Repurchase intention: the effect of similarity and client knowledge
Halimin Herjanto
H-E-B School of Business and Administration, University of the Incarnate Word, San Antonio, Texas, USA, and
Muslim Amin
School of Management and Marketing, Faculty of Business and Law, Taylor’s University, Subang Jaya, Malaysia
Abstract
Purpose–The objective of this study was to investigate the effect of appearance, lifestyle and status similarity on interaction intensity, satisfaction with a banker and repurchase intention. Also examined was the moderating effect of client knowledge in the enhancement of customer satisfaction with a banker.
Design/methodology/approach–A total of 800 questionnaires using the snowball sampling technique were performed to distribute the questionnaires to bank customers at different ethnic community centers in New Zealand. A total of 377 useable questionnaires were collected for further analysis.
Findings–The findings indicated that the three types of similarity affect interaction intensity differently.
Lifestyle similarity was found to positively influence interaction intensity. The similarity constructs of appearance and status were found to have an insignificant relationship with interaction intensity. The findings show that appearance similarity and interaction intensity are able to enhance customer satisfaction with a banker. Customer satisfaction with a banker has a significant relationship with repurchase intention. Client knowledge influences the degree of interaction intensity and satisfaction with a banker.
Practical implications–The findings of this study help bankers to understand the importance of their similarities with a customer and to design recruitment strategies and training sections to improve customer satisfaction.
Originality/value–This study contributes to the body of knowledge by incorporating interaction intensity, similarity and satisfaction with a bank into the repurchase intention model.
KeywordsInteraction intensity, Similarity (appearance, lifestyle, and status) satisfaction with a bank and repurchase intention, New Zealand
Paper typeResearch paper
1. Introduction
New Zealand has an open-door immigration policy and is subsequently a country with a great deal of diversity. As reported by Statistics NZ (2019), more than 100,000 short-term international visitors, and new permanent and long-term migrants from all over the world arrived in New Zealand in 2018. New Zealand businesses, especially banks, recognize that this significant influx has massive future potential for the business market. This potential has attracted several giant Asian multinational banks to New Zealand, including China Construction Bank, ICBC and Bank of China (Gaynor, 2018), as well as Bank of India and Bank of Baroda (NBR, 2011), to operate branches and compete with local, Australian and internationally owned banks. According toChuah (2018), the Head of Migrant Banking and Customer Segments at ANZ National Bank, migrant customers are a fast-growing sector and are helping to increase bank performance. Many migrants are wealthy (Oliver, 2003), innovative (Chin, 2018), hardworking and their entrepreneurial mindset can significantly contribute to New Zealand’s export and economic growth (Herrick, 2015).
Banks are currently attempting to establish a relationship with their migrant customers by providing different types of banking products and services to fulfill these customers’ financial and banking needs. For example, banks work with local government and foreign consulates, as well as other businesses (e.g. law firms, media, ethnic communities and
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The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0265-2323.htm
Received 15 March 2020 Revised 31 May 2020 29 June 2020 Accepted 29 June 2020
International Journal of Bank Marketing Vol. 38 No. 6, 2020 pp. 1351-1371
© Emerald Publishing Limited 0265-2323 DOI10.1108/IJBM-03-2020-0108
business owners), to stage“migrant expos”which are specifically designed to help migrant customers smoothly integrate to their new life and the banking system in New Zealand.
Banks have also opened migrant branches with a dedicated multi-ethnic and multilingual team to provide a range of unique products and services to fulfill the needs of migrant customers (ANZ Bank, 2014). Migrant customers are also able to open a New Zealand bank account and apply for a home loan from their home country before they arrive in New Zealand (Westpac, 2019).
Gauret al.(2012)point out that the banks’initiative to provide such services is to gain a better understanding of diverse markets and to strengthen the relationship with migrant customers. Furthermore,Gauret al.(2012)argue that a bank’s long-term relationship with its customers relies on bankability to develop similarity with prospective customers.
Researchers have found mixed results concerning buyer–seller similarity. Several studies have established that similarity improves liking (Sprecher, 2013), attraction (Tidwellet al., 2013), commitment and trust (Avery et al., 2008) and creating and maintaining fruitful business relationships (Brashears, 2008). In the banking context, customers from different cultures and countries will always compare their present banking experience with their banking experience of the past; they will also rely on the experiences other members of their ethnic group have with a particular bank (Herjanto and Gaur, 2011). For this reason, similarity involves an assessment of the buyer’s belief that a salesperson will share collective interests and values (Bonnefon et al., 2017); therefore, similarity with customers is an extremely effective relationship-building strategy (Palmatier et al., 2006; Kunz and Seshadri, 2015).
