Smart Retail Technologies: The Future of Retailing?
Investigating the relation of smart retail technologies on customer loyalty and
the mediating roles of satisfaction and store image
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Smart Retail Technologies: The Future of Retailing?
Investigating the relation of smart retail technologies on customer loyalty and
the mediating roles of satisfaction and store image
University of Groningen Faculty of Economics and Business
Department of Marketing
MSc Marketing Management Master Thesis
January 27, 2020
First supervisor: dr. J. Berger Second supervisor: dr. A. Schumacher
By Joppe Voortman joppevoortman@gmail.com
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ABSTRACT
The presence of smart retail technologies is developing, and their importance is being
recognized by scholars and practitioners. Retailers are exploring new technologies in order to resist the increasing competition of online retailing and in recent times, the potential benefits of smart retail technology became a prominent topic in the marketing literature, but until now, evidence was missing. This study looks further than the adoption and acceptance of smart retail technology and finds new insights on the impact of smart retail technologies, by investigating the relationship between the perceived value of smart retail technology and loyalty. Loyalty is divided into behavioral and attitudinal loyalty and satisfaction and store image are considered mediators in this relationship. This results in two multiple mediation models, one including behavioral loyalty as the dependent variable, and the other including attitudinal loyalty as the dependent variable. An experimental research was conducted, and the models were tested using data from a convenience sample of 139 participants. The findings of this research show that smart retail technology has a positive influence on both behavioral and attitudinal loyalty. Moreover, smart retail technology has a positive influence on satisfaction and store image as well, and subsequently, satisfaction and store image both have a positive influence on behavioral and attitudinal loyalty. Ultimately, the results showed that the relation between perceived value of smart retail technology and behavioral loyalty is fully mediated by satisfaction but was unable to find mediation of store image. The relation between perceived value of smart retail technology and attitudinal loyalty is partially
mediated by satisfaction and store image. Finally, additional analysis found that the loyalty of customers increased after the use of smart retail technology. This study provides contributions to the academic literature by finding evidence for the expected benefits of smart retail
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Table of Contents
1. Introduction ... 4
2. Theoretical framework ... 6
2.1 Perceived value of Smart Retail Technology ... 7
2.2 Loyalty ... 8
2.3 Satisfaction ... 10
2.4 Store Image ... 11
3. Methodology ... 12
3.1 Research design and procedures ... 12
3.2 Measures ... 13 3.3 Plan of Analysis ... 15 4. Results ... 16 4.1 Descriptive statistics ... 16 4.2 Validity analysis ... 16 4.3 Tests of hypotheses ... 17
4.3.1 Multiple mediation analysis model behavioral loyalty ... 17
4.3.2 Multiple mediation analysis model attitudinal loyalty ... 19
4.4 Additional results ... 21
5. Discussion ... 22
5.1 Findings and theoretical implications ... 22
5.2 Managerial implications... 24
5.3 Limitations and Future Research ... 25
References ... 27
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1. Introduction
The internet, advanced technologies and information systems are rapidly and dramatically changing the retail industry. Online retail is continuously expanding and as a consequence, the retail environment is becoming increasingly competitive. In order to stay competitive,
retailers and in particular physical retail stores need to transform their existing business models. Scholars seem to agree that in this environment, customer experience is one of the most important attributes of a retail business. Renko and Druzijanic (2014) state that if retailers want to compete effectively, their focus should be directed on customer shopping experience. Furthermore, Verhoef et al. (2009) revealed that the establishment of a superior customer experience, is the most crucial process for retailers in this environment.
The importance of customer experience is recognized by retail managers as well, Gartner (2014) found that almost 90 percent of retailers are determined to compete on customer experience.
It is apparent that customer experience is vital for improving retailer’s performance, so it is important to understand which methods could improve the customer experience. One method in particular is gaining a lot of interest from scholars and practitioners, the implementation of new technologies in the retail store (Pantano and Naccarato, 2010). Considering these new technologies, one of the most promising are called smart retail technologies. Smart retail technologies are distinct from other retail technologies because these technologies are smart or intelligent, this means that the technology has sensing and controlling capabilities and are interconnected with other technologies, objects or networks (Roy et al., 2017). Some
examples of smart retail technologies are self-service checkouts, smart mirrors, mobile applications and service robots. Several studies suggested a variety of benefits deriving from smart retail technologies, including the capture of and access to real-time data (Roy et
al.,2017), personalization, customization and recommendations (Pantano and Viassone,2014), customer interaction and providing information (Inman and Nikolova, 2017). Moreover, researchers imply that these benefits will result in an enhanced customer experience and consequently lead to superior shopping performance, improved customer satisfaction, and increased business profitability (Bullinger et al.,2010; Kim et al.,2016; Renko and
Druzijanic,2014).
5 Ultimately, research that investigates the effects of smart retail technology on consumer behavior and retail performance is still lacking. As the before mentioned studies imply, the use of smart retail technology has many potential benefits, but they need to be tested first. Many authors in this field are calling for more research on this topic. Chuah et al. (2016) state that there is no accurate investigation of customer experiences with smart retail technology and corresponding consequences. Furthermore, Roy et al. (2017) mention that there is a lack of empirical research examining the smart retail experience.
