Enhancing User Experience Through Pervasive Information Systems

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International Journal of Information Management 27 (2007) 319–335

Enhancing user experience through pervasive information

systems: The case of pervasive retailing

Panos E. Kourouthanassis, George M. Giaglis, Adam P. VrechopoulosÃ

Department of Management Science and Technology, Athens University of Economics and Business,

47A Evelpidon & 33 Lefkados Street, 11362 Athens, Greece

Abstract

Pervasive information systems (PIS) constitute an emerging class of information systems (IS) where information

technology (IT) is gradually embedded in the physical environment, capable of accommodating user needs and wants when

desired. PIS differ from desktop information systems (DIS) in that they provide new means of interaction and can generate

new experiences for their users. This paper investigates the effects of PIS to user experience in the context of retailing.

A prototype PIS was implemented to serve as vehicle for a field experiment in a Greek supermarket. Shoppers were invited

to use the system and provide feedback on its effects on their shopping experience within the store. The research revealed

that several dimensions of the shopping experience, namely entertainment, shopping efficiency, budget monitoring, time

pressure, information search, checkout problems, and promotions overload, were positively affected by the PIS. The study

results suggest that embedding pervasive technologies to the retail arena may enable retailers to differentiate by providing

customer-centric services that alleviate shoppers’ perception of confusion, stress, and routine during the shopping sessionand increase store loyalty.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Pervasive computing; User experience

1. Introduction

Information technology (IT) artefacts are already embedded in more places than just our desktop

computers, providing innovative services in ways unimaginable in the near past. This shift in the viewpoint of

information systems (IS) is commonly referred to as ‘post-desktop’ (Jonsson, 2002) or ‘ubiquitous’ computing

(Weiser, 2002). This trend has fired a shift away from computers towards computerised artefacts. A new

generation of information appliances has emerged (Roussos, 2003), differing from traditional general-purpose

computers in what they do and in the much smaller learning overhead they impose on the user. Instead of

having IT in the foreground, triggered, manipulated, and used by humans, nowadays we witness that IT

(irrespectively whether it comprises of computers, small sensors, or other communication means) gradually

resides in the background, monitoring the activities of humans, processing and communicating this

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ÃCorresponding author. Tel.: +30 210 8203687; fax: +30 210 8203685.

E-mail addresses: [email protected] (P.E. Kourouthanassis), [email protected] (G.M. Giaglis), [email protected] (A.P. Vrechopoulos).

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information to other sources and intervening should it be required. This new class of IS has been called

‘pervasive information systems’ (PIS) (Birnbaum, 1997) and enables new interaction means beyond the

traditional desktop paradigm.

In this paper, we argue that PIS can enhance user experience beyond the level achievable by their desktop-

based counterparts. This is supported by the recent advances in sensing and recognition technologies that

enable the provision of more human-like communication capabilities, while at the same time effectivelytreating implicit actions as meaningful system inputs (Abowd, Mynatt, & Rodden, 2002). To substantiate our

claim, we have implemented a prototype PIS in the retail context. By installing and testing a PIS in a real

supermarket, we deducted that several dimensions of the shopping experience, namely entertainment,

shopping efficiency, budget monitoring, time pressure, information search, checkout problems, and

promotions overload, can be positively affected by the system.

The following section sheds light on the nature of PIS, presenting their novel characteristics compared to

traditional desktop information systems (DIS). Section 3 defines user experience and identifies ways in which

PIS may affect it. Section 4 applies our rationale in a particular context (retail sector), while Section 5 discusses

the development of our research model. Section 6 presents the research methodology and results of our field

test. The final section concludes with a critical appraisal of the future of PIS, as well as a discussion on the

limitations of our study.

2. Pervasive information systems overview

PIS constitute an emerging IS class where IT pervades the physical space and extends the system boundaries

beyond the desktop computer. PIS bridge the evolution in mobile computing technologies and distributed

systems by flavouring from the novel properties these disciplines introduce. Several studies have tried to

outline the differentiating elements of this new class of IS [e.g. ( Abowd & Mynatt, 2000; Lyytinen & Yoo,

2002; Saha & Mukherjee, 2003; Satyanarayanan, 2001; Weiser, 1993)], examining PIS from multiple

perspectives. In essence, PIS revisit the way we interact with computers by introducing new input modalities

and system capabilities. So far, the interaction paradigm for IS has been the desktop. Thus, the design and

implementation of IS was based on this paradigm. PIS extend this paradigm by introducing a set of novel

characteristics that may be summarised in the points below.First, PIS always deal with non-traditional computing devices that merge seamlessly into the physical

environment. As such, the desktop (in the form of the personal computer) is just ‘another access device’.

Consequently, conventional HCI design methods and interaction schemes may not be appropriate for the new

IS class since the physical interaction between users and the system will, most certainly, not resemble the

prevailing DIS keyboard/mouse/display paradigm. Thus, apart from solely physical interactions with the

system, PIS may also incorporate elements of ambient interactions with devices or objects from the physical

space in a natural and unobtrusive manner [e.g. (Maes, 2005; Quek et al., 2002)].

