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Internet-based intangible network good (IING) has undergone rapid developments, even revolutionized multiple industries in recent years. IING is highly dependent on the rapid diffusion rates for development success. For firms, how to select the initial targets or “seeding points” to accelerate the adoption process is critical in network marketing campaigns. The purpose of this study is to provide a new method to identify the optimal initial adopters and adoption paths.

First, the author generalize three aspects influencing IING’s adoption, namely, innovation attributes, customer’s personality and word-of-mouth. Next, we establish a modified gravity model to describe how social interactions affect consumer’s adoption behavior. Then, simulate the adoption process by setting each agent as the initial adopter to identify the optimal initial adopters. Finally, trace the information flow to forecast the adoption paths.

The model reveals how individual interactions (micro level) aggregate into the diffusion process (macro level). The optimal initial adopters are determined by a combination of factors as follows: IING’s attributes, the adopter’s diffusion ability, the potential-adopter’s personality and the trust degree between adopters and potential-adopters. Among all these factors, trust degree plays a most important role.

This study proposes the conceptual model of IING’s adoption from a perspective of dyadic influence, in which an adopter’s influence on its peers depends on pairwise characteristics of both parties. The authors propose a new method to identify the optimal initial adopters and adoption paths based on the gravity model. It is the first time to introduce the gravity model to describe IING’s adoption, which is a creative application of social physics. The findings provide new insights in IING’s adoption and identifying the key nodes in networks.

Although online reviews have become a key source of information for consumer purchasing decisions, little is known about how the concreteness of language used in these reviews influences perceptions of deception. This study aims to address this important gap by drawing on psycholinguistic research and Language Expectancy Theory to examine how and when the concreteness of online reviews (abstract vs concrete) impacts consumers’ perceived deception.

Two scenario-based experiments were conducted to examine how the concreteness of online reviews (abstract vs concrete) influences consumers’ perceptions of deception, considering the mediating role of psychological distance to online reviews and the moderating effects of Machiavellianism (Mach) and reviewer identity disclosure.

Online reviews that include concrete language lead to lower perceived deception by reducing consumers’ psychological distance from the review. For consumers with higher levels of Mach, online reviews written in abstract (vs concrete) language result in higher perceived deception via psychological distance, while for consumers with lower Mach, online reviews written in concrete (vs abstract) language result in higher perceived deception via psychological distance.

To the best of the authors’ knowledge, this study is one of the first to highlight the relevance of linguistic style (i.e. concrete review vs abstract review) on consumers’ perceived deception toward online reviews in the context of e-commerce.

The framework enables managers of online retailing platforms to identify the most effective strategies to decrease consumers’ perceived deception via the appropriate utilize of linguistic styles of online reviews.

This study contributes to both theory and practice by deepening knowledge of how and when the concreteness of online reviews (abstract vs concrete) affects consumers’ perceived deception and by helping managers of online retailing platforms make the most effective\ strategies for reducing consumers’ perceived deception toward online reviews during online shopping.

Based on the literature on disruptive innovation, this research explores how disruptive innovation directly and indirectly (via innovation speed and innovation quality) influences firm performance in relation to the contingency of market-supporting institutions.

A sample of 207 firms was gathered through questionnaires targeting senior managers and R&D managers from high-tech firms in China with two waves including explanatory variables and outcome variables.

This empirical results indicate that disruptive innovation positively affects firm performance, and that innovation speed and innovation quality mediate the relationship between disruptive innovation and firm performance. Meanwhile, market-supporting institutions positively moderate the relationship between innovation speed and firm performance, but negatively moderate the relationship between innovation quality and firm performance.

This study suggests that disruptive innovation is important to firm performance, innovation speed and innovation quality play mediating roles, and market-supporting institutions acts as moderating effects. A research limitation is that the data were collected mainly through a questionnaire.

Firms should incorporate disruptive innovation as an important strategy and improve innovation speed and innovation quality to promote firm performance, and policymakers should improve the levels of market-supporting institutions to facilitate innovation and performance.

This study contributes the literature of disruptive innovation by uncovering the positive effect of disruptive innovation and firm performance and the mediating effects of innovation speed and innovation quality on the abovementioned relationship, and revealing their contingency effects of market-supporting institutions.