This study will examine this gap and explore if smart retail technologies are really effective in increasing value for the customer and the retailer. In order to do so, this research will test the influence of smart retail technology on (store) loyalty, (store) satisfaction and (store) image. Moreover, it is expected that smart retail technology has a positive relation on loyalty and that satisfaction and image mediate this relationship. Besides that, smart retail technology is conceptualized as the perceived value of smart retail technology.
Loyalty is chosen because it is a strong predictor of retail performance (Smith and
Wright,2004) and Chiu et al. (2014) showed that loyalty is crucial for the success of retail stores. Moreover, initial research regarding smart retail technologies demonstrate that it is expected that the use of this technology will produce more word-of-mouth, although this depends on how satisfied customers are with the smart retail technology experience (Roy et al.,2017). This is a plausible suggestion because numerous studies already found a positive relation between satisfaction and loyalty (Cronin et al.,2000). Lastly, Roy et al. (2017) suggest that future research should investigate the effect of smart retail technology on store image because this could result in a better understanding of smart retail technology
experience. Yoon and Park (2018) confirm that in-store experience could generate a favorable store image, and this could result in store revisit intentions.
This study is determined to find new insights into the field of smart retail technologies, consumer behavior and retail performance, the research starts with a literature review leading to the hypotheses in the next chapter. After that, research design, data collection and plan of analysis will be covered in the methodology section. Finally, the results will be presented and discussed, theoretical and managerial implications are given and to conclude,
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2. Theoretical framework
This chapter consists of a discussion of the literature regarding the topic of this study. The theoretical background is used to provide information in order to formulate a conceptual model. All variables, that are being used in the model, are discussed as well as hypotheses regarding the relationships are explained. Figure 1 presents the conceptual model.
Figure 1. Conceptual model
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2.1 Perceived value of Smart Retail Technology
First of all, it is important to define the smart retail technologies that are being used in this research. As mentioned before, there is a wide array of particular types of smart retail
technologies. Smart retail technologies are being used in three dominant environments such as in-store (point-of-sale), online and supply chain (Renko and Druzijanic,2014). This research centers on offline retailing, so consequently the focus in this paper is on in-store technologies. Secondly, shopper marketing is becoming prevalent in the retail marketing literature and research shows that retailers can use this concept to create an advantage (Shankar, 2011; Shankar et. al,2016). In the light of shopper marketing this paper focuses on shopper-oriented technologies and especially technologies that need human (customer) interaction.
In order to accomplish a meaningful research, it is important to narrow the technologies down even more and choose a specific category. Pantano and Viassone (2014) established a
classification of the retail technologies. The first category is (i) touch screen displays/in-store totems, these are technologies belonging to the point of sale such as virtual garment fitting systems and self-service technologies. The second category is (ii) mobile applications, these are systems made for the mobile of the consumers in order to make payments, search items or comparing items. The third and last category is (iii) hybrid in-store systems, these
technologies can often be moved around the store. These systems are usually based on RFID or barcode scanners and provide the customer with more details, recognizes the profile of the customer and are able to make recommendations. A great example is the intelligent shopping trolley.
For the purpose of this research the third category will be used, mainly because of the reasons mentioned earlier, the technology in this category is in-store and shopper – oriented with customer interaction. Furthermore, Pantano and Viassone (2014) state that the main advantage of these technologies is their capability of providing more useful information for supporting consumers' in-store experience, by allowing them to save time through enriched and
customized information, useful functions, and entertaining tools.
Besides this example, other researchers (Roy et al., 2017,2018; Wünderlich et al.,2013) suggest that the smart retail technology can provide value for the customer and Willems et. al (2017) state that retail technologies can generate value to customers by influencing one or a more value dimensions, smart retail technologies are able to decrease the cost side or increase the gains side in the value equation.
8 In order to study the impact of smart retail technology this paper adopts the perceived value of using the smart retail technology as a construct. As found in many studies, utilitarian and hedonic values should be considered when measuring perceived value, especially in accordance to shopping experience and a retail environment (Mishra, 2014).
Moreover, utilitarian value is related to factors such as quality, availability and variety and is functional of nature (Stoel et al., 2004). When a customer succeeds to satisfy their need and accomplishes their shopping task, utilitarian value is created. Hedonic value is on the other hand related to emotions and aspects like fun, enjoyment and pleasure. This can lead to the experience of feelings like joy and freedom while shopping (Ipek et al., 2016). This study recognizes this view and agrees that value consists of utilitarian and hedonic value., but for the purpose of this research value is not divided into two dimensions and perceiver value as a whole is utilized.
2.2 Loyalty
Loyalty has received a lot of attention in retail marketing literature, but it is always hard to define because a lot of researchers used different approaches. Originally the concept was defined by using a behavioral perspective like repetition of purchases in the store (Sivadas and Baker-Prewitt, 2000), repeat patronage (Johnson et al., 2015). However, other researchers stated that the concept of loyalty also has an attitudinal approach. Dick and Basu (1994) created a framework that consist of an attitudinal and a behavioral part. The attitudinal component consists of affective variables like emotions and feelings to the store. Morgan and Hunt (1994) found that trust and attachment could be a part of the attitudinal component as well. You may conclude that the behavioral approach, by itself, may not be a sufficient indicator of loyalty. Some form of psychological commitment on the part of the customer is also a necessary ingredient of true store loyalty (Bloemer and Ruyter,1988).
