Augmented Reality Shopping and Its Consequences:
The Relevance of the Retail Salesperson
An assessment of the influence of augmented reality shopping solutions on the importance of the salesperson considering the role of importance of privacy
Augmented Reality Shopping and Its Consequences:
The Relevance of the Retail Salesperson
An assessment of the influence of augmented reality shopping solutions on the importance of the salesperson considering the role of importance of privacy
Author’s name: M. te Flierhaar Author’s address: Saffierstraat 196
9743LN, Groningen Phone number: +31613077454
E-mail: m.te.flierhaar@student.rug.nl Student number: S3541606
Qualification: Master Thesis
Department: Department of Marketing
Faculty of Economics and Business Department address: Nettelbosje 2
ABSTRACT
PREFACE
New technologies, such as AR, have always fascinated me. Especially the potency of these technologies reshaping and affecting the conventional marketing strategies and operations has motivated me to conjure up a research concept including such a phenomenon. Additionally, I am grateful for the fact that a design including overarching facets from different expertises and research areas was made possible.
I enjoyed the challenge of writing my master’s thesis during the four months it took. In particular, it was exciting to test my writing skills and to realize that the process resembled a learning curve. At times, I was surprised by the amount of cognitive resources it required to come up with strong rationales and subsequently transcribe these in order for them to be understandable.
Without a single doubt, my thesis could have never been completed without the guidance of my supervisor, Dr. A.E. Vomberg. Via this way, I would like to express my gratitude and wish him the best of luck and a lot of inspiration for the coming years being active as a supervisor and professor at the University of Groningen.
Throughout the process of composing the thesis and conducting the research, I found myself to be supported by my family and friends. If they had not been there for me, it would have definitely taken its toll on the quality of the thesis.
TABLE OF CONTENTS
1 | INTRODUCTION 6
2 | LITERATURE REVIEW 10
2.1 | Changes in consumers’ shopping processes 10
2.2 | Augmented reality in retailing 11
2.3 | The salesperson pressured by the informed customer 12
2.4 | Role of privacy 13
3 | HYPOTHESES 15
3.1 | Development of conceptual model 15
3.2 | Hypotheses development 16
4 | METHODOLOGY 21
4.1 | Design and sample 21
4.2 | Procedure 21
4.3 | Measures 22
4.4 | Analysis 24
5 | RESULTS 25
5.1 | Assumptions and scales 25
1 | INTRODUCTION
In 2019 the retailing context seems to be shaped by endless desires and wishes, customization, self-service, humanizing digital, and, for some, store closures. At the end of 2018, 20 percent of all retail sales was e-commerce, and the bulk of growth seems to be coming from online (Deloitte, 2018). As we further progress into the third decade of the 2000s, experts expect advanced technologies to be a critical part of both the in-store and online shopping processes, one of which is augmented reality (CBRE, 2018).
Augmented reality, AR, refers to integrating elements generated by computers into a user’s real-world context using imagery-manipulation. Visuals of virtual content are synchronized or aligned with a real-world context (Carmigiani et al., 2011). This form of technology is widely used by retailers to assist consumers in their shopping processes, both in-store as well as online. Over the last approximately five years, several brands have introduced mobile AR shopping applications (IKEA, Tesco, Lacoste, etc.) in order to enhance their mobile marketing efforts. The technology is developed in various forms: mobile applications, head-mounted displays (e.g. Google Glass), contact lenses, and devices.
Particularly the furniture industry seems to benefit from the development of AR mobile applications. IKEA, Houzz, Wayfair, and Lowe’s Vision are all examples of tools for personalization of customer needs. This personalization of customer needs, in the context of furniture shopping, is through empowering a consumer’s decision making by the ability to visualize products such as a sofa, bed or chair within their personal environment. This visualization from an in-home perspective enables the customer to optimally assess fit of a product within his/her desired context.
Despite many benefits of AR for retailers in creating brand awareness, favorability, and consideration, multichannel retailers will have to consider potential risks of implementing AR in their sales channels. One of which refers to the consequences AR may have on the relevance of the in-store salesperson. Through the use of AR in a shopping process, a customer may become less dependent on a salesperson’s knowledge and provision of information.
shopping solutions (Schuster & Danes, 1986). The renewed, current way in which consumers purchase products and services is by way of re-intermediation of the roles that manufacturers, retail salespersons, and intermediaries play (Coltman et al., 2001; Kracht and Wang, 2010). This devaluation of the in-store salesperson may be strengthened by a multichannel retailer’s decision to implement AR in their sales channels. To exemplify, in a furniture shopping context, it would disregard a salesperson’s knowledge since the customer assesses fit and desired quality his/herself because of the ability to visualize the product in a chosen personalized setting. (Pantano et al., 2017).
However, a consumer’s susceptibility to privacy concerns, as with most of the AR oriented research, is likely to play a significant role in the usage of AR and its relationship with the importance of a salesperson (Hubert et al., 2017; Rauschnabel et al., 2018). Since a consumer’s importance of privacy pose a large impact on the adoption of AR, usage of AR, and valuation of AR, it is of great interest to the notion of this research to investigate the role it plays within a multichannel setting. In particular in the setting of furniture shopping, consumers may be reluctant to fully engage in the AR app since it requires relatively personal input as information.
To add to the direction Scholz & Duffy (2018) headed with their study, that is, a focus on in-home use of AR, while also preserving to contribute to the academic field, this study is aimed at assessing the effects of AR within a multichannel environment. This multichannel environment is characterized by combining the environment of in-home usage of AR and the in-store assessment of a salesperson and fitting these two settings into one research design. In particular, within the research field of multichannel shopping, there has yet to be investigated what the role of the salesperson denotes if AR is taken into consideration.
