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Mitigating the 'Green Premium' Barrier: How Digital Information
Richness and Material Transparency Enhance Customer Trust in
High-Priced Sustainable Products
Dwi Sandini
1
, Ifani Hariyanti
2
,Salman Topiq
3
1
A lecturer and researcher at the Faculty of Economics, ARS University, Indonesia. Her research
interests primarily focus on green marketing strategy, consumer behavior analysis, and sustainable
business development. She has published various articles concerning the economic impacts of
environmental awareness. Contact: Jl. Sekolah Internasional No.1-2, Antapani, Bandung, Indonesia.
2
AN academic at the Faculty of Information Technology, ARS University, Indonesia. Her current
research explores the implementation of information systems in modern marketing and e-commerce
adoption. She is actively involved in studying the role of digital technology in shaping consumer trust.
Contact: Jl. Sekolah Internasional No.1-2, Antapani, Bandung, Indonesia.
3
A lecturer at the Faculty of Information Technology, ARS University, Indonesia. His expertise lies in
data analytics and the application of signaling theory within digital marketplaces. He is currently
investigating how digital artifacts can reduce information asymmetry in online transactions.
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.150600275
Received: 18 July 2026; Accepted: 23 July 2026; Published: 03 August 2026
ABSTRACT
The global paradigm shift towards sustainable consumption is frequently hindered by the "Green Premium" the
additional cost associated with eco-friendly products. While classical economic theory suggests that high prices
deter purchase intention, this study posits that in the digital marketplace, the primary barrier is information
asymmetry, not merely price. Integrating Signaling Theory and the Information Systems (IS) Success Model,
this research investigates how the quality of information provided by e-commerce platforms moderates the
negative relationship between price and customer trust. We analyzed a secondary dataset of 3,587 eco-friendly
products from Amazon, employing text mining techniques to quantify "Information Granularity" (description
depth) and "Material Transparency." The findings reveal a paradox: while higher prices generally diminish
customer trust, this negative effect is significantly attenuated when the product page exhibits high information
richness. This study contributes to the literature by demonstrating that Information Systems function as a critical
validation mechanism that justifies the green premium, shifting consumer focus from cost to value.
Keywords: Green Marketing, Information Systems, Customer Trust, Green Premium, E-Commerce.
INTRODUCTION
Background of the Study
The last decade has witnessed a marked reorientation of global consumption toward sustainability: consumers
increasingly evaluate products not merely by functional attributes but by ecological and ethical performance,
leading to accelerated growth for goods marketed with Environmental, Social, and Governance (ESG) claims
relative to conventional products (Robichaud & Yu, 2021; Aminravan et al., 2025). Evidence from studies on
ethical and green consumption demonstrates that younger cohorts, particularly Generation Z and young adults,
exhibit a strong attitudinal commitment to ethical and organic purchasing, highlighting a growing market niche
for sustainably positioned offerings (Robichaud & Yu, 2021; Qi et al., 2024) . These attitudinal shifts have
significant market consequences because willingness-to-pay for environmentally preferable alternatives
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underpins many corporate and policy strategies aimed at promoting sustainable consumption (Aminravan et al.,
2025).
Despite pro-environmental attitudes reported in surveys, a well-documented attitude-behavior gap persists:
consumers frequently express a higher willingness to pay for sustainable products but often fail to act upon it
when faced with price premiums in real market situations (Aminravan et al., 2025; Robichaud & Yu, 2021). Bill
Gates' concept of the "green premium" the price differential consumers must pay to select a cleaner option,
captures this tension and highlights the economic barrier that impedes the transition to greener consumption at
scale (Aminravan et al., 2025). Empirical research on ecolabels and willingness-to-pay indicates that price
remains a decisive constraint and that the perceived credibility of claims significantly influences whether
consumers are willing to accept such premiums (Aminravan et al., 2025; Qi et al., 2024; Caliskan et al., 2024).
The expansion of e-commerce as a dominant retail channel complicates the dynamics of green consumption
because digital environments create physical and cognitive distance between buyer and product. Unlike brick-
and-mortar retail, where tactile inspection can immediately reduce uncertainty, online marketplaces often rely
on mediated representations (such as text, images, labels, and indicators), which can increase information
asymmetry and heighten consumer skepticism toward sustainability claims (Caliskan et al., 2024; Dong et al.,
2022; Deventer & Lues, 2023) . Studies indicate that information quality, system quality, and visible verification
mechanisms (including traceability features, organic labels, and credible ecolabels) directly influence perceived
value and purchase intention for green products on e-commerce platforms (Caliskan et al., 2024; Dong et al.,
2022; Deventer & Lues, 2023).
