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Journal of Retailing and Consumer Services 17 (2010) 205–215

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Journal of Retailing and Consumer Services

0969-69

doi:10.1

� Corr

E-m

a.j.newm

rmichon

(J. Josk1 Te2 Te3 Te4 Te

journal homepage: www.elsevier.com/locate/jretconser

The mediating effects of perception and emotion: Digital signagein mall atmospherics

Charles Dennis a,�, Andrew Newman b,1, Richard Michon d,4, J. Josko Brakus a,2, Len Tiu Wright c,3

a Brunel Business School, Brunel University, Uxbridge, Middlesex UB8 3PH, UKb Salford Business School, University of Salford, Maxwell Building, Manchester M5 4WT, UKc De Montfort University, Leicester Business School, Bede Island, The Gateway, Leicester LE1 9BH, UKd Ted Rogers School of Management, Ryerson University, 350 Victoria Street, Toronto, ON, Canada M5B 2K3

a r t i c l e i n f o

Keywords:

Environmental psychology

Shopping center

Cognitive processing

Atmospherics

Digital signage

Digital communications network

89/$ - see front matter & 2010 Elsevier Ltd. A

016/j.jretconser.2010.03.009

esponding author. Tel.: +44 1895 265242.

ail addresses: charles.dennis@brunel.ac.uk (C.

an@salford.ac.uk (A. Newman),

@ryerson.ca (R. Michon), josko.brakus@brun

o Brakus), lwright@dmu.ac.uk (L. Tiu Wright)

l.: +44 161 295 5324.

l.: +44 1895 26 6844.

l.: +44 116 250 6329.

l.: +1 416 9795000x7454.

a b s t r a c t

Digital signage (DS), public screens showing video, is an important, little-researched topic. The ‘‘direct’’

route in the elaboration likelihood model suggests that DS influences cognition, which then influences

emotions whereas the ‘‘peripheral’’ route is emotion-cognition. We predict that these operate in

parallel and report a survey of mall consumers (n¼315). DS has a significant, positive, total effect on

approach behaviors, mediated by positive affect and (arguably) perception of mall environment. Results

extend the limited capacity model of mediated message processing from television to DS, which

predicts the effectiveness of vivid moving visual images as atmospheric stimuli.

& 2010 Elsevier Ltd. All rights reserved.

1. Introduction

Despite academic research and practitioner experiments over aconsiderable period (see Turley and Milliman, 2000), themechanisms by which people perceive stimuli and convert thoseperceptions into actions are still not fully understood. This paperaddresses the mechanisms through which a stimulus acts bychanging consumers’ perceptions of a mall and increasingemotions such as pleasure and arousal. Given the competitivenature of malls, and the current economic pressure, for a retailmix to be successful, the retail strategy will necessitate contin-uous improvements to a range of factors, including those makingup atmosphere. This paper explores how mall managers canmanipulate stimuli using an exemplar stimulus to increaseconsumers’ ‘‘approach’’ behaviors (i.e., the extent to whichshoppers approach or avoid perceived stimuli). In the retailcontext, approach behaviors may include, for example: spending,intention to revisit and frequency of visits. The stimulus used inthis research consists of digital signage, sometimes known as adigital communications network (DCN), or private plasma screennetwork. Digital signage consists of screens in a public place

ll rights reserved.

Dennis),

el.ac.uk

.

showing video. Content typically includes (e.g.) advertisements,community information, entertainment and news. TV screenshave been used in retail environments for some time but since theadvent of digital control and flat screens, the use of networks ofscreens has made digital signage available as an effective, easilycontrolled communication medium. Referring to digital bill-boards, the Outdoor Advertising Association of America describesthem as: ‘y updated electronically through a variety of methods.Some are networked together, most are operated remotely, and allof them can be updated quickly, sometimes with just the click of amouse. This ability gives digital [signage] flexibility and nimble-ness. This nimbleness gives local businesses a unique andpowerful way to reach a large number of geographically targetedconsumers very quickly’ (OAAA, 2009).

According to Point of Purchase Association International(POPAI), more than 70 percent of purchase decisions are madein store at the point of purchase (Jugger, 1999). Digital signagetherefore aims to talk to shoppers while they are captive and inthe mood to buy. Retailers in countries including the US (e.g.Albertson’s, Kroger, Target), the UK (e.g. Asda, Harrods, Sainsbury,Tesco,) and China (e.g. Carrefour) have launched digital signagenetworks. In addition to pushing merchandise, digital signage alsogenerates hefty advertising revenues. Brand manufacturers payanywhere from $60,000 to $293,000 for a 4-week campaign onWal-Mart’s TV network connecting more than 2500 stores (TheEconomist, 2006). Although research figures are sparse, industryinsiders estimate that digital signage is worth around $2billion inthe US (Computerworld.com, 2008).

Digital signage might be considered as part of ‘‘atmosphere’’.Leo J. Shapiro & Associates, the firm that conducts store

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atmospherics surveys for Chain Store Age (Wilson, 2005) cate-gorizes in-store TV among interactive atmospheric elementshelping retailers building a competitive advantage. Researchindicates that although consumers are generally satisfied withthe convenience, quality, selection and value of today’s retailoffers, they would welcome more product information (Burke,2002). Shoppers tend to consider that they would benefit fromtechnological innovations such as electronic shelf-edge displays(a special case of digital signage) and product information kiosks(which parallel digital signage) (Burke, 2002).

Digital signage is thus an important tool for retail atmo-spherics. Yet, there is little scholarly research into digital signage(for an exception, see Newman et al., 2006). This study thereforesets out to address this research gap. The paper aims to make atheory contribution by exploring processes by which digitalsignage influences perception of mall environment, affect andapproach/avoidance behaviors. There are important implicationsfor mall owners and for retailers, as, if digital signage can bedemonstrated to enhance perceptions of a mall environment,research demonstrates that shoppers transfer perceptions of themall environment to the store images of individual retailers(Chebat et al., 2006), which may significantly impact revenue. Onthe other hand, digital signage content might be designed to elicitpositive emotions directly. People who are in a good mood mayhave a better perception of the retail offer and consequentlyspend more (Puccinelli, 2006).

