Keywords

Moral/Ethical Value, Pre-owned Goods, Seller Satisfaction, Resale Intention, Sustainable Marketing.

JEL Classification

E2, F64, P46.

Introduction

In recent years, there have been substantial modifications to the pre-owned products market. The flea market, which was previously informal, has transformed into a structured retail format and organised resale platform that is driven by technology. Numerous factors, such as economic (affordability and value), environmental (waste reduction and resource efficiency), and ethical (responsible consumption and community sharing), are the driving forces behind this transformation. Reselling has become a substantial element of the circular economy as a result of the uniqueness and affordability of pre-owned items, as well as the growing awareness of environmental issues (Guo et al., 2022).

The sale of products in India has a long-standing tradition that is ingrained in cultural values that prioritise resource optimisation, reuse, and frugality. These customs are now in accordance with the realities of rapid urbanisation, income disparity, and the ubiquitous use of technology. The resale of pre-owned goods is crucial for the economy and aids the United Nations in achieving its Sustainable Development Goals (SDGs), particularly SDG 12 concerning responsible consumption and production. Reselling products prolongs their life cycles, thereby reducing the necessity for the production of new items. This conserves resources and safeguards the environment.

Extensive research has been conducted on perceived value as a multidimensional construct influencing consumer decisions (Sánchez-Fernández & Iniesta-Bonillo, 2007); however, its moral and ethical dimensions in the sales context remain underexplored, particularly in emerging markets such as India. It is essential to acknowledge this, as sellers' ethical considerations can influence their satisfaction and their propensity to continue participating in the pre-owned market. Recent research (Kaur & Manna, 2024) indicates that seller satisfaction serves as the link between perceived value and behavioural intentions. This suggests that ethically framed resale transactions may lead to increased engagement. Global studies indicate that values associated with sustainability, equity, and resource optimisation are significant motivators for peoples to engage in resale activities (Jibril et al., 2024; Xiao et al., 2023).

The current study presents and evaluates the "EcoEthi Sale Disposal Scale," the inaugural standardised instrument designed to assess the moral and ethical implications of selling pre-owned items. This scale aids researchers and practitioners in comprehending the psychological and ethical motivations for resale. It additionally endorses strategies that enhance seller satisfaction and motivate their continued participation. The study directly addresses the research scope of the established method for assessment grounded in marketing and consumer behaviour theory, aligned with strategies for marketing that emphasise sustainability, applicable in both Indian and global markets. Practical applications for retailers, resale platforms, and policymakers seeking to leverage moral and ethical values to increase consumer purchases. This study enhances understanding of resale in academia and demonstrates how to profit in the rapidly expanding pre-owned market by positioning resale at the intersection of sustainability and marketing.

Literature Review and Theoretical Background

The Market for Pre-Owned Goods and Environmental Sustainability

In the past decade, the market for pre-owned goods has expanded significantly. This is due to heightened environmental awareness, a desire for cost savings, and the pursuit of distinctive products. In developing nations such as India, resale occurs through various methods, ranging from traditional flea markets to advanced digital platforms. This alteration transcends mere operational adjustments in retail; it reflects a profound alignment with the principles of the circular economy, characterised by prolonged product utilisation, reduced waste, and diminished demand for new resources (Guo, Zheng, Wang, & Zhang, 2022).

The ethical and sustainable aspects of purchasing and selling pre-owned items are becoming more appealing, despite the fact that affordability and accessibility are still significant to consider. However, this practice is not exclusively motivated by profit; it also serves to mitigate pollution and protect the environment. A substantial number of sellers engage in this practice. A feeling of purpose can significantly enhance the probability of repeat purchases and elevate people happiness (Jibril, Amoah, Egala, & Odei, 2024). Global study indicates that resale platforms may enhance vendor loyalty and involvement by successfully conveying the social and environmental advantages of transactions (Kapitan & Bhargave, 2013; Xiao, Zhou, & Mao, 2023).

Theoretical Foundations

The relevance of moral and ethical considerations in resale conduct may be comprehended via the use of many established theories:

Ajzen's Theory of Planned Behaviour (1991) illustrates the influence of attitudes, perceived social standards, and behavioural control on intentions. The propensity of peoples to engage in resale activities may be enhanced by their positive views towards sustainability and their self-assurance in their selling capabilities.

