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Previous research focused on open innovation (OI) suggests that enterprises benefit from adopting the journey; however, the relationship among OI, marketing journey and knowledge-intensive innovation marketing activities (KIIMA) remains unclear. The present study proposes a conceptual model of the marketing journey linking heterogeneous modes of marketing collaboration to knowledge-intensive activities.

The conceptual model was tested via ordinary least squares (OLS) linear regression based on a sample of data drawn from the Eurostat database.

The results indicate that strategies are a robust proxy for evaluating KIIMA, and partnerships, heterogeneous sources of knowledge and different marketing modes for collaboration among European knowledge-intensive firms are core antecedents of KIIMA, such as new-product development and marketing innovation, as well as firms' sustainable competitive advantage.

This study fills the gap by tracking the role of the journey within marketing collaborations on KIIMA, and it intervenes in the debate about interactive marketing innovation mechanisms. The study contributes to OI, knowledge management and the marketing literature by identifying the heterogeneous modes for marketing collaborations under which the marketing journey enhances knowledge-intensive activities such as those for marketing innovation.

This study aims to investigate the effects of open innovation (OI) and big data analytics (BDA) on reflective knowledge exchange (RKE) within the context of complex collaborative networks. Specifically, it considers the relationships between sourcing knowledge from an external environment, transferring knowledge to an external environment and adopting solutions that are useful to appropriate returns from innovation.

This study analyzes the connection between the number of patent applications and the amount of OI, as well as the association between the number of patent applications and the use of BDA. Data from firms in the 27 European Union countries were retrieved from the Eurostat database for the period 2014–2019 and were investigated using an ordinary least squares regression analysis.

Because of its twofold lens based on both knowledge management and OI, this study sheds light on OI collaboration modes and highlights the crucial role they could play in innovation. In particular, the results suggest that OI collaboration modes have a strong effect on innovation performance, stimulating the search for RKE.

This study furthers a deeper understanding of RKE, which is shown to be an important mechanism that incentivizes firms to increase their efforts in the innovation process. Further, RKE supports firms in taking full advantage of the innovative knowledge they generate within their inter-organizational network.

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 study aims to explore the interplay between open innovation and intellectual property. Differently from previous studies, we argue that open innovation fosters firm's patenting activity.

We use linear regression analysis to test model's hypotheses. Data are drawn from the Eurostat statistics and refer to a large sample of European firms (NACE Rev.2).

The findings confirm that open innovation fosters patenting activity in health care, also thanks to huge governments' expenditures in this market.

The study focuses solely on European firms and it adopts a traditional linear approach. So, we cannot exclude that different dynamics may occur across European borders. Future research should address this concern by focusing on multi-country comparative studies.

Open innovation is the most suitable model for health industry, because it improves both innovation performance and intellectual capital of firms.

The study tackles an existing gap of the literature by considering how the presence of large customers impacts the strength of intellectual property protection.

In this paper, we solve by a finite difference upwinded method an extended hydrodynamic model for semiconductors, with viscous terms in the momentum equation. In particular, we consider the simulation of a one‐dimensional n⁺‐n ‐n⁺ diode, whose solution exhibits at low temperatures strong discontinuities, and investigate the effect of the momentum viscosity on the shock waves. Numerical experiments, performed also on a two‐dimensional test case, demonstrate that the numerical scheme, working on non‐uniform grids, is suitable to describe solutions with strong variations in time and space. Well‐posedness for the boundary conditions is discussed, and a linear stability estimate is established for the one‐dimensional n⁺‐n ‐n⁺ diode benchmark problem.

The purpose of this paper is to present and discuss a model to evaluate the top management quality and its impact on the default probability/survival probability of companies operating in the Italian food and beverage industry. The focus is on SMEs and private companies (ie. companies with no external or public rating). The general aim of this paper is to initiate a new field of research enjoying the fast and growing number of information underlying the development of the private lending market (both banking channel and private debt channel) and the recent developments in assessing the managerial styles of leadership.

The methodology used in the research is a mixed method based on quantitative and qualitative analysis. The authors have followed the sequential mixed methods design (Creswell and Plano Clark, 2007; Almalki, 2016) belonging to a practice perspective (Tashakkori and Creswell, 2007). The two components (quantitative and qualitative) are integrated in the combined approach: a final proposed evaluation model is explained and discussed.

According to the experience (and private market best practice) the leadership style has a material impact on the survival probability of a company (and, on the contrary, on the default probability of a company). In other words, the leadership style – other variables be equal – can provide significant information to investors about the future evolution of the financial performance and related credit risk. In the paper, the authors provide a useful model (and tool) in order to capture the above mentioned relationship to support investment decisions in food and beverage industry.

