• Title/Summary/Keyword: Social Media Impact

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Effects of Storytelling in Advertising on Consumers' Empathy

  • Park, Myungjin;Lee, Doo-Hee
    • Asia Marketing Journal
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    • v.15 no.4
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    • pp.103-129
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    • 2014
  • Differentiated positioning becomes increasingly difficult when brand salience weakens. Also, the daily increase in new media use and information load has led to a social climate that regards advertising stimuli as spamming. For these reasons, the focus of advertisement-related communication is shifting from persuading consumers through the direct delivery of information to an emphasis on appealing to their emotions using matching stimuli to enhance persuasion effects. Recently, both academia and industry have increasingly shown an interest in storytelling methods that can generate positive emotional responses and attitude changes by arousing consumers' narrative processing. The purpose of storytelling is to elicit consumers' emotional experience to meet the objectives of advertisement producers. Therefore, the most important requirement for storytelling in advertising is that it evokes consumers' sympathy for the main character in the advertisement. This does not involve advertisements directly persuading consumers, but rather, consumers themselves finding an answer through the advertisement's story. Thus, consumers have an indirect experience regarding the product features and usage through empathy with the advertisement's main character. In this study, we took the results of a precedent study as the starting point, according to which consumers' emotional response can be altered depending on the storytelling methods adopted for storytelling ads. Previous studies have reported that drama-type and vignette-type storytelling methods have a considerably different impact on the emotional responses of advertising audiences, due to their different structural characteristics. Thus, this study aims to verify that emotional response aroused by different types of advertisement storytelling (drama ads vs. vignette ads) can be controlled by the socio-psychological gender difference of advertising audiences and that the interaction effects between the socio-psychological gender differences of the audience and the gender stereotype of emotions to which advertisements appeal can exert an influence on emotional responses to types of storytelling in advertising. To achieve this, an experiment was conducted employing a between-group design consisting of 2 (storytelling type: drama ads vs. vignette ads) × 2 (socio-psychological gender of the audience: masculinity vs. femininity) × 2 (advertising appeal emotion type: male stereotype emotion vs. female stereotype emotion). The experiment revealed that the femininity group displayed a strong and consistent empathy for drama ads regardless of whether the ads appealed to masculine or feminine emotions, whereas the masculinity group displayed a stronger empathy for drama ads appealing to the emotional types matching its own gender as well as for vignette ads. The theoretical contribution of this study is significant in that it sheds light on the controllability of the audiences' emotional responses to advertisement storytelling depending on their socio-psychological gender and gender stereotype of emotions appealed to through advertising. Specifically, its considerable practical contribution consists in easing unnecessary creative constraints by comprehensively analyzing essential advertising strategic factors such as the target consumers' gender and the objective of the advertisement, in contrast to the oversimplified view of previous studies that considered emotional responses to storytelling ads were determined by the different types of production techniques used. This study revealed that emotional response to advertisement storytelling varies depending on the target gender of and emotion type appealed to by the advertisement. This suggests that an understanding of the targeted gender is necessary prior to producing an advertisement and that in deciding on an advertisement storytelling type, strategic attention should be directed to the advertisement's appeal concept or emotion type. Thus, it is safe to use drama-type storytelling that expresses masculine emotions (ex. fun, happy, encouraged) when the advertisement target, like Bacchus, includes both men and women. For brands and advertisements targeting only women (ex. female clothes), it is more effective to use a drama-type storytelling method that expresses feminine emotions (lovely, romantic, sad). The drama method can be still more effective than the vignette when women are the main target and a masculine concept-based creative is to be produced. However, when male consumers are targeted and the brand concept or advertisement concept is focused on feminine emotions (ex. romantic), vignette ads can more effectively induce empathy than drama ads.

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Spatial effect on the diffusion of discount stores (대형할인점 확산에 대한 공간적 영향)

  • Joo, Young-Jin;Kim, Mi-Ae
    • Journal of Distribution Research
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    • v.15 no.4
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    • pp.61-85
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    • 2010
  • Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown

    . In a result of the Bass model(I), the estimates of innovation coefficient(p) and imitation coefficient(q) are 0.017 and 0.323 respectively. While the estimate of market potential is 384. A result of the Bass model(II) for each district shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. A result of the Bass model(II) shows the estimates of innovation coefficient(p) in SG is 0.019 and the lowest among 5 areas. This is because SG is the diffusion center. The estimates of imitation coefficient(q) in BG is 0.353 and the highest. The imitation coefficient in the vicinity of the diffusing center such as BG is higher than that in the diffusing center because much information flows through various paths more as diffusion is progressing. In a result of spatial diffusion model(IV), we can notice the changes between coefficients of the bass model and those of the spatial diffusion model. Except for GJ, the estimates of innovation and imitation coefficients in Model IV are lower than those in Model II. The changes of innovation and imitation coefficients are reflected to spatial coefficient(${\gamma}$). From spatial coefficient(${\gamma}$) we can infer that when the diffusion in the vicinity of the diffusing center occurs, the diffusion is influenced by one in the diffusing center. The difference between the Bass model(II) and the spatial diffusion model(IV) is statistically significant with the ${\chi}^2$-distributed likelihood ratio statistic is 16.598(p=0.0023). Which implies that the spatial diffusion model is more effective than the Bass model to describe diffusion of discount stores. So the research question (1) is supported. In addition, we found that there are statistically significant relationship between similarity of retail environment and spatial effect by using correlation analysis. So the research question (2) is also supported.

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