A Digital Tale of Two Cities—Observing the Dynamics of the Artificial Intelligence Ecosystems in Berlin and Sydney

In entrepreneurial ecosystems (EEs), geographical and contextual factors play a big role in shaping the knowledge bases for digital innovation. While cities around the world compete to be perceived as successful “tech startup hubs”, proactive urban strategies are needed to create knowledge spillovers into EEs. This study explores the evolution of artificial intelligence (AI) knowledge practices in the EEs of Berlin and Sydney by using knowledge-spillover theory of entrepreneurship. The study utilizes a bibliometric analysis of secondary data in combination with exploratory stakeholder interviews conducted for both cities. Findings underline the critical role of experimental knowledge in driving the momentum of the EEs and the supporting role of policies imprinting knowledge practices. The paper shows how the dynamics of EEs can be explored empirically and raises awareness of the role of specialised and integrated policies in determining a city’s overall success in building EEs

A Systematic Study of Research Productivity of the Disciplines in Social Sciences and Humanities: The Maharaja Sayajirao University of Baroda.

The purpose of this paper is to explore and provide an overview of the growth and development of research output pertaining to the disciplines covered in Humanities and Social Sciences (SSH), in terms of number of publications, total citations from the year 2001 up to 2020 of The Maharaja Sayajirao University of Baroda(MSU), Vadodara as reflected in Dimensions in various subject domains such as History and Archaeology, Historical Studies, Sociology, Psychology, Archeology, Education, etc. as shown in (Table-1). The main investigation is based on the primary literature, mostly scholarly articles from different subject fields. The authors attempt to employ the quantitative analysis of bibliometric indicators of the research publications which has been accessed from dimensions online indexing data. Dimensions were launched by Digital Science in January 2018, which covers humanities and social sciences. The Research output data of MSU are collected by using different searching facilities provided by Dimensions Database. The Dimensions online indexing data are also providing data of researchers, research categories, publication type, source title, journal list, open access journals along with publication year, which helps the authors to analyze the growth and development of research activity of the faculty members of MSU during the prescribed year. There were 6,354 research publications received with 73789 Citations, with an average citation per paper is 8.05. The data collected on 25th May 2021. The published materials such as articles, Book, Book chapters, review, letter, proceedings paper, biographical-item, book review, editorial material, meeting abstract, Erratum, Note, etc. are considered as research publications for this study. It suggests that Dimensions Database has been used as the data updating is the continuous process of development in humanities and social sciences. The scientific processes, as well as the methods for dissemination of information, are very similar within these fields. The database chosen is Dimensions, which has the oldest and most comprehensive records of citation indexes and includes a very authentic source in order to get an accurate and consolidated picture of the research output of the university. The findings of the research will be a great concern for various policy-making bodies of The Maharaja Sayajirao University of Baroda, such as UGC, NAAC, Internal Quality Assurance Cell (IQAC), NIRF, Ministry of HRD, etc

Customer relationship management (CRM): a bibliometric analysis

[EN] This is a bibliometric study of the publications about customer relationship management (CRM), as one of the nowadays most implemented and extended enterprise management software. The objective of this paper is twofold: on the one hand to analyse the impact and focus of influence of the different authors and entities that have been researching on CRM, and secondly to determine (based on the results of the bibliometric study of the publications on CRM) if it may be of interest to investigate and deepen the benefits and impact on CRM results as a modern and leading enterprise management solution. Bibliometrics is a fundamental field of information science that studies bibliographic material quantitatively. This study presents a bibliometric overview of CRM research using the web of science database, identifying the most prolific and influential journals, authors, institutions and countries, considering the period since 1900-2017.Guerola-Navarro, V.; Oltra Badenes, RF.; Gil Gómez, H.; Gil-Gómez, J. (2020). Customer relationship management (CRM): a bibliometric analysis. International Journal of Services Operations and Informatics. 10(3):242-268. https://doi.org/10.1504/IJSOI.2020.108988S24226810