While a positive relationship between a participative style of leadership and the financial performance is widely accepted in the literature; there is no published research on the relationship between managerial styles of leadership and default probability/survival probability. There are several workstreams to be performed in future research in order (1) to provide more business evidence and (2) to extent the analysis to further industries (other than food and beverage). The first step is to collect more data and company information on managerial styles of leadership and to start to track, to measure and monitor the evolution of the credit risk over time in each of the four clusters identified in the combined model.

The practical implication is to provide a methodological contribution to develop an evaluation model of top management quality to be used for the certification of the quality system. The proposed evaluation model is intended to support both (1) the ISO quality management system certifiers and (2) financial analysts and auditors in order to assess the going concern and the business sustainability and (3) the credit risk assessment and evolution in investment decisions.

The authors believe that a more deep understanding on the effectiveness of managerial styles of leadership on credit risk can improve the credit and investment allocation and to enhance the borrowing capabilities of the food and beverage industry (with relevant implications on number of employees and size of new investments).

This is the first applied research on the link between the default probability/company survival probability and the quality of management in the Italian food and beverage industry.

As various different and even contradictory concepts are proposed to depict a firm's capabilities related to big data, and extant relevant research is fragmented and scattered in several disciplines, there is currently a lack of holistic and comprehensive understanding of how big data alters value creation by facilitating firm capabilities. To narrow this gap, this study aims to synthesize current knowledge on the firm capabilities and transformation of value creation facilitated by big data.

The authors adopt an inductive and rigorous approach to conduct a systematic review of 185 works, following the “Grounded Theory Literature-Review Method”.

The authors introduce and develop the concept of big data competency, present an inductive framework to open the black box of big data competency following the logic of virtual value chain, provide a structure of big data competency that consists of two dimensions, namely, big data capitalization and big data exploitation, and further explain the evolution of value creation structure from value chain to value network by connecting the attributes of big data competency (i.e. connectivity and complementarity) with the transformation of value creation (i.e. optimizing and pioneering).

The big data competency, an inclusive concept of firm capabilities to deal with big data, is proposed. Based on this concept, the authors highlight the significant contributions that extant research has made toward our understanding of how big data alters value creation by facilitating firm capabilities. Besides, the authors provide a future research agenda that academics can rely on to study the strategic management of big data.

Despite the increasing studies concerning external knowledge for innovative firms or for innovations, little research demonstrates as what are those capabilities that enable firms to explore and assess high-valuable knowledge. The aim of this study is to examine those capabilities that aid innovative firms to search and identify the potential knowledge for open innovation. This study is an empirical and theoretical examination of knowledge search and identification capabilities of the UK-based biotechnology firms. The literature has been drawn from the research streams into knowledge management, open innovation and dynamic capabilities.

Forty-five semi-structured interviews with senior-level innovation and R&D managers were completed, and thematic analysis using NVivo 12 was performed.

Evidence from 45 interviews with senior-level innovation and R&D managers in the UK-based biotechnology firms and thematic analysis was used to develop a process framework capturing the key capabilities. By identifying the role and contribution of each of the capabilities in knowledge identification in the practices of open innovation, this study contributes to open innovation and knowledge management literature.

Managerial implications suggest knowledge-oriented leads greatly influence the development of identification capabilities. Hence, firms with knowledge-oriented leads are better crafted approaches to achieve competitive advantages in the practices of open innovation.

This study offers a new theoretical perspective and empirical evidence to view knowledge identification capabilities as the dynamic capabilities. This study offers a process framework of identification capabilities.

With the advent of Industry 5.0, digital transformation (DT) has received much attention in the tourism industry. Therefore, this research aims to provide a thematic map of the DT of tourism in Industry 5.0 and then provide a model for tourists’ acceptance of Industry 5.0 digital technologies.

First, a systematic literature review was done to provide the thematic map of this field, and the data were analyzed using the R-Tool. In the second step, a meta-analysis of all available studies on technology acceptance by tourists in Industry 5.0 was conducted, and the data were analyzed using CMA3 software.

The findings are divided into four main themes: motor themes (acceptance of technology by tourists); basic themes (smart tourism through digital technologies); niche themes (digital transformation of tourism in small and medium-sized enterprises) and essential or declining themes (digital transformation in destination marketing). The second part showed that performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV) and habit (HB) positively affect behavioral intention (BI). FC, HB and BI have a positive effect on use behavior (UB). Age variable moderates the impact of FC, HM and HB on BI but does not moderate the impact of PV on BI. Age variable moderates the effect of HB on UB. Gender variable moderates the impact of HB on UB but does not moderate the effect of FC, HM, PV and HB on BI. The experience variable moderates the effect of FC on BI, HB on UB and BI on UB but does not moderate the impact of HM and HB on BI.

This research is the first to present a thematic map of DT in the tourism industry in Industry 5.0. It is also the first research demonstrating the digital technology acceptance model by tourists in Industry 5.0.