This document summarizes a research study that compares factors influencing consumers' intentions to purchase accessible luxury goods online versus in stores. It hypothesizes that online consumers pay more attention to merchandise variety, price, and time/effort savings while having less risk aversion. In-store consumers prioritize experiential aspects like interacting with salespeople. The study aims to provide retailers insights to improve the shopping experience across channels by analyzing correlations between these factors. A quantitative analysis of accessible luxury goods in electronics and fashion tested the hypotheses. The results confirmed prior research and provided operational guidelines for retailers around tools like social media, personalization, and differentiation.

1. Accessible luxury goods: Consumers’ in-store and
online purchase intentions
ANTONELLA ANGELINI* ELISA SERGI**
* Professore associato di Economia e gestione delle imprese presso il Dipartimento
di Economia e Management - Università degli Studi di Pisa. e-mail:
antonella.angelini@unipi.it
** Dottore magistrale in Marketing e Ricerche di Mercato presso l’Università degli
Studi di Pisa. e-mail: ​elizee712@gmail.com
While the article is the result of a joint effort of the Authors, the individual
contributions are as follows: Antonella Angelini wrote Abstract and paragraphs
1-2-3-7. Elisa Sergi wrote paragraphs 4-5-6.
1

2. Accessible luxury goods: Consumers’ in-store and
online purchase intentions
Abstract
Purpose of the paper: Compare factors able to influence customer purchase intentions
for accessible luxury goods in shops and online and propose suggestions to retailers aimed at
improving the customer shopping experience.
Methodology: A quantitative analysis has been conducted which tested some hypotheses
of research, starting from the above factors
Research findings: The results of research of purchasing behavior of luxury products in
literature have also been confirmed with regard to accessible luxury goods. Online customers
pay more attention to the merchandise, the price and the savings in time and effort. The
in-store customers instead give more importance to experiential and recreational aspects and
show a greater aversion to risk. The analysis of correlations between factors has allowed us
to advance some suggestions aimed at improving the experience between customers and
retailers.
Research limitations/practical implications: The data obtained allowed the identification
of some significant correlations that were considered as offering some operational guidelines
to enhance the customer value experience. A greater use of social communication tools,
differentiation, and personalized solutions could help increase loyalty and brand reputation.
The analysis can be further developed considering separately a few sub-categories of
accessible luxury goods (such as electronic ones and personal ones) to take into account the
specificities of demand.
Originality of the paper: The paper focuses on accessible luxury products ​for which
scientific contributions are still very limited because mostly related to luxury products in the
strict sense of the word​. The analysis of correlations between variables has provided
important insights into the operational plan.
Key words: accessible luxury goods, e-commerce, online shopping, Internet dilemma
1. Introduction
The spread and the success of the Internet not only represents one of the most
relevant technological conquests of recent years, but has completely transformed the
marketing strategies of modern companies and the entire chain of value. Nowadays,
the digital world and the new communication technologies allow companies to
create new forms of virtual ubiquity (Berquier and Gherold, 2000), creating the
conditions to move from the market-place to the market-space (Tesser, 2002) and
creating the opportunity to cancel physical distances and facilitating access to
products and services on a global scale. Regardless of how transactions occur, online
or in-store, what is certain is that the buying decision on the part of consumers is

3. intended to be determined by a blend between the physical elements and the virtual
ones: the line of demarcation between the two spaces will tend increasingly to
intersect and overlap. These considerations today may be also advanced in the
luxury sector, a sector that has been rather slow to embrace the digital revolution in
the context of their own distributive choices (Kluge and Fassnacht, 2015; Chevalier
and Gutsatz, 2012) because of its traditional requirements of rarity and exclusivity
(Okonkwo, 2007). Despite the impetuous revolution of e-commerce, for the luxury
brands online sale is not universally regarded as a viable solution, in addition to the
traditional ones, mainly due to the difficulty of replicating the emotional and
physical features of these goods in a digital environment. Moreover, only few years
ago electronic commerce was considered a “hazard” toward the exclusive image of
luxury brands, by placing the same companies in front of the so-called "Internet
dilemma" (Kapferer and Bastien, 2012) defined as the apparent mismatch between a
luxury brand’s concept of exclusiveness and mass medium Internet. In luxury,
maintaining scarcity represents a critical success factor (Kapfere and Florence, 2016;
Brun and Castelli, 2013) and, for this reason, Internet has exposed such companies
to new challenges. In spite of this, recently the luxury sector has showed a great
dynamicity and today the possibility to shop on line is the second most important
feature of a luxury brand web site (Roland Berger, 2013). This is also because more
and more consumers have accepted Internet purchasing; the luxury brands have
quickened their adoption of Internet and begun to use sophisticated information
technologies with particular attention to how luxury brand homepages should be
designed to evoke perceptions of luxury (Kluge ​et al., 2013), improve their online
presence and promote brand awareness (Okonkwo, 2009). A recent study shows that
the online accessibility of luxury goods does not affect consumer-perceived scarcity
and, hence, does not dilute brand desirability (Kluge and Fassnacht, 2015). This
“no-dilution” finding applies to both high - and low-involvement goods and persists
irrespective of whether or not retail prices are explicitly displayed. The increasing
use of internet for luxury products therefore seems to be an unstoppable
phenomenon. However it is necessary that companies of luxury brands have a deep
understanding of the factors which push the consumers of those goods to buy online
and in-store in order also to define the best channel strategy, exploiting synergies
that can be generated between these different distribution solutions. The idea of
research arises from the fact that despite many studies having analyzed the purchase
of luxury goods in-store, as well as e-commerce in general, studies are more limited
which have investigated jointly the reasons relating to the purchase of luxury goods
on both channels. After all, the research into online luxury purchasing is still at a
rudimentary stage (Liu ​et al., 2013) and there are many other areas of research still
to investigate. Our study fits into this line of research, taking into consideration the
factors which have a direct impact on the intention to purchase luxury products
online and offline, carrying out a comparison through a quantitative analysis. Our
attention focuses on two different categories of luxury goods: electronic goods