Based on the literature, this study defines loyalty as a behavioral and an attitudinal component and will investigate the effect of smart retail technology on both components of loyalty. This could lead to more profound implications and it enables this research to explore a potential difference between the effect on behavioral and attitudinal loyalty. The main reasoning for finding a potential difference is because this study expects that the experience of using a smart retail technology is task-related or emotional related, or in other words, utilitarian and
hedonic. Moreover, the utilitarian-related experience is expected to have more influence on behavioral loyalty and the hedonic-related experience on attitudinal loyalty.
9 Subsequently, Jones et al. (2006) suggest that hedonic value is related to the attitudinal
component of loyalty. The authors use the antecedents of the attitude theory of Dick and Basu (1994), emotions and moods and show that they relate to aspects of hedonic value. Moreover, Jones et al. (2006) report that consumers establish positive attitudes in relation to experiences that produce psychological rewards. These experiences are created by hedonic values like the feeling of enjoyment during a shopping trip. Adapa et al. (2019) found that perceived value of using a new technology is an important predictor of approach or avoidance behavior. Thus, when customers perceive a smart retail technology as providing value, customers will be more likely to revisit the store.
As mentioned earlier, this study used a comprehensive construct of value and did not divide value into more dimensions, in order to measure the perceived value from using smart retail technology. Nevertheless, the distinction between utilitarian and hedonic is important because it could explain suggestions and the proposition of the hypotheses.
The following hypotheses are proposed based on the review of the literature.
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2.3 Satisfaction
Satisfaction has been defined in two different ways. The first type of satisfaction is called transaction specific satisfaction and is interpret as “the post-choice evaluative judgement of a specific purchase occasion” (Anderson et al,1994). This approach states that the satisfaction appears after a single encounter with the store or service provider. The second type is called overall satisfaction and is based on the last purchase and all other experiences with the service provider, which results in an overall evaluation (Veloutsou et. al, 2005). In this paper the overall perspective of satisfaction will be used, mainly because research found that this approach could be a better indicator of future loyalty and business performance. Besides that, in this study satisfaction refers to the customer’s satisfaction with the store and more specific the customer’s overall evaluation of the store experience (Macintosh and Lockshin, 1997). Smart retail technologies are able to offer personal service, better control of the shopping process and increased convenience and/or enjoyment (Roy et. al, 2018). It is plausible to expect that the use of smart retail technology will lead to positive evaluation of the store experience and consequently increases satisfaction.
Satisfied customers tend to have a higher usage level of a service than those who are not satisfied (Bolton& Lemon, 1999; Ram & Jung, 1991). They are more likely to possess a stronger repurchase intention and to recommend the product or service to their family and friends (Zeithaml et al., 1996). Especially the behavioral aspect of loyalty is confirmed by Szymanski and Henard (2001), their study found a positive significant correlation between satisfaction and repeat-purchase in 15 of 17 correlations.
Bloemer and Ruyter (1998) found that two types of satisfaction (manifest and latent) both had a positive impact on store loyalty, but the effect of manifest satisfaction was greater than latent satisfaction. Manifest satisfaction corresponds to the definition that is used in this study because it means that an explicit evaluation of the store is made, which in case of a positive evaluation leads to store commitment.
Inman and Nikolova (2017) stated in their study that “given the documented benefits of customer satisfaction for customer retention and loyalty and for a firm’s performance, we argue that retailers should assess how the various technological innovations they are
considering might impact their shoppers’ satisfaction’’. This paper investigates this statement by proposing the following hypotheses
11 The relationships and interrelationships between perceived value, satisfaction and loyalty has been documented in many different studies. Cronin et al (2000) found a positive relationship in service environments. Besides that, research in the tourism and aviation environment found positive relationships between satisfaction and loyalty (De Rojas and Camarero,2008; Petrick and Backman,2002). An important study of Yang and Peterson (2004) found customer loyalty can be generated through improving customer satisfaction and offering high product/service value and hypothesized that customer satisfaction could be a mediating variable in linking customer perceived value and loyalty. This study expects that satisfaction has a positive influence on both dimensions of loyalty, a few examples are shown, but the academic literature agrees that satisfaction is a strong predictor of loyalty.
Following these earlier studies, this paper suggests that satisfaction mediates the relation between the perceived value of smart retail technology on loyalty. According to this expectation the following hypotheses are proposed.
H4. Satisfaction has a positive influence on behavioral loyalty H5. Satisfaction has a positive influence on attitudinal loyalty
2.4 Store Image
Store image is often expressed as how customers view the store or as Bloemer and Ruyter (1988) define it “the complex of a consumer’s perceptions of a store on different attributes”. In order to study the influence of smart retail technologies on image it is important to
understand how consumers form an image of the store.