The purpose of this paper is to analyze the inverted U-shaped relationship between external search in the collaboration network and firm innovation outcomes. It also seeks to explore whether these curvilinear relationships are moderated by the network centrality and structural holes in the knowledge network.

In this empirical research, the authors collected a sample of patents in the smartphone industry over the period of 2000-2017. Then the authors examined the direct roles of external search breadth and depth in the collaboration network and the moderating role of network embeddedness in the knowledge network by using negative binomial regression.

Results found that external search in the collaboration network contributes more to firm innovation outcomes when the breadth and depth of the external search are moderate rather than high or low. Furthermore, both network centrality and structural holes in the knowledge network have positive effects on the external search breadth – innovation outcomes and external search depth – innovation outcomes relationships.

The authors collected the patent data within the single industry and excluded other types of industries. This may limit the generalization of the findings.

The paper has practical implications for adopting appropriate search strategies in the collaboration network and developing a better understanding of the effect of network embeddedness in the knowledge network on firm innovation outcomes. The findings suggest future directions for technology-intensive industries to improve their innovation output.

This study adds value to open innovation literature by pointing out a curvilinear relationship (inverted U-shaped) between external search breadth/depth and innovation outcomes in collaboration networks, in contrast to studies focused on firms’ external collaboration strategies in a certain industry context. Furthermore, this study reinforces the key contingent role of embeddedness in knowledge networks. This study provides a valuable theoretical framework of innovation outcome determinants by connecting the network perspective of open innovation theory with an embeddedness view.

The purpose of this study is to investigate the impact of corporate social responsibility (CSR) on innovation performance and examine the moderating role of social media strategic capability and big data analytics capability. Specifically, the authors explore the effects of both external and internal CSR on innovation performance.

The authors collected data from 221 senior, middle and research and development (R&D) managers of high-tech firms in China, using a questionnaire survey with a six-month interval.

The empirical results show that both external and internal CSR positively influence innovation performance. Furthermore, social media strategic capability has a positive moderating effect on the relationship between CSR and innovation performance, while big data analytics capability moderates the relationship between external CSR and innovation performance.

The data comes from high-tech firms in China, which may limit the generalizability and external validity of the findings. Future studies should replicate this study in other industries and types of organizations.

The study suggests that high-tech firms should engage in both external and internal CSR activities to promote innovation performance. Moreover, leveraging social media strategic capability and big data analytics capability can enhance innovation performance.

This study contributes to the literature on CSR outcomes by empirically exploring the effects of external and internal CSR on innovation performance, thus extending stakeholder theory. Additionally, by revealing the contingency effects of social media strategic capability and big data analytics capability, this study enriching the research on dynamic capabilities theory in the context of digital transformation.

Building on theories of inter-organizational knowledge flows and social network, we explored how two types of collaboration network embeddedness (NE) (i.e. structural embeddedness (SE) and relational embeddedness (RE)) drive firms' inbound and outbound open innovation (OI) practices from a knowledge flow perspective, and further examined these relationships are to what extent contingent on network inertia (NI).

In this empirical research, the authors collected a sample of patents in the unmanned aerial vehicle (UAV) industry over the period of 2000–2018. Then the authors examined the direct roles of SE and RE in collaboration networks on firms' inbound and outbound OI practices from a knowledge flow perspective, and the moderating role of NI by using negative binomial regression.

Empirical results from our study of 96 firms showed that both bridging structural holes position in collaboration networks (i.e. SE) and having stronger tie strength (i.e. RE) would positively affects firms' inbound OI practices, whereas only having stronger tie strength in collaboration networks (i.e. RE) would facilitate outbound OI practices. In addition, NI strengthens the relationships between SE and firm OI practice, but weakens the positive roles of RE on firm OI practice.

This empirical research provides new insights into whether and how firms can grasp the benefits of collaboration NE to conduct OI activities by exploring NI contingencies. It further sheds lights on the scope of the NE–OI issue from a knowledge flow perspective by extending its research context to UAV industry.

This study was aimed at obtaining a micro understanding of corporate social responsibility (CSR) by investigating the effect of perceived CSR on job performance. Especially, an attempt is made to explore the mediating role of perceived organizational support and the moderating role of collectivism on the relationship between perceived CSR and job performance.

This study collected questionnaire data from 219 employees of Chinese manufacturing firms, then used hierarchical multiple regression analysis to test our theoretical model.

