Enterprise apps across the product life cycle

Enterprise apps across the product life cycle

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Apps on mobile devices like smartphones have become the core of the digital life of consumers. Apps are used, e. g., for shopping or communicating in social networks. Recently, apps are gaining more and more attention in enterprises as enabler for agile process optimization. In this article, we discuss the potentials and challenges of exploiting th...

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... LCDPs address this growing demand for company-specific software applications for processing information and digitizing processes. Furthermore, they support the trend towards the use of apps on mobile devices by creating essential prerequisites for programming "enterprise apps" (Gröger et al., 2013). ...
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... The increasing use of digital learning apps is part of a larger societal trend in which apps running on cellphones and tablets are serving multiple purposes in daily life ranging from mediating adolescents' social interactions to facilitating manufacturing (Gröger et al., 2013;Harari et al., 2019). With this wide range of uses, apps are being downloaded in high numbers (e.g., 205.4 billion mobile apps downloaded in 2018). ...
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... • Efficacy was defined as the ability to produce a desired or intended result [50]. • Technology apps were defined as applications for novel mobile consumer devices with a touchscreen, especially smartphones and tablet PCs [51]. In this review, the terms "app" is sued in the stricter sense with more on self-monitoring apps. ...
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... De acuerdo a la definición de Gröger et al. (2013) las apps son aplicaciones utilizadas en cualquier dispositivo informático, normalmente dispositivos de pantalla táctil como tabletas; mientras que VMs son representaciones interactivas visuales de un objeto dinámico (Moyer et al., 2002), que presenta oportunidades para construir conocimiento matemático, podemos decir que distintas apps contienen dichos VMs. ...
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... The term App was originally used in the context of mobile platforms such as iOS and Android. However, there is yet no established common definition [7]. An App is essentially a software application or web application with a limited range of functions. ...
Chapter
Software is playing an ever-increasing role in providing the flexibility and efficiency required for handling complex processes. However, the IT capabilities of manufacturers are mostly limited to legacy systems or expensive, slow and inflexible development of new software. Therefore, new paradigms are needed for managing and scaling modern manufacturing processes with the help of software systems. This paper presents the organizational concepts of a software eco-system for the shop floor based on independent software modules called Apps. Additionally, we present the methodology used in the creation of industrial Apps. These concepts were successfully implemented in real world manufacturing scenarios. We focus on describing the specific challenges and requirements for industrial Apps, the technical architecture of the ScaleIT platform and a step by step process model to identify App ideas. An evaluation in the form of a questionnaire describes the assessment of the App-based approach by an industrial consortium.
... 47 Vgl. Caus et al. (2010), S. 243, Gröger et al. (2013), Giessmann et al. (2012), Fitzek und Reichert (2007). 48 Vgl. ...
Thesis
Mobile Applikationen gewinnen in Unternehmen zunehmend an Bedeutung. Der betriebliche Trend zur Einführung von Mobile Business Apps folgt der Entwicklung, die im privaten Nutzungskontext seit Jahren anhält. Betrieblich genutzte Mobile Business Apps der ersten Generation unterstützen in der Regel fragmentierte Querschnittsaufgaben, wie Kommunikation oder Filesharing. Seit ein paar Jahren entwickelt sich der Trend in Unternehmen weiter zu spezialisierten Mobile Business Apps aus der Cloud. Hierzu zählen unternehmensindividuell angepasste Mobile Business Apps, die zur Unterstützung von mobil arbeitenden Mitarbeitern bei spezifischen Transaktionen dienen. Bei der Beschaffung von Mobile Business Apps stehen Entscheider der IT-Abteilungen vor einer Herausforderung, die