[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122238-en":3,"doc-seo-122238-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},122238,1374391975076,"Riley","https://ap-avatar.wpscdn.com/avatar/14000253ca4ec9f6853?x-image-process=image/resize,m_fixed,w_180,h_180&k=1783305029341752051",8,"Research & Report","From smart firms to smart consumers - Complex Systems and Machine Learning for Industry 4.0","The thesis investigates how Industry 4.0 technologies reshape firm design, production, and distribution by intertwining Industrial Internet of Things, cloud connectivity, and machine learning into an integrated manufacturing process. Firms are modeled as complex systems, where the evolution of each productive element depends on tightly coupled connections across the whole organization. The study develops graph-theoretic and machine-learning methods to extract actionable insights, analyze startup ecosystems, and interpret consumers’ reviews. It applies community detection, graph metrics, and text-to-number techniques to support innovation, forecast startup success, and support future perspectives.","Repository Istituzionale dei Prodotti della Ricerca del Politecnico di Bari  \nFrom smart firms to smart consumers: Complex Systems and Machine Learning for Industry 4.0  \nThis is a PhD Thesis  \nOriginal Citation:  \nFrom smart firms to smart consumers: Complex Systems and Machine Learning for Industry 4.0 / De Nicolò, Francesco.  \n-ELETTRONICO. - (2024) . [10 .60576/poliba/iris/de-nicol-francesco_phd2024]  \nAvailability:  \nThis version is available at [http://hdl.handle.net/11589/266240 since: 2024-03-10](http://hdl.handle.net/11589/266240 since: 2024-03-10)  \nPublished version  \nDOI:10.60576/poliba/iris/de-nicol-francesco_phd2024  \nPublisher: Politecnico di Bari Terms of use:  \n(Article begins on next page)  \nDE NICOLO' FRANCESCO PUTIGNANO (BA) 25/04/1989  \nPUTIGNANO (BA) FRATELLI BANDIERA, 6 [francesco.denicolo@poliba.it](francesco.denicolo@poliba.it)  \nINDUSTRIA 4.0 36  \nFROM SMART FIRMS TO SMART CONSUMERS: COMPLEX SYSTEMS AND MACHINE LEARNING FOR INDUSTRY 4.0  \nINDUSTRIA 4.0 36  \nBARI, 27/12/2023  \nBARI, 27/12/2023  \nContents  \n1 Industry 4.0, Complex Systems and Machine Learning 3  \n1.1 Complex Systems in Industry 4.0.................. 3  \n1.2 Taming Complex Systemgsr:aph theory .............. 5  \n1.3 Exploiting Complex Systema: chine [Learning mode.ls.... 6](Learning mode.ls.... 6)  \n[1.4 Thesis organization.......................... 7](1.4 Thesis organization.......................... 7)  \n[2 How to extract insights for Industry 4.0: graph theory and](2 How to extract insights for Industry 4.0: graph theory and)[ ](2 How to extract insights for Industry 4.0: graph theory and)Machine Learning 9  \n2.1 Fundamentals of graph theor.y................... 9  \n2.1.1 Complex Systems and grap.h.s .............. 9  \n2.1.2 Graphs’ value in modelling Complex Syst.em..s .... 11  \n2.1.3 Multi-graph, simple graph and weighted gr.ap. h.... 12  \n2.1.4 Degree and Adjacency matrix................ 13  \n2.1.5 Geodetic paths........................ 15  \n2.1.6 Closeness. . . . . . . . . . . . . . . . . . . . . . . . . . . 17  \n2.1.7 Betweenness  . . . . . . . . . . . . . . . . . . . . . . . 18  \n2.2 Machine Learning algorithm. s................... 19  \n2.2.1 Unsupervised Machine Learnim: munity detection in graphs ............................. 19  \n2.2.2 Supervised Machine Learninl:gorithms and Explainability ............................. 24  \n3 Startups and consumersr’eviews:use-cases and why they are important 33  \n3.1 The startup ecosystemits: importance and modellin.g..... 34  \n3.1.1 The importance of the startup ecosystem for Industry34.0  \n3.1.2 Countries’ innovation ecosystes:StartupBlink ranking 35  \n3.1.3 Interplay among startups and investCorusn: chbase... 38  \n3.2 Why studying tourists’ tastes in Industry 4...0......... 39  \n3.2.1 Tourists’ experiences in Apulia from TripAdvreisvoire:wsand rating ........................... 40  \n4 How to boost innovation and customers’ satisfacieopnl:oying graph theory and Machine Learning 43  \n4.1 StartupBlink:equity oriented rethinking through community detection ................................. 