Building on the existing literature on AR shopping, multichannel management, privacy concerns, and the role and consumer’s perception of the salesperson, a research is developed. The scope of this study is limited to investigating the effects of AR mobile shopping solutions within a context of furniture shopping. More specific, this area of retailing is characterized by implementation of AR in a “passive”-sense. This passivity refers to virtual try-on systems instead of for example test-driving applications in which the consumer is actively participating (Baum & Spann, 2014). Implications of this research would therefore be broadly applicable to industries such as fashion, eyewear or DIY.
This research aims to obtain insight into consequences of AR mobile shopping solutions for the importance of the salesperson whilst taking the role of privacy into account by raising the following questions:
(1) In what way and to what extent do AR mobile shopping solutions influence the importance of the salesperson? (2) Does the importance of privacy play a mediating role and to what extent does it play a role in the relationship between AR shopping solutions and the importance of the salesperson? (3) In what way and to what extent does the importance of privacy influence the importance of the salesperson?
relationships, consumer behavior (Javornik, 2016), decision-making process (Pantano et al., 2017), and customer engagement (Jin et al., 2015).
This research contributes in several ways. First, it adds to our understanding of the effects of AR mobile shopping applications on the importance of a salesperson from a consumer’s perspective. Second, it further explains the strength of the relationship of AR shopping solutions and the importance of the salesperson and thereby denotes the role of importance of privacy. Therefore, the research contributes to the multichannel (with emphasis on AR) literature by providing empirical insights linking the relationships between AR with the consumer’s perceived importance of a salesperson and importance of privacy in a multichannel setting.
Managerial implications of this study are marked by equipping managers with information on the extent to which implementation of AR mobile shopping solutions within a multichannel environment influences the importance of the salesperson. Additionally, this research provides information on the role of importance of privacy in a relationship between AR mobile shopping solutions and the importance of a salesperson.
Particularly, the role of privacy is assessed within a framework of AR shopping solutions, characterized by their in-home use, and the perceived importance of the person, in a retailing setting. This multifaceted approach is of even greater relevance to managers operating in a multichannel environment, by which they are empowered with a tailored source of information. Therefore, managers are further leveraged in their decision-making by the insights as a result of this study. In terms of timing, because of the limited timeframe in which research has been able to evolve, managers are eager to be informed by new developments within the field.
2 | LITERATURE REVIEW 2.1 | Changes in consumers’ shopping processes
Consumers go online looking for product information when faced with the opportunity of purchase. Since consumers rapidly adopted various devices accessing this information, it is important to understand how consumers perceive information relevant to their shopping process (Mosteller et al., 2014). Additionally, consumers adopt decision-making strategies suitable to cope with seemingly endless choices and large amounts of information (Hall et al., 2017). This development of decision-making strategies is mostly due to the fact that consumer purchasing process becomes laborious and frustrating under current conditions of large amounts of information (Hölscher & Strube, 2000).
The retail landscape is rapidly changing but consumers’ needs still drive purchase decisions. However, retailers seem to implement newer technologies, business models and big data/predictive analytics, suggesting that the process is on a tipping point into an unknown realm (Grewal et al., 2017). Retailers are constantly developing new technologies to make shopping more exciting for their customers (Renko & Druzijanic, 2014). The innovation has to respond to both consumers’ preferences as well as retailers’ needs and expectations though (Pantano & Viassone, 2014). Usage of the new technology influences the consumer’s shopping experience (Verhoef et al., 2009). These developments in new shopping technologies push retailers to identify new business models in response to changing market conditions and technology (Sorescu et al., 2011).
richness in mobile communications embodying arrays of digital phenomena among which AR is positioned (Persaud & Azhar, 2012).
2.2 | Augmented reality in retailing
Ever since the second decade into the 2000s, AR seems to have taken up a place in many of retail managers’ minds (Javornik, 2016). Augmented reality (AR) systems integrate virtual information into a user’s physical environment so that the information is perceived as existing in the environment (Schmalstieg & Höllerer, 2017). Marketing and advertising denote the largest application opportunity for AR according to Gervautz & Schmalstieg (2012).
AR systems are either “active” or “passive”. This distinction is characterized by the extent to which the consumer actively participates in the application. For example, we distinguish test-driving applications in which the consumer is actively participating from passive applications such as a tool to fit eyeglasses (Baum & Spann, 2014).
AR is beneficial to both retailers and consumers in that it allows consumers to view themselves actually wearing diverse virtual products without physically trying them on in a store (Verhagen et al., 2014). In a context of online shopping, AR enriches a consumer’s shopping experience by displaying product visualizations on images of consumers’ physical features (Ma & Choi, 2007). With regard to online shopping, the interaction and visualization aspects of augmented reality greatly enhances a consumer’s information gathering (Ariely, 2000). AR also provides the user with enriched product information gained from a physical store as well as online store (Poushneh & Vasquez-Parraga, 2017).
virtual try-on system would substitute the physical try-on by meeting their preferences within their own augmented reality (Pantano et al. 2017).
The additional product information by visualization supports consumers in their product decision making process (Adhani et al., 2014). This, in turn, leads to an increase in usefulness of AR in shopping experiences and purchasing decisions to consumers (Noort et al., 2012). Particularly in fashion we witness the usage of AR to assist consumers in their product orientation for glasses or make-up. Oh et al. (2018) note that AR enables consumers to make decisions with more certainty.