Trust emerges as a central mechanism mediating the attitude-behavior gap in digital green marketing. Multiple
streams of research converge on the proposition that online trust, composed of platform competence,
transparency of claims, and visible evidence of certification, conditions consumers' willingness to pay price
premiums for sustainable products (Caliskan et al., 2024; Dong et al., 2022). Qualitative research underscores
that a lack of transparency, inadequate integrated claim systems, and perceived incompetence of platforms can
erode both sellers' and buyers' trust, emphasizing trust as a systemic property of the marketplace rather than
merely an interpersonal attribute (Caliskan et al., 2024). Parallel studies of live-streaming commerce
demonstrate that informativeness, interactivity, telepresence, and social cues can enhance trust, which, in turn,
increases purchasing intention and continued use of platforms (Dong et al., 2022; She et al., 2024; Wang et al.,
2024) . These findings suggest that trust can be cultivated through various digital affordances.
Information systems (IS) play a dual and decisive role in resolving the green premium paradox in e-commerce.
First, the platform itself serves as a primary communication medium that substitutes for in-person verification;
high-quality information (accurate, complete, and verifiable descriptions, traceability data, and third-party
certifications) acts as a digital signal that reduces perceived risk and uncertainty (Caliskan et al., 2024; Deventer
& Lues, 2023; Dong et al., 2022). Second, interactive and experiential system features (e.g., live streaming, rich
multimedia, social proof, and advanced UI/UX) can enhance perceived credibility and telepresence, thereby
strengthening green trust and the perceived value proposition of premium green products (Dong et al., 2022;
Tian et al., 2023; Luo, 2024). Empirical models that combine system quality and information characteristics find
that these platform attributes positively influence perceived value, trust, and, ultimately, purchase or repurchase
intention for sustainable goods (Caliskan et al., 2024; Deventer & Lues, 2023; Dong et al., 2022).
Nevertheless, the literature remains fragmented across disciplinary boundaries. Marketing and consumer
behavior scholarship has extensively explored ecolabel efficacy, price sensitivity, and attitudinal determinants
of green consumption, while IS research has focused on platform usability, information quality, and trust
formation in digital contexts (Aminravan et al., 2025; Deventer & Lues, 2023; Caliskan et al., 2024). A growing
body of integrative research (including studies on live-streaming green commerce and platform information
design) suggests that combining insights from both fields can clarify whether and how digital information
richness can justify the green premium by restoring trust among skeptical consumers (Dong et al., 2022; Tian et
al., 2023; Caliskan et al., 2024). For instance, studies show that when platforms deliver high informational and
experiential quality, green trust increases, as do green purchase intentions, illustrating a pathway by which digital
affordances can translate into acceptance of pricing differentials (Dong et al., 2022; Tian et al., 2023). Further
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research using structural models and mixed methods indicates that platform characteristics (system quality,
evaluation/review systems) and product information (labels, traceability, ingredient information) jointly shape
perceived value and purchase intentions among young online consumers, reinforcing the need for
multidisciplinary approaches (Caliskan et al., 2024; Wang et al., 2024; She et al., 2024).
Finally, tools such as blockchain and verified traceability systems have been proposed as technical means to
increase the transparency and credibility of sustainability claims within supply chains, potentially reducing the
perceived green premium through enhanced trust and verifiability (Farooq et al., 2024; Aminravan et al., 2025).
Additionally, content design and review systems (balancing criticism and praise) and user-generated social cues
on platforms have been shown to influence consumer trust and evaluation processes, mediating perceptions and
responses to price differentials (raj, 2024; Syahlan et al., 2023; Caliskan et al., 2024). Together, these insights
point to a research agenda that integrates information quality, interactive features, verification technologies, and
consumer psychology to address the core research question: Can digital information richness justify the green
premium and restore customer trust lost due to high prices?
Problem Statement
The central problem addressed in this study is the interdependent and adversarial interaction among Price,
Information, and Trust in online markets for sustainable goods. Empirical and conceptual literatures indicate
that price functions simultaneously as a quality cue and as a perceived sacrifice; in green markets saturated with
unverifiable claims, premium pricing often produces cognitive dissonance that consumers resolve by demanding
external validation. The failure of many e-commerce platforms to supply sufficiently granular, verifiable product
information, what this study terms a deficient “Trust Infrastructure”, magnifies information asymmetry and
weakens the digital signals that premium green products require to compete. The remainder of this section
synthesizes the extant evidence supporting these claims, clarifies the theoretical framing used in this research,
and situates the present contribution relative to prior work.
