Effects Of Network Externalities Research Articles

A Differential Game Approach to Investment in Greentech Innovation in a Duopoly with Network Externality

In this paper, we revisit a well-known differential game model to investigate the R&D activity for Greentech innovation in a duopoly market with network externality. In our study, firms carry out independent R&D or Cartel R&D for Greentech innovation which aims to reduce end-of-pipe emission and network externality effects play a role in the R&D activity via the inverse demand functions. Firms are concerned not only with their own profits, but also with the relative profits. At the steady-state equilibrium, the efforts for Greentech innovation under independent R&D are higher than that under Cartel R&D when the degree of altruism is higher than the degree of technological R&D spillover, and the network size under independent R&D is lower than that under Cartel R&D. Moreover, under a given market structure, whether profits under independent R&D are higher than under Cartel R&D depends on the initial network size, which means that at the initial moment firms can decide to undertake independent or Cartel R&D activities based on the initial network size.

Evolution game model and simulation of enterprise R&D cooperative innovation network under network externalities

ABSTRACT Multi-agent cooperation, pooling innovative resources, helps to develop key technologies and major projects in enterprises. However, the multi-agent cooperation of enterprises makes the cooperative relationship unstable, and behaviours such as moral hazard, spillover of technology or information are more likely to occur, thereby increasing the risk of enterprises. In this research an enterprise R&D cooperative evolutionary game model is built to investigate the influence of Network externalities on enterprise R&D cooperation in innovation networks. Furthermore, the evolution of innovative network structure of game results is simulated by means of computer technology so that the effects of network externalities on corporation degree, agglomeration and network structure are analyzed. The results show that Network externalities led to a decrease of cooperated partners, a decline in cooperation degree and agglomeration of enterprises, and a shrinking enterprise R&D cooperation tendency. The influence of network externalities shows significant structural differences in the three types of enterprise networks: the degree of enterprise cooperation and agglomeration fluctuates greatly in the scale-free network, but slightly in the small-world network and the random network.

Effect of Network Externalities and Promotional Incentives on Mobile Payments

Effect of Network Externalities and Promotional Incentives on Mobile Payments

Novel R&D Capabilities as a Response to ESG Risks-Lessons From Amazon’s Fusion of Diverse Knowledge

Environmental, Social, and Governance (ESG) management is essential for transforming corporate financial performance-oriented business strategies into Finance (F) + ESG optimization strategies to achieve the Sustainable Development Goals (SDGs). In this trend, the rise of ESG risks has divided firms into two categories. Former incorporates a growthmindset that creates a passion for learning, and urges it to improve itself by endeavoring Research and development (R&D) -driven challenges, while the other category, characterized by risk aversion, avoids challenging highly uncertain R&D activities and seeks more manageable endeavors. This duality underscores the complexity of corporate R&D strategies in addressing ESG risks and necessitates the development of novel R&D capabilities for corporate R&D transformation strategies towards F + ESG optimization. Building on this premise, this paper conducts an empirical analysis, utilizing reliable firms data on ESG risk and brand value, with a focus on 100 global R&D leader firms. It analyzes R&D and actions for ESG risk mitigation, and assesses the development of new functions that fulfill F + ESG optimization through R&D. The analysis also highlights the significance of network externality effects, with a specific focus on Amazon, a leading R&D company, providing insights into the direction for transforming R&D strategies towards F + ESG optimization. The dynamics of stakeholder engagement in F + ESG optimization are indicated with the example of amazon's activities. Through the analysis, it became evident that Amazon's capacity encompassing growth and scalability, specifically its ability to grow and expand, is accelerating high-level research and development by gaining the trust of stakeholders in the "synergy through R&D-driven ESG risk mitigation." Finally, as examples of these initiatives, the paper discussed the Climate Pledge led by Amazon and the transformation of Japan's management system.