Second, PIS support a multitude of heterogeneous device types that differ in terms of size, shape, and

functionality (simple mobile phones, portable laptops, pagers, PDAs, sensors, and so on), providing

continuous interaction which moves computing from a localised tool to a constant presence. Opposed to

desktop environments where the access devices are stationary, PIS support nomadic devices which may be

carried around by users and present location-based information. Furthermore, the participating elements of a

pervasive system may be highly embedded in the physical environment. This implies that they will inevitably

interact with the existing architecture of the environment.

Furthermore, PIS emerge a revised viewpoint in the way we perceive system design. ‘Conventional’ system

design incorporated more and more of the physical world inside the computer. In this sense, the actual system

intelligence has been purely cybernetic, comprising of software designed to execute predefined tasks and

activities efficiently. Moreover, systems were designed in such ways that enhanced overall utility and

productivity, especially when applied to organizational contexts. In the case of PIS the system’s intelligence no

longer resides solely in the computer, but it is embedded in the physical world. Thus, each artefact may be

specialised to support a single task performed in a more efficient way. This task may depend on a geographical

location or may be triggered by an event such as a user request, a sensor reading change, and so on. Therefore,

PIS introduce the property of context awareness as a result of the pervasive artefacts capability to collect,

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process, and manage environmental or user-related information on a real-time basis. Opposed to desktop

computing, where user action precedes system response, PIS promote system pro-action based on environmental

stimuli .

Finally, in PIS environments users may range from being vaguely familiar with IT to expert users. In

addition, they may be opportunistic in the sense that they may use the system only sporadically (e.g. users of a

smart museum), implying that they may not be subject to training prior to system use. The following table

summarises the differences among the desktop paradigm (DIS) and PIS under six examination dimensions

Table 1.

We argue that the aforementioned novel characteristics of PIS will have a positive impact on user experience

compared to the typical user experience in DIS. The following section attempts to shed light on thecharacteristics of IS user experience before proceeding to exemplify how pervasive IS may augment it.

3. Understanding user experience

Experience is an intangible process of interaction between people and the world that exists in humans’

minds and is triggered by new interactions (Davis, 2003). These may create different types of experiences such

as physical, sensual, cognitive, emotional, and aesthetic (Forlizzi & Battarbee, 2004), which, if incorporated in

the design process, may extend simple usability techniques to differentiate the design product (Bloch, 1995).

Over the past few years several attempts have been made to create theories (Alben, 1996; Makela & Fulton

Suri, 2001), frameworks (Forlizzi & Battarbee, 2004; Forlizzi & Ford, 2000), as well as efforts to categorise

specific types of experiences relating to design products (Pine & Gilmore, 1998; Shedroff, 2001). Forlizzi and

Battarbee (2004) have grouped these approaches examining user experience into product centred, user centred,

and interaction centred. Product-centred approaches describe the experience types that must be considered

during the design and evaluation of an IT artefact. User-centred approaches help designers and developers to

understand the people who will use the IT artefact or full-grown system. Interaction-centred approaches

describe the experience types that are evoked during the actual artefact or system use. According to the same

authors, there are three types of experiences that may be yielded by user–product interactions. The first,

‘experience’, is a constant stream of ‘self-talk’ that happens when we interact with products or environments

(e.g. a walk in the park). The second, ‘an experience’, can be articulated or named since it has a clear beginning

and end, inspiring behavioural and emotional change (such as watching a movie, visiting a museum, and so

on). The final one, ‘co-experience’ is about user experience in a social context, created together and shared

with others (such as playing a game with friends or interacting in a chat room).

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Table 1

DIS and PIS differentiating elements

Desktop information systems Pervasive information systems

User Committed Opportunistic

Known Unknown

Trained Untrained

Role model: office clerk Role model: citizen

Task Generic Specific

Focused on utility and productivity Focused on service delivery and experience

Medium Localised Constant presence

Homogeneous Heterogeneous

‘Point and click’ paradigm Natural interaction and multimodal paradigm

Space Cybernetic Physical

Product Virtual Tangible and virtual

Time Reactive Proactive

P.E. Kourouthanassis et al. / International Journal of Information Management 27 (2007) 319–335 321



In short, the user experience may be viewed as a sum of momentary constructions that grow from the

interaction of users with their environments. These constructions may be affected by several strands that

include, but are not limited to, compositional, sensory, emotional, spatio-temporal, and interaction-based

factors (Battarbee & Koskinen, 2005). In the IS context, the user experience is mostly generated through the

interplay of interactions between the system and the user. Depending on design factors such as the user

interface, the navigation structure, the time that the system requires to process a request, and the relevance of results to name but a few elements that have been identified by IS scholars [e.g. (Garrett, 2002; Hassenzahl,

2004; Kuniavsky, 2003; Sears & Jacko, 2000)] a user may evoke positive experiences for either utilitarian or

emotional reasons. The utilitarian aspect of the IS user experience relates to the accomplishment of user tasks

in a more efficient or effective way. The emotional aspect of the IS user experience relates to the induction of

positive or negative feelings (such as excitement or frustration) during or after using the system.