Value-Belief-Norm Theory (Stern et al., 1999) connects environmentally advantageous behaviours to people norms. This suggests that moral responsibility can provide a compelling justification for engaging in reselling activities.

Social Exchange Theory (Blau, 1964) posits that people engage in actions when perceived benefits, such as moral satisfaction, social recognition, and financial returns, surpass the associated costs. For sellers, the inherent gratification of contributing to environmental preservation can be equally significant as financial gain.

Perceived Value Theory (Sánchez-Fernández & Iniesta-Bonillo, 2007) posits that decision-making resembles evaluating the advantages and disadvantages of various alternatives. Moral and ethical values are critical components of this evaluation, particularly when the impacts on the environment and society are evident.

Moral and Ethical Aspects of Perceived Value

Perceived value is frequently discussed as a multi-faceted concept encompassing functional, economic, emotional, and social advantages relative to costs. Much is understood regarding these matters; however, the moral and ethical dimensions have not been examined as thoroughly in the context of commerce. Moral and ethical value refers to the psychological gratification derived from adhering to environmental and social standards, such as reducing overconsumption and conserving resources (Türe, 2013).

This moral impetus is not confined to Western markets. People in India frequently opt to sell pre-owned items due to enduring cultural traditions of frugality, sharing, and resource optimisation (Usha, 2012). Recent studies indicate that such motivations can influence a seller's happiness, subsequently impacting their likelihood of reselling (Kaur & Manna, 2024).

Linking Ethics, Satisfaction, and Behavioural Intentions

Sellers who believe their actions benefit society and the environment experience greater happiness, increasing their likelihood of future sales (Kaur & Manna, 2024). Xiao et al. (2023) discovered that equity and transparency in resale transactions enhance customer satisfaction and promote continued business engagement. Özer (2021) demonstrated that equitable pricing and just interactions between buyers and sellers contribute to the sustained operation of resale markets.

Positioning resale as a virtuous and environmentally sustainable practice can effectively incentivise consumer purchases. Disseminating empirical outcomes, such as data on reduced waste production or community advantages, enhances a platform's brand reputation and distinguishes it in an increasingly competitive market (Kapitan & Bhargave, 2013).

Research Gap

Research on the moral and ethical principles that motivate sellers, particularly in developing markets, is far less extensive than that on the reasons why consumers purchase used goods. Furthermore, there is an absence of a standardised, validated instrument for quantifying these values, complicating the efforts of marketers and policymakers to devise effective strategies for leveraging this motivation.

The "EcoEthi Sale Disposal Scale" was developed and tested in this study to address the gap in the existing literature. This tool is specifically intended to quantify the moral and ethical implications of selling used goods. The study not only measures these values but also examines their impact on seller satisfaction and resale intention, offering theoretical insights and practical recommendations for promoting sustainable commerce.

Methodology

Research Design

This descriptive, cross-sectional quantitative study was designed to develop and assess a scale that quantifies the ethical and moral considerations associated with the sale of used products. The study was cross-sectional, which made it possible to collect data at a certain point in time and provide a clear picture of the sellers' attitudes and intentions. The descriptive design was used to systematically gather and evaluate the sellers' ethical assessments (Malhotra & Dash, 2015).

The scale was made using the well-known structure that Churchill came up with in 1979. This framework shows how to build measurement tools that are both valid and reliable in a methodical way. The first step in this process was to clearly define the idea. After that, potential items were created based on the qualitative study and conclusions. A lot of empirical testing was done to check the reliability and validity. By following this methodical plan, the final instrument was shown to be both theoretically strong and psychometrically valid, which proved that it could be used reliably in business and for future study.

Sample and Data Collection

This study's data were gathered from 74 respondents who now sell pre-owned items in Haryana, Chandigarh, Panchkula, Sirsa, Mohali, Patiala, and Bathinda. The people who answered came from a wide range of ages, incomes, and levels of education. The example profile is in Table 1. The study used random selection to get a group of people with different ages, income levels, and levels of education. This ensured the results were representative of a wide spectrum of people in the used car market. The number of people who answered the questions in this study's exploratory factor analysis was far higher than the usual minimum of five people per item (Worthington & Whittaker, 2006). Research on structural equation modelling has demonstrated that models with a modest level of complexity may use samples of more than 50 people as long as the data is reliable and genuine (Iacobucci, 2010).

