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Several studies show that identity is a critical success factor in design-intensive industries, leading managers and executives to identify solutions that enable firms to simultaneously innovate while preserving their link with the past. Accordingly, scholars have recently revealed the role of the so-called innovation through tradition strategy. Thus, the purpose of this study/paper is to understand how design intensive firms may exploit knowledge pertaining to the past.

The research contributes to this line of inquiry by conducting a longitudinal analysis of two leading Italian design-intensive firms, B&B Italia and Cassina S.p.A. Specifically, through almost 30 h of interviews with 11 key informants and the analysis of various secondary sources, a unique database of over 900 products covering the period of 1960-2016 was developed.

The findings reveal that both firms leverage knowledge from the past mainly to preserve firm identity, as indicated by the two indicators used to capture the use of knowledge pertaining to the past (i.e., design tradition intensity and design tradition depth). In addition, the study shows that the values of these indicators significantly increase when ownership control shifts from family-based to fund-based.

The paper looks at design artifacts as a source of knowledge, exploring how they can support firms in reinforcing their identity. The original contribution to the design through traditional literature is in unveiling the product signs dimension of this particular innovation strategy.

This paper analyzes the effect of circular economy practices on firm performance for a circular supply chain and explores the moderating role that big-data-driven supply chain plays within these relationships.

This study uses data collected through an online survey distributed to managers of 378 Italian firms that have adopted circular economy principles. The data are processed using multiple regression analysis.

The results indicate that the three categories of circular economy practices investigated – namely circular economy supply chain management design, circular economy supply chain relationship management and circular economy HR management – play a crucial role in enhancing firm performance from a circular economy perspective. A big-data-driven supply chain acts as a moderator of the relationship between circular economy HR management and firm performance for a circular economy supply chain.

This study makes a number of original contributions to research on circular economy practices in a big-data-driven supply chain and provides useful insights for practitioners. First, it answers the call to capture digital transformation trends and to extend research on sustainability in supply chain management. Second, it enhances the literature by investigating the relationships between three different kinds of circular economy supply chain practices and firm performance. Finally, it clarifies the moderating role of big data in making decisions and implementing circular supply chain solutions to achieve better environmental, social and economic benefits.

With the accelerated technological advancement, innovation has become a critical factor, which affects the core competitiveness of a company. However, studies about the relationship between internal stock option mechanisms and innovation productivity remain limited. Therefore, this paper aims to examine the impact of stock options and their elements design on innovation output from an internal mechanism perspective.

Using a sample of 302 stock option incentive plans announced and implemented between 2006 and 2016, this study uses the propensity score matching and difference-in-difference model to find out whether the implementation of stock options improves the innovation outputs of enterprises.

Based on the statistical analysis, it is concluded that: stock options can stimulate corporate innovation; a stock option may drive innovation outputs through two ways, performance-based incentives and risk-taking incentives, with the latter one playing a more dominant role and the risk-taking incentives of stock options, could be optimised when the non-executives granting proportion is larger, the granting range is limited, the incentive period is longer, the exercisable proportion is increasing, the price-to-strike ratio is lower and relatively loose performance assessment criteria are applied.

The conclusion reached in the study may provide valuable information to listed firms in designing and implementing the stock option plans.

This paper aims to examine the influence that family firms’ top management team (TMT) behavior and characteristics exert on their innovation opportunity realization.

Data were collected through a survey addressed to a representative sample of Italian firms. The analyzed sample consists of 237 firms, 120 of which are family firms. A series of ordinary least squares models were used to test the four hypotheses.

Family firms realize fewer innovation opportunities than non-family firms. This result is fully mediated by the knowledge exchange in the TMT as follows: in family firms, the TMT exchanges less knowledge than in non-family firms, which drives their lower realization of innovation opportunities. In family firms TMT, the increase in the non-family members positively influences the TMT knowledge exchange, but only when the time the Chief Executive Officer (CEO) spends in searching for innovation opportunities outside the firm is low. The more the CEO search increases, the more this positive influence decreases, up to the point it becomes negative.

The study contributes to the literature on innovation, knowledge management and organizational design in family firms. Nevertheless, data were collected at a single point in time and in a single country.

The study suggests family firms on how to foster the realization of innovation opportunities. A greater TMT knowledge exchange allows to realize more innovation opportunities and the TMT characteristics emerged as the drivers of this TMT knowledge exchange. As such, family firms should examine the interaction of their TMT composition in terms of non-family and family members with the effort that the CEO deploys to search for innovation opportunities outside the firm.

Empirical investigation of the link between family ownership, absorptive capacity and innovation performance by considering TMT behavior and characteristics.

The purpose of this study is to investigate whether and how inter-firm cooperation and firm age moderate the relationship between family ownership and productivity.

We first estimate the total factor productivity (TFP) of a large sample of Italian firms observed over the period 2010–2018 and then apply a Poisson random effects model.

