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Article

Exploring the Impact of Integrated Marketing Communication Tools on Green Product Purchase Intentions among Diverse Green Consumer Segments

by
Chun-Shuo Chen
1,
Chih-Ching Yu
2,* and
Kuan-Yu Tu
2
1
Chinese International College, Dhurakij Pundit University, Bangkok 10210, Thailand
2
Department of Business Administration, National Taipei University, New Taipei City 237, Taiwan
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(24), 16841; https://doi.org/10.3390/su152416841
Submission received: 7 October 2023 / Revised: 2 December 2023 / Accepted: 6 December 2023 / Published: 14 December 2023
(This article belongs to the Special Issue Sustainability Marketing and Consumer Behavior)
Review Reports Versions Notes

Abstract

:
In response to escalating environmental pressures and the growing global consensus on comprehensive green initiatives, marketers encounter the challenge of effectively communicating with diverse green consumer segments. The purpose of this study is to explore the preferences of different IMC tools among different types of green consumers and then attempt to propose effective communication tools for different types of green consumers to boost sustainable consumption. This study examined 13 widely used integrated marketing communication (IMC) tools and delved into their impact on the purchase intentions of different consumer segments toward green products. Meanwhile, departing from conventional approaches, we replaced consumer awareness with actual consumer behavior to more accurately segment green consumers. This distinction allowed us to categorize green consumers into three segments: light green (including colorless), medium green, and dark green consumers. By analyzing these IMC tools based on the dimensions of media richness theory—feedback, multiple cues, language variety, and personal focus—we found that (1) only three communication tools can effectively provide green consumers with different levels of green behavior with the green product information they need to enhance their green products purchase intention; (2) dark green consumers demonstrate a markedly stronger preference for these three types of IMC tools than the others; (3) there are significant differences in only two constructs, namely “feedback” and “language variety” among these three types of green consumers; and (4) both dark green and medium green consumers are more concerned about the level of personalization in messages than light green (including colorless) consumers. Ultimately, practical insights are provided to empower businesses and marketers in boosting consumer preference for green products.

1. Introduction

As comprehensive green initiatives have gradually gained global societal consensus in response to escalating environmental pressures, consumers have also started to alter their initial consumption habits, with green products becoming increasingly ubiquitous in their daily lives “Spielmann, 2021 [1]”. Simultaneously, marketers and advertisers have seized this market opportunity to produce more sustainable products, intensify their green marketing efforts, and cultivate a greener brand image “Ham et al., 2022 [2]”. Moreover, firms have increasingly prioritized corporate social responsibility and environmental enhancements in alignment with current environmental trends “Chen, 2022 [3]; Fang et al., 2017 [4]; Chen and Chang, 2013 [5]”. They are actively promoting green products and the concept of environmental protection, thus reshaping and enhancing their sustainable brand value. On the other hand, “Shrum et al., 1995 [6]” pointed out that green consumers are careful shoppers who are often skeptical of advertisements when seeking product information. Therefore, marketers face a dual theoretical and practical challenge in delivering communication messages that effectively cater to diverse green consumer needs.
Despite a growing body of emerging literature discussing the relationship between the heterogeneity of green consumer and sustainable (green) marketing in recent years (e.g., “Zhao et al., 2023 [7]; Zhang and Zheng, 2022 [8]; Ma et al., 2022 [9]; Yang et al., 2019 [10]”, studies on how to develop effective communication strategies for different types of green consumers have been few and far between. “Banarjee and McKeage 1994 [11]”identified a correlation between consumers’ personality traits and sustainable consumption behavior, where consumers’ personality traits can be used to predict their sustainable consumption behavior and used as a variable for market segmentation. Although we know that green consumers are perceived as caring for the environment, pursuing health, and improving living standards based on their adoption of universal values, there is often a green intention–behavior gap in their awareness and behavior “Tawde et al., 2023 [12]; Chatterjee et al., 2022 [13]; Davari and Strutton, 2014 [14]; Gleim and Lawson, 2014 [15]”. Therefore, effectively segmenting the target market by accurately distinguishing different types of green consumers to develop communication strategies that can influence their purchase decisions is crucial for promoting sustainable consumption behavior and assisting in the sustainable development of firms. Moreover, it serves as a critical mission for green marketers on the subject of sustainability issues.
Empirically, socio-demographic variables are usually not effective enough in explaining sustainable (green) consumption behavior. As regards the classification of green consumers, these variables, in general, can only describe consumers’ environmental knowledge or personal norms and values without a clear definition of consumer segmentation (e.g., “Dangelico et al., 2021 [16]; Nimri et al., 2020 [17]; Jansson et al., 2010 [18]; Diamantopoulos et al., 2003 [19]; Ottman, 1998 [20]; Roberts, 1996 [21]”. Hence, the first objective of this study is to effectively distinguish different types of green consumers according to their green preferences.
Based on the above information, we believe that different contents of product information provided by different communication tools will influence consumers’ purchase decisions for consumers with diverse green preferences when choosing green products. If uncertainty and ambiguity in product information among consumers can be reduced by increasing media richness, consumers will be better able to make purchase decisions based on adequate product information, which can increase their purchase intention. Therefore, this study attempts to develop an effective scale to measure media richness and carry out in-depth investigations into how the four constructs above (i.e., multiple cues, language variety, feedback, and personal focus) influence the intention of green consumers with diverse green preferences to purchase green products to therefore propose recommendations with regards to effective IMC tools.
Again, although previous scholars have paid much attention to exploring integrated marketing communication (IMC), there is seemingly a dearth of research on the relationships between IMC strategies and green consumers with diverse green preferences. Hence, this study endeavors to fill this gap by exploring the preferences of different IMC tools among different types of green consumers and then attempting to propose effective communication tools for different types of green consumers to boost sustainable consumption in both practical and academic fields, and practical insights are provided to empower businesses and marketers in boosting consumer preference for green products.

