Impact of satisfaction with e-retailers touch points on purchase behavior: the moderating effect of search and experience product type

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1 Mark Lett (2015) 26: DOI /s x Impact of satisfaction with e-retailers touch points on purchase behavior: the moderating effect of search and experience product type Jeen-Su Lim & Abdulrahman Al-Aali & John H. Heinrichs Published online: 28 October 2014 # Springer Science+Business Media New York 2014 Abstract This study develops and tests a consumer touch-point satisfaction model of online purchase. The model captures the moderating effect of search and experience product type on the relationships among the satisfaction with two of the e-retailer s touch points (e-shopping site and social media sites), loyalty intention, and purchase. Analysis results show significant moderating effect of product type on these relationships. The results show that the effect of e- shopping site satisfaction on loyalty intention and the effects of social media site satisfaction as well as loyalty intention on purchase are stronger for search products than for experience products. However, the effect of social media sites satisfaction on loyalty intention is stronger for experience products than that of search products. The paper concludes with a discussion of managerial implications, limitations, and future research directions. Keywords E-retailer s touch points. E-retailer s e-shoppingsite satisfaction. E-retailer s social media site satisfaction. Product type. Loyalty intention. Purchase 1 Introduction Electronic retail commerce represents an expanding and significant opportunity for e- retailers e-shopping sites (Ayanso et al. 2010). The internet assists consumers in their J.<S. Lim (*) Marketing and e-commerce College of Business and Innovation, The University of Toledo, Toledo, OH 43606, USA jlim@utnet.utoledo.edu A. Al-Aali Marketing College of Business Administration, King Saud University, Riyadh, Saudi Arabia alaali@ksu.edu.sa J. H. Heinrichs Information Systems College of Business Administration, Wayne State University, Detroit, MI 48202, USA ai2824@wayne.edu

2 226 Mark Lett (2015) 26: search process for product and/or service information and comparing prices as well as locating products and/or services using mobile or computer-based information searching devices. In response to this information searching behavior by consumers, many online e-retail e-shopping sites are focusing on delivering interactive, media-rich content hoping to achieve higher search engine rankings as well as enhancing and simplifying the consumers e-shopping experience. To compete effectively in increasingly competitive global online markets, e-retailers are utilizing various touch points such as e-shopping sites, permission-based campaigns, and online social media sites to reach and manage their relationships with current and potential e-shoppers (Shankar et al. 2011). With the increased use of social media, e-retailers are establishing and customizing their social media sites and facilitating the creation of virtual communities to reach, interact, and collaborate with current and potential e-shoppers. The e-retailer s social media sites are playing an increasingly critical role as a part of the new media integrated marketing communication plan and as a critical touch point for interacting with customers (Edelman 2010; Reinold and Tropp 2012). For example, the e-shopping site of Teavana lists five social media site links where e-shoppers can visit those sites to join conversation with Facebook, follow the e-retailer with Twitter, pin with Pinterest, learn and explore with YouTube, and join the circle with Google plus. Research studies suggest that e-retailers need to assess e- shoppers reaction to the various touch points available to them (Reinold and Tropp 2012). Thus, effectively managing and coordinating multiple touch points is becoming extremely important for e-retailers to succeed in this intensely competitive global internet marketplace. While the effects of e-shopping site factors on e-purchase behavior have been well documented in the literature (Dillon and Reif 2006; Grewal and Levy 2007; Ha and Stoel 2009), the emerging role of social media sites as an important touch point and their impact on e-purchase behavior has received limited attention. Thus, it is important to assess the combined effects of the two touch points: e-retailers e-shopping site and social media sites. In addition, previous research has not fully assessed the product contingency associated with online purchase behavior. While previous research has identified many different online product classifications schemes (Kiang et al. 2011; Korgaonkar et al. 2004; Nelson 1974), how product type contingencies influence the effects of e-retailers touch points on online purchase behavior is not well established. Therefore, this study intends to develop and test a conceptual model that captures the relationships among satisfaction with two important touch points (the e-retailer s e- shopping site and social media sites), loyalty intention, and purchase. The proposed conceptual model also posits that these relationships are contingent upon the product type. This study empirically tests the moderating effect of the product type on these relationships using survey data. 2 Conceptual model This study develops and tests a user touch-point satisfaction model of online purchase. The proposed model posits that the satisfaction with two of the e-retailer touch points (e-shopping site and social media sites) have direct effects on loyalty intention and purchase. The type of products purchased by individuals moderates these relationships.

