THE IMPORTANCE OF E-CRM IN ONLINE SHOPPING: A COMPARISON BETWEEN SOUTH KOREA AND INDONESIA

Transcription

1 THE IMPORTANCE OF E-CRM IN ONLINE SHOPPING: A COMPARISON BETWEEN SOUTH KOREA AND INDONESIA Willy Gunadi, Universitas Pelita Harapan, Indonesia Kyeong Seok Han, Soongsil University, South Korea ABSTRACT This research aims to investigate the effect of e-crm on customer loyalty in online shopping in two countries. A total of 551 surveys were collected and analyzed using structural equation modeling. The results of this research indicated that e-crm had successfully enhanced customer loyalty. Keywords: e-crm, Online shopping, Loyalty INTRODUCTION The Internet has provided a platform to deliver customer relationship management functions on the Web (e-crm). Thus, as business moves to the Web, e-crm will move to center stage. CRM and e-crm have direct and indirect impact on customer satisfaction, sales, profit, and loyalty (Feinberg & Kadam, 2002). Retaining customers is financial imperative for electronic vendor (e-vendor), especially as attracting new customers in online store is considerably more expensive than in comparable, traditional, bricks-and-mortar stores (Reichheld & Schefter, 2000). As a type of electronic commerce that facilitates business-to-business (B2B) and business-to-consumer (B2C) transactions, online shopping has shown a great success, especially in B2C transaction. Therefore, it is necessary to determine whether consumers satisfy and loyal to a particular online shopping provider which they cannot touch. Korean consumers are the most active online shoppers in Asia Pacific with 95 percent of Internet users are intended to make a web purchase in the next six months, while one-fifth

2 of residents in Indonesia do not plan an online purchase in the upcoming months (Nielsen, 2010). By considering the number of online shoppers in both countries, the research about online shoppers behavior turns out to be essential. The purpose of this research is to investigate how e-crm can indirectly affect customer loyalty through trust, customer satisfaction, and perceived value in, South Korea and Indonesia. In addition, this research also investigates whether the loyal customers will participate in repurchase intentions, price sensitivity reaction, and positive word-ofmouth (WOM) in both countries. LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT The simple definition of e-crm is customer relationship management on the web; however, e-crm also includes the use of , e-commerce activity, and any other Internet-based customer touch points. Electronic customer relationship management (e- CRM) enables retailers to better meet the needs of their customers across retail formats and, at the same time, to maximize the strategic benefits of a multichannel strategy (Warrington et al., 2007). Trust is vital in many business relationships, especially those containing an element of risk, including interacting with an e-vendor (Luarn & Lin, 2003). Trust is defined as one party s confidence in the other member s reliability, durability, and integrity and the belief that its actions are in the best interest of and will produce positive outcomes for the trusting party (Peppers & Rogers, 2004). According to Gefen et al. (2003), trust is also defined as a set of specific relationship intentions dealing primarily with integrity,

3 benevolence, competence, and predictability of an Internet online retailer. Therefore, it is very important for companies to create trust-based customer relationships through the action of their employees and partners, and also through company strategies and policies (Peppers & Rogers, 2004). It is commonly believed that e-crm leads to customer satisfaction, which at the end results in company s sales and profitability. Customer satisfaction in e-commerce activity can be identified as user information satisfaction or end-user satisfaction. Both user information satisfaction and end-user computing satisfaction scales have been used to measure user satisfaction indirectly through information quality, system quality, and other variables (Luarn & Lin, 2003). Satisfied customers are generally more inclined to remain in the relationship, whereas dissatisfied customers will generally seek to replace the supplier with any available alternative (Peppers & Rogers, 2004). Feinberg and Kadam (2002) found e-crm and customer satisfaction are related. Perceived value is the perceived e-service utility relative to its monetary and nonmonetary costs, assessed by customer and based on simultaneous considerations of what is received and been given up (Luarn & Lin, 2003). According to Kim et al. (2008), perceived value has four components which are acquisition value, transaction value, inuse value, and redemption value. Companies have to identify what creates value for each customer and then deliver that value to the customer. Kelley et al. (2003) found that e- CRM implementation was related to the perceived degree of e-crm. Therefore, we test the following hypotheses: H1: e-crm Effort will positively affect Trust.

