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The Antecedents of Negative e-WOM and Their Effects on Purchasing Intention of Energy Drinks: An Empirical Study in Indonesia

  • Received : 2021.03.20
  • Accepted : 2021.06.01
  • Published : 2021.07.30

Abstract

The aim of this study is to fill gaps in emerging empirical evidence and negative electronic word of mouth (NeWOM) in repurchase intention (RI) moderated by the roles of social network sites (SNS) and company mitigation response (CMR). This type of research is descriptive. The sample used in this study is online consumers who buy energy drinks, based on the questionnaire obtained by 145 respondents. Based on the results of testing the estimation of the structural equation model, it was found that the negative variable brand experience sharing had no significant effect on NeWOM; the negative variable electronic reviews had a significant effect on the electronic word of mouth variable, the negative variable electronic reviews had a significant effect on the negative electronic variable word of mouth, the variable intensity of the use of social networking sites can strengthen the direction of the causal influence between the negative variables sharing brand experiences on negative electronic words of mouth. The variable social networking sites usage intensity can strengthen the direction of the effect of causality between negative electronic review variables on negative electronic word of mouth, the negative brand experience sharing variable does not have a significant effect on the repurchase intention variable.

Keywords

1. Introduction

Technological developments do not always have a good impact, various negative impacts also often appear. Many think that all the information that is spread on social networking sites (SNS) or the Internet has become an important source of information for consumers because of the accessibility, speed and volume of information obtained. Consumers rely on information from others in order to make purchasing decisions, especially in uncertain situations (Mitchell & McGoldrick, 1996). Consumers not only seek medical information electronically and use word of mouth (WOM) from other consumers who have the same problem or have related experiences, but also share their experiences, opinions and knowledge with other consumers on SNS, for example, the viral message circulating on SNS such as Facebook regarding a list of dangerous drinks that can trigger brain cancer, diabetes, and hardening of the spinal cord. Some negative news about the dangers of aspartame, which causes brain cancer, diabetes, and hardening of the spinal cord, are also spread by many social communities via electronic media, electronic communities, electronic customer reviews, SNS include WhatsApp groups, Facebook, electronic media, blogs, and others.

In recent years, the energy drink market has continued to decline. This is indicated by the market growth, which is stagnant, even decreasing every year. According to research from a marketing intelligence company in 2019, the energy drink market in America and Australia experienced a slight decline of 0.5%.

In Indonesia, the decline in sales of energy drink products reached 5.5%. Several energy drink products in Indonesia such as extrajoss decreased by 8.3%, Kuku Bima by 9.9%, Hemaviton by 12.8%, Ejuss by 65.5%, Ena’o by 1.9%, and Proman by 88.8%.

The downward trend in energy drink products arises from the negative stigma attached in the minds of consumers due to the spread of negative news on SNS called negative electronic word of mouth (NeWOM), which has negative origins brand experience sharing (NBES) and negative electronic reviews (NER), so that a company mitigation response (CMR) is needed to produce repurchase intention (RI) of energy drink products (Budiman, 2021; Ilyas et al., 2020).

The Internet has changed the way customers can express their dissatisfaction with the company and their ability to mobilize mass audiences against the company. This suggests that customer complaints change, from the private realm to a public phenomenon. Ortiz et al. (2014) state that SNS is one of the earliest and best examples of customers who take advantage of the new power offered by the Internet. For that reason, it can be concluded that SNS has intensified customer empowerment and their ability to complain to the world.

The effects of NeWOM can include forming negative attitudes, switching to other products, and reducing RIs. These results can have a negative impact on the company. It is possible that companies will lose their reputation and have lower revenue due to negative messages from eWOM (Kakirala & Singh, 2020). However, if consumers do not intend to receive the message, nothing will change even if they are exposed to the NeWOM message. Therefore, information adoption is essential to estimate the NeWOM effect. Based on research conducted by Kakirala and Singh (2020), NeWOM is adopted as a readiness for information and an intention to rely on NeWOM messages.

Many cases where comments and posts on social networking sites show the influence of eWOM and also the interconnected consumer power of technology (Pfeffer et al., 2014). The first blog post served to build a theoretical understanding of changing the paradigm of WOM and customer power with a major focus on NeWOM.