The desktop paradigm reinforces the utilitarian or emotional aspect of the IS user experience through the

interactions of users with the personal computer. Conversely, in the context of PIS, experiences may be

generated through user interactions with both the heterogeneous devices deployed and the physical

environment. This interplay of interactions comprises the differentiating factor that may augment the

behavioural, emotional, or sensoral experiences for the user. IT may be embedded in a natural setting,

supporting actions, tasks, or activities that the user performs on a conscious or sub-conscious level, providing

new services or applications, but still without super-imposing the technology to create cognitive overloads.Examples of such IT-augmented experiences include the visiting experience in a museum and the learning

experience in a campus.

Specifically, usability studies in IT-augmented museums [e.g. (Bellotti, Berta, De Gloria, & Margarone,

2001; Fleck et al., 2002; Hsi & Fait, 2005) and many others] indicate that the provision of context-aware

multimedia services through wireless museum guides may significantly enhance visitors’ satisfaction during

their visiting trip by providing increased efficiency, speed, and added informational value. Similarly,

researchers noticed that pervasive computing technologies may streamline the learning experience of students

in campuses by providing ad hoc notification about the academic schedule and course-related material [e.g.

(Abowd, 1999; Storz et al., 2006)].

The IS user experience may be quantified and measured if investigated under a particular context. Following

the applications exemplified before, we may be able to identify factors that affect visitors’ experience within amuseum, students’ learning experience during a course, even an individual’s experience while walking in the

park. To this end, in each case we may evaluate the effect of PIS on the user experience, by assessing whether

these factors are positively or negatively affected, if at all. In our research, we have selected the retail context

to evaluate the effect of PIS on the shopping experience (a ‘type two’ experience, having a clear beginning and

end). The following section identifies factors that negatively affect shopping experience in traditional

supermarket shopping and proposes ways in which PIS may be used to enhance it.

4. Conceptualizing pervasive retailing

A shopping experience is affected by the reasons people buy. Early studies developed taxonomies of

supermarket shoppers in an attempt to infer shopping motivations from distinct ‘types’ of shoppers, such as

the ‘economic’ or ‘apathetic’ shopper (Stone, 1954). Other studies have developed taxonomies based on

orientations to product usage (Dardin & Reynolds, 1971), actual patronage and shopping behaviour

(Stephenson & Willett, 1969), use of product information (Moschis, 1976), shopping enjoyment (Bellenger &

Korgaonkar, 1980), and retail attribute preferences (Bellenger, Robertson, & Greenberg, 1977; Dardin &

Ashton, 1974).

In essence, a shopping experience can be driven towards the maximization of utility and efficiency (e.g. an

economic shopping trip, a convenient shopping trip), or towards entertainment (Lewison, 1997; Westbrook &

Black, 1985):

The utilitarian dimension of the shopping experience has often been characterised as task related and

rational (Batra & Ahtola, 1991), and related closely to whether or not a product acquisition ‘mission’ was

accomplished (Babin, Darden, & Griffin, 1994).

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Entertaining shopping experiences are similar to the task orientation of utilitarian shopping motives, but

they result to hedonic fulfillment, such as experiencing fun and amusement (Babin et al., 1994; Langrehr,

1991; Roy, 1994; Wakefield & Baker, 1998). Moreover, they are characterized by intrinsic satisfaction,

perceived freedom, and involvement (Babin & Darden, 1995b; Bloch, Sherrell, & Ridgway, 1986; Gunter &

Gunter, 1980; Hirschman, 1983; Mannell, 1980; Unger & Kernan, 1983).

In traditional in-store shopping, the shopping experience is mainly created through the store environment,

and through the service offered at the checkout (Dawes & Rowley, 1998). Moreover, a shopping experience is

highly affective, creating positive or negative feelings to shoppers depending on several in-store elements such

as crowding, noise, music, and so on. From a management perspective, researchers recognize the importance

of affective reactions in shoppers. Emotion experienced while shopping has been shown to affect a variety of

responses, such as approach behaviour (Hui, Dube, & Chebat, 1997), spending levels (Donovan & Rossiter,

1982), retail preference and choice (Dawson, Bloch, & Ridgway, 1990), willingness to buy (Baker, Grewal, &

Levy, 1992), and shopping satisfaction (Machleit & Eroglu, 2000a). Consequently, over the past years,

researchers and practitioners have attempted to identify factors that negatively affect the shopping experience,

and create negative emotions for shoppers.

Therefore, past studies revealed that the shopping experience might be affected by a number of store-related

factors which include—but are not limited to—ambience (temperature, scent, music, and so on) [e.g. ( Baker,1986; Bruner, 1990b; Donovan & Rossiter, 1982; Fried & Berkowitz, 1979; Gorn, 1982)], service quality (Siu &

Cheung, 2001), store image (Corstjens & Doyle, 1983; Curhan 1973), and situational elements (such as

crowding, time, and budget availability by the consumers) (Donovan & Rossiter, 1982; Levy & Weitz, 2001).