2. Literature Review

2.1. Green Products and Green Consumers

The increasing customer awareness of environmental sustainability during the last decade has had an influence on many manufacturers to produce green products “Ghazali et al., 2021 [22]”. “Sahni and Osahan, 2019 [23]” defined green products as recyclable and biodegradable products that consume less energy and do not pollute the environment. They also regarded green products as a generic term for environmentally friendly and sustainable products. We regard green food as the green product in this study which includes fair trade, environmentally friendly, organic, non-toxic, and sustainable products with eco or green labels, such as traceable food products. In contrast, the definition of green consumers remains unclear, even though previous studies have mostly discussed the characteristics of green consumers “González et al., 2015 [24]”.
“White et al., 2019 [25]” pointed out that green consumers are those who engage in behaviors that improve social and environmental outcomes while boosting consumer wellbeing. Consumers usually choose to purchase green products due to their ethical ideologies or the belief that the production of green products is friendly to the environment (e.g., “Chatterjee et al., 2022 [13]; Yan et al., 2021 [26]; Halder et al., 2020 [27]; Zanoli, 2002 [28]”. “Ottman, 1998 [20]”revealed that it is difficult to segment green consumers demographically and establish clear groups of target customers. Nevertheless, all the arguments above only center upon consumers’ environmental knowledge or personal norms but lack a clear definition of green consumer segmentation. Viewed through the lens of green marketing, the absence of effective market segmentation poses a significant challenge for green products. Developing successful marketing strategies and conveying the value of their products becomes arduous, and the goal of increasing green product sales becomes even more elusive.
Previous research on classifying green consumers has predominantly centered on gauging their awareness or attitudes, often neglecting their actual behaviors (e.g., “Dawes and Messick, 2000 [29]; Panda et al., 2020 [30]; Chitra, 2007 [31]; Ottman, 1998 [20]; Wulandari et al., 2012 [32]; González et al., 2015 [24]; Magnusson et al., 2003 [33]”. Yet, we contend that a more insightful understanding of consumer traits emerges from studying their behaviors rather than their awareness. Hence, instead of employing awareness-based classification, this study categorizes consumers into three clusters based on their green behaviors: “light green (including colorless) consumers”, “medium green consumers”, and “dark green consumers”. Subsequently, we examine how different IMC tools influence green food purchase intention among these varied green consumer segments.

2.2. Integrated Marketing Communication (IMC)

IMC is the process of assessing the value of various communication tools in marketing campaigns and planning how to develop effective communication strategies to deliver consistent product and brand messages to target consumers to provide maximum communication influence with greater clarity and consistency “Moriarty et al., 2019 [34]”. That is to say, IMC involves the coordination of marketing activities through multiple channels to maximize exposure effects and brand influence on targeted populations “Jackson et al., 2014 [35]”. “Duralia, 2018 [36]” suggested that firms should first identify and establish channels to communicate with consumers when engaging in IMC, so that their products and brands can reach consumers more efficiently, and then form a bridge of communication to build a positive influence over the long run (for firms that intend to actively promote green products). “Carlson et al., 1996 [37]”debated that firms should convey a green image using more than one method, and IMC strategies should be the most effective way to build environmental awareness. Also, IMC plays an important role in educating and changing consumer attitudes and behavior with respect to health-related products and services “Parameswaran, 2023 [38]”.

