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The aim of this paper is to develop the conceptual design of an information and communication technologies (ICT) platform supporting the inbound open innovation (OI) process within the technological developments business unit of Leonardo Defence Systems.

After a preliminary phase concerning the context analysis, methodology includes three main steps: conceptualization of functions; preliminary design; and conceptual design of the system/SW architecture. In each of these phases, the authors tried to merge evidence from the scientific literature with empirical insight emerging from the field.

Results report the conceptual design proposal for an integrated ICT platform supporting the OI. It includes the conceptualization of main functions, the preliminary design deriving from use cases and the proposal for the overall system architecture and data model.

The research focuses only on the conceptual design phase; at this stage, the platform has not been still implemented or tested. Also, generalizability concerns may arise from the single-application context.

The outcoming conceptual design can be useful for firms that open their boundaries to external partners, as well as for software developers which could draw on it. Firms approaching similar OI challenges can re-contextualize the platform to their own setting.

Originality of this research relies on the attempt to show how ICT can support firms in their OI processes and, secondly, to support firms aiming to create a positive environment that encourages people at leveraging existing external technological opportunities and sources of knowledge. In so doing, a systematic design approach to the definition of the conceptual proposal is also pursued.

The innovation expected by clients is identified as a business success factor of industrial companies in the current decade and the accountability of it is primarily attributable to Research and Development (R&D), which makes it a strategic topic for studies on the decision-making process. In light of this, the purpose of this paper is to present a decision aiding methodology used to support R&D management in the technology-based company, specialised in refrigeration solutions and world leader in the hermetic compressor market.

It is an exploratory study and has deductive-inductive logic and uses a quail-quantitative approach. It uses the Knowledge Development Process Constructivist (ProKnow-C) to systemically revise the literature surrounding the theme in order to identify research opportunities in the subject and adopts the Multi-Criteria Decision Aiding Constructivist (MCDA-C) methodology as an instrument of organisational performance evaluation to fulfil the research opportunities identified.

In the theoretical aspect, this research fulfilled the opportunities observed in recent and qualified literature about R&D performance evaluation. The paper also offers practical implications for the performance evaluation in R&D, since the methodology allowed the R&D manager to build knowledge to understand the consequences of his decisions in the criteria deemed important by himself.

The importance of this work covers academic and practical interests, as it documents the application of MCDA-C and increases knowledge concerning R&D management, whilst developing a recurrent tool of decision aiding in the context of the company studied.

The purpose of this paper is to analyze the innovation strategies of the sugar–energy industry in Central-Southern Brazil with regard to its resource structure and results.

The data were collected through a questionnaire covering the three-year period from 2015 through 2017. The results were extracted based on a combination of factor analysis and multiple regression analysis.

The innovation strategies of Brazilian sugar–energy companies are characterized as defensive and imitative based on the resources dedicated to innovation and the implementation of innovation with respect to products, processes, eco-innovation and cost reductions.

The sample is representative, but it does not cover all companies in the Brazilian sugar–energy industry. The data were acquired using a survey, and the results could not be compared to the financial results of the companies.

Sugar–energy companies need to define their innovation strategies, as these strategies lead to different results that can be achieved only through the management of resources dedicated to the generation and implementation of innovations. Managers and analysts need to know the profile of these innovation strategies to evaluate the effectiveness of the results based on the resources that were invested.

This study presents an exploratory model that identified two factors related to innovation efforts and three results. It is possible to define the innovation strategies of companies in the Brazilian sugar–energy industry, which is one of the most competitive in Brazil.

Behavioral finance research has almost exclusively investigated the decision making of lay individuals, mostly ignoring more sophisticated institutional investors. The purpose of this paper is to better understand the relatively unexplored field of investment decisions made by pension fund trustees, an important subset of institutional investors, and identify future avenues of further exploration.

This paper starts by setting out the landscape in which pension fund trustees operate and make their decisions, followed by a literature review of the extant behavioral finance research applicable to similar situations.

Despite receiving training and accumulating experience in financial markets, these are limited and sparse; therefore, pension fund trustees are unlikely to be immune from behavioral biases. Trustees make decisions in groups, are heavily reliant on advice and make decisions on behalf of others. Research in those areas has uncovered many inefficiencies. It is still unknown how this specific context can affect the psychological effects on their decisions.

Given how much influence trustees’ decisions have on asset allocation and by extension in financial markets, this is a surprising state of affairs. Research in behavioral finance has had a marked influence on policy in the past and so we anticipate that exploring the decisions made within pension funds may have wide ramifications for the industry.

As far as the authors are aware, no behavioral research has empirically tested pension fund trustees’ decisions to investigate how the combination of group decisions, advice and surrogacy influence their decisions and, ultimately, the sustainability of our pensions.

Since 2012, the Brazilian Stock Exchange has recommended that listed companies inform them if they have conducted voluntary disclosure. The purpose of this study is to describe the voluntary disclosure by companies listed in the B3 in Brazil and to analyze which characteristics of the board of directors influence this disclosure.

The study involves quantitative research using a sample of 285 companies and 575 reports from 2011 to 2014. A fixed-effects regression model with panel data was used for the analysis.

The results were statistically significant for gender and duality variables, which confirms the theory that the presence of women as members of the board positively influences voluntary disclosure and that chief executive officer and chairman of the board positions have a negative effect. The age and independence of the board variables did not present statistical significance.

