<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.179246.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>The Impact of Green Advertising and the Mediating Role of Perceived Credibility on Consumers&#x2019; Purchase of 
                    <italic>Lontar</italic>-Based Products in Indonesia</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: awaiting peer review]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Lopes Amaral</surname>
                        <given-names>Maria Augustin</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-7963-7765</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Haro</surname>
                        <given-names>Andrian</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-5522-2469</uri>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Putri</surname>
                        <given-names>Dian Puspita Eka</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Ketmoen</surname>
                        <given-names>Adrianus</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Saputra</surname>
                        <given-names>Dedi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Management, Widya Mandira Catholic University, Kupang, East Nusa Tenggara, Indonesia</aff>
                <aff id="a2">
                    <label>2</label>Management, Jakarta State University, East Jakarta, Special Capital Region of Jakarta, Indonesia</aff>
                <aff id="a3">
                    <label>3</label>Science Education, State Islamic University Sultan Syarif Kasim Library, Pekanbaru, Riau, Indonesia</aff>
                <aff id="a4">
                    <label>4</label>Economic Development, Widya Mandira Catholic University, Kupang, East Nusa Tenggara, Indonesia</aff>
                <aff id="a5">
                    <label>5</label>Economy, Raden Fatah State Islamic University, Palembang, South Sumatra, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:maria_amaral@unwira.ac.id">maria_amaral@unwira.ac.id</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>29</day>
                <month>4</month>
                <year>2026</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2026</year>
            </pub-date>
            <volume>15</volume>
            <elocation-id>640</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>6</day>
                    <month>4</month>
                    <year>2026</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Lopes Amaral MA et al.</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
                <license>
                    <license-p>The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/15-640/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>The growing concern over environmental issues has increased interest in eco-friendly packaging as an alternative to conventional plastic. In Indonesia, packaging made from 
                        <italic toggle="yes">lontar</italic> leaves represents a sustainable option that is also closely related to local resources and practices. However, consumers are often reluctant to pay a higher price for environmentally friendly packaging. Understanding the factors that shape willingness to pay more is therefore important. This study examines how green advertising influences willingness to pay more for eco-friendly packaging made from 
                        <italic toggle="yes">lontar</italic> leaves, with perceived credibility and green future estimation as the underlying psychological mechanisms.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>This study used a quantitative survey design. Data were collected from 401 consumers who were familiar with and or had used eco-friendly packaging. The relationships among green advertising, perceived credibility, green future estimation, and willingness to pay more were tested using Partial Least Squares Structural Equation Modeling with SmartPLS software. The analysis included both direct effects and parallel mediation effects.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>The results show that perceived credibility and green future estimation have significant positive effects on willingness to pay more. Green advertising does not have a significant direct effect on willingness to pay more. However, green advertising significantly influences perceived credibility and green future estimation. Both variables, in turn, significantly increase willingness to pay more. The findings indicate that perceived credibility and green future estimation fully mediate the relationship between green advertising and willingness to pay more through a parallel mediation mechanism.</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>Green advertising is more effective when it strengthens consumer trust and builds positive expectations about future environmental benefits. Clear, relevant, and credible sustainability messages are therefore important for encouraging consumers to accept premium prices for eco-friendly 
                        <italic toggle="yes">lontar</italic>-leaf packaging in Indonesia.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>green advertising; perceived credibility; green future estimation; willingness to pay more; palm leaf packaging</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source> Director of Technology and Public Services</funding-source>
                    <award-id>136/C3/DT.05.00/PL/2025</award-id>
                </award-group>
                <funding-statement>We would like to formally acknowledge and express our deep appreciation to the Director of Technology and Public Services for their crucial assistance and invaluable contributions to the advancement of this research (Decree No. 136/C3/DT.05.00/PL/2025). Their in-depth expertise and unwavering support were instrumental in the successful implementation of this research endeavor.</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>1. Introduction</title>
            <p>Purchasing power plays a critical role in shaping sustainable consumption and can accelerate progress toward the Sustainable Development Goals (SDGs). In developed countries, increases in purchasing power are associated with heightened consumer expectations for environmentally friendly products and services, which in turn encourage corporate responses. Examples include initiatives in Canada&#x2019;s food sector to reduce single-use plastics and to strengthen Corporate Social Responsibility (CSR) practices aligned with SDG 12 (
                <xref ref-type="bibr" rid="ref34">Ta&#x015f;k&#x0131;n et al., 2020</xref>; 
                <xref ref-type="bibr" rid="ref36">Walker et al., 2021</xref>). The adoption of green practices also enhances competitiveness in international markets and supports efforts to reduce carbon emissions (
                <xref ref-type="bibr" rid="ref17">Hepner et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref22">Khalaf et al., 2023</xref>). In contrast, in developing countries, limited purchasing power constrains the allocation of resources toward environmentally friendly products. Nevertheless, consumers in these contexts still tend to prefer sustainable products when prices are affordable and when supported by government policies (
                <xref ref-type="bibr" rid="ref3">Babatunde et al., 2018</xref>; 
                <xref ref-type="bibr" rid="ref25">Liu, 2019</xref>; 
                <xref ref-type="bibr" rid="ref33">Shimul &amp; Cheah, 2022</xref>).</p>
            <p>Differences in purchasing power underscore that both economic and non-economic factors influence sustainable consumption decisions. In developed countries, environmental awareness, social norms, and sustainability-oriented marketing increase consumers&#x2019; intentions to purchase green products, while corporate commitment strengthens brand image and customer loyalty (
                <xref ref-type="bibr" rid="ref55">Huo et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref32">Rahman &amp; Nguyen-Viet, 2023</xref>; 
                <xref ref-type="bibr" rid="ref87">Zanon &amp; Teichmann, 2016</xref>). In developing countries, although economic capacity is more limited, interest in environmentally friendly products increases when their benefits are perceived as directly relevant to daily life. Moreover, environmental knowledge can continue to drive purchasing decisions even when green products are priced higher (
                <xref ref-type="bibr" rid="ref58">Kamel, 2020</xref>; 
                <xref ref-type="bibr" rid="ref25">Liu, 2019</xref>; 
                <xref ref-type="bibr" rid="ref72">Nocella et al., 2023</xref>).</p>
            <p>Product innovation rooted in local wisdom has increasingly been recognised as a strategic pathway to strengthen sustainability and community empowerment in developing countries. Various initiatives leverage local resources while revitalising cultural values to meet the demands of modern markets. These initiatives range from natural-based personal care products (
