Content uploaded by Chris Lazaris
Author content
All content in this area was uploaded by Chris Lazaris on Jun 27, 2016
Content may be subject to copyright.
Store Atmosphere in “Physical Web” Retailing:
An IoT Disruption to Omnichannel Evolution
C. Lazaris*, A. Vrechopoulos, G. Doukidis
ELTRUN – The E-Business Center
Department of Management Science and Technology, School of Business,
Athens University of Economics and Business, Greece, 76, Patission St.
*lazaris@aueb.gr
The introduction of the Physical Web as a proximity-based gateway to the Internet of Things (IoT) constitutes a
disruption to Omnichannel & Pervasive Retailing, creating a new breed: Physical Web Retailing. The interconnection
of the World Wide Web with the physical world has been attempted several times in the past, however, this new
approach relies on ubiquitous technologies (Bluetooth, URL, etc) with low cost and a critical user base of smartphone
owners. When these users behave as Omnishoppers, the Physical Web could transform the physical store into a blended
experience that has an impact on Store Atmosphere, as well. The aim of this study is to define Physical Web
Atmospherics as online & offline atmospheric cues that are integrated with the Physical Web. A brief literature review
of Store Atmosphere across channels and the Physical Web is presented in order to formulate these new concepts.
Furthermore, future research directions and important managerial implications that derive from the introduction of the
Physical Web to the retailing field are thoroughly discussed.
Keywords: Omnichannel Retailing, Store Atmosphere, Physical Web, Bluetooth Beacons, Internet of Things (IoT),
Pervasive Retailing
1. FROM MULTICHANNEL TO OMNICHANNEL RETAILING
The introduction of the World Wide Web as a channel to conduct commerce has altered the retailing landscape forever.
Retailers embraced web retailing and became either pure electronic players or multichannel ones. Multichannel retailers
experimented with several strategies in order to create synergies between their brick and mortar stores and their
electronic counterparts. They were often characterized as “click and mortar” retailers, since they utilized both online
and offline channels in parallel.
At first, desktop and laptop computers were the prevalent devices that provided the internet experience through a web
browser. However, several technological advances transferred the web experience to mobile devices, as well. At first,
mobile phones had small screens and weak processing power; therefore conventional html, web’s language, could not
be handled properly. Thus, optimized versions emerged, such as wml and c-html, in order for mobile phones to offer a
proper experience. Nevertheless, that need was soon diminished due to the fact that newer devices in the form of
smartphones, featured specifications comparable to personal computers. As a result, users started to heavily depend on
internet access though smartphones for all kind of purposes, including e-commerce transactions. As m-commerce
evolved, consumers began using all retailing channels simultaneously, becoming Omnichannel shoppers (Lazaris et. al,
2014).
Omnichannel Retailing was originally characterized by Rigby (2011, p.4) in academia as: “an integrated sales
experience that melds the advantages of physical stores with the information-rich experience of online shopping”. Then,
Levy, et al. (2013, p.67), defined “omniretailing” as: “a coordinated multichannel offering that provides a seamless
experience when using all of the retailer’s shopping channels”.
The driver for omnichannel behavior is the internet access on the move, especially in-store (Lazaris et. al, 2014).
Consumers started to realize that the best way to overcome the physical store’s disadvantages was by using the online
channel to complement the shopping experience (Luo et al., 2014; Quint et al., 2013). In parallel, retailers started to
experiment with online features inside the physical store (Wurmser, 2014), becoming “bricks and clicks” retailers
(Herhausen et al., 2015). However, although Omniretailing has its roots on Multichannel Retailing, as the offline and
online channel are continuously trying to achieve convergence, Pervasive Retailing principles are also involved in the
context of this evolving phenomenon (Lazaris & Vrechopoulos, 2014). A reason for this is that, although consumers
could now utilize the online channel in-store through their smartphones, a key essence of Omnichannel, the “seamless”
experience, needs an integration technology in order to be effectively delivered. In sum, throughout the years, several
technological approaches tried to blend the two worlds, however cost and other barriers prohibited pervasive retailing
application scenarios (see section 2.2 of this study).