These lead to increased levels of stress for the supermarket shopper (Aylott & Mitchell, 1998) and may serve to

create a new form of shopper who have no interest in, or actively dislike, shopping and appear to endure

rather than enjoy the whole experience (Reid & Brown, 1996). The following table illustrates some of the most

important store-related factors that affect the shopping experience by categorising them into four dimensions:

Ambient factors, comprising of background features that may or may not be consciously perceived but that

affect human senses (such as scent, music, and noise).

Design factors, comprising of features that relate to the image of the store (e.g. layout) and are directlyperceptible by shoppers.

Social factors, comprising of people in the environment, both other shoppers, and sales personnel.

Situational factors, comprising of store events that occur randomly and affect the shoppers’ experience

within the store Table 2.

As food retailers seek new means to reach their consumers, they may turn to IT as a means of enhancing the

shopping experience in terms of addressing some of the aforementioned factors. The embedment of IT in the

retail outlet for the benefit of the shoppers may generate a subclass of PIS, namely pervasive retail information

systems (PRIS). A PRIS applies the major properties of PIS to the retail context. Pervasive retailing can be

thought of as the natural evolution of multi-channel retailing, namely reaching the consumer through

alternative channels. Indeed, retailers have investigated new approaches to reach consumers and streamline

core supply chain operations through the Internet [e.g. (Elliot & Fowell, 2000; Lim & Palvia, 2001; Rahman,

2003; Williamson, Harrison, & Jordan, 2004)] or by offering new ways of purchasing products within the

supermarket mainly in the form of self-service scanners (Dabholkar & Bagozzi, 2002; Meuter, Ostrom,

Roundtree, & Bitner, 2000). Pervasive retailing aims at expanding the portfolio of consumer-focused services

while at the same time streamlining core supply chain management operations.

A typical scenario of how a shopper may interact with a pervasive retail system is illustrated in Fig. 1, based

on pervasive IS literature (Asthana, Cravatts, & Krzyzanowski, 1994; IBM, 2005). In the supermarket

environment, the shopper can pick up a wirelessly connected shopping cart equipped with a display device and

a radio frequency identification (RFID) sensor capable of scanning the contents of the cart. The shopper can

use her loyalty card to log in the system, which welcomes her and presents her the shopping list she has

uploaded prior to her visit to the store. She can then start navigating within the store as usual, picking up

products and placing them inside the shopping cart. Each time a product is placed in the cart, the display

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device shows its description and price, and updates the total cost of the cart contents. At the same time, the

product is removed from the shopping list. Moreover, at any time the shopper can request additional

information about a product (e.g. nutritional value or ingredients), get informed about ongoing promotional

activities (fully personalised based on the shopper’s profile and past consumption patterns), and request

navigation assistance within the store. Finally, during checkout, the system transmits the list of purchased

products along with the total amount to the cashier, who bills the shopper and issues the receipt, thus

alleviating the need for queues and product loading/unloading at the checkout.

In this research, we followed the scenario described above to design and implement a pervasive system that

addresses some of the aforementioned factors affecting the shopping experience. Specifically, a shopping cart

was specially modified in order to incorporate a Tablet PC and an RFID reader capable of scanning RF-

enabled supermarket products. All system services were available to users through the Tablet PC. We selected

the RFID technology (Smith & Konsynski, 2003) due to its increased capabilities compared to conventional

barcode scanning, and its potential to develop a user-friendly solution. Connectivity with backend systems was

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Table 2

Factors affecting the shopping experience

Category Definition Factors References

Ambient Factors Background conditions

that exist below the level

of shoppers’ immediate

awareness

Music (Baker, 1986; Bitner, 1992; Bruner,

1990a,b; Donovan & Rossiter, 1982;

Donovan, Rossiter, Marcoolynn, &

Nesdale, 1994; Fried & Berkowitz,

1979; Gorn, 1982; Mattila & Wirtz,

2001; Milliman, 1982; Mitchell, Kahn,

& Knasco, 1995; Turley & Milliman,

2000)

Scent

Lightning

Temperature

Humidity

Noise

Design Factors Store attributes and

stimuli that exist at the

forefront of shoppers’

awareness

Layout (Aylott & Mitchell, 1998; Biswas &

Blair, 1991; Corstjens & Doyle, 1983;

Crowley, 1993; Curhan, 1973; d’

Astous, 2000; Dickson & Sawyer, 1990;

Mazumdar & Monroe, 1990; Monroe,

1971; Olney, Holbrook, & Batra, 1991;

Sundstrom, 1977; Urbany, Bearden, &

Weilbaker, 1988; Wilkie & Dickson,

1985)

Store aesthetics

Signage

Architecture

Scale

Materials

Promotions/advertisements

Pricing

Social Factors Other shoppers’ and sales

personnel’s behaviour

Service quality (Babin & Darden, 1995a; Berry,

Seiders, & Grewal, 2002; Bitner, 1990;

Brady & Cronin, 2000; Dabholkar,

Thorpe, & Rentz, 1996; Darden &

Babin, 1994; Siu & Cheung, 2001;

Vazquez, Rodriguez-Del Bosque, Ma

Diaz, & Ruiz, 2001; Woodside, Frey, &

Daly, 1989; Zeithaml 1988)