                <xref ref-type="bibr" rid="ref19">Kahraman &amp; Kazan&#x00e7;o&#x011f;lu, 2019</xref>) to sustainable agriculture employing traditional cultivation techniques (
                <xref ref-type="bibr" rid="ref63">Kurnia et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref32">Rahman &amp; Nguyen-Viet, 2023</xref>), and cultural tourism experiences that integrate local products and practices to enhance economic benefits while preserving cultural heritage (
                <xref ref-type="bibr" rid="ref57">Jaelani et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref58">Kamel, 2020</xref>). In addition, handicrafts made from natural materials such as rattan and bamboo, as well as 
                <italic toggle="yes">lontar</italic>-based 
                <italic toggle="yes">lontar</italic>-leaf packaging in Indonesia, exemplify how local materials can be transformed into culturally embedded sustainable products (
                <xref ref-type="bibr" rid="ref62">Kosfraedi, 2024</xref>; 
                <xref ref-type="bibr" rid="ref33">Shimul &amp; Cheah, 2022</xref>; 
                <xref ref-type="bibr" rid="ref79">Siarudin et al., 2023</xref>; 
                <xref ref-type="bibr" rid="ref81">Tan &amp; Quang, 2023</xref>).</p>
            <p>Green advertising has become increasingly important for micro, small, and medium-sized enterprises (MSMEs), as informative and credible messages enhance consumer awareness and purchase intentions (
                <xref ref-type="bibr" rid="ref39">Aldaihani et al., 2024</xref>; 
                <xref ref-type="bibr" rid="ref83">Wang et al., 2023</xref>). In Indonesia, MSMEs interact directly with local communities and are therefore well-positioned to leverage environmental issues as a source of competitive advantage. Practices observed in initiatives such as Creabrush demonstrate that green advertising requires clear and transparent information so that consumers understand product value and the justification for premium pricing, while also facilitating access to broader markets, including international markets that demand eco-friendly standards (
                <xref ref-type="bibr" rid="ref41">Andriyansah et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref71">Munandar et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref78">Sholehuddin &amp; Sudarmiatin, 2024</xref>). The effectiveness of green advertising is influenced by message composition and visual elements; the use of green colour schemes and environmental symbols has been shown to strengthen positive brand attitudes and purchase intentions (
                <xref ref-type="bibr" rid="ref66">Lim et al., 2020</xref>; 
                <xref ref-type="bibr" rid="ref76">Sahin et al., 2019</xref>). Furthermore, MSMEs need to emphasise environmental benefits and build trust through supply chain transparency and clarity about product value, which, in turn, contributes to consumers&#x2019; willingness to pay more (
                <xref ref-type="bibr" rid="ref42">Bailey et al., 2016</xref>; 
                <xref ref-type="bibr" rid="ref51">Duan &amp; Aloysius, 2019</xref>).</p>
            <p>Perceived credibility plays a pivotal role in increasing willingness to pay more for environmentally friendly products, as consumers are more inclined to accept premium prices when they trust the brand and its green claims. This finding is consistent with evidence that brand credibility and trust in environmental claims increase purchase likelihood across product categories (
                <xref ref-type="bibr" rid="ref1">Akturan, 2020</xref>) and that strong brand identity is associated with higher purchase intentions (
                <xref ref-type="bibr" rid="ref53">Guerreiro et al., 2023</xref>). Conversely, when consumers suspect greenwashing, trust declines and WTPM weakens, highlighting transparency as a critical factor (
                <xref ref-type="bibr" rid="ref43">Bairrada et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref60">Knight et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref77">Shojaei et al., 2024</xref>). In addition, green future estimation increases willingness to pay more because consumers expect current green choices to yield future environmental benefits, especially when brands clearly communicate tangible, consistent impacts (
                <xref ref-type="bibr" rid="ref86">Wu et al., 2024</xref>).</p>
            <p>Several studies (
                <xref ref-type="bibr" rid="ref40">Ampornklinkaew, 2025</xref>; 
                <xref ref-type="bibr" rid="ref15">Hasrama et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref59">Khan et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref70">Moon &amp; Song, 2026</xref>) indicate that green advertising can shape consumer preferences toward sustainable products; however, its effectiveness is strongly contingent on consumer trust in the credibility of environmental claims. When advertisements are perceived as misleading or indicative of greenwashing, purchase responses tend to weaken. Cross-contextual evidence also suggests that credible sustainability cues, such as sustainability badges, enhance brand evaluations and willingness to pay more (
                <xref ref-type="bibr" rid="ref73">Vinish et al., 2025</xref>). Moreover, green future estimation has a positive effect on the willingness to pay more among Generation Z consumers, and this effect reflects the importance of long-term environmental benefit expectations in premium pricing decisions (
                <xref ref-type="bibr" rid="ref52">Gawshinde et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref7">Gomes et al., 2023</xref>; 
                <xref ref-type="bibr" rid="ref84">Witek &amp; Ku&#x017a;niar, 2021</xref>; 
                <xref ref-type="bibr" rid="ref91">Zhuang et al., 2021</xref>).</p>
            <p>Existing green advertising research has largely focused on its effects on attitudes or purchase intentions (
                <xref ref-type="bibr" rid="ref59">Khan et al., 2025</xref>; 
                <xref ref-type="bibr" rid="ref89">Zhao et al., 2025</xref>) and typically employs a single mediating variable, such as perceived credibility (
                <xref ref-type="bibr" rid="ref40">Ampornklinkaew, 2025</xref>; 
                <xref ref-type="bibr" rid="ref48">Chaturvedi &amp; Sangwan, 2025</xref>; 
                <xref ref-type="bibr" rid="ref50">Dondapati, 2025</xref>; 
                <xref ref-type="bibr" rid="ref70">Moon &amp; Song, 2026</xref>; 
                <xref ref-type="bibr" rid="ref74">Rohden et al., 2025</xref>) or environmental awareness (
                <xref ref-type="bibr" rid="ref15">Hasrama et al., 2025</xref>). In Asia, evidence related to green future estimation has more frequently been linked to green purchase decisions, such as in Bangladesh through extensions of the Theory of Planned Behavior (
                <xref ref-type="bibr" rid="ref28">Nekmahmud &amp; Fekete-Farkas, 2020</xref>), and in India, where green future estimation has been shown to heighten environmental concern (
                <xref ref-type="bibr" rid="ref52">Gawshinde et al., 2025</xref>). Other studies demonstrate that source credibility, including influencer credibility, enhances purchase decisions by strengthening information credibility (Hasim &amp; Mahbob, 2025; P et al., 2025). Despite the extensive body of research on green advertising, few studies have examined dual mediation mechanisms, specifically perceived credibility and green future estimation within the context of culturally rooted sustainable products from developing countries, particularly those produced by MSMEs.</p>
            <p>In Indonesia, particularly in East Nusa Tenggara Province (Nusa Tenggara Timur, NTT) the 
                <italic toggle="yes">lontar</italic> palm is often referred to as the &#x201c;tree of life&#x201d; due to its extensive contributions to food and beverages (e.g., sap processed into sugar or palm wine), construction materials, handicrafts (e.g., bags, hats, and the sasando musical instrument), traditional medicine, as well as its potential for bioethanol and organic fertiliser production (
                <xref ref-type="bibr" rid="ref62">Kosfraedi, 2024</xref>). 
                <italic toggle="yes">Lontar</italic> leaves (Borassus flabellifer) are also used in education, cultural traditions, and creative enterprises, and hold significant potential as materials and sources of inspiration for economically valuable, sustainable products. The integration of local wisdom into 
                <italic toggle="yes">lontar</italic>-leaf packaging development is believed to support environmental conservation and the achievement of the SDGs (
                <xref ref-type="bibr" rid="ref65">Lestari et al., 2024</xref>). Strengthened utilisation can foster the development of culturally distinctive and competitive handicraft products and can also contribute to the expansion of economic opportunities for local communities (
                <xref ref-type="bibr" rid="ref82">Utomo et al., 2023</xref>). 