2. PHYSICAL WEB RETAILING DYNAMICS AND RESEARCH OBJECTIVES
Only recently, a disruption in the World Wide Web has taken place: Google announced the Physical Web open source
project (https://github.com/google/physical-web). It is a gateway to the Internet of Things (IoT) that utilizes the
ubiquitous Bluetooth technology as discovery service for the web. Bluetooth in the form of Beacons, (at version 4.0,
also called Bluetooth Smart or Bluetooth Low Energy - BLE) was introduced by Apple Inc in 2013, as a proximity
sensor technology. At that point, Bluetooth Beacon devices were programmed to be detected by special mobile apps
which provided push notifications that followed the iBeacon protocol. Since then, several retailers have experimented
with this promising technology developing mobile applications (Grant, 2014). However, at 2015, Google, observing the
success and user acceptance of iBeacon decided to extend the protocol adding more parameters to it: telemetry and
URL. The latter, a key essence of the web, is also a key differentiation to Apple’s approach, since the requirement for
special mobile apps development could now be bypassed. These new specifications characterized the Eddystone
Beacons (https://github.com/google/eddystone), a Google version that could remain backwards compatible with Apple
iBeacon. Afterwards, Google introduced the Physical Web which enables cross-platform Eddystone Beacon discovery
services for web browsers. In that way, almost any Bluetooth-enabled smartphone could show and open web URLs in
proximity to Beacons that are related to physical objects or areas of interest. Actually, the discovery service works as
physical search engine, since it sends a request for what's nearby and then a ranked list of results is shown to the user.
The request is generated via a pull approach, meaning that the user chooses when to search and browse the Physical
Web.
The Physical Web could now seamlessly blend the online & the offline channel, paving the ground for new research
directions across several scientific domains. Retailing, in particular, could now evolve to “Physical Web Retailing”: the
omnichannel offering of products and services for sale that is communicated to customers over the Physical Web (in
accordance to Internet Retailing definition by Levy & Weitz, 2012, p. 58). As a result, several retailing scenarios and
features could now be enriched by the Physical Web interconnection of all channels.
This study concentrates on the store atmosphere retailing notion and combines it with the Physical Web IoT technology
following a multidisciplinary research approach. The aim is to introduce store atmosphere in omnichannel retailing
under the Physical Web umbrella, providing research insights and discussing managerial implications.
3. STORE ATMOSPHERE AND PHYSICAL WEB STUDIES
The following section provides a brief literature review of both store atmosphere and physical web, in order to identify
matching patterns that will serve as a common ground to initiate new retailing concepts.
3.1 Store Atmosphere across channels
According to Eroglu & Machleit (1990) conventional (offline) store atmosphere comprises “all the physical and non-
physical elements of a store, which are within the retailer‘s control to enhance customers’ shopping experience in the
store”. Kotler (1973) was the first to introduce four atmospheric dimensions (visual, aural, olfactory, tactile) of store
atmosphere, based on the four human senses (sight, sound, scent, touch). Over a decade later, Baker (1986) stated that
store atmosphere consists of three factors: ambient (scent, temperature, music, and lighting), social (store employees
and customers), and design (architecture and layout). She considered the environmental background conditions as
ambient factors, the people as social factors and functional and aesthetic elements as design factors. Then, Lewison
(1994) followed a different approach describing three components of the store environment: store image (external &
internal impressions), store atmospherics (sight, sound, scent, touch & taste appeal) and store theatrics (décor themes &
store events). At the same period of time, Berman & Evans (1995) anticipated four components: the exterior of the
store, the general interior, the layout & design, and the point-of-purchase & decoration. In addition to these, Turley &
Milliman (2000), added the human factor (employee characteristics, employee uniforms, crowding, customer
characteristics, and privacy), too.
Correspondingly, web atmospherics has been defined as “the conscious designing of web environments to create
positive effects in users in order to increase favourable consumer responses” (Dailey, 2004, p.796). Dailey (1999) was
the first to introduce web atmospherics and Vrechopoulos et al. (2000) created a store environment framework
consisting of virtual layout & design (tree/hub, pipeline & guiding pathway structure), virtual atmospherics (site view,
sound, scent) and virtual theatrics (animation techniques). The following year, Eroglu et al. (2001) divided web
atmospheric cues into high task-relevant ones (utilitarian) and low task-relevant (hedonic). Next, McKinney (2004)
pointed out external & internal links, layout & design, point of purchase and customer services as atmospheric
elements. Then, Sautter et al. (2004) pioneered dual environment interactions by proposing that the virtual store
environment coexists with the “operator’s environment” (consumer’s physical location).
