Hong Kong PolyU: Valentina Cotton-Chan Leuphana University Lüneburg, Germany: Paula Maria Bögel Lisa Ulsamer Sigrid Bekmeier-Feuerhahn Cultural Differences in the Credibility of Cause-related- Marketing Campaign: A Sino- German Comparison CSR in Hypermodern Time BledCom 2017 30 June
Recipient of Faculty Award for Outstanding Performance/Achievement 2014/2015 (Teaching) Valentina Cotton-Chan, Teaching Fellow Contact Information Email: Valentina.chan@polyu.edu.hk Telephone: 2766-7462 Facebook: https://www.facebook.com/ykv.chan.polyu Facebook email: ykvchan@polyu.edu.hk WeChat: tinachanhk Twitter: ekwanc@gmail.com Skype: ekwanc
Content 1. Introduction & Purpose 2. Literature review & hypotheses 3. Methodologies & Hypotheses Testing 4. Results 5. Discussion 6. Q & A
Content 1. Introduction & Purpose 2. Literature review & hypotheses 3. Methodologies & Hypotheses Testing 4. Results 5. Discussion 6. Q & A
1) Introduction > A key problem of CSR communication is the rising scepticism from the consumers towards CSR and the related promotional forms, e.g., cause-related marketing (CrM). > Previous studies conclude that credibility, as a critical success factor of CrM campaigns, varies according to the nationalities of the consumers. > This study contributes to the literature by investigating the cultural differences between young Germans and Mainland Chinese regarding their perceived credibility of a chosen CrM campaign. > The two nationalities are selected due to their economic impact and the lack of coverage in past comparative literature of CSR.
Content 1. Introduction & Purpose 2. Literature review & hypotheses 3. Methodologies & Hypotheses Testing 4. Results 5. Discussion 6. Q & A
2) Literature Review (1/6) - Intercultural comparisons on CSR communication is a gap > Numerous scholars suggest that intercultural comparisons on CSR and CSR communication is a significant research gap (Diehl et al. 2015). For example, Furrer et al. (2010, 393) described the CSR research development on crossnational differences as embryonic. > The few studies address this subject mostly focus on the differences within Western European countries; and; between these European countries and the U.S.A. (cf., e.g., Fifka 2013). Research on countries that have more profound diversities in terms of their cultural proximities and CSR development cycle (Guzman & Becker-Olsen 2010) are very few.
2) Literature Review (2/6) - CSR Life cycle model (Guzman & Becker-Olsen: 2010) Figure 1: CSR Life-cycle model. Guzman & Becker-Olsen (2010)
2) Literature Review (3/6) - Assumptions > China is considered in the early market expansion phase of the CSR development cycle with consumer awareness starting to raise (Cotton-Chan, 2015); whereas Germany is regarded as a more mature market in the competitive turbulence and fragmentation phase similar to the U.S.A. > The assumption is that Chinese consumers are less knowledgeable about CSR than the Germans, as CSR is less common comparatively. Previous studies indicate more knowledge about CSR leads to a more skeptical evaluation of CSR campaigns.
2) Literature Review (4/6) - Motive attribution (Independent variable) > Attribution theory deals with how people explain their own as well as the behaviour of authors (Aronson et al., 2004, p. 115); Ellen et al. (2006, p. 147) differentiate between four motives: > Strategic (extrinsic & intrinsic) > Egoistic (extrinsic) > Stakeholder-driven (extrinsic) > Value-driven (intrinsic) > And further explain that consumers tend to perceive strategic and valuedriven motives positively whereas egoistic & stakeholder-driven motives are viewed negatively (Ellen et al., 2006, p. 154). > Bigne-Alcaniz, et al. (2009) further elaborate that altruistic attributions are the most powerful antecedent to brand credibility in CrM campaign.
2) Literature Review (5/6) - Motive attribution (Germans) > Germans high level of CSR knowledge in combination with a general tendency of distrusting institutions (Oloko, 2008) drive them to attribute self-centered motives to CrM campaigns, which have been proven to diminish campaigns credibility.
2) Literature Review (6/6) - Motive attribution (Chinese) > Chinese consumers are more result-oriented in CSR issues; their most concern is not firm s real motivation to engage in CSR, but the consequences and sustainability of CSR (Tian et al., 2011). > Chinese consumers are more likely to assign other-centered motives to CrM campaigns as they generally consider companies as trustworthy and caring (Ramasamy & Yeung, 2009). They therefore are more inclined to believe that the reasons for companies to conduct CrM campaigns stem from an intrinsic motivation to do good
3) Hypotheses >H1: The Chinese assign a higher degree of credibility to a CrM campaign than the Germans. >H2: The relationship between Nationality and Campaign Credibility can be explained by the motives attributed to the company s social engagement.