The remainder of this paper is organised as follows. In thefollowing section, we outline the conceptual framework, addres-sing the extended role of shopping malls beyond simply supplyingproducts, then retail atmospherics, followed by the application ofretail atmospherics to shopping malls. This leads on to considera-tion of the limited prior research on digital signage, where we setthis topic within theory frameworks of the limited capacity modelof mediated message processing (LCM) and elaboration likelihoodmodel (ELM). We then develop hypotheses concerning theeffectiveness of digital signage. Next, we outline the method,model and measurement scales that we use to test thehypotheses. In the ‘Results’ section, we test the hypothesizedmodel and alternatives, exploring the mechanisms by whichdigital signage influences shoppers’ approach behaviors such asspending. After addressing the necessary limitations of the studyand suggestions for further research, we discuss the results,drawing conclusions and commenting on the implications.

2. Conceptual framework

2.1. The role of the shopping mall

Shoppers, of course, use the shopping mall as a convenient wayto obtain goods and services. Nevertheless, as we demonstrate inthis section, consumers also patronize shopping malls for manyless-utilitarian purposes. For example, shopping frequency inmalls is correlated with (among other variables) recreation (Roy,1994); and propensity for unplanned purchases is influenced byhedonic as well as utilitarian considerations (Chebat, 1999).Personal life values also influence mall patronage (Shim andEastlick, 1998). Shoppers patronize shopping centers for walkingand exercise (Hangland and Cimbalo, 1997) and as a social andrecreation meeting place (Graham, 1988). The shopping mall isconsidered as a public place for community development amongnon-shoppers (Lewis, 1990), for the construction of social links(Aubert-Gamet and Cova, 1999), a city within a city (Backes,1997) and as an ecological habitat for consumers (Bloch et al.,1994). Enjoyment and entertainment are important benefits ofshopping (e.g. Babin et al., 1994; Sit et al., 2003; Yoo et al., 1998),

valued by consumers, and reflected in their spending (e.g.Donovan et al., 1994; Jones, 1999; Machleit and Mantel, 2001;Sherman and Smith, 1987; Smith and Sherman, 1993).

Against this background of substantial hedonic motivations forshopping, many older malls have difficulty competing against moremodern ones (Reynolds et al., 2002). The importance of the physicalenvironment has long been recognized (Baker, 1998; Baker et al.,1994, 2002; Bitner, 1990, 1992; Theodoridis and Chatzipanagiotou,2009) and has more recently been extended to that of the shoppingmall (e.g. Chebat and Morrin, 2007). Ways that malls can competeinclude improving the mall environment, making it more pleasur-able place to spend time there, resulting in customers wanting tostay longer and spend more money (Wright et al., 2006). The nextsub-section briefly reviews prior research into ways that marketerscan improve the environment and positively influence shoppers bymanipulating atmospheric stimuli.

2.2. Retail atmospherics

The capacity to alter in-store behavior through retail atmo-spherics is well known by retailers and researchers (e.g. Turleyand Milliman, 2000). Retail atmospherics can be adapted toenhance the likelihood of triggering particular shopping beha-viors. A wide spectrum of shopping behaviors can be influenced ina variety of retail formats. Appropriate music, in particular, has apositive effect on patronage across a range of retail contexts(Garlin and Owen, 2006, in a meta-analysis). Examples include:manipulation of music styles and tempos that impact sales insupermarkets (Herrington and Capella, 1996; Morin et al., 2007);impulse buying in department stores (Yalch and Spangenberg,1990); responses to waiting in banks (Hui et al., 1997); sales inwine shops (North et al., 1999); and music ‘‘fit’’ on perceptions ofan apparel brand (Beverland et al., 2006).

Other examples of patron responses to retail atmosphericsinclude: increased sales due to effective exterior store windows(Edwards and Shackley, 1992); the effect of lighting on thenumber of items handled by shoppers and time spent at a display(Summers and Hebert, 2001); store layout on price perceptions(Smith and Burns, 1996); merchandise arrangement on purchaseintentions in a wine store (Areni et al., 1999); and gender-appropriate scent on perceptions of apparel store environment,merchandise and approach behaviors such as spending (Spangen-berg et al., 2006).

Apart from in-store behavioral response, retail ambianceinfluences a variety of consumers’ emotions and attitudes: theeffect of crowding on shopper satisfaction (Machleit et al., 1994);the mediating effect of the environment on the affective reactionsof department store shoppers (Sherman et al., 1997); theinfluence of color on furniture store displays (Babin et al.,2003); the impact of the general environment on store image ofa card and gift store (Baker et al., 1994); the effect of facilities andproduct assortment on consumers’ pleasant emotions (Yoo et al.,1998); and the effect of redesigning the environment of a dentaloffice on service satisfaction (Andrus, 1986). Babin and Darden(1995) also observe that the effect of a store atmosphere might bemediated by a consumer’s general shopping style thus producingvarious reactions from different segments of consumers.

2.3. Mall atmospherics

We predict that mall atmospherics will not only contribute tobuilding mall traffic, but also promote sales and additionalspending. Based on the environmental psychology paradigm(Foxall and Soriano, 2005; Mehrabian and Russell, 1974), ashopping-congruent atmosphere is expected to put consumers

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in a favorable mood, have them stay longer in the mall, andencourage them to spend more.

