Review Reports

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study demonstrates considerable practical relevance and applied value. But there is a  weakness that limit the robustness of its scholarly and empirical contribution. I mean the limited consideration of cross-cultural differences in consumer behavior, greenwashing perception, and psychological responses in marketing communication. The empirical foundation of the GWAMA system is based exclusively on data collected in Thailand. From manuscript is not clair if the behavioral assumptions embedded in the model may may be fully transferable to other countries or cultural contexts.

Perceptions of environmental claims, trust in sustainability messaging, and skepticism toward green advertising are strongly influenced by cultural values, regulatory environments, consumer awareness, and market maturity. The authors should explain us the broader cultural and international validation.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

1. Page 2: “Prior research demonstrates that perceived greenwashing negatively influences consumer responses, including reduced trust, unfavorable brand attitudes, and lower purchase intention [3–5]. These findings are typically implemented at the aggregate research level and are not easily translated into useful tools for real-time decision-making. Think about reducing the complexity of the second sentence to make it easier to read.
2. Page 3: “This gap is particularly pronounced in emerging market contexts such as Thailand, where green semiotics and eco-label cues have been shown to produce complex and sometimes counterintuitive consumer responses [10].” Some readers outside of the field may not be familiar with the phrase 'green semiotics'. For clarity, consider briefly defining the term or rephrasing it.It should be revised to include environmental symbols and eco-label cues, as they have been proven to produce complex and sometimes counterintuitive consumer responses [10].
3. Page 4:“While both approaches play important roles in identifying and regulating greenwashing, they operate either at a conceptual or legal level and do not provide integrated, user-friendly systems for real-time evaluation.”Replace the wording 'operate either at a conceptual or legal level' with a more concise one, if possible. The suggested modification is: '...they function mainly at the conceptual or regulatory level and do not provide integrated, user-friendly systems for real-time evaluation.'
4. Page 5: “GWAMA operationalizes a Stimulus–Organism–Response (S-O-R) framework [15], in which Perceived Greenwashing Communication (PGC) functions as the stimulus…” When introducing it for the first time, it may be beneficial to define the S-O-R framework more clearly, especially for interdisciplinary readers who are unfamiliar with consumer behavior theory.
5. Page 6:“Instantiation artifacts provide empirical validation in real-world contexts, demonstrating whether theoretically grounded models can be effectively translated into practical applications.”The length of this sentence could be reduced by splitting it. The proposed modification: 'Instimation artifacts provide empirical validation in real-world contexts.' The effectiveness of translating theoretically grounded models into practical applications is demonstrated by them.
6. Page 9: “Revenue Protection: This cluster translates diagnostic results into estimated behavioral outcomes by applying the structural equation model to predict the potential impact on purchase intention.”The academic tone of the paper may be influenced by the managerial or commercial tone of the heading 'Revenue Protection'. Consider if a term like 'Behavioral Impact Prediction' might be more aligned with the study's analytical focus.
7. Page 10:“The final stage presents the integrated results dashboard, which combines composite PGC and GST scores with SEM-based PI prediction.” To make it easier to read, consider briefly restating the meaning of PI here, as abbreviations can be difficult to track across sections.
8. Page 11:“This approach preserves the relative contribution of each indicator in accordance with the reflective measurement structure [26,27].”For practical interpretation within the system, you may want to briefly explain the importance of preserving indicator contributions.
9. Page 13:“To maintain usability for non-technical users, GWAMA presents the point estimate as the primary diagnostic output.” It's worth considering whether confidence intervals or uncertainty ranges will be included in future versions of the system.
10. Page 15:“The factor-loading-weighted method is retained as the primary scoring approach because it preserves the proportional psychometric contribution of each indicator…”Take into account simplifying 'proportional psychometric contribution' to make it easier to read. Possible revision: '...because it preserves the relative importance of each indicator estimated in the measurement model.'

Comments on the Quality of English Language

minor errors - typos

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The reviewed manuscript addresses a timely and interesting issue related to greenwashing in marketing communication within the food industry, while also attempting to operationalize behavioral research findings through the development of a web-based decision support system called GWAMA (Greenwashing Advertising Message Assessment). The authors position the study within the fields of sustainability communication and Design Science Research (DSR), proposing a solution intended to support the assessment of greenwashing risk in food-related marketing messages. Conceptually, the article integrates the Stimulus-Organism-Response (S-O-R) framework, SEM-based modeling, and the Technology Acceptance Model (TAM), creating a multi-stage framework that moves from behavioral models toward an implemented system artifact. I particularly appreciate the idea of translating SEM findings into a practical diagnostic tool accessible to market practitioners. In my opinion, the authors correctly identify the existing gap between academic research on greenwashing and practical tools supporting the evaluation of sustainability communication. The paper fits well within the growing stream of research on sustainable marketing governance. Nevertheless, I believe the manuscript still requires several important revisions and clarifications.