Many researchers agree that image is the result of a process. This sensory process arises from ideas, feelings, and previous experiences with a firm that are retrieved from memory and transformed into mental images (Yuille and Catchpole, 1977)
As shown by earlier research, shopping experience in a retail store is important in generating a favorable image of the store (Yoon and Park, 2018). The paper of Hong (2015) found that in-store shopping experience which focused on sensual and cognitive responses had a positive impact on the store image. The use of smart retail technologies could create these kind of shopping experiences that trigger sensual and cognitive responses. In addition to this, smart retail technology is able to create a shopping experience that is associated with entertainment, fun and enjoyment. These types of experiences create hedonic shopping value for the
customers. Koschate et. al (2014) demonstrate that hedonic values influence store image. Thus, if the shopping value will increase by using the smart retail technology, the experience of customer will be remembered and consequently the customer will gain a more favorable image of the store. Thereby, proposing the following hypothesis.
12 Perhaps the earliest, and most widely cited, works in respect to store-image were generated by Pierre Martineau (1958). He maintained store loyalty is a function of store-image. If
individuals have a favorable image of the store, they are likely to develop a certain degree of loyalty commensurate to the favorableness of the image. Martensen (2007) states that a favorable brand image will have a positive impact on consumers’ behavior towards the brand, such as the opportunity to command premium prices, buyers who are more loyal, and more positive word-of-mouth. Yoon and Park (2018) found that a favorable store image causes store revisit intention. Besides that, for many customers smart retail technology could be a new and innovative technology. Reinders et. al (2008) found that if customers have the option to use a new technology in a retail store it produces more positive attitudes towards the store. The literature demonstrates evidence for the positive relationship between store image and loyalty. This study proposes the following hypotheses and expects that image mediates the relation between perceived value of smart retail technology and loyalty.
H7. Image has a positive influence on behavioral loyalty H8. Image has a positive influence on attitudinal loyalty
3. Methodology
In this chapter, the research design and procedures used to test the hypotheses will be explained. First, the research design and procedures will be examined. Secondly, the
measurement and the definition of the variables are explained. Lastly, the plan of analysis is given.
3.1 Research design and procedures
For this study a quantitative research is performed in the form of a scenario-based online questionnaire. The questionnaire was developed with Qualtrics and includes a scenario illustrated by different stimuli, a baseline measurement for loyalty, as well as items to test the variables of the conceptual model and at last several control questions. The questionnaire was distributed among friends, family and colleagues.
The primary method of data collection is the Qualtrics survey. Participants were asked to fill in the survey and the survey required a maximum of ten minutes to fill in. The survey
commenced with a general introduction to the study, explaining the aim of the study. Besides that, the introductory page demonstrates the instructions and procedure of the survey and at last ensures the anonymity and confidentiality of the participants and their information. After agreement of the participant the survey starts with a few general questions around
demographics. Ensuing the general questions, participants observe a picture of the
13 This study selected the Mediamarkt because it is a popular electronics store in the Netherlands and everyone has visited the Mediamarkt once. Furthermore, an electronics store is selected because electronics are high-involvement products and research found that customers are more likely to display loyalty, especially attitudinal loyalty for high-involvement products instead of low-involvement products (Knox & Walker, 2003). Most importantly, this study chose an existing store instead of a fictional store because participants are not able to give reliable answers regarding loyalty, especially attitudinal loyalty, if they see and / or enter the store for this first time. On the other hand, when an existing store is being used participants could already feel loyal towards this store. Therefore, a baseline measurement is included in the study which can be used to examine the difference in loyalty before and after the use of the smart retail technology. The participants will proceed and are exposed to several stimuli that depict the scenario. In short, the scenario consists of the participant being in the
Mediamarkt and interacts with the smart retail technology. This scenario is created by using photos and videos of an existing smart retail robot and complementary information. A short story helps the participant to imagine the situation. Examples of the stimuli can be found in Appendix A.
The smart retail technology is a retail robot that moves around the store and is very well explained by means of text, pictures and a video. The reason this study chose for a retail robot as an example of smart retail technology is already briefly explained in chapter 2. Besides that, the reasoning for the retail robot is also based on the value that derives from using the robot. The retail robot is able to provide utilitarian and hedonic value because on the one hand, customers are able to accomplish their task more easily. On the other hand, the retail robot can provide enjoyment, fun or pleasure.
After the experience with the smart retail technology, participants are asked to state their opinion about several statements that measure the perceived value of the smart retail technology, (store) image, (store) satisfaction and behavioral and attitudinal loyalty. At the end, the participant is thanked for his or her participation and can leave the survey.
3.2 Measures Loyalty
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Perceived value of Smart Retail Technology
In prior studies perceived value is often measured by using scales that focus entirely on value in terms of price or money, generally defined as functional value. On the other hand, research points out that a broader concept of value is more important to customers. (Zeithaml,1988; Sweeney and Soutar,2001). In this paper, perceived value is based on using a smart retail technology and it is to be expected that this could be a new and/or exciting experience for the customer. Therefore, this study will use a broader value dimension that encompasses
functional and emotional value or in other words consists of utilitarian and hedonic
components. The study of Ipek et. al (2016) uses a measurement scale that is centered around utilitarian and hedonic components of value. This scale is adapted and employed in this study. See table 1.