4. (smartphones, laptops, cameras and video cameras) and personal goods, such as
fashion products, perfumes and body decoration products. These luxury products
used to be still considered as a single category. ​Furthermore, this paper is based on
a specific definition of luxury that considers accessible luxury products. Customers
ascribe to these products functional, hedonistic, symbolic/expressive or financial
value (Yang, Mattila, 2015). The luxury products are also characterized by
excellence, brand aura and desirability, where the product's rarity and uniqueness
increase desirability but are not essential for the classification of a luxury product or
brand (Antoni et.al 2004). ​This is in line with what has been suggested by Wiedman
et al. (2009). They proposed an integrated tri-partite model of these key values
created by luxury, distinguishing functional, individual (luxury for self) and social
values (luxury for others). As a result, the motivation for purchasing luxury products
may also vary and the perceived utility and cost of a product are not the only
features that have been used to characterize a luxury product (Brun and Castelli,
2013). Based on these assumptions, accessible luxury products include relatively
low-priced versions of exclusive and expensive goods (Okonkwo, 2007; Thomas,
2007). In recent years the luxury market ​has undergone a profound change​, with a
conversion from extremely exclusive products to less expensive and non-rare ones.
Therefore, the effects of “luxury democratization” (Mattia G., 2010) require greater
attention by researchers and professionals. This is the reason why the study has
carried out a more in-depth analysis in this area. This paper proceeds as follows.
First, it describes factors able to have effects on intent to purchase online and offline
luxury products and tests some research hypotheses. Second, the methodology and
the main results obtained are illustrated. Third, managerial implications and final
consideration are discussed.
2. Conceptual background and Research hypotheses
The online distribution of luxury products allows retailer and customers to obtain
various benefits, but at the same time different concerns arise as described in
literature and resumed in the Table 1.
Tab. 1: Benefit and concerns of online distribution of luxury products
Benefits Concerns
Business view Additional sales Loss of desirability
Profitability Transparency
Control Costs of infrastructure
Client contact Channel conflicts
Customer view Convenience Lack of touch and feel
Product availability Lack of human factor
Intimacy Security concerns
Facilitates comparison Reduced feeling of exclusiveness

5. Source: adapted from Kluge, Fassnacht, 2015
Based on these considerations, past studies (Baker ​et al., 2002; Chiang and Li,
2010; Grewal ​et al., 1998a) investigated the main factors which influence the online
and offline purchase intentions. Liu et al. (2013) also recently investigated the
different motivational factors influencing online and in-store luxury shoppers. The
results show that online luxury shoppers are more sensitive to price, prefer the
online product availability and have a higher level of trust towards online customer
reviews. In-store shoppers who are more averse to online risks nd it very important
to see the product personally before purchasing and value shopping experience and
interactions.
This paper starts from the description of these factors, focusing the attention on
the most important ones for the purchasing of luxury goods, both using the
traditional and online channel (Liu et al., 2013). These factors are service quality,
merchandise quality, price and the shopping experience costs and benefits
(time/effort costs, perceived risk, and enjoyment). On the basis of these factors,
several research hypotheses have been defined which take into consideration the
findings of previous studies on consumer purchase behavior. The aim is to
understand the differences in motivational factors between online and in-store
accessible luxury shoppers and to analyze the existence of possible correlations that
could have important managerial implications.
Merchandise quality
This research defines merchandise quality as the overall opinion a customer has
on the number, the quality and the variety of the alternatives. Although many studies
consider the importance of this aspect both in the offline channel (Baker et al., 2002;
Berry, 1969; Lindquist, 1974; Reardon and Miller, 1995; Coskun, Kelly, Hunt,
1998) and in the online channel (Francis and White, 2004; Szymanski and Hise,
2000; Wolfinbarger and Gilly, 2003), the research of Donthu and Garcia finds that,
in general, online buyers are more variety seekers than the in-store shopper (Donthu
and Garcia,1999). Consumers seem to be motivated to buy online because of the
bigger variety in terms of sizes, colours and styles. From this consideration, we
define the first research hypothesis:
H1. Online accessible luxury consumers hold a more positive opinion about the
variety offered by the online context than in-store accessible luxury consumers.
Service quality
The quality of a service is not an absolute value, but the comparative opinion

