Evaluation of the role of digital technology on customer experience

UNIVERSITEIT GENT FACULTEIT ECONOMIE EN BEDRIJFSKUNDE ACADEMIEJAAR 2014 – 2015

Evaluation of the role of digital technology on customer experience

Masterproef voorgedragen tot het bekomen van de graad van Master of Science in de Toegepaste Economische Wetenschappen

Jens Scheerlinck onder leiding van Prof. dr. Dirk Van den Poel en Matthijs Meire  

 

 

 

 

 

 

 

UNIVERSITEIT GENT FACULTEIT ECONOMIE EN BEDRIJFSKUNDE ACADEMIEJAAR 2014 – 2015

Evaluation of the role of digital technology on customer experience

Masterproef voorgedragen tot het bekomen van de graad van Master of Science in de Toegepaste Economische Wetenschappen

Jens Scheerlinck onder leiding van  

 

Prof. Dirk Van den Poel en Matthijs Meire    

 

     

 

 

 

Vertrouwelijkheidsclausule     PERMISSION Ondergetekende  verklaart  dat  de  inhoud  van  deze  masterproef  mag  geraadpleegd   en/of  gereproduceerd  worden,  mits  bronvermelding.   Naam  student:  Jens  Scheerlinck  

 

 

Samenvatting    

Vorig onderzoek heeft aangetoond hoe de koopervaring kan gemeten worden in een online context (Guo & Poole, 2009; Hsieh, Hsieh, Chiu, & Yang, 2014; Novak, Hoffman, & Yung, 2000; Rose, Clark, Samouel, & Hair, 2012). Daarnaast hebben verschillende studies de effecten van meerdere verkoopkanalen, zowel online als offline, op de koopervaring bestudeerd (Sousa & Voss, 2006; van Birgelen, de Jong, & de Ruyter, 2006; Wang, Song, & Yang, 2013). Er is echter nauwelijks onderzoek verricht naar het effect van verschillende toestellen waarmee online content geraadpleegd wordt. Waar vroeger enkel een desktop computer of laptop gebruikt werd, zien we dat smartphones en tablets in populariteit blijven toenemen. Daarom wordt in deze studie onderzocht of er een verschil bestaat in online koopervaring tussen traditionele toestellen zoals desktop computers of laptops enerzijds en mobiele toestellen anderzijds. Bovendien wordt er gekeken of de online koopervaring verbetert wanneer bedrijven de inhoud van hun e-commerce toepassingen aanpassen aan het toestel dat de klant gebruikt. Tot slot kijken we of het mogelijk is een carry-over effect van koopervaring te detecteren tussen verschillende toestellen, analoog aan het carry-over effect tussen online en offline kanalen dat reeds werd aangetoond in de literatuur. Om deze vragen te beantwoorden werd gebruik gemaakt van het model voor online koopervaring door Rose et al. (2012). Een vragenlijst werd verspreid die peilt naar de ervaring van consumenten met e-commerce op verschillende toestellen, gevolgd door een voorstelling van drie koopervaringen die beoordeeld dienden te worden door de respondenten. De analyse van de resultaten heeft aangetoond dat er een verschil in koopervaring bestaat, afhankelijk van welk toestel gebruikt wordt door de consument. Dit verschil werd vastgesteld voor de aankoop van hetzelfde product bij hetzelfde bedrijf. Daarnaast werd aangetoond dat een e-commerce applicatie die specifiek ontworpen is voor een mobiel toestel een significant betere koopervaring oplevert dan wanneer dit niet het geval is. Deze resultaten tonen aan dat bedrijven en e-retailers rekening dienen te houden met het gebruik van verschillende toestellen, en dat het lonend kan zijn om een specifieke applicatie te ontwikkelen voor mobiele toestellen om de online koopervaring te verbeteren. Dit wordt verder ondersteund door de bevinding dat afhankelijk van het type toestel andere verwachtingen worden geschept ten opzichte van de antecedenten van online koopervaring. Een significant carry-over effect werd in deze studie niet gevonden, wat impliceert dat het voor bedrijven belangrijk is op elk toestel een sterke online koopervaring neer te zetten, aangezien positieve ervaringen op bijvoorbeeld een desktop computer niet worden overgedragen naar een smartphone.

 

  I  

Foreword  

  The   last   eight   months   of   my   education   at   Ghent   University   have   been   an   interesting   journey,   during   which   a   lot   of   time   was   devoted   to   the   writing   of   this   thesis.   I   am   extremely   happy   to   have   been   able   to   research   a   topic   in   which   I   have   great   interest.   I   am   convinced   that   both   technology   and   customer   experience   have   a   great   and   lasting   impact   on   people   and   companies   alike.   During  the  writing  of  this  thesis  progress  was  not  always  as  fast  paced  as  I  would   have   liked   it   to   be,   but   the   end   result   has   provided   me   with   a   great   sense   of   fulfillment.       I   would   like   to   thank   everyone   who   has   helped   me   to   complete   this   thesis.   In   particular  I  wish  to  thank  Prof.  dr.  Dirk  Van  den  Poel  for  the  opportunity  to  work   on   this   interesting   research   topic,   which   has   helped   me   to   secure   a   job   in   technology  consulting,  and  Matthijs  Meire  for  the  excellent   supervision  and  the   fast  and  helpful  feedback.       Special  thanks  go  to  Sofie  Van  den  Abbeele  for  rigorously  proofreading  my  thesis,   and   my   parents   for   their   continuous   support   and   the   opportunity   they   have   given   me   to   obtain   a   Master’s   degree.   Lastly   I   would   like   to   thank   all   the   respondents  who  filled  in  my  questionnaire,  without  whom  I  would  have  never   been  able  to  complete  this  thesis.  

 

 II  

 

Table  of  Contents   1.  Introduction  ...................................................................................................................  1   2.  Literature  Review  .........................................................................................................  3   2.1.  Customer  experience  and  the  importance  of  touch  points  ..................................  3   2.2.  Integration  of  different  channels  in  the  customer  experience  ...........................  4   2.4.  Hypothesis  development  .................................................................................................  6  

3.  Methodology  ...................................................................................................................  9   3.1.  Sample  and  participants  ..................................................................................................  9   3.2.  Experimental  design  .......................................................................................................  10   3.3.  Procedure  ...........................................................................................................................  11  

4.  Discussion  of  the  results  ..........................................................................................  13   4.1.  Differences  in  OCE  between  traditional  versus  mobile  devices  and   traditional  versus  adapted  content.  ..................................................................................  13   4.2.  Analyzing  the  carry-­‐over  effect  between  online  experiences  for  traditional   and  mobile  devices.  .................................................................................................................  16   4.3.  Differences  in  antecedents  and  outcomes  of  OCE  for  traditional  and  mobile   devices.  ........................................................................................................................................  17  

5.  Conclusions  and  practical  implications  ..............................................................  20   6.  Limitations  and  future  research  ............................................................................  22   Bibliography  .....................................................................................................................  22   Appendix  1.  Measurement  scales  for  online  customer  experience.  ................  1   Appendix  2.  Measurement  scales  for  outcomes  of  online  customer   experience  on  mobile  devices  .......................................................................................  2   Appendix  3.  Measurement  scales  for  outcomes  of  online  customer   experience  on  traditional  devices  ...............................................................................  3   Appendix  4.  Measurement  scales  for  antecedents  of  online  customer   experience  on  mobile  and  traditional  devices.  .......................................................  4   Appendix  5.  Excerpt  of  survey  ......................................................................................  5  

 

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List  of  Abbreviations     AES   CES   OCE   ANOVA   ANCOVA  

   

 

Affective  experiential  state   Cognitive  experiential  state   Online  customer  experience   Analysis  of  variance   Analysis  of  covariance  

 

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List  of  Tables     1.  Availability  and  usage  of  devices  .........................................................................  10   2.  Experimental  design  to  measure  OCE  for  different  devices  and  content  ..............................................................................................................................................  11   3.  Means  for  traditional  desktop,  traditional  mobile  and  adapted  mobile   experiences  ......................................................................................................................  14   4.  Differences  in  means  between  traditional  desktop,  traditional  mobile   and  adapted  mobile  experiences  ..............................................................................  14   5.  Analysis  of  the  effect  of  confounding  variables  on  the  mean  differences   between  the  traditional  desktop  experience,  adapted  mobile  experience   and  traditional  mobile  experience.  .........................................................................  15   6.  Descriptive  statistics  regarding  a  difference  in  OCE  based  on  the  first   shown  experience.  .........................................................................................................  16   7.  ANOVA  tests  for  a  difference  in  OCE  based  on  the  first  shown  experience  ..............................................................................................................................................  17   8.  Reliability  of  variables  concerning  the  outcomes  of  OCE  ............................  17   9.  Paired  Samples  T-­‐Test  for  variables  concerning  the  outcomes  of  OCE  ...  18   10.  Paired  Samples  T-­‐Test  for  variables  concerning  the  antecedents  of  AES  ..............................................................................................................................................  18  

List  of  Figures     1.  Model  for  online  customer  experience  by  Rose,  Clark,  Samouel,  &  Hair    ..............................................................................................................................................  9   2.  Diagram  with  regard  to  the  measurement  of  OCE  for  different  devices   and  content  types  in  the  online  questionnaire    ...................................................  12  

 

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1.  Introduction     In  the  complex  and  rapidly  changing  environment  we  live  in  today,  finding  and   sustaining  a  competitive  advantage  is  harder  than  ever  (Gosselin  &  Tindemans,   2012).  Within  this  context  a  unique  and  satisfying  customer  experience  can  act   as   a   strong   differentiator   and   be   the   source   of   a   competitive   advantage   (Rawson,   Duncan,   &   Jones,   2013a).   In   order   to   develop   a   unique   and   enjoyable   customer   experience,  the  use  of  (digital)  technologies  is  becoming  increasingly  important   (Moran,  Muzellec,  &  Nolan,  2014).  At  the  same  time  a  lot  of  touch  points  that  help   shape  the  total  customer  experience  now  lie  beyond  the  control  of  the  company   itself.  Instead  they  are  taking  place  in  the  digital  realm,  e.g.  on  search  engines  and   social   media   (Edelman,   2010).   These   so   called   earned   media   (Bao   &   Chang,   2014)  –  media  not  at  the  discretion  of  the  company  -­‐  are  visited  through  a  wide   array   of   devices:   from   traditional   desktop   computers   to   more   and   more   portable   devices   such   as   laptops,   tablets,   smartphones   and   as   of   recent   even   wearable   devices   like   smart   watches   and   smart   eyewear.   In   2013   20,2%   of   the   population   worldwide   was   in   the   possession   of   a   smartphone   (“Smartphone   Users   Worldwide   Will   Total   1.75   Billion   in   2014   -­‐   eMarketer,”   2014).   As   of   writing   this   number   is   expected   to   increase   to   24,4%   for   2014.   By   the   end   of   2017   this   number   is   believed   to   increase  to  33,8%.   Meanwhile,   the   next   growth   wave   for   digital  technologies  is  already  emerging  in  the  form  of  wearables  (Drubin,  2014).     Existing   research   has   focused   primarily   on   the   dimensions   of   the   customer   experience   (Guo   &   Poole,   2009;   Hamzah,   Alwi,   &   Othman,   2014)   and   on   online   interactions  such  as  through  a  company’s  website  (Lee  &  Jeong,  2014;  McKinney,   Yoon,  &  Zahedi,  2002),  a  retailer’s  website  such  as  Amazon  (Hamzah  et  al.,  2014)   or   social   media   (Misopoulos,   Mitic,   Kapoulas,   &   Karapiperis,   2014;   Uzunoğlu   &   Misci  Kip,  2014).  Yet  little  or  no  research  has  been  conducted  on  what  the  effect   of  the  devices  used  by  consumers  is  on  the  customer  experience  when  viewing   digital  content,  nor  whether  this  content  should  be  adapted  to  the  device  that  is   used.   Technology   has   already   accommodated   the   different   devices   consumers’  

 

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use;   responsive   design   is   a   well-­‐known   concept   with   web-­‐   and   application   developers  alike.       Should   marketers   and   companies   be   using   these   technologies   to   deliver   more   compelling   digital   experiences?   In   this   study   we   will   research   whether   there   is   a   significant   difference   in   customer   experience   for   different   types   of   devices   a   (potential)   customer   might   be   using   and   whether   the   content   itself   has   an   influence  on  this  relationship.  

