Farhod.karimov - Adoption of Social Media by Online Retailers

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    January-March 2011, Vol. 2, No. 1

    S I M

    GE Pi E-Agenda 2020: Where Do We Go from Here? Uncovering Future E-Business

    Opportunities for Entrepreneurs and Innovators Tobias Kollmann, University of Duisburg-Essen, Germany Andreas Kuckertz, University of Duisburg-Essen, Germany

    R A

    1 Megatrends in Electronic Business: An Analysis of the Impacts on SMEs Marko Ovaskainen, Central Ostrobothnia University of Applied Sciences, Finland Markku Tinnil, Aalto University School of Economics

    16 Innovative Electronic Business: Current Trends and Future Potentials Tobias Kollmann, University of Duisburg-Essen, Germany Patrick Krell, University of Duisburg-Essen, Germany

    26 Adoption of Social Media by Online Retailers: Assessment of Current Practices andFuture Directions

    Farhod Karimov, Vre Universiteit Brussels, Belgium Malaika Brengman, Vre Universiteit Brussels, Belgium

    46 Change for Entrepreneurial Chances? E-Government in the European Union

    2020 and 2040 Ina Kayser, University of Duisburg-Essen, Germany

    InternatIonalJournalof

    e-entrepreneurshIpand

    InnovatIon

    Table of Contents

    http://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeeihttp://www.igi-global.com/ijeei
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    26 International Journal of E-Entrepreneurship and Innovation, 2(1), 26-45, January-March 2011

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    Keywords: Content Analysis, E-Commerce, Social Cue, Social Media, Social Presence, Website Design

    INTRODUCTION

    Forecasting how rapidly tchnologies will ad-vance and how society will use them is not aneasy task. While a decade ago, many scholarspredicted that by offering 24x7 online services,internet retailing would be superior and wouldreplace traditional retailing instantaneously(Peterson et al., 1997; Swinyard, 1997), currentU.S. e-commerce sales still only account for3.4 percent of total retail sales (U.S. Census

    Adoption of Social Media

    by Online Retailers:Assessment of Current Practices

    and Future Directions

    Farhod P. Karimov, Vrije Universiteit Brussel, Belgium

    Malaika Brengman, Vrije Universiteit Brussel, Belgium

    ABSTRACT

    In the online environment, the absence of social presence may prevent consumers from purchasing online,while it can enhance their trust, loyalty and enjoyment toward the e-retailer. Thus, today many online retailerstry to create social presence by adopting media-rich technologies. In this paper, the authors assess to whatdegree social media cues are currently adopted by thriving web-vendors and on that basis speculate aboutfuture developments. To this purpose, 210 top B2C e-commerce websites have been content analyzed to iden-tify how they differ in the deployment of diverse social media cues. While a wide range of social media cuesare adopted by a majority of top e-retailers, a number of more advanced social media features like avatars,recommendation agents, and video-streams are in their infancy where adoption is concerned. The paperdemonstrates that the utilization of social media features differs according to the monetary and symbolicvalue of products sold by the e-commerce vendors.

    Bureau, 2009). One of the main factors hold-ing back consumers from purchasing online isthe lack of social contact with store employeesas well as with other shoppers (Lowry et al.,2010). As this deficiency can be overcome bythe application of new media-rich technologiesconveying social-presence (Gefen & Straub,2003, 2004), we feel this can be an importantfactor contributing to the future success ofe-retailers.

    While the absence of social-presence in

    the online environment may prevent consumersfrom purchasing online, its presence can enhanceDOI: 10.4018/jeei.2011010103

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    customer trust, loyalty and enjoyment towardsthe e-retailers. Thus, today many e-commercebusinesses are trying to create social-presenceby adopting media-rich technologies. The aim

    of this paper is to provide an understandingof how the adoption of different social-mediafeatures can affect online sales and also to as-sess the current deployment of diverse social-presence enhancing technologies among tope-retailers in order to reveal opportunities forother e-commerce businesses and to speculateabout future developments in this area.

    We will first discuss how different social-media features can be applied by e-retailers toenhance perceptions of social-presence andwhy this can be important in generating onlinesales. Because it is necessary to understand thepresent adoption of technological trends beforemaking any predictions for the future (Odlyzko,2010) we subsequently investigate the currentadoption of such social-media features by topbusiness-to-consumer (B2C) online retailers.We also examine more specifically how e-commerce websites differ in their utilizationof these social-media cues depending on the

    monetary and symbolic value of the productsthey sell. Based on these findings we will pointout prospects for other e-businesses and will dis-cuss what the future may bring. Understandinghow top e-retailers differ in their utilization ofsocial-media cues depending on the monetaryand symbolic value of the products they sellwill contribute to a better understanding ofsocial-media diffusion among the variety ofe-retailers and will allow us to make betterpredictions about the future.

    THE IMPORTANCE OFSOCIAL-MEDIA CUESFOR E-RETAILERS

    In the offline retailing world, direct contactwith a salesperson provides the customer withimportant cues for the establishment of trust (i.e.,eye contact and gestures) which enhance therelationship and intentions to buy (Steinbrcket al., 2002). In contrast, the Internet lacks these

    kinds of human aspects, limiting the potentialof purely virtual businesses (Anderson et al.,2010). To enhance this capacity, e-commercecompanies must deploy mechanisms which

