64,816 research outputs found

    Adaptation and survival in new businesses: Understanding the moderating effects of (in)dependence and industry.

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    New ventures as well as new business units experience significant difficulties in finding a viable market application or business model. They often need to adapt their initial business model and this need for adaptation is mainly due to high degrees of uncertainty and ambiguity they are confronted with. This paper hypothesizes that adaptation is crucial for new ventures' and new business units' survival, but that differences exist between the need for adaptation in business units of established companies versus in independent start-ups. According to insights obtained from institutional isomorphism as well as from the resource-based theory of the firm, the effects of adaptation on survival are complex and multifaceted. We test the adaptation-survival hypothesis through a survival analysis of a sample of 117 new ventures and new business units. We find that the main effect of adaptation on survival is negative, but that this effect is moderated and even reversed by the (in) dependence of the new business and by the industry in which it is active.Innovation; Research; Model; Companies; Performance; Startups; Processes; Factors; Effects; Industry; Market; Uncertainty; Theory; Dependence;

    Handling Concept Drift for Predictions in Business Process Mining

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    Predictive services nowadays play an important role across all business sectors. However, deployed machine learning models are challenged by changing data streams over time which is described as concept drift. Prediction quality of models can be largely influenced by this phenomenon. Therefore, concept drift is usually handled by retraining of the model. However, current research lacks a recommendation which data should be selected for the retraining of the machine learning model. Therefore, we systematically analyze different data selection strategies in this work. Subsequently, we instantiate our findings on a use case in process mining which is strongly affected by concept drift. We can show that we can improve accuracy from 0.5400 to 0.7010 with concept drift handling. Furthermore, we depict the effects of the different data selection strategies

    Strategic Orientations and Technology Policy: An Empirical Test of Relationship in Developing Countries

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    There is a growing awareness of the pivotal role of technology in securing and maximizing competitive positions. This study based on primary data from two banks in Nigeria examines the relationship between technology policy and strategy dimensions. Differentiation and futurity strategy dimensions were found to be marginally dominant in the managerial practices of these firms. In addition, the study found new evidence of relationship between the strategy dimensions; and the pattern of relationship between technology policy and strategic orientations indicate the use technology to foster defensive behaviours rather than securing competitive edge. Futurity orientation was also found not to be significantly related with most of the technology policy dimensions investigated. These results are expected to provide management and management theorists with valuable practical insight into the relationship between pattern of strategic orientation and technology policy

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

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    This report documents the program and the outcomes of GI-Dagstuhl Seminar 16394 "Software Performance Engineering in the DevOps World". The seminar addressed the problem of performance-aware DevOps. Both, DevOps and performance engineering have been growing trends over the past one to two years, in no small part due to the rise in importance of identifying performance anomalies in the operations (Ops) of cloud and big data systems and feeding these back to the development (Dev). However, so far, the research community has treated software engineering, performance engineering, and cloud computing mostly as individual research areas. We aimed to identify cross-community collaboration, and to set the path for long-lasting collaborations towards performance-aware DevOps. The main goal of the seminar was to bring together young researchers (PhD students in a later stage of their PhD, as well as PostDocs or Junior Professors) in the areas of (i) software engineering, (ii) performance engineering, and (iii) cloud computing and big data to present their current research projects, to exchange experience and expertise, to discuss research challenges, and to develop ideas for future collaborations
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