 

 

 

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2.  Literature  Review   2.1.  Customer  experience  and  the  importance  of  touch  points     Meyer  and  Schwager  (2007)  have  defined  customer  experience  as  “the  internal   and   subjective   response   that   customers   have   to   any   direct   or   indirect   contact   with  a  company”  (p.  118).  These  direct  or  indirect  contacts  with  a  company  are   defined   as   touch   points   (Rawson   et   al.,   2013a).   Marketers   used   to   focus   efforts   on   awareness   and   closing   the   deal   at   point   of   purchase.   But   touch   points   have   changed  in  both  number  and  nature  (Edelman,  2010).  A  lot  of  these  touch  points   now   reside   in   the   online   world:   social   media,   customer   reviews   on   retailers’   websites,  expert  reviews  on  YouTube  and  the  companies  own  website  are  just  a   few  examples  of  how  customers  interact  with  brands,  products  and  companies  in   an   online   environment.   Furthermore,   a   lot   of   these   touch   points   are   not   controlled  by  the  company  itself,  but  instead  monitored  by  bloggers,  advocates,   critics  and  other  third  parties  (Moran  et  al.,  2014;  Novak  et  al.,  2000).  All  of  these   touch   points   form   expectations   towards   the   brand,   product   or   service.   This   implicates   that   all   touch   points   have   an   influence   on   the   customer   experience   (Meyer   &   Schwager,   2007).   Different   authors   have   noted   the   importance   of   taking  all  touch  points  into  account  simultaneously  in  order  to  fully  understand   customer   experience   (Edelman,   2010;   Rawson,   Duncan,   &   Jones,   2013b;   Roggeveen  &  Schlesinger,  2008;  Tax,  McCutcheon,  &  Wilkinson,  2013).     Analogous   to   touch   points   forming   expectations   and   influencing   the   customer   experience,  a  model  of  customer  experience  creation  proposed  by  Verhoef  et  al.   (2009)   recognizes   that   experiences   in   alternative   channels   influence   one   another.  For  example,  the  experience  a  customer  enjoys  in  a  physical  store  will   carryover  to  a  future  purchase  on  the  website  of  the  same  company.  This  carry-­‐ over   effect   of   customer   experience   between   channels   had   already   been   established   by   various   other   studies   (Sousa   &   Voss,   2006;   van   Birgelen   et   al.,   2006).   However,   no   research   has   been   conducted   to   find   a   similar   carry-­‐over   effect   between   different   devices   (e.g.   a   laptop,   tablet   and   smartphone).   We   believe  a  similar  effect  on  the  customer  experience  can  be  found.    

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2.2.  Integration  of  different  channels  in  the  customer  experience     As  the  number  of  channels  forming  the  customer  experience  increases,  so  does   the  need  for  the  integration  of  various  physical  and  virtual  channels.  A  study  by   Sousa   and   Voss   (2006)   has   shown   that   integration   quality   is   an   important   determinant   of   overall   perceived   customer   experience.   Furthermore   they   have   identified   two   dimensions   determining   integration   quality:   channel-­‐service   configuration   and   integrated   interactions.   Channel-­‐service   configuration   comprises   the   variety   of   channels   customers   are   able   to   choose   from   and   their   knowledge   about   these   channels   and   the   channels’   attributes.   The   integrated   interaction  dimension  takes  into  account  content  consistency  between  channels   as  well  as  process  consistency;  conveying  the  same  brand  values  throughout  all   processes  is  key  here  (Sousa  &  Voss,  2006).     The   importance   of   consistency   between   channels   has   been   empirically   verified   for  the  hotel  branch  using  congruity  theory  as  a  theoretical  background  (Lee  &   Jeong,   2014).   Meanwhile,   in   the   banking   sector,   evidence   has   been   found   that   suggests  the  customer’s  satisfaction  with  multiple  service  channels  is  important   for  the  formation  of  behavioral  intentions  (van  Birgelen  et  al.,  2006).       Research  by  Wang  et  al.  (2013)  shows  that  a  substitution  effect  exists  between   online   and   traditional   channels   and   that   this   result   is   consistent   for   different   product   categories.   Drawing   from   the   status-­‐quo   bias   they   prove   that   a   consumer  is  less  likely  to  switch  channels  after  the  search  stage  due  to  perceived   switching   costs,   stemming   from   incomplete   product   information   prior   to   purchase.   This   negative   influence   is   most   relevant   to   experiential   goods,   which   are  traditionally  purchased  offline  and  use  online  channels  to  funnel  customers   into   their   stores.   Internet   based   virtual   reality   technologies   (e.g.   360°   tours,   visualized   product   configurators)   are   believed   to   reduce   these   cross-­‐channel   dissynergies  (Wang  et  al.,  2013).  These  findings  reinforce  the  notion  that  cross-­‐ channel  consistency  in  both  content  and  process  is  important.        

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2.3.  Digital  customer  experiences     Customer  experience  in  an  offline  setting  as  well  as  through  different  channels   has  been  a  widely  researched  topic.  However,  studies  focusing  on  digital  or   online  customer  experience  remain  scarce.  The  most  comprehensive  model  is   posited  by  Rose  et  al.  (2012)  and  is  shown  in  figure  1.     Their   contributions   include   the   discovery   of   perceived   control   as   a   mediating   variable  influencing  the  affective  experiential  state  (AES)  and  that  both  AES  and   cognitive   experiential   state   (CES)   form   the   online   customer   experience.   Previously  this  relation  had  only  been  found  for  offline  customer  experience.  The   authors   also   propose   flow   as   a   replacement   for   CES   in   an   online   context,   with   telepresence   (being   fully   immersed   in   the   experience)   and   challenge   (a   test   of   skill)  as  antecedents  (Rose  et  al.,  2012).     Flow   in   an   online   context   is   defined   as   “a   cognitive   state   experienced   during   online   navigation”   (Novak   et   al.,   2000)   and   has   been   found   to   positively   relate   to   exploratory  behavior  –  the  will  to  experiment  and  look  for  new  things  -­‐    (Ghani  &   Deshpande,  1994;  Novak  et  al.,  2000;  Webster,  Trevino,  &  Ryan,  1993)  as  well  as       Figure  1:  Model  for  online  customer  experience  by  Rose,  Clark,  Samouel,  &  Hair  (2012,  p.310)  

   

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purchase   intention   (Koufaris,   Kambil,   &   Labarbera,   2001;   Toñita   Perea   y   Monsuwé,   Benedict   G.C.   Dellaert,   &   Ko   de   Ruyter,   2004).   Guo   &   Poole   (2009)   have  proposed  a  model  that  explains  the  effect  of  perceived  website  complexity   on   customer   experience   using   the   original   flow   theory   as   introduced   by   Csikzentmihalyi   (1988).   The   results   across   all   studies   agree   that   in   an   online   context  (perceived)  challenge  is  an  important  factor  influencing  flow  as  well  as   telepresence.    

2.4.  Hypothesis  development     Research  has  provided  insights  into  multi-­‐channel  customer  experience  –  using   both   offline   and   online   channels   –   and   has   shown   how   traditional   online   channels   such   as   websites   influence   customer   experience.   As   of   recent,   however,   the   number   and   type   of   devices   customers   use   to   access   digital   content   has   increased.  While  companies  make  use  of  multiple  channels  in  an  online  context   (websites,   social   media,   retailer   platforms…),   customers   start   using   multiple   devices   to   access   this   content,   often   in   conjunction.   Software   companies   have   acted  on  this  by  introducing  continuity  features  in  their  operating  systems.  For   example,   both   Apple   and   Microsoft   have   recently   introduced   features   that   facilitate  the  ‘hand-­‐off’  of  tasks  such  as  e-­‐mailing  and  file  sharing  from  websites   to   desktop   computers   and   vice   versa.   Moreover   the   number   of   mobile   application   keeps   growing   and   the   time   spent   in   mobile   applications   increased   by  21%  between  2013  and  2014  (Hoch,  2014).     We   are   therefore   interested   in   how   the   type   of   device   used   by   a   customer   influences   their   customer   experience   with   the   same   product   or   brand.   In   this   study   we   will   research   differences   in   customer   experience   between   traditional   personal   computers   (desktops   and   laptops)   and   mobile   devices   (tablet   computers  and  smartphones),  based  on  the  content  a  user  is  exposed  to.  In  our   research   we   will   use   the   conceptual   model   for   online   customer   experience   as   posited  by  Rose  et  al.  (2012).  To  make  our  results  more  actionable  we  will  also  

 

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gauge   amongst   consumers   which   specific   features   enhance   their   experience   on   a   traditional  device  and  a  mobile  device  respectively.     Specifically,  we  will  test  the  following  hypotheses:   H1   Using  traditional  content  –  defined  as  the  average  online  content  not  adapted  to   any   particular   screen   size   or   device,   but   originally   intended   to   be   viewed   on   a   desktop   computer   or   laptop   –   online   customer   experience   (OCE)   using   a   traditional  device  (desktop  or  laptop)  is  different  from  viewing  the  same  content   on  a  mobile  device  (smartphone  or  tablet).  We  expect  the  OCE  for  mobile  devices   to   be   lower,   possibly   due   to   reduced   ease-­‐of-­‐use   caused   by   excessive   scrolling   necessary  to  view  the  content.   H2   When   content   is   adapted   to   the   device   a   customer   is   using   -­‐   as   in   specifically   designed  and  developed  for  use  on  a  particular  type  of  device,  e.g.  a  smartphone  -­‐ ,   we   expect   no   significant   difference   in   OCE   when   using   a   traditional   device   versus  a  mobile  device.   H3   People   enjoying   a   positive   customer   experience   on   a   mobile   device   are   more   likely   to   have   a   positive   experience   with   the   same   company   or   product   on   a   traditional   device   and   vice   versa.   In   other   words,   a   carry-­‐over   effect   of   customer   experience  exists  between  traditional-­‐  and  mobile  devices.   H4   We   hypothesize   that   consumers   have   different   purchase   intentions   for   a   particular  product  or  service  dependent  on  the  device  they  are  using.  We  expect   to  see  higher  purchase  intentions  for  traditional  devices.   H5   Furthermore   we   expect   to   see   differences   in   the   importance   of   antecedents   of   the   affective   experiential   state,   which   ultimately   form   the   online   customer  

 

7    

experience.   Implicating   that   different   features   are   important   for   consumers   depending  on  which  device  they  are  using.     The  above  hypotheses  will  be  tested  using  an  online  survey.  