Although the relationship between similarity and customer satisfaction exists, there is much to be understood about this relationship. Traditionally, firm–customer relationships evolve over time based on experiences and are dependent on strengthening customer interaction with a firm. For example,Van Zalk and Denissen (2015)emphasize that customers interact more frequently with sellers when they receive more information about the sellers, thus minimizing their uncertainty about future behaviors and improving their relationship.
In addition, consumers who are motivated to interact with sellers (Kwok and Xie 2018;
Kacherskyet al., 2014) and utilize their time well during interactions (Ankitha and Basri, 2019) will significantly contribute to building successful relationships. In spite of academic recognition of the critical role interaction plays in firm–customer satisfaction relationships, the effect of similarity, interaction intensity and customer satisfaction with a banker has been less researched. A high level of interaction is an essential condition in the similarity–customer satisfaction relationship.
Banking services are intangible, complex and customized, and the relationship between customer and banker is vital. A basic principle of this relationship is to create repurchase intention. Most scholars have demonstrated that the main challenge in the banking industry is to retain and enhance existing relationships rather than attracting new customers (Palmatier and Crecelius, 2019; Sayil et al., 2019; Yu and Tseng, 2019). Although the importance of customer satisfaction in developing repurchase intentions is emphasized in the bank marketing literature (Adel, 2019;Amin, 2016;Boateng, 2019), studies have failed to identify the role of client knowledge in influencing these relationships. In this study, client knowledge is measured as a moderator that affects interaction intensity and customer satisfaction relationships with a banker. As relationships grow, customers will become more knowledgeable of products and services, which in turn will increase customers’confidence and desire to maintain relationships with a bank (Amin, 2016; Palmatier et al., 2006).
Therefore, the objective of this study is to investigate how similarity and interaction intensity enhance customer satisfaction with a banker and customer repurchase intentions. Another objective is to identify the moderating effect of client knowledge on the relationship between interaction intensity and customer satisfaction with a banker. A better understanding of
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these concepts will provide a significant contribution to the banking industry’s desire to maintain relationships with their customers. The study will also provide a significant contribution to researchers through two insights: more comprehensive knowledge of similarity, interaction intensity and customers’satisfaction with a banker and the importance of client knowledge in enhancing customer satisfaction with a banker and customer repurchase intentions. In addition, this study highlights how similarity, interaction intensity and client knowledge delimit commercial relationship outcomes.
2. Literature review and hypothesis development 2.1 Repurchase intention
In the banking context, customer repurchase intention reflects the desire to upgrade, switch or buy new banking products. For example, a customer may increase the limit of their credit card or loan, swap an existing product to a similar or new product, such as from a traditional savings account to a newly introduced savings account or term deposit or buy alternative products such as investment and wealth management products. In most cases, customers are not involved with these transactions regularly and in most cases, these transactions do not involve fresh money. That is, customers move their funds from one account to another account within the same bank. However, despite the lack of fresh money, these transactions are crucial to the bank as the more willing customers are to keep their accounts or start new ones, the less potential there is for them to switch (Aminet al., 2011). In this study, repurchase intention refers to a customer’s positive decision to maintain their current accounts and perform future transactions with their bank (Hume and Mort, 2010). Scholars believe that repurchase intention is based on less perceived risk (Wu and Chiang, 2007) and satisfaction with the overall product and service performance of their bank over time (Hume and Mort, 2010). Repurchase intention is also an expression of loyalty (Amin, 2016;Zhanget al., 2011), commitment (Kim and Ok, 2009;Tabraniet al., 2018) and a sign that the bank is doing its job correctly (Leeet al., 2011). Moreover, repurchase intention provides a bank with a competitive advantage because it helps the bank to gain positive word of mouth (WOM) (Mero, 2018), lower customer maintenance costs (Rojas-Mendezet al., 2009) and maintain bank profitability (Okharedia, 2013). Consequently,Ekaputriet al.(2016)assert that repurchase intention is very important for bank sustainability.Koriret al.(2012)argue that customer repurchase intention is a complicated and subjective decision-making process. During this process, timing and different stimuli (i.e. psychological, cultural, personal, technical and product characteristics) affect a customer differently and therefore it is difficult to understand which stimuli are more powerful at a given time. Therefore, researchers have continuously investigated the repurchase intention phenomena (Kim and Ok, 2009). In this paper, the author hypothesizes that interaction intensity, satisfaction with a banker and similarity are the chief determinants of repurchase intention.
