BÁO CÁO TÔNG KẾTĐÈ TÀI NGHIÊN cứu KHOA HỌC THAM GIA XÉT GIẢI THƯỞNG “NHÀ NGHIÊN CỨU TRẺ UEH” NĂM 2024 SCRUTINIZING HOW PRODUCT TRANSFORMATION SALIENCE INFLUENCES PERCEIVED GREEN BRAND C
Extraordinary
Warren et al (2019) highlight that many respondents view cool brands as extraordinary rather than just useful, with Apple being a prime example due to its innovative capabilities and industry leadership This perception of brand coolness aligns with previous research emphasizing the positive aspects of coolness and dictionary definitions of the term Furthermore, it is reasonable to consider cool green brands as exceptional, as they aim to provide high-quality products and services while actively working to reduce their environmental impact and promote positive change.
This assertion does not aim to undermine the significance of the useful variable as a lower-order construct contributing to the higher-order concept of brand coolness Additionally, this idea aligns with existing literature on green brand coolness, particularly its subdimension of extraordinary attributes (e.g., Lin et al., 2023).
Original
Research highlights a strong link between coolness and originality, as noted by several studies (Bruun et al., 2016; Rahman, 2013; Sundar et al., 2014; Warren et al., 2019; WaiTen & Campbell, 2014; Warren & Reimann, 2019) Rahman (2013) identifies "unique" as the third most significant theme in a hierarchical model of coolness, ranking alongside other attributes such as interesting, different, and innovative Warren et al (2019) further emphasize that brand coolness is closely tied to originality, asserting that cool brands often emerge within subcultures through their distinctiveness One respondent poignantly noted that “the uncool will be doing tomorrow what the cool have done before,” reflecting the perception of cool brands as trendsetters.
“original, creative, 'one step ahead,’ and as consistently reinventing themselves” (Warren et al., 2019, p 39).
The theme of originality significantly influences positive autonomy, which in turn affects brand coolness (Warren et al 2019) Consumers often prefer cool brands to express their autonomous identity, particularly in counter-cultural contexts (Warren & Campbell, 2014) Individuals value authenticity, seeking brands that remain true to themselves and resist conformity to societal norms This authenticity is vital for green brands, as a lack of originality may lead consumers to perceive them as insincere or merely profit-driven Therefore, it is essential for green brands to embody originality to maintain credibility and genuine commitment to sustainability, a viewpoint supported by Lin, Huang, and Li (2023).
Subcultural
Consumers often view certain brands as "cool" when they diverge from mainstream norms and resonate with specific subcultures, offering unique benefits to niche groups (Sundar et al., 2014; Warren et al., 2019) Previous studies indicate that cool brands connect with various subcultures, including alternative rock, extreme sports, and eco-conscious communities (Danesi, 1994; Lin et al., 2023) We propose that pro-green individuals initially embrace green brands they perceive as cool, which may eventually attract more conventional consumers, highlighting the role of subculture in shaping perceptions of green brand coolness (Lin et al., 2023).
Consumer traceability knowledge 14 2.5 Research model 16 3 Methodology 17 3.1 Scope and delimitation 17 3.2 Research method 18 3.3 Measures 19 3.4 Stimuli design 21 3.5 Sample and data collection 21 3.6 Model assessment 23 4 Results and discussion 24 4.1 Assessment of measurement model 24 4.1.1 The first stage
The second stage
In the second stage of our analysis, we evaluated the measurement model of the higher-order PGBC, along with PTS, GPI, and CTK Most items and lower-order dimensions demonstrated strong loadings onto their respective parent constructs; however, the first-order subcultural dimension showed an outer loading of 0.685 onto the higher-order PGBC, which is below the recommended threshold of 0.708 We will continue to assess additional criteria before deciding whether to remove this lower-order latent variable.
Outer loadings in the second stage.
Notes CTK: consumer traceability knowledge; GPI: green purchase intention; PGBC: perceived green brand coolness; PTS: product transformation salience.
Table 9 exerts that PGBC achieved internal consistency reliability (composite reliability higher than 0.70) and convergent validity (AVE greater than 0.50).
Internal consistency reliability and convergent validity of the higher-order construct.
Cronbach's alpha Composite reliability Average variance extracted
Notes PGBC: perceived green brand coolness.
