Your SlideShare is downloading. ×
Understanding Customer Engagement in the Digital Age
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Understanding Customer Engagement in the Digital Age

14,114

Published on

I have investigated the notion of engagement in new media and customer interests in brand utility in the course of my final degree in Marketing. This study focuses on IKEA and explores al the facets …

I have investigated the notion of engagement in new media and customer interests in brand utility in the course of my final degree in Marketing. This study focuses on IKEA and explores al the facets of customer engagement. More than 500 individuals took part in the study. Please contact me if you are interested in some of the findings.

Published in: Business, Technology
0 Comments
8 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
14,114
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
0
Comments
0
Likes
8
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Understanding Customer Engagement in the Digital Age. Emmanuel Peype - Dissertation Project
  • 2. 3 Abstract Social media has become a real challenge for marketers likely to connect with an audience. The rising empowerment of customers in these new media tends to change marketing landscape and oblige companies to start a conversation with them. The concept of customer engagement highlights the imminent need to focus on building personal two-way relationships with the audience and engaging them on new media platforms. The aim of the study was to investigate the impact of customer engagement on customer brand interactions, specifically in social media platforms using IKEA as a focal company. In addition to customer engagement, the study was measuring two other concepts likely to impact on those interactions: passion and brand utility. The research was elaborated through the use of conceptual models of engagement. In complement, motivations for engaging with brand in social were identified in current literature. Conceptual frameworks were indeed tested along the study. The empirical study was conducted in summer 2011. An online questionnaire was used to collect information from 305 respondents. The questionnaire aimed at measuring insights related to IKEA as well as testing constructs in the process of engagement. The result of this study proves the validity of conceptual model of engagement used. Results show that customer engagement had several implications with concepts related customer brand relationships such as satisfaction, loyalty and passion. However, customer engagement in social media was indirectly related to those constructs, as it did not impact positively on some variables. The study also identified the importance of intrinsic motivations for customers likely to engage with IKEA, such as getting fun and getting information. Finally the study identified passion and brand utility as two important aspects of customer-brand interactions likely to encourage customers in engaging.
  • 3. 7 Table of Contents Contents Abstract....................................................................................................................3 Declaration & Statements.........................................................................................4 Ethical Evaluation Form ............................................................................................5 Record of Supervision...............................................................................................6 List of Tables.............................................................................................................9 List of Figures .........................................................................................................10 1 Introduction....................................................................................................11 2 Literature Review............................................................................................15 2.1 Customer Engagement.....................................................................................................................15 2.2 Social Media..........................................................................................................................................17 2.2.1 Types of Social Media ..........................................................................................................................17 2.2.2 Characteristics of Social Media.......................................................................................................19 2.2.3 User participation on social media...............................................................................................19 2.3 Customer engagement on social media.....................................................................................22 2.3.1 Types of Customer Engagement on social media...................................................................22 2.3.2 The Engagement Ladder....................................................................................................................24 2.3.3 Measuring  the  overall  “Engagement  Score”.............................................................................26 2.4 Motivations for engaging in social media.................................................................................27 2.5 Customer-Brand relationship........................................................................................................30 2.5.1 Emotional attachment and Passion..............................................................................................31 2.5.2 Brand Utility............................................................................................................................................32 3 Statement of research and hypotheses............................................................33 4 – Methodology................................................................................................37 4.1 Research Purpose...............................................................................................................................37 4.2 Research Strategy...............................................................................................................................38 4.3 Research Method................................................................................................................................38 4.4 Sample Selection.................................................................................................................................39 4.5 Data collection .....................................................................................................................................39 4.6 Questionnaire Design........................................................................................................................40 4.7 Pilot study..............................................................................................................................................42 4.8 Validity and Reliability.....................................................................................................................42 4.9 Measurement implications.............................................................................................................42 5 Results and analysis ........................................................................................43 5.1 Profile of respondents ......................................................................................................................43 5.2 Consumer Behaviour with IKEA...................................................................................................44 5.2.1 IKEA purchases over the last 12 months....................................................................................44 5.2.2 Offline Engagement..............................................................................................................................45 5.2.3 Reasons for visiting an IKEA store.................................................................................................46 5.3 The use of Social Media among respondents..........................................................................47 5.3.1 Frequency of Use....................................................................................................................................47
  • 4. 8 5.3.2 Level of Participation ..........................................................................................................................48 5.4 User Engagement with IKEA in Social Media..........................................................................49 5.5 Motivations for engaging with IKEA...........................................................................................51 5.5.1 Confirmatory Factor Analysis..........................................................................................................51 5.5.2 Reliability of scale .................................................................................................................................51 5.5.3 Construct Validity..................................................................................................................................52 5.5.4 Exploratory Factor analysis.............................................................................................................53 5.6 Relationship Quality..........................................................................................................................54 5.6.1 Satisfaction...............................................................................................................................................54 5.6.2 Loyalty........................................................................................................................................................54 5.6.3 Passion........................................................................................................................................................54 5.6.4 Brand Image............................................................................................................................................54 5.6.5 Product Image ........................................................................................................................................55 5.7 Passion points and brand utility ..................................................................................................55 5.7.1 Passion points..........................................................................................................................................55 5.7.2 Brand Utility............................................................................................................................................56 5.8 Regression analyses ..........................................................................................................................58 5.8.1 Consumption............................................................................................................................................58 5.8.2 Predictors of User Engagement......................................................................................................59 5.8.3 Predictors of Offline Engagement..................................................................................................60 5.8.4 Relationship Quality and User Engagement.............................................................................61 5.9 Brand Utility .........................................................................................................................................63 5.9.1 Predictors of Perceived Brand Utility...........................................................................................63 5.9.2 Predictors of Brand Utility types....................................................................................................64 5.10 Additional findings.............................................................................................................................65 5.10.1 Effect of Age on the study.............................................................................................................65 5.10.2 User Engagement and Relationship Quality .......................................................................66 5.11 Evaluation of Hypotheses................................................................................................................67 5.11.1 Initial Hypotheses............................................................................................................................67 5.11.2 Additional results.............................................................................................................................68 5.11.3 Final Model of Engagement........................................................................................................70 6 Conclusions & Discussion............................................................................71 6.1 The Process of Engagement ...........................................................................................................71 6.2 Motivations for engaging in social media.................................................................................73 6.3 Customer engagement and Passion............................................................................................73 6.4 Customer engagement and Brand Utility .................................................................................74 6.5 Customer engagement and Consumption................................................................................75 6.6 Managerial implications ..................................................................................................................75 6.7 Limitations and further research.................................................................................................76 Bibliography ...........................................................................................................78 Appendices.............................................................................................................84
  • 5. 11 1 Introduction Background of the study For decades, companies relied on traditional push marketing to sell products and services to both newly acquired or existing customers (Urban, 2004). Overwhelming people with approximately 3000 messages everyday was apparently an efficient way to generate  profits  based  on  company’s  marketing  efforts.  However  studies  estimated  the   cost of acquiring new customers to be 5 to 10 times higher than the cost involved in satisfying its own customers (Murphy et al. 2002). As a consequence, companies have emphasized the idea of strengthening relationships with customers to build advocacy over time. According to Urban (2004), quality of products, customer satisfaction and transparency appeared as critical conditions to develop consumer trust towards companies and to maintain long-lasting relationships. For instance, relationship marketing programs such as loyalty card or airline flyer programs were established in order to maximize customer value and profitability for companies, rather than focusing on  consumers  ‘expectations  (Ashley  et  al.,  2011).  Thus,  relational  tactics  didn’t  manage   at fully engaging with people by a lack of commitment with consumers as well as the use of one-way communication. With the rise of the Internet, traditional communication channels have been challenged on  the  basis  of  a  wide  media  fragmentation.  Described  by  Chaffey  (2008)  as  “a  trend  to   increasing   choice   and   consumption   of   media   channels”,   media   fragmentation   has   implied new obstacles to marketers in the process of reaching a relevant audience. As cable TV did with TV networks in the 1980s, the Internet and new media such as social networking platforms tend to split audience across all the available channels, thus making   the   capture   of   people’s   attention harder (Forrester Research, 2004). For instance, individuals among young generations may prefer to watch streaming video online rather than traditional TV programs. Thus, consumers dedicate far less attention to each media, which strongly impact on advertising effectiveness (Hennig-Thurau et al., 2010). In the meantime, new media have contributed to the emergence of empowered consumers.  Individuals  have  become  more  acknowledged  about  brands  by  “gathering   and exchanging information about products, how they   obtain   and   consume   them”.  
  • 6. 12 Thanks to the plethora of available social media platforms, consumers have increased their  opportunities  to  experience  new  roles  such  as  “authors  on  Wikipedia,  retailers  on   eBay   or   content   generators   on   YouTube”   (Hennig-Thurau et al., 2010). Above all, consumers have reached the status of influential referents concerning buying decision; according to Nielsen (2009), consumers used to trust more in peer recommendations (90%) and consumer opinions (70%) than in paid media channels. The rise of social networking platforms has intensified eWOM communication and therefore made it a powerful voice against untruthful marketing practices. As recently seen this year with the Jasmine revolution in Tunisia, social media helped protestors in connecting each other and spreading their ideas, that contributed in the ignition of a revolution (Buhl, 2011). From a company perspective, the social media phenomenon seems to provide extensive opportunities for brands to connect with target audience. In 2010, it represented about 23% of the time spent online and was one of the most important activity for Internet users (AOL, 2010). Despite assumptions about their ability to reach mainstream segments, social media platforms have enabled brands to listen people, to identify their interests and motivations, and then, to start a conversation with mass markets. For instance, Facebook recently reached 750 million users. Twitter had about 200 million users last January whereas geo-location social service Foursquare surpassed 10 million members (Rao, 2011; Chiang, 2011, LA Times, 2011). Consequently, social media is now considered as a mass medium. Indeed, Forrester Research defined Internet-based services as mass media with regards to the number of influence impressions for products   and   services,   the   users’   consumption,   their   impact   on   information   media   as   well as their consideration by large companies such as Procter & Gamble (Ray, 2010). Nevertheless, this recently appeared mass channel tends to require a disruptive approach for companies likely to enter in. In the era of conversation, brands are supposed to adopt a two-way communication process and engage with the audience. As stated by Antony Young, CEO of Optimedia US,  “social  media  is  not  a  strategy,  but  a venue  for  marketers  (…)  that  enables  them  to amplify  and  elevate  brands”  (Young, 2011). That seems to imply that success on this medium is not depending on brands, but on what people say. Furthermore, marketers need  to  understand  that  “the  currency  on  social media is not euros, pesos or dollars, but meaningful  engagement,  participation  and  value  creation”  (Qualman, 2009).
  • 7. 13 Given this new marketing environment, marketers have been increasingly considering “the   imminent   need   to   focus   on   building   personal   two-way   relationships”   as   an   opportunity to amplify interactions between their brands and customers (Kumar et al., 2010). This strategic approach of customer-brand interactions is known as customer engagement, and is partially connected to various major concepts  in  today’s  marketing   such as customer satisfaction, customer value or services quality. Scope of the study Customer   engagement   can   be   defined   as   “a   customer’s   behavioural   manifestation   toward  a  brand  or  firm”  (Van  Doorn  et  al.,  2010).  This  concept  is an emerging research topic for marketing academics as a consequence of empowered consumers and an increasingly   digital   world.   Generally   considered   as   reluctant   to   brands,   “connected   consumers”  seem  to  embrace  brands  on  new  media  platforms.  In  2009,  Razorfish FEED survey   highlighted   that   “78%   of   consumers   welcomed   brand   advertising   on   social   networks”   and   “40%   of   them   were   actually   friends   with   a   brand   on   Myspace   and   Facebook”.   Thus,   digital   consumers   seem   to   have   15%   stronger   relationships   with   brands than offline consumers (Jack, 2009). This interesting fact regarding digital users seems  to  be  confirmed  with  people’s  interest  for  deals,  a  status  of  real  consumers/fans   and a search of entertaining contents (Razorfish, 2009). For instance Starbucks succeeded in driving customers to its outlets while providing them relevant rewards, such as discounts or free products through the use of Foursquare (Van Grove, 2011). Moreover, a US based food truck Kogi BBQ succeeded in engaging with 86000 twitter users as it uses social networks to indicate them where it will deliver its Korean tacos (Gelt, 2009). Both initiatives enabled Starbucks and Kogi BBQ to benefit from increased traffic and to maximize revenues compared to competitors. Indeed, a deep correlation between engagement on social media and financial performance seems to exist, as stated in a 2009 Altimeter study performed among Top 100 Brands (Altimeter, 2009). Objectives of the study As highlighted previously, customer engagement on social media can become a source of business opportunities or even competitive advantage for companies. The purpose of
  • 8. 14 this study is to understand the process of customer engagement and consumers’   motivations to engage with a specific brand and finally to investigate potential opportunities for this brand. To enable an in-depth analysis, this research project will focus on one company, IKEA as this Swedish furniture retailer is involved in international markets and targets wide range of market segments. Research questions will be introduced further.