                <italic toggle="yes">Lontar</italic>-based 
                <italic toggle="yes">lontar</italic>-leaf packaging serve as tangible environmental and cultural signals that reinforce perceived credibility. The development of media and creative products grounded in local wisdom can further strengthen this synergy, as such initiatives contribute to cultural preservation and foster innovation (
                <xref ref-type="bibr" rid="ref80">Sukadari et al., 2023</xref>).</p>
            <p>This study examines the key mechanisms shaping consumer demand for sustainable products and their influence on consumers&#x2019; willingness to pay premium prices. Theoretically, the study extends signaling theory in green marketing by clarifying how environmental signals are translated into consumer value evaluations and premium payment intentions through specific psychological pathways. Methodologically, the study advances prior research by testing a parallel mediation model that positions green future estimation and perceived credibility as simultaneous mediators, and by validating these constructs within the context of a developing-country market. In practice, the findings offer actionable guidance for MSMEs on designing credible green signals, crafting communications that strengthen consumers&#x2019; future-oriented green evaluations, and developing more sustainable premium pricing strategies. Finally, this study offers empirical evidence from Indonesia and addresses an important gap in the contemporary green marketing literature, as this context remains underrepresented in international research.</p>
        </sec>
        <sec id="sec6">
            <title>2. Literature review</title>
            <sec id="sec7">
                <title>2.1 Signaling theory</title>
                <p>Signaling theory explains the presence of information asymmetry between signalers, who possess superior information, and receivers, who have more limited knowledge. Signalers convey observable cues to demonstrate credibility, quality, or commitment, which receivers then use as a basis for evaluation and decision making (
                    <xref ref-type="bibr" rid="ref49">Connelly et al., 2011</xref>; 
                    <xref ref-type="bibr" rid="ref54">Giachetti et al., 2024</xref>). Within this framework, signals must be credible; otherwise, receivers are likely to disregard them and refrain from responding (
                    <xref ref-type="bibr" rid="ref7">Gomes et al., 2023</xref>). Recent studies have linked the consumption of environmentally friendly products to consumers&#x2019; willingness to pay more through the lens of signaling theory (
                    <xref ref-type="bibr" rid="ref68">Lopes et al., 2024</xref>; 
                    <xref ref-type="bibr" rid="ref69">Macchione Saes et al., 2025</xref>). When the environmental quality of a product is difficult to observe, corporate signals can reduce information asymmetry, making marketers&#x2019; ability to clearly communicate environmental benefits critical for shaping consumer perceptions and purchase intentions (
                    <xref ref-type="bibr" rid="ref44">Baskoro et al., 2023</xref>). In practice, sustainability signals often take the form of eco-labels and certifications that differentiate products in the marketplace and enhance perceived value (
                    <xref ref-type="bibr" rid="ref45">Baskoro et al., 2024</xref>). Such signals foster trust and strengthen willingness to pay more when consumers perceive that a brand&#x2019;s commitment to environmental standards is accountable and verifiable (
                    <xref ref-type="bibr" rid="ref64">Le &amp; Tang-Le, 2024</xref>). Sustainability signals are also associated with social identity, particularly among younger consumers who interpret green purchasing as an expression of personal values and self-image (
                    <xref ref-type="bibr" rid="ref18">Huh &amp; Kim, 2024</xref>). Moreover, consistent sustainability communication can reinforce perceptions of price fairness and the price&#x2013;quality relationship, thereby increasing consumers&#x2019; acceptance of premium pricing (
                    <xref ref-type="bibr" rid="ref61">Konuk, 2023</xref>; 
                    <xref ref-type="bibr" rid="ref67">Lin et al., 2020</xref>). Accordingly, signaling theory provides a robust theoretical foundation for understanding how sustainability communication and cues shape trust and drive consumers&#x2019; willingness to pay more for environmentally friendly products.</p>
            </sec>
            <sec id="sec8">
                <title>2.2 Perceived credibility and willingness to pay more</title>
                <p>Consumers are willing to pay higher prices for brands perceived as credible and authentic. This pattern has been documented both in the context of sustainable products more broadly (
                    <xref ref-type="bibr" rid="ref20">Kamboj &amp; Matharu, 2021</xref>) and in the context of green products specifically, where green brand equity and brand credibility strengthen consumers&#x2019; willingness to pay more (
                    <xref ref-type="bibr" rid="ref1">Akturan, 2020</xref>). From a psychological perspective, credibility helps consumers assess risk and product quality, thereby increasing their acceptance of premium prices. Moral and ethical value dimensions may further reinforce this tendency when products are perceived as aligned with consumers&#x2019; personal beliefs and values (
                    <xref ref-type="bibr" rid="ref56">Hwang, 2018</xref>). Brand experience and perceived authenticity also deepen the influence of credibility on willingness to pay more (
                    <xref ref-type="bibr" rid="ref75">Safeer et al., 2021</xref>). Evidence from the food safety context similarly shows that trust in product attributes increases consumers&#x2019; willingness to pay higher prices (
                    <xref ref-type="bibr" rid="ref47">Bozoglu et al., 2019</xref>). Conversely, when credibility is questioned, consumer scepticism increases and willingness to pay more declines (
                    <xref ref-type="bibr" rid="ref46">Bie et al., 2025</xref>; 
                    <xref ref-type="bibr" rid="ref88">Zhan et al., 2021</xref>). Overall, the literature consistently indicates that perceived credibility is a key determinant of willingness to pay more by reinforcing trust, authenticity, and consumers&#x2019; perceived ethical value.
                    <statement id="state1">
                        <label>H1:</label>
                        <p>Higher levels of perceived credibility lead to a greater willingness to pay more for sustainable products.</p>
                    </statement>
                </p>
            </sec>
            <sec id="sec9">
                <title>2.3 Green future estimation and willingness to pay more</title>
                <p>Consumers who hold more optimistic projections regarding the future state of the environment and demonstrate stronger sustainability concerns tend to assign higher value to green products and are therefore more willing to pay premium prices. Environmental concerns and perceived product quality reinforce green purchase intentions, which, in turn, have implications for consumers&#x2019; willingness to pay more (
                    <xref ref-type="bibr" rid="ref28">Nekmahmud &amp; Fekete-Farkas, 2020</xref>). In addition, consumers exhibit a higher willingness to pay for products that carry sustainability labels, indicating that a future-oriented green mindset plays an important role in shaping value perceptions and preferences (
                    <xref ref-type="bibr" rid="ref18">Huh &amp; Kim, 2024</xref>). Communication and transparency regarding sustainability practices also enhance perceived product value and strengthen willingness to pay more (
                    <xref ref-type="bibr" rid="ref85">Wongprawmas et al., 2015</xref>). Furthermore, consumer education on sustainability and the environmental consequences of purchasing decisions serves as a critical driver that reinforces green future expectations and consumers&#x2019; commitment to paying premium prices (
                    <xref ref-type="bibr" rid="ref20">Kamboj &amp; Matharu, 2021</xref>). Overall, green future estimation influences willingness to pay more because it reflects consumers&#x2019; beliefs that current consumption choices can generate positive environmental outcomes in the future.
                    <statement id="state2">
                        <label>H2:</label>
                        <p>Higher levels of green future estimation lead to a greater willingness to pay more for sustainable products.</p>
                    </statement>
                </p>
            </sec>
            <sec id="sec10">
                <title>2.4 Green advertising and willingness to pay more</title>
                <p>Green advertising is increasingly used to translate rising environmental awareness into consumers&#x2019; acceptance of price premiums. Experimental studies show that exposure to green advertising and green (vs. non-green) appeals can increase willingness to pay, largely by strengthening perceived green value, and the effect depends on how the message is framed and made more concrete (
                    <xref ref-type="bibr" rid="ref10">Guo et al., 2024</xref>; 
                    <xref ref-type="bibr" rid="ref11">Gutentag &amp; Antonia Russell, 2025</xref>; 
                    <xref ref-type="bibr" rid="ref38">Zheng et al., 2022</xref>). Willingness to pay also rises when eco-friendly ads are perceived as relevant and meaningful and when consumers are receptive to green advertising through trust-building mechanisms (
                    <xref ref-type="bibr" rid="ref9">Gotlieb, 2019</xref>; 
                    <xref ref-type="bibr" rid="ref30">Nguyen-Viet &amp; Thanh Tran, 2024</xref>). Credibility cues further support premium price acceptance, whereas skepticism toward green advertising can weaken it (
                    <xref ref-type="bibr" rid="ref2">Al Mamun et al., 2023</xref>; 
                    <xref ref-type="bibr" rid="ref29">Nguyen-Viet &amp; Nguyen, 2024</xref>).