2.2 Customer satisfaction with banker and repurchase intentions
According to Clark and Hwang (2000), satisfaction with a banker refers to a customer’s positive emotional and cognitive perceptions of their overall interaction experiences with their banker. During buyer–seller interactions, a customer evaluates their overall experience with their banker (Chiu et al., 2012) and decides whether the experience meets their expectation (Kincadeet al., 2002). The more a banker confirms a customer’s expectation, the more the customer is satisfied (Papaionanouet al., 2013).Rutherford (2012)suggests that positive emotional reaction is a combination of economic and non-economic satisfaction. In the banking context, economic satisfaction reflects direct and tangible financial rewards–for example, a lower interest rate for a home loan or a fee-waiver for a credit card annual fee. On
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the other hand, non-economic satisfaction is broader, intangible and multifaceted. This includes a banker’s ethical behavior (Roman and Ruiz, 2005), personality (Clark and Hwang, 2000), knowledge (Steward, 2008), selling and service orientation (Kim, 2011), cultural sensitivity (Gauret al., 2019), communication and listening skills (Aggrawalet al., 2005) and after-sales communication (Pawar, 2014). Customer satisfaction with a banker is crucial to bank sustainability because a high degree of satisfaction improves the sense of overall satisfaction with the bank (Aminet al., 2011;Aminet al., 2013;Preis, 2003) and promotes a better quality buyer–seller relationship (Lee et al., 2011), commitment (Rutherford, 2012;
Tabraniet al., 2018), positive brand attitude (Choi and Choo, 2016) and ultimately higher repurchase intention (Amin, 2016;Kitapciet al., 2014). Based on this argument, therefore, it is reasonable to hypothesize:
H1. Customer repurchase intention is positively correlated with customer satisfaction with a banker.
2.3 Interaction intensity
Interaction intensity or frequency refers to the number of interactions per unit of time between buyers and sellers (Ankitha and Basri, 2019;Palmatieret al., 2006). A high level of interaction intensity empowers buyers and sellers to improve the level of information flow and minimize uncertainty (Herjanto and Gaur, 2011). Furthermore,Lin (2012)emphasizes that interaction intensity fosters trust by providing buyers with information that will benefit them to foresee the salesperson’s future outcome. In addition,Contractoret al.(2011)explain that interaction intensity describes the effort by a salesperson to retain communication frequency with a customer and thus commitment to sustaining the relationship. Moreover,Lin and Hsieh (2011) suggest that maintaining high-level contact services require extensive interaction between customers and firms to achieve successful outcomes based on high customer intimacy, high communication duration and rich information exchange (Lovelock and Wirtz, 2007). Consequently, frequent interactions play an important role in developing a better understanding and communication between the buyer and the sales agent (Ankitha and Basri, 2019). A high level of customer interaction indicates a robust link between customers and the firm (Islam and Rahman, 2016). Customers tend to build relationships that support their beliefs, feelings and behavior and thus minimize psychological rigidity in maintaining relationships (Gaur et al., 2019). For this reason, understanding the role of interaction intensity in building customer–firm relationships will provide a practical guideline for bankers who seek to strengthen their relationships with customers.
Prior literature has proposed several potential antecedents of interaction intensity. In the financial services context, the more extensive a relationship, the greater the investment both parties make in the relationship, and the greater the prospect for the experience-based benefit to accumulate (Daggeret al., 2009;Doney and Cannon, 1997). For exampleAnderson and Weitz (1989) explain that interaction intensity establishes an important relationship between customers and firms, and consequently will increases customer loyalty and retention (Yu and Tseng, 2016), as well as high sales, profits and market share (Crosbyet al., 1990). Social cognitive theory suggests that healthy customer banker interactions are responsible for customer satisfaction with a banker. Based on this,Lin and Hsieh (2011) maintain that friendly interactions between buyers and sellers result in a positive emotional response that creates a bond between customers and banker. Consequently, the range of customer service activities provided by a bank directly contributes to the enhancement of customer satisfaction, positive WOM, customer loyalty and repurchase intention (Balaji, 2015;Bojei et al., 2013; Dwivedi, 2015; Price and Arnould, 1999). More specifically,Boateng (2019) clarifies that interactivity between customers and banker has a significant influence on
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customers’intention to patronize a bank. Therefore, Lin and Hsieh (2011) indicate that friendly interactions between customers and banker create positive emotional responses that help build strong relationships. Thus, it is hypothesized:
H2a. Customer satisfaction is positively correlated with interaction intensity.
H2b. Customer repurchase intention is positively correlated with interaction intensity.
2.4 Similarity
Buyer–seller similarity has been widely studied in the marketing literature and is frequently used as a theoretical framework to study the dyadic relationships between sellers and buyers (Coadet al., 2017;Crosbyet al., 1990;Montoyaet al., 2008;Rajaobelina and Bergeron, 2009;
Smith, 1998). According to buyer–seller similarity business theory developed byLichtenthal and Tellefsen (2001), similarity is when a salesperson shares similar traits to a buyer, such as age, gender, birthplace and education, which helps build their bond-relationship (Kwok and Xie, 2018). Lichtenthal and Tellefsen (2001) classify salesperson traits as internal or observable characteristics that can help in determining similarity. In this definition, buyers who perceive a salesperson to be similar to themselves expect the salesperson to similar values expressed through behaviors, goals and dogmas, which consequently makes it easier for buyers to predict the salesperson’s future behavior (Doney and Cannon, 1997). According toChurchillet al.(1975)the concept of similarity can be conceptualized as visible and variable similarities. Visible similarities refer to common characteristics such as physical appearance characteristics, while variable similarities refer to psychological characteristics such as lifestyle and status (Swamiet al., 2007). Although definitions of similarity vary, most scholars follow the similarity construct theory (Crosbyet al., 1990), which consists of appearance, status and lifestyle similarity. Appearance refers to appearance, dress, mannerisms, speech and personality similarity. Status represents education, income and social class similarity.
