Purpose: This paper aims to demonstrate that online complainants' reactions to a company's service recovery attempts (webcare) can significantly vary across two different types of dissatisfied customers ("vindictives" vs "constructives"), who have dramatically diverging complaint Goal orientations. Design/methodology/Approach: Online multi-country survey among 812 adult consumers who recently had a dissatisfying brand experience and turned to a marketer-generated social media site to voice an online complaint for achieving their ultimate complaining goals. Scenario-based online experiment for cross-validating the survey findings. Findings: Results suggest that "vindictive complainants" - driven dominantly by brand-adverse motives - are immune to any form of webcare, while "constructive complainants" - interested in restoring the customer-brand relationship - react more sensitively. For the latter, "no-responses" often trigger detrimental brand-related reactions (e.g. unfavorable brand image), whereas "defensive Responses" are likely to stimulate postwebcare negative word-of-mouth. Research limitations/implications: This research identifies the gains and harms of (un-)desired webcare. By doing so, it not only sheds light on the circumstances when marketers have to fear negative effects (e.g. negative word-of-mouth) but also provides insights into the conditions when such effects are unlikely. While the findings of the cross-sectional survey are validated with an online experiment, findings should be interpreted with care as other complaining contexts should be further investigated. Practical implications: Marketers have to expect a serious "backfiring effect" from an unexpected source, namely, consumers who were initially benevolent toward the involved brand but who received an inappropriate response.

Service failure within the airline industry has been a prominent topic within the media. Each story of a failure features a disgruntled passenger. Emotions are already high during the consumption of any airline service, and a service failure will bring on а slew of unwanted emotions. The purpose of this paper is then to understand what type of relationship do these negative emotions and feelings of lack of control have after a service failure, and do any of those given emotions lead to negative word-of-mouth (NWOM). The method used to accomplish this is correlation hypothesis testing of survey results in relation to the specified negative emotions and the causal attribution theory of control, as well as analysis between the same emotions and NWOM, again using correlation tests. This aim will be achieved by breaking service failure down into five negative incidents that are referred to as service failure scenarios, namely: luggage handling, delayed/cancelled flight, missed flight due to factors beyond customers’ control, negative customer service at the airport, and negative service experience during the flight. The five scenarios are studied against six specified emotions which are anger, frustration, helplessness, nervousness, worry, and panic. The relationship between these emotions and lack of control is tested, then these same emotions are tested in regards to NWOM. The findings express a weak to moderate positive relationship between at least one of the emotions and lack of control in three of the scenarios, leading to the conclusion that customers’ lack of control over the situation increases the intensity of the emotions. In the findings for emotions and NWOM, four out of the six tested negative emotions lead to NWOM, which are anger, frustration, helplessness, and worry. This discovery proves that different emotions in different scenarios make people react in a different manner, and this leads to the conclusion that emotions should be tested separately and scenarios should be created to research the real intensity of the emotions in different situations, without grouping them into one.

Since the limitations for the presentation of information on the internet, shopping online makes consumers feel cognitive dissonance more easily compared with traditional shopping. While experiencing cognitive dissonance after shopping, consumers would search and browse the internet for word-of mouth in order to rationalize their purchase behavior. However, there seems little research for the impact on consumers¡¦ feelings by online word-of-mouth during post-purchase. Therefore, this study is going to be focused on the influence of searching online word-of-mouth on consumer post-purchase cognitive dissonance level, consumer attitudes and intention s to spread negative word-of-mouth. This study is adopted an experiment to understand the effect of reading wording-of-mouth on consumers. The degree of consumer cognitive dissonance is measured by the comparison between the difference of consumer expectation and their feelings in actual products. The word-of-mouth design is applied to content analysis to understand the actual word-of-mouth and thus this is resulted in an online word-of-mouth contented ¡§more negative messages and less positive ones¡¨. According to this research, there is no significant difference between cognitive dissonance and consumer attitude after reading the word-of-mouth in the high degree of cognitive dissonance case; nevertheless, the intention to spread negative word-of-mouth would be significantly decreased. On the other hand, in the low degree of cognitive dissonance case, after reading word-of-mouth, cognitive dissonance would be significantly increased, and consumer attitude could be significantly decreased and negative word-of-mouth intention will significantly increase.