This study reviews repurchase intention (RI), company mitigation responses (CMR), negative electronic word of mouth (NeWOM), social networking sites (SNS), negative brand experience sharing (NBES), negative electronic reviews (NER), and energy drink products in Indonesia.

2. Literature Review and Hypotheses

2.1. Relationship Between NBES and NeWOM Characteristics for Energy Drink Products

Based on research by Zhou et al. (2019), sharing negative experiences usually has a greater impact on users than sharing positive experiences. Consumers who share negative experiences about a product usually expect positive responses from others, although sharing negative experiences has the risk of being criticized and criticized (Guo & Turan, 2016). Sharing through NeWOM was found to be related to online support activities such as helping others and sharing information that will strengthen feelings such as self- affirmation. Consumers can engage in NeWOM to draw attention to problems that cause consumer dissatisfaction with the aim of finding solutions or as a method of reducing anxiety through venting negative emotions (Lin et al., 2018). We can examine the relationship between the characteristics of NBES and NeWOM for energy drink products with the following hypothesis:

H1: The characteristics of NBES have a positive effect on NeWOM for energy drink products.

2.2. Relationship Between NER and NeWOM Characteristics for Energy Drink Products

Based on research by Balaji et al. (2016), the influence of online consumer reviews on companies and on readers, especially NERs posted on SNS, can affect companies such as decreasing sales and can influence readers to affect other readers about a certain product. EWOM communication via SNS can go viral because it can reach many audiences in a short time. It is very important for companies to understand how to respond to NER and minimize product deterioration and degradation as a result. Bae and Lee (2011) found that potential consumers perceive NER to be more useful and informative than positive reviews, and the extent to which NER reduces the number of purchases is higher than the effect of positive reviews on increasing the number of purchases. We can examine the relationship between the characteristics of NER and NeWOM for energy drink products with the following hypothesis:

H2: The characteristics of NER have a negative effect on NeWOM for energy drink products.

2.3. The relationship Between NBES and NeWOM Characteristics is Getting Stronger if the SNS is Bigger for Energy Drink Products

Balaji et al. (2016) found that the influence of online consumer reviews on companies and on readers, especially NERs posted on SNS, can affect companies such as decreasing sales and can influence readers to influence other readers about a certain product. EWOM communication via SNS can go viral because it can reach many audiences in a short time. It is very important for companies to understand how to respond to NER and minimize product deterioration and degradation as a result. Hennig-Thurau et al. (2004) found that potential consumers perceive NER to be more useful and informative than positive reviews, and the extent to which NER reduces the number of purchases is higher than the effect of positive reviews on increasing the number of purchases. The relationship between the characteristics of NBES and NeWOM is getting stronger if the SNS is greater for energy drink products, so we can test the following hypothesis:

H3: The positive effect of NBES on NeWOM is getting stronger if the SNS is greater for energy drink products.

2.4. The relationship Between NER and NeWOM Characteristics is Getting Stronger if the SNS is Getting Bigger for Energy Drink Products

In the research by Hennig-Thurau et al. (2004), NER has a greater impact than positive online reviews. This finding can be attributed to the effect of negativity (Lee & Cranage, 2007). In an attempt to illustrate this effect, Lee and Cranage (2007) stated that, when consumers got NER from other consumers, they tended to see the product as low quality. Conversely, online reviews that are positive or neutral tend to be less useful in determining the perceived quality of a product. NER is considered to be more accurate for decision-making purposes (Chan & Ngai, 2011). Similar studies have supported this view by showing that negative messages have a stronger influence on brand evaluation and purchase intentions (Lafferty et al., 2002). Consumers are happy to find the latest information and rely on reviews from previous users before buying, this causes WOM to play an important role in formulating product evaluations in buying decisions, NER can also influence the decision to buy a product (Chan & Ngai, 2011). The relationship between the characteristics of NER and NeWOM is getting stronger if the SNS is greater for energy drink products, we can test the following hypotheses:

H4: The positive effect of NER and NeWOM is getting stronger if the SNS is greater for energy drink products.