Compared with store atmospherics, there are fewer studiesabout how consumers perceive or respond to a mall’s environ-ment. Studies note that the atmosphere can have a major effect onthe perceived attractiveness (Teller and Reutterer, 2008) andimage, which can thus impact on sales performance (Dennis et al.,2002; Finn and Louvi�ere, 1996; Hildebrandt, 1988). Chebat et al.(2006) found that stores significantly benefit from improvementsto a mall’s image including a better atmosphere. Wakefield andBaker (1998) found that the physical environment of the mallgenerates an emotional response in shoppers and can positivelyinfluence both the excitement consumers feel and their desire tostay in a mall. Their research indicates that all environmentalfactors studied, with the exception of the ambient lighting andtemperature, are positively associated to excitement or desire tostay at the mall, or to both. There are a limited number ofpublished papers on consumers’ responses to manipulation ofatmospheric cues in a shopping mall. One notable exception isChebat and Michon (2003), who report the positive effects ofaroma on perceptions of mall environment, positive affect andspending.

2.4. Digital signage as an atmospheric stimulus

As a relative newcomer to the retail environment, digitalsignage networks are now found in the marketing toolbox.Despite the growing commercial importance of digital signage,there is little scholarly research into digital signage. The impact ofdigital signage on consumers’ perception of the environment andconsumers’ responses falls in general within the environmentalpsychology paradigm (Mehrabian and Russell, 1974) and, morespecifically to the digital signage stimulus, the LCM, which modelshow people process television communications, predicting theeffectiveness of vivid moving visual images (Lang, 2000).

We are able to cite only a single published paper on digitalsignage in a scholarly journal: a qualitative study by Newmanet al. (2006), which reports on the acceptability of digital signageto shoppers. The authors find that digital signage creates anambience that influences participants’ perceptions of the mallenvironment, giving it a more modern image. Digital signage addsenjoyment to shopping experiences and provides useful informa-tion, informing shopping choices. There are few objections todigital signage but a minority of the participants consider it to beboring and not attention-grabbing (Newman et al., 2006). On thebasis of the prior research outlined above, research hypothesescan be framed concerning the effectiveness and process of digitalsignage as an atmospheric stimulus influencing shopper behavior.

As outlined in the ‘Retail atmospherics’ sub-section above,environmental stimuli, including music (e.g. Beverland et al.,2006); color (e.g. Babin et al., 2003); lighting (e.g. Golden andZimmerman, 1986); design (e.g. Baker et al., 2002); and aroma(e.g. Ellen and Bone, 1998), induce emotions that in turn influenceapproach/avoidance behavior (Mehrabian and Russell, 1974).Alternatively, Chebat and Michon (2003) suggest that the effectsof atmospheric cues on consumers’ emotions and behavioralresponses are initially mediated by cognition (e.g. Lazarus, 1991).In the case of the digital signage stimulus, the two competingapproaches are not necessarily mutually exclusive but are bothconsistent with the ELM of Petty and Cacioppo (1986), which hasbeen extensively studied in the field of advertising. The appeal canbe either rational or emotional. The rational appeal may be moreeffective when the elaboration likelihood of the communicationsituation is high, i.e. when shoppers stop to watch the digitalsignage and perceive specific information. Under these conditions,

a consumer’s cognitive responses will determine the behavioraloutcome – the ‘central route’. Alternatively, when the elaborationlikelihood is low, i.e. when the digital signage is perceived asbackground ‘wallpaper’, perhaps with pleasant scenes, consumerswill not process messages cognitively but may still be influencedemotionally and this emotional appeal may still positivelyinfluence approach behavior – the ‘peripheral route’. Advertisingresearch over past decades has produced many examples of boththe rational appeal (e.g. Golden and Johnson, 1983) and theemotional appeal (e.g. Page et al., 1990) being claimed to be moreeffective, with other scholars accepting that the two types ofappeal are not mutually exclusive (e.g. Puto and Wells, 1984).People tend to rely on feelings as a way of simplifying judgmentthat operates mainly in the peripheral mode – the ‘‘how do I feelabout it’’ or ‘‘feelings-as-information’’ heuristic, in which peopleequate pleasant feelings as evidence of liking and satisfaction(Pham, 2004). This mechanism tends to operate by default and isonly questioned if an alternative explanation for their feelings ismade obvious (Gorn et al., 1993). Irrelevant of the competingemotion-cognition (Zajonc and Markus, 1984) or cognition-emotion (Lazarus, 1991) theories, marketers can manipulateatmospherics to improve consumers’ images of a location andincrease spending.

As mentioned in the section above, there is limited research onthe effect of digital signage. By implication, in accordance with theLCM (Lang, 2000), which holds that people have limited cognitiveresources to process many information simultaneously andtherefore allocate processing resources to those most demandingstimuli that have a high information rate and distinctive featuressuch as movement, color and vividness (Li and Bukovac, 1999),digital signage should act as a more effective atmosphericstimulus, with higher recall of messages than those that arestatic or less vivid (Taylor and Thompson, 1982). Moving imagesattract viewers’ attention (Reeves and Nass, 1996). These priorfindings support the LCM in this context.

Research on store perception suggests that, at least for hedonicproducts such as perfume, jewellery and gifts, store atmosphereaffects perceptions of product quality (Schlosser, 1998). Hedonicbenefits are more likely to increase positive affect and loyalty thanutilitarian ones (e.g. Chitturi et al., 2008) and hedonic aspects areplaying more part in shoppers decisions even for discount shopping(Carpenter and Moore, 2009), so we expect that a pleasantatmosphere will be increasingly relevant for all types of shopping.

