Significance of eWOM in the road of customer journey.
Acceptance of eWOM towards cross- cultural boundaries.
Rahat Israque Fahim, Shakhawat Rafi
Department of Business Administration Master's Program in Marketing Master's Thesis in Business Administration III, 30 Credits, Spring 2021 Supervisor: Vladimir Vanyushyn 2
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ACKNOWLEDGEMENT
The master’s thesis is an essential opportunity and interesting learning process for the students to broaden their knowledge in a specific field based on their interests. Of course, the way to complete the thesis is not so smooth and stressful and especially in the current pandemic which makes us separate from each other.
In that situation, we have found some persons to whom we as a team would like to express our deepest appreciation to support throughout this journey.
We would like to express our gratitude to our thesis supervisor, Vladimir Vanyushyn for his professional guidance, commitment, and valuable support we received throughout the research process. His motivations and experiences in the field of Marketing as well as in the business research field help us make significant development in this thesis.
We also express appreciation to all of those participants who spent their valuable time participating in our survey. We admit that without their help the analysis would not be possible. Lastly, we are expressing the deepest appreciation for our parents who support us financially and mentally to through the entire study period in Sweden.
Umeå, May 23, 2021 Rahat & Rafi
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ABSTRACT
The digital era began a few years ago and day by day the dominance of the digital era is easily captivating all aspects of life. The business world is not out of that and for that reason, eWOM has born as a completely customer dominant platform. A few years back, people either normally depended on the information that the manufacturer wants them to know or had not enough opportunity to know in detail. Alternatively, traditional WOM (word of mouth) is where people get opinions from their friends and family members, and we would like to express it as a limited opportunity. Now the platform is getting wider, and information is vastly available to all because of technology.
The goal of this thesis is to determine how eWOM influences consumer purchase intentions, as well as to determine how eWOM influences cultural variations in purchase intentions. Customer purchase intent is a complicated notion that requires customers to go through a procedure known as the customer journey. In this journey, different touchpoints and interactions might influence the consumer journey differently which can affect customer’s taste or brand loyalty. As a result, customer's taste or brand loyalty might be affected. Previous researchers have found some noticeable positive findings of the relationship between customer journey and the touchpoints, but the analysis based on cultural aspects and considering eWOM as newly emerged touchpoints remained unexplored. Our expressed research question is,
How does eWOM affect throughout the customer journey towards the customer’s purchase intention in Bangladesh and in Sweden?
To develop the conceptual framework, we have used customer journey theory, customer touchpoints and its newly emerged components of eWOM. To examine the cultural aspect, we have chosen two elements out of six developed by Hofstede. Because we believe culture is the core value of a society, which has a significant impact on people.
For the analysis and result we have justified four components of eWOM, such as channels, source trustworthiness, valence, and length. Concerning the customer's purchase intention, we have found that eWOM has a significant impact on the customer buying behavior regarding to the Bangladesh and Sweden. Finally, our study shows that the channels and the source trustworthiness of eWOM have more influential effect on the customer journey that leads to the purchase intention. Again, the valence and the length of eWOM have unique variances between the two different cultural contexts.
Keywords: eWOM, electronic word of mouth, Customer journey, touchpoints, Individualist- Collectivist culture, Customer purchase intention.
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Table of Contents:
1. Introduction: ……………………………………………………………………...….9 1.1. Entering the Digital Era: ...... 9 1.2. Theoretical Background ...... 10 1.3. Problem Conceptualization: ...... 11 1.4. Research Gap: ...... 12 1.5. Research Question: ...... 13 1.6. Research Purpose: ...... 13 2. Theoretical Framework: ...... 15 2.1. Introducing eWOM: ...... 15 2.2. Classification of eWOM: ...... 19 2.3. Advantages and disadvantages of eWOM: ...... 20 2.4. Components of eWOM: ...... 21 2.4.1. Channels:...... 21 2.4.2. Valence: ...... 21 2.4.3. Source trustworthiness: ...... 22 2.4.4. Length: ...... 22 2.5. Introducing Customer Journey: ...... 22 2.6. Stages of the customer journey: ...... 26 2.7. Non-linear customer journey:...... 26 2.7.1. Social and cultural influence:...... 27 2.7.2. Technological Influence: ...... 27 2.7.3. Numerical information and packaging cues: ...... 28 2.8. The role of Culture: ...... 28 2.9. Individualist vs. Collectivist in eWOM: ...... 29 2.10. Purchase intention and eWOM: ...... 30 2.11. Conceptual Framework: ...... 32 3. Scientific methodology: ...... 33 3.1. Research Philosophy: ...... 33 3.2. Research Approach: ...... 34 3.3. Research Design: ...... 34 3.4. Research Strategy: ...... 35 3.5. Choice of theories: ...... 36 4. Practical Methodology:...... 38 7
4.1. Experimental stimulus product: ...... 38 4.2. Sampling and Respondents: ...... 38 4.3. Sample Size and Data collection: ...... 39 4.4. Pre-test:...... 39 4.5. Questionnaire design: ...... 40 4.6. Quality Criteria:...... 43 4.7. Ethical Consideration: ...... 44 5. Empirical findings and Analysis: ...... 45 5.1. Demographic and Geographic:...... 45 5.2. Cross-Tabulation of Usage & Experience:...... 47 5.3. Mean: T-test ...... 49 5.4. Cronbach's Alpha and Single Item Measurement: ...... 51 5.5. Pearson Correlation: ...... 52 5.6. Regression: ...... 53 5.6.1. Regression 1 (Sweden): ...... 53 5.6.2. Regression 2 (Bangladesh): ...... 55 6. Discussion:...... 57 6.1. Investigating eWOM and its components towards customer journey: ...... 57 6.2. Impacts of eWOM towards customer purchase intention in different cultural boundaries:…………………………………………………………………………………58 7. Conclusion: ...... 61 7.1. General Conclusion: ...... 61 7.2. Theoretical Contributions:...... 62 7.3. Societal Implications: ...... 63 7.4. Managerial contributions...... 63 7.5. Limitations and Future Research: ...... 64 8. References: ...... 65 9. Appendix Questionnaire: ...... 77
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List of Tables: Table 1: Research question and overview of the purposes ...... 14 Table 2: Literature table of eWOM ...... 19 Table 3: Literature Table of customer journey ...... 25 Table 4: Scale of Questionnaire...... 43 Table 5 ...... 45 Table 6 ...... 45 Table 7 ...... 46 Table 8 ...... 50 Table 9 ...... 50 Table 10 ...... 52 Table 11 ...... 53 Table 12 ...... 53 Table 13 ...... 54 Table 14 ...... 54 Table 15 ...... 56 Table 16 ...... 56 Table 17 ...... 56 Table 18: Summary of factors correlation ...... 59
List of Figures: Figure 1: Attitude towards eWOM channels ...... 21 Figure 2: Customer Journey Process...... 26 Figure 3: Cultural dimensions between Bangladesh and Sweden ...... 30 Figure 4: Conceptual Framework ...... 32 Figure 5 ...... 46 Figure 6 ...... 47 Figure 7 ...... 48 Figure 8 ...... 49
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1. Introduction:
The introduction chapter will introduce the reader to the chosen subject of the thesis. We will also present the relevance and importance of the chosen subject by using prior theories. After that, the theoretical background section will contain earlier studies and will discuss the problem in the practice field, followed by this study's research gap and research question. At the end of the introduction chapter, we will mention the primary purposes of this study and explain the essential terms.
1.1. Entering the Digital Era: From the beginning, human society has gone through several evolution to survive in the world and made life even more straightforward than in previous days. Now, we belong to a technological era where we cannot do a single task without the intervention of technology. Most significantly, the invention of the Internet and the easy access to the Internet worldwide have brought those considerable changes in daily life and the business world. The statistic says, in 2019, there were 3.97 billion internet users worldwide, and by 2023, this figure will grow to 5.3 billion (Statista, 2021). This amount of accessibility to the internet will bring significant changes and have started changing everything. Researchers have conducted many studies and analysis on this newly emerging digital marketing field and the invention is going forward in academics. Digital marketing is a marketing technique to increase sales using digital platforms (Lopez et al., 2019, p. 2). Kanan and Li (2017, p. 22) redefined digital marketing as an operation, organization, and process powered by digital technologies to develop, interact and provide value for improving consumers and stakeholders by adopting the definition of marketing by the American Marketing Association. The authors also regard digital marketing as an 'Umbrella concept' (Kanan & Li, 2017, p. 24). In the marketing, strategy developers are highly considering tech-issue to make the business more sustainable and secure than competitors. Sridhar and Fang (2019, p. 977) mentioned that marketing strategy had seen the three new evaluations of "Ds" (digital, data-rich, and developing markets) from the past decade. In short, 3Ds are the marketing strategies that deal with digital platforms judiciously using digital resources (e.g., web analytics, social media, smartphone), and the aim is to generate differentiation and sustainable value for customers (Bharadwaj et al., 2013, cited in Sridhar & Fang, 2019, p. 977). In the digital platform, digital marketing is helping gather unprecedented data in terms of behavior (both organization and consumer behavior). Generally, numerical data on consumer buying behavior, data related to digital marketing interventions of a firm, and massive unstructured data such as text, audio, the video created by consumers and firms (Wedel & Kanan 2016, cited in Sridhar & Fang, 2019, p. 977). Nevertheless, Sridhar and Fang (2019, p. 977) argued that marketing is a context- driven system, and traditionally, it has adopted the power to adjust with a continuously developing and newly evolving marketplace. Recently, the market development highly depends on digital and data-rich platforms. In the USA 2015, online sales of retain products have increased 7.4% compared with the last sixteen years (Kanan & Li, 2017, p. 22). In the same year, sales of smartphones have increased 10 by 22-27% in the USA (Kanan & Li, 2017, p. 22). It is easily noticeable that most of the successful business are highly related with the internet as well as different online platforms (e.g., Facebook, Microsoft, Google, Spotify, Amazon, Alibaba). Alternatively, the business world is getting the opportunity from this tech development and the customers. Customers are now more value-driven rather than product-centric. In marketing 3.0, Kotler et al., (2010) mentioned that the consumers will choose those companies and products that can meet deeper needs for participation, creativity, community, and idealism. So, these changes happened because of the availability of online information within people's reach, and it influenced people to create awareness about their purchasing intention (Lopez et al., 2019, p. 2). For that reason, Traditional "word of mouth" or user-generated content is now become electronic word of mouth (eWOM), where customers can share their experience by using various online platforms. Surprisingly, organizations are also being motivated to be digital in every aspect of operations and maintain customer relationships. In addition, the theory of consumer relationship management is getting new direction because of technological development which creates a buzz in the corporate world to maintain the relationship with customers through digital services (Kanan & Li, 2017, p. 22).
1.2. Theoretical Background The development of technology and the internet has had a significant impact on our approach to life. The internet has opened a whole new world, and there are no restrictions about the information that one person can access. Just like any other immersing technology, digital marketing did not just appear suddenly to take this visible place in the world. An exploration by Lamberton and Stephen (2016, p. 149) highlighted three eras of digital marketing the world had faced: 1) digital media shaping and facilitating buyer behavior, 2) consumers taking an active role in shaping digital media, 3) the age of social media. All these developments have led to the present where digital marketing is just marketing because relatively all the marketing activities a firm considers might have some digital aspects (Lamberton & Stephen, 2016, p. 168). Another paper by Leeflang et al. (2014, p. 2) mentioned that technological development has not only influenced our daily lives instead it has also changed consumer behaviors as well as the approach of the businesses. Social media is one of the channels of digital marketing that have got an increasing amount of attention to the practitioners. For defining social media as a significant channel for digital marketing Kohli et al. (2015, p. 37) mentioned employing mobile and web-based technologies to create highly interactive platforms via which individuals and communities share, co-create, discuss, furthermore, modify user-generated content. Murphy (2019) conducted a survey which highlighted that average consumer read at least ten reviews from different social media sites before making a purchase decision, 97% of them reads business responses, positive reviews, which help to increase the willingness to buy by 91%, and 88% of them trust online reviews or eWOMs (Electronic word-of-mouth) as much as personal recommendations, therefore, we think that this topic is getting more attention to the businesses and consumers. The rapid growth of the internet and the spread of social networks are changing how consumers can communicate among themselves and with the business. Traditional word-of-mouth communication is 11 restricted to people whom they know and interact with, but thanks to social networking sites that can help to exchange opinions and reviews with people all over the world (Jun et al., 2017, p. 379). Online word-of-mouth platforms are product review websites, retailer’s websites, brand’s websites, personal blogs, message boards, and social networking sites. These will help people to create, publish and share experiences and information with other potential customers (Lee & Youn, 2009; Ghosh & Venugopal, 2014). These online consumer communication platforms lead to the electronic word of mouth (eWOM) that can be defined as any positive or negative statement made by potential, actual, or former customers about a product or company, which is made available to a multitude of people and institutions via the internet, and it can be generated by both consumers and merchants (Yusuf et al., 2018, p. 493). Further, we have discussed more eWOM (Electronic word-of-mouth) in the literature part of this study. The development of online review platforms has allowed the consumers and businesses to share their experiences about any product/service between the social groups and help each other in the decision-making process before purchasing (Hussain et al., 2017, p. 97). The core article of the customer journey (Lemon & Verhoef, 2016, p. 79) defined customer journey as the customers interactions with multiple touchpoints, moving from consideration, search and purchase to post-purchase, consumption, and future engagement or repurchase. There is growing acceptance that eWOM (Electronic word-of-mouth) has a significant impact on the process of customer journey within its different stages and touchpoints (Hall et al., 2017, p. 499). The characteristics of eWOM (Electronic word-of-mouth) can change the way customers gather information about a product at different stages of the customer journey. Besides, (Goodrich & De Mooij, 2014) have also mentioned a strong impact of eWOM (Electronic word-of-mouth) during the different stages of the customer journey. We also have discussed more on customer journeys in the theoretical part. In this context, we have combined eWOM with the stages of the customer journey to conduct our research.