  • 9. 15 2 Literature Review This chapter aims to develop a better understanding of concepts that seem to play an important role in the area of customer engagement. Current literature provides relevant material related to the specific research objectives, a large part of this background will consist  in  investigating  customers’  motivations  to  engage  with  a  brand  on  social  media,   the  importance  of  customers’  bonds  with  a  brand,  as  well  as  the  type  of  outputs  that   customers are likely to benefit from such a relationship. By referring to various notions connected to engagement and social media usage, this review will provide pertinent theoretical foundations for the design of a conceptual framework. 2.1 Customer Engagement The notion of engagement used to be investigated in various academic disciplines, such as psychology and organizational behaviour. Prior studies on employee-firm interactions   identified   “positive   consequences   at   both   individual   and   organizational   levels”   (Bowden,   2009),   such   as   positive   individuals’   behaviour   (Saks,   2006),   job   satisfaction and high organizational commitment and performance (Salanova et al., 2005). Furthermore, academics also reveal that employee engagement positively contributes in increasing customer satisfaction and loyalty (Bowden, 2009). As a matter of fact, authors have extended the scope of engagement to customer-firm interactions.  McEwen  (2004)  refers  to  engagement  as  “a  measure  of  the  overall  strength   of   company’s   customer   relationships”, that is to say that it   encompasses   “both emotional and rational bonds formed by customers with particular brands”.  In  addition   to   McEwen   (2004),   Patterson   et   al.   (2006)   define   this   concept   as   “the   level   of   customer’s   physical,   cognitive   and   emotional   presence   in   their   relationships with a company”  (Hollebeek,  2010).  On  the  other  hand,  it  tends  to  emphasize  that  customer   engagement is not restricted to transactions, but also behavioural manifestations related to a brand (Van Doorn et al. 2010). Therefore, investigating the concept of customer engagement implies to consider all types of direct brand interactions such as word-of- mouth, customer recommendations and referrals as well as physical interactions commonly defined as customer touchpoints (Hollebeek, 2010). In practice, customers
  • 10. 16 who regularly discuss a brand with peers, interact via online channels with a specific brand or visit a store are considered as individuals who engage. Furthermore, these manifestations   can   be   both   positive   or   negative   and   even   extended   to   company’s stakeholders (Van Doorn et al. 2010) A number of studies tend to clarify the position of customer engagement among other marketing concepts, as literature suggests that engagement has a predictive power on customer loyalty (Hollebeek et al. 2010). Based   on   McEwen’s   definition,   Bowden   (2009) investigates how rational and emotional bonds might impact on customer loyalty.   The   model   developed   from   this   research   underlines   that   “engagement,   as   a   process, arises out of a combination of calculative commitment, following by the development   of   trust,   involvement   and   eventually   affective   commitment”   (Bowden,   2009). While conceptualising the process of customer engagement, Hollebeek (2010) identifies distinct relationships between engagement and a series of marketing constructs related to customer – brand interactions. Firstly, involvement and interactivity appear being two antecedents whereas the concept of flow may act as a psychological antecedent state encouraging customer engagement (Hollebeek, 2010; Patterson et al. 2006). The author classifies   as   engagement   consequences   “rapport,   value   co-creation, brand experience and  perceived  quality”.  Thus,  these  concepts   refer  to   output  behaviours  of  customer- brand  relationships,  although  “rapport”  can  be  considered  as  an inhibitor in the process of engaging existing customers (Hollebeek, 2010). Furthermore, as proposed in Bowden (2009), customer satisfaction, empowerment, trust, commitment, customer value and brand   loyalty   are   viewed   as   “consequences   of   engagement   with   potential positive relationships  between  these”  (Hollebeek,  2010). Figure 1 - Process of Engagement
  • 11. 17 Conceptual models tend to emphasize customer engagement as a holistic approach to consumer behavioural manifestations over time. Customer involvement and interactivity with a specific brand are considered as two initial steps of engagement whereas satisfaction, trust and commitment (both affective and calculative) may enhance it over time, by strengthening customer-brand relationships. Fig.1 shows the process of engagement as conceptualized by Hollebeek (2010; 2011). Besides, it is advisable to consider other dimensions of customer engagement behaviour when investigating such a process. Van Doorn et al. (2010) highlight the choice of channels  as  well  as  consumer’s  purpose  when  engaging  with  a  brand. 2.2 Social Media Although it is commonly restricted to social networking sites (SNS), the notion of social media,  as  defined  by  Kaplan  and  Haenlein  (2009),  refers  to  “Internet-based applications that   help   consumers   share   opinions,   insights,   experience   and   perspectives”.   This   concept encompasses several types of platforms, from collaborative projects to social networks. Kaplan and Haenlein (2010) distinguish 6 distinct types of social media as followed: collaborative projects, blogs, content communities, social networking sites, virtual game worlds and virtual social worlds. 2.2.1 Types of Social Media Collaborative projects emphasize the creation of content through participation of many end-users. Users involved into collaborative platforms may be responsible for generating a specific content (i.e: writing or editing an article on Wikipedia) or simply sharing and organizing relevant media content available online (Solis, 2010). The idea underlying applications such as Wikipedia and social bookmarking service Delicious is to  lead  to  a  better  outcome  by  joining  users’  efforts  (Kaplan  and  Haenlein,  2010).  As  an   example, Wikipedia had over 18 million articles but only 90000 active contributors (Reagle, 2010).
  • 12. 18 Blogs and microblogs are given as one manifestation of user-generated content. Generally managed by a single user, blogs give individuals an opportunity to express and share their opinions through a dedicated medium. However this type of platform enables interaction with other Internet users via comments and may help them in spreading positive or negative feelings related to a brand among other consumers (Kaplan and Haenlein, 2010). In August 2011, there are over 168 million blogs available online  according  Nielsen’s  Blogpulse  (Nielsen,  2011).   To  another  extent,  content  communities  have  enabled  users  to  publish  and  share  “a  wide   range  of  different  media  types”  on  the  Internet.  YouTube  (videos),  FlickR  (pictures)  and   Slideshare (presentations and documents) are among the most popular platforms to publicly publish and share content (Kaplan and Haenlein, 2010). For example, YouTube members upload 48 hours of video every minute while more than 3 billion videos are watched on a daily basis (YouTube, 2011). As a result, the success of video sharing communities is challenging traditional media such as TV and it also empowers individuals to generate online content (Hennig-Thurau et al, 2010). Currently considered as a high popular new media, social networks are applications that enable individuals to create a personal profile and interact with other users. Being active on social communities consists of sharing and publishing any type of objects (i.e: photos, videos, audio files or links) communicating with online contacts and posting updates about his/her activity (Kaplan and Haenlein, 2010; Solis, 2010). In fact, Facebook allows 750 million users to share various types of information with friends and experience a real social life online whereas Twitter provides its 200 million users a microblogging platform on which they can share instant messages (Rao 2011; Chiang, 2011). With a common purpose, geo-location social service Foursquare allows its 10 million users to check-in places they used to go and share personal tips to their online contacts.   Furthermore,   some   authors   emphasize   the   fact   that   “online   communities   complement their real world counterparts and serve as forums for consumers exchanging  their  thoughts  and  ideas”  (Hennig-Thurau et al. 2010). In this way, social networking platforms provide possibilities for consumers to share and interact directly with both individuals and brands (i.e. Facebook pages, Twitter corporate accounts and Foursquare’s  places).
  • 13. 19 In comparison with aforementioned platforms, virtual game worlds and social worlds might be considered differently as these applications are associated with entertainment and differing from real life (i.e. Second Life, World of Warcraft). Through the creation of virtual representations of themselves,  users  interact  with  others  “within  the  constructs   and  missions  of  dedicated  worlds”  (Kaplan  and  Haenlein,  2010;;  Solis,  2010).  Despite  a   virtual context, these applications provide opportunities for companies to promote themselves via game mechanics platforms. For instance, British bank Barclays unveiled in 2010 a virtual game to reach a younger audience. 2.2.2 Characteristics of Social Media Generally,   digital   innovations   have   enabled   audiences   “to   talk   back   and   talk   to   each   other”  without  any  effort  and  encouraged them to play a more active role (Deighton & Kornfeld, 2009; Hennig-Thurau et al., 2010). According to Hennig-Thurau et al. (2010), 5  distinct  characteristics  define  the  concept  of  “new  media”:  “digital,  pro-active, visible, real-time, ubiquitous and networks”.   With regards to digitality and ubiquity, any consumer with an Internet connection is able to blog, write reviews and share content with peers. Otherwise, instantaneity and visibility   of   consumers’   new   media   activities   may   strengthen   relationships between users and contribute in developing intangible but more powerful networks. As a result, proactivity of new media highlight their potential contributions in creating value for both individuals and organisations; i.e: reporting flaws to a company or participating into co-creation projects (Hennig-Thurau et al. 2010). 2.2.3 User participation on social media Due to the bulk of social media platforms available to Internet users, it is advisable to make a distinction in terms of user participation. Early studies have investigated user participation on the Internet, online shopping platforms and social media In the process of identifying opportunities for brands, Li & Bernoff (2007) provide a general classification of user participation on new media, known as   “Social   Technographics   ladder”.   This   framework   aims   at   grouping   users   according   to   six   increasing levels of participation they may reach in their online activities (Li & Bernoff, 2007)
  • 14. 20 Figure 2 - Social Technographics ladder (Forrester, 2010) Spectators As explained in Li & Bernoff (2007), Spectators defines people who generally perform activities   such   as   “reading   blogs   and   customer   reviews,   listening   podcasts   or   watch   videos  on  Youtube”.  In  2010,  68%  of  adult  online  population frequently participated in similar activities (Forrester, 2010). Although this level of participation is compatible with others, Spectators appear less likely to adopt Creator, Conversationalists or Critics behaviours and remain in a traditional way to consume new media platforms (Li & Bernoff, 2007). Joiners To the next level, researchers identify Joiners as users who are active on SNS by maintaining a profile and visiting regularly sites such as Facebook, Myspace or Orkut. Forrester (2010) estimates that Joiners represent 59% of online population and was the youngest category in 2007 Social Technographics (Li & Bernoff, 2007; Forrester, 2010). A study from Pew Research corroborates it as 65% of online adults use SNS in 2011, including 83% in the 18-29 age group (Madden & Zickuhr, 2011).
  • 15. 21 Collectors This   third   level   of   participation   tends   to   introduce   a   variation   concerning   users’   motivations. Internet users who use RSS feeds or bookmark websites in the process of collecting and aggregating information are considered by Li & Bernoff (2007) as Collectors. Collectors behaviour can be related to a professional use of social media and only represent 19% of adult online population (Forrester, 2010). Critics This category of online consumers correlates with the idea of active role offered to the audience enhanced by Hennig-Thurau (2010). Critics are users who respond to content from  others  “by  posting  reviews  of  products,  commenting  on  blogs  or  contributing  to   online   forums”.   About   33%   of   online   population participated regularly in Critics activities (Forrester, 2010). Conversationalists Conversationalists are defined in the typology as “people  who update their statuses on platforms like Facebook and Twitter at least weekly”   (Ray, 2010). Considering implications of social media in terms of instantaneity and user connectivity, Conversationalists, who represent 31% of online population, are likely to play an important role among other users. Indeed, 83% of them generally share opinions or give product advice to friends and relatives (Forrester, 2010; Ray, 2010). Creators The most active level of participation identified by Li & Bernoff (2007) is Creators, which   emphasizes   the   involvement   of   people   who   frequently   “publish   a   blog   or   a   website, upload videos and   write   articles   and   post   them”.   About   23%   of   online   population are frequently expressing themselves by creating on the Internet (Forrester, 2010). In their 2007 study, Li & Bernoff underlined the fact that some of them (14%) were endorsing this role on several platforms.
  • 16. 22 On the contrary, Inactives represent those who do not perform any of the social computing activities aforementioned. These non-participating users represent 19% of online population, and are less likely to engage in electronic word of mouth and influence others (Forrester, 2010). But, Li & Bernoff (2007) point out the fact that Inactives  “can  be  affected  when  the  activities  of  others  get  covered  in  the  news  media”. The  “Social   Technographics  ladder”  provides  a   unique  and  versatile   classification of user participation towards the investigation of customer engagement. First, applying the ladder of participation to SNS enables researchers to measure the level of participation on these platforms, and then to identify differences related to engagement on media. To another extent, it enables measurement of brand-related involvement by classifying user behaviours towards brand-related content. In the process of investigating customer engagement with IKEA, these constructs form a relevant basis to measure the level of customer participation with the brand. Nevertheless, it implies to successively address customer motivations for engaging on these platforms. 2.3 Customer engagement on social media The definition of customer engagement refers to direct brand interactions as customer involvement and interactivity with a specific brand represent two main antecedents to engagement (Hollebeek, 2011). For instance, watching an IKEA commercial on YouTube, liking an official IKEA page on Facebook or checking into an IKEA store via Foursquare will be considered as examples of consumer brand-related online activities (Muntinga et al. 2010). Nevertheless, indirect brand interactions such as electronic word of mouth on blog platforms should be also integrated into the scope of brand-related online activities. For instance, a user-generated blog entry about IKEA might be assimilated to a brand-related content as it enhances user manifestations towards the brand. 2.3.1 Types of Customer Engagement on social media Muntinga et al. (2010) propose a typology of consumer online brand related activities based on Li & Bernoff (2007; 2008). Thus, consumers who perform brand-related
  • 17. 23 online activities can have three usage behaviours: from consuming, contributing, to creating brand related content (see Fig.3). Figure 3 - Typology of Consumers online brand-related activities (Muntinga et al. 2010) These usage types are inherent to the process of engagement as they determine the level of user participation on brand-related online activities. It helps in differentiating consumers based on their involvement, assuming that creating a brand-related content is the highest level of online engagement a consumer may have towards a brand (Muntinga et al., 2010; Li & Bernoff, 2007). Based on the previous usage types, the level of user participation has been conceptualized for 5 social media platforms IKEA consumers are likely to engage with the brand (Fig.4). Nevertheless, it is compulsory to adapt these typologies to each online platform, in order to measure the overall level of customer participation in brand-related activities.
  • 18. 24 Figure 4 - The User Participation ladder (author generated) 2.3.2 The Engagement Ladder In regards to previous frameworks, the level of customer engagement can be ranged according  to  users’  behaviours.  In  order  to  quantify  engagement,  a  4-point measurement scale is elaborated and applied to a number of new media allowing consumers to engage with IKEA. 5 distinct platforms have been selected based on the existence of customer- brand interactions as well as their recent use by brands in advertising campaigns. Facebook, Twitter, Youtube and Foursquare are the most popular platforms for online advertising in 2011, meaning that brands are encouraging both indirect and direct interactions with users (eMarketer, 2011). In complement to social networks and content communities, blogs are the most popular user-generated platforms and deserves great attention in customer engagement as they enable consumers to express themselves and interact about a certain brand (Hennig-Thurau et al. 2011).
  • 19. 25 Figure 5 - The Engagement ladder (author generated) Fig. 5 exhibits 4 levels of engagement consumers have on specific social media platforms.  This  “engagement  ladder”  takes  a  full  consideration  of  existing  variations  on   the basis of customer-brand interactions. For instance, Twitter enables customers and brands to engage in a conversation. Thus, the highest level of engagement is reached when a direct customer-brand interaction (i.e: a direct message (DM) or a mention (@)) occurs. While it is assimilated to other social media in Fig.4, Foursquare does not let users assume a role of creator in brand interactions. Except sharing tips about users, the ultimate  level  of  brand  engagement  is  to  obtain  the  “mayor”  status  of  a  brand-related place (i.e an IKEA store), awarded to the user who visited the more frequently a place over a 60 days period (Foursquare, 2011). As a matter  of  fact,  a  Foursquare  “mayor”  is   assumed to be a loyal customer, therefore a brand advocate among other users. Nevertheless, this minimal difference does not affect the measurement of interactivity between IKEA and its customers.