Lifestyle refers to family situations, interest, political views and values similarity (Crosby et al., 1990;Gauret al., 2012).
2.4.1 Appearance similarity.Crosbyet al.(1990)suggest that appearance similarity is the most visible and the easiest to recognize. Such similarity includes ethnicity, mannerisms and personality (Benbasatet al., 2020;Hankset al., 2020;Dunlop and Beuchamp, 2011). In the banking industry, Berscheid and Reis (1998) consider appearance similarity as key to triggering buyer–seller interactions. This is because appearance similarity is the first characteristic that a customer encounters in a banker and it serves as a deciding feature in whether a customer feels comfortable to approach and interact with the banker. In other words, a high degree of appearance similarity generates a high level of banker attractiveness (Lichenthal and Tellefsen, 2001), greater customer comfort (Losinet al., 2017), and more importantly, it determines a customer’s desire for future interactions (Peretti and Abplanalp, 2004). Appearance similarity improves trust (Losinet al., 2017) and encourages a customer to share information beyond their financial information (Amodio and Showers, 2005). This personal information helps a banker to understand a customer’s situation and thus allows them to reduce a customer’s potential financial risks and improve their financial rewards by recommending better and more suitable banking products or services. As a result, the customer experiences a positive outcome and views the banker as an advisor (Wuytset al., 2002). When this situation occurs, a customer is more likely to appreciate a banker’s effort in taking care of them and accordingly, a customer feels satisfied with the banker (Gauret al., 2012) and more likely to make future purchases (Lichenthal and Tellefsen, 2001). Thus, based on the arguments above, the present study hypothesizes:
H3a. Buyer–seller appearance similarity positively affects buyer–seller interaction intensity.
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H3b. Buyer–seller appearance similarity positively affects customer satisfaction with a banker.
H3c. Buyer–seller appearance similarity positively affects customer repurchase intention.
2.4.2 Lifestyle similarity.In the banking context, lifestyle refers to a customer’s personal choice on how they live their life (Sathish and Rajamohan, 2012). In general, lifestyle relates to a customer’s activities, interests and opinions (Krishnan, 2011), which include family situations, personal interests, political views and personal values (Kwak and Ingersoll- Dayton, 2020;Crosbyet al., 1990).Herawatiet al.(2019)suggest that a customer’s lifestyle determines their future customer behavior. In the banking industry, when a banker shares a lifestyle similarity with a customer, the banker can predict the customer’s future behavior and more importantly, the banker can personalize their communication with the customer (Lelakos and Giaglis, 2007). Hobman et al. (2003) suggest that lifestyle similarity is a necessary element in maintaining relationship quality between buyer and seller. According to Benn (2003), similarity allows a customer to treat a banker as one of their in-group members, reduce relationship conflicts and enhance group harmony (Hobmanet al., 2003) and increase a customer’s sense of assurance and stability (Zajadacz and Sniadek, 2013). In addition, discovering lifestyle similarity encourages a customer to remain in good communication with their banker (Crutchfieldet al., 2003).Crutchfield et al.(2003)note that lifestyle similarity allows a customer to explore their banker’s attitude and personality before they commit themselves to the banker. When a customer finds a banker shares similar attitudes and values, they regard the banker as like-minded, and this increases their desire for a stable (Amodio and Shower, 2005) and committed relationship (Duffy and Ferrier, 2003). Thus, it is hypothesized that:
H4a. Buyer–seller lifestyle similarity positively affects buyer–seller interaction intensity.
H4b. Buyer–seller lifestyle similarity positively affects customer satisfaction with a banker.
H4c. Buyer–seller lifestyle similarity positively affects customer repurchase intention.