1.3. Problem Conceptualization: As discussed in this thesis's theoretical background, both customer journey and eWOM (Electronic word-of-mouth) are the fields in business that are just coming into existence and beginning to display signs of future potentiality. Managing the customer's journey is not an easy task because it consists of a multi-touchpoint, multi-channel, always-on, hyper- competitive consumer market (Maechler et al., 2016). Touchpoint is the medium of communication used by companies or customers to finalize their purchase decision such as advertisement, physical store, websites, membership facilities (Lemon & Verhoef, 2016, p. 76). There are two different ways to divide touchpoints; the company generated touchpoints and the customer generated touchpoints such as consumer-generated content word of mouth (WOM) or newly developed Electronic Word of mouth (eWOM). Both have a significant effect on the customer journey to finalize the decision. Managing the touchpoints in the customer journey in digitally enriched markets and not adequately managed markets could negatively affect the brand (Lemon & Verhoef, 2016, p.82). Again, when a customer starts their purchase journey and gets involved with multiple channels, their experience would considerably be worse than the single-channel experiences, and this journey cannot be controlled by the organizations (Maechler et al., 2016). A conceptual model constructed by Lemon and Verhoef (2016, p. 77) showed four main types of touchpoints: (1) brand-owned, (2) partner-owned, (3) 12 customer-owned, and (4) social and external touchpoints. When considering the different variants of touchpoints that can be included in each category, the mind starts to tumble. An industry report by Kitewheel (2018, p. 4) shows that in 2017 the total amount of customer journey interactions was at a little under 3.5 billion. Therefore, many practitioners have worked on managing and designing touchpoints in the customer journey as best as possible. For example, Accenture, IBM, and McKinsey invest heavily in capabilities that combine design thinking, marketing, and data analytics to plan entire customer journey for understanding their potential customers (The Economist, 2015). The evaluation of Web 2.0 has changed the perspective of the internet into a social domain where consumers generate their perspective about a brand/product and share it with others to make a better purchase decision. This shared information is considered to as electronic word of mouth (eWOM), and both consumers and merchants can generate it. A study shows that about 61% of consumers resort to eWOM (Electronic word-of-mouth) before buying any product, and 80% of the consumers are only willing to purchase online after investigating online customer reviews (Yusuf et al., 2018, p. 493). Because of these numerous of potentialities, researchers are showing a great interest in this technological field. Further, complicating the academic debate on eWOM (Electronic word-of-mouth) is playing the dual role of the consumers in eWOM (Electronic word-of-mouth) exchange. To this date, most researches on eWOM have focused on one of these roles at a time and consumer’s motivation behind the sending and receiving eWOM (Rosario et al., 2019, p. 423). While we explored the implication of the adoption of eWOM, there is limited understanding of the impacts of eWOM (Electronic word-of-mouth) on the customer journey. There is a growing acceptance that eWOM has a significant impact on the customer journey (Hall et al., 2017). Most of the previous studies focused on either the characteristics of eWOM or consumer behavior (Yusuf et al., 2018, p. 494). However, Knoll (2016) suggested that the characteristics of eWOM and eWOM information towards consumer behavior are necessary to improve our understanding of eWOM management but not sufficient to understand the influences of eWOM on consumer's buying journey. Additionally, investigating the influence of eWOM in the customer journey remained an open area to conduct research (Yusuf et al., 2018, p. 494).
1.4. Research Gap: Though both customer journey and eWOM have upward trends in the business field, relatively little attention is received for combining these two phenomena to investigate the influence on customer purchase decisions. According to (Kannan & Li, 2017, p. 27) understanding, the role of various touchpoints for determining customer purchase journey is an important area to focus on for the practitioners. It also highlights that the characteristics of eWOM have a significant influence on making purchase decisions (Hall et al., 2017, p. 499). Therefore, the statement mentioned above leads us to believe that there would be some considerable influences of eWOM, and these influences can last throughout the customer journey of the consumers. Again, when a business operates internationally on a digital platform, national boundaries become the main obstacle for the consumers in different cultural settings (Park & Jung, 2018, p. 391). However, prior psychological studies by Nisbet et al. (2001) investigated that there are lots of differences between the thinking style between the easterners and the westerners where 13 the Easterners prefer to think holistically, and the Westerners prefer analytically. These cross- cultural behavioral differences between the national boundaries may influence the processing of eWOM during the journey of making a purchase decision. While searching the literature, we find that research on cultural differences on the customer purchase journey for the influence of eWOM has been significantly undetermined in the practice field. For finding out the importance of our research gap, we looked for the Marketing Science Institute (MSI), which publishes research agendas and proposals concerning the impact and importance of the topic in the present marketing field. The current MSI’s research priorities, 2020-2022, are grounded in marketing topics to collaborate researchers and marketers. The recent COVID-19 pandemic has incredibly increased online activity (Marketing Science Institute, 2020). Marketing Science Institution discovers several areas for conducting research, and several research priorities relate to determining the behavior of consumers. Several marketing research trends are omnichannel customer journey, customer decision-making trends, and the customer technology interface related to the influence of eWOM on determining customer purchase intention. Therefore, we intended a research gap where we can identify the influence of eWOM during the different stages of the customer journey. Furthermore, the customer journey is a complex process, and the purchase decision of the consumers directly depends on this road of purchase. Despite this research gap in the practice field, we have presented our research question in the coming up section.
1.5. Research Question:
Based on the presented research gaps, we have chosen to conduct our research on the influence of eWOM in the stages of the customer journey and that creates direct consequences on the process of making the purchase decision. There has not been a lot of research looking at eWOM influences throughout the entire customer journey but only the single aspects for both fields. The combination of eWOM and the customer journey influences the consumer's purchase intention and buying behavior with the unique cultural characteristics of the consumers.
Additionally, a customer journey and cultural boundaries are the complex structure that needs to be evaluated and considered in various paradigms. For this study summing up everything we have discussed, we prepared our research question to continue our thesis.
How does eWOM affect throughout the customer journey towards the customer’s purchase intention in Bangladesh and in Sweden?
1.6. Research Purpose: The primary purpose of our study is to investigate the differences in the customer’s purchase intention because of eWOM towards two different cultural boundaries. We have decided to use Hofstede’s cross-cultural dimensions theory to examine the cross-cultural differences between Bangladesh and Sweden. Moreover, this phase of our research question will help us contribute 14 broader knowledge on the differences between cultural boundaries in terms of making purchase decisions by eWOM. Nevertheless, this paper consists of two sub-purposes that aims to identify the characteristics of eWOMs in different stages of the customer journey. We expect that the effects of the eWOM throughout the customer journey might be different in every stage. Therefore, by examining this motive, we can determine which stage of the customer journey eWOM has the most vital influence. The outputs of our study will help future researchers and businesses get ideas about the most effective stage of the customer journey influenced by eWOMs. The second sub-purposes of this paper are to prosper in a more profound knowledge about the customer journey and eWOM since these two aspects are the active topics for the practitioners. More specifically, our purpose with this research question is to investigate a specific type of touchpoints in the customer journey that we consider as eWOM and its significant influences throughout the journey.
A total overview of the purposes can be found in Table 1.
Research How does eWOM affect throughout the customer journey towards the Question customer’s purchase intention in Bangladesh and in Sweden?
Main Purpose To examine the cultural differences between Bangladesh and Sweden in terms of customer’s purchase intention by eWOM.
Sub-purpose 1 Go through in-depth of different components of eWOM that impact customer journey leading to influence customer purchase intention.
Sub-purpose 2 To investigate a specific type of touchpoints in the customer journey that we are considering as eWOM and find out its influences throughout the customer journey.
Table 1: Research question and overview of the purposes
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2. Theoretical Framework:
In this chapter we will present the main theories and literature. We will further discuss those theories in relation to our research question and the purposes of this study. The chapter will end with a conceptual framework that servers as a foundation of our empirical research. 2.1. Introducing eWOM: In consumer behavior studies, the understanding of social interactions has always been a fundamental issue for marketing research (Vázquez-Casielles et al., 2013). As a part of social interactions, the concept of word of mouth (WOM) has gradually developed as a critical factor influencing consumer behavior and their purchase decisions (Torlak et al., 2014). The first author defining word of mouth was Arndt (1967), who stated that 'Oral, person-to-person communication between a receiver and a sender in which the receiver receives non-commercial messages related to products or services from the sender.' Strong relationships between receivers and senders increase the power of WOM (Bansal & Voyer, 2000, p. 175). WOM can either be consumer-generated or marketer-generated. However, consumer-generated WOM is more credible than marketer-generated WOM for the consumers (Arndt, 1967). After the inception of WOM, there have been several pieces of research have been conducted as it becomes a vital issue for determining consumer behavior. Furthermore, a study shows that WOM is nine times more effective than traditional media advertising (Day, 1971). Previous research suggests that WOM influences consumer behavior more than product information provided by the companies (e.g., advertisement). WOM has always been the focus of researchers; in the past few years, with the emergence of the internet and new possibilities of communication, a new form of WOM is present on the market described as the electronic word- of-mouth (eWOM). However, this newly emerging phenomenon is more ubiquitous rather than being personal like traditional WOM. By getting technological support, the internet has become extremely widespread, and it has influenced the modes of communication used and preferred by people (Nuseir, 2019, p. 759). Since the inception of eWOM, it has become the widely used medium to share opinions and reviews of various products and services available in the market. For consumers, eWOM as a crucial source of product information with a considerable influence on buying behavior. In this response, organizations are conferring more importance to the management of eWOM (Tsao & Hsieh, 2015, p. 510). In today's world, before purchasing an electronic gadget, selecting the travel destination, or choosing the airlines, a customer tends to go on the internet to look for other customers or expert's opinion and the aim is to make better purchase decision (Khan et al., 2018, p. 330). The internet has transformed and facilitated the way people communicate with each other. This progress has brought a new ground-breaking perspective for the traditional word of mouth and a new name, 'electronic word of mouth (eWOM).' Electronic word of mouth refers to the product and service-related opinions and experiences shared by other consumers or experts via an online platform (Khan et al., 2018, p. 330). One of the recognized definitions of eWOM given by Hennig-Thurau et al (2004, p. 39) is 'any positive or negative feedback made by potential, actual or former customers about a product or company that is made available to a multitude of people and institutions via the internet.' So, eWOM is a positive or negative statement about a product, service, or company spread by consumers via the Internet. (Hennig-Thurau et al., 2004) also state that eWOM mostly takes 16 place on online opinion websites (e.g., Yelp, Google my business), websites that are indexing reviews (e.g., IMDb), shops that offer customers the possibility to review and rate products (e.g., Amazon, Alibaba), and other consumer websites. Again, eWOM also exists on different social media platforms like Facebook, Twitter, and YouTube in the form of video reviews. The constant development of online and social media environments shapes the way individuals interact with other potential or actual customers about products, services, and different brands. Communicating one's own experiences with products or brands has never been easier, as now it only takes a few seconds, for instance, to rank the quality and specifications of an electronic product one has already used on Yelp.com, which helps the potential future consumer to make vital purchase decisions. Litvin et al. (2008, p. 461) define e-WOM as "any informal communications directed at customers via the internet on the use or the qualities of specific goods and services, or their sellers." This type of interaction between the consumers falls under uncontrollable marketing communication where companies are not involved rather than consumers directly initiate the contents and control them (Krystallis & Chrysochou, 2014, p. 142). Many researchers have discussed this power shifting from the companies to consumers (Burton & Khammash, 2010; Labrecque et al., 2013; Laroche et al., 2012). This power enables the consumer to influence the products or brands by voicing any concern on the Internet where they become visible to many individuals. Thus, the companies may find it more challenging to influence the consumers by the marketing communication messages with various alternative sources of product-related information available to the individuals by the actual consumer (Yang et al., 2016, p. 118). EWOM also can be both consumer-generated and marketer-generated, just like traditional WOM. There are number of possible contexts where eWOM can take place and exact conceptual boundaries. Depending on the research components of eWOM and focus of the study, the eWOM concepts can encompass additional elements. In the table:2, we present various conceptualization and operationalization of eWOM from the year 2002-2020 where we can identify various definition of eWOM as well as the research components and contexts.
Conceptualization and Operationalization of eWOM:
Author(s) Year Definition Research Research Components Context
Ridings et al. 2002 N/A Desire to get Virtual information, desire community to give information
Hennig-Thurau 2004 eWOM communication Frequency of Consumer et al. is any positive or platforms visits, opinion negative statement made number of platforms by potential, actual, or comments written former customers about a 17
product or company, which is made available to a multitude of people and institutions via the Internet and can take place in many ways.
Goldsmith & 2006 eWOM considers the Opinion leadership, Consumer Horowitz fastest and easiest way opinion seeking opinion for the pre-purchase platforms consumer to get all the sorted list of either positive or negative comments from the experienced consumers.
Dellarocas et al. 2007 N/A Volume, Valence, Review Dispersion websites
Fong & Burton 2008 N/A Information seeking Online and information discussion board giving
Litvin et al. 2008 eWOM can be defined as Intention to give all informal information, communications directed intention to obtain Online brand at consumers through information, bulletin boards Internet-based intention to pass technology related to the information usage or characteristics of particular goods and services, or their sellers.
Bronner & 2011 eWOM involves Advice seeking, Consumer consumers comments advice giving generated, De Hoog about products and marketer services posted on the generated, Internet; for example, the mixed websites rating on a 10-point scale of a hotel and textual comments on the service and location. 18
Wolny & 2013 eWOM can be observed eWOM engagement Facebook, Mueller by peers such as ‘liking’ Twitter. a brand on Facebook or recommending a story on Twitter, as well as product reviews and comments on social networks.
Filieri 2015 Online consumer reviews Information quality, Online settings, (OCRs), which are the product ranking, online electronic version of source credibility organizations word of mouth, are enabling consumers to share their experiences, opinions, and feedback regarding products, services, or brands for other consumers.
Chu & Kim 2018 eWOM involves the eWOM and viral Online behavior of exchanging advertisement, advertisers, marketing information effects of eWOM, policy makers among consumers in drivers of eWOM online environments or via new technologies (e.g., mobile communication.)
Ismagilova et al. 2019 Electronic word of Argument quality, Customer mouth (eWOM) is valence, usefulness, purchase defined as the dynamic trust, credibility, intention and ongoing information attitude, volume exchange process between potential, actual, or former consumers regarding a product, service, brand, or company, which is available to a multitude of individuals and institutions via the Internet 19
Ngarmwongnoi 2020 N/A eWOM quantity, Purchase, post- et al. credibility, attitude purchase, towards eWOM customer journey
Tandon et al. 2020 N/A Website quality, Website quality, effects on e-shopping satisfaction, repurchase intention, shipping and handling
Zhang et al. 2020 Virtual communication Information quality, Social e- between consumers who trust, social Commerce have never met in real phycological platforms life. distance, purchase intention
Table 2: Literature table of eWOM
2.2. Classification of eWOM: The information on the internet is often provided by the marketers via company-generated websites while the online communities enable people to share their views and opinions by creating discussion content. Blogs, consumer review websites, shopping websites, and social media websites are all different types of eWOM platforms (Cheung & Thadani, 2012, p. 466). According to Hu and Ha (2015, p. 17), eWOM has differentiated into four channels.
• Specialized e-WOM: It refers to customer reviews posted on specialized comparison- shopping or rating websites. These websites do not sell products rather they provide customer reviews on specific products or all kinds of products. (e.g., Yelp, Consumer Search, IMDB).
• Affiliate e-WOM: It refers to customer reviews on retail websites. These websites provide both products/services as well as reviews at the same time. (e.g., Amazon, AliExpress).
• Social e-WOM: It defines any information related to brands or products in the social media platforms to its users. (e.g., Facebook, Twitter, YouTube).