Price as dual signal: quality cue versus sacrifice
Price operates as a heuristic cue in consumer judgment: higher prices can activate a price, quality schema that
signals superior product attributes (Pfeuffer & Phua, 2021). At the same time, when consumers suspect
unverifiable claims (for example “eco-friendly”), the same price can be interpreted through a price-sacrifice
schema i.e., as an increased financial risk that must be justified by credible evidence (Aminravan et al., 2025;
Pfeuffer & Phua, 2021). This tension underlies the “green premium” concept popularized in policy and
practitioner discourse, whereby consumers must pay more for cleaner alternatives but require trust-enhancing
signals to accept that premium (Aminravan et al., 2025; Pfeuffer & Phua, 2021).
Information asymmetry and the online context
E-commerce increases physical and cognitive distance between buyers and products, placing the burden of
verification on platform-mediated information. Research on information quality and system quality
demonstrates that inadequate or generic product descriptions amplify uncertainty and undermine website
satisfaction and behavioral intentions in online contexts (Deventer & Lues, 2023; Pfeuffer & Phua, 2021).
Studies of online marketplaces find that review content, media richness, and the presence of specific information
attributes act as trust cues that shape consumer evaluations and purchase decisions, especially for higher-priced
items (Pfeuffer & Phua, 2021; Liang et al., 2021). Hence, a lack of granular, technical, or traceability data on
product pages reduces the persuasive power of a premium price in green markets (Caliskan et al., 2024; Liang
et al., 2021).
Trust as a systemic property shaped by platform affordances
Trust in online commercial contexts is not solely interpersonal but is also grounded in platform competence,
transparency, and integrated claim systems. Qualitative inquiry among small sellers shows that perceived
platform incompetence, absence of integrated claim systems, and opacity erode trust across supply-side and
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demand-side actors (Caliskan et al., 2024). Empirical studies of live-streaming and platform commerce further
demonstrate that information quality, system quality, telepresence, and social cues jointly increase “green trust”
and, ultimately, purchase intention for eco-labelled products (Dong et al., 2022; Tian et al., 2023). These findings
indicate that trust is a mediating mechanism through which information richness and platform features can
mitigate price resistance.
The “Trust Infrastructure” deficiency
Many product listings on large marketplaces rely on summary labels or short marketing copy that omit raw
material data, technical specifications, traceability statements, or verifiable certification details. When
information systems fail to present such granular evidence, the digital signal corresponding to a premium price
becomes weak and unconvincing, causing genuine green products to lose competitive advantage not because of
inferior quality but because of insufficient informational signaling (Caliskan et al., 2024; Pfeuffer & Phua, 2021).
Research on fulfillment and deception also indicates that transparent operational metadata (e.g., fulfillment
provenance) functions as a signal that reduces blame and mitigates trust erosion when issues arise, suggesting
that similarly granular product metadata could reduce perceived risk associated with green premiums (Peinkofer
& Jin, 2023).
Theoretical framing: Signaling Theory and IS Success Model
This study situates product description and related metadata within Signaling Theory: product texts and platform
artifacts function as signals intended to reduce information asymmetry between sellers and buyers, with signal
strength determined by richness, verifiability, and observability (Pfeuffer & Phua, 2021; Liang et al., 2021;
Peinkofer & Jin, 2023). Simultaneously, the DeLone & McLean IS Success Model (operationalized here through
information quality, system quality, and service quality constructs) specifies how platform affordances determine
perceived usefulness, trust, and behavioral outcomes in information systems contexts (Deventer & Lues, 2023;
Luo, 2024). Combining these lenses allows the conceptualization of “Information Granularity” as a measurable
signaling variable embedded within IS success determinants, thereby linking the content of product descriptions
to trust formation and price sensitivity (Deventer & Lues, 2023; Luo, 2024; Pfeuffer & Phua, 2021).
Empirical and methodological rationale: using behavioral data and text mining
Prior work on green consumer behavior has predominantly used surveys, which can be subject to social
desirability bias and hypothetical bias about willingness-to-pay (Aminravan et al., 2025; Pfeuffer & Phua, 2021).
To overcome these limitations, this study proposes to analyze real-world behavioral data (Amazon ratings,
reviews, and listing metadata) and to operationalize Information Granularity via text mining metrics (e.g., word
counts, technical term density, presence of traceability terms). The value of online reviews and listing text as
behavioral and informational substrates for consumer choice is well documented: online reviews provide rich
evidence of sentiment and preferences and can be superior to survey responses for understanding actual
consumer evaluation processes, especially with respect to high-price purchases (Liang et al., 2021; Pfeuffer &
Phua, 2021). Thus, the methodological novelty lies in triangulating large-scale observational data with IS
constructs and signaling variables to explain trust and price acceptance more robustly than survey-based studies
allow (Liang et al., 2021; Tian et al., 2023).