sich in Komplexität und Umfang nach der Art der zu beschaffenden Mobile Business App richtet. So sind etwa nutzungsoffene Mobile Business Apps out-of-the-box für Querschnittsaufgaben recht einfach, zu vergleichsweise niedrigen Kosten, implementierbar. Die Beschaffung und Einführung nutzungsspezifischer Mobile Business Apps der zweiten Generation, stellen hingegen eher komplexe Unterfangen dar. Phasenmodellen des betrieblichen Software-Beschaffungsablaufs folgend, werden von den Entscheidungsbeteiligten Informationen zu Software und Hersteller konsumiert, wobei keine Aussage über die Quelle der Informationen getroffen wird. Die vorliegende Arbeit widmet sich nun der Frage, ob im betrieblichen Kontext Kundenrezensionen genutzt werden, da diese in öffentlich zugängigen App Shops verfügbar sind. Dem Trend des Konsumgütermarketings folgend, ist die Wahrnehmung von Kundenrezensionsinformation Gegenstand zahlreicher wissenschaftlicher Arbeiten, häufig unter Nutzung der Modelle der persuasiven Informationsverarbeitung. Grundlegend wird die Frage gestellt, nach welchen Merkmalen die zahlreichen und verschiedenen Typen von Mobile Business Apps, im Hinblick auf die Beschaffungsaufgabe, eingeordnet werden können. Die Analyse der Kundenrezensionsinformation in App Shops dient zur Darstellung, welche Typen von Informationsfragmenten in Kundenrezensionen zur Verfügung stehen. Unter Berücksichtigung der verschiedenen Typen von Mobile Business Apps, wird die Frage beantwortet, welche Typen von Informationen aus Kundenrezensionen von Entscheidern als nützlich beurteilt werden. Somit wird ein Forschungsbeitrag zu Einflussfaktoren auf die wahrgenommene Nützlichkeit der Informationen geleistet. Teil des Forschungsbeitrags ist zudem die Untersuchung subjektiver Zuschreibungen und Heuristiken der Nachfrager, die eine Aussage über die wahrgenommene Vertrauenswürdigkeit von Kundenrezensionen zulassen. Unter Diversifizierung dreier verschiedener Beschaffungs-Konstellationen, den betrieblichen Einzelkaufentscheidungen, den Buying Centern mit IT-Experten bei der Beschaffung von nutzungsoffenen Business Apps und, als Drittes, den nutzungsspezifischen Mobile Business Apps, werden Experten zu Ihrer Wahrnehmung und Praxis befragt. Diese Arbeit schließt mit Handlungsempfehlungen für Business-App-Hersteller und App-Shop-Betreiber und identifiziert weiteren Forschungsbedarf.
... With the popularity of smart-phones and similar tablet devices, the practicality of implementing a standardized modular application-driven environment in industrial settings is gaining support. Gröger et al. [47] discusses the idea of a "App"-based manufacturing tool-set. With a unified platform for application development users could develop specific tools that aid in every level of production manufacturing. ...
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Machine learning (ML) (a subset of artificial intelligence that focuses on autonomous computer knowledge gain) is actively being used across many domains, such as entertainment, commerce, and increasingly in industrial settings. The wide applicability and low barriers for development of these algorithms are allowing for innovations, once thought unattainable, to be realized in an ever more digital world. As these innovations continue across industries, the manufacturing industry has also begun to gain benefits. With the current push for Smart Manufacturing and Industrie 4.0, ML for manufacturing is experiencing unprecedented levels of interest; but how much is industry actually using these highly-publicized techniques? This paper sorts through a decade of manufacturing publications to quantify the amount of effort being put towards advancing ML in manufacturing. This work identifies both prominent areas of ML use, and popular algorithms. This also allows us to highlight any gaps, or areas where ML could play a vital role. To maximize the search space utilization of this investigation, ML based Natural Language Processing (NLP) techniques were employed to rapidly sort through a vast corpus of engineering documents to identify key areas of research and application, as well as uncover documents most pertinent to this survey. The salient outcome of this research is the presentation of current focus areas and gaps in ML applications to the manufacturing industry, with particular emphasis on cross domain knowledge utilization. A full detailing of methods and findings is presented.