• Miscellaneous e-WOM: It includes brand/product-related information on any other online platform. (e.g., E-mails, Blogs). 20
2.3. Advantages and disadvantages of eWOM: The increasing usage of the internet has contributed a lot to the progress of eWOM. Traditional word of mouth communication strategies has become easier and faster via technology, particularly for the internet (Trusov et al., 2009, p. 90). Due to rapid and more widespread spans, customers' decision-making process has become more powerful and informative than traditional word-of-mouth (Ishida et al., 2016, p. 1). Besides, the advent of mobile devices has made eWOM more and more convenient, as it enables people to reach the internet from anywhere and at any time. Like traditional WOM, this new version of conducting word of mouth has some advantages and disadvantages both for consumers and marketers.
The main benefit of eWOM is the user will have the ability to gather information about any products or services before purchase and can give comments as a review about brands which helps the future customers to process their buying decision (Hennig-Thurau et al., 2004, p. 41). On the one hand, this is a great opportunity for marketers to introduce their products and services in a cost-effective way. In addition, the internet provides a platform on eWOM for both marketers and consumers to communicate with one another and this chance for communication can be beneficial for both consumers and marketers.
One of the serious disadvantages we have noticed during our study is the unethical use of eWOM which is known as fake reviews. Fake reviews can be classified in two ways; create review by using a false identity (Malbon, 2013, p. 10) and review purchase (Davide et al., 2020). Both are harmful for businesses. Malbon (2013, p. 13), also mentioned fake reviews as unfair treatment of products. For investigating more on unethical issues of eWOM, HBR (Harvard Business Review) has done an empirical analysis and found that, fake reviews are spreading overwhelmingly, and it is getting harder for marketers to root them out. Amazon is taking this issue seriously and in 2019, Amazon spent more than $500 million and more than 8000 employees to filter out those fake reviews and successfully removed 40% of them (Davide et al., 2020). According to HBR, Yelp has filtered out 16% of reviews and considers them as fake reviews. The US, and UK government have also considered this issue as an illegal practice and in 2008 the UK governments defined that “falsely acting oneself as a consumer” is a crime and set penalty rules (Malbon, 2013, p. 13). Again, some specific people search for ordinary people on social media platforms to make positive reviews and get paid and many people are taking this opportunity as an easy way to earn (Davide et al., 2020).
However, two more critical features of eWOM can be both advantages and disadvantages for marketers. First, eWOM can reach a large audience even millions of users through the internet (Cakim, 2009). Second, an opinion on eWOM platforms can be spread in a very short time (King et al., 2014). These two features offer a great opportunity for the marketers, but negative reviews and comments are also spread quickly in a huge number of consumers; in such cases, eWOM can be harmful to the product as well as the brand (Ferguson & Johnston, 2011, p. 120). Besides, eWOM is very difficult to control just like traditional word of mouth (Godes & Mayzlin, 2004) Overall, eWOM has some negative aspects in addition to its positive ones yet it is considered as a powerful marketing tool in the Web 2.0 era (Sweeney et al., 2012, p. 249).
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2.4. Components of eWOM: As we mentioned, eWOM is very crucial because modern customers search for more information before making a purchase decision. In previous studies on this field, researchers studied different components of eWOM. However, in the following section, we provide an insight into several components of eWOM from the consumer perspective as our study fits on that.
2.4.1. Channels: Lamberton and Stephen (2016, p. 168), stated that we are rapidly entering into a ‘post digital’ world where digital marketing is just marketing, simply because all marketing activities have a digital aspect. The easy access to the internet has allowed customers to take the role of spreading product-related content to many audiences. Gvili and Levy (2016, p. 1033) mentioned that channels corresponding to eWOM are distinctive in terms of how they are applied, their capability to fulfill the customer demand, and their usage characteristics.
We have discussed four different channels or platforms where eWOM can be generated. Due to the differences between the channels, audiences or users may differ too, and as a result, firms use various methods to communicate with the potential customer (Kudeshia & Kumar, 2017). As the reviews and comments are delivered differently on different platforms, customers show different attitudes towards different eWOM mediums; therefore, marketers rely on five determinants of customer attitude towards eWOM (Gvili & Levy, 2016, p. 1031). These are Entertainment, Irritation, Value, Credibility, and Informativeness. Figure 1 illustrates the relationship between these five determinants.
Figure 1: Attitude towards eWOM channels (Adopted from Gvili & Levy. 2016, p. 1031)
2.4.2. Valence: Valence on eWOM has an impact on purchase intention (Kudeshia & Kumar, 2017). Amblee and Bui (2011) explain that the valence of eWOM pinpoints the nature of the information, which could reveal a neutral, positive, or negative tone. Furthermore, Lin and Xu (2017, p. 364), claim that positive reviews are more appreciated and passed on to other people because it impacts how customers perceive the brand. Some negative reviews on eWOM platforms are more appreciated and seen as more informative by the consumers (Schindler & Bickart, 2012, p. 235). On the other hand, products with positive reviews and comments are more recommended to friends than products with negative reviews (Kudeshia & Kumar, 2017, p. 322). 22
Positive valence has a significant impact to accelerate customer buying behavior. Earlier research claims that the valence of eWOM has a significant effect on purchasing intention (Mauri & Minazzi, 2013); (Ladhari & Michaud, 2015) while (Teng et al., 2014) have shown that the effect is not so notable. Therefore, valence is one of the eWOM components mentioned in this study to offer new insights into its effect on consumer purchase decisions.
2.4.3. Source trustworthiness: In the context of reviews and comments, the source trustworthiness is the vital determinant of the effect of eWOM (Lin & Xu, 2017). The perception of user-generated eWOM is described as more trustworthy and reliable compared to company-generated reviews (Kudeshia & Kumar, 2017). Kudeshia and Kumar (2017) argued that the higher the source trustworthiness of eWOM is perceived by potential consumers, the stronger is the intention to purchase. Therefore, source trustworthiness towards the consumer is positively related to the credibility of the eWOM which helps to affect the consumer purchase decision.
2.4.4. Length: Length is another important component of eWOM that has an impact on properly reading the full review or comment. Previous literature suggests that longer reviews and comments receive higher helpfulness ratings from potential consumers. However, in the platform of eWOM, a review or opinion can be too long or too short. (Schindler & Bickart, 2012, p. 236) state that based on the maxim of quantity, the main rule in conversations is that the reviewers only deliver necessary information about the product to avoid confusion between other consumers.
Lengthy online reviews increase the user ratings and for sensible products, lengthy eWOM is more helpful in generating consumer purchase decisions (Mudambi & Schuff, 2010, p. 194). However, Park and Lee (2008, p. 387), argued that the products that receive larger online reviews might demand a larger burden on future potential consumers. Information overload exposes that the consumer purchase processing ability has been shown to make low-quality decisions with low confidence, nonetheless if receiving too little information the consumer may feel as though they do not have enough information (Furner et al., 2016, p. 800). Previous studies on the length of eWOM suggested that an overwhelming amount of information in the eWOM platform may block the consumer purchase intention (Park & Lee, 2008, p. 389). Therefore, we believe that the length of eWOM is the component that triggers the customer purchase intention.
2.5. Introducing Customer Journey: Over the decades, marketing and consumer behavior processes are investigated by researchers with the five stages of the decision process, which started with need recognition and ended with the post-purchase stage. The concept of the customer journey is relatively new in terms of being reviewed in marketing literature. Kojo et al. (2014, p. 263) characterized the customer journey as 'all activities and events related to the service delivery from the customer's perspective. It is an emotional and physical journey that customers experience.' According to Norton and Pine (2013, p. 12), "customer journey, in essence, means the sequence of events – whether designed or not – those customers go through to learn about, purchase and interact with company offerings – including commodities, goods, services or experiences." Böcker 23
(2015, p. 167) centralized the customer journey on the relevance of searching information by the consumers and the customer journey as a process starting with the first desire of buying a product and ending with the actual purchase. Lemon and Verhoef's (2016) recent contribution are considered one of the leading articles of the customer journey and referred by other articles in this field. Lemon and Verhoef (2016, p. 79) explained customer journey as "customer’s interaction with multiple touchpoints and moving from consideration, search, and purchase to post-purchase, consumption, and future engagement or repurchase." Another study defined the customer journey as visual representations of the events or touchpoints identified sequentially and often accompanied by emotional indicators (Halvorsrud et al., 2016, p. 3). Furthermore, Wozniak et al (2018, p. 88) mentioned customer journey as a series of exposures or experiences of touchpoints in multiple channels and media along different stages of the consumer decision-making process. After recognizing the influence of touchpoints in the customer journey roughly, all the authors appreciated touchpoints as vital for proceeding with the customer journey. Again, in the literature, there exist two different views about the structure of the customer journey. Wolny and Charoensuksai, 2014; Canfield and Basso, 2017 argued that the customer journey process is not linear rather than a customer-oriented technique. While other authors claim customer journey as a process of the stage, sequence, or series (Lemon & Verhoef, 2016; Hamilton et al., 2019; Wozniak et al., 2018; Yachin, 2018). In addition, the customer plays the center role of the customer journey (Wolny & Charoensuksai, 2014; Lemon & Verhoef, 2016; Canfield & Basso, 2017; Hamilton et al., 2019), and the previous experience of the customer influences a lot for prospering the customer journey more thoroughly (Lemon & Verhoef, 2016; Kuehnl et al., 2019). Nearly all the authors admitted that customers and the customer’s experiences are the vital elements in the customer journey and the decision-making process towards purchasing. Table 3 shows the list of articles on customer journey from the year 2014-2020. We have analyzed and compared these articles based on presented structure of customer journey. As we earlier mentioned earlier that customer journey can be both looping and non-linear in nature and associate with behavioral and cognitive customer responses. This chart also illustrates the various findings of the customer journey that reflects the findings of the previous studies.
Literature table of Customer Journey Findings and Structure:
Author(s) Year Title Findings Structure
Mapping customer Understanding on how journeys in consumers use and react Wolny & 2014 multichannel decision- to different media and Non- Charoensuksai making channels in the linear
customer journey of buying cosmetics. 24
Helping firms reduce Developing and testing Anderl et al. complexity in taxonomy-based 2015 multichannel online approach that influence Non- data: a new taxonomy- customer decision linear
based approach for making process. customer journeys.
Integrating satisfaction Testing the map of and cultural background customer journey along Canfield & 2016 in the customer journey: the service process and Non- Basso a method development improve managerial linear
and test application on customer journey process.
Improving service Using customer journey quality through framework as an Halvorsrud et al. 2016 customer journey approach, designed to Linear
analysis the service delivery process.
Understanding Understanding of customer experience customer experience Lemon & 2016 throughout the and customer journey Linear Verhoef customer journey process towards
complex customer behavior.
Customer experience Demonstrating mobile research with mobile ethnography as the Bosio et al. 2017 ethnography: a case assessment of customer Linear
study of the alpine experience by accessing destination serfaus-fiss- data in a holistic way. ladis
Understanding Explaining a fruitful customer journey from foundation to complex Varnali 2018 the lenses of complexity nature of customer Non- theory experience and linear understanding the concept of the customer journey. 25
Psychological Analyzing the effects of antecedents of mobile psychological factors on Wozniak et al. 2018 consumer behavior and mobile consumer Linear implications for behavior. customer journeys in tourism
The customer journey: Exploring customer learning from customers encounters towards Yachin 2018 in tourism experience customer journey as Linear encounters. learning opportunities.
The effects of scarcity Reviewing research on on consumer decision marketing, psychology, Hamilton et al. 2019 journeys economics, and Linear economic construct an integrative framework and influence consumer in various stage of customer journey.
Grewal & 2020 Understanding retail Understanding the role Non- Roggeveen experiences and of customer experience linear customer journey throughout customer management journey and the non- linear nature of customer journey.
Here today, gone Understanding tomorrow? Mapping marketplace-based pop- Rudkowski et al. 2020 and modeling the pop- ups within the customer Non- linear up retail customer journey and exploring journey. the touchpoints ownership.
Table 3: Literature Table of customer journey
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2.6. Stages of the customer journey: Lemon and Verhoef (2016, p. 74) propose that the customer's experience can be defined as a journey that includes various touchpoints towards the entire process. The customer journey starts from pre-purchase, which incorporates all aspects the customer has experienced regarding the brand, product category, and environment before purchase. This phase of the journey usually includes needing recognition, independent search, and alternative evaluation. The purchase stage covers all customer interactions with the brand and its environment during the purchase event itself. Acts such as choosing, ordering, and paying are typical features of this phase. The final stage, post-purchase, includes all the customer interactions with the brand/product after the purchase transaction. This phase involves the most significant interactions between customer and product; therefore, it is considered crucial in the customer journey. These interactions cover behavior such as convention, consumption, evaluation, and other post- purchase functions. Figure 2 describes different functions of the customer journey in each stage.
Figure 2: Customer Journey Process (Adopted from Lemon & Verhoef 2016)
2.7. Non-linear customer journey: As in the earlier part, we have discussed an alternative view on adhering to linear or sequential stages in the customer journey. Wolny and Charoensuksai (2014, p. 319) mentioned that the customer journey is a non-linear structure contrary to linear decision-making models. Again, the recent article (Grewal & Roggeveen, 2020, p. 4) referred that there is a loop in the customer journey where past experiences influence present and future experiences and today's experiences become the past experiences for tomorrow. Because of the increased intensity of trialability, consumers may jump from the pre-purchase stage to the post-purchase stage. Advanced technologies (e.g., AI, mobile, internet) can help non-linearities mark the customer journey (Roggeveen et al., 2020). For example, electronic goods and cars can order replacement products, request service, or scheduled deliveries that do not need the customers 27 to be involved in the purchase stage. Grewal and Roggeveen (2020, p. 7) mentioned that each decision stage of the consumer journey is incorporated with cognitive, emotional, and behavioral elements. The technological role, the importance of social and cultural factors, and the role of the business environment, numeric information, and packaging are the aspects that represent non-linearity in the customer journey.
2.7.1. Social and cultural influence: Social influence has always been an essential aspect of consumer behavior. According to Argo and Dahl (2020), social influence on the customer journey can appear active or passive. An active social presence implies verbal and physical interactions between the customers and others. In opposed passive social presence approaches without any personal interactions but the customers relate to employees using other sources. Recently, several researchers have tried to determine the importance of social media to influence customer journeys (Appel et al., 2020; Grewal et al., 2019; Roggeveen et al., 2020). For example, at present, consumers are more preferred to read online reviews, check ratings, and engage with virtual employees or chatbots before making a purchase decision. These social and technological tools create a plethora of opportunities for manufacturers, consumers, and researchers. Some iconic issues will be presented below in the technology section. Hofstede (1984), various dimensions of culture also have a noticeable influence on the customer journey (Grewal & Roggeveen, 2020, p. 6). Recent studies by Shavitt and Barnes (2020) demonstrated novel insights on how collectivist and individualist cultural differences influence the customer journey. When a consumer evaluates a product, compares price, reads reviews, or receives a coupon in the mail, cultural factors strongly influence how they respond (Shavitt & Barnes 2020 p. 40). Again, other cultural dimensions, such as power distance, global-local identities, uncertainty avoidance, masculinity/femininity, and time orientation, also significantly influence the customer journey. Likewise, modern technology agents (e.g., chatbots, virtual employees) have different impacts on the customer journey in different cultures.