Behaviour

Appearance

Number

Situational

factors

Personal attributes or

store events that occur

randomly and affect theshoppers’ experience

within the store

Time constraints/ constraints to

complete the purchases

(Altman, 1975; Babin & darden, 1996;

Dawson et al., 1990; Donovan &

Rossiter, 1982; Eroglu & Harrell, 1986;Eroglu & Machleit, 1990; Eroglu,

Machleit, & Barr, 2005; Hui & Bateson,

1991; Iyer 1989; Levy & Weitz, 2001;

Machleit, Eroglu, & Mantel, 2000b;

Machleit, Kellaris, & Eroglu, 1994;

Oliver, 1993; Reid & Brown, 1996;

Robinson & Nicosia, 1991)

Budget constraintsCrowding at checkout

Perception of shopping trip

ineffectiveness

Routineness of the shopping trip (lack

of entertainment during the shopping

trip)

Promotions’ overload

Increased information search and

information overload




established through IEEE 802.11b. Moreover, a middleware layer was deemed necessary for bridging the

retailer’s backend systems with the Tablet PC. The middleware supported real-time communication among the

system components through SOAP. RF tags were attached to a selected assortment of supermarket products.All tags were encoded following the electronic product code (EPC) specification (Sarma, Brock, & Engels,

2001). A detailed technical analysis of the prototype implementation, as well as its architecture, has been

provided in (Kourouthanassis & Roussos, 2003; Roussos, Gershman, & Kourouthanassis, 2003).

We should highlight that in this research we did not focus to holistically address the entireness of factors

negatively affecting the in-store shopping experience. Instead, we decided to focus on the dimension of

situational factors for reasons that stemmed from budget and time constraints, as well as analysis of past

studies’ findings investigating similar phenomena. For example, studies investigating shoppers’ perceptions

against self-scanning technology [e.g. (Bateson, 1985; Dabholkar, Bobbitt, & Lee, 2003; Meuter, Ostrom,

Bitner, & Roundtree, 2003)] suggested that an IT-facilitated shopping trip improves the efficiency and overall

speed of shopping, especially during checkout. Similarly, user evaluations of personal shopping assistants

(Wolfram, Scharr, & Kammerer, 2004) indicated that pervasive retailing might organize product promotionsbetter and provide a more entertaining shopping session. The following section presents the development of

our research model and discusses our evaluation methodology.

5. Research model elicitation

In our research model, we propose that PIS may have positive effect to seven situational factors that

negatively affect the shopping experience within supermarkets. In effect, past studies revealed that situational

factors are among the prime determinants of stress for supermarket shoppers [e.g. (Arnold, Reynolds, Ponder,

& Lueg, 2005; Aylott & Mitchell, 1998)]. Ineffective budget monitoring has been reported to be one of the

contributing factors to generate stress for shoppers [e.g. (Aylott & Mitchell, 1998; Machleit & Eroglu, 2000a;

Reid & Brown, 1996)]. The development of IT-mediated shopping solutions has proved to positively

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Fig. 1. A conceptual scenario of a pervasive retail information system.




contribute in alleviating the perceptions of time pressure within stores. For example, personal shopping

assistants and personal self-scanners have been reported helping shoppers to continuously monitor the

running price of products they have already placed in their shopping cart thus, feeling ‘in control’ of their total

budget [e.g. (Dabholkar, 1996; Dabholkar & Bagozzi, 2002; Menczer, Street, Vishwakarma, Monge, &

Jakobsson, 2002; Zhu, Owen, Li, & Lee, 2004)]. Therefore, we propose the following hypothesis H1.

H1. Pervasive retail systems may provide a more effective mechanism for budget monitoring compared to thetraditional environment

The majority of consumer studies reported queuing during checkout as the most important stress factor [e.g.

(Aylott & Mitchell, 1998; Bennett, 1998; Chu & Morrison, 2002)]. The introduction of personal self-scanners

successfully managed to relatively speed up the checkout process by giving shoppers the option of scanning

themselves the barcode labels of the products they purchased [e.g. (Dabholkar & Bagozzi, 2002; Dabholkar

et al., 2003; Meuter & Bitner, 1998; Meuter et al., 2000)]. Moreover, new technologies such as RFID-based

self-service terminals and personal shopping assistants promise to further streamline the checkout process by

transparently scanning the contents of the shopping cart at checkout and transmitting all payment-related

data wirelessly to the cashier [e.g. (Loebbecke, 2005; Pramataris, Doukidis, & Kourouthanassis, 2004;

Prater, Frazier, & Reyes, 2005; Smith & Konsynski, 2003; Wolfram et al., 2004)]. Therefore, we propose

hypothesis H2.

H2. Pervasive retail systems may streamline the checkout process compared to the traditional environment.

Perceptions of an ineffective shopping trip in terms of, for example, neglecting to purchase every product on

the shopping list have also been reported to negatively affect the shopping experience [e.g. (Arnold et al., 2005;

Dawes & Rowley, 1998)]. In the past few years, several IT solutions have emerged promising to provide a

more effective shopping trip [see e.g. (Dawes & Rowley, 1998; Pramataris et al., 2004; Wolfram et al., 2004)].

