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Capgras Syndrome is a subcategory of delusional disorder. People affected by this syndrome believe that a close associate such as a friend or family member has been replaced by an identical imposter. This case report describes a 23-year-old woman with no prior psychiatric history, whom developed Capgras syndrome, via folie a deux, in the setting of poly-substance use. In this patient, a combination of Aripiprazole 10 mg daily and Escitalopram 10 mg daily were effective in resolving symptoms. Clonazepam was utilized for anxiety and Omega-3 fatty acids 1 g for anti-oxidative effects. Further studies are needed to investigate the effects of a variety of causes and treatments for Capgras Syndrome.

This study was conducted to investigate the Social Physique Anxiety (SPA) level in adolescent and young women with polycystic ovarian syndrome (PCOS).

This is a descriptive study. It was conducted in Turkey. The study was conducted from January 1, 2017 to December 31, 2017. It was completed with a total of 150 young women – 75 of them had PCOS and 75 of them were healthy. Study data were collected using demographic information form and Social Physique Anxiety Scale (SPAS).

The study was found that the adolescent and young women with PCOS had higher subscales and total scores for total SPAS at a statistically significant level than healthy adolescent and young women (p < 0.05).

The findings of this study may be used for planning and implementing interventions in health-care practice such as screening and early treatment of SPA of women with PCOS.

It was found that PCOS in adolescent and young women increased the SPA level. In line with these results, health professionals must be particularly aware of the potential psychosocial and health needs of adolescent and young women with PCOS.

This study investigates the role of “soft” factors of total quality management – in terms of empowerment and engagement of employees – in facilitating or hindering organizational performance of the university technology transfer offices.

The authors developed an Ordinary Least Squares (OLS), multiple regression model to test if empowerment and engagement affect organizational performance of the university technology transfer offices.

The authors found that “soft” factors of total quality management – in terms of empowerment and engagement – facilitate the improvement of organizational performance in university technology transfer offices.

The authors’ analysis shows that soft total quality management practices create the conditions for improving organizational performance. This study provides practical implications by showing that, in the evaluation of the technology transfer office, not only the “hard” variables (e.g. number of employees and employee experience) but also the “soft” one (e.g. empowerment and engagement) matter. Therefore, university technology transfer managers or university technology transfer delegates should take actions to promote not only empowering employees but also create a climate conducive to employees' engagement in the university technology transfer offices.

With regards to the differences in organizational performances of university technology transfer offices, several studies have focused their attention on technology transfer professionals in technology transfer offices, but only a few of them have examined the “soft side” of total quality management. Thus, this study examines the organizational goals of technology transfer offices through “soft” factors of total quality management in terms of empowerment and engagement employees.

Recognizing novel entrepreneurial opportunities arising from a crisis is of paramount importance for firms. Hence, understanding the pivotal factors that facilitate firms in this endeavor holds significant value. This study delves into such factors within a representative empirical context impacted by a crisis, drawing insights from existing literature on opportunity recognition during such tumultuous periods.

The authors conducted a qualitative inspection of 14 Italian firms during the COVID-19 pandemic crisis. The authors collected a rich body of multi-source qualitative data, including 34 interviews (with senior managers and entrepreneurs) and secondary data (press releases, videos, web interviews, newspapers, reports and academic articles) in two phases (March–August 2020 and September–December 2020).

The results suggest the existence of a process model of opportunity recognition during crises based on five entrepreneurial influencing factors (entrepreneurial knowledge, entrepreneurial alertness, entrepreneurial proclivity, entrepreneurial personality and entrepreneurial purpose).

Various scholars have highlighted that, in times of crises, it is not easy and indeed very challenging for entrepreneurs to identify novel entrepreneurial opportunities. However, recent research has shown that crises can also positively impact entrepreneurs and their capacity to identify new entrepreneurial opportunities. Given these findings, not much research has analyzed the process by which entrepreneurs identify novel entrepreneurial opportunities during crises. This study shows that some entrepreneurial influencing factors are very important to identify new entrepreneurial opportunities during crises.

The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

This paper aims to verify how the intellectual property (IP) box affects firms’ effective tax rate, growth and innovation activity outcomes related to intellectual property rights.

Implementing the innovation box regimes into the tax system intends to encourage firms to engage in more innovative activities. In UK, Italy and Poland, the IP box tax relief was introduced in 2013, 2015 and 2019, respectively. In return, companies may reduce their tax rate to increase their investment and innovativeness. With a panel model approach – system GMM and DiD with multiple time periods – it analyses data from the Orbis database for 2011–2019 of 673 firms from the gaming industry in 11 countries and hand-collected data on intellectual property rights protection. The authors study public and private companies from the gaming sector in leading European markets and all three countries that protect intellectual property rights of software (Japan, South Korea, the USA).

Recent reforms enable gaming companies to use preferential tax treatment for IP-related income and significantly impact a firm’s revenue growth.

Nevertheless, European gaming firms require time to leap the gap to the growth and innovativeness of countries that protect software.

The authors show that the IP box stimulates gaming firms to protect IP via wordmarks, figurative marks, trademarks and software patents that bring effects in five years. Despite the critics against IP box, the authors prove its lagged efficiency, especially in profitable and larger firms.

