THE RELATIONSHIP BETWEEN SERVICE RECOVERY AND CUSTOMER SATISFACTION IN ONLINE SHOPPING A CASE STUDY OF SHOPEE, LAZADA AND TIKI45324

THE RELATIONSHIP BETWEEN SERVICE RECOVERY AND CUSTOMER SATISFACTION IN ONLINE SHOPPING - A CASE STUDY OF SHOPEE, LAZADA AND TIKI Khuat Thao Nguyen™ ABSTRACT E-commerce EC market has bee

THE RELATIONSHIP BETWEEN SERVICE RECOVERY AND CUSTOMER SATISFACTION IN ONLINE SHOPPING -

A CASE STUDY OF SHOPEE, LAZADA AND TIKI

Khuat Thao Nguyen™ ABSTRACT

E-commerce (EC) market has been growing significantly, however, there has been many existed service failure problems about products quality Service recovery (SR) activities become more and more important to improve customer satisfaction This studies three biggest

EC companies in Vietnam including Shopee, Lazada and Tiki, focusing on how customer's fairness perception of SR page can affect

on their satisfaction Data used in this study was collected through an online survey which gathered individual evaluation of 350 customers

of these three EC websites Based on existing researches that are related to SR, a model is adapted to test the relationship between fairness including three dimensions: Interactive fairness, Outcome fairness, Procedural fairness and Customer satisfaction Data was analyzed by using linear regression ‘The result shows that Interactive fairness and Procedural fairness have a positive effect on customer satisfaction while Outcome fairness does not have significant relationship Regarding empirical implications, this research gives

1 VNU University of Economics and Business, Vietnam

*Corresponding author: khuatthaonguyen@gmail.com

184 PRODUCTIVITY AND QUALITY IN THE ERA OF DIGITAL TRANSFORMATION

some recommendations for EC companies to consider SR as effective tool of strategy, they should focus interactive fairness and procedural fairness to increase customer satisfaction, however, still maintain the outcome fairness

Keywords: Service recovery, customer satisfaction, online shopping

1 INTRODUCTION

When the Internet is rapidly growing, there are more and more people having tendency of shopping online because of saving time and cost Hence, online retailers are increasing significantly accompanied with the increase of using online shopping website such as Shopee, Lazada, Tiki, etc According to the Minister of Information and Communications, Vietnam had approximately 54% Internet penetration rate in 2017, while the global average of 46.5%; which can show that online shopping area is going to be well-positioned

to hold the key to success for e-commerce in Viet Nam Currently, most of Vietnamese companies have had compensation policies for consumers in case of service failure These policies have affected in improving customer perceptions lead to the quality of the service is positively transformed However, handling customer complaints or

SR are still considerable issues

Under increasingly intense competitive pressure, understanding how customers feel when they are dissatisfied with products/services and handling these issues or “service recovery” is essential; however,

this problem is not easy for most businesses (Stauss et al., 2005)

According to a research in the retail sector in Vietnam context, handling a customer’ problems has a positive and significant impact

on customer loyalty (Phan Chi Anh, 2006) In order to build a sustainable brand, organizations not only actively improve the quality

of services but also must effectively recover existing service failure

International Conference Proceedings 185

(Luu Trong Tuan, 2017) Although there are some conclusions from

related studies about service quality, there is little research on SR in

EC, which should be enlarged

This research aims at finding which factors of SR can affect CS and causes of those effects by comparing return/refund policies of Shopee, Lazada and Tiki This research also can be applied for others online retailers, who have created market of selling products online

2 LITERATURE REVIEW

2.1 Customer satisfaction and e-serqual

Zeithaml et al (2001, 2002) developed the e-SERVQUAL

measure of e-service quality to study how customers judge e-service quality This model was drawn up through a three-stage process involving exploratory focus groups and two phases of empirical data collection and analysis It contains seven dimensions: (1) efficiency,

(2) reliability, (3) fulfillment, (4) privacy, (5) responsiveness, (6) compensation and (7) contact The first four dimensions are classified

as the core service scale, and the latter three dimensions are regarded as

a recovery scale, since they are only salient when online customers have questions or problems Contents of three recovery scale dimensions

are shown below:

e Responsiveness: Compares the capability of e-retailers to give appropriate data to customers when a problem happens, having mechanisms for handling returns, and giving online guarantees

¢ Compensation: Consists receiving money back and returning shipping and handling expenditures

¢ Contact: The requirement of customers to speak to a living customer service agent online or on the phone

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Customer Satisfaction (CS)

CS have been defined as an overall evaluation based on the customer's total purchase and consumption experience with a good

or service over time (Anderson, Fornell and Mazvancheryl, 2004;

Fornell, 1992)

