Charitable Behaviour and the Moderating
Role of Information Specificity
First supervisor: Dr. J.C. Hoekstra Second supervisor: Dr. J.A. Voerman
University of Groningen
Faculty of Economics and Business MSc Marketing Management
Master Thesis Defense Dilyana Doychinova
Introduction
Framing – presentation of the same information in different ways which may influence decision making
Information specificity – specific information about how exactly the donations will be used to achieve the fundraising goal.
Conceptual Model
• H1: A message in a negative frame will result in higher donation intentions than a message in a positive frame • H2: Information specificity
moderates the negative effect of message framing on donation intention.
• H3: The moderating effect of
information specificity is larger in case of negative message framing.
Methodology
• Online survey • 211 respondents • 2x2 between subjects experimental design. Info. specificityFraming Low level of IS High level of IS
Negative Condition 2 Condition 4
Positive Condition 1 Condition 3
Condition 1: With your help, we will be able to provide her the things she
might need to go to school and, thus, change her life for the better.
Condition 2: Without your help, we won’t be able to provide her the things
she might need to go to school and, thus, her life will stay the same.
Condition 3: With your help, we will be able to provide her a scholarship
and the pocket money she needs to go to school and, thus, change her life for the better.
Condition 4: Without your help we won’t be able to provide her a
scholarship, or the pocket money she needs to go to school and her life will stay the same.
Method of analysis
• Factor analysis
• Reliability analysis
• T-test
• Regression Model 1: DI= β0 + β1 × Gender + β2 × Age + β3 × Nationality + β4 × Education + β5 × Kids + β6 × DP + ε
• ANCOVA
• Regression Model 2: DI= β0 + β1 × F + β2 × IS + β3 × F × IS + β4 × DP + ε • Regression Model 3a: DI= β0 + β1 × IS + β2 × DP + ε
Results - ANCOVA
Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 112,791a 2 56,395 32,227 .000
Intercept 40,284 1 40,284 23,02 .000 DP 83,545 1 83,545 47,742 .000 Framing 30,081 1 30,081 17,19 .000 Error 349,984 200 1,75 Total 4080,75 203 Corrected Total 462,775 202
Table 3 –ANCOVA results Figure 2 – Difference between DI in negative and positive conditions
• Significant difference between negative and positive
message framing on the mean of donation intentions of respondents.
• A negatively framed message results in higher
donation intentions than a positively framed message
Results – Regression Analysis Model 2
• Main effect of the independent
variable is negative and highly significant
• Interaction effect is insignificant
• Significant, direct effect of information
specificity
• Significant effect of the control variable
H2 – Rejected
* : at least 90% of significance ** : at least 95% of significance ***: at least 99% of significance
Table 2 – Regression analysis for donation intentions
Variables Hypothesis
(Effect) Model 1 Model 2 Model 3a Model 3b
1 1,2 1,4 1,6 1,8 2 2,2 2,4
Negative framing Positive framing
Do na tio n Inte nti ons Low IS High IS
Results – Regression Analysis Model 3a,b
• H3 – Rejected
* : at least 90% of significance ** : at least 95% of significance ***: at least 99% of significance
Table 2 – Regression analysis for donation intentions
Variables Hypothesis
(Effect) Model 1 Model 2 Model 3a Model 3b
Constant .708 1.800 1.248 1.975 Main Variables Framing -.306*** Control variables Gender .014 Age -.006 Nationality -.109 Education .074 Kids .079 Donation proneness .420*** .365** .397*** .471*** Moderators H3 (+) Information specificity H2 (+) .218*** .177** .094 Interaction Effects Framing * Information specificity .068 R2 (Adjusted R2) (.174) .199 (.285) .299 (.182) .197 (.219) .236 R2 change .168*** .002 .157*** .221*** F-value .109*** 21.119*** 12.774*** 14.342***
Additional analysis
Figure 5 – PROCESS Model 3 – Conceptual and statistical diagram, based on Hayes (2013)**
Model 4: DI=β0+β1*F+β2*IS+β3*N+β4*F*IS+β5*F*N+β6*IS*N+β7*F*IS*N, Model 5a: DI= β0+β1*IS+β2*DP+β3*N+β4*IS*N, (POSITIVE FRAMING)
Model 5b: DI= β0+β1*IS+β2*DP+β3*N+β4*IS*N, (NEGATIVE FRAMING)
Figure 4 – CAF World Giving Index (2016)*
Results – Additional analysis
Model 4
• Main effect of the independent
variable is negative and highly significant
• Significant direct effect of DP & IS
• 3-way interaction effect is
significant
c: at least 90% of significance b: at least 95% of significance a: at least 99% of significance
Table 4 – Regression analysis – Additional analysis
Results – Additional analysis
Model 5 a & b
• Significant effect of information
specificity in the case of negative framing (Model 5b)
• Insignificant effect of information
specificity in the case of negative framing (Model 5a)
• Significant direct effect of DP
c: at least 90% of significance b: at least 95% of significance a: at least 99% of significance
Table 4 – Regression analysis – Additional analysis
Results
Hypothesis analysisMain Additional analysis H1 Negatively framed message will result in higher donation intentionsthan a positively framed message. Supported Supported
H2 Information specificity moderates the negative effect of messageframing on donation intention. Rejected Supported
H3 The moderating effect of information specificity is larger in case ofnegative message framing. Rejected Supported Table 6 – Hypotheses testing
Discussion
• Negative framing is effective in soliciting significantly higher donation intentions
regardless of the specificity of the information given.
• High information specificity condition leads to higher donation intentions on average
than low information specificity condition.
• Characteristics of the sample
• Donation intentions ≠ behaviour
• Cultural differences - Laufer et al. (2010) *