The purpose of this paper is to present a procedure to design an experimental setup meant to validate an innovative approach for simulating, via computational fluid dynamics, a high-pressure gas release from a rupture (e.g. on an offshore oil and gas platform). The design is based on a series of scaling exercises, some of which are anything but trivial.

The experimental setup is composed of a wind tunnel, the instrumented scaled (1:10) mock-up of an offshore platform and a gas release system. A correct scaling approach is necessary to define the reference speed in the wind tunnel and the conditions of the gas release to maintain similarity with respect to the real-size phenomena. The scaling of the wind velocity and the scaling of the gas release were inspired by the approach proposed by Hall et al. (1997): a dimensionless group was chosen to link release parameters, wind velocity and geometric scaling factor.

The theoretical scaling approaches for each different part of the setup were applied to the design of the experiment and some criticalities were identified, such as the existence of a set of case studies with some release parameters laying outside the applicability range of the developed scaling methodology, which will be further discussed.

The resulting procedure is one of a kind because it involves a multi-scaling approach because of the different aspects of the design. Literature supports for the different scaling theories but, to the best of the authors’ knowledge, fails to provide an integrated approach that considers the combined effects of scaling.

Drawing upon the importance of research and development (R&D) alliances in driving firm innovation performance, extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance. Despite such analyzes, research has generally underestimated the configurations of partner attributes leading to firm innovation performance. This research gap is interesting to explore, as firms involved in R&D alliances usually face a combination of partner attributes. Moreover, gaining a better understanding of how R&D partner attributes tie into configurations is an issue that is attracting particular interest in coopetition research and alliance literature. This paper aims to obtain a better knowledge of this underrated, but important, aspect of alliances by exploring what configurations of R&D alliance partner attributes lead firms involved in R&D alliances to achieve high innovation performance. To tackle this question, first, this study reviews the extant literature on R&D alliances by relying on the knowledge-based view of alliances to identify the most impactful partner attributes on firms’ innovation performance. This paper then applies a fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of R&D alliance partner attributes that lead firms involved in R&D alliances to achieve high innovation performance.

This study selects 27 R&D alliances formed worldwide in the telecom industry. This paper explores the multiple configurations of partner attributes of these alliances by conducting a fsQCA.

The findings of the fsQCA show that the two alternate configurations of partner attributes guided the firms involved in these alliances to achieve high innovation performance: a configuration with extensive partner technological relatedness and coopetition, but no experience; and a configuration with extensive partner experience and competition, but no technological relatedness.

The research highlights the importance of how partner attributes (i.e. partner technological relatedness, partner competitive overlap, partner experience and partner relative size) tie, with regard to the firms’ access to external knowledge and consequently to their willingness to achieve high innovation performance. Moreover, this paper reveals the beneficial effect of competition on the innovation performance of the firms involved in R&D alliances when some of the other knowledge-based partner attributes are considered. Despite these insights for alliance and coopetition literature, some limitations are to be noted. First, some of the partners’ attributes considered could be further disentangled into sub-partner attributes. Second, other indicators might be used to measure firms’ innovation performance. Third, as anticipated this study applies fsQCA to explore the combinatory effects of partner attributes in the specific context of R&D alliances in the telecom industry worldwide and in a specific time window. This condition may question the extensibility of the results to other industries and times.

This study also bears two interesting implications for alliance managers. First, the paper suggests that R&D alliance managers need to be aware that potential alliance partners have multiple attributes leading to firm innovation performance. In this regard, partner competitive overlap is particularly important for gaining a better understanding of firm innovation performance. When looking for strategic partners, managers should try to ally with highly competitive enterprises so as to access their more innovative knowledge. Second, the results also highlight that this beneficial effect of coopetition in R&D alliances can be amplified in two ways. On the one hand, when the partners involved in the alliance have not yet developed experience in forming alliances. Partners without previous experience supply ideal stimuli to unlock more knowledge in the alliance because new approaches to access and develop knowledge in the alliance could be explored. On the other hand, this paper detects the situation when the allied partners are developing technologies and products in different areas. When partnering with firms coming from different technological areas, the knowledge diversity that can be leveraged in the alliances could drive alliance managers to generate synergies and economies of scope within the coopetitive alliance.

Extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance but has concurrently underestimated the configurations of partner attributes leading to firm innovation performance. Therefore, this paper differs from previous studies, as it provides an understanding of the specific configurations of R&D alliance partner attributes leading firms involved in R&D alliances to achieve high innovation performance.

The purpose of this paper is to present a model depicting the relationship between the behavioral intention of tourists in the conditions prevailing during a pandemic and other variables.

In constructing the research procedure, two measurements of tourist behavioral intention were taken into account, which were taken far apart in time. In verifying the developed model, the results of surveys of 1,615 people carried out in June 2021 and 917 people carried out in December 2021 were considered.

As a result of the habituation process, tourists show greater acceptance of the restrictions.

Information on the basis of which companies make management decisions plays a significant role in the creation of company value. In the tourism sector, the information concerns primarily consumer behavior.

Changes over time in risk perception, health protection motivation, and reactance due to perceived pandemic-related restrictions were taken into account in the context of behavioral intention towards tourism.