Shoppers may previously load their shopping list to their personal digital assistant (PDA) which may be

equipped with a barcode scanner or an RFID reader. Thus, they may have a tool to remind them of the

products they need to purchase, as well as help them organize better their purchases. Therefore, we propose

hypothesis H3.

H3. Pervasive retail systems may provide increased effectiveness on the overall shopping trip compared to the

traditional environment.

Lack of entertainment during the shopping trip has also been reported to generate negative emotions to the

shopping experience in terms of apathy and stress [e.g. (Arnold et al., 2005; Reid & Brown, 1996; Sit,

Merrilees, & Birch, 2003)]. There are several ways in which IT may contribute to generate more entertaining

shopping trips. Over the past years, retailers have installed multimedia info-kiosks and interactive

advertisement displays in their stores providing an alternative way to reach their customers and reducing

the effect of routine from the conventional shopping trip [e.g. (Boston Consulting Group, 2005; Chu &

Morrison, 2002; Dawes & Rowley, 1998). Similarly, personal self-scanners and shopping assistants have been

reported to stimulate the interest of shoppers and evoke feeling of pleasure and fun especially by shoppers that

are relatively familiar with IT (Dabholkar et al., 2003; METRO Future Store, 2006). Thus, we propose

hypothesis H4.

H4. Pervasive retail systems may provide a more entertaining shopping experience compared to the


The wide assortment of contemporary supermarkets may result to a cognitive information overload, which

may generate stress to shoppers. For example, the novel attributes of new products complicate shoppers

during the evaluation step of their decision making process (Mukherjee & Hoyer, 2001). Additional factors

leading to cognitive information overload include brand confusion (Foxman, Berger, & Cote, 1992; Kapferer,

1995), product positioning (Mitchell & Papavassiliou, 1999), and product proliferation (Quelch & Kenney,

1994). The Internet enabled shoppers to compare the value and properties of competing properties minimising

the sense of confusion during purchases [e.g. (Szymanski & Hise, 2000)]. In the shop floor, multimedia info-

kiosks incorporating barcode scanners enable shoppers to scan products and view useful information such as

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recipes, features, nutritional value, and attached promotions (METRO Future Store, 2006). Personal

shopping assistants provide the same functionality only in a more personalised manner for each shopper

(Menczer et al., 2002; Zhu et al., 2004). Furthermore, they may provide navigation assistance guiding

shoppers during their shopping trip. Based on the above, we propose the following hypothesis H5.

H5. Pervasive retail systems may minimize information search costs for supermarket products compared to

the traditional environment.

Overloading shoppers with too many or too complex promotional messages may also be the source of stress

and confusion. This overload generally results from the accumulated effects of many advertisements, sales

offers, or price deviations among similar products [e.g. (Berne, Mugica, Pedraja, & Rivera, 2001; Biswas &

Blair, 1991; Hardesty & Bearden, 2003; Mitchell & Papavassiliou, 1999; Zeithaml, 1988)]. In the context of

PIS, retailers may place interactive advertisement displays promoting products based on their sales ratio or

time of the day (METRO Future Store, 2006). Personal shopping assistants and PDA-based self-scanners

promise to streamline promotions management by sending only the active promotions to the terminal device

of shoppers and filter them using the shoppers’ buying preferences and current contents of their shopping cart

(Wolfram et al., 2004; Zhu et al., 2004). Therefore, we propose hypothesis H6.

H6. Pervasive retail systems may increase promotions effectiveness during the supermarket visit compared tothe traditional environment.

Finally, Fram (1992), Fram and Ajami (1994) identified time pressure as one of the most prominent

shopping stressors. Aylott and Mitchell (1998) also support this finding in an exploratory study that they

performed in the UK with 239 respondents. However, IT in the form of RFID or barcode-based self-scanners

and personal shopping assistants may decrease the effect of time pressure by streamlining time-consuming

processes such as checkout and alternative products evaluation (Prater et al., 2005; Smith & Konsynski, 2003;

Wolfram et al., 2004). Thus, we propose hypothesis H7.

H7. Pervasive retail systems may reduce the sense of time pressure for supermarket shoppers compared to the


The aforementioned research hypotheses aim to test whether there are significant differences between the‘traditional’ and the ‘tested’ (i.e. PRIS augmented) shopping environments in terms of seven user behaviour-

dependent variables. Subjects were asked to compare the effectiveness of these two environments in terms of

these dependent variables. Likewise, the system services comprise of the manipulated variables aiming to

facilitate user behaviour in terms of the dependent variables (e.g. the ‘‘Product/Promotion Information’’ area

aims to facilitate the information search cost variable). In the remainder of this paper, we discuss the findings of

our field test.

6. Trial preparation and results

Scholtz and Consolvo (2004) proposed an evaluation framework for PIS taking into account the broader

context of a pervasive environment, addressing the social perspective of PIS, and identifying adaptations of

various evaluation methodologies such as self-reporting (Hsieh & Mankoff, 2003), ethnographic techniques

(Intille et al., 2003; Masten & Plowman, 2003), and field experiments. In our case, we employed the latter

approach to evaluate how the pervasive system affects the shopping experience by inviting shoppers to use the

system as part of their shopping in a Greek supermarket.