3 Mark Lett (2015) 26: Satisfaction with e-retailers touch points This study selected two important e-retailer s touch points, that is, the e-retailer s e- shopping site and social media sites. Satisfaction with these two touch points and their combined effects is critical in understanding e-user behavior and purchase decisions. Researchers report that satisfaction positively affects the individual s intention to shop online (Chiu et al. 2009), to acquire products and/or services from an e-retailer and to repurchase products and/or services (Belanche et al. 2012; Bourlakis et al. 2008). Research provides evidence that a direct relationship exists between consumers satisfaction with an e-retailer site and the various intentions and usage of that site such as revisiting, additional purchases, continued dependence and usage, and providing a recommendation for the e-retailer (Carlson and O Cass 2010; Ha 2012; Wolfinbarger and Gilly 2003). Thus, consumers satisfaction with an e-retailer s e-shopping site will influence the intention to use the e-retailer s sites, usage, and repeated purchase. To establish an engaging social presence, e-retailers need to develop social media sites containing interesting and informative content, attracting individuals to become fans of their social media sites, and interacting with these individuals in a myriad of ways (Qin et al. 2011). Dennis et al. (2010) suggest that major opportunities exist for e- retailers if they combine social media sites with e-retail e-shopping sites. Firms incorporate social commerce by using and maintaining an active presence in various social networking sites (Zhou et al. 2013) and establishing content-related social experiences (Oestreicher-Singer and Zalmanson 2013). E-retailers who can satisfy e- shoppers with effective applications and features of various social media sites can increase online retail sales (Ayanso et al. 2010). It is expected that satisfaction with e- retailers two important touch points, that is, e-shopping site satisfaction and social media site satisfaction, can positively influence repurchase intention and purchase. 2.2 Loyalty intention Previous research suggests that e-retail site loyalty results from a customer s commitment to the e-store through an explicit decision-making process (Bloemer and Ruyter 1998). As such, loyalty intention is defined as consumers intention to continue doing business with and purchase products and services from the e-retailer in the future (Cyr 2008). Previous research theorizes that conation representing loyalty intention leads to action in the loyalty flow (Oliver 1999; 2010). Loyalty intention positively influences actual repeat purchase of products that include purchasing more and different products from the same e-retailer and not switching to another e-retailer (Feick and Lee 2001; Flavián et al. 2006). Others also found significant effect of intention to buy on actual buying in internet shopping (Sia et al. 2009; Valvi and Fragkos 2012). Thus, consumers would visit the e-retail site more frequently and purchase more if they have higher loyalty intention to a specific e-retailer. 2.3 Moderating effect of product type The proposed model posits that the type of product purchased moderates the relationships among the e-retailer s e-shopping site satisfaction, the e-retailer s social media site satisfaction, loyalty intention, and purchase. The type of purchased product can

4 228 Mark Lett (2015) 26: influence consumers information search, purchase strategy, and purchase decisions on the internet (Ha and Stoel 2009). While many product classification schemes have been proposed in the literature (Degeratu et al. 2000; de Figueiredo 2000; Kiang et al. 2011), this study adopts the classification schemes of search and experience (Korgaonkar et al. 2004; Nelson1974). This classification scheme involving search versus experience product types has been widely discussed and accepted in the literature (Korgaonkar et al. 2004; Weathers et al. 2007) to the point that researchers have suggested that all products actually involve a combination of search and experience attributes (Lynch and Ariely 2000). While search products are those where the individual does not have to interact with the product directly to assess the products most important attributes, experience products are those for which the important attributes associated with the products involve both the mind and body and are not known or difficult to obtain without direct experience with the products (Girad and Dion 2010; Huang et al. 2009). Huang et al. (2009) found significant difference between search and experience products in e-shopping information search and quality evaluation processes. Because features of search products are standardized and communicated through the internet more effectively, the satisfaction with e-shopping sites would lead to greater loyalty intention for search products than for experience products. On the other hand, social media sites can provide more personalized information such as product reviews and usage experiences for experience products through social media brand communities. Purchasing experience products requires consumers to search more broadly and gather more personal and customized information about the products. As a result, satisfaction with social media sites would have more positive effect on loyalty intention for experience products than search products. These discussions lead to the following hypotheses: H1 H2 The relationship between e-shopping site satisfaction and loyalty intention will be stronger for search products than for experience products. The relationship between e-retailer s social media site satisfaction and loyalty intention will be stronger for experience products than for search products. As experience products require physical inspection and experience of the products before consumers purchase those products, it is more difficult to evaluate quality online for experience products (Chung and Rao 2012). Even though consumers are satisfied with e-retailers e-shopping sites for experience products, they are less likely to make actual purchases from those e-shopping sites as experience products are less standardized. The positive effect of e-shopping site satisfaction on purchase will be greater for search products than experience products. Social media site satisfaction can also have greater impact on purchase for search products than experience products as the reviews and comments in social media sites can be used by e-shoppers directly as search products are standardized and easy to compare and evaluate. In addition, for experience products, consumers will continue to search for more variety in other e-retailers e-shopping site or social media sites as experience products may change in style (Bock et al. 2012). Moreover, consumers will have less confidence in their repurchase decision from previous e-retailers in whom they were satisfied because assessing the quality of experience products online is more difficult. Further, evaluating variations in the quality of each product and judging the exact fit of the