6. customers express by comparing their expectation with the perception of what has
been offered to them.
A better service quality can lead to positive effects on profits and revenue,
especially for service-based companies focused on customer satisfaction (Anderson
and Mittal, 2000).
The measurement of the subjective aspects of customer service depends on the
compliance of the expected benefit with the perceived result. This in turn depends
on the customers’ expectations in terms of the service they might receive and the
service provider's ability and talent to provide said expected service. Successful
companies add benefits to their offer that not only satisfy the customers but also
surprise and ​delight​ them. Delighting customers is a question of exceeding their
expectations.
For the purposes of this research, the service quality is mainly referred to the
experiential dimension, which strongly affects the shopping activity. Tangible
aspects, such as knowledge and kindness of shop assistants, their ability to inspire
trust and a customized and caring assistance, seem to be important elements for
in-store luxury buyers (Pratibha and Bagozzi, 2002; Cervellon and Coudriet, 2013).
These customers might be reluctant to purchase something without the help of an
expert shop assistant, able to offer them useful advice; these kinds of customers, in
fact, tend to give great relevance to shop assistance and want to satisfy their
entertainment and social interaction needs, exactly the ones that cannot really be
satisfied in the online context. On the other hand, lots of users prefer online
shopping just to escape the face-to-face interaction with the shop assistant that they
consider oppressive and/or embarrassing. This feeling affects most of those
customers who had negative experiences with a shop assistant or those who prefer to
maintain their freedom to choose and purchase products by themselves.
H2. Online accessible luxury buyers give less relevance to the experiential
dimension than in-store accessible luxury buyers.
Monetary price
Monetary price is the customer’s perception on prices proposed by online and
offline retailers. Smith (Smith, 2002) states that the Web offers more possibilities to
compare prices and offers, in addition to a bigger choice of goods and services. In
fact, by now, many people assert that Internet shopping can be less expensive than
traditional in-store purchasing. Some customers point out they often have just the
illusion that the online price of the same article is lower; actually its cost is not that
much different from the one applied in the physical store. Still it remains curious to
notice how the majority of Internet users believes that everything you can buy from
the Web is actually cheaper (Windham and Orton, 2002). For the purposes of our
research we suppose that

7. H3. Online accessible luxury buyers hold a more positive opinion about finding
online items at good prices than in-store accessible luxury buyers.
Perceived risks
The perceived risk is the uncertainty perceived by customers in the purchase
decision. The sales channel they use has a strong influence on the perceived risk
level. In fact, when the physical contact between retailer and customer lacks, e.g. in
online transactions, the perceived risk of the common user is higher than the one
perceived during in-store shopping. There are three main types of perceived risk
(Pascucci, 2013):
- The uncertainty about possible malfunctioning of the purchased product or the
lack of correspondence between the product and the pre-purchase user’s
expectations;
- The uncertainty related to possible monetary losses, caused, for example, by a
missed delivery;
- The uncertainty they perceive in sharing sensitive information during the
transaction (e.g. the bank account, the shipping address, etc.).
In-store luxury buyers prefer to watch, feel, touch or smell the product with their
own hands, and are afraid to rely only on product photos and features seen on a
computer screen. They fear the online purchased product might not meet their
expectations (Donthu and Garcia,1999). Moreover, it becomes apparent that the
average online customer is innovative, impulsive and has a reduced aversion to risk
compared to the typical in-store buyer. Based on these considerations, we define the
fourth research hypothesis:
H4. Accessible luxury online buyers have a reduced aversion to risk if compared
with the typical in-store accessible​ luxury ​buyer.
Time/effort costs
One of the main reasons for the spread of online shopping seems to be time and
effort saving (Avery, 1996; Moon and Kim, 2001). With respect to traditional stores,
online shops are open 24-hours a day, 7 days a week. Customers do not search only
for products, but also services. Some retailers have an online customer service
available all day long, so clients can ask for information, assistance or products
support, and this is convenient especially after working hours. Buying online, people
do not have to worry about driving to town and searching for parking; in addition,
when they find their favourite products, it is easier to compare their prices from
multiple sources, directly at home.
The convenience and promptness potential will be obviously perceived by users
who are more familiar to online shopping. Human beings are methodical, they get
attached to daily routines and are well satisfied to stick to their own habits, as things

8. are going well. Online customers soon get used to the design of a website and the
way it works. This is a key aspect related to convenience and saving of time. In fact,
it is convenient to use a familiar website because it takes less time using it. Once a
website becomes familiar, a group of customers will become “faithful” to the
website itself (Windham and Orton, 2002). In other terms, the familiarity with a
website represents a switching cost. In general, a business can reduce customers’
perceived risk to increase switching costs against the competition for customer
retention in e-commerce (Yen, 2015). Based on these considerations, we define the
following research hypothesis:
H5. Online accessible luxury buyers hold a more positive opinion about the
possibility to save time and efforts thought online shopping with respect to in-store
accessible luxury buyers.
Enjoyment
Many people consider shopping a recreational activity, useful for distracting
themselves from the daily routine and enjoying their free-time. Similarly to Childers
work (Childers et al.​, 2001), this research assumes that this aspect is less important
for online purchasers.
Thus,
H6. Online accessible ​luxury buyers give less importance to the recreational
aspect of shopping activities than in-store accessible​ luxury​ buyers.
The previous hypotheses are resumed in Table 2.
Tab. 2: Online and in-store motivational factors
Online motivational factors
Product availability
Possibility of comparing stores and searching for low prices
Time and effort saving
In-store motivational factors
Experiential dimension and tangible aspects, such as knowledge and
courtesy of store assistants, their ability to inspire trust with customized
and caring assistance
Perception of risk and insecurity in online business transactions
Recreational aspect of shopping activities
Source: Authors