                    <statement id="state3">
                        <label>H3:</label>
                        <p>Green advertising has a significant positive effect on consumers&#x2019; willingness to pay a premium.</p>
                    </statement>
                </p>
            </sec>
            <sec id="sec11">
                <title>2.5 Green advertising and perceived credibility</title>
                <p>Green advertising that emphasises environmental benefits can enhance brand credibility when the message is delivered transparently and honestly, and aligns with genuine sustainability practices (
                    <xref ref-type="bibr" rid="ref24">Kumar &amp; Tripathi, 2019</xref>). Advertiser characteristics can also strengthen advertising credibility; high levels of attractiveness and expertise make green messages more persuasive and enhance brand credibility in consumers&#x2019; eyes (
                    <xref ref-type="bibr" rid="ref23">Khandelwal &amp; Singh, 2023</xref>). Furthermore, hedonic involvement and emotional appeals in advertising enhance favourable attitudes toward advertisements and, in turn, contribute to the development of perceived credibility. Green cues within advertisements serve as positive signals of brand responsibility, especially when sustainability messages remain consistent across various communication channels, including social media (
                    <xref ref-type="bibr" rid="ref8">Gonzalez-Lafaysse &amp; Lapassouse-Madrid, 2016</xref>). Taken together, the literature suggests that green advertising contributes to higher perceived credibility when truthful claims, effective message sources, and coherent sustainability communication underpin it.
                    <statement id="state4">
                        <label>H4:</label>
                        <p>Green advertising has a positive and significant effect on perceived credibility.</p>
                    </statement>
                </p>
            </sec>
            <sec id="sec12">
                <title>2.6 Green advertising and green future estimation</title>
                <p>Beyond promoting environmentally friendly products, green advertising increases awareness of the environmental consequences of consumption behaviour, thereby fostering more optimistic expectations of a green future (
                    <xref ref-type="bibr" rid="ref19">Kahraman &amp; Kazan&#x00e7;o&#x011f;lu, 2019</xref>). When companies communicate their sustainability commitments effectively, consumers are more likely to believe that their support for green products contributes meaningfully to long-term environmental improvement (
                    <xref ref-type="bibr" rid="ref21">Khaireddine et al., 2023</xref>). This process is strengthened when advertising provides transparent, clear information, because credible environmental claims encourage consumers to form more optimistic expectations about future environmental outcomes (
                    <xref ref-type="bibr" rid="ref31">Prasad et al., 2017</xref>). Additionally, when advertising highlights practical benefits and fosters emotional alignment with sustainability values, consumers pay closer attention and show greater optimism about future environmental outcomes. (
                    <xref ref-type="bibr" rid="ref35">Vafaei-Zadeh et al., 2024</xref>). Thus, clear, credible, and relevant green advertising can play a critical role in reinforcing green future estimation, as it underpins consumers&#x2019; psychological orientations toward green attitudes and consumption choices.
                    <statement id="state5">
                        <label>H5:</label>
                        <p>Green advertising positively and significantly influences green future estimation.</p>
                    </statement>
                </p>
            </sec>
            <sec id="sec13">
                <title>2.7 Green advertising, perceived credibility, green future estimation, and willingness to pay more</title>
                <p>Green advertising can increase willingness to pay more (WTPM) through two complementary psychological pathways, namely perceived credibility and green future estimation. When green advertisements communicate environmental claims clearly, consistently, and transparently, consumers are more likely to perceive the brand as credible. This enhanced credibility strengthens trust in the product&#x2019;s environmental benefits and makes the acceptance of premium pricing more justifiable (
                    <xref ref-type="bibr" rid="ref1">Akturan, 2020</xref>; 
                    <xref ref-type="bibr" rid="ref24">Kumar &amp; Tripathi, 2019</xref>; 
                    <xref ref-type="bibr" rid="ref31">Prasad et al., 2017</xref>; 
                    <xref ref-type="bibr" rid="ref32">Rahman &amp; Nguyen-Viet, 2023</xref>). At the same time, green advertising can reinforce consumers&#x2019; beliefs that their current consumption choices contribute to improved environmental conditions in the future. As a result, the long-term value of green products is perceived as higher, which in turn encourages a greater willingness to pay more (
                    <xref ref-type="bibr" rid="ref18">Huh &amp; Kim, 2024</xref>; 
                    <xref ref-type="bibr" rid="ref20">Kamboj &amp; Matharu, 2021</xref>; 
                    <xref ref-type="bibr" rid="ref28">Nekmahmud &amp; Fekete-Farkas, 2020</xref>). Therefore, green advertising serves not merely as a promotional message but also as a catalyst for trust and future-oriented optimism, which explains why consumers are willing to pay a premium for environmentally friendly products (
                    <xref ref-type="bibr" rid="ref1">Akturan, 2020</xref>; 
                    <xref ref-type="bibr" rid="ref37">Zabkar &amp; Hosta, 2012</xref>).
                    <statement id="state6">
                        <label>H6:</label>
                        <p>The effect of green advertising on willingness to pay more is mediated by perceived credibility.</p>
                    </statement>

                    <statement id="state7">
                        <label>H7:</label>
                        <p>Green future estimation serves as a mediating mechanism through which green advertising influences willingness to pay more.</p>
                    </statement>
                </p>
            </sec>
        </sec>
        <sec id="sec14" sec-type="methods">
            <title>3. Methods</title>
            <sec id="sec15">
                <title>3.1 Sample and procedure</title>
                <p>The present study employed a quantitative research design and collected primary data via an online questionnaire. The target respondents were consumers who had prior experience purchasing environmentally friendly products, such as eco-friendly packaging, natural soaps, recycled tissue products, reusable plastic bags or bottles, LED lighting, and food products manufactured using environmentally sustainable processes. A convenience sampling technique was applied. In total, 500 questionnaires were distributed directly to consumers who were connected to MSMEs operating in the East Nusa Tenggara Province (Nusa Tenggara Timur, NTT), Indonesia. These consumers were selected because they are considered potential agents of change in promoting the adoption of environmentally friendly products, particularly sustainable packaging made from 
                    <italic toggle="yes">lontar</italic> leaves. In addition, NTT specifically Kupang City, was chosen as the study location due to the high concentration of MSMEs that utilise 
                    <italic toggle="yes">lontar</italic>-based materials, making the region a relevant and contextually rich setting for examining consumer responses to sustainable packaging initiatives (
                    <xref ref-type="bibr" rid="ref4">Dadag, 2024</xref>).</p>
                <p>After data screening, 401 valid responses were retained from the 500 distributed questionnaires for analysis. The screening procedure involved a set of preliminary questions designed to ensure respondents&#x2019; relevance to the research context. Specifically, respondents were asked: (1) whether they had previously purchased environmentally friendly products; (2) whether they paid attention to the materials used in products during purchase decisions; and (3) whether they had purchased and used product packaging made from 
                    <italic toggle="yes">lontar</italic> leaves or similar natural materials. Only respondents who confirmed prior experience in purchasing environmentally friendly products and demonstrated awareness of sustainable packaging materials were allowed to proceed to the main questionnaire. As a result, 401 respondents met the inclusion criteria and constituted the final sample for analysis. This sample size is considered adequate for the analytical approach employed in this study. 