2.7.2. Technological Influence: Technology is becoming an unavoidable factor in the consumer journey. Various studies mentioned the technology factors; in-store technologies (Grewal et al., 2019), mobile technologies (Grewal et al., 2018; Tong et al., 2019), social media (Appel et al., 2020; Herhausen et al., 2019), and AI (Davenport et al. 2019; Longoni et al., 2019) that the consumers adopt for having the better purchase decision process and the manufacturers for investigating the touchpoints in the customer journey. An appealing consequence of recent technological advances made the consumers more powerful than ever (Grewal & Roggeveen, 2020, p. 7) such as e-WOM, consumers can share their opinions towards any product/brand on a public platform and can make an impact on other’s purchase decisions by using this technological advancement. Moreover, these platforms allow consumers to share content about their experiences (Schmidt-Rauch & Schwabe, 2013), promoting user-generated content (Dedeoğlu et al., 2020; Hays et al., 2013), and exploiting eWOM (Yu et al., 2013). We have discussed earlier that eWOM has various potentialities to 28 influence the touchpoints throughout the customer journey. Another recent advancement of technology is personalized solutions where the consumer can personalize their desired product. Van Osselaer et al. (2020) discuss how powerful personalization can be towards the customer journey. As technology advances, the customer journey has derived and has become even more complex. To understand the influence of technology on consumer purchase decisions, we have to look for the modern-day customer journey. Today’s consumers want a different experience depending on the product they are looking for (Vidal, 2017). Luckily, technology helps them provide the exact solution they are searching for which intensely impacts the customer journey.
2.7.3. Numerical information and packaging cues: Consumers encounter a wide range of numerical cues (Grewal & Roggeveen, 2020, p. 7). Some numbers are readily apparent such as prices, size, weights, calories, and nutritional information. Other compelling numerical cues are age (e.g., the year a wine was produced), the number of clicks on a used camera, model number of a phone, etc. On the other hand, in the online customer journey, apart from these numerical cues, consumers observe the number of reviews posted, star ratings. Researchers have conducted some interesting insights on these numerical cues, such as whether the large number should be to the left or right (Biswas et al., 2013) in a comparative context, numerical fluency, and number multiply (Coulter & Roggeveen, 2014), numeric framing cues (Guha et al., 2018). This explicit research highlights the importance of number signs shaping the customer journey. Another critical determinant that influences the customer journey is packaging cues. Millions of packages are being sent by e-commerce platforms, and nearly every major manufacturer has its products delivered. Moreau (2020, p. 157) mentioned that when a product is delivered in a specific packaged way and unpacked by the consumers, it can have a considerable impact on the current consumption experience and their future purchase decision. These determinants structured the customer journey nonlinearly and influenced the final purchase decision. By accepting these factors, consumers can jump into any stage of the customer journey and possess a better experience for their future purchases.
2.8. The role of Culture: Bennett (2015, p. 551) defined culture as "shared perceptions of the social environment that incorporates language, art, customs, habits, knowledge, morals, and beliefs acquired by a person in the process of socialization. For understanding the cross-cultural differences across the world, several models have been developed (e.g., Hofstede, 1984; De Mooij & Hofstede, 2010; Voss, 2012). The framework developed by Hofstede (1994) is widely used in global marketing and advertising studies, and he defined culture as the collective programming of the mind that separates members of one group or category of people from members of other groups or categories. The most recent research defined Culture as "values, stories, frames, toolkits or categories of a social group" (Beugelsdijk et al., 2016, p. 31). However, Hofstede's cultural dimensions model acknowledges Culture as a national-level phenomenon and can be used for determining individual behavior between different nations (Luo et al., 2014, p. 446). 29
Hofstede developed six cultural dimensions named; power distance, uncertainty avoidance, individualism-collectivism, masculinity, long-term orientation, and indulgence (Hofstade, 2011, p. 8). There has been increasing interest to investigate cultural dimensions and their impact on eWOM among the researchers (Choi & Kim, 2019; Stamolampros et al., 2020; Tang, 2017; Wen et al., 2018). Significantly, the cultural dimension of individualism and collectivism play a vital role in influencing electronic word-of-mouth as this determinant indicates the relationship of social media users, which can shape consumer’s motivation and behaviors (Tao & Jin, 2017, p. 65). Several numbers of cultural research documented that electronic word-of- mouth behaviors among social media users are significantly influenced by the individualistic and collectivistic culture (Chu & Choi, 2011; Jackson & Wang, 2013; Qiu et al., 2012). An experimental study by Argyriou (2012) found that the eWOM more likely influences the easterners due to their collectivistic tendency than Westerners. Again, Chu and Choi (2011) suggested that Chinese social media users (easterners) are more active in opinion seeking and opinion giving activities than the Americans (westerners). Likewise, individualistic cultural consumers are more scientific, data-oriented, and direct, whereas collectivistic cultures prefer to seek information from online reviews as they tend to be more intuitive and subjective (Choi & Kim, 2019, p. 294). Since the patterns and motives of social media users are shaped by the cultural context that has influenced the pattern of eWOM across the national boundaries (Lam et al., 2009, p. 64), we anticipated that the easterner eWOM users are driven by a different set of motivation than the westerners. As we have mentioned, most of the prior research on eWOM and culture has primarily addressed the cross-country-level comparisons of the influences of individualism and collectivism usage of eWOM. The next part will discuss more about the individualist and collectivist cultural behavior, examples, and its influences over eWOM.
2.9. Individualist vs. Collectivist in eWOM: The individualist and collectivist dimension of culture aims to explain the relationship between peoples within a society. It signifies the way individuals live together, such as nuclear families, tribes, or extended families. High individualism cultures are generally 'I-conscious' cultures where people only maintain slender bonds with others. In contrast, low individualism, also called collectivism, is 'We-conscious' where other members are denied top priority to hold close bonds with friends, families, and society (Hofstede, 2011, p. 11). These differences between the cultures are powerfully relevant to the procedural perception of something emerging. Procedural justice perception differs across the individuals depending on their individualist and collectivist cultural values (Kurosawa, 1992, p. 252). Individualism and collectivism are the most frequently used dimension of cross-cultural consumer research (Aaker & Maheswaran, 1997; Han & Shavitt, 1994, Chu & Choi, 2011; Jackson & Wang, 2013; Qiu et al., 2012). Additionally, past eWOM research showed the influences of individualist and collectivist culture among online communities (Madupu & Cooley, 2010, p. 364). To conduct this study, we have used (Compare Countries, 2020) to determine the cultural differences between the easterner and the westerner, and we select Bangladesh as the eastern and Sweden as the western country. According to Compare Countries, 2020, there are huge gaps between these two countries in every dimension of Hofstede's cultural insight. Figure: 3 shows the cultural differences between these two countries. 30
Figure 3: Cultural dimensions between Bangladesh and Sweden (Adapted from Compare Countries, 2020) As we mentioned prior, it is obvious to assume that all people in an individualistic and collectivistic country are individualists or collectivists. Figure 3 demonstrated that Bangladesh is a low individualistic country with a score of 20, whereas Sweden is a high individualistic country by scoring 71. Again, the figure highlights that individualism and indulgence are the two cultural dimensions comparing Bangladesh and Sweden, which have the highest variation. However, Chu and Choi (2010) discover that online social networking site users in the individualist culture tend to demonstrate their performance. On the contrary, the collectivist culture tends to present itself to build up social ties with friends and family. Similarly, several studies (Yamagishi et al., 1998; Allik & Realo, 2004; Huff & Kelley 2003; Van Hoorn, 2015; Tang, 2017) have found that individualist countries such as the USA or Sweden have a higher level of propensity to trust eWOM than the collectivist country like China or Bangladesh. Furthermore, in this study, we consider that consumer-generated content on the internet includes positive and negative reviews, which have different motivation sets across different national boundaries, such as Bangladesh and Sweden.
2.10. Purchase intention and eWOM: Determining consumer purchase intention has always been a topic of particular interest among researchers in the marketing field. Therefore, many models and theories have been developed analyzing how purchase intentions within consumers are formed and which factors influence the process. Many factors influence consumer purchase intention. Everything related to human activities and behavior can be investigated whether it influences purchase intention or not. Traditional word of mouth is a powerful source of information that influences the consumer purchase intention by constructing a perception towards a product or service (Steffes & Burgee, 2009, p. 42). The WOM originated from the strength and impact of interpersonal relationships (family, friends, peer-group). The stronger these relationships and bonds, the more faith is generated regarding the experiences that may cause a positive or negative WOM, directly impacting consumer purchase intention (O'Reilly & Marx, 2011, p. 332). 31
Additionally, eWOM is an extension of traditional WOM communication set in social networking sites or brand webpages and has a potential influence on consumer purchase intention (Joshi & Singh, 2017, p. 150). another researcher mentioned that One of the most common consequences of eWOM communication is consumer purchase intention. (Sher & Lee, 2009; Lee & Lee, 2009). A considerable number of researchers has found eWOM as a very influential variable on purchase intention (Bickart & Schindler, 2001; Chan & Ngai, 2011; Huang et al., 2011; Kumar & Benbasat, 2006; Park et al., 2007; See-To & Ho, 2014; Zhang et al., 2010). Customer attitudes towards a product or brand depend on the positive and harmful amount of eWOM in different platforms (Lee et al., 2008, p. 17). Again, Chang and Chen (2008) mentioned that recommendations from the previous customers are positively associated with the future customer’s intention to purchase, and in a straight line can affect customer's choice. Social media plays an essential role in enhancing eWOM conversations by allowing customers to interact with others. The introduction of social networking platforms such as Facebook, Twitter has become the most extensive online virtual community and the biggest platform for eWOM generation and information gathering (Royo‐Vela & Casamassima, 2011, p. 517). Moreover, with the emergence of social media, people prefer to spend more time on different online social networking channels, which likely generate more eWOM conversations and facilitate the exchange of opinions and experiences among customers before making the purchase decision. This consumer attitude has encouraged the researchers to figure out the significance of eWOM on the purchase intention in social media (Wallace et al., 2011; Wang et al., 2012; See-To & Ho, 2014; Erkan & Evans, 2016). With the arrival of advanced Web 2.0 and search engine optimization, today's consumers can search about any product or service at any time. This advanced intermediary helps consumers make purchase decisions and inspect several opinions given by the previous consumers (Xu, 2014, p. 139). These shared opinions can generate positive or negative eWOM that influences the customer's purchasing intention. Positive reviews lead the consumers to believe the product to be desirable because of other consumers who bought the product before (Park & Lee, 2007, p. 129). In contrast, if masses of the reviews are negative, consumers willing to reject the product as "disagreement with others is likely to result in psychological distress" (Park & Lee, 2008, p. 387). Products with many reviews are identified as famous by the consumers considering the number of individuals who previously bought them, and the consumers use these shared opinions to rationalize their purchase intention (Park & Lee, 2007, p. 126). Nonetheless, eWOM is considered as one of the robust marketing tools that can leverage consumer purchase intention. EWOM has a positive influence on online shopping purchase intentions; consumers consider eWOM information when they make offline purchase decisions (Chan & Ngai, 2011; Lee et al., 2008). As in the leading article, eWOM (Hennig-Thurau et al., 2004) defined as positive and negative statements that are made by potential, actual or former customers or website visitors made through the internet regarding products or services they have used which is readily available to other consumers or internet users and the marketers as well. Before purchasing a product, consumers get influenced by the eWOM, which they do not need to conform to, rather than building trust towards the product and make the best possible decision. Therefore, in this study, we consider that eWOM has a substantial impact on customer purchase intention. 32
2.11. Conceptual Framework: In this section, we discuss the main objectives that we will study by presenting our conceptual model. We earlier mentioned our research question: How does eWOM affect throughout the customer journey towards the customer’s purchase intention in Bangladesh and in Sweden? The selected aim of this research is to justify various elements of eWOM in the road of customer journey and find out the cultural differences between two nationalities to interpret eWOM towards influencing customer purchase intention. In this chapter, we discussed the eWOM and different attributes of eWOM that are Channels; Valance; Length; Source trustworthiness. These components of eWOM impact differently to the customer journey in the context of cultural variation. Further, we mentioned Hofstede's cross-cultural theory and identified 'Individualist' as the most efficient dimension for measuring the influence of eWOM. Both individualist and collectivist cultural consumer journeys are influenced by eWOM but in a different manner that leads to the customer purchase intention. By conducting this study, we identify the differences between two national boundaries regarding processing eWOM for enabling purchase intention. Figure 4 demonstrates our full conceptual model for answering our proposed research question.
Figure 4: Conceptual Framework
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3. Scientific methodology:
3.1. Research Philosophy: Research philosophy is the assumptions concerning the nature of reality and what seen as proper knowledge (Wilson, 2014, p. 8). The main objective of scientific research is to regulate laws and theories to determine social and natural phenomena which create new knowledge. According to Saunders et al. (2012, p. 107), research philosophy is the researcher’s worldview consisting of the thoughts about the nature of a study, which influence the choice of topic, method, and research findings. During the stages of a study, the researchers have to make several assumptions regarding the reality (ontology), how the knowledge is defined (epistemology), and to what extent the subjective assumptions will affect the process (axiology) (Saunders et al., 2012, p. 124). The two fundamental research philosophies are ontology and epistemology paradigm by which researchers think and carry out their research process. We will discuss these two philosophical paradigms while simultaneously arguing for our adopted position choice regarding our research question. Ontology is the assumption which concerns the nature of the social reality in which humans exist (Long et al., 2000, p. 190). Bryman and Bell (2011, p. 716) has defined ontology as a "theory of the nature of social entities." Two factors are concerned in ontological views of research, such as objectivism and constructivism/subjectivism. "Objectivism represents the position that social entities exist in reality and external to and independent of social actors" (Saunders et al., 2012, p. 132). In the sense of objectivism ontological position, social actors have no influencing power on society. On the other hand, subjectivism interprets that "social phenomena are created from the perceptions and actions of the social actors" (Saunders et al., 2012, p. 132). Constructivism is just the opposite of objectivism, where social actors influence society's influence. The social actors are the ones who build the society, culture, and organization. Further organization or culture is determined by those actors (Bryman & Bell, 2011, p. 21). The nature of our study is designed for examining a social phenomenon to determine the behavior of the consumers and how they depict the various components of eWOM on their purchase intention. For the subjectivist paradigm, it is essential to understand the subjective reality of the consumer for determining the consumer intention, motives, behaviors, and actions toward a particular social phenomenon. Due to the nature of our study, we are taking a subjectivist or constructivist approach and believe that social actors strongly influence society. Again, the chosen subject of this study influences society. For example, this thesis will find the answer on how different factors of eWOM are influencing consumer purchase intention, and we have argued that interpreting eWOM is related to the culture where the customer’s behavior influences that culture. The second aspect of the research philosophy is epistemology, which is concerned with how to generate knowledge. According to Bryman and Bell (2011, p. 711), epistemology is the manners through which knowledge is developed or treated in discipline, and he has expressed epistemology as a theory of knowledge.' For designing a research study, this philosophy is fundamental for the researchers to decide the proper knowledge and add that knowledge to a discipline that might influence the conclusion. There are three aspects of the epistemological 34 approach: positivism, interpretivism, and realism (Saunders et al., 2012, p. 132-137). Some researchers view positivism as a descriptive method; some view it as a deprecatory term (Bryman, 2012, p. 27). However, there are still disagreements about the results through a positivist approach (Bryman & Bell, 2011, p. 15). Positivism defined that collecting data is like collecting factual information (Bryman & Bell, 2011, p. 14). On the other hand, interpretivism views humans as separate entities from the physical phenomenon because they create meaning, and an interpretivism approach aims to interpret those meanings (Saunders et al., 2016). Therefore, the role of interpretivism is to explore the behaviors of the social actors and depict them into the reality of a phenomenon. Finally, realism is the third epistemological approach, and it has a connection with the positivism approach. Realism can objectively explain consumer behavior for examining the phenomenon, and the hidden reality of a social phenomenon can be interpreted by practical and theoretical processes of social science (Saunders et al., 2012, p. 136). However, after considering all three aspects of epistemology, we chose positivism as a more practical philosophy for our study because it will enable us to reflect upon our collected data about reality, and we can get knowledge about reality by following a scientific method of answering our research question (Saunders et al., 2012).