Is AI testing beneficial for the manufacturer and social welfare? Optimal test strategy of a smart product

The rapid technological revolution of Industry 4.0 has set off rapid advancement in the smart product development. Testing the smart product’s system before release to market is crucial for ensuring proper functioning. Smart product manufacturers must carefully consider different testing modes to choose the optimal one based on product characteristics and consumer’s shopping intention. Additionally, different testing modes have varying impacts on the environment and social welfare, as well as profitability of the product. This study utilizes a two-period game theory model to analyze a smart product manufacturer’s optimal testing mode and pricing decision. Three testing mode are evaluated: manual testing mode (MT mode), artificial intelligence testing mode (AT mode), and public testing mode (PT mode). Consumers’ utility is influenced by factors such as consumer preferences, product quality, usage duration, and network externality effect. Our findings indicate that the optimal testing mode depends on quality improvement and network effect coefficients. Specifically, when the degree of quality improvement is high and the network effect is moderate, MT mode is preferred; when the quality improvement is high but the network effect is small, AT mode dominates; under other conditions, PT mode is optimal. Quality improvement and network effect coefficients have similar effects on pricing decisions but impact the profits in different manners. Social welfare is the highest under MT mode when the network effect is high and quality improvement is low, under AT mode when network effect is low and quality improvement is high, and under PT mode when both factors are high or low. Finally we provide a numerical example of how profit-driven business decisions may conflict with social welfare, potentially leading to lower social welfare than the theoretical optimum under the chosen testing mode strategy.

Differential pricing in social networks with strategic consumers

This study analyzes a monopolistic seller's optimal differential pricing problem with strategic consumers connected in social networks. The consumers who purchase in the later period can get positive externalities from their friends who purchased in the early period but have to bear a utility discount for the delayed consumption. We first characterize consumers' strategic purchase decisions under general network structures. We then derive the optimal differential pricing strategies and demonstrate that different network structures lead to substantially different strategies. We find that when the intensity of the network externality effect is lower than a threshold and the influence matrix is symmetric, it is always optimal for the seller to conduct an increasing‐pricing strategy. However, when the network externality effect is strong, a decreasing‐pricing strategy may also be optimal. We further examine how the imbalance of influence, degree heterogeneity, and network topology impact the optimal pricing policy and profit. We find that when the intensity of network externality is relatively low, it is more profitable to sell products through many interconnected low‐influencer networks; however, when the network externality intensity is high, it is better to sell through a few high‐influencer networks. Finally, we show that the profit loss caused by uniform pricing strategies or by ignoring consumer network structures can be significant under certain conditions, thereby revealing the substantial value of differential pricing in social networks.

Exploring lead users' continued participation intention in crowdsourcing innovation community in China: the effects of network externalities

PurposeLead users are essential participants in crowdsourcing innovation events; their continuance intention significantly affects the success of the crowdsourcing innovation community (CIC). Although researchers have acknowledged the influences of network externalities on users' sustained participation in general information systems, limited work has been conducted to probe these relationships in the CIC context; particularly, the predictors of lead users' continued usage intention in such context are still unclear. Hence, this paper aims to explore the precursors of lead users' continuance intention from a network externalities perspective in CIC.Design/methodology/approachThis work ranked users' leading-edge status to recognize lead users in the CIC. And then, the authors proposed a research model based on the network externalities theory, which was examined utilizing the partial least squares (PLS) technique. The research data were collected from an online survey of lead users (n = 229) of a CIC hosted by a China handset manufacturer.FindingsResults revealed that the number of peers, perceived complementarity and perceived compatibility significantly influence lead users' continuance intention through identification and perceived usefulness.Originality/valueThis work contributes to the crowdsourcing innovation research and provides views regarding how lead users' sustained participation can be developed in the CICs. This work also offers an alternative theoretical framework for further research on users' continued intention in open innovation activities.

Channel Management for Digital Products in the Two-sided Market with Network Externality Effects

Channel selection is a critical trade-off for digital products firms whose products are characterized by network externality. This work develops the models of consumers’ utility impacted by the network externality for two channel strategies of the digital product firms in the two-sided market: direct channel strategy and platform channel strategy. Deriving from the consumers’ utility, the optimization models of the two channel strategies are presented. The optimization models are solved through the Lagrangian method, and the comparative statics analysis is conducted to investigate the effect of network externality on optimality. Mathematical results show that if the intensity of network externality in the online platform surpasses that in the direct channel, the platform channel strategy dominates the other channel strategy; otherwise, the direct channel strategy is the firms’ optimal decision. In addition, the two channels share the equal optimal price, and the firms’ profit (and demand) would be positively impacted by the network effect and the products’ features but negatively impacted by the consumers’ learning cost. This work provides decision support for the digital product firms on channel selection in the context of the two-sided market.

