Topic Measuring customer loyalty in the context of multi-channel retailing: Case study for fashion industry in danang, vietnam

Nội dung text: Topic Measuring customer loyalty in the context of multi-channel retailing: Case study for fashion industry in danang, vietnam

1. Trường Đại học Kinh tế - Đại học Đà Nẵng This research studies a specific field in the fashion world, which is clothing. We will focus on new aspects, find out the characteristics, strengths and limitations of building and developing loyalty strategies, find out the keys factors that affect loyalty in the customer in the context of multi-channel retail for fashion clothing in Da Nang city. Loyalty plays an important role in the developing of fashion businesses, which is a long-term source of profit, affecting the survival of the business. Therefore, our paper studies the loyalty of consumers under the perception of customers. What are the factors that influence customer loyalty? What do businesses need to do for each retail channel to build and develop loyalty? This paper will clarify all those questions. Based on the reasons mentioned above, we decided to choose the topic: “Measuring customer loyalty in the context of multi-channel retailing: Case study fashion retailers in Danang, Vietnam.” Looking at current trade trends, it can be said that multi-channel sales are becoming important. Consumers tend to use more channels for shopping. Multi-channel development helps businesses grow stronger and faster than traditional sales channels. If a retailer has 2 or more sales channels, the average revenue will likely to increase. Nearly two thirds of retailers think that multi-channel sales are extremely important to them, but less than 40% of them adapt to the initial multi-channel sales test phase. This poses challenges and opportunities for different retailers to join the multi-channel sales network ("Bán hàng đa kênh có thể giúp các doanh nghiệp bán lẻ truyền thống thành công hơn?," 2017) The research objectives of the study are as follows: (1) Understanding the concept of customer loyalty, factors that contribute the loyalty; Building model that measures the factors influencing customer loyalty in the context of multi-channel retail; (3) Applying the model to measure the level of antecedents of loyalty in the context of multi-channel fashion clothing, (4) Giving some ideas and contributing to increase customer loyalty in multi-channel retailing. 2. Literature review and Research Methodology 2.1. Literature review 2.1.1. Customer Loyalty According to (Oliver, 2014; Walsh, Evanschitzky, & Wunderlich, 2008), customer loyalty is "a strong commitment of the customer that he or she will re-purchase or re-sponsor a consistent product or service in the future, resulting in a repetitive purchase of the same brand. The number of conversion behaviors that may occur due to marketing efforts from competitors". Some models of customer loyalty are summarized in Table 1 Table 1. Customer loyalty models Author Year Model Components Mokhtar and 2016 The impact of a number of factors on customer Service Quality Yusr loyalty in the context of B2B. Company image Customer trust Customer Acquisition Cost Rai and Medha 2013 The antecedent of customer loyalty in the context Service Quality of life insurance industry in India. Customer Satisfaction Trust Commitment Company Image Conversion Cost Communication From the above statements of loyalty, our team offers a general concept of "loyalty" that: Customer loyalty is defined as a positive attitude and a strong commitment that will continue to trust and use the 110
2. Trường Đại học Kinh tế - Đại học Đà Nẵng 2.2. Research Model Our research model will inherit three traditional component of loyalty: satisfaction, business image and trust from research models of Rai and Medha (2013), Zhang, Ren, Wang, and He (2018) and Li, Li, Liu, and Huang (2019). Zhang et al. (2018) have proved that trust and satisfaction effects consumer behavioral loyalty and Li et al. (2019) have shown that business image also influence the consumer retention. Another component that we added to the paper is channel integration, which includes: integration promotion, integration of product and price, integrated transaction information, integrated information access, integrated order fulfillment and integrated customer service. First, this is an important and necessary variable inherit from Zhang et al. (2018) research which is in the same multi-channel retailing context. Second, even though Zhang et al. (2018) model mainly investigated the relationship between channel integration and consumer empowerment, which may not quite suitable to our topic, but Schramm-Klein (2011) and Lee and Kim (2010) have proved that consumer loyalty is influenced by channel integration. The complete model consists of 9 