Particularly in furniture retailing, AR technologies are implemented to reduce return costs and bring down return rates (Dacko, 2017). Here, AR is used to allow customers to measure the dimensions of a real-life room from the smartphone-camera’s perspective and render an accurate picture of the furniture in relation to the rest of the environment (Baier et al., 2015). Since then, multiple developers have launched apps to visualize these products in a personal environment, aiding customers prior to making their real purchase (Tabusca, 2014).
2.3 | The salesperson pressured by the informed customer
2.4 | Role of privacy
Research has shown that people react negatively to technologies that collect too much information about them (Debatin et al., 2009). Collier (1995) defines privacy concerns as “ they
are about the perceived threat to our individual privacy owing to the staggering and increasing power of information processing technology to collect vast amounts of information about us… outside our knowledge, let alone our control.” . Privacy risks create a psychological risk barrier that involves feelings of uncertainty and vulnerability. Concerns about privacy threats circumvent the development of trust in the technology and results in a perceived risk of privacy loss (Connolly & Bannister, 2007). For example, technologies that do not collect any personal data (e.g., a traditional calculator) are not likely to be associated with privacy risks (Herz & Rauschnabel, 2019).
Users who place a high value on the privacy of their personal information may experience a diminished sense of control over that information (Stone et al., 1983). With consumer data collection increasing in the retail landscape, there is a growing concern for data security and consumer privacy (Bhatnagar & Ghose, 2004). Eastlick et al. (2006) have shown that technology adoption is negatively influenced by privacy concerns. Consumers find some retail technologies too invasive to one’s privacy, ultimately leading to reactance undermining their benefits (White 2004).
Privacy concerns are not only a key antecedent to technology adoption, they also are to shopping behavior and intentions (Rose et al., 2012). Thakur & Srivastava (2013) have observed that privacy and security concerns negatively influence the adoption of online shopping technologies. On the other hand, if consumers are significantly influenced by the benefits obtained from the technologies using their personal information, their privacy concerns are likely to be mitigated (Inman & Nikolova, 2017).
sensitive to the fact that AR is a platform that can create and share information with other devices or mobile contexts (Olsson et al., 2013).
3 | HYPOTHESES 3.1 | Development of conceptual model
Figure 1 contains the conceptual model developed to research the hypothesized relationships for this study. The model visualizes a potential relationship between AR online shopping solutions and the importance of the salesperson, mediated by the importance of privacy. It is hypothesized that AR online shopping solutions negatively influence the importance of the salesperson.
AR online shopping solutions are defined as mobile applications enabling customers to render a picture of a product within their real-life environment, aiding a consumer in his/her purchase decision-making process. Schwartz (2011) connected effects of virtual try-ons and fitting measures with purchase intention, and thus, it is suitable to adapt AR online shopping solutions to the purpose of examining its effects on the consumer’s buying process.
To fit the purpose of this study, the impact of AR online shopping solutions will be researched using an experimental survey, wherein AR online shopping solutions are operationalized by exposing such an application to the participants.
The importance of a salesperson to a consumer is defined by multiple factors, such as relationship with a salesperson, recommendations given by a salesperson, and information provided by the salesperson. (Rippé et al., 2017; Haas & Kenning, 2014; Munshi & Hanji, 2014). Additionally, relating to the salesperson’s capabilities and characteristics of importance to a consumer, the following are denoted; trustworthiness, patient assistance, product competence, friendly relationship, and enthusiastic solutions (Hawes, Rao & Baker, 1993).
Operationalization of these factors and aspects representing the salesperson’s importance to a consumer, takes place through the use of two widely acclaimed and adopted scales. The used scales and measurement to capture the importance of a salesperson to a consumer are contained in chapter 4 of this report.
Importance of privacy is composed of multiple aspects, such as valuation of personal information (Smith, Milberg & Burke, 1996), perceived preservation of personal information (Dinev & Hart, 2006), and concern about privacy risks (Bhatnagar & Ghose, 2004).
Its influence is assessed using multiple scales to measure a consumer’s self-reported importance of privacy. Further details on the scales and measurement of this variable are included in chapter 4 of this report.
To visualize the hypotheses, the conceptual model is included below (figure 1).
Figure 1 - Conceptual Model
3.2 | Hypotheses development
AR online shopping solutions and the importance of the salesperson
qualities of the salesperson might not weigh up to the recently developed AR shopping solutions that further empower the customer with information.
In the context of this research, a furniture retailing setting, AR is used to enable customers to render a picture of the furniture within the measured dimensions of the real-life room from a consumer’s smartphone-perspective. Such AR mobile shopping applications aid consumers in their purchase decision-making process. In several aspects, the consumer’s perceived importance of a salesperson may decrease due to the AR online shopping solutions.
First of all, through the use of AR online shopping solutions the consumer is less dependent on the information a salesperson would have facilitated if the consumer lacked the information. In turn, the consumer becomes less reliant on provision of information by a salesperson, which is one of the primary salesperson’s roles. Pantano & Servidio (2012) pointed out that AR is the remedy to a loss of product information and inability to handle or assess products, functioning as a bypass of this information loss. Additionally, Adhani et al., 2014 have shown that the additional product information obtained through the use of AR online shopping solutions support consumers in their product decision making process. Moreover, Oh et al. (2017) have shown that consumers obtain more certainty in their decision-making process through the use of AR shopping experiences.
Second, Hall et al. (2017) state that consumers adopt decision-making strategies suitable to cope with the endless choices and large amounts of information. To prevent the frustration of information-seeking (Hölscher & Strube, 2000), one might replace consulting a salesperson in their shopping process by using the newly developed AR online shopping solutions.
