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Article
Publication date: 4 October 2021

Armando Papa, Alice Mazzucchelli, Luca Vincenzo Ballestra and Antonio Usai

Previous research focused on open innovation (OI) suggests that enterprises benefit from adopting the journey; however, the relationship among OI, marketing journey and…

Abstract

Purpose

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.

Design/methodology/approach

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

Findings

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.

Originality/value

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.

Details

International Marketing Review, vol. 39 no. 3
Type: Research Article
ISSN: 0265-1335

Keywords

Open Access
Article
Publication date: 15 September 2020

Armando Papa, Roberto Chierici, Luca Vincenzo Ballestra, Dirk Meissner and Mehmet A. Orhan

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…

2058

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Details

Journal of Knowledge Management, vol. 25 no. 4
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 8 February 2018

Luca Vincenzo Ballestra, Stefano Fontana, Veronica Scuotto and Silvia Solimene

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Details

Management Decision, vol. 56 no. 6
Type: Research Article
ISSN: 0025-1747

Keywords

Article
Publication date: 2 September 2020

Beatrice Orlando, Luca Vincenzo Ballestra, Domitilla Magni and Francesco Ciampi

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…

Abstract

Purpose

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.

Design/methodology/approach

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).

Findings

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

Research limitations/implications

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.

Practical implications

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

Originality/value

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

Details

Journal of Intellectual Capital, vol. 22 no. 2
Type: Research Article
ISSN: 1469-1930

Keywords

Abstract

Details

Management Decision, vol. 56 no. 6
Type: Research Article
ISSN: 0025-1747

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