43  \n4.1.1 StartupBlink country network............... 44  \n4.1.2 Community detection algorithms and Resolution R.ati4.  \n4.1.3 WDI country communities and StartupBlink [rethink.ing50](rethink.ing50)  \n4.2 Crunchbaseg: raph model and forecasting succe. s.s....... 55  \n4.2.1 Modelling the economic interpla.y............. 55  \n[4.2.2 Defining and measuring succe.ss](4.2.2 Defining and measuring succe.ss)............. 57  \n4.2.3 Strategic elements in the startup ecosyst.em....... 58  \n4.2.4 Forecasting success..................... 61  \n4.3 TripAdvisor:extracting insights from tourists’ revie. w. s.... 66  \n4.3.1 From text to number:F-IDF matrix . . . . . . . . . . . 66  \n4.3.2 Reviews’ classification   . . . . . . . . . . . . . . . . . 67  \n4.3.3 Strengths and weaknesses of the Apulian tourism. o. ffr8  \n5 Insights and future perspectives for startups and reviews’ analysis in Industry 4.0 71  \n5.1 Highlighting","cbCaikHjI3EyDNs0","https://ap.wps.com/l/cbCaikHjI3EyDNs0","pdf",5746857,1,130,"English","en",105,"# Industry 4.0, Complex Systems and Machine Learning\n## Complex Systems in Industry 4.0\n## Taming Complex Systems: graph theory\n## Exploiting Complex Systems: machine learning\n## Thesis organization\n# How to extract insights for Industry 4.0: graph theory and Machine Learning\n## Fundamentals of graph theory\n## Machine learning algorithms\n# Startups and consumers’ reviews: use-cases and why they are important\n## The startup ecosystem: importance and modelling\n## Why studying tourists’ tastes in Industry 4.0\n# How to boost innovation and customers’ satisfaction: using graph theory and Machine Learning\n## StartupBlink: equity oriented rethinking through community detection\n## Crunchbase: graph model and forecasting success\n## TripAdvisor: extracting insights from tourists’ reviews\n# Insights and future perspectives for startups and reviews’ analysis in Industry 4.0\n## Best practices via community detection\n## Graph metrics and startups’ success\n## Unveiling tourists’ tastes and needs\n## Future perspectives\n# Appendices","[{\"question\":\"How does the thesis connect Industry 4.0 with complex systems modeling?\",\"answer\":\"It frames a firm as a complex system where every productive element is linked to others, so its evolution cannot be studied in isolation but within a holistic framework driven by these connections.\"},{\"question\":\"Which analytical approach is used to extract insights for Industry 4.0?\",\"answer\":\"The work combines graph theory with machine learning, using graph fundamentals and machine-learning algorithms to analyze relationships and derive interpretable insights.\"},{\"question\":\"How are startup ecosystems and consumer/tourist reviews addressed in the research?\",\"answer\":\"Startup ecosystems are modeled and analyzed using community detection and graph metrics, while consumer insights are extracted from tourists’ reviews using techniques such as transforming text into numeric representations and review classification.\"}]","From smart firms to smart consumers - Complex Systems and Machine Learning for Industry 4.0 | 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does the thesis connect Industry 4.0 with complex systems modeling?","Question",{"text":75,"@type":76},"It frames a firm as a complex system where every productive element is linked to others, so its evolution cannot be studied in isolation but within a holistic framework driven by these connections.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which analytical approach is used to extract insights for Industry 4.0?",{"text":80,"@type":76},"The work combines graph theory with machine learning, using graph fundamentals and machine-learning algorithms to analyze relationships and derive interpretable insights.",{"name":82,"@type":73,"acceptedAnswer":83},"How are startup ecosystems and consumer/tourist reviews addressed in the research?",{"text":84,"@type":76},"Startup ecosystems are modeled and analyzed using community detection and graph metrics, while consumer insights are extracted from tourists’ reviews using techniques such as transforming text into numeric representations 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