Fourth, Poushneh & Vasquez-Parraga (2017) state that AR is a powerful tool providing the user with enriched product information gained from both physical stores as well as online stores. Subsequently, the mere presence of a salesperson may become redundant to a customer, shifting his/her focus solely to an online or in-home shopping environment.
To concretely exemplify the stated decrease in necessity of information previously provided solely by a salesperson in an offline setting: A consumer willing to buy a pair of glasses, having to cross a hurdle of measuring fit, would be less likely to visit a retailer to orientate or seek advice from a salesperson if s/he can assess fit using AR online shopping solutions. Extending this notion to a broader perspective, an individual is less in need of information normally supplied by the salesperson within an offline setting. Subsequently, a customer relies less on interaction and recommendation by a salesperson, resulting in a potential devaluation of the salesperson’s importance and decrease in buyer-seller interactions (Rippé et al., 2017). Therefore, AR online shopping solutions have a negative effect on the importance of the salesperson. The following hypothesis serves to raise the main problem this research is concerned about:
H1: “Passive” AR mobile shopping solutions have a negative effect on the importance of a salesperson.
The mediating role of the importance of privacy
AR online shopping solutions may vary in impact on the importance of the salesperson according to the extent to which a user/consumer is attached to his/her privacy. AR technologies request extensive information to be shared by the users in order to work effectively. The ability to control this flow of personal information is essential when users interact with such technologies (Ackerman & Mainwaring, 2005).
Additionally, protection of personal information becomes increasingly important, in particular since AR technologies need visual input such as photos and/or videos, contact information, and locations in order to personalize the output (Poushneh, 2018). Since people differ in their valuation of privacy, the impact of AR online shopping solutions decreases if the consumer’s importance of privacy is relatively high. To illustrate, a user of an AR furniture shopping application may feel as if the application requires too much sensible information resulting in lesser enjoyment, trustworthiness (Olsson et al., 2013) or shopping behavior (Rose et al., 2012). This rationale leads to the following hypothesis:
H2: The effect of “passive” AR online shopping solutions on the importance of a salesperson is mediated by the importance of privacy.
Importance of privacy and the importance of the salesperson
Subsequently, the customer is less likely to devalue the importance of a salesperson since a salesperson does not digitally process visual, personal customer information with the usage of a technological device and subsequently stores it. The privacy issue is more critical in the mobile context because a variety of personal information, such as exact time, location, and preference relevant to a specific behavior, is readily available the minute customers agree to provide such information via mobile apps (Wang et al., 2016).
One might argue that the salesperson should pose a greater threat on the privacy concerns of an individual since actual interaction through persons takes place. However, primarily features of location-awareness and the required input of environmental information personal to the user cause new privacy risks to consider to the customer ( Emmanouilidis et al., 2013). Comparing the threat a salesperson poses on personal information, participants in a study conducted by Olsson et al. (2013) were mainly concerned about “ what information about their activity will be saved and where, how public is the interaction with the service, and who can eventually access the content they have shared themselves.”. This illustrates the central difference to the information processing of a salesperson to the AR shopping solutions, which is the storage and vaguely indicated access.
the context where this information is unnecessary, therefore, the importance of privacy positively influences the importance of a salesperson.
H3: The importance of privacy positively influences the importance of a salesperson.
4 | METHODOLOGY 4.1 | Design and sample
The study was composed of an online survey in which approximately half (59 out of 130 by random assignment) of the participants were exposed to the augmented reality shopping solution in the form of an advertisement advocating the use of an AR-shopping-app. The other 71 participants were exposed to two product overviews extracted from the website of the same retailer, Lowe’s, advocating the use of the AR-shopping-app. The participants were drawn from a convenience sample (Saunders et al., 2009). Participants were recruited by direct messages over social media platforms. Table 1 below gives an overview of the descriptives of the sample.
Variable Value Sample Sample %
Age 18-20 15 11.54% 20-30 93 71.54% 30-40 8 6.15% 40-50 7 5.38% 50-60 4 3.08% 60-70 3 2.31% Mean age 26.95 Gender F 57 56.15% M 73 43.85%
Daily internet usage < 1 hour 4 3.08%
1-2 hours 33 25.38%
3-4 hours 44 33.85%
5-6 hours 29 22.31%
> 7 hours 20 15.38%
Bad experience with regard to online privacy Yes 46 35.38%
No 84 64.62%
Online purchases in last 3 months None 3 2.31%
1-3 51 39.23%
4-8 52 40.00%
8-15 16 12.31%
15 or more 8 6.15%
Highest degree High school 20 15.38%
Trade/Technical school (MBO) 18 13.85%
Bachelors Degree (HBO) 74 59.92%
Masters Degree (WO) 18 13.85%
Professional status Student 52 40.00%
Employed part-time 26 20.00%
Employed full-time 44 33.85%
Self-employed 6 4.62%
Retired 1 0.77%
Unable to work 1 0.77%
Table 1 - Sample descriptives
4.2 | Procedure
(Gillin, 2008). randomly assigned to either one of the conditions to isolate the measurements within either the AR-setting or the non-AR-setting. Approximately half of the participants were either exposed to an AR-app-advertisement created by American retailer Lowe’s, specialized in home improvement. This stimulus was a 30-second long video-advertisement (appendix 1) in which a family quickly demonstrates the use of the AR-app by Lowe’s. This video-advertisement was embedded in the questionnaire from YouTube, the online video-sharing platform. The advertisement advocates the company’s ‘View-in-your-space’-app which enables consumers to assess what a product will look like in their ‘own space’, e.g. in their own living room.