 

 

8    

3.  Methodology   3.1.  Sample  and  participants     Research   was   conducted   in   the   Flemish   Region   of   Belgium.   An   online   questionnaire   was   distributed   through   the   social   network   Facebook   and   the   popular   Flemish   message   board   9lives.be.   The   questionnaire   was   written   in   Dutch.   Respondents   were   recruited   on   a   self-­‐selection   basis.   In   total   260   respondents  completed  the  questionnaire.     The   division   in   gender   male-­‐female   was   respectively   51%-­‐49%,   while   72%   of   respondents   were   between   the   age   of   18   and   25.   Also,   68%   of   respondents   indicated  that  they  have  received  higher  education  (college  or  university).     Notable   results   in   terms   of   usage   are   the   high   availability   of   laptops   and   smartphones.   94.31%   of   respondents   indicated   they   have   a   laptop   available   to   them,   while   84.83%   of   respondents   have   a   smartphone   available.   The   2015   global  results  are  respectively  84%  and  85%,  while  the  2015  Belgian  results  are   respectively   83%   and   68%   (“DigitasLBi‘s   2015   Connected   Commerce   study,”   2015).   The   discrepancy   between   the   Belgian   results   according   to   DigitasLBi’s   (2015)   survey   and   this   study   can   be   explained   by   the   smaller   sample   size   of   this   study  as  well  as  the  large  portion  of  respondents  between  the  age  of  18  and  25.       When   comparing   the   usage   of   different   devices   for   search   purposes,   it   is   apparent   that   again   the   laptop   and   smartphone   are   the   most   popular   devices.     For  laptops,  42.41%  of  respondents  search  for  products,  services  or  companies   on  a  daily  basis.  While  50,24%  of  respondents  use  their  smartphone  every  day  to   search  for  products,  services  or  companies.  For  purchasing  products  or  services   online,  63.74%  of  respondents  use  their  laptop  at  least  once  per  month.  22.98%   of  smartphone  owners  use  their  device  at  least  once  a  month  to  make  an  online   purchase.      

 

9    

Table  1:  availability  and  usage  of  devices   Availability  of  devices  to  respondents   Desktop  

Laptop  

Tablet  

Smartphone  

46,91%  

94,31%  

55,92%  

84,83%  

Usage  of  devices  to  search  for  products,  services  and  companies    

Never  

Yearly  

Monthly  

Weekly  

Daily  

Desktop  

36,96%  

13,03%  

20,85%  

17,30%  

11,85%  

Laptop  

4,97%  

2,13%  

14,69%  

35,78%  

42,41%  

Tablet  

28,91%  

9,95%  

22,27%  

23,22%  

15,64%  

Smartphone  

13,74%  

2,37%  

9,00%  

24,64%  

50,24%  

Usage  of  devices  to  purchase  products  and  companies    

Never  

Yearly  

Monthly  

Weekly  

Daily  

Desktop  

57,82%  

17,77%  

10,19%  

4,98%  

2,13%  

Laptop  

12,56%  

23,70%  

48,34%  

11,61%  

3,79%  

Tablet  

69,43%  

10,66%  

14,22%  

3,79%  

1,90%  

Smartphone  

65,88%  

11,14%  

13,74%  

5,21%  

4,03%  

  As   an   incentive   for   filling   out   the   questionnaire   two   film   tickets   were   raffled   amongst  respondents.  

3.2.  Experimental  design     The  main  goal  of  the  questionnaire  was  to  assess  online  customer  experience  for   different   devices.   Therefore   the   variable   ‘online   customer   experience’   (OCE)   was   measured   on   three   levels:   desktop   browser   experience,   smartphone   browser   experience  and  smartphone  application  experience.  To  measure  the  OCE  on  the   three   aforementioned   levels,   three   videos   were   created.   Each   video   contains   footage  of  creating  a   reservation  on  the  travel  website  booking.com,  followed  by   ordering   a   book   on   amazon.com,   a   popular   e-­‐retailer.   They   respectively   represent  the  online  purchase  of  a  service  and  a  product.  The  video  format  was   chosen   as   opposed   to   redirecting   respondents   to   an   actual   website   so   that   the   checkout   process   could   be   included   in   order   to   measure   the   full   online   customer   experience.   The   videos   were   shown   in   random   order.   Furthermore,   a   within-­‐ subjects   design   was   used,   every   video   was   shown   to   every   respondent.   An   overview  is  shown  in  table  2.    

Additionally  five  antecedents  and  three  outcome  variables  were  measured,  based   on  the  work  by  Rose  et  al.  (2012).  The  outcome  variables  ‘online  shopping      

10    

Table  2:  Experimental  design  to  measure  OCE  for  different  devices  and  content.    

Video  1  

Video  2  

Video  3  

Dependent  variable  

OCE  

OCE  

OCE  

Device  

Desktop  

Smartphone  

Smartphone  

Content  

Booking.com  website  

Booking.com  mobile  

Booking.com  website  

Amazon.com  website  

application  

Amazon.com  website  

Amazon.com  mobile   application   Content  type  

Traditional  –  not  

Adapted  to  device  

adapted   Level  of  OCE  measured  

Traditional  –  not   adapted  

Traditional  desktop  

Adapted  mobile  online  

Traditional  mobile  

online  customer  

customer  experience  

online  customer  

experience   Display  order  

experience   Randomized  

  satisfaction’   ‘trust   in   online   shopping’   and   ‘online   repurchase   intention’   were   measured   on   two   levels   using   a   within-­‐subjects   design:     traditional   device   (desktop/laptop)  and  mobile  device  (smartphone/laptop).  The  same  design  was   used  to  measure  five  antecedents:  ‘ease-­‐of-­‐use’,  ‘customization’,  ‘connectedness’,   ‘aesthetics’  and  ‘perceived  benefits’.  

3.3.  Procedure     After   a   brief   introduction   text   respondents   were   prompted   to   answer   a   set   of   questions   with   regard   to   which   devices   they   have   access   to   and   how   they   use   them.  Respondents  were  asked  whether  they  have  access  to  a  desktop  computer,   laptop,  tablet  or  smartphone.  Then,  respondents  had  to  order  these  devices  from   most   frequently   used   to   least   frequently   used.   If   a   device   was   not   available   to   them,  participants  were  asked  to  imagine  how  often  they  would  use  it  in  case  it   were.  Next,  two  questions  were  asked  to  measure  how  frequently  they  use  each   device  to  either  search  for  products,  services  or  companies  online  or  to  purchase   products  or  services  online.  A  five-­‐point  scale  was  used  containing  the  following   options:  never,  yearly,  monthly,  weekly  and  daily.     Afterwards,   respondents   were   briefed   about   the   scenario.   Three   videos   were   presented   to   them   in   random   order.   Each   consisted   of   booking   a   holiday   followed  by  purchasing  a  book.  Following  each  video,  respondents  were  asked  to    

11    

rate   their   online   customer   experience   using   scales   that   measure   affective   experiential  state  (AES)  and  cognitive  experiential  state  (CES).  AES  and  CES  are   the   two   components   that   form   online   customer   experience   (Rose   et   al.,   2012).   AES  was  measured  using  eight  items,  each  on  a  seven-­‐point  scale,  which  can  be   found   in   appendix   1.   CES   was   also   measured   on   a   seven-­‐point   scale   using   the   concept  of  flow  (appendix  1).  Respondents  were  asked  to  which  extent  they  did,   or   did   not,   experience   flow   during   the   online   shopping   experience   that   was   displayed.  Showing  videos  was  preferred  over  instructing  respondents  to  visit  a   particular   website   and   browse   around   themselves   in   order   to   standardize   the   experiences.     Figure   2:   Diagram   with   regard   to   the   measurement   of   OCE   for   different   devices   and   content   types   in   the   online  questionnaire.  

    Subsequently,  respondents  were  asked  to  answer  a  set  of  questions  with  regard   to   the   antecedents   and   outcomes   of   online   customer   experience   for   both   traditional   and   mobile   devices   separately,   based   on   their   personal   experience   with  them.  A  five-­‐point  Likert  scale  was  used  to  measure  the  outcome  constructs   (appendix   2   and   3),   while   participants   were   asked   to   rate   the   importance   of   different  antecedents  on  a  scale  ranging  from  0  to  100  (appendix  4).     To  conclude  the  questionnaire,  respondents  were  asked  about  their  gender,  age   and   level   of   education.   After   which   they   were   thanked   for   their   cooperation.   A   full  excerpt  of  the  questionnaire  can  be  found  in  appendix  5.    

 

12    

4.  Discussion  of  the  results   4.1.  Differences  in  OCE  between  traditional  versus  mobile  devices  and   traditional  versus  adapted  content.     In   order   to   test   the   first   two   hypotheses,   concerning   the   difference   in   OCE   between   a   traditional   desktop   experience,   adapted   mobile   experience   and   traditional   mobile   experience,   two   Repeated   Measures   ANOVA   tests   were   executed:   one   for   CES   as   dependent   variable   and   one   for   AES   as   dependent   variable,  which  are  the  components  of  OCE.  The  mean  scores  for  these  variables   were   used   to   compare   traditional   desktop   to   traditional   mobile   and   adapted   mobile   experiences.   CES   was   measured   using   the   concept   of   flow   (Rose   et   al.,   2012),  while  AES  was  measured  using  eight  items  as  found  in  previous  research   (source).   Both   components   were   measured   using   seven-­‐point   scales.   The   mean   score   on   the   eight   AES   items   is   used   in   the   analysis.   Reliability   of   the   AES   measurement   items   was   verified   for   the   traditional   desktop   experience   (Cronbach’s   α   =   .829),   traditional   mobile   experience   (Cronbach’s   α   =   .799)   and   adapted  mobile  experience  (Cronbach’s  α  =  .818).     Results   show   that   a   significant   difference   exists   between   a   traditional   desktop   and  traditional  mobile  experience.  The  traditional  desktop  experience  was  rated   significantly  higher  in  terms  of  both  CES  (F(2,  480)  =  19.943,  p  <  .001)  and  AES   (F(2,  480)  =  29.837,  p  <  .001).  Equally,  a  significant  difference  was  found  for  CES   (F(2,  480)  =  19.943,  p  =  .013)  and  AES  (F(2,  480)  =  29.837,  p  <  .001)  between  the   traditional   desktop   experience   and   adapted   mobile   experience,   in   favor   of   the   traditional   desktop   experience.   Using   OCE   as   dependent   variable,   calculated   as   the   mean   of   CES   and   AES,   results   are   consistent.   Again,   the   traditional   desktop   experience  is  rated  significantly  higher  versus  the  traditional  mobile  experience   (F(2,   480)   =   15.963,   p   <   .001)   and   the   adapted   mobile   experience   (F(2,   480)   =   15.963,   p   =   .001).   An   overview   of   the   results   can   be   found   in   tables   3   and   4.   Based  on  these  findings  it  is  possible  to  confirm  H1;  the  traditional  desktop  OCE   (using   a   desktop   or   laptop)   is   rated   significantly   higher   than   the   traditional   mobile   OCE   (using   a   smartphone   or   tablet).   However,   H2   cannot   be   confirmed.    