    enable two-way interactions between custom-ers and e-retailers. This involves embeddingsocial-media cues (i.e., cues based on humancharacteristics) into website interfaces viadifferent communication media (Wang &Emurians, 2005). Today, new media tools likeweblogs, instant messaging platforms, videoconferencing, and online social-networks arereengineering the way people interact and areunleashing the potential of businesses world-wide (Hawn, 2009; Reding, 2010). Face-to-facecommunication is being replaced by synchro-nous and asynchronous communication such ase-mail, texting, blogging, podcasting, instantmessaging and mobile devices (Badawy, 2009).The integration of such social-media cues intoretail websites will increase the perception ofemployee presence and improve consumersonline experiences (Wang et al., 2007). Virtualadvisors, one particular form of website social-presence, may for instance facilitate customers

    to make a decision to purchase the right product(Dash & Saji, 2007).Scholars found that social-presence has

    a positive impact on trust, loyalty, perceivedusefulness and enjoyment, and in turn positivelyinfluences the customers intention to purchaseproducts and services online (Cyr et al., 2007;Dash & Saji, 2007; Gefen & Straub, 2003).Social-media permit firms to engage in timelyend-consumer contact at relatively low cost andwith high efficiency (Kaplan & Haenlein, 2010).Dell Inc., for example, generated a total of $6.5million in revenue in orders for PCs, acces-sories and software from their social-presenceon Twitter (Guglielmo, 2009). Active users onFacebook are contributing more than 3% of alltraffic to the top retail sites online, and 25% ofsocial-network users post links to other com-panies, products or services (Mahoney, 2009).Thus, e-retailers need to invest in creating andmaintaining effective social-media channels

    with potential customers if they want to staycompetitive in the future. While it is necessary

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    for Web based companies to know what kindsof social-presence enhancing new media-richtechnologies they need to implement, depend-ing on their resources, capabilities as well as

    commodities traded, research evaluating differ-ent online social-media mechanisms (i.e., text,voice or video chat, the use of avatars, etc.) ispredominantly lacking (Benbasat, 2010). Thispaper aims to fill this gap.

    ONLINE SOCIAL-MEDIA CUES

    In this paper the focus is on the instrumentswhich generate social-presence in e-commerce

    websites (Table 1). Because the degree ofsocial-presence clearly differs between offlineand online communications, investigating themechanisms of online social-presence is a valu-able Information Systems (IS) research topic(Lowry et al., 2010). Social-presence can bedefined as the degree of illusion that othersappear to be real physical persons in eitheran immediate (i.e., real time/synchronous) ora delayed (i.e., time-deferred/asynchronous)communication episode (Kreijns et al., 2010).In a Web environment, social-presence canbe achieved either via virtual communities,message boards, chats or via socially rich textand picture content, personalized greetings,human audio and video, intelligent agents, etc(Hassanein & Head, 2007). These social-mediacues refer to the emerging digital communi-cation channels where anyone can generateand disseminate information content, bothas provider as well as consumer (Kim et al.,

    2010). The availability of more social-mediacues in a website generates a higher level ofsocial-presence (Lowry et al., 2010), and mayenhance consumers trust and purchase inten-tions (Gefen & Straub, 2004).

    In the subsequent paragraphs we discussdifferent instruments that can be used by e-retailers to generate online social-presence:photo cues, video cues, avatars, recommenda-

    tion agents, live help features, online social-networks, support web-blogs and user custom-ization features.

    Photo-cues of people can convey a senseof personal, sociable and sensitive human con-tact and so the perception of social-presencecan be created by presenting photos of smilingpeople on the web interface (Gefen & Straub,2004). Embeddingfacial photo-cuesis costlessand does not require any additional resources.

    Video-cues are rich media streamsembedded into the website and can generatea high level of social-presence by simulatingface-to-face interaction as they transmit manyvisual and audio cues (Aldiri et al., 2008). Thedeployment of a video-streamfeature can becostly and may require extra resources bothtechnological and human.

    Avatars are 2D or 3D humanoid inter-face characters which entail humanlike char-acteristics, such as facial expressions, speech

    output, body gestures, auditory and kinestheticfeedback, human emotions, and social intelli-gence (Qiu & Benbasat, 2009). These graphiccharacteristics can be animated by means ofcomputer technology (Holzwarth et al., 2006).The integration of avatarsinto retail websitesmay enhance the perception of employeepresence and influence consumers purchaseintentions (Holzwarth et al., 2006; Wang et al.,2007; Keeling et al., 2010). Obviously there areconsiderable costs associated with the imple-mentation of avatarsin e-commerce websites.

    Recommendation Agents (RAs) aresoftware entities that carry out some set ofoperations on behalf of online-shoppers suchas content-filtering, providing shopping advice

    Table 1. Web-based instruments to generate online social-presence

    Photo cues Assistive interfaces Support blogs Instant help

    Video cues Social networks Review boards User customization

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    and guiding and directing consumer choices(Schafer et al., 2001). Consumers treat onlineRAs as social actors and perceive humancharacteristics (e.g., benevolence and integrity)

    in computerized agents (Wang & Benbasat,2005). The appropriateness and deployment ofonline RAsdiffer according to business goals(Schafer et al., 2001). They can bring addedvalue to online-shoppers particularly in the caseof complex purchase decisions.

    Instant messaging is the most popularmanifestation of near-synchronous technologieswhich support Internet-based synchronous chatwith point-to-point communication between us-ers on the same system (Grinter & Palen, 2002).These live helpfunctions allow consumers toengage in social interaction when making theirshopping decisions and are deemed particularlyrelevant when perceived risk associated withthe purchase is high. The deployment of media-rich communication technologies such as textchat, audio and video chat can be costly andrequire additional financial and human resourceinvestments to operate.

