1,721,017 research outputs found
Nuovi modelli di ricerche di marketing: le potenzialità della social network analysis applicata ai social media
No full textIn questo lavoro si affronta il tema del rapporto tra le ricerche di marketing e le
opportunità fornite dalla Rete. In particolare, ci si focalizza sui recenti sviluppi derivanti dalla nascita di strumenti digitali come i social media e la possibilità di accedere ad un continuo flusso di dati, mediante l’impiego di piattaforme per l’analisi dei Big Data. Le tecnologie alla base dei Big Data hanno difatti impattato fortemente nelle performance di ricerca dando vita a nuove tecniche, potenziandone altre o riportando in auge metodologie che negli anni avevano perso appeal. A tal proposito, in questo studio viene presa in considerazione la tecnica della social network analysis che, grazie ai recenti sviluppi dei social media può essere adottata per numerosi scopi di marketing.
Obiettivo della tesi è l’individuazione di un modello di analisi basato sulla metodologia della social network analysis utile a condurre ricerche di marketing all’interno dei social media.
Lo strumento utilizzato è il software open source NodeXL sviluppato dalla Social Media Research Foundation, l’applicazione di NodeXL è stata effettuata seguendo la metodologia dell’Internet Research. Il software consente la mappatura dei network creati dai profili social aziendali, in questo caso sono state
effettuate due mappature utilizzando i dati provenienti da Twitter, relativi ad un noto brand italiano del settore fashion.
Attraverso il nuovo modello è stato possibile ottenere una serie di informazioni utili al marketing per comprendere il contesto online in cui l’impresa si trova ad operare.
Le metriche proposte e descritte sono state selezionate in base alla loro capacità di generare insights in grado di supportare il ricercatore di marketing per una serie di valutazioni.
Si ritiene pertanto, che il modello presentato possa fornire un contributo per un nuovo approccio al marketing, che vede l’utilizzo dei social media come una risorsa e un’opportunità di individuazione di rilevanti implicazioni manageriali e di marketing.This work adresses the issue of the relationship between marketing research and the opportunities provided by Internet. In particular, we focus on the recent developments arising from the rising of digital tools such as social media and the ability to access to a continuos stream of data through the use of Big Data
Analysis platforms.
Indeed, Big Data technologies have strongly impacted in research performances giving rise to new techniques, enhancing or bringing back other methodologies which had lost appeal over the year. In this regard, the social network analysis technique in considered in this study. It can be adopted for many marketing purposes thanks to the recent developments of social media.
The aim of the thesis is the identification of an analysis model based on the social network analysis methodology, useful to conduct marketing research within social media.
NodeXL, the open source software developed by the Social Media Research Foundation is the instrument used for this study. The application of NodeXL is carried out following the Internet Research Methodology. The software allows the mapping of the networks created by the enterprise in social media. In this case,
two maps were made using Twitter data related to a well-know brand from the Italian fashion industry.
Throungh the application of the new model it was possible to obtain a series of useful insights to uderstand the online marketing context where the compani operates.
Metrics described have been selected based on their capabilities to generate insights that can support marketing researcher for a series of evaluations. Therefore it is considered that the present model can contribute to create a new marketing approach, where the use of social media can be seen as a resource and as an opportunity for the relevant managerial and marketing implications identification
Digital marketing analytics: metodologie e metriche per la misurazione della performance
No full textThe use of digital marketing tools in SMEs: needs, problems and opportunities. An empirical study in the Marche Region
No full textProblematiche e prospettive di sviluppo del digital marketing nelle PMI: i risultati di un’indagine empirica
No full textDigital marketing analytics: metodologie e metriche per la misurazione della performance
No full textExploring the relationship between entrepreneurial ecosystem inputs and outcomes: the role of digital technology adoption
Full text linkPurpose
This work aims to explore the relationship between entrepreneurial ecosystems' (EEs) inputs and outcomes within a digital-technology-driven EE. Specifically, it focuses on how being part of an EE enhances digital technology adoption (DTA) and consequently facilitates EE outcomes.
Design/methodology/approach
This paper employs a single-case study approach, focusing on Italian EE. The data analysis is based on the researchers' direct observations and semi-structured interviews with the EE founders' teams and the top management of the small- and medium-sized enterprises (SMEs) operating therein. Given the novelty of the topic and the lack of a clear research framework of analysis, a qualitative method is well suited for studying digital-technology-driven EE, thus gaining rich data about the phenomenon in a real-life context.
Findings
The findings of the study reveal that when specific eco-inputs (financial, knowledge, social and institutional assets) are correctly exploited to enhance DTA, important outcomes, namely, SME competitiveness and new technology-based venture creation and development, are generated.
Originality/value
The paper contributes to a relatively unexplored topic in the existing literature on EEs and digital technology. Specifically, through the proposition of a conceptual model, it sheds light on the relationship among EE inputs, DTA and EE outcomes
How AI re-structure actors and relationship of the new Healthcare Ecosystem
No full textArtificial intelligence raises serious questions in all areas as it can help to address the majorchallenges facing contemporary society. Among the most critical sectors on which the greatchallenges will impact is the healthcare sector. Climate change, social change and demographictrends threaten its sustainability. Artificial intelligence can compensate and support the entireecosystem, but to understand and build optimal solutions, it is good to understand how thecurrent healthcare ecosystem is changing under the influence of artificial intelligence. Thispaper through a co-occurrence analysis mapped current trends and actors in the currenthealthcare ecosystem and then mapped current trends and actors in the healthcare ecosystembut transformed by AI.Once the main actors on which the research is focusing were identified, we proceeded inaccordance with the Actor Network Theory to map how the relationships between the nodeschange under the influence of the different types and tools of AI support. The paper offersnumerous theoretical and managerial perspectives by offering a first mapping of the healthcareecosystem marked by AI which can be of assistance in the implementation of social policies,construction of AI architectures and for a rethinking of the capabilities and roles of the differentactors of the AI’s healthcare ecosystem. It is confirmed how AI can risk making the human element disappear in most of activities, but it could help us become not only Human Plus butmost of all help us not to lose our Human Factor
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