Seguindo as linhas de pesquisa que visam relacionar o impacto do relacionamento com os clientes aos resultados financeiros da empresa, o presente estudo procura avaliar o impacto do word-of-mouth (WOM) negativo no retorno da ação da empresa. O comportamento de falar mal da empresa por parte dos consumidores insatisfeitos pode destruir o valor dos market-based assets (customer equity e brand equity), comprometendo o desempenho das ações da companhia. Considerando a literatura existente, esta pesquisa busca identificar o impacto do WOM negativo no desempenho das ações das empresas no curto e no longo prazo. O primeiro estudo replica o modelo de Luo (2007) para identificar o impacto do WOM negativo nos retornos de curto prazo da ação das empresas. O segundo estudo busca verificar o impacto de longo prazo a partir da comparação do desempenho de portfólios compostos por ações de empresas em relação ao seu nível de reclamações. Os resultados do primeiro estudo convergiram em certa medida com os resultados apresentados por Luo (2007) para o setor bancário, apontando para um impacto negativo das reclamações no retorno da ação, mas foram mistos quando as empresas foram avaliadas individualmente. O segundo estudo demonstrou que o portfólio composto por ações de empresas menos reclamadas teve um retorno acumulado superior ao portfólio composto pelas ações mais reclamadas, além de apresentar um risco inferior ao risco de mercado. As implicações e limitações do estudo são discutidas e são sugeridas pesquisas futuras a partir deste estudo. / Following previous research that seek to integrate customer relationship impact to firm value, the present study focus to assess the impact of negative word-of-mouth (WOM) on stock returns. Dissatisfied customers that spread negative WOM about the company can ruin market-based assets (customer equity and brand equity) and hurt its performance. Based on present literature, this research seeks to identify the impact of negative WOM on stocks’ short and long term performances. The first study replicates Luo’s (2007) model to identify the short term impact of negative WOM on stock performance. The second aims to identify the long term impact of negative WOM by comparing the performance of portfolios created based on companies level of complaints. The first study accomplished to partially replicate the results found by Luo (2007) for banking industry, finding a negative impact of negative WOM on firm stock returns, although it found mixed results when the impact was assessed for each company individually. The second study demonstrates that a portfolio with less complained companies has a superior performance over a portfolio with more complained companies, while presenting a risk below market’s level. The results implications and limitations are discussed and further studies suggestions are made.

Seguindo as linhas de pesquisa que visam relacionar o impacto do relacionamento com os clientes aos resultados financeiros da empresa, o presente estudo procura avaliar o impacto do word-of-mouth (WOM) negativo no retorno da ação da empresa. O comportamento de falar mal da empresa por parte dos consumidores insatisfeitos pode destruir o valor dos market-based assets (customer equity e brand equity), comprometendo o desempenho das ações da companhia. Considerando a literatura existente, esta pesquisa busca identificar o impacto do WOM negativo no desempenho das ações das empresas no curto e no longo prazo. O primeiro estudo replica o modelo de Luo (2007) para identificar o impacto do WOM negativo nos retornos de curto prazo da ação das empresas. O segundo estudo busca verificar o impacto de longo prazo a partir da comparação do desempenho de portfólios compostos por ações de empresas em relação ao seu nível de reclamações. Os resultados do primeiro estudo convergiram em certa medida com os resultados apresentados por Luo (2007) para o setor bancário, apontando para um impacto negativo das reclamações no retorno da ação, mas foram mistos quando as empresas foram avaliadas individualmente. O segundo estudo demonstrou que o portfólio composto por ações de empresas menos reclamadas teve um retorno acumulado superior ao portfólio composto pelas ações mais reclamadas, além de apresentar um risco inferior ao risco de mercado. As implicações e limitações do estudo são discutidas e são sugeridas pesquisas futuras a partir deste estudo. / Following previous research that seek to integrate customer relationship impact to firm value, the present study focus to assess the impact of negative word-of-mouth (WOM) on stock returns. Dissatisfied customers that spread negative WOM about the company can ruin market-based assets (customer equity and brand equity) and hurt its performance. Based on present literature, this research seeks to identify the impact of negative WOM on stocks’ short and long term performances. The first study replicates Luo’s (2007) model to identify the short term impact of negative WOM on stock performance. The second aims to identify the long term impact of negative WOM by comparing the performance of portfolios created based on companies level of complaints. The first study accomplished to partially replicate the results found by Luo (2007) for banking industry, finding a negative impact of negative WOM on firm stock returns, although it found mixed results when the impact was assessed for each company individually. The second study demonstrates that a portfolio with less complained companies has a superior performance over a portfolio with more complained companies, while presenting a risk below market’s level. The results implications and limitations are discussed and further studies suggestions are made.