    Online social-networks (OSNs) refer to

    online platforms where people are intercon-nected (Douglis, 2010). These platforms areused for information sharing, video sharing,photo sharing, chatting, tagging and blogging(Hoadley et al., 2010). OSNs became verypopular despite the probability that they mayput the privacy of internet users in danger (Vas-cellaro, 2010). Today, individuals, businesses,and even governments communicate with eachother, their customers, and constituencies viaOSNssuch as YouTube, Facebook, and Twit-ter(Badawy, 2009).Facebook.comalone, forexample, has more than 500 million activeusers (Facebook, 2010). While the impact ofsuch social-networks on online customerspurchasing behavior has not been studied yet,we expect that they will be of more relevancein purchasing high involvement products whenperceived risk is higher.

    Support web-blog (forum) is Web in-formation sharing technology (Boulos et al.,

    2006). It contains an online personal journal

    with reflections and comments, and is updatedwith individual entries or postings frequentlyaccording to the website owners editorialpurposes (Reichardt & Harder, 2005). Support

    forumscontribute to Web content by linking andfiltering evolving content in a structured way andby connecting people through shared interests(Lindahl & Blount, 2003). They engage peoplein knowledge sharing, reflection and debate,constructing knowledge around a common topicwithin a community of practice (Boulos et al.,2006). Online customers may seek supportiveinformation for some technically complicatedproduct categories, especially when there islittle brand information or for very specializedbut less familiar niche products.

    Online product review/rating is pro-vided by customers who previously purchasedproducts and may add value for prospectiveconsumers (Mudambi & Schuff, 2010; Williamset al., 2010). Today they have become a majorinformation source for consumers regardingproduct quality (Hu et al., 2008). Interest-ingly, consumers who shop from an unfamiliare-retailer in search of lower prices seek more

    negative word-of-mouth information and aremore likely to believe that problems may occuras compared to e-retailers with whom they aremore familiar (Chatterjee, 2001). However,positive as well as negative reviews increaseconsumer awareness, whereas positive reviews,in addition, improve attitudes toward products(Vermeulen & Seegers, 2009). Hence,customerreviewsare found to have a positive relationshipwith sales (Chen et al., 2004). Even thoughDuan et al. (2008) found online user reviews tohave little persuasive effect on actual consumerpurchase decisions, their positive impact ap-pears to be stronger for less-popular productsthan for more-popular ones (Chen et al., 2004).

    User customization enables e-retailersto automatically interact with their customers,offering them a variety of web-based personal-ization opportunities that might drive customersatisfaction and trust (Riemer & Totz, 2001).The positive impact of offering customiza-

    tion possibilities on customer trust has been

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    empirically confirmed by different scholars(Chen & Barnes, 2007; Koufaris & Hampton-Sosa, 2004). The personalization of productsto specific requirements obviously increases

    customer value and lowers the competitivecomparability, thus increasing switching costs(Riemer & Totz, 2001). User customizationop-portunities may vary depending on the type ofthe products sold. Some products such as airlinetickets, laptops and gifts are easily customizable.For example, online-shoppers can customizethe dates, times and number of stop-overs forplane tickets or they can customize the entirehardware and software configuration of laptops(Koufaris & Hampton-Sosa, 2004). In addition,customization featurescan serve as a key meansof acquiring customer information (Chellappa& Sin, 2005).

    E-RETAILER CATEGORIESAND THEIR NEED FORSOCIAL-PRESENCE

    Some products appear to sell better on theinternet than others. Products that have a lowcost, intangible value proposition and whichscore relatively high on differentiation are morelikely found to be purchased online (Phau &Poon, 2000). As a consequence, the lack ofonline social-presence can be a strong inhibitorfor purchasing certain product categories onthe Internet. For that reason we assume thatthe need for social-presence and consequentlyalso the adoption of social-media cues will varydepending on the kind of products offered by the

    e-retailer. Many scholars have offered diversecategorizations of e-retailers according to thetype of goods they trade (Choi et al., 2006; DeFigueriedo, 2000; Girard et al., 2003; Petersonet al., 1997; Rosen & Howard, 2000). Most ofthem categorized online retailers based on cus-tomer involvement (i.e., low versus high) andproduct characteristics (i.e., search versus ex-perience goods). Correspondingly, we proposethat commercial websites can be distinguishedaccording to the monetary and symbolicvalue of the products they sell and that their

    need for social-presence and consequently alsotheir adoption of social-media cues will differaccordingly. The proposed categories are notconceived to be clear-cut but rather to represent

    a continuum with two axes from less to moreexpensive and from more functional to moresymbolic (Figure 1). The general proposition isthat e-retailers belonging more or less to thesedifferent categories will vary in their need forsocial-presence and consequently in their adop-tion of social-media cues.

    Monetary value is probably the mostcommonly used indicator of consumer involve-ment because perceived risk is higher when theprice is high (Laurent & Kapferer, 1985). Thisevokes more complex information search be-havior, as such products are bought less fre-quently and increases the need for confirmation.Therefore, we assume that the need for social-presence and the adoption of social-presenceenhancing features will be higher for e-retailersselling more expensive products.

    H1: e-retailers selling products of highermonetary value are expected to utilize

    more social-media cues.

    Symbolic value refers to the differen-tiation of products based on brand image. Incontrast to more functional products, whereimage is less important, products with a highersymbolic value, like fashion for example, aremore ego-involving because of their symbolicmeaning which conveys ones lifestyle or per-sonality (Laurent & Kapferer, 1985). As it can

    be tricky to express such symbolic qualities viathe website interface (Degeratu et al., 2000), weassume that the need for social-presence will behigher in the case of e-retailers selling productsof higher symbolic value. In accordance, Has-sanein and Head (2006) found websites sellinghigh symbolic value products (e.g., apparel) tobenefit from higher levels of social-presence,while websites selling more functional products(e.g., headphones) did not exhibit a positive ef-fect from higher levels of social-presence. Thus,

    they confirm that the effect of social-presencediffers according to the type of products offered

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    by the e-retailer and more specifically, accordingto the symbolic value of the products offered.Consequently, we assume that the utilizationof social-presence enhancing features will behigher for e-retailers selling more symbolicversus more functional products.

