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Sergio Martín
Ferran Giones
Dr. Francesc Miralles
Social Media engagement as an
e-commerce driver, a consumer
behavior perspective
CISTI 2014
Barcelona
18-21 June 2014
Introduction (1/2)
• The irruption of the Web 2.0 and the Social Media
offer opportunities and challenges for e-commerce
players (Kim & Srivastava, 2007) .
• Social Media allows consumers to generate
information and share opinions with a bigger scope and
much more impact (Hennig Thurau et al., 2010).
• Consumers have gained influence on other
consumer's decision and purchase process.
2
Introduction (2/2)
• Companies have lost perception of control on the
information flow during the purchase decision process.
• Organizations in e-commerce could benefit from a
better understanding of this often unobserved first
stage that now can be explored: problem recognition
stage (Santesmases, 2004).
• This work aims to analyze the relationship between
Social Media engagement (Facebook usage) and the
drivers of the problem recognition stage for the
purchase process.
3
Literature Review (1/4)
• Understand the consumer behavior change and the
influence of the Social Media.
• The Engel, Kollat and Blackwell Model (EKB) uses the
purchase decision process to study the consumer
behavior.
• The EKB Model pictures the components of the
decision making process and highlights the multiple
links and interactions between different components.
4
Problem
Recognition
Search
Evaluation of
alternatives
Choice Outcomes
Literature Review (2/4)
• The problem recognition is a passive process, difficult to
predict or influence (Sirgy et al., 2008).
• Problem recognition is the psychological process by which
the individual evaluates the difference between the “actual
state” and the “desired state” in relation to a good or
service.
• Actual state: the way an individual perceives his or her
feelings and situations to be at the present time.
• Desired state: the way an individual wants to feel or be at
the present time (Hawkins et al., 2010).
5
Literature Review (3/4)
• The problem recognition stage of the consumer is
affected by different factors: (1) situational influences,
(2) consumer influences and (3) marketing influences
(Sirgy et al., 2008).
6
Desired
State
Actual
State
Literature Review (4/4)
• Marketing and e-commerce researchers are
interested in understanding how the Web 2.0 and
Social Media are influencing the consumer behavior
(Kaplan et al., 2010).
• Facebook has emerged as the dominant online social
network and it’s a reference to study Social Media
engagement and the consumer behavior changes
(Wilson et al., 2012).
• Facebook could be a great platform to channel the
influence from one to another consumer, impacting on
the desired state of the consumer (Mukina, 2010).
7
Research gap (1/2)
• Consumer behavior and Social Media literature offer
the possibility to build a framework to advance on the
understanding of the e-commerce era purchase
process.
• To the knowledge of the authors of this research, there is
still little empirical research on this area.
• Theoretical framework to explore different patterns in
the activation of the problem recognition using
Facebook usage as an indicator.
8
Research gap (2/2)
*Based in the framework proposed by Punj & Srinivasan (1992)
• Explore whether the usage of Facebook introduces
differences in perceived state and thus would be
indicative of different paths to problem recognition
activation*.
9
FB Usage↑
FB Usage↓
Desired state
Actual state
Problem
Recognition
- Higher expected
satisfaction
- New need
- Current dissatisfaction
- Product depletion
H1a
H2
Need
Opportunity
Method & Data
• Quantitative research approach, hypothesis test.
• Study on the acquisition of a smartphone.
• Self-administered online questionnaire to gather
evidence available during summer of 2013.
• Statistical analysis using T-Student test to check
significant differences in the perceived state (actual vs
desired) regarding the activation of the problem
recognition.
10
Results (1/2)
• 101 individuals, 44% women and 56% men, with an
average age of 28 years.
• Facebook usage frequency as a group variable: “low
Facebook usage” and “high Facebook usage”.
• The two groups show differences in the state that
motivated their problem recognition:
• “High usage of Facebook” presents a closer influence to the
desired state as the activator of the purchase.
• “Low usage of Facebook” presents a closer influence to the
actual state as the activator of the purchase.
11
Results (2/2)
12
Social Media engagement
Usage characteristics
0 – actual state
1 - undetermined
2 – desired state
Limitations & Further Research
• Social and cognitive changes related to age and
experience could affect consumer state.
• Further research could benefit from introducing other
types of products purchases and reaching a more
varied population sample, both in age and
demographic profiles.
13
Conclusions
• Web 2.0 and Social Media era have reignited the e-
commerce adoption.
• High Facebook usage profiles show higher desired
state as the activator of the problem recognition.
• Better understanding on how differences in Social
Media engagement could affect individuals’ e-
commerce purchases.
• Companies could personalize marketing messages so
that the efficacy of their marketing efforts increase.