Apart from the web, other online store atmosphere channels have also been introduced: Manganari et al. (2007)
introduced mobile commerce (m-atmospherics), while Koutsiouris et al. (2007) discussed store atmosphere for location
based retail (LBS) mobile services (L-Atmosphere). Next, Krassonikolakis et al. (2014) defined Virtual Reality Store
Atmosphere (VRSA) and applied the concept in virtual worlds. In addition to these, Park et al. (2014) presented social
networking atmosphere, whereas Poncin & Mimoun (2014) combined traditional and electronic store atmosphere
frameworks, introducing a holistic approach to atmospherics. Recently, Lazaris et al. (2015) discussed Omnichannel
Retailing Store Atmosphere (ORSA), a channel approach to atmospherics.
In sum, store atmosphere has evolved along with multichannel retailing, in a sense that it has presence across all retail
channels.
3.2 Physical Web origins and recent studies
Although the Physical Web is a new technology, the vision of IoT has its roots from the beginning of the millennium.
The Auto-ID Lab at MIT (http://autoid.mit.edu/) pioneered the area by attempting to standardize RFID, introducing the
Physical Markup Language (PML), a universal language for physical objects (Brock, 2001). This attempt provided
several research directions. For example, Kourouthanassis et al. (2001) proposed a business model through a research
project
1
, where RFIDs, wireless technologies and PML where employed to provide pervasive retailing across the supply
chain, up to the last mile. The following year, Kindberg (2002), in the context of ubiquitous computing, implemented
physical hyperlinks using identifier resolution in the form of RFID tags, infrared beacons and GPS coordinates.
However, the previous attempts to link the internet with physical objects did not prevail, mainly due to technology
immaturity and costs. In 2010, research on the Internet of Things started to emerge, concentrating on web technologies
and wireless sensors (Guinard et al., 2010a). Actually, Guinard et al. (2010b) proposed a Web of Things architecture.
This concept evolved the following years and was enhanced with the use of cloud computing (Christophe et al., 2011).
At the same period, Shou et al. (2011) presented a cyber-physical search engine that scans for web objects in the
physical space. Finally, Gu et al. (2013) introduced a framework for the cyber-physical web that incorporated the
Cyber-Physical Markup Language (CPML) and smartphone sensors.
It was not until the following year, that the Physical Web project from Google was presented by Scott Jenson at an
ACM conference keynote speech (Jenson, 2014). Next, Want et al. (2015) from Google compared RFID, NFC, QR
Codes & Bluetooth Beacons as IoT enablers. They presumed that beacons offer significant advantages to the other
competitive technologies and therefore they were more suitable for the Physical Web project. Then, Jenson et al. (2015)
elaborated on the Physical Web as an integration of the IoT with web technologies using Bluetooth beacons. They
mentioned that this technology is scalable in contrast to mobile apps, therefore they postulated that it would prevail and
drive the IoT revolution.
Apart from the previous Google research associates publications, the topic gained attention to the rest academia, too.
The Physical Web was compared to Apple iBeacon approach by Jergefelt (2015), who concluded that bluetooth beacons
will play a major role in the IoT evolution. Also, Namiot & Sneps-Sneppe (2015) applied the Physical Web concept to
smart cities, where wireless proximity served for navigation and control of physical objects. Zachariah et al. (2015)
presented a Physical Web browser demo in order to showcase that a web approach to the IoT is scalable, seamless,
intuitive and more functional. Similarly, Kibria (2015) introduced a Web of Object (WoO) application server for the
Physical Web and Daradkeh & Namiot (2015) concluded that the push-based data delivery (iBeacon mobile app
notifications) has usability limitations, whereas the pull-based (browsing) approach, that the Physical Web utilizes, is
superior.
In sum, the Physical Web is the intersection of IoT and the World Wide Web providing a ubiquitous, scalable and cost
effective solution to empower the omnichannel vision.
