Information security management in ICT and non-ICT sector companies: A preventive innovation perspective

Recognizing the preventive quality in the adoption of innovations: The case of third-party ownership photovoltaic systems in Finland

This study explores the role of the preventive quality of innovations on their adoption intention. The preventive quality of innovations is a distinctive feature of innovations that is directed towards avoiding a future, possibly harmful event. Empirically grounded in third-party ownership of photovoltaic systems in Finland, this study examines data collected from an online survey measuring respondent intention to adopt. A series of hypotheses theoretically grounded in the Diffusion of Innovations theory and the preventive quality of innovations were tested through Partial Least Squares Structural Equation Modeling with SmartPLS4. Findings for the overall sample reveal that the preventive quality and the relative advantage of innovations influenced adoption intention positively. Findings highlight the preventive quality of innovations as a construct that acts as the greatest contributor to the dependent variable.

It Is Time for Anti-Bribery: Financial Institutions Set the New Strategic “Roadmap” to Mitigate Illicit Practices and Corruption in the Market

The financial sector is characterized by complexity due to the management of a large volume of transactions, which can lead to the difficulty of considering, identifying, and monitoring them. The lack of mechanisms in monitoring and control transactions can contribute to the development of illegal practices within a company, such as fraud, corruption, bribery, and money laundering. These phenomena can affect financial institutions negatively. Therefore, the development of an appropriate corporate governance system can ensure to members of the board and executives in a company that any illegal practice can be detected. This study aims to highlight the factors that contribute to the development of illegal practices within European financial institutions. This can help executives to plan and mitigate the illicit practices that may emerge. For this purpose, a binary logit regression analysis on panel data from 2018 to 2020 was applied to 336 European financial companies. The findings of this research emphasize the crucial role of corporate governance in the prevention of the development of illicit issues within European financial institutions, while human resources can be characterized as a pathway to corruption. Both factors, corporate governance and human resources, are main pillars of environmental, social, and corporate governance (ESG), which indicates the need of the financial sector in Europe for the elaboration of anti-corruption strategies. Thus, companies within the sector can improve their ESG score.

Connecting firm's web scraped textual content to body of science: Utilizing microsoft academic graph hierarchical topic modeling

This paper demonstrates a method to transform and link textual information scraped from companies' websites to the scientific body of knowledge. The method illustrates the benefit of Natural Language Processing (NLP) in creating links between established economic classification systems with novel and agile constructs that new data sources enable. Therefore, we experimented on the European classification of economic activities (known as NACE) on sectoral and company levels. We established a connection with Microsoft Academic Graph hierarchical topic modeling based on companies' website content. Central to the operationalization of our method are a web scraping process, NLP and a data transformation/linkage procedure. The method contains three main steps: data source identification, raw data retrieval, and data preparation and transformation. These steps are applied to two distinct data sources.