The Effect of Word-of-Mouth on Purchase Intention: A Case Study of Low-Cost Carriers in Indonesia

Abstract

This study aims at testing word-of-mouth (WOM) by mediating positive and negative perceptions of purchase intention on low-cost carriers (LCC) flights in Indonesia. One of the communications mixes that airlines can carry out is WOM. WOM is a form of communication between passengers after using a flight. The formation of a positive perception of WOM is expected by airlines. If a positive perception of WOM has formed, a purchase intention will arise. The study population included LCC flight passengers in Indonesia, involving 387 respondents. For indicators and variables, validity and reliability tests were conducted using CFA, CR, and AVE tools. Sampling locations were Soekarno-Hatta and Kualanamu airports. Sample collection was obtained through purposive sampling, and the analytical tool used was structural equation modeling (SEM) with Lisrel. The results showed that WOM influenced purchase intention through positive and negative perceptions of WOM. It can be seen that a positive perception of WOM has a direct effect, while a negative perception of WOM has the opposite effect. In conclusion, the mediation of perceptions influences purchase intention, whether it in the same direction or the opposite ones. To conclude, WOM is an antecedent for it influences purchase intention.

1. Introduction

Air transportation is one transportation modes many people opt for. According to domestic passenger departure data from 2013–2018 in Indonesia, fluctuations occurred, and in 2013 there was a decline in the number of passengers from 73, 594, 917 to 71, 625, 696 in 2014, and after that, it increased until 2018 to 96, 652, 313 passengers. Increasing numbers of passengers is a concern for the airline industry since it reflects customers’ satisfaction to repurchase the same flight. Flight types in Indonesia can be grouped based on service quality: full service, medium service, and no-frills service. This research focuses on aviation with the concept of no-frills service in Indonesia or low-cost carriers (LCC).

The flight process, starting from looking for flight information, purchasing tickets, check-in, on-time performance, in-flight and post-flight, these concepts are the same, but what differentiates them at in-flight. The low-cost carrier concept emphasizes simple operations to minimize costs and increase efficiency (Doganis, 2010). These simple operations cause lower operating costs. Lower costs lead to cheap airfare. Apart from simple procedures, there have also been changes to the LCC concept of physical appearance, especially the seats’ distance.

Companies emphasize that the LCC concept needs to pay attention to the value for passengers so that consumers are satisfied and want to reuse. One of the values that need to be considered is on-time performance because this is required for passengers who use air transportation services. The impact of fair value for passengers can lead to positive word-of-mouth (WOM) and vice versa; if the perceived value is less, it will cause a negative WOM. Companies can design WOM as an antecedent by informing positive values for passengers.

Sajadi, Way, & Bohrer (2016) state that perceived pre-flight and in-flight service quality and perceived price fairness result in satisfaction as price fairness induces willingness to pay and loyalty (Wai et al., 2019). Airlines with low-fare concept need to pay attention to service quality considering its influence on satisfaction (Ardani, Rahyuda, Giantari, & Sukaatmadja, 2019; Soelasih, 2015; Tjahjaningsih, Ningsih, & Utomo, 2020; Yang, Shih, Nha, & Wang, 2017).

Value for money affects satisfaction (Ban & Kim, 2019) in airline industry because customers correlate what they receive and what they pay or perceived value (Yang et al., 2017). Perceived value for money will lead to recommendations (Šebjan, Tominc, & Širec 2017). Recommendations stimulate WOM for customers. Ahmadi (2019) affirmed that service convenience influences WOM through service quality and customer satisfaction in the airline industry in Thailand. Suki (2014) stated that empathy influences WOM through customer satisfaction, while tangible airlines and tangible terminals do not influence WOM through customer satisfaction in airline industry in Malaysia. Perceived value forms WOM directly or through customer satisfaction (Gürler & Erturgut, 2018). Service quality and price perception influence WOM and have an impact on revisit intention (Liu & Lee, 2016) on low-cost carriers in Taiwan.

According to Saha & Theingi (2009), service quality influences satisfaction that leads to WOM and repurchase intention (Dewi, Adhianata, & Suwignyo, 2018; Okadiani, Mitariani, & Imbayani, 2019; Soelasih & Sumani, 2020). If a service failure occurs, it will cause a negative electronic WOM (Beneke, Mill, Naidoo, & Wickham, 2015). Meanwhile, Saleem, Zahra, & Yaseen (2017) viewed WOM as a moderating variable between service quality variables–trust, customer satisfaction, and brand image (Chun, Lee, & Park 2020). In relation to this, Ranaweera & Menon (2013) emphasized negative and positive WOM is influenced by customer satisfaction by moderating the relationship between age and continuance commitment.