4. STORE ATMOSPHERE IN “PHYSICAL WEB” RETAILING
The previous sections of this study discussed how the Physical Web could seamlessly blend the online with the offline
channel. In that way, Omniretailing could be greatly benefited since its core scope is to provide a seamless experience
when using all retailing channels simultaneously. Because store atmospherics exist in both conventional and electronic
retailing, in the context of Physical Web Retailing, the Physical Web could impact store atmosphere perception as well.
Actually, the interplay of multiple atmospheric cues to consumers has gained increased attention among academics the
past few years (Mari & Poggesi, 2013). In fact, research implies that multisensory cues could provide a joint effect that
could offer improved stimuli to shoppers (Spence et al., 2014). Recently, Pantano & Viassone (2015) demonstrated that
the simultaneous availability of all channels in the physical store has an impact on store atmosphere perception.
Therefore, store atmospherics at the presence of the Physical Web should be redefined in order to include the
interconnection of channels in the context of this evolving shopping environment. In 2004, Dailey stated (2004, p.796)
that a web atmospheric cue is “comparable to a brick-and-mortar atmospheric cue and can be defined as any web
1
http://www.eltrun.gr/mygrocer/?lang=en
interface component within an individual’s perceptual field that stimulates one’s senses”. Elaborating on the previous
metaphor, we can transfer the store atmospheric cue concept to the Physical Web Retailing as follows:
“A Physical Web atmospheric cue is a bricks and clicks atmospheric cue and can be defined as any interconnection
between a physical object and a web interface component through a proximity-based discovery service within an
individual’s perceptual field that stimulates one’s senses”.
In addition to that, based on web atmospherics definition (Dailey, 2004, p.796) we could also define Physical Web
Atmospherics:
“Physical Web Atmospherics is the conscious design of physical & web environments, that are interconnected
through a proximity-based discovery service, to create positive effects in users in order to increase favourable
consumer responses”
In Physical Web Retailing, Web Atmospherics derive through mobile web browsers, since physical web access is
achieved through smartphones. Modern mobile web browsers can offer the desktop web experience, except for the
smaller screen size. Furthermore, mobile web can be presented via responsive design or dedicated mobile web sites.
Thus, m-atmospherics (Manganari et al., 2007) are quite similar to conventional web atmospherics.
Moreover, web atmospherics include social media atmospherics, too (Park et al., 2014). Research has shown that the
human factor is also an important store atmosphere component (Turley and Milliman, 2000). Therefore, virtual social
presence (Manganari et al., 2009), in the form of social media channel (user reviews, blogs, social networks) could
prove to play an important role in store atmospherics, too.
Thus, following an omnichannel approach to atmospherics, we postulate that store atmosphere in Physical Web
Retailing consists of the following channels: the offline channel (the physical store) and the online channel (mobile &
social media channel) that are seamlessly integrated through the Physical Web IoT technology. Hence, Physical Web
Atmospheric components can be illustrated in the following figure (Figure 1):
Figure 1: Physical Web Atmospherics Framework
5. IMPLICATIONS FOR RESEARCH AND PRACTICE
The Physical Web extends the Internet into the physical world, establishing itself as a new dimension of the World
Wide Web. It is a universal platform that provides relevant digital information to the physical space, in an interactive
way, through ubiquitous technologies. At the retailing field, it could transform the shopping environment, store
atmospherics, in particular. Store atmosphere in Physical Web Retailing is, in fact, a multisensory approach to
atmospherics. The simultaneous presence of both conventional & online atmospheric cues could create a new holistic
perception of store atmosphere. Moreover, since these cues are present through the omnichannel notion, a joint effect
could be created: the amplification of the resulting hybrid store atmosphere.
Thus, future research should address Physical Web Atmospherics as a whole and investigate how the final outcome
could be optimized. Multiple sensory cues could create synergies under specific circumstances and perceived channel
congruence (Bèzes, 2013) & channel integration (Herhausen et al., 2015) could play a vital role in this unification.
