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Biotech companies stand as key actors in pharmaceutical innovation. The high risk and long timelines inherent with their R&D investments might hinder their access to funding, potentially stifling innovation. This study aims to explore into the appeal of biotech companies to capital market investors, whose financial backing could bolster the growth of the biotechnology sector.

This paper uses a dataset of 774 US publicly listed biotech firms to investigate their risk and return characteristics by comparing them to pharmaceutical firms and a sample of matched non-biotech R&D-intensive firms over the sample period 1980–2021. Tests show that the conclusions remain consistent across diverse methodological approaches.

The paper shows that biotech companies are riskier than the average firm in the market index but outperform on a risk-adjusted basis both the market and a matched group of R&D-intensive firms. This is particularly true for large capitalization biotech, which is also shown to provide a diversification benefit by reducing the downside risk in past crisis periods.

This paper provides insight relevant to the current debate about the overall performance of the biotech industry in terms of policy changes and their impact on small, early-stage biotech firms. While small and early-stage biotech firms are playing an increasing role in scientific innovation, this study confirms their greater vulnerability to financial risks and the importance of access to capital markets in enabling those companies to survive and evolve into larger biotech.

Numerous biotechnology and pharmaceutical firms have undergone considerable changes and adapted to the challenge of developing sustainable products and services. However, few studies have explored the factors that contribute to the success of external innovation and value co-creation strategies adopted by biotechnology and pharmaceutical firms. The purpose of this study is to examine how biotechnology and pharmaceutical industries use value co-creation strategies to obtain external resources.

This study developed a conceptual framework based on the relevant literature. The study applied a resource-based approach, dynamic capability theory and a qualitative multiple-case study design to investigate several research questions; semi-structured interviews were conducted with representatives from 11 biotechnology/pharmaceutical firms in Taiwan, and the data extracted from the interview content were axially coded.

This study revealed that factors such as dynamic marketing capabilities and process optimization contributed to the success of the aforementioned strategies; several propositions were also developed on the basis of the literature review and coded data, thereby providing insights regarding the relative efficacy and propriety of various external innovation and value co-creation strategies and models in various situations and contexts. Firms and technology providers might enter a technology licensing agreement, establish a joint venture company; participate in a merger/acquisition depending on their size, research and development capabilities; or goals and time- and cost-related factors.

The main original contributions of this study are the proposed conceptual framework and the insights provided regarding the relative efficacy and propriety of different external innovation and value co-creation strategies and models in different situations and contexts.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

Technology acquisition is a common phenomenon of acquiring external knowledge, but we have a limited understanding of conditions in which the acquirer integrates the target or not. On one hand, the acquirer may have a policy to integrate the target to benefit from its prior knowledge. On the other hand, the target may face challenges in continuing its knowledge creation and the acquirer may want to provide it autonomy to not disrupt it. This paper aims to identify conditions in which targets tend to be less integrated after acquisitions, allowing them to maintain more autonomy and contribute more to knowledge creation.

We test our arguments in the empirical setting of the global biopharmaceutical industry using a difference-in-difference approach on a longitudinal dataset of matched patents. We examine self-cites received by patents belonging to acquirers and the targets before and after the acquisitions.

We find that, on average, the targets’ prior patents do not receive more self-cites after the acquisition. We conclude that this is because their R&D activities are disrupted, suggesting a higher level of post-acquisition integration. However, more nuanced findings reveal that it may not be the case all the time. When the target has more research experience, is international or is specialized in complementary technologies, prior patents of targets continue to receive more self-cites after the acquisition. It indicates that the targets in such conditions continue knowledge creation, suggesting a lower level of post-acquisition integration.

Our findings contribute to post-acquisition integration research. While post-acquisition integration downside is common, we present conditions in which such a downside may be less likely. We highlight that the context of an acquisition may be an important determinant of the extent of integration of the target. Moreover, we supplement the integration research (cultural, structural and human resource and leadership perspectives of integration) by adding a knowledge-based perspective to it. Such dynamics have important implications for acquirers and targets in deriving value from the acquisition.

The objective of this work is to demonstrate the relationships between the two main processes of research and development (R&D) activities: the knowledge generation phase (KPP) and the knowledge commercialization, or transfer, phase (KCP), in a sector that is intensive in this type of activity, such as the pharmaceutical sector. In addition, within the framework of the general objective of this work, the authors propose two other objectives: (1) make advances in network efficiency measurement models, and (2) determine the factors associated with efficiency in the KPP and in the KCP in companies of the pharmaceutical sector in Spain.

A Network Data Envelopment Analysis (NDEA) model (Färe and Grosskopf, 2000) with categorical variables (Lee et al., 2020; Yeh and Chang, 2020) has been applied, and a sensitivity analysis of the obtained results has been performed through a DEA model of categorical variables, in accordance with the work of Banker and Morey (1986), to corroborate the results of the proposed model. The sample is made up of 77 companies in the pharmaceutical sector in Spain.

The results obtained point to a greater efficiency of pharmaceutical companies in the KPP, rather than in the KCP. Furthermore, the study finds that 1) alliances between companies have been the accelerating factors of efficiency in the KCP (but patents have slowed this down the most); 2) the quality of R&D and the number of R&D personnel are the factors that most affect efficiency in the KPP; and 3) the quality of R&D again, the benefits obtained and the position in the market are the factors that most affect efficiency in the KCP.