main components: Integrated promotion (THQC), Integrated product and price (THSP), Integrated transaction information (THGD), Integrated information access (THTT), Integrated order fulfillment (THDH), Integrated customer service (THKH), Trust (T), Business image (HA) and Satisfaction (TM). Our research model is shown in Figure 1 Figure 1. Research model 2.2.1. Research Hypothesis a) Channel Integration and customer loyalty Channel integration is defined as a combination of using many different forms of interaction, from offline channel like physical stores to online channel such as multi-channel retail, media or websites. Its purpose is to make use of the advantages of all channels, eliminate competition, and create synergy in company resources and thereby raise working efficiency and company performance (Neslin et al., 2006). In the current multi-channel retail context, selecting integration channels is considered as a promising option to ensure increasing in customer satisfaction by providing seamless shopping services (Goersch, 2002; King, Sen, & Xia, 2004) 112
3. Trường Đại học Kinh tế - Đại học Đà Nẵng H7: Trust has a positive impact on customer loyalty. c) Business image and customer loyalty Aaker (1996) concluded that images are a result of all the experiences, impressions, beliefs, feelings and knowledge that people perceive of a company. Sirgy and Samli (1989) had made conclusion that images have a direct impact on customer’s loyalty to the store. . Kaur and Soch (2013) studied the direct and indirect effects of Business Image on customer loyalty and both effects are particularly relevant. They also consider Business Image an essential determinant for customer loyalty. Therefore, we suggest the following hypotheses: H8: Business image has a positive impact on customer loyalty d) Satisfaction and customer loyalty Oliver Richard (1980) explained that customer satisfaction occurs when customers consider the actual results they receive compared to their expectations. Over the years, several researchers such as Ganesan (1994); Mittal, Ross Jr, and Baldasare (1998); Mittal and Kamakura (2001) and others have proved that customer satisfaction affects factors that demonstrate customer loyalty, thus influences the creation of a long- term relationship. Therefore, we suggest the following hypotheses: H9: Satisfaction has a positive impact on customer loyalty. 2.3. Research methodology The main purpose of this paper is to study on measuring customer loyalty in the context of multi- channel retailing, specifically the garment market in Da Nang. Therefore, we will use both quantitative research methods and quantitative methods. The surveys are conducted offline within Danang City. The group conducts a direct survey at fashion stores, using convenient data collection methods: Go to a fashion stores in the city of Da Nang to collect answers until receive enough number of samples for the study. From the objectives of the study, our group needs Vietnamese respondents to identify, evaluate the market of clothing and the factors that help develop loyalty to the product. Therefore, our study’s main target is both genders above 18 years old, living in Da Nang and have been using the services related to the goods that the group is studying. Apply formulas to calculate sample size: Formula 1: For EFA discovery factor analysis: Based on research by (Hair, Anderson, Tatham, & William, 1998) n = 5 * 50 = 250 (sample) Formula 2: For multivariate regression analysis: (Tabachnick & Fidell, 1996) n = 50 + 8 * m = 50 + 8 * 11 = 138 (sample) Therefore, when selecting the number of samples, it is necessary to satisfy both of the above formulas and the principle is that surplus is better than lack of samples. Therefore, we decided to choose the estimated size of 320 direct offline surveys at fashion stores. The questionnaire was developed based on the measurement model for customer loyalty in the context of multi-channel retail which includes 09 components with 40 variables. Besides, there are 5 variables of Loyalty factor that are also included for survey. 3. Results and discussion 3.1. Results 3.1.1. Sample description 114