2.3. Media Richness Theory

The media richness theory proposed by “Daft et al., 1987 [39]” explores the value of different types of media based on the characteristics of media from an information processing perspective to explain how to meet an organization’s requirements for adequate information and reduce message ambiguity. However, many studies often measured media richness using a single construct (e.g., “D’Ambra et al., 1998 [40]; Lim and Benbasat, 2000 [41]; Trevino et al., 1990 [42]”. “Ferry et al., 2001 [43]”pointed out that past studies have not been able to measure the constructs of media richness in depth. If only a single construct is used to measure media richness, we cannot fully understand what causes equivocality and uncertainty in communication. “Maity et al., 2018 [44]”argued that when there is a high level of media richness, consumers can not only acquire more information about their options, but are also better able to make purchase decisions based on specific facts rather than impressions or biases about the product. “Daft et al., 1987 [39]” suggested that researchers can explore media richness using the following four constructs: multiple cues (i.e., sending multiple cues through multiple channels of communication), language variety (i.e., supporting the use of language variety), feedback (i.e., providing immediate feedback), and personal focus (i.e., supporting a high degree of personalization).

3. Methods

3.1. Operational Definition and Measurement of Variables

3.1.1. Types of Green Behavior among Consumers

Consumer behavior serves as the foundation for distinguishing various types of green behavior in this study. To this end, we adopt the Socially Responsible Consumer Behavior (SRCB) scale introduced by “Roberts, 1995 [45]”. It is worth noting that this scale assesses both ecologically and socially conscious consumer behavior. Given the narrower focus of our study, which centers on ecologically conscious consumer behavior, we exclusively employ items related to this aspect from the SRCB scale to gauge consumers’ green behavior. Additionally, to effectively differentiate the “dark green consumers” cluster from the others, we incorporate items related to altruistic behavior. This approach aligns with findings from “Magnusson et al., 2003 [33]”. In total, our questionnaire comprises 18 items, each requiring respondents to select a single option, with ratings denoting “Never”, “Rarely”, “Occasionally”, “Often”, and “Always”, respectively.

3.1.2. Types of IMC Tools

Drawing upon the concept of “mixed media” introduced by “Moriarty et al., 2019 [34]”, this study opts for a comprehensive selection of 13 frequently employed IMC tools. These tools encompass newspapers, magazines, brochures, radio, television, billboards, posters, online advertising, packaging, personal sales and customer service, e-mail, official websites, and social media. Our aim is to assess whether respondents can acquire information about green foods through these communication channels and gauge the extent to which each tool contributes to heightening their purchase intention. The questionnaire items are assessed using a five-point Likert scale.

3.1.3. Characteristics of Communication Tools

In this study, we employ four characteristics derived from the media richness theory, specifically feedback, multiple cues, language variety, and personal focus, as indicators of media richness within communication tools. In addition, we construct 11 questionnaire items following the media richness scale proposed by “Ferry et al., 2001 [43]”, assessing these items on a five-point Likert scale. Respondents are tasked with evaluating to what extent the four communication tool characteristics enhance their intention to purchase green foods. The whole questionnaire is presented in Appendix A.

3.2. Pretest Analysis Results

Before conducting the official questionnaire survey, we administered and collected 70 pretest questionnaires as a foundation for the formal survey. Subsequently, we assessed the reliability and validity of the gathered pretest data. The reliability analysis revealed high Cronbach’s α values of 0.91 for “consumers’ green behavior”, 0.89 for “types of communication tools”, and 0.85 for “characteristics of communication tools” “Wortzel, 1979 [46]”, indicating strong reliability across these dimensions. In the validity analysis, we eliminated inappropriate questionnaire items to ensure that the formal questionnaire remained valid. The results of the analysis showed that the overall scale of the formal questionnaire achieved a Cronbach’s α of 0.92, while “consumers’ green behavior”, “types of communication tools”, and “characteristics of communication tools” attained values of 0.85, 0.91, and 0.931, respectively. These outcomes affirm the reliability of the formal questionnaire.

3.3. Data Collection and Research Sample

To facilitate more effective rating of questionnaire items, this study focuses on green foods, which are among the most widely circulated and consumed green products. Our research involves a sample of Taiwanese consumers who have a history of purchasing green foods. We employed convenience sampling by distributing the questionnaire online via SurveyCake (https://www.surveycake.com/en (accessed on 6 October 2023)), targeting primarily online green food communities and online green food discussion boards in Taiwan. We successfully collected a total of 632 valid questionnaires from our respondents.

