Electronic Word of Mouth: Improving the City Image and Increasing the Intention of Tourist Visit
Terra Saptina Maulani1,2*, Mohamad Hadi Prasetyo1,2
1 Management Study Program, Sekolah Tinggi Ilmu Ekonomi Ekuintas, Bandung, Indonesia
2 Doctoral of Economy Program, Parahyangan Chatolic University, Bandung, Indonesia
*Corresponding Author: [email protected] Accepted: 15 December 2022 | Published: 31 December 2022
DOI:https://doi.org/10.55057/ijarti.2022.4.4.1
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Abstract: The tourism sector makes a significant contribution to the economic development of the country by contributing to the creation of income and employment in the community. This study was conducted in one of the cities in Indonesia, Bandung City which is the capital city of West Java province. Every year, the one source of regional income comes from tourism activities, hotel taxes, entertainment, and restaurants. However, for 2 (two) years the Covid- 19 pandemic has been shaking the world, it has had an impact on national and regional tourism where there has been a significant decrease in visits. One of the efforts to encourage economic recovery is to increase marketing by strengthening the tourism image. The development of information technology has grown to a new term in marketing communication, Electronic Word of Mouth (eWOM) can reach a wider market than conventional advertising. A positive eWOM helps develop a destination's image so that it has a positive effect on attitudes toward a particular destination. This study aims to analyze how the influence of electronic word of mouth is one of the antecedents to the image of the city as a tourist destination and analyzes the city's image as a tourist destination, especially during the reopening of regional borders due to the COVID-19 pandemic and its impact on tourist interest in visiting Bandung as a destination. This study uses a quantitative approach with data collection tools in the form of questionnaires distributed to 144 respondents. Analysis of the research model and hypothesis testing through structural equation modeling (SEM) using the AMOS 23.
Keywords: Electronic Word Of Mouth, City Image, Visit Intention
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1. Introduction
Tourism is one of the sectors that encourage the community's economy in addition to the manufacturing industry sector by contributing to the creation of income and employment in the community, so that the tourism sector makes a significant contribution to the development of a country. Indonesia has natural and cultural wealth that is very diverse in terms of geography, demographics, and various different characteristics, this has become a potential for regional tourism. The tourism service sector can contribute to absorbing labor and contributing to regional income. One of the provinces in Indonesia is West Java Province with eighteen regencies and nine cities which have a diversity of tourist attractions and experience growth in tourist visits every year, both domestic and foreign tourists.
Tourism becoming very interesting topic for researchers at this time, especially the tourism sector is a sector that is very affected because of the COVID-19 pandemic which has resulted
in limited human activities for the 2 (two) years and has an impact on regional income which has decreased. This study was conducted in one of the cities in Indonesia is Bandung City which is the capital city of West Java province. Every year, one source of regional income comes from tourism activities, both hotel taxes, entertainment, and restaurants. However, for 2 (two) years, the Covid-19 pandemic has been shaking the world, it has an impact on national and regional tourism where it has been a significant decrease in visits. One of the efforts to encourage economic recovery is to increase marketing by strengthening the image of tourism.
Developing a positive image of a tourist destination in the target market to gain a real competitive advantage (Souiden et al., 2017). The development of information technology has growth to a new term in marketing communication, it’s Electronic Word of Mouth (eWOM), a new paradigm in word-of-mouth communication. The eWOM can reach a wider market than conventional advertising. Information technology and the scope of WOM have developed with a type of knowledge exchange on an online platform with the public called Electronic Word of Mouth (eWOM) (Charo et al., 2015). Communication using the Internet through social media such as Instagram, Facebook, Twitter, and Blogs are facilitates of eWOM. eWOM, both positive and negative, helps develop a destination's image. The empirical studies show that online reviews have a significant effect on destination image (Govers and Go, 2004; Mridula, 2009). Jalilvand et al (2012) their research shows that e-WOM has a positive effect on attitudes towards certain goals. Suwarduki, et.al (2016), Wang (2015) and Doosti et al., (2016) show that the image of a destination has a significant effect on visiting intentions. An image that allows to differentiate between tourist destinations. In addition, the image of the destination is an integral and influential part of the tourist decision-making process (Baloglu and Brinberg, 1997).