Otherwise, the realized benefits could be diminished. For example, a customer that walks at the TVs aisle of a physical
retail store should be presented with congruent cues (similar and consistent) that are assisted with omnichannel
integration in terms of services and functions. The Physical Web could evolve as a valuable tool towards this
PHYSICAL STORE ATMOSPHERICS
Offline Channel Atmospheric Cues
WEB ATMOSPHERICS
Online Channels Atmospheric Cues
- Mobile Channel Cues
- Social Media Channel Cues
PHYSICAL WEB
convergence since the interconnection of both worlds is accomplished seamlessly, conveniently and interactively, while
following permission marketing guidelines. Indicatively, the use of pull instead of push approach towards customer
interaction facilitates the effective application of permission marketing guidelines, offering privacy and control. The
latter, perceived control, has yet to be achieved in physical shopping environments mainly due to the lack of
customization (at least to the extent that it is applicable online) and other relevant offline channel constraints
(Vrechopoulos, 2010). On the other hand, the online shopping environments feature these characteristics but lack the
tactile feedback of the physical space (e.g. physical product inspection). Therefore, Physical Web Atmospherics could
omit these disadvantages offering a sense of dominance to the consumer (Hsieh et al., 2014).
Another research direction could involve showrooming and webrooming behavior (Rapp et al., 2015). It would be
intriguing to explore how these types of consumer behavioural patterns could be affected by the omnichannel retailing
store atmosphere and Physical Web retailing, in general. Indicatively, price is always a major store selection criterion
but why would a consumer leave the physical store to buy elsewhere if the shopping experience is enhanced, and at the
same time he/she could also benefit from web prices? Regarding webrooming, a consumer researching online in order
to purchase offline, could probably have more incentives to purchase from the physical web retailer if he/she is offered
physical web exclusive prices. Similarly, such research attempts could also contribute to the pure online stores' strategic
marketing planning since they can provide useful knowledge regarding the evolving business practices and
corresponding changes in consumer behavioural patterns in the context of Omnichannel and Physical Web Retailing.
Thus, taking into account these emerging trends, pure online stores could focus on building sustainable competitive
advantages (e.g. value added services, unique products/services, attractive prices, 3D graphical user interfaces,
omnichannel features, etc.). It should be clarified that omnichannel practices are also applicable for non-physical-store
retailing like the case of pure web-based stores (e.g. Call Centers, E-Mail, Physical points for pick-up services, printed
catalogues with QR technologies, door-to-door selling, use of POS terminals, Social Media, etc.). Therefore, pure e-
tailers should adapt to this evolving retailing landscape by either strengthening their omnichannel presence or even
leveraging the Physical Web by executing proximity-based outdoor advertising or indoor marketing campaigns (e.g. at
exhibitions or metro stations).
Regarding marketing activities, Physical Web could provide several innovative opportunities as well. In addition to
outdoor advertising campaigns, window shopping activities could be greatly enhanced, since the consumer could be
attracted to visit a store through multiple cues even before entering it. Also, in-store Proximity Marketing could now
take place without special mobile application development, providing relevant call to action at preconfigured times.
Moreover, digital programmatic advertising could now appear in the physical space, which could also be rented for
specific intervals. Additionally, an advanced scenario could involve telemetry-triggered marketing campaigns, where
the embedded environmental sensors inside Bluetooth beacons could display advertising content based on telemetry
parameters (e.g. heating appliances at cold days versus air conditioners at hot days). Finally, the sales assistance
personnel role could now be affected through in-store web chat: a consumer could trigger support for digital assistance
or request physical assistance to come nearby.
To sum up, the physical world could now become the new digital channel, as the Physical Web evolves to the Internet
of Things gateway to omnichannel. “Bricks & Clicks” seems to be the evolution of “Click & Mortar” and retailers
could adapt to this new retailing paradigm that promises to offer challenging opportunities and mutual benefits for the
involved players.
References
1. Baker, J. (1986). The role of the environment in marketing services: the consumer perspective. The Services
Challenge: Integrating for Competitive Advantage, 1(1), 79–84.
2. Berman, B. R., & Evans, J. R. (2012). Retail Management: A Strategic Approach (12th Edition). Book. Englewood
Cliffs, NJ: Prentice-Hall, Inc.