4 H2: e-crm Effort will positively affect Customer Satisfaction. H3: e-crm Effort will positively affect Perceived Value. Luarn and Lin (2003) have proposed that trust, customer satisfaction, and perceived value were important determinants of purchase loyalty. Trusting beliefs and trusting intention, which are part of interpersonal trust may be engaged to the trust related behavior such as loyalty (McKnight & Chervany, 2002). Customer loyalty is one of the most significant contributors to the bottom line in a technology-mediated environment (Taylor & Hunter, 2002). It is believed that customer satisfaction will lead to loyalty, although as mentioned previously, a satisfied customer does not guarantee loyalty (Brown & Gulycz, 2002). In addition, Kelley et al. (2003) found that e-crm implementation effort related to the perceived degree of e-crm received, and, in turn, was linked to the loyalty experiences by a virtual customer towards e-retailers. The greater perceived value of the company s products or services, the greater the loyalty effect (Bergeron, 2002). Therefore, we test the following hypotheses: H4: Trust will positively affect Customer Loyalty. H5: Customer Satisfaction will positively affect Customer Loyalty. H6: Perceived Value will positively affect Customer Loyalty. It is suggested that loyal customer will stay in good relationship with company and show behavioral intentions. Repurchase intention is defined as individual s judgment about buying again a designated service from the same company, taking into account his or her current situation and likely circumstances (Hellier et al., 2003). The more loyal a customer to an online shopping provider, the more he/she will perform repurchase

5 intention through the same provider. Customer repurchase decision often depends on general assessment of the service and supplier, based on multiple service transaction experiences with a particular supplier (Liljander & Strandvik, 1995). Taylor and Hunter (2002) proposed that loyal customer was engaged in the activities that support and strengthen their relationship with sponsoring e-crm company, as well as engage in positive word-of-mouth activities within their own professional community. Consumers may use WOM as a mean to gain attention, social status, superiority, or power by showing off what they have bought, what they have been doing, or to enhance their reputation as an expert (Wojnicki, 2006). Through the popularity of electronic consumer in virtual communities, when making a purchasing decision, consumers may turn to the community to gather information, ask for advice, or review experts opinions. The result is an ongoing process of interpersonal influence and online word-of-mouth recommendation (de Valck, 2006). Previous research (Keeley et al., 2003) which took place in United Kingdom (UK) found that the more loyal a customer is towards an e-retailer, the less sensitive he/she becomes towards price. Price and quality of the products/services is very important for customers. The relative ease to compare the product over the Internet would increase the importance of price in a buyer s decision-making process, thus forcing prices to drop to relatively similar levels (Kelley et al., 2003). Degeratu et al. (1998) found that customer s price sensitivity towards products purchased on the Internet was lower than that in traditional channels. However, Korean and Indonesian consumers may have different perception/behavior towards price compare to UK consumers. Furthermore, based on the

6 conflicting views that price on the Internet may or may not be important, it is proposed that the relative ease that products can be compared over the Internet will increase the importance of price in a buyer s decision-making process (Kelley et al., 2003). Therefore, we test the following hypotheses: H7: Customer Loyalty will positively affect Repurchase Intentions. H8: Customer Loyalty will positively affect Price Sensitivity. H9: Customer Loyalty will positively affect Word-of-Mouth behavior. RESEARCH METHODOLOGY The data were collected using online survey. The questionnaire used five-point Likert scale items ( strongly disagree to strongly agree ) to capture all of the constructs identified in the research model. This research used total sample of 551 students from South Korea and Indonesia. The data collection for the Korean respondents took place in Seoul where the online shopping phenomena was highly performed which used data from a sample of 333 students (see Table 1). The data collection for the Indonesian respondents took place in Jakarta which used data from a sample of 218 students (see Table 2). The objects of this research were the well-known online shopping Web sites in South Korea and Indonesia. The validity analysis and research hypotheses were tested using structural equation modeling (SEM) analysis. Insert Table 1 Here Insert Table 2 Here The measures in this research were mainly adapted from prior studies to ensure content validity. The items for the e-crm constructs were mainly adopted from Kelley et al.