Store Image
In previous literature, researches have been divided about the operationalization of the store image. Broadly, three different operationalizations are used to measure store image. These operationalizations are semantic differential scales, multi item scales and unstructured free-response data(Hartman and Spiro,2005). Recent marketing research shows a tendency to multi item scales and this study will follow, mainly because this measurement determines
consumers’ perceptions of the store from various perspectives. The items are adopted from Grewal et al.(1998) and Bao et al.(2011). As for the other constructs in this study the items are measured using a 7-point Likert scale.
Store Satisfaction
The operationalization of store satisfaction is aswell an object of debate in marketing research. This is mainly a discussion about whether it should be measured as a global
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3.3 Plan of Analysis
SPSS statistics is the software that is being used in this study to perform the analyses. The data from all the completed surveys on Qualtrics is downloaded into the SPSS software. The dataset is reviewed, and invalid data is eliminated. Before combining the items into new variables, a validity analysis was performed. The decision has been made to not include a factor analysis because all the measurement scales are already used in previous research and proven to have a high validity. The Cronbach’s alpha is examined to ensure validity. To test the hypotheses, multiple mediation regression analyses are explained and performed with the PROCESSMacro by Hayes (2013). Lastly, a one-sample t-test is performed in order to investigate if the use of the smart retail technology made a significant difference on the loyalty towards the retail store.
Constructs Items
Perceived value of SRT (VA) 1. I had the possibility to buy what I really needed.
2. I found the items I was looking for.
3. This shopping trip was truly joyful.
4. I continued to shop, not because I had to, but because I wanted to.
5. Compared to other things I could have done, the time spent shopping was enjoyable.
6. I enjoyed this shopping trip for its own sake, not just for the items I have purchased,
(Store) Loyalty – Behavioral (LB) 1. I will shop more at this retail store in the next few months
2. I consider this retail store as my first choice. 3. I intend to continue to do business with this
store.
(Store) Loyalty – Attitudinal (LA) 1. I would recommend the store to friends and family.
2. I say positive things about the company to other people.
3. I am willing to make an effort to shop at this store.
Store Image (IM) 1. This store has a pleasant atmosphere.
2. This store looks attractive.
3. This store is close to my ideal store. 4. This store is close to my ideal store.
5. Overall, I have a favorable view of this store. Satisfaction (SAT) 1. I am satisfied with the service I get from this
store.
2. I feel at ease in this store.
3. I am satisfied with my decision to purchase products at this store.
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4. Results
In the previous chapter the research design and procedures, measures and plan of analysis were discussed. In the current chapter the results are presented. First, the descriptive statistics are examined. Subsequently, the analyses of the scales are presented and at last the tests of the hypotheses are explained.
4.1 Descriptive statistics
In total a number of 145 participants completed the survey. After a review of the data, six respondents were excluded from the sample, because they did not answer the questions in the survey. The sample contained 139 respondents with an average age of 29.97 years old (SD = 7.17), a minimum age of 23 and a maximum age of 65. A greater share of the participants was male comprising 69.8 percent of the sample and 29.5 percent were female. The majority (90.6 percent) of the sample was full-time employed, whereas 3.6 percent was part-time employed and 4.3 percent self-employed. Only 1.5 percent of the participants was a student. Table 2 shows a summary of the sample characteristics.
Gender % Age % Employment %
Male 69.8 < 25 14.4 Full-time 90.6
Female 29.5 25 – 35 72.7 Part-time 3.6
Other .7 36 – 45 7.9 Self-employed 4.3
> 45 5.0 Student 1.5
Mean Age (SD) 29.97 (7.17) Table 2: Descriptive statistics
4.2 Validity analysis
In order to assess the internal consistency of the measurement scales, reliability analyses were performed. First, the Cronbach’s alpha of each construct was examined. Every Cronbach’s alpha was well above the minimum value of 0.6, indicating good internal consistency (Bland and Altman,1997). Thereafter, the principle ‘’Cronbach’s alpha if item is deleted” is
inspected. The findings showed no or a very slight difference if an item was deleted for all scales. Considering the overall Cronbach’s alpha was high, not a single item was deleted. See table 3 for the results of the validity analysis.
Overall, the study used all items as defined in the methodology section of the paper.
After the validity analysis, the items were constructed into new variables by using the mean scores. These variables are utilized for the analyses to test the hypotheses
Table 3: Validity analysis
Construct Cronbach’s Alpha
Perceived Value of SRT (VA) .753 (Store) Loyalty – Behavioral (LB) .776 (Store) Loyalty – Attitudinal (LA) .813
Store Image (IM) .787
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4.3 Tests of hypotheses
Multiple mediation analysis was used to estimate and test the hypotheses deriving from the conceptual model. The conceptual model has two dependent variables, namely behavioral and attitudinal loyalty. For this reason, two mediation analyses were performed. The first analysis was performed with behavioral loyalty as dependent variable and the second analysis with attitudinal loyalty as dependent variable. The multiple mediation analysis was performed using PROCESS Macro by Hayes (model 4, 5000 bootstrap samples). The tested model is shown in figure 2.