3. Bèzes, C. (2013). Effect of channel congruence on a retailer’s image. International Journal of Retail & Distribution
Management, 41(4), 254–273. http://doi.org/10.1108/09590551311330537
4. Brock, D. (2001). The Physical Markup Language. Retrieved from http://xml.coverpages.org/PML-MIT-AUTOID-
WH-003.pdf
5. Christophe, B., Boussard, M., Lu, M., Pastor, A., & Toubiana, V. (2011). The web of things vision: Things as a
service and interaction patterns. Bell Labs Technical Journal, 16(1), 55–61. http://doi.org/10.1002/bltj.20485
6. Dailey, L. (1999). Designing the world we surf in: a conceptual model of web atmospherics. In American Marketing
Association Conference Proceedings (Vol. 10, p. 225).
7. Dailey, L. (2004). Navigational web atmospherics. Journal of Business Research, 57(7), 795–803.
http://doi.org/10.1016/S0148-2963(02)00364-8
8. Daradkeh, Y. I., & Namiot, D. (2015). Network Proximity and Physical Web. In I. J. Rudas (Ed.), Mathematics and
Computers in Sciences and Industry (Mathematic, pp. 170–175). Retrieved from
http://www.inase.org/library/2015/books/bypaper/MCSI/MCSI-32.pdf
9. Eroglu, S. A., & Machleit, K. A. (1990). An Empirical Study of Retail Crowding: Antecedents and Consequences.
Journal of Retailing, 66(2), 201–221.
10. Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2001). Atmospheric qualities of online retailing. Journal of Business
Research, 54(2), 177–184. http://doi.org/10.1016/S0148-2963(99)00087-9
11. Grant, R. (2014). Shopkick users have earned $25M in rewards, scanned 70M products, and viewed 4B offers -
VentureBeat. Retrieved April 28, 2016, from http://venturebeat.com/2014/02/13/shopkick-users-have-earned-25m-
in-rewards-scanned-70m-products-and-viewed-4b-offers/
12. Gu, X., Shou, L., Lu, H., & Chen, G. (2013). A generic framework for cyber-physical web. In Proceedings of the
First International Workshop on Middleware for Cloud-enabled Sensing - MCS ’13 (pp. 1–6). New York, New
York, USA: ACM Press. http://doi.org/10.1145/2541603.2541607
13. Guinard, D., Trifa, V. M., & Wilde, E. (2010a). Architecting a mashable open world wide web of things. Institute
for Pervasive Computing. ETH Zürich, Zürich, Switzerland: ETH, Department of Computer Science.
http://doi.org/10.3929/ethz-a-006851061
14. Guinard, D., Trifa, V., & Wilde, E. (2010b). A resource oriented architecture for the Web of Things. In Internet of
Things (IOT) (pp. 1–8). IEEE. http://doi.org/10.1109/IOT.2010.5678452
15. Herhausen, D., Binder, J., Schoegel, M., & Herrmann, A. (2015). Integrating Bricks with Clicks: Retailer-Level and
Channel-Level Outcomes of Online–Offline Channel Integration. Journal of Retailing, 91(2), 309–325.
http://doi.org/10.1016/j.jretai.2014.12.009
16. Hsieh, J.-K., Hsieh, Y.-C., Chiu, H.-C., & Yang, Y.-R. (2014). Customer Response to Web Site Atmospherics:
Task-relevant Cues, Situational Involvement and PAD. Journal of Interactive Marketing, 28(3), 225–236.
http://doi.org/10.1016/j.intmar.2014.03.001
17. Jenson, S. (2014). The Physical Web. In Proceedings of the extended abstracts of the 32nd annual ACM conference
on Human factors in computing systems - CHI EA ’14 (pp. 15–16). New York, New York, USA: ACM Press.
http://doi.org/10.1145/2559206.2580095
18. Jenson, S., Want, R., Schilit, B. N., & Kravets, R. H. (2015). Building an On-ramp for the Internet of Things. In
Proceedings of the 2015 Workshop on IoT challenges in Mobile and Industrial Systems - IoT-Sys ’15 (pp. 3–6). New
York, New York, USA: ACM Press. http://doi.org/10.1145/2753476.2753483
19. Jergefelt, M. (2015). An Internet of Pings: Enhancing the Web User Experience of Physically Present Patrons with
Bluetooth Beacons. Weave: Journal of Library User Experience, 1(2).