7 (2003). The items to measure trust, customer satisfaction, perceived value, and loyalty were taken from Luarn and Lin (2003), where the items for loyalty were including commitment attitude. The items to measure repurchase intentions and word-of-mouth behaviors were adapted from Taylor and Hunter (2002). Finally, the items to measure price sensitivity were adapted from Goldsmith et al. (2005) and modified to fit the online shopping context in South Korea and Indonesia. RESULTS In this research, we did two methods of validity test. Those validity analyses were convergent validity analysis and discriminant validity analysis. We conducted a confirmatory factor analysis (CFA) to get evidence of convergent and discriminant validity of the measurement scales. The convergent validity analysis was tested using the analysis for each construct, which represented construct reliability (CR) and average variance extracted (AVE). The details of the validity analysis for each construct are presented in the Table 3. Furthermore, the details of discriminant validity analysis are represented in the Table 4. Based on the correlation matrix of the variables, we tested if the concepts were the same (Φ±2 standard error = 1.0 in 95% confidence interval) or not. There was no variable that the value was one. We concluded that the discriminant validity in the model had been achieved. Insert Table 3 Here Insert Table 4 Here The model indicated minimally acceptable fit (marginal fit) as other researchers did (Etezadi-Amoli and Farhoomand, 1996; Mulaik et al, 1989). RMSEA (Root Mean

8 Square Error of Approximation), GFI (Goodness of Fit Index), AGFI (Adjusted Goodness of Fit Index), NFI (Normed Fix Index), CFI (Comparative Fit Index), and IFI (Incremental Fit index) values were 0.072, 0.823, 0.793, 0.784, 0.830, and 0.831, respectively. Chi-Square and Normalized Chi-Square (df=396) values were and 3.852, respectively. Thus, it could be concluded that the model fit was acceptable for testing the hypothesized relationship. The hypothesized relationship was tested using structural modeling. Standardized path estimates are shown in Figure 1. In hypotheses H1, H2, and H3, we investigated the influence of e-crm effort on trust, customer satisfaction, and perceived value. As expected, e-crm had a strong positive effect on trust (path coefficient = 0.474), customer satisfaction (path coefficient = 0.605), and perceived value (path coefficient = 0.708). Therefore, hypotheses H1, H2, and H3 were supported. Based on these path coefficients, e-crm had the strongest effect on perceived value. Insert Figure 1 Here Hypotheses H4, H5, and H6 examined the paths from trust, customer satisfaction, and perceived value to customer loyalty. Trust (path coefficient = 0.267), customer satisfaction (path coefficient = 0.183), and perceived value (path coefficient = 0.333) had a significant positive effect on customer loyalty. However, it was found that customer satisfaction had shown a weak effect on customer loyalty and perceived value had the strongest effect on customer loyalty. Therefore, it indicated that hypotheses H4, H5, and H6 were supported.

9 The hypotheses H7, H8, and H9 suggested that loyal customer would participate in repurchase intention, sensitive towards price, and promote positive word-of-mouth. Customer loyalty had positive effect on intention (path coefficient = 0.896), price sensitivity (path coefficient = 0.431), and word-of-mouth (path coefficient = 0.530). Customer loyalty had very strong effect on repurchase intention. However, customer loyalty also showed strong effect on price sensitivity and word-of-mouth. Therefore, hypotheses H7, H8 and H9 were supported. The details of the main hypothesis testing results are shown in Table 5. Insert Table 5 Here This research used chi-square (x 2 ) comparison which would tell us whether there was any difference between South Korean and Indonesian consumers in each hypothesis. There were some specific differences between South Korean and Indonesian consumers perception as shown in Table 6 and Table 7. Insert Table 6 Here Insert Table 7 Here DISCUSSION Through the total consumers of both countries, it is generally accepted that e-crm effort has strong positive effect on trust, customer satisfaction, and perceived value, which indirectly influenced customer loyalty. This finding suggests that e-crm plays an important role to maintain relationship with the customers and support customers needs very well. However, there is a significant difference between Korean and Indonesian consumers perception on the e-crm Effort Trust performance link. The Korean