4. Trường Đại học Kinh tế - Đại học Đà Nẵng information (THGD) THGD3 .642 .690 THGD4 .630 .697 Integrated THTT1 .781 .855 .893 information access THTT2 .818 .841 (THTT) THTT3 .831 .838 THTT4 .634 .909 Integrated order THDH1 .841 .778 .857 fulfilment (THDH) THDH2 .517 .863 THDH3 .874 .776 THDH4 .758 .804 THDH5 .412 .890 Trust (T) T1 .683 .885 .895 T2 .881 .841 T3 .867 .843 T4 .858 .845 T5 .450 .931 Business Image (HA) HA1 .719 .822 .859 HA2 .101 .908 HA3 .919 .781 HA4 .918 .779 HA5 .897 .784 HA6 .362 .884 Satisfaction (TM) TM1 .478 .643 .701 TM2 .484 .641 TM3 .553 .611 TM4 .546 .615 TM5 .250 .735 Loyalty (LTT) LTT1 .508 .763 .785 LTT2 .518 .759 LTT3 .562 .745 LTT4 .502 .764 LTT5 .726 .687 3.1.3. Exploratory factor analysis (EFA) The exploratory factor analysis EFA (with the extraction of the factor used as Principal Components and Direct Oblimin rotation) was conducted with the aim to eliminate some variables to reduce it to a more significant set of variables after checking Cronbach’s Alpha reliability. Disqualified variables including HA2 and TM5 were removed in Cronbach’s Alpha test and will be not included in the EFA analysis. Therefore, we will analyze EFA with 10 components including 43 variables as follows: 5 Trust variables, 5 Image variables, 4 variables of Satisfaction, 4 Integrated promotion variables, 4 Integrated product and price variables, 3 Integrated customer service variables, 4 Integrated transaction information variables, 4 Integrated information access variables, 5 Integrated order fulfilment variables and 5 Loyalty variables. After running EFA analysis 6 times for Independent variables, the final result is shown as Table 5, 6. 116
5. Trường Đại học Kinh tế - Đại học Đà Nẵng 3.1.4. Building a customer loyalty index in multi-channel retailing Regarding Multiple regression models, the results are like Table 7,8,9 Table 7. Model Summary Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .889a .791 .785 .260 Table 8. Anova ANOVAa Model Sum of Squares F Mean Square F Sig. 1 Regression 74.044 9 8.227 122.062 .000b Residual 19.546 290 .067 Total 93.591 299 a. Dependent Variable: LTT b. Predictors: (Constant), TM, THTT, HA, THDH, THKH, THSP, THQC, T, THGD Table 9. Coefficients Coefficientsa Model Unstandardized Standardized t Sig. 90.0% Confidence Coefficients Coefficients Interval for B B Std. Error Beta Lower Upper Bound Bound 1 (Constant) -.101 .121 -.833 .405 -.300 .099 THQC .045 .017 .076 2.587 .010 .016 .073 THSP .076 .022 .102 3.431 .001 .039 .112 THDH .206 .017 .349 12.455 .000 .179 .233 THKH .077 .016 .137 4.734 .000 .050 .104 THGD .206 .029 .241 7.216 .000 .159 .254 THTT .035 .017 .059 2.105 .036 .008 .062 T .229 .020 .358 11.739 .000 .197 .262 HA .074 .014 .150 5.135 .000 .050 .098 TM .085 .027 .096 3.152 .002 .040 .129 a. Dependent Variable: LTT According to the results of ANOVA analysis, because F = 122.062 and Sig. = 0.00 <0.05, we affirm that there exists a relationship between loyalty and other independent variables (Appendix). For correlation coefficients, we have 0.5 <R = 0.889<1 so we can conclude that these variables have a high correlation. 118
6. Trường Đại học Kinh tế - Đại học Đà Nẵng in customers’ mind. Based on survey data from consumers in Da Nang, businesses can identify and promote their strengths while overcome their weaknesses before entering the market. 4.2. Contribution of research In terms of practice, the results of this study have introduced a new model to measure customer loyalty in a multi-channel retailing context, helping to provide new directions in the selection of retail channels to increase customer loyalty, creating plans and strategies appropriate to the characteristics of fashion industry (including clothing and accessories). We also hope that this research can help businesses in Da Nang in particular and other cities in general can understand the components that make up loyalty, thereby giving suitable strategies and plans, thus increase the efficiency of business operations, and create a more developed economy that catching up with trends in the world. Along with the economic development, social life in both material and spiritual aspects will be improved, helping to increase the quality of life as well as the needs and desires of consumers. 4.3. Limitations and future research directions This research may not suitable for others industry. Therefore, some considerations should be made before applying this research model for measuring for a specific industry. This paper analyzes only one area of fashion clothing business, which causes a restriction when comparing this industry to similar types of businesses to see whether the measurement model is compatible. The following studies can increase its empirical value by adding other types of businesses and products to compare and contrast. The R index corrects R2 = 0.791. Thus, 1 – R2 = 0.209 is explained by factors not included in the model and this is considered one of the limitations of the study. This study is done using convenient sampling method, so the ability to represent the population is quite limited. Other limitations come from time, resources, honesty of respondents, In theory, future researches can consider adding other variables related to measuring loyalty in the context of multi-channel retail such as consumer culture. Moreover, other methods should be bringing into consideration to overcome the limitations of the two methods used and increase the effectiveness and accuracy of the paper. In practice, we recommend to expand the scope of research, not only for fashion products such as clothing, but also for other industries such as electronics, cosmetics, etc. and expand the scope of the study to whole country to increase representation for the sample. 