3.2. Research Approach: According to Saunders et al. (2012, p. 144), it is essential to use theory for conducting research, and there are three ways of approaching the subject: deductive, inductive, and abductive. The result of the deduction is based on existing theory, and the researchers need to formulate hypotheses to examine the collected data. The inductive approach collects empirical data and observations to explore a phenomenon (Saunders et al., 2012, p.146). The abductive process is a mixture of both deduction and induction approaches (Saunders et al., 2012). Researchers use this approach to formulate generalized understandings.
As we mentioned, a deductive approach is when existing theories are being used to create hypotheses, and we choose this approach to conduct our study. The deductive approach allows us to draw conclusions from the result and examine our assumptions whether or not to support the theory (Saunders et al., 2012, p. 145). We have developed a conceptual framework from the existing ideas for conducting our study following we collect data and analyze it for contributing to the philosophy. Therefore, we think that the deductive approach is best suited for our selected philosophy and the primary purpose of our thesis is to testify to existing theories rather than invent a new one. Figure 5 demonstrates the process of our deduction research approach.
3.3. Research Design: The research design is an overall plan for answering the research question (Saunders et al., 2012, p. 159). Research should be designed according to the objective of the study and the study purpose. There are four classification of research purpose, and they are exploratory, descriptive, explanatory, and evaluative study (Saunders et al., 2012, p. 160). When the research problem is unexplored, it is suitable for exploratory research, while descriptive analysis is characterized by developing structure and rules to investigate a well-understood problem (Ghauri & Grønhaug, 2010, p. 56). An explanatory study aims to answer explainable 35 research questions and clarify the relationship between the variables (Saunders et al., 2012, p. 176). Lastly, a researcher wants to understand a specific phenomenon and evaluate it with different variables called an evaluative research study (Bryman & Bell, 2011, p. 52). As our research question aims to investigate other variables of eWOM throughout the customer journey towards customer purchase intention, the chosen design for conducting this research is explanatory. Further, in this study, we also evaluate the characteristics of eWOM in two different cultural aspects; therefore, an evaluative research approach is also appropriate for this thesis.
According to Bryman and Bell (2011, p. 26), the consideration of ontology, epistemology, and research approach leads to two main research designs: the quantitative and the qualitative research design. The quantitative method is characterized by the quantification of numbers, testing, and verification, structured data collection, and predetermination (Ghauri & Grønhaug, 2010, p. 105). On the other hand, the qualitative method is closely connected with the interpretive approach. It ascribes to explain a specific phenomenon related to the constructed meaning or point of view (Ghauri & Grønhaug, 2010, p. 105). To conduct this study, we have chosen the quantitative research design as a qualitative method, usually the natural methodological choice for a researcher who has a positivist epistemological assumption (Saunders et al., 2012, p. 165). The first reason for choosing a quantitative research design for the present study is that a quantitative method places emphasis on the quantification in the data collection and analysis of data, which means that the researcher has to collect data from a large sample to ensure the generalizability of the results (Bryman & Bell, 2011, p. 26). The second reason for choosing a quantitative research design is to identify if the survey questions covered all the units that we are meant to measure in this study. Moreover, from an epistemological and ontological perspective, quantitative research strategies are related to the natural science models of positivism and subjectivism paradigms (Bryman & Bell, 2011, p. 27).
We believe that using quantitative methods is more efficient and coherent with the purposes of the research question of this thesis that aim to explain the four variables of eWOM; channels, valence, length, and source-trustworthiness connected with the customer journey and lead to influence customer purchase intention. Further, we evaluate the exceptions of two national boundaries on how they obtain eWOM. To achieve our research question's primary purposes, we decided that a quantitative approach is the most appropriate research method to observe the customer purchase intention and the experiences of eWOM in between two different cultural nations.
3.4. Research Strategy: A research strategy is a step for the researchers to respond to the research issue (Saunders et al., 2012, p. 173). There are several approaches to answering the research questions, each with its own set of characteristics. The applicability of an appropriate strategy is determined by the research philosophies chosen, the data gathering method used, and the data analysis performed (Saunders et al., 2012, p. 173). The research strategy is also determined by the length of the study and the need to engage in the event. The quantitative research methodology encompasses a wide range of research methodologies, including survey research, correlational research, causal-comparative research, and experimental research. Because our quantitative research is founded on positivism, survey research is a better fit for our study design (Saunders et al., 2012, p. 174). Again, survey strategies are frequently used in deductive research methodologies to answer the questions "what," "where," "when," "who," and "how." with an experimental test of the question (Saunders et al., 2012, p. 173). Our study is both explanatory and evaluative, 36 intending to reveal the relationships between eWOM and customer purchase intent and otherwise investigating the effects of eWOM between easterners and westerners. Therefore, we think a survey is the most appropriate technique to conduct our study, which aims to "explore the relationship between eWOM and consumer’s purchase intention regarding two different cultural dimensions."
Moreover, our research followed a cross-sectional survey strategy because we used more than one case in our study. According to (Bryman & Bell, 2011, p. 53), "cross-sectional design entails collecting data on more than one case and at a single point to collect a body of quantitative data in connection with two or more variables." Cross-sectional surveys are mainly aimed at observations, and researchers aim to collect data from a sample of a target population. As our research question explores the behavior of two cultural contexts of eWOM, we believe a cross-sectional survey is more suitable for targeting our respondents.
The questionnaire for our cross-sectional survey is a self-completed questionnaire that allows the researcher to collect quantitative data and can be studied numerically through the lens of statistics and testing (Saunders et al., 2012, p. 178). A self-completed survey requires a lower cost, and it saves time compared to telephone and structured interviews. To minimize our biases, we decided to prepare a web-based questionnaire that will save money and be sent out to thousands of people at the same time. Again, the respondents have the flexibility to answer the survey at a convenient time for them. This compliance minimizes the pressure of the respondents that we expect unbiased responses for our research (Bryman & Bell, 2011). After considering all the research design alternatives, we agreed to apply a web-based survey and manual distribution on the internet to our target population. We believe that the chosen strategy suits our research question and helps us determine the relationship of eWOM between consumers in a cross-cultural context.
3.5. Choice of theories: Literature reviews are conducted to accomplish the research and theories applied in the previous study (Saunders et al., 2012, p. 603). This thesis scopes us to go through the following contents: eWOM, customer journey, culture, and customer purchase intention. Based on the previous research and theories of these, we developed our conceptual model. Firstly, we go through the existing views of eWOM and the customer journey. At the beginning of the literature, we introduced eWOM using prior theories and classified them into four platforms. In this study, we reviewed 15 articles on eWOM and determined four components of eWOM from the consumer perspective. Later, we used these four components as variables for our survey questions to identify the relationship between eWOM and the consumers. After that, we briefly discuss the customer journey and the stages of the journey. For reviewing the customer journey, we have used 12 articles from 2014-2020 and discussed the argumentation between the researchers of being linear and non-linear customer journey. From our selected papers on the customer journey, half of the researchers agreed on being a linear customer journey, and the other six argued to be non-linear. We believe that the non-linear customer journey is most suitable for identifying the relationship between eWOM and customer purchase intention for our research question.
In the second step of our study, we discuss culture by utilizing Hofstede’s cultural dimensions. The following purpose of our research is to investigate the cultural differences for accepting eWOM between the easterners and the westerners. While reviewing Hofstede’s cultural theory, we determined individualist-collectivist cultural differences are the most connectable 37 dimension for acquiring eWOM in the customer purchase intention. For clarifying this cultural dimension, we discussed the differences between the easterners and the westerners for proceeding eWOM. In the third step, we have explained the customer purchase intention and examine how eWOM influences the customer purchase intention, which leads to the customer buying behavior.
Finally, we applied these theories and developed our conceptual framework for this research to have an understandable shape. We aim to create a solid skeleton for the study that can assist us in answering our proposed research question.
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4. Practical Methodology:
4.1. Experimental stimulus product: Using the internet and smartphones is becoming widely popular these days. In such circumstances, smartphone manufacturers constantly invent new models and functions to attract their consumers and meet their needs. The smartphone is the selected stimulus to conduct this study for two reasons. First, smartphones are the products that are appealing to both easterners and westerners and purchased by the respondents. Smartphone penetration is very high in both Bangladesh and Sweden. Moreover, a prior study by Dwidienawati et al. (2020) suggests that online reviews of high-end products, such as smartphones, are the relevant stimulus to determine the real purchase intention of the consumer. For example, Xiaomi brand smartphones have recently faced a significant positive change in market share among other smartphone brands, and this fact occurs because of huge eWOM about the brand in different online platforms to influence consumer purchase intention (Putra et al., 2020). The second reason for choosing smartphones as our stimulus product is the fact of Generation Y. Generation Y is the people who were born between 1981 to 2000, and in the present time, their age is between 30-40. We consider that the consumer of the Y generation is more attracted to buy updated smartphones in both eastern and western cultural context. We will discuss this generation more in the 'Sampling and Respondents' section of this study. For these two reasons we have chosen smartphones as our experimental stimulus product to have a better conclusion for these two reasons.
4.2. Sampling and Respondents: Sampling the population is an integral part of the research process. According to Saunders et al. (2012, p. 261), there are two types of sample selection technique: probability sample and non-probability sample. In the probability sample, each respondent has been chosen randomly by the researchers. The researchers do not know about their representative for the study, and everyone in the population has an equal chance to be part of the study (Saunders et al., 2012). On the other hand, in non-probability samples, the generalizability of the findings is limited (Saunders et al., 2012, p. 262). Saunders et al. (2012) suggested that a simple sampling technique is better than a few hundred sample sizes. To conduct this research, we used a non-probability sampling strategy. Bryman and Bell (2011) state that a sample is a valid representative segment of the population selected for investigation. In our study, we consider Generation Y as our sample in the age range of 30-40 and middle- aged adults living in Bangladesh and Sweden. Generation Y is the more innovative generation in the marketing field, and this generation consists of those born from 1981 to 2000 (Aureejo et al., 2020, p. 1198). Generation Y is strongly connected with the internet and eWOM, and it is based on young, middle-aged people who share the typical purchasing attitude towards new technology and motivations. Therefore, for our study, we choose generation Y as our target respondents living in Bangladesh and Sweden and determine the influence of eWOM in their purchase intention. 39
4.3. Sample Size and Data collection: Sample size determination is an essential and often difficult step in planning an empirical study. According to Saunders (2012), the size of the total population, the tolerable margin of error, and the type of analysis are the main determinants of the sample size. The most important reason for us to determine a sample size is that we could not cover the entire population. Although a large sample size is recommended for our study, the vast population would waste time and resources. Therefore, we choose to follow cluster sampling. This technique divides the population into clusters and then takes a simple random sample from each set (Investopedia, 2021). We planned to have a sample size of 100 respondents for conducting our study. As we have selected cluster sampling for our research, we divided our population into two clusters: respondents from Bangladesh and Sweden. We decided to have 50 respondents from each set to evaluate the cultural dimension between two national boundaries. For the data collection, we have used Google Form in order to design our survey. It would help us make our questions clear and take the respondents a short time to answer all the questions. A brief introduction about us and the purpose of the survey will be mentioned at the beginning of the study. Most of the questionnaire questions are mandatory to answer, which helps us make sure that our survey is fully answered.
4.4. Pre-test: Our questionnaire is written in the English language. However, it is essential to emphasize that neither the authors of this thesis nor the respondents are native English speakers. Because the participants in this study come from two different cultural backgrounds, we decided to collect data using an international language. Furthermore, the study's primary respondents are Generation Y, primarily students or workers from both cultural backgrounds. As a result, it is critical to ensure the questionnaire's standard and quality considering the language chosen. According to Saunders et al. (2009, p. 394), a practitioner should get a specialist to inspect the questionnaire language in order to maintain the grade and quality of the survey questions. As a result, we carefully designed and confirmed the questionnaire with the help of three people: a Swedish who is currently studying for a master's degree at Umeå University, a Bangladeshi who completed his master's degree at Gothenburg University and is currently working as a teacher in a Bangladeshi university, and finally the supervisor of this thesis.
A pretest of the questionnaire was also conducted before the final survey to ensure that the questions were intelligible to the respondents and that the questionnaire would work as a data collection tool (Saunders et al., 2009, p. 394; Bryman & Bell, 2011, p. 262). Five students (Swedish and International) from Umeå University have been randomly selected to pretest the questionnaire. Respondents did not have difficulty comprehending the questionnaire during the pretest, though some did inquire about grammatical changes. The primary survey was done after the pretest and adjustment of the questionnaire.
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4.5. Questionnaire design: We created a survey to investigate our study question. Our survey questions have been tailored to collect customer attitudes concerning eWOM and purchase intent across two cultural boundaries. We examined works by Sanders et al. (2012) and Bryman and Bell (2011) to design our questionnaires before beginning our survey. According to Saunders et al. (2012), two main types of research are self-completed and structured interviews. Again, Saunders et al., 2012, (p.420-422) have advised that customers' attitudes be investigated through structured interviews in which the interviewer is allowed to explain complex questions. However, a lengthier survey has a poor response rate (Bryman & Bell, 2011, p. 234). Therefore, we tried constructing simple to comprehend questions that require the least amount of time to complete.