Content 1. Introduction & Purpose 2. Literature review & hypotheses 3. Methodologies & Hypotheses Testing 4. Results 5. Discussion 6. Q & A
3) Methodologies >An empirical online survey was conducted with 98 Germans and 91 Han-Chinese students aged between 18-24 in their native languages during June and July 2016. (Total number of survey filled out was 413 before screening). >They were asked to evaluate the CrM campaign All for Children by fashion retailer H&M with regards to its campaign credibility and corporate motives. >H&M is chosen for the study due to the familiarity among these two groups of participants, while the campaign theme also has universal value.
3) Sample: Demographic Data Table 1: Demographic Data of the German and Han-Chinese Samples N Age Gender Germans 98 18-24 (61%) Han- Chinese 91 18-24 (97%) Femal e 82 (84%) 49 (54%) Male 15 (15% ) 40 (44% ) Place of Residenc e Germany (99%) Mainland China (54%) University Leuphana Universität Lüneburg (77%) The Hong Kong Polytechnic University (100%) Field of Study Economics/Busine ss Administration/ Management (42%) Economics/Busine ss Administration/ Management (46%)
3) Hypotheses Testing - Multiple regression analyses > The hypotheses of the examination model are tested by means of multiple regression analyses. It hereby needs to be mentioned that only those respondents who indicate a high familiarity with H&M are included in the analyses. > Apart from the results for H&M s corporate ability, the company s credibility as well as the nationalities individualism-collectivism index and their humane orientation, all of the above-shown variables are non-normally distributed. This means that the assumption of normality is not fulfilled by the majority of the variables. In this case, researchers are advised to apply bootstrapping, a test that is robust to violations in the assumption of normally-distributed data (Efron and Tibshirani, 1993, p. 175) > High familiarity with H&M is herein understood as a familiarity value of four or higher. This reduces the sample to N = 179 with 93 Germans and 86 Han-Chinese.
Content 1. Introduction & Purpose 2. Literature review & hypotheses 3. Methodologies & Hypotheses Testing 4. Results 5. Discussion 6. Q & A
4) Results: Summary Overview >The study reveals that Chinese assign a higher credibility to CrM campaign than Germans. Hereby, the motives attributed to a CrM initiative are found to have a mediating effect: Germans assign more selfcentered motives while Chinese participants attribute other-centered motives to the H&M s CrM initiative. >The results emphasize that consumers motive attribution is a suitable variable to explain the influence of people s cultural background on the perceived campaign credibility.
4) Hypotheses testing: Hierarchical regression analysis > The hierarchical regression analysis, where the main predictors are successively added, is composed of 4 models as presented in table 2. The 4 predicators are: Nationality, Motive Attribution, Reputation and Importance of Corporate Motives > The first model refers to the relationship between the respondents nationality and their assigned credibility to the H&M s CrM campaign. > The results signalize that the predictor Nationality explains a significant proportion of variance in credibility scores, R2 =.377, F(1, 153) = 92.518, p <.001.
4) Hypotheses testing: Hierarchical regression analysis > Also the following models, where the predictors Motive Attribution, Reputation and Importance of Corporate Motives are successively added explain a significant and increasing proportion of variability in the outcome variable (see Table 2). > The regression models are therefore successful in predicting the credibility of the CrM campaign by H&M. > When comparing R2 and adjusted R2, only minor differences can be detected signalizing a high cross-validity and generalizability to the overall population. > This means that the models would account for a similar variance in the outcome variable if the model was derived from the population rather than a sample.
