34 resultados para Information Systems Applications
Resumo:
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.
Resumo:
Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.
Resumo:
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.
Resumo:
Current advanced cloud infrastructure management solutions allow scheduling actions for dynamically changing the number of running virtual machines (VMs). This approach, however, does not guarantee that the scheduled number of VMs will properly handle the actual user generated workload, especially if the user utilization patterns will change. We propose using a dynamically generated scaling model for the VMs containing the services of the distributed applications, which is able to react to the variations in the number of application users. We answer the following question: How to dynamically decide how many services of each type are needed in order to handle a larger workload within the same time constraints? We describe a mechanism for dynamically composing the SLAs for controlling the scaling of distributed services by combining data analysis mechanisms with application benchmarking using multiple VM configurations. Based on processing of multiple application benchmarks generated data sets we discover a set of service monitoring metrics able to predict critical Service Level Agreement (SLA) parameters. By combining this set of predictor metrics with a heuristic for selecting the appropriate scaling-out paths for the services of distributed applications, we show how SLA scaling rules can be inferred and then used for controlling the runtime scale-in and scale-out of distributed services. We validate our architecture and models by performing scaling experiments with a distributed application representative for the enterprise class of information systems. We show how dynamically generated SLAs can be successfully used for controlling the management of distributed services scaling.
Resumo:
Limited in motivation and cognitive ability to process the increasing amount of information on their Newsfeed, users apply heuristic processing to form their attitudes. Rather than extensively analysing the content, they increasingly rely on heuristic cues – such as the amount of comments and likes as well as the level of relationship with the “poster” – to process the incoming information. In the paper we explore what impact these heuristic cues have on the affective and cognitive attitude of users towards the posts on their Newsfeed. We conduct a survey on based on a Facebook application that allows users to evaluate Newsfeed posts in real time. Applying two distinct panel-regression methods we report robust results that indicate that there is a certain relationship primacy effect when users are processing information: only if the level of relationship with the “poster” is low, the impact of comments and likes on the attitude is considered, whereby likes trigger positive, whereas comments – negative evaluations.
Resumo:
The problem of information overload on Facebook is exacerbating as users expand their networks. Growing quantity and increasingly poor quality of information on the Newsfeed may interfere with the hedonic experience of users resulting in frustration and dissatisfaction. In the long run, such developments threaten to undermine sustainability of the platform. To address these issues, our study adopts a grounded theory approach to explore the phenomenon of information overload on Facebook. We investigate main sources of information overload, identify strategies users adopt to deal with it as well as possible consequences. In-depth analysis of the phenomenon allows us to uncover individual peculiarities for identification of relevant information. Based on them we provide valuable recommendations for network providers.
Resumo:
This chapter introduces a conceptual model to combine creativity techniques with fuzzy cognitive maps (FCMs) and aims to support knowledge management methods by improving expert knowledge acquisition and aggregation. The aim of the conceptual model is to represent acquired knowledge in a manner that is as computer-understandable as possible with the intention of developing automated reasoning in the future as part of intelligent information systems. The formal represented knowledge thus may provide businesses with intelligent information integration. To this end, we introduce and evaluate various creativity techniques with a list of attributes to define the most suitable to combine with FCMs. This proposed combination enables enhanced knowledge management through the acquisition and representation of expert knowledge with FCMs. Our evaluation indicates that the creativity technique known as mind mapping is the most suitable technique in our set. Finally, a scenario from stakeholder management demonstrates the combination of mind mapping with FCMs as an integrated system.
Resumo:
Many technological developments of the past two decades come with the promise of greater IT flexi-bility, i.e. greater capacity to adapt IT. These technologies are increasingly used to improve organiza-tional routines that are not affected by large, hard-to-change IT such as ERP. Yet, most findings on the interaction of routines and IT stem from contexts where IT is hard to change. Our research ex-plores how routines and IT co-evolve when IT is flexible. We review the literatures on routines to sug-gest that IT may act as a boundary object that mediates the learning process unfolding between the ostensive and the performative aspect of the routine. Although prior work has concluded from such conceptualizations that IT stabilizes routines, we qualify that flexible IT can also stimulate change because it enables learning in short feedback cycles. We suggest that, however, such change might not always materialize because it is contingent on governance choices and technical knowledge. We de-scribe the case-study method to explore how routines and flexible IT co-evolve and how governance and technical knowledge influence this process. We expect to contribute towards stronger theory of routines and to develop recommendations for the effective implementation of flexible IT in loosely coupled routines.