13    

The   traditional   desktop   OCE   was   rated   significantly   higher   than   the   adapted   mobile  OCE,  while  no  significant  difference  was  expected.     Table  3:  means  for  traditional  desktop,  traditional  mobile  and  adapted  mobile  experiences.    

CES  

AES  

OCE  

Experience  

Mean  

Std.  Deviation  

Mean  

Std.  Deviation  

Mean  

Std.  Deviation  

Traditional  Desktop  

3,66  

1,706  

4,166  

0,87595  

3,9131  

1,15179  

Adapted  mobile  

3,37  

1,777  

3,980  

0,86918  

3,6748  

1,18309  

Traditional  mobile  

3,00  

1,614  

3,794  

0,80908  

3,3989  

1,07554  

  Table  4:  differences  in  means  between  traditional  desktop,  traditional  mobile  and  adapted  mobile   experiences.   CES  

 

Mean  Difference  

Sig.  

I  

J  

(I  -­‐  J)  

Traditional  desktop  experience  

Adapted  mobile  experience  

.290  

.013  

Traditional  mobile  experience  

.656  

.000  

Adapted  mobile  experience  

Traditional  desktop  experience  

-­‐.290  

.013  

 

Traditional  mobile  experience  

.365  

.002  

Traditional  mobile  experience  

Traditional  desktop  experience  

-­‐.656  

.000  

Adapted  mobile  experience  

-­‐.365  

.002  

AES  

 

Mean  Difference  

Sig.  

I  

J  

(I  -­‐  J)  

Traditional  desktop  experience  

Adapted  mobile  experience  

.186  

.000  

Traditional  mobile  experience  

.373  

.000  

Adapted  mobile  experience  

Traditional  desktop  experience  

-­‐.186  

.000  

 

Traditional  mobile  experience  

.187  

.001  

Traditional  mobile  experience  

Traditional  desktop  experience  

-­‐.373  

.000  

Adapted  mobile  experience  

-­‐.187  

.001  

OCE  

 

Mean  Difference  

Sig.  

I  

J  

(I  -­‐  J)  

Traditional  desktop  experience  

Adapted  mobile  experience  

.238  

.001  

Traditional  mobile  experience  

.514  

.000  

Adapted  mobile  experience  

Traditional  desktop  experience  

-­‐.238  

.001  

 

Traditional  mobile  experience  

.276  

.000  

Traditional  mobile  experience  

Traditional  desktop  experience  

-­‐.514  

.000  

Adapted  mobile  experience  

-­‐.276  

.000  

  Using   Repeated   Measures   ANCOVA   these   results   were   tested   for   the   effect   of   confounding  variables.  Next  to  the  dependent  variable  OCE,  the  analysis  included   the  independent  variables  frequency  of  search  and  purchase  on  different  devices   as   well   as   socio-­‐demographic   variables   such   as   gender,   age   and   level   of    

14    

education.   The   between-­‐subjects   factors   ‘purchase   frequency   on   smartphones’   (F(4,   236)   =   2.755,   p   =   .029)   and   ‘purchase   frequency   on   laptop’   (F(4,   236)   =   4.239,  p  =  .002)  had  a  statistically  significant  effect  on  the  measured  level  of  OCE,   our  dependent  variable.  When  accounting  for  purchase  frequency  on  laptops,  the   difference   between   the   traditional   mobile   experience   and   the   adapted   mobile   experience   was   not   significant   (p   =   .412).   This   does   not   contradict   earlier   findings  about  H1  and  H2.  Taking  the  purchase  frequency  on  smartphones  into   consideration,   no   significant   difference   was   found   between   the   traditional   desktop   experience   and   the   adapted   mobile   experience  (p  =  1.000).   The  higher   the  purchase  frequency  on  smartphones,  the  higher  the  adapted  mobile  OCE  was   rated.   Respondents   indicating   that   they   never   use   their   smartphone   to   make   online  purchases  rated  the  adapted  mobile  OCE  on  average  3.5185  on  a  7-­‐point   scale,   while   respondents   using   their   smartphone   weekly   to   make   online   purchases  rated  the  adapted  mobile  OCE  4.5625  on  average.    This  result  suggests   that   it   is   possible   to   confirm   H2   -­‐   no   significant   difference   in   OCE   exists   between   a  traditional  desktop  experience  and  adapted  mobile  experience  -­‐  for  people  that   are   accustomed   to   using   their   smartphone   for   online   purchases.   This   indicates   that  a  learning  curve  might  exist  for  online  purchases  on  smartphones,  which  has   to   be   overcome   in   order   to   rate   the   adapted   mobile   OCE   equally   high   as   the   traditional  desktop  OCE.       Table  5:  analysis  of  the  effect  of  confounding  variables  on  the  mean  differences  between  the  traditional   desktop  experience,  adapted  mobile  experience  and  traditional  mobile  experience.    

F  

p  

Gender  (male  or  female)  

F(1,  220)  =  2.562  

p  =  .111  

Age  

F(4,  217)  =  1.197  

p  =  .313  

Level  of  education  

F(3,  218)  =  .502  

p  =  .681  

Search  frequency,  desktop  

F(4,  236)  =  2.372  

p  =  .053  

Search  frequency,  laptop  

F(4,  236)  =  1.102  

p  =  .356  

Search  frequency,  tablet  

F(4,  236)  =  2.185  

p  =  .071  

Search  frequency,  smartphone  

F(4,  236)  =  1.552  

p  =  .188  

Purchase  frequency,  desktop  

F(4,  236)  =  1.310  

p  =  .267  

Purchase  frequency,  laptop  

F(4,  236)  =  4.239  

p  =  .002  

Purchase  frequency,  tablet  

F(4,  236)  =  .705  

p  =  .589  

Purchase  frequency,  smartphone  

F(4,  236)  =  2.755  

p  =  .029  

 

15    

4.2.  Analyzing  the  carry-­‐over  effect  between  online  experiences  for   traditional  and  mobile  devices.   In   order   to   detect   a   possible   carry-­‐over   effect   between   online   experiences,   the   effect  of  display  order  on  the  device-­‐  and  content  dependent  OCE  was  analyzed.   Three   videos   were   displayed,   giving   six   possible   display   orders.   Using   display   order   as   a   between-­‐subjects   independent   factor   in   a   Repeated   Measures   ANCOVA   analysis,   with   OCE   as   the   dependent   factor   over   three   experiences   yielded   no   significant   result   (F(5,   235)   =   .542,   p   =   .744).   The   variable   display   order   was   then   recoded   to   reduce   the   possible   combinations   from   six   to   three,   allowing   for   a   less   complex   interpretation.   The   new   variable   indicated   which   experience   (traditional   desktop   OCE,   adapted   mobile   OCE   or   traditional   mobile   OCE)  was  shown  first.  The  Repeated  Measures  ANCOVA  analysis  was  run  again,   indicating  that  the  variable  first  experience  is  not  a  significant  between-­‐subjects   factor  (F(2,  238)  =  .444,  p  =  .642).  Finally,  a  One-­‐Way  ANOVA  test  was  conducted   with  traditional  desktop  OCE,  adapted  mobile  OCE  and  traditional  mobile  OCE  as   dependent  variables  and  first  shown  experience  as  independent  variable.  Again,   there   was   no   significant   difference   in   OCE   for   any   of   the   displayed   experiences   with   the   first   shown   experience   as   between-­‐subjects   factor.     Thus,   there   is   no   evidence   supporting   the   existence   of   a   significant   carry-­‐over   effect   of   OCE   between  devices.  Therefore  it  is  not  possible  to  confirm  H3.   Table 6: Descriptive statistics regarding a difference in OCE based on the first shown experience. First  shown    

experience  

Traditional   Desktop  OCE  

Std.   Mean  

Deviation   Std.  Error  Minimum   Maximum  

Traditional  Desktop   92  

3,7262  

1,11133  

,11586  

1,13  

6,63  

Adapted  Mobile  

80  

3,9852  

1,10608  

,12366  

1,75  

6,44  

Traditional  Mobile   88  

4,0362  

1,20533  

,12849  

1,50  

6,00  

260   3,9108  

1,14642  

,07110  

1,13  

6,63  

Total  

N  

Adapted  Mobile  

Traditional  Desktop   80  

3,6586  

1,20102  

,13428  

1,13  

6,63  

OCE  

Adapted  Mobile  

94  

3,5047  

1,07561  

,11094  

1,63  

5,75  

Traditional  Mobile   90  

3,7951  

1,21217  

,12777  

1,00  

6,00  

264   3,6503  

1,16379  

,07163  

1,00  

6,63  

Total  

Traditional  Mobile   Traditional  Desktop   78  

3,3566  

1,07218  

,12140  

1,19  

6,06  

OCE  

3,5313  

1,09501  

,12399  

1,31  

5,63  

Traditional  Mobile   104   3,3702  

1,09810  

,10768  

1,44  

6,00  

Total  

1,08797  

,06747  

1,19  

6,06  

 

Adapted  Mobile  

78  

260   3,4144  

16    

Table 7: ANOVA tests for a difference in OCE based on the first shown experience.  

F  

p  

Traditional  Desktop  OCE  

F(2,  257)  =  1.900  

p  =  .152  

Adapted  Mobile  OCE  

F(2,  261)  =  1.440  

p  =  .239  

Traditional  Mobile  OCE  

F(2,  257)  =  .644  

p  =  .526  

4.3.  Differences  in  antecedents  and  outcomes  of  OCE  for  traditional  and   mobile  devices.     First,   the   reliability   of   the   variables   with   regard   to   the   outcomes   of   OCE   was   established.  The  results  are  displayed  in  table  8.  Based  on  these  findings  we  can   conclude   that   the   constructs   ‘trust   in   online   shopping’,   ‘online   shopping   satisfaction’  and  ‘online  repurchase  intention’  are  internally  consistent  for  both   traditional  and  mobile  devices.     Table  8:  Reliability  of  variables  concerning  the  outcomes  of  OCE.   Traditional  devices  

Mobile  devices  

Construct  

Cronbach’s  α  

Construct  

Cronbach’s  α  

Trust  in  online  shopping  

.770  

Trust  in  online  shopping  

.810  

Online  shopping  

.791  

Online  shopping  

.837  

satisfaction   Online  repurchase  

satisfaction   .832  

intention  

Online  repurchase  

.831  

intention  

    In  order  to  analyze  differences  between  the  outcomes  of  OCE  for  traditional  and   mobile   devices,   a   paired   samples   T-­‐Test   was   executed.   The   results   are   given   in   table   9.   This   test   allows   us   to   conclude   that   there   is   a   significant   difference   between   traditional   and   mobile   devices   concerning   the   outcome   variables   of   OCE.   Trust   in   online   shopping,   online   shopping   satisfaction   and   online   repurchase   intention   are   all   significantly   higher   on   traditional   devices   than   on   mobile   devices.   This   result   further   aids   to   supports   the   earlier   findings   for   H1   and   H2,   since   a   higher   OCE   directly   leads   to   higher   trust   in   online   shopping,   online  shopping  satisfaction  and  online  repurchase  intention  (Rose  et  al.,  2012).   Moreover   it   is   possible   to   confirm   H4,   purchase   intentions   differ   based   on   the   device  used  and  purchase  intentions  for  traditional  devices  are  still  higher  than   those  for  mobile  devices.    