14
Sergio Martin
Ferran Giones
Dr. Francesc Miralles
Social Media engagement as an
e-commerce driver, a consumer
behavior perspective
CISTI 2014
Barcelona
18-21 June 2014

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Social Media engagement as an e-commerce driver, a consumer behavior perspective, by Sergio Martín

  • 1. Sergio Martín Ferran Giones Dr. Francesc Miralles Social Media engagement as an e-commerce driver, a consumer behavior perspective CISTI 2014 Barcelona 18-21 June 2014
  • 2. Introduction (1/2) • The irruption of the Web 2.0 and the Social Media offer opportunities and challenges for e-commerce players (Kim & Srivastava, 2007) . • Social Media allows consumers to generate information and share opinions with a bigger scope and much more impact (Hennig Thurau et al., 2010). • Consumers have gained influence on other consumer's decision and purchase process. 2
  • 3. Introduction (2/2) • Companies have lost perception of control on the information flow during the purchase decision process. • Organizations in e-commerce could benefit from a better understanding of this often unobserved first stage that now can be explored: problem recognition stage (Santesmases, 2004). • This work aims to analyze the relationship between Social Media engagement (Facebook usage) and the drivers of the problem recognition stage for the purchase process. 3
  • 4. Literature Review (1/4) • Understand the consumer behavior change and the influence of the Social Media. • The Engel, Kollat and Blackwell Model (EKB) uses the purchase decision process to study the consumer behavior. • The EKB Model pictures the components of the decision making process and highlights the multiple links and interactions between different components. 4 Problem Recognition Search Evaluation of alternatives Choice Outcomes
  • 5. Literature Review (2/4) • The problem recognition is a passive process, difficult to predict or influence (Sirgy et al., 2008). • Problem recognition is the psychological process by which the individual evaluates the difference between the “actual state” and the “desired state” in relation to a good or service. • Actual state: the way an individual perceives his or her feelings and situations to be at the present time. • Desired state: the way an individual wants to feel or be at the present time (Hawkins et al., 2010). 5
  • 6. Literature Review (3/4) • The problem recognition stage of the consumer is affected by different factors: (1) situational influences, (2) consumer influences and (3) marketing influences (Sirgy et al., 2008). 6 Desired State Actual State
  • 7. Literature Review (4/4) • Marketing and e-commerce researchers are interested in understanding how the Web 2.0 and Social Media are influencing the consumer behavior (Kaplan et al., 2010). • Facebook has emerged as the dominant online social network and it’s a reference to study Social Media engagement and the consumer behavior changes (Wilson et al., 2012). • Facebook could be a great platform to channel the influence from one to another consumer, impacting on the desired state of the consumer (Mukina, 2010). 7
  • 8. Research gap (1/2) • Consumer behavior and Social Media literature offer the possibility to build a framework to advance on the understanding of the e-commerce era purchase process. • To the knowledge of the authors of this research, there is still little empirical research on this area. • Theoretical framework to explore different patterns in the activation of the problem recognition using Facebook usage as an indicator. 8
  • 9. Research gap (2/2) *Based in the framework proposed by Punj & Srinivasan (1992) • Explore whether the usage of Facebook introduces differences in perceived state and thus would be indicative of different paths to problem recognition activation*. 9 FB Usage↑ FB Usage↓ Desired state Actual state Problem Recognition - Higher expected satisfaction - New need - Current dissatisfaction - Product depletion H1a H2 Need Opportunity
  • 10. Method & Data • Quantitative research approach, hypothesis test. • Study on the acquisition of a smartphone. • Self-administered online questionnaire to gather evidence available during summer of 2013. • Statistical analysis using T-Student test to check significant differences in the perceived state (actual vs desired) regarding the activation of the problem recognition. 10
  • 11. Results (1/2) • 101 individuals, 44% women and 56% men, with an average age of 28 years. • Facebook usage frequency as a group variable: “low Facebook usage” and “high Facebook usage”. • The two groups show differences in the state that motivated their problem recognition: • “High usage of Facebook” presents a closer influence to the desired state as the activator of the purchase. • “Low usage of Facebook” presents a closer influence to the actual state as the activator of the purchase. 11
  • 12. Results (2/2) 12 Social Media engagement Usage characteristics 0 – actual state 1 - undetermined 2 – desired state
  • 13. Limitations & Further Research • Social and cognitive changes related to age and experience could affect consumer state. • Further research could benefit from introducing other types of products purchases and reaching a more varied population sample, both in age and demographic profiles. 13
  • 14. Conclusions • Web 2.0 and Social Media era have reignited the e- commerce adoption. • High Facebook usage profiles show higher desired state as the activator of the problem recognition. • Better understanding on how differences in Social Media engagement could affect individuals’ e- commerce purchases. • Companies could personalize marketing messages so that the efficacy of their marketing efforts increase. 14
  • 15. Sergio Martin Ferran Giones Dr. Francesc Miralles Social Media engagement as an e-commerce driver, a consumer behavior perspective CISTI 2014 Barcelona 18-21 June 2014