This study aims to analyze how the influence of electronic word of mouth is one of the antecedents to the image of the city as a tourist destination. This study also analyzes the image of the city as a tourist destination, especially during the reopening of regional borders due to the COVID-19 pandemic and its impact on tourist interest in visiting destinations.
2. Literature Review
Electronic Word of Mouth
Communication in marketing “plays” an important role in increasing sales. Viewed from the consumer side, communication also helps in determining the decision to visit tourists. One of the marketing tools that is believed to influence the decision of prospective tourists is Word of Mouth (WOM). Word of Mouth (WOM) is a verbal communication related to product offerings, services between individuals (Arndt, 1967; Jalilvand and Heidary, 2015). In this connectivity era, face to face WOM has developed into Electronic Word of Mouth (eWOM), the dissemination can be through online media, for example via email and social networks (such as Facebook, Twitter, Instagram, Youtube). WOM plays an important role in services to create high trust such as in the tourism and hospitality industry. Electronic word of mouth is defined as positive or negative statements from previous customers, potential customers and actual customers about a product or company that can be accessed by many people and very widely via the internet (Thurau and Gianofranco, 2004). eWOM is a source of information when consumers decide to consume a product before deciding to consume a product. Consumer perception of the credibility of eWOM information is important because it relates to personal knowledge so that it creates motivation to be offered or recommended in wen sites or online forums (Chatterjee, 2001). Several ways can be used to obtain eWOM information, especially on social networks. Users can previously post about the performance of a product or service company consumed. They can also unintentionally display their preferences to their network
such as interacting by posting brand content without the aim of advertising and commenting on it.
City Image
Departing from psychology was developed in the US, concerning microeconomics and behavioral psychology assuming that there is a relationship between stimuli and responses, economic psychology introduces intervening factors from subjects (people) with perceptions and preferences. Stimuli- perception (image)- response (experience) (Govers & Go, 2009).
Image is defined as subjective knowledge that is believed by the individual as a personal justification of the individual (Boulding, 1956). Image is also defined as a cognitive representation of empirical knowledge and stimuli that are formed in a more structured manner (Hacker, 1995). Images are classified into 3 groups based on the level of consumer elaboration (level elaboration), which is determined by the extent to which the subject is involved with an object (Govers & Go, 2009):
1) High. Image are stored in memory as a network of meanings
2) Middle. Image as a weighted sum of beliefs about a project: perceptions of salient attributes 3) Low. Image as a general holistic impression of an object
The city is a destination for traveling. For this study has adopts the concept of destination image developed by several researchers. Kim et al., (2017), destination image can be defined as impressions, perceptions, feelings and beliefs that a person has of a destination. Gallarza et al., (2002), destination image is a number of beliefs, ideas, and impressions that a person or group of people has about a destination. Traveling is a human need, where humans have different motivations in doing, so every place must have a strategy to create a memorable experience so that tourists want to come. In consumer behavior, the "behavior intention" is essential because it will produce actual behavior (Ajzen, 1991). Desire is a motivating state of mind in which there are reasons and judgments to act (Perugini and Bagozzi, 2001). Intention is the individual's steady possibility or readiness to take a certain action. There are 3 (three) components in image formation where a tourist forms a cognitive image on the basis of him developing an affective image and then a unique image (Chen and Phou, 2013; Qu et al., 2011;
Gartner, 1993). The cognitive component refers to the beliefs and knowledge tourists hold about destination attributes. The affective component is represented by feelings or emotional responses to various features of a place. A unique image is at the heart of destination positioning because of its ability to differentiate a destination from competitors to enter the minds of consumers, which simplifies information continuously.