  • 20. 26 2.3.3 Measuring the overall “Engagement Score” The endeavour to measure the overall level of engagement requires considering at channel importance for customers when engaging with a brand. A recent study from digital agency Razorfish focused on the channel importance and frequency of use to identify the most important consumer engagement channels (Razorfish, 2011:14). Apparently, Google company websites, word of mouth and e-mail are the most preferred channels to connect online with a brand while social media platforms seem to fail  at  meeting  people’s  expectations  (Razorfish,  2011:16).  As  this   study aims to investigate customer engagement on new channels, it is advisable to consider frequency of use and channel importance into the measurement. Media Richness Theory To date, there have not been academic studies, which have investigated channel importance among new media. In their attempt to define social media, Kaplan & Haenlein (2009) provide a classification of social media platforms according to the degree of self-disclosure required and media richness of a specific platform. The concept of self-disclosure   is   related   to   “the amount of personal information that one person  is  willing  to  disclose  to  another”  in  order  to  develop  close  relationships  (Jourard,   1959). Applied to engagement, self-disclosure is compared to the level of interaction between consumers and brands. Alternatively, media richness is concerned with existing  variations  between  media  in  “their ability to enable users to communicate and change understanding”  (Dennis et al. 1999; Draft & Lengel, 1984). It suggests that the richer the medium is, the better understanding it may provide. Figure 6 - Classification of Social Media by media richness and self-disclosure (from Kaplan & Haenlein, 2009)
  • 21. 27 In the context of social media, Kaplan & Haenlein (2009) consider blogs, microblogs and collaborative projects as leaner mediums than SNS and content communities. For example, blogs and collaborative projects are often text-based and do not allow the same level of user interactivity available on social networks (Kaplan & Haenlein, 2009). This classification suggests that certain social media are more appropriate to enhance communication between brands and customers, thus to enable a stronger level of customer engagement. In practice, it means that a fan from one IKEA Facebook page would be able to engage than someone following IKEA on twitter. Although similar assumptions  can  be  raised  for  other  platforms,  the  determination  of  a  “media  richness”   coefficient into the calculation of engagement requires preliminary studies and cannot be applied in this research. Therefore, to simplify the measurement, engagement scores by  platforms  will  be  cumulatively  aggregated  to  obtain  an  overall  “Engagement  score”. 2.4 Motivations for engaging in social media In complement to the level of user participation, identifying key motivations of customers to engage with IKEA on social media is inherent to the process of understanding engagement. Early theories on traditional media, based on television, focused on identifying behaviours and reasons why individuals use a specific media (Quan-Haase & Young, 2010).   “Uses   and   Gratifications”   approach   provides   a   “user-centric functionalist perspective”,   that   appears   to   be   appropriate in the context of engagement in social media, as it emphasizes the importance of media content to gratify audience needs (Calder et.al, 2009; Muntinga et al. 2010; Ruggiero, 2000). McQuail (1983) classifies into four categories motivations for using media: Information, Personal Identity, Integration and social integration and Entertainment (Fig.1). Studies on interactive marketing tend to confirm the validity and potential application of U&G theory to social media (Calder et al. 2009; Bronner and Neijens, 2006; Nambisan and Baron, 2007). However, recent applications of U&G approach include  additional  motivation  categories  compared  to  McQuail’s  framework  (Muntinga et al. 2010).
  • 22. 28 Figure 7 – McQuail’s  typology  of  motivations  in using media Information This type of motivation covers information-related outputs provided by the use of media.   Media   tend   to   help   people   in   “finding   out   relevant   events   and   conditions,   seeking advices and opinions, satisfying curiosity and general interest”  or  even  reducing   risks in decision choices (Calder et al. 2009). Therefore, it is possible to connect consumer’s   motivation   for   information   to   the   growth   of   customer   review   platforms,   blogs, and social networking sites, on which users generally share information. Applying U&G approach to Twitter, Johnson & Yang (2009) identify that information gratifications are main motivations of using Twitter, as positive relationships exist with Twitter use. Personal Identity As stated in Muntinga et al. (2010), media gratifications induced by the personal identity motivation are related to the shelf. Sub-motivations  are  for  example  “finding   reinforcement  for  personal  values”,  self-identification to others and recognition among peers. Identity expression, self-fulfilment and self-enhancement are generally the most important motivations for social using networks and blogs (Muntinga et al. 2010). For instance, being fan on Facebook is a way to promote its shelf by supporting a brand, an organisation or celebrities. Integration and Social Interaction In comparison to Personal Identity, this dimension refers to media gratifications obtained by the interaction with other people. It covers several sub-motivations such as “identifying  with  others  and  gaining  a  sense  of belonging, connecting with friends and
  • 23. 29 family, finding a basis for conversation and substituting real-life   companionship”   (McQuail, 1987; Muntinga et al 2010). Considering social connectivity on SNS, Quan- Haase & Young (2010) discovered that about 85% of their research participants had joined Facebook because of social pressure, being as one of their friends had suggested it. Entertainment As identified in McQuail (1987), media can provide users with four entertainment gratifications   including   “escaping or being diverted from problems, relaxing, getting cultural   or   aesthetic   enjoyment,   passing   time   and   emotional   release”.   While   investigating   users’   active   participation   on   YouTube,   Hanson   &   Haridakis   (2008)   figure out that entertainment is one primary motivation for users to watch and share videos among their peers. Otherwise, Lindqvist et al. (2011) identify that Foursquare rewards (i.e. badges, mayorships) are entertainment gratifications, which motivates in engaging on this location-based service. New types of motivation for U&G approach have emerged from recent academic studies focusing on new media as reviewed in Liu et al. (2010) (Wang & Fesenmaier, 2003; Cheung and Lee, 2009). Muntinga et al. (2010) introduce two relevant motivations while considering brand-related social media use: empowerment and remuneration. Empowerment New   media   have   offered   opportunities   for   individuals   to   “extert   their   influence   or   power”  on  other  users.  As  consumers  have  become  aware  of  it,  previous  studies  suggest   that empowerment is a driver of participation in online communities (Cova & Pace, 2006) and in UGC practices (Berthon et al., 2008). Additionally, social networking sites   tend   to   enhance   consumers’   empowerment   by   encouraging   the   emergence   of   influencers. Johnson & Wang (2009) show that the ability to express himself freely on Twitter is an important social motive for users compared to groups on facebook which succeed in changing the behaviour of brands, such as Cadbury and Nestlé (Meadows- Klue, 2008).
  • 24. 30 Remuneration Consequently  to  growing  brand’s  presence  on  social  media,  remuneration  appears  as  a   driver for people to engage on some platforms. Economic incentives (e.g: money, prize), job-related benefits (e.g. information) or personal wants have been identified in Muntinga et al. (2010) as examples of rewards people may expect. In location-based services, the possibility of getting discounts and special offers generally motivates the use of Foursquare (Lindqvist et al., 2011), whereas Facebook launched local deal services  as  a  way  to  reward  Facebook  Places’  users  (Chang  &  Sun,  2011).  Otherwise,   Zhao & Rosson (2009) underline through a series of interviews the usefulness of microblogging service Twitter in informal communication at work. In accordance to prior studies, the U&G approach identifies relevant motives to user participation.  Unlike  Rodgers’  Web  Motivation  Inventory  that  4  general  motives  of  uses   (Rodgers et al., 2007), the 6 motivation categories focus on audience needs and provide a better understanding of how a brand may gratify it through online interactions with customers. 2.5 Customer-Brand relationship While conceptualizing impacts of customer engagement, Hollebeek (2010; 2011) suggests  the  importance  of  Relationship  Quality,  defined  as  a  “higher-order construct comprising  the  dimensions  of  trust,  commitment  and  customer  satisfaction”.  According   to prior studies, these concepts are positively correlated to the development of relationships between customers and brands, and may lead further to the development of brand loyalty (Bowden et al., 2009). For instance, the dimension of trust tends to turn a customer-brand  relationship  into  more  “emotionally-oriented and affective connections, associated  with  affiliation,  identification  and  attachment”  (Hess  &  Story, 2005; Bowden et al., 2009). McEwen (2004) enhances the requirement of emotional bonds in building strong relationships and defines 4 levels of customer engagement that reflect important emotional bonds in customer-brand   relationships:   “Confidence,   Integrity, Pride, Passion”.  While  confidence  refers  to  customer  trust,  integrity  stands  for  “the  belief  that   a  brand  will  treat  its  customers  with  fairness”.  Beyond  the  level  of  pride  a  consumer  
  • 25. 31 benefits from its personal relationship with brand, the ultimate level of engagement, passion,  is  defined  as  “the  belief  that  the  brand  is  irreplaceable”  and  perfectly  “fits  with   the  customer’s  personal  needs”  (McEwen,  2004). 2.5.1 Emotional attachment and Passion A number of studies continue to investigate passion and emotional attachment in customer-brand interactions (Albert et al., 2008; Yim et al., 2008; Grisaffe & Nguyen, 2010; Patwardhan & Balasubramanian, 2011). Grisaffe & Nguyen (2010) distinguish 5 antecedents of emotional attachment to brands between controllable (i.e. superior marketing characteristics, customer outcomes and user-derived benefits) and less controllable (i.e. socialization, sentimental memory). Based on their study, authors highlight  a  need  to  outperform  customers’  expectations  “to  achieve  attachment-inducing satisfaction”.  To  another  extent,   Yim et  al.  (2008)  suggest  that  “affectionate  ties  that   comprise  both  intimacy  and  passion”  are  inherent  in  order  to  cultivate  customer  loyalty   and   require   a   dynamic   approach,   as   “passion   fades   and   intimacy   gets   challenged”.   However, as explained in Patwardhan & Balasubramanian (2011), emotional attachment is not compulsory in building relationships: according to Park et al. (2009) consumers can be strongly involved with a brand without having developed emotional connections with. For instance, such a behavior may result in people engaging in social media with IKEA but with a poor personal consideration for the brand. Otherwise, the notion of passion and emotional attachment with a brand can be approached from a different manner. Marketers tend to develop customer engagement through the use of passion branding. In an attempt to target an audience, it aims at creating associations between a specific passion platform (i.e. sports, art events) and a brand in order to generate real emotions for potential customers (Duffy & Hooper, 2003). For example, sport events and celebrity endorsements provide opportunities for brands to promote brand attributes as well as brand personality. In the UK, Orange succeeded in engaging customers through innovative arts sponsorships (Duffy & Hooper, 2003). In the context of social media, the notion of passion branding may appear in terms of online published content. A recent AOL study considers content as the fuel of social
  • 26. 32 web  as  “23%  of  social  media  messages  include  links  to  content”  and  “60%  of  content   sharing  message  mention  a  brand  name  or  product”  (AOL, 2010). Implications toward content are important, as it tends to create motivations for engaging with a brand, such becoming a Facebook fan or a follower. On social networking sites, IKEA tends to raise its brand awareness among customers by sharing content dealing with art, home decorating, and provides a subjective value of engagement. 2.5.2 Brand Utility In addition to emotional bonds, McEwen emphasizes the need of rational bonds in customer engagement. Besides the emergence of customer engagement, brands have introduced the notion of brand utility in the way to offer extra value to customers. As explained in Contagious Magazine (2008), brand utility redefines customer-brand relationships  as  “it  is  about  giving  something  away  to  earn  people’s  time  and  attention”.   For example, releasing a branded mobile application and offering an extra free service on social networks are ways to improve brand value for customers and to generate a unique brand experience compared to competitors. To  date,  there  haven’t  been  academic  studies  which  have  been  investigated  the  concept   of brand utility and its impact on consumer engagement. However, a large number of communication campaigns tend to confirm positive impacts on customer-brand relationships. Trend consultancy Trendwatching (2010) identifies 8 categories of utilities brand were likely to provide for their customers including Transparency (information utility), Saving money, Finding, Connectivity, Health, nutrition & exercise, Skills & advice, Eco-friendly (environmental utility) and Tools & amenities This classification is seemingly related to existing motivations of customers to engage with brands,   but   may   provide   accurate   insights   concerning   customers’   expectations   from a focal brand such as IKEA. Fig.8 provides a summarized approach of engagement within customer – brand relationships. Even though academics have different views on the importance of emotional ties on loyalty, it appears possible for brands to reach consumers using appropriate passion points and offering a strong brand utility. Figure 8 - The impact of Engagement in Customer- Brand relationship (author generated)
  • 27. 33 3 Statement of research and hypotheses The preceding discussion reviews existing literature and frameworks of customer engagement as well as other related marketing constructs. Additionally, it makes an attempt to apply conceptual models of customer engagement to social media platforms, while considering specific attributes that may create variations towards traditional engagement. A measurement scale, the engagement ladder, has been generated in order to estimate user engagement on social media. Thus, further research is required to provide a better understanding of how engagement on social media impacts on traditional engagement, consumption as well as customer loyalty. Since there are variations in terms of consumer behaviour towards social media, this study will focus on the following research problem. “How  does  user  engagement  impact  on  customer-brand interactions and to what extent it may leverage the overall customer engagement with a focal brand such as IKEA?” This research problem will be investigated in four different sections. First, the impact of both traditional engagement and online engagement on consumption will be tested. Then, the model of engagement conceptualized by Hollebeek (2010; 2011) will be applied to online engagement and an attempt to define predictors of user engagement will be made. In complement to the identification of predictors, a third section aims to point out how user engagement affects concepts related to customer- brand relationships (i.e satisfaction, loyalty and passion). Finally, a fourth part will focus on possibilities to leverage customer engagement through extra value proposition (brand utility) A – Consumption Hypotheses H1: Consumers who engage offline with IKEA consume more than others. H2: Consumers who engage in social media with IKEA consume more than others.
  • 28. 34 The preceding review does not refer to the impact of consumer engagement on the level of consumption, even though Bowden (2009) make a distinction between new and existing customers concerning the process of engagement. Nevertheless, consumption is inherent to customer-brand relationships and the impact of engagement deserves to be tested. B – Predictors of User Engagement Hypotheses H3: People who participate in social media engage more in social media with IKEA. H4: People who engage offline with IKEA engage in social media platforms. H5: Motivations for engaging with IKEA impacts positively on user engagement H6: Consumers who are satisfied with IKEA experience engage more in social media than others. H7: Consumers who are loyal to IKEA engage more in social media than others. H8: Customers’  passion  about  IKEA  impacts  positively  on  user  engagement. H9: The more positive IKEA image is, the more people engage in social media. H10: People who purchase from IKEA engage more than others. Figure 9 - The Process of Online Engagement (adapted from Hollebeek, 2010; 2011)
  • 29. 35 The conceptual model of Hollebeek (2011) identifies customer involvement and interactivity as antecedents of engagement. Furthermore, the author emphasizes satisfaction and other constructs related to relationship quality as potential antecedents for existing customers. Usually seen as consequences of engagement, loyalty and passion are tested to identify if there are recursive associations with customer engagement. C – Impacts of User Engagement Hypotheses H11: User engagement in social media impacts positively on satisfaction. H12: IKEA consumers who engage in social media are more loyal. H13: User engagement impacts positively on customer passion about IKEA. Hollebeek (2010; 2011) and Bowden (2009) propose that customer satisfaction and customer loyalty are consequences of engagement with potential positive relationships between these constructs. To another extent, McEwen (2004) underlines passion as the apex of customer engagement. D – Brand Utility Hypotheses The notion of brand utility refers in this study to the extra value proposition IKEA is able to offer in the process of strengthening its current bonds with customers. In order to link this concept to customer engagement, it is relevant to test whether the level of IKEA brand utility perceived by customers is predicted by brand passion, loyalty, satisfaction and user engagement. In case one of these constructs is related to customer perceived brand utility, it might infer that IKEA value proposition can influence the process of engagement on social media. Figure 10 - Perceived Brand Utility and User engagement
  • 30. 36 H14: User engagement in social media impacts positively on IKEA perceived brand utility. H15: Consumers who are satisfied with IKEA experience have more positive perceptions of IKEA brand utility. H16: Passion impacts positively on perceptions of IKEA brand utility. H15: Consumers who are loyal to IKEA have more positive perceptions of IKEA brand utility.
