3.4.1. Factor Analysis
Keywords are a distillation of the core ideas of a text. Keywords that appear more frequently can reflect the hot topics in a field of study [
9]. In this study, we conducted a PCA for dimensionality reduction and clustering of keywords to reveal the research hotspots in the area of green consumption.
First, we used the COOC 1.9 software, which is a bibliometric analysis software from the GitHub (San Francisco, CA, USA), to build the keyword co-occurrence matrix D, which was a 6324 × 6324 matrix, as shown in
Table 4. This represented the 6324 keywords we obtained from 2194 papers, and each matrix indicated the frequency of the keywords corresponding to the ranks and columns appearing together in the same document. Since keywords with low co-occurrence frequencies are not representative, we selected 115 keywords with co-occurrence frequencies of ten or more (as shown in
Table 4) to build the original keyword co-occurrence matrix (see an example (fragment) in
Table 5). Then, the original matrix was transformed to a Pearson correlation coefficient matrix using SPSS. The degree of resemblance between two papers was represented by a correlation: the stronger a positive relationship, the higher the level of perceptual similarity between the papers. [
32]. Since the data may be normalized and the number of zeros minimized, correlation coefficients are better than co-occurrence frequencies for statistical analysis [
33]. The correlation matrix was used as input for the multivariate analysis of the data and to explain the conclusions employed. In this study, we employed three multivariate methodologies to examine the hot regions in green consumption, including PCA and MDS analysis, which are in line with the prior literature [
34].
We began our research by mapping and describing the selected green consumption keywords. To cluster the keywords, we initially used factor analysis. A factor analysis was used to group published papers into related groups or factors, depending on their degree of similarity [
34]. The factor analysis enabled us to uncover some of the new study areas in green consumption research by looking at how keywords fit together.
The number of extracted factors was determined using Kaiser criteria and scree tests, using PCA as the extraction method and varimax rotation of the extracted factors as the interpretation method. Factor loadings show the relationship between a paper and a factor, as well as how much of the paper belongs to the set [
34]. The analysis resulted in three factors which explained 79.7% of the variance (as shown in
Table 6).
To explain the three factors, we examined each set of keywords, looking for common themes. The final interpretation was summarized by the authors, and the three final research hotspots identified included: research on consumer green behavior (Factor 1), research on corporate green production (Factor 2), and research on green marketing in social media (Factor 3).
Factor 1 contained the most keywords among the three factors, and it also explained the majority of the variance (51.5%). Regarding Factor 1, at first glance, it focused on examining consumer behavior, and more specifically, considered the representativeness of each keyword in the factor. The closer a positive value of the keyword loadings is to one, the more representative the keyword is. The most representative keywords in Factor 1 are “consumer behavior”, “trust”, “happiness”, “culture”, “values”, “pro-environmental behavior”, and “well-being”. By combining the papers in which the keywords were found, we found that the most popular research on green consumption focused on factors influencing consumers’ green consumption behaviors. The keywords “trust” and “value” represent consumers’ perceptions of green products. Whether a green product is trustworthy and the level of trust consumers have in the product are very important factors influencing consumers’ green consumption behaviors [
35], and trust also performs a key role in consumers’ opinions toward the value of a product. [
36]. “Happiness” and “culture” are based on the study of consumers’ own attributes. Consumers’ own core values, happiness, and cultural influences also play important roles in green consumer behavior, and are an important area for research [
37]. The next most popular factors are “theory of planned behavior”, “attitude”, “willingness to pay”, and “green consumption behavior”. The loadings of the keywords were also greater than 0.7, indicating that research on consumers’ attitudes, intentions, and behaviors was also a hot topic. Consumers’ intentions are not equivalent to consumers’ behaviors, and it is very important that consumers’ intentions become behaviors. Research in this direction is also essential.
With regards to Factor 2, the most important keywords are “supply chain management”, “green procurement”, “sustainable consumption and production”, “corporate social responsibility”, and “sustainable production”. The fact that these keywords stood out shows that the scholars mainly focused on the green production of corporations and the social responsibility of corporations in their green production. However, less research has been done on after-sale services and PR for products. For green products, after-sale services and PR are very important aspects, affecting consumers’ sales experiences and their evaluation of the corporations [
38]. Therefore, scholars should devote more effort to research on after-sale services and public relations of corporations.
Finally, Factor 3 focuses on green marketing in social media. The most important keywords associated with Factor 3 are “green marketing”, “social media”, “sustainable marketing”, and “marketing”. The loadings above 0.7 showed that these keywords are important. Social media has a huge impact on both consumers and corporations [
2]. Corporations can use social media to gain information about potential consumers and directly recommend green products [
39]. It is also mainly through social media that consumers obtain information about products, making decisions based on that information [
40]. In the traditional consumer sector, research on social media is well established. In the area of green consumption, green marketing has consistently demonstrated positive customer response, but there are still many areas for further research [
41]. Especially considering the emergence of new concepts such as metaverse technology, social media marketing is set to change even more profoundly and generate more research opportunities [
42].
Overall, the above three factors identified three current research hotspots. Factor 1 focused on consumers’ green behaviors and factors that transform consumers’ attitudes, intentions, and behaviors; Factor 2 focused on the green production of corporations, while Factor 3 focused on green marketing in social media (as shown in
Table 7).
3.4.2. Multidimensional Scaling
For the purposes of this subsection, MDS is used to test the soundness and robustness of the performed PCA [
43]. Using a Pearson correlation coefficient matrix, the MDS analysis generates a two-dimensional graph in which the position of each keyword depends on the distance between keywords; the closer the keywords are relative to each other, the more similar the concepts between them, and the more internal consistency there is. We usually used RSQ to test whether the result was accepted or not. RSQ represents the fraction of total variance that can be interpreted by distance relative to space [
22]. The MDS results show that RSQ equals 0.97, which is very close to 1. Therefore, the multidimensional scale fitting of the distances between keywords is quite good and the data are acceptable.
The MDS map is shown in
Figure 4. It is evident that it is compatible with the factor analysis results. In fact, the examined keywords tended to cluster visually in three main sets, similar to the three factors, and occupied specific places; we accentuated these factors to enable scholars to make comparisons between MDS and factor analyses. Factor 1 (consumer green behavior) is concentrated on the map on the left. Factor 2 (corporate green production) is concentrated on the map on the right, while Factor 3 (green marketing in social media) is mainly distributed in the middle of Factors 1 and 2.
Additionally, as illustrated in
Figure 4, the majority of keywords are spread across the right-hand side of the chart, indicating that the overwhelming bulk of research has been focused on consumers. This is not difficult to understand, as the consumer is the most important subject in green consumption.