Knowledge- and innovation-based business models for future growth: digitalized business models and portfolio considerations

Today’s key challenge for firm growth relies in the integration of digital technologies and their use in new business models. Thus, firms increasingly engage in a digital transformation and in digitalizing their business model. Firms can apply digital technologies for improved or novel internal and external processes and integrate them in new business models. The digital transformation itself demands diverse knowledge from diverse origins in the firm. We examine the key concepts related to business model digitalization. We develop a conceptual matrix for portfolio considerations of firm business model digitalization. We introduce the seven contributions in this special issue on knowledge and innovation related to business and offer some recommendations for future research on the new working conditions and digital identities of firms

Knowledge- and innovation-based business models for future growth : digitalized business models and portfolio considerations.

Today’s key challenge for firm growth relies in the integration of digital technologies and their use in new business models. Thus, firms increasingly engage in a digital transformation and in digitalizing their business model. Firms can apply digital technologies for improved or novel internal and external processes and integrate them in new business models. The digital transformation itself demands diverse knowledge from diverse origins in the firm. We examine the key concepts related to business model digitalization. We develop a conceptual matrix for portfolio considerations of firm business model digitalization. We introduce the seven contributions in this special issue on knowledge and innovation related to business and offer some recommendations for future research on the new working conditions and digital identities of firms

Entrepreneurial Orientation and Firm Performance in the Context of Upper Echelon Theory

Entrepreneurial Orientation (EO) is a firm-level phenomenon, which involves the firm’s prospects to take risks, be proactive, and be innovative. Most of the research assumes a positive EO-performance relationship adopting the EO-as-advantage perspective without providing enough theoretical foundations of the way EO enhances performance. This paper provides insights into the EO and firm performance relationship looking into the EO-as-experimentation perspective. Through EO-as-experimentation perspective, we argue for the importance of looking into the differential effects of each of the EO dimensions on firm performance in active and inactive firms. We hypothesized that the effect of each of the proactiveness and innovativeness dimension of EO on firm performance is positive among active firms and negative among inactive firms. Whereas risk taking dimension of EO is negative among active and inactive firms. Based on the results of firm fixed effect regression some empirical support for the hypotheses is presented and discussed

Leading Trends in Technology Transfer

The Journal of Technology Transfer (JOTT) published its first issue in 1977. Since this first issue, the JOTT has made major contributions to its field. This chapter uses dynamic bibliometric techniques and the Scopus database to analyze all JOTT issues published between 1977 and 2018. Citations are considered up to and including September 30, 2019. The primary objective is to determine the leading research trends in technology transfer by analyzing the most influential studies published in the JOTT and studying their evolution. The evolution of these research trends suggests that entrepreneurial universities, university-industry collaboration, and knowledge management have become the leading trends in technology transfer in the last few years, alongside entrepreneurial ecosystems, which rose to prominence in 2019. Finally, to complement the previous analyses, examining the most influential JOTT articles is carried out from a policy perspective, as public policies are one of the main factors affecting the environment for technology transfer. A qualitative text analysis of these 16 articles shows that the words policy and policies are found in 15. A more profound review reveals that the policies mentioned and dealt with in these articles can be grouped into three different types: technology transfer, entrepreneurship, and regional innovation policies

Determinant Factors of High Performing Agricultural Regions

Determinant factors of high performing agricultural regions. One indicator of agricultural performance is the agricultural labour productivity, as measured by the gross value added per annual working unit. Econometric approaches have been used to evaluate factors contributing to such productivity. However, these estimates require detailed data that often are not available at the regional level. We propose an alternative approach to disentangle the contribution of different drivers that lead to high productivity in EU regions, defined at NUTS 2 level. The fuzzy set Qualitative Comparative Analysis (fsQCA) provides a framework to identify combinations of attributes present in the most productive EU regions, by revealing pathways or sets of sufficient drivers present in such cases. We selected drivers based on previous research, and our findings show that there is not a unique pathway to reach high agricultural productivity. However, some drivers as strong farm structure and relevant public support appear in most of the pathways. Other dimensions related to research, development and innovation, and to natural conditions, seem also relevant. Acknowledgement : Dr. Garcia-Alvarez-Coque and Dr. Mart nez-G mez acknowledge support of the Project AGL2015-65897-C3-3-R funded by the Ministry of Economy and Competitiveness, for this research. Ms. Olfa Gharsi benefited from a scholarship from the Mediterranean Agronomic Institute of Zaragoza