  • 31. 37 4 – Methodology This chapter tends to describe the research approach and design used in the course of the study. It will provide the different steps of the research process (i.e. questionnaire design, data sources, data collection) conducted in order to investigate the research problem. The main purpose of the study is to evaluate the impact of user engagement on customer-brand interactions and to identify potential ways to leverage engagement, using IKEA as focal brand. 4.1 Research Purpose The first objective is to determine which research design the study will follow by considering information requirements. Generally, a research problem can be investigated according to three different purposes: exploratory, descriptive and causal (Hair et al., 2003). On   one   hand,   exploratory   research   is   conducted   to   “clarify   a   problem, or identify opportunities”.  Either  secondary  or  primary  data  can  be  used  in  an  unstructured  process   to provide more information on the basis of the investigation (Hair et al., 2003; Zikmund et al., 2009). On the other hand, descriptive research is generally used as a procedure to describe an existing   situation.   It   focuses   on   “collecting   raw   data   and   creating   data   structures”   in   order to determine relations between variables and aspects of a phenomenon (Hair et al., 2003). To another extent, an explanatory  or  causal  approach  aims  to  model  “cause-and-effect relationships   between   several   variables”   in   order   to   highlight   their   impacts   on   the   “outcome  predicted”  (Hair  et  al.,  2003).  Zikmund  &  Babin  (2009)  emphasize  the  use  of   causal research in complement to exploratory and descriptive research, as this technique requires  “a  good  understanding  of  a  situation”. Based on the objectives of the study, the research problem is twofold and requires both descriptive and exploratory researches. First, it aims to describe the concepts of offline
  • 32. 38 and online engagement in order to understand to what extent measured variables tend to impact on the process of engagement. Then, the research will try to explore potential effects of passion and brand utility on the same process among IKEA consumers. 4.2 Research Strategy A research study can be conducted through quantitative and qualitative methods. Quantitative   refers   to   the   use   of   “formalized   surveys   with   predetermined   response   options”  submitted  to  a  large  number  of  respondents while qualitative methods put on emphasis on less structured approaches to collect detailed insights from a small sample (Hair et al., 2003). It is often used in the preliminary stages of research to gain a better understanding of research problems whereas quantitative methods are appropriate to test and verify the validity of hypotheses on a large sample (Zikmund et al., 2009). The process of customer engagement applied throughout the study is based on a conceptual model elaborated from existing literature by Hollebeek (2011). As pointed out by the author, a few academics have investigated the concept of customer/brand engagement to date through the use of qualitative and quantitative researches (Ilic, 2008; Sprott et al., 2009 in Hollebeek, 2011) while motivations of engagement were identified in Muntinga et al. (2010) by using qualitative techniques such as interviews. In addition, aforementioned authors emphasize the need of empirical testing and validation in order to evaluate the consistency of their researches. As this study investigates two forms of customer engagement, quantitative methods will be  used  to  test  empirically  conceptual  models  for  “offline”  and  “online”  engagements,   as defined in Chapter 2. Thus, key findings will potentially help to confirm the relevance  of  Hollebeek’s  model  for  traditional  engagement  and  provide  insights  about   engagement with IKEA. 4.3 Research Method Consequently to the selection of quantitative methods, customer engagement with IKEA was addressed through an online questionnaire. Zikmund et al. (2009) considers that Internet   surveys   allow   the   research   “to   reach   a   large   audience   quickly   and   cost-
  • 33. 39 effectively”  with  a  higher  response  rate.  Furthermore,  it  appears  as  the  most  appropriate   research method to connect with individuals who participate in social media platforms, as the study aims to do. 4.4 Sample Selection The main objective of the study is to evaluate the process of engagement among IKEA consumers. As IKEA is currently established in 42 countries (IKEA, 2011), no restriction related to geographic locations or age was applied. Being an IKEA customer and engaging at least offline with the brand (i.e. visiting stores) was the only requirement to access the study. As defined in Zikmund et al (2009), two general sampling techniques can be used based on a nonzero probability of selection (probability sampling) or personal judgement and convenience (nonprobability sampling). In this study, probability sampling such as snowball technique was used at the launch (i.e. peer recommendations) while nonprobability procedures such as random sampling occurred later (i.e: mass mailing, website links). The use of various sampling techniques tends to minimize risks of sampling errors. For example, using only mass mailing among university students would increase errors related to the representativeness of students and the accuracy of data (Hair et al., 2003). 4.5 Data collection The data were collected through an online questionnaire available in English and French for 5 weeks. Initially, the link was shared via e-mails and social media platforms (Facebook, Twitter, Foursquare) to users who were actually engaging with the brand (i.e. Facebook fans, Foursquare mayors etc.). Furthermore, the questionnaire was also displayed on the home page of IKEA Hackers (http://www.ikeahackers.net/), an online community of IKEA  lovers  interested  in  “modifications  on  and  repurposing  of  IKEA  products”  (IKEA   Hackers, 2011). Moreover, a participation incentive (2 £15 gift cards) was given away to respondents in order to increase level of participation in this 15 minute questionnaire. About 310 individuals took part in the study from early August h to early September but 248 respondents were finally kept for data analysis because of missing data.
  • 34. 40 4.6 Questionnaire Design The questionnaire was developed to measure the constructs highlighted in the theoretical   framework,   which   are   “consumption”,   “offline   engagement”,   “user   participation”,   “user   engagement”,   “motivations   for   engaging”,   “satisfaction”,   “loyalty”,   “passion”,   “brand   image”,   “product   image”   as   well   as   “brand   utility”   (Appendix 1) The questionnaire was structured with regard to the four sections underlined in the statement of research (Table 1). It was made up with 25 questions including 7 demographic items. In order to reduce time and effort required by respondents, most of the questions were close ended, allowing the sample to select an item or a level of intensity (Hair et al., 2003). For example, the level of consumption in the last 12 months was measured on 5-point   scale,   ranging   from   “Never”   to   “7+   times”.   Moreover,   the   level of agreement was assessed on a 5-point Likert scale, considered as the norm. Although academics consider a 7-point scale more reliable, Colman et al. (1997) point out that scores from 5-point and from 7-point are virtually equivalent. Otherwise, respondents  had  the  opportunity  to  provide  extra  information  related  to  “brand  utility”   and  “passion”  thanks  to  open  questions. Besides, a ratio scale was developed in order to evaluate the level of user participation and level of engagement on social media. As emphasized in Chapter 2, respondents were asked to select the level of participation in social media platforms, ranked on 4 distinct  behaviours,  from  “Inactives”  to  “Creators”.  This  ratio  scale  elaborated  from  Li   (2008) and Muntinga et al. (2010) offers the opportunity to identify types of participation and to compare it with other variables (Hair et al., 2003). The same 4-point scale was applied to the concept of user engagement in order to enhance the validity of comparisons between those variables (see Fig 4 and 5, Chapter 2). Table 1 provides further information about the questionnaire design in terms of constructs. Except the development of user participation and engagement scales, the questionnaire integrated some constructs applied in other studies. In fact, reliable and
  • 35. 41 valid scales for Loyalty and Passion were used from a recent research on customer intimacy and passion (Yim et al., 2008). Table 1 - Questionnaire Design Constructs and Questions Scale Adopted from Consumption & Offline Engagement Q1 - Frequency of purchase from IKEA selling points (consumption) 5 point scale (Ordinal) Researcher Q2 - Frequency of visits to IKEA selling points (offline engagement) 5 point scale (Ordinal) Researcher Q3 - Reasons for visiting an IKEA store Rank order scale Researcher Q4 - Loyalty Program Member Yes / No Researcher User Participation Q5 - Frequency of use of social media platforms 5 point scale (Ordinal) Researcher Q6 - Level of Participation in social media 4 point scale (Ratio) Li (2008), Muntinga et al. (2010) User Engagement Q7 - Level of Engagement with IKEA in social media 4 point scale (Ratio) Li (2008), Muntinga et al. (2010) Motivations for engaging Q8 - Motivations to connect with IKEA 5 point Likert scale Muntinga et al. (2010), ExactTarget (2010) Brand Image Q9 - Perceptions of IKEA as a brand 5 point Likert scale Researcher Product Image Q10 - Perceptions of IKEA products 5 point Likert scale Researcher Satisfaction Q11 - Overall Satisfaction 5 point Likert scale Researcher Loyalty Q12 - Level of loyalty 5 point Likert scale Yim et al. (2008) Passion Q13 - Level of Passion 5 point Likert scale Yim et al. (2008) Q14 - Passion platforms Nominal scale Researcher Brand Utility Q15 - Types of Brand Utility 5 point Likert scale Contagious (2008), TrendWatching (2010) Q16 - Brand Utility platforms 5 point Likert scale Researcher
  • 36. 42 4.7 Pilot study As shown in the previous section, a number of research questions were newly developed based on Chapter 2. In order to evaluate the validity of the framework, a pilot study was conducted. According to Hunt et al.1989, it might help in avoiding issues with  “ambiguous  word,  inappropriate  vocabulary  and  scaling  methods”. Thus, an initial questionnaire was pre-tested among a sample of 17 students to ascertain the adequacy of the framework with the investigated research problem as well as the need for introducing more questions. On one hand, pre-testing the questionnaire contributes in evaluating items related to motivation factors and brand utility. Factor analyses highlight a need for reformulating some variables while a new question related to brand utility platforms was introduced into the final questionnaire. 4.8 Validity and Reliability Although a pilot study was run prior the launch of final questionnaire, it is advisable to assess the quality of results by looking at the validity and reliability of constructs. Validity refers to the extent a measure of a concept is accurate while reliability represents the internal consistency of a measure (Zikmund et al. 2009). In the process of statistical analyses, these two concepts will have to be verified to avoid measurement issues, for instance, when running confirmatory factor analyses. 4.9 Measurement implications Due to the inexistence of reliable measurement scales, Chapter 2 introduced the notion of user engagement score as an aggregate score of the engagement level a respondent has on each platform. For example, an individual who only engages with IKEA on Facebook as a fan will have an overall engagement score of 6 (Facebook: 2; Twitter: 1; Youtube: 1; Foursquare: 1; Blogs: 1). This empirical measurement scale implies that the higher the overall score is, the more an individual engages with IKEA.
  • 37. 43 5 Results and analysis 5.1 Profile of respondents The total number of respondents who took part in this study was 305. However, missing values were identified on engagement-related variables, contributing in the exclusion of 57 respondents from the analysis. Table 1 (in Appendix 2) shows the basic information about the surveyed population. The sample was divided between 185 females (74,6%) and 63 males (25,4%), therefore it was not equally representative in terms of gender. Respondents were relatively young as the mean age was 27.99 years old. Indeed, 48.4% of the respondents were aged 24 and below whilst the total number of the 35+ respondents was approximately equal to 17% (see Fig.11). Consequently to the use of both French and English surveys, 41.5% of the sample was living in France while the UK and the US accounted respectively for 24.6% and 16.1% of respondents’   provenance.   The   remaining   18% of respondents were from 22 other countries, including Germany, Spain, Australia, Canada and China (see Fig.12). When considering their current occupations, 50% of respondents were students whilst 36.7% of them were employed in organizations. Moreover, only 5.6% of the sample are considered as economically inactive (i.e. retired, housewives and unemployed persons) Figure 11 - Age of Respondents Figure 12 - Country of Residence
  • 38. 44 while   “Others”   mainly   consisted   of   apprentices,   entrepreneurs   and   the self-employed person. Furthermore, the proportion of respondents who were living in close proximity to an IKEA store was approximately equal to 47%, which implies potential variations in terms of frequency of visits among respondents. 5.2 Consumer Behaviour with IKEA The starting point of this study is to investigate respondent behaviour as an IKEA consumer. It aims to define the level of consumption, the level of offline engagement with the brand as well as their loyalty over the last 12 months. 5.2.1 IKEA purchases over the last 12 months In order to identify the level of consumption among respondents, three different types of purchases were considered according to the available selling points used by IKEA: stores, official websites and catalogues. Respondents were asked to estimate the number of times they purchased items at IKEA during the year. Figure 13 - Current Occupation Figure 14 - IKEA purchases over the last 12 months
  • 39. 45 First, 35.1% of respondents used to purchase 2 to 3 times in IKEA stores over the last years whereas a quarter of the total (25.8%) purchased more than 4 times. Nevertheless, only 12.5% of the sample did not consume in any IKEA store during the same period. When considering other selling points, a large majority of respondents (respectively 89.1% and 89.9%) have never purchased from the IKEA websites and catalogues. 5.2% of the respondents purchased once from the website while 5.6% of them ordered online more than 2 times over the last 12 months. In contrast, 6.4% ordered more than 2 times using the catalogues as selling points. Results show that the respondents were not familiar with purchasing on IKEA websites and via the official IKEA catalogue. Based on these findings, an overall score for consumption is calculated for each respondent. As shown in Appendix 3, consumption score has a mean equal to 5.2258, which is quite low (min= 3; max = 14). 5.2.2 Offline Engagement With  regards  to  Hollebeek’s  definition  of  customer  engagement,  this  study  will  define   as   “offline   engagement”   direct   interactions   occurring   between   IKEA   and   customers   outside social media environment. Thus, offline engagement will refer to the level of interactivity respondents experienced with the brand on the aforementioned selling points along the last 12 months. Figure 15 - Offline Engagement in the 6 months
  • 40. 46 Results point out that catalogues and websites are the two most frequently used touch- points (see Appendix 4). Indeed, when considering respondents interacting regularly with IKEA, 25.7% of the sample visited IKEA websites, 20.9% of them browsed through an IKEA catalogue while a tenth (9.7%) went to an IKEA store more than once a month. In fact, a majority of respondents estimated to have visited a store less than 12 times during the last year (66,9%). Nevertheless, IKEA stores appear as the most used touch-points, as only 24.2% of the sample admitted visiting it less than once a year, compared to 40.7% for catalogue readings. Similarly to consumption variables, an overall score for offline engagement is calculated. The mean of offline engagement among respondents is 5.8 (min= 3; max= 12). 5.2.3 Reasons for visiting an IKEA store Reasons for visiting stores are inherent to understand variations in consumer behaviour as IKEA provides non-related in-stores services such as low cost catering. All respondents were asked to rank from 1 to 5 possible reasons for going to an IKEA store. Based on analysis of frequencies (Fig.16),  “looking  for  furniture”  is  the  primary  reason   for visiting an IKEA store according to 37.9% of respondents. The second reason appears  to  be  “looking  for  furnishing  items”  for  37.5% of the sample whereas the third motive consists of getting some inspiration (35.9%). Finally, “window-shopping” and “going to an IKEA restaurant” are respectively the fourth and fifth reasons to visit a Figure 16 - Reasons for visiting an IKEA store
  • 41. 47 store. Nevertheless, results highlight some variations among respondents; with for example 37.5%  of  them  stating  that  “looking  for  furnishing  items”  is  the  main  reason.   These differences will be considered later on in the discussion. 5.3 The use of Social Media among respondents As this research focuses on social media platforms, the use of new media was investigated among the sample. Indeed, respondents were asked to define the frequency of use as well as the level of participation in 5 of the most commonly used platforms: Facebook, YouTube, Twitter, Foursquare and blogs. 5.3.1 Frequency of Use The questionnaire addressed the use of social media by asking respondents to estimate the frequency of use over the last 6 months according to a 5-point Likert scale (from Never to Very Often). First, the analysis of means points out the fact that Facebook (4.37) and YouTube (4.15) are the two platforms most frequently used. Meanwhile, respondents appear to be less familiar with the use of Foursquare (1,46) (see Appendix 6). Figure 17 - Use of Social Media