2.5. Relationship Between NeWOM and RI Characteristics for Energy Drink Products

Without a NeWOM message from consumers, the company would not have realized that there was a problem with its product. Research by Kim et al. (2015) shows that successful CMR can lead to positive consequences, such as RI, positive WOM (Prayogo & Kusumawardhani, 2017), and trusting relationships. RI is the main basis for explaining consumer repurchase behavior. Research by Chiu et al. (2009) explains that repurchasing is a subjective possibility that someone will buy a product in the future. Based on research by Jiang and Rosenbllom (2005), it is also explained that consumers doing RI is a behavior or intention that is useful for business continuity. RI is a consumer commitment that is formed after a consumer purchases a product or service. This commitment arises from consumer impressions of a product purchased. The impact of NeWOM, such as being able to form negative attitudes from individuals, switching to other products, and reducing the repurchase intention of a product has a negative impact on the company (Chang & Wang, 2011). We can examine the relationship between the characteristics of NeWOM and RI energy drink products with the following hypothesis:

H5: NeWOM characteristics have a negative effect on RI for energy drink products.

2.6. The relationship Between the Characteristics of NeWOM and RI will weaken if the CMR is Greater for Energy Drink Products

The growing influence of electronic evaluation on consumer behavior has increased managerial interest and corporate research on CMR strategies that can reduce transmission of NeWOM (Ma et al., 2015). Companies need to show exactly how to respond to NeWOM messages that are scattered on SNS (Chevalier et al., 2018). Several studies have suggested to approach consumers with empathic responses and explanations. Companies need to formulate responses that can minimize negative effects. Responses involving the company can also include substantiated explanations, and the number of reasons offered is more influential than the content of the reasons for the decision (Seibold et al., 2010). When the company provides a more substantive argument, it can increase perceived quality and response effort among audiences in the electronic product community (e.g., “We can’t help you quickly because the store is very busy”). By providing more explanations, firms can improve their CMR evaluation. Needs in the research of effective CMR strategies can influence future consumer behavior such as future repurchase intentions (Swanson & Kelley, 2001). In previous studies, it was agreed that five general results from NeWOM – dissatisfaction, complaints, switching to other products, negative messages, and stopping buying – required efforts to increase consumer perception and increase consumer loyalty. The relationship between the characteristics of NeWOM and RI is getting stronger if the CMR is greater for energy drink products, we can test the following hypotheses:

H6: The negative effect of NeWOM on RI weakens if the CMR is greater for energy drink products.

2.7. Relationship Between the Characteristics of NBES and RI for Energy Drink Products

Based on the findings by Zarantonello and Schmitt (2010), the experience of sharing information about a product is an important factor that encourages relationships between consumers and companies, such as customer satisfaction and consumer loyalty, which can be positive or negative. When consumers experience unpleasant experiences, consumers often express their emotions on SNS and share stories with other consumers to ease the burden caused by their negative experiences about products (Zhou et al., 2019). Therefore, NBES is the behavior that consumers share and communicate with others about the negative feelings or attitudes they experience. The increased use of SNS such as online forums creates many opportunities for consumers to share these experiences. We can examine the relationship between the characteristics of NBES and RI for energy drink products with the following hypothesis:

H7: The characteristics of NBES have a negative effect on RI for energy drink products.

2.8. Relationship Between NER and RI Characteristics for Energy Drink Products

Online reviews distributed by consumers on SNS have become the main source of information for potential consumers and marketers regarding the quality or information of a product, these reviews can represent eWOM as a whole and have a strong influence on the decision-making process of other potential consumers. Prospective consumers are more likely to rely on recommendations from consumers than marketers (Enginkaya & Yilmaz, 2014). Enginkaya and Yilmaz (2014) found that the influence of online consumer reviews on companies and on readers, especially NERs posted on SNS, can affect companies such as decreasing sales and can influence readers to affect other readers about a certain product. Bae and Lee (2011) found that potential consumers perceive NER to be more useful and informative than positive reviews, and the extent to which NER reduces the number of purchases is higher than the effect of positive reviews on increasing the number of purchases. We can examine the relationship between the characteristics of NER and RI for energy drink products with the following hypothesis:

H8: The characteristics of NER have a negative effect on RI for energy drink products.