    H2: e-retailers selling products of highersymbolic value are expected to utilizemore social media cues.

    METHODOLOGY

    Content Analysis: Methodand Procedure

    In order to establish to what extent media-richtechnologies which convey social-presence areadopted by B2C e-retailers, we content analyzedtheir websites identifying the different social-

    media cues utilized (see first column of Table2). Content analysis is a scientific, objective,systematic, quantitative, and generalizable re-search technique for making replicable and validinferences from textual, pictorial, or audiblematter to the contexts of their use (Krippendorff,2004). This method has been used by manyscholars to investigate website content acrossdifferent domains (Choi et al., 2007; Govers &Go, 2005; Henry & Story, 2009; Maynard &

    Tian, 2004; Zhao & Zhao, 2004). The analysisof the website content was carried out during

    June-July 2010 and proceeded in 2 stages: (1)careful investigation of the websites front page,(2) choosing a product and clicking till the lastcheckout page. While browsing through theshopping process, we carefully investigatedweb pages for the presence or absence of thedifferent social-media cues using a pragmaticcoding scheme (absence=0; presence=1). Theobtained data is reliable because coding twoclear possibilities satisfies the condition of

    reliability and there is no need to perform anadditional record of nominal data by differentobservers (Hayes & Krippendorff, 2007).

    Sample

    The sample consisted of 210 top revenue produc-ing B2C e-commerce retailers as identified byInternet Retailers Top 500 Guide. In view ofthe fact that utilizing a broad range of interac-tive web features may require high financial

    and human resource investments to maintaineffective e-commerce activity, it is expected thattheInternet Retailers Top 500companies canbe considered as the most apt to have adequateresources to employ fully-featured websites.The Top 500ranks B2C retailers in the U.S.and Canada based on full-year online sales,including retail chains, catalogers, Web-onlymerchants, brand manufacturers and digitalcontent sellers (Internet Retailer, 2010). As weaimed to examine whether there are significantdifferences in the utilization of social-media

    Figure 1. Categorization of e-retailers according to the monetary and symbolic value of

    products sold

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    Table 2. Adoption of social-media cues among e-retailer categories

    Soci

    al-cue

    fea

    ture

    2x4design

    Total

    %

    df=3

    Sig.

    2-sided

    2x2design

    Total

    %

    df=1

    Sig.

    1-sided

    2x2design

    Total

    %

    df=1

    Sig.

    1-sided

    Lowmonetary

    value

    Highmon

    etary

    value

    Monetary

    value

    Symbolic

    value

    Low

    symb.

    value%

    High

    symb.

    value%

    Low

    symb.

    value%

    High

    symb.

    value%

    Low%

    High

    %

    Low%

    High

    %

    Photocue

    62.7

    81.7

    50.9

    57.1

    63.8

    13.24

    .004

    71.2

    53.5

    62.9

    6.971

    .0

    06

    55.6

    71.6

    63.3

    5.792

    .012

    Videocue

    25.5

    28.3

    31.6

    19.0

    26.7

    2.071

    .558

    25.2

    26.3

    25.7

    .029

    .4

    94

    29.6

    24.5

    27.1

    .695

    .249

    Av

    atar

    .0

    .0

    .0

    2.4

    .5

    4.019

    .259

    .0

    1.0

    .5

    1.127

    .4

    71

    .0

    1.0

    0.5

    1.064

    .486

    R

    A

    .0

    .0

    5.3

    .0

    1.4

    7.169

    .043*

    .0

    3.0

    1.4

    3.412

    .1

    03

    2.8

    .0

    1.4

    2.874

    .247

    Livehelp

    15.7

    31.7

    43.9

    33.3

    31.4

    10.02

    .018

    24.3

    37.4

    30.5

    4.206

    .0

    29

    29.6

    32.4

    31.0

    .182

    .391

    Review

    tool

    56.9

    76.7

    75.4

    52.4

    66.7

    10.73

    .013

    67.6

    65.7

    66.7

    .086

    .4

    41

    66.7

    66.7

    66.7

    .000

    .558

    Ratingtool

    49.0

    80.0

    66.7

    45.2

    61.9

    17.41

    .001

    65.8

    57.6

    61.9

    1.488

    .1

    41

    58.3

    65.7

    61.9

    1.203

    .170

    Support

    blog

    39.2

    16.7

    38.6

    21.4

    29.0

    10.72

    .013

    27.0

    31.3

    29.0

    .466

    .2

    98

    38.9

    18.6

    29.0

    10.44

    .001

    Facebook

    54.9

    56.7

    70.2

    57.1

    60.0

    3.432

    .330

    55.9

    64.6

    60.0

    1.685

    .1

    24

    63.0

    56.9

    60.0

    .813

    .223

    Tw

    itter

    45.1

    55.0

    64.9

    45.2

    53.3

    5.633

    .131

    50.5

    56.6

    53.3

    .786

    .2

    27

    55.6

    51.0

    53.3

    .441

    .300

    Myspace

    5.9

    13.3

    10.5

    14.3

    11.0

    2.182

    .535

    9.9

    12.1

    11.0

    .262

    .3

    85

    8.3

    13.7

    11.0

    1.564

    .152

    Flickr

    .0

    3.3

    10.5

    .0

    3.8

    10.73

    .013*

    1.8

    6.1

    3.8

    2.590

    .1

    06

    5.6

    2.0

    3.8

    1.850

    .159

    Youtube

    5.9

    18.3

    35.1

    16.7

    19.5

    15.10

    .002

    12.6

    27.3

    19.5

    7.158

    .0

    06

    21.3

    17.6

    19.5

    .445

    .312

    Cust

    omize

    11.8

    5.0

    10.5

    7.1

    8.6

    2.028

    .567

    8.1

    9.1

    8.6

    .064

    .4

    96

    11.1

    5.9

    8.6

    1.830

    .134

    *Theassumptionhasnotbeenmetbecau

    setheminimumexpectedcountislessthan5.