10 consumers have shown greater effect rather than Indonesian consumers. It maybe caused by Korean consumers have no worries and feel safe to rely on the online shopping provider s e-crm effort which is strongly covered by the Korean regulation due to this kind of business. On the other hand, the Indonesian consumers has low effect of e-crm effort on trust maybe caused by online shopping is not as popular and secure as in Korea and the product quality can also be unreliable. Perceived value plays a crucial role in the effect of e-crm on customer loyalty. This finding suggests that it is very important for online shopping provider to make sure what the customers want based on their expectation. However, trust and customer satisfaction do not show strong positive effect on customer loyalty. This finding suggests that although customers trust and satisfied with the products/services of the online shopping providers, it does not guarantee that they will loyal to those online providers due to a high level of competition in online shopping context. Interestingly, we discover a significant difference between Korean and Indonesian consumers perception on the Trust Customer Loyalty performance link. The Indonesian consumer s has shown greater effect than Korean consumers. For Korean consumers, since they know that the e-crm effort has incredibly fulfilled their trust, it has not become a first priority anymore to create customer loyalty. Conversely, for Indonesian consumers, trust is very important since online businesses are still under developing progress at this time. Customer loyalty has a very strong effect on repurchase intention because of the indirect effect from perceived value through customer loyalty. If the customers have a great

11 experience from a particular online shopping provider in their last transaction, they will not be doubtful to make another purchase in the future. Though, trust and satisfaction does not have strong effect on customer loyalty, there is still a possibility of an indirect effect between trust and satisfaction on repurchase intention through customer loyalty. This finding suggests that some customers can stay loyal with their online shopping provider and participate in repurchase intention which maybe caused by the high level of achieved trust and satisfaction or it may be no other alternative for them to buy the product. Moreover, this research has also shown that customer loyalty has a strong effect on price sensitivity. This situation may be related to the consumers who have achieved high level of trust, satisfaction, and perceived value which has developed great loyalty towards online shopping provider. This finding suggests that while the consumers become loyal to the online shopping provider, they become so interested in price context and sensitive towards price. There are some useful insights from the demographical data. Many Korean and Indonesian youngsters with low expenditure level per month dominate online shopping activities in this research, which push them to buy something from the Internet with lower price. In addition, the inability to feel and touch the products sold through online shopping provider causes the customers depend on price in evaluating the product. Finally, customer loyalty has shown a strong positive effect on word-of-mouth. This finding suggests that loyal customers have a great intention to share their experiences in online shopping to other people by promoting positive word-of-mouth. It is expected that the positive word-of-mouth will attract new customers to participate in online shopping

12 transaction. This research finds a significant difference between Korean and Indonesian consumer s perception on Customer Loyalty Word of Mouth performance link. The Indonesian consumers have shown greater effect rather than the Korean consumers. This finding may be related to the importance of trust to gain customer loyalty in online shopping for Indonesian consumers and the role of opinion leader is very important and useful for Indonesian consumers before making a purchase. CONCLUSION AND SUGGESTIONS FOR FUTURE RESEARCH As conclusion, e-crm implementation in South Korea and Indonesia are successful to enhanced customer loyalty in online shopping context, through indirect effects from customer trust, customer satisfaction, and customer perceived value as the mediators. Additionally, customer loyalty influences high-level of repurchase intention, creates sensitivity towards price, and promotes positive word-of-mouth. Furthermore, this research has shown interesting findings where there are some significant differences between South Korean and Indonesian consumers in online shopping activities. Those differences are found on e-crm - trust performance link (dominated by South Korean), Trust - customer loyalty performance link (dominated by Indonesian), and finally customer loyalty - word of mouth performance link (dominated by Indonesian). The results of this research encourage online shopping providers to keep implementing great efforts on e-crm to maintain the relationship with existing as well as new customers, because e-crm can be also achieved by new customers when they visit an online shopping Web site and intend to make a transaction. Online shopping providers are encouraged to implement e-crm in pre-purchase transaction to enhance trust,