4. Analysis and Results

4.1. Types of Green Behavior among Consumers

In this study, consumer classification based on their level of green behavior necessitated an examination of the questionnaire’s factor structure using exploratory factor analysis (EFA). The results of EFA indicated a robust Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy at 0.863, coupled with a significant Bartlett’s test of sphericity (p-value < 0.000), confirming the suitability of EFA for this questionnaire section. Following the removal of inappropriate questions based on pretest outcomes, the formal questionnaire was refined to encompass a total of 12 items. Principal component analysis was employed to extract factors, followed by orthogonal rotation using the Varimax method. The Kaiser method guided factor selection, retaining those with eigenvalues exceeding one, resulting in the extraction of three factors. Factor 1, labeled “Intentional Purchase of Green Products”, characterizes consumers who deliberately buy green products. Factor 2, named “Refusal to Purchase Environmentally Harmful Products”, describes consumers who avoid products detrimental to the environment. Factor 3, termed “Altruism”, encompasses collective behaviors associated with altruistic individuals. All factors exhibit factor loadings exceeding 0.5. The EFA of green behavior among consumer results are presented in Table 1.
The initial cluster analysis in this study delved into Items 16 to 18, which gauged altruism within the “consumers’ green behavior” section of the questionnaire. This analysis resulted in the classification of consumers into two distinct clusters, the “dark green consumers” cluster and the “other consumers” cluster. Utilizing a five-point Likert scale, these three questions collectively contributed a maximum of 15 points. Among the 632 valid samples, 226 were assigned to the “dark green consumers” cluster, while the remaining 406 fell into the “other consumers” cluster. The median scores for these clusters were 11.29 points and 6.92 points, respectively. Subsequently, the second cluster analysis shifted its focus to the remaining items in the “consumers’ green behavior” section, excluding Items 16 to 18. These nine questions, assessed on a scale that allowed a maximum of 45 points, were subjected to cluster analysis within the “other consumers” cluster. Within this analysis, the 406 samples were divided into 160 samples in the “light green (including colorless) consumers” cluster and 246 samples in the “medium green consumers” cluster. The median scores for these clusters were 27.65 points and 35.80 points, respectively. The consumer cluster analysis is presented in Table 2.

4.2. Preference of Communication Tools

We investigate the preference of the aforesaid 13 IMC tools among three types of consumers (i.e., light green (including colorless) consumers, medium green consumers, and dark green consumers) when purchasing green foods. After performing a one-way analysis of variance (ANOVA), only the F-values of newspaper, radio, and e-mail are significant as their p-values are 0.04, 0.04, and 0.00, respectively, all of which are less than the critical value of 0.05. Therefore, the following analysis only presents the test results for these three types of communication tools. In addition, the results of the post hoc comparison of preference for these three types of communication tools show that the “dark green consumers” cluster demonstrates a stronger preference for “newspaper” and “radio” than the “medium green consumers” cluster. At the same time, the “dark green consumers” cluster demonstrates a stronger preference for “e-mail” than both the “medium green consumers” cluster and the “light green (including colorless) consumers” cluster. The comparison results are presented in Table 3.

4.3. Model Fit Test on Communication Tools

In terms of absolute fit indices, the χ2/df value is 2.73; the GFI value is 0.97; the AGFI value is 0.95; the RMR value is 0.03; the SRMR value is 0.02; and the RMSEA value is 0.05, all of which satisfy the standard values. Regarding incremental fit indices, the NFI value is 0.98; the NNFI value is 0.98; the CFI value is 0.99; the RFI value is 0.97; and the IFI value is 0.99, all of which satisfy the standard values. With respect to parsimonious fit indices, the PNFI value is 0.62, and the PGFI value is 0.52, all of which satisfy the standard values. Overall, all the fit indices of the overall model lie within the acceptable level, confirming that the data have passed the model fit test.

4.4. Convergent and Discriminant Validity Tests on Communication Tools

According to the results of the convergent validity test, all the standardized factor loadings (SFLs) in the data are greater than 0.5, and the results of the t-test are significant “Hair et al., 1998 [47]”. Furthermore, the composite reliability (CR) is greater than 0.6, while the average variance extracted (AVE) is greater than 0.5, thereby satisfying the criteria for convergent validity “Bagozzi and Yi, 1988 [48]; Fornell and Larcker, 1981 [49]”. In the discriminant validity part, Table 4 shows that the diagonal elements are greater than 75% of the off-diagonal elements (the correlation coefficient of constructs), so this model has discriminant validity.