                    <xref ref-type="bibr" rid="ref13">Hair et al. (2020)</xref> the minimum sample size was determined using the ten-times rule, which suggests a sample size of at least 10 times the number of indicators used in the model. In this study, the measurement model comprised 11 indicators; therefore, the minimum required sample size was 110 respondents.</p>
                <p>Ultimately, 401 valid responses were obtained and used for data analysis, representing a response rate of approximately 82%. A descriptive analysis was conducted to provide an overview of respondents&#x2019; socio-demographic characteristics. As presented in 
                    <xref ref-type="table" rid="T1">
Table 1</xref>, 56% of the respondents (n&#x00a0;=&#x00a0;224) were female, while 44% (n&#x00a0;=&#x00a0;177) were male. In the context of NTT, female consumers tend to engage more frequently in shopping activities than male consumers, as women in Kupang city are more commonly responsible for managing daily and household needs. This distribution of roles results in a higher observed shopping frequency among women than among men.</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>
Table 1. </label>
                    <caption>
                        <title>Demographic profile of participants (n&#x00a0;=&#x00a0;401).</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Variable</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Category</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Frequency</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Percentage (%)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Gender</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Female</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">224</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">56</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">Male</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">177</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">44</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>401</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>100</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Age</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt; 20&#x00a0;years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">53</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">20&#x2013;29&#x00a0;years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">149</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">37</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">30&#x2013;39&#x00a0;years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">132</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">40&#x2013;49&#x00a0;years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">44</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2265; 50&#x00a0;years</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>401</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>100</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="5" valign="top">
                                    <bold>Educational attainment</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">High school</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">136</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">34</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Diploma</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Bachelor&#x2019;s degree</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">186</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">46</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Master&#x2019;s/Doctoral degree</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>401</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>100</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Occupation</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Student</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">65</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">Housewife</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">Public/Private servants</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">147</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">37</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">Entrepreneur</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">Other</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">67</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>401</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>100</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Monthly</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">&lt; IDR1,000,000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">53</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">IDR 1,000,000&#x2013;IDR 2,999,999</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">70</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">IDR 3,000,000&#x2013;IDR 4,999,999</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">123</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">31</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">IDR 5,000,000&#x2013;IDR 6,999,999</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">89</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt; IDR 7,000,000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">66</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>401</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>100</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="5" valign="top">
                                    <bold>Frequency buying sustainability product in the last 3&#x00a0;months</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Never</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1&#x2013;2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">3&#x2013;5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">205</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">51</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt;5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">103</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">26</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>401</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>100</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec16">
                <title>3.2 Measurement scale</title>
                <p>The measurement model was evaluated using partial least squares structural equation modelling (PLS-SEM) in SmartPLS. PLS-SEM is a widely applied statistical technique for examining complex relationships among latent variables, which makes it particularly suitable for predictive-oriented research objectives (
                    <xref ref-type="bibr" rid="ref12">Hair et al., 2017</xref>). Screening questions were included in the questionnaire to ensure that only respondents with prior experience purchasing environmentally friendly products were included in the study. In addition, all measurement items were adapted to the local context of 
                    <italic toggle="yes">lontar</italic>-leaf packaging products and were translated using a back-translation procedure to ensure linguistic accuracy and conceptual equivalence.</p>
                <p>Construct reliability and validity were assessed using Cronbach&#x2019;s alpha, Composite Reliability (CR), and Average Variance Extracted (AVE). The results indicate that all constructs demonstrate satisfactory reliability, with Cronbach&#x2019;s alpha and CR values exceeding the recommended threshold of 0.70, and adequate convergent validity, as evidenced by AVE values above 0.50. Discriminant validity was further evaluated using the Fornell&#x2013;Larcker criterion and the heterotrait&#x2013;monotrait (HTMT) ratio. The findings confirm that each construct is empirically distinct from the others (
                    <xref ref-type="bibr" rid="ref6">Fornell &amp; Larcker, 1981</xref>; 
                    <xref ref-type="bibr" rid="ref16">Henseler et al., 2015</xref>). All indicators exhibit outer loadings above the recommended threshold of 0.70, indicating that the measurement items are appropriate and internally consistent in capturing their respective constructs. The highest loading is observed for green future estimation (GFE1&#x00a0;=&#x00a0;0.910), while the lowest loading appears for green advertising (GA3&#x00a0;=&#x00a0;0.852); nevertheless, both values remain well within acceptable PLS-SEM standards. In addition, all variance inflation factor (VIF) values are well below the threshold of 5, suggesting no multicollinearity issues.</p>
                <p>
                    <xref ref-type="table" rid="T2">
Table 2</xref> summarises the results of the reliability and validity assessments. Overall, the measurement model demonstrates adequate robustness and is suitable for proceeding to the structural model evaluation, particularly for examining the relationships among green advertising (GA), green future estimation (GFE), perceived credibility (PC), and willingness to pay more (WTPM).</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>
Table 2. </label>
                    <caption>
                        <title>Reliability and validity test.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Code</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Items</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Factor loadings</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">AVE</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">&#x221d;</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">CR</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
VIF</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">Green Advertising (
                                    <xref ref-type="bibr" rid="ref15">Hasrama et al., 2025</xref>)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Advertising about 
                                    <italic toggle="yes">lontar</italic>-leaf packaging shows that producers/MSMEs pay attention to consumers&#x2019; environmental concerns</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.884</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.758</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.841</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.904</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.175</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Advertising about 
                                    <italic toggle="yes">lontar</italic>-leaf packaging emphasises the environmentally friendly aspects of 
                                    <italic toggle="yes">lontar</italic> packaging</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.876</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.306</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Advertising about 
                                    <italic toggle="yes">lontar</italic>-leaf packaging provides clear information on why 
                                    <italic toggle="yes">lontar</italic>-leaf packaging is considered environmentally friendly</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.852</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.374</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">Green Future Estimation (
                                    <xref ref-type="bibr" rid="ref28">Nekmahmud &amp; Fekete-Farkas, 2020</xref>)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">GFE1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Environmentally friendly products (including 
                                    <italic toggle="yes">lontar</italic>-leaf packaging) will become popular in our country</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.910</td>
                                <td align="char" char="." colspan="1" rowspan="2" valign="top">0.825</td>
                                <td align="char" char="." colspan="1" rowspan="2" valign="top">0.788</td>
                                <td align="char" char="." colspan="1" rowspan="2" valign="top">0.904</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.143</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">GFE2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Consumers will embrace the future of environmentally friendly products (including 
                                    <italic toggle="yes">lontar</italic>-leaf packaging)</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.907</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.630</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">Perceived Credibility (
                                    <xref ref-type="bibr" rid="ref7">Gomes et al., 2023</xref>)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PC1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Advertising for environmentally friendly 
                                    <italic toggle="yes">lontar</italic>-leaf packaging accurately conveys the environmental benefits of using such packaging</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.902</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.781</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.860</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.914</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.623</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PC2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Small and medium enterprises (SMEs) that advertise 
                                    <italic toggle="yes">lontar</italic>-leaf packaging have a genuine intention to protect the environment</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.871</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.538</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PC3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">I am confident that the environmental claims presented in advertisements for 
                                    <italic toggle="yes">lontar</italic>-leaf packaging are true</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.878</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.514</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="6" rowspan="1" valign="top">Willingness to pay more (
                                    <xref ref-type="bibr" rid="ref5">Fauzi et al., 2024</xref>)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">WTPM1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">I am willing to pay more to purchase products that use environmentally friendly 
                                    <italic toggle="yes">lontar</italic>-leaf packaging.</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.874</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.750</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.833</td>
                                <td align="char" char="." colspan="1" rowspan="3" valign="top">0.900</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,991</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">WTPM2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Paying more for products with 
                                    <italic toggle="yes">lontar</italic>-leaf packaging is reasonable in order to protect the environment</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.869</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,967</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">WTPM3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">I do not mind paying more if the product is packaged using natural, environmentally friendly materials such as 
                                    <italic toggle="yes">lontar</italic>
</td>
                                <td align="char" char="." colspan="1" rowspan="1" valign="top">0.855</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,841</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Source: Author&#x2019;s creation.</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>

                    <bold>3.2.1 Fornell-Larcker criterion</bold>
                </p>
                <p>The Fornell&#x2013;Larcker criterion was used to assess discriminant validity by comparing the square roots of the Average Variance Extracted (AVE) for each construct (diagonal values) with the inter-construct correlations (off-diagonal values). As shown in 
                    <xref ref-type="table" rid="T3">
Table 3</xref>, the diagonal values for all constructs (bolded) exceed the corresponding correlations within the same rows and columns. This result indicates that each construct explains its own indicators more strongly than it relates to other constructs, thereby confirming adequate discriminant validity (
                    <xref ref-type="bibr" rid="ref6">Fornell &amp; Larcker, 1981</xref>).</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>
Table 3. </label>
                    <caption>
                        <title>Fornell-Larcker criterion.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Latent variable</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">1</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">2</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">3</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
4</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1. GA</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.871</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">2. GFE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.690</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.908</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">3. PC</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.708</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.601</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.884</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">4. WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.587</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.651</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.670</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.866</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>

                            <italic toggle="yes">Note:</italic> The diagonal elements (shown in bold) represent the square roots of the AVE, while the off-diagonal elements represent the correlations.</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>For example, the square root of the AVE for WTPM is 0.866, which exceeds its correlations with GA (0.587), GFE (0.651), and the other constructs in the model. Therefore, the measurement model satisfies the requirements for discriminant validity, indicating that all constructs are empirically distinct and have been measured appropriately in this study.</p>
                <p>

                    <bold>3.2.2 HTMT criterion</bold>
                </p>
                <p>The heterotrait&#x2013;monotrait (HTMT) ratio was employed to further assess discriminant validity by examining inter-construct correlations. 