Practical urgency and managerial relevance
If the hypothesis that improved information granularity and material transparency attenuate the negative effect
of high price on trust is supported, the implications for platform designers and green marketers are direct:
enhancing product page information (traceability, raw material data, technical specifications, third-party
verification details) and system features that highlight such information (media richness, review cues, fulfillment
provenance) should increase conversion for premium green products by strengthening the digital signals that
justify the green premium (Dong et al., 2022; Tian et al., 2023; Peinkofer & Jin, 2023). Studies of media richness
and e-commerce capabilities corroborate that interactive and information-rich presentation formats contribute
to online trust formation and willingness to buy (Luo, 2024; Kirkos, 2021).
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Research gap and novelty (synthesis)
o Methodological gap: existing literature relies heavily on surveys and experiments vulnerable to self-report
biases; this study fills that gap by employing large-scale Amazon behavioral data and text mining to observe
revealed preferences and actual consumer evaluations (Liang et al., 2021; Tian et al., 2023; Pfeuffer & Phua,
2021).
o Theoretical intersection: prior studies seldom integrate Signaling Theory (from economics) with the IS
Success Model (from information systems); this research combines these theories to reconceptualize product
descriptions as measurable signals embedded within IS quality constructs (Pfeuffer & Phua, 2021; Deventer
& Lues, 2023; Luo, 2024).
o Focus on information granularity: instead of binary indicators (label/no label), this study quantifies textual
quality (word counts, technical term density, traceability markers) and examines moderating effects on price–
trust relationships using moderated regression and SEM/ANN hybrid techniques previously applied in live
e-commerce and user-stickiness research (Wang et al., 2024; Dong et al., 2022).
Concluding statement
The problem statement therefore is: in digital green markets, premium price signals can either confer perceived
quality or generate price-sacrifice anxiety; inadequate platform Trust Infrastructure and low Information
Granularity weaken the signaling needed to justify the green premium. This research tests whether richer, more
granular, and transparently verifiable product information on e-commerce platforms increases green trust and
attenuates consumers’ negative reactions to higher prices, using behavioral Amazon data and text mining in
combination with established IS and signaling frameworks (Aminravan et al., 2025; Caliskan et al., 2024; Dong
et al., 2022; Deventer & Lues, 2023; Pfeuffer & Phua, 2021; Liang et al., 2021; Peinkofer & Jin, 2023).
LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT
Theoretical Framework
Signaling Theory in Digital Green Markets
The exchange of credence goods in online marketplaces creates a fundamental information asymmetry in which
sellers generally possess far greater knowledge of product attributes (e.g., material composition, provenance,
carbon footprint) than buyers who rely on platform-mediated representations (Zhang et al., 2025). The economic
and marketing literature conceptualizes many “green” products as credence goods whose environmental
attributes cannot be reliably verified by consumers even post-purchase, increasing skepticism and greenwashing
concerns in digital settings (Zhang et al., 2025; Hà et al., 2022). Signaling Theory provides an appropriate
explanatory lens: sellers with superior environmental performance can reduce information asymmetry by
sending observable, costly, and verifiable signals that are difficult for low-quality (greenwashing) sellers to
imitate (Pfeuffer & Phua, 2021; Zhang et al., 2025; Hà et al., 2022). In e-commerce contexts, signals may be
embedded in multiple artifacts, third-party certifications, traceability records, fulfillment metadata, and the
textual and multimedia content of product pages, each varying in visibility, verifiability, and imitation cost
(Zhang et al., 2025).
Empirical research in online commerce shows that cue-based information (e.g., detailed reviews, review volume,
content attributes of review videos) functions as trust cues that influence consumer evaluations, especially for
higher-priced items where perceived risk is greater (Pfeuffer & Phua, 2021; Liang et al., 2021). Live-streaming
studies find that information quality, telepresence, and interactivity operate as signal enhancers that increase
“green trust” and purchasing intention for green agricultural products (Dong et al., 2022; Tian et al., 2023).
Conversely, platform-level evidence indicates that unverifiable eco-claims produce heterogeneous effects
depending on platform governance and credibility: on platforms with weak credibility frameworks, unverifiable
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signals can backfire, underscoring the need for signals that are both rich and tied to credible institutional support
(Zhang et al., 2025).
Taken together, these findings imply that the digital information system is not a neutral conduit but an active
signal generator: its content richness, traceability features, and integration with verification mechanisms
determine signal strength and thus mediate the buyer’s response to premium pricing for green products (Dong
et al., 2022; Zhang et al., 2025).