Visit Intention
In the marketing, there is consumer behavior that is closely related to the process before making a purchase and consuming a product to the evaluation of the product consumed. Consumer behavior is a consumer action that includes consuming or disposing of goods and services as well as evaluating expectations that are used as a reference for decisions. This is in accordance with Kotler and Keller (2016: 187) that consumer behavior is a process and activity when a person relates to the search, selection, purchase, use, and evaluation of products and services to meet needs and desires.
Meanwhile, according to Schiffman (2015) is the study of consumer actions in searching for, buying, using, evaluating and disposing of products and services that they expect will satisfy their needs. Consumer behavior is strongly influenced by the circumstances and situations of the society in which he was born and developed. This means that consumers from different walks of life or environments will have different assessments, needs, opinions, attitudes, and
tastes, so that decision making in the buying stage will be influenced by several factors. Factors that influence consumer behavior according to Kotler and Keller (2016:179). Cultural factors, cultural factors have a broad and deep influence on consumer behavior. Cultural factors consist of: culture, sub-culture and social class. Social Factors. In addition to cultural factors, a consumer's behavior is influenced by social factors such as reference groups, family and social status. Personal factors, personal factors that contribute to consumer behavior consist of: age and life cycle stage, work and economic environment, lifestyle, personality and self-concept.
Psychological factors, a person's purchase choice is influenced by four main psychological factors, namely motivation, perception, learning, and beliefs and convictions.
3. Method
The research method in this research is descriptive and exploratory, with data collection tool is questionnaires. Several indicators related to the relevant variables will be represented in several questions in the questionnaire. This questionnaire is distributed in April-May 2022, where tourism access in the City Bandung began to open due to the relaxation of government policies related to the Covid-19 pandemic. The total respondents who became the sample in this study were 144 respondents. The validity test of each question item of an instrument, a validity test is needed. In this study, a validity test has been carried out on each question and the value of r count > r table is above 0.164. Based on the results of reliability testing, Cronbach's alpha value is above 0.6, it means that the instrument has reliable results, so this instrument or questionnaire is a reliable and consistent instrument.
The city is a tourist destination, in this study adopting a previous study conducted by Jalilvand and Heidary (2015), the destination image consists of cognitive, affective and unique components. And there is also an overall image of a destination that can be seen and measured based on holistic attributes, functional-psychological, and unique-common characteristics.
Then an analysis of the research model and hypothesis testing was carried out through path analysis using AMOS 23.
The hypotheses of this study are:
Ha1: There is a significant effect of Electronic word of mouth on Cognitive image Ha2: There is a significant effect of Electronic word of mouth on Affective image Ha3: There is a significant effect of Electronic word of mouth on Unique image Ha4: There is a significant effect of Cognitive image on Overall image
Ha5: There is a significant effect of Affective image on Overall image Ha6: There is a significant effect of Unique image on Overall image Ha7: There is a significant effect of Overall image on Visit Intention
4. Result dan Discussion
In this section, calculations and discussions will be carried out based on the data obtained in the field during the research period. The analysis consists of descriptive analysis and verification analysis using path analysis. Path analysis is used to calculate eWOM studies in the public image to increase the level of tourist visits. The total respondents who became the sample in this study were 144 respondents. The results of the validity and reliability tests in this study are valid and reliable. The number used as a comparison to see whether an item is valid or not is 0.164 (r table for sample 144). While the reliability test is used to see the stability or consistency of the measurement results, the value of the result is more than 0.6. Reliability tests have been carried out with the following results:
Result of Descriptive Analysis
The description of the respondent's response data can be used to enrich the discussion, through the description of the respondent's response data it can be seen how the condition of each variable indicator is being studied. To make it easier to interpret the variables being studied, categorization of respondents' responses is carried out based on respondents' response scores.
Categorization of respondents' response scores was carried out based on the range of maximum and minimum scores divided by the number of desired categories using the following formula.
Respondents' responses to each statement item were categorized into 5 categories of very good, good, sufficient, not good and very bad with the following calculations:
• Maximum Index Value = Highest Scale = 5
• Minimum Index Value = Lowest Scale = 1
• Distance Interval = [maximum value - minimum value]: 5
= (5 –1)/5 = 0.8
The descriptive analysis was conducted in order to obtain an overview of respondents' perceptions of the variables in the study. The variables in this study were eWOM, the image consisting of cognitive image, affective image, unique image and overall image as well as visit intention based on the results of calculations from 144 respondents who had been obtained.