In studies by Ahmadi (2019); Gürler & Erturgut (2018); Saha & Theingi (2009); Suki (2014), variables that affect WOM were elaborated, such as service convenience, customer satisfaction, and perceived value. Whereas, in a study by Liu & Lee (2016), WOM was formed by service quality and price perception. Furthermore, Saleem et al. (2017) viewed the WOM variable as moderation, while Ranaweera & Menon (2013) examined the impact of customer satisfaction on negative and positive WOM. WOM is vital in airline industry because it is a form of communication with the passengers that can influence the flight use/re-use. As a result, many studies were conducted on WOM variables, but gaps in these variables still exist. Existing studies view WOM variables as mediation or consequent. What makes this study distinctive from the previous ones is that WOM is viewed as an antecedent.

Currently, WOM is formed by customers’ perceptions consisting of existing information, whether they have used or consumed a product or service. WOM plays a crucial role in social media as it has the potential to influence customers’ perceptions. It occurs to the airline industry, although customers have never tried Low-Cost Carriers (LCC) flights, WOM is still formed. Therefore, this study aims at acknowledging the effect of WOM variables as antecedents that influence purchase intention through negative and positive perceptions of WOM on LCC flights.

2. Literature Review

2.1. Word of Mouth

Blackwell, Souza, Taghian, Miniard & Engel (2006), shows that consumer satisfaction is measured by evaluating consumer actions after consuming a product or service. Evaluation results lead to buybacks if the assessment is positive, but if it is negative, consumers are not interested to repurchase. Satisfied consumers will not necessarily make a repurchase (Stewart, 1997), but consumers will make repurchases if the level of satisfaction is total (Lewis, 1998).

After consuming, evaluation results can lead to positive WOM if consumers’ value is following their expectations. Still, if the value is not following consumer expectations, it will cause negative WOM (Blackwell et al., 2006). Consumers evaluate after purchase; if the evaluation results are dissatisfaction, it will lead to complaints (Blackwell et al., 2006). According to Yi & La (2004), satisfaction can be measured by complaints, repurchases, and positive WOM.

Customer satisfaction is the most significant factor in forming WOM (Munap & Yahaya, 2019; Saha & Theingi, 2009). In relation to this, E-WOM quantity, credibility, and quality have an influence on repurchase intention through trust and perception usefulness (Matute, Redondo, & Utrillas, 2016). Furthermore, negative communication or negative WOM will affect brand image and brand attitude towards purchase intention (Yu, Liu, Lee, & Soutar, 2018).

According to Dick & Basu (1994), cognitive, affective, and conative antecedents can form WOM as a consequence of loyalty. This is in line with Söderlund (1998) who viewed WOM as a mediating variable between customer satisfaction and loyalty. Xia & Bechwati (2008) suggest that affective evaluations are the most important aspect in shaping WOM for customers as Dick & Basu (1994) and Xia & Bechwati (2008) affirm that affective is a perception arising among customers. If the affective is positive, it gives rise to recommendations (Xia & Bechwati, 2008).

Ng, David, & Dagger (2011) conducted a study on service experience with positive word of mouth, resulting in the importance of positive word of mouth in service companies considering its potentials to influence customers’ behavior. Conversely, service failure will affect the negative word of mouth (Noone, 2012).

WOM can be formed before or after purchase and it can be perceived as negative or positive by the customer (Buttle, 1998). Furthermore, Erkan & Ervans (2016) concluded that WOM is antecedent by dividing four sub-variables, namely information quality, information credibility, needs of information, and attitudes towards information by testing e-WOM against purchase intention through information usefulness and information adoption.

Vahdati & Nejad (2016) examine e-WOM against purchase intentions directly and indirectly through brand equity. By mediating brand equity, Vahdati & Nejad (2016) proved that e-WOM had an influence on purchase intention directly. Meanwhile, Doh & Hwang (2009) looked into the effect of the number of positive or negative messages on e-WOM with the moderation of involvement and prior knowledge. The results of the WOM study on negative and positive WOM serve as the basis of the hypothesis formation.

H1: WOM influences negative perception of WOM.

H2: WOM influences positive perception of WOM.

2.2. Positive and Negative Perceptions of WOM and Purchase Intention

According to Tsai, Liao, & Hsieh (2014), service failure triggers the formation of a negative WOM. When a company performs service recovery, it is expected that the negative WOM changes to positive ones (Choi & Choi, 2014).

The research results by Saha & Theingi (2009) shows that the success of the LCC is not only due to the low fare factor, but also the quality of service that must be considered because it affects passenger satisfaction in Thailand. Satisfaction influences behavioral intentions such as WOM, repurchase intention, and provision of feedback.

