A COMPARISON OF THE EFFECTS OF ONLINE SOCIAL

A COMPARISON OF THE EFFECTS OF ONLINE SOCIAL

INTERACTIONS ON THE CONSUMERS DECISION

MOTIVATION TO STUDY

•

Psychological background

•

Customers decision making process is not optimal

•

Gap in existing literature

Research questions:

•

“To what extent do consumers rely on observational learning (OL) cues in an online

decision making process for annuities, compared to regular durable goods?”

•

“To what extent do consumers rely on electronic word of mouth (eWOM) in an online

decision making process for annuities, compared to regular durable goods?”

CONCEPTUAL

MODEL

• SOCIAL INTERACTIONS

• OBSERVATIONAL LEARNING

• ELECTRONIC WORD OF MOUTH

MAIN FINDINGS

•

The analysis shows that the two product types do differ on its characteristics.

•

According to the literature this also leads to different sequence of steps in the

decision making processes. In addition, persuasion will be determined by different

kinds of information.

•

The main effects of social interaction slightly differs for annuities compared to

regular durable goods.

•

However, for both product types the moderating effects turned out to be only

marginally significant and only for a couple of social interaction valences.

•

Overall: Useful insights for managers and consumers on the effects of online social

THEORETICAL

FRAMEWORK

• THE DIFFERENCES

• DECISION MAKING PROCESS

• FCB-GRID

• ELABORATION LIKELIHOOD MODEL

• ACCESSIBILITY-DIAGNOSTICITY MODEL

Regular durable good

(Digital camera)

Annuity

(Health insurance)

Payment is made once Payments are made over time within the accumulation phase

Relatively short term oriented (< 5 years)

Long term oriented Price is determined, and value is only

changing due to deprecation

Price is fluctuating due to inflation and value depends on the accumulation phase The moment of delivery of the product is

the same as the moment of buying

The moment of delivery (i.e. annuitization phase) of the product is delayed to a later

moment in time

THEORETICAL FRAMEWORK

•

FCB-GRID

•

ELABORATION LIKELIHOOD MODEL

•

ACCESSIBILITY-DIAGNOSTICITY MODEL

RESEARCH

DESIGN

• CHOICE-BASED CONJOINT ANALYSIS

• TWO ONLINE QUESTIONNAIRES

• ONE ENTRY LINK

RESEARCH DESIGN

•

…

Price (Filler) • €104,95 (per month) • €120,95 (per month) • €124,95 (per month) Linear/ Part-worth Brand age (Filler)

• This brand is ten years on the market • This brand is three years on the market • This brand is one year on the market

Part-worth Percentage of

bought items

(OL)

• Positive (85% of the customers who viewed this

product, actually bought it)

• Negative (15% of the customers who viewed this

product, actually bought it) • No (Unknown)

Part-worth

Customer review

(eWOM)

• Positive (Perhaps one of the best digital cameras I

have ever had. And yes, after 1 year I am still satisfied with my choice!)

• Negative (This is one of the worst digital cameras I

RESULTS

• SAMPLE CHARACTERISTICS

• Mainly Dutch people

• Age: 16-61 • Education level • Experience • MAIN EFFECT • INTERACTION EFFECTS Experience Yes No Experience Yes No Education Level No degree

Secondary school (Middelbare school) Community college (MBO)

University (HBO and higher) Other

Education Level

No degree

Secondary school (Middelbare school) Community college (MBO)

RESULTS – MAIN EFFECTS

OBSERVATIONAL LEARNING

•

Positive OL has positive influence

•

Negative OL has negative influence

•

No OL also has a negative influence

ELECTRONIC WORD OF MOUTH

•

Positive eWOM has a positive influence

•

Negative eWOM has a negative

influence

•

Neutral eWOM has a positive influence

•

No eWOM has a negative influence

• Covariates: Education level and Experience • Checking Model fit and validity

RESULTS – MAIN EFFECTS: COMPARISON

12 • Comparison between the two product types:

• Electronic word of mouth is ranked first for both product types, but the relative importance is higher in the digital camera setting.

• Observational learning is ranked second for both product types, but the relative importance is higher in the digital camera setting.

RESULTS – INTERACTION EFFECTS

• The model without interaction effect will make better prediction of the preferences of the respondents than a model with an interaction between OL and eWOM valence.

• However, to check the hypotheses according to this interaction it was necessary to include the interaction effects.

• Only three moderating effect are significant, and only on a 0.10 significance level.

Supported

• “Positive OL has a weaker effect on product preference when displayed with positive eWOM.” • “Positive OL has a weaker effect on product preference when displayed with negative eWOM.”

Rejected

RESULTS – INTERACTION EFFECTS: COMPARISON

14 • Comparison between the two product types:

DISCUSSION

• THEORETICAL IMPLICATIONS

• MANAGERIAL IMPLICATIONS

• LIMITATIONS

THEORETICAL IMPLICATIONS (I)

16

•

The relative attribute importance of e-WOM for a digital camera is even higher than

for a health insurance.

• The reason for this can be found in the decision making process where the need to make a more well considerate decision for a health insurance is more important than for a digital camera. This can explain the relatively more equally divided importance across all the

different attributes.

• Another explanation can be, that customers of annuities are more likely to choose to follow a more credible source of information (OL) instead of information with the highest

diagnosticity (eWOM).

•

No OL cue seems to be less preferred than negative OL

• A possible reason for this remarkable finding can be that people do not trust an OL signal

that only indicates “Unknown”, and therefore prefer a product with a negative OL cue

THEORETICAL IMPLICATIONS (II)

•

The impact of negative eWOM for health insurances indeed turned out to have a

bigger impact than positive eWOM. However, for digital cameras this was not the

case, since the magnitude of negative signals is smaller, compared to positive signals.

• A possible reason for this can be that digital cameras are not associated with a high level

of risk. And therefore the effect of negative reviews will be weaker.

•

It should be kept in mind that the findings according to the interaction effects did

only become significant at a ten per cent significance level. Moreover, the impact of

the interaction effects within this research are rather small.

• Therefore, one should be careful with the interpretation of this interaction effect.

PRACTICAL IMPLICATIONS AND LIMITATIONS

18

•

Managers – I would recommend managers to experiment with OL cues on their own

webpage or in other online settings.

• Since the positive effect of positive OL are relatively larger compared to negative OL. The possible gains turned out to be larger than the possible losses.

•

Managers – Be careful with presentation of eWOM.

• The relative high importance is also the result of the large downside of eWOM. Negative eWOM can hurt the preference for your products significantly.

• “The negative impact of negative reviews comes quickly and goes slowly” (Tirunillai & Tellis, 2012).

•

Limitations: number-of-level effect, number of respondents.

REFERENCES

20

• Chen, Y., Wang Q., and Xie J. 2011. Online social interactions: a natural experiment on

word of mouth versus observational learning. Journal of Marketing Research, 48 (2): 238-54.

• Feldman, J. & Lynch, J. 1988. Self-generated validity and other effects of measurement on belief, attitude, intention, and behavior. Journal of Applied Psychology, 73 (3): 421– 35.

• Fennis, B. M. & Stroebe, W. 2016. The Psychology of advertising. Abingdon (Oxon): Routledge.

• Petty, R. E., Cacioppo, J. T., and Schumann, D. 1983. Central and peripheral routes to

advertising effectiveness: the moderating role of involvement. Journal of Consumer

Research, 10 (3): 135-146.