Half a century of Quality & Quantity: a bibliometric review

© 2018, Springer Nature B.V. The Quality & Quantity was established in 1967 and in 2017 it completed its half century. The journal is interdisciplinary in nature and it mainly discusses methodological application of mathematics and statistics in the social sciences, particularly sociology, economics, and social psychology. It was created with the idea of advancing methodology of the various social studies. This study looks back journey of the journal from 1967 to 2017 aims to develop a bibliometric analysis of all the publications of the journal. Web of Science Core Collection database is used to collect data. The present study discovered the significant contributions of the journal in terms of impact, topics, authors, universities and countries. Utrecht University of Netherlands is the most productive university. Asian Universities are emerging and growing quickly in the recent years. Although USA leads among the countries but Europe leads among the six supranational regions. Finally, the visualization of similarities viewer software is used to present network visualization of the bibliographic coupling, co-citation, citation, co-authorship and co-occurrence of keywords

Co-citation, bibliographic coupling and leading authors, institutions and countries in the 50 years of Technological Forecasting and Social Change

Technological Forecasting and Social Change (TF&SC) is a leading international journal that publishes major advances related to technological forecasting and future studies. The journal was launched in 1969 and in 2019 celebrated its 50th anniversary. To celebrate 50 years of outstanding contributions, this study presents a bibliometric analysis of TF&SC publications and patterns of citations within TF&SC in terms of authors, institutions and countries. The analysis relies on the Web of Science Core Collection database for bibliographic content and Visualization of Similarities viewer software for mapping of bibliometric data. Our analysis identifies leading authors, universities and countries that produce publications in TF&SC. This study also applies bibliometric analysis of co-citations and bibliographic coupling. Results suggest that authors and publications originating in the USA and the Netherlands are particularly influential. However, the journal is becoming more geographically diverse. Mapping of co-citations and bibliographic coupling suggests that work published in TF&SC is represented by several heterogeneous clusters

Uncovering the knowledge flows and intellectual structures of research in Technological Forecasting and Social Change: A journey through history

© 2020 Technological Forecasting and Social Change (TF&SC) celebrates its fiftieth anniversary this year. The anniversary represents an appropriate time for an introspective analysis of the journal's history and impact. This study presents a bibliometric analysis of TF&SC in terms of how often TF&SC is cited by other journals (citation outflow), how often other journals are cited by TF&SC (citation inflow), citations by Web of Science and SCImago disciplinary categories, most-cited articles in TF&SC, co-citation of journals, and co-occurrence of author keywords. Analysis is conducted by using the Web of Science (WOS) database and Visualization of Similarities (VOS) viewer software. The incoming versus outgoing citation patterns identified here suggest an asymmetry in the knowledge flows of TF&SC. Papers published in TF&SC have increasingly cited knowledge from journals in Technology and Innovation Management (TIM), Engineering, and Decision Sciences, but the journal impacts a different set of disciplinary categories such as Energy, Environmental Sciences, and Social Sciences. From 1969–2018, Innovation, Foresight and Forecasting feature as the most popular keywords. Focus on topics such as Patents/Patent Analysis, Climate Change, Sustainability, and Energy seems to have intensified in the last decade. Findings suggest that focus on two countries of interest, India and China, is emerging in research published in TF&SC. Different regions of the world can be expected to place differential emphasis on various topics based on their socioeconomic-technological environments. The journal needs to be receptive to this diversity of perspectives from a growing community of scholars worldwide