Characteristics of respondents obtained in this study, the majority are women with a proportion
of about 53%. Then the respondents who are male are 47%. A total of 124 people stated that they had visited Bandung more than three times, as many as 10 people stated that they had visited for the first time, 6 people stated that they had visited 2 (two) times, and as many as 4 people stated that they had visited three times.
Descriptive Analysis Results: Electronic Word Of Mouth
The following are the results of the eWOM variable analysis, represented by the following six statement indicator items.
Based on the results of data processing that has been described in table above, it can be seen that the total score for the eWOM variable is 3.478 with an average of 4.03. This average value is in the range of 3.40-4.20. It can be concluded that the respondent's perception of Electronic word of mouth is in the good category.
Descriptive Analysis Results: Cognitive image
Based on the results of the Cognitive image variable analysis, represented by 9 (nine) item indicator statements as follows.
Based on the results of data processing that has been described in table above, it can be seen that the total score for the cognitive image variable is 5,428 with an average of 4.19. This average value is in the range of 3.40-4.20. It can be concluded that the respondent's perception of cognitive image is in the good category.
Descriptive Analysis Results: Affective image
Based on the results of the analysis of the affective image variable, it is represented by five statement indicator items as follows.
Based on the results of data processing that has been described in table above, it can be seen that the total score for the Affective image variable is 3.310 with an average of 4.60. This average value is in the range of 4.20-5.00. It can be concluded that the respondent's perception of affective image is in the very good category.
Descriptive Analysis Results: Unique image
Based on the results of the unique image variable analysis, it is represented by five statement items as follows:
Based on the results of data processing that has been described in table 4.17 above, it can be seen that the total score for the Unique image variable is 3,090 with an average of 4.29. This average value is in the range of 4.20-5.00. It can be concluded that the respondent's perception of Unique Image is in the very good category.
Descriptive Analysis Results: Overall image
Based on the results of the analysis of the overall image variable, it is represented by five statement indicator items as follows:
Based on the results of data processing that has been described in table above, it can be seen that the total score for the Overall image variable is 3.152 with an average of 4.38. This average value is in the range of 4.20-5.00. It can be concluded that the respondent's perception of the overall image is in the very good category.
Descriptive Analysis Results: Visit intention
Based on the results of the analysis of the visit intention variable, it is represented by four statement indicator items as follows:
Based on the results of data processing described in table above, it can be seen that the total score for the Visit Intention variable is 2,432 with an average of 4.22. This average value is in the range of 4.20-5.00. It can be concluded that the respondent's perception of visit intention is in the very good category.
Explanatory Analysis Results
Based on the data that has been collected through the questionnaire, in this section we will examine the effect of eWOM on visit intention through cognitive, affective, uniqe and overall image. To test this hypothesis, path analysis was used using the AMOS version 23.0 application. The following is a picture of the results of path analysis calculations based on research data.
After the total model image is formed, the next step is to test the hypothesis to see which of these variables has a significant effect.
Source: AMOS Data Processing Results, 2022
The hypothesis testing for the effect of electronic word of mouth on cognitive image, it shows based on the table above, it can be seen that the direction of the relationship between Electronic word of mouth and Cognitive image is positive (the value in column), there is written 0.665, it means that when there is an increase in Electronic word of mouth, it will increase Cognitive image. Then the writer tested the hypothesis using the t-test where the t-count value of 10,658 was bigger than the t-table of 1.977 (df=n-k-1=144-1-1=142). In addition, it can also be seen by looking at the magnitude of the p-value (sig) compared to 0.05 (significance level = 5%).
Based on the provisions that have been stated previously, which obtained a p-value of 0.001 so that the p-value < = 0.05 and the t-count is greater than 1.977. This means that H01 is rejected and Ha1 is accepted, then there is a significant influence between Electronic word of mouth on Cognitive image. Thus the hypothesis which states that there is a significant influence between electronic word of mouth on cognitive image can be accepted.