Our questionnaire was developed by using our conceptual framework described in the previous chapter. Our current research has focused on several eWOM influencing elements in a cross- cultural context connected to smartphone purchase intent. Our questionnaire was divided into three sections, the first of which included demographic questions such as gender, age, and nationality. Our research must discover the cross-cultural context in our subject. The answers to these questions aid us in understanding the identity of our respondents. The next section of the survey asked the fundamental questions regarding the respondent's experiences of eWOM and how they use it. The elements of eWOM that influence purchasing intent is the subject of this thesis. So, questions like, "Have you ever read an online review?" or "What platform do you use to check online reviews?" can be utilized to generalize our respondents' relationship and impression of eWOM so that we can offer a suitable conclusion at the end of this thesis.
In the final part of our questionnaire, we focus on getting answers about how different online reviews are essential to customers when they intend to buy a smartphone. We go through several articles to determine the scale of eWOM Zhang et al., 2015, p. 201; Cheung et al., (2008); Bhattacherjee and Sanford (2006); Cheung et al., (2009), Kiecker and Cowles (2002), Dellarocas et al., (2007), Teng et al., (2014, p. 753). We selected seven scales of eWOM that we think are appropriate to conduct our study. The seven determinants are Argument quality, Credibility, Acknowledgement, Acceptance, Trustworthiness, Behavioral Change, and Purchase intention. Table 4 illustrates the scale and statements of our questionnaire. We designed these questions in a Likert scale where (1 = strongly disagree and 5 = strongly agree) was used for collecting data on the eWOM and purchase intention. For more details about the questionnaire, please address 'Appendix Questionnaire' in the appendix.
Scale Variables Dimensions Statement Source Argument Quality Source AQ1 Online review Teng et al., Trustworthiness comments are (2014); informative. Bhattacherjee &
Sanford (2006); Online review Cheung et al., AQ2 comments (2008); Cheung satisfy my needs. et al., (2009)
Online review AQ3 comments are reliable.
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AQ4 Online review comments are up to date. AQ5 Online review comments are consistent with real life experience. Credibility Channels C1 People who Cheung et al., posted reviews (2009); are reliable. Bhattacherjee & Sanford (2006); People who Teng et al., (2014 C2 posted reviews are experienced.
People who C3 posted reviews are experts. Acknowledgement Source A1 Online reviews Zhang et al., Trustworthiness are useful. (2015)
Online reviews A2 are helpful. I check online A3 reviews before purchasing a smartphone. A4 I check customer ratings before purchasing a smartphone. Acceptance Length, Valence AC1 I would Zhang et al., appreciate the (2015); Teng et review if the al., (2014) reviewer posted something similar to mine. AC2 I appreciate the review more if the reviewer is known to me. AC3 I hardly believe online reviews
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from unknown people. AC4 Lengthy online reviews are boring to read Trustworthiness Source T1 Online review Teng et al., Trustworthiness, reflects a true (2014), Zhang et Channels, picture of a al., (2015) Valence subject. T2 I cannot always believe what is said in online reviews.
Most online T3 reviews are intended to mislead.
Lots of online T4 reviews are paid reviews. Behavioral Customer BC1 I am likely to Zhang et al., Change journey accept online (2015); Teng et reviews. al., (2014); Kiecker & I am influenced Cowles (2002) BC2 by online reviews.
I share these BC3 online reviews and comments.
Dwidienawati et Purchase Customer PI 1 After reviewing al., (2020); Lien Purchase the online Intention et al., (2015); Intention comments, the Dellarocas et al., likelihood of (2007) purchasing a smartphone is high.
I intend to PI2 recommend my friends and family to check online reviews before
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purchasing a smartphone.
I intend to check PI3 online reviews for my future smartphone purchase.
Table 4: Scale of Questionnaire.
4.6. Quality Criteria: To solve our study topic, we have chosen a quantitative approach. There are two ways of evaluating the quality of quantitative research: reliability and validity (Bryman & Bell, 2011, p. 157). The study should include both reliability and validity to enhance the study quality (Agresti & Finlay, 2009, p. 11). In ensuring the quality of the data collected, we examine the research’s reliability and validity.
Bryman and Bell (2011, p. 158) define reliability as the consistency with which the research concept or idea is measured. Quantitative research is required to identify the measurement consistency of the research scales. Finding data consistency can refer to reliability because it demonstrates whether the gathered data approach follows the same process under the same circumstances for producing the same experiment if it is replicated by another researcher (Saunders et al., 2012, p. 192). Cronbach's Alpha is a popular reliability evaluation tool that the researchers considered when creating the questionnaire. If the Cronbach's Alpha coefficient is larger than 0.9, it means exceptional; larger than 0.7 is good; larger than 0.5 is acceptable; lower than 0.5 is unacceptable (Hinton et al., 2014). In this study, we use Cronbach's Alpha to ensure our reliability by providing that all the indicators are related to one another using past surveys and scales to arrive at the correct question for the current study.
Furthermore, our questionnaire questions are based on earlier studies and theories, and we include all our questionnaire materials in the ''Appendix Questionnaire'' allowing future researchers to retest if necessary. However, all respondents remain anonymous for privacy reasons. Therefore, the survey did not reveal any of the respondent's identities. Finally, we gathered data using an online web service that freely allows respondents to answer questions without being influenced by the authors.
Validity measures how well a measurement is employed in a study to depict the findings of what you primarily want to learn from the thesis (Bryman & Bell, 2011, p.160). Validity refers to research that is focused on the correctness of findings and reveals whether the components in the study are appropriately analyzed and described in the way that they are designed to measure (Saunders et al., 2016, p. 157). Face validity, concurrent validity, predictive validity, concept validity, and other types of validity testing methodologies were described by Bryman and Bell (2011, p. 160). Face validity is a process that involves the following that is commonly tested by soliciting opinions from persons who are experts in the topic of inquiry in this study (Bryman & Bell, 2011, p. 165). To meet these research criteria, we always have a professor from Umeå University to supervise our thesis writing process. 44
4.7. Ethical Consideration: The research principles that should be fulfilled during the data collecting stage of the investigation are known as ethical considerations (Saunders et al., 2011, p. 187). It is essential to understand the ethical principles that govern research to make moral decisions (Bryman & Bell, 2011, p. 122). According to Saunders (2011, p. 189), there are several ethical problems, and hence ethical standards are provided for them.
Our study followed the ethical principles for internet-mediated research and focused on the participant's best interests. According to Bryman and Bell (2011, p. 132), it is vital to know about the participant's interests and defend them by ensuring sufficient privacy. Concerning this ethical principle, we did not maintain any physical contact with the respondents who have participated in our study. This principle also helps us keep the social distance with all the participants in Covid 19 circumstance. We administered these ethical issues by a personal agreement from the participants to participate in the survey. We informed the participants regarding the survey purpose and issue by providing written information about us as researchers. We tried to ensure the informed consent principle because informed consent is required in business research (Bryman & Bell, 2011, p. 136). We explicitly stated the goal of our study at the outset of our questionnaire, and we did not conceal our identity as the study's author. We also gave the respondents complete discretion over whether they wanted to participate in the study. Finally, we had included our contact information in the questionnaire to contact us via email or Facebook comments. During the survey we bear in mind that the invasion of respondent's privacy is the subsequent research ethics.
Additionally, we stated in the questionnaire that the responses would never be used for any other purpose than this research. This policy also ensures that the data we receive from our participants is kept private. Finally, we are concerned about the misinterpretation of our study. According to Bryman and Bell (2011, p. 137), researchers should not include all study material in the questionnaire because this will limit the number of natural respondents, which is a regular occurrence in business research. Only the objective of our study is mentioned in the questionnaire, which aids respondents in understanding the topic and context of our study. Therefore, the authors of this study believe that the respondents were given all the necessary information while filling out our questionnaire. As a result, we can claim that our study met all the relevant ethical requirements, and our research has been done ethically.
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5. Empirical findings and Analysis:
This chapter presents the data analysis and the result of the empirical investigation. We analyzed the collected data through questionnaires via several testing in SPSS and subsequently presented via descriptive statistics, Cronbach’s Alpha, Pearson Correlation, and two regression analyses. We decided to combine empirical findings and analytical parts in this chapter to make it easier and better understanding for the reader.
5.1. Demographic and Geographic: In the demographic section, we have generalized the population sample because those samples are helpful to inferences some characteristic, attitude, or behavior of this population which can differ based on gender, age, and culture (Babbie, 1990, cited in Creswell, J., 2009, p. 138). As we mentioned in the earlier chapter, we randomly sent an electronic questionnaire link from different online platforms to our respondents. However, we have presented the demographic questions intentionally on the questionnaires to see what percentage of male and female people are aware of eWOM. We also considered the age group to observe which age group of people are more active about using that (eWOM), and our targeted group was Generation Y, aged between 20-40. Moreover, the conducted survey questionnaire was distributed by emails and social platforms, and in total, we randomly chose 100 respondents; 50 from Sweden and the other 50 from Bangladesh (Table: 6). As discussed earlier, this thesis aims to conduct a cross- cultural analysis between culturally different countries (Sweden and Bangladesh). For that reason, survey questionnaires distribution and data collection have been shown in these two cultural boundaries.
Gender Frequency Percent Valid Percent Cumulative percent
Male 68 61.8 68 68.0
Female 32 29.1 32 100
Total 100 90.9 100
Table 5
Geography Frequency Percent Valid Percent Cumulative percent
Sweden 50 45.5 50 50.0
Bangladesh 50 45.5 50 100
Total 100 90.9 100
Table 6
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According to Table 5, we had 100 respondents; 68% were male, and 32% were female. In terms of the age group, a significant part of this group was between 20 and 30 (78%) years old, and the rest were 30–40 (22%) years old (Table 7). However, we have not found any participants in the age group 40+ during the survey as we provide our questionnaire only to the selected generation. However, we consider age as a factor for identifying what percentage of people know this newly emerged user-generated content. This study found that young people mainly keep knowledge about eWOM, and they use it in real-life situations. Even though middle-aged people have an awareness of eWOM, they limitedly use it in their purchasing decisions.
Age Frequency Percent Valid Percent Cumulative percent
20-30 78 70.9 78 78.0
30-40 22 20.0 22 100
Total 100 90.9 100
Table 7
In this survey, our selected stimuli product was smartphones, and, in the questionnaires, we have asked about the preferable smartphone the respondent uses now. We have designed this question based on the operating system of smartphones (e.g., Android, Apple IOS, or others). From the frequencies, we have found that 65% of respondents are using Android OS-oriented smartphones. Alternatively, 34% prefer Apple OS, and 1% of users prefer other smartphones (see Figure: 5). According to the Statista report, Android is the leading smartphone OS in the market, and it has gained a 71.93% market share in January 2021 (Statista, 2021b). So, if we compare this figure with our collected data, then the result is similar. We have also found that the android OS has more users than other operating systems.
Figure 5 47
5.2. Cross-Tabulation of Usage & Experience: In this part of our study, we analyzed respondent's technical online review facilities, habits, and experience with eWOM that can be of use for customers and marketers. These findings provide an overview of the most common communication channels of eWOM, respondent's willingness to use eWOM, and it also specifies the respondent's involvement towards eWOM. Both customers and marketers can leverage these data for their mutual satisfaction suggested. Attached below, Figure 6 illustrates some information related to the intentions of people who are willing to read online reviews before purchasing products such as smartphones. We have presented those data by geographically dividing them, and we found that, comparatively, Bangladeshis are more willing to read online reviews (45 recipients) than Sweden (43 recipients). We also found some respondents in Sweden who have never read eWOM, and other recipients are not sure about online reviews. However, in Bangladesh, we found (1 recipient) never reading online reviews and (4 recipients) not sure about it. By this bar chart, our understanding is, within these two countries (Sweden and Bangladesh), the cultural differences between the intention of reading online reviews are similar or have little differences.
Figure 6 Next, we have found significant differences in terms of review sharing. People of Sweden are more willing to post reviews compared with Bangladesh. From our survey data, we found that 16 recipients among 50 recipients post reviews on different platforms. However, 24 recipients are not interested in publishing online reviews, and ten recipients never posted any reviews of any platforms before (Figure 7). On the opposite side, 31 replicants from Bangladesh are 48 uninterested in sharing their views on the online platform, and only 14 recipients post reviews, and five recipients respond as "Maybe" (Figure 7). Therefore, our overall observation is that Swedish people are more aware of sharing their experiences on online platforms than Bangladeshi people.
Figure 7 Finally, the last multiple choices from our questionnaire are about preferred social platforms for sharing eWOM. From the statistics, we distinguish that in Bangladesh, social media platforms such as Facebook, Twitter, Instagram are prevalent compared with other platforms and populations. Overall, 30 recipients use social media platforms as the leading online review searching and sharing sites. But only six recipients choose Amazon and AliExpress (e- commerce site), five recipients use Yelp and Trip advisor (review site), four recipients use Blogs and emails (Figure 8). On the contrary, in Sweden, all the platforms of eWOM are almost equally popular with slight fluctuations. Our survey found that 16 recipients answered that they select social media platforms like Facebook, Instagram, and Twitter as information gathering and sharing sites. Fifteen recipients use e-commerce sites (e.g., Amazon and AliExpress). Specific review sharing sites such as Yelp and TripAdvisor are also informative for Swedish people (14 recipients) but Blogs and emails are the least selected platform (Figure 8). 49
Figure 8 In the end, we can say that the influences of social media are highly considerable in both Swedes and Bangladeshi culture. However, consumers of Bangladesh are highly dependent on social media for using and experiencing eWOM comparing Sweden.