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    cues depending on the type of products traded,we included various industries in our sample,classified according to the monetary and sym-bolic value of products sold (cf. Figure 1):

    Selling products which are relatively cheap in

    price and low in symbolic value:

    Books/Music/Videos (N=20) Flowers/Gifts (N=11) Food/Drug (N=20)

    Selling products which are relatively cheap in

    price and high in symbolic value:

    Apparel/Accessories (N=20) Health/Beauty (N=20) Sporting Goods (N=20)

    Selling products which are relatively expensive

    and low in symbolic value:

    Computers/Electronics (N=20) Hardware/Home Improvement (N=20) Office Supplies (N=17)

    Selling products which are relatively expensive

    and high in symbolic value:

    Jewelry (N=15) Housewares/Home Furnishings (N=20) Automotive Parts/Accessories (N=7)

    Analyses and Results

    The quantified data gathered from the contentanalyses was entered into SPSS and the fre-quencies of adoption of the social-media cuesunder investigation were counted (Singleton& Straits, 2009). We performed ANOVA andcross-tabulations to measure the variation andrelation between our variables of interest.

    An overview of our findings regarding theoverall adoption of the different social-mediacues is presented in Figure 2. While somesocial-media cues have been readily adopted bye-retailers (a.o., facial photographs, customerreviews and ratings, and some online socialnetworks such as Facebook and Twitter), othersocial-media cues appear to be still in their

    infancy what their adoption is concerned (a.o.

    video features, avatars, recommendation agentsand live help and support blogs).

    The results also indicate that the adoptionof social-media cues (mean = 4,40; st.dev. =

    2,49) appears to vary markedly along the web-sites investigated: 13 out of 210 websites didnot display any social-media cues, while 9 ofthem featured 9 or more different kinds ofsocial-media cues and should be consideredexemplary in this regard (i.e., Mountain Equip-ment Co-op, Dell Inc., Newegg Inc., HP Homeand Home Office Store, Abt Electronics Inc.,Weight Watchers International, Gaiam Inc.,Recreational Equipment Inc. and BestBuy).

    Differences in the amount of social-mediacues utilized across website categories are firstcompared by means of a 2 by 2 (monetaryvalue x symbolic value) ANOVA. This initialanalysis, pertaining to the summated totalnumber of social-media cues featured in thewebsites, reveals that there are no main differ-ences in adoption of social-media cues whenthe monetary or symbolic value of products soldis concerned. However, there does appear toexist a significant interaction effect (F=12,788;

    p

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    media cues than those selling cheaper products,which partially confirms our expectations (av.number of social-cues = 5,21

    SV low x MV highversus

    3,71SV low x MV low

    ; post hoc Bonferroni p=.012).In summary, rather remarkably, when thereappears to be congruency between the mon-etary and symbolic value of products offeredon the website, which can both either be lowor high, then there seems to be less usage ofsocial-media cues in the website than in thecase where there is some form of incongru-

    ency between both (av. number of social-cues= 3.73

    Congruent Valuesversus 4.93

    Incongruent Values; t-test

    p

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    be used more in websites offering cheaperproducts as compared to those selling moreexpensive products (71% versus 54%, 2-testp=.006), which seems logical considering the

    low cost needed for the implementation.Facialphoto-cuesare also used more in websites of-fering products of high symbolic value than inthose offering more functional products (72%versus 56%, 2-test p=.012), which is in linewith expectations. As a matter of fact e-retailersselling cheaper products of a high symbolicvalue appear to make the most use of facialphoto-cuesin their websites (82%).

    Video-cuesare used in only 27% of allthe websites investigated. Although we noticesome slight variations among website catego-ries, these differences appear to be insignificant.Websites making use of video-cues are notlimited to those demonstrating their product bya representative through an embedded video-stream, but there are also some which enabletheir customers to upload user-generated videoclips showing their experiences with productsthey purchased.

    An Avatarwas only used in one of all

    the websites examined (i.e., Ikea.com). WhileIkea does offer some relatively cheap decorativeproducts, it also sells more expensive built-inkitchens, bedding and upholstered furniture.In our categorization, e-tailers selling home-furnishings were classified in general as sellingmore expensive and more symbolic products.It is in the line of expectations that some tech-nologically more advanced social-media toolswould rather be adopted within this categoryof online retailers.

    Recommendation agentsalso appear tobe scarce as they were used in only 3 of all thewebsites scrutinized (1,4%). The e-retailersfeaturingRAsin their websites (i.e., SonyStyle.com, HP Home & Home Office Store and DellInc.) all can be categorized as selling more ex-pensive products of a more functional nature,which may require somewhat more technicalassistance.

    Live-helpcan be found in 31% of all the

    investigated e-commerce websites. They turnout to be featured more by e-retailers selling

    more expensive products (37% versus 24%,2-test p=.029), which might be due to the costand human resource investments associatedwith adoption. While there does not seem to

    be a significant difference when the symbolicvalue of the products sold is concerned, live-help chat lines actually seem to be utilizedmost by e-retailers putting expensive productsof low symbolic value on the market and leastby those vending cheap products of low sym-bolic value (44% versus 16%; 2-test p=.018),demonstrating a clear interaction effect. Onlya few websites utilized the instant audio-chatfeature (5.7%).

