The German business and information technologies project

The Business and Information Technologies (BIT) project strives to reveal new insights into how modern IT impacts organizational structures and business practices using empirical methods. Due to its international scope, it allows for inter-country comparison of empirical results. Germany — represented by the European School of Management and Technologies (ESMT) and the Institute of Information Systems at Humboldt-Universität zu Berlin — joined the BIT project in 2006. This report presents the result of the first survey conducted in Germany during November–December 2006. The key results are as follows: • The most widely adopted technologies and systems in Germany are websites, wireless hardware and software, groupware/productivity tools, and enterprise resource planning (ERP) systems. The biggest potential for growth exists for collaboration and portal tools, content management systems, business process modelling, and business intelligence applications. A number of technological solutions have not yet been adopted by many organizations but also bear some potential, in particular identity management solutions, Radio Frequency Identification (RFID), biometrics, and third-party authentication and verification. • IT security remains on the top of the agenda for most enterprises: budget spending was increasing in the last 3 years. • The workplace and work requirements are changing. IT is used to monitor employees' performance in Germany, but less heavily compared to the United States (Karmarkar and Mangal, 2007).1 The demand for IT skills is increasing at all corporate levels. Executives are asking for more and better structured information and this, in turn, triggers the appearance of new decision-making tools and online technologies on the market. • The internal organization of companies in Germany is underway: organizations are becoming flatter, even though the trend is not as pronounced as in the United States (Karmarkar and Mangal, 2007), and the geographical scope of their operations is increasing. Modern IT plays an important role in enabling this development, e.g. telecommuting, teleconferencing, and other web-based collaboration formats are becoming increasingly popular in the corporate context. • The degree to which outsourcing is being pursued is quite limited with little change expected. IT services, payroll, and market research are the most widely outsourced business functions. This corresponds to the results from other countries. • Up to now, the adoption of e-business technologies has had a rather limited effect on marketing functions. Companies tend to extract synergies from traditional printed media and on-line advertising. • The adoption of e-business has not had a major impact on marketing capabilities and strategy yet. Traditional methods of customer segmentation are still dominating. The corporate identity of most organizations does not change significantly when going online. • Online sales channel are mainly viewed as a complement to the traditional distribution means. • Technology adoption has caused production and organizational costs to decrease. However, the costs of technology acquisition and maintenance as well as consultancy and internal communication costs have increased.

An Exploratory Study of Data Quality Management Practices in the ERP Software Systems Context

Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

Approximate decoding approaches for network coded correlated data

This paper considers a framework where data from correlated sources are transmitted with the help of network coding in ad hoc network topologies. The correlated data are encoded independently at sensors and network coding is employed in the intermediate nodes in order to improve the data delivery performance. In such settings, we focus on the problem of reconstructing the sources at decoder when perfect decoding is not possible due to losses or bandwidth variations. We show that the source data similarity can be used at decoder to permit decoding based on a novel and simple approximate decoding scheme. We analyze the influence of the network coding parameters and in particular the size of finite coding fields on the decoding performance. We further determine the optimal field size that maximizes the expected decoding performance as a trade-off between information loss incurred by limiting the resolution of the source data and the error probability in the reconstructed data. Moreover, we show that the performance of the approximate decoding improves when the accuracy of the source model increases even with simple approximate decoding techniques. We provide illustrative examples showing how the proposed algorithm can be deployed in sensor networks and distributed imaging applications.

Firm-level strategic orientation and performance: a synthesis and extension of the knowledge base on entrepreneurial, market and learning orientation

Should a firm stay focused or should it rather adopt a broader strategic perspective? This dissertation summarizes and extends the existing knowledge base on entrepreneurial, market, and learning orientation. Building on multiple theoretical perspectives, empirical evidence from prior studies, as well as on survey and archival data collected in two economic contexts, performance effects from individual orientations, their dimensions and combinations are explored. Results reveal that the three strategic orientations are highly interrelated and that their relationship to firm performance is more complex than previously assumed.

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.

Analyzing spatio-temporal patterns of genuine cross-correlations

In multivariate time series analysis, the equal-time cross-correlation is a classic and computationally efficient measure for quantifying linear interrelations between data channels. When the cross-correlation coefficient is estimated using a finite amount of data points, its non-random part may be strongly contaminated by a sizable random contribution, such that no reliable conclusion can be drawn about genuine mutual interdependencies. The random correlations are determined by the signals' frequency content and the amount of data points used. Here, we introduce adjusted correlation matrices that can be employed to disentangle random from non-random contributions to each matrix element independently of the signal frequencies. Extending our previous work these matrices allow analyzing spatial patterns of genuine cross-correlation in multivariate data regardless of confounding influences. The performance is illustrated by example of model systems with known interdependence patterns. Finally, we apply the methods to electroencephalographic (EEG) data with epileptic seizure activity.