  • 42. 48 As displayed in Fig. 12, respondents often use Facebook (72.6%), YouTube (48.4%) and blogs (29%). On the contrary, Twitter and Foursquare are two platforms that respondents use less frequently with respectively 48.4% and 82.7% of them who did not connected recently 5.3.2 Level of Participation As mentioned in Chapter 2, the level of participation in social media was measured according to a 4 point-scale. Thus, respondents were required to select the most relevant item towards their   type   of   participation   in   these   platforms,   for   example   from   “I’m   inactive”  to  “I  have  created  a  fan  page” in Facebook. Considering blogs (Fig.18), 42.3% of all respondents tend to be spectators by reading blog posts whereas almost 16.9% participates one step further by reading and writing comments. Equally, 16.9% of the sample consists of creators, as these users write themselves posts. As previously shown with the frequency of use, a large majority of respondents (98%) are active on YouTube. It consisted in watching videos (73.4%), watching and commenting (17.7%) while the remaining 6.9% of respondents publish videos (Fig.19). Facebook tends to encourage user Figure 20 - User participation in Facebook Figure 19 - User participation in YouTubeFigure 18 - User participation in blogs
  • 43. 49 contribution and creation as 56.9% of respondents share content with their friends and 18.5% of the sample has even created a fan page or group. Nonetheless, about 7.7% of the respondents are not active on this particular social network (Fig.20) As shown in Fig.21 and 22, Twitter and Foursquare have the largest proportion of inactive users, with respectively 54.4% and 83.5% of respondents. However, 14.1% of respondents were using micro-blogging platform Twitter to create conversation with other users. Concerning Foursquare, 6% of the sample was actually participating as creators, by sharing tips about places. Even though further analysis will be carried out on user online participation, previous outputs emphasize probable impacts of demographics on the adoption and use of social media platforms. Otherwise, the study takes into account an aggregate score of user participation in order to evaluate its whole impact on consumer engagement. On average, the user participation score among respondents is equal 10,6 (min= 5; max 20). 5.4 User Engagement with IKEA in Social Media Chapter 2 referred to user engagement as the level of interactions occurring on social media between users and a particular brand. The level of engagement was measured similarly to user participation, using a 4-point scale based on 4 existing user types and adapted to each platform (see Appendix 7). For example, respondents could define their engagement with IKEA on YouTube  from  “Never”  (Inactives) to  “I  have published a video  about  IKEA”  (Creators). Figure 22 - User participation in Twitter Figure 21 - User participation in Foursquare
  • 44. 50 Fig. 23 highlights variations among respondents who had already engaged with IKEA on new media platforms at the time of the study. As a consequence of low user participation and their newness, Foursquare and Twitter are two digital platforms on which the sample engages with IKEA the least. When considering the tenth of respondents engaging in Foursquare, 4.8% of them have already checked-in an IKEA store while 4.4% have contributed by sharing tips within platform users. Moreover, Twitter was used by 7.2% of all respondents in the process of engaging with IKEA. Even though only 8 individuals were following an IKEA account (3.2%), 8 have already retweeted an IKEA related message (3%) while 2 respondents experienced previously a direct exchange with the brand. Besides, 21% of all respondents have already interacted with an IKEA fan page on Facebook. While 10.9% of the sample was fan of the brand, 22 individuals (8.9%) have endorsed a role of contributor by liking or commenting an entry. Otherwise, YouTube and blog platforms consisted of two relevant engagement platforms as they represent respectively 32.2% and 37.1% of all respondents. In a similar way, a large majority of individuals engaging with IKEA via such a platform act generally as spectators by watching videos (27%) or reading a blog entry about the brand (26.2%). Nevertheless, results underline that individuals are more likely to express themselves about IKEA by writing blog entries (2.0%) than editing a video (0.4%) or writing on a Facebook page (1.2%). Figure 23 - User Engagement with IKEA
  • 45. 51 When aggregating a “user   engagement”   score   for   each   respondent,   the   level   of   engagement in this sample appears to be low (mean= 6,45 with min=5; max=17). 5.5 Motivations for engaging with IKEA Based on literature review, a series of 13 statements were used to measure 6 potential motivations for respondents to engage in social media. A confirmatory factor analysis was carried out to reduce items into smaller factors and later, to test prior assumptions identified in Chapter 2. (Pallant, 2001) 5.5.1 Confirmatory Factor Analysis In regards with motives predefined in Chapter 2, “Renumeration”,   “Information”,   “Personal   Identity”,   “Empowerment”,   “Integration   Social”   and “Entertainment” were tested through confirmatory factor analyses (see Appendix 8). It requires an assessment of the suitability and factorability by looking at the Kaiser-Meyer-Olkin measure of sampling   adequacy   and   the   Bartlett’s   test   of   sphericity.   According   to Tabachnik & Fidell  (1996),  the  KMO  measure  should  be  higher  than  .6  while  the  Bartlett’s  test  of   sphericity must be significant (p < .005) in order to provide a good factor analysis (Pallant, 2001). According to Pallant (2001), the appropriateness of these factors has to be confirmed with two characteristics: reliability and validity. In case each factor appears to be reliable and valid, it implies that motives can be generalized to other studies. 5.5.2 Reliability of scale The reliability of scale must be tested for each factor in order to control the internal consistency of measurement and confirm their relevance (Pallant, 2001). To  confirm  the  consistency  of  a  factor,  Cronbach’s  alpha  coefficient  has to be ideally above 0.7 however values between 0.6 and 0.7 are acceptable. Furthermore, it is advisable to consider a high sensitivity of Cronbach’s  alpha which is sensitive towards the number of items (Pallant, 2001:85). Results displayed in Table 1 confirm the reliability of 4 factors   (“Renumeration”,   “Information”,   “Personal   Identity” and
  • 46. 52 “Enpowerment”)  while  2  others  (“Entertainment”  and  “Integration  Social”)  fail to reach an  acceptable  Cronbach’s  alpha  value.  A closer look at the validity will provide more information about issues occurring with these two factors. Table 2 – Motivation factors and Reliability of Scale Factors KMO Total Variance explained Cronbach α   Renumeration I want to receive discounts and promotions. 0.5 81,99% 0.780 I want to get free products. Information 0.5 74,30% 0.653I want to learn about IKEA as a company. I want to stay informed about IKEA (future products). Personal Identity 0.5 74,20% 0.652A friend recommends me to like / follow IKEA. I want to show to others my support to IKEA. Empowerment 0.669 65,50% 0.736 I want to benefit from customer service. I want to share my opinions and ideas directly with IKEA. I want to get access to exclusive content. Integration Social 0.5 69,60% 0.564 I want to interact and share my interest with people about IKEA. I want to take part in challenges or events organised by IKEA. Entertainment 0.5 68,37% 0.537I want to get fun and entertainment from content. I want to enter a contest organised by IKEA. 5.5.3 Construct Validity Campbell & Friske (1959) distinguish two subcategories of construct validity as requirements   “for   the   justification   of   novel   measures”:   convergent   validity   and   discriminant validity. Convergent validity is demonstrated if higher correlations between items occur within the same factor. In complement, discriminant validity is achieved if the strength of correlation is higher with items apart of the same factor than with   other   factors’ items. Therefore, it is required to look carefully at correlations between all 13 items, to detect factors that overlap. Appendix 9 shows inter-correlations between items. Except “Renumeration”   factor,   other predefined motivation factors are invalid, because of not meeting conditions above. According to Bagozzi et al. (1991), measurement errors, such as invalid constructs, might potentially threaten the validity of research results. Thus, the research
  • 47. 53 will not consider previous motivation categories and an exploratory factor analysis must be carried out to define valid factors. 5.5.4 Exploratory Factor analysis As a result, two components with an eigenvalue over 1 were extracted (Appendix 10). Factor 1 consisted of 9 items (explaining 34.686 of total variance) whereas Factor 2 was made of 4 items (for 23,458 of total variance). Nonetheless, several cross-loading items were found and deleted as they load above 0.32 on both factors (Tabachnick & Fidell, 2001). A second EFA excluding cross-loading items was run and resulted in 2 factors explaining 62,767% of total variance.   Factor   1,   named   as   “Brand   Interaction”   and   Factor   2   “Extra   value   for   Customers”   met   respectively   conditions   of   reliability   with Cronbach’s  alphas  above  0.7,  as  displayed  in  Table  2. Motivations   of   “Brand   interaction”   are   related   to   the   intrinsic   value   that   IKEA   may   provide to individuals through online interaction. For example, providing information, listening to customer opinions or offering entertainment may enhance customer experience   and   IKEA  core  values.   On  the  opposite,  motivations  of  “extra  value”  are   restricted to IKEA products and services and enhance consumer interests in extrinsic rewards such as vouchers and free products. Table 3 - Motivation factors Factors Cronbach  α   Factor 1 - Brand interaction 0.816 I want to get fun and entertainment from content. I want to interact and share my interest with people about IKEA. I want to share my opinions and ideas directly with IKEA. I want to learn about IKEA as a company. I want to show to others my support to IKEA. Factor 2 - Extra value for customers 0.773 I want to receive discounts and promotions. I want to get free products. I want to benefit from customer service. Items deleted due to cross-loading I want to stay informed about IKEA (future products). I want to enter a contest organised by IKEA. I want to take part in challenges or events organised by IKEA. I want to get access to exclusive content. A friend recommends me to like / follow IKEA.
  • 48. 54 5.6 Relationship Quality 5.6.1 Satisfaction Respondents   were   asked   to   rate   their   overall   satisfaction   from   “not   at   all”   to   “extremely”.  Generally, most of the sample (79%) was more than very satisfied with the IKEA experience while about 18.5% of respondents were moderately satisfied (see. Appendix 11). 5.6.2 Loyalty As mentioned in methodology, a series of 3 items was used to measure loyalty among respondents. Almost 66% of the sample tends to agree that IKEA was their first furniture store they chose in order to buy furniture. To another extent, less than 40% of all respondents would remain IKEA customers if prices increase (Appendix 12). To consider the impact of loyalty on customer engagement, a factor analysis was carried out. One component with an eigenvalue over 1 was extracted and explained 65.444% of total variance. Furthermore, this component was reliable (Cronbach’s alpha = .722), therefore it will be integrated in further analyses (Appendix 12). 5.6.3 Passion Like loyalty,  consumers’  passion  for  IKEA  was  measured  with  3  items. More than 60% of all respondents agree that going to an IKEA store will never bored them, whereas 40% of them stated that they love IKEA. A factor analysis was also used to extract a single component of passion (explaining 73.07% of total variance) and the high coefficient of reliability   (Cronbach’s   alpha   =   0.815) implies its use further (Appendix 13). 5.6.4 Brand Image Moreover, IKEA brand image among the sample was evaluated with three items related to reputation, ethics and eco-friendliness. Respondents have generally positive opinions
  • 49. 55 toward IKEA as a company. A majority of them (87%) agreed that it is a well-reputed company even though 45% were neutral about ethical practices. To measure potential impacts of brand image on engagement, one reliable factor was extracted (Total variance explained = 70,195; Cronbach alpha = 0.788). 5.6.5 Product Image Consumers’  opinions about IKEA were measured with 5 items in relation with product characteristics for design, price and functionality (Appendix 14). A factor analysis was used to extract smaller factors but two items were cross-loadings (i.e. functionality) or simply inaccurate (i.e. unconventional design). Once irrelevant variables dismissed, two factors “Product  Design”  and  “Price  attractiveness”  were finally extracted (explaining 75,815% of total variance).  “Product  Design”  (3  items)  was  reliable  (Cronbach  alpha=   .732)  where  “Price  attractiveness”  was  only  made  of  one  item. 5.7 Passion points and brand utility Chapter 2 widens the notion of customer–brand interactions to the development of emotional and rational bonds. Investigating IKEA-related passion platforms and brand utility in social media platforms aimed at providing insights about existing bonds between IKEA and respondents. For instance, some passion platforms could enhance motivations for brand interaction while the perceptions of IKEA brand utility could raise the interest of people in engaging with the brand. 5.7.1 Passion points To discover IKEA-related interests, respondents were invited to choose out of 20, 3 centres of interest likely to evoke their passion for IKEA. However, the questionnaire enabled respondents to propose other interests.
  • 50. 56 Respondents tend to frequently associate IKEA   with   “Do-it-Yourself”,   “Art/Design”,   “Crafts”,  “Cooking”  as well as “time  with  relatives”. These particular interests might evoke IKEA as they imply a close proximity with IKEA products or shared values with the brand. Consequently, people may refer to the brand when practising for example a do-it-yourself activity. Further implications of passion platforms will be discussed later (Appendix 15). 5.7.2 Brand Utility Brand utility was measured through the use of 14 concrete examples of utilities IKEA may provide to improve daily life of consumers. Respondents were asked to select their level of interest for each proposition. (Appendix 15) An exploratory factor analysis was carried out to identify distinct categories of brand utility and their potential impact on customer passion and engagement. Indeed, the more interesting utilities are, the more consumers should be likely to interact with IKEA. Four factors assuming conditions of factorability and reliability were finally extracted. To strengthen factor structures, two items with high cross-loadings were withdrawn (Tabachnick & Fidell, 2001). Table 3 summarizes several types of brand utility IKEA might provide to its consumers, as presented  in  Chapter  2:  “Connectivity”,  “Altruism  /   Eco-friendliness”,  “Skills  &  Advices”  and  “Saving  Money”.   Figure 20 – IKEA-related interests
  • 51. 57 Table 4 - 4 types of IKEA Brand Utility Factors KMO Total Variance explained Cronbach α   Factor 1 - Connectivity / Transparency By enabling me to connect in real life with people living in my city 0.694 49,82% 0.655 By sponsoring and curating art events (exhibitions, performance) By sharing tips about Best Things to do in the city I live at the moment By learning me Cultural tips about Sweden and Swedes Factor 2 - Altruism / Eco-friendliness 0.637 59,57% 0.6583 By providing more information about environment impact of product I buy By creating an online service to support non-profit organizations (..) By giving 1% of consumers' spending to a local charity consumers choose Factor 3 - Skills & advices 0.653 58,48% 0,644 By offering online How to video guides to help me in assembling furnitures By launching online based consumer community By offering me in-store tutorials on how to assemble furnitures Factor 4 - Saving Money 0.500 72,54% 0,621 By offering vouchers, free samples to reward my regular coming in stores By helping consumers to customize their furnitures at low price Items deleted due to cross-loading By helping me in adopting eco-responsible behaviour in my daily routine By letting me know promotional offers about products I'm interested in Similarly to previous constructs, an overall score of brand utility is measured and will be   integrated   in   further   analyses   as   “perceived   brand   utility”   variable   (mean=   49,07   with min=25; max=70) (see Appendix 15). Otherwise, the importance of brand utility platforms was also subjected to analysis. Respondents were asked to evaluate their preferences between mobile apps, blogs, printed magazines or branded entertainment. By looking at statistical means (Table 4.), the sample appeared considering a traditional blog (mean= 3.29), an extra service in stores (mean=3.20) or a mobile app as a valuable platform to provide them brand utility. Even though widgets and branded entertainment were seen less useful, differences in terms of user participation in social media will require a closer look. Table 5 - Preferences in terms of brand utility platforms Brand utility platforms Means Official blog/website 3.29 Extra service in store / streets 3.20 Mobile applications 3.03 Print  media  (magazine…) 3.00 Branded entertainment 2.70 Widgets 2.70
  • 52. 58 5.8 Regression analyses In the process of clarifying relationships between all constructs, multiple regression analyses were carried out to confirm theoretical assumptions on customer engagement in social media. Multiple regression analyses help in examining the influence of a set of independent  variables  on  a  “dependent  variable of  interest”  and  in  providing the best predictor for a particular outcome (Hair et al., 2003; Pallant, 2001). Hypothesis drawn in Chapter 3 from the model of online customer engagement will be partly tested through regression analyses. 5.8.1 Consumption According to literature, customer engagement is generally considered as a positive contributor to consumption. However, other considerations in customer-brand interactions such as satisfaction, loyalty or passion may encourage individuals to increase their level of consumption. To assess potential contributions in consumption, a multiple regression analysis was run including dimensions of engagement as well as other predefined constructs. The initial step of regression analysis is to evaluate to which extent independent variables explain the total variation in the dependent variable, using the value of R- square (Pallant, 2001). As the value of R-square equals 0.307, this implies that all independent variables can explain 30,7% of total variance in consumption (Appendix 16). Then, the overall significance of regression model is tested with an analysis of variance. The ANOVA table confirms the existence of linear relationship between consumption and other variables, as the significant level p equals 0.00. Finally, a closer look at beta coefficients provides the contribution of each variable in predicting  consumption.  As  displayed  in  the  “Coefficients  table”  (Appendix  16),  three variables tend to significantly impact on consumption: offline engagement, user engagement and a motivation factor  “Brand  interaction”.  