9.
3. Methodological approach
An online survey, built with Qualtrics platform, has been created and distributed
to achieve the objectives stated above and to validate the developed hypotheses. By
distributing the URL of the Qualtrics survey, we had the chance of recruiting
participants with different socio-demographic and educational profiles. Furthermore,
we recruited people using social network links and posts, newsgroups and online
forums.
The survey opens with the explanation of personal and/or electronic luxury
goods. In our study, these goods are defined as “products which are not considered a
necessity but which tend to make life more pleasant for the consumer”.
After having provided this definition, we identified luxury buyers among the
respondents. Many researchers hesitate in targeting this kind of buyer, mainly
because literature still has not a clear definition of luxury buyers. This can create
confusion as to how they can be distinguished from non-luxury consumers and
ultimately, how to identify them for empirical studies (Heine, 2010).
Similarly to Liu ​et al. (Liu ​et al.​, 2013), in our study we consider a personal
and/or electronic luxury buyer someone who has bought these kinds of goods once
over the last two years.
The following four multiple-choice questions investigated the respondents’
information-seeking patterns in order to identify the sources and devices utilized for
obtaining information on brands and products. After defining in-store shoppers as
those who have not made at least one online purchase of luxury products in the last
two years, twenty-one statements were ranked using the 7-point Likert scale. This
enabled participants to highlight what they consider important during their buying
process and provided the raw data for understanding what motivates online and
in-store consumers. Finally, the last section was designed to acquire demographic
information.
4. Measurement scales used in the study
To measure the importance customers give to quality of service, merchandise
quality, monetary price and costs/benefits of the shopping experience, we used
multi-item scales available from previous researches and adapted them to our
purpose (see Appendix).
The items related to merchandise quality and perceived risk are based on Donthu
and Garcia (1999) study; the ones regarding quality of service from Brady and
Cronin (2001) and Rohm and Swaminathan (2004) papers. The scale used to
measure items related to monetary price was adapted from Darden and Perreault

10. (1976). In the end, scales about non-monetary costs (time and effort costs) and
enjoyment were re-adapted from Broekhuizen study (2006).
All these items used a seven-point Likert scale, which ranked from strongly
disagree to strongly agree.
Quantitative data collected using this scale are used to verify our research
hypotheses.
5. Consistency test of the measurement scales
The coherence of the multi-item scales used in our study has been evaluated
using Cronbach Alpha, an index which reflects the consistency of a test by
describing the internal coherence of groups of item.
Cronbach Alpha can assume values between 0 and 1 and it is widely used in
surveys which describe human behaviours. High values of alpha stand for a coherent
behaviour of the survey’s participant about each item belonging to every studied
dimension. Researchers agree in using an alpha value greater or equal to 0. 70 as a
threshold to reach a satisfying level of consistency of the constructs used in the
survey. As Table 3 explains, sub-scales used in our survey show great reliability
scores. For each dimension taken into account, the value of alpha is greater than the
minimum threshold of consistency.
Tab. 3: Constructs’ consistency
Item Scale Cronbach's Alpha Numero di item
Merchandise quality 0,8723 3
Service quality 0,8605 5
Monetary price 0,8760 3
Perceived risk 0,8605 5
Time/effort costs 0,8716 3
Enjoyment 0,9128 2
Source: Authors’ analysis
6. Results
Among a total of 301 respondents, our research identifies 193 accessible luxury
buyers and 108 accessible non-luxury shoppers. The higher number of the first
probably stems from the fact that we have considered accessible luxury goods,
which are now part of our daily life. The sample of luxury shoppers consisted of 76
men and 117 women and with equal distribution between different age brackets.
53% of the participants had a Bachelor or a Master degree, 38% a high-school
diploma; the majority of the participants (31%) had an annual household income

11. ranging between 15,000 and 49,999 euro, while 50% of them earned more than
50,000 euro (Tab.4).
Tab. 4 - Demographic characteristics of the sample
of accessible luxury shoppers (n=193)
Age Frequency %
<19 19 10%
20-29 51 26%
30-39 38 20%
40-49 41 21%
>50 44 23%
Gender
Male 76 39%
Female 117 61%
Education
High-school diploma 74 38%
Bachelor Degree 58 30%
Master degree 44 23%
PhD 3 2%
Other 14 7%
Income
<15.000 37 19%
15-50.000 60 31%
50.000-79.999 43 22%
80.000-99.999 28 15%
>100.000 25 13%
Considering online luxury buyers those who have purchased these kind of goods
online at least once in the last 2 years, we finally identified 129 online buyers and 64
in-store buyers.
The results highlight the importance of the Web both in the information