5.3. Mean: T-test From the frequency table of geography (Table 6), we know that half of our respondents are Swedes, and the other half are Bangladeshi. Therefore, we tested an independent sample t-test for identifying the influence of the variable in different geographical contexts. Independent sample t-test compares the mean value between easterner and westerner respondent's responses considering components of eWOM. From the group statistics data (Table 8), we can see little difference between the mean value of argument quality, credibility, acknowledgment, acceptance, and trustworthiness between Swedes and Bangladeshi. The independent sample t-test table (see Table 9) showed that Levene's test for equality of variances of argument quality significant value is .136, which is greater than .05. Table 9 also demonstrates the variance of credibility and trustworthiness, respectively .577 and .221, which are also greater than .05 as well. If the significance of Levene's test for equality of variances is more numerous than .05, the variability between easterners and westerner respondents is the same. Scientifically, it means that the variability between the Swedish and Bangladeshi groups is not significantly different in the cultural context. On the other hand, the equality variance of acknowledgment and acceptance is .011 and .022, lower than 0.5. It defines that acknowledgment and acceptance have unique differences between the easterner's and westerner's culture. 50
Group Statistics
Geography N Mean Std. Deviation Std. error Mean
Argument Quality Sweden 50 3.824 .497 .0703
Bangladesh 50 3.668 .590 .0835
Credibility Sweden 50 3.233 .687 .0972
Bangladesh 50 3.300 .580 .0820
Acknowledgement Sweden 50 3.945 .435 .0615
Bangladesh 50 3.885 .639 .0904
Acceptance Sweden 50 3.520 .497 .0702
Bangladesh 50 3.685 .657 .0930
Trustworthiness Sweden 50 3.570 .434 .0614
Bangladesh 50 3.380 .553 .0783
Table 8
Independent Sample Test F Sig. t df Argument Quality Equal variances assumed 2.265 .136 1.428 98
Equal variance not assumed 1.428 95.258
Credibility Equal variances assume .314 .577 -.524 98
Equal variance not assumed -.524 95.308
Acknowledgement Equal variances assume .674 .011 .549 98
Equal variance not assumed .549 86.401
Acceptance Equal variances assume .415 .022 -.557 98
Equal variance not assumed -.557 91.198
Trustworthiness Equal variances assume .467 .221 1.908 98
Equal variance not assumed 1.908 92.755 Table 9
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5.4. Cronbach's Alpha and Single Item Measurement: Cronbach's alpha is a method by which we can measure the reliability of the scales. The value of Cronbach's alpha identifies which scale should be deleted to increase reliability. According to Bryman and Bell (2011, p. 158), reliability between the variables can measure the consistency and accuracy of the concept. To get an idea about the strength of the internal consistency relationship for each variable, we used seven scale questions in our questionnaire. Cronbach's alpha's most popular measurement technique is the internal reliability test (Bryman & Bell, 2011, p. 159). Based on our testing, we have found that six out of seven scales are higher than the minimum value of Cronbach's Alpha (0.5). In table 10, we notice that argument quality, acknowledgment, and purchase intention have the higher reliability value that indicates a good level of consistency relationships between these scales. Similarly, credibility, acceptance and behavioral change have an acceptable consistency relationship. On the other hand, trustworthiness is the scale that has an unacceptable reliability consistency value (.372) between the items. We are aware that maintaining internal reliability for the scale is essential for our research credibility. Finally, we believe that the single-item measurement technique will be an excellent indicator to represent a construct measurement for the present study. The mean value of different scales of our conceptual model is essential to understand how the respondents feel and perceive various affective factors of eWOM. Table 10 highlights the value of means and standard deviation of all the scales of our questionnaire. The highest mean value is for the purchase intention (3.94), and the lowest mean value is for credibility (3.27). The standard deviation of the scales varies between 0.50 to 0.67. The highest mean value reveals that most of the respondents designate eWOM as intended to purchase a product. Again, the result shows that acknowledgment and argument quality is vital for eWOM in the purchase, with the mean value of 3.91 and 3.75. These two scales of eWOM indicate that respondents believe that online reviews are informative, up to date, consistent with real-life experience, helpful, and people tend to check online reviews and customers' ratings before purchasing smartphones. The mean value of credibility and trustworthiness is equal to 3.27 and 3.47. Most of our study respondents do not believe online reviews are not thoroughly trustworthy, and sometimes they can also mislead the customers. Finally, the mean value of behavioral change and purchase intention reveals that eWOM has less influence on behavioral change towards the customer. It still significantly impacts the customer purchase intention.
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Scale No. of items Cronbach’s Alpha Means Stand. Deviations
Argument Quality 5 .748 3.75 0.55
Credibility 3 .671 3.27 0.63
Acknowledgement 4 .746 3.91 0.54
Acceptance 4 .574 3.55 0.58
Trustworthiness 4 .372 3.47 0.50
Behavioral Change 3 .502 3.56 0.56
Purchase Intention 3 .789 3.94 0.67 Table 10
5.5. Pearson Correlation: Correlation analysis is generally used to distinguish the strength and direction of change between the scales. In this study, we used SPSS and did several statistic-based tests to find the correlation between the variables. We can determine the items having the largest and the least impact on our conceptual model with the correlation values. Thus, we can calculate the average of individual items' impact on our model. We used the Pearson correlation coefficient analysis, and this technique allows us to measure the correlation between the two variables. Saunders et al. (2012, p. 521) mentioned the valid correlation range should be between -1 and +1.
In Table 11, we can see that argument quality and purchase intentions are the most positively correlated factors (correlation = +.669), and the lowest correlated items are (correlation = .126) acceptance and behavioral change. Furthermore, Pearson correlation test results indicate that our statistical test variables are significant at the significance level of 0.01 and 0.05. From the correlation coefficient analysis, it can be observed that factors of eWOM like argument quality, credibility, acknowledgment, and behavior change all these factors of eWOM significantly impact customer purchase intention. In addition, acceptance and trustworthiness have a weak correlation with the values .137 and .318. However, argument quality, credibility, acknowledgment, acceptance, and trustworthiness are the determinants of eWOM that have less impact on the behavioral change of customers. However, the behavior change of customers is strongly correlated with purchase intention. Furthermore, argument quality and credibility of eWOM are strongly correlated with each other. Similarly, trustworthiness and acceptance have a weak statistical significance on the credibility of eWOM.
Finally, according to the correlation analysis (Table 11), all the variables are within valid correlation ranges with each other’s. Thus, all the items of our conceptual model are positively correlated with a correlation significance range between 0.1 and 0.7.
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Pearson Argument Credibility Acknowledgement Acceptance Trustworthiness Behavioral Purchase Correlation Quality Change Intention
Argument Quality 1 .520 .398 .185 .287 .472 .669
Credibility .520 1 .398 .199 .168 .415 .522
Acknowledgement .398 .398 1 .186 .178 .558 .599
Acceptance .185 .199 .186 1 .162 .126 .137
Trustworthiness .287 .168 .178 .162 1 .260 .318
Behavioral .472 .415 .558 .126 .260 1 .638 Change
Purchase .669 .522 .599 .137 .318 .638 1 Intention
Table 11
5.6. Regression: Based on our conceptual framework, we apply regression analysis and thus attempt to achieve the goal of this study. At the beginning of our chapter, we have conducted Cronbach's alpha and correlation tests to prove the construct's reliability and validity in the conceptual model. These statistical tests are the prerequisites for the following regression analysis. We testified to two regression analyses based on our conceptual model.
5.6.1. Regression 1 (Sweden): In regression 1, we analyzed the components of eWOM, and behavioral change of individualist culture referred to as customer journey in our conceptual model. We entered argument quality, credibility, acknowledgment, acceptance, trustworthiness, and behavioral change as the independent variable and purchase intention as the dependent variable.
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .775a .601 .545 .42272
a. Predictors: (Constant), Behavioral Change, Trustworthiness, Acceptance, Acknowledgement, Argument Quality, Credibility Table 12
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To measure the effect between independent variables towards dependent variables, we concluded our regression one analysis. In Table 12, we can see that the value of R-square is .601, which explains that the determinants of eWOM have 60.1% (.601x100=60.1%) of the variance in purchase intention. It has a significant relationship with the variables. More than .5 is considered a strong relationship. In addition, adjusted R-square explains the sum of independent variables. For this regression analysis, the adjusted R-square was .545; this means that independent variables were responsible for 55% of the variance in eWOM towards purchase intention. It also means the factors of eWOM are on average 55% positively involved with the customers' purchase intention. Furthermore, Table 13 showed that the low F value and less significance value (p<1) indicate that the model has a statistical significance and a relationship between the variables. Table 13 shows that the present study's model is statistically significant as there is a valid F value.
ANOVA
Model Sum of df Mean Square F Sig. Squares Regression 11.552 6 1.925 .774 .000b
Residual 7.684 43 .179
Total 19.236 49
Dependent Variable: Purchase Intention Predictors: (Constant), Behavioral Change, Trustworthiness, Acceptance, Acknowledgement, Argument Quality, Credibility Table 13
Coefficients Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Error Beta (Constant) -1.124 .990 -1.136 .262 Argument Quality .337 .153 .268 2.208 .033 Credibility .152 .115 .167 1.327 .192 Acknowledgement .437 .157 .303 2.772 .008 Acceptance -.086 .123 -.068 -.693 .492 Trustworthiness .143 .150 .099 .952 .347 Behavioral Change .416 .117 .371 3.566 .001 Dependent Variable: Purchase Intention Table 14
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The coefficients analysis table 14 highlights that mostly all of the predictors have significantly positive effect on purchase intention except Acceptance (B = -.086, p < 0.1); Argument quality (B = .337, p > 0.1), Credibility (B = .152, p > 0.1), Acknowledgement (B = .437, p > 0.1), Trustworthiness (B = .143, p > 0.1), and Behavioral change (B = .416, p > 0.1) shows affirmative number. B values ranging between -1 and +1, where 0 means no impact at all and +1, stand for a positive effect with the dependent variable. For instance, if argument quality increases one unit, the positive impact towards purchase intention increases by 33.7%. Similarly, one unit increase for the acceptance leads to increased negative attitudes towards behavioral change by 8%. Thus, we can conclude that regression 1 is a good predictor of determining the importance of the components of eWOM towards customer purchase intention. Coefficients table also helps to identify the factor testing for a study. The most important value to interpret is Sig. value. Table 14 also demonstrate the strength of the relationship between the factors and dependent variable with which it impacts. The factors Sig. value should be below the tolerable level of significance for the study. Less than 0.05 significance value refers that the factors have positive impact on the dependent variable. In Swedes perspective, argument quality (.033), acknowledgement (.008), and behavioural change (.001) are the factors which have less than 0.05 Sig. value and it indicates that these eWOM factors have positive impacts on customer purchase intention.
5.6.2. Regression 2 (Bangladesh):
Regression 2 addresses the significance of eWOM components and behavioral change with the dependent variable purchase intention in a collectivist culture. Table 15 demonstrates that the adjusted R-square value is .721; therefore, independent variables were responsible for 72.1% of the variance in purchase intention. According to (Saunders et al., 2012, p. 525), 0.5 of R- square is an average predictor of the variation. Therefore, we can conclude that regression 2 is better than an average predictor of the dependent variable's purchase intention in this study. Also, Table 16 ANOVA represents that regression 2 is significant as F = .104: (p <1). The linear regression analysis results show that the predictor has significant positive effects on the purchase intention; argument quality (B = .442), credibility (B= .021), acknowledgement (B= .358), acceptance (B= .010), trustworthiness (B= .037), and behavioral change (B = .372) (see Table 17). According to our coefficient analysis, all the customers' eWOM factors and behavioral changes are positively related to purchase intention. However, credibility, acceptance, and trustworthiness are of lower significance with the purchase intention, while other variables are highly significant with the dependent variable.
As for Bangladeshi respondents, argument quality (.001), acknowledgement (.001), and behavioral change (.007) are the Sig. value that have lower than the tolerable level of significance. So, our coefficients table of Bangladesh indicates that these three eWOM factors have positive impacts on the dependent variable.
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Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .869a .755 .721 .36811
Predictors: (Constant), Behavioral Change, Acceptance, Trustworthiness, Acknowledgement, Credibility, Argument Quality Table 15
ANOVA Model Sum of Squares df Mean Square F Sig. Regression 17.971 6 2.995 .104 .000b
Residual 5.827 43 .136
Total 23.798 49 Dependent Variable: Purchase Intention Predictors: (Constant), Behavioral Change, Acceptance, Trustworthiness, Acknowledgement, Credibility, Argument Quality Table 16
Coefficients Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Error Beta (Constant) -.758 .457 -1.659 .104 Argument Quality .442 .125 .375 3.551 .001 Credibility .021 .120 .018 .179 .859 Acknowledgement .358 .105 .328 3.412 .001 Acceptance .010 .089 .010 .118 .907 Trustworthiness .037 .109 .030 .342 .734 Behavioral .372 .133 .301 2.808 .007 Change Dependent Variable: Purchase Intention Table 17
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6. Discussion:
This study aims to create more profound knowledge about the customer journey and eWOM determinants towards customer purchase intention in a cross-cultural context. However, we have chosen smartphones as our research stimuli product; therefore, we believe that our statistical analyses are primarily suitable for purchasing daily used electronic devices between Sweden and Bangladesh. Our research question for the present study is:
How does eWOM affect throughout the customer journey towards the customer’s purchase intention in Bangladesh and in Sweden?
To answer our research question, we aim to describe the purposes and the sub-purposes (Table: 1) of the study; therefore, a conceptual model was developed. In the model, we include all possible influencing factors of eWOM that might affect the customer when purchasing a smartphone. In the theoretical chapter, we have identified four components of eWOM that can influence customer purchase intention towards the customer journey. Further, we have differentiated the customer journey according to the two contrasting cultural boundaries, individualist and collectivist. In this chapter, we have discussed the possible factors of our analysis and interpret the research question of this study.
6.1. Investigating eWOM and its components towards customer journey: The first purpose of our study is to investigate the determinants of eWOM as the touchpoint of customer journey and find out its influence on the customer purchase intention. According to Hall et al., 2017 eWOM has a significant impact on the customer journey, leading to customer purchase intention. This study focused on four components of eWOM from the customer perspective: channels, valence, length, and source trustworthiness. Further, we have designed the questionnaire for this study with these components as the variable of scales. The data analysis chapter observed that the importance of argument quality on eWOM has no relationship with acceptance and a weak relationship with acknowledgment and trustworthiness. In contrast, argument quality has a moderate relationship with credibility and behavioral change and a strong relationship with purchase intention (see Table 11). In this study, we defined argument quality as the source of trustworthiness of eWOM. Kudeshia and Kumar (2017) mentioned that potential customers perceive the source trustworthiness of eWOM as for purchase intention. Therefore, the argument quality of eWOM is strongly connected with the purchase intention and maintains a moderate relationship with the behavioral change that we have defined as the customer journey. Further, we consider the credibility of eWOM as the platform where consumers can choose their preferred medium for getting involved with eWOM. Table 11 shows that acknowledgment, acceptance, and trustworthiness have no or weak relationship with credibility, whereas argument quality, behavioral change, and purchase intention have a moderate relationship. For purchasing sensitive products like (smartphones, electronic gadgets) channels are one of the most critical components of eWOM. A reliable channel of eWOM serves better product information to the consumer and influences the customer journey and customer purchase intention (Gvuli & Levy, 2016, p. 1042). 58
Additionally, the influence of acknowledgment in eWOM has a weak and no relationship with argument quality, credibility, acceptance, and trustworthiness towards the customer journey. However, acknowledgment as the source trustworthiness has a moderate association with the behavioral change and purchase intention. Lin and Xu (2017) stated that the reliability of the eWOM source is not equally important in all product categories, although it is relevant for purchasing sensitive products. We assumed that our eWOM component’s scale are not significant with acknowledgment, but other elements of eWOM might influence the customer journey and customer purchase intention. Similarly, Table 12 shows that acceptance and trustworthiness are the scales of valence and length that have no relationship with the other two components of eWOM and a weak relationship with customer journey and customer purchase intention. As we mentioned in our theoretical part, there is a controversy between the researchers about the significant effect of valence and length of eWOM (Mauri & Minazzi, 2013); (Ladhari & Michaud, 2015); (Teng et al., 2014). In this study, we find weak relationships in valence and length of eWOM between our respondents. Finally, from the correlation analysis, we can mention that behavioral change of the customers that we have considered as the customer journey has a moderate relationship with argument quality, credibility, and acknowledgment (scale of eWOM channels and source trustworthiness). In contrast, there are no and weak relationships with acceptance and trustworthiness (scale of eWOM valence and length). However, our analysis also highlights that customer journeys through eWOM have a strong relationship with customer purchase intention. Nonetheless, eWOM is considered as one of the robust marketing tools that can leverage consumer purchase intention. It positively influences online shopping purchase intentions; consumers believe eWOM information when they make offline purchase decisions (Chan & Ngai, 2011; Lee et al., 2008). For a better understanding, we demonstrate the summary of the correlation between the variables of eWOM towards customer journey and customer purchase intention (see Table 18). From our analysis, we observe that channels and source trustworthiness are the most influential components of eWOM for the customer journey. Customers are more aware of determining the reliable platforms of eWOM before making a purchase decision. To answer the first part of our research question, we can clarify that eWOM positively impacts the customer journey. In addition to the four selected eWOM components, two of them (channels and source trustworthiness) significantly affect the customer journey, which leads to influence customer purchase intention. This study also examines the most preferred eWOM channels for the customers; in the next part of this chapter, we will discuss about it.