5 Mark Lett (2015) 26: experience product to their preferences, size, and specific needs is difficult (Bae and Lee 2011; Chung and Rao 2012; Girad and Dion 2010; Huang 2011). Thus, loyalty intention may have greater influence on purchase decisions for search products than for experience products. These discussions lead to the following hypotheses: H3a The relationship between e-shopping site satisfaction and purchase will be stronger for search products than for experience products. H3b The relationship between social media site satisfaction and purchase will be stronger for search products than for experience products. H4 The relationship between loyalty intention and purchase will be stronger for search products than for experience products. 3Methodology 3.1 Sample and procedures This study used a self-administered questionnaire method. To recruit the adult sample, this study used individuals from a major university campus in Saudi Arabia. The sample consisted of 210 evening MBA students. Their age groups were (22.4 %), (54.7 %), (21.0 %), and (1.9 %). The male to female respondents of the sample was 128 (61 %) male to 82 (39 %) female. A bilingual business professor of a Saudi Arabian university translated the original English questionnaire into Arabic and then another bilingual English professor translated the questionnaire back into English. This study utilized the Arabic version of the questionnaire for data collection. The respondents were asked to respond to the questions considering the e-retailer used for making their most recent online purchases. Respondents were also asked to consider the e-retailer s shopping site used for making the most recent online purchases and the directly linked e-retailer s social media sites. Using the purchased product responses, this study categorized the respondents into two groups, that is, the search product group and the experience product group. This study adopted Girad and Dion s (2010) pretested list of search and experience products in classifying respondents. The respondents purchasing search products such as various types of electronics, music CDs, and DVDs were classified under the search product group. The respondents purchasing products such as clothes, shoes, and perfume were classified under the experience product group. There were 126 respondents placed in the search product group and 84 respondents placed in the experience product group. 3.2 Variables The survey instrument contained question items measuring e-retailer s e-shopping site satisfaction, e-retailer s social media site satisfaction, loyalty intention, and purchase. A three-item Likert scale captured e-retailer s e-shopping site satisfaction. These three items are: (1) I am satisfied with my decision to purchase from this e-shopping site; (2) I did the right thing by using this e-shopping site; and (3) my choice for this e-shopping