4.5. Analysis of the Constructs of Media Richness in Communication Tools

In this section, we examine how the preference for the four constructs of media richness and their sub-constructs among three consumer types affects their intent to purchase green foods. First, the “feedback” construct and its sub-constructs pass the homogeneity of variance test, aligning with the one-way ANOVA model. In post hoc comparisons, we detect significant differences in two sub-constructs, specifically, “providing product information in real-time (F1)” and “updating product information in real-time (F2)”, between the “medium green consumers” and “light green (including colorless) consumers” clusters. Both sub-constructs exhibit p-values equal to or less than 0.05, indicating that medium green consumers exhibit a stronger preference for the “feedback” construct sub-constructs compared to light green (including colorless) consumers (refer to Table 3).
This section explores how the preference for multiple cues influences the intention to purchase green foods among three green consumer types. Initially, the “multiple cues” construct and its first sub-construct, “introducing products in words (MC1)”, did not meet the homogeneity of variance criteria, leading us to employ the Brown–Forsythe test statistic. However, the results of this test remained insignificant (0.11 > 0.05), indicating no significant difference in the preference for communication tools introducing products in words among the three consumer types. Although the other two sub-constructs of the “multiple cues” construct, “introducing products with videos (MC2)” and “introducing products with pictures (MC3)”, passed the homogeneity of variance test, their p-values in one-way ANOVA were 0.580 and 0.800, respectively, all exceeding 0.05. These outcomes indicate no significant differences in the preference for MC2 and MC3 among the three green consumer types (refer to Table 5).
Meanwhile, the “language variety” construct and its three sub-constructs (i.e., labeling the nutritional content of the product with numbers (LV1), describing the idea of environmental protection of the product in words (LV2), and explaining the product with easy-to-understand words (LV3)) pass the homogeneity of variance test. However, the p-values of these three sub-constructs in one-way ANOVA are 0.19, 0.11, and 0.32, respectively, all greater than 0.05. These findings suggest no significant difference in the preference for language variety among these three types of consumers (see Table 4).
Lastly, our study delves into the impacts of the “personal focus” construct and its three sub-constructs: (1) the ability to remind me of my next purchase time based on my purchase cycle (PF1), (2) the ability to provide me with an appropriate purchase plan based on my purchase habits (PF2), and (3) the ability to provide me with information about green products in nearby areas (PF3). Similar to previous constructs, the “personal focus” construct and its sub-constructs met the homogeneity of variance criteria. Upon conducting post hoc comparisons, our findings reveal significant disparities among these sub-constructs between the “medium green consumers” and “light green (including colorless) consumers” clusters. All three sub-constructs exhibited p-values equal to or less than 0.05, signifying that the “medium green consumers” cluster exhibits a stronger preference for the sub-constructs of personal focus compared to the “light green (including colorless) consumers” cluster. Furthermore, significant differences were observed in these three sub-constructs between the “dark green consumers” and “light green (including colorless) consumers” clusters, with all p-values less than or equal to 0.05. These results indicate that the “dark green consumers” cluster also possesses a stronger preference for the sub-constructs of personal focus compared to the “light green (including colorless) consumers” cluster (refer to Table 3 for detailed information).

5. Conclusions and Implications

This study takes an innovative approach, departing from previous methods by shifting the focus from consumer awareness to actual consumer behavior. It effectively categorizes consumers based on their level of green behavior into three clusters: the “light green (including colorless) consumers” cluster, the “medium green consumers” cluster, and the “dark green consumers” cluster. Moreover, the study examines 13 commonly used IMC tools and conducts an in-depth investigation into the impact of four constructs derived from the media richness theory “Daft et al., 1987 [39]”—feedback, multiple cues, language variety, and personal focus—on the intention to purchase green foods among various green consumer types.
First, in terms of communication tool preferences to enhance the intention to purchase green foods, our study reveals significant differences among the three types of consumers for only three communication tools, newspapers, radio, and e-mail. These tools effectively provide consumers with varying levels of green behavior and the necessary green product information to enhance their purchase intention. Dark green consumers exhibit a notably stronger preference for these three tools compared to the other two consumer types. Newspapers, suitable for distributing news to well-educated and affluent consumers “Moriarty et al., 2019 [34]”, align with the characteristics of dark green consumers, who also show a greater intention to purchase green foods than the other two types of consumers “Santucci et al., 1999 [50]; Gracia and Magistris, 2007 [51]”.
Furthermore, radio stations possess the capacity to target consumers at precise moments and deliver periodic product information aligned with prevailing trends, addressing the personalized messaging preferences of dark green consumers. Conversely, e-mail’s ability to provide comprehensive details and promptly address inquiries aids consumers in cultivating a profound comprehension of green foods, a critical aspect for effectively conveying the sustainability value associated with these products.
Regarding the influence of the four media richness constructs on the intention to purchase green foods among the three consumer types, significant differences emerge in only two constructs, “feedback” and “language variety”. Medium green consumers prioritize communication tools that provide immediate product-related information and real-time updates more than light green (including colorless) consumers. This preference likely stems from medium green consumers’ initial knowledge and preference for green foods, as real-time updates assist in their decision-making process.
Notably, no significant difference exists in the “feedback” construct between light green (including colorless) consumers and dark green consumers or between medium green consumers and dark green consumers. Dark green consumers do not prioritize the immediate feedback ability of communication tools, suggesting that their strong green awareness and altruistic behavior dominate their green consumption choices.
Furthermore, both dark green and medium green consumers exhibit a heightened interest in message personalization compared to their light green (including colorless) counterparts. Customized messages significantly enhance the purchase intention of dark green and medium green consumers, indicating their growing interest in obtaining personalized information amid increasing green awareness. In the era of information overload, consumers seek tailored messages to navigate the vast array of available information effectively. Another insight we can glean from the examination of the remaining two constructs, namely “multiple cues” and “language variety”, is that consumers with a strong green inclination prioritize the substance of product information over its presentation when making green food purchases.
In conclusion, light green (including colorless) consumers represent a valuable market for increased marketing efforts. Given their limited familiarity with green issues and environmental concerns, we recommend green marketers engage them through topics of personal interest. By raising their health awareness and linking it with green products using communication tools, marketers can gradually shift their consumption behavior and bridge the gap between these consumers and green products.
In addition, according to the above empirical analysis, the results indicate a rising consumer preference for tailored green product messages like e-mail due to growing environmental awareness. To deepen green awareness and green consumption behavior across various green consumer segments, firms should increase the use of customizable communication tools. Furthermore, because dark green consumers often possess a deep understanding of green issues, they can serve as catalysts, encouraging others to adopt sustainable practices. Hence, firms can leverage word-of-mouth marketing through these informed “dark green” consumers to influence the perceptions and buying decisions of other green consumer groups.
Regarding medium green consumers, our study finds their primary concern is prompt access to product-related information when buying green foods. To address this, firms should create communication tools, such as mobile apps, capable of swiftly delivering or updating messages. This approach can boost their inclination towards green consumption. Additionally, akin to dark green consumers, medium green consumers prioritize message personalization. Hence, firms must offer customized messages to align with their product preferences, thereby influencing their actual purchasing behavior.