4) Table 2: Model Summary Hierarchical Regression Analysis Modell R R 2 Adjusted R 2 Changes in R 2 Changes in F df1 df2 Sig. changes in F 1.614 a 2.811 b.377.373.377 92.518 1 153.000.658.653.281 124.596 1 152.000 3.816 c.667.660.009 4.116 1 151.044 4.822 d.676.668.010 4.438 1 150.037 Table 2: Model Summary Hierarchical Regression Analysis a. Predictor variables: (Constant), Nationality b. Predictor variables: (Constant), Nationality, Motive Attribution c. Predictor variables: (Constant), Nationality, Motive Attribution, Reputation d. Predictor variables: (Constant), Nationality, Motive Attribution, Reputation, Importance of Corporate Motives
4) Results: H1: Han-Chinese assign a higher degree of credibility to a CrM campaign than Germans. > The descriptive analysis has already indicated a significant mean difference between Germans and Han-Chinese regarding the credibility of the CrM campaign All for Children by H&M. > Moreover, a significant, positive correlation can be determined between Nationality and Credibility of the CrM Campaign (r =.614, p <.001), which is further investigated by means of a multiple regression analysis as shown in the following equation:
4) Results: H1: Han-Chinese assign a higher degree of credibility to a CrM campaign than Germans. > Credibility CrM Campaign = 3.165 + (1.214 x Nationality) Germans: > Credibility CrM Campaign = 3.165 + (1.214 x 0) = 3.165 Han-Chinese: > Credibility CrM Campaign = 3.165 + (1.214 x 1) = 4.379 > Based on these results, it can be assumed that, on average, Han-Chinese assign a higher level of credibility to the investigated CrM campaign than Germans with Nationality functioning as a significant predictor of the outcome variable, β Nat = 1.214, p =.001. As a consequence, hypothesis 1 is supported.
4) Results: H2: The relationship between Nationality and Campaign Credibility can be explained by the motives attributed to the company s social engagement. > In order to verify if the relationship between Nationality and the Credibility of the CrM Campaign is influenced by the type of motives assigned to the responsible company, it needs to be checked whether Han-Chinese constantly assign a higher credibility no matter the attributed type of motives. > For this hypothesis to be approved, four conditions need to be validated, according to Baron and Kenny (1986):
4) Results: H2: The relationship between Nationality and Campaign Credibility can be explained by the motives attributed to the company s social engagement. >(1) The predictor variable (X) must significantly predict the outcome variable (Y) as well as >(2) the mediator variable (M), >(3) the mediator variable (M), in turn, needs to significantly predict the outcome variable (Y) and >(4) the relationship between the predictor (X) and the outcome variable (Y) must be smaller when the mediator (M) is included in the regression in comparison to when it is not.
4) Results: H2: The relationship between Nationality and Campaign Credibility can be explained by the motives attributed to the company s social engagement. > To test these four conditions of mediation, a series of regression analyses needs to be conducted, according to Baron and Kenny (1986), which are visualized in figure 2. > The first regression predicts the outcome, here the Credibility of the CrM Campaign, from the predictor Nationality (c). > In the second regression, the mediator Motive Attribution is predicted by Nationality (a). > The third regression predicts the outcome Credibility of the CrM campaign from both the predictor Nationality (c ) and the mediator Motive Attribution (b). > Mediation is then said to be prevalent if the strength of the relationship between predictor and outcome is reduced by including the mediator (Field, 2013, p. 408), meaning that the indirect effect (c ) needs to be smaller than the direct effect (c).
4) Results: H2: The relationship between Nationality and Campaign Credibility can be explained by the motives attributed to the company s social engagement. > The results of these three regression analyses are listed here below: > Nationality significantly predicts the CrM campaign s credibility, c = 1.214, p =.001, meaning that the first condition is met. > Nationality significantly predicts the mediator Motive Attribution, a = 1.558, p =.001, stating that the second condition is satisfied. > Motive Attribution significantly predicts the CrM campaign s credibility, b =0.663, p =.001, which means that the third condition is fulfilled. > The relationship between Nationality and Credibility of CrM Campaign is significantly smaller when Motive Attribution is included in the regression, c = 0.303, p =.016 in comparison to when it is not, c = 1.214, p =.001. The fourth condition is thus met as well. It can be concluded that Motive Attribution significantly mediates the relationship between Nationality and Credibility of the CrM Campaign. > Consequently, H2 is supported.
4) Figure 2. Mediation Model
Content 1. Introduction & Purpose 2. Literature review & hypotheses 3. Methodologies & Hypotheses Testing 4. Results 5. Discussion 6. Q & A
5) Discussion Video Interviews
5) Discussion - Practical and social implications > The findings show that the credibility of the CrM campaign differs across cultures, which organizations should factored in when designing CrM campaigns. > Among the Germans, the attribution of other-centered motives must be encouraged to increase their low level of campaign credibility. A shift in motives can be achieved when outsiders speak for the social engagement on the companies behalf. > For both nationalities, transparency and reporting are the most important factors to establish an authentic and credible CrM campaign.