2.4.3 Status similarity.Status similarity is regarded as one of the chief components of strong interpersonal connections (Donget al., 2020;Reagans, 2011). A customer who shares status similarity with a banker has fundamental characteristics in common, such as occupation, income (Crosbyet al., 1990), knowledge (Reagans, 2011) and economic well-being (Kniggeet al., 2014). This similarity allows a banker to reduce a customer’s ambiguity and to generate a sense of security and compatibility. As a result, the customer feels that the banker treats them fairly and consequently, the customer chooses to maintain their alliance with the banker and to seek further collaboration (Chunget al., 2000). In the banking industry, sharing status similarity means that a customer and a banker complement each other. For example, a banker can share their financial knowledge with a customer while also learning about other banks’products and services from the customer. In this situation, a customer views a banker as a partner who is committed to improving their welfare by cooperating more effectively and providing fair treatment and beneficial products or services. Therefore, when a positive perception exists, a customer will exhibit a higher appreciation and share their real opinions about the bank’s products and services (Gaur et al., 2012). Accordingly, based on this information, a banker will be able to satisfy a customer by tailoring the bank’s services and offering more suitable products. Chung et al. (2000) conclude that status similarity encourages buyer–seller alliances. Bellieveauet al. (1996) suggest that status similarity affects an individual’s social capital and influences how a customer views a banker based on
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the banker’s affiliation with their social network. A customer perceives a banker who shares the same social capital as having a similar work ethic and responsibilities, and this similarity improves the banker’s likability (Nahemow and Lawton, 1975) as well as the mutual understanding (Crutchfield et al., 2003) and trust (McPherson et al., 2001) between the customer and banker, and ultimately the customer’s repurchase intention (Banik and Gao, 2020). Therefore, it is hypothesize that:
H5a. Buyer–seller status similarity positively affects buyer–seller interaction intensity.
H5b. Buyer–seller status similarity positively affects customer satisfaction with a banker.
H5c. Buyer–seller status similarity positively affects customer repurchase intention.
2.5 Client knowledge as a moderator
Client knowledge is defined as a customer’s recognition and understanding of products and services (Grableet al., 2020;Nora, 2019;Rossanty and Nasution, 2018). A customer’s buying and consumption experiences, as well as their information exposures to marketing and non- marketing sources, determine the degree of their product familiarity and product knowledge (Nguyenet al., 2015). As a result,Thomas and Mills (2006)believe that product knowledge generates a customer’s perception of a product and provides guidance in the purchasing decision-making process. A customer with lower product knowledge has limited information and therefore does not have the ability to understand the advantages/disadvantages of a product and to compare it with alternative products or services (Tariqet al., 2013). In contrast, a customer with higher product knowledge knows the attributes and the structures of the product and can therefore compare it with alternative products (Smith, 2000). Consequently, in the banking context, a customer with higher product knowledge has more confidence in making good financial decisions, whereas a customer with lower product knowledge is uncertain and tends to seek help when making financial decisions. In sum, the higher the level of product knowledge, the less financial issues a customer will experience (Rossanty and Nasution, 2018).
In addition, customer satisfaction serves as the fundamental component of a bank’s profitability and sustainability (Caruana, 2000). To improve customer satisfaction, modern banks rely heavily on the abilities and efforts of their bankers to maintain relationships (Rahmani-Nejadet al., 2014) through interaction intensity (Scharitzer and Kollarits, 2000).
Wuyts et al. (2002) believe that buyer–seller interaction intensity allows bankers to understand their customers personally and thus offer suitable and error-free products or services. However, the frequency and duration of interaction intensity depend on customers’ product knowledge (Tariqet al., 2013). That is, the lower the customers’product knowledge, the higher the interaction intensity. Thus, it is reasonable to hypothesize:
H6. The degree of a customer’s knowledge moderates the relationship between interaction intensity and the customer’s satisfaction with a bank.
3. Methodology 3.1 Data collection process
Respondents who have bank accounts at commercial banks in New Zealand were selected as the sample. A pilot study was conducted with bank customers and 50 respondents participated. Minor modifications and refinements were made to ensure validity and clear understanding of the content. A snowball approach was used whereby a total of 800 questionnaires were distributed to bank customers at different ethnic community centers and
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return envelopes were attached. To control respondents, customers needed to have a minimum of one-year experience with New Zealand banks and be at least 20 years of age. A total of 377 useable questionnaires were collected for further analysis.Table 1shows the demographic profiles.
3.2 Questionnaire development
All the items used in this present study were adopted and adjusted from the published literature. Multiple items for measuring similarity in appearance, status and lifestyle were adopted fromCrosbyet al.(1990). Three items fromDoney and Cannon (1997)were borrowed and adjusted to measure interaction intensity. The construct of customer satisfaction with a banker was measured using four items fromRamsey and Sohi (1997). Items fromKumaret al.
(1995) were drawn to measure repurchase intention, and the items to measure client knowledge were taken and modified fromFlynn and Goldsmith (1999). A seven-point Likert scale ranging from strongly disagree (1) to strongly agree (7) was employed to measure each construct.
4. Data analysis
Following the recommendation from Hair et al. (2019), two analytical techniques were conducted in this study: the measurement model and the structural model (hypothesis testing).