Research Limitations and Recommendations for Future Research

Regarding the measurement method and tools, we utilize selected items from the SRCB scale proposed by “Roberts, 1995 [45]”as a foundational framework for initially categorizing types of green consumers. We also incorporate altruistic behavior as a distinguishing factor to identify dark green consumers. This classification approach results in three clusters: light green (including colorless) consumers, medium green consumers, and dark green consumers. It is worth noting that the development of scales and consumer classification for socially responsible behavior is still evolving, and our study provides a preliminary categorization based on the level of green behavior. We anticipate that future research will refine and enhance the classification methods to achieve a more detailed differentiation of green consumers based on their consumption behaviors. Furthermore, future research may think about those consumers who are not interested in green food or even resist it, and this would maybe garner some interesting results that are different from this study.
In addition, despite the comprehensive examination of 13 IMC tools in our investigation of communication tools’ impact on the intention to purchase green foods, certain contemporary communication tools like mobile apps were not encompassed in this study. Consequently, we recommend that future research endeavors to incorporate emerging communication tools that possess media richness, which would lead to a more extensive exploration of their effects.
Meanwhile, this study involves a sample of Taiwanese consumers who have a history of purchasing green foods, and we employed convenience sampling by distributing the questionnaire online. From the perspective of statistical theory, these samples may lack generalization power, and so it may not suitable to draw the same inferences for other consumer groups.
Finally, the scope of the organic products analyzed is not comprehensive. Consequently, we recommend that future research endeavors expand the scope of the organic products analyzed or consider other green products.

Author Contributions

Conceptualization, C.-S.C. and C.-C.Y.; Formal analysis, K.-Y.T.; Investigation, K.-Y.T.; Writing—original draft, K.-Y.T.; Writing—review & editing, C.-S.C. and C.-C.Y.; Supervision, C.-C.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Appendix A.1. Questionnaire of This Study

