Abstract:This article examines the possibilities for increasing organizational performance in the public sector using big data by conducting a systematic literature review. It includes the results of 36 scientific articles published between January 2012 and July 2019. The results show a tendency to explain the relationship between big data and organizational performance through the Resource-Based View of the Firm or the Dynamic Capabilities View, arguing that performance improvement in an organization stems from unique… Show more
“…For the initial search we got around n=79,191 results. Since our primary motive was understanding Human factors and other ergonomic issues related to the Human and autonomy teaming, we narrowed our research [32] to the Ergonomics domain in Web of Science (WoS) that published most articles related to maritime transportation , knowing that some papers could be included in other categories (for instance Business for research that include cost-arguments in relation to maritime safety) Reading the abstracts, we excluded all the articles that were unrelated to the topic leading to n=789 results.. As the topic of HAT is multidisciplinary in nature, similar to [33], we included all the articles found without considering the journal or discipline they belong to.…”
Recent technological advances in the field of Artificial intelligence (AI) and machine learning led to the creation of smart AI-enabled automation systems that are drastically changing maritime transportation. We developed a systematic literature review to understand how automation, based on Information Technologies (IT), has tackled the challenges related to human and machine interactions. We notably discuss the conceptual evolution from Human-Automation Interaction (HAI) to Human Autonomy Teaming (HAT) and present the risks of high levels of automation and the importance of teamwork in safety critical systems. Our results lie on a map of five clusters that highlight the importance of trust in the interactions between humans and machines, the risks related to automation, the human errors that are arising from these interactions, the effects of automation on situational awareness and the social norms in human-computer interactions. This literature show that human-machines interactions have mainly been studied from the computer/information systems' (IS) point of view, hence neglecting the social dimensions of humans. Building on the difference between the concepts of automation and autonomy, we suggest the development of the concept of Social Human Autonomy Machine Teaming (SHAMT) to better consider the social dimensions of humans in these new interactions. Future research should focus on the right equilibrium between social needs, social interactions among humans and with autonomous machines with AI to optimize the global autonomy of the humanmachine teammates in a whole ecosystem.
“…For the initial search we got around n=79,191 results. Since our primary motive was understanding Human factors and other ergonomic issues related to the Human and autonomy teaming, we narrowed our research [32] to the Ergonomics domain in Web of Science (WoS) that published most articles related to maritime transportation , knowing that some papers could be included in other categories (for instance Business for research that include cost-arguments in relation to maritime safety) Reading the abstracts, we excluded all the articles that were unrelated to the topic leading to n=789 results.. As the topic of HAT is multidisciplinary in nature, similar to [33], we included all the articles found without considering the journal or discipline they belong to.…”
Recent technological advances in the field of Artificial intelligence (AI) and machine learning led to the creation of smart AI-enabled automation systems that are drastically changing maritime transportation. We developed a systematic literature review to understand how automation, based on Information Technologies (IT), has tackled the challenges related to human and machine interactions. We notably discuss the conceptual evolution from Human-Automation Interaction (HAI) to Human Autonomy Teaming (HAT) and present the risks of high levels of automation and the importance of teamwork in safety critical systems. Our results lie on a map of five clusters that highlight the importance of trust in the interactions between humans and machines, the risks related to automation, the human errors that are arising from these interactions, the effects of automation on situational awareness and the social norms in human-computer interactions. This literature show that human-machines interactions have mainly been studied from the computer/information systems' (IS) point of view, hence neglecting the social dimensions of humans. Building on the difference between the concepts of automation and autonomy, we suggest the development of the concept of Social Human Autonomy Machine Teaming (SHAMT) to better consider the social dimensions of humans in these new interactions. Future research should focus on the right equilibrium between social needs, social interactions among humans and with autonomous machines with AI to optimize the global autonomy of the humanmachine teammates in a whole ecosystem.
“…Bu nedenle bilgi güvenliği ve bilginin korunması amaçlı kamu politikalarının oluşturulması akademik çalışmalarda yeralan ortak öneriler arasındadır (Gül, 2018). Giest (2017) (Guirguis, 2020).…”
Section: Di̇nami̇k Büyük Veri̇ Anali̇ti̇ği̇ Yeteneği̇ni̇n Kamu Kuruml...unclassified
Özet
Küreselleşme ve teknolojik gelişmeler, özel sektörde olduğu gibi kamu yönetiminde de önemli yapısal ve süreçsel değişimlerin yaşanmasına yol açmaktadır.