Biomedical Convergence Facilitated by the Emergence of Technological and Informatic Capabilities

We analyzed Medical Subject Headings (MeSH) from 21.6 million research articles indexed by PubMed to map this vast space of entities and their relations, providing insights into the origins and future of biomedical convergence. Detailed analysis of MeSH co-occurrence networks identifies three robust knowledge clusters: the vast universe of microscopic biological entities and structures; systems, disease and diagnostics; and emergent biological and social phenomena underlying the complex problems driving the health, behavioral and brain science frontiers. These domains integrated from the 1990s onward by way of technological and informatic capabilities that introduced highly controllable, scalable and permutable research processes and invaluable imaging techniques for illuminating fundamental structure-function-behavior questions. Article-level analysis confirms a positive relationship between team size and topical diversity, and shows convergence to be increasing in prominence but with recent saturation. Together, our results invite additional policy support for cross-disciplinary team assembly to harness transdisciplinary convergence.Comment: 12 pages, 4 figures; 8 pages of Supplementary Informatio

Adoption Factors of Artificial intelligence in Human Resource Management

Tesis por compendio[ES] El mundo es testigo de nuevos avances tecnológicos que afectan significativamente a las organizaciones en diferentes departamentos. La inteligencia artificial (IA) es uno de estos avances, visto como una tecnología revolucionaria en la gestión de recursos humanos (RRHH). Profesionales y académicos han discutido el brillante papel de la IA en RRHH. Sin embargo, el análisis profundo de esta tecnología en el proceso de RRHH es aún escaso. Con todo ello, el objetivo principal de esta tesis es investigar el estado de la IA en RRHH y así identificar factores clave de implementación concretos. Primero, construyendo un marco académico para la IA en RRHH; segundo, analizar las aplicaciones de IA más utilizada en los procesos de RRHH; tercero, identificar las formas óptimas de transferir el conocimiento en los procesos de implementación de IA. La metodología utilizada para la investigación combina la revisión sistemática de la literatura y técnicas de investigación cualitativa. Como base y medida preparatoria para abordar las preguntas de investigación, se llevó a cabo un extenso análisis de la literatura en el campo AI-RRHH, con un enfoque particular en las publicaciones de algoritmos de IA en HRM, análisis de HR-Big data, aplicaciones/soluciones de IA en HRM e implementación de IA. En la misma línea, el autor publicó artículos en varias conferencias que contribuyeron a mejorar la madurez de las preguntas de investigación. Con base en este conocimiento, los estudios publicados ilustraron la brecha entre la promesa y la realidad de la IA en RRHH, teniendo en cuenta los requisitos técnicos de la implementación de la IA, así como las aplicaciones y limitaciones. Posteriormente, se entrevistó a expertos en recursos humanos y consultores de IA que ya habían adquirido experiencia de primera mano con los procesos de recursos humanos en un entorno de IA para descubrir la verdad de la aplicación de la IA dominante en el proceso de RRHH. Los principales hallazgos de esta tesis incluyen la derivación de una definición completa de IA en RRHH, así como el estado de las estrategias de adopción de aplicaciones de IA en RRHH. Como resultado adicional, se explora la utilidad y las limitaciones de los chatbots en el proceso de contratación en la India. Además, factores clave para transferir el conocimiento del proceso de implementación de IA a los gerentes y empleados de recursos humanos. Finalmente, se concluye identificando desafíos asociados con la implementación de IA en el proceso de recursos humanos y el impacto de COVID-19 en la implementación de IA.