4.4. Conclusion From the model we gave, we offer some suggestions for administrators (in the field of clothing business) to increase customer loyalty in the context of multi-channel retailing (especially in the Da Nang market): In order to increase the weight of Channel Integration components, we recommend businesses: Open more payment channels, creating more favorable conditions for shopping through multiple channels of customers; update specific information about goods on many retail channels; combine multiple channels to increase your chances of interacting with other customers. To increase customer trust in businesses, our team proposes some measures such as: ensuring and improving the quality of goods and services for customers, implementing promises and assurances, ensuring customer information security, solving customer problems, For Business Image component, to increase weight, there should be the following solutions: Building a positive image of the brand to make a good impression on customers; building innovative image strategies to catch up market trends, create new ways to attract customers. 120
7. Trường Đại học Kinh tế - Đại học Đà Nẵng [18] Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of management review, 20(3), 709-734. [19] Mittal, V., & Kamakura, W. A. (2001). Satisfaction, repurchase intent, and repurchase behavior: Investigating the moderating effect of customer characteristics. Journal of marketing research 38(1), 131-142. [20] Mittal, V., Ross Jr, W. T., & Baldasare, P. M. (1998). The asymmetric impact of negative and positive attribute-level performance on overall satisfaction and repurchase intentions. Journal of marketing 62(1), 33-47. [21] Neslin, S. A., Grewal, D., Leghorn, R., Shankar, V., Teerling, M. L., Thomas, J. S., & Verhoef, P. C. (2006). Challenges and opportunities in multichannel customer management. Journal of service research, 9(2), 95-112. [22] Neslin, S. A., & Shankar, V. (2009). Key issues in multichannel customer management: current knowledge and future directions. Journal of Interactive marketing, 23(1), 70-81. [23] Nunnally, J. (1978). Psychometric methods. In: New York: McGraw-Hill. [24] Oh, L.-B., Teo, H.-H., & Sambamurthy, V. (2012). The effects of retail channel integration through the use of information technologies on firm performance. Journal of operations management 30(5), 368- 381. [25] Oliver Richard, L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of marketing research 17(4), 460-469. [26] Oliver, R. L. (2014). Satisfaction: A Behavioral Perspective on the Consumer: A Behavioral Perspective on the Consumer: Routledge. [27] Peterson, R. A. (1994). A meta-analysis of Cronbach's coefficient alpha. Journal of consumer research, 21(2), 381-391. [28] Rai, A. K., & Medha, S. (2013). The antecedents of customer loyalty: An empirical investigation in life insurance context. Journal of Competitiveness, 5(2), 139-163. [29] Reichheld, F.F., & Sasser, W. E. (1990). Zero defections: Quality comes to services. Harvard Business Review, 68(5), 105-111. [30] Reichheld, F. F., & Sasser. (1990). Zero defections: Quality comes to services. Harvard Business Review, 68(5), 105-111. [31] Rigby, D. (2011). The future of shopping. Harvard Business Review, 89(12), 65-76. [32] Rowley, J. (2005). The four Cs of customer loyalty. Marketing intelligence planning, 23(6), 574-581. [33] Schramm-Klein, H. (2011). Integrated retail channels in multichannel retailing: do linkages between retail channels impact customer loyalty? In European Retail Research (pp. 111-128): Springer. [34] Sirgy, M. J., & Samli, A. C. (1989). The store loyalty concept: dimensions and measurement. Retail Marketing Strategy, New York, quorum [35] Slater, S. F. (1995). Issues in conducting marketing strategy research. Journal of strategic Marketing, 3(4), 257-270. [36] Tabachnick, B. G., & Fidell, L. S. (1996). SPSS for Windows workbook to accompany large sample examples of using multivariate statistics: HarperCollins College Publishers. [37] Trọng, H., & Ngọc, C. N. M. (2008). Phân tích dữ liệu nghiên cứu với SPSS: NXB Hồng Đức. [38] Verhoef, P. C., & Donkers, B. (2005). The effect of acquisition channels on customer loyalty and cross- buying. Journal of Interactive marketing, 19(2), 31-43. [39] Villanueva, J., Yoo, S., & Hanssens, D. M. (2008). The impact of marketing-induced versus word-of- mouth customer acquisition on customer equity growth. Journal of marketing research, 45(1), 48-59. [40] Walsh, G., Evanschitzky, H., & Wunderlich, M. (2008). Identification and analysis of moderator 122