Amaç: Konu çalışma, uluslararası ve yerel bağlamda dinamik dijital yeteneklerin ve özel olarak dinamik büyük veri analitiği yeteneğinin kamu örgütlerinde dijital dönüşüm süreçleri üzerindeki olumlu ve olumsuz etkilerini incelemeyi amaçlamaktadır.
Yöntem: Çalışmada, kapsamlı bir literatür taraması gerçekleştirilmek suretiyle kamu sektöründe dinamik yetenekler yaklaşımının dünyada ve Türkiye’deki pratik uygulamaları irdelenmiştir.
Bulgular: Çalışmanın sonuçları, kamuda dijital dönüşüm projelerinde büyük veri analitiği yeteneğinin geniş çaplı kullanımının verimlilik artışı, veriye dayalı karar almanın güçlenmesi, bürokrasinin azaltılması, yenilikçi kamu hizmetlerinin geliştirilebilmesi ve geleneksel kamu yönetimi anlayışının daha fazla vatandaş katılımı ile performans ve şeffalığa dayalı yeni bir kamu yönetimi anlayışına evrilmesinin hızlanması gibi önemli faydalar sağladığını ortaya koymuştur. Buna karşın, veri güvenliği ve vatandaşlar arasında eşitsizliğe yol açabilecek uygulamalar başta olmak üzere çeşitli risk unsurlarının mevcudiyeti, özellikle kamu otoritelerinin bu alanda yaptıkları planlama ve uygulamalarda ne kadar hassas ve dikkatli davranmaları gerektiğini göstermektedir.
“…Aunque el concepto más extendido es el de «big data», que inicialmente se refería a aquellos datos digitales que son demasiado grandes, poco elaborados o desestructurados para ser analizados mediante técnicas convencionales de bases de datos relacionales, y que posteriormente evolucionó para incluir los procesos a través de los cuales las organizaciones obtienen valor de ellos (Guirguis, 2020;Kim et al, 2014). Una definición que, en el contexto del presente artículo, se asocia también a la acumulación de datos en repositorios, cuyo análisis mediante algoritmos propicia la toma de decisiones -sin que sea imprescindible la intervención humana-, generando procesos de transformación del trabajo, las organizaciones y la sociedad (Jones, 2019;Galliers et al, 2017).…”
Section: Miquel Salvador Sernaunclassified
“…A partir de las aportaciones de la literatura al respecto (Guirguis, 2020;Desouza et al, 2020;Keding, 2020;Susar y Aquaro, 2019;Ramió, 2019Ramió, y 2018Desouza, 2018), en el presente artículo se propone interpretar estos condicionantes en términos de componentes de la gobernanza de datos que es necesario atender para su desarrollo y vinculación con la IA. Los componentes destacados son:…”
El desarrollo y la integración de la Inteligencia Artificial (IA) a nivel transversal en las organizaciones del sector público, trascendiendo de iniciativas puntuales de carácter sectorial, requiere contar con nuevas capacidades. La revisión de diferentes aproximaciones que abordan esta cuestión permite destacar la importancia de los datos y, más concretamente, de su gobernanza en las administraciones públicas. Para profundizar en ello se analizan las diferentes dimensiones de la gobernanza de datos y se identifican cinco componentes para su desarrollo: la estrategia, la arquitectura e infraestructura de datos, la organización (incluyendo la estructura y los procesos), la gestión del talento y las competencias de los profesionales y el modelo de relaciones de la organización con su entorno. A través de la reflexión conceptual y su aplicación a un estudio de caso sobre el Ayuntamiento de Barcelona, con aportes en los diferentes componentes, se destacan aprendizajes y se formulan propuestas para cada uno de ellos. Las conclusiones permiten destacar la necesidad de contar con una estrategia integrada de refuerzo institucional que relacione los diferentes componentes de una gobernanza de datos vinculada al desarrollo de la Inteligencia Artificial en el sector público.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.