4.3.1 Multiple mediation analysis model behavioral loyalty
a. Total effect model
b. Direct effect model
Figure 2: Mediation model 1
The total effect model of the analysis (R²= .45, p < 0.1) shows that perceived value of SRT has a positive effect on behavioral loyalty (β = .88, p = .00). The effect is substantial, so an increase in the perceived value of the SRT will result in more behavioral loyalty. By means of this analysis it can be concluded that hypothesis 1 is confirmed.
Perceived Value of Smart
Retail Technology Behavioral Loyalty
.88***
Perceived Value of Smart
Retail Technology Behavioral Loyalty
18 Furthermore, results of the analysis (R² = .47, p = .00) reveal that perceived value of SRT has a positive and significant effect on satisfaction (β = 0.88, p = .00) supporting hypothesis 3. Furthermore, the model that demonstrates the effect of perceived value of SRT on image (R²
= .57, p = .00) shows that the effect is significant and positive (β = .81, p = .00) supporting
hypothesis 6. By supporting these two hypotheses it indicates that higher perceived value of a smart retail technology leads to higher levels of satisfaction and a better store image.
The model for demonstrating the direct effects of the mediator satisfaction, image and the independent variable perceived value of SRT on behavioral loyalty is well fitted with a R² value of 0.73 and a p-value of .00, showing that 73 percent of the variance is explained by the model. The direct effect of satisfaction on behavioral loyalty is positive (β = .59, p = .00). Besides that, the direct effect of image on behavioral loyalty is also positive (β = .29, p =
.007). Lastly, the direct relation of perceived value of SRT on behavioral loyalty is not
significant ( p = .15). These results demonstrate that satisfaction and image have a positive influence on behavioral loyalty, supporting hypotheses 4 and 7. Furthermore, the analysis shows that the direct effect of the independent variable on the dependent variable is non-significant. According to the approach of Baron and Kenny (1986) this suggests that a full mediation occurs because the direct effect is substantially closer to zero than the total effect and it is non-significant when accounting for the mediators.
Nevertheless, the results of the indirect effects (95% confidence interval, 5000 bootstrap samples) show that the mediating effect of image is non-significant (LL = -.0061, UL=
.4558).
The mediating effect of satisfaction is positive and significant (β = .52, LL = .3001, UL =
.7589). In conclusion, there is no indirect effect (mediation) of perceived value of SRT
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4.3.2 Multiple mediation analysis model attitudinal loyalty
The second multiple mediation analysis was performed with attitudinal loyalty as the dependent variable. The results of the total effect model (R² = .053, p = .00) demonstrates that perceived value of SRT has a positive and significant effect on attitudinal loyalty
(β = .96, p = .00). This result shows a very strong positive relationship between the perceived value of a smart retail technology and attitudinal loyalty. As a result of this analysis,
hypothesis 2 is supported. The tested model is shown in figure 2.
a. Total effect model
b. Direct effect model
Figure 3: Mediation model 2
Perceived Value of Smart
Retail Technology Attitudinal Loyalty
.96***
Perceived Value of Smart Retail
Technology Attitudinal Loyalty
20 Furthermore, the mediation analysis tested the direct effects of perceived value of SRT, image and satisfaction on attitudinal loyalty. The direct effect of image on attitudinal loyalty is positive and significant (β = .21, p = .029). The direct effect of satisfaction on attitudinal loyalty is also positive and significant (β = .61, p = .00). The final direct effect of the perceived value of SRT on attitudinal loyalty is positive and significant as well (β = .25,
p = .003).
This model scored an R square value of .78, showing that 78 percent of the variance is explained by the model. This demonstrates that the predictor variables explain the dependent variable quite clearly. The results of this model indicate that a strong image and high
satisfaction both have a positive influence on attitudinal loyalty. By this result, hypotheses 5 and 8 are supported. The direct effect of perceived value of SRT on attitudinal is significant but the coefficient is considerably closer to zero in comparison to the total effect of perceived value of SRT on attitudinal loyalty, so according to Baron and Kenny (1986) a partial
mediation exists. Ultimately, the results of bootstrap confidence interval (5000 samples) demonstrate that the indirect effect of image is significant (LL = .0048, UL = .3735) with a β value of .17. The indirect effect of satisfaction was significant and positive as well (β = .54
LL = .2486, UL = .8390). These results suggest that the effect of the perceived value of SRT
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4.4 Additional results
The objective of the previous section was on finding support for the hypotheses, this section contains additional findings that are interesting and provide implications for both the literature and retailers. In this study, the primary objective of performing an additional analysis was to investigate if the use of smart retail technology is effective in increasing loyalty towards the retail store. In other words, did customer loyalty increase after using the smart retail
technology in comparison to before using the smart retail technology. In order to study this effect, a baseline measurement of loyalty towards the retails store (The Mediamarkt) was included at the start of the survey. On a 7-point Likert scale, participants could answer how loyal they were at that moment towards The Mediamarkt. The mean of this baseline
measurement was calculated in SPSS and the value is 5.36.
