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This paper aims to investigate the production function of firms based on the use of intellectual capital. The authors come up with this problem since believe that the new economy conditions require an adjustment and a development of classical firm theory.

The research question addressed in this study is mainly related to the empirical validation of the function based on companies' intangibles in the Cobb-Douglas framework. This model enables the authors to advocate the idea of the complementarity of intellectual resources as well as simplifies the analysis of intellectual capital features. To accomplish the purpose of the research, the authors design a log-linear model and estimate it on a sample of more than 400 European and American companies.

Application of Cobb-Douglas framework allowed designing a production function based on intellectual capital. The complementarity of intellectual capital components is justified on the empirical results obtained in this research. The increasing return to scale for intellectual capital was established for the sample examined in this study.

The main shortcoming of the approach implemented in this study is related to the proxy indicators of intellectual capital. Nevertheless, the authors statistically validate the chosen indicators applying hedonic approach.

Practical accomplishment of this research is mainly associated with the conclusion about an increasing return to scale of intellectual capital. This phenomenon appears to be of a particular importance for investment decisions.

The findings of this paper provide a new insight into intellectual resources interrelation that enhances companies' value creation. The authors also hope to assist future research attempts in application of the theory of company's growth driven by its intangible capital.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

The present study develops a multi-theoretic framework of the mechanisms of value creation in interorganizational relationships and of the key factors influencing those mechanisms. The integrative use of several theories in building the model is justified by numerous studies suggesting that a multi-theoretic approach is required to understand the complexity of interorganizational relationships (Gulati, 1998; Osborn & Hagedoorn, 1997; Park et al., 2002). We believe that the relationships between start-up companies and their corporate investors, with each party holding a diversity of strategic and financial objectives, are not less complex than other potential interorganizational relationships. They may therefore also require ideas from several theories to be properly understood. In this study, we build the models applying primarily the resource-based and the knowledge-based views, as well as social capital theory. Ideas from other theoretical approaches are used to complement these theories.

The purpose of this paper is to investigate the impact of two dimensions of technological relatedness, namely technological similarity and complementarity, on collaborative performance, plus the mediating role of collaboration network stickiness and the moderating role of partner expertise and geographical distance in interfirm collaboration contexts.

This study takes Chinese Scientific and Technological Achievements (STA) of inter-firm collaboration in five high-tech fields in 2010–2020 as the sample and uses OLS regression to test the hypothesis.

Technological similarity and complementarity positively affect collaborative performance. Partner expertise negatively moderates the relationship between similarity, complementarity and collaborative performance. Geographical distance positively moderates the relationship between similarity and collaborative performance while negatively moderates that between complementarity and collaborative performance. Collaboration network stickiness partly mediates the relationship between similarity and collaborative performance.

This study expands literature on inter-firm collaboration, especially research on the antecedents of collaborative performance. Moreover, this study not only compensates for lack of empirical analysis in partner selection research, but also utilizes second-hand data to enhance the objectivity of analysis. Additionally, we enrich the research on the moderating role of partner expertise and geographical distance as well as the mediating role of collaboration network stickiness.

In this article, intellectual capital is seen as complementary capacities of competence and commitment. Based on theoretically and empirically robust human capital theory, we define intellectual capital as individuals’ complementary capacity to generate added value and thus create wealth. Resources are then perceived to be both tangible and intangible. This view is an extension of human capital theory to include the intangible capacities of people. Implications for future research are discussed.

Our purpose is to evaluate effectuation and bricolage through their unique and shared references to understand possible overlaps and conceptual complementarities between these theoretical approaches.

The use of bibliometric techniques to examining simultaneously both theoretical approaches is one of the distinctions of this work. Another important methodological feature is the use of co-citation and bibliographic coupling and their interaction, to verify 179 published documents relating to their references.

The study reveals the intellectual structures underlying the approaches and differences originating from their knowledge bases, as well as the research trends.

By identifying the differences in the decision process and behaviors that culminate in opportunity creation in each, it offers a complementary vision of previous works. The evidence stresses it is interesting to explore their integration, considering the complementarity of their unique aspects.

This paper examines the limits of pragmatism in strategy formulation in the new, knowledge‐rich economy. By tracing the history of pragmatism in social and management thought, and assessing the commonalties and complementarities between a firm’s vision and mission, we explore the possibility and consequences of an intangible resource curse for firms pursuing strategies of incessant pragmatic growth in the expanding Web‐based domain. Ultimately, we posit a combined influence of market‐based governance and strategy simplification as an effective antidote to the executive intangible resource binging, which is sustainable as long as confidence and trust continue to be shared among the firm stakeholders.