The research results by Kim & Lee (2011) state that airlines with the LCC concept need to develop tangibles and responsiveness to increase passenger satisfaction and behavioral intentions. The results of the tangibles and responsiveness variables are significant to customer satisfaction. Satisfaction measures in WOM communication, purchase intentions, and complaining behavior. Nadiri, Hussain, Ekiz, & Erdogan (2008) state that service quality affects customer satisfaction and retention so that it impacts WOM.

On the other hand, dissatisfaction will lead to negative WOM (Blodgett, Granbois, & Walters, 1993). Rahman, Karpen, Reid, & Yuksel (2015) compared WOM during consumption (customer to customer interaction) and WOM after consumption, with the hypothesis that good interaction can change brand perception leading to customers’ trust, resulting in positive WOM after consumption.

In their study, Markovic, Iglesias, Singh, & Sierra (2018) proved that customer loyalty shaped by customer affective commitment and customer perceived quality has the most significant influence on positive WOM. Social visibility of consumption has a direct and indirect effects on WOM (So, Wu, Xiong, & King, 2018). The results of these previous studies suggest that negative WOM reduces purchase intention, while positive WOM increases purchase intention.

Matos & Rossi (2008) suggest that WOM can be influenced by satisfaction, loyalty, quality, commitment, trust, and perceived value. Moreover, WOM can also be a moderator variable, as seen from the positive and negative WOM. Positive cognitive personalization will lead to purchase intention (Xia & Bechwati, 2008), while negative customers’ reviews of brands negatively influence purchase intention (Brunner, Ullrich, & Oliveira, 2019). The results of the previous studies form the following hypothesis:

H3: Negative perception of WOM influences purchase intention.

H4: Positive perception of WOM influences purchase intention.

The results showed more WOM variables as moderators, mediation, and consequent. However, according to Buttle (1998), WOM could be both antecedent and consequent. Therefore, the research model is depicted in Figure 1.

Figure 1: Research Model

3. Methodology

Objects of this study comprised domestic low-cost carrier airline customers in Indonesia. The sample size is needed to describe the population of the study (Krejcie & Morgan, 1970). The minimum sample consists of 100 respondents using Lisrel (Hair, Black, Babin, Anderson, & Tatham, 2006). In this study, 387 samples were taken at Soekarno Hatta Airport and Kualanamu Airport. The questionnaires were directly distributed to the respondents. At Soekarno Hatta Airport, the questionnaires were distributed at departure area of terminal 1 and 2, while at Kualanamu Airport they were distributed in waiting room of departure area. Purposive sampling was employed, and the questionnaires were distributed in June 2019.

The instrument used in the study referred to various previous studies. The WOM variable relates to research conducted by Ahmadi (2019) and Gürler & Erturgut (2018). The variables of a negative perception of the WOM and positive perception of the word of mouth referrals to research by Beneke et al. (2015), Brunner et al. (2019), and Ranaweera & Menon (2013). Finally, the purchase intention variable refers to the research of Yu et al. (2018).

Instruments and variables were tested for validity and reliability. Validity shows the accuracy of the instrument to the variable, while reliability indicates replication (Winter, 2000). The instrument uses an attitude scale with six choices, considering there is no neutral value, and the respondent knows the instrument’s statement and can be divided into two groups (Agung, 2011). The indicators used are developed from previous studies, forming WOM, negative perception of WOM, positive perception of WOM and purchase intention. The validity test used confirmatory factor analysis (CFA) while reliability used composite reliability (CR) and average variance extracted (AVE). In the WOM validity and reliability test for the CFA instrument on WOM1 = 0.88, WOM2 = 0.88, WOM3 = 0.89, WOM4 = 0.91, CR WOM = 0.94 and AVE WOM = 0.79. For the CFA value at NPW1 = 0.83, NPW2 = 0.89, NPW3 = 0.87, NPW4 = 0.81, CR NPW = 0.91 and AVE NPW = 0.73. Indicator PPW1 = 0.76, PPW2 = 0.75, PPW3 = 0.85, PPW4 = 0.89, PPW5 = 0.83, CR PPW = 0.91 and AVE PPW = 0.67. Indicators PI1 = 0.83, PI2 = 0.88, PI3 = 0.86, PI4 = 0.85, CR PI = 0.92, and AVE PI = 0.73. These results indicate that the CFA and AVE values are above 0.5 while the CR value is above 0.6. According to Hair Jr, Black W.C., Babin B.J., & Anderson R. E., (2014), a valid instrument forms a variable when the factor loading value is above 0.5. Calculation results for CR values above 0.6 and AVE above 0.05 are said to be reliable (Fornell & Larcker, 1981).