Seguindo as linhas de pesquisa que visam relacionar o impacto do relacionamento com os clientes aos resultados financeiros da empresa, o presente estudo procura avaliar o impacto do word-of-mouth (WOM) negativo no retorno da ação da empresa. O comportamento de falar mal da empresa por parte dos consumidores insatisfeitos pode destruir o valor dos market-based assets (customer equity e brand equity), comprometendo o desempenho das ações da companhia. Considerando a literatura existente, esta pesquisa busca identificar o impacto do WOM negativo no desempenho das ações das empresas no curto e no longo prazo. O primeiro estudo replica o modelo de Luo (2007) para identificar o impacto do WOM negativo nos retornos de curto prazo da ação das empresas. O segundo estudo busca verificar o impacto de longo prazo a partir da comparação do desempenho de portfólios compostos por ações de empresas em relação ao seu nível de reclamações. Os resultados do primeiro estudo convergiram em certa medida com os resultados apresentados por Luo (2007) para o setor bancário, apontando para um impacto negativo das reclamações no retorno da ação, mas foram mistos quando as empresas foram avaliadas individualmente. O segundo estudo demonstrou que o portfólio composto por ações de empresas menos reclamadas teve um retorno acumulado superior ao portfólio composto pelas ações mais reclamadas, além de apresentar um risco inferior ao risco de mercado. As implicações e limitações do estudo são discutidas e são sugeridas pesquisas futuras a partir deste estudo. / Following previous research that seek to integrate customer relationship impact to firm value, the present study focus to assess the impact of negative word-of-mouth (WOM) on stock returns. Dissatisfied customers that spread negative WOM about the company can ruin market-based assets (customer equity and brand equity) and hurt its performance. Based on present literature, this research seeks to identify the impact of negative WOM on stocks’ short and long term performances. The first study replicates Luo’s (2007) model to identify the short term impact of negative WOM on stock performance. The second aims to identify the long term impact of negative WOM by comparing the performance of portfolios created based on companies level of complaints. The first study accomplished to partially replicate the results found by Luo (2007) for banking industry, finding a negative impact of negative WOM on firm stock returns, although it found mixed results when the impact was assessed for each company individually. The second study demonstrates that a portfolio with less complained companies has a superior performance over a portfolio with more complained companies, while presenting a risk below market’s level. The results implications and limitations are discussed and further studies suggestions are made.

abstract: When consumers find that something critically out of the ordinary has occurred, they direct attention to evaluate such a critical incident more closely. The results of this evaluation may put consumers on a switching path or it might lead them to engage in unfavorable behaviors from the perspective of the organization, such as engaging in negative word-or-mouth online. The negative consequences of some product (goods or services) failures go beyond simple product attribute defects, leading customers to terminate the relationship with the organization. This dissertation, which is composed of three essays, investigates how consumers engage in negative word-of-mouth on social media channels in response to their various product failures and explores an important relationship event of betrayal, which can be triggered by certain product failures. It investigates how betrayal is perceived by customers and influences a range of their behaviors across business-to-consumer and business-to-business contexts. / Dissertation/Thesis / Doctoral Dissertation Business Administration 2019