17    

Table  9:  Paired  Samples  T-­‐Test  for  variables  concerning  the  outcomes  of  OCE.    

Mean  

t(df)  

p  

Trust  in  online  shopping  

Mtraditional  =  3.2970  

t(185)  =  -­‐6.181  

<  .001  

t(185)  =  -­‐12.855  

<  .001  

t(185)  =  -­‐14.574  

<  .001  

Mmobile  =  2.9987   Online  shopping  

Mtraditional  =3.8333  

satisfaction  

Mmobile  =  3.1331  

Online  repurchase  

Mtraditional  =  3.9104  

intention  

Mmobile  =  2.6792  

 

With   regard   to   the   antecedents   of   OCE,   respondents   were   asked   to   rate   the   importance   of   each   of   the   affective   experiential   state   antecedents   on   a   0-­‐100   scale.   The   results   in   table   10   show   that   only   the   variables   ‘connectedness’   and   ‘perceived   benefits’   differ   significantly   for   traditional   and   mobile   devices.   Connectedness   –   as   in   connecting   with   other   users,   for   example   through   customer  reviews  or  social  media  sharing  options  –  is  perceived  more  important   on   traditional   devices   than   on   mobile   devices,   while   perceived   benefits   (e.g.   timesaving,   availability   of   information,   etc.)   for   traditional   online   shopping   is   rated  as  more  important  than  perceived  benefits  for  mobile  online  shopping.  The   difference   in   the   importance   of   perceived   benefits   for   the   users   could   be   attributed   to   the   existence   of   a   learning   effect   for   mobile   devices,   since   the   results   indicate   that   mobile   devices   are   less   frequently   used   for   online   purchase.   An  alternative  explanation  could  be  that  shopping  on  a  mobile  device  is  regarded   more   as   a   game,   thus   lowering   the   importance   of   perceived   benefits   like   timesaving   over   offline   shopping.   Drawing   conclusions   for   the   antecedent   connectedness  is  difficult  due  to  the  relatively  marginal  difference  in  importance       Table  10:  Paired  Samples  T-­‐Test  for  variables  concerning  the  antecedents  of  AES.    

Mean  

t(df)  

p  

Ease-­‐of-­‐use  

Mtraditional  =  86.4080  

t(200)  =  -­‐.176  

=  .860  

t(190)  =  -­‐1.371  

=  .172  

t(180)  =  -­‐2.452  

=  .015  

t(196)  =  0.82  

=  .935  

t(196)  =  -­‐3.782  

<  .001  

Mmobile  =  86.1990   Customization  

Mtraditional  =57.3455   Mmobile  =  55.3979  

Connectedness  

Mtraditional  =  39.9061   Mmobile  =  37.1934  

Aesthetics  

Mtraditional  =  70.0152   Mmobile  =  70.1066  

Perceived  benefits  

Mtraditional  =  76.4315   Mmobile  =  71.6294  

 

18    

(Mtraditional   =   39.9061   versus   Mmobile   =   37.1934).   Notwithstanding,   one   might   argue  that  when  using  a  mobile  device,  people  are  more  focused  on  the  main  goal   (purchasing  a  product  or  service)  and  don’t  want  to  be  distracted  by  connecting   or   relating   with   other   consumers.   Supporting   this   interpretation   with   data,   however,  lies  beyond  the  scope  of  this  study.    

 

 

19    

5.  Conclusions  and  practical  implications   The   goal   of   this   study   was   to   contribute   to   the   research   of   online   customer   experience  by  evaluating  how  different  devices  such  as  desktops,  laptops,  tablets   and   smartphones   and   different   types   of   content   like   a   traditional   website   or   a   device-­‐specific   application   influence   the   online   customer   experience.   This   research  uses  existing  models  (Guo  &  Poole,  2009;  Novak  et  al.,  2000;  Rose  et  al.,   2012;   Sousa   &   Voss,   2006)     to   analyze   these   differences.   The   conclusions   and   practical  implications  of  this  study  are  relevant  for  all  companies  that  currently   serve   their   customers   via   one   or   more   digital   channels   and   companies   that   are   looking  to  do  so  in  the  future.     First,   a   difference   in   online   customer   experience   was   established   between   traditional   devices   (desktop   or   laptop)   and   mobile   devices   (smartphone   or   tablet).  For  the  same  content  –  in  this  research  a  traditional  website  was  used  –   the   online   customer   experience   was   lower   for   mobile   device   users.   While   adapted   content   (a   device-­‐specific   application)   received   a   significantly   better   online   customer   experience   rating   than   the   aforementioned   traditional   website   on  a  mobile  device.  For  users  frequently  making  purchases  on  a  smartphone,  the   difference   in   online   customer   experience   between   a   traditional   website   and   an   adapted   mobile   application   was   insignificant.   Therefore,   companies   looking   to   provide  a  consistently  high  online  customer  experience  across  different  devices   should   put   effort   towards   optimizing   their   e-­‐commerce   specifically   for   each   type   of   device.   When   doing   so,   companies   should   first   analyze   how   customers   use   their  e-­‐commerce  tool  by  conducting  an  experiment  of  their  own,  or  by  analyzing   online   traffic   with   the   help   of   tools   like   Google   Analytics.   In   practice,   different   options  exist  for  adapting  content  to  different  devices.  From  making  an  existing   website   responsive   -­‐   where   the   existing   website   adapts   itself   to   the   device   a   customer  is  using  -­‐  to  creating  a  dedicated  application  for  mobile  devices,  like  the   examples  Booking.com  and  Amazon  used  in  this  study  have  done.       This  study  was  unable  to  detect  a  carry-­‐over  effect  of  online  customer  experience   from   one   device   to   another.   This   entails   that   a   low   or   high   online   customer   experience   on   one   device   has   no   predictive   power   for   the   online   customer    

20    

experience   on   a   different   device,   used   subsequently.   This   leads   to   two   possible   implications.   First,   a   bad   online   customer   experience   on   one   device   does   not   necessarily  lower  the  online  customer  experience  on  another  device.  Effectively   providing  the  company  with  a  second  chance.  Secondly,  it  is  important  to  provide   an   excellent   online   customer   experience   on   each   device   a   customer   might   use,   because   a   positive   online   customer   experience   is   not   carried   over   either.   Therefore   a   bad   online   customer   experience   on   a   specific   device   might   lead   to   lost  sales.     Analyzing   the   outcomes   of   online   customer   experience   shows   that   online   (re)purchase   intention   is   still   significantly   lower   for   mobile   devices   like   smartphones  and  tablets.  This  is  caused  by  the  lower  online  customer  experience   on   these   devices,   as   this   negatively   impacts   the   online   repurchase   intention   (Rose   et   al.,   2012).   With   smartphone   users   growing   to   an   expected   33.8%   worldwide   by   2017   (“Smartphone   Users   Worldwide   Will   Total   1.75   Billion   in   2014   -­‐   eMarketer,”   2014),   this   should   serve   as   another   incentive   to   adapt   e-­‐ commerce   content   to   specific   types   of   devices   such   as   smartphones,   by   means   of   a   mobile   application   or   responsive   website.   In   terms   of   antecedents   of   online   customer   experience,   two   differences   were   found   between   traditional   and   mobile  devices.  A  small  difference  was  found  for  the  antecedent  connectedness.   Connectedness   is   perceived   slightly   less   important   on   mobile   devices   than   on   traditional   devices.   However,   suggesting   omitting   features   concerning   connectedness   on   mobile   devices   would   be   premature,   but   perhaps   their   position  could  be  made  less  prominent.  A  suggestion  for  companies  is  to  conduct   their   own   analysis   on   the   importance   of   antecedents   of   online   customer   experience   for   their   specific   e-­‐commerce   tool,   in   order   to   determine   which   aspects   should   receive   more   attention   on   traditional   websites   and   mobile   applications  respectively.    

 

 

 

21    

6.  Limitations  and  future  research     The   findings   in   this   study   are   somewhat   constrained   by   limitations   in   the   research.   Some   of   these   limitations   provide   opportunities   for   future   research.   The   geographic   region   in   which   this   study   was   conducted   is   limited   to   the   Flemish   speaking   region   of   Belgium.   The   same   research   may   yield   different   results  in  other  geographic  areas  due  to  differences  in  availability  and  usage  of   devices.  Next,  a  large  portion  of  respondents  (72%)  was  between  the  age  of  18   and   25.   This   is   not   representative   for   the   actual   population.   Conducting   a   research  with  a  quota-­‐based  sample  instead  of  a  convenience  sample  will  resolve   this  issue.    Lastly,  for  testing  the  first  two  hypotheses  concerning  a  difference  in   online  customer  experience  for  different  devices  and  different  types  of  content,  a   between-­‐subjects   design   would   be   preferable   over   a   within-­‐subjects   design   in   order  to  limit  learning  effects  and  the  effects  of  boredom.  Furthermore,  a  notable   result   of   this   study   is   that   while   50.24%   of   respondents   use   a   smartphone   to   search  for  products,  services  or  companies  on  a  daily  basis,  only  22.98%  of  them   indicate   making   a   purchase   on   their   smartphone   at   least   once   a   month.   The   purchase  frequency  for  laptops  is  almost  three  times  higher  while  the  number  of   respondents   using   the   device   to   search   for   products   on   a   daily   basis   is   lower.   Future  studies  could  try  to  identify  in  detail  what  the  causes  of  this  discrepancy   are.  In  general  it  is  important  that  more  research  is  conducted  towards  the  role   of   mobile   devices   on   the   customer   experience   and   other   aspects   of   marketing,   because   of   their   increasing   popularity   and   their   as   of   yet   unexplored   capabilities   to  increase  overall  customer  experience  and  customer  satisfaction.      