    The results show that numerous tope-commerce websites try to create a social-presence by utilizing different kinds of OnlineSocial Networks. Among many, Facebook.com (60%) and Twitter.com (53.3%) are themost utilized ones compared toMySpace.com(11%) orFlickr.com(3.8%) which are adoptedto a far lesser extent. Although we notice someslight variations in adoption among websitecategories, these differences appear to beinsignificant. For YouTubeon the other hand,

    which is adopted by 20% of e-retailers, wecan reveal a significant difference in adoptionamong e-retailers depending on the cost of theproducts sold, with 27% of those selling expen-sive products featuring YouTubeas comparedto only 13% of those selling cheaper products(2-test p=.006). While there does not seem tobe a significant difference when the symbolicvalue of the products offered is concerned,YouTubeactually seems to be utilized most bye-retailers putting more expensive products oflow symbolic (i.e., more functional) value onthe market and least by those vending cheaperproducts of low symbolic value (35% versus 6%;2-test p=.002), demonstrating a clear interactioneffect once again. Especially, e-retailers whichsell technically complicated and expensiveproducts are trying to show video clips of theirproducts via YouTube.

    Support forums, discussion boards, and

    blogs for sharing ideas were available in

    29% of all the websites investigated. Resultsindicate that especially websites offering more

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    functional products appear to feature supportforumsin comparison to those selling productswith a more symbolic value (39% versus 19%;2-test p=.001). When the monetary value of the

    products on sale is concerned, no significantdifferences can be discerned in the adoptionofsupport forumsamong website categories.

    Customer reviewswere featured in 67%of all the websites inspected and customerratingswere available in 62% of them. Thus,most web based companies are allowing theircustomers to post their experiences about theproducts or services they have purchased.Although we cannot reveal any main effectswith regard to the monetary or symbolic valueof the products sold in the websites, a clearinteraction effect becomes apparent. Whenthere appears to be congruency between themonetary and symbolic value of products of-fered on the website, which can both eitherbe low or high, then customer reviewsappearto be less featured in the website than in thecase where there is some form of incongru-ency between both (76%

    Incongruent Valuesversus

    55%Congruent Values

    ; 2-test p=.002). The same

    is true for the display of customer ratings(74%Incongruent Values

    versus 47%Congruent Values

    ; 2-testp

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    live-help and YouTube media-stream. Whenthe impact of the symbolic value of productstraded is concerned, we can conclude that web-sites selling products of a more functional (i.e.,

    less symbolic) nature utilize support forums,discussion boardsand blogsfor sharing ideasmore often. Websites selling more symbolicproducts, on the other hand, appear to makemore use of simplefacial photo-cues.

    Having portrayed the current situation ofsocial-media adoption among online retail-ers, we would like to take the opportunity tospeculate a little about future developments. Asthe lack of social contact with store employeesas well as with other shoppers is still one ofthe main factors holding back consumers topurchase online (Lowry et al., 2010), we feelthat further application of new media-richtechnologies conveying social-presence canbe an important factor contributing to thefuture success of e-retailers. The integrationof such social-media cues into retail websiteshas actually been demonstrated to positivelyaffect consumers online experiences, trust,loyalty, perceived usefulness, enjoyment and

    purchase intentions (Cyr et al., 2007; Dash &Saji, 2007; Wang et al., 2007; Gefen & Straub,2003). The findings of our research clearlyindicate that there is still considerable potentialto enhance social-presence in a majority of toponline retailer websites. As we expect that thetechnology behind these social-media featureswill further evolve and mature and that the costsinvolved in adopting more advanced social-media features will reduce correspondingly, weanticipate an increased adoption of social-mediain e-commerce websites and predict a brightfuture for online retailing.

    Obviously, the supporting technologies arein constant evolution and it is not an easy taskto imagine what the future might bring. One hasto bear in mind that online social-networkingsites, for example, such as Facebook and Twitter,did not even exist just a couple of years ago.Today, new Web technologies allow the use ofsocial-networking tools which are becoming

    an essential part of our daily life that cannotbe ignored or simply turned off (Badawy,

    2009). Since the boom of Web 2.0, onlinesocial-networkingwebsites have been on therise (Van den Eede, 2010). As a result, everyday more people are getting connected through

    popular OSNsto express themselves, and sharecontent (Mislove et al., 2010). Most e-commercecompanies are recognizing the importance ofthis trend and have started utilizing OSNsat afast pace. Simultaneously, the usage of virtualcommunities such as Second Life is grow-ing for activities like dating, sharing ideas andeducation as well as for purchasing productsfrom e-retailers (Berthon et al., 2010; Salmon,2009). We expect that in the future the social-networks as well as virtual communities willcontinue to grow and that businesses will investmore in community building applications as amarketing driver.

    The current study also revealed that cus-tomer reviewsand ratingshave been readilyaccepted by top online retailers. As they havebeen demonstrated to positively impact sales(Chen et al., 2004; Chevalier & Mayzlin,2006; Mudambi & Schuff, 2010), we expectthat in the future e-retailers will utilize Web

    technologies which allow customers to postnot only textbut also their ownphotosas wellas user-generated audioand video commentsto share individual product experiences. In thefuture, more powerful streaming and advancedtechnology will enable more e-retailers to adoptthese features. This would definitely engendermore social atmosphere in the websites and willadd value for prospective consumers, loweringtheir perceived risks and thus increasing theirpurchase intentions (Mudambi & Schuff, 2010;Williams et al., 2010).