網際網路興起與行動裝置普及後，人們越來越容易在各大社群媒體、討論區留下評論。其中，本來就影響甚大的負面口碑，結合了網路驚人的散步速率和廣大接觸群眾的特性，轉變為影響更為巨大的網路負面口碑。 過往有許多針對負面口碑的研究，這些研究大多面向一般企業，卻鮮少有研究針對公眾人物。然而，同時也有許多研究指出，許多企業會與公眾人物合作，而公眾人物自身做為容易被社會關注的目標，負面口碑有可能對其職業生涯與形象造成不良影響，故希望能針對網路負面口碑之於公眾人物的留言動機、內容以及解決方式研究。 本研究著重個案分析，我們將從PTT，全台灣知名的網路討論板，找尋針對個案中公眾人物評論，並且分析留言的措辭與內容，歸納留言者的動機、該負面留言的內容類型。並從網路上蒐集該公眾人物處理該負面網路口碑的資訊，分析其策略。 最終，本研究將歸納整理出動機、留言內容與公眾人物使用的策略，為未來在這塊學術領域有興趣繼續研究的同好們提供一個基礎，並為公眾人物以及其公關團隊避免與解決網路負面口碑提供建議與方針。 / Since the rise of social media and the spread of mobile devices, sharing comments, advice and information with people on the internet without the constraints of time and space has become part of modern life and has resulted in major changes to how people receive information. Because of these changes, one particular issue has become more important than before: the influence of electronic word of mouth (EWOM), especially the negative type. Word of mouth has long been a topic of research, and researchers have found that negative word of mouth (NWOM) can have a greater impact than positive or neutral word of mouth. Furthermore, EWOM can spread faster and wider than traditional WOM. Thus, if negative word of mouth were spread via electronic channels such as social media on internet, it can cause unimaginable damage to the target individual or organization. To date, few studies focus on public figures’ negative EWOM. However, public figures play important roles in many areas because of their high attention from society and may sometimes be the target of negative EWOM. Based on the above, this study seeks answers to the following questions: Why do people on the internet reply negatively to the target public figures (negative EWOM motivation)? What types of negative content do people on the internet generate toward the public figures? What types of strategies may be applied to deal with different types of negative EWOM and negative EWOM motivation more frequently? This study first searched and reviewed previous literature related to NWOM, EWOM and public figures and categorized a few motivation, types of negative content and strategies. We then chose twenty case studies, and collected comments about these twenty cases on PTT, the largest terminal-based bulletin board system (BBS) based in Taiwan. Based on the using words of these comments, we can find out new motivation and new types of negative content did not exist in previous literature. Furthermore, we tracked how these public figures deal with NWOM, and tried to find out new patterns of strategies. The research results can help managers and researchers prevent crises caused by negative EWOM or take appropriate approaches for these crises. Keywords: Negative Word of Mouth, Electronic Word of Mouth, Public Figures