Relevant background perceptions tend to be perceived only ina general or ambient manner and there is no guarantee that anyspecific component of the perception of the environment willactually be evaluated individually (Jacoby, 2002). Perception ofthe environment can be considered as a ‘‘package’’ of interactingcomponents (Jacoby, 2002). Therefore, the atmosphere or back-ground may be manipulated to ‘‘prime’’ people’s perceptions andthus change behavior in such a manner that they may or may notbe aware of the presence of the stimulus (Dijksterhuis et al., 2005;Mandel and Johnson, 2002). Even though consumers may paylittle attention to digital signage, they are likely to perceive it andits content as part of the atmosphere background. This priming islikely to increase choice and spending (Mandel and Johnson,2002). Accordingly, an atmospheric stimulus such as digitalsignage may affect other components of the perception of themall environment, such as the cleanliness. According to the LCM(Lang, 2000), the moving images of digital signage shouldconstitute an effective atmospheric stimulus that may influenceconsumers’ images of the shopping environment, for exampleproviding information. Newman et al. (2006) report that con-sumers value the information content of digital signage in helpingwith their shopping decisions. Any means that helps people withfluent decision processes is likely to result in increased liking

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ApproachBehavior

H1

Perceptionof Mall

Environment

PositiveAffect

H2DigitalSignage

H1

Fig. 1. Schematic representation of hypotheses H1 and H2.

C. Dennis et al. / Journal of Retailing and Consumer Services 17 (2010) 205–215208

(Schwarz, 2004). This is consistent with the conventionalconceptualization of decision making processes that involvesconsciously applying rules governing actions in response tostimuli (Berkowitz, 1993).

Alternative evidence can be presented in support of the claimthat atmospheric stimuli influence emotion (Donovan andRossiter, 1982) and that emotion influences cognitive perceptionsand approach behavior (Zajonc and Markus, 1984). This argumentis consistent with the peripheral route of the ELM (Petty andCacioppo, 1986) and the ‘‘how do I feel about it’’, feelings-as-information heuristic (Pham, 2004). The process of directinfluence of stimuli on emotion may follow the ‘‘relatively basicand automatic y processes’’ that snap into play before cognitivethinking can get started (Berkowitz, 1993, p. 12; see also Ullman,1984). In this conceptualization, relevant digital signage content(e.g. pleasant scenes) may positively influence emotion directly.

Prior research on advertising (e.g. Petty and Cacioppo, 1986)and shopping mall environmental psychology (e.g. Chebat andMichon, 2003) has tended to assume that cognition-emotionand emotion-cognition are separate processes. On the otherhand, Berkowitz’s (1993) work on anger, consistent with Epstein’s(1993) Cognitive-Experiential Self-Theory, suggested that the twotend to work in parallel in response to any particular stimulus: abasic, rapid system based on the unconscious emotional responseand a more deliberative, sophisticated cognitive process. Inproduct choice decisions, these routes can work together.Consistent with the LCM, in conditions where the resources ofcognitive processing are limited (which may be the case whenshoppers are coping with parallel with tasks such as work orfamily responsibilities), spontaneous emotional response to astimulus has a greater effect on choice. On the other hand, whenmore cognitive processing resources are available (perhaps whenon a dedicated shopping-for-pleasure trip), cognition has moreimpact (Shiv and Fedorikhin, 1999). Clearly, in the case of theshopping mall, both conditions can apply and we thereforepredict that digital signage influences both cognition andemotion; and that cognition and emotion both influence con-sumers’ approach behaviors. We consider both positive affect andpositive cognitive evaluations, so (again following Shiv andFedorikhin, 1999), we predict that positive affect and positivecognitive evaluations will act together to increase approachbehavior. A stimulus such as digital signage is expected to haveboth cognitive and affective elements, both of which can influenceapproach behavior.

We predict that various types of content on digital signage caninfluence both cognition and emotion; and that, in accordancewith the above argument, cognition and emotion can operate inparallel to influence consumers’ approach behaviors. A stimulussuch as digital signage is expected to have both cognitive cues,such as providing information about stores and products; andaffective elements such as pleasant scenes, both of which caninfluence approach behavior. The research hypotheses areformalised in the next section.

3. Research hypotheses

We hypothesize that mall atmospherics will not onlycontribute to building mall traffic, but also promote sales andmotivate additional spending. Based on the environmentalpsychology paradigm (Mehrabian and Russell, 1974; Donovanand Rossiter, 1982), a shopping-congruent atmosphere isexpected to put shoppers in a favorable mood, encourage themto visit more frequently and to spend more.

We expect that, according to the LCM (Lang, 2000), the movingimages of digital signage should constitute an effective

atmospheric stimulus that may influence shoppers’ images ofthe shopping environment. Digital signage should constitute aneffective marketer-manipulable atmospherics stimulus, increas-ing positive affect and positive perceptions of the mall environ-ment. We therefore predict that:

H1. Digital signage will positively influence positive affect andpositive perceptions of the mall environment.

The environmental psychology paradigm has been previouslytested in a retail setting (e.g. Chebat and Michon, 2003). Theperception of a pleasant shopping environment (Dube and Morin,2001) should elicit positive emotions such as pleasure and arousal(Ang et al., 1997) and result in higher spending (Spies et al., 1997). Inline with this, Puccinelli (2006) finds that people who are in a goodmood have a better perception of products and are willing to spendmore money. Similarly, Fedorikhin and Cole (2004) report thatpositive mood leads to lower perceived risk and influencesconsumers’ choices towards trying new products. Those authorsalso find that the effect is greater when consumers’ constructiveprocessing is higher, which we consider describes the condition ofconsumers’ comparison shopping in a mall. These prior empiricalfindings and the conceptual considerations in the ‘Digital Signage asan Atmospheric Stimulus’ section above lead us to postulate thatcognition-emotion and emotion-cognition combine to make upthe main influences on approach behavior. In other words:

H2. The effect of digital signage on shoppers’ approach behaviorswill be fully mediated by positive affect and positive perceptionsof the mall environment.

The research hypotheses are summarized in Fig. 1.