3. Research Methods

Awareness of the importance of the influence of social networking sites (SNS) and company mitigation responses (CMR) is not only aimed at maintaining consumers to faithfully use the product, but also to increase the repurchase intention (RI) of energy drink products. The impact of negative electronic word of mouth (NeWOM) arising from negative brand experience sharing (NBES) and Negatives Electronic Reviews (NER) can have a negative impact on the survival of the company. Quantitative research methods are used in this study to achieve the objectives of this study.

The design of this research starts from problem formulation, data collection, and then data processing to the preparation of research reports. This type of research is descriptive and verification. The area of this research is limited to the energy drink business environment in Central Java. The selection of the Central Java region was chosen because the rate of decline was the highest compared to other regions in Indonesia, which was −74%. Based on the above calculations, the minimum sample can be used using 145 samples of respondents.

4. Results and Discussion

The number of respondents who filled out the questionnaire consisted of 167 men and 60 women, as many as 214 respondents had SNS while only 13 respondents did not have SNS, indicating that 56% of respondents consumed the Kuku Bima Ener-G brand, namely, 128 respondents, 70 respondents chose the brand Extra Joss, 26 respondents chose the Hemaviton brand, two respondents chose E-Juss, and one respondent chose the Proman brand.

4.1. Goodness of Fit Index Full Model

The goodness of fit index test is used to determine whether the model built has met the fit criteria or not. To find out this test, several suitability indices and cut-off values are needed which are then used in testing a model. Sarstedt et al. (2014) provide a guideline to consider whether or not modifications to a model are needed, by looking at the number of residuals generated in the model. Some of the suitability indices and their cut-off values are used in testing whether a model can be accepted or rejected as described in Table 1.

Table 1: Goodness of Fit Index

OTGHEU_2021_v8n7_341_t0001.png 이미지

Based on the results of the goodness of fit index test as presented above, it can be explained that the values of GFI, IFI, TLI, NFI and CFI are close to the cut-off value or close to 1. This shows that the analysis results are getting closer to the value of 1, indicating there is a very good fit. Although the results of the value of this research model still have not reached the recommended fit (cut-off value). The conclusion that can be drawn in this testing model is that this research model is feasible to use.

So, based on the results of hypothesis testing with structural equation modeling analysis, it can be presented in the form of an image to understand what direction of causality has a significant effect and which one is not significant, either directly or indirectly, as presented in Figure 1.

OTGHEU_2021_v8n7_341_f0001.png 이미지

Figure 1: Hypothesis Testing Results with Structural Equation Modeling

4.2. Discussion

Based on the research results, it can be concluded that there are several solutions. The results of the data processing show that the following are the results of hypothesis testing as presented below.

The negative effect of brand experience sharing on negative electronic words of mouth

Based on the test results of the structural equation modeling parameter, the critical ratio value is −1.016 ≤ 1.96 with a significance probability value of 0.310 ≥ α significance of 0.05. It can be interpreted that the negative variable brand experience sharing does not have a significant effect on the negative variable electronic words of mouth. The results of this study are in accordance with the results of research conducted by Van and Willemsen (2012) who said that negative brand experience sharing has a significant effect on negative electronic words of mouth.

The effect of negative electronic reviews on negative electronic words of mouth

Based on the test results of the structural equation modeling parameter, the critical ratio value is 1.9 ≥ 1.9 with a significance probability value of 0.05 ≤ α significance of 0.05. It can be interpreted that the negative electronic reviews variable has a significant effect on the negative variable electronic words of mouth. Kietzmann and Canhoto (2013) said that companies must immediately respond positively to negative reviews submitted by consumers electronically in order to create an atmosphere of good marketing relations between consumers and companies. In addition, companies must respond quickly and make efforts to respond to these negatives rather than ignoring negative reviews from consumers, which of course will have a negative impact on the company’s survival (business survival).