[CA] El món és testimoni de nous avanços tecnològics, que afecten significativament les organitzacions en diferents departaments. La intel·ligència artificial (IA) és un d'aquests avanços que s'anuncia àmpliament com una tecnologia revolucionària en la gestió de recursos humans (HRM). Professionals i acadèmics han discutit el brillant paper de la IA en HRM. No obstant això, encara és escàs l'anàlisi profund d'aquesta tecnologia en el procés de HRM. Per tant, l'objectiu principal d'aquesta tesi és investigar l'estat de la IA en HRM i derivar factors clau d'implementació concrets. Primer, construint un marc acadèmic per a la IA en HRM; segon, analitzar l'aplicació de IA més utilitzada en el procés de recursos humans; tercer, identificar les formes òptimes de transferir el coneixement dels processos d'implementació de IA. La metodologia utilitzada per a la investigació es combina entre una revisió sistemàtica de la literatura i una tècnica d'investigació qualitativa. Com a base i mesura preparatòria per a abordar les preguntes d'investigació, es va dur a terme una extensa anàlisi de la literatura en el camp IA-HRM, amb un enfocament particular en les publicacions d'algorismes de IA en HRM, anàlisis de HR-Big data, aplicacions/soluciones de IA en HRM i implementació de IA. En la mateixa línia, l'autor va publicar articles en diverses conferències que van procedir a millorar la maduresa de les preguntes d'investigació. Amb base en aquest coneixement, els estudis publicats van illustrar la bretxa entre la promesa i la realitat de la IA en HRM, tenint en compte els requisits tècnics de la implementació de la IA, així com les aplicacions i limitacions. Posteriorment, es va entrevistar experts en recursos humans i consultors de IA que ja havien adquirit experiència de primera mà amb els processos de recursos humans en un entorn de IA per a descobrir la veritat de l'aplicació de la IA dominant en el procés de recursos humans. Les principals troballes d'aquesta tesi són la derivació d'una definició completa de IA en HRM, així com l'estat de les estratègies d'adopció d'aplicacions de IA en HRM. Com a resultat addicional, explore la utilitat i les limitacions dels chatbots en el procés de contractació a l'Índia. A més, factors clau per a transferir el coneixement del procés d'implementació de IA als gerents i empleats de recursos humans. També es van concloure els desafiaments associats amb la implementació de IA en el procés de recursos humans i l'impacte de COVID-19 en la implementació de IA.[EN] The world is witnessing new technological advancements, which significantly impacts organizations across different departments. Artificial intelligence (AI) is one of these advancements that is widely heralded as a revolutionary technology in Human Resource Management (HRM). Professionals and scholars have discussed the bright role of AI in HRM. However, deep analysis of this technology in the HR process is still scarce. Therefore, the main goal of this thesis is to investigate the status of AI in HRM and derive concrete implementation key factors. Through, first, building an academic framework for AI in HRM; second, analyzing the most commonly used AI applications in HR process; third, identifying the optimal ways to transfer the knowledge of AI implementation processes. The methodology used for the investigation combines a systematic literature review and a qualitative research technique. As a basis and preparatory measure to address the research questions, an extensive literature analysis in the AI-HRM field was carried out, with a particular focus on publications of AI in HRM, HR-Big data analysis, AI applications/solutions in HRM and AI implementation. Along similar lines, the author published papers in several conference proceedings to improve the maturity of research questions. Based on this work, the published studies illustrate the gap between the promise and reality of AI in HRM, taking into account the requirements of AI implementation as well as the applications and limitations. Subsequently, HR experts and AI consultants, who had already gained first-hand experience with HR processes in an AI environment, were interviewed to find out the truth of the dominant AI's application in HR process. The main findings of this thesis are the derivation of a complete definition of AI in HRM as well as the status of the adoption strategies of AI applications in HRM. As a further result, it explores the usefulness and limitations of chatbots in the recruitment processes in India. In addition, derived the key factors to transfer the knowledge of AI implementation process to HR managers and employees. Challenges associated with AI implementation in the HR process and the impact of COVID-19 on AI implementation were also concluded.Tuffaha, M. (2022). Adoption Factors of Artificial intelligence in Human Resource Management [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/185909Compendi