4. Method

4.1. Research setting

The method consisted of the trial installation of digital signagescreens and an associated questionnaire survey at an in-town,sub-regional shopping mall near London, UK. In this quantitativesurvey, we measured reported shopper spending and othervariables using questionnaire responses. We eschewed retailersales data in order to avoid anomalies caused by (e.g.) weather,interest rates and competitor advertising that would haveconfounded the results. The mall consists of a single level witha typical blend of retail provision and services. In addition to the

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usual apparel and other comparison retailers, the mall alsoincludes a drugstore and a grocery supermarket, making shop-pers’ trip purposes more typical of shopping in general (Arentzeet al., 2005; Dellaert et al., 1998). Most atmospherics researchuses simulations rather than real retail environments and studentrespondents rather than typical shoppers (for an exception, seeSpies et al., 1997). For this study, we obtained rare access to datafrom real mall customers in a real shopping environment.

The survey instrument was a self-report questionnaire,requiring respondents to rate the digital signage screens andtheir content, plus the mall and various emotions. The designutilized 5-point Likert-like scales (e.g. very poor to very good). Thequestionnaire grouped variables into core themes: perception,pleasure-arousal, approach-avoidance, and general demographics.

A plasma screen digital signage network was installedespecially for the trial, which consisted of a 1-week familiarisa-tion plus 2 weeks evaluation. The digital signage consisted of 12,1.2-m plasma screens distributed around the public areas, plusadditional screens placed in the stores of 10 participating retailers– making up 22 screens in total. The participating stores were (i) amen’s apparel store, (ii) a young women’s accessories store,(iii) a children’s apparel store, (iv) a children’s learning/toy store,(v) a music and media store, (vi) an electronics store, (vii) anoptician and optical store, (viii) the drugstore, (ix) a cafe, and (x) aluxury chocolates store with cafe.

Broadcast content consisted of 200 messages sourced partlyfrom promotional material from the mall operator and the retailstores (from both those with, and some without, screens in theirstores); and partly new material. The new material on the screensin the mall areas included information about the mall’s facilitiesand public information about external services such as the towntheatre and farmers’ market. Screens in the participating retailstores mainly carried content specific to those retailers but somealso carried selected general information.

Selection of the sample was problematic. Should the studyaims have sought to explicate a more representative and randomsample, this would have called for a postal survey. Following thisroute would have placed the study in danger of under-represent-ing the more frequent users of the mall. The findings concern mallshoppers, and the results have implications for mall managers.Therefore, the sample was as representative as practicable of themall’s customers. A convenience mall intercept survey achievedthe desired sampling technique (vis-�a-vis omitting non-customers).Howard (1992) and Hackett and Foxall (1994) use a similarmethod for comparing shopping malls. This sampling provideshigh quality data that can be as accurate as other methods (Bushand Hair, 1985). The technique is more likely to select respon-dents who stay longer, and therefore is weighted so as to be morelikely to be representative of mall shoppers’ approach behaviorsthan would be a true random sample (Nowell and Stanley, 1991).

Researchers intercepted respondents near three coffee shopsor in the general mall concourse. Respondents self-completed thequestionnaire in order to minimise bias from the interviewer(although a researcher was on hand to help if necessary).Fieldwork spanned 2 weeks and most opening times, with twoor three researchers working at the times when the mall was,respectively, busier and busiest, in order to approximate morerepresentation in the sample at the busiest shopping times. Inorder to simulate the conditions of a permanent installation(where almost all shoppers would be expected to be aware of thedigital signage), respondents were pre-screened based onwhether they had seen the screens (92 percent had). Theresponses consisted of 315 completed questionnaires (afterdeducting the eight percent of shoppers approached who hadnot seen the screens). This sample comprised 73 percent females.Females were thus sampled approximately proportionately to

their anticipated spending in the mall, based on owners’ data. Thenumber classified in the higher socio-economic status of manage-rial, administrative, professional, supervisory or clerical was 57percent. This compared, for example, with this mall owner’s owndata of 63 percent and other typical in-town malls down to 55percent (Dennis, 2005). The proportion in the older age groups of45 years and over was 51 percent (in line with the mall owner’sexpectations of ‘‘around 50 percent’’). It was therefore consideredthat the range of socio-economic groupings and age profiles wereas representative as practicable of consumers at the mall.

In order to compare the results for the digital signage at themall with a control location that does not have digital signage, themethod followed the approach of McGoldrick and Thompson(1992) and Dennis (2005), by requiring respondents to similarlyrate an alternative control shopping location, the one at whichrespondents shopped most (or next most after this mall).Respondents thus rated both the test mall and the control andthe items used are based on the differences between them. Forexample, for ‘pleasure’, the rating for ‘pleasure’ for the controlshopping location (1–5 scale) was subtracted from the rating for‘pleasure’ for the test mall (with 5 added to each value to ensurethat all values were positive), making a 9-point scale (which werescaled 0–1 for use in the model). None of the control locationswas equipped with digital signage screens.

4.2. Models and measurement scales

The next step investigated if and how digital signage influencesconsumers’ positive affect, perception of the mall environment andapproach behavior. This was done through latent path structuralequation modeling (SEM) using SPSS AMOS (Arbuckle, 2006). TheSEM analysis illustrates mediation and the indirect effects of thedigital signage on consumers’ behavioral responses.

Four scales were used in this study: consumers’ evaluations ofdigital signage, perception of the mall environment, positiveaffect, and approach behavior. All scales were taken from theliterature and were based on multiple-item measurements. Weare unaware of any prior scale for digital signage, so we based thismeasurement on those previously reported for other stimuli suchas aroma (e.g. Ellen and Bone, 1998). Scales were first subjected toexploratory factor analysis (EFA) (ensuring that the scales loadedas distinct variables) before being re-screened through confirma-tory analysis and introduced into the structural model. Inaccordance with Bollen (1989, p. 244) and Kline (2005, p. 314),a limited number of the latent variable indicators were kept in thepath analysis, selected for their higher loading in the EFA. Table 1outlines the measurement scales with selected items, alphacoefficients, factor loadings and sources.

