A dynamic discount pricing strategy for viral marketing

Zhong, Xuefei; Zhao, Junhui; Yang, Lu‐Xing; Yang, Xin‐She; Wu, Yingbo; Tang, Yuan Yan

doi:10.1371/journal.pone.0208738

Cited by 8 publications

(3 citation statements)

References 49 publications

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“…An individual-based WOM propagation model classifies each OSN individual into a few classes based on his state [19]- [22]. Inspired by [16], [20] suggested an individualbased positive/negative WOM mixed propagation model. [21] proposed an individual-based WOM propagation model with static influence-based discount pricing mechanism.…”

Section: A Wom Propagation Modelmentioning

confidence: 99%

“…Recently, optimal control theory has been applied to the maximization of marketing profit by means of WOM propagation. For instance, [19] studied the marketing profit maximization problem in the framework of influence-based discount pricing, [20] dealt with the problem in the presence of both positive and negative WOMs, and [22] addressed this problem in the context of competitive marketing. To our knowledge, the marketing profit maximization problem in the presence of after-sale service has not been addressed through optimal control approach.…”

Section: B Optimal Control Approach To Wom Marketingmentioning

confidence: 99%

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Dynamic Maintenance Strategy for Word-of-Mouth Marketing

et al. 2020

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After-sale service is an integrable part of marketing activities. The after-sale service experience of a consumer can be measured by the dynamic maintenance (DM) strategy used by the merchant, i.e., the instantaneous fractions of the maintenance cost paid by the merchant in the total maintenance cost at all time. This paper aims to develop an optimal DM strategy for a word-of-mouth (WOM) marketing campaign. First, we propose an individual-based WOM propagation model in which the effect of the DM strategy is accounted for. Second, we convert the original problem into an optimal control problem, where the objective functional stands for the expected marketing profit, each optimal control stands for an optimal DM strategy. Third, we derive the optimality system for the optimal control problem. By solving the optimality system, we get a potential optimal control. Next, through comparative experiments we conclude that the DM strategy associated with the potential optimal control outperforms most DM strategies in terms of the expected marketing profit. Therefore, we recommend this potential DM strategy. Finally, we examine the effect of some factors on the expected marketing profit for the potential DM strategy. Our findings help to enhance the marketing profit of a WOM marketing campaign.

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Section: A Wom Propagation Modelmentioning

confidence: 99%

Section: B Optimal Control Approach To Wom Marketingmentioning

confidence: 99%

Dynamic Maintenance Strategy for Word-of-Mouth Marketing

et al. 2020

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“…Human societies are built upon social networks that form the infrastructure for sharing information, such as ideas (Leskovec et al, 2009;Orellana-Rodriguez and Keane, 2018), product innovations (Leskovec et al, 2007;Zhong et al, 2018), and political movements (Polletta and Jasper, 2001). The network metaphor suggests a discrete and static property (edge/no edge), however, agent-to-agent interactions have certainly different intensities and durations.…”

Section: Introductionmentioning

confidence: 99%

Modulating Interaction Times in an Artificial Society of Robots

Khaluf

Hamann

2019

The 2019 Conference on Artificial Life

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In a collaborative society, sharing information is advantageous for each individual as well as for the whole community. Maximizing the number of agent-to-agent interactions per time becomes an appealing behavior due to fast information spreading that maximizes the overall amount of shared information. However, if malicious agents are part of society, then the risk of interacting with one of them increases with an increasing number of interactions. In this paper, we investigate the roles of interaction rates and times (aka edge life) in artificial societies of simulated robot swarms. We adapt their social networks to form proper trust sub-networks and to contain attackers. Instead of sophisticated algorithms to build and administrate trust networks, we focus on simple control algorithms that locally adapt interaction times by changing only the robots' motion patterns. We successfully validate these algorithms in collective decision-making showing improved time to convergence and energy-efficient motion patterns, besides impeding the spread of undesired opinions.

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Price regulation, network externality, and product innovation strategies: A dynamic analysis

Ge,

2024

Manage Decis Econ

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For many high‐tech and Internet‐related products, consumers' utility depends partly on the scale of user groups, which is called network externality. This phenomenon plays a crucial role in shaping firms' innovation strategies, especially in markets with price regulation. This paper aims to investigate a monopolist's dynamic product innovation problem in a price‐regulated market exhibiting network externality. We identify the sufficient conditions guaranteeing the existence of optimal steady‐state equilibrium. Our analysis mainly shows the following: (i) the product quality and network size move in opposite directions along the path to the steady‐state equilibrium; (ii) the equilibrium result of product innovation increases with the regulated price but decreases with the intensity of network externality; (iii) the social‐welfare maximizing path of product innovation can be replicated by a dynamic price regulation regime, involving a premium on quality and a premium or a penalty on network size. Numerical experiments are performed to characterize the dynamic patterns of product innovation. We find that firms with high brand power prefer adopting mild product innovation strategy while for firms with low brand power, almost constant high‐quality strategy is better.

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A dynamic discount pricing strategy for viral marketing

Cited by 8 publications

References 49 publications

Dynamic Maintenance Strategy for Word-of-Mouth Marketing

Dynamic Maintenance Strategy for Word-of-Mouth Marketing

Modulating Interaction Times in an Artificial Society of Robots

Price regulation, network externality, and product innovation strategies: A dynamic analysis

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