  • 53. 59 Offline engagement is the main predictor variable of consumption with a beta value of 0.410 (p=.000) while user engagement positively impacts on consumption (b= 0.291; p=.000). This underlines that consumers who engage with IKEA on selling points and social media tend to consume more than less-engaged individuals. Nevertheless,  “brand  interaction”  factor  is  significantly  related  to  consumption,  but  with   a negative beta value. This means that   lower   interests   in   “brand   interaction”   are   associated with higher levels of consumption. Ultimately, users engaging with IKEA for such a motivation will consume less than others. Consequently to these findings, hypotheses related to consumption H1 and H2 have been verified. 5.8.2 Predictors of User Engagement Chapter 2 tends to connect customer engagement with a series of constructs both potential predictors and consequences. These theoretical assumptions must be analysed when investigating user engagement to see whether social media platforms are subject to differences in terms of engagement. The following analysis tests hypotheses from H3 to H11. As shown in Appendix 17, almost 58% of total variance in user engagement can be explained with all concepts related to customer-brand interactions while the ANOVA table confirms the significance of this regression model (p=.000). According to the Coefficients table (Appendix 17), six independent variables out of sixteen appear as significant   predictors   of   user   engagements:   “offline   engagement”, motivations for “brand   interaction”   and   “extra   value   for   customers”,   “user   participation”,   “price   attractiveness”  and  “consumption”.   Results show that user participation in social media is the stronger predicting variable for user engagement (b= 0.442; p=.000), as engaging with a brand implies to be active on new media. This statement appears consistent with offline engagement according to its positive impact on the dependent variable (b=0.240; p=.000). Secondly, motivations for interacting with IKEA are contributing to the level of user engagement (b= 0.258; p=.000)   whereas   “extra   value   for   customers”   is   negatively   correlated with it (b= -0.106; p=.037). As a consequence, individuals more interested
  • 54. 60 IKEA intrinsic value (i.e. content, advices) are likely to engage more than those looking for extrinsic value (i.e. rewards). Consumption seems to impact positively on user engagement with a beta value of 0.178 (p=.000). Thus, a recursive relationship exists between the two variables. Finally,   “price   attractiveness” has a low negative relationship with user engagement (b=-0.096;;   p=.037).   Similarly   to   motivations   for   “extra   value”,   this   variable   slightly   induces a weaker engagement among those who consider IKEA as price attractive. The preceding analysis introduces two sub-hypotheses for H5 and H10 and fully confirms several hypotheses (H3, H4, H11). Nevertheless four theoretical assumptions were rejected (H6, H7, H8, H9). 5.8.3 Predictors of Offline Engagement Although the main purpose of the study is to investigate engagement in social media platforms, the impact of offline engagement on the overall model (see Chapter 3) deserves more attention as  the  variable  is  significantly  contributing  to  “consumption”   and  “user  engagement”.   As exhibited in Appendix 18, a 43,3% of variations in offline engagement was explained   by   10   variables.   Table   5   distinguishes   “consumption”,   “user   engagement”,   “loyalty”   and   “passion”   as   strong   predicting   variables,   while   “product   design”   and   motivations   of   “extra   value”   seem   to   negatively   impact on traditional engagement. Based on this, Hypothesis n°15 is verified. Table 6 - Predictors of Offline Engagement Predictors of Offline Engagement Beta value Sig. Consumption .298 .000 User Engagement .223 .000 Brand Interaction (Motive) .046 .450 Extra Value for Customers (Motive) -.115 .023 Satisfaction .039 .554 Loyalty .180 .010 Passion .223 .001 Brand Image .019 .754 Product Design -.133 .032 Price Attractiveness .024 .645
  • 55. 61 5.8.4 Relationship Quality and User Engagement With regards to existing models mentioned in Chapter 2, impacts of engagement on customer-brand relationship need to be addressed when dealing with social media. Chapter 2 underlines several assumptions between customer engagement, consumption- related constructs (satisfaction, loyalty) and affective connections (passion). Using multiple regression analyses, predictors of each construct will be identified and then compared to hypotheses from Chapter 3. 5.8.4.1 Predictors of satisfaction Results exhibit in Appendix 19 do not provide support to a direct causality between satisfaction and user engagement. Even though the regression model was significant and only explained 14,7% of total variance in satisfaction, four predictors of satisfaction were identified as shown in Table 6. Table 7 - Predictors of Satisfaction Offline  engagement  and  motivations  for  “Brand  Interaction”  are the main predictors of customer satisfaction with b value over .2 while consumption contributes less in prediction. However, the variable of user engagement has a negative relationship with satisfaction, meaning that the higher level of user engagement is, the less satisfied individuals are. This particular finding may be corroborated with aforementioned motivations   for   “Brand   Interaction”,   and   particularly   user   engagement   as   a   way allowing customers to express their dissatisfaction to IKEA. Besides, the second motive for engaging with IKEA was not significant toward satisfaction. Predictors of Satisfaction Beta value Sig. Offline Engagement .249 .001 Consumption .138 .046 User Engagement - 0.164 .028 Brand Interaction (Motive) .215 .002 Extra Value for Customers (Motive) .062 .302
  • 56. 62 5.8.4.2 Predictors of Loyalty The following analysis attempts to identify potential predictors of customer loyalty among engagement-related concepts. The impact of satisfaction on loyalty, considered in literature as inherent, was also tested. The regression model was significant and able to explain 41,1% of total variance in loyalty (Appendix 20). As exhibited in Table 7, satisfaction is the strongest predicting variable of loyalty (b=.482; p=.000), while offline engagement also contributes significantly in customer loyalty. Moreover, motivations for brand interaction seem to be positively associated with loyalty. Indeed it is consistent that people who engage for interacting with IKEA are more loyal than those who engage for extrinsic rewards. Table 8 - Regression of Loyalty Predictors of Loyalty Beta value Sig. Offline Engagement .219 .001 Consumption .021 .721 User Engagement -.100 .110 Brand Interaction (Motive) .162 .007 Extra Value for Customers (Motive) .056 .264 Satisfaction .482 .000 5.8.4.3 Predictors of Passion Chapter 2 emphasizes passion as the apex of customer engagement, encompassing all aforementioned constructs. As exhibited in Appendix 21, the significant level of the regression model used was confirmed and 48,6% of total variance in passion was explained by selected independent variables. Table 8 provides consistent results toward passion as an emotional state of mind predicted by satisfaction (b= .218; p=.000) and loyalty (b= .208; p=.002). Motivations for brand interaction (b= .156; p=.007) and offline engagement (b= .202; p= .001) impact positively on customer passion in a similar way than they do with other previous emotional concepts.
  • 57. 63 Table 9 - Regression of Passion against Engagement, Satisfaction, Loyalty These findings tend to reject some hypotheses referring to the positive impact of user engagement on satisfaction (H12), loyalty (H13) and passion (H14). User engagement does not have any direct influence on loyalty and passion while a negative relationship exists with satisfaction. 5.9 Brand Utility The notion of brand utility offers a different approach to customer-brand relationships as it is seen as an extra value for people. Although this concept is not covered in existing models of engagement, assessing its potential impacts on customer engagement might emphasize the importance of specific value proposition for IKEA. 5.9.1 Predictors of Perceived Brand Utility First, a multiple regression analysis was carried out to identify whether relationships between consumers’ perceived brand utility and other constructs exist or not. As displayed in Appendix 22, the R-square value of 0,326 implies that all variables included can explain 32.6% of total variance in perceived brand utility. Moreover, the overall significance of the regression model is confirmed with the ANOVA table (p=.000). Predictors of Passion Beta value Sig. Offline Engagement .202 .001 Consumption -.038 .485 User Engagement .055 .362 Brand Interaction (Motive) .156 .007 Extra Value for Customers (Motive) .064 .183 Satisfaction .218 .000 Loyalty .208 .002 Brand Image .102 .082 Price Attractiveness (Cheap products) -.066 .187 Product Design .127 .031
  • 58. 64 Table 10 - Predictors of Perceived Brand Utility Predictors of Perceived Brand Utility Beta value Sig. Consumption .064 .306 User Engagement .021 .758 Brand Interaction (Motive) .387 .000 Extra Value for Customers (Motive) .301 .000 Satisfaction .053 .442 Loyalty .080 .185 Passion .095 .001 Offline Engagement -.166 .018 Results in Table 9 do not provide support to direct relationships between brand utility and user engagement. Nonetheless, motivations, passion and offline engagement seem to contribute significantly to the way individuals perceive IKEA brand utility. Motivations   of   “brand   interaction”   and   “extra   value   for   customers”   are   the   main   predictor variables of brand utility. The feeling of passion that consumers experience with IKEA also impacts perceived brand utility. Furthermore, offline engagement and perceived brand utility have a negative relationship (b= -.166; p=.000). In other words, consumers who frequently visit stores or IKEA websites tend to perceive less brand utility than those who do not interact with the brand. Consequently, three hypotheses (H16, H17 and H19) are rejected. 5.9.2 Predictors of Brand Utility types Additionally, it is advisable to identify how the four types of brand utility impact on the newly identified relationships (see part 7.2). A series of regression analyses involving predictors of perceived brand utility were run in order to evaluate to what extent those types could  predict  “motivations  for  engaging”,  “passion”  or  “offline  engagement”. Table 11 - Regression of Brand Interaction against Brand Utility Regression of Brand Interaction against types of Brand Utiliy (r2 =.213) Beta value Sig. Factor 1 - Connectivity .328 .000 Factor 2 - Altruism / Eco-friendliness -.012 .848 Factor 3 - Skills & Advices .246 .000 Factor 4 - Saving Money -.006 .922
  • 59. 65 Table 12 - Regression "Extra Value" against Brand Utility Regression of "Extra Value" against types of Brand Utiliy (r2 =.207) Beta value Sig. Factor 1 - Connectivity .141 .026 Factor 2 - Altruism / Eco-friendliness -.050 .433 Factor 3 - Skills & Advices -.009 .883 Factor 4 - Saving Money .413 .000 Tables 10 and 11  point  out  positive  contributions  from  “Connectivity”  (b=.328;;  p=.000)   and   “Skills   &   advices”   (b=.246;;   p=.000)   to   motivations   of   brand   interaction.   Concerning  motivations  of  “extra  value”,  “Saving  Money”  and  “Connectivity”  utilities   are positively impacting on (Table 11). Otherwise, “passion”  can  be  predicted  by  two   types   of   utilities   as   exhibited   in   Table   12:   “Saving   Money”   (b=.296;;   p=.000)   and   “Connectivity”  (b=.133;;  p=.046  <  .05). Table 13 - Regression of Passion against Brand Utility Regression of "Passion" against types of Brand Utiliy (r2 =.125) Beta value Sig. Factor 1 - Connectivity .133 .046 Factor 2 - Altruism / Eco-friendliness -.077 .247 Factor 3 - Skills & Advices .045 .496 Factor 4 - Saving Money .296 .000 Nevertheless,   Appendix   23   shows   that   a   regression   of   “offline   engagement”   against   types of Brand Utility is not relevant as the value of R-square is low (r2= .032) and the overall significance of the model is not confirmed (p= .089 >.05). Preceding outputs highlight positive relationships between components of brand utility, motivations of engagement and passion. As a matter of fact, the notion of brand utility seems to affect indirectly user engagement in social media. 5.10 Additional findings 5.10.1 Effect of Age on the study
  • 60. 66 As the study was conducted within a heterogeneous sample, the effect of age on customer engagement need to be addressed in order to support final results. Analyses of variance (ANOVA) were carried out to identify potential differences among age categories for the following variables: “consumption”, “offline   engagement”, “user   participation”,   “user   engagement”,   “motivations   for   engaging”,   “satisfaction”,   “loyalty”,  “passion”  and  “perceived  brand  utility”.   Appendix  24  shows  that  the  Levene’s  test  for  equality  of  variances  is  not  significant (p < 0.05) for all variables, meaning that assumptions for equal variances are not confirmed (Pallant, 2001). Nevertheless, according to the ANOVA table, the significance  level  p  is  only  below  0.05  for  “user  engagement”,  “consumption”,  “offline   engagement”,   “passion”   as   well   as   “motivations   for   extra-value. This implies that differences among age categories are significant for those variables. The   table   “Multiple   Comparisons”   displayed in Appendix 24 indicates which age groups significantly differ from others. Concerning   “user   engagement”,   35-44 years old respondents tend to engage more with IKEA in social media (mean= 7.65) than the group of 17-24 years old ones (mean= 6.225) By comparing means, there is a strong difference between age groups in terms of offline engagement. Indeed, the older respondents are, the more they engage (Appendix 24). 45-54 years old respondents purchase significantly more than the group of 17-24 years old respondents. Moreover, 17-24  years  old  individuals  appear  as  being  more  motivated  by  “extra   value”  than  older  groups  do. There are no strong differences between age categories concerning passion. Nonetheless, means for each group show that older respondents tend to be more passionate than under 35s (mean 17-24= .04; mean 25-34= -.25; mean over 55s= .755). 5.10.2 User Engagement and Relationship Quality Prior analyses did not provide support to a series of hypotheses raised in Chapter 3 (H12, H13, H14). Indeed, user engagement in social media does not predict
  • 61. 67 significantly satisfaction, loyalty and passion among customers, as offline engagement seems to do. Nevertheless, positive correlations between user engagement and emotional constructs may exist. A Pearson product moment correlation analysis was carried out to measure the degree of associations existing between those variables. As shown in Appendix 25, there are two significant positive relationships with user engagement: “Passion”  and  “user  engagement”  have  a  small   positive  relationship   (r=  .270;;   p=.000). This means that the more passion people feel about IKEA, the more they engage. There is a small positive relationship between  “loyalty”  and  “user  engagement”   (r= .125; p=.05), No   significant   relationships   have   been   identified   between   “user   engagement”   and  “satisfaction”. 5.11 Evaluation of Hypotheses This part aims at looking how preceding results provide support to initial research hypotheses drawn in Chapter 3. Moreover, the initial model of engagement will take into account new significant relationships identified between concepts. 5.11.1 Initial Hypotheses Table 13 provides details about hypotheses that preceding results analyses have confirmed. Initial Hypotheses Supported Path Correlation Consumption H1 - Offline Engagement - Consumption Yes .410** H2 - User Engagement - Consumption Yes .291** User Engagement
  • 62. 68 H3 - User Participation - User Engagement Yes .442** H4 - Offline Engagement - User Engagement Yes .240** H5a - "Brand Interaction" - User Engagement Yes .258** H5b - "Extra Value for Consumers" - User Engagement Yes -.106* H6 - Satisfaction - User Engagement No H7 - Loyalty - User Engagement No H8 - Passion - User Engagement No H9 - Brand Image - User Engagement No H10a - "Product Design" - User Engagement No H10b - "Price Attractiveness - User Engagement Yes -.096* H11 - Consumption - User Engagement Yes .178** Impacts of User Engagement H12 - User Engagement - Satisfaction Yes -.164* H13 - User Engagement - Loyalty No H14 - User Engagement - Passion No H15 - User Engagement - Offline Engagement Yes .223** Brand Utility H16 - User Engagement - Perceived Brand Utility No H17 - Satisfaction - Perceived Brand Utility No H18 - Passion - Perceived Brand Utility Yes .095** H19 - Loyalty - Perceived Brand Utility No H20a - "Brand Interaction" - Perceived Brand Utility Yes .387** H20b - "Extra Value" - Perceived Brand Utility Yes .301** Note: ** p < .001 / * p < .05 Theoretical assumptions related to the development of engagement were supported both for traditional engagement and online engagement whereas those dealing with consequences of engagement could not be applied specifically to social media platforms; for example, positive impacts of user engagement on loyalty and passion. Nevertheless as mentioned in part 9.2 positive correlations exist between those constructs. Furthermore, the notion of brand utility tested appears being indirectly related to the process of engagement in social media thanks to significant relationships with customer motivations 5.11.2 Additional results In the process of testing initial hypotheses, additional results have been obtained from data (Table 14). Additional findings Path Correlation
  • 63. 69 Consumption F1- "Brand Interaction" - Consumption -.162* Offline Engagement F2 - Loyalty - Offline Engagement .180* F3 - Passion - Offline Engagement .223** F4 - Consumption - Offline Engagement .298** F5 - "Extra Value for Customers" - Offline Engagement -.115* F6 - Product Design - Offline Engagement -.133* Satisfaction F7 - Offline Engagement - Satisfaction .249** F8 - Consumption - Satisfaction .138* F9 - Brand Interaction - Satisfaction .215* Loyalty F10 - Offline Engagement - Loyalty .219** F11 - "Brand Interaction" - Loyalty .162* F12 - Satisfaction - Loyalty .482** Passion F13 - Offline Engagement - Passion .202** F14 -"Brand Interaction" - Passion .156* F15 - Satisfaction - Passion .218** F16 - Loyalty - Passion .208* F17 - Product Design - Passion .127* Brand Utility F18 - Offline Engagement - Perceived Brand Utility -.166* Note: ** p < .001 / * p < .05 Unlike engagement in social media, traditional engagement tends to impact positively on customer satisfaction, loyalty and even passion. These three concepts, which have strong inter-correlations, tend also to contribute in offline engagement both directly (passion, loyalty) and indirectly (satisfaction).  On  the  other  hand,  motivations  of  “brand   interaction”  have  a  significant  impact  on  those  concepts.  This  implies  that  customers   who are more motivated by interacting with the brand and its personality are more likely to be loyal and passionate. In addition, product design appears as a predictor of passion (b=.127; p= .031), meaning that positive considerations of IKEA products might imply higher level of passion.