The relationship between latent variables representing con-sumers’ perception of the mall environment, positive affect andapproach behavior was investigated in a path analysis (Fig. 2). Inline with the argument above that cognition-emotion andemotion-cognition tend to work in parallel, we predict thatpositive affect and positive perception of the mall environmentwill have a parallel effect on approach behavior. Notwithstandingthis, because perception of the mall environment and positiveaffect are conceptually (and empirically) distinct constructs, wedo not combine them into a single variable. Rather, in order todemonstrate their parallel effects and neutralize the likely co-linearity problem arising from the parallel effects, we constrainthe path coefficients of their effects on approach behavior to beequal. In passing, we speculate that the likely co-linearity arisingfrom the parallel effects may well contribute to the inconsistencyof previous research results reported for cognition-emotion vs.emotion-cognition directions in previous studies.

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Table 1Measurement scales.

Digital signage- Perception mall environment- Positive affect- Approach behavior

Explained variance (%) 18.0 16.3 18.0 11.2

Alpha .83 .77 0.82 0.69

Perception of digital signage (Ellen and Bone, 1998) very poor/very good

Community information .90

Information on special events .89

Entertainment .87

What do you think of the digital signage overall .55

Perception of mall environment (McGoldrick and Thompson, 1992) very poor/very good

Covered shopping .80

Cleanliness .76

Availability of good restrooms .75

Affective security in the mall and car park .69

Affect (Mehrabian and Russell, 1974)

Unhappy/happy .81

Melancholic/contented .81

Dissatisfied/satisfied .80

Unstimulated/stimulated .71

Approach behavior (Adapted from Donovan and Rossiter, 1982; Dennis, 2005; Chebat and Michon, 2003)

Frequency of visits .80

Likelihood of revisiting soon, very unlikely/very likely .69

Spending (non-food) 0.68

Principle components extraction, varimax rotation.

Based on 5-point questionnaire scales (except for approach: frequency of visits and spending, which are scale variables).

ApproachBehavior

0.20(3.3)

Perceptionof Mall

Environment

PositiveAffect

DigitalSignage

DigitalSignageOverall

CommunityInformation

SpecialEvents

Entertainment

0.15(2.2)

0.24(3.1)

0.90(7.1)

0.90(7.1)

0.78(6.9)

0.40(N/A)

CoveredShopping Cleanliness

RestroomsSecurity

HappyContentSatisfiedStimulated

Frequencyof Visits

RevisitSoon

Spending

0.74(8.9)

0.75(8.5)

0.66(8.0)

0.56(N/A)

0.73(10.3)

0.79(10.8)

0.78(10.8)0.64

(N/A)

0.47(3.3)

0.39(2.8)

0.77(N/A)

0.22(3.3)

Fig. 2. Latent path analysis (testing H1 and H2). Standardized coefficients (Z-value). Method: ML, Chi-square¼175.5, df¼87, CFI¼ .94, RMSEA¼ .057.

C. Dennis et al. / Journal of Retailing and Consumer Services 17 (2010) 205–215210

5. Results

The latent variable path analysis outlines the relationshipsbetween the stimulus (digital signage) and consumers’ response.The SEM exhibits an excellent goodness of fit (w2

¼175, df¼87,CFI¼ .94, RMSEA¼ .057). Digital signage has a significant directinfluence on perception of the mall environment (standardized

coefficient¼ .24, critical ratio (C.R.)¼3.1) and positive affect(standardized coefficient¼ .15, C.R.¼2.2. In turn, perception ofthe mall environment (standardized coefficient¼ .22, C.R.¼3.3)and positive affect (standardized coefficient¼ .20, C.R.¼3.3)together have a significant effect on consumers’ approachbehaviors (it is the unstandardized rather than the standardizedcoefficients that are constrained equal). The modification indices

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(MIs) indicate that no additional paths are suggested except forsuggested paths in both directions perception of the mallenvironment-positive affect (MI 37.0, par change 0.38) andpositive affect-perception of the mall environment (MI 38.8, parchange 0.38). These are the paths that would be expected bothfrom conventional cognition-emotion and competing emotion-cognition paths rather than the hypothesized model, which willbe explored later, below. The SEM shows that the influence ofdigital signage on consumers’ behavior is mediated by perceptionof the mall environment and positive affect. The structural modeldoes not hint at the possibility of any partial mediation (Fig. 2).The total effect of digital signage on approach behavior (.08) issignificant. Hypotheses H1 and H2 are supported.

In following the common shorthand claiming support for ourhypotheses, we have not, of course, demonstrated causality, onlyan association: ‘‘data do not confirm a model, they only fail todisconfirm it’’ (Cliff, 1983). Indeed, Editor (2001) points out thatwhen a model is not disconfirmed, there may be many othercompeting (but untested) models that are not disconfirmed aswell. Accordingly, in order to address such considerations, wehave tested alternative models from competing theory frame-works. First, we fitted a conventional environmental psychologycognition-emotion model (Fig. 3). This SEM also exhibits anexcellent goodness of fit (w2

¼131.5, df¼87, CFI¼ .97,RMSEA¼ .040). Digital signage has a significant direct influenceon consumers’ perception of the mall environment (standardizedcoefficient¼ .23, C.R.¼3.10). Consumers’ perception of the mallenvironment influences consumers’ emotions (coefficient¼ .47,C.R.¼5.48). In turn, consumers’ affect impacts approach behavior(coefficient¼ .36, C.R.¼3.57). The modification indices (MIs)indicate that no additional paths are suggested. In thisalternative conceptualization, testing for mediation (Baron andKenny, 1986; Iacobucci et al., 2007), the SEM shows that theinfluence of digital signage on consumers’ behavior is mediatedby consumers’ perceptions and emotions. The structural modeldoes not hint at the possibility of any partial mediation. Applyingthe same test also indicates that the effect of digital signage onconsumers’ emotions is also fully mediated. Nevertheless, wehesitate to confirm this conclusion as there is both conceptual and

0.23(3.1) Perception

of MallEnvironment

DigitalSignage

DigitalSignageOverall

CommunityInformation

SpecialEvents

Entertainment

0.4(5.