6 230 Mark Lett (2015) 26: site is a wise one. These items were adapted from Chang and Chen (2009). E-retailer social media site satisfaction was captured by a two-item rating scale. These two items are: (1) overall, I am satisfied with my experience with the social media sites; and (2) overall, the social media site experience is exactly what I needed. These two items formed a new rating scale for this study. A three-item Likert scale measured loyalty intention. The three items are: (1) I will make repeated purchases from this internet retailer; (2) I recommend this internet retailer to my friends; and (3) I intend to continue doing business with this website over the next few years. An itemized rating scale captured purchase. The items include (1) number of items purchased, (2) frequency of online purchases, and (3) frequency of visits. This study adopted these items from Chen et al. (2002) and Lim et al.(2008). 4Analysisandresults 4.1 Confirmatory factor analysis This study utilized confirmatory factor analysis to assess the measurement properties. Table 1 shows the confirmatory factor analysis results. The fit indices showed a good fit of the model to the data (χ 2 =46.60, 38 d.f., goodness-of-fit index (GFI)=0.97, normed fit index (NFI)=0.96, and root mean square residual (RMSR)=0.038). All the items loaded significantly on the expected constructs. The composite reliabilities (CR) for the constructs ranged from 0.81 to 0.86 with the factor loadings from 0.52 to 0.94, and the average variance extracted (AVE) ranged from 0.60 to These results indicate convergent validity of the measures. Discriminant validity was tested using chi-square difference test for each pair of constructs. The chi-square difference tests provide evidence of discriminant validity. The average variance extracted (AVE) from each construct was higher than the corresponding shared variance for all possible pairs of constructs. Thus, all constructs used in the model show adequate reliability and validity. As this study collected data from a single informant using the same survey instrument, the Harman s single factor test was performed to verify the presence of common method bias (Podsakoff et al. 2003). If method variance is largely responsible for the covariation among the measures, a confirmatory factor analysis should indicate that a single factor fits the data. A single factor model did not fit well (χ 2 = with 38 d.f., GFI=0.77, NFI=0.80, and RMSR=0.11). Thus, these results indicate that there is no strong common method bias present in the data. 4.2 Testing hypotheses Structural equation modeling via LISREL was used for data analysis. To test the hypothesized model, the summated scores of the constructs were used as indicators. Multi-group LISREL analysis was performed to evaluate the direct effects and moderator variable effect. Table 1 shows mean values and standard deviations for the summated scores of the constructs. Mean values ranged from 2.17 to Table 2 provides the multi-group analysis results showing the path coefficient estimates for the two product types and the chi-square difference test results between the path coefficients of the search product group and the

7 Mark Lett (2015) 26: Table 1 Confirmatory factor analysis results Items Factor loadings Mean SD CR AVE e-shopping site satisfaction Sat Sat Sat Social media site satisfaction SMsat SMsat Loyalty intention LI LI LI Purchase P P P Fit indices: χ 2 /d.f.=46.60/38, goodness-of-fit index (GFI)=0.97, normed fit index (NFI)=0.96, root mean square residuals (RMSR)=0.038 All coefficients are significant at the 0.05 level CR composite reliability, AVE average variance extracted experience product group. Chi-square difference tests are utilized to test the moderating effect of the product type on the relationships among satisfaction with the e-retailer s e- shopping site, satisfaction with the social media site, loyalty intention, and purchase. The chi-square difference test for the relationship between satisfaction with the e- retailer s e-shopping site and loyalty intention is significant (Δχ 2 =4.05, 1 d.f., p<0.05). The chi-square difference test revealed that the path coefficient for the search products (γ search products =0.78, p<0.01) was significantly stronger than the path coefficient for the experience products (γ experience products =0.54, p<0.05). The path coefficients from e-retailer s e-shopping site satisfaction to loyalty intention for both the search and experience products were significant at the 0.05 level. These results provide support for hypothesis 1. Similarly, the chi-square difference test for the relationship between satisfaction with the social media site and loyalty intention is significant (Δχ 2 =4.00, 1 d.f., p<0.05). The path coefficient from social media site satisfaction to loyalty intention was significantly larger for the experience products (γ experience products=0.17, p<0.05) than for the search products (γ search products = 0.01, p>0.05). The path from social media site satisfaction to loyalty intention was significant at the 0.05 level for the experience product group but not significant for the search product group. Therefore, the results support hypothesis 2. The chi-square difference test for the relationship between e-shopping site satisfaction and purchase was not significant (Δχ 2 =0.13, 1 d.f., p>0.05) providing no support for hypothesis 3a. The path from e- shopping site satisfaction to purchase was significant at the 0.05 level for the search and experience products with path coefficients of 0.43 and 0.55, respectively.