Table 1 Profile of the Sample
Gender	F	Percentage
Male	40	54.1
Female	34	100
Age (Years)
18-24	15	20.3
25-34	21	28.4
35-44	16	21.6
45-60	19	25.7
60+	3	4.1
Education
Illiterate	2	2.7
Literate but no formal schooling/ School. Up to 4 years	2	2.7
School- 5 to 9 years	7	9.5
Class 10th / Class 12th	15	20.3
Some Colleges (including a Diploma) but not Graduate	13	17.6
Graduate/ Post Graduate: General	23	31.1
Graduate/ Post Graduate: Professional	12	16.2

A bootstrapping approach was used to evaluate the parameter estimations' stability and improve the dependability of the results. Through 1,000 new datasets from the original data in order to find the standard errors and confidence intervals. This made it easier to draw stronger statistical conclusions about the target group. Bootstrapping is especially useful in scale validation studies with small sample sizes because it gives more reliable estimates of how stable and important a model is (Efron & Tibshirani, 1993).

Instrument Development

A preliminary collection of products was compiled by utilising established literature on sustainable consumption and value perception (Türe, 2013; Sánchez-Fernández & Iniesta-Bonillo, 2007). The pool was even better because of the ideas that came from essays and focus group conversations with people who work in the used goods sector. Two senior marketing academics and two experienced marketing practitioners conducted two rounds of the Delphi technique to ensure that the items were both theoretically sound and relevant to the situation. The redesigned items were a good fit for the Indian resale market because the creators had extensive knowledge of sustainable marketing and consumer behaviour. Also, they were honest, acceptable for all cultures, and easy for people from all backgrounds to understand.

The qualitative content of the prototype scale was examined in detail through interviews with ten marketing experts (five academics and five practitioners). The experts looked at each item to see if it was clear, relevant, and in line with the planned build dimensions. This combined method, which included adapting to the situation and getting expert feedback, provided strong proof of content validity for the specified criteria.

Natural Language Processing (NLP) tools were used on the qualitative comments to enhance the process. This analysis made it easier to find common themes, made sure that the meaning was clear, and checked that the phrasing and frame of each item made sense in a range of cultural and linguistic settings.

A bootstrapping approach was used to improve the reliability of the results and test the stability of the parameter estimates. To find the standard errors and confidence intervals, 1,000 new datasets were made from the original data. This made it easier to draw stronger statistical inferences about the target population. Bootstrapping is especially helpful in scale validation studies with small sample numbers because it gives more accurate estimates of model stability and significance (Efron & Tibshirani, 1993). The final instrument comprised:

• Moral/Ethical Value (6 items) created and enhanced specifically for resale purposes.

• Seller Satisfaction (3 items; adapted from Lin et al., 2005) assesses seller satisfaction.

• Resale Intention (3 items; adapted from Cronin et al., 2000)

All items were evaluated on a 7-point Likert scale, with 1 denoting ardent disagreement and 7 denoting strong agreement. This allowed to get better, more comprehensive answers and gauges of opinions.

Pre-test and Refinement

A pilot test with 10 people was used to see how easy it was to understand the scale parts. The answers from the participants showed that little changes to the wording will make the questions clearer and make them more like the everyday language used in Indian resale situations. These changes made sure that people from all walks of life could understand and relate to the scale.

Data Analysis

The analysis made use of a systematic, multi-stage strategy to ensure the scale's dependability and accuracy. The study employed Maximum Likelihood Estimation with Direct Oblimin rotation for Exploratory Factor Analysis (EFA). This was to determine the number of dimensions the constructs had and which items to retain. The technique was selected to allow for correlations between factors, enabling more accurate estimates of factor loadings in behavioural research settings (Byrne, 2010). The next step after the Exploratory Factor Analysis (EFA) phase was to use Confirmatory Factor Analysis (CFA) to confirm the factor structure. Different indices are used to assess the model’s fit, such as the Comparative Fit Index (CFI), the Tucker-Lewis Index (TLI), the Goodness-of-Fit Index (GFI), and the Root Mean Square Error of Approximation (RMSEA). The Cronbach's alpha helped check for internal consistency (numbers over 0.70 were fine), Composite Reliability (CR) and Average Variance Extracted (AVE) to check for convergent validity, and the Fornell–Larcker criterion to check for discriminant validity. This rule (Fornell & Larcker, 1981) says that the square root of the Average Variance Extracted (AVE) of each construct must be greater than its inter-construct correlations. Ultimately, Structural Equation Modelling (SEM) was employed to examine the hypothesised relationships among moral/ethical values, seller satisfaction, and the intention to resell. This approach enabled the simultaneous analysis of both measurement and structural models (Kline, 2015)

Findings

Scale Discrimination

Independent-sample t-tests were performed to examine the discrimination power of each item on the moral/ethical value scale. All t-values were significant at the 0.01 level, indicating that each item effectively distinguished between respondents with high and low moral/ethical value perceptions (Table 2).