0.90(7.1)

0.90(7.0)

0.78(6.9)

0.40(N/A)

CoveredShopping

Cleanliness

Restrooms Security

0.73(8.6)

0.76(8.7)

0.66(8.2)

0.56(N/A)

Fig. 3. Latent path analysis (cognition-emotion conceptualization). Standardized coef

empirical support for this direct link, illustrated in Fig. 2. Later inthis section we test an alternative model suggested by the MIsand are unable to disconfirm the direct link stimulus-emotion.

As the literature does not fully resolve the competingtheoretical approaches of the direction cognition-emotion vs.emotion-cognition, an alternative emotion-cognition model isalso fitted to the results for comparison. This SEM emotion-cognition model exhibits a similar goodness of fit to thecognition-emotion model (w2

¼147.0, df¼87, CFI¼ .96,RMSEA¼ .047) with all paths significant (Fig. 4).

Nevertheless, with this model, the MIs suggest the addition ofpaths that would add elements of cognition-emotion. These are:digital signage-perception of the mall environment (MI¼6.4, parchange¼ .23); and positive affect-approach behavior (MI¼5.2,par change¼ .36). If these two paths are added to the model, thefit is still good (w2

¼130.0, df¼85, CFI¼ .97, RMSEA¼ .041) but thepath perception of the mall environment-approach behaviorbecomes non-significant (Fig. 5). In this version of the model, theinfluence of digital signage on approach behavior is not mediatedby perception of the mall environment, calling into question thispart of H2. With this modified emotion-cognition model, thestandardized total effect of digital signage on approach behavior(.07), emotions (.14) and perception of the mall environment (.23)remains significant. This pragmatic data-driven model (includingthe path direction emotion-perception of the mall environment)includes a significant path directly from digital signage toemotion (standardized coefficient¼ .14, C.R.¼2.1). These resultslend support to the direct influence of the atmospheric stimuluson positive affect, which is more clearly conceptualized in ouroriginally hypothesized model illustrated in Figs. 1 and 2.

In the data-driven model in Fig. 5, the path perception of themall environment-approach behavior is non-significant. Forcomparison, we also report that, if the constraint in our originallyhypothesized model, that positive affect and perception of themall environment act in parallel and are constrained equal, isrelaxed, the path perception of the mall environment-approachbehavior becomes non-significant (standardized coefficient 0.11,C.R. 1.4). These two interpretations would seem to suggest thatperception of the mall environment would have no influence

ApproachBehavior

PositiveAffect

75)

0.36(3.6)

Happy Content

Satisfied Stimulated

Frequencyof Visits

RevisitSoon

Spending

0.73(10.3)

0.79(10.8)

0.73(10.7)

0.65(N/A)

0.47(3.4) 0.39

(2.8)

0.78(N/A)

ficients (Z-value). Method: ML, Chi-square¼131.5, df¼87, CFI¼ .97, RMSEA¼ .040.

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ApproachBehavior

0.16(2.3) Perception

of MallEnvironment

PositiveAffect

DigitalSignage

DigitalSignageOverall

CommunityInformation

SpecialEvents

Entertainment

0.48(5.7)

0.23(2.2)

0.90(7.1)

0.90(7.0)

0.78(6.9)

0.40(N/A)

CoveredShopping

Cleanliness

Restrooms Security

Happy Content

Satisfied Stimulated

Frequencyof Visits

RevisitSoon

Spending

0.72(10.3)

0.80(10.8)

0.77(10.7)

0.65(N/A)

0.72(8.1)

0.78(8.7)

0.64(8.1)

0.56(N/A)

0.56(4.0) 0.46

(3.8)

0.65(N/A)

Fig. 4. Latent path analysis (emotion-cognition conceptualization). Standardized coefficients (Z-value). Method: ML, Chi-square¼147.0, df¼87, CFI¼ .96, RMSEA¼ .047.

ApproachBehavior

0.14(2.1)

Perceptionof Mall

Environment

PositiveAffect

DigitalSignage

DigitalSignageOverall

CommunityInformation

SpecialEvents

Entertainment

0.17(2.4)

0.10(1.1)

0.90(7.1) 0.90

(7.0)

0.78(6.9)

0.40(N/A)

CoveredShopping

Cleanliness Restrooms

Security

Happy

Content

Satisfied Stimulated

Frequencyof Visits

RevisitSoon

Spending0.73(10.3)

0.79(10.8)

0.77(10.8)

0.65(N/A)

0.73(8.6) 0.76

(8.7)

0.65(8.2)

0.56(N/A)

0.46(3.3)

0.38(2.8)

0.80(N/A)

0.16(2.3)

0.44(5.4)

Fig. 5. Latent path analysis (alternative modified stimulus-emotion version). Standardized coefficients (Z-value). Method: ML, Chi-square¼130.0, df¼85, CFI¼ .97,

RMSEA¼ .041.