4.1 Measurement model
To assess the measurement model, internal consistency reliability, convergent validity and discriminant validity were identified.Table 2provides the measurement results: Cronbach’s alpha ranged from 0.802 to 0.938, composite reliability (CR) ranged from 0.884 to 0.956 and the average variance extracted (AVE) ranged from 0.558 to 0.844, indicating that construct validity was established (Anderson and Gerbing, 1988;Hairet al., 2012). In this study, two approaches were used to confirm discriminant validity: the Fornell–Larcker procedure (Fornell and Larcker, 1981) and the heterotrait–monotrait (HTMT) technique (Sinkovicset al., 2016).Table 3shows the results of the Fornell–Larcker calculation explaining that the square root of AVE between each pair of factors was higher than the correlation estimated between
Characteristics Frequency (%) Characteristics Frequency (%)
Age Employment
<25 years 59 (16) Full-time 253 (67)
25–34 151 (40) Part-time 53 (14)
35–44 103 (27) Student 46 (12)
45–54 48 (13) Unemployed 25 (7)
>55 years 16 (4)
Gender
Male 185 (49)
Years of NZ banking experience Female 188 (50)
Other 4 (1)
1–10 years 322 (86)
11–20 years 47 (13) Ethnicity
21–30 years 5 (0.5) Asian 355 (96)
>30 years 3 (0.5) Eastern European 4 (1)
Others 18 (5)
Table 1.
Participants’profile overview
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factors, thus indicating discriminant validity was established (Bagozzi and Yi, 1988). The HTMT ratio of correlations explaining all values of HTM were lower than the recommended
Construct Loadings
Cronbach’s
alpha CR AVE
Interaction intensity
My banker frequently calls me 0.769 0.802 0.884 0.718
My banker takes a lot of time to learn my needs 0.880 My banker spends considerable time getting to know me 0.887 Client knowledge
I know a lot about banking products 0.902 0.865 0.896 0.686
I don’t feel very knowledgeable about banking 0.910 Among my friends, I am considered an expert on banking
matters
0.716 Compared to most other people, I know less about banking 0.768 Similarity appearance
I feel my banker has a similar appearance to mine 0.717 0.879 0.912 0.675 I feel my banker has a similar fashion style to mine 0.825
I feel my banker has similar mannerisms to mine 0.860 I feel my banker has a similar speech style to mine 0.874 I feel my banker has a similar personality to mine 0.824 Similarity lifestyle
I feel my banker has a similar family situation to mine 0.792 0.872 0.911 0.719 I feel my banker has similar interest/hobbies to mine 0.879
I feel my banker has similar political views to mine 0.865 I feel my banker has similar values to mine 0.854 Similarity status
I feel my banker has a similar education to mine 0.864 0.823 0.893 0.736 I feel my banker has a similar income level to mine 0.862
I feel my banker has a similar social class to mine 0.847 Satisfaction with banker
The amount of contact that I have had with my banker was adequate
0.898 0.938 0.956 0.844
I am satisfied with the level of service my banker has provided 0.935 In general, I am pretty satisfied with my dealings with my
banker
0.946 I am satisfied with the staff who deliver the service in my bank 0.896 Repurchase intentions
I expect my relationship with my banker to continue for a long time
0.812 0.867 0.898 0.558
The renewal of the relationship with my banker is virtually automatic
0.698 I will most probably switch to an alternative bank in the
foreseeable future
0.674 I definitely intend to maintain my current relationship with this
bank
0.779 I am willing to put more effort and investment into building our
business with the help of my banker’s products and services
0.739 If my banker requested it, I would be willing to make further
investment in supporting my banker
0.682
I will purchase from this banker again 0.831
Table 2.
Measurement model
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level of 0.90, thus confirming acceptable discriminant validity for all constructs (Hair et al., 2016).
4.2 Structural model
To test the structural model and hypothesis,Hairet al.(2019)require that the path coefficient (β), coefficient of determination (R2) and effect size (f2) are reported. A bootstrapping technique was applied with a re-sampling of 5,000 and to examine the hypothesis testing, path estimates andt-statistics were calculated. Table 4andFigure 1show the structural model hypothesis testing. The results showed that there were no significant relationships between similarity status and interaction intensity, satisfaction with a banker and repurchase intentions (β50.011,p50.896;β50.039,p50.637;β50.104,p50.120). Thus,H5a,H5b and H5c were not supported. Lifestyle similarity had a significant relationship with interaction intensity and no significant relationships with satisfaction with a banker and repurchase intentions (β50.258,p50.001;β50.055,p50.511;β50.047,p50.476). Thus, H4a was supported and H4b and H4c were not supported. Meanwhile, similarity in appearance did not have a significant relationship with interaction intensity or repurchase intentions, but it did have significant relationship with satisfaction with a banker (β50.010, p50.902;β50.068,p50.309;β50.165,p50.012). Thus,H3aandH3cwere not supported andH3bwas supported. In addition, interaction intensity had a significant relationship with satisfaction with a banker and repurchase intentions (β 50.341, p50.001; β 50.122, p 5 0.002), and thus H2a and H2b were supported. Satisfaction with a banker had a significant relationship with repurchase intentions (β50.709,p50.001), and thusH1was supported.