As a theoretical contribution, the authors aim to complement sustainability, finance and strategy research by using agency theory and measuring the variable of voluntary disclosure and the board, which is rarely studied in this context.

As social and empirical contributions, a better understanding of this theme in the context of emerging countries, which is the peculiarities of Brazil with little information transparency and well-known corruption scandals, is likely to aid investors. Increased access to company information can help investors better select their investment portfolios and assist in the choice of their board representatives in companies in which they have participation and voting rights.

The fact that Brazil is an emerging country, where the lack of transparency of information and corruption in these environments stand out the importance of studying the subject of voluntary disclosure in this context. All data were collected manually specifically for this research.

This paper aims to present the application of a tailored systematic engineering design procedure to the concept design of a small production plant for compostable packaging made by straw fibres and bioplastic. In particular, the obtained boxes are intended to be used for wine bottles.

A systematic procedure has been adopted, which underpins on a comprehensive analysis of the design requirements and the function modelling of the process. By considering well-known models of the engineering design process, the work focuses on the early design stages that precede the embodiment design of the whole components of the plant.

The followed design approach allowed to preliminarily evaluate different alternatives of the process from a functional point of view, thus allowing to identify the preferred conceptual process solution. Based on the identified functional sequence, a first evaluation of the potential productivity and the required human resources has been performed.

The procedure shown in this work has been applied only for the considered case of compostable packaging, and other applications are needed to optimize it. Nevertheless, the adopted systematic approach can be adapted for any context where it is necessary to conceive a new production plant for artefacts made by innovative materials.

The work presented in this paper represents one of the few practical examples available in the literature where systematic conceptual design procedures are presented. More specifically, to the best of the authors’ knowledge, this is the very first application of systematic design methods to compostable packaging production.

We explore the impact of a specific knowledge management framework on the quality of innovation, the geographic distribution of R&D and the cross-regional integration. We use directly observed indicators of cross-regional knowledge application within the firm as well as examine collaborative mechanisms that firms may use to promote such knowledge translation.

Our analysis is based upon successful patents in biotechnology sector applied for during 2011–2014. The empirical assessment follows a mixed method approach. The sample used for testing the empirical hypotheses is composed of 130,720 patents from 860 large US firms. The sample of patents was obtained from USPTO and NBER dataset.

The idea of this paper was to introduce a model specifically developed for the process of knowledge translation. This research contributes to the literature related to the emergent and new issue namely collaborative knowledge translation (CKT), especially emphasizing the key role of the knowledge translation practices and tools for the internationalization of R&D teams and supporting the quality of innovations in different ways.

This research is conceptually based on the broader concepts of spiral of knowledge of Nonaka and Takeuchi. In spite of the increasing research in innovation, few studies have been done about the diverse contexts' role in the knowledge flows supporting the innovation development. In the attempt to cover this gap, the objective of this research is to answer the following main research question: How to support and manage the process of knowledge translation in innovation processes occurring in collaborative teams?

The purposes of this study were to calculate the confirmatory factor analysis in the measurement model using robust measures (McDonald’s omega and Cronbach’s alpha) to ensure the reliability of the proposed scale and to explore the measurement invariance of the scale per the participants’ gender.

The methodological sample had 408 students from a private university in northern Mexico, of which 200 (49%) were male and 208 (51%) were female; the sample age range was 18–58 years (M = 22.4 years, SD = 6.0). The data analysis included descriptive and normality, dimensionality, reliability and measurement invariance.

The social entrepreneurship competency measurement model showed acceptable adjustment indexes in evaluating the internal structure, reliability and factorial invariance by gender of the study participants.

Even though the contributions of this study are evident, these findings must be taken with caution due to some limitations. First, the proposed measurement model uses a self-reported scale, so it is essential to include other measurement methods with less implicit social desirability. Second, although the sample was intended to be representative, it only drew from a specific geographical area, making it difficult to generalize these findings to culturally diverse areas. Third, this study did not consider other validity measures; for example, concurrent, divergent and predictive, so future studies should consider examining the relationship of social entrepreneurship with other factors.

From the practical perspective, this study provides a parsimonious instrument regarding the number of items included in the measurement model. From the theoretical perspective, the present study contributes to delimiting the dimensions of social entrepreneurship competency.

This study contributes to the field of social entrepreneurship, particularly in the area of construct measurement, by offering a measurement model with solid evidence of internal structure validity, reliability and factorial invariance for the perceived achievement of social entrepreneurship competency.

The purpose of this paper is to identify the relationships between process modeling and Industry 4.0, the strategic themes and the most used process modeling language in smart factories. The study also presents the growth of the field of study worldwide, the perspectives, main challenges, trends and suggestions for future works.

To do this, a science mapping was performed using the software SciMAT, supported by VOS viewer.

The results show that the Business Process Model and Notation (BPMN), Unified Modelling Language (UML) and Petri Net are the most relevant languages to smart manufacturing. The authors also highlighted the need to develop new languages or extensions capable of representing the dynamism, interoperability and multiple technologies of smart factories.

It was possible to identify the most used process modeling languages in smart environments and understand how these languages assist control and manage smart processes. Besides, the authors highlighted challenges, new perspectives and the need for future works in the field.