The hypothesis testing for the effect of electronic word of mouth on affective image Based on the table 9 above, it can be seen that the direction of the relationship between electronic word of mouth and affective image is positive (the value in column ), it is written 0.321, meaning that when there is an increase in electronic word of mouth, it will increase the affective image.
Then the writer tested the hypothesis using the t-test where the t-count value of 4.050 is bigger than the t-table of 1.977 (df=n-k-1=144-1-1=142). In addition, it can also be seen by looking at the magnitude of the p-value (sig) compared to 0.05 (significance level = 5%) .Based on the provisions that have been stated previously, which obtained a p-value of 0.001 so that the p- value < = 0.05 and the t-count is greater than 1.977. This means that H02 is rejected and Ha2 is accepted, then there is a significant influence between Electronic word of mouth on Affective image. Thus the hypothesis which states that there is a significant influence between electronic word of mouth on the affective image can be accepted.
The hypothesis testing for the effect of electronic word of mouth on unique image Based on the table 9 above, it can be seen that the direction of the relationship between Electronic word of mouth and Unique image is positive (the value in column ), it is written 0.518, meaning that when there is an increase in Electronic word of mouth, it will increase the Unique image. Then the writer tested the hypothesis using the t-test where the t-count value of 7.243 is bigger than the t-table of 1.977 (df=n-k-1=144-1-1=142). In addition, it can also be seen by looking at the magnitude of the p-value (sig) compared to 0.05 (significance level = 5%).Based on the
provisions that have been stated previously, which obtained a p-value of 0.001 so that the p- value < = 0.05 and the t-count is greater than 1.977. This means that H03 is rejected and Ha3 is accepted, then there is a significant influence between Electronic word of mouth on Unique image. Thus the hypothesis which states that there is a significant influence between Electronic word of mouth on Unique Image can be accepted.
The hypothesis testing for the effect of cognitive image on overall image. Based on the table 9 above, it can be seen that the direction of the relationship between Cognitive image and Overall image is positive (the value in column ), there is 0.518 which means that when there is an increase in Cognitive image, it will increase the Overall image. Then the writer tested the hypothesis using the t-test where the t-count value of 5.543 is bigger than the t-table of 1.977 (df=n-k-1=144-3-1=140) so the hypothesis 4 is accepted. In addition, it can also be seen by looking at the magnitude of the p-value (sig) compared to 0.05 (significance level = 5%). Based on the provisions that have been stated previously, which obtained a p-value of 0.001 so that the p-value < = 0.05 and the t-count is greater than 1.977. This means that H04 is rejected and Ha4 is accepted, then there is a significant influence between Cognitive image on Overall image. Thus the hypothesis which states that there is a significant influence between Cognitive image on Overall image can be accepted.
The hypothesis testing for the effect of affective image on overall image. Based on the table 9 above, it can be seen that the direction of the relationship between Affective image and Overall image is positive (the value in column ), there is written 0.428, it means that when there is an increase in Affective image, it will increase the Overall image. Then the writer tested the hypothesis using the t-test where the t-count value of 6.901 is bigger than the t-table of 1.977 (df=n-k-1=144-3-1=140). In addition, it can also be seen by looking at the magnitude of the p- value (sig) compared to 0.05 (significance level = 5%). Based on the provisions that have been stated previously, which obtained a p-value of 0.001 so that the p-value < = 0.05 and the t- count is greater than 1.977. This means that H05 is rejected and Ha5 is accepted, then there is a significant influence between Affective image on Overall image. Thus the hypothesis which states that there is a significant influence between Affective image on Overall image can be accepted.