                    <xref ref-type="table" rid="T4">
Table 4</xref> presents the HTMT results. All HTMT values in this study fall below the conservative threshold of 0.85. The highest HTMT value is 0.848, observed between GA and GFE. These findings indicate that each construct is empirically distinguishable from the others, thereby providing additional support for discriminant validity (
                    <xref ref-type="bibr" rid="ref16">Henseler et al., 2015</xref>).</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>
Table 4. </label>
                    <caption>
                        <title>HTMT criterion.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Latent variable</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">1</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">2</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">3</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
4</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1. GA</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">2. GFE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.848</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">3. PC</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.832</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.729</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">4. WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.701</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.804</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.790</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>In addition, the lowest HTMT value, which occurs between WTPM and GA (0.701), also remains well within the acceptable range. Therefore, the HTMT criterion confirms discriminant validity, indicating that the latent constructs in this study are distinct from one another both conceptually and statistically.</p>
            </sec>
        </sec>
        <sec id="sec17">
            <title>4. Findings</title>
            <sec id="sec18">
                <title>4.1 Structural model assessment</title>
                <p>The structural model was employed to examine the hypothesised relationships among latent variables within the conceptual framework, using the PLS-SEM approach. In this study, the structural model evaluates both direct and indirect effects among the key constructs, including independent, dependent, and mediating variables (
                    <xref ref-type="bibr" rid="ref14">Hair et al., 2019</xref>, 2017). Path coefficients indicate the direction and strength of the relationships among constructs, whereas the coefficient of determination (R
                    <sup>2</sup>) reflects the proportion of variance in each endogenous variable explained by its predictors. Higher R
                    <sup>2</sup> values indicate greater model explanatory power. The statistical significance of each path was assessed using p-values or t-statistics obtained through bootstrapping. Mediation effects were evaluated by examining indirect effects, while moderation effects were assessed through interaction terms.</p>
                <p>
                    <xref ref-type="table" rid="T5">
Table 5</xref> reports the R
                    <sup>2</sup> values, which indicate the proportion of variance in each dependent variable explained by its predictors. WTPM shows an R
                    <sup>2</sup> value of 0.546, indicating that the model explains 54.6% of the variance in WTPM and demonstrates strong predictive power. In contrast, PC has an R
                    <sup>2</sup> value of 0.501, suggesting that the model accounts for 50.1% of the variance in PC and that additional factors outside the current framework may play a substantial role in shaping credibility perceptions. GFE yields an R
                    <sup>2</sup> of 0.476, indicating that the model explains 47.6% of the variance. The moderate R
                    <sup>2</sup> for GFE indicates that the included predictors, such as green advertising, may not fully capture the primary determinants of green future estimation in the context of environmentally friendly packaging. These findings further suggest that GFE may function more prominently as an intervening construct, strengthening relationships among key variables, while also serving as an endogenous variable directly influenced by other constructs in the model.</p>
                <table-wrap id="T5" orientation="portrait" position="float">
                    <label>
Table 5. </label>
                    <caption>
                        <title>R-Square.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Variables</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">R-square
</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
R-square adjusted</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">GFE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.476</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.475</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PC</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.501</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.500</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.546</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.543</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>From a methodological perspective, the relatively lower R
                    <sup>2</sup> value for PC does not undermine the model&#x2019;s overall robustness, as both WTPM (R
                    <sup>2</sup>&#x00a0;=&#x00a0;0.546) and PC (R
                    <sup>2</sup>&#x00a0;=&#x00a0;0.501) demonstrate adequate explanatory power. Nevertheless, these results signal that future research should extend the nomological network of credibility by incorporating additional constructs, such as trust, attitudes, source attractiveness, and social awareness. Expanding the theoretical framework in this way would provide a more comprehensive explanation of credibility formation and enhance the model&#x2019;s predictive capability regarding PC.</p>
            </sec>
            <sec id="sec19">
                <title>4.2 Hypothesis testing and mediation effects</title>
                <p>Hypothesis testing was conducted using PLS-SEM to examine the direct effects among the model&#x2019;s constructs. A structural path was considered statistically significant when the p-value was below 0.05, and the t-statistic exceeded 1.96. The results indicate that PC has a positive and significant effect on WTPM (&#x03b2;&#x00a0;=&#x00a0;0.425, t&#x00a0;=&#x00a0;8.129, p&#x00a0;&lt;&#x00a0;.001), which supports the proposed hypothesis. GFE also exerts a positive and significant influence on WTPM (&#x03b2;&#x00a0;=&#x00a0;0.380, t&#x00a0;=&#x00a0;7.522, p&#x00a0;&lt;&#x00a0;.001). In contrast, GA does not have a significant direct effect on WTPM (&#x03b2;&#x00a0;=&#x00a0;0.024, t&#x00a0;=&#x00a0;0.414, p&#x00a0;=&#x00a0;.679). However, GA shows a strong and significant effect on PC (&#x03b2;&#x00a0;=&#x00a0;0.708, t&#x00a0;=&#x00a0;15.901, p&#x00a0;&lt;&#x00a0;.001) and on green future estimation (&#x03b2;&#x00a0;=&#x00a0;0.690, t&#x00a0;=&#x00a0;17.092, p&#x00a0;&lt;&#x00a0;.001). A summary of these direct effects is presented in 
                    <xref ref-type="table" rid="T6">
Table 6</xref>.</p>
                <table-wrap id="T6" orientation="portrait" position="float">
                    <label>
Table 6. </label>
                    <caption>
                        <title>Summary of hypotheses testing.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Hypothesis</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Path</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Original Sample (O)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Sample Mean (M)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Standard Deviation (STDV)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
T Statistics (|O/STDEV|)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