Limitation and Suggestion > Results from this study are limited to young Germans and Chinese university students with constrained sample size, one should not make generalization of the nations population merely based one single study. > The Chinese students sample are collected from the Hong Kong Polytechnic University database, those students are on exchange programmes from 3 months to 4 years. Their view could be different to those students who have never left the country. > To further enrich the knowledge of culture-specific CSR communication, it would be interesting to investigate how the credibility of CrM campaigns is evaluated by more different nationalities; and other cultural dimensions apart from nationalities.
Other Limitations & Caveats > As over 40% of the sample are students studying business and administration, they may be more knowledgeable about CSR / CrM than their non-business major peers. > Non-probability sampling. > Video feedback are using convenient sampling. > This study is of the exploratory nature, more data in a more control environment should be included for future analysis.
Major Reference > Cotton-Chan, Valentina Y. K. (2015), The High-Hanging Fruit: CSR in the Context of the Chinese Food and Beverage Industry, in: Ng, P. P./Ngai, C. S. (eds.), Role of Language and Corporate Communication in Greater China, Springer Berlin Heidelberg, Berlin, pp. 149-173. > Fifka, M. S. (2013): Corporate citizenship in Germany and the United States Differing perceptions and practices in transatlantic comparison. Business Ethics, 22 (4), 341-356.
Q & A
Appendix Table 3: Regression Results Confounder Analysis Table 4: Initial Regression Results Student Video Interviews
4) Table 3: Regression Results Confounder Analysis Model 1 2 3 4 5 54.1% R 2 p <.001 a 64.3% p <.001 b 65.4% p <.001 c 66.8% p <.001 d 5.4% p =.011 e Regression Coefficient Significance (2-tailed) a. Predictor variables: (Constant), Nationality; Outcome variable: Credibility of CrM Campaign b. Predictor variables: (Constant), Nationality; Outcome variable: Motive Attribution c. Predictor variables: (Constant), Motive Attribution; Outcome variable: Credibility of CrM Campaign d. Predictor variables: (Constant), Nationality, Motive Attribution; Outcome variable: Credibility of CrM Campaign e. Predictor variables: (Constant), Nationality; Outcome variable: Importance of Corporate Motives 95% Confidence Interval Lowest value Highest value Constant 3.337.001 3.182 3.492 Nationality.782.001.542 1.030 Reputation.403.001.297.502 Constant 3.344.001 3.165 3.495 Nationality 1.005.001.747 1.282 Reputation.569.001.443.675 Constant 3.698.001 3.605 3.791 Motive Attribution.579.001.452.690 Reputation.117.044.007.235 Constant 3.558.001 3.406 3.715 Nationality.321.011.093.577 Motive Attribution.493.001.342.623 Reputation.118.056.009.257 Constant 5.271.001 4.997 5.580 Nationality -.689.004-1.203 -.210 Reputation.017.881 -.187.247
4) Table 4: Initial Regression Results Model 1 2 3 R 2 Regression Coefficient Significance (2-tailed) 95% Confidence Interval Lowest value Highest value 36.6% Constant 3.165.001 2.994 3.282 p <.001 a Nationality 1.214.001.984 1.858 39.8% Constant 3.083.001 2.874 3.495 p <.001 b Nationality 1.558.001 1.284 1.282 65.0% Constant 3.706.001 3.611 3.802 p <.001 c Motive Attribution.663.001.452.739 4 5 66.3% p <.001 d 5.8% p =.002 e Constant 3.571.001 3.423 3.732 Nationality.303.016.061.547 Motive Attribution.584.001.477.687 Constant 5.264.001 4.994 5.552 Nationality -.706.003-1.134 -.288 a. Predictor variables: (Constant), Nationality; Outcome variable: Credibility of CrM Campaign b. Predictor variables: (Constant), Nationality; Outcome variable: Motive Attribution c. Predictor variables: (Constant), Motive Attribution; Outcome variable: Credibility of CrM Campaign d. Predictor variables: (Constant), Nationality, Motive Attribution; Outcome variable: Credibility of CrM Campaign e. Predictor variables: (Constant), Nationality; Outcome variable: Importance of Corporate Motives
Appendix) Video Interview > Clip 1 > https://youtu.be/qetkqcgmuh0 > Clip 2 > https://youtu.be/ekl3ao7cq5s > Clip 3 > https://youtu.be/igfifwpkbdk > Clip 4 > https://youtu.be/fcyggqvau_a > Clip 5 > https://youtu.be/xlvvhf_lvhw