6.2. Impacts of eWOM towards customer purchase intention in different cultural boundaries: The final purpose of this study is to examine the cultural differences between the Easterners and Westerners for eWOM towards customer purchase intention. To answer this research question, we surveyed a random Generation Y people within Bangladesh and Sweden. We believe that most smartphone users are connected with eWOM. Therefore, we designed our questionnaire according to the customer's smartphone purchase intention. Figure 6 shows us that all the respondents use smartphones to determine the influence of eWOM in terms of their purchasing smartphones. 59
According to our conceptual model, the customer journey influences the customer purchase intention by the context of individualist and collectivist culture. Further, we have identified Bangladesh as a collectivist and Sweden as an individualist culture using Hofstede's cultural dimension theory. From the analysis, we can determine that both easterners and westerners are significantly mutually involved with eWOM. From the regression analysis, we have sorted out that eWOM influences both western and eastern consumer's purchase intention, respectively 55% and 72%. A large portion of the population from both easterners and westerners prefer to read online reviews before making a purchase decision Figure 7. Similarly, for posting online reviews, both of the cultural context shows lower responses. However, we predicted that Bangladesh is a collectivist culture and the involvement of eWOM would be higher in comparing with individualist culture. Still, our statistical analysis determined that the involvement of posting eWOM is almost the same in between Easterners and Westerners.
Factors AQ C Ack Acc T BC PI
Argument Quality x Moderate Weak No Weak Moderate Strong
Credibility Moderate x Weak No No Moderate Moderate
Acknowledgement Weak Weak x No No Moderate Moderate
Acceptance No No No x No No No
Trustworthiness Weak No No No x Weak Weak
Behavioral Change Moderate Moderate Moderate No Weak x Strong
Purchase Intention Strong Moderate Moderate No Weak Strong x
Table 18: Summary of factors correlation
Additionally, our analysis depicts that westerner prefer to use nearly all the eWOM platforms for seeking product information. On the other hand, most of the easterners choose to use social media platforms such as Facebook, Twitter, and Instagram for acquiring eWOM. Finally, we can mention that using and experiencing eWOM in both individualist and collectivist cultures are almost the same, but it differs in selecting the platform of eWOM. It shows us that collectivist cultural boundaries are more active and available on social media platforms than individualist. Afterward, we examined the mean value for easterners and westerners to find out the significance of eWOM in customer purchase intention in a cultural context. Table 9 shows the mean value of eWOM components, channel, valence, length, and source trustworthiness. All 60 the scales of features have mostly the same results for both easterners and westerners. It signifies that all the four components of eWOM have almost the same relationship towards purchase intention in two different cultural dimensions. According to our products category, the trustworthiness of eWOM as the scale of argument quality and acknowledgment is the most significant eWOM component for westerners. On the other hand, the easterner's most significant factors are acknowledgment and acceptance, representing trustworthiness and length of eWOM. This study signifies that both individualist and collectivist cultures relied on the source trustworthiness of eWOM. Westerners prefer to pursue eWOM from specialized, affiliate, and social platforms of eWOM, whereas easterners mostly prefer the social media platform of eWOM. As we previously discussed, collectivist cultures are more active in social media than westerners and because of that, they grasp eWOM from social media sites (Argyriou 2012). Moreover, we examined the significance level of the eWOM components for both Westerners and Easterners' cultural context. Table 10 illustrates that argument quality, credibility, and trustworthiness, representing channels and source trustworthiness, have a similar variance between the easterners and westerners. On the other hand, the valence and length of eWOM are pursued differently by the easterners and westerners and have unique variance levels. The valence and length of eWOM perceived to avoid confusion between products and consumers (Kudeshia & Kumar, 2017) are highly dependent on the consumer's cultural values (Schindler & Bickart, 2012). This component of eWOM delivers overwhelming information about the product and is conditionally associated with the customer's way of interpreting eWOM. On the other hand, channels and source trustworthiness are the components of eWOM applied to achieve customer demand and judge the reliability of eWOM (Gvili & Levy, 2016); (Kudeshia & Kumar, 2017). The easterners and westerners have a similar way to construe purchase decisions by the influence of the platforms and trustworthiness of eWOM because these are primary components involved with eWOM as a consumer. In conclusion, we come up with this study that both easterners and westerners have a similar way to interpret eWOM for influencing their purchase intention, but some components of eWOM (valence; length) have noticeable differences to affect customer purchase intention between these two cultural contexts.
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7. Conclusion:
This chapter aims to check if the research question was answered, the purposes were met, and if the study has contributions. Thus, the chapter begins with a conclusion, then the theoretical contribution, followed by social and managerial contribution. Later we discussed the limitations of this study and provided some suggestions for future research. 7.1. General Conclusion: This research examined the effect of eWOM in terms of customers purchasing intentions. Another intention was to detect to what extent eWOM affects the cultural differences in the purchase intention. In the research gap section, we have found that customer journey towards the final purchasing decision and eWOM, customer-generated information (as a customer touchpoint) has already gained more attraction to previous researchers. However, we have not found enough evidence to conduct research combining these two concepts to see the effect of purchasing intentions.
From that gap, our research question is stated as follows:
How does eWOM affect throughout the customer journey towards the customers’ purchase intention in Bangladesh and in Sweden?
To explore those factors, we have investigated four main theoretical foundations (customer journey, eWOM, culture, and purchase intention) and connected them to our research aim. We have developed our survey to analyze what, when and how consumers motivate themselves to use eWOM before purchasing gadgets (e.g., smartphones). In the conceptual model, we have developed it with all related components, which significantly influence the entire customer journey (e.g., need recognition to purchase decision). We also examined four features of eWOM in our analysis tools and have developed results based on that. The data collection method was the online-based survey, and for analysis purposes, we decided to use statistical analysis.
Our intentions through this thesis were to develop theoretical and practical contributions to the existing research in marketing and electronic word of mouth in particular. As we mentioned earlier, the purpose of this thesis was to investigate the impact of eWOM components on customer purchase intention and its influence over two different cultural boundaries. However, previous studies have shown that consumers, in general, have positive attitudes towards eWOM. In our research, we could have observed the same pattern among generation Y. Yet during our work, we examined the influential components of eWOM through the customer journey and split our analysis among the easterners and westerners towards their purchase intention. From the regression analysis, we sort out that eWOM influences both western and eastern consumer's purchase intention, respectively 55% and 72%. Again, platforms and source trustworthiness are the components of eWOM that have the most significant impact on customer purchase intention, thus proving previous research studies by Kudeshia and Kumar (2017) and Gvili and Levy (2016). Looking closer to the channels of eWOM, Google often comes up as the most relied-on tool in the early stage of purchase intention. The Google search results help the consumers decide which channels should be used for perceiving eWOM. Our results show that easterners are more likely to consider social eWOM medium, whereas westerner’s trend towards relying on several different channels for searching product information. This could be the effect of the differences between the easterner and westerner as 62 individualist and collectivist cultural views. Following the high collectivist culture, easterners rely upon social eWOM channels to find different opinions about a product.
In contrast, westerners rely upon a more extensive range of channels to collect information. When comparing the result of eWOM, westerners are more likely to have comparatively short reviews. In contrast, easterners prefer to get long reviews as they believe it can help them get more information about any product. However, as mentioned in (Kudeshia & Kumar, 2017), the valence of eWOM strengthens the purchase intention. This study shows that the valence of the eWOM effect is limited to some degree between both the easterners and westerners.
Thus, we can answer our research question and provide some practical suggestions to understand the components of eWOM and its significance on purchase intention in two different national boundaries. Additionally, our research has strengthened the previous theories and academic research regarding eWOM influences on customer purchase intention.
7.2. Theoretical Contributions: This study contributed to the existing literature on eWOM, and customer buying behavior and touched upon Hofstede's cultural dimension theories to conduct this study. One of the study's key objectives is understanding eWOM as consumer-generated opinions and different components of eWOM that consumers considered before involving it. Channels, valence, length, and source trustworthiness are the eWOM features that we include in this study and present a model that illustrates the differences of eWOM towards customer purchase intention in two cultural contexts.
This study filled a gap in the area of eWOM involvement in the different cultural contexts. Our analysis shows that eWOM plays a significant role in the customer journey towards customer purchase intention. Hall et al., (2017, p. 499) mentioned that eWOM has a considerable influence on customer purchase intention. The results of our study also state the impact of the eWOM components on purchase intention in different cultural contexts. These study components of eWOM have proved it is positively accepted towards the customer in different cultural contexts. The availability of technological advancement makes the eWOM stronger than its older version, and the consumers found that eWOM is effective in making better purchasing decisions.
Secondly, the customer journey explains the overall consumer activities. This process starts from the "need recognition" and ends up to the "after purchase experiences. Lemon and Verhoef (2016) have done an empirical experiment by referring to other researcher's works in this field. In that study, Rudkowski et al. (2020, p. 79) found a positive relationship between consumer journey and different touchpoints and acknowledged that different touchpoints affect the consumer journey. Our research has also found that eWOM has a positive relationship with the customer journey and finalizes the purchase.
Finally, to understand the cultural differences and the dependence of humans on culture, we have added the cultural aspect to our research questions and chosen the best options (individualism vs. collectivism) to explain the situation, which we have determined to explore. Our statistical analysis showed that almost all the components of eWOM are interpreted in the same way for eastern and western consumers. These findings contradict Tang (2017) that mentioned westerners have a higher level of prosperity to trust eWOM than the easterners. We feel that such a statement is a new contribution in the theoretical field of eWOM towards 63 customer purchase intention in a cultural context. The findings of this thesis give rise to further discussion of whether or not the components of eWOM affect the purchase in different cultural boundaries within the theories of customer purchase intention. This research also helped us to identify the influence of different elements of eWOM in two cultural boundaries. Our study observed that that eWOM influences eastern consumers more depending on the trustworthiness and valence. In contrast, western consumers consider judging the source trustworthiness of online reviews before they intend to purchase smartphones.
7.3. Societal Implications: The research we conducted for this thesis generated a notable outcome in societal implications. Regarding purchase intention and behavioral changes, we found that eWOM is less important toward behavioral changes, but it successfully can bring a change in customer's purchasing preferences. It means that eWOM may not change the habit or how a customer is being followed for an extended period. Nevertheless, before final purchase, the eWOM can help select a better and suitable choice of (product/service) to meet a customer's demand by comparing it with the other present alternatives.
Firstly, (on behalf of customers perspective), we have mentioned that eWOM has a significant positive effect on customer's purchase intentions. We are all aware that today's world is more advanced in terms of technological development. More people have better access to technology compared with 10-15 years ago. For that reason, eWOM has been introduced, and it helps people know more about product information based on experiences from others who have already used/been using it. Data is now becoming universal and accessible all at a time because the social awareness of products and services is rapidly increasing by using eWOM.
Secondly, (on behalf of the organization's perspective), information spread rapidly as an open platform and rapid development of social media and e-commerce sites. Nowadays, organizations are losing the exaggerated power of advertisements to convince people. Also, organizations are bound to present accurate product information on ads or packaging. In addition, R&D facilities are becoming mandatory business operations to make organizations one step ahead. Shortly, people will experience better and user-friendly products and services for that reason.
7.4. Managerial contributions Despite the theoretical and Societal contribution, the analysis and the results we have developed can equally contribute to the decision-making process from a managerial perspective.
First, in the demographic section, we have found that the younger generation is more interested and concerned about eWOM. However, it is not difficult to predict technological emergence and helps younger people to get to be involved in these kinds of activities. So, they are creating data by sharing opinions on online platforms. That data is a vital source for organizations to develop their products by identifying the pros and cons. On the other hand, eWOM is adequate to predict current marketing trends to keep the productions updated.
Second, a noticeable fact we have found that In Bangladesh, social media is comparatively popular as an online review post and read website (See Figure: 8). Alternatively, in Sweden, e- commerce, social media, and specialized review sites are equally popular with some differences. Remarkably, these findings indicate that online platform popularity and useability 64 can differ from country to country. It is favorable for organizations to select the most suitable platforms to promote their products.
One of the most critical issues we have realized while conducting the thesis is that people gain power over organizations by sharing their opinions. The monopolistic business opportunity may be reduced, but the newer company can achieve success quickly by offering something trendy. In that sense, we can predict that a manager should consider consumer power and keep developing business strategies up to date by getting information from eWOM.
7.5. Limitations and Future Research: The research area of this thesis is based within the countries of Bangladesh and Sweden; more precisely, random generation Y citizens of these two countries. We believe this is a limitation for this study as we could not collect study data broadly. Therefore, it is recommended that future researchers conduct similar research on eWOM with a significant variance of demographic and age groups. The following limitations are essential to keep in mind for this study.
1. The study did not include all components of eWOM, and the excluded components of eWOM are also needed to investigate for having solid results. 2. We have a comparatively lower sample, and in terms of the quantitative method, a more extensive selection is helpful to get a better result. 3. Only one product stimuli were selected to have the development of this study. 4. This study focused on the random respondents of generation Y.
The present study did not consider all the components of eWOM. We have focused on four elements of eWOM, such as channels, valence, length, and source trustworthiness; we could not include all components of eWOM and cultural variances. Again, we considered smartphones as our research stimuli product; future research should focus on different product stimuli.
However, we hope there is still possibility to do some in-depth research on this field and we want to make the following suggestion for future researchers:
1. Conducting this research with countries except Bangladesh and Sweden. 2. Generalize the research by qualitative research. 3. Conduct the same study with an alternative product stimulus. 4. Further study this research with other components of eWOM (Inorganic eWOM, social ties, communication style, expertise). 5. Look at the possibility of studying a service instead of a goods. 6. Further, explore the relationship between channels and source trustworthiness of eWOM. 7. Additionally, examine the reliability for eWOM towards purchase intention through customer brand attitude.
In general, based upon the mentioned research avenues, a further suggestion is to study the relationship between the components of eWOM rather than customer journey and purchase intention.
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