    Support forums, discussion boards, and

    blogs for sharing ideasare currently offered byabout one third of top online retailers. As Webinformation sharing technology is evolving ata fast pace, enabling people to connect throughshared interests and engaging them in knowl-edge sharing, reflection and debate concerningcertain topics of interest within a community(Lindahl & Blount, 2003; Boulos et al., 2006),

    we anticipate that such social-media featureswill be eagerly adopted by online retailers in the

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    future. They can be used to engage consumersand can provide a way to draw in online shop-pers. Particularly, we see a positive evolution inthe adoption of multi-media chat-room features

    where customers can instantly socialize witheach other, not only through text-chat, but alsothrough live audio and video-streams.

    Live-help features also appear to beutilized somewhat less commonly by onlineretailers. As this might be due to the cost andhuman resource investments associated withproper adoption, we feel that this will initiallystay an important obstacle and that its use in thenear future will stay a privilege for online retail-ers selling more expensive products. However,as conversational interface devices (such asSpoken Dialog Systems) and humanlike agentsthat can talk to customers using data-rich se-mantic protocols will probably become readilyaccessible in the somewhat further future, thisobstacle should be overcome easily, makingthe prospect of daily interactions with hundredsof millions of people within the system overmobile devices or communication networksactually feasible (Hge et al., 2008; Pieraccini,

    2009). While most online retailers currently onlyfeature text-chat help, for the future we see anevolution towards audio-and video-chat helpfeatures. It has actually been demonstrated thatvoice-chathas a significantly better effect ontrust and cooperation than text-chat(berg &Shahmehri, 2001). As the competition amongonline businesses is becoming more intense,we can therefore, expect that in the future moreinstant multi-media (i.e., including audio andvideo) feedback and sharing opportunities willbe provided, integrating different social-mediacues which are designed to enhance customerinvolvement.

    The adoption of recommendation agents(RAs), as means to enhance social-presence,appears still very uncommon. Only three topretailers in the current study have alreadyadopted this technology. Considering that thissocial-media cue can induce trust towards theWeb retailer, that the technology behind it is

    advancing at a fast pace, and that it will become

    a necessity for any e-commerce website that hasa large amount of products or services to offer,we speculate that its utilization by e-retailerswill rise considerably in the near future. Empiri-

    cally, it has been demonstrated that online RAsare actually able to provoke consumer trust to-wards e-retailers (Qiu & Benbasat, 2009; Wang& Benbasat, 2007). The technology behindrecommendation systems is also in full evolu-tion and has shifted from characteristic-basedrecommendation algorithms to social-basedrecommendation algorithms (Ochi et al., 2010).Because of their positive impact on the onlineshopping experience we expect that especiallythis last type ofRAswill become popular.

    Our findings also show that current useof avatar technology by top e-retailers isalmost non-existent. An avatar was only usedin one of all the websites examined. As recentempirical literature emphasizes the positiveeffects of such a virtual salesperson on percep-tions towards the Web retailer, we assume thatthis social-presence enhancing feature will beutilized more frequently by e-retailers in thefuture. Avatar sales agents have actually been

    demonstrated to engender more satisfaction withthe e-retailer, a more positive attitude towardsthe products, and a greater purchase intention(Holzwarth et al., 2006). In addition, avatarpresence has been shown to induce consumertrust towards e-retailers (Keeling et al., 2009;Luo et al., 2006). While at moderate levels ofproduct involvement, featuring an attractiveavatar appears most effective, at high levels ofproduct involvement, an expert avatar turns outto be a more successful sales agent (Holzwarthet al., 2006). Due to the current technologicaladvancements, which will become commonlyavailable at a lower cost, we also expect thathigh quality personalized 3D avatars will be-come soon accessible and will be adopted bye-retailers enabling customers to use virtualfitting rooms to try on fashion products (cf.,OptiTex fashion design software featured inTim Gunns Guide to Style). The online shop-pers personal avatar wearing the new clothes

    and accessories can subsequently be revealed

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    to friends or other shoppers for advice andconfirmation regarding likeability and fit. Thiswill reduce the online shoppers cognitive dis-sonance and will enhance his online shopping

    experience considerably, which should give aboost to e-tailers in the fashion industry.While providing user customizationpos-

    sibilities involves increased costs, Web mer-chants should realize that it can be a perfectway to generate more customer value and todifferentiate their offer from that of the com-petition. Therefore, we are also positive on ourexpectations for its future adoption. Finally,considering these trends and evolutions, wepredict that current advancements which makethe Internet more social might help online shop-ping to displace traditional shopping behaviorto some extent in the next decades.

    LIMITATIONS ANDSUGGESTIONS FORFURTHER RESEARCH

    This study is based on a sample of top e-retailers. Because these most probably havethe necessary resources to invest in their web-sites, the findings of this study will most likelygive a more positive impression with regardto the adoption of social-media cues than ifwe would look at the general population ofB2C e-commerce websites. As, based on thissample, we can already reveal a huge potentialfor improvement, we can only assume that thispotential will be even bigger in reality. It wouldbe interesting if the adoption of social-media

    cues could actually be compared between higherand lower ranked online retailers.

    Based on our investigations, carried out ata certain point in time, we have tried to depictthe current adoption of different social-mediacues by online retailers, in order to be able tomake some predictions about the future. It wouldbe fascinating to actually track the evolution ofthe adoption of social-media cues in the web-sites investigated by performing a longitudinalstudy. This would allow us to get a better viewof the actual diffusion of social-media among

    e-retailers. The fact that supporting social-mediaWeb technologies are in constant evolution willmake such longitudinal research all the morechallenging.