In line with the findings of Sarstedt and Cheah (2019), we evaluated the discriminant validity of the second-order PGBC against the first-order latent variables of PTS, GPI, and CTK The analysis revealed that the square roots of the AVE for all latent variables exceeded their correlations with other constructs, as shown in Table 10 Additionally, all items and first-order latent variables exhibited stronger loadings on their respective parent constructs than on alternative ones (refer to Table 11) The HTMT values between pairs of latent variables remained below 0.85, and none reached 1 within the 95% confidence intervals (see Table 12) Consequently, this confirms the establishment of discriminant validity in the second stage.
Discriminant validity—Fornell-Larcker criterion—in the second stage.
Notes CTK: consumer traceability knowledge; GPI: green purchase intention; PGBC: perceived green brand coolness; PTS: product transformation salience.
Discriminant validity—cross loadings—in the second stage.
Notes CTK: consumer traceability knowledge; GP1: green purchase intention; PGBC: perceived green brand coolness; PTS: product transformation salience.
Discrim in an t validity HTMT in the second stage.
Notes CTK: consumer traceability knowledge; GPI: green purchase intention; PGBC: perceived green brand coolness; PTS: product transformation salience; 95% confidence intervals.
We have chosen to retain the subcultural aspect in our model, as it meets all other criteria Additionally, we assert that subcultural appeal plays a significant role in conveying the perceived coolness of a green brand, highlighting its contextual relevance in understanding PGBC and underscoring its conceptual importance.
To evaluate the structural model and test the proposed hypotheses, we utilized the bootstrapping procedure in SmartPLS 4.0.9.8, configuring it with 10,000 subsamples, parallel processing, and a bias-corrected and accelerated (BCa) bootstrap confidence interval method We employed a one-tailed test with a significance level of 0.05 and a fixed seed generator Additionally, we performed PLSpredict/CVPAT to derive the effect size (Ọ2) as outlined in the works of Hair et al (2011), Hair, Hult, Ringle, & Sarstedt (2021), and Sarstedt et al (2017).
We assessed the risk of multicollinearity in our proposed model by analyzing the variance inflation factor (VIF) for the inner model The VIF values were 1.288 for PTS and GPI, 1.079 for PTS and PGBC, 1.567 for PGBC and GPI, 1.317 for CTK and GPI, and 1.079 for CTK and PGBC These results indicate that there is no multicollinearity risk in the proposed path model (Hair, Hult, Ringle, & Sarstedt, 2021).
In our hypothesis testing, we analyzed the direct effects indicated by the path coefficients The findings in Table 13 reveal that PTS significantly and positively influences GP1 (A = 0.327, 95% BCa CT [0.230; 0.413], t = 5.902, p < 0.001) and PGBC (A = 0.365, 95% BCa CI [0.266; 0.464], t = 6.065, p < 0.001), thereby confirming hypotheses H1 and H2 Additionally, PGBC demonstrates a significant positive direct effect on GPI.
- 0.339, 95% BCa CI [0.261; 0.418], t = 7.137,/? < 0.001), which supports H3 Based on these path coefficients, it seems that PGBC directly influences GPI a little more strongly than PTS does.
Afterward, the authors inspect results derived from the mediation analysis, presented in Table 14 They show' that PGBC has a significant positive mediating effect on how PTS influences GPI (b = 0.124, 95% BCa CI [0.083; 0.171], t = 4.603,/2
The findings indicate that while PTS has a significant direct effect on GPI, PGBC serves as a partial mediator that enhances this positive relationship The total effect of PTS on GPI is notably significant, with a coefficient of 0.450 and a confidence interval of [0.362; 0.531], confirming the support for hypothesis H4.
Moderating and moderated mediating effects were assessed lastly The results in Table 15 signify that CTK indeed moderates how PTS influences GPL yet surprisingly in a negative manner (/) = - 0.109, 95% BCa CI [- 0.175; - 0.029], t = 2.447, p = 0.007
The analysis revealed a significant moderating effect, yet it contradicts the initial hypothesis H5, which suggested that CTK positively moderates the impact of PTS messaging on GPI, leading to the rejection of H5 Additionally, the moderated mediating effect was found to be slightly positive but nonsignificant (b = 0.004, 95% BCa CI [0.027; 0.039], t = 0.216, p = 0.415 > 0.05), resulting in the rejection of H6 as well.
