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Introduction – In recent years, there has been a growing interest in innovation, not only in developed countries but also in developing countries. However, there has been limited literature for the developing countries.

Purpose – The literature on national innovation systems (NIS) mainly consists of case studies or qualitative researches aiming to explain the patterns of innovation, while the quantitative analysis are limited in explaining the innovation capability and efficiency of innovation. This study is unique in a sense that it compares the innovation efficiencies of the EECA countries. This chapter aims to measure the efficiency of NIS via data envelopment analysis (DEA) method.

Methodology – DEA is used to consider a sample of 18 Eastern European and Central Asian (EECA) countries and Turkey. One of the main issues is to determine the input and output variables because the available data for some of these countries were limited. Therefore, research and development expenditure (% of GDP), government expenditure on education, total (% of GDP), imports of goods and services (% of GDP) and foreign direct investment, net inflows (% of GDP) were determined as input variables. Output variables were as follows; patent applications both residents and non-residents, high-technology exports (% of manufactured exports) and scientific and technical journal articles.

Findings – Based on the key findings it can be noted that Kazakhstan, Turkey, Latvia and Uzbekistan are more efficient in innovation performance compared to other EECA countries. Throughout the results of the DEA, these countries may develop new policies about their innovation systems to reach out the higher performance.

This chapter presents the strategy employed to develop a methodology to evaluate research collaboration networks in a higher education context. The research design comprised four successive tracks. We understand these methodological tracks as the tactics employed to organise available means to accomplish an objective. In the first track, we selected the key subjects, the ego networks and the network leaders to be analysed. In the second track, we visualised networks through graphs. In the third track, the statements of the subjects about formed networks were pursued, based on interviews. In the fourth track, case studies were researched and described. The study included qualitative and quantitative data to uncover the interactive processes of doing collaborative research inside a network. The methodology was useful to obtain visual understanding of the networks of co-authorial relations, quantitative and qualitative markers to be used in participatory evaluation of collaborative research networks, as well as an extended view of the life cycles of collaborative research networks. The main contribution of the chapter is to show a sequence of cross-disciplinary methodological steps allowing to understand different types of relations inside research network.

The study of the diffusion of innovations into libraries has become a cottage industry of sorts, as libraries have always provided a fascinating test-bed of nonprofit institutions attempting improvement through the use of new policies, practices, and assorted apparatus (Malinconico, 1997). For example, Paul Sturges (1996) has focused on the evolution of public library services over the course of 70 years across England, while Verna Pungitore (1995) presented the development of standardization of library planning policies in contemporary America. For the past several decades, however, the study of diffusion in libraries has tended to focus on the implementation of information technologies (e.g., Clayton, 1997; Tran, 2005; White, 2001) and their associated competencies (e.g., Marshall, 1990; Wildemuth, 1992), the improvements in performance associated with their use (e.g., Damanpour, 1985, 1988; Damanpour & Evan, 1984), and ways to manage resistance to technological changes within the library environment (e.g., Weiner, 2003).

Marit Kristine Ådland is a Ph.D. student at Oslo and Akershus University College of Applied Science. Her research interests and activity is within knowledge organization, information behavior, information retrieval, and information architecture. Her current research explores users’ tags and tagging behavior in the field of cancer information. She teaches classification and indexing to students training in librarianship.

Purpose: The study’s objective is to look at the link between money laundering and economic and financial performance, emphasising the effectiveness of the literature and possible later research directions using science mapping, which allows for scientific knowledge analysis.

Need for the Study: This study is related to a better understanding of the field’s historical evolution in terms of publications.

Methodology: This study used bibliometric approaches to analyse a sample of 660 studies from the Web of Science between 1994 and 2022, concentrating on keywords, author, paper, journal, and subject analysis. This study focused on performance analysis and scientific mapping of articles using the R package.

Findings: The empirical results indicated that the research field’s primary issues include corporate governance, fraud, machine learning, fraud detection, financial fraud, financial statement, corruption, earnings management, ethics, governance, financial reporting, bankruptcy, internal control, or performance. M. S. Beasly, D. B. Farber, E. M. Fich, R. Romano, and A. Shivdasani are the most well-known authors on the issue of money laundering and financial and economic performance. At the same time, the most typical journals are the Journal of Business Ethics, Journal of Money Laundering Control, Accounting Review, Journal of Financial Economics, and Journal of Corporate Finance.

Practical Implications: This study will act as a guide for researchers of various fields to evaluate the development of scientific publications in a particular theme over time, especially for those who are in the field of money laundering and financial performance.

We contribute to the growing literature examining how social enterprises might best accommodate their hybrid structure when pursuing dual goals of social improvement and economic sustainability. Drawing on extant literature, the case is made for why synergy between the social and commercial business models that hybrid social enterprises employ should positively impact effectiveness in delivering organization outcomes. We then develop a method for comparing the synergy between the social and commercial business models employed within and across organizations, and test the method using a sample of seven social enterprises operating in different social fields. Results demonstrate that our method can be applied consistently across a range of social enterprise types and that variation in degree of synergy is considerable with overlap rates ranging from 9% to 77%. Using learning from this exploratory study, we develop propositions describing how and why social entrepreneurs develop business model synergy, the relationship between business model synergy and organizational performance, and suggest future research to test these propositions. Implications for theory development and practice are discussed.