Identifying the business and social networks in the domain of production by merging the data from heterogeneous internet sources

Abstract

People, companies, and institutions form networks as part of their technical, economic, and social activities. As a consequence, these networks have an influence on how companies conduct business. Recently, the Internet, professional, and scientific social networks have contributed to the ease and simplicity of the network forming process and the public availability of the corresponding data. We investigate whether useful information about the relationships between individuals, companies, and institutions for the domain of production can be extracted from publicly available, structured and unstructured data that is merged from various Internet sources. We demonstrate that relevant information about the structures of these networks can be obtained by merging publicly available data using a combination of advanced computational methods including web crawling, machine learning, and creating mash-ups of publicly available services. The feasibility and the applicability of the approach are shown for a case in the automotive domain. A potential use case of the resulting data is demonstrated, showing how the approach can be used to find specific skills and expertise for a scientific

Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations

“…Data has become one of the most valuable assets for modern organisations (Weerakkody et al, 2017;Kozjek et al, 2018;Albergaria and Jabbour, 2019). Moreover, organisations are becoming increasingly digital, and as a result a large volume of data is being generated in their supply chains (Sheng et al, 2017;Tan et al, 2017;Akter et al, 2017;Ji-Fan Ren et al, 2017;Ivanov et al, 2019a;Frank et al, 2019;Dolgui et al, 2019a,b).…”

Assessing the implementation feasibility of intelligent production systems based on cloud computing, industrial internet of things and business social networks

“…Through integrating the data from heterogeneous Internet sources, Kozjek et al (2018) identified market and social networks in the development field. The article illustrates the utilization of modern computing techniques and data analytics to classify publicly accessible, organized and unorganized, and heterogeneous data networks of individuals, enterprises, and organizations.…”

Advancing manufacturing systems with big-data analytics: A conceptual framework

“…This section demonstrates the use of a conceptual framework on the selected studies of introducing data analytics in manufacturing systems. Five existing case studies of developing data-analytics solutions in manufacturing systems, i.e., (Kozjek et al 2017a(Kozjek et al , 2017b(Kozjek et al , 2018a(Kozjek et al , 2018bVrabič, Kozjek, and Butala 2017), are selected. Data-analytics solutions developed within these projects are either innovative ways of reducing the incompleteness of information and discovering new knowledge through additional use of data or they enable the more efficient reduction of information incompleteness than the conventional approaches.…”

“…Title, Description, and Mapping 5 Title: Identifying the business and social networks in the domain of production by merging the data from heterogeneous internet sources (Kozjek et al 2018a) Description: It is demonstrated that relevant information about the structures of networks that connect individuals, companies, and institutions for the domain of production can be obtained by merging publicly available internet data using a combination of advanced computational methods including web crawling, machine learning, and creating mash-ups of publicly available services. The feasibility and the applicability of the approach are shown for a case in the automotive domain and a case of the scientific community consisting of people from industry and academia.…”