12. collection phase and in the luxury goods purchasing. ​Among 129 luxury goods
consumers only 2% declare that they do not search for information before the
purchase of a product. Thus, the profile which results is a customer deeply involved
who prefers to search for information in-depth to reach a careful final decision,
especially as far as luxury product, although accessible luxury products. Most of the
accessible luxury shoppers use portals or websites (75%) to search for information.
54% of them visit the official website of the brand or its physical shop (46%), or
they ask relatives, friends and acquaintances (44%). From the collected data, it
becomes clear that 76% of the participants who search for information on portals or
websites use Comparison Shopping Engines (CSEs), websites which collect
different offers of a product displaying them in order of price. Regarding the devices
used by accessible luxury shopper to collect information and purchase a product it is
worth noting that, for both phases, the personal computer is still the preferred device
(97% of respondents use it to collect information, 67% to purchase a product), while
Smartphones and tablets are mainly used to search for information, as they can be
accessed everywhere at any time. With the purpose of revealing possible significant
differences related to the demographic data considered, we used Pearson’s
chi-squared (χ2) test. We found that there were not significant differences in gender,
age, income and education between internet and in-store buyers of accessible luxury
goods (Tab. 5).
Tab. 5: Pearson’s ​χ​2 test
Null hypothesis (H0) χ​2
χ​α
2
p-value Sig.
(p<0,05)
Gender There are no relevant differences
between online and offline buyers
0,76 3,84 0,381 N
Age There are no relevant differences
between online and offline buyers
7,54 9,49 0,09 N
Income There are no relevant differences
between online and offline buyers
1,51 9,49 0,825 N
Education There are no relevant differences
between online and offline buyers
7,45 9,49 0,11 N
Source: Authors’ analysis
The next step consists in testing the formulated hypotheses with a t-test for
independent samples. The results of the test, showed in Table 6, support the
hypotheses made in the previous paragraph.
Tab. 6 - Hypotheses test on the difference between the two means

13. Hypotheses Online buyers’mean
(μ1)
(n=129)
In-store
buyers’mean (μ2)
(n=64)
H0 p-value Sig.
(p<0,05)
H1. MQ 5,09 3,39 µ1 - µ2 ≤ 0 0,000 Y
H2. SQ 3,63 4,98 µ1 - µ2 ≥ 0 0,000 Y
H3. MP 5,43 3,63 µ1 - µ2 ≤ 0 0,000 Y
H4. PR 4,12 5,37 µ1 - µ2 ≥ 0 0,000 Y
H5. TE 5,33 3,30 µ1 - µ2 ≤ 0 0,000 Y
H6. ENJ 4,17 5,05 µ1 - µ2 ≥ 0 0,003 Y
Source: Authors’ analysis
Comparing the mean of the two samples, relevant differences arise for
merchandise quality, attention to prices and saving of time and efforts (H1, H3, H5):
for each of these factors, the online shoppers group has higher means than in-store
customers. Data support also hypotheses H2, H4, H6. In-store purchasers seem to be
more risk-averse, as they need to feel/touch the product before purchasing it and/or
afraid to meet with problems during the process of online purchase. Differently from
online shoppers, they give more importance to the experiential and recreational
aspect of shopping. ​Considering the results obtained, the typology of accessible
luxury goods appears to be quite similar to that of luxury goods in general with
regard to the characteristics of the purchase behavior described above.
In order to obtain managerial implications useful to companies and in order to
offer some suggestions to retailers for improving the consumer experience, we tested
the significance of the correlations between the factors influencing the choice of a
channel (Tab. 7).
Tab. 7: Correlations between factors which influence the channel choice
MQ MP PR TE ENJ SQ
MQ 1 0. 70* -0. 28** 0. 74* -0. 02 -0. 33*
MP 0,65* 1 -0. 26** 0. 71* 0. 09 -0. 39*
PR -0. 11 0.02 1 -0. 34* 0. 42* 0. 75*
TE 0. 57* 0. 63* -0. 15 1 -0. 05 -0.34*
ENJ 0. 06 0. 07 0. 34* 0. 09 1 0. 58*
SQ -0. 17 -0. 08 0. 72* -0. 12 0. 41* 1
Note:
a. ME=Merchandise Quality, MP=Monetary Price, PR=Perceived Risk, TE=Time and effort
cost, ENJ=Enjoyment, SQ=Service Quality
b. Correlations below the diagonal (in bold) refer to the context on-line, those above to the
context off-line.
c. *p<0. 01, **p<0. 05
Source: Authors’ analysis