Table 2 Discriminating Power of Moral/Ethical Value Scale Items
Items	Mean	Mean for Lower Quartile	Mean for upper Quartile
	N=74	N=18	N=19
sMV1	5.03	3.94	6
sMV2	5.12	3.56	6.58
sMV3	5.04	3.5	6.32
sMV4	5.36	3.72	6.53
sMV5	5.12	3.61	6.26
sMV6	5.28	3.94	6.16

Uni-dimensionality and Factor Structure

Table 3 provides evidence that the scale is unidimensional. The majority of the items had considerable correlations with the total, all of which were significant at the 0.01 level and exceeded 0.700. Item sMV1 was the sole exception to this trend. It exhibited a notable correlation, but reduced to 0.575.

Table 3 EFA Results for Moral/Ethical Value of Selling Pre-Owned Goods
Items	Item-Total Correlation
Moral/Ethical value of selling (n = 74)
sMV1	.575
sMV2	.759
sMV3	.770
sMV4	.756
sMV5	.766
sMV6	.744

Confirmatory Factor Analysis (CFA)

EFA results confirmed that all six items of the moral/ethical value construct loaded onto a single factor, supporting uni-dimensionality. The Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.865, and the total variance explained was 60.51%, exceeding the recommended 60% threshold (Malhotra, 2015). Factor loadings ranged from 0.600 to 0.833 (Table 4).

Table 4 Assessment of Uni-Dimensionality of the Scale
No. of factors	1
KMO	.865
% of Variance Explained	60.511
Items
sMV1	.600
sMV2	.815
sMV3	.833
sMV4	.792
sMV5	.810
sMV6	.793

The results of the Confirmatory Factor Analysis (CFA) indicate that the Moral/Ethical Value evaluation model aligns effectively with the data. The Chi-square statistic (χ² = 52.699, df = 51) yielded a probability value of 0.408, exceeding the 0.05 criterion. This indicates that the model closely aligns with the actual data, which is desirable in Confirmatory Factor Analysis (Byrne, 2010). The CMIN/DF ratio was 1.033, well below the recommended maximum threshold of 5.0. This indicates that the model is straightforward and clearly delineated (Kline, 2015).

The Goodness of Fit Index (GFI) of 0.892 approaches the ideal threshold of 0.90; yet, it remains sufficient for behavioural research, particularly when considered alongside other favourable fit statistics (Hair, Black, Babin, & Anderson, 2019). The Adjusted Goodness of Fit Index (AGFI) achieved a score of 0.835, above the minimum criterion of 0.80. The Root Mean Square Error of Approximation (RMSEA) was 0.021, significantly lower than the suggested threshold of 0.08, indicating a strong alignment between the model and the data (Hu & Bentler, 1999).

Incremental fit measurements contribute to the validation that the model is sufficiently robust. The Comparative Fit Index (CFI) achieved a score of 0.997, but the Normed Fit Index (NFI) attained a score of 0.909. Both scores are above the 0.90 threshold for an optimal match. The Relative Fit Index (RFI) was 0.882, somewhat below the optimal value of 0.95, although still within an acceptable range due to the robustness of the other indices (Byrne, 2010). Collectively, these results indicate that the measurement model fits the data well and corroborates the scale's construct validity (Table 5).

