Business Models 4.0 Using Network Effects: Case Study of the Cyfrowy Polsat Group

Niemczyk, Jerzy; Trzaska, Rafał; Wilczyński, M.; Borowski, Kamil

doi:10.3390/su132111570

Cited by 5 publications

(5 citation statements)

References 42 publications

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“…Another mechanism is that media manufacturers can sell their media repeatedly as consumables for many years and earn profits. The purpose of a business is to generate profitable and sustainable revenue streams [47]. The aforementioned mechanisms contribute to the generation of a sustainable business.…”

Section: Discussionmentioning

confidence: 99%

“…It was then popularized by the invention of Ethernet and, for many years, was associated with telecommunication, information and IT infrastructure [47] The gain received from a product or service and the number of users mutually and cyclically increase when such a mechanism works; thereby, the product or service is spread exponentially [6]. The network effect is defined as the phenomenon in which the benefit of using a product or service increases when the number of users who use the same or compatible products or services increases [47]. The increased value accrued by network participants is contingent on the number of other users in the network with whom they can interact [4,48].…”

Section: Network Effectmentioning

confidence: 99%

“…Business ecosystems are reinforced by mutual dependency [4] as the number of customers joining a network increase [48]. Indirect network effects occur when the benefits from using a product improve with the use of a complementary set of compatible goods [47]. Indirect network effects are ancillary benefits that accrue to network participants as the network grows, such as the development of complementary services, standards formation, and price reduction [30].…”

Section: Network Effectmentioning

confidence: 99%

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Mechanisms for Business Ecosystem Members to Capture Value through the Strong Network Effect

Awano

Tsujimoto

2022

Sustainability

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Business ecosystem leaders tend to focus on their own success rather than carefully monitoring the success of business ecosystem members, and each member must find a mechanism to capture value. Rarely has business ecosystem research examined the success of business ecosystem members. This study investigates the mechanisms by which business ecosystem members capture value in the business ecosystem related to different types of storage formats and how these mechanisms contribute to the sustainability of the business ecosystem. We identify two value capture mechanisms in the storage business ecosystem. First, media manufacturers, being members of the storage business ecosystem, can capture value through strong network effect in the server backup markets. They can sell a significant amount of media for every single unit of a drive sold through the strong network effect. Second, media manufacturers can capture value by selling their media repeatedly as consumables for many years. We quantitatively confirm these mechanisms using a vector autoregressive model to measure the strength of the indirect network effect. These mechanisms help business ecosystem members in staying within the business ecosystem and also contribute to the business ecosystem’s sustainability.

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Section: Discussionmentioning

confidence: 99%

Section: Network Effectmentioning

confidence: 99%

Section: Network Effectmentioning

confidence: 99%

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Mechanisms for Business Ecosystem Members to Capture Value through the Strong Network Effect

Awano

Tsujimoto

2022

Sustainability

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“…The energy plans made for different regions in different countries involve energy efficiency and the expansion of renewable energy, with the most significant referring to Canada, Italy, and regions in other countries [26][27][28][29][30]. The significance of regional planning has been accepted a reason as to why the EU has taken a number of initiatives aiming at developing energy plans from local and regional authorities, such as the Covenant of Mayors initiatives (CoM 2020 and 2030) [30][31][32][33].…”

Section: Literature Reviewmentioning

confidence: 99%

Energy and Mineral Resources Exploitation in the Delignitization Era: The Case of Greek Peripheries

et al. 2022

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The efficient and sustainable exploitation of energy resources may secure a sustainable economic growth for different regions. However, the peripheries are subject to social, economic, and political constraints, with limited power over energy management. The present work examines regional convergence in exploitation efficiency as synopsized in the GDP generated by energy and minerals in an era of the country’s efforts to shut down the lignite-run power production. With the assistance of panel unit root tests, we confirm non convergence of the variables employed, an expected result given the fact that different energy sources are being used for energy production by each different periphery, generating different economic results. In the second stage the methodology employed is a Bayesian vector auto-regressive model (BVAR) with an informative prior on the steady state. The particular methodology outperforms the conventional VAR methodology due to limited degrees of freedom. The Impulse response analysis and the Variance Decomposition analysis confirmed interlinkages among the regions studied. This result implies that the growth generated by different energy and mineral resources are interconnected. Furthermore, the energy transition taking place in Megalopoli and West Macedonia, where the two greatest lignite industries were located until recently, affects the growth generated by energy and resource exploitation for all the other peripheries, according to our findings. The novelty of the present work stands on the concept to detect interlinkages of energy and resources-based growth for the peripheries in Greece with the assistance of the Bayesian Var. The results of the present work are significant, since our findings suggest to policy makers tools to promote economic growth generated by energy based on alternative energy sources, including the environmentally friendly ones, by taking into consideration the interlinkages established by the existing infrastructure and the conventional energy sources used.

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“…Scholars have confirmed the existence of network effects in OSNs. Network effects mean that the benefit of using a good/service increases with the number of users adopting the same or compatible good/service [27,28]. According to network effect theory, new users will prefer products with large adopter networks, which makes the large networks larger [29].…”

Section: Network Effectsmentioning

confidence: 99%

Multi-Agent Simulation of Product Diffusion in Online Social Networks from the Perspective of Overconfidence and Network Effects

et al. 2022

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Online social networks (OSNs) have steadily become the primary mechanism of product promotion. However, previous studies have paid little concern to the irrational consumer behavior (e.g., overconfidence) and network effects that influence product diffusion in OSNs. We use overconfidence theory, network effects theory, and evolutionary game theory to build a multi-agent simulation model that captures the nonlinear relationship between individual actions to examine the effects of overconfidence and network effects on product diffusion in OSNs. We found that (1) overestimation is profitable for improving the diffusion level of product diffusion in OSNs and maintaining market stability; however, the closer the degree of overprecision is to 1 (i.e., individuals are more rational), the more stable the market will be. We also found that (2) moderate network effect intensity can better promote product diffusion on the social network. When the network effect intensity is small, the non-overconfident scenario has the highest percentage of adoption. The overprecision scenario has the highest percentage of adoption where the network effect intensity is high. Additionally, we found that (3) the scale-free network is more conducive to the diffusion of products in OSNs, while the small-world network is more susceptible to overconfidence and network effect. This research laid the groundwork for investigating dynamic consumer behavior utilizing a multi-agent method, network effects theory, and a psychological theory.

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Business Models 4.0 Using Network Effects: Case Study of the Cyfrowy Polsat Group

Cited by 5 publications

References 42 publications

Mechanisms for Business Ecosystem Members to Capture Value through the Strong Network Effect

Mechanisms for Business Ecosystem Members to Capture Value through the Strong Network Effect

Energy and Mineral Resources Exploitation in the Delignitization Era: The Case of Greek Peripheries

Multi-Agent Simulation of Product Diffusion in Online Social Networks from the Perspective of Overconfidence and Network Effects

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