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A Dynamic Analysis of the Effects of Word-Of-Mouth on Online Brand Communities

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A Dynamic Analysis of the Effects of Word-Of-Mouth on Online Brand Communities SUMA DE NEGOCIOS, 9(20), 77-85, Julio-Diciembre 2018, ISSN 2215-910X Doi: http://dx.doi.org/10.14349/sumneg/2018.V9.N20.A1 SUMA DE NEGOCIOS Research article A dynamic analysis of the effects of word-of-mouth on online brand communities Milton M. Herrera1, Leonela S. León2 and Lorena K. Vargas-Ortiz3 1 Università Degli Studi di Palermo and Universidad Militar Nueva Granada, Faculty of Economic Sciences, Bogotá, Colombia. (Corresponding author) Email address: [email protected]. ORCID: 0000-0002-0766-8391. 2 Universidad Piloto de Colombia and Escuela Europea de Dirección y Empresa, Faculty of Social Sciences and Business, Bogotá, Colombia. Email address: [email protected]. ORCID: 0000-0001-6212-9713. 3 Universidad Piloto de Colombia, Faculty of Social Sciences and Business, Bogotá, Colombia. Email address: [email protected]. ORCID: 0000-0002-8974-6719. ARTICLE HISTORY A B S T R A C T Received on May 23rd 2018 The increase of brand communities is an important aspect that affects the purchase Accepted on August 8th 2018 process of online consumers. This research aims to assess the effects of word-of-mouth Available online on September 8th 2018 (WOM) on online brand communities in the food industry in Colombia. The paper presents a simulation model of online consumers’ purchase processes which allows us to under- JEL Classification: stand the viral marketing strategy and answers the following question: What is the func- M31, C63, Q13, M39 tion of WOM for online brand communities and what role does it play in food consumption? The model shows the change of consumer states and allows the understanding of behavior Keywords: during the development of the brand, WOM, the viral effects in the market and the analysis Word-of-mouth; of market penetration or the adoption of a complex service structure in closed cycles. The Viral marketing; findings from research into these issues can be used as guidelines to determine a suitable Simulation modeling; Online brand communities; marketing policy that could be adopted for agribusiness. Food consumption. Un análisis dinámico de los efectos del boca a boca en las comunidades de marcas en línea R E S U M E N Palabras clave: El aumento de las comunidades de marcas es un aspecto importante que afecta el proce- Boca a boca, mercado viral; so de compra de los consumidores en línea. Este artículo tiene como objetivo evaluar los modelado de simulación; efectos del boca a boca (WOM, por sus siglas en inglés) en las comunidades de marcas en comunidades de marca en línea; consumo de alimentos. línea de la industria de alimentos en Colombia. El artículo presenta un modelo de simula- ción del proceso de compra que permite comprender la estrategia de marketing viral y res- ponder al interrogante: ¿Cuál es el papel de WOM en las comunidades de marcas en línea y su dinámica en el consumo de alimentos? El modelo muestra el cambio de los estados de los consumidores y permite comprender el comportamiento en el tiempo del desarro- llo de la marca, el WOM, los efectos virales en el mercado y el análisis de la penetración en el mercado o la adopción de una compleja estructura de servicio en ciclo cerrado. Estos hallazgos se pueden utilizar para determinar la política de comercialización adecuada que podría adoptarse para el agro negocio. Award to the best article of the issue © 2018 Fundación Universitaria Konrad Lorenz. Este es un artículo Open Access bajo la licencia CC BY-NC-ND (http://creativecommons. org/licenses/by-nc-nd/4.0/). 78 SUMA DE NEGOCIOS, 9(20), XX-XX, Julio-Diciembre 2018, ISSN 2215-910X contributes to market penetration modeling from product Introducción development dynamics and viral market effect on close- loop perspective. The WOM communication channel is a common way of Studies on the innovation implementation process sug- creating enduring customer value through the influence of gest that three new constructs (including motivation thresh- online communities (Kumar and Reinartz, 2016; Li and Du, old) characterize the dynamics of implementation (Repen- 2017; Li et al., 2018a; Rintamäki and Kirves, 2017). Nowa- ning, 2002). Our paper carried out an analysis of viral markets days, digital marketing strategies have become a global which provides insights into the motivation threshold. Thus, tool for WOM recommendations which come from family, the importance of studying the effect of WOM on market dy- friends, and social networking (Li et al., 2018b). Sharing in- namics through simulation scenarios allows viral marketing formation contributes to the awareness process and it has to be implemented and then the effects of market policies even affected on a greater scale the purchase process. At can be understood. first the exposition may be seen attractive and can encour- Advances in technology and the ways people connect in age consumers to buy and further share information about virtual environments have led to an exponential