13 satisfaction, and perceived value for customers and in post-purchase to enhance customer loyalty that will lead to participation in repurchase intention, less sensitive towards price, and creation of positive word-of-mouth. This research used students as the respondents which might not reflect the population of online shopping consumers and did not included cultural dimension in the comparison of both countries. In the future, this kind of research can be done in other countries with different culture where the online shopping phenomenon is not highly performed due to security awareness, traditional shopping satisfaction and lower technology infrastructure. REFERENCES Bergeron, B.P. (2002). Essential of CRM: a guide to customer relationship management. John Wiley & Sons, Inc., New York. Brown, S.A., & Gulycz, M. (2002). Performance driven CRM: How to make your customer relationship management vision a reality. John Wiley & Sons, Inc., Canada, de Valck, K. (2006). Word-of-mouth in virtual communities: A netnographic analysis. Special Session Summary: Word-of-Mouth and Word-of-Web: Talking About Products, Talking About Me. Advances in Consumer Research, 33, 574. Degeratu, A., Rangaswamy, A., & Wu, J. (1998). Consumer choice behavior in online and regular stores: the effects of brand name, price and other search attributes marketing science and the Internet. Paper presented at the INFORM College of Marketing Mini- Conference, Cambridge, MA. Etezadi-Amoli, J., & Farhoomand, A. F. (1996). The End User Computing Success Construct, European Conference on Information Systems, Feinberg, R., & Kadam, R. (2002). E-CRM Web service attributes as determinants of customer satisfaction with retail Web sites. International Journal of Service Industry Management, 13 (5), Gefen, D., Karahanna, E., & Straub, D.W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27 (1),

14 Goldsmith, R.E., Kim, D.W., Flynn, L.R., & Kim, W.M. (2005). Price sensitivity and Innovativeness for fashion among Korean consumers. The Journal of Social Psychology, 145 (5), Hellier, P.K., Geursen, G.M., Carr, R.A., & Rickard, J.A. (2003). Customer repurchase intention: A general structural equation model. European Journal of Marketing, 37 (11/12), Kim, C., Zhao, W., & Yang, K.H. (2008). An empirical study on the integrated framework of e-crm in online shopping: Evaluating the relationships among perceived value, satisfaction, and trust based on customers perspectives. Journal of Electronic Commerce in Organizations, 6 (3), Lee-Kelley. L, Gilbert, D., & Mannicom, R. (2003). How e-crm can enhance customer loyalty. Marketing Intelligence & Planning, 21 (4), Liljander, V., & Strandvik, T. (1995). The nature of customer relationships in services, in Swartz, T.A., Brown, D.E. and Brown, S.W. (Eds), Advances in Services Marketing and Management, 4, JAI Press, Greenwich, CT, Luarn, P., & Lin, H.H (2003). A customer loyalty model for e-service context. Journal of Electronic Commerce Research, 4 (4), McKnight, D.H., & Chervany, L. (2002). What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology. International Journal of Electronic Commerce, 6 (2), Mulaik, S.A., James, L.R., Alstine, J., Bennett, N., Lind, S., & Stilwell, C.D. (1989). Evaluation of Goodness-of-Fit. Psychological Bulletin, 105, Nielsen Company. (2010). Global Trends in Online Shopping. Retrieved November 2011, from Peppers, D., & Rogers, M. (2004). Managing customer relationships: a strategic framework. John Wiley & Sons, Inc., Hoboken, NJ. Reichfeld, F.R., & Schefter, P. (2000). E-loyalty: your secret weapon on the Web. Harvard Business Review, Taylor, S.A., & Hunter, G.L. (2002). The impact of loyalty with e-crm software and e- services. International Journal of Service Industry Management, 13 (5), Warrington, P.T., Gangstad, E., Feinberg, R., & de Ruyter, K. (2007). Multi-channel retailing and customer satisfaction: Implications for e-crm. International Journal of E- Business Research, 3 (2),

15 Wojnicki, A.C. (2006). Subjective expertise and word-of-mouth. Special Session Summary: Word-of-Mouth and Word-of-Web: Talking About Products, Talking About Me. Advances in Consumer Research, 33, 573.