Exploring Innovation Activities of Firms from Peripheral Regions in Estonia and Germany: A Relational Perspective

Die vorliegende Dissertation exploriert Innovationsaktivitäten von Unternehmen des produzierenden Gewerbes in zwei unterschiedlich strukturierten peripheren Regionen: in Südestland und dem Erzgebirgskreis. Die Arbeit erweitert bestehende Forschung, da periphere Regionen und low-tech Industriezweige sich nur vereinzelt in wirtschaftsgeographischen Forschungsagenden finden. Ausgehend von einer relationalen Perspektive fokussiert die Forschungsarbeit auf Akteursbeziehungen und insbesondere darauf, wie diese Beziehungen Wirtschaftsprozesse wie Wissensgenerierung und Innovation bedingen. Als analytische Perspektiven innerhalb dieses relationalen Rahmens werden Netzwerke und unterschiedliche Dimension von Nähe und Distanz herangezogen (geographische, soziale, kognitive, institutionelle und organisationale). Die Dissertation erarbeitet kontextualisierte Erkenntnisse zu räumlichen und relationalen Elementen von Innovationsaktivitäten in peripheren Regionen. Methodisch orientiert sich die Arbeit am Ansatz der Innovationsbiographien. Dazu werden konkrete Innovationsprojekte und ihre Netzwerke aus räumlicher und zeitlicher Perspektive rekonstruiert. Entsprechend wird im empirischen Teil der Arbeit ein evolutionäres, interaktives und wissensbasiertes Innovationsverständnis aufgegriffen. Die Arbeit stellt heraus, dass Unternehmen in beiden Untersuchungsregionen aktiv Innovationsprozesse vorantreiben bzw. an diesen teilhaben. Periphere Lage und sozioökonomische Herausforderungen prägen die Innovationspraktiken der Unternehmen entlang unterschiedlicher Dimensionen. Insbesondere lassen sich zielgerichtete Netzwerkaktivitäten, ein hoher Mobilitätgrad sowie die strategische Ausrechterhaltung bzw. der Ausbau einer umfassenden Technologie- und Fertigungstiefe identifizieren. Diese Praktiken fungieren als Mechanismen zur Überwindung potenzieller Strukturnachteile peripherer Regionen. Basierend auf diesen Erkenntnissen illustriert die Dissertation Ansätze zur Erweiterung wirtschaftsgeographischer Innovationstheorie und diskutiert Maßnahmen zur Förderung der Innovationstätigkeit von Unternehmen in peripheren Regionen.This dissertation explores innovation activities of LMT manufacturing firms located in two differently structured peripheral regions: South Estonia and the Erzgebirgskreis. Thus, the dissertation expands existing scholarship in economic geography by investigating innovation in localities and sectors that are not part of broader research agendas. Operating from a relational perspective, this research emphasises the diverse actor relations and how these relations shape economic processes of knowledge creation and innovation. Within this relational framework, networks and multi-layered dimension of proximity and distance (geographical, social, cognitive, institutional and organisational) are mobilised as central analytical perspectives. Thereby, the dissertation provides contextually grounded insights on the spatial and relational elements that drive innovation activities in peripheral regions. Methodologically, this research is guided by the innovation biographies approach. Specific innovation projects and their networks are traced throughout space and time. Thereby, the evolutionary, interactive and knowledge grounded understanding of innovation is empirically addressed. This research finds that firms in both study regions actively pursue and participate in innovation activities. Operating at distance shapes the practices of firms in a number of decisive ways: purposive networking activities, high levels of actor mobility and maintenance of comprehensive internal capacities are identified in particular. These practices operate as mechanisms to overcome potential shortcomings of peripheral regions. Based on its findings, the dissertation outlines avenues to expand dominant approaches towards innovation theory in economic geography and provides avenues for policy measures that aim at fostering firm innovation in peripheral regions