Validation of climate model-inferred regional temperature change for late-glacial Europe

Comparisons of climate model hindcasts with independent proxy data are essential for assessing model performance in non-analogue situations. However, standardized palaeoclimate data sets for assessing the spatial pattern of past climatic change across continents are lacking for some of the most dynamic episodes of Earth’s recent past. Here we present a new chironomid-based palaeotemperature dataset designed to assess climate model hindcasts of regional summer temperature change in Europe during the late-glacial and early Holocene. Latitudinal and longitudinal patterns of inferred temperature change are in excellent agreement with simulations by the ECHAM-4 model, implying that atmospheric general circulation models like ECHAM-4 can successfully predict regionally diverging temperature trends in Europe, even when conditions differ significantly from present. However, ECHAM-4 infers larger amplitudes of change and higher temperatures during warm phases than our palaeotemperature estimates, suggesting that this and similar models may overestimate past and potentially also future summer temperature changes in Europe.

The application of medical informatics to the veterinary management programs at companion animal practices in Alberta, Canada: a case study.

Companion animals closely share their domestic environment with people and have the potential to, act as sources of zoonotic diseases. They also have the potential to be sentinels of infectious and noninfectious, diseases. With the exception of rabies, there has been minimal ongoing surveillance of, companion animals in Canada. We developed customized data extraction software, the University of, Calgary Data Extraction Program (UCDEP), to automatically extract and warehouse the electronic, medical records (EMR) from participating private veterinary practices to make them available for, disease surveillance and knowledge creation for evidence-based practice. It was not possible to build, generic data extraction software; the UCDEP required customization to meet the specific software, capabilities of the veterinary practices. The UCDEP, tailored to the participating veterinary practices', management software, was capable of extracting data from the EMR with greater than 99%, completeness and accuracy. The experiences of the people developing and using the UCDEP and the, quality of the extracted data were evaluated. The electronic medical record data stored in the data, warehouse may be a valuable resource for surveillance and evidence-based medical research.

Mining free-text medical records for companion animal enteric syndrome surveillance.

Large amounts of animal health care data are present in veterinary electronic medical records (EMR) and they present an opportunity for companion animal disease surveillance. Veterinary patient records are largely in free-text without clinical coding or fixed vocabulary. Text-mining, a computer and information technology application, is needed to identify cases of interest and to add structure to the otherwise unstructured data. In this study EMR's were extracted from veterinary management programs of 12 participating veterinary practices and stored in a data warehouse. Using commercially available text-mining software (WordStat™), we developed a categorization dictionary that could be used to automatically classify and extract enteric syndrome cases from the warehoused electronic medical records. The diagnostic accuracy of the text-miner for retrieving cases of enteric syndrome was measured against human reviewers who independently categorized a random sample of 2500 cases as enteric syndrome positive or negative. Compared to the reviewers, the text-miner retrieved cases with enteric signs with a sensitivity of 87.6% (95%CI, 80.4-92.9%) and a specificity of 99.3% (95%CI, 98.9-99.6%). Automatic and accurate detection of enteric syndrome cases provides an opportunity for community surveillance of enteric pathogens in companion animals.

Target difficulty, intra-year target revisions and firm performance: evidence from business units' targets

Target difficulty is often argued to increase performance. While this association is well established in experimental research, empirical evidence in field research is rather mixed. We attempt to explain this inconsistency by analyzing the importance of intra-year target revisions, which are especially prevalent in real-world field settings. Using survey and archival data from 97 firms, we find that firms with more challenging business unit targets revise targets more often, in line with asymmetric, downward target revisions. Results further show that the degree to which targets are revised during a period results in negative effects on firm performance, as the anticipation of revision negatively affects the business unit management’s performance incentives. Additionally, we find that using targets predominantly for either decision-making or control influences the overall performance effects of target revisions. Our findings may partially explain the mixed field study evidence regarding the effects of target difficulty.

Enterprise software adoption and perceived business performance — an empirical investigation in Germany and the U.S.

This work contributes to the ongoing debate on the productivity paradox by considering CIOs’ perceptions of IT business value. Applying regression analysis to data from an international survey, we study how the adoption of certain types of enterprise software affects the CIOs’ perception of the impact of IT on the firm’s business activities and vice versa. Other potentially important factors such as country, sector and size of the firms are also taken into account. Our results indicate a more significant support for the impact of perceived IT benefits on adoption of enterprise software than vice versa. CIOs based in the US perceive IT benefits more strongly than their German counterparts. Furthermore, certain types of enterprise software seem to be more prevalent in the US.

Performance on auditory and visual temporal informationprocessing is related to psychometric intelligence

The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.