The correctedR-squared values reported inTable 4exhibit the explanatory power of the predictor variable(s) on the respective constructs. Interaction intensity explained 6.7% of similarity appearance, status and lifestyle (R250.067), satisfaction with a banker explained 18.9% of interaction intensity (R250.189) and repurchase intentions explained 55.9% of satisfaction with a banker (R250.559). The effect size (f2) value showed that similarity appearance, status and lifestyle had no effect on interaction intensity, satisfaction with a banker or repurchase intentions (0.002; 0.001; 0.011). Interestingly, interaction intensity had a
Construct 1 2 3 4 5 6 7
Fornell and Larcker
1. Client knowledge 0.828
2. interaction intensity 0.154 0.847
3. Repurchase intention 0.150 0.389 0.747
4. Satisfaction with banker 0.168 0.381 0.732 0.919
5. Similarity appearance 0.081 0.164 0.235 0.196 0.822
6. Similarity lifestyle 0.021 0.259 0.196 0.172 0.653 0.848
7. Similarity status 0.050 0.195 0.223 0.163 0.557 0.735 0.858
HTMT
1. Client knowledge
2. Interaction intensity 0.186
3. Repurchase intention 0.162 0.459
4. Satisfaction with banker 0.152 0.437 0.797
5. Similarity appearance 0.091 0.191 0.271 0.214
6. Similarity lifestyle 0.057 0.300 0.220 0.183 0.749
7. Similarity status 0.086 0.239 0.267 0.180 0.634 0.856
Note(s): Below the diagonal: correlation estimated between the factors; Diagonal: square root of AVE Table 3.
Discriminant validity
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small effect on satisfaction with a banker (0.019) and has a high effect on repurchase intentions (1.067). Satisfaction with a banker had a high effect on repurchase intentions (1.067).
4.3 Moderating analysis
In this study, the hypothesis was established that client knowledge has a moderating effect on the relationship between interaction intensity and customer satisfaction with a banker.
The PLS product-indicator method was performed to test the moderating effects, as suggested byHenseler and Fassott (2010).Table 4shows that client knowledge moderated the relationship between interaction intensity and satisfaction with a banker. Thus,H6was supported.
5. Discussion
The findings indicated that three types of similarity affected interaction intensity differently.
Lifestyle similarity was found to positively influence interaction intensity. The similarity constructs of appearance and status showed an insignificant relationship with interaction intensity. The lifestyle similarity result showed that the more lifestyle characteristics a banker shares with a customer, the more intensely the customer will interact with the banker.
Hypothesis Beta
t- statistics
p-
values 2.50% 97.50% R2 f2 Results
H1. Satisfaction with
banker→repurchase intention
0.709 23.33 0.001 0.642 0.763 0.549 1.067 Supported
H2a. Interaction
intensity→satisfaction with banker
0.341 7.253 0.001 0.248 0.433 0.189 0.019 Supported
H2b. Interaction
intensity→repurchase intention
0.122 3.104 0.002 0.044 0.194 0.549 1.067 Supported
H3a. Appearance
similarity→interaction intensity
0.010 0.123 0.902 0.164 0.140 0.067 0.000 Not
supported H3b. Appearance
similarity→satisfaction with banker
0.165 2.506 0.012 0.025 0.285 0.189 0.018 Supported
H3c. Appearance
similarity→repurchase intention
0.068 1.017 0.309 0.061 0.201 0.549 0.006 Not
supported H4a. Lifestyle similarity→interaction
intensity
0.258 3.123 0.002 0.089 0.416 0.067 0.027 Supported
H4b. Lifestyle
similarity→satisfaction with banker
0.055 0.657 0.511 0.217 0.110 0.189 0.002 Not
supported
H4c. Lifestyle similarity→repurchase intention
0.047 0.712 0.476 0.177 0.079 0.549 0.002 Not
supported H5a. Status similarity→interaction
intensity
0.011 0.130 0.896 0.148 0.168 0.067 0.000 Not
supported H5b. Status similarity→satisfaction
with banker
0.039 0.472 0.637 0.133 0.196 0.189 0.001 Not
supported H5c. Status similarity→repurchase
intention
0.104 1.554 0.120 0.033 0.231 0.549 0.011 Not
supported H6. Interaction intensity3client
knowledge→satisfaction with banker
0.284 4.086 0.037 0.007 0.164 Supported
Note(s): Significant at 5% level
Table 4.