 

22    

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VII    

Decision  Making.  Journal  of  Advertising  Research,  54(2),  200–204.   http://doi.org/10.2501/JAR-­‐54-­‐2-­‐200-­‐204   Novak,  T.  P.,  Hoffman,  D.  L.,  &  Yung,  Y.-­‐F.  (2000).  Measuring  the  Customer   Experience  in  Online  Environments:  A  Structural  Modeling  Approach.   Marketing  Science,  19(1),  22–42.   http://doi.org/10.1287/mksc.19.1.22.15184   Rawson,  A.,  Duncan,  E.,  &  Jones,  C.  (2013a).  The  Truth  About  Customer   Experience.  Harvard  Business  Review,  91(11),  26–26.   Rawson,  A.,  Duncan,  E.,  &  Jones,  C.  (2013b).  Touchpoints  matter,  but  it’s  the  full   journey  that  really  counts.  Harvard  Business  Review,  91(9),  90–+.   Roggeveen,  A.,  &  Schlesinger,  L.  (2008).  Customer  Experience  Creation:   Determinants,  Dynamics  and  Management  Strategies.  Journal  of  Retailing.   Retrieved  from  http://digitalknowledge.babson.edu/mktgpw/1   Rose,  S.,  Clark,  M.,  Samouel,  P.,  &  Hair,  N.  (2012).  Online  Customer  Experience  in   e-­‐Retailing:  An  empirical  model  of  Antecedents  and  Outcomes.  Journal  of   Retailing,  88(2),  308–322.  http://doi.org/10.1016/j.jretai.2012.03.001   Smartphone  Users  Worldwide  Will  Total  1.75  Billion  in  2014  -­‐  eMarketer.  (2014,   January  16).  Retrieved  November  3,  2014,  from   http://www.emarketer.com/Article/Smartphone-­‐Users-­‐Worldwide-­‐Will-­‐ Total-­‐175-­‐Billion-­‐2014/1010536   Sousa,  R.,  &  Voss,  C.  A.  (2006).  Service  Quality  in  Multichannel  Services   Employing  Virtual  Channels.  Journal  of  Service  Research,  8(4),  356–371.   http://doi.org/10.1177/1094670506286324   Tax,  S.  S.,  McCutcheon,  D.,  &  Wilkinson,  I.  F.  (2013).  The  Service  Delivery   Network  (SDN):  A  Customer-­‐Centric  Perspective  of  the  Customer  Journey.    

VIII    

Journal  of  Service  Research,  16(4),  454–470.   http://doi.org/10.1177/1094670513481108   Toñita  Perea  y  Monsuwé,  Benedict  G.C.  Dellaert,  &  Ko  de  Ruyter.  (2004).  What   drives  consumers  to  shop  online?  A  literature  review.  International   Journal  of  Service  Industry  Management,  15(1),  102–121.   http://doi.org/10.1108/09564230410523358   Uzunoğlu,  E.,  &  Misci  Kip,  S.  (2014).  Brand  communication  through  digital   influencers:  Leveraging  blogger  engagement.  International  Journal  of   Information  Management,  34(5),  592–602.   http://doi.org/10.1016/j.ijinfomgt.2014.04.007   Van  Birgelen,  M.,  de  Jong,  A.,  &  de  Ruyter,  K.  (2006).  Multi-­‐channel  service   retailing:  The  effects  of  channel  performance  satisfaction  on  behavioral   intentions.  Journal  of  Retailing,  82(4),  367–377.   http://doi.org/10.1016/j.jretai.2006.08.010   Wang,  Q.,  Song,  P.,  &  Yang,  X.  (2013).  Understanding  the  substitution  effect   between  online  and  traditional  channels:  evidence  from  product   attributes  perspective.  Electronic  Markets,  23(3),  227–239.   http://doi.org/10.1007/s12525-­‐012-­‐0114-­‐2   Webster,  J.,  Trevino,  L.  K.,  &  Ryan,  L.  (1993).  The  dimensionality  and  correlates  of   flow  in  human-­‐computer  interactions.  Computers  in  Human  Behavior,   9(4),  411–426.  http://doi.org/10.1016/0747-­‐5632(93)90032-­‐N  

   

 

 

IX    

Appendix  1.  Measurement  scales  for  OCE.   Construct  

Reference  

Adapted  Scale  (English)  

Adapted  Scale  (Dutch)  

Cognitive  

 

•  The  word  “flow”  is  used  to  describe  

•  Het  woord  “flow”  wordt  gebruikt  om  

Experiental  State  

a  state  of  mind  sometimes  

een  gemoedstoestand  te  beschrijven  

(Flow)  

experienced  by  people  who  are  

die  soms  ervaren  wordt  door  mensen  

deeply  involved  in  some  activity.  One  

die  diep  betrokken  zijn  in  een  

example  of  flow  is  the  case  where  a  

activiteit.  Een  voorbeeld  van  flow  is  

professional  athlete  is  playing  

het  geval  waar  een  professionele  

exceptionally  well  and  achieves  a  

atleet  uitstekend  aan  het  spelen  is  en  

state  of  mind  where  nothing  else  

in  een  gemoedstoestand  komt  waar  

matters  but  the  game;  he  or  she  is  

niets  telt  behalve  het  spel.  Hij  of  zij  is  

completely  and  totally  immersed  in  it.  

er  compleet  in  ondergedompeld.  Niet  

The  experience  is  not  exclusive  to  

alleen  atleten  ervaren  dit;  veel  

athletics;  many  people  report  this  

mensen  melden  deze  

state  of  mind  when  playing  games,  

gemoedstoestand  wanneer  ze  

engaging  in  hobbies,  or  working.  

videospellen  spelen,  zich  engageren  in  

Activities  that  lead  to  flow  completely  

hun  hobby  of  aan  het  werk  zijn.  

captivate  a  person  for  some  period  of  

Wanneer  iemand  flow  ervaart  is  het  

time.  When  one  is  in  flow,  time  may  

vaak  zo  dat  tijd  lijkt  stil  te  staan,  en  de  

seem  to  stand  still,  and  nothing  else  

rest  van  de  wereld  lijkt  te  verdwijnen.  

seems  to  matter.  Flow  may  not  last  for  

Flow  hoeft  niet  noodzakelijk  lang  te  

a  long  time  on  any  particular  

duren  en  kan  komen  en  gaan.  Flow  

occasion,  but  it  may  come  and  go  over  

wordt  beschreven  als  een  aangename  

time.  Flow  has  been  described  as  an  

ervaring.  

intrinsically  enjoyable  experience.    

  •  Antwoord  op  de  volgende  vraag  

•  Thinking  about  your  most  recent  

terugdenkend  aan  je  meest  recente  

Internet  shopping  experience,  

internet  aankoop  op  een  mobiel  

respond  to  the  following  (1–7  scale):  

toestel  (1-­‐7  schaal):  

•  When  Internet  shopping  I  have  

•  Ik  heb  flow  ervaren  tijdens  het  

experienced  flow...When  Internet  

internetshoppen  …  Ik  heb  geen  flow  

shopping  I  have  never  experienced  

ervaren  tijdens  het  internetshoppen.  

flow.     Affective   Experiental  State  

 

Using  the  rating  scale  below  indicate  

Duidt  op  onderstaande  schalen  aan  

the  feelings  you  had  following  your  

hoe  u  zich  voelde  tijdens  de  getoonde  

most  recent  online  shopping  

online  koopervaringen.  

experience  (1–7  scale):  

  Ongelukkig  

Gelukkig  

Unhappy  

Happy  

Ontevreden  

Tevreden  

Melancholic  

Contented  

Vervelend    

Plezierig  

Annoyed    

Pleased  

Sloom    

Enthousiast  

Sluggish    

Frenzied  

Kalm    

Levendig  

Calm    

Excited  

Ontspannen    

Geprikkeld  

Relaxed    

Stimulated  

Begeleid    

Autonoom  

Guided    

Autonomous  

Beïnvloed    

Invloedrijk    

Influenced    

Influential    

 

 

 

1    

Appendix  2.  Measurement  scales  for  outcomes  of  OCE  on   mobile  devices     Construct  

Reference  

Adapted  Scale  (English)  

Adapted  Scale  (Dutch)  

Trust  in  Online  

 

•  Internet  shopping  is  reliable.    

•  Mobiel  internet  shoppen  is  

•  In  general  I  can  rely  on  Internet  

betrouwbaar.  

vendors  to  keep  the  promises  that  

•  In  het  algemeen  kan  ik  vertrouwen  

they  make.    

op  de  beloftes  die  gemaakt  worden  

•  Internet  shopping  can  be  trusted,  

door  verkopers  op  mobiele  internet  

there  are  no  uncertainties.  

shopping  applicaties.  

•  Internet  shopping  is  a  trustworthy  

•  Mobiel  internet  shoppen  is  te  

experience.    

vertrouwen,  er  zijn  geen  

Shopping  

onzekerheden.    

•  Mobiel  internet  shoppen  is  een   vertrouwenswaardige  ervaring.  

Online  Shopping  

 

Satisfaction  

•  I  am  satisfied  with  my  overall  

•  Ik  ben  tevreden  met  de  algemene  

experiences  of  Internet  shopping.  

koopervaring  wanneer  ik  winkel  op  

•  I  am  satisfied  with  the  pre-­‐purchase  

mijn  mobiel  toestel.  

experience  of  Internet  shopping  

•  Ik  ben  tevreden  met  de  ervaring  

websites  (e.g.,  consumer  education,  

voorafgaand  aan  de  aankoop  bij  

product  search,  quality  of  information  

mobiel  internet  shoppen  (bv.  

about  products,  product  comparison).  

beschikbaarheid  en  kwaliteit  van  

•  I  am  satisfied  with  the  purchase  

informative,  zoeken  naar  producten,  

experience  of  Internet  shopping  

vergelijken  van  producten).  

websites  (e.g.,  ordering,  payment  

•  Ik  ben  tevreden  met  de  

procedure).  

koopervaring  bij  mobiel  online  

•  I  am  satisfied  with  the  post-­‐

winkelen  (bv.  bestel-­‐  en  

purchase  experience  of  Internet  

betaalprocedure).  

shopping  websites  (e.g.,  customer  

•  Ik  ben  tevreden  met  de  dienst  na  

support  and  after  sales  support,  

verkoop  wanneer  ik  aan  mobiel  

handling  of  returns/refunds,  delivery  

online  shoppen  doe.  

care).   Online  repurchase   intention  

 

•  It  is  likely  that  I  will  repurchase  

•  Het  is  waarschijnlijk  dat  ik  in  de  

from  Internet  shopping  websites  in  

nabije  toekomst  aankopen  zal  doen  

the  near  future.  

via  mijn  mobiel  toestel.  

•  I  anticipate  repurchasing  from  

•  Ik  koop  regelmatig  aan  via  dezelfde  

Internet  shopping  websites  in  the  

mobiele  shopping  applicaties.  

near  future.  

•  Ik  voorzie  in  de  nabije  toekomst  

•  I  regularly  repurchase  from  the  

aankopen  te  doen  via  mijn  mobiel  

same  websites.  

toestel.  

•  I  expect  to  repurchase  from  Internet  

 

shopping  websites  in  the  near  future.    

 

 

2    

Appendix  3.  Measurement  scales  for  outcomes  of  OCE  on   traditional  devices     Construct  

Reference  

Adapted  Scale  (English)  

Adapted  Scale  (Dutch)  

Trust  in  Online  

 

•  Internet  shopping  is  reliable.    

•  Internet  shoppen  is  betrouwbaar.  

•  In  general  I  can  rely  on  Internet  

•  In  het  algemeen  kan  ik  vertrouwen  

vendors  to  keep  the  promises  that  

op  de  beloftes  die  gemaakt  worden  

they  make.    

door  verkopers  op  internet  shopping  

•  Internet  shopping  can  be  trusted,  

websites.  

there  are  no  uncertainties.  