Previously, many studies have been conducted in the context

of service quality and CS (Ahmed et al., 2010; Arasli et al., 2005; Caruana et al., 2000; Taylor and Baker, 1994; Wang et al., 2003; Zhu et al., 2002) These studies suggest that service quality and CS

are key factors of the service industry If a customer is satisfied with a

service or product after having used it, then the chances increases in

repeating the purchase of that service or product (East, 1997)

Moreover, CS can influent a firm’s market value Firms with satisfied customers tend to enjoy greater customer loyalty (Bolton and Drew, 1991; Oliver, 1980), positive word of mouth (Szymanski and Henard 2001), and a customer's willingness to pay premium prices (Homburg, Koschate and Hoyer, 2005), all of which can increase a firm’s market value Indeed, firms with higher levels of CS can achieve higher levels of cash flows (e.g., Gruca and Rego, 2005; Fornell, 1992; Mittal et al., 2005) and less volatility of future cash flows, thus leading to superior market value (e.g., Anderson, Fornell and Mazvancheryl, 2004; Fornell et al., 2006; Srivastava, Shervani and Fahey, 1998)

2.2 Service recovery

One of the first definitions of “service recovery” was given by Grönroos in 1988, referring to the action taken by a service provider

to address a customer complaint regarding a perceived service failure

In 1993, Boulding defined a broader SR, involving what a service

International Conference Proceedings 187 provider does to respond to service failure The objective of recovery

is to solve problems in two potential situations: during the service encounter (i.e before a customer complaint) and shortly after the

service encounter if the customer is dissatisfied (Gro”nroos, 2007)

SR in online sector has become more important as part

of strategic management in companies because of extremely competition E-commerce often eliminates the human interaction which is often viewed as a vital component of traditional service experience (Forbes et al., 2005; Holloway et al., 2003; Oliver et al., 1898) Thus, service problems might emerge during online retailing

service processes (Forbes et al., 2005; Kelley et al., 1993) Researches

also confirm the importance of SR, and the effect of SR on consumer loyalty (Harris et al., 2006; Maxham et al., 2001; McCollough et al.,

2000; Smith et al., 1999; Wirtz et al., 2004)

2.3 Relationship between E-SR and customer satisfaction

The inseparable and intangible nature of services makes it difficult for service providers to avoid service failures during service delivery Most customers who encountered a service failure anticipate service recovery (Blodgett, Hill and Tax, 1997; Goodwin and Ross, 1992; Holloway and Beatty, 2003) Via effective recovery strategies, service providers can still appease unsatisfied customers to return

them to a state of satisfaction, increase the customer retention rate

(McCollough, Berry and Yadav, 2000) and even foster a long lasting telation with dissatisfied customers (Kelley, Hoffman and Davis,

1993), ultimately making them loyal ones (Boshoff, 1997)

According to Tammo (2014) in a research of online context,

it was suggested that the highest repurchase intentions arose among consumers who complained and expressed satisfaction with the complaint handling, in support of the service recovery paradox in an

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online setting Successful SR also can enhance customers’ perceptions

of the quality of the service and the organization, lead to positive

word-of-mouth (WOM) communication, enhance customer

satisfaction, and build customer relationships and customer loyalty

(Michel, Bowen & Johnston, 2009) Adamson and Matos et al even

noted that effective SR could lead to higher satisfaction level than that without any service problem at all

3 METHODOLOGY

The theory of fairness has been widely used as a principle theoretical framework in service recovery studies to explain whether

a customer has been treated fairly after a service failure (Example: Tax

et al., 1998; Smith and Bolton, 1998; Smith et al., 1999; Goodwin and Ross, 1992; Tax and Brown, 1998) Recently, the fairness theory

has been applied in studies in this area (eg., Evandro and Marcos

(2015); Van Vaerenbergh and Orsingher, 2016) because perceived

fairness is a strong driver of customer satisfaction with the recovery

effort (Stefan, 2009) This research model used in this research based

on the literature review part and is partly adapted from model of

Collier et al (2006) Research model is represented in Figure 1

Interaction

fairness

Outcome fairness >| Service recovery >

“4 satisfaction Procedure fairness

Figure 1: The Conceptual model of research

Source: Adapt from research model of Collier et al (2006).

International Conference Proceedings T88 There are three hypotheses as follow:

Hypothesis 1: There is a significant positive relationship between interactive fairness and a customer’ satisfaction with an e-retailer Hypothesis 2: There is a significant positive relationship between outcome fairness and a customer’ satisfaction with an e-retailer

Hypothesis 3: There is a significant positive relationship between procedural fairness and a customer's satisfaction with an e-retailer

Quantitative research methodology is used to finding the trend

of customers’ perception about EC companies Besides, qualitative analysis is also used to point out differences among SR policies After using SPSS to analyze the data and policies analysis, three main research questions will be answered, which are:

1 What are the impacts of IK OF and PF on customer satisfaction in retail sector on E-commerce, especially in the case of Shopee, Lazada and Tiki?