The influence of social networking sites use intensity in moderating negative brand experience sharing on negative electronic words of mouth

Based on the test results of the structural equation modeling parameter, the critical ratio value is 2.149 ≥ 1.96 with a significance probability value of 0.032 ≤ α significance of 0.05. It can be interpreted that the social networking sites use intensity variable can strengthen the direction of the causal effect between the negative brand experience sharing variables on the negative electronic words of mouth. The results of this study are in accordance with the results of research conducted by Balaji et al. (2016), which state that social networking sites use intensity can moderate negative effects brand experience sharing of negative electronic words of mouth, either directly or indirectly.

The influence of social networking sites use intensity in moderating negative electronic reviews on negative electronic words of mouth

Based on the test results of the structural equation modeling parameter, the critical ratio value is 3.140 ≥ 1.96 with a significance probability value of 0.002 ≤ α significance of 0.05. It can be interpreted that the social networking sites use intensity variable can strengthen the direction of the causality effect between the negative electronic review variables on negative electronic words of mouth. The results of this study are in accordance with the results of research conducted by Balaji et al. (2016), which said that the variable social networking sites usage intensity can moderate the effect of negative electronic reviews on negative electronic words of mouth, either directly or indirectly.

The negative effect of brand experience sharing on repurchase intention

Based on the test results of the structural equation modeling parameter, the critical ratio value is 1.296 ≤ 1.96 with a significance probability value of 0.195 ≥ α significance of 0.05. It can be interpreted that the negative brand experience sharing variable does not have a significant effect on the repurchase intention variable. The results of this study are inconsistent with the results of research conducted by Liang et al. (2017), which say that the negative brand experience sharing variable has a significant effect on repurchase intention.

The effect of negative electronic reviews on repurchase intention

Based on the test results of the structural equation modeling parameter, the critical ratio value is 2.319 ≥ 1.96 with a significance probability value of 0.020 ≤ α significance of 0.05. It can be interpreted that the negative electronic reviews variable has a significant effect on the repurchase intention variable. The results of this study are in accordance with the results of research conducted by Wang and Mattila (2011), which states that the Internet has changed consumer behavior patterns and their life styles in analyzing the products offered by the company. When consumers experience negative experiences, companies usually offer something in the form of compensation to restore the situation such as making an explanation or an apology which can have a positive impact on consumer satisfaction and product repurchase intentions. Efforts to restore unpleasant impressions experienced by consumers are very important in maintaining consumer feelings about the negative experiences they have experienced.

The negative effect of electronic words of mouth on repurchase intention

5. Conclusion

Based on the test results of the structural equation modeling parameter, the critical ratio value is −0.103 ≤ 1.96 with a significance probability value of 0.918 ≥ α significance of 0.05. It can be interpreted that the negative variable electronic words of mouth does not have a significant effect on the repurchase intention variable. The results of this study are inconsistent with the results of research conducted by Chang et al. (2013), which said that the negative variable electronic words of mouth has a significant effect on repurchase intention.

The influence of company mitigation responses in moderating negative electronic words of mouth on repurchase intention

Based on the results of testing the structural equation modeling parameters, the critical ratio value is 2.708 ≥ 1.96 with a significance probability value of 0.007 ≤ α significance of 0.05. It can be interpreted that the company mitigation responses variable can moderate the negative electronic words of mouth variable on repurchase intention. The results of this study are in accordance with the results of research conducted by Liang et al. (2018), which states that the variable company mitigation responses can moderate negative electronic words of mouth on repurchase intention, either directly or indirectly.

5. Conclusion

Based on the results of testing the estimation of the structural equation modeling, it is found that the negative variable brand experience sharing does not have a significant effect on the negative variable electronic words of mouth, the negative electronic reviews variable has a significant effect on the negative variable electronic words of mouth, the social networking sites variable. Usage intensity can strengthen the direction of the effect of causality between the negative variable brand experience sharing on negative electronic words of mouth, the social networking sites usage intensity variable can strengthen the direction of the effect of causality between the negative electronic review variables on the negative electronic words of mouth a significant influence on the repurchase intention variable, the negative electronic reviews variable has a significant effect on the repurchase intention variable, the negative electronic variable words of mouth do not have a significant effect on the repurchase intention variable and the company mitigation responses variable can moderate the negative electronic words of mouth variable on repurchase intention.

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