16 TABLES AND FIGURE Table 1. Demographic data summary (South Korea) Variable Category Frequency % Gender Male Female Age < 18 years years years years > 45 years Professional Qualification High School Graduates Bachelor Degree Master Degree Doctorate Degree Others Marital Status Single Married Monthly Expenditure < KRW 500,000 KRW500,000 KRW1,000,000 KRW1,000,000 KRW2,000,000 > KRW2,000, Favorite Online Shopping Web Site (Respondents can choose more than one option) Auction G-Market Interpark Danawa D&Shop GS e-shop Others Most Products Bought (Respondents can choose more than one option) Electronics Books or CDs Fashion Tickets Housewares Automotive tools Others

17 Table 2. Demographic data summary (Indonesia) Variable Category Frequency % Gender Male Female Age < 18 years years years years > 45 years Professional Qualification High School Graduates Bachelor Degree Master Degree Doctorate Degree Others Marital Status Single Married Monthly Expenditure < Rp. 1,000,000 Rp. 1,000,000 Rp. 3,000,000 Rp. 3,000,000 Rp. 5,000,000 > Rp. 5,000, Favorite Online Shopping Web Site (Respondents can choose more than one option) Bhineka Amazon E-bay GlodokShop Kaskus AirAsia Others Most Products Bought (Respondents can choose more than one option) Electronics Books or CDs Fashion Tickets Housewares Automotive tools Others

18 Table 3. Convergent validity analysis Variable Item FL* Error t R 2 CR* AVE* e-crm Trust Customer Satisfaction Perceived Value A A A A A B B B B C C C D D D E Customer Loyalty Repurchase Intention Price Sensitivity E E E E F F F G G G H H Word-of-Mouth H H Goodness of Fit Statistics of the Confirmatory Factor Analysis: GFI=0.883, AGFI=0.855, NFI=0.855, CFI=0.902, IFI=0.903,Chi-Square(x 2 )= , RMSEA=0.056, df=377, p-value=0.000

19 Table 4. Discriminant validity analysis ecrm Trust Customer Satisfaction Perceived Value Customer Loyalty Repurchase Intention Price Sensitivity Word- of- Mouth ecrm 1.00 Trust Customer Satisfaction (0.302) (0.428) Perceived Value (0.563) Customer Loyalty (0.411) Repurchase Intention (0.388) Price Sensitivity (-0.017) Word-of- Mouth (0.089) (0.696) (0.599) (0.466) (0.475) (0.405) (0.392) (0.837) (0.513) (0.579) (0.159) (0.270) (0.554) (0.588) (0.140) (0.323) (0.866) (0.397) (0.483) (0.405) (0.537) (0.547) 1.00 Table 5. Summary of hypotheses-testing results Hypothesis Factor Loading t-value Support H *** Yes H *** Yes H *** Yes H *** Yes H *** Yes H *** Yes H *** Yes H *** Yes H *** Yes *** p < Table 6. Comparison between South Korean & Indonesia Link Chi-Square (X 2 ) p-value Support Dominant A B 4.620** Yes South Korea A C No None A D No None B E 3.968** Yes Indonesia C E No None D E No None E F No None E G No None E H *** Yes Indonesia *** p < ** p < 0.05

20 Table 7. Summary of South Korea & Indonesia hypotheses-testing results Link South Korea Indonesia Factor Loading t-value Factor Loading t-value A B 0.552*** ** A C 0.667*** *** A D 0.754*** *** B E 0.173** ** C E 0.139* *** D E 0.323*** *** E F 0.890*** *** E G 0.360*** *** E H 0.358*** *** *** p < ** p < 0.05 * p < 0.1 Variables Note: A = e-crm B = Trust C = Customer Satisfaction D = Perceived Value E = Customer Loyalty F = Repurchase Intention G = Price Sensitivity H = Word of Mouth Fig. 1. Hypotheses testing result