In order to compare this value of loyalty to the value of loyalty after using the smart retail technology a new variable is created. The new variable is created by merging the variable behavioral loyalty (LB) and the variable attitudinal loyalty (LA). This study is aware of the fact that the same question for calculating loyalty was not included after using the smart retail technology. This could be seen as a limitation, but this study thinks that if the same question was repeated after the use of smart retail technology, participants would remember the first question and subconsciously fill in the same level of loyalty. In order to increase the
reliability, this study chose to combine attitudinal and behavioral loyalty and use this variable as loyalty after using the smart retail technology. On the other hand, it is valid to state that this study could have used two baseline measurements, one regarding behavioral loyalty and one regarding attitudinal loyalty. This study did not choose for this option, because if the
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5. Discussion
In this chapter, the findings of this study will be discussed, as well as the theoretical and managerial implications. Furthermore, the limitations of this research will be presented and finally, recommendations for future research will be given.
5.1 Findings and theoretical implications
The purpose and main goal of this study was to investigate if smart retail technology could influence the loyalty of customers. More specifically, smart retail technology was
conceptualized as the perceived value obtained from using a smart retail technology and loyalty was conceptualized as behavioral and attitudinal loyalty. Moreover, it was expected that this relation was mediated by the image of the store and satisfaction.
First of all, this study predicted that a positive value perception of using a smart retail technology has a positive influence on behavioral loyalty and a positive influence on attitudinal loyalty as well. The results of the analyses confirm the positive relationship between perceived value of smart retail technology and behavioral loyalty. Besides that, the positive effect is very strong. This finding is in line with research on customer-perceived value in retail settings. Chang and Wildt (1994) found that customer-perceived value is a dominant contributor to purchase intentions. Moreover, the study of Yang and Peterson (2004) reports that if customers perceive the value to be high, their motivation for patronage increases significantly. It is important to note that customer value can be created by other aspects in a retail setting, but why does the use of a smart retail technology have such a profound effect on behavioral loyalty. This might be explained by the utilitarian value derived from using a smart retail technology. The use of a smart retail technology makes it easier for customers to acquire information or find a product in the store, which in turn leads to an increase in the efficiency of their shopping experience. The feeling of accomplishment of the shopping trip in terms of convenience and / or savings contributes to a higher utilitarian value. Customers that experienced this feeling at a retail store, are more likely to visit this store again, because they will recall their accomplishment. (Jones et. al,2006). For this reason, Jones et. al (2006) state that if customers experience utilitarian value in their shopping experience the likelihood of repatronage will increase.
23 Moreover, hedonic value is associated with emotions such as pleasure, enjoyment, fun and surprise. Customers that interact with smart retail technology could experience these emotions. High hedonic value implies that customers have experienced these positive consumption related emotions. Hirschman and Holbrook (1982) found that customers who experience these emotions will develop a powerful form of commitment to the store. This finding could be a plausible explanation for a stronger effect on attitudinal loyalty.
Surprisingly, the findings of Jones et. al (2006) showed that the influence of hedonic value was not significantly higher than the influence of utilitarian value on loyalty.
A possible explanation could be that the perceived value of smart retail technology not only consists of utilitarian and hedonic value. Symbolic value could also be a part of smart retail technologies, symbolic value can be defined as positive consumption meanings that are attached to the self and / or others (Rintamaki et al, 2007). It is very plausible that consumers could feel a sense of innovativeness or tech-savviness when they use smart retail
technologies, which in turn leads to higher levels of symbolic value. Subsequently, these higher levels of symbolic value could have an effect on loyalty, but this is not examined in this study and is beyond the scope of this research.
Aside from the effects on loyalty, this study also revealed that the perceived value of smart retail technology has a positive influence on satisfaction and subsequently, satisfaction positively affects behavioral and attitudinal loyalty. First of all, the positive relation between smart retail technology and satisfaction is a new insight in regard to smart retail technologies. Pantano and Naccaratto (2010) already proposed that new technologies could strengthen customer satisfaction via an enhanced shopping experience. One of the primary drivers of smart retail technology is enhancing the shopping experience for the customers. Thus, this study confirms the suggestion and contributes to this research. Numerous studies in the field of marketing and consumer behavior already explored the relation between satisfaction and loyalty. Besides that, a great part of these studies made a distinction between behavioral and attitudinal loyalty as well. It is clear that the literature agreed upon the fact that satisfaction is a significant direct antecedent of attitudinal loyalty (e.g. Bodet,2008; Bloemer and De
Ruyter,1997). So, the expectation was that this study confirms this relationship as well. On the other hand, findings on the relation with behavioral loyalty are not conclusive and the debate is still going if satisfaction has a relation with behavioral loyalty (e.g. Harris and Goode,2004) or that there is no significant relation (e.g. Bodet,2008). This study extends the literature because this research confirms a positive relation between satisfaction and
behavioral loyalty.
24 As well as the effect of smart retail technology on store image the relation of store image on behavioral and attitudinal loyalty is also confirmed. As for the relation of satisfaction to loyalty, the relation of store image was expected to be confirmed because various studies already determined this relation (e.g. Martenson, 2007; Konuk, 2018).