The hypothesis testing for the effect of unique image on overall image. Based on the table above, it can be seen that the direction of the relationship between Unique image and Overall image is positive (the value in column ), it’s 0.178, meaning that when there is an increase in Unique image, it will increase the Overall image. Then the writer tested the hypothesis using the t-test where the t-count value of 2.758 is bigger than the t-table of 1.977 (df=n-k-1=144- 3-1=140). In addition, it can also be seen by looking at the magnitude of the p-value (sig) compared to 0.05 (significance level = 5%). Based on the provisions that have been stated previously, which obtained a p-value of 0.006 so that the p-value < = 0.05 and the t-count is greater than 1.977. This means that H06 is rejected and Ha6 is accepted, then there is a significant effect between Unique image on Overall image. Thus the hypothesis which states that there is a significant influence between Unique image on Overall image can be accepted.
The hypothesis testing for the effect of overall image on visit intention. Based on the table 9 above, it can be seen that the direction of the relationship between overall image and visit intention is positive (the value in column ), it says 0.586, it means that when there is an increase in overall image, it will increase visit intention. Then the writer tested the hypothesis using the t-test where the t-count value of 8.is bigger than the t-table of 1.977 (df=n-k-1=144-1-1=144).
In addition, it can also be seen by looking at the magnitude of the p-value (sig) compared to
0.05 (significance level = 5%). Based on the provisions that have been stated previously, which obtained a p-value of 0.006 so that the p-value < = 0.05 and the t-count is greater than 1.977.
This means that H07 is rejected and Ha7 is accepted, then there is a significant influence between Overall image on Visit Intention. Thus the hypothesis which states that there is a significant influence between overall image and visit intention can be accepted.
The most of tourists often read online travel reviews to ensure that they choose the right destination, these reviews are a great source of information before traveling. They stated that if they do not read online reviews they are worried about making the wrong decision, reading online reviews makes them confident in visiting destinations.
Destination image consists of aspects of cognitive, affective and unique image. In the results of this study, the cognitive image variable is an aspect that is considered good in the minds of tourists because they state that the quality and accommodation in the city of Bandung is considered adequate and varied. In an effort to implement health protocols during the COVID- 19 pandemic, many accommodations such as hotels and restaurants apply the CHSE (Cleanliness, Health, Safety, and Environment Sustainability) standard, thus making tourists feel safe and comfortable. Tourists consider that the quality of the restaurants offered in the city of Bandung is quite good and offers delicious and interesting food. The tourist also stated that visiting the city of Bandung did not require a high expenditure. Based on the aspect of affective image, the tourists stated that the city of Bandung is a city that is fun, exciting, a city that is suitable for relaxing, interesting and comfortable. Based on the uniqe image aspect, tourists stated that the city of Bandung has a very unique tourist destination because it offers various tourist destinations such as natural tourism located in the eastern region of the city of Bandung, namely Pasir Kunci and Pasanggrahan, cultural tourism that is unique because it is an original Indonesian cultural heritage in Indonesia. West Java, namely Saung Udjo and Echo Bambu, where tourists can interact directly to play these traditional musical instruments.
Tourists also stated that the city of Bandung has a unique culinary tourism because it has a variety of cuisines, and there are interesting museums and zoo to visit. Overall, Bandung is a safe city to visit after there was a policy of easing activities during the covid-19 pandemic due to declining covid 19 cases and incessant vaccinations. Bandung City offers tourist attractions that are considered interesting to visit and have their own charm, cool climate factor and also cost-effective for tourists, thereby increasing high interest for tourists to visit.
Conclusion
Tourist interest in visiting tourist attractions can be influenced by the image of the destination, where the overall image can be formed through cognitive image, affective image and unique image. In cognitive image, tourists feel how they respond to tourist attractions through the five senses, in this study, especially during the COVID-19 pandemic, in addition to local attractions such as food factors that are considered attractive, accommodation factors that meet CHSE standards as well considered important. The affective image factor is considered important that affects the overall image, where the city of Bandung is a fun and exciting city to visit and also has a unique image because it has a culinary tourism area that serves a variety of local foods.
In the era of increasingly sophisticated and rapid technology and communication, tourists before traveling often read travel reviews so that from these reviews they make a distinct impression as readers of the image of the tourist attractions.
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