In this questionnaire, the term ‘green products’ pertaining to food encompasses a range of items, such as those aligned with fair trade standards, products characterized by their environmental benignity, organically produced foodstuffs, edibles devoid of toxic substances, and food items accompanied by certified documentation of their production and marketing processes. Additionally, ‘sustainable products’ in the context of food refers specifically to those items that have been awarded either the Eco Label or Green Label certification.
Consumer Green BehaviorNeverRarelyOccasionallyOftenAlways
1I buy products that are low in pollutants. (e.g., environmentally friendly paints)□□□□□
2I buy recycled products. (e.g., recycled paper)□□□□□
3When choosing between two similar products, I buy the one that is less harmful to the environment. (e.g., regular air conditioners and energy-efficient air conditioners)□□□□□
4I buy products that can be recycled.□□□□□
5I categorize household garbage for recycling.□□□□□
6Given a choice, I buy the least polluting products. (e.g., fans and air conditioners)□□□□□
7Given the choice, I buy products with reusable or recyclable packaging. (e.g., laundry detergent that comes in refill packets).□□□□□
8I refuse to buy products if I know they may be harmful to the environment.□□□□□
9I have successfully persuaded family or friends to refuse to buy certain products that are harmful to the environment.□□□□□
10I do not buy environmentally harmful household products.□□□□□
11I use recycled products. (e.g., recycled paper products)□□□□□
12I reduce the use of products made from non-renewable resources. (e.g., plastics)□□□□□
13I replace a product because I care about the environment. (e.g., electric cars instead of regular cars)□□□□□
14I purchase products that are certified with green labels.□□□□□
15A company’s commitment to the environment affects my willingness to purchase products.□□□□□
16I participate in collective environmental activities. (e.g., beach cleanups, green marches, or green road races)□□□□□
17I respond to collective fair trade activities. (e.g., refusing child labor, supporting small farm products)□□□□□
18I donate to environmental organizations or groups concerned with environmental issues.□□□□□
Envision a scenario wherein your intent is to purchase eco-conscious food items, such as those classified as organic, devoid of toxins, or possessing verifiable marketing histories. Please evaluate the degree to which each enumerated communication mechanism facilitates your comprehension of the product and augments your propensity to procure it. Assign a rating on a scale from 1 to 5, where 1 signifies the minimal impact on your purchasing inclination and 5 denotes the maximal.
Types of Communication Tools12345
Newspaper□□□□□
Magazine□□□□□
Product Catalog□□□□□
Radio□□□□□
Television□□□□□
Poster□□□□□
Outdoor advertising□□□□□
Online Advertisement□□□□□
Official Website□□□□□
Social Media□□□□□
Packaging□□□□□
Sales & Service□□□□□
E-Mail□□□□□
In this survey, you are requested to evaluate the extent to which the subsequent communication instruments would enhance your propensity to purchase green food products. Please assign a rating from 1 to 5, where 1 signifies the lowest and 5 the highest degree of influence on your purchasing inclination.
Characteristics of Communication Tools12345
1A communication tool that provides real-time product information.□□□□□
2A communication tool to update product information in real time.□□□□□
3A communication tool that introduces products in text.□□□□□
4A communication tool that introduces products with sound.□□□□□
5A communication tool that introduces products with images.□□□□□
6A communication tool that introduces products with pictures.□□□□□
7A communication tool to label the nutritional content of the product with figures.□□□□□
8A communication tool that describes the product’s environmental philosophy in words.□□□□□
9A communication tool that maximizes the use of easy-to-understand vocabulary to explain product information.□□□□□
10A communication tool that reminds me of my next purchase according to my purchasing cycle.□□□□□
11A communication tool that provides me with appropriate purchasing options based on my purchasing habits.□□□□□
12A communication tool that provides information about green products in my neighborhood.□□□□□
Personal information
Your age□ Under 18 years old □ 18–25 years old □ 26–35 years old
□ 36–45 years old □ 46–55 years old
□ 56–65 years old □ 65 years old and above
Your gender□ Male □ Female
Your occupation□ Agriculture, forestry, fishery and livestock raising □ Manufacturing
□ Financial services □ Food and beverage services □ Technology
□ Military, police, public officials □ Commercial administration
□ Healthcare personnel □ Freelance □ Student □ Household □ Retiree
□ Other
Your education level□ Junior high school or below □ High school (vocational)
□ University (specialized) □ Institute (or above)

Appendix A.2. Demographic Distribution of Respondents

Characteristics of SubjectsClassificationPercentage of Total Data (%)Percentage of Light Green (Including Colorless) Data (%)Percentage of Medium-Green Data (%)Percentage of Dark Green Data (%)
AgeUnder 18 years0.47%1.08%0.00%0.44%
18~25 years21.99%32.97%21.72%13.27%
26~35 years11.55%16.22%10.86%8.41%
36~45 years14.40%18.38%13.12%12.39%
46~55 years25.79%18.38%28.51%29.20%
56~65 years19.78%9.73%17.65%30.09%
65 years & above6.02%3.24%8.14%6.2%
GenderMale40.51%41.62%39.37%40.71%
Female59.49%58.38%60.63%59.29%
OccupationStudents22.15%35.68%21.72%11.50%
Military, Police, and Public Officials15.98%12.97%16.29%18.14%
Retirees9.81%5.95%12.22%10.62%
Technology6.96%4.32%6.33%9.73%
Business Administration6.96%8.11%6.79%6.19%
Freelance6.65%5.95%4.98%8.85%
Finance6.01%3.78%4.07%9.73%
Household Management6.01%5.95%6.33%5.75%
Manufacturing4.27%2.70%3.17%6.64%
Food and Beverage Services2.69%2.70%2.71%2.65%
Healthcare workers1.58%2.16%1.36%1.33%
Agriculture, Forestry, Fisheries and Animal Husbandry0.32%0.54%0.00%0.44%
Others10.60%9.19%14.03%8.41%
Education levelGraduate (or above)36.87%44.32%32.13%35.40%
University (College)53.96%49.73%57.47%53.98%
High School (Vocational)8.23%5.41%9.05%9.73%
Junior high school (including)0.95%0.54%1.36%0.88%