Structural model
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A higher degree of lifestyle similarity is likely to provide psychological closeness; that is, a banker with a similar lifestyle to a customer is likely to share similar fundamental values (Crosbyet al., 1990). In essence, personal values are enduring beliefs motivate a banker to be professional (Braithwaite and Blamey, 1998). Thus, a high degree of similarity is likely to show a banker’s behavior stability, and therefore generate a higher sense of security in a customer who then seeks frequent interactions with the banker. These findings support Zajadacz and Sniadek’s (2013)study in which the authors found that lifestyle similarity improves communication times between deaf and hearing people. Although, appearance similarity and interaction intensity were not supported, appearance similarity had a significant relationship with customer satisfaction with a banker. One explanation could be that a customer regards appearance similarity as a tool to initiate the first interaction.
However, when the interaction is established, a customer is more likely to focus on a banker’s credibility and orientation. These findings complement the study of Rajaobelina and Bergeron (2009), which found that appearance similarity improves relationship quality.
The findings strongly suggest that appearance similarity and interaction intensity are able to enhance customer satisfaction with a banker. Consistent interactions can result in a customer becoming more intimate with a banker, and therefore more willing to share what they have in mind. In addition, a banker may also be able to identify a customer’s needs, tailor their approach and offer suitable products and services to fulfill the customer’s requirements.
Previous studies have found that appearance similarity and interaction intensity improve customer satisfaction with a salesperson and promote a customer’s relationship with the salesperson (Amodio and Showers, 2005;Daggeret al., 2009;Nasri, 2015;Ngoet al., 2016). As a result, when a customer perceives that a banker shares appearance similarity, the customer tends to assimilate and get to know a banker personally. For example, a customer may ask where a banker has their hair cut or buys their clothes and vice versa. This example shows that appearance similarity promotes relationships beyond the work setting. Consequently, a customer who perceives similarity may view a banker as willing to provide service that goes the extra mile and accordingly feels satisfied.
Although it was shown that appearance, status and lifestyle similarity did not influence repurchase intentions, customer satisfaction with a banker had a significant relationship with repurchase intentions. This means that a banker may not be comfortable sharing their social and economic status with a customer, leading to a speculative and subjective customer
Interacon intensity Sasfacon with a
banker Repurchase intenon
Lifestyle Similarity
Client knowledge
H2a H1
H2b
H3a
H6 Appearance Similarity
Status Similarity
H3b
H3c H4a H4b H4c
H5c H5a H5b
Figure 1.
Research model
IJBM 38,6
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evaluation of the banker’s status. In addition, a customer may have a task-oriented mindset and does not view different social status and social class characteristics as affecting a banker’s performance. Therefore, it is important for a banker to consistently satisfy their customer. Suitable products and proper services are helpful in generating trust, communication quality, positive emotion and satisfaction with a banker. These findings lend support to the studies ofKitapci et al.(2014)and Preis (2003)who also found that satisfaction leads to a customer’s higher intention to repurchase. Interestingly, the effect of interaction intensity on customer satisfaction with a banker and repurchase intentions were found to be positive. This indicates that banker–customer relationships are well established.
Accordingly, interaction intensity is more a courtesy service to maintain customer satisfaction rather than an opportunity to sell banking products. Thus, it is important for a banker to stick to their objectives when interacting with a customer.
The moderating effect of client knowledge and interaction intensity and customer satisfaction with a banker was found to be significant. Client knowledge influences the degree of interaction intensity and satisfaction with a banker. When a customer has low or moderate banking knowledge, they tend to have more interactions with a banker to minimize their financial disadvantages. For example, a customer may not understand how to calculate credit card interest, and therefore in order to manage their credit card usage, a customer may consult with a banker. Therefore, the more interactions a customer has with a banker, the more confident and satisfied the customer feels with the banker. Thus, these results suggest that customer satisfaction with a banker serves as an important factor in improving a customer’s repurchase intention.
5.1 Theoretical and managerial implications
The results of this study offer some important theoretical and practical implications.
Academically, the findings extend Gauret al.’s (2012)similarity model by incorporating interaction intensity, client knowledge and repurchase intention. This new model provides new insight into the concept of similarity, and the results indicate that lifestyle similarity is the most important type of similarity as it promotes more interactions and improves satisfaction. In addition, these results show that psychological similarity is more powerful than physical and social/economic similarities. Thus, these results extend the theoretical understanding of similarity. Moreover, the findings also contribute positively to business practitioners. These findings suggest that a banker should be comfortable in showing their similarities to a customer and wisely control and utilize these similarities. In particular, a banker is recommended to highlight their psychological similarity more often than their appearance and status similarities.
6. Limitation and future research directions
This study was conducted in the Auckland region only; therefore, it may only be applicable to this area and cannot be generalized to other areas or countries. Furthermore, these findings were achieved by focusing solely on the banking industry; thus, the results may only be applicable to this industry. In addition, the focus of this research was limited to customers’ perception of their similarity to bankers. Future research may consider investigating a banker’s perception of their similarity to a customer. Finally, this model only incorporates a few constructs and may oversimplify the concept of similarity. Future research could integrate other constructs such as reputation as a potential moderator.
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