The other half of the participants were exposed to two mobile product overview-images directly derived from the same company’s online web store. This extraction took place by way of print-screens from the concerning website, Lowe’s online web store. Both of the stimuli were acquired from Lowe’s, an American company specialized in home improvement. The second stimulus, which was used to recreate an online shopping experience, was composed of two print-screens of product overviews (appendix 2) including pictures (detailed product pictures and general overview picture of the product) of a sofa and chair sold by Lowe’s. After the participants were exposed for approximately 30 seconds to either one of the mentioned stimuli, they were required to fill in a questionnaire containing a total of 57 questions. These 57 questions were mostly (about ⅔) Likert-scaled in terms of measurement. It took participants 9 minutes on average (excluding outliers based on IQR-method (Tukey, 1991)). Several questions were matrix-styled, resulting in a total amount of 18 grouped questions.
4.3 | Measures
Variable & items Question (Likert-scale) α α if item dropped Importance of salesperson (DV)
[1/2]
In shopping decisions, how important are the following aspects concerning a salesperson?
0.74 Items (Rippé et al., 2017; Haas
& Kenning, 2014; Munshi & Hanji, 2014)
Relationship with salesperson 0.69
Recommendations of a salesperson 0.73
Information given by a salesperson 0.70
General importance of salesperson 0.68
Importance of salesperson (DV) [2/2]
How important are the following salesperson's attributes in a general setting? 0.74 Items (Hawes, Rao & Baker,
1993) Trustworthiness (sincere, dependable) Patient assistance (s/he lets me take my own time to decide, does not pressure me) 0.72 0.74 Product competence (shows alternatives, ability to explain) 0.72 Friendly relationship (s/he cares for me, recognizes me after sale) 0.70 Enthusiastic solutions (confident, eager to sell) 0.72 Importance of privacy (IV) [1/2] Please indicate the extent to which you agree or disagree with each statement. 0.78 Items (Smith, Milberg & Burke,
1996)
It usually bothers me when companies ask me for personal information. 0.77 Companies should devote more time and effort to preventing unauthorized access
to personal information.
0.75 When companies ask me for personal information, I sometimes think twice before
providing it.
0.75 Companies should have better procedures to correct errors in personal
information.
0.75 Companies should take more steps to make sure that the personal information in
their files is accurate.
0.76 Companies should never sell personal information in their databases to other
companies.
0.75 Companies should not use personal information for any purpose unless it has
been authorized by the individuals who provided the information.
0.74 Computer databases that contain personal information should be protected from
unauthorized access - no matter how much it costs.
0.74 Importance of privacy (IV) [2/2] Indicate the extent to which you agree or disagree with the statement. 0.74 Items (Dinev & Hart, 2006) I feel I have enough privacy when I use websites. 0.68
I am comfortable with the amount of privacy I have. 0.68 I think my online privacy is preserved when I use websites. 0.74 I do not feel comfortable with the type of information websites request from me. 0.69 I feel that websites gather higher personal information about me. 0.71 The information I provide to websites is very sensitive to me. 0.69 Uncertainty avoidance Indicate to what extent you agree with the following statements. 0.83 Items: Derived from CVSCALE,
a five-dimensional scale of individual cultural values (Yoo, Donthu & Lenartowicz, 2011)
It is important to have instructions spelled out in detail so that I always know what I’m expected to do.
0.80 It is important to closely follow instructions and procedures. 0.77 Rules and regulations are important because they inform me of what is expected
of me.
0.79 Standardized work procedures are helpful. 0.82 Instructions for operations are important. 0.79 Consumer innovativeness Indicate to what extent the following statements are true of you. 0.72 Items (Jahanmir & Cavadas,
2018)
I believe people learn to be innovators. 0.72 If I had the chance, I would like to innovate. 0.70
I have trust in my new ideas. 0.64
I can convince people to accept my new ideas. 0.65
I consider myself to be an innovator. 0.62
I am convinced that, following a structured methodology, I can come up with new ideas.
Besides the measures for the variables stated above, several demographics were asked for in the questionnaire. Additionally, the following material was asked for: (1) Whether people have ever had a bad experience with regard to their online privacy (yes/no). (2) Daily internet usage (anchors: less than an hour - 7 hours or more), (3) online purchases done within the last 3 months (anchors: none - 15 or more), (4) gender (female, male, other), (5) age, (6) highest degree or level of school completed (anchors: no schooling - doctorate’s degree), and (7) professional status (unable to work, retired, out of work, self-employed, part-time, full-time or student).
4.4 | Analysis
The hypotheses will be tested by way of an ordinary least squares linear regression analysis (OLS) (Stigler, 1981). Several control variables are included within the model, such as demographics and consumer characteristics such as consumer innovativeness and uncertainty avoidance.
Variable Levels Type
(non-)AR-setting 2 IV (Main)
Importance of privacy 1 IV (Main)
Bad privacy experience 2 Control (binary)
Daily internet usage 5 Control (nominal)
Uncertainty avoidance 1 Control (Likert)
Consumer innovativeness 1 Control (Likert)
Age inf. Control (continuous)
Education 4 Control (nominal)
Profession 6 Control (nominal)
Table 3 - Variables composing linear regression model
Based on the results of the Cronbach analysis, the variables composed of multiple items (Likert-matrices) are summarized on their mean-value. “It has become common practice to assume that Likert-type categories constitute interval-level measurement” (Jamieson, 2004),
5 | RESULTS 5.1 | Assumptions and scales
The hypotheses were tested using regression analysis (Stigler, 1981). For this analysis, required assumptions were met after the removal of 3 (out of 130) responses. These 3 observations negatively affected the normality assumption (Razali & Wah, 2011). The tests which were used to assess whether the assumptions for the regression analysis were met and their outcomes are summarized in the following table (4).