The authors have not found studies that show whether the efficiency obtained by R&D-intensive companies in the KPP phase is related to better results in terms of efficiency in the KCP phase. No papers have been found that analyse the role of alliances between R&D-intensive companies and patents, as agents that facilitate efficiency in the KCP phase, covering the gap in the research on both problems. Notwithstanding, this work opens up a research path which is related to the improvement of network efficiency models (since it includes categorical variables) and the assessment of the opinions of those who are responsible for R&D departments; it can be applied to decision-making on the aspects to improve efficiency in R&D-intensive companies.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

This paper provides a structural model to value startup companies and determine the optimal level of research and development (R&D) spending by these companies.

This paper describes a new variant of float-the-money options, which can act as a financial instrument for financing R&D expenses for a specific time horizon or development stage, allowing the investor to share in the startup's value appreciation over that duration. Another innovation of this paper is that it develops a structural model for evaluating optimal level of R&D spending over a given time horizon. The paper deploys the Gompertz-Cox model for the R&D project outcomes, which facilitates investigation of how increased level of R&D input can enhance the company's value growth.

The author first introduces a time-varying drift term into standard Black-Scholes model to account for the varying growth rates of the startup at different stages, and the author interprets venture capital's investment in the startup as a “float-the-money” option. The author then incorporates the probabilities of startup failures at multiple stages into their financial valuation. The author gets a closed-form pricing formula for the contingent option of value appreciation. Finally, the author utilizes Cox proportional hazards model to analyze the optimal level of R&D input that maximizes the return on investment.

The integrated contingent claims model links the change in the financial valuation of startups with the incremental R&D spending. The Gompertz-Cox contingency model for R&D success rate is used to quantify the optimal level of R&D input. This model assumption may be simplistic, but nevertheless illustrative.

Once supplemented with actual transaction data, the model can serve as a reference benchmark valuation of new project deals and previously invested projects seeking exit.

The integrated structural model can potentially have much wider applications beyond valuation of startup companies. For instance, in valuing a company's risk management, the level of R&D spending in the model can be replaced by the company's budget for risk management. As another promising application, in evaluating a country's economic growth rate in the face of rising climate risks, the level of R&D spending in this paper can be replaced by a country's investment in addressing climate risks.

This paper is the first to develop an integrated valuation model for startups by combining the real-world R&D project contingencies with risk-neutral valuation of the potential payoffs.

Intellectual capital (IC) is essential to the success of new technology-based firms. However, young firms only possess some of the resources and capabilities needed to develop, produce and market their innovative products and services. Hence, many form alliances to access complementary resources. This paper investigates the signaling effect of technology-based start-ups’ stock of IC on alliance formation.

This study analyzes primary data concerning specific classes of IC and the alliances formed. Data were collected from founders of 233 technology-based new ventures in the USA. Hypotheses were tested via hierarchical linear regression.

This study demonstrates that firms' IC, in the form of founders with doctorates and patents, is positively related to the classes of alliances formed. These stocks of IC send signals about credibility to the market for alliance partners, enabling the firms to form alliances and gain access to complementary resources. The number of founders with doctorates was positively related to R&D alliances and alliance partners in a similar place in the value chain as the focal firm. In contrast, the number of patents was positively related to total alliances, production-oriented alliances and alliances considered upstream from the focal firm.

This paper collects retrospective data from founders of technology-based new ventures. The research contributes to the literature with its results that founder human capital and patent portfolios are essential for technology-based firms' innovation and growth. However, little research has investigated how firms' possession of IC facilitates alliance formation. This paper investigates this connection explicitly.

Crises, such as COVID-19 pandemic, are critical events that provoke important changes in organizational practices, regulations and actors' roles. The pharmaceutical sector has been strongly affected because of the urgency to produce drugs that are effective and safe. However, the validation process and regulations are historically restrictive in this sector. This study aims to study how biotechnology firms, small companies lacking resources, have undertaken strategic actions during crisis time to induce important changes to their advantage within such a highly regulated environment.

Interviews were conducted with 21 managers in four mRNA-based biotechnology firms.

Results showed that rhetorical strategies and institutional actions are used in order to manage change opportunities. Media attention, greater openness of state agencies and public willingness to accept new ways of treatment illustrated this opportunity of change in favor of biotechnology firms.

Highly regulated environments tend to be unfavorable to smaller firms with limited resources to overcome these constraints. The authors show that times of crisis can reverse this assumption through the provision of new opportunities as long as the smaller firms skillfully use strategic actions to exploit the institutional changes at play.

At the beginning of the 21st century, multiple and diverse social entities, including the public (consumers), private and nonprofit healthcare institutions, government (public health) and other industry sectors, began to recognize the limitations of the current fragmented healthcare system paradigm. Primary stakeholders, including employers, insurance companies, and healthcare professional organizations, also voiced dissatisfaction with unacceptable health outcomes and rising costs. Grand challenges and wicked problems threatened the viability of the health sector. American health systems responded with innovations and advances in healthcare delivery frameworks that encouraged shifts from intra- and inter-sector arrangements to multi-sector, lasting relationships that emphasized patient centrality along with long-term commitments to sustainability and accountability. This pathway, leading to a population health approach, also generated the need for transformative business models. The coproduction of health framework, with its emphasis on cross-sector alignments, nontraditional partner relationships, sustainable missions, and accountability capable of yielding return on investments, has emerged as a unique strategy for facing disruptive threats and challenges from nonhealth sector corporations. This chapter presents a coproduction of health framework, goals and criteria, examples of boundary spanning network alliance models, and operational (integrator, convener, aggregator) strategies. A comparison of important organizational science theories, including institutional theory, network/network analysis theory, and resource dependency theory, provides suggestions for future research directions necessary to validate the utility of the coproduction of health framework as a precursor for paradigm change.