We evaluated the quality of our research model using the coefficient of determination (R²), which measures the extent to which the variance in the outcome construct is explained by the predictor latent variables In the context of our study on green and sustainable marketing, R² values of 0.75, 0.50, and 0.25 are classified as having substantial, moderate, and weak explanatory power, respectively, according to established research (Chin, 1998; Hair et al., 2011; Hair, Hult, Ringle, & Sarstedt, 2021; Henseler et al., 2015; Sarstedt et al.).
The R2 values for PGBC and GPI were found to be 0.362 and 0.587, respectively, indicating that PTS and CTK account for approximately 36.20% of the variance in PGBC, reflecting a lower-moderate explanatory power In contrast, PTS, PGBC, and CTK together explain around 58.70% of the variance in GPI, demonstrating a moderate explanatory power of these predictor variables.
The adjusted R² provides a more accurate representation of the variance explained in outcome latent variables compared to the standard R² In this study, the adjusted R² values were found to be 0.354 for PGBC and 0.580 for GPI (p < 0.001) This indicates that PTS and CTK account for approximately 35.40% of the variance in PGBC, reflecting a lower-medium level of explanatory power Conversely, PTS, PGBC, and CTK collectively explain around 58% of the variance in GPI, demonstrating a moderate level of explanatory strength.
We conducted an analysis of the effect size of each influence within the inner model using Cohen's f², which reflects the change in R² when an exogenous construct is removed The f² value observed between PTS and PGBC was 0.193, with a significance level of p = 0.004.
< 0.01), 0.201 between PTS and GPI (p = 0.009 < 0.01), and 0.177 between PGBC and GPI (p = 0.001 < 0.01); each of them denotes a medium effect size (Cohen, 1988; Hair,
The study by Hult, Ringle, and Sarstedt (2021) reveals that the influence of Psychological Trauma Symptoms (PTS) on General Psychological Impact (GPI) is substantial but not statistically significant, with an effect size of 0.033 (p = 0.135) In contrast, the effect of PTS on Post-Traumatic Growth Behavior Change (PGBC) is extremely weak and also nonsignificant, showing an effect size of approximately 0.000 (p = 0.487) These findings align with previous research by Aguinis et al (2005), Hair et al (2021), and Kenny (2018).
The authors evaluated the predictive relevance of the structural model using the Q2 criterion, originally developed by Slone and Gcisscr According to Hair et al (2021) and Henseler et al (2009), a Q2 value above zero indicates that the path model has predictive relevance The Q2 values for PGBC and GP1 were found to be 0.334 and 0.494, respectively, demonstrating that the path models possess upper-moderate predictive power and confirming the predictive relevance of the structural model.
Figure 2 summarizes the primary results for the assessment of structural model.
Notes CTK: consumer traceability knowledge; GP1: green purchase intention; PGBC: perceived green brand coolness; PTS: product transformation salience; **** p < 0.001;
Notes GP1: green purchase intention; PGBC: perceived green brand coolness; PTS: product transformation salience; **** p< 0.001.
Total effect Direct effect Indirect effect
Results of moderated mediation analysis.
Notes CTK: consumer traceability knowledge; GPI: green purchase intention; PGBC: perceived green brand coolness; PTS: product transformation salience; ^ p > 0.05 (nonsignificant).
Figure 2 Final structural model and summarized results.
Notes, adj: adjusted; GP1: green purchase intention; PGBC: perceived green brand coolness; ****/?< 0.001; ***/;< 0.01; *^>0.05 (nonsignificant).
Our study replicates the research framework by Lin et al (2023), incorporating higher-order PGBC with lower-order dimensions of extraordinary, original, and subcultural traits, which we believe signify the perceived coolness of a green brand This perspective aligns with the brand coolness literature by Warren et al (2019) Interestingly, the subcultural dimension shows weaker representation of perceived coolness compared to the other constructs, likely because green brands aim to engage a broader audience to raise environmental awareness and promote sustainable values While focusing on niche markets can be challenging for achieving green goals, offering unique value to specific consumer groups can still support overall sustainability objectives Thus, this lower-order attribute is more relevant for brands targeting higher customer segments or specific markets.