http://doi.org/10.3998/weave.12535642.0001.202
20. Kibria, M. G. (2015). Knowledge based open IoT service provisioning through cooperation between physical web
and WoO. In 2015 Seventh International Conference on Ubiquitous and Future Networks (pp. 395–400). IEEE.
http://doi.org/10.1109/ICUFN.2015.7182573
21. Kindberg, T. (2002). Implementing physical hyperlinks using ubiquitous identifier resolution. In Proceedings of the
eleventh international conference on World Wide Web - WWW ’02 (p. 191). New York, New York, USA: ACM
Press. http://doi.org/10.1145/511446.511472
22. Kotler, P. (1973). Atmospherics as a marketing tool. Journal of Retailing, 49(4), 48–64.
23. Kourouthanassis, P., Koukara, L., Lazaris, C., & Thiveos, K. (2001). Last-mile supply chain management: Mygrocer
innovative business and technology framework. In Proceedings of the 17th International Logistics Congress:
Strategies and Applications (pp. 264–273). http://doi.org/10.13140/2.1.1106.8489
24. Koutsiouris, V., Polychronopoulos, C., & Vrechopoulos, A. (2007). Developing 3G Location Based Services: The
Case of an Innovative Entertainment Guide Application. In International Conference on the Management of Mobile
Business (ICMB 2007) (pp. 1–1). IEEE. http://doi.org/10.1109/ICMB.2007.26
25. Lazaris, C., & Vrechopoulos, A. (2014). From Multichannel to “Omnichannel” Retailing: Review of the Literature
and Calls for Research. In 2nd International Conference on Contemporary Marketing Issues, (ICCMI), 18-20 June.
Athens, Greece. http://doi.org/10.13140/2.1.1802.4967
26. Lazaris, C., Vrechopoulos, A., Doukidis, G., & Fraidaki, K. (2015). The Interplay of Omniretailing & Store
Atmosphere on Consumers’ Purchase Intention towards the Physical Retail Store. In 12th European, Mediterranean
& Middle Eastern Conference on Information Systems (EMCIS), 1-2 June. Athens, Greece.
http://doi.org/10.13140/RG.2.1.3928.3048
27. Lazaris, C., Vrechopoulos, A., Fraidaki, K., & Doukidis, G. (2014). Exploring the “Omnichannel” Shopper
Behaviour. In AMA SERVSIG, International Service Research Conference, 13-15 June. Thessaloniki, Greece.
http://doi.org/10.13140/2.1.1278.2089
28. Levy, M., & Weitz, B. (2012). Retailing Management. New York, USA: McGraw-Hill/Irwin; 8th edition.
29. Levy, M., Weitz, B., & Grewal, D. (2013). Retailing Management. New York, USA: McGraw-Hill/Irwin; 9th
edition.
30. Lewison, D. M. (1999). Retailing, Canadian Edition. Book (5th Edition). New York, USA: Mac millan Publishing
Company.
31. Luo, Q., Oh, L.-B., Zhang, L., & Chen, J. (2014). Examining the showrooming intention of mobile-assisted
shoppers in a multichannel retailing environment. In Pacific Asia Conference on Information Systems (PACIS) (p.
Paper 141). Retrieved from http://aisel.aisnet.org/pacis2014/141
32. Manganari, E., Siomkos, G., & Vrechopoulos, A. (2007). Atmospheric qualities in mobile commerce: an initial
approach. In Proceedings of the 36th European Marketing Academy Conference (EMAC) (pp. 1–7). Reykjavik,
Iceland: McGraw-Hill.
33. Manganari, E. E., Siomkos, G. J., & Vrechopoulos, A. (2009). Store atmosphere in web retailing. European Journal
of Marketing, 43(9/10), 1140–1153. http://doi.org/10.1108/03090560910976401
34. Mari, M., & Poggesi, S. (2013). Servicescape cues and customer behavior: a systematic literature review and
research agenda. The Service Industries Journal, 33(2), 171–199. http://doi.org/10.1080/02642069.2011.613934
35. McKinney, L. N. (2004). Creating a satisfying internet shopping experience via atmospheric variables. International
Journal of Consumer Studies, 28(3), 268–283. http://doi.org/10.1111/j.1470-6431.2004.00368.x
36. Namiot, D., & Sneps-Sneppe, M. (2015). The Physical Web in Smart Cities. In Advances in Wireless and Optical
Communications (RTUWO) (pp. 46–49). IEEE. http://doi.org/10.1109/RTUWO.2015.7365717
37. Pantano, E., & Viassone, M. (2015). Engaging consumers on new integrated multichannel retail settings: Challenges
for retailers. Journal of Retailing and Consumer Services, 25, 106–114.