P values</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Result</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="8" rowspan="1" valign="top">Direct Effect</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">PC&#x2794;WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.425</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.428</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.052</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.129</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Accepted</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">GFE&#x2794;WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.380</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.377</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.050</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.522</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Accepted</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA&#x2794;WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.024</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.020</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.058</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.414</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.679</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Declined</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA&#x2794;PC</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.708</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.708</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.045</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15.901</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Accepted</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA&#x2794;GFE</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.690</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.688</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.040</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.092</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Accepted</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="8" rowspan="1" valign="top">Indirect Effect</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA&#x2794;PC&#x2794;WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.301</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.303</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.046</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6.502</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Accepted</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">H7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">GA&#x2794;GFE&#x2794;WTPM</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.262</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.260</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.038</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6.988</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Accepted</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Source: Author&#x2019;s creation.</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>The indirect effect along the GA&#x00a0;&#x2192;&#x00a0;PC&#x00a0;&#x2192;&#x00a0;WTPM pathway is statistically significant (&#x03b2;&#x00a0;=&#x00a0;0.301, t&#x00a0;=&#x00a0;6.502, p&#x00a0;&lt;&#x00a0;.001), which indicates that perceived credibility serves as an important mechanism through which green advertising influences willingness to pay more. When green advertising intensifies, consumers tend to perceive the brand as more credible, and this enhanced credibility increases their readiness to accept premium prices. In a similar manner, the indirect effect of green advertising on willingness to pay more through green future estimation is also significant (GA&#x00a0;&#x2192;&#x00a0;GFE&#x00a0;&#x2192;&#x00a0;WTPM; &#x03b2;&#x00a0;=&#x00a0;0.262, t&#x00a0;=&#x00a0;6.988, p&#x00a0;&lt;&#x00a0;.001). This finding suggests that stronger green advertising fosters more optimistic expectations of future environmental benefits, which, in turn, encourage consumers to pay more for environmentally friendly products.</p>
            </sec>
        </sec>
        <sec id="sec20" sec-type="discussion">
            <title>5. Discussion</title>
            <p>First, the PLS-SEM results indicate that PC has a positive and statistically significant effect on WTPM (&#x03b2;&#x00a0;=&#x00a0;0.425, t&#x00a0;=&#x00a0;8.129, p&#x00a0;&lt;&#x00a0;.001), as summarised in 
                <xref ref-type="table" rid="T6">
Table 6</xref>, confirming that the PC&#x00a0;&#x2192;&#x00a0;WTPM path is statistically robust. This finding aligns with and extends prior literature by clarifying how credibility drives consumers&#x2019; willingness to pay a premium for green products. It is consistent with 
                <xref ref-type="bibr" rid="ref1">Akturan (2020)</xref>, who shows that brand credibility supports pay-premium behavior and underscores the importance of expertise and trustworthiness in making green claims believable. In both studies, credibility helps justify the premium price by reducing doubts about green claims; however, while Akturan adopts a brand-based lens across product involvement levels, the present study suggests that for locally embedded natural materials such as 
                <italic toggle="yes">lontar</italic> leaves, credibility can be an even stronger trigger of WTPM. Moreover, 
                <xref ref-type="bibr" rid="ref20">Kamboj and Matharu (2021)</xref> highlight that WTPM reflects consumers&#x2019; cognitive foundations (e.g., perceived effectiveness, attitudes, and knowledge). Accordingly, in 
                <italic toggle="yes">lontar</italic>-leaf packaging, credibility emerges as a key gateway through which sustainability claims are accepted as genuine value rather than an added marketing cost.</p>
            <p>Second, the structural model results indicate that GFE has a positive and statistically significant effect on WTPM for environmentally friendly 
                <italic toggle="yes">lontar</italic>-leaf packaging (&#x03b2;&#x00a0;=&#x00a0;0.380, t&#x00a0;=&#x00a0;7.522, p&#x00a0;&lt;&#x00a0;.001), as shown in 
                <xref ref-type="table" rid="T6">
Table 6</xref>. This finding suggests that a future-oriented green outlook leads consumers to view the price premium as an &#x201c;investment&#x201d; in long-term environmental benefits rather than merely an added cost. The result aligns with 
                <xref ref-type="bibr" rid="ref28">Nekmahmud and Fekete-Farkas (2020)</xref>, who show that positive expectations about the future of green practices/marketing encourage green consumption decisions, and the present study extends this logic by demonstrating that such beliefs can also translate into a WTPM. In addition, the finding is consistent with the green signaling perspective, which views green choices as signals of prosocial commitment that increase acceptance of added value; accordingly, consumers are more willing to accept a premium price when they link their choice to a better environmental future (
                <xref ref-type="bibr" rid="ref18">Huh &amp; Kim, 2024</xref>). In the context of 
                <italic toggle="yes">lontar</italic>-leaf packaging, GFE helps consumers interpret plastic-waste reduction and long-term ecosystem impacts as tangible benefits that justify the additional cost.</p>
            <p>Third, contrary to H3, the results show that GA does not have a significant direct effect on WTPM. This finding differs from evidence reported in China, where controlled experimental designs often capture stronger advertising effects on premium-price outcomes. For instance, 
                <xref ref-type="bibr" rid="ref10">Guo et al. (2024)</xref> demonstrate that green advertising can increase pro-environmental willingness to pay, particularly when message framing (e.g., loss/negative framing) heightens consumers&#x2019; evaluation of environmental consequences, suggesting that GA is more likely to shift payment decisions when the stimulus is deliberately designed to make environmental trade-offs salient. Likewise, 
                <xref ref-type="bibr" rid="ref38">Zheng et al. (2022)</xref> show that GA appeals increase WTPM for green food products in China, especially when advertising helps reduce information asymmetry and is supported by institutional cues such as recognized green marks/labels, which make the &#x201c;green&#x201d; attribute easier to trust and price into the decision. In contrast, in NTT, 
                <italic toggle="yes">
lontar</italic>-leaf packaging is relatively familiar in everyday life. In such a setting, advertising exposure may function mainly as a reminder rather than a source of new value creation, so advertising alone is unlikely to trigger the financial sacrifice implied by paying a premium.</p>
            <p>Fourth, the trust-based mediation pathway (GA&#x00a0;&#x2192;&#x00a0;PC&#x00a0;&#x2192;&#x00a0;WTPM) suggests that consumers view a price premium for 
                <italic toggle="yes">lontar</italic>-leaf packaging as justifiable only when green advertising strengthens the credibility of sustainability claims. This aligns with 
                <xref ref-type="bibr" rid="ref1">Akturan (2020)</xref>, who shows that brand credibility drives pay-premium behavior by reducing perceived risk and doubt, and with 
                <xref ref-type="bibr" rid="ref24">Kumar and Tripathi (2019)</xref>, who indicate that credibility often influences behavioral intentions indirectly through shifts in evaluations and attitudes. The importance of credibility is especially salient in the 
                <italic toggle="yes">lontar</italic> context, as GA in developing country settings frequently relies on ambiguous, hard-to-verify credence claims and limited certification or labeling, which heightens skepticism and greenwashing concerns (
                <xref ref-type="bibr" rid="ref31">Prasad et al., 2017</xref>). Accordingly, the mediation effect of PC indicates that GA supports premium-price acceptance only when its claims are clear, consistent, and verifiable, enabling consumers to perceive the premium as genuine value rather than an added marketing cost.</p>