14.
A positive correlation was found between merchandise quality and monetary
price (ρ​on​/ρ​off ​= 0. 65/0. 70). One simple implication for the retailer could be to offer
specific discounts or benefits in general based on the number of online orders/offline
purchases, for example by including free delivery when the order cost goes above a
fixed threshold or by offering some coupons to be used for future purchases. It may
also be useful to implement loyalty programs that consider not only the achievement
of expenditure thresholds, but also the channel used and the customer’s lifestyle in
the aim of increasing the link between the company and loyal customers. In order to
achieve this result, loyalty programs need to develop “loyalists”, customers who
receive high satisfaction, show high loyalty, and will stay and be supportive of the
company (Mcilroy A., Barnett S., 2000). Moreover, loyalty program effectiveness
seems to be achieved if there is an ongoing search for differentiation, reduced loss
(discounts) and extra gain (prizes) initiatives (Cedrola, Memmo, 2010). Time and
effort cost is correlated to merchandise quality (ρon/ρoff = 0. 57/0.74) and monetary
price (ρon/ρoff = 0. 63/0.71); these data show how important it is to allow customers
to find their desired products quickly and easily, and to make discounts and offers as
visible as possible. In an online context this comes with the necessity of creating and
maintaining a simple, functional and smartphone/table-friendly website. A recent
study indicate that for goal-directed consumers web site content and customization
play a more significant role in influencing their satisfaction and revisit intentions
than convenience. Inside the store interactive shopping windows could be introduced
to quickly show the availability and the position of a product and compare prices,
models and available sizes in real time. Our results show that pleasure related to the
shopping activity can be increased by leveraging on the experiential aspect (ρon/ρoff
= 0. 41/0. 58). Therefore, retailers have to invest in the quality of service, advising
or helping the customers in the shop. In this case there will be an advantage for
companies that have adopted effective systems of customer relationship
management (CRM), using also the social network solutions that have helped to
make easier the opportunities for interaction between companies and their
customers. Moreover, such interaction is not only between organizations and their
current and potential customers, but also between customers in peer-to-peer
interactions (Sashi, 2012), influencing others’ purchase decisions. Therefore, proper
use of the social instruments could promote the dissemination of information with
regard to the customers’ service experience, with an impact on engagement and
brand reputation. It’s possible use different solutions of social media, as social
networking (e.g., Facebook), professional networking (e.g., LinkedIn), video-sharing
(e.g., YouTube), picture-sharing (e.g., Flickr), social bookmarking (e.g., Delicious,
Digg), social knowledge-sharing (e.g., Wikipedia), microblogging (e.g., Twitter),
blogs (e.g., Blogger), and user forums (Tsimonis & Dimitriadis, 2014).

15. The optimal use of these tools must be carried out within an overall
communications strategy in order to coordinate the various initiatives and produce
synergic effects (Angelini A., et.al, 2017). Moreover, it could be useful to create or
improve the FAQs sections on the websites online chat services or Skype numbers to
guarantee an easy, customized and always-available access to the brand services for
their clients; in this way retailers can also increase risk disposition (ρon/ρoff = 0.
72/0. 75) and reduce time/effort costs of the shopping activity in-store (ρoff = -0.
34). In this regard, retailers could launch in-store virtual dressing rooms and smart
shelves. The first are special fitting rooms which use technologies able to scan the
human body and its facial features and virtually show how different products will fit,
while the latter allow the display of product information (e.g. sizes, models and
colours) when a customer moves or pulls up one of the exposed products.
7. Discussion and conclusion
In the literature studies that have considered online luxury behavior are still
limited as are also those which have considered jointly buyers on line and off line of
these products. In particular, while the contributions referring to the category of
accessible luxury goods are still scarce, there has recently been considerable growth
in the demand of, using both online and off-line channels. The digital revolution is
now a reality and the companies selling luxury cannot escape from considering the
innovative solutions that are currently available for improving the techniques
involved in distribution and at the same time brand awareness. We believe that
future research could focus on luxury goods belonging to the premium or
super-premium categories, since, in the present study, were considered the category
of accessible luxury. There may, however, be clearly evident differences in terms of
consumer behavior which could involve different solutions as regards distribution
techniques. For a company it is, in fact, appropriate to develop an omni-channel
strategy that allows customers to communicate and buy products at the moment and
in the way in which they consider to be most convenient and appropriate. Every
company should seek to develop suitable channel strategies based on the needs of its
customers by directing resources in such a way as to allow the best possible
integrated, coherent and satisfactory experience of buying. This probably requires
not considering luxury goods in a comprehensive manner but identifying
sub-categories with specific characteristics and specificity. For example, divide
luxury goods into personal and electronic ones, the first being tied more to an
emotional aspect, and the second to a functional one (Brun and Castelli, 2013).
Consequently, this may lead to the emergence of differences in attitude. Finally, an
area to investigate further with regard to the Internet dilemma, considering both the