2 What are differences among the three companies’ policy, which effect of customer satisfaction on service recovery

experience?

3 How can EC companies improve their performance on

service recovery activities to increase customer satisfaction?

A questionnaire was designed in two main parts and was demonstrated shortly to answer the research questions and test hypotheses The first part consists of some general information regarding the information of the participants The second part includes the information that is related to customer perceptions of factors affecting their satisfaction The survey was sent to fans of EC market in Vietnam Data collection had a sample of 325 Vietnamese

190 PR0DUCTIVITY AND QUALITY IN THE ERA 0F DIBITAL TRANSFDRMATIDN

respondents, who are using the EC in three markets including

Shopee, Lazada and Tiki

In the sample, the difference between men and women of respondents is insignificant The gender proportion is 46.5% male and 53.5% female Regarding age, the sample focus on young people, those who can access and update according to the e-commerce market, with 41.5% under 25, 35.7% between 25 and 40 years, 15.7% between 40 and 55 years and only 7.1% over 55 years old

‘They are also from various working groups, with different monthly income and most of them have income under 12 million VND per

month (89.5%)

Likert Scale 1-5 was used to collect data from participants The recovery dimensions of the survey were incorporated from the

seminal recovery study of Tax, Brown, and Chandrashekaran (1998)

and were slightly changed to apply to an online setting (Collier, 2009) Lastly, the CS scales were adapted from the Tax, Brown, and

Chandrashekaran (1998) and Mathwick (2002) research studies

Cronbach's Alpha of all four components are: CS = 0.733, IF = 0.845, OF = 0.748 and PF = 0.804 respectively, which are more than 0.6 Thus, all items have internal consistency, closely correlated with each other All factors have satisfactory authenticity; the Eigenvalues values are greater than 1, factor loadings are all over the value of 0.5

4, RESULTS AND DISCUSSIONS

Correlation analysis

All correlation is significant at the 0.01 level (2-tailed) Thus,

there exists a positive correlation relationship between the dependent

variable (CS) and each independent variable (IK OF PF) Those

correlation relationships are positive with the correlation coefficients

International Conference Proceedings 191 are in the range of 0 to +1 Besides, the correlation between the

dependent side CS and the independent variable IF represents the

strongest correlation (0.518), then CS and PF (0.501) and finally CS with OF (0.473)

Table 1: Correlation analysis

** Correlation is significant at the 0.01 level (2-tailed)

Source: Analysis results from SPSS software Linear regression analysis

Table 2 shows that adjusted R-square value is 29.4%, which

indicates the percentage of variances in CS can be explained by three

variables

Table 2: Linear regression analysis result

ˆẼ ẽ 1ˆ

OF 0.504 0.294 | 30.681 | 0000 0.066 0.512 | 3.073

Note: Dependent variable: Customer satisfaction Source: Analysis results from SPSS software

F = 30.681 and Sig = 0.000 < 0.05 means at least one of independent variables put in the model has a significant impact on

192 PRODUCTIVITY AND QUALITY IN THE ERA OF DIGITAL TRANSFORMATION

the dependent variable So, the value confirms the group of three

factors with statistically significant interaction with amount of purchasing variable

All the VIF (variance inflation factor) values in the table are

smaller than 4 so there is no multi-collinearity phenomenon That means, independent variables are not much related, being able to interpret dependent variables independently

Hypothesis testing

Hypotheses 1 is validated; Standardized coefficients = 0.295 and Sig (or the p-value) = 0.002 much lower than 0.05 There is a positive relationship between IF and CS This factor also has the strongest relationship to CS among three factors

Hypothesis 2 is invalid because Sig = 0.512 that is much more

than 0.05 Thus, it is not enough to conclude OF has a positive

impact to CS although the Standardized coefficients is 0.066 (> 0)

Hypothesis 3 is supported because Standardized coefficients =

0.239 and Sig (or the p-value) = 0.010 much lower than 0.05 Thus,

there is a positive relationship between PF and CS

Research context

According to EVBN report, in Vietnam, although EC market

is growing up significantly, it still approaches a little market size

of total retail market Currently, the proportion of operating Vietnamese EC market is only less than 5% Besides, a statistic of Vietnam E-Commerce and Digital Economy Agency showed that the highest percentage of customers buying goods more than second

times is from 10 to 30%, which can be reached by 17% total EC

website or mobile apps These numbers mean that EC markets are