在這網路發達的世界，電子口碑(electronic word of mouth)一直以來都是學術界研究的重點。電子口碑分成正面跟負面，尤其以負面電子口碑備受關注，因為這會帶給企業難以估計的傷害。而在2014年，開始有學者提出了網路風暴(online firestorm)的新名詞，描述在現代社群網路下，負面口碑在網路上突然大量流傳的現象。 關於網路風暴的文獻相當少，但在台灣2014年舉辦的九合一選舉中，可以看出網路風暴對選情的影響之大，我們觀察到某些候選人可以藉由應對來有效控制情勢，但有些回應卻會讓負面口碑風暴越趨惡化，因此我們想要探究這之間的問題所在。所以本研究首先透過文獻了解口碑風暴的定義，從而利用文獻推斷出口碑風暴形成過程。並以Google Trend設計出衡量口碑風暴的方式，以此找出選舉中符合口碑風暴標準的負面口碑案例。之後把案例分成三種情境，每種情境以兩個不同候選人的個案為例，把從Opview收集到的負面口碑資料套用在設計出的公式裡來判斷選舉人的應對有效與否。選舉人的應對則會利用Benoit印象修復理論來做進一步說明。最後，由於此篇研究是以選舉中的口碑風暴為主，因此我們會把選舉中的口碑風暴與傳統商業中的口碑風暴做比較，來看兩者間有何不同或相同之處。 / During the political election period in Taiwan in Nov. 2014, this study observed significant effects caused by online firestorms: some candidates used appropriate responses to mitigate their effects or minimize the harm, some turned negative into positive support of their brand, but some candidates were unable to manage the crisis and lost their brand value. To date, few studies have noted the importance of negative WOM (NWOM) management in political election campaigns. Nor have studies noted the effects of online firestorms on brand value. This study undertakes research to seek answers to the following research questions: What is the uniqueness of online firestorms in a political election? And, how do candidates respond the online firestorm to retain brand value? This study initially reviewed the literature on negative WOM and online firestorm, and consolidated these studies to formulate the forming process of an online firestorm. Then the study classified online political election firestorm cases into three categories including fault, defect, and counterforce slander, and analyzed the best responses in each situation. Next, the study applied Google Trend to measure the online firestorm and referred image restoration theory to form an understanding of the response of a brand manager. The study results show that for fault situation, the most useful strategies seem to be mortification, minimization the offensive feeling, and ignoring to respond to most offensive accusations. For defect situation, the most used strategies are insisting the main opinion and using attack strategy to evade the most offensive accusations. Last, for counterforce slander situation, most candidates used full denial, blame shifting and accuser attack strategies to prove their innocence. Finally, the study further distinguished the difference between conventional business online firestorm and political elections online firestorm from several angles which include: online firestorm targets, causes, consumer reactions, initiatives, effects and dissemination.

口碑一直以為都是企業行銷的重要利器，而同時也是要害之一，且隨著網路的發達和社群網路的發展，對企業的影響也越來越大。而近幾年在媒體中開始出現一個新名詞，用來形容負面口碑在社群媒體中傳播的現象-線上口碑風暴(Online Firestorm)。 線上口碑風暴的相關研究相當的稀少，而在許多口碑的相關研究中也未多著墨，但隨著社群媒體的發展，此現象已越來越普遍，因此有研究探討的價值，所以在本研究中將先定義出線上口碑風暴，並以Google搜尋趨勢設計出測量線上口碑風暴的方式，以利將其從負面口碑的傳播分辨出來，並利用這樣的方法找出六個線上口碑風暴的個案來進行研究，配合Coombs的印象修復理論來進一步分析。 研究結果發現，可以將線上口碑風暴依成因分成「過去不好的服務或產品體驗」、「錯誤的時機情境」和「不適當的聲明或宣傳」，而各類別的最佳回應策略在文中有詳細講述。另外，當企業使用的回應策略越多時，線上口碑風暴持續的時間就可能越久。影響線上口碑風暴的因素有很多，經本研究的討論分析後，發現「負面訊息傳播的平台」、「回應策略的運用」和「企業的規模和性質」為最會影響線上口碑風暴的因素。 / Word-of-Mouth (WOM) has been a major marketing tool to the enterprise, but could also be one of its threats. With the development of the Internet and social networks, the impact of WOM on enterprises is also growing. In recent years, the rapid propagation of negative Word-of-Mouth in social media has gained much attention in media and is named “Online Firestorm.” Academic studies about Online Firestorm are rare, and researchers of Word-of-Mouth have not investigated it. Giving the development of social media, this phenomenon has become increasingly common. Therefore it is important for companies to know and better handle it and for researchers to investigate this new issue. In this study, we will define and measure Online Firestorm though Google Trends. We will also collect data from six cases and analyze how different responding strategies may result in different outcomes. Research found that Online Firestorm can be categorized into “past bad service or prouduct experience”, “bad timing scenarios” and “inappropriate statements or propaganda” according to the causes of the storm. The best response strategies to all kinds are described in the text. In addition, when used more response strategies, Online Firestorm duration may longer. There are many factors affecting the Online Firestorm, after the discussion and analysis found that "negative information dissemination platform", "the using of response strategies" and "the scale and nature of the enterprises" and as the factors that most likely to affect the Online Firestorm.