Mathematical Optimization on Hybrid Channel Pricing Digital Products in Two-Sided Market with Network Effect

In the two-sided market where the third-party platforms connect the providers and consumers, the online platforms become the significant distribution channel of digital products; therefore, the digital product firms face the hybrid channel pricing problem in the two-sided market in which the products are launched through the platform channel and the existing direct channel. Because the network externality effect is the significant economic characteristic of digital products and services, the current work presents the models of consumers’ utility obtained by adopting digital products from the direct and platform channels, and the utility models use the network effect in the direct and platform channels as the parameters. The optimization model on pricing is derived from the utility models and solved mathematically. The closed-form solutions show that the price in the direct channel is supposed to be lower than that in the platform channel, while the prices of digital products would be affected by the network effect only when the products are distributed through the direct channel. The comparative statics analysis on the network effect illustrates that the network effect in the direct channel and the platform channel would, respectively, have the positive and negative impact on the products’ prices and the firms’ profit. The current work explores the hybrid channel pricing problem and provides insights for the digital product firms on the optimal pricing decision in the context of the emerging platform economy.

The Timing of Technology Adoption in Network Industries

This paper analyzes the effect of network externalities on firms’ timing of new technology adoption in a network industry. In a pre-commitment game under Cournot competition, network effects tend to accelerate the timing of the leader and the follower regarding their adoption dates: under the rational expectations hypothesis and also under the firms’ output commitment. However, while an increase in network effects tends to reduce the discrepancy between the optimal social timing of the new technology adoption and the market-driven time of adoption in the rational expectations model, the opposite occurs under the output commitment game.

Network Externality Effects on Behavioral Intention to Use Consumer Internet of Things Among Urban Citizens in Indonesia

Abstract One of the most popular technologies is the internet of things (IoT). It refers to the number of users and penetration in the industry (I-IoT) and consumer (C-IoT) sectors. The previous stud-ies indicated that the usage rate of the C-IoT is outperforming the I-IoT worldwide. However, the contrary indication occurred in Indonesia. Among developing countries, the spending level of IoT in Indonesia is significant, but the use level of the technology is less developed. This survey study purposed to predict what factors influence the behavior intention to use C-IoT. The researchers extended the unified theory of acceptance and use of technology (UTAUT) model by adopting the network externality aspects. Around 400 valid data were collected from urban communities in the six most populous provinces in the country. The scholars used the partial least squares structural equation modeling (PLS-SEM) method using SmartPLS 3.3 in the data analysis stage. The findings expressed that the number of users and social influence factors are not influential factors influencing behavior intention to use IoT. Besides that, the UTAUT model extension may also be one of the theoretical references for future similar studies. Practically, the findings may also be one of the considerations for the stakeholders of C-IoT implementation in Indonesia.

Unpacking Detrimental Effects of Network Externalities on Privacy Invasion, Communication Overload and Mobile App Discontinued Intentions: A Cognition-Affect-Conation Perspective.

Recently, mobile apps are rapidly emerging as an important information instrument, with the potential to boost convenience and efficiency in everyday life. The adoption of mobile apps can exert a positive influence on individuals, but also lead to adverse perceptions in different ways. The crucial issue arising is what motivates people's discontinued use of such services. Furthermore, the roles of communication overload and privacy invasion between network externalities and discontinued use intentions have not been thoroughly examined. The primary objective of this article is to investigate if negative network externalities may result in privacy invasion, communication overload and discontinued intentions, and how the underlying mechanism operates. This current research collected and evaluated data from 696 mobile app users utilizing the structural equation model (SEM) technique. The findings demonstrate that perceived critical mass and perceived complementarity positively affect the privacy invasion of mobile app users. Particularly, it was discovered that privacy invasion and communication overload mediate the association between network externalities and mobile app discontinued use intentions. This article may not only enrich the ongoing contemporary critical discussion on new information technology usage, but also offer significant theoretical and practical implications for mobile app researchers and practitioners.