http://doi.org/10.1016/j.jretconser.2015.04.003
38. Park, M.-S., Shin, J.-K., & Ju, Y. (2014). Social networking atmosphere and online retailing. Journal of Global
Scholars of Marketing Science, 24(1), 89–107. http://doi.org/10.1080/21639159.2013.867681
39. Poncin, I., & Ben Mimoun, M. S. (2014). The impact of “e-atmospherics” on physical stores. Journal of Retailing
and Consumer Services, 21(5), 851–859. http://doi.org/10.1016/j.jretconser.2014.02.013
40. Quint, M., Rogers, D., & Ferguson, R. (2013). Showrooming and the rise of the mobile-assisted shopper. Columbia
Business School - Aimia. Retrieved from https://www4.gsb.columbia.edu/filemgr?file_id=7313935
41. Rapp, A., Baker, T. L., Bachrach, D. G., Ogilvie, J., & Beitelspacher, L. S. (2015). Perceived customer
showrooming behavior and the effect on retail salesperson self-efficacy and performance. Journal of Retailing,
91(2), 358–369. http://doi.org/10.1016/j.jretai.2014.12.007
42. Rigby, D. (2011). The Future of Shopping. Harvard Business Review, 89(12), 64–75.
43. Sautter, P., Hyman, M. R., & Lukošius, V. (2004). E-tail Atmospherics: a critique of the literature and model
extension. Journal of Electronic Commerce Research, 5(1), 14–24. Retrieved from
http://www.csulb.edu/web/journals/jecr/issues/20041/Paper2.pdf
44. Shou, L., Chen, K., Chen, G., Zhang, C., Ma, Y., & Zhang, X. (2011). What-you-retrieve-is-what-you-see: a
preliminary cyber-physical search engine. In Proceedings of the 34th international ACM SIGIR conference on
Research and development in Information - SIGIR ’11 (p. 1273). New York, New York, USA: ACM Press.
http://doi.org/10.1145/2009916.2010156
45. Spence, C., Puccinelli, N. M., Grewal, D., & Roggeveen, A. L. (2014). Store Atmospherics: A Multisensory
Perspective. Psychology & Marketing, 31(7), 472–488. http://doi.org/10.1002/mar.20709
46. Turley, L. ., & Milliman, R. E. (2000). Atmospheric Effects on Shopping Behavior. Journal of Business Research,
49(2), 193–211. http://doi.org/10.1016/S0148-2963(99)00010-7
47. Vrechopoulos, A. (2010). Who controls store atmosphere customization in electronic retailing? International
Journal of Retail & Distribution Management, 38(7), 518–537. http://doi.org/10.1108/09590551011052115
48. Vrechopoulos, A., Keefe, R. M. O., & Doukidis, G. I. (2000). “Virtual Store Atmosphere” in Internet Retailing. In
13th International Bled Electronic Commerce Conference, June 19-21 (pp. 1–12). Bled, Slovenia.
49. Want, R. (2015). The Physical Web. In Proceedings of the 2015 Workshop on IoT challenges in Mobile and
Industrial Systems - IoT-Sys ’15 (pp. 1–1). New York, New York, USA: ACM Press.
http://doi.org/10.1145/2753476.2753496
50. Wurmser, Y. (2014). Retailers Playing Catch-Up with Consumers - Emarketer. eMarketer. Retrieved from
http://www.emarketer.com/public_media/docs/state_of_omnichannel_retail.pdf
51. Zachariah, T., Adkins, J., & Dutta, P. (2015). Demo: Browsing the Web of Things with Summon. In Proceedings of
the 13th ACM Conference on Embedded Networked Sensor Systems - SenSys ’15 (pp. 481–482). New York, New
York, USA: ACM Press. http://doi.org/10.1145/2809695.2817864
