on an applicability analysis of traditional approaches to economic IT project justification, basic steps and responsibilities for the justification of Data Warehousing projects are derived.

The Big Five in Context: Personality, Diversity and Attitudes toward Equal Opportunities for Immigrants in Switzerland

The paper analyzes the link between personality traits and attitudes of Swiss citizens toward equal opportunities for immigrants. In particular, we examine the extent to which this relationship is moderated by the socio-structural context. We test the assumption that the direct links between personality traits and attitudes toward equal opportunities are strengthened by perceived ethnic diversity. Based on our empirical analyses, we are able to replicate central findings of the research on personality traits and attitudes toward immigrants for the Swiss context. While openness toward experience and agreeableness are positively related to a preference for equal opportunities, conscientiousness is negatively linked to these attitudes. Furthermore, our results reveal that the link between conscientiousness and attitudes toward equal opportunities is significantly moderated by the perceived share of foreigners in the neighborhood. This finding is especially relevant for future research on the effects of personality traits.

Scientific drilling projects in ancient lakes: Integrating geological and biological histories

Sedimentary sequences in ancient or long-lived lakes can reach several thousands of meters in thickness and often provide an unrivalled perspective of the lake's regional climatic, environmental, and biological history. Over the last few years, deep-drilling projects in ancient lakes became increasingly multi- and interdisciplinary, as, among others, seismological, sedimentological, biogeochemical, climatic, environmental, paleontological, and evolutionary information can be obtained from sediment cores. However, these multi- and interdisciplinary projects pose several challenges. The scientists involved typically approach problems from different scientific perspectives and backgrounds, and setting up the program requires clear communication and the alignment of interests. One of the most challenging tasks, besides the actual drilling operation, is to link diverse datasets with varying resolution, data quality, and age uncertainties to answer interdisciplinary questions synthetically and coherently. These problems are especially relevant when secondary data, i.e., datasets obtained independently of the drilling operation, are incorporated in analyses. Nonetheless, the inclusion of secondary information, such as isotopic data from fossils found in outcrops or genetic data from extant species, may help to achieve synthetic answers. Recent technological and methodological advances in paleolimnology are likely to increase the possibilities of integrating secondary information. Some of the new approaches have started to revolutionize scientific drilling in ancient lakes, but at the same time, they also add a new layer of complexity to the generation and analysis of sediment-core data. The enhanced opportunities presented by new scientific approaches to study the paleolimnological history of these lakes, therefore, come at the expense of higher logistic, communication, and analytical efforts. Here we review types of data that can be obtained in ancient lake drilling projects and the analytical approaches that can be applied to empirically and statistically link diverse datasets to create an integrative perspective on geological and biological data. In doing so, we highlight strengths and potential weaknesses of new methods and analyses, and provide recommendations for future interdisciplinary deep-drilling projects.

Putting Up a Big Front: Car Design and Size Affect Road-Crossing Behaviour

Previous research suggests that people tend to see faces in car fronts and that they attribute personality characteristics to car faces. In the present study we investigated whether car design influences pedestrian road-crossing behaviour. An immersive virtual reality environment with a zebra crossing scenario was used to determine a) whether the minimum accepted distance for crossing the street is larger for cars with a dominant appearance than for cars with a friendly appearance and b) whether the speed of dominant-looking cars is overestimated as compared to friendly-looking cars. Participants completed both tasks while either standing on the pavement or on the centre island. We found that people started to cross the road later in front of friendly-looking low-power cars compared to dominant-looking high-power cars, but only if the cars were relatively large in size. For small cars we found no effect of power. The speed of smaller cars was estimated to be higher compared to large cars (size-speed bias). Furthermore, there was an effect of starting position: From the centre island, participants entered the road significantly later (i. e. closer to the approaching car) and left the road later than when starting from the pavement. Similarly, the speed of the cars was estimated significantly lower when standing on the centre island compared to the pavement. To our knowledge, this is the first study to show that car fronts elicit responses on a behavioural level.