•  Internet  shoppen  is  te  vertrouwen,  

•  Internet  shopping  is  a  trustworthy  

er  zijn  geen  onzekerheden.  

experience.    

•  Internet  shoppen  is  een  

Shopping  

vertrouwenswaardige  ervaring.     Online  Shopping  

 

Satisfaction  

•  I  am  satisfied  with  my  overall  

•  Ik  ben  tevreden  met  de  algemene  

experiences  of  Internet  shopping.  

koopervaring  wanneer  ik  online  

•  I  am  satisfied  with  the  pre-­‐purchase  

winkel.  

experience  of  Internet  shopping  

•  Ik  ben  tevreden  met  de  ervaring  

websites  (e.g.,  consumer  education,  

voorafgaand  aan  de  aankoop  bij  

product  search,  quality  of  information  

internet  shoppen  (bv.  

about  products,  product  comparison).  

beschikbaarheid  en  kwaliteit  van  

•  I  am  satisfied  with  the  purchase  

informative,  zoeken  naar  producten,  

experience  of  Internet  shopping  

vergelijken  van  producten).  

websites  (e.g.,  ordering,  payment  

•  Ik  ben  tevreden  met  de  

procedure).  

koopervaring  bij  online  winkelen  (bv.  

•  I  am  satisfied  with  the  post-­‐

bestel-­‐  en  betaalprocedure).  

purchase  experience  of  Internet  

•  Ik  ben  tevreden  met  de  dienst  na  

shopping  websites  (e.g.,  customer  

verkoop  wanneer  ik  aan  online  

support  and  after  sales  support,  

shoppen  doe.  

handling  of  returns/refunds,  delivery   care).   Online  repurchase   intention  

 

•  It  is  likely  that  I  will  repurchase  

•  Het  is  waarschijnlijk  dat  ik  in  de  

from  Internet  shopping  websites  in  

nabije  toekomst  aankopen  zal  doen  

the  near  future.  

via  een  internet  shopping  website.  

•  I  anticipate  repurchasing  from  

•  Ik  koop  regelmatig  aan  via  dezelfde  

Internet  shopping  websites  in  the  

websites.  

near  future.  

•  Ik  plan  in  de  nabije  toekomst  

•  I  regularly  repurchase  from  the  

aankopen  te  doen  via  internet  

same  websites.  

shopping  websites.  

•  I  expect  to  repurchase  from  Internet  

 

shopping  websites  in  the  near  future.    

 

 

3    

Appendix  4.  Measurement  scales  for  antecedents  of  OCE  on   mobile  and  traditional  devices.   Construct  

Reference  

Adapted  Scale  (English)  

Adapted  Scale  (Dutch)  

Mobile  devices:  

 

How  important  are  the  following  

Hoe  belangrijk  vindt  u  onderstaande  

Ease-­‐of-­‐use,  

characteristics  to  you  when  shopping  

eigenschappen  tijdens  het  winkelen  

customization,  

on  your  smartphone  or  tablet?  (Scale  

op  uw  smartphone  of  tablet?  (Schaal  

connectedness,  

0-­‐100)  

0-­‐100)  

aesthetics,  

 

perceived  benefits  

•  Ease-­‐of-­‐use  

•  Gebruiksgemak  

•  Customization  

•  Personaliseerbaarheid  

•  Connectedness  (with  other  users)  

•  Verbondenheid  (met  andere  

•  Aesthetics  

gebruikers)  

•  Benefits  in  comparison  to  traditional  

•  Ontwerp  en  uiterlijk  

shopping  (e.g.  time-­‐saving,  price  

•  Voordelen  ten  opzichte  van  

comparison,  availability  of  

traditioneel  shoppen  (tijdsbesparing,  

information,…)  

prijsvergelijking,  beschikbaarheid  van   informatie,…)  

Traditional  

 

How  important  are  the  following  

Hoe  belangrijk  vindt  u  onderstaande  

devices:  Ease-­‐of-­‐

characteristics  to  you  when  shopping  

eigenschappen  tijdens  het  winkelen  

use,  customization,  

on  your  computer  or  laptop?  (Scale  0-­‐

op  uw  computer  of  laptop?  (Schaal  0-­‐

connectedness,  

100)  

100)  

aesthetics,  

 

perceived  benefits  

•  Ease-­‐of-­‐use  

•  Gebruiksgemak  

•  Customization  

•  Personaliseerbaarheid  

•  Connectedness  (with  other  users)  

•  Verbondenheid  (met  andere  

•  Aesthetics  

gebruikers)  

•  Benefits  in  comparison  to  traditional  

•  Ontwerp  en  uiterlijk  

shopping  (e.g.  time-­‐saving,  price  

•  Voordelen  ten  opzichte  van  

comparison,  availability  of  

traditioneel  shoppen  (tijdsbesparing,  

information,…)  

prijsvergelijking,  beschikbaarheid  van   informatie,…)  

 

 

 

4    

Appendix  5.  Excerpt  of  survey   The  effect  of  digital  technology  on  customer  experience     S1  Beste  deelnemer,  Ik  voer  momenteel  een  onderzoek  uit  in  het  kader  van  mijn   masterthesis.  In  functie  van  dit  onderzoek  werd  een  enquête  opgesteld,  het   invullen  hiervan  zal  maximaal  tien  minuten  in  beslag  nemen.Door  het  invullen   van  deze  vragenlijst  doet  u  mij  niet  alleen  een  ontzettend  plezier,  maar  u  maakt   ook  kans  op  een  Kinepolis  duoticket.  Indien  u  wenst  mee  te  dingen  naar  het   Kinepolis  duoticket  moet  u  op  het  einde  van  de  vragenlijst  uw  e-­‐mail  adres   achterlaten.Alvast  bedankt!Jens  ScheerlinckMaster  student  Toegepaste   Economische  Wetenschappen:  MarketingUniversiteit  Gent         Q1  Over  welke  van  de  volgende  toestellen  beschikt  u?   Desktop  computer  (1)   Laptop  (2)   Tablet  (3)   Smartphone  (4)     Q2  Rangschik  onderstaande  toestellen  volgens  uw  gebruiksfrequentie.  Het   toestel  dat  u  het  vaakst  gebruikt  komt  bovenaan.  Indien  u  niet  beschikt  over  één   of  meerdere  toestellen,  stel  u  dan  voor  hoe  vaak  u  het  toestel  zou  gebruiken  ten   opzichte  van  de  toestellen  waar  u  wel  over  beschikt.   ______  Desktop  computer  (1)   ______  Laptop  (2)   ______  Tablet  (3)   ______  Smartphone  (4)     Q3  Hoe  vaak  gebruikt  u  de  volgende  toestellen  om  informatie  op  te  zoeken  over   bedrijven,  diensten  en/of  producten?  Bijvoorbeeld:  openingsuren,   productinformatie,  beschikbaarheid,  prijzen,...    

 

Nooit  (1)  

Jaarlijks  (2)  

Maandelijks  

Wekelijks  

Dagelijks  

(3)  

(4)  

(5)  

5    

Desktop  

 

 

 

 

 

Laptop  (2)  

 

 

 

 

 

Tablet  (3)  

 

 

 

 

 

 

 

 

 

 

computer  (1)  

Smartphone   (4)  

    Q4  Hoe  vaak  gebruikt  u  de  volgende  toestellen  om  online  goederen  en/of   diensten  aan  te  kopen?  Bijvoorbeeld:  aankopen  van  producten,  aankopen  van   muziek,  aankopen  van  films  of  series,  aankopen  van  videospelletjes  of   applicaties,  het  boeken  van  een  vakantie,...    

Desktop  

Nooit  (1)  

Jaarlijks  (2)  

Maandelijks  

Wekelijks  

Dagelijks  

(3)  

(4)  

(5)  

 

 

 

 

 

Laptop  (2)  

 

 

 

 

 

Tablet  (3)  

 

 

 

 

 

 

 

 

 

 

computer  (1)  

Smartphone   (4)  

    S2  U  krijgt  nu  enkele  opnames  te  zien  van  online  aankopen  op  verschillende   toestellen,  gevolgd  door  enkele  vragen.  Het  is  belangrijk  dat  u  zich  voorstelt  dat   u  zelf  aan  het  online  shoppen  bent.Het  scenario  is  telkens  hetzelfde:  u  boekt   eerst  een  vakantie  en  gaat  vervolgens  op  zoek  naar  een  boek  om  mee  te  nemen   op  reis.De  opnames  bevatten  geen  geluid.     V1  Bekijk  onderstaande  video  in  fullscreen:     Q5  Het  woord  “flow”  wordt  gebruikt  om  een  gemoedstoestand  te  beschrijven  die   soms  ervaren  wordt  door  mensen  die  diep  betrokken  zijn  in  een  activiteit.  Een    

6    

voorbeeld  van  flow  is  het  geval  waar  een  professionele  atleet  uitstekend  aan  het   spelen  is  en  in  een  gemoedstoestand  komt  waar  niets  telt  behalve  het  spel.  Hij  of   zij  is  er  compleet  in  ondergedompeld.  Niet  alleen  atleten  ervaren  dit;  veel   mensen  melden  deze  gemoedstoestand  wanneer  ze  videospellen  spelen,  zich   engageren  in  hun  hobby  of  aan  het  werk  zijn.  Wanneer  iemand  flow  ervaart  is   het  vaak  zo  dat  tijd  lijkt  stil  te  staan,  en  de  rest  van  de  wereld  lijkt  te  verdwijnen.   Flow  hoeft  niet  noodzakelijk  lang  te  duren  en  kan  komen  en  gaan.  Flow  wordt   doorgaans  beschreven  als  een  aangename  ervaring.Duid  op  onderstaande  schaal   uw  ervaring  aan  met  de  getoonde  online  koopervaring.    

1  (1)  

2  (2)  

3  (3)  

4  (4)  

5  (5)  

6  (6)  

7  (7)  

 

 

 

 

 

 

 

Ik  heb  geen  flow   ervaren  tijdens  het   internetshoppen.:Ik   heb  flow  ervaren   tijdens  het   internetshoppen   (1)  

    Q6  Duidt  op  onderstaande  schalen  aan  hoe  u  zich  voelde  tijdens  de  getoonde   online  koopervaring.    