Test Assuming Value/statistic
Shapiro-Wilk test (source) The null-hypothesis of this test is that the population is normally distributed. p = 0.8766 Residual-test (source) (mean) The mean of the residuals should be exactly or very close to zero. μ = 7.261247e-18 Breusch Pagan Test for
Heteroskedasticity
The H0 of this test is that the variance of the errors from a regression analysis is dependent on the values of the independent variables.
p = 0.482
Runs-Test (source) The H0 suggests that the sequence was produced in a random manner. p = 0.423 Durbin-Watson Test (source) Test for autocorrelation in the residuals from a statistical regression analysis. DW = 1.9187
p = 0.3114 Correlation Test (source) The predicting variables and residuals are uncorrelated. corr(X,Y) < 0.06 Variance Inflation Factor
(VIF-)scores
If the VIF of a variable is high, it means the information in that variable is already explained by other variables present in the given model.
<1.436795 for all variables. Table 4 - Assumptions for linear regression and results
Interpreting the results stated in table 4 above, it is evident that the regression analysis can be safely conducted without violating any of the requirements (Allen, 1939). Besides the interpretation of the statistics resulting from the stated tests, several plots were visually interpreted to assess whether the assumptions to continue the analyses were met. These visual representations were: (1) Q-Q-normality plots (in addition to the Shapiro-Wilk test), (2) residuals (e) vs. fitted plot, and (3) scale-location plot to check for homoscedasticity. As mentioned earlier, 3 data points were removed because of their critical impact on the normality of the population data. The p-value for the Shapiro-Wilk test before the removal was p = 0.04353*, after the removal, this became p = 0.8766. Thus, since the null-hypothesis is unrejectable, it is certain that the population is normally distributed even regardless of the central limit theorem (CLT) (Mitic, 1996).
corresponding scales were taken into account for this research. These variables, characterized by their arithmetic functionality, are included in table (5) below, in which descriptives of these variables are summarized.
Variable μ σ x̃ min max
Importance of salesperson 3.43 0.48 3.44 1.89 4.56 Importance of privacy 3.73 0.48 3.79 2.36 4.93 Uncertainty avoidance 3.67 0.64 3.60 1.80 5.00 Consumer innovativeness 3.62 0.59 3.67 2.33 5.00
Age 26.95 9.95 24 18 70
Table 5 - Arithmetic variables & descriptives
5.2 | Main effects
OLS output with interaction DV: Importance of Salesperson
Variables Estimates Std. Error t p
(Intercept) 3.233 0.432 7.490 <0.001
AR-setting 0.135 0.089 1.520 0.131
No bad experience (privacy) 0.046 0.089 0.519 0.605
Daily internet usage
1-2 h 0.019 0.253 0.076 0.940 3-4 h -0.064 0.247 -0.260 0.796 5-6 h 0.038 0.258 0.149 0.882 7 h or more -0.078 0.274 -0.285 0.776 Uncertainty avoidance 0.070 0.066 1.057 0.293 Consumer innovativeness 0.054 0.076 0.706 0.481 Gender Female -0.024 0.094 -0.258 0.797 Age -0.008 0.005 -1.429 0.156 Education Trade/Technical School(MBO) -0.127 0.169 -0.751 0.454 Bachelors Degree(HBO) -0.221 0.123 -1.794 <0.10 Masters Degree(WO) -0.170 0.166 -1.029 0.306 Profession Employed Part-Time 0.097 0.132 0.738 0.462 Employed Full-Time 0.171 0.116 1.473 0.144 Self-Employed 0.194 0.219 0.886 0.378 Retired 0.691 0.533 1.298 0.197 Unable to Work -0.347 0.465 -0.745 0.458 Observations 127 R2 / adjusted R2 : 0.118 / -0.048
Table 6 - Results of regression analysis (model 1: Main effects only)
Initially, it is noticeable that the overall model fit is not significantly good ( F(18, 108) = 0.7279; p = 0.7759) (Mooi & Sarstedt, 2011). Variance in the data is poorly explained by this model (R 2
= 0.1082) compared to other models in similar research (Pantano et al., 2017; Poushneh, 2018). This model includes the hypothesized main effect (H1) of “ AR-setting” on the dependent variable “Importance of Salesperson”. H1 assumes that the AR-shopping-solutions negatively
influence the importance of a salesperson. The predictor-variable “ AR-setting” is insignificant (p
= 0.122) (table 6). Therefore, the AR-shopping-solutions do not negatively influence the
importance of a salesperson as formulated in H1 (β = 0.139; p = 0.122) (Baron & Kenny, 1986).
5.2 | Presence of mediation
OLS output DV: Importance of Privacy
Variables Estimates std. Error t p
(Intercept) 3.677 0.049 75.529 <0.001
AR-setting 0.047 0.073 0.640 0.523
Observations 127
R2 / adjusted R2 0.003 / -0.005
Table 7 - Results of regression analysis for test of presence of mediation
Despite the insignificance of the main-effect and in order to determine whether the hypothesized mediation-effect takes place through the importance of privacy, we interpret the results of the regression analysis included in table 7. Here, the variable “ AR-setting” seems insignificant in its impact on the mediating variable “ Importance of Privacy” (β = 0.139; p = 0.523). Mediation takes place only if the predictor variable influences the mediating variable, otherwise the variable is just a third that may or may not be associated with the importance of a salesperson (Shrout & Bolger, 2002). Therefore, the importance of privacy does not seem to mediate the effect of AR-shopping-solutions on the importance of a salesperson. Nonetheless, paragraph 5.3 contains an analysis of the full model as it would have been a part of the mediation analysis.