DeLone and McLean IS Success Model as an Operational Lens
To operationalize signal quality within digital retailing, the DeLone & McLean IS Success Model, particularly
the Information Quality and System Quality dimensions, offers a coherent framework linking platform
affordances to user perceptions and behavioral outcomes (Deventer & Lues, 2023; Luo, 2024). Information
Quality in the IS literature is characterized by accuracy, completeness, relevance, and timeliness; in the green-
product context, we argue these translate into measurable properties such as description depth, specification
completeness, presence of traceability indicators, and third-party certification metadata, collectively termed
Information Granularity and Material Transparency in this study (Deventer & Lues, 2023; Luo, 2024). Empirical
IS research finds that information quality is a strong antecedent of trust, satisfaction, and intentions to use online
systems across contexts (university websites, sharing economy, live e-commerce), which supports mapping
granular product content to trust formation in e-commerce (Deventer & Lues, 2023; She et al., 2024; Wang et
al., 2024). Moreover, system quality and interactive affordances (e.g., live streaming, media richness) amplify
the persuasive power of information by increasing telepresence and perceived credibility, thereby strengthening
signals that reduce perceived risk (Dong et al., 2022; Wang et al., 2024; Peinkofer & Jin, 2023).
Hypothesis Development
The Green Premium and Trust Vulnerability
The Green Premium defined as the price uplift consumers face for choosing environmentally preferable
alternatives creates a dual interpretive frame in consumer cognition: price may act as a price–quality cue but
also as a price-sacrifice cue, the latter being particularly salient when claims are unverifiable (Aminravan et al.
2025; Hà et al., 2022). Experimental and field research indicates that, absent diagnostic cues, higher prices for
credence goods often increase perceived transaction risk and can lower trust because consumers lack means to
validate premium claims (Zhang et al., 2025; Hà et al., 2022). Platform studies further show that when sellers
or platforms lack transparent, integrated claim systems (e.g., fulfillment provenance, verifiable certifications),
both sellers’ and buyers’ trust erodes (Dong et al., 2022; Zhang et al., 2025). Therefore:
H1. There is a negative relationship between Product Price and Customer Trust in the context of online
sustainable products.
Justification and citations: price as a dual heuristic and the green premium concept (Aminravan et al. 2025);
empirical findings on trust erosion under unverifiability and poor platform transparency (Dong et al., 2022;
(Zhang et al., 2025) ; credence goods literature on trust dependence in such markets (Zhang et al., 2025; Hà et
al., 2022).
Information Granularity as a Trust Builder
Information Granularity operationalized as textual depth and the inclusion of sourcing, process, and technical
specifications on product pages, is hypothesized to function as a diagnostic, effortful, and partly verifiable signal.
Psychological and IS studies indicate that longer, more detailed descriptions and richer presentations reduce
cognitive uncertainty, serve as heuristics of seller effort and competence, and increase perceived information
quality and trust in online contexts (Deventer & Lues, 2023; Pfeuffer & Phua, 2021; Liang et al., 2021). Live-
streaming research corroborates that higher information quality (including content completeness) boosts green
trust and purchase intention (Dong et al., 2022) . Consequently:
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H2. Information Granularity (measured by description richness) positively influences Customer Trust.
Justification and citations: DeLone & McLean mapping of information quality to trust and usage intentions
(Deventer & Lues, 2023; Luo, 2024); cue-based trust and review-based selection studies (Pfeuffer & Phua, 2021;
Liang et al., 2021); empirical live-streaming evidence linking information quality to green trust (Dong et al.,
2022).
Material Transparency as a Validation Signal
Material Transparency denotes the explicit declaration of raw material composition (e.g., “100% organic
cotton,” supplier identity, or traceable batch codes). Such specificity functions as a “hard” signal, more objective,
verifiable, and costly to fabricate, thus lowering the incentive and feasibility of imitation by greenwashers. Prior
work shows that concrete disclosures (traceability, certification, fulfillment metadata) enhance consumer
perceptions of transparency and can reduce perceived risk, with blockchain and traceability systems frequently
cited as technological enablers of credible disclosure (Zhang et al., 2025; Zhao & Cao, 2024). Empirical findings
also suggest that explicit material claims strengthen trust and perceived product legitimacy compared to vague
eco-language (Robichaud et al., 2024; Hà et al., 2022). Hence:
H3. Material Transparency (the explicit declaration of material composition) positively influences Customer
Trust.
Justification and citations: studies on traceability, blockchain, and supply chain disclosure improving perceived
credibility and trust (Zhang et al., 2025; Zhao & Cao, 2024); consumer research on the positive effect of specific
material claims versus vague eco-terms (Robichaud et al., 2024; Hà et al., 2022).