The hypothesis test employed structural equation modeling analysis. Therefore, the model test is conducted beforehand to indicate whether or not the research model is feasible. To test the model, structural equation modeling with Lisrel software 8.8 was used. The model test results showed that NFI = 0.97, NNFI = 0.97 and CFI = 0.98 means good fit. For the SRMR = 0.08, GFI = 0.84 and AGFI = 0.78, they fall into the marginal fit category. This value indicates that we can use the normal data on the NFI and NNFI values and the fit model in research. The study conducted by Jannoo, Yap, Auchoybur, & Lazim Jannoo, Yap, Auchoybur, & Lazim (2014) show that normally distributed data with a large sample size covariance-based (CB) -SEM can be used, as for testing latent variables and models with mediating variables, Lisrel can be used (Bentler, 2010).

4. Results and Discussion

We grouped the data taken to see the characteristics of the respondents. The number of respondents was 387 with the characteristics where women aged between 20–30, with a bachelor’s level of education, or working as private employees. Respondents with age ranging from 20–30 years old were more likely to use social media and share information despite having no prior experience regarding the obtained information. This can be inferred as the root of WOM.

To answer the hypothesis, a test was conducted using structural equation modeling with Lisrel 8.8. Hypothesis test results are displayed in the following Table 1.

Table 1: Hypothesis Test Results

Test results of hypothesis 1 show a path coefficient of –0.789, meaning that if the positive WOM occurs, the negative perception of WOM will decrease, but negative WOM will increase the negative perception of WOM. Where the level of competition for airlines is high, it is necessary to build positive WOM to increase passengers’ attractiveness to use LCC flights. Positive WOM can be a reference for prospective flight passengers because positive information will create a trust (Matute et al., 2016). Meanwhile, perceptions of negative WOM will have an influence on brand image and brand attitude that have an impact on purchase intention (Yu et al., 2018). The results of hypothesis 1 prove that positive WOM is needed in building passengers’ trust.

Test results of hypothesis 2 show a path coefficient of 0.858, meaning that positive WOM will form a higher positive perception of WOM. The test results prove the theory that positive WOM forms a positive perception. The formation of a positive perception makes it easier for companies to sell their products to consumers. Positive perceptions will create customer trust so that they affect purchase intention.

The results of this study were in line with Buttle (1998), where WOM can be antecedent. Saha &Theingi (2009); Munap & Yahaya (2019) suggest WOM as a consequence, thus variables are needed to form WOM, such as customer satisfaction. Ng et al. (2011) showed the significance of a positive WOM, while Noone (2012) and Tsai et al. (2014) emphasized negative WOM due to customers’ dissatisfaction. Many researchers show WOM as a mediating, moderation, and consequent variables. Söderlund (1998), for example, viewed WOM as mediation.

Test results of hypothesis 3 show a path coefficient of –0.263, meaning that if there is a negative perception of WOM, it will decrease purchase intention. Hypothesis 3 test strengthens the theory, where the negative perceptions that arise cause consumers not to make purchases because the created brand image is also negative. The results of this study support Yu et al. (2018) and Brunner et al. (2019).

Test results of hypothesis 4 show a path coefficient of 0.682, meaning that a positive perception of WOM causes an increase in purchase intention. Hypothesis 4 test shows that positive perceptions formed from WOM will increase purchase intention. Meanwhile, customer trust is also created from WOM and positive perceptions, giving rise to a positive customer attitude. The results of this study support Ng et al. (2011); Rahman et al. (2015); and Xia & Bechwati (2008).

Test results of hypotheses 1 to 4 show the significance of WOM created by customers considering its impact on purchase intention. As a result, WOM as an antecedent need to be considered by the company. The influence of WOM is what shapes customers’ purchase intention.

This study is similar to the one conducted by Erkan & Ervans (2016) who tested WOM as an antecedent and use four sub-variables with information usefulness and information adoption as mediation variables to form purchase intentions. In this study, however, WOM was not divided into sub-variables, but WOM formed customers’ perceptions, hence the separation between negative and positive perceptions influences purchase intention. This study’s novelty is the formation of WOM as an antecedent variable that creates a negative perception or positive perception and affects purchase intention. Companies need to design WOM for consumers by providing information about the value or benefits of using LCC flights.

5. Conclusion

The results showed that WOM influenced the negative and positive perceptions of WOM. Therefore, if there is a negative WOM, it will cause a negative perception of WOM. Considering the potential of WOM, companies need to be careful in building communication with customers. Interactions between customers can also result in WOM. Therefore, companies, especially those engaged in services, need to pay attention to the communication that occurs both from the company and between customers.

The negative and positive perceptions of WOM also influence purchase intention. It means that should a negative perception arise, purchase intention will be low and vice versa; if a positive perception arises, purchase intention will rise as well. Furthermore, perceptions that arise among customers will affect buying behavior.