Our empirical results demonstrate that perceived internal and perceived external CSR are positively associated with job performance. In addition, perceived organizational support mediates the relationship between perceived CSR and job performance, and collectivism positively moderates the relationship between perceived external CSR and perceived organizational support.

This study highlights the importance of adopting various strategies to conduct CSR practices, enhancing perceived organizational support and leveraging employee collectivism, which would be beneficial to improve job performance.

This study reveals employees’ underlying attitudes and behaviors responses to perceived CSR, thereby deepening the micro understanding of CSR. In addition, it extends the literature on social exchange theory by dividing perceived CSR into perceived internal and perceived external CSR and exploring their separate effects on job performance. Moreover, the study reveals the mediating role of perceived organizational support and the moderating role of collectivism, enriching the knowledge based on social exchange theory.

This paper aims to propose the following questions: How do structural network embeddedness influence firms’ incremental innovation capability? Does technology cluster moderate the relationships between them?

In this empirical research, the authors collected a sample of patent data in the smartphone industry over the period of 2000-2018. Then, the authors examined the direct roles of structural network embeddedness on firms’ incremental innovation capability and the moderating role of technology cluster by using ordinary linear squares regression.

The empirical results show that occupying the central position positively affects firms’ incremental innovation capability, and clustering strengthens this linear relationship. Furthermore, bridging structural holes has an inverted U-shaped effect on incremental innovation capability, and clustering positively moderated this nonlinear relationship, while bridging ties across different clusters plays a negative moderation role in this relationship.

This empirical research provides new insights into whether and how firms can grasp the benefits of structural network embeddedness to conduct incremental innovations and the moderation effects of technology cluster contingencies. It further contributes to the structural network embeddedness–incremental innovation capability issue by extending its research context to the smartphone industry.

Internet-based intangible network good (IING) has revolutionized multiple industries in recent years. This paper aims to reveal the laws of consumer’s decision-making on IING from a perspective of kinetic energy and potential energy.

In this paper, 4 aspects and 17 factors influencing IING adoption were generalized. Based on the theory of social physics, an agent-based simulation model, introducing physical energy theory to depict consumer’s decision-making, was built. An agent’s kinetic energy reflects the agent’s perceived effect of mass media on the agent’s decision-making on IING adoption. An agent’s potential energy reflects the agent’s perceived effect of social interactions on the agent’s decision-making on the adoption of IING. An agent’s final energy is the sum of the kinetic energy and potential energy, which reflects the agent’s final decision.

Some factors mainly influence the diffusion velocity, while other factors have a dramatic impact on both diffusion velocity and diffusion scale. The agent’s personality can make a difference at the early and middle stages of IING adoption, but a faint impact at the later stage because of the effects of network externalities and word of mouth. There is a critical value of the number of initial adopters which can dramatically speed up IING adoption.

This study provides new insights for firms on the effects of factors influencing consumers’ decision-making on IING adoption.

This paper defines a new kind of innovation, IING, and generalizes IING’s special characteristics. As a new application of social physics, the physical energy theory has been creatively introduced to depict consumer’s decision-making on IING adoption. A kinetic and potential energy model of IING adoption has been built. Based on simulation experiments, new insights of IING adoption have been gained.

This paper aims to analyze the extent to which the influence of external knowledge search activities on firms’ incremental innovation capability, and the moderating roles of the relatedness between the partners’ technological bases and a firm’s network embeddedness in the innovation network.

In this empirical research, the authors collected a sample of patents in the UAV industry over the period of 2004–2018. Then the authors examined the direct role of external knowledge search on firms’ incremental innovation capability and the joint moderating effects of technological proximity and network embeddedness.

We found that external knowledge search in innovation networks positively affects firms’ incremental innovation capability. Moreover, we discovered that high technological proximity to other peers positively strengthens the impact of firms’ external knowledge search on their incremental innovation capability. Finally, the findings suggested that the relationship between a firm’s external knowledge search activities and its incremental innovation capability is stronger for high technological proximity coupled with high network centrality or poor structural holes in innovation networks.

This study adds value to open innovation literature by pointing out a positive relationship between external knowledge search and firm incremental innovation capability. Furthermore, this study reinforces the key joint contingent roles of technological proximity and network embeddedness. This study provides a valuable theoretical framework of incremental innovation capability determinants by connecting the different perspectives.