This study distinguished itself by examining the relation on a behavioral and attitudinal component. A significant difference of the effect of store image between behavioral and attitudinal was not found. Although, a significant difference between the effect of satisfaction and store image on loyalty was found. The relation between satisfaction and loyalty is
stronger than the relation of store image and loyalty. This finding is a potential explanation for the findings of the mediating effects in the model. The results showed that the relation between perceived value of smart retail technology and behavioral loyalty was fully mediated by satisfaction, but not by store image. However, the relation between perceived value of smart retail technology and attitudinal loyalty is partially mediated by both satisfaction and store image. These findings show that store image has no indirect effect on behavioral loyalty. This could be explained by the suggestion that behavioral loyalty is related to utilitarian value and unlike satisfaction, utilitarian value is less related to store image. Moreover, previous findings showed that the effect of satisfaction is considerably stronger on behavioral loyalty than the effect of store image.
Finally, the additional results show that the use of smart retail technology generates higher levels of customer loyalty in comparison to an experience without a smart retail technology. This finding in combination with the main findings of the study adds a contribution to the marketing literature by establishing a positive effect of smart retail technology on customer loyalty and on satisfaction and store image. In the next section, practical implications will be elaborated.
5.2 Managerial implications
This research adds value to the field of smart retail technology and is one of the first studies that looks further than the adoption of smart retail technology. The findings of this study are relevant for retailers, because it provides evidence that smart retail technologies are an effective tool for increasing customer loyalty, customer satisfaction and generating a favorable store image. These findings are especially relevant present-day, as an increasing number of retail stores are facing competition from online stores. Retailers need to explore new options in order to stay competitive. Online shopping has an advantage in terms of convenience but lacks in experience. This study confirms that smart retail technologies are a valuable option for retailers to stay competitive, as these technologies can increase
convenience and / or create a superior experience.
25 Research on customer loyalty states that attitudinal loyalty is a stronger form of loyalty and studies propose that retailers should direct their focus onto attitudinal loyalty (Bloemer and Ruyter, 1988). Interestingly, Pantano and Viassone (2014) found that retailers concentrate on the utilitarian advantages of smart retail technologies and tend to overlook the hedonic benefits. The study of Willems et al. (2017) confirmed this finding. The authors analyzed the type of smart retail technologies at 176 retailers and found that 45 percent of the technologies provided hedonic value and 65 percent utilitarian value, whereas 70 percent was cost and/or time-saving technology.
Based on the existing literature and suggestions made in this study, retailers should explore the recreational benefits of smart retail technologies as well and focus on technologies that provide hedonic value in order to develop a strong form of loyalty.
Nevertheless, it is important that retailers explore which type of smart retail technology is suitable with their shopping experience and the needs of the customer. In some retailing contexts, recreational-focused technologies are a perfect match but, in another context, it could result in a discrepancy between the needs of the customer and expected experience. To illustrate, grocery stores are a perfect example of a utilitarian retail context. In most cases, customers want to complete their purchase in an efficient manner and are not looking for distractions. The introduction of a recreational-focused technology could lead to a mismatch, and consequently result in negative reactions from your customers. Meaning, not every type of technology is suitable for a particular retail store and managers should be aware of this. To conclude, smart retail technologies are able to generate valuable benefits for retailers, but it is crucial that retail managers start with an examination of the needs of their customers and the corresponding shopping experience. After this examination, retail managers are able to choose an appropriate retail technology.
5.3 Limitations and Future Research
This study identified various meaningful implications. However, it is important to
acknowledge that this research comes with several limitations. First and foremost, data was collected by means of an online questionnaire, in which participants were asked to picture themselves into an imaginary situation. The essential part of this scenario was interaction with a retail robot at an electronics store. Participants may have had trouble visualizing this
situation and this could result in a different response in comparison to participants that had no trouble doing so. Furthermore, as the application of smart technologies in retail stores is in an emergent phase, there is a high probability that the average consumer had little to none
26 The sample of this study is acquired by means of a convenience sampling method, which implies that the respondents are accumulated via the network of the author. The main disadvantage resulting from the method used in this study is that the average age is 30 years old. Besides that, there is a limited presence of variance in the age of the respondents. This could lead to some constraints, especially in this study. The reason being, older people are less tech-savvy than younger consumers and this could lead to the possibility that older consumers do not understand the use of smart retail technology. Therefore, the responses may not display the behaviour of older people accurately, which might affect the generalizability of the sample. This paper recommends that future research should focus on older age
categories in order to establish a better representation of behaviour of the whole population. As mentioned earlier, this study used a retail robot as an example of smart retail technology. Pantano and Viassone’s (2014) classification shows that smart retail technologies are divided into three different categories. Each category consists of several different smart retail
technologies. This demonstrates that the retail robot is one of many other smart retail
technologies. In order to get a better understanding of the effects of smart retail technologies, more types of technologies should be studied but this was beyond the scope of this research. Subsequently, this study recommends future research to focus on other types of smart retail technologies and ideally, starting with smart retail technologies belonging to the first and second category of the classification of Pantano and Viassone (2014).
At last, this paper suggested that perceived value of using smart retail technology consists of a utilitarian component and a hedonic component. This suggestion is based on existing
literature that shows that customer value consists of both these components (Jones et
al.,2016). Although, this study did not divide perceived value into the two separate values, it is considered that this could be a very legitimate proposition. Therefore, this study
27
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Appendices
Appendix A
Stimuli that was used in this study to create a scenario, where the participant could imagine themselves have interaction with a retail robot.
Picture to help the participants think about the mediamarkt.