5.3 | Mediating effect
OLS output with intercept DV: Importance of Salesperson
Variables Estimates std. Error t p
(Intercept) 3.017 0.524 5.575 <0.001
AR-setting 0.139 0.089 1.557 0.122
1-2 h -0.017 0.258 -0.065 0.949 3-4 h -0.090 0.250 -0.361 0.719 5-6 h 0.008 0.262 0.032 0.975 7 h or more -0.124 0.282 -0.439 0.661 Uncertainty avoidance 0.057 0.069 0.831 0.408 Consumer innovativeness 0.054 0.077 0.700 0.486 Gender Female -0.025 0.094 -0.272 0.786 Age -0.009 0.006 -1.592 0.114 Education Trade/Technical School(MBO) -0.129 0.169 -0.764 0.447 Bachelors Degree(HBO) -0.231 0.124 -1.860 0.066 Masters Degree(WO) -0.180 0.167 -1.083 0.281 Profession Employed Part-Time 0.105 0.133 0.795 0.428 Employed Full-Time 0.186 0.118 1.577 0.118 Self-Employed 0.215 0.221 0.973 0.333 Retired 0.764 0.543 1.408 0.162 Unable to Work -0.335 0.466 -0.718 0.474 Observations 127 R2 / adjusted R2 : 0.113 / -0.043
Table 8 - Results of regression analysis (model 2: Mediator included)
Hypothesis p-value β
H1 AR-shopping → Importance of salesperson Not supported 0.122 0.139
H2 AR-shopping → Importance of privacy Not supported 0.523 0.047
H3 Importance of privacy → Importance of salesperson Not supported 0.466 0.087
Table 9 - Hypotheses, confirmations, and results
6 | DISCUSSION
The main question addressed in this research is whether or not and to what extent AR online shopping solutions decrease the importance of a salesperson from a consumer’s perspective. Additional to this question, the importance of privacy is involved in order to determine whether and to what extent it mediates the relationship between AR online shopping solutions and the importance of a salesperson. Finally, the question about whether the importance of privacy positively influences the importance of a salesperson was raised.
According to these rationales, three hypotheses were developed. The first hypothesis that was developed, cogitated that “passive” AR mobile shopping solutions decrease the importance of a salesperson. Secondly, H2 hypothesized that the importance of privacy mediates the strength relationship between the “passive” AR mobile shopping solutions and the importance of a salesperson. At last, hypothesis 3 was defined. Hypothesis 3 suggested that the importance of privacy would increase the importance of a salesperson.
The first maintained hypothesis was rejected. “Passive” AR mobile shopping solutions do not negatively influence the importance of the salesperson. First of all, in contrast to what was hypothesized, the importance of the salesperson was greater when people were exposed to the “passive” AR mobile shopping solution. This finding may seem rather unlikely in the light of prior research. Therefore, it adds to the broadness and depth of research within the field of new shopping technologies. Evidently, AR shopping solutions do not seem to affect the importance of a salesperson to a consumer.
salespeople stay vital to persuade the multichannel consumer. Ahearne and Rapp (2010) state that technology might replace general knowledge structures, but they do not believe that these technologies are able to duplicate salesperson experiences or that these are capable of adapting to the customer style as needed.
Second, the importance of privacy does not act as mediator in the relationship of AR shopping solutions and the importance of the salesperson. Despite the fact that influence of AR shopping solutions on the importance of the salesperson is non-existent, the importance of privacy does not play a role as mediator, which could have been the case. Should this hypothesized relationship been evident, the role of privacy would still be nihil.
Support for the nonfinding is to be found in some conducted research. Xu et al. (2011) have uncovered the privacy paradox. The privacy paradox is the explanation for the constant tension between personalization and privacy, in which some consumers pick personalization over privacy. This paradox is key in the understanding of the insignificance of the importance of privacy within the composed research design. If the personalization facilitated by AR weighs heavier than the importance of privacy, despite its isolated measurement, then the importance of the role of privacy becomes inferior. Accordingly to what was speculated within the research agenda of Javornik (2016), privacy concerns with AR do indeed represent less of an issue, since the AR content is delivered based on pull and not push communication which therefore is perceived as less intrusive. As this research has shown, support to this speculation was found in the nonfinding of the irrelevance of the importance of privacy.
6.1 | Academic contributions
The research that is conducted, adds value to the research field of marketing and AR. Following the research agenda developed by Javornik (2016) to further investigate the subject of AR within a context of marketing issues, this research further explores the rather new field of AR in an academic setting. The fact that this study provides empirical findings derived from quantitative results characterizes its relevance. The field of research including AR is quite new since the technology itself has not been around for many years. Therefore, this study is quite essential to the academic field that attempts to further investigate the influences of the new technology in a domain of marketing and retailing.
Specifically, the outcomes of this research, symbolized by their contradiction, may challenge existing views on the impact of AR. Whereas prior research mostly focused on constructs such as the adoption of AR technology, the importance of a salesperson excluding the role of new shopping solutions, and the importance of privacy within a context of sole online shopping, this newly developed research combines and integrates multiple rationales and contexts. The unexpected findings this research yields, challenge the sustainability of findings from conventional studies. This challenge becomes more present within a context where newly developed shopping solutions are being adopted like the furniture retailing context.