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Table 1. EFA of green behavior among consumer.
Table 1. EFA of green behavior among consumer.
ComponentCorrelation Coefficient
EigenvaluesExplained Variation%Accumulated Explained Variation%Cronbach’s α
Factor 13.0325.2625.260.82
Factor 22.3819.8045.060.77
Factor 32.0917.4562.510.74
Table 2. Consumer cluster analysis.
Table 2. Consumer cluster analysis.
Questions and Total Scores Used in This ClusterThe Name of ClusterCluster Size
(Number)		Cluster Center Point
(Point)
The first time cluster analysisQuestions 16~18, a total of three questions, with a total score of 15 pointsDark green
consumer cluster		22611.29
Other consumer
cluster		4066.92
The second time cluster analysisThere are a total of 9 questions except questions 16~18, with a total score of 45 points.Light green (including colorless) consumer cluster16027.65
Medium green consumer cluster24635.80
Table 3. Comparison of preference on the adoption of communication tools for green consumption.
Table 3. Comparison of preference on the adoption of communication tools for green consumption.
Communication ToolF-Valuep-ValueDifference between Clusters
Newspaper3.130.04C1 > C2
Radio3.190.04C1 > C2
E-mail8.740.00C1 > C2, C1 > C3
Magazine1.190.18ns
Product Catalog1.420.28ns
TV1.280.26ns
Poster1.550.27ns
Outdoor Advertising1.440.28ns
Online Advertisement1.290.27ns
Official Website1.340.28ns
Social Media1.220.14ns
Packaging Description1.270.11ns
Sales and Service1.490.27ns
Note: C1 = the “dark green consumers” cluster; C2 = the “medium green consumers” cluster; C3 = the “light green (including colorless) consumers” cluster.
Table 4. Discriminant validity test for the model.
Table 4. Discriminant validity test for the model.
ConstructCorrelation Coefficient
ABCD
A. Feedback0.93
B. Multiple cues0.700.77
C. Language variety0.680.800.76
D. Personal focus0.600.610.650.84
Note: The diagonal is the root value of AVE.
Table 5. Comparison of preference on the adoption of communication media richness for green consumption.
Table 5. Comparison of preference on the adoption of communication media richness for green consumption.
Construct and Sub-ConstructF-ValueBrown–Forsythe Statisticp-ValueDifference between Clusters
Feedback3.23-0.04C2 > C3
F13.00-0.05C2 > C3
F23.78-0.02C2 > C3
Multiple cues-1.100.33ns
MC1-2.210.11ns
MC20.55-0.58ns
MC30.22-0.80ns
Language variety1.33-0.26ns
LV11.69-0.19ns
LV22.25-0.11ns
LV31.14-0.32ns
Personal focus7.51-0.00C1 > C3, C2 > C3
PF19.96-0.00C1 > C3, C2 > C3
PF2-5.660.00C1 > C3, C2 > C3
PF39.90 0.00C1 > C3, C2 > C3
Note: C1 = the “dark green consumers” cluster; C2 = the “medium green consumers” cluster; C3 = the “light green (including colorless) consumers” cluster; ns = non-significant; F1 = providing product information in real-time; F2 = updating product information in real-time; MC1 = introducing products in words; MC2 = introducing products with videos; MC3 = introducing products with pictures; LV1 = labeling the nutritional content of the product with numbers; LV2 = describing the idea of environmental protection of the product in words; LV3 = explaining the product with easy-to-understand words; PF1 = the ability to remind me of my next purchase time based on my purchase cycle; PF2 = the ability to provide me with an appropriate purchase plan based on my purchase habits; PF3 = the ability to provide me with information about green products in nearby areas.
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Chen, C.-S.; Yu, C.-C.; Tu, K.-Y. Exploring the Impact of Integrated Marketing Communication Tools on Green Product Purchase Intentions among Diverse Green Consumer Segments. Sustainability 2023, 15, 16841. https://doi.org/10.3390/su152416841

AMA Style

Chen C-S, Yu C-C, Tu K-Y. Exploring the Impact of Integrated Marketing Communication Tools on Green Product Purchase Intentions among Diverse Green Consumer Segments. Sustainability. 2023; 15(24):16841. https://doi.org/10.3390/su152416841

Chicago/Turabian Style

Chen, Chun-Shuo, Chih-Ching Yu, and Kuan-Yu Tu. 2023. "Exploring the Impact of Integrated Marketing Communication Tools on Green Product Purchase Intentions among Diverse Green Consumer Segments" Sustainability 15, no. 24: 16841. https://doi.org/10.3390/su152416841

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