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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.

Although previous research has recognized the pivotal role of mobile social media in knowledge sharing among project members, little is known about what factors affect knowledge sharing in mobile social media groups (MSMGs). Against this background, using normative social influence theory, this study attempts to explore factors influencing knowledge sharing in MSMGs.

Data from 205 Chinese construction project members are collected and used for analysis. Ordinary least squares regression by Stata 16 is used to test the proposed hypotheses.

Concerning role norms, gender difference in knowledge sharing behavior (KSB) is found, while it is not the case for knowledge quality (KQ). Work experience is found to positively affect KQ, but shows no influence on KSB. As for group norms, the inverted-U relationship between number of members and KSB is partially supported. In addition, organizational norms generally exhibit the greatest influence on both KSB and KQ among the three forms of norms.

This study deepens the understanding of knowledge sharing factors in mobile social media environments and affords practical implications for how to make full use of social media for knowledge management within construction project teams.

This historical example of the creation of the arms industry in the Connecticut River Valley in the 1800s provides new insights into the value of government venture capital (GVC) and government demand in creating a new industry. Since current theoretical explanations of the best uses of governmental venture capital are still under development, there is considerable need for further theory development to explain and predict the creation of an industry and especially those industries where failures in private capital supply necessitates governmental involvement in new firm creation. The purpose of this paper is to provide an in depth historical review of how the arms industry evolved spurred by GVC and government created demand.

This study uses abductive inference as the best way to build and test emerging theories and advancing theoretical explanations of the best uses of GVC and governmental demand to achieve socially required outcomes.

By observing this specific historical example in detail, the authors add to the understanding of value creation caused by governmental venture capital funding of existing theory. A major contribution of this paper is to advance theory based on detailed observation.

The relatively limited research literature and theory development on governmental venture capital funding and the critical success factors in startups are enriched by this abductive investigation of the creation of the historically important arms industry and its spillover into creating the specialized machine industry.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

Social commerce (s-commerce) has gained widespread popularity as a social platform where customers engage in resource-sharing activities such as information exchange, advice-seeking and expressing their opinions on mutual interests. However, existing studies have not fully comprehended the drivers of electronic customer-to-customer interaction (eCCI) and how such behavior contributes to the customer “stick” on s-commerce sites. This study develops the Motivation–Opportunity–Ability (MOA) theory and investigates the impact of MOA factors on eCCI, which in turn affects customer stickiness.

A survey was used to acquire data from 455 valid respondents, and the research employed a combination of fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling.

The results revealed associations between perceived self-efficacy, intrinsic motivation, tie strength with other customers, eCCI and customer stickiness.

Considering the limited availability of complete eCCI frameworks in existing scholarly works, the authors present valuable perspectives on the role of consumer characteristics as both antecedents and consequences of eCCI. Additionally, this study proposes a research agenda for the field of eCCI on s-commerce sites.

This paper aims to contribute to the understanding of novelty emergence in the context of an “off-line” open innovation system. Several contributions address novelty generation implying open innovation that is typically mediated by IT systems, while fewer address open innovation that takes place off-line, through new forms of collaboration happening in the so-called “physical spaces” and in widespread creativity contexts involving whole cities and territories. This research aims to clarify what the critical elements for novelty generation are, and how and why they interact in producing novelty.

This paper presents the case study of the Blackshape, a high-tech start-up that has become the Italian symbol of a new bottom-up economy that is grounded on high-education, a mix of territorial competencies and young initiative, and produces the development or growth of territories experiencing present or foreseen economic retardation for various reasons. This is a case in which novelty is emergent and takes place through exaptation. The case is used to elaborate an inductive understanding of the process of novelty generation through exaptation and follows a “conceptual composition” format (Berends and Deken, 2019).

This paper shows that initiatives building widespread creativity on the territory play a prominent role for emergent novelty generation, as they provide the context that sustains the efforts to keep on trying of entrepreneurs, welcomes unforeseen interaction and keeps interesting people on the territory that can be involved in random encounters. This paper adds that crucial contributions for the definition of the innovative project come from contributors that are expected to provide suggestions in other areas. Such prominent contributors are engaged in a sense “by mistake”, and here the randomness perceived by the actors experiencing it, because they are perceived to be able to provide some contributions, while they provide others that are more important to the project. This paper argues that such “perceived randomness” sustains a mechanism of selection of novelty generation partners that allows to go beyond the ability of actors themselves to design and foresee other actors’ contribution into the project. Finally, two other elements play a role: how the project is narrated, as well as, how the entrepreneurial team communicates their entrepreneurial competence for the project.

This theoretical understanding builds on only one case study; further research might validate the critical role of our understanding of novelty generation elements and help develop their dynamics further.