This paper attempts to propose an integrated model for measuring the knowledge transfer effectiveness in university‐industry alliances. The so‐called “RDCE” model is thereby proposed as an integrated model for measuring the knowledge transfer effectiveness. By combining inter‐organizational relations (IORs), knowledge‐based view (KBV) and resource‐based view (RBV) of firms, this paper aims to focus on the influence of determinant factors such as partner complementarities, partner attributes, the characteristics of the coordination and relationship quality between industrial companies and universities that may lead to the effectiveness of knowledge transfer.

This framework thereby clarifies how mediating variables influenced the paths that constitute the direct, indirect and total effects of mediated models by integrating moderated regression analysis together with bootstrap resampling methods to ensure the precision in estimating confidence intervals of indirect effects and path analysis using structural equation models to test all the hypotheses simultaneously for the robustness of the results and conclusions.

The statistical results reveal that the proposed model has a significant mediating effect that contributes to knowledge transfer effectiveness. Only partner attributes and relationship factors have a direct impact on the effectiveness of knowledge transfer. This appears plausible since mere complementarities and coordination between partners may not lead to learning or knowledge transfer, which requires a certain depth of the partner interaction in terms of the specific attributes of partners, coordination and relationship quality.

The authors assumed that the alliance constitutes partnerships between firms of roughly equal size and market power. Therefore, this study provided only broad perspectives of collaboration among alliance partners, and did not capitalize on different degree of alliance integration and different types of collaboration.

Managerial suggestions on how to improve their knowledge transfer effectiveness are also provided at the end of the text.

There are numerous studies examining alliance network performance. Very few studies, however, have examined detailed collaborative activities in dyadic university‐industry partnerships and potential constructs for measuring knowledge transfer and commercialization in the research and development alliance between industrial firms and university context.

The purpose of technology mergers and acquisitions (M&A) is to achieve innovation. The authors use the data from the China Patent Research System of China National Intellectual Property Administration to classify technical correlations into three types: similar, complementary and nonrelatedness (cross-sectoral category). And the authors explore three issues: the market reaction to technology-oriented M&A, the impact of technology-oriented M&A on goodwill and how technology-oriented M&A affects innovation.

The authors use data from China Patent Research System of China National Intellectual Property Administration to classify technical correlations into three types: similar, complementary and nonrelatedness (cross-sectoral category). And the authors explore three issues: the market reaction of technology-oriented M&A, the impact of technology-oriented M&A on goodwill and how technology-oriented M&A affects innovation. The empirical research shows that the cross-sectoral M&A is popular in the market and is positively correlated with cumulative abnormal return (CAR) and premium rate of M&A. However, the technology-similarity M&A, which is committed to in-depth exploration of original technology, is negatively correlated with CAR and goodwill.

The empirical research shows that cross-sectoral M&A is popular in the market and is positively correlated with CAR and premium rate of M&A. However, the technology-similarity M&A, which is committed to in-depth exploration of original technology, is negatively correlated with CAR and goodwill. In addition, empirical results show that there is an inverted U-shaped relationship between technology-oriented M&A and innovation output, and the inflection points are 41.8%, 48.9% and 38.8%, respectively.

The research contributions of this paper are as follows: first, most domestic studies simply and roughly measure the degree of technical relevance based on whether the firms belong to the same industry and whether there is common knowledge between them, but the authors provide a more accurate measure of technology-oriented M&A. Second, in the research on the economic consequences of technology-oriented M&As, a large number of literatures have mainly focused on the innovation performance of the acquirer after deals, including the number of patent applications, the number of patent citations, innovation output, etc., and they pay less attention to its impact on the market reaction and goodwill.

This paper argues that intellectual capital and intangible assets are difficult resources for two different reasons. First, intellectual capital and intangibles assets are not (yet) disentangled by the institutions of the capital markets, and therefore they are not (yet) translatable with any degree of confidence into predictions about stock price behaviour. Second, intellectual capital and intangibles are not absent from capital market intelligence; they are just typically translated into financial form, when they are presented to actors in the capital markets, even if in forms that are themselves “invisible”. The capital market may have limited understanding of intellectual capital, but it is also always seeking to understand the complexity of business and (im)possible futures. Its appreciation of intellectual capital is therefore fragile.