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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.

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.

Based on the resource bricolage theory, we investigate the impact of proactive market orientation and responsive market orientation on firms’ disruptive green innovation. We also examine the impact of resource bricolage on disruptive green innovation and the mediating role of resource bricolage.

Quantitative data were collected from 232 firms in China. Structural equation modelling was used to test hypotheses.

The result show that proactive market orientation had positive effect on firm’s disruptive green innovation, whereas responsive market orientation had negative effect on firm’s disruptive green innovation. In addition, resource bricolage positively promotes firm’s disruptive green innovation. Resource bricolage played a mediating role between proactive market orientation and disruptive green innovation. Resource bricolage had a suppressing effect between responsive market orientation and disruptive green innovation.

This study makes up for the deficiency of the existing research on the relationship between market orientation and enterprise disruptive green innovation, improves the guidance mechanism of disruptive green innovation.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

Joint research is pointed out by the literature as a potentially virtuous cooperation scheme to generate learning in the public sphere and beneficial effects in society. The purpose of this study, based on the Argentine experience in the COVID-19 pandemic, is to analyze the network of capacities, relationships and effects generated, over time, by a series of projects financed by the State in 2010, to clarify the link between learning effects and social effects.

A qualitative methodology focused on the multiple case study method was used. Each case covers joint R&D projects financed 10 years ago by the state that subsequently led to different solutions for COVID-19.

The work identifies a public learning process that integrates both industry’s contributions and the intellectual dimension of economic benefits and their translation into specific capabilities; conceptualizes the capacities accumulation process as a multiplier of social effects (direct and indirect) that emerge as knowledge is reused; identifies the articulation between different schemes as a condition for learning effects and social effects to manifest over time.

An aspect not studied in the literature is addressed, the relationship between the learning process induced by joint research, in terms of capabilities, and the social effects specifically generated over time. This is taking place in a context, such as the COVID-19 pandemic, where calls from the scientific and academic community to promote science–industry cooperation are multiplying.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

This study analyzes the role of regional cooperative banks in identifying and financing small and medium-sized enterprises (SMEs) from a proximity perspective. Access to finance is a major challenge for SMEs. Regional cooperative banks can remove this barrier based on cooperative bank's characteristics and geographic proximity to SMEs. Understanding the interplay between these financial actors and firms can contribute to a better support of SMEs development.

The results are based on a case study of eight SMEs located in southwestern France. Interviews were conducted with two regional cooperative funds and eight SMEs. The interview guide included questions related to the company, the projects financed and how financing was accessed.

Results reveal that a combination of three forms of proximity allows regional cooperative banks and SMEs to establish effective financing operations. They show that regional cooperative banks are key players in the existing financing mechanisms for SMEs. Such financing is often used to gain access to larger players at a later stage. The findings suggest the need for public policies that promote the integration of financing actors in regional ecosystems to advance SMEs' development.

This article examines how SMEs access financing, with a focus on regional cooperative banks, which have received little attention in the literature. Moreover, the relationships between these actors are studied through the lens of proximity. Regional cooperative banks are able to finance projects that may have been overlooked by traditional banks due to trust-building local dynamics.

This study aims to investigate and classify the hospital logistics key performance indicators (KPIs) using the context of public hospitals in remote areas.

The public hospitals in northern Thailand were selected for the case study. The questionnaire was developed and used to collect data from hospital logistics experts. Then, the analytic hierarchy process (AHP) method was used to evaluate the hospital logistics KPIs in each dimension.

This research found that the procurement management dimension is ranked highest. Information and technology management is the last rank in the hospital logistics KPIs used for public hospitals in remote areas.

The public hospitals located in northern Thailand were selected for the case study. Fuzzy multi-criteria decision-making methods can be used to reduce the vagueness of the values.

The results from this study can be a guideline for hospitals to improve the efficiency of their logistics operations.

The decision-makers in the hospital can use these results to improve the hospital’s logistics performance in the future, which could help increase the service level and the safety of the patients.

The hospital logistics KPIs were revised, and the crucial KPIs were prioritized for improving the hospital logistics using the AHP method.

The purpose of this paper is to understand US federal government policy during the early stages of the COVID-19 pandemic and the connections to graduate education. Using the multiple streams framework, the paper outlines these actions through various streams (problems, policy and political) and perspectives (defining problems, articulating options and mobilizing responses).

The primary sources of data collected for this study were US federal government policies from March 2020 through May 2021. Policies were examined through introduction, implementation and alteration (when possible) within the specific time period of the study. The policies outlined in this paper were connected to the US Department of Education, and to a lesser extent, the National Institutes of Health, the National Science Foundation and other federal agencies. Data analysis was a two-fold process. First, the individual policy was considered as a single case and second, a cross-case comparison occurred across the multiple cases.

Analysing the study’s data in the problem stream provides a strong indicator of how the pandemic was perceived as a challenge for US graduate education. The pandemic served as a focusing event and illuminated the connections of graduate education to key institutional functions, including research and teaching. Broadly, US federal policy actions in this area focused on giving institutions resources and flexibility to support graduate students and allow them to continue their academic work while also seeding funding and incentives to continue the movement of knowledge, activities and people in the research pipeline. Actions in the policy stream aligned with the decentralized nature of the US higher education system and allowed for choice by academic institutions within the parameters of options.

This paper extends extant literature related to policy-making and graduate education to consider policy-making during a time of crisis. The paper offers methodological and conceptual ideas for consideration in future research.

The purpose of this study is to detect the effect of some natural cellulosic polymers in their nano forms with the addition of zinc oxide nanoparticles on restoring the lost mechanical strength of degraded papyrus without any harmful effects on the inks.

In the current study, the USB digital microscopy, scanning electron microscope, measurement of mechanical properties (tensile and elongation), pH measurement, color change and infrared spectroscopy were undertaken for the samples before and after treatment and aging.

In the current study, the USB digital microscopy, scanning electron microscope, measurement of mechanical properties (tensile and elongation), pH measurement, color change and infrared spectroscopy were undertaken for the samples before and after treatment and aging.

The effect of strengthening materials was studied on cellulose and carbon ink, which makes this study closer to reality as the manuscript is the consistent structure of cellulose and inks, whereas most of the literature stated the impact of consolidation materials on the strengthening the cellulosic supports without attention to their impact on inks.