Search results

This paper aims to provide an experimental evaluation of geometric errors on the edges of parts manufactured by the fused deposition modeling (FDM) process.

An experimental plan was conducted by building parts in ABS thermoplastic resin on a commercially available machine with given combinations of the three geometric variables (inclination, included and incidence angle) defined in the first part of the paper. Edges on built parts were inspected on a two-dimensional non-contact profilometer to measure position and form errors.

The analysis of measurement results revealed that the edge-related variables have significant influences on the geometric errors. The interpretation of error variations with respect to the different angles confirmed the actual occurrence of the previously discussed error causes. As an additional result, quantitative predictions of the errors were provided as a function of angle values.

The experimental results refer to fixed process settings (material, FDM machine, layer thickness, build parameters, scan strategies).

The two-part paper is apparently the first to have studied the edges of additively manufactured parts with respect to geometric accuracy, a widely studied topic for surface features.

Design thinking is widely recognized as an effective problem-solving approach in the professional and academic world, albeit with varying interpretations. It has been studied in multiple forms – as a tool, a practice, a skill and a mindset – leading to ongoing debates about its fundamental nature. This study aims to explore the use of design thinking in practice and determine how its application varies depending on the characteristics of the innovation projects, namely, the types of goals pursued and the level of uncertainty involved.

Using a survey methodology and a knowledge-intensive empirical setting, this study analyzes a data set of 221 innovation consulting projects based on design thinking conducted by European consulting firms and design agencies.

By analyzing the survey data, the authors identify six distinct sets of design thinking practices: discovering user needs, understanding the problem addressed, challenging existing assumptions, navigating the problem-solution pair, ideating through visualizations and learning through prototypes. The authors also identify configurations of these design thinking practices that are used to address different innovation project goals and levels of uncertainty.

The study draws attention to the need for design thinking practitioners to be aware of how different innovation project goals and levels of uncertainty can be pursued/addressed through the use of alternative configurations of design thinking practices.

To the best of the authors knowledge, this study is one of the first large-scale quantitative analyses of the nature of design thinking in action, providing a solid foundation for future research on design thinking.

The purpose of this paper is to propose a method for simulating the profile of part edges as a result of the FDM process. Deviations from nominal edge shape are predicted as a function of the layer thickness and three characteristic angles depending on part geometry and build orientation.

Typical patterns of edge profiles were observed on sample FDM parts and interpreted as the effects of possible toolpath generation strategies. An algorithm was developed to generate edge profiles consistent with the patterns expected for any combination of input variables.

Experimental tests confirmed that the simulation procedure can correctly predict basic geometric properties of edge profiles such as frequency, amplitude and shape of periodic asperities.

The algorithm takes into account only a subset of the error causes recognized in previous studies. Additional causes could be integrated in the simulation to improve the estimation of geometric errors.

Edge simulation may help avoid process choices that result in aesthetic and functional defects on FDM parts.

Compared to the statistical estimation of geometric errors, graphical simulation allows a more detailed characterization of edge quality and a better diagnosis of error causes.

Social media are emerging as the ideal channel for building one-to-many communication and disseminating intellectual capital (IC) information. Their rise is bringing out new research challenges to investigate the implications of their use. However, there needs to be more research contributions relating to the financial benefits of using social media for IC disclosure (ICD). This study aims to bridge this gap by analyzing, under the lens of signaling theory, the effect of ICD through Twitter on firm value.

This study is based on a content analysis of tweets disseminated by 262 companies aimed at examining the amount of IC information disclosed and on a regression analysis aimed at analyzing the impact of this type of information on firm value.

Empirical results show that a large ICD via Twitter favors an increase in firm value. They also demonstrate that disclosing information relating to the three IC dimensions positively affects the firm value. These findings suggest that actively and comprehensively communicating IC information via Twitter can help improve the perception and evaluation of the company by investors and other stakeholders.

This study offers empirical evidence about the financial benefits associated with using social media as disclosure tools by companies. It also enriches the literature on the relationship between ICD and firm value and consolidates the goodness of the signaling theory as an ideal theoretical perspective to frame the relationship between IC information and firm value.

This study offers important managerial implications for firms and investors. In light of the significant financial benefits, firms should use social media to disclose IC information and should seek to increase their visibility on such platforms to convey the information to a greater number of users. Investors should also heed social media when gathering IC information, combining the analysis of these platforms with that of traditional corporate documents.