growth in their experiences (Misirlis and Vlachopoulou, 2018; Wang the amount of WOM information accessible to consumers. and Zhang, 2017). Social networking can be a powerful tool to guide the col- This situation gradually generates consumption patterns lective moral judgment. Although some authors discuss the that change by slowly increasing the purchase of similar relevance of online groups and communities, they state that products. This could be related with friends and acquain- the community has been at the heart of the Internet since tances’ products reviews, and, as a result, the message can its inception. The simple status of individuals as members reach millions of consumers through multiple exchanges of a green products group can generate a common identity. Social interaction, such as chat rooms and customer feed- and interactions (Françoise and Tosan, 2018). Other studies back, has the potential to increase consumer influence. The agree that the informal exchange of information through importance of the Internet as a marketing strategy provides personal conversations can influence consumer choice and space for a wider range of relationships between people decision-making (Lee et al., 2017; Wouters and Kirchberger, who recognize that they have something in common with a 2015; Wu et al., 2018). Compared to traditional advertising, sense of community and solidarity. WOM communications have big advantages such as signifi- A social network is a platform that groups users together cantly lower costs and much faster propagation; this is par- so that they can establish friendships and interact with each ticularly true for online social networks (Li and Du, 2017; Li other based on interests they have in common. Social net- et al., 2018b; Relling et al., 2016). In this context, what is the works connect users through sharing thoughts and build- function of WOM for online brand communities and what ing friendships. The high degree of privacy among users fa- role does it play on food consumption? cilitates WOM marketing. Information is quickly dispersed It is becoming increasingly difficult to ignore the impor- on a social network and it is generally highly valued by the tance of the Internet as a marketing strategy. Thus, Internet- recipients. For this reason, social networks are commonly based strategies are having a viral effect on customers. Re- used for WOM marketing (Balaji et al., 2016; Li and Du, 2017; search into these strategies has been carried out by several Park et al., 2017). studies (De Pelsmacker et al., 2018; Li et al., 2018b; Peres et This paper develops an analysis of the effect of WOM al., 2010). Although diffusion modeling has been researched through viral marketing for product development. Simula- extensively, there are new potential directions that can be tion methodology is used with dynamic systems that show explored in emerging economies, web-services, social net- consumer behavior in two different time scenarios that works, and complex service product structures (Peres et al., relate to product development and the spread rate of viral 2010). For instance, the agent-based models only help to un- marketing. derstand the role knowledge plays in diffusing competitive In the following section, literature on WOM in online com- brands (Jiang et al., 2016), but do not help to understand the munities is discussed, the method, data, and results obtained complexity approach to market systems (Cosenz and Noto, are then presented. Finally, the paper concludes with a dis- 2016; Herrera-Ramírez et al., 2017). This paper carried out cussion and conclusions for managers and policy makers. a simulation model to understand brand development and the viral market effect on online communities which allows market penetration to be analyzed or adopted in complex An overview of WOM in online communities service product structures. The diffusion of technology is a process where new prod- WOM is perceived to be a credible and trustworthy tool ucts are spread within and across economies through in- and it plays an important role on the web, blogs and social novation (Korres, 2012; Lee et al., 2015; Walrave and Raven, networks which can employ several WOM activities such as: 2016). Hereby, this paper attempts to analyze market pen- community marketing, referral programs, viral marketing, etration or adoption using simulation scenarios for brand and guerrilla marketing (Agag and El-Masry, 2016; Li et al., development; this contrasts with other studies which uses 2018a; Wu et al., 2018). In this sense, WOM has an intention- dynamic structure for modeling through integrating the al influence on consumer-to-consumer communications development of products with an innovation process (Ford through marketing techniques. It is influenced by the desire and Sterman, 1998; Walrave and Raven, 2016). Our work to help others: to warn of bad experiences that consumers SUMA DE NEGOCIOS, 9(20), 77-85, Julio-Diciembre 2018, ISSN 2215-910X 79 have suffered (Balaji et al., 2016; Chu and Sung, 2015; Stand- factors are relevant in the online-based WOM, while the ing et al., 2016).
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