My first concern relates to the theoretical status of the proposed system itself. The authors state that the aim of the study is not to re-test behavioral relationships, but rather to translate an existing model into a decision support system. However, a substantial part of the manuscript still adopts the language of a traditional empirical study, which creates some ambiguity regarding the paper’s primary contribution. At times, the article reads like a conventional SEM study; at other times, it resembles an information systems paper or a description of a web application implementation. The authors should more clearly structure the scientific contribution of the study and explicitly indicate whether the primary contribution lies in a new theoretical model, a novel scoring method, or the DSR artifact itself. At present, these three levels are partially intertwined. This issue is particularly visible in the Discussion and Contributions sections (pp. 20-21, lines 756-816).

My second concern relates to the operationalization of purchase intention prediction. The authors employ a unified population-level model based on a sample of N = 400 and implement the SEM coefficients as fixed parameters within the scoring engine (p. 5, lines 170-177; p. 8, lines 279-283). On the one hand, this solution is methodologically understandable from the perspective of model stability. On the other hand, it introduces the problem of excessive simplification of the predictive process. The authors themselves emphasize the contextual dependence of greenwashing perception on message framing and offering type (product vs. service) (p. 6, lines 179-192), yet purchase intention is ultimately based on a single universal regression equation. Consequently, the system claims contextual sensitivity, but does not actually implement context-specific predictive models. The manuscript should provide a stronger justification for why separate models for food products and food services were not developed, or at least why measurement invariance between groups was not tested.

The methodological section is highly detailed and comprehensive, which should be evaluated positively. At the same time, I feel that the level of technical detail is occasionally excessive relative to the main purpose of the paper. This particularly concerns the extensive description of the scoring algorithm, the multiple standardization procedures, and the illustrative mathematical calculations (pp. 11-14, lines 373-545). Some of these elements could be moved to the Appendix.

I also have concerns regarding the interpretation of predicted purchase intention. The authors repeatedly emphasize that PI is not a direct measure of greenwashing risk, but rather a behavioral consequence of greenwashing perception (p. 12, lines 399-418). However, the problem is that the dashboard may suggest to users a more precise and deterministic behavioral prediction than is actually supported by a model with R² = 0.311 (p. 13, lines 452-470). Although the authors acknowledge the predictive limitations of the model and describe the outputs as indicative rather than deterministic, the manuscript should more strongly emphasize the limited explanatory power of the model and the potential risk of overinterpretation by business practitioners. This issue is particularly important given the declared role of the system as a decision support tool.

I positively evaluate the overall Design Science Research logic and the attempt to position the artifact within established DSR frameworks. The authors appropriately refer to the classical works of Hevner, March and Smith, and Gregor and Hevner (pp. 6-7, lines 198-230). Particularly valuable is the clear anchoring of the system in the governance gap between academic research and marketing practice. The article effectively demonstrates the potential of validated behavioral models for developing practitioner-oriented tools.

The section devoted to TAM usability evaluation is generally well prepared, although it remains more declarative than genuinely evaluative. The very high levels of perceived usefulness and intention to use are interesting, but it should be remembered that the study was conducted using purposive snowball sampling, partially recruited through the authors’ professional networks (p. 16, lines 561-573). In addition, the evaluation is based solely on users’ declared perceptions rather than on actual business outcomes resulting from system implementation. The authors should more explicitly acknowledge that the current evaluation concerns usability acceptance rather than the real effectiveness of greenwashing reduction.

I also have some doubts regarding the very concept of “greenwashing risk” used throughout the paper. In practice, the system primarily measures perceived greenwashing communication and green skepticism, rather than the objective level of greenwashing itself. This means that the tool evaluates perceived communication risk rather than the actual consistency between marketing claims and firms’ environmental practices. The authors partially acknowledge this distinction, but the terminology at times suggests a more objective diagnostic capability than the system can realistically provide. A clearer distinction between perceived greenwashing risk and actual greenwashing practices would strengthen the conceptual clarity of the manuscript.

At present, the Discussion section focuses mainly on summarizing the functioning of the system and reiterating the declared contributions, while devoting less attention to deeper theoretical and methodological interpretation of the findings. In my opinion, the authors should engage more extensively with the literature on greenwashing governance, decision support systems, and the broader challenges associated with translating behavioral models into practical diagnostic tools.

I also have several comments regarding the figures. Figure 1 provides only a very general overview of the sequential research program and largely duplicates information already described in the text (p. 2, lines 78-85). In its current form, it offers limited methodological or conceptual value. I would recommend removing the figure, incorporating its content into the narrative discussion, or combining it with Figure 2 to simplify the manuscript’s visual structure. Figure 4 also has limited scientific value in its current form. The screenshots mainly present standard user registration and consent procedures rather than substantive aspects of the system architecture or scoring logic. I would therefore recommend removing this figure. In my opinion, Figure 5 should be simplified, while Figure 6 is currently difficult to read and requires substantial improvement.

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The authors responded thoroughly and substantively to all of the comments raised and introduced numerous revisions of both conceptual and methodological importance. I particularly appreciate the clearer delineation of the system’s interpretative boundaries, the explicit distinction between perceived greenwashing and actual greenwashing, and the stronger positioning of the manuscript within the literature on greenwashing governance and decision support systems. The clarification of the article’s contribution hierarchy and the more balanced discussion of the predictive model’s limitations are also important improvements. In addition, the authors addressed most of the comments related to the manuscript structure and visual presentation by simplifying and redesigning several figures. Overall, the revised version represents a significant improvement over the previous manuscript.