8 232 Mark Lett (2015) 26: Table 2 LISREL estimates and the moderating effect of product type Path Search products Experience products χ 2 Difference (with 1 d.f.) e-shopping site satisfaction Loyalty intention 0.78** 0.54** 4.05 (p<0.05) Social media site satisfaction Loyalty intention * 4.00 (p<0.05) e-shopping site satisfaction Purchase 0.43** 0.55** 0.13 (p>0.05) Social media site satisfaction Purchase 0.28** (p<0.01) Loyalty intention Purchase 0.56* (p<0.10) Fit indices: χ 2 /d.f.=8.66/2, goodness-of-fit index (GFI)=0.97, normed fit index (NFI)=0.96, root mean square residuals (RMSR)=0.085 *p<0.05; **p<0.01 The chi-square difference test for the relationship between social media site satisfaction and purchase is significant (Δχ 2 =7.20, 1 d.f., p<0.01). The chi-square difference test revealed that the path coefficient for the search products (γ search products =0.28, p<0.01) was significantly stronger than the path coefficient for the experience products (γ experience products = 0.21, p>0.05). The path from social media site satisfaction to purchase was significant at the 0.05 level for the search product group but not significant for the experience product group. These results provide support for hypothesis 3b. The chi-square difference test for the relationship between loyalty intention and purchase is marginally significant (Δχ 2 =3.11, 1 d.f., p<0.10). The chi-square difference test revealed that the path coefficient for the search products (β search products =0.56, p<0.05) was significantly stronger than the path coefficient for the experience products (β experience products =0.13, p>0.05). The path coefficient from loyalty intention to purchase was significant at the 0.05 level for the search products but was not significant for the experience products. Therefore, the results provide support for hypothesis 4. 5 Discussion and conclusion This study developed and tested a consumer touch-point satisfaction model of online purchase by examining the moderating effect of search and experience product type on the relationships among the satisfaction with two e-retailer touch points, loyalty intention, and purchase. The results show significant moderating effect of product type on the relationships between e-retailer social media site satisfaction as well as social media site satisfaction and loyalty intention. These results provide support for H1 and H2. Interestingly, the moderating effect of product type on the relationship between e-retail site satisfaction and purchase is not significant providing no support for H3a. E-shopping site satisfaction shows significant positive effect on purchase intention for both search and experience products. This nonsignificant moderating effect may be due to the critical role played by e-shopping site satisfaction in e-purchase process regardless of the type of product purchased (Carlson and O Cass 2010; Wolfinbarger and Gilly 2003). This study found the moderating effect of product type on the relationships between social media site satisfaction and purchase and between loyalty intention and purchase providing support for H3b and H4. These results show the differential roles of social

9 Mark Lett (2015) 26: media as a customer touch point in e-purchase process. Thus, this study confirmed previous findings of the moderating effect of product type on purchase behavior (Girad and Dion 2010; Huang et al. 2009). The analysis results provide support for the direct effects of the satisfaction with the two touch points (e-retailer s e-shopping site satisfaction and social media site satisfaction) on loyalty intention and purchase. The findings show how satisfaction with the two important e-retailers touch points influence e-shoppers loyalty intention and purchase. The results provide support for the contention that the internet has provided access to information and that this access has changed at which touch-point individuals are open to being influenced (Edelman 2010). The findings of this study have an interesting implication for e-retailers. As customer satisfaction with touch points is found to be critical for customer retention and purchase for even experience products, e-retailers must continually evaluate and improve their various customer touch points. E-retailers should develop differential strategies of utilizing various customer touch points including social media sites considering the type of products sold in their e-shopping sites. In addition, the relationship between loyalty intention and purchase is much weaker for experience products than for search products, e-retailers selling experience products should put an additional emphasis on customer retention and continue to try to attract new customers (Chung and Rao 2012; Girad and Dion 2010). E-retailers can provide indirect experiences about dominant attributes, multimedia of user experience, consumer-generated reviews, and online community on their e-shopping site and social media sites for experience products. This study has several limitations. The sample used in this study somewhat limits the generalizability of the findings. Online shoppers with different levels of knowledge and experience may have different perceptions of e-shopping site and social media site satisfaction and purchase. Therefore, future research should evaluate the effect of the individual shopper characteristics such as e-shopping experience and product knowledge on the proposed touch-point satisfaction model relationships. While this study s results show significant moderating effects of product type, future research should validate the findings using e-shopping sites selling other various categories of product types operating in different cultures and countries. In addition, as this study evaluated the effects of two customer touch points of an e-retailer s e-shopping site and social media sites, future research should evaluate the interaction effect of these two touch points as well as the effects of other touch points and their interactions with e-shopping and social media sites. It is important for firms to develop optimal strategy for utilizing these multiple touch points. Acknowledgments The authors extend their appreciation to the Deanship of Scientific Research at the King Saud University for funding the work through the Research Group Project No. RGP-011. References Ayanso, A., Lertwachara, K., & Thongpapanl, N. (2010). Technology-enabled retail services and online sales performance. Journal of Computer Information Systems, 50(3), Bae, S., & Lee, T. (2011). Product type and consumers perception of online consumer reviews. Electronic Markets, 21(4),

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