| Abstract [eng] |
Purpose – This study aims to identify the key explanatory indicators and their consistency in facilitating various types of innovation in five consecutive waves of the Community Innovation Survey (CIS) from 2010 to 2018. Approximately 2,000 Lithuanian companies were observed in each wave. The authors identify the determinants affecting different types of innovation in each wave, such as product innovation (i.e. goods and services), process innovation (production, logistics, marketing, human resource management [HRM] and management), and any type of innovation (companies adopting at least one type of innovation). Design/methodology/approach – The authors use a two-step approach involving naive Bayes and probit regression models. Explanatory variables are taken from the CIS and grouped into 12 types: strategy, work organization, customers and suppliers, external collaboration, innovation activity, technology, financial incentives, turnover, market scope, marketing, company characteristics and other expenditure. Findings – Work organization, external collaboration-related practices and company characteristics (i.e. sector, size) are the most important determinants of innovation, affecting seven or more types. In addition, some determinants consistently impact certain types of innovation across multiple measurement waves. Specifically, technology-related indicators are crucial for production innovation; work organization–related indicators are the mainstay of HRM and management innovations; and external collaboration indicators are essential determinants of service innovation. Originality/value – The ability to predict innovativeness is relevant because its measurement by the CIS is performed every two years, with the results made publicly available after a considerable delay. The results of this study suggest a way of predicting whether a company innovates and provide a means of tracking innovation trends in a country at any time. |