16. business point of view and that of customers is the question, is it possible to
reconcile visibility and exclusivity? This study is therefore a contribution in this
direction but the themes to be developed are still many and of particular relevance.
References
ANGELINI A., FERRETTI P., FERRANTE G., GRAZIANI P., (2017), “Social Media
Development Paths in Banks”, ​Journal of Promotion Management​, DOI
10.1080/10496491.2017.1294868
ANTONI F., BULGELMAN R.A., MEZA P., (2004), “LVMH in 2004: the challenges of
strategic integration”, ​Harvard Business School case​.
BAKER J., PARASURAMAN A., GREWAL D., VOSS G.B. (2002), “The Influence of
Multiple Store Environment Cues on Perceived Merchandise Value and Patronage
Intentions”, ​Journal of Marketing​, vol. 66, n. 2, pp. 120-141
BERQUIER-GHEROLD V. (2000), ​De linfomédiarie au ‘portal communautaire’:
restructuration desmarchés et protection de la vie privée, La protection de la vie
privée dans la société d’information​, Paris Presses Universitaires de France, Paris.
BERRY L.L. (1969), “The Components of Department Store Image: A Theoretical and
Empirical Analysis”, ​Journal of Retailing​, vol. 45, n. 1, pp. 3-20
BRADY M.K., CRONIN J. (2001), “Some new thoughts on conceptualizing perceived
service quality: a hierarchical approach”, ​Journal of Marketing​, vol. 65, n. 3, pp.
34-49.
BROEKHUIZEN T.L.J., (2006), ​Understanding Channel Purchase Intentions: Measuring
Online and Offline Shopping Value Perceptions​,​ ​Labyrinth Publications.
BRUN A., CASTELLI C. (2013), “The nature of luxury: a consumer perspective”,
International, ​Journal of Retail & Distribution Management​, vol. 41, n. 11/12, pp.
823-847.
CEROLA E., MEMMO S., (2010), “Loyalty marketing and loyalty cards: a study of the
Italian market”, ​International Journal of Retail&Distribution Management​, Vol.38,
n.3. pp.205-225
CERVELLON M.C., COUDRIET R., (2013) “Brand social power in luxury retail:
Manifestations of brand dominance over clients in the store”, ​International Journal of
Retail & Distribution Management​, vol. 41, n. 11/12, pp.869-884.
CHEVALIER, M., GUTSATZ, M., (2012), ​Luxury Retail Management,​ John Wiley & Sons.
CHIANG W.K., Li Z., (2010) “An analytic hierarchy process approach to assessing
consumers' distribution channel preference”, ​International Journal of Retail &
Distribution Management​, vol. 38, n. 2, pp.78-96.
CHILDERS T.L., CARR C.L., PECK J., CARSON S. (2001), “Hedonic and utilitarian
motivations for online retail shopping behavior”, ​Journal of Retailing​, vol. 77, n. 4,
pp. 511-35.
COSKUN S.A., KELLY J.P., HUNT H.K. (1998), “Improving Retail Performance by
Contrasting Management- and Customer-Perceived Store Images: A Diagnostic Tool
for Corrective Action”,​ Journal of Business Research​, Vol.43, n.1, pp. 27-38.
DARDEN W., PERREAULT W. Jr (1976), “Identifying interurban shoppers: multiproduct
purchase patterns and segmentation profiles”, ​Journal of Marketing Research​, vol. 13

17. n. 1, pp. 51-60.
DONTHU N., GARCIA A., “The Internet Shopper” (1999), ​Journal of Advertising Research​,
vol. 39, n. 3, pp. 52-58.
FRANCIS J.E., WHITE L., (2004), “Value Across Fulfillment-Product Categories of Internet
Shopping”, ​Managing Service Quality​, vol. 14, n. 2/3, pp. 226-234.
GREWAL DHRUV, KENT B. MONROE, R. KRISHNAN, (1998a), “The Effects of Price-
Comparison Advertising on Buyers' Perceptions of Acquisition Value, Transaction
Value, and Behavioral Intentions”, ​Journal of Marketing​, vol. 62, n. 2, pp. 46-59.
LIU X.,BURNS ALVIN C., HOU Y., (2003), “Comparing online and in-store shopping
behavior towards luxury goods”, ​International Journal of Retail & Distribution
Management​, vol. 41, n. 11/12, pp. 885-900.
MATTIA G. (2010), “I segmenti generazionali e le percezioni nei confronti degli accessible
luxury goods: una Ricerca empirica su quattro fasce di età”, ​Mercati e Cometitività​,
n.3, pp.51-73.
HEINE K. (2010), “Identification and Motivation of Partecipants for Luxury Consumer
Surveys through Viral Partecipant Acquisition”, ​The Electronic Journal of Business
Research Methods​, vol. 8, n. 2, pp. 132-145.
KAPFERER J.N.,BASTIEN V. (2012), ​The Luxury Strategy: Break the Rules of Marketing to
Build Luxury Brands​, KoganPage, London, Philadelphai, New Delhi.
KAPFERER J.N, FLORENCE P.V. (2016), “Beyond rarity: the paths of luxury desire. How
luxury brands grow yet remain desirable”, ​Journal of Product & Brand Management​,
vol. 25. n. 2 pp. 120 - 133
KLUGE P.N., FASSNACHT M. (2015), “Selling luxury goods online: effects of online
accessibility and price display”, ​International Journal of Retail & Distribution
Management​, vol.43, n. 10/11, pp.1065-1082.
KLUGE P.N., KONIGSFELD J.A., FASSNACHT M., MITSCHKE F. (2013), “Luxury web
atmospherics: an examination of homepage design”, ​International Journal of Retail &
Distribution Management​, vol. 41, n. 11/12, pp. 901-916.
LINDQUIST J.D. (1974), “Meaning of Image: A Survey of Empirical and Hypothetical
Evidence”, ​Journal of Retailing​, vol. 50, n.4, pp. 29-39.
LIU X, BURNS A.C., HOU Y. (2013), “Comparing online and in-store shopping behavior
towards luxury goods”, ​International Journal of Retail & Distribution Management​,
vol.41, n.11/12, pp.885-900.
MCILROY A., BARNETT S. (2000), “Building customer relationships: do discount cards
work?”, ​Managing Service Quality: An Internationa Journal​, Vol. 10, n.6, pp.
347-355.
MOON J.W., KIM Y.G. (2001), “Extending the TAM for a World-Wide-Web context”,
Information & Management​, vol. 38, n. 4, pp. 217-230.
OKONKWO U. (2009) “Sustaining the Luxury brand on the Internet”, ​Journal of Brand
Management​, vol. 16, n. 5/6, pp. 302-310.
OKONKWO, U. (2007), “Luxury Fashion Branding”, Palgrave Macmillan, New York, NY.
PASCUCCI F. (2013), ​Strategie di Marketing online per il vantaggio competitivo aziendale​,
Società Editrice Esculapio
PRATIBBA D.A., BAGOZZI R.P. (2002), “An Attitudinal Model of Technology-Based
Self-Service: Moderating Effects of Consumer Traits and Situational Factors”,
Journal of the Academy of Marketing Science​, vol. 30, n. 3, pp. 184-201.
REARDON, J. C. E. MILLER (1995), “Applied Scale Development: Measurement of Store
Image”, ​Journal of Applied Business Research​, vol.11, n.4, pp. 85-93.

