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The paper contributes to the discussion on valuation in organization studies and strategic management literature. The nascent literature on valuation practices has examined established markets where producers and consumers are known and rivalry in the market is a given. Furthermore, previous research has operated with a narrow meaning of value as either a financial profit or a subjective consumer preference. Such a narrow view on value is problematic and insufficient for studying the interlacing of innovation and value creation in emerging technoscientific business domains.

The authors present an empirical study about value creation in an emerging technoscience business domain formed around personalized medicine and digital health data.

The results of this analysis show that in a technoscientific domain, valuation of innovations is multiple and malleable, entails pursuing attractiveness in collaboration and partnerships and is performative, and due to emphatic future orientation, values are indefinite and promissory.

As research implications, this study shows that valuation practices in an emerging technoscience business domain focus on defining the potential economic value in the future and attracting partners as probable future beneficiaries. Commercial value upon innovation in an embryonic business milieu is created and situated in valuation practices that constitute the prospective market, the prevalent economic discourse, and rationale. This is in contrast to an established market, where valuation practices are determined at the intersection of customer preferences and competitive arenas where suppliers, producers, service providers and new entrants to the market present value propositions.

The study findings extend discussion on valuation from established business domains to emerging technoscience business domains which are in a “pre-competition” phase where suppliers, customers, producers and their collaborative and competitive relations are not yet established.

As managerial implications, this study provides insights into health innovation stakeholders, including stakeholders in the public, private and academic sectors, about the ecosystem dynamics in a technoscientific innovation. Such insight is useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To business managers, the findings of this study about valuation practices are useful in strategic decision-making about ecosystem strategy and ecosystem business model for value proposition, value creation and value capture in an emerging innovation domain characterized by collaborative and competitive relations among stakeholders. To policy makers, this study provides an in-depth analysis of an overall business ecosystem in an emerging technoscience business that can be propelled to increase the financial investments in the field. As a policy implication, this study provides insights into the various dimensions of valuation in technoscience business to policy makers, who make governance decisions to guide and control the development of medical innovation using digital health data.

This study's results expand previous theorizing on valuation by showing that in technoscientific innovation all types of value created – scientific, clinical, social or economic – are predominantly promissory. This study complements the nascent theorizing on value creation and valuation practices of technoscientific innovation.

The impact of education and research skills on the strategic digital transformation of education is straightforward. In this context, the Saudi National Institute of Health plays a pivotal role in the design and implementation of a resilient and robust strategy for the development of skills and competencies to young health professionals. In this chapter, the authors provide a brief overview of the Vision 2030 in Saudi Arabia and its basic priorities in the areas related to the Education and Research in the healthcare domain. The authors also elaborate on the key plans and initiatives undertaken by the education and research skills directory of the Saudi National Institute of Health (SNIH) towards transformative learning with impact on the implementation of the Vision 2030.

One of the most neglected sources of energy loss is streetlights that generate too much light in areas where it is not required. Energy waste has enormous economic and environmental effects. In addition, due to the conventional manual nature of operation, streetlights are frequently seen being turned ‘ON’ during the day and ‘OFF’ in the evening, which is regrettable even in the twenty-first century. These issues require automated streetlight control in order to be resolved. This study aims to develop a novel streetlight controlling method by combining a smart transport monitoring system powered by computer vision technology with a closed circuit television (CCTV) camera that allows the light-emitting diode (LED) streetlight to automatically light up with the appropriate brightness by detecting the presence of pedestrians or vehicles and dimming the streetlight in their absence using semantic image segmentation from the CCTV video streaming. Consequently, our model distinguishes daylight and nighttime, which made it feasible to automate the process of turning the streetlight ‘ON’ and ‘OFF’ to save energy consumption costs. According to the aforementioned approach, geo-location sensor data could be utilised to make more informed streetlight management decisions. To complete the tasks, we consider training the U-net model with ResNet-34 as its backbone. Validity of the models is guaranteed with the use of assessment matrices. The suggested concept is straightforward, economical, energy-efficient, long-lasting and more resilient than conventional alternatives.

In times of crisis, such as the Covid-19 global pandemic, journalists who write about biomedical information must have the strategic aim to be clearly and easily understood by everyone. In this study, we assume that journalistic discourse could benefit from language redundancy to improve clarity and simplicity aimed at science popularization. The concept of language redundancy is theoretically discussed with the support of discourse analysis and information theory. The methodology adopted is a corpus-based qualitative approach. Two corpora samples with Brazilian Portuguese (BP) texts on Covid-19 were collected. One with texts from a monthly science digital magazine called Pesquisa FAPESP aimed at students and researchers for scientific information dissemination and the other with popular language texts from a news Portal G1 (Rede Globo) aimed at unspecified and/or non-specialized readers. The materials were filtered with two descriptors: “vaccine” and “test.” Preliminary analysis of examples from these materials revealed two categories of redundancy: paraphrastic and polysemic. Paraphrastic redundancy is based on concomitant language reformulation of words, sentences, text excerpts, or even larger units. Polysemic redundancy does not easily show material evidence, but is based on cognitively predictable semantic association in socio-cultural domains. Both kinds of redundancy contribute, each in their own way, to improving text readability for science popularization in Brazil.

The internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation of industrial processes, promises to deliver performance improvements through smart functionalities. This study investigates how digital transformation translates to performance gain by adopting a systems perspective to drive smartness.

This study uses qualitative research to collect data on the lived experiences of digital transformation practitioners for theory development. It uses semi-structured interviews with industry experts and applies the Gioia methodology for analysis.

The study determined that enterprise smartness is an organizational capability developed by digital transformation, it is a function of integration and the enabler of organizational performance gains in the Industry 4.0 context. The study determined that performance gains are experienced in productivity, sustainability, safety and customer experience, which represents performance metrics for Industry 4.0.

This study contributes a model that inserts smartness in the linkage between digital transformation and organizational outcomes to the digital transformation and production management literature.

The study indicates that digital transformation programs should focus on developing smartness rather than technology implementations, which must be considered an enabling activity.

Existing studies recognized the positive impact of technology on performance in industrial production. The study addresses a missing link in the Industry 4.0 value creation process. It adopts a systems perspective to establish the role of smartness in translating technology use to performance outcomes. Smart capabilities have been the critical missing link in the literature on harnessing digital transformation in organizations. The study advances theory development by contributing an Industry 4.0 value model that establishes a link between digital technologies, smartness and organizational performance.

Higher education institutions (HEIs) have a great responsibility to put education for sustainable development at the centre of their work. Curricula should therefore start to incorporate the sustainable development goals (SDGs) and key competencies in sustainability, and research should be carried out to determine effective learning methods for this. This study aims to explore the usefulness of problem-based learning (PBL) approaches to train biomedical students in sustainability and to provide some recommendations for the design and implementation of new PBL-SDG scenarios.

Two PBL-SDG scenarios were designed, implemented and evaluated for 110 students of human biology degree. Learning outcomes and student perceptions of this approach were analysed through questionnaires, student productions, non-participant observation and focus groups.

The results show that the PBL-SDG scenarios effectively addressed several SDGs and sustainability competencies in a transversal, collaborative and innovative manner. According to student perceptions, the elements that contributed most to the development of these competencies were emotional involvement with the scenario, reflection on their own actions, freedom to approach the problem and tutors who empowered them with their proposals.

The PBL-SDG approach presented in this study is an example of a pedagogical strategy that can help HEIs educate their learners as key change agents. The findings of this study provide evidence for this important aspect and give guidelines and strategies to successfully designing and implementing such methodologies in biomedical education.

Health profession education has evolved to incorporate didactic instruction and experiential learning opportunities over time. Constructivism and interprofessional education are essential theoretical concepts that have shaped modern health profession education. However, transformative active learning is an approach that is particularly well suited to the needs of healthcare professionals. By integrating theoretical knowledge with practical skills, transformative active learning helps prepare students for the complex challenges they will face in their future careers and encourages them to become agents of change committed to improving healthcare practice. Saudi National Institute of Health (Saudi NIH) is one of the Ministry of Health's initiatives in the National Transformation Program 2020 to achieve the Kingdom's Vision 2030, as it supports biomedical research in the health sector in Saudi Arabia. One of the mandates of Saudi NIH is to build the research capacity through well-designed educational and training programs through the directory of education and research skills adopting active learning strategies. This chapter aims to communicate the methodological framework of the Education and Research Skills Directory of the SNIH for integrating active learning in the various training programs and initiatives aiming to promote the core learning capabilities with excellence, diversity, diversity, uniqueness, competency, and efficiency values.

The development of new advanced materials, such as photopolymerizable resins for use in stereolithography (SLA) and Ti6Al4V manufacture via selective laser melting (SLM) processes, have gained significant attention in recent years. Their accuracy, multi-material capability and application in novel fields, such as implantology, biomedical, aviation and energy industries, underscore the growing importance of these materials. The purpose of this study is oriented toward the application of new advanced materials in stent manufacturing realized by 3D printing technologies.

The methodology for designing personalized medical devices, implies computed tomography (CT) or magnetic resonance (MR) techniques. By realizing segmentation, reverse engineering and deriving a 3D model of a blood vessel, a subsequent stent design is achieved. The tessellation process and 3D printing methods can then be used to produce these parts. In this context, the SLA technology, in close correlation with the new types of developed resins, has brought significant evolution, as demonstrated through the analyses that are realized in the research presented in this study. This study undertakes a comprehensive approach, establishing experimentally the characteristics of two new types of photopolymerizable resins (both undoped and doped with micro-ceramic powders), remarking their great accuracy for 3D modeling in die-casting techniques, especially in the production process of customized stents.