To conclude, besides the combination and integration of the constructs, none of the hypothesized effects have ever been specifically researched. Thus, the findings of this research add to the understanding of the influence of AR on the importance of a salesperson. Additionally, the research contributes to the understanding of the importance of privacy and what type and strength of influence it has within a context including AR. Finally, it clarifies whether and to what extent the importance of a salesperson depends on the importance of privacy.
6.2 | Managerial contributions
whether the importance of privacy mediates the relationship between the importance of a salesperson and implementation of AR mobile shopping solutions. These results and insights generally increase the managers’ understandings of AR and its consequences by which they become more informed to make decisions concerning this subject in a constantly evolving technological market. To exemplify implications, some scenarios are given in the following paragraphs.
First of all, the role of the salesperson does not become irrelevant even if newly developed shopping technologies, such as AR, are implemented, which is in line with the assumption of Ahearne and Rapp. To managers’ decision making, this is crucial, it implies that, according to the findings of this research, AR mobile shopping solutions while retaining the function of the salesperson can function properly conjointly.
Second, should managers operate retailing within an environment where their customers tend to value their privacy, then they are now assured that no additional adjustments have to be taken to compensate a loss in the importance of the salesperson. Since the importance of privacy does not influence the importance of a salesperson, it is unnecessary to undertake any action to compensate for a loss of importance with regard to the salesperson.
Third, the importance of a salesperson within a retailing setting is not subject to any of the factors included in the design to control for a potential intervention of effects. These factors include gender, age, education, and profession. This finding could make a difference in managers’ decision making in terms of recruiting salespeople within settings where these factors fluctuate. The basic assumption, derived from the results of this research, is that the manager does not have to adjust his/her strategies concerning the salespeople based on changes in gender, age, education, or profession.
6.3 | Limitations
research including additional variables and interacting effects. At the same time, these constraints have an upside in terms of possibilities for future researchers.
A second limitation of this research was the choice of the measurement instrument to capture the effect of AR. This limitation is two-fold: On the one hand, respondents were exposed to an advertisement about an AR shopping solution instead of actually experiencing the AR shopping solution itself. On the other hand, the stimulus representing the AR shopping solution was rather universal in terms of the fact that it applies to a scenario both men and women and most generations in terms of age can refer to. The choice for a universal stimulus may have been limiting since it did not contain a strong appeal to the user’s privacy. Other research within the field of AR and marketing (Poushneh, 2018; Scholz & Duffy, 2018; Pantano et al., 2017) is conducted mostly using AR shopping applications that require visual input of the users’ faces. The AR shopping application demonstrated in this research required visual input but did not require personal information in terms of the physicality of the user him/herself.
Third, it could be that the importance of privacy itself does not directly relate to the importance of the salesperson, but that this effect is captured within different variables not controlled for. This potential susceptibility could have been controlled for if the accurate variables had been included in the design phase of the methodology.
A fourth limitation is that this study was conducted among participants all of a Dutch nationality. This will take its toll on the generalizability of the results and implications of this research. Had there been more variety in participants’ nationalities, then the results would have been more generalizable and its implications would have been more applicable across different cultures. Dutch participants are characterized by traits of Western culture, however, the results and implications are likely to be different if multiple cultures were included in the sample of the study.
6.4 | Future research
The focus of attention for this research was the importance of the salesperson within the context of AR and the importance of privacy. If considering the area yet to be discovered within this rapidly growing (technological) field of research, this research contributed a relatively small but crucial part.
First of all, as Dacko (2017) suggested, more research is to be done on how users of AR shopping solutions actually assess usability and added value of these shopping methods. In the scope of this research, it is necessary to conduct more research on the potential consequences of implementing AR shopping solutions for a retailer in a multichannel setting. This research has not uncovered all the potential consequences of AR shopping solutions and solely investigated what the influence is on the perceived importance of a salesperson.
Second, what determinants in AR shopping solutions influence the importance of a salesperson, positively or negatively, is an interesting inquiry to be investigated in future research. What specific aspects of AR shopping solutions do or do not play a role in their impact on the importance of a salesperson? The current research only investigated the effect of exposure to an AR shopping solution and whether and to what extent it determines the importance of a salesperson. However, the research has not taken into account what factors of AR are more important than others in the hypothesized relationship.
Third, deriving from Pantano et al.’s (2017) notion of comparing research outcomes in the field of AR future research, this current research could be implemented across different sectors. Where the current research was conducted within a setting, due to the stimuli that were used, of retail-furniture-shopping, this research could be conducted within a fashion- or cosmetics sector likewise.
7 | CONCLUSION
By analyzing the perceived importance of a salesperson of a consumer, this research has displayed how AR shopping solutions and the importance of privacy shape the role of a salesperson. First of all, the research provides evidence to state that AR shopping solutions do not influence the importance of the salesperson. Second, the relationship between AR shopping solutions and the importance of the salesperson is not mediated by the importance of privacy in any way. At last, this research has shown that if privacy is important to a consumer, it does not sequentially imply that the role of a salesperson becomes more important.
There is value in the non-findings. Specifically, since there has not been prior research on the importance of the salesperson including the role of new shopping solutions and the importance of privacy, it adds a unique contribution to the academic field. Concurrently, the research contains managerial relevance by its facilitation of new information on the possible consequences of implementing AR on the importance of the salesperson. Besides, it is better understood what role the importance of privacy plays and that it has virtually no effect on the importance of the salesperson.
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