TFP is, on average, higher for non-family firms (non-FFs) than for FF. Furthermore, inter-organizational cooperation and firm age mitigate the negative effect of family ownership. In detail, it is found that belonging to a network acts as a moderator in different ways according to firm age. Indeed, young FFs underperform non-FF peers, although the TFP gap decreases with age. In contrast, the benefits of a formal network are high for older FFs, suggesting that an age-related learning process is at work.

The study provides evidence that FFs can outperform non-FFs when they move away from Socio-Emotional Wealth-centered reference points and exploit knowledge flows arising from high levels of social capital. In the case of mature FFs, networking is a driver of TFP, allowing them to acquire external resources. Since FFs often do not have sufficient in-house knowledge and resources, they must be aware of the value of business cooperation. While preserving the familiar identity of small companies, networks grant FFs the competitive and scale advantages of being large.

Despite the wide but ambiguous body of research on the performance gap between FFs and non-FFs, little is known about the role of FFs’ heterogeneity. This study has proven successful in detecting age as a factor in heterogeneity, specifically to explain the network effect on the link between ownership and TFP. Based on a representative sample, the study provides a solid framework for FFs, policymakers and academic research on family-owned companies.

In the past decade, in the space industry, many initiatives intended at offering open access to big data from space multiplied. Therefore, firms started adopting business models (BMs) which lever on digital technologies (e.g. cloud computing, high-performance computing and artificial intelligence), to seize these opportunities. Within this scenario, this article aims at answering the following research question: which digital technologies do impact which components the BM is made of?

An exploratory multiple case study approach was used. Three cases operating in the space industry that lever on digital technologies to implement their business were analyzed. Despite concerns regarding reliability and validity, multiple case studies allow greater understanding of causality, and show superiority respect to quantitative studies for theory building.

Big data, system integration (artificial intelligence, high-performance computing) and cloud computing seem to be pivotal in the space industry. It emerges that digital technologies involve all the different areas and components of the BM.

This paper sheds light on the impact that digital technologies have on the different BM components. It is only understanding which technologies can support the value proposition, which technologies make the infrastructural part able to support this proposition, which technologies may be helpful for delivering and communicating this value to customers and which technologies may help firms to appropriate the value that it is possible to seize the impact of digital technologies on BM.

This paper aims to investigate the phases of new product development within the design-driven innovation (DDI) process, the role of designers and collaborators in the process and how this process relates to some quality principles.

This study adopted a qualitative approach using Gioia methodology. In particular, four Italian manufacturing companies in the home appliances and furniture industry were selected, and data mainly collected through direct interviews were analysed through content analysis.

The new product development related to DDI includes the following phases: the company brief, the designer research, the concept of the designer, the design, legal protection, prototyping, production and the market launch. Designers play a strategic role in the above phases of DDI, but other actors also cooperate and some quality principles affect positively on the process. This study proposes a model for a DDI process in the home appliances and furniture sector.

Although this exploratory study was conducted on only four companies, it advances the DDI research in relation to new product development.

This study makes recommendations to entrepreneurs and managers on how to innovate successfully and to effectively manage designers and collaborators to ensure competition.

This analysis highlights that design-based innovation contributes to improving the quality of life of consumers.

To the best of the authors' knowledge, this is the first qualitative study to examine the phases of new product development in DDI process, the actors involved and relationship to quality principles for the Italian home appliances and furniture sector.

This study aims to develop an assessment methodology using a Bayesian network (BN) to predict the failure probability of oil tanker shipping firms.

This paper proposes a bankruptcy prediction model by applying the hybrid of logistic regression and Bayesian probabilistic networks.

The proposed model shows its potential of contributing to a powerful tool to predict financial bankruptcy of shipping operators, and provides important insights to the maritime community as to what performance measures should be taken to ensure the shipping companies’ financial soundness under dynamic environments.

The model and its associated variables can be expanded to include more factors for an in-depth analysis in future when the detailed information at firm level becomes available.

The results of this study can be implemented to oil tanker shipping firms as a prediction tool for bankruptcy rate.

Incorporating quantitative statistical measurement, the application of BN in financial risk management provides advantages to develop a powerful early warning system in shipping, which has unique characteristics such as capital intensive and mobile assets, possibly leading to catastrophic consequences.

The purpose of this study is to analyze the influence of the firms' external environment on their export intensity. More specifically, it assesses whether domestic market characteristics such as domestic demand and general export environment related to tradability across borders affect firms' export intensity.

The authors use a sample of 29,266 firms from nine European countries, for the period of 2010–2016, and test several estimation methods (random effects models, Tobit models, and Heckman's selection models).

Results show that external factors such as domestic demand and ease of trade across borders are important determinants of firms' export intensity. Moreover, results reveal that firm's internal characteristics such as age, size and productivity also play an import role.

Studies about the influence of the firms' external environment on firms' export intensity are scarce because most of them are confined to a single country context. In this way, the present study contributes to the body of knowledge on the influence that external factors can have on firms' export performance by analyzing firms from nine European countries, which has important policy implications.