The impact of virtual interaction on consumers' pro-environmental behaviors: the mediating role of platform intimacy and love for nature

PurposeCompanies are increasingly designing pro-environmental games to motivate users to implement pro-environmental behaviors (PEBs). However, how different types of virtual interactions affect PEBs in pro-environmental games is not clear. Thus, the authors propose that two types of virtual interaction, interactions with game objects and interactions with other users, can induce platform intimacy and love for nature and that platform intimacy has a direct effect on love for nature. Simultaneously, the authors examine the moderating effect of network externality on the relationship between the two types of virtual interaction and platform intimacy.Design/methodology/approachThe authors, respectively, employed data from 92 students and 574 Chinese mobile users to empirically investigate the research framework.FindingsThe findings indicate that participants in interactions with game objects and interactions with other users reported stronger feelings regarding platform intimacy and love for nature, which, in turn, positively influences PEBs. Consumers with stronger perceptions of network externalities were more likely to be affected by the initiation effect of the interaction with game objects.Originality/valueThe authors introduce the notion of love for nature to the pro-environmental behaviors field and discuss the priming effect of two types of interactions on platform intimacy and love for nature. In addition, the authors focus on the important effect of network externality on users' emotions.

Multi-round auction-based resource allocation for edge computing: Maximizing social welfare

5G NR-Lite technology still suffers from inadequate response to low latency, high speed and mass connectivity scenarios in high mobility conditions. Building on 4G and 5G, 6G networks will work to more fully enable the Internet of Things (IoT) paradigm, working to provide secure wireless computing for the digital world. In order to ensure the resource utilization of edge computing, it is usually necessary to allocate resources among mobile devices. Many scholars have applied auction theory to resource allocation in mobile edge networks and achieved specific results in recent years. However, most existing studies unilaterally consider the utility of users or edge servers, and few jointly consider social welfare and user selection priorities, which cannot maximize the overall utility of mobile edge networks. This paper proposes a multi-round auction algorithm that pursues maximizing social welfare in a multi-user–multi-server network. The algorithm combines combinatorial auction with double auction, allowing users and servers to adjust their bids and asking prices in each auction round. To enhance the generalizability of the study, the algorithm takes full advantage of the flexibility of the auction mechanism and considers the users’ demand for different servers, the variability of bidding strategies, and the variability of the total resources of edge servers so that the users can obtain resources with higher priority and improve social welfare. To ensure that social welfare is maximized, we adopt the Vickrey–Clarke–Groves (VCG) payment mechanism and consider the effect of network externalities. Extensive comparative experiments show that the algorithm can effectively improve social welfare and maximize the overall benefits of the mobile edge network.

Continued usage of smart wearable devices (SWDs): cross-level analysis of gamification and network externality.

With the increasing maturity of mobile networks and big data technology, smart wearable devices (SWDs) are regarded as a new technology trend following smartphones. Especially during the COVID-19 pandemic, the increase in telework and the growing interest in self-health monitoring have greatly promoted the market growth of SWDs. This study aimed to investigate the factors affecting the continued use of SWDs. A cross-level analysis model that integrates technical characteristics, gamification theory, perceived value theory, and network externality was constructed. A hierarchical linear model was employed to evaluate the data and test it against the hypotheses. The empirical results showed that, at the individual level, gamification enhances users’ value perceptions. Users pay more attention to rewards in gamification than to competition. Rewards were also found to effectively promote the users’ value perception and increase the intention to continue using the device. At the group level, the effect of network externality significantly influences the intention to continue using SWDs. Moreover, SWDs are associated with the phenomenon by which consumers conspicuously display and highlight their own characteristics, and this attribute is also a crucial factor enticing consumers to continue using SWDs. Developers should therefore establish clear product positioning and strengthen interactivity as early as possible to build a loyal customer base.

Social media networks, fake news, and polarization

We study how the structure of social media networks and the presence of fake news affects the degree of misinformation and polarization in a society. For that, we analyze a dynamic model of opinion exchange in which individuals have imperfect information about the true state of the world and exhibit bounded rationality. Key to the analysis is the presence of internet bots: agents in the network that spread fake news (e.g., a constant flow of biased information). We characterize how agents’ opinions evolve over time and evaluate the determinants of long-run misinformation and polarization in the network. To that end, we construct a synthetic network calibrated to Twitter and simulate the information exchange process over a long horizon to quantify the bots’ ability to spread fake news. A key insight is that significant misinformation and polarization arise in networks in which only 15% of agents believe fake news to be true, indicating that network externality effects are quantitatively important. Higher bot centrality typically increases polarization and lowers misinformation. When one bot is more influential than the other (asymmetric centrality), polarization is reduced but misinformation grows, as opinions become closer the more influential bot’s preferred point. Finally, we show that threshold rules tend to reduce polarization and misinformation. This is because, as long as agents also have access to unbiased sources of information, threshold rules actually limit the influence of bots.