The field test of the prototype PRIS spanned over a 2-week period. We decided to invite only loyalty club

members due to privacy concerns raised by other participants during the pilot evaluation of the system.

Loyalty club members have already given permission to the supermarket to use their personal information to

receive added value services, such as discounts, and, thus, they represented an ideal group to test the

functionality of the system.

Initially, we prepared the trial environment in terms of (i) selecting the appropriate products, (ii) preparing a

specially modified corridor inside the supermarket, (iii) preparing the technical infrastructure to support the

trial, and (iv) inviting the trial participants. We invited the participants through phone interviews, where we

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also collected their demographic data. We invited 110 participants with total response rate was over 50%.

Sixty loyalty club members agreed to participate in our field experiment. The majority of the participants

(85%) belonged to the age range of 30–54 years old, while 77% of the participants were female. The level of

education was high, with over 71% of the participants having university or higher education. Regarding

familiarity with IT, 66% were relatively familiar with PCs while 15% had never used personal computers

before.The execution of the trial was organized in a sequence of three distinct steps. Initially, the trial participants

were shown the system functionality by a facilitator (10 min). After the end of the system demonstration,

shoppers were prompted to use the system on their own (10–15 min). Shoppers were able to purchase the

products that were displayed in the modified corridor (including the promotions that were displayed by the

system). Following their interaction with the system, the participants completed a questionnaire evaluating the

effect of the system on their shopping experience.

We employed established constructs with high loading factors from past highly cited studies ( Table 3).

Instrumentation validity, internal validity, and statistical conclusion validity was performed following Straub,

Boudreau, and Gefen (2004). Unreliable questions were removed from the respective constructs through the

use of the Cronbach Alpha reliability test (Table 4). We dropped items with values lower that 0.60 as indicated

by Straub et al. (2004). The questionnaire was pre-tested for usability and reliability problems by 17 members

of the store personnel. Normality tests indicated that non-parametric tests have been used for the examinedconstructs due to normality violation. Violation of normality may be attributed to the small sample size.

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Table 3

Questionnaire variables and corresponding items

Examined variable Source No. of items

Budget monitoring Berne et al. (2001) 3

Checkout process Pommer, Berkowitz, and Walton (1980) 3

Shopping effectiveness Childers, Carr, Peck, and Carson (2001) 3

Entertainment Putrevu and Ratchford (1997) 3

Information search costs Putrevu and Ratchford (1997) 3Promotions effectiveness Chandon, Wansink, and Laurent (2000) 3

Time pressure Putrevu and Ratchford (1997) 4

Table 4

Construct reliability results

Nos. Examined variable Pre-test Final test Items dropped

Variables measuring the shopping experience before using the system

SE1a Budget monitoring 0.62 0.68 None

SE2a Checkout process 0.60 0.75 None

SE3a Shopping effectiveness 0.41 0.66 1

SE4a Entertainment 0.64 0.80 None

SE5a Information search costs 0.61 0.68 None

SE6a Promotions effectiveness 0.60 0.69 None

SE7a Time pressure 0.72 0.90 None

Variables measuring the shopping experience after using the system

SE1b Budget monitoring 0.60 0.64 None

SE2b Checkut process 0.86 0.65 None

SE3b Shopping effectiveness 0.81 0.75 None

SE4b Entertainment 0.65 0.69 None

SE5b Information search costs 0.69 0.92 None

SE6b Promotions effectiveness 0.90 0.72 None

SE7b Time pressure 0.80 0.87 None




The analysis of the questionnaires using the Wilcoxon-Signed Ranks non-parametric test ( Hair, Anderson,

Tatham, & Black, 1998) indicated that PRIS statistically enhance the traditional shopping experience on all

the examined hypotheses, namely entertainment, shopping effectiveness, information search costs, checkout

process, time pressure, budget monitoring and promotions effectiveness (Table 5).

All of our research hypotheses have been validated by the trial results. Subjects evaluated their shopping

experience using the system as amusing and pleasant (with over 70% characterizing it as exciting), while 78%of them stated that the system enables them to monitor effectively the products in their shopping cart while at

the same time, organizing their supermarket purchases better. Furthermore, 85% of the participants stated

that the system saves them time to search for additional information or promotional offers regarding the

products they want to purchase.

Although the prototype was not fully integrated within the supermarket, shoppers identified that the use of

such a system will improve the checkout process, while almost all of them stated that they expect to wait less at

the cashiers using such a system. An interesting observation derives from the fact that 89% of the trial

participants stated that waiting less time in the cashiers would influence their decision to shop at a certain

supermarket. Furthermore, shoppers perceived that the system improves the effect of time pressure within the

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Table 5Comparison of consumers’ shopping experience between the conventional and PRIS-augmented shopping environment

Research

hypotheses

Normality test

(Kolmogorov–Smirnov)

Means Wilcoxon

Signed-Ranks

Test

Findings

H1 (budget

constraints)

Conventional: .019 Conventional: 3.12 Z ¼ À5.581 Pervasive retail systems

facilitate shoppers to

monitor their budget

more effectively

Pervasive retail: .000 Pervasive retail: 4.53 Asymp.