            <p>Lastly, the future-oriented mediation pathway (GA&#x00a0;&#x2192;&#x00a0;GFE&#x00a0;&#x2192;&#x00a0;WTPM) suggests that educational and emotionally engaging green advertising helps consumers connect 
                <italic toggle="yes">lontar</italic>-leaf packaging with long-term environmental benefits, leading them to perceive the price premium as an &#x201c;investment&#x201d; in a better future. Investment is consistent with 
                <xref ref-type="bibr" rid="ref7">Gomes et al. (2023)</xref>, who report that GFE positively influences WTPM, indicating that future-oriented green beliefs raise the perceived value of green products. It also aligns with 
                <xref ref-type="bibr" rid="ref37">Zabkar and Hosta (2012)</xref>, who argue that pro-environmental behavior develops from concern to willingness and is activated by information, while green consumption often requires sacrifice (higher costs) and thus depends on perceived benefits, including future outcomes and social meaning. Accordingly, the GFE pathway in this study reinforces the view that green advertising can mobilize WTPM not through direct price persuasion, but by strengthening consumers&#x2019; belief that choosing 
                <italic toggle="yes">lontar</italic> today contributes to better environmental outcomes in the future, making the premium more acceptable when those long-term benefits feel tangible and worthwhile.</p>
        </sec>
        <sec id="sec21">
            <title>6. Implications</title>
            <p>The findings of this study confirm that GA enhances WTPM primarily by improving PC and GFE. Accordingly, marketing campaigns for 
                <italic toggle="yes">lontar</italic>-leaf packaging should present specific, consistent evidence, such as biodegradability, production processes, and estimated reductions in plastic use, alongside narratives highlighting the long-term environmental impacts on digital platforms (
                <xref ref-type="bibr" rid="ref1">Akturan, 2020</xref>; 
                <xref ref-type="bibr" rid="ref24">Kumar &amp; Tripathi, 2019</xref>; 
                <xref ref-type="bibr" rid="ref32">Rahman &amp; Nguyen-Viet, 2023</xref>). To prevent trust erosion arising from suspicions of greenwashing, environmental claims must be transparent and verifiable, for example, through sustainability badges or labels and third-party endorsements (
                <xref ref-type="bibr" rid="ref43">Bairrada et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref60">Knight et al., 2021</xref>; 
                <xref ref-type="bibr" rid="ref77">Shojaei et al., 2024</xref>). From a policy perspective, ecosystem strengthening should focus on establishing minimum standards for sustainability claims and labelling, complemented by incentives and sustainability-oriented digital literacy training for MSMEs, ensuring that green communication remains ethical and credible.</p>
        </sec>
        <sec id="sec22">
            <title>7. Limitations and future direction</title>
            <p>This study has several limitations that also point to avenues for future research. First, the data were collected using a cross-sectional design and self-reported questionnaires, which limits the strength of causal inferences and may be subject to response bias. Future studies could adopt longitudinal or experimental designs and incorporate behavioural data, such as actual purchase records or product-choice data from e-commerce platforms, to strengthen causal inference. Second, the research context is limited to consumers in Indonesia and to eco-friendly packaging made from 
                <italic toggle="yes">lontar</italic> leaves. As a result, the findings may not be directly generalisable to other types of green packaging or to different national contexts. Subsequent research should consider cross-regional or cross-country comparisons and examine differences across consumer segments, such as age, income, and levels of environmental literacy. Third, the relatively modest R
                <sup>2</sup> values for perceived credibility and green future estimation suggest that additional explanatory variables remain unaccounted for. Future studies may extend the model by incorporating factors such as eco-literacy, environmental concern, perceived greenwashing, or trust in institutions. Researchers may also explore moderating variables, such as scepticism toward green claims or consumer involvement in environmental issues, to assess whether the proposed relationships vary across groups. Finally, green advertising in this study was measured as a general perception without distinguishing between message formats or content. Given that media type, message framing (rational versus emotional), and the use of local cultural narratives may lead to different consumer responses, future research is encouraged to employ real advertising stimuli and experimental designs to identify which elements of green advertising are most effective in enhancing perceived credibility, green future estimation, and willingness to pay a premium for 
                <italic toggle="yes">lontar</italic>-leaf packaging.</p>
        </sec>
        <sec id="sec23" sec-type="conclusion">
            <title>8. Conclusion</title>
            <p>This study demonstrates that green advertising, perceived credibility, and green future estimation play key roles in shaping WTPM for eco-friendly packaging made from 
                <italic toggle="yes">lontar</italic> leaves in NTT. The PLS-SEM results confirm that GA does not exert a direct effect on WTPM, but operates indirectly by enhancing PC and strengthening projections of a greener environmental future. Both PC and GFE significantly increase WTPM, which shows that consumers are willing to pay a price premium when they trust a brand&#x2019;s sustainability claims and believe that their consumption choices generate positive environmental impacts. At the same time, GA contributes to the reinforcement of PC, GFE, and WTPM, and this result indicates that the overall model has adequate explanatory power.</p>
        </sec>
        <sec id="sec24">
            <title>Ethics and consent</title>
            <p>To ensure compliance with research ethics and educational regulations, this research was officially approved by the research institution and the Institute for Research and Community Service of Widya Mandira Catholic University No. 002/WM.H9/LPPM/SKKEP/VIII/2025. Official research permission has been granted, and the authorization letter is publicly accessible through its DOI link: 
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.19366187">https://doi.org/10.5281/zenodo.19366187</ext-link>. All participants were informed about the purpose of the study prior to data collection, and informed consent was obtained from all participants. For participants under the age of 20, consent was also obtained from their parents or legal guardians. The consent was provided in written form, and participants were assured of the confidentiality and anonymity of their responses.</p>
        </sec>
    </body>
    <back>
        <sec id="sec27" sec-type="data-availability">
            <title>Data availability statement</title>
            <p>The dataset underlying the research have been deposited in Zenodo and are accessible at: 
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.19366058">https://doi.org/10.5281/zenodo.19366058</ext-link> (CC0 license) under the title &#x201c;List of Data- The Impact of Green Advertising and the Mediating Role of Perceived Credibility on Consumers&#x2019; Purchase of 
                <italic toggle="yes">
Lontar</italic>
-leaf packaging products in Indonesia&#x201d; (
                <xref ref-type="bibr" rid="ref26">Lopes Amaral, M. A., 2026a</xref>), include all supplementary files:</p>
            <p>Supplementary Figure 1: Research Model.</p>
            <p>Supplementary Table 1:Demographic profile of participants (n&#x00a0;=&#x00a0;401).</p>
            <p>Supplementary Table 2: Reliability and validity test.</p>
            <p>Supplementary Table 3: Fornell-lacker Criterion.</p>
            <p>Supplementary Table 4: HTMT Criterion.</p>
            <p>Supplementary Table 5: R-Square.</p>
            <p>Supplementary Table 6:Summary of hypotheses testing.</p>
            <p>Data are available under the terms of the 
                <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">Creative Commons Zero &#x201c;No rights reserved&#x201d; data waiver</ext-link> (CC0 1.0 Public domain dedication).</p>
            <sec id="sec28">
                <title>Extended data</title>
                <p>Extended data including the questionnaire and data processing results are available in Zenodo repository: 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.19365983">https://doi.org/10.5281/zenodo.19365983</ext-link> (
                    <xref ref-type="bibr" rid="ref27">Lopes Amaral, M. A., 2026b</xref>).</p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">Creative Commons Zero &#x201c;No rights reserved&#x201d; data waiver</ext-link> (CC0 1.0 Public domain dedication).</p>
            </sec>
        </sec>
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