Moderating Role of Information Richness and Material Transparency on the Price–Trust Relationship
We propose that Information Granularity and Material Transparency moderate the negative effect of Price on
Trust by strengthening the informational signal that justifies premiums. The moderating mechanism is supported
by S-O-R-oriented IS and live-ecommerce studies showing that when consumers engage in high-involvement
processing (triggered by high price), they seek diagnostic cues; richly informative and verifiable product
presentations supply such cues and therefore attenuate price-induced distrust (Dong et al., 2022; Tian et al.,
2023). Conversely, sparse or vague content will exacerbate the price-sacrifice interpretation and steepen the
negative slope between price and trust (Zhang et al., 2025). Empirical platform analyses reveal platform
heterogeneity in the efficacy of unverifiable signals, highlighting that signal richness and verifiability matter for
moderating price effects (Zhang et al., 2025). Thus:
H4. Information Granularity moderates the relationship between Price and Trust; specifically, the negative
impact of Price on Trust is weaker when Information Granularity is high.
H5. Material Transparency moderates the relationship between Price and Trust; specifically, the negative impact
of Price on Trust is weaker when Material Transparency is present.
Integrative Conceptual Model (summary)
Synthesizing Signaling Theory and the DeLone & McLean IS Success Model yields an integrative conceptual
model in which Product Price exerts a direct (negative) effect on Customer Trust (H1), while Information
Granularity (H2) and Material Transparency (H3) function as information-quality signals that build trust.
Importantly, Information Granularity (H4) and Material Transparency (H5) moderate the Price→Trust link by
supplying diagnostic, verifiable signals that attenuate the price-sacrifice interpretation and reframe the premium
as an investment in verified environmental performance. Empirical tests should operationalize these constructs
using behavioral platform data (e.g., Amazon listing metadata, review sentiment, purchase/review behavior) and
text-mining metrics (word counts, technical-term density, presence of traceability/certification tokens), and
analyze relationships via moderated regression, SEM, and hybrid ANN/SEM approaches to capture potential
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non-linearities as demonstrated in prior live-commerce and user-sticky research (Dong et al., 2022; Wang et al.,
2024).
Empirical and theoretical grounding for credence goods and information asymmetry in online green markets
(Zhang et al., 2025; Hà et al., 2022); signaling theory and cue-based trust in eWOM and product reviews
(Pfeuffer & Phua, 2021; Liang et al., 2021); DeLone & McLean IS success constructs applied to information
quality and trust in online systems (Deventer & Lues, 2023; Luo, 2024); live-streaming evidence on
information/system quality increasing green trust (Dong et al., 2022; Tian et al., 2023); platform transparency,
fulfillment metadata, and blockchain/traceability literature as verifiability enablers (Zhang et al., 2025; Zhao &
Cao, 2024); platform heterogeneity and unverifiable signals research (Zhang et al., 2025) ; practical examples
of bridging information asymmetry in sustainable clothing e-commerce (Robichaud et al., 2024).
RESEARCH METHODOLOGY
Research Design and Data Source
This study adopts a quantitative, explanatory research design to investigate the causal relationships and
moderating effects between price, information system quality, and customer trust. Unlike the majority of prior
studies in green marketing that rely on self-reported survey data (stated preference), this research leverages
actual behavioral data (revealed preference) extracted from a major e-commerce platform.
The primary data source is the "Amazon Eco-Friendly Products" dataset. This dataset was selected for its
high ecological validity, as it contains Stock Keeping Units (SKUs) explicitly categorized under the "Climate
Pledge Friendly" program, ensuring relevance to the domain of sustainable consumption.
Data Cleaning and Sampling:
The initial dataset contained 3,587 product entries. A purposive sampling technique was applied with the
following inclusion criteria:
1. The product must have a valid, non-null numerical value for Price.
2. The product must have an aggregate Star Rating and Review Count (to serve as trust and popularity
proxies).
3. The product must contain textual data in the Description field for text mining analysis.
After removing entries with missing values in key variables and filtering out outliers, the final sample size used
for analysis is N = 2,894. This sample size provides sufficient statistical power (> 0.95) for the proposed
multivariate regression analysis.
Operationalization of Variables
To test the proposed hypotheses, raw data fields were transformed into measurable research variables. The
operationalization logic is detailed below:
A. Dependent Variable: Customer Trust (Y)
In e-commerce literature, the aggregate Star Rating is widely accepted as the most robust proxy for customer
trust and post-purchase satisfaction. It represents the collective consensus of verified buyers regarding the
product's reliability and the accuracy of the seller's claims.
Measurement: Continuous variable ranging from 1.0 to 5.0.
Source: rating column.
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B. Independent Variable: Price / Green Premium (X)
This variable represents the monetary sacrifice required from the consumer. It captures the "Green Premium",
the cost barrier associated with sustainable products.
Measurement: The listed selling price in USD. Data was cleaned to remove currency symbols and formatted
as a float data type.
Source: price column.
C. Moderator 1: Information Granularity (M1)
Based on Signaling Theory, the depth of the product description serves as a costly signal of seller integrity. We
define Information Granularity as the volume of information provided by the system.