    As this research focused specifically onB2C online retailers, it would also be interestingto look at the adoption of social-media cues byB2B e-vendors or C2C e-commerce portals. Infuture studies also a comparison could be madeof the adoption of social-media features by pureplays versus bricks and clicks retailers, as itcould be assumed that the need for integrationof social-presence will be even higher for pureplays as they lack physical stores altogether.

    In the current research paper a categoriza-tion of online retailers was proposed, classifyingthem according to the monetary and symbolicvalue of products sold, because we expected thatthe need for social presence and consequentlyalso the adoption of social-media cues wouldbe different between these online merchants.Understanding such differences should contrib-ute to a better comprehension of social-mediadiffusion among the variety of e-retailers. Nev-ertheless, categorizing e-commerce companies

    based on the products they sell is not alwaysstraightforward as often they sell different kindsof products. For example, e-retailers sellingoffice-supplies may offer simple inexpensivegoods such as a variety of office-stationery aswell as expensive customized office furnitureor multi-function laser printers. While theproposed categories were not conceived to beclear-cut but rather to represent a continuumwith two axes from less to more expensiveand from more functional to more symbolic,we categorized different industries representinga variety of retailers in each of the categories.We acknowledge however that also within theseindustries there can be a huge variety betweene-retailers which was not really taken into ac-count in the present study (e.g. Ikea.com versusRestorationhardware.com, both offering homefurnishings but to a diverse audience and clearlywith a different price-positioning). Furtherresearch should investigate how consumers

    experience the need for social-presence amongdifferent kinds of online retailers and whether

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    the proposed e-tailer classification is adequatein this regard or whether it should be refined.

    Furthermore, it would be interesting toinvestigate the impact of the implementation

    of different social-presence enhancing techno-logical features such as synchronous video-cue,audio-cue and social-networks on consumertrust and buying behavior. As the likelihood toshop online depends on the consumers shop-ping orientation such as price-consciousness,risk-aversion, innovativeness, brand-loyalty,variety-seeking inclination, impulsiveness aswell as information processing (Girard et al.,2003), it should also be interesting to investigatehow different types of online shoppers varyin their dependence on social-media cues ine-retailer websites.

    Finally, while the deployment of some ofthese social-media tools still may be relativelycostly and require high financial and humanresource investments to utilize them effectively(Whelen & McGrath, 2002), the challenge facedis that their use can be quite tricky and mayrequire some new ways of thinking (Kaplan &Haenlein, 2010). Making suggestions to users

    via social-networks to increase their degree ofengagement is becoming a common practice,but the most important task for e-retailers isto know how to recommend the right content,products, or ads to consumers (Machanavajjhalaet al., 2010). Thus, in adopting these emerginge-business technologies internal capabilitiesof a company may play a more influential rolethan the environmental drivers (Chang, 2010).Thus, the central concern is not whether toutilize these new media tools but how to utilizethem. These new media tools can enhance theshopping experience, but applications shouldbe tailored to meet the unique requirementsof product categories and consumer segments(Burke, 2002). Further research has to investi-gate how social-media should be used to leadto optimal results.

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    Farhod P. Karimov is a doctoral scholar at the Vrije Universiteit Brussel (Belgium). He received

    his bachelor degree in business administration from Tashkent State Technical University (Uz-

    bekistan) and master degree in marketing science from University of Ulster (UK). From 2002 to2006, he was vice-president of Marketing at Ulugbek Textile joint-stock company where he was

    responsible for leading, directing and mentoring marketing team to success. In 2006, he started

    his academic career at Westminster International University in Tashkent (WIUT), where he has

    been lecturing on Marketing Management, Marketing Research, and Creating and Delivering

    Customer Value. As a guest lecturer he has also been teaching Marketing, Consumer Behavior,

    and Pricing Strategies in Marketing at International Business School in Tashkent. His current

    scientific research is focused on understanding the impacts of website atmospherics on online

    consumers shopping motivations and behavior. The aim of the research is to capture the lessons

    of successful models for e-businesses serving promising online segment. He is actively involved

    in studying the role of social-media in e-commerce and specifically how it influences the ac-

    ceptance of online shopping. In addition to his interest in Internet marketing, he also studies

    entrepreneurial marketing and ICT research in transition economies.

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    International Journal of E-Entrepreneurship and Innovation, 2(1), 26-45, January-March 2011 45

    C i ht 2011 IGI Gl b l C i di t ib ti i i t l t i f ith t itt i i f IGI Gl b l

    Malaika Brengman (PhD in Applied Economics, University of Ghent) (UG), is Associate Profes-

    sor at the Vrije Universiteit Brussel (VUB), where she teaches Marketing, Strategic Marketing

    Management, Consumer Behaviour and Market Research. She started her academic career as

    Assistant Professor at Hasselt University, where she has also been lecturing in Marketing Com-

    munications, e-Business, Services Management and Customer Relationship Management. She hasalso been guest lecturing at other academic institutions such as Solvay Business School at the

    Universit Libre de Bruxelles and the International School of Management at the Leti-Lovanian

    University in St. Petersburg, Russia. Guided by her strong interests in Retailing, Marketing

    Communications and Consumer Behaviour, her scientific research generally focuses on the

    impact of store atmospherics and consumers shopping motivations and behaviour, specifically

    also with regard to alternative distribution channels such as e-commerce and shopping in Vir-

    tual Worlds. She also studies marketing communications effectiveness, especially with regard

    to new media. She has published her work in well-established journals, such as the Journal ofElectronic Commerce Research, the Journal of Business Research, the Journal of Market-ing Communications, the Journal of Retailing and Consumer Services, the Journal of BrandManagement, the Journal of Product and Brand Management, and Advances in ConsumerResearch. She has presented her findings at numerous international conferences.