  • 64. 70 5.11.3 Final Model of Engagement Based on previous results, the measurement model designed in Chapter 3 can be updated considering confirmed hypotheses and coefficients of correlation between elements. Figure 24 - The Process of Engagement, as applied to social media Overall, the model of engagement applied to social media provides relevant findings as most of initial assumptions were confirmed. User engagement is in fact highly correlated with traditional engagement and seems to enhance indirectly general consequences of engagement. Indeed, any strong relationship between user engagement and elements defining relationship quality were identified. Otherwise, the notion of extra value proposition underlined with perceived brand utility tends to impact on customer motivations, therefore to enhance customer engagement in new media platforms. The implications concerning the impact of user engagement on customer- brand interactions will be discussed in the next section.
  • 65. 71 6 Conclusions & Discussion This main purpose of this research was to investigate the concept of customer engagement in new media and to identify its potential effects on customer-brand relationships. Assuming existing models of engagement, the study attempted to test assumptions through the use of IKEA as focal brand and to provide a number of insights for enhancing user engagement. From a theoretical approach, findings tend to confirm empirically the validity of conceptual engagement model from literature (Hollebeek, 2011; Bowden, 2009) and the positive impact of customer engagement on customer-brand relationships. However, the study   emphasizes   that   the   process   of   engagement   in   social   media,   defined   as   “user   engagement”,  does  not  contribute  directly  to  customer-brand relationships as traditional engagement does. Additional findings also provide a better understanding of emotional and rational bonds toward customer engagement and some implications toward the strengthening of customer-brand interactions. 6.1 The Process of Engagement The conceptual model of engagement elaborated by Hollebeek (2011) emphasizes a number of relationships between engagement behaviours and other constructs. First, the author identified customer involvement and interactivity as antecedents of engagement. In the study, involvement was defined with two variables: the frequency of contact  with  IKEA  selling  points  (“offline  engagement”)  and  user  participation  in  social   media. Offline engagement appeared to be influenced significantly by the level of consumption (F4), loyalty (F2) and passion (F3) that consumers experience with IKEA. Moreover, user participation has been identified as a strong positive predictor of user engagement (H3), completed with the level of consumption (H11) and motivations for brand interaction (H5a). Otherwise, user engagement and offline engagement tend to contribute significantly to each other (H4, H15), reinforcing the strength of the overall engagement. Indeed, a consumer who engages offline with IKEA is more likely to engage in social media with the same brand in order to fulfil his own needs.
  • 66. 72 On a second   part,   Hollebeek’s   model   (2011)   points   out   other   concepts   related   to   relationship quality (satisfaction, trust, commitment) and loyalty as consequences of customer engagement with positive relationships as well as a retroactive inhibition. This study did not measure trust but commitment was assimilated to engagement. Nevertheless, the variable of passion was investigated as an higher level of affective bonds with IKEA. Based on the results, customer engagement is positively contributing in satisfaction through the variable offline engagement (F7). Concerning other constructs of loyalty and passion, offline engagement is both contributing in and predicted by those variables, meaning a recursive relationship. Therefore, the frequency of visits in IKEA selling points depends on the level of customer loyalty and passion for the brand. Besides, user engagement has any relationship with the former variables but a negative contribution in satisfaction (H6). With regards to Van Doorn et al. (2010), manifestations of engagement can be both positive and negative. In this case, this negative correlation implies another facet of engagement in social media, such as connecting to express dissatisfaction. To another extent, as conceptualized in her initial model, satisfaction impacts positively on customer loyalty (F12) as well as passion for the brand (F15). Despite the integration of other variables, the conceptual model of customer engagement appears to be quantitatively consistent and reliable. However, applied to user engagement, the model infers a need to consider engagement in social media as a different construct a part of the overall engagement behaviour one. Engaging in social media does not impact directly on customer satisfaction, loyalty and passion, and this means that its effect on customer-brand relationships is not valid at the moment. Consequently, further explanations may be identified through an evaluation of customer motivations for engaging in social media with IKEA.
  • 67. 73 6.2 Motivations for engaging in social media Six distinct motivations for engaging online with a brand have been identified among prior researches (Muntinga et al. 2010), but a lack of quantitative applications minimized reliability of scale and validity of items. Nevertheless, two distinct factors were  elaborated  by  including  8  items  out  of  13:  “motivations  for  brand  interaction”  and   “motivations  for  extra  value”.  Literature  supports  the  two  factors  extracted  as  one  of   them is concerned with intrinsic value and the other with extrinsic value. Based on the results, IKEA consumers are more concerned with brand interaction (Mean = -2.33) than with extrinsic value (Mean =-3.10). Therefore, consumers who are engaged or not are willing to share their interest with others, to learn about IKEA or even to get fun through published content. On the opposite, economic rewards or extra service support are not the main interest for engaging with the brand. Indeed, customer-brand relationships  seem  to  be  affected  by  consumers’  emotional  bonds  rather than rational ones. Consequently, motivations for brand interaction (H5a) contribute more in user engagement than other motivations (H5b). Consumers who are more interested in IKEA intrinsic value are more likely to engage in social media platforms. Additionally, the variable  “brand  interaction”  appears  as  a  predicting  variable  for  the  level  of  satisfaction,   loyalty (F11) and passion (F14) with IKEA. Indeed, an individual looking for intrinsic and emotional needs will be more satisfied than an individual interested in discounts and free products. This statement emphasizes a potential contribution of passion in user engagement through this motivation variable. Otherwise, results about motivations tend to support previous researches in motivations for engaging in social media. For example, social pressure, entertainment as well as sense of belonging are among the motivations for connecting with a brand. Nevertheless, a deeper understanding of user motivation might be required to identify consumer expectations from the brand. Results show for instance than 17-24 years old individuals  were  more  motivated  by  “extra  value”  than  other  age  groups. 6.3 Customer engagement and Passion Defined  as  the  “apex  of  customer  engagement”  (McEwen,  2004),  the  concept  of  passion   seems to be inherent to the model of customer engagement confirmed above.
  • 68. 74 Academics have various considerations concerning passion. Yim et al. (2008) points out its requirements for customer loyalty whereas Park et al (2009) suggest that the level of involvement with a brand does not depend on developed emotional connections. Based on the results, passion can be predicted by offline engagement (F13), “motivations  for  brand  interaction”  (F14),  satisfaction  (F15),  loyalty  (F16)  and  product   design (F17). Product design is the only IKEA-related characteristic that enhances the level of consumer passion. It implies that product design might encompass some features of IKEA experience in the mind of customers, such as easiness to assemble, design and quality. This can be corroborated with the fact that most important reasons for visiting an IKEA store is to look at furniture and furnishing items. Although there are no predicting each other, passion and user engagement have a small positive relationship, meaning that the more passionate individuals are more likely to engage than others. As a consequence, the study assumes a different opinion than Park et  al.  (2009)  on  the  basis  that  passion  is  a  predictor  of  consumers’  involvement.   Furthermore, the study investigates customer passion platforms in the process of defining which types of emotional associations exist among customers. Indeed, IKEA customers may refer to the brand when practising a do-it-yourself activity, doing crafts, cooking, speaking about art/design or even when spending time with relatives. These centres of interest are relevant in order to connect with IKEA consumers and raise the interest in engaging online with the brand. For example, Facebook users will be more likely to like IKEA in case they know that published content relates to their centres of interest and can potentially provide them with valuable content (i.e. information, entertainment). 6.4 Customer engagement and Brand Utility The notion of brand utility was introduced into the study in order to evaluate the impact of rational bonds on customer engagement, as highlighted in McEwen (2004). The level of perceived brand utility was used to assess whether the sample considered IKEA as a brand likely to provide extra free services in exchange of stronger interactions. Perceived brand utility is strongly impacting on motivations for engaging in social media with the brand while offline engagement is negatively contributing to this
  • 69. 75 variable. This fact might be supported by assuming that consumers with a low level of traditional engagement perceive and expect more brand utility from a brand; for example due to a lack of information on brand offers. Nevertheless, a small relationship between passion and perceived brand utility exists, meaning that people who have a passion for IKEA might perceived more utility than others. To another extent, the existing relation between those variables may reinforce the proximity of emotional and rational bonds. In other words, brand utility might probably impact on customers through the use of passion platforms. For example, a mobile application providing cooking recipes or DIY hints may be perceived more valuable for people than a type of services unrelated with IKEA-related passions. Despite its lack of consistency within the model of engagement, the concept of brand utility seems to indirectly impact on user engagement via motivations. 6.5 Customer engagement and Consumption Finally, customer engagement is considered as a process encompassing all behavioural manifestations customers are likely to experience with a brand. Visiting a store, reading a catalogue or even being fan of IKEA on Facebook are likely to enhance customer- brand interactions and potentially encourage customers to purchase (Bowden, 2009). Results of this study show that both offline and online forms of engagement were contributing significantly to the level of consumption. In the study, stores were the most frequently used and visited selling points, whereas other IKEA touch-points enable regular interactions with IKEA. User engagement enhances the requirement for regular interactions in platforms heavily used by customers. However, understanding customer expectations from the brand is required to strengthen customer-brand relationships. Passion is another construct to identify as it strongly impacts on engagement and it contains affectionate ties likely to create intimacy through the use of passion points. 6.6 Managerial implications Social media platforms have offered wide opportunities for companies to connect with potential  customers  willing  to  participate  with  a  brand.  From  a  “like”  to  a  “check-in”,   customers interact in order to share their interest, get entertained, benefit from valuable information or to express their affiliation to a brand.
  • 70. 76 However, due to the attractiveness of these platforms, customers face a larger number of choices and start considering to which level they really love a brand and the value this brand can offer to them. This study provides a useful framework to evaluate customer expectations in engaging with a brand based on their relationship built over time with it. Instead of considering social media as new media, marketers should put an emphasis on the importance of content. Passion is inherent to any customer-brand relationships even though customers used to deny. To inhibit those affectionate ties, a brand needs to use specific platforms to raise interest among customers through content. Because passion platforms are related to brand image and identity in the eyes of customers, it is critical to use these brand-related points in order to strengthen an existing relationship. In a similar approach to passion, brand utility is a way to enhance customer-brand interactions by creating proximity between people and a brand. Because engagement is no longer restricted to selling points, a brand must provide utilities in order to keep on offering value to people in real life. Otherwise, the notion of customer engagement in social media has to be carefully distinguished from general engagement. Indeed, results show that user engagement was not likely to create satisfaction, loyalty and passion for a brand. It only impacts on consumption and offline engagement. Therefore, the use of social media platforms is crucial for business and an appropriate use is critical to avoid any counter-effect and losses of customers. 6.7 Limitations and further research This study has a number of limitations related to customer motivations to engage with a brand. Motivations identified in literature could not be properly used in the process of the study therefore two general motivations have been generated. Otherwise, measurement scale for user participation and user engagement was relevant in regards to literature but did not consider differences among platforms. Indeed, social media platforms tend to differ according to media richness theory. Therefore a Facebook fan may be considered more important a follower on Twitter.