A series of analyses were conducted, including scanning electron microscopy, energy-dispersive X-ray spectroscopy, mapping and roughness tests. Additionally, the structural integrity and molecular bonding of these resins were assessed by Fourier-transform infrared spectroscopy–attenuated total reflectance analysis. The research also explored the possibilities of using metallic alloys for producing the stents, comparing the direct manufacturing methods of stents’ struts by SLM technology using Ti6Al4V with stent models made from photopolymerizable resins using SLA. Furthermore, computer-aided engineering (CAE) simulations for two different stent struts were carried out, providing insights into the potential of using these materials and methods for realizing the production of stents.

This study covers advancements in materials and additive manufacturing methods but also approaches the use of CAE analysis, introducing in this way novel elements to the domain of customized stent manufacturing. The emerging applications of these resins, along with metallic alloys and 3D printing technologies, have brought significant contributions to the biomedical domain, as emphasized in this study. This study concludes by highlighting the current challenges and future research directions in the use of photopolymerizable resins and biocompatible metallic alloys, while also emphasizing the integration of artificial intelligence in the design process of customized stents by taking into consideration the 3D printing technologies that are used for producing these stents.

Knowledge is companies’ crucial asset, especially when they are inserted in continuous collaboration and value co-creation. However, problems related to knowledge may occur without proper management, which can compromise the strategic objectives associated with a business collaboration network. Given the presented gap, this study aims to propose and test a business-to-business (B2B) knowledge management (KM) framework focused on value co-creation. Therefore, this study seeks to answer the following guiding questions: what are the main elements that a KM model should present in a context of value co-creation between companies? What are the limitations? What are the advantages and disadvantages? Is there any group that would benefit most from it?

This is an exploratory study grounded on mixed methods, having a qualitative approach (systematic literature review and content analysis) followed by a quantitative approach (exploratory and confirmatory factor analysis), which grounded the proposed framework.

The qualitative approach grounded on the systematic literature review resulting in 38 articles that were submitted to content analysis, which resulted in six record units: active communication between the organization, employees and other stakeholders; documents and organizational knowledge stored; knowledge map; collaborative network; searching tools and database, which provided the KM elements to develop and test the proposed framework by the quantitative approach. The results have shown that the framework may assist in managing knowledge in B2B value co-creation relationships.

As an exploratory study, the chosen research approach used nonprobabilistic for convenience sampling. Therefore, the results may lack generalizability. Thus, researchers are encouraged to use probabilistic sampling techniques to ensure generability. Also, more and better items should be used to upgrade the initial questionnaire, improving it and, by doing so, have a better scale.

Assuming the proposed framework’s effectiveness, company managers can use it to drive knowledge within the network of interested parties to promote cooperative products and services. In addition, due to the theoretical framework’s broad vision, it can serve as a strategic aid to leverage innovation, productivity and competitive advantage. This study also provides an initial instrument that assists in understanding KM elements, which may assist in value co-creation.

It was learned that the elements, tools, concepts and KM preconized solutions can assist in value co-creation. Considering that value assists business performance, and value co-creation is one way to enhance it, furthermore, by knowledge sharing, the value co-creation may occur in the B2B ecosystem. Also, it is the first theoretical KM framework proposed to assist companies to understand better ways that could get advantages on structuring knowledge, meaning mapping it, sharing it through a system that can retain what is needed and release it to the ones that need and have the defined access to receive it.

The opening of government data is high on the policy agenda of governments worldwide. However, data release faces barriers due to limited support of civil servants, whereas the literature neglects civil servants' role in opening data. This paper aims at understanding why civil servants can be reluctant to support the disclosure of data. The authors developed a model to explain civil servants' behavioral intention to open data.

The authors test a series of hypotheses by collecting and analyzing survey data from 387 civil servants and by applying multivariate hierarchical regression.

The results indicate the factors influencing the behavior of civil servants. Social influences, performance expectancy, data management knowledge and risks have a significant influence. Personal characteristics control these effects.

Caution is needed to generalize the findings towards the support to open data provision by civil servants. Though the analyzed sample was limited to Brazil, other countries and cultures might yield different outcomes. Larger and more diversified samples might indicate significant effects on variables not found in this research.

The insights can be used to develop policies for increasing the support of civil servants towards governmental data disclosure.

This study suggests factors of influence to civil servants' behavior intentions to disclose governmental data. It results in a model of factors, specifically for their behavioral intention at the individual level.