18. ROHM A.J., SWAMINATHAN V. (2004), “A typology of online shoppers based on
shopping motivations”, ​Journal of Business Research​, vol. 57, n. 7, pp. 748-757.
SASCHI C.M., (2012), “Customer engagement, buyer-seller relationships, and social media”.
Mangement Decision, vol.​50, n.​2. pp. 253-272.
SMITH M.D. (2002), “The Impact of Shopbots on Electronic Markets”, ​Journal of the
Academy of Marketing Science​, vol. 30, n. 4, pp. 446-454.
SZYMANSKI D.M., HISE R.T. (2000), “e-Satisfaction: An Initial Examination”, ​Journal of
Retailing​, vol.76, n. 3, pp. 309-322.
TESSER E. (2002), “Le politiche distributive multicanale Business-to-Consumer: dal
Marketplace al Market-Space Management”. ​Symphonya. Emerging N.s in
Management (www.unimib.it/symphonya), n.1, pp.123-136.
THOMAS, D., (2007), ​Deluxe​, Penguin, London.
TSIMONIS, G., DIMITRIADIS, S. (2014). “Brand strategies in social media”. ​Marketing
Intelligence & Planning​, VOL.32​, ​n. 3, pp.328-344.
WINDHAM L., ORTON K. (2002), ​Clienti e consumatori​, Edizione italiana a cura di Alberto
Mattiacci, Milano, Apogeo.
WOLFINBARGER, M., MARY C. G. (2003), “eTailQ: Dimensionalizing, Measuring and
Predicting Etail Quality”, ​Journal of Retailing​, vol. 79, n. 3, pp. 183-198.
YANG, W., MATTILA A.S. (2015), “Why do we buy luxury experiences? Measuring value
percepitions of luxury hospitality services”, International Journal of Contemporary
Hospitality Management, Vol.28 No 9, pp. 1848-1867.
YEOMAN,I.U. (2011), “The changing behaviours of luxury consumption”, Journal of
Revenue and Pricing Management, Vol. 10 No. 1, pp. 47-50
YUNG-SHEN YEN (2015), “Managing perceived risk for customer retention in e-commerce
The role of switching costs”, ​Information & Computer security​, vol. 23, n. 2, pp.
145-160.
WIEDMANN, K.P., HENNIGS, N.,SIEBEL, A. (2009), “Value based segmentation of luxury
consumption behaviour”, Psychology and Marketing, Vol. 26 No. 7, pp. 625-651.

19. Appendix – Scale items
Merchandise
quality
Merchandise
quality1
Online you can access to a broader range
of products
Donthu e Garcia (1999)
Merchandise
quality2
The web allows me to look for the style
more suitable for me
Merchandise
quality3
Online you can find more easily products
and sizes
Service quality Service quality1 I give greater importance to the
assistance in the store rather than to the
online reviews
Brady and Cronin (2001);
Rohm and Swaminathan
(2004)
Service quality2 I need to interact with other people
during the shopping
Service quality3 I like to feel treated with respect and
courtesy
Service quality4 I need the contact and advice of sales
personnel
Service quality5 Shopping allows me to live an experience
at 360°
Monetary price Monetary price1 I think that buying a product online lets
me save
Darden and Perreault (1976)
Monetary price2 Use the Internet to compare prices of
products and find the best offer
Monetary price3 Online you can find best deals with
respect to the store
Perceived risk Perceived risk1 I prefer to make sure that the product
isn’t faulty or counterfeit
Corbit ​et al.​ (2003)
Perceived risk2 I have a poor security in online payment
methods and in the dissemination of
personal data
Perceived risk3 I fear eventual problems in the transport
of the product purchased online
Perceived Risk4 I prefer to touch or feel the product
before buying it
Perceived Risk5 I prefer to be sure of the quality of the
product before buying it
Time/effort costs Time/effort costs1 I believe that buying online allows me to
save time
Baker ​et al.​ (2002)
Time/effort costs2 I prefer to easily make the purchase from
home without queues and tackle
problems of adverse climate
Time/effort costs3 Buying online allows me to make
purchases at any time
Enjoyment Enjoyment1 Shopping relaxes me Thijs Broekhuizen (2006)
Enjoyment2 I enjoy shopping