Many elements in our understanding of novelty generation have typically been understood as resulting from luck and randomness, leaving, therefore, very little hope to actors’ interest in supporting them. This paper claims that such elements and such dynamics can be sustained and novelty generation can indirectly be supported, for instance, by suggesting a high openness and sharing of one’s own project even to accidentally encountered actors, as one’s own ability to foresee how they might contribute to the project is very poor.

This paper provides a tentative understanding of the elements and dynamics of novelty generation through exaptation building on theoretical elaboration that is inductively triggered and stimulated by empirical evidence.

This study aims to evaluate the impact of extrinsic, intrinsic and amotivation on an individual’s knowledge-sharing behavior.

The authors reviewed the literature on self-determination theory (SDT) as an applied predictor of knowledge-sharing behavior, and documented the extent to which SDT conceptual framework components have been studied in relation to predict knowledge sharing.

Building from SDT and its sub-theories, this study uncovers a gap in the knowledge-sharing literature as the continuum of the SDT framework has yet to fully be applied to knowledge-sharing behavior.

Contributing to the literature on knowledge management and knowledge sharing, this study is the first, to the best of the authors’ knowledge, of its kind to apply Deci and Ryan’s self-determination continuum, in its entirety, to a knowledge-sharing conceptual framework. The authors thereby address the potential impact of amotivation on an individual’s knowledge-sharing behavior.

Crowdfunding models recently emerged as relevant enhancing systems aimed at fostering innovation and entrepreneurial dynamics. Accordingly, great attention has been paid to seeker firms' characteristics and platforms. For this reason, adopting a holistic knowledge-based perspective on crowdfunding is essential. This paper first identifies and categorizes the potential knowledge-based dimensions grounding crowdfunding and technological scouting strategies to provide a theoretically-grounded framework potentially useful for driving decision-making processes. Then, it is applied to interpret a real crowdfunding strategy developed by an Italian platform in the field of the real estate sector.

The paper combines deductive and inductive approaches. After elaborating a conceptual framework identifying the potential knowledge-based dimensions for a crowdfunding strategy, it is tested and applied by re-interpreting a real crowdfunding strategy.

The study identifies the potential knowledge assets dimensions grounding a crowdfunding strategy through elaborating a dedicated conceptual framework. Then, the case study enriches the proposed conceptual arguments with a set of empirical evidence.

The paper provides a conceptual framework capable of fostering a specific research stream and carrying out a first holistic and systematic knowledge-based perspective. The authors believe that their research may provide a relevant contribution to the existing literature, depicting a comprehensive picture of the intellectual capital components that seekers have to identify and manage in crowdfunding. While doing so, the study significantly addresses the challenge launched by Troise et al. (2021) in order to enrich prior but highly fragmented studies on the role of intellectual capital components in crowdfunding.

The analysis of the models and tools developed and discussed can be useful to support the elaboration and the application of practical knowledge-based approaches, protocols and routines for the value generation in the crowdfunding field and to drive the designer of crowdfunding platforms and strategies to develop more effective and impactful initiatives and campaigns. Accordingly, when elaborating a crowdfunding strategy, it should be effectively highlighted that seekers have and are capable of managing intellectual capital in different manners. This is particularly true for new ventures that are generally challenged to provide information about their quality, in particular about founders, their previous experiences, potential and real networks and partnerships, innovation capacity.

This paper contributes to the further development of the crowdfunding literature according to a knowledge-based perspective.

Sharing and obtaining information over social media has enabled people to express their opinions regarding any event. Since the tweets regarding the Russia-Ukraine war were extensively publicized on social media, this study aims to analyse the temporal sentiments people express through tweets related to the war.

Relevant hashtag related to the Russia-Ukraine war was identified, and tweets were downloaded using Twitter API, which were later migrated to Orange Data mining software. Pre-processing techniques like transformation, tokenization, and filtering were applied to the extracted tweets. VADER (Valence Aware Dictionary for Sentiment Reasoning) sentiment analysis module of Orange software was used to categorize tweets into positive, negative and neutral ones based on the tweet polarity. For ascertaining the key and co-occurring terms and phrases in tweets and also to visualize the keyword clusters, VOSviewer, a data visualization software, was made use of.

An increase in the number of tweets is witnessed in the initial days, while a decline is observed over time. Most tweets are negative in nature, followed by positive and neutral ones. It is also ascertained that tweets from verified accounts are more impactful than unverified ones. russiaukrainewar, ukraine, russia, false, war, nato, zelensky and stoprussia are the dominant co-occurring keywords. Ukraine, Russia and Putin are the top hashtags for sentiment representation. India, the USA and the UK contribute the highest tweets.

The study tries to explore the public sentiments expressed over Twitter related to Russia-Ukraine war.