Measurement: A text mining technique was employed to extract the text from the description field and
calculate the Word Count. Higher word counts indicate higher information granularity.
Source: Feature extraction from the description column.
D. Moderator 2: Material Transparency (M2)
This variable captures the specificity of the information system regarding raw materials. It distinguishes between
vague claims and specific material disclosures (e.g., "100% Organic Cotton").
Measurement: A binary dummy variable. It is coded as 1 if the material data field is populated with specific
text, and 0 if the field is null or generic.
Source: material column.
E. Control Variable
To isolate the effect of price and information, we controlled for Product Popularity. Highly popular products
may engender trust through "social proof" regardless of price.
Measurement: The natural logarithm of the reviewsCount (Ln(Reviews)) was used to normalize the
distribution, as review counts typically follow a power-law distribution.
Analytical Strategy
The data was analyzed using Moderated Regression Analysis (MRA) to test the interaction hypotheses. To
mitigate potential multicollinearity issues arising from interaction terms, the continuous independent variable
(Price) and the moderator (Information Granularity) were mean-centered before creating the interaction terms.
The regression equation is specified as follows:
Y = β
0
+β
1
X+β
2
M+β
3
(X.M)+β
4
C+€
Where:
Y = Customer Trust (Rating)
X = Price (Green Premium)
M = Information Granularity / Material Transparency
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X.M = Interaction Term (Testing the Moderation Effect)
C = Control Variable (Log Reviews)
A Hierarchical Linear Regression approach was employed in three steps:
1. Model 1 (Direct Effects): Introduced the Control Variable and Independent Variable (Price) to test H1.
2. Model 2 (Main Effects of Moderators): Added Information Granularity and Material Transparency to test
H2 and H3.
3. Model 3 (Interaction Effects): Added the interaction terms (Price x Granularity and Price x Transparency)
to test the novelty hypotheses H4 and H5.
RESULTS AND DISCUSSION
Descriptive Statistics and Correlation Matrix
Table 1 presents the descriptive statistics and Pearson correlation coefficients for the study variables. The final
dataset consists of 2,894 observations. The average product rating is 4.12 (SD = 0.84), indicating a generally
positive skew in customer sentiment. The correlation matrix provides initial support for our hypotheses,
particularly the negative correlation between Price and Trust (r = -0.14).
Table 1. Descriptive Statistics and Correlations
Variable
Mean
SD
1
2
3
1. Customer Trust
4.12
0.84
1
2. Price (Green Premium)
34.50
21.30
-0.14**
1
3. Info. Granularity
145.20
82.10
0.28**
0.03
1
4. Material Transparency
0.65
0.47
0.19**
-0.05
0.12*
Note: N = 2,894. *p < 0.05; **p < 0.01. Values on diagonal represent unity.
Hypothesis Testing (Hierarchical Regression Analysis)
To test the direct and moderating effects, a three-step hierarchical regression analysis was conducted. The results
are summarized in Table 2.
Table 2. Hierarchical Regression Results (Dependent Variable: Customer Trust)
Predictor
Model 1 (β)
Model 2 (β)
Model 3 (β)
Controls
Popularity (Log Reviews)
0.05*
0.04
0.03
Independent Variable
Price (Green Premium)
-0.18*
-0.15**
-0.21***
Moderators (IS Quality)
Info. Granularity
0.31*
0.28***
Material Transparency
0.15*
0.14*
Interactions
Price x Granularity
0.22
Price x Transparency
0.04 (ns)
Model Fit
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R
2
0.04
0.16
0.19
∆R
2
-
0.12***
0.03**
Note: Standardized Coefficients reported. *p < 0.05, **p < 0.01, ***p < 0.001. ns = not significant.
Analysis of Table 2:
Model 1 (H1 Supported): Price has a significant negative effect on trust (β= -0.18).
Model 2 (H2 & H3 Supported): Both Information Granularity and Material Transparency directly increase
trust.
Model 3 (H4 Supported): The interaction term Price $\times$ Granularity is positive and significant (β=
0.22), indicating a buffering effect.
DISCUSSION AND VISUALIZATION
The "Green Premium" as a Trust Barrier
The findings confirm that consumers penalize high prices when information is lacking ($H1$). The negative
beta coefficient suggests that price is perceived as a sacrifice rather than a quality signal in the absence of detailed
data.
Interaction Effect Analysis (Figure 1)
To visualize the significant moderation effect found in Model 3, we plotted the relationship between Price and
Trust at two levels of Information Granularity: High (+1 SD) and Low (-1 SD).
Figure 1. Interaction Effect of Price and Information Granularity on Customer Trust
As illustrated in Figure 1:
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Red Dashed Line (Low Granularity): Shows a steep downward slope. This means for products with poor
descriptions, a higher price leads to a sharp drop in trust.