This study enriches the limited literature on ICD via social media and extends knowledge about the relationship between IC information and firm value. In this regard, the originality also lies in the individual analysis of the impact of the three IC dimensions on firm value.

This study aims to delve into the relationship between open innovation and organizational effectiveness, expanding upon previous research that primarily focused on the impact of open innovation on firm performance.

Based on data collected from top- and middle-level managers across diverse sectors in India, the authors examined the intricate dynamics of open innovation and its effects on organizational effectiveness. The authors took two approaches to examine the data; using structural equation modeling and using the fuzzy set qualitative comparative analysis (fsQCA) approach.

This empirical evidence underscores the potential advantages of adopting open innovation practices within organizations. The contribution extends to both theoretical and practical domains.

Theoretically, this research enriches the literature on open innovation and organizational effectiveness by providing empirical substantiation for their interconnection.

From a practical perspective, the findings offer actionable insights for practitioners and organizational leaders, suggesting that embracing open innovation can significantly enhance organizational effectiveness, ultimately fostering improved performance and competitiveness. The findings also have implications for external stakeholders aiming to engage with innovation-driven organizations for purposes of commercialization and knowledge exchange.

This study advocates for incorporating inbound and outbound open innovation practices within strategic decision-making processes to achieve organizational effectiveness.

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 paper is to examine what strategies the CEOs of research and development (R&D) intensive small/medium enterprises (SMEs) in the life sciences sector carry out in regard to open innovation (OI), as R&D costs continue to rise, placing pressure on innovation managers.

A qualitative study was carried out, consisting of 30 semi-structured interviews with CEOs of small R&D intensive SMEs in the life sciences sector. The authors analysed the key factors identified by the CEOs in relation to their OI strategies.

SMEs adopt a range of OI strategies and collaborations, subject to certain conditions. A multilevel mapping developed from the analysis connects actors to the wider domain, setting the outcomes of the research in context.

This qualitative study provides detailed understandings that could provide the basis for a wider quantitative study that would provide greater coverage of the sector, thus reinforcing the outcomes.

The study will be relevant to practising CEOs who are considering the range of options offered by OI.

While large firms are adopting OI strategies, less is known about the OI strategies developed in SMEs. The study addresses that gap. The life sciences context is also novel.

Nowadays, an analysis of the circumstances that have led to the development of specific industries within regional entrepreneurial ecosystems (EEs) is extremely relevant. The chapter carries out a twofold analysis, in order to fully explore the reasons that have led to the creation of a specific industrial district. On the one hand, the tissue paper industry in the Italian province of Lucca is analysed through a qualitative approach; on the other hand, the contextual traits of the Toscana EE influencing firm performance are investigated through using a quantitative research approach. This mixed research analysis provides some important hints. First, it helps to understand how systemic, framework and human conditions affect firm performance. Second, it examines how historical, social, and economic factors have shaped regional industries. Through an in-depth analysis, the chapter provides theoretical and empirical insights into the dynamics that affect industrial transformation in response to globalisation, technological innovation, and changing market demands. After completing the chapter, readers will understand how knowledge, collaboration, and shared resources drive regional competitiveness. Through the qualitative analysis, readers will be aware of the tissue paper industry evolution. The combination with the quantitative study allows us to capture the different drivers swaying firm performance, such as infrastructure, innovation capacity, and institutional support. Therefore, the use of empirical data enables for a more objective assessment of the earlier contextual elements, revealing trends and patterns that may not be immediately evident through qualitative analysis.

The purpose of this paper is to report on the study of the two acquisitions of Telecom Italia carried out by Olivetti and Pirelli in the last decade, to evaluate how changes in ownership structure and corporate governance affected minority protection.

The paper presents an analysis of how Olivetti's and Pirelli's takeovers were achieved. Then the authors contrast the two operations with regards to extraction of private benefits and expropriation of minorities' wealth.

Shows that, in the case of Telecom Italia, the implementation of pyramids is connected with the existence of large private benefits, and that the acquisitions resulted in the substantial expropriation of minority shareholders.

The analysis is referred to a very unique case. While a lot can be learnt from this approach, generalisations are not trivial.

The conclusion is that groups owning several listed companies deserve a special discipline, as many are the policy implications of their presence in financial markets.

Proposes an ad hoc methodology to consider companies from the top to the bottom of the pyramid chain, and to put in a common framework the non‐simultaneous operations linked by a common strategic goal, namely an acquisition. Further, a set of governance lessons is provided.