C. Dennis et al. / Journal of Retailing and Consumer Services 17 (2010) 205–215212

(direct or indirect) on consumers approach behavior. This isconceptually inconceivable and inconsistent with the conven-tional environmental psychology model in Fig. 3. We cannotdisconfirm that the perception of the mall environment influencesconsumers approach behavior and therefore, on balance, considerthat our originally hypothesized model in Figs. 1 and 2 is mostpreferred. We would most likely attribute the non-significantpaths perception of the mall environment-approach behavior inalternative models to the expected co-linearity due to thehypothesized parallel effects of perception of the mall environ-ment and positive affect. In other words, we cannot disconfirm

the positive effects of digital signage on perception of the mallenvironment and positive affect and the mediating effects ofperception of the mall environment and positive affect on therelationship between digital signage and consumers’ approachbehavior (although the mediating effects of perception of the mallenvironment can be questioned).

The possibility of a direct stimulus-positive affect link is animportant one, which we are unable to reject. In terms of the ELM,the cognition-positive affect model in Fig. 3 represents thecentral route, where information provided by the digital signageis valued by consumers and used in their cognitive responses to

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determine their behavioral outcomes. Nevertheless, shoppers maynot always be aware of all the information content on the digitalsignage (in fact, the majority were unable to recall a specificindividual store’s content featured). In addition to providinginformation, the digital signage may also act as a backgroundwallpaper constituent of the mall atmospherics. The alternativemodel with the direct stimulus-positive affect path in Fig. 5 (andthat part of the originally hypothesized model in Figs. 1 and 2) isin accordance with the peripheral route, where processing of thestimulus relies upon the way in which it is presented, rather thancognitive processing. If relevant content on digital signage caninfluence positive emotions directly, then, in line with thefeelings-as-information heuristic, in the absence of any discon-firmation, consumers will interpret the pleasant feelings asrepresenting satisfaction, which should positively influenceapproach behaviors, as in the models in Figs. 2 and 5. In thisinterpretation, non-significance of the perception of the mallenvironment-approach behavior path would be expected;because consumers use feelings-as-information, they have lessneed for the cognitive perceptions in taking their shoppingdecisions.

6. Limitations and further research

Before closing, we add a necessary note of caution in theinterpretation of our results. First, this study is cross-section andhas modeled the effects of preferences for digital signage ratherthan its presence or absence. Further experimental studies arecalled for.

Second, Editor (2001) points out that when a model is notdisconfirmed, there may be many other competing (but untested)models that are not disconfirmed as well. Accordingly, in order toaddress such considerations, we have tested alternative modelsfrom competing theory frameworks, which we are unable toreject. We recommend further research, particularly longitudinal,to evaluate competing models.

7. Discussion, conclusions and implications

The environmental psychology paradigm linking atmosphericstimuli to perceptions of a retail environment, positive affect andapproach behavior is not new to retail atmospherics (althoughseldom applied for malls). Ample research (e.g. Chebat andMichon, 2003; Dube and Morin, 2001; Sherman et al., 1997) hasshown that environmental cues will impact consumers’ cognitionand emotions, and trigger some approach behavior. What is newhere is the advent of digital signage in the retail atmospherictoolbox as a stimulus with a substantial effect, as predicted by theLCM. Digital signage has a dual usage: it conveys informationwhen and where shoppers are in the mood to shop (the centralroute of the ELM), and has an affective or entertainmentcomponent (the peripheral route). These results indicate thatdigital signage is an effective stimulus, adding to positiveperceptions of the mall environment, emotions and approachbehavior such as spending, as predicted by the LCM. The resultstherefore extend the applicability of the LCM from television todigital signage.

People who are in a good mood before shopping may have abetter perception of the products that they see and consequentlyspend more (Puccinelli, 2006). Marketers can enhance thatprocess using sensory stimuli that positively influence consumers’moods leading to more spending. This effect is consistent acrossour parallel model (Figs. 1 and 2) and the competing cognition-affect (Fig. 3) and alternative affect-cognition (Fig. 5) models.

Digital signage content can be designed to provide information toshoppers that they consider to be useful (such as communityinformation or store-specific offers). This information will beprocessed and have a positive effect on consumers approachbehaviors (central route). On the other hand, content may also bedesigned to impact on consumers’ emotions directly (e.g. pleasantscenes). This type of atmospheric stimulus need not be processedcognitively but nevertheless, will impact positive emotion andalso positive approach behavior (peripheral route, feelings-as-information).

Previous research indicates the effectiveness of only fewsensory stimuli significantly associated with increased spending(e.g. aroma, Chebat and Michon, 2003; and music, Mattila andWirtz, 2001, in a store setting rather than a mall). This study addsa new stimulus, digital signage, as an important tool that mallowners may utilize.

Putting the size of the effect of the digital signage intoperspective, we estimate that the digital signage has lessinfluence on approach behavior than do cleanliness, securityand helpfulness of staff; but more than the mall’s layout,restrooms, or the range of merchandise available. The resultsdemonstrate higher levels of approach behavior (raised by anestimated 1.5 percent), equivalent to increased levels of spend orlike-for-like retail sales. Achieving the same result throughimprovements to design, decor and extensions could cost aregional mall over $20 million. The installation of the digitalsignage has a manipulable effect on the internal surroundingsleading to improvements in consumers’ perceptions of the mall.The magnitude of the effect of the digital signage may soundsmall, but should be viewed in the light of our estimate that, atleast in the long term, the improvement in sales figures could beworth around $1 million per year in extra rental income for aregional shopping mall.

Regardless of the mechanism (parallel vs. stimulus-cognitionvs. stimulus-emotion), digital signage has a significant, positive,total effect on perception of the mall environment, positiveemotion and approach behaviors. The contribution of this paper isto add digital signage to the short list of successful mallatmospheric stimuli and demonstrate the mediating effects ofemotion. The results also extend the limited capacity model ofmediated message processing (LCM) from television to digitalsignage, which predicts the effectiveness of vivid moving visualimages as atmospheric stimuli.

Acknowledgements

The authors thank the mall owners for providing access andfacilities; and Globecast and How and Why Ltd. for a generousresearch grant.

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