Green Solid Line (High Granularity): Shows a nearly flat or slightly positive slope. This indicates that
when the description is rich and detailed, consumers are not sensitive to price increases. The high-quality
information system successfully "explains" the value, neutralizing the negative effect of the Green
Premium.
CONCLUSION, IMPLICATIONS, AND LIMITATIONS
Conclusion
This study set out to address a critical paradox in the sustainable digital economy: the tension between the "Green
Premium" (higher prices) and the necessity of "Customer Trust." By analyzing behavioral data from 2,894 eco-
friendly products on Amazon, we integrated Signaling Theory with the IS Success Model to demonstrate how
digital information systems can resolve this tension.
The empirical results lead to three definitive conclusions. First, the "Green Premium" creates a genuine trust
barrier; without context, higher prices correlate with lower trust ratings, validating the existence of a price-
sacrifice schema in online green markets. Second, the quality of the Information System, specifically
Information Granularity (description depth) acts as a powerful trust-building mechanism. Third, and most
importantly, Information Granularity successfully moderates the negative impact of price. A detailed, data-rich
product description buffers the consumer against sticker shock, allowing high-priced sustainable products to
maintain high trust levels. This suggests that the barrier to green consumption is not solely financial, but
informational. When the system reduces information asymmetry, the price becomes justified.
Theoretical Implications
This research offers significant contributions to the intersection of Information Systems (IS) and Marketing
literature:
1. Extension of Signaling Theory to Digital Text: Traditional signaling theory focuses on warranties or brand
names as signals. This study extends the theory to "Textual Granularity." We provide empirical evidence
that the sheer volume and depth of text in an e-commerce interface function as a "High-Cost Signal." Writing
a detailed description requires effort and knowledge, which distinguishes genuine green sellers from
opportunistic greenwashers who typically use vague, short descriptions.
2. The "Information-Price" Trade-off: We introduce a nuanced understanding of the Price-Trust
relationship. Existing literature often treats price sensitivity as a static consumer trait. Our findings argue
that price sensitivity is dynamic and malleable based on the quality of the IS interface. The negative slope
of price on trust is not fixed; it can be flattened by high-quality information.
3. Differentiating IS Dimensions: By finding that Granularity (H4) moderates price sensitivity while Material
Transparency (H5) does not, we highlight distinct roles of IS features. Material transparency acts as a
"Hygiene Factor" (necessary for baseline trust but doesn't justify extra cost), whereas Granularity acts as a
"Motivator" that adds the perceived value necessary to support premium pricing.
Managerial Implications
For e-commerce platform developers and sustainable brand managers, the findings offer actionable strategies:
1. "Content is Currency": Sellers of high-priced sustainable products must view the product description field
not as a marketing afterthought, but as a critical asset. Investing in professional copywriting that elaborates
on sourcing, manufacturing processes, and technical specifications is as important as the product quality
itself. A short description on a high-priced item is a red flag for consumers.
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2. System Design for Transparency: E-commerce platforms (like Amazon, Shopee, or niche green
marketplaces) should redesign their back-end systems to force or highly encourage "Structured Data Entry"
for materials. While our study showed transparency didn't moderate price sensitivity, it had a direct positive
effect on trust. Platforms should provide specific fields for "Material Composition" rather than leaving it to
unstructured text.
3. Overcoming the Green Premium: To sell a $50 organic t-shirt vs. a $10 conventional one, the "Digital
Narrative" must fill the $40 gap. Managers should use the information system to "show their work"
explaining the supply chain complexity that drives the cost. The data shows consumers will read and will
trust if the information is there.
Limitations and Future Research
While this study provides robust insights using real-world data, it has limitations that open avenues for future
research:
1. Cross-Sectional Nature: The data represents a snapshot in time. We cannot observe how trust evolves for a
specific product over time as its price or description changes. Future research could employ longitudinal
tracking.
2. Platform Specificity: The data is limited to Amazon. Cultural nuances in other platforms (e.g., Alibaba in
China or Tokopedia in Indonesia) regarding trust and price sensitivity may differ. Comparative cross-
platform studies would be valuable.
3. Textual Analysis Depth: Our measure of "Information Granularity" relied primarily on word count and
keyword density. With advancements in Natural Language Processing (NLP), future scholars could use
Sentiment Analysis or Topic Modeling (LDA) to assess not just the quantity of text, but the semantic
quality and emotional tone of the descriptions.
4. Visual Signaling: This study focused on text. Future research should investigate the role of Visual
Information Quality (e.g., number of images, presence of certification logos in images) using Computer
Vision techniques to see if visual signals are more potent than textual ones in justifying high prices.
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