1  (1)  

2  (2)  

3  (3)  

4  (4)  

5  (5)  

6  (6)  

7  (7)  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Vervelend:Plezierig  (3)  

 

 

 

 

 

 

 

Sloom:Enthousiast  (4)  

 

 

 

 

 

 

 

Kalm:Levendig  (5)  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Ongelukkig:Gelukkig   (1)   Ontevreden:Tevreden   (2)  

Ontspannen:Geprikkeld   (6)   Begeleid:Zelfstandig  

 

7    

(7)   Beïnvloed:Invloedrijk  

 

(8)  

 

 

 

 

 

 

  V2  Bekijk  onderstaande  video  in  fullscreen:     Q7  Het  woord  “flow”  wordt  gebruikt  om  een  gemoedstoestand  te  beschrijven  die   soms  ervaren  wordt  door  mensen  die  diep  betrokken  zijn  in  een  activiteit.  Een   voorbeeld  van  flow  is  het  geval  waar  een  professionele  atleet  uitstekend  aan  het   spelen  is  en  in  een  gemoedstoestand  komt  waar  niets  telt  behalve  het  spel.  Hij  of   zij  is  er  compleet  in  ondergedompeld.  Niet  alleen  atleten  ervaren  dit;  veel   mensen  melden  deze  gemoedstoestand  wanneer  ze  videospellen  spelen,  zich   engageren  in  hun  hobby  of  aan  het  werk  zijn.  Wanneer  iemand  flow  ervaart  is   het  vaak  zo  dat  tijd  lijkt  stil  te  staan,  en  de  rest  van  de  wereld  lijkt  te  verdwijnen.   Flow  hoeft  niet  noodzakelijk  lang  te  duren  en  kan  komen  en  gaan.  Flow  wordt   doorgaans  beschreven  als  een  aangename  ervaring.Duid  op  onderstaande  schaal   uw  ervaring  aan  met  de  getoonde  online  koopervaring.    

1  (1)  

2  (2)  

3  (3)  

4  (4)  

5  (5)  

6  (6)  

7  (7)  

 

 

 

 

 

 

 

Ik  heb  geen  flow   ervaren  tijdens  het   internetshoppen.:Ik   heb  flow  ervaren   tijdens  het   internetshoppen   (1)  

    Q8  Duidt  op  onderstaande  schalen  aan  hoe  u  zich  voelde  tijdens  de  getoonde   online  koopervaring.     Ongelukkig:Gelukkig   (1)  

 

1  (1)  

2  (2)  

3  (3)  

4  (4)  

5  (5)  

6  (6)  

7  (7)  

 

 

 

 

 

 

 

8    

Ontevreden:Tevreden  

 

 

 

 

 

 

 

Vervelend:Plezierig  (3)  

 

 

 

 

 

 

 

Sloom:Enthousiast  (4)  

 

 

 

 

 

 

 

Kalm:Levendig  (5)  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(2)  

Ontspannen:Geprikkeld   (6)   Begeleid:Zelfstandig   (7)   Beïnvloed:Invloedrijk   (8)  

    V3  Bekijk  onderstaande  video  in  fullscreen:     Q9  Het  woord  “flow”  wordt  gebruikt  om  een  gemoedstoestand  te  beschrijven  die   soms  ervaren  wordt  door  mensen  die  diep  betrokken  zijn  in  een  activiteit.  Een   voorbeeld  van  flow  is  het  geval  waar  een  professionele  atleet  uitstekend  aan  het   spelen  is  en  in  een  gemoedstoestand  komt  waar  niets  telt  behalve  het  spel.  Hij  of   zij  is  er  compleet  in  ondergedompeld.  Niet  alleen  atleten  ervaren  dit;  veel   mensen  melden  deze  gemoedstoestand  wanneer  ze  videospellen  spelen,  zich   engageren  in  hun  hobby  of  aan  het  werk  zijn.  Wanneer  iemand  flow  ervaart  is   het  vaak  zo  dat  tijd  lijkt  stil  te  staan,  en  de  rest  van  de  wereld  lijkt  te  verdwijnen.   Flow  hoeft  niet  noodzakelijk  lang  te  duren  en  kan  komen  en  gaan.  Flow  wordt   doorgaans  beschreven  als  een  aangename  ervaring.  Duid  op  onderstaande  schaal   uw  ervaring  aan  met  de  getoonde  online  koopervaring.    

1  (1)  

2  (2)  

3  (3)  

4  (4)  

5  (5)  

6  (6)  

7  (7)  

 

 

 

 

 

 

 

Ik  heb  geen  flow   ervaren  tijdens  het   internetshoppen.:Ik   heb  flow  ervaren   tijdens  het  

 

9    

internetshoppen   (1)  

  Q10  Duidt  op  onderstaande  schalen  aan  hoe  u  zich  voelde  tijdens  de  getoonde   online  koopervaring.    

1  (1)  

2  (2)  

3  (3)  

4  (4)  

5  (5)  

6  (6)  

7  (7)  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Vervelend:Plezierig  (3)  

 

 

 

 

 

 

 

Sloom:Enthousiast  (4)  

 

 

 

 

 

 

 

Kalm:Levendig  (5)  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Ongelukkig:Gelukkig   (1)   Ontevreden:Tevreden   (2)  

Ontspannen:Geprikkeld   (6)   Begeleid:Zelfstandig   (7)   Beïnvloed:Invloedrijk   (8)  

    Answer  If  Over  welke  van  volgende  toestellen  beschikt  u?  Smartphone  Is   Selected   Q11  Onderstaande  vragen  polsen  naar  uw  eigen  ervaringen  met  online  winkelen   op  uw  smartphone  of  tablet.  Denk  hierbij  aan:  aankopen  van  producten,   aankopen  van  muziek,  aankopen  van  films  of  series,  aankopen  van   videospelletjes  of  applicaties,  het  boeken  van  een  vakantie,...    

Helemaal  

Niet  

Neutraal  

Akkoord  

Helemaal  

niet  

akkoord  

(3)  

(4)  

akkoord  

akkoord  

(2)  

(5)  

(1)   Mobiel  internet  

 

 

 

 

 

 

10    

shoppen  is   betrouwbaar.  (2)   In  het  algemeen  kan   ik  vertrouwen  op  de   beloftes  die  gemaakt   worden  door  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

verkopers  op  mobiele   internet  shopping   applicaties.  (3)   Mobiel  internet   shoppen  is  te   vertrouwen,  er  zijn   geen  onzekerheden.   (4)   Mobiel  internet   shoppen  is  een   vertrouwenswaardige   ervaring.  (5)   Ik  ben  tevreden  met   de  algemene   koopervaring   wanneer  ik  winkel  op   mijn  mobiel  toestel.   (6)   Ik  ben  tevreden  met   de  ervaring   voorafgaand  aan  de   aankoop  bij  mobiel   internet  shoppen  (bv.   beschikbaarheid  en   kwaliteit  van   informatie,  zoeken   naar  producten,   vergelijken  van  

 

11    

producten).  (7)   Ik  ben  tevreden  met   de  koopervaring  bij   mobiel  online   winkelen  (bv.  bestel-­‐  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

en  betaalprocedure).   (8)   Ik  ben  tevreden  met   de  dienst  na  verkoop   wanneer  ik  aan   mobiel  online   shoppen  doe.  (11)   Het  is  waarschijnlijk   dat  ik  in  de  nabije   toekomst  aankopen   zal  doen  via  mijn   mobiel  toestel.  (9)   Ik  koop  regelmatig   aan  via  dezelfde   mobiele  shopping   applicaties.  (51)   Ik  voorzie  in  de  nabije   toekomst  aankopen  te   doen  via  mijn  mobiel   toestel.  (10)  

    Q12  Hoe  belangrijk  vindt  u  onderstaande  eigenschappen  tijdens  het  winkelen  op   uw  smartphone  of  tablet?  Bij  0  hecht  u  absoluut  geen  belang  aan  deze   eigenschap,  bij  100  vindt  u  deze  eigenschap  erg  belangrijk.     ______  Gebruiksgemak  (1)   ______  Personaliseerbaarheid  (2)   ______  Verbondenheid  (met  andere  gebruikers)  (3)   ______  Ontwerp  en  uiterlijk  (4)    

12    

______  Voordelen  ten  opzichte  van  traditioneel  shoppen  (tijdsbesparing,   prijsvergelijking,  beschikbaarheid  van  informatie)  (5)     Q13  Onderstaande  vragen  polsen  naar  uw  eigen  ervaringen  met  online  winkelen   op  uw  computer  of  laptop.  Denk  hierbij  aan:  aankopen  van  producten,  aankopen   van  muziek,  aankopen  van  films  of  series,  aankopen  van  videospelletjes  of   applicaties,  het  boeken  van  een  vakantie,...    

Helemaal  

Niet  

Neutraal  

Akkoord  

Helemaal  

niet  

akkoord  

(3)  

(4)  

akkoord  

akkoord  

(2)  

(5)  

(1)   Internet  shoppen  is   betrouwbaar.  (1)  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In  het  algemeen  kan   ik  vertrouwen  op  de   beloftes  die  gemaakt   worden  door   verkopers  op  internet   shopping  websites.   (2)   Internet  shoppen  is  te   vertrouwen,  er  zijn   geen  onzekerheden.   (3)   Internet  shoppen  is   een   vertrouwenswaardige   ervaring.  (4)   Ik  ben  tevreden  met   de  algemene   koopervaring   wanneer  ik  online   winkel.  (5)  

 

13    

Ik  ben  tevreden  met   de  ervaring   voorafgaand  aan  de   aankoop  bij  internet   shoppen  (bv.   beschikbaarheid  en  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

kwaliteit  van   informatie,  zoeken   naar  producten,   vergelijken  van   producten).  (6)   Ik  ben  tevreden  met   de  koopervaring  bij   online  winkelen  (bv.   bestel-­‐  en   betaalprocedure).  (7)   Ik  ben  tevreden  met   de  dienst  na  verkoop   wanneer  ik  aan  online   shoppen  doe.  (8)   Het  is  waarschijnlijk   dat  ik  in  de  nabije   toekomst  aankopen   zal  doen  via  een   internet  shopping   website.  (9)   Ik  koop  regelmatig   aan  via  dezelfde   websites.  (11)   Ik  plan  in  de  nabije   toekomst  aankopen  te   doen  via  internet   shopping  websites.   (10)  

 

14    

    Q14  Hoe  belangrijk  vindt  u  onderstaande  eigenschappen  tijdens  het  winkelen  op   uw  computer  of  laptop?  Bij  0  hecht  u  absoluut  geen  belang  aan  deze  eigenschap,   bij  100  vindt  u  deze  eigenschap  erg  belangrijk.     ______  Gebruiksgemak  (1)   ______  Personaliseerbaarheid  (2)   ______  Verbondenheid  (met  andere  gebruikers)  (3)   ______  Ontwerp  en  uiterlijk  (4)   ______  Voordelen  ten  opzichte  van  traditioneel  shoppen  (tijdsbesparing,   prijsvergelijking,  beschikbaarheid  van  informatie)  (5)     Q15  Wat  is  uw  geslacht?   Man  (1)   Vrouw  (2)     Q16  Wat  is  uw  leeftijd?   jonger  dan  18  jaar  (1)   18-­‐25  jaar  (2)   26-­‐40  jaar  (3)   41-­‐55  jaar  (4)   ouder  dan  55  jaar  (5)     Q17  Wat  is  het  hoogste  opleidingsniveau  dat  u  genoten  hebt?   Lager  onderwijs  (1)   Lager  secundair  (2)   Hoger  secundair  (3)   Hogeschool  (4)   Universitair  (5)     Q18  Wenst  u  kans  te  maken  op  een  Kinepolis  filmticket?  Vul  dan  hier  uw  e-­‐mail   adres  in.      

15    

Q19  Browser  Meta  Info   Browser  (1)   Version  (2)   Operating  System  (3)   Screen  Resolution  (4)   Flash  Version  (5)   Java  Support  (6)   User  Agent  (7)    

 

16