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The purpose of this paper is to investigate the relationship between international diversification (ID) and performance in multinational firms by proposing a new and unified theory of multinationality that incorporates, integrates and extends previous concepts and hypotheses.

The study relies on data concerning the world’s largest companies, derived from the Fortune Global 500. An OLS regression analysis has been carried out in order to test a four-stage relationship between ID and performance.

On a final sample of 391 multinationals, this paper provides an empirical evidence that support the existence of a four-stage theory by using a relevant sample of “top” multinational firms.

This study has two main limitations: first, a single indicator was used to measure ID; second, some potential variables have had to be excluded due to data availability.

This paper offers some intriguing practical implications, as well: first, it points out to some thresholds where performances are higher at certain level of ID; second, it highlights that performance will face two kinds of decreases due to intra-regional and inter-regional liability of foreignness; finally, it individuates differences with regard to some firms’ characteristics such as home or host country’s behaviors and about the kind of industries in which they operate, as well.

This is one of the first studies that tests and finds positive evidences about a four-stage theory, regarding to the relationship between ID and performance. Moreover, it proposes other interesting results with regard to the differences between home vs host country-oriented firms and between manufacturing vs services multinational firms.

The purpose of this paper is to develop a simplified but accurate finite element procedure for the analysis of the conjugate conduction-convection heat transfer in cross-flow micro heat exchangers.

The velocity fields in single microchannels are calculated by solving the parabolised form of the momentum equations and later mapped onto the three-dimensional grid, corresponding to an appropriate portion of the micro heat exchanger, which is used for the solution of the energy equation in its elliptic form. To allow the use of finite elements elongated in the flow direction, layers of perpendicular microchannels can be meshed independently with grids that do not match at the common interface (domain decomposition).

An original and easy-to-implement method has been developed to deal with non-matching grids. Computed results show that increasing the number of microchannels per layer yields relative pressure drop increments that are larger than those displayed by the relative heat flow rates.

The simplified procedure requires the assumption of constant thermophysical properties. The adopted domain decomposition technique yields non-symmetric system matrices.

The procedure can be very useful in the design of cross-flow micro heat exchangers.

The finite element procedure described in the paper requires only limited computational resources for the analysis of the conjugate conduction-convection heat transfer in cross-flow micro heat exchangers with a large number of microchannels per layer.

This paper aims to investigate three key factors (i.e. cognitive dimensions, the knowledge-driven approach and absorptive capacity) that are likely to determine the preference for informal inbound open innovation (OI) modes, through the lens of the OI model and knowledge-based view (KBV). The innovation literature has differentiated these collaborations into informal inbound OI entry modes and formal inbound OI modes, offering an advocative and conceptual view. However, empirical studies on these collaborations are still limited.

Building on the above-mentioned theoretical framework, the empirical research was performed in two stages. First, data were collected via a closed-ended questionnaire distributed to all the participants from the sample by e-mail. Second, to assess the hypotheses, structural equation modelling (SEM) via IBM® SPSS® Amos 20 was applied.

The empirical research was conducted on 175 small to medium enterprises in the United Kingdom, suggesting that the knowledge-driven approach is the strongest determinant, leading to a preference for informal inbound OI modes. The findings were obtained using SEM and are discussed in line with the theoretical framework.

Owing to the chosen context and sector of the empirical analysis, the research results may lack generalisability. Hence, new studies are proposed.

The paper includes implications for the development of informal inbound OI led by knowledge-driven approach.

This paper offers an empirical research to investigate knowledge-driven preferences in informal inbound OI modes.

The purpose of this study is to explore how companies can adopt digital humanism (DH), defined as the integration of humanistic skills in the development process of digital technologies, to create value and consequently develop effective business models. Specifically, the aim is to answer the following research question: what are the main DH mechanisms through which companies create value?

Given the limited understanding of the phenomenon under investigation, a qualitative approach was adopted based on a multiple-case study to explore how companies are embracing DH. The study will focus on three exemplar cases in the use of DH, namely, IBM, Microsoft and SAP, well recognized as three of the market leaders in the IT industry. In addition, the selected companies are recognized as some of the most innovative in their specific industries, hence offering a rich set of information on how to specifically embrace DH.

This study unveils the main mechanisms through which companies can create value by implementing DH’s approaches into their business models.

The originality of this research lies in its focus on how companies integrate DH into their business models. Indeed, the study aims at uncovering the main mechanisms that companies use to integrate DH into their overall business practices. Overall, this research provides valuable insights into how companies can effectively integrate DH into their business models, which could have important implications for creating responsible, sustainable and inclusive solutions that prioritize human needs and values.

The purpose of this paper is to propose a new statistical approach to evaluate complex open innovation projects on a quantitative basis. In certain circumstances, open innovation entails a radical change of policy that involves various different functions of a company such as R&D, production, and management over a period of years and gives rise to mechanisms of mutual interaction with several business partners, such as collaboration with other companies, universities and R&D institutions, and new suppliers. Then, the question arises of how to measure the impact of such complex open innovation processes on the overall performances of companies.

A holistic case study is applied to analyze the effect of open innovation projects on a corporate company’s stock price dynamics. The scope is to identify two different scenarios pre- and post-adoption of an open innovation model by a multinational company, Fujifilm. In particular, a stochastic model, namely the log-normal model, is applied along with three statistical tests: Kolmogorov-Smirnov, Cramer von Mises, and F-test for equal variances, in order to verify if the adoption of an open innovation model causes any significant change in the stock price dynamics of the corporate company.

From the findings emerges evidence that open innovation projects have a moderate effect on Fujifilm’s stock price dynamics, but a greater improvement of the perception of Fujifilm’s stock value. This enhances the management and financial literature review by offering a novel, empirical perspective on the effect of the adoption of an open innovation model on a corporate company’s stock price dynamics.

This research is limited to a single case study, but it can be extended to other stock market companies and therefore improve on the present study.

An original application of Kolmogorov-Smirnov tests to detect and measure the differences between the two regimes of pre-open innovation and post-innovation regimes.

The purpose of this paper is to scrutinize and classify the literature linking Big Data analytics and management phenomena.

An objective bibliometric analysis is conducted, supported by subjective assessments based on the studies focused on the intertwining of Big Data analytics and management fields. Specifically, deeper descriptive statistics and document co-citation analysis are provided.

From the document co-citation analysis and its evaluation, four clusters depicting literature linking Big Data analytics and management phenomena are revealed: theoretical development of Big Data analytics; management transition to Big Data analytics; Big Data analytics and firm resources, capabilities and performance; and Big Data analytics for supply chain management.

To the best of the authors’ knowledge, this is one of the first attempts to comprehend the research streams which, over time, have paved the way to the intersection between Big Data analytics and management fields.