Sig. ¼ .000

H2 (Checkout

process)


streamline the check-

out process enablingsupermarket shoppers

to wait less time in

queues


Sig. ¼ .000

H3 (shopping

effectiveness)


make the overall

shopping experience

more efficient


Sig. ¼ .000

H4

(entertainment)


create a more enjoyable

and entertaining

shopping experience


Sig. ¼ .000

H5(information

search)

Conventional: .074 Conventional: 3.24 Z ¼ À5.304 Pervasive retail systemsorganize and present

information regarding

supermarket products

in a more efficient way


Sig. ¼ .000

H6 (promotions

effectiveness)


enhance promotions

effectiveness in the

supermarket


Sig. ¼ .000

H7 (time

pressure)


reduce the sense of time

pressure for

supermarket shoppers


Sig. ¼ .000




supermarket since over 80% responded that the system offers them more time to conduct their shopping, while

at the same time reduces the sense of time pressure and contributes to less hurry in the supermarket.

Regarding the continuous monitoring of the cart total value, 93% of the participants stated that pervasive

retail can help them monitor their budget more effectively and that such a system allows them not to spend

more money than they have budgeted for. Finally, they responded that pervasive retail systems may improve

promotions effectiveness by presenting and organizing product promotions efficiently.

7. Conclusions and discussion

This paper investigates the potential of PIS as a means of enhancing user experience. This hypothesis has

been tested in a field trial of a prototype pervasive system in the context of retail. Our research revealed that

pervasive retail systems can provide a more entertaining and efficient shopping trip compared to the

conventional way of shopping. Our findings compliment existing user evaluation studies of PIS that have been

performed in other application settings [e.g. (Bellotti et al., 2001)] and reinforce the perception that pervasive

technologies may be employed by corporate or public bodies to generate new and positive experiences for

humans. Whether these are related to the utilitarian or affective dimension of the user experience depends on

the profile and expectations of users, as well as the objective of the pervasive system.The results of this study suggest that PIS may be employed as a vehicle for competitive differentiation and

new services provision. In the retail context, PIS may generate multiple benefits. Retailers may have a tool that

enables them to ‘work with their consumers’ making them an indistinguishable part of their operations and

reaching them in a way that they become a real stakeholder, part of their vision for an optimised value chain

(Doukidis, Mylonopoulos, & Pouloudi, 2003). The direct benefits for the retail value chain (including

consumers) deriving from the incorporation of leading edge technologies in the retail arena include among

others:

Real-time information provision regarding the products’ lifecycle within the value chain optimising the

forecasting process of future demand, eliminating out-of-shelf situations, and enabling one-stop-shop

situations. Real-time information provision regarding shopper consumption behaviour providing the ability to

identify and model shoppers’ emerging needs, thus satisfying consumer needs in the most effective way.

Introduction of personalised marketing/promotional programmes, including accurate monitoring of

promotion effectiveness.

However, the most important benefit deriving from the deployment of pervasive retail systems is the

creation of new shopping experiences and consequently, enthusiasm for the consumers. This is particularly

important in the competitive retail sector where the provision of complimentary shopping schemes (e.g. loyalty

club and direct marketing programmes), the advent of the Internet, and the urbanization of nowadays society

have created the new consumer who is more knowledgeable about comparable product costs and price; more

changeable in retail and brand preferences; showing little loyalty; self-sufficient, yet demanding more

information; who holds high expectations of service and personal attention; and is driven by three new

currencies: time, value, and information. This research evinced that pervasive technologies may support these

priorities by organizing more efficiently and speeding up the shopping trip, provide accurate merchandise and

store-related information on a real-time basis, and minimising several important shopping stressors.

The basic limitations of the present study are that the system has not been fully integrated in the

supermarket environment and it has not been tested for a substantial time period. We tested the system on one

supermarket corridor, using a subset of the supermarket assortment and giving the opportunity to the

participants to use the system for a fraction of their supermarket trip. Although the trial resembles a real

shopping visit, a longitudinal study, where we could continuously observe the behaviour of participants for a

substantial time period, would undoubtedly yield important additional findings regarding the lasting effects of

the system on user experience. We acknowledge that the eventual acceptance of pervasive retail systems by

shoppers is also dependent to additional factors that refer to system interoperability and reliability, integration

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with organizational processes and legacy systems, as well as issues related to consumer privacy (Davies &

Gellersen, 2002).

We should also acknowledge that since shoppers had not been exposed to similar innovative shopping

systems before, their high appreciation of the prototype might derive from the fact that they consider it new

and exciting (the well-known ‘honeymoon effect’). Finally, since our research focused on the effect of

pervasive systems to the human experience, we intentionally did not investigate any organizational issuesarising from their deployment. We acknowledge their importance as it is evident in IS literature (Doherty &

King, 2001).

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