Effects of Network Externalities and Recycling Channels on Closed-loop Supply Chain Operation Incorporating Consumers’ Dual Preferences

Consumers’ awareness of environmental protection is gradually strengthened, and they often consider environmental protection characteristics of products during purchasing products. Based on the characteristic of consumers’ dual preferences for product quality and environmental friendliness, this paper constructs a novel closed-loop supply chain with network externalities for new products and remanufactured products under different waste product recycling channel strategies. It discusses the influence of product recycling channel strategies and network externalities on the optimal decision of the company. By establishing the Stackelberg game model, the analysis found that the retail price of new products and remanufactured products is not affected by network externalities and recycling channel strategies, even if the wholesale price of remanufactured products increases with the influence of network externalities. The changing trend of market demand for new products and remanufactured products is different between products with network externalities and without network externalities. When the cost of remanufactured products is within certain range, the existence of network externalities makes the market demand for new products and remanufactured products increase simultaneously. Our study also found that even if products have positive network externalities that increases consumer utility, when the cost of remanufactured products is outside certain range, the company’s profit will be higher when products have no network externalities than that when products have network externalities.

E-Banking Continuance: An Integration of Network Externalities and Flow Theory

This study examines the effect of network externalities and flow on continual usage of e-banking services. A sample of 400 e-banking users was conveniently engaged using a structured questionnaire. The method of analysis used included Spearman’s correlation analysis, confirmatory factor analysis and structural equation modelling analysis. The findings indicate that referent network size does not significantly influence continuance intention of e-banking users. However, flow positively influences continuance intention of e-banking users. Stakeholders in the financial institutions will understand the driving factors behind continual usage of e-banking services. Some researchers have explored continual usage of e-banking but such studies are rare in the African context. This study will contribute to extant literature by adding a new dimension, intrinsic and extrinsic factors, of e-banking continual usage.

The impact of network externalities and altruistic preferences on carbon emission reduction of low carbon supply chain

This paper explores the manufacturer's carbon emission reduction in the presence of network externalities and altruistic preferences. Existing literature mainly analyzes the impact of government regulations and firms' behavior characteristics on manufacturers' decisions, while little literature investigates the role of network externalities and altruistic preferences in promoting carbon emission reduction of manufacturers. Our results show that network externalities and altruistic preferences are conducive to improving manufacturers' profits and carbon emission reduction levels. However, we find that manufacturers' carbon emission reductions are more likely to be optimal without network externalities and altruistic preferences when the cost of low-carbon technologies is low, and consumer preferences are high. Interestingly, when the low-carbon technologies cost is high, the combined effect of network externalities and altruistic preferences is more favorable for manufacturers to implement carbon emission reductions. However, when the cost of low-carbon technologies is moderate, we find that the combined effect of network externalities and retailers' altruistic preferences does not always increase the level of carbon emission reductions. In addition, we also find that network externalities or altruistic preferences enhance manufacturers' ability to afford the costs of low-carbon technologies, which implies that manufacturers are more inclined to reduce carbon emissions compared to scenarios without network externalities and altruistic preferences.

Quality Competition and Market-Share Leadership in Network Industries

Abstract This paper incorporates network externalities into a model of vertical product differentiation to examine how firms determine product quality and network size. We show that, with significant network benefits from quality improvement, the effects of network externalities differ depending on the type of competition. In response to an increase in network externalities, vertical product differentiation enlarges under price competition but shrinks under quantity competition. Moreover, under price competition, the network size of a high-quality product increases, whereas that of a low-quality product decreases for a sufficiently large extent of network externalities, resulting in a reversal in the leading position in terms of network size from the low- to the high-quality product. By contrast, the network sizes of high- and low-quality products both increase under quantity competition; moreover, the gap between their network sizes shrinks for a sufficiently large extent of network externalities.