  • 71. 77 In the research area of customer engagement, it would be interesting to investigate several types of motivations for engaging with a brand on social media. On the other hand, further research is needed to establish a relevant measurement scale for engagement in order to extend possibilities in data analysis. To another extent, identifying reasons why non-customers engage online would provide interesting insights about brand passion among these segments.
  • 72. 78 Bibliography ALBERT, N., MERUNKA, D. & VALETTE-FLORENCE, P., 2008. When consumers love their brands: Exploring the concept and its dimensions. Journal of Business Research, 61(10), p.1062-1075. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0148296307002871 ALTIMETER (2009). Engagement db report. Online access at : http://www.altimetergroup.com/2009/07/engagementdb.html AOL (2010). Content is the Fuel of the Social Web. Online access at : http://advertising.aol.com/research/research-reports/social-web ASHLEY C., NOBLE S., DONTHU N., LEMON K. (2011), Why customers won't relate: Obstacles to relationship marketing engagement. Journal of Business Research, 64, 749–756 BAGOZZI, R. P., YI, Y., & PHILLIPS, L. W. (1991). Assessing Construct Validity in Organizational Research. Administrative Science Quarterly. BERTHON, P.R., PITT, L.F. & CAMPBELL, C. (2008) Ad lib: when customers create the ad. California Management Review, 50(4), pp. 6–30. BOWDEN, J.L.H., 2009a. The process of customer engagement: A conceptual framework, Journal of Marketing Theory and Practice 17 (1), 63-74. BRONNER, F. & NEIJENS P. (2006) Audience experiences of media context and embedded advertising; a comparison of eight media. International Journal of Market Research, 18(1), pp. 81–100. BUHL, H.U (2011). From Revolution to Participation: Social Media and the Democratic Decision- Making Process. Business and Information Systems Engineering, 3, 1-4 CALDER, B.J., MALTHOUSE, E.C. & SCHAEDEL U. (2009) An experimental study of the relationship between online engagement and advertising effectiveness. Journal of Interactive Marketing, 23(4), pp. 321–331. CAMPBELL, D. T., & FISKE, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix CHAFFEY, D. (2008). Internet marketing. Harlow, Financial Times Prentice Hall CHANG, J. & SUN, E. (2011). Location3: How Users Share and Respond to Location- Based Data on Social. In Proceedings of the Fifth International Conference on Weblogs and Social Media (July 2011), Barcelona, Spain.
  • 73. 79 CHIANG, O. (2011). Twitter Hits Nearly 200M Accounts, 110M Tweets Per Day, Focuses On Global Expansion. Forbes. Online access at : http://www.forbes.com/sites/oliverchiang/2011/01/19/twitter-hits-nearly-200m-users- 110m-tweets-per-day-focuses-on-global-expansion/ COLMAN, A. M., NORRIS, C. E., & PRESTON, C. C. (1997). Comparing rating scales of different lengths: equivalence of scores from 5-point and 7-point scales. Psychological Reports, 80, 355-362 CONTAGIOUS MAGAZINE (2008). Branded Utility. Online access at: http://www.contagiousmagazine.com/resources/BU_extracts.pdf COVA B. & PACE, S. (2006) Brand community of convenience products: new forms of customer empowerment – the  case  ‘my  Nutella  The  Community’.  European Journal of Marketing, 40, pp. 1087–2005. DAFT, R.L. & LENGEL, R.H. (1984). Information richness: a new approach to managerial behavior and organizational design. In L.L. Cummings & B.M. Staw (eds.), Research in organizational behavior 6, 191-233. Homewood, IL: JAI Press 1984. DEIGHTON, J., & KORNFELD, L. (2009). Interactivity's Unanticipated Consequences for Marketers and Marketing. Journal of Interactive Marketing : a Quarterly Publication from the Direct Marketing Educational Foundation, Inc. 23, 4. DENNIS, A.R. and VALACHIC, J.S. Rethinking Media Richness: Towards a Theory of Media Synchronicity. In Proceedings of HICSS. 1999 DUFFY, N., & HOOPER, J. (2003). Passion branding: harnessing the power of emotion to build strong brands. Chichester, England, John Wiley & Sons. eMARKETER (2011). Advertisers Begin to Look Beyond Facebook and Twitter Online access at : http://www.emarketer.com/Article.aspx?R=1008520 FORRESTER RESEARCH (2010). The latest Global Social Media Trends May Surprise You. Online access at : http://blogs.forrester.com/jackie_rousseau_anderson/10-09-28- latest_global_social_media_trends_may_surprise_you GELT J. (2009) Kogi Korean BBQ, a taco truck brought to you by Twitter. LATimes. Online access at : http://www.latimes.com/features/la-fo-kogi11- 2009feb11,0,4771256.story GODIN, S. (1999). Permission marketing: turning strangers into friends, and friends into customers. New York, Simon & Schuster. GRISAFFE, D.B. & NGUYEN, H.P., 2010. Antecedents of emotional attachment to brands. Journal of Business Research, In Press,(10), p.1052-1059. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0148296310002250.
  • 74. 80 HAIR, J. F., BUSH, R. P., & ORTINAU, D. J. (2003). Marketing research: within a changing information environment. Boston, McGraw-Hill/Irwin. HANSON, G., & HARIDAKIS, P. (2008). YouTube Users Watching and Sharing the News: A Uses and Gratifications Approach. Journal of Electronic Publishing. HENNIG THURAU, T., GWINNER, K.P., WALSH, G. & GREMLER, D.D. (2004) Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet? Journal of Interactive Marketing, 18(1), pp. 38– 52. HENNIG THURAU, T., MALTHOUSE E, FRIEDGE C, GENSLER S, LOBSCHAT L, RANGASWAMY A, and SKIERA B (2010),   ‘‘The   Impact   of   New   Media   on   Customer  Relationships,’’  Journal  of  Ser- vice Research, 13 (August), 311-330. HESS, J., STORY, J., 2005. Trust-based commitment: multidimensional consumer- brand relationships. Journal of Consumer Marketing 22 (6), 313-322. HOLLEBEEK, L.D., 2010. Demystifying customer engagement: Exploring the loyalty nexus. Journal of Marketing Management, Forthcoming. HOLLEBEEK, L. (2011). Demystifying customer brand engagement: Exploring the loyalty nexus. Journal of Marketing Management. 27, 7-8. HUNT, S.D., SPARKMAN, R. D. and WILCOX, J. B. (1989). The Pretest in Survey Research: Issues and Preliminary Findings. Journal of Marketing Research, 19, 269-73. JACK, L (2009). Internet turns customers into ambassadors. Marketing Week. Online access at: http://www.marketingweek.co.uk/internet-turns-customers-into- ambassadors/3001054.article JOHNSON, P.R. & YANG, S.-U., 2009. Uses and Gratifications of Twitter: An Examination of User Motives and Satisfaction of Twitter Use. Association for Education in Journalism and Mass Communication. Available at: http://www.allacademic.com//meta/p_mla_apa_research_citation/3/7/6/3/6/pages37636 7/p376367-1.php JOURARD S. (1959). Self-disclosure and other-cathexis. Journal of Abnormal and Social Psychology, 59(3), 428-431. KAPLAN, A., HAENLEIN, M., 2009. The fairyland of Second Life: Virtual social worlds and how to use them. Business Horizons 52 (6), 563-572. KAPLAN, A., HAENLEIN, M., 2010. Users of the world, unite! The challenges and opportunities of Social Media. Business Horizons 53 (1), 59-68. KUMAR, V., AKSOY, L., DONCKERS, B., VENKATESAN, R., WIESEL, T., and TILLMANS,  S.  (2010),  ‘‘Undervalued  or  Overvalued  Customers:  Capturing  Total   Customer  Engagement  Value,’’  Journal  of  Service  Research,  13  (August),  297-310.
  • 75. 81 LATimes(2011).Foursquare has more than 10 million users. Online access at : http://latimesblogs.latimes.com/technology/2011/06/foursquare-number-users.html LI, C.,BERHNOFF J, (2007). Social Technographics ® TRENDS. Reproduction, p.1- 17. Available at: http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Social+Technographi cs#1 LINDQVIST J , CRANSHAW J , WIESE J , HONG J , ZIMMERMAN J (2011) I'm the mayor of my house: examining why people use foursquare - a social-driven location sharing application, Proceedings of the 2011 annual conference on Human factors in computing systems, May 07-12, 2011, Vancouver, BC, Canada LIU, I. and LEE, M. (2010). Understanding Twitter Usage: What Drive People Continue to Tweet. In Proceedings of the Pacific Asia Conference on Information Systems, Taipei, Taiwan. MADDEN M, ZICKUHR K (2011) 65% of online adults use social networking sites. Pew Research. Online access at : http://www.pewinternet.org/~/media//Files/Reports/2011/PIP-SNS-Update-2011.pdf McEWEN, W. (2004). Why satisfaction isn't satisfying. Gallup Management Journal Online November, (1-4). McQUAIL, D. (1983) Mass Communication Theory. London: Sage Publications. MEADOWS-KLUE, D. (2008). Opinion piece: Falling in Love 2.0: Relationship marketing for the Facebook generation. Journal of Direct, Data and Digital Marketing Practice. 9, 245-250 MUNTINGA, D.G., MOORMAN, M. & SMIT, E.G., 2011. Introducting COBRAs: Exploring motivations for brand-related social media use. International Journal of Advertising, 30(1), p.13. Available at: http://www.warc.com/Articles/10.2501/IJA-30- 1-013-046. MURPHY, E. C., & MURPHY, M. A. (2002). Leading on the edge of chaos: the 10 critical elements for success in volatile times. Paramus, N.J., Prentice Hall Press. NIELSEN (2009). Global Advertising: Consumers Trust Real Friends and Virtual Strangers the Most. Online access at: http://blog.nielsen.com/nielsenwire/consumer/global-advertising-consumers-trust-real- friends-and-virtual-strangers-the-most/ NIELSEN (2011). Nielsen Blogpulse. Online access at: http://www.blogpulse.com/ PARK, C.W., MacINNIS, D.J. and PRIESTER,  J.R.  (2009),  “Research   directions  on   strong   brand   relationships”,   in   MacInnis,   D.J.,   Park,   C.W.   and   Priester,   J.R. (Eds),
  • 76. 82 Handbook of Brand Relationships, Society for Consumer Psychology, M.E. Sharpe, Armonk, NY and London, pp. 379-93. PATTERSON P., YU, T., DE RUYTER K., 2006. Understanding customer engagement in services, Proceedings of ANZMAC 2006 Conference: Advancing Theory, Maintaining Relevance, Brisbane, 4-6 Dec PATWARDHAN, H. & BALASUBRAMANIAN, S.K., 2011. Brand romance: a complementary approach to explain emotional attachment toward brands. Journal of Product & Brand Management, 20(4), p.297-308. Available at: http://www.emeraldinsight.com/10.1108/10610421111148315. QUALMAN, E. (2009). Socialnomics: how social media transforms the way we live and do business. Hoboken, N.J., Wiley. QUAN-HAASE, A. & YOUNG, A.L., 2010. Uses and Gratifications of Social Media: A Comparison of Facebook and Instant Messaging. Bulletin of Science Technology Society, 30(5), p.350-361. Available at: http://bst.sagepub.com/cgi/doi/10.1177/0270467610380009. URBAN, G. L. (2005). Customer Advocacy: A New Era in Marketing? Journal of Public Policy & Marketing. 24, 155-159 RAY, A. (2010), Four Signs Social Media is now a mass medium. Forrester Research. Available online at: http://blogs.forrester.com/augie_ray/10-12-12- four_signs_social_media_is_now_a_mass_medium RAO, L. (2011). Zuck Confirms That Facebook Now Has 750 Million Active Users. Techcrunch. Online access at: http://techcrunch.com/2011/07/06/zuck-confirms-that- facebook-now-has-750-million-users/ RAZORFISH (2009). Feed. Online access at : http://feed.razorfish.com/ RAZORFISH (2011). Liminal, Customer Engagement Report. Online access at : http://feed.razorfish.com/ RODGERS, S., WANG, Y., RETTIE, R. & ALPERT, F. (2007) The Web Motivation Inventory: replication, extension and application to internet advertising. International Journal of Advertising, 26(4), pp. 447–476 (accessed on 9 April 2009). REAGLE, JOSEPH MICHAEL. (2010). Good Faith Collaboration The Culture of Wikipedia. MIT Press. RUGGIERO, T. (2000). Uses and Gratifications Theory in the 21st Century. Mass Communication and Society. 3, 3-37 SAKS A.M. 2006. Antecedents and consequences of employee engagement. Journal of Managerial Psychology 21 (7), 600-619.
  • 77. 83 SALANOVA M, AGUT S., and PEIRO, J (2005). Linking Or- ganizational Resources and Work Engagement to Employee Performance and Customer Loyalty: The Mediation of Service Climate. Journal of Applied Psychology. 90 (6).1217–1227. SOLIS, B. (2010). Engage!: the complete guide for brands and businesses to build, cultivate, and measure success in the new web. Hoboken, N.J., John Wiley. TABACHNICK, B. G., & FIDELL, L. S. (2001). Using multivariate statistics. Boston, Allyn and Bacon. TRENDWATCHING (2010). Brand Butlers report. Online access at : http://trendwatching.com/trends/brandbutlers/ VAN DOORN J., LEMON, K.E., MITTAL, V., (2010). Customer engagement behavior: Theoretical foundations and research directions. Journal of Service Research, Forthcoming. VAN GROVE J. (2011). Mayors of Starbucks Now Get Discounts Nationwide with Foursquare. Mashable. Online access at : http://mashable.com/2010/05/17/starbucks- foursquare-mayor-specials/ YIM, C.K.B., TSE, D.K. & CHAN, K.W., 2008. Strengthening Customer Loyalty Through Intimacy and Passion: Roles of Customer–Firm Affection and Customer–Staff Relationships in Services. Journal of Marketing Research, 45(6), p.741-756. Available at: http://www.atypon-link.com/AMA/doi/abs/10.1509/jmkr.45.6.741. YOUNG, A. (2011). Social Media is a Venue, Not a Strategy. AdAge. Online access at : http://adage.com/article/mediaworks/viewpoint-social-media-a-venue-a- strategy/228192/ WANG, Y., & FESENMAIER, D. R. (2003). Assessing Motivation of Contribution in Online Communities: An Empirical Investigation of an Online Travel Community. Electronic Markets. 13, 33-45. ZHAO , D. , ROSSON, M.B. (2009). How and why people Twitter: the role that micro- blogging plays in informal communication at work, Proceedings of the ACM 2009 international conference on Supporting group work, May 10-13, 2009, Sanibel Island, Florida, USA ZIKMUND, W. G., & BABIN, B. J. (2009). Exploring marketing research. Mason, Ohio, South-Western.
  • 78. 84 Appendices

×