Table 5 Results of Measurement Model: Confirmatory Factor Analysis
Sr. No.	Indicators	Moral/Ethical value of buying	Acceptable value
1	Chi-square	52.699	Non-significant
2	Degree of freedom	51
3	Chi-square probability	.408	>0.05
4	CMIN/DF	1.033	<5
5	Goodness of fit index (GFI)	.892	>0.9
6	Adjusted goodness of fit index (AGFI)	.835	>0.8 or >0.9
7	Root mean square error of approximation (RMSEA)	.021	<0.08
8	Comparative fit index (CFI)	.997	>0.9
9	Normed fit index (NFI)	.909	>0.9
10	Relative fit Index (RFI)	.882	Close to 0.95

Reliability and Validity

The reliability analysis in Table 6 indicates that all three constructs exhibit strong internal consistency. The Moral/Ethical Value of Selling Used Items scale, with six items, had a Cronbach's alpha of 0.899, much exceeding the recommended threshold of 0.70. This indicates that the scale is very trustworthy (Nunnally & Bernstein, 1994). The Seller's Satisfaction, assessed by three items, had a superior alpha of 0.921, indicating a high level of item consistency. The Intention to Resell construct, derived from three questions, exhibits a Cronbach's alpha of 0.821, indicating excellent reliability for behavioural research. All these results indicate that the components inside each construct function cohesively to precisely depict the notions they are intended to portray.

Table 6 Reliability of the Scales Used
Variable	No. of Items	Coefficient alpha	n
Moral/Ethical value of selling used items	6	.899	74
Seller’s satisfaction	3	.921	74
Intention to Resell	3	.821	74

The measures satisfy the standards for discriminant and convergent validity, as demonstrated in Table 7. All constructs had Composite Reliability (CR) values significantly exceeding the requisite minimum of 0.70, with values ranging from 0.820 for Intention to Resell to 0.913 for Seller's Satisfaction. This indicates that the constructions were very consistent with one another (Hair, Black, Babin, & Anderson, 2019). The Average Variance Extracted (AVE) values for all constructs exceeded the 0.50 criterion, varying from 0.605 for Moral/Ethical Value to 0.778 for Seller's Satisfaction. This indicates that each concept accounts for over fifty percent of the variance in its respective indicators (Fornell & Larcker, 1981).

Table 7 Assessment of Convergent Validity and Discriminant Validity of the Scales
	CR	AVE	MSV	ASV
SAT	0.913	0.778	0.421	0.338
MV	0.901	0.605	0.421	0.310
InS	0.820	0.608	0.255	0.227

To demonstrate that the constructs were distinct, each construct's Average Variance Extracted (AVE) needed to exceed both its Maximum Shared Variance (MSV) and its Average Shared Variance (ASV). The Moral/Ethical Value possesses an AVE of 0.605, above both its MSV of 0.421 and ASV of 0.310. This trend was consistent across all constructions, demonstrating that each is more closely linked to its own elements than to those of other constructs. This indicates that they are empirically distinct.

The measures satisfy the standards for discriminant and convergent validity, as demonstrated in Table 7. All constructs had Composite Reliability (CR) values significantly exceeding the requisite minimum of 0.70, with values ranging from 0.820 for Intention to Resell to 0.913 for Seller's Satisfaction. This indicates that the constructions were very consistent with one another (Hair, Black, Babin, & Anderson, 2019). The Average Variance Extracted (AVE) values for all constructs exceeded the 0.50 criterion, varying from 0.605 for Moral/Ethical Value to 0.778 for Seller's Satisfaction. This indicates that each concept accounts for over fifty per cent of the variance in its respective indicators (Fornell & Larcker, 1981).

To demonstrate that the constructs were distinct, each construct's Average Variance Extracted (AVE) needed to exceed both its Maximum Shared Variance (MSV) and its Average Shared Variance (ASV). The Moral/Ethical Value has an AVE of 0.605, above its MSV of 0.421 and ASV of 0.310. This trend was consistent across all constructions, demonstrating that each is more closely linked to its own elements than to those of other constructs. This indicates that they are empirically distinct.

Concurrently, these results provide compelling evidence that the measurement model exhibits satisfactory convergent and discriminant validity, thereby underscoring the scale's robustness and reliability.

Structural Equation Modelling (SEM):

The results of the Structural Equation Modelling (SEM) (Figure 1) indicate that Moral/Ethical Value (MV) has a substantial and statistically significant positive influence on Seller Satisfaction (SAT) (β = 0.648, p < 0.01). Seller satisfaction significantly enhances Intention to Resell (InS) (β = 0.545, p < 0.01), indicating that satisfaction is a crucial determinant in the decision to sell again.

The correlation between Moral/Ethical Value and Intention to Resell was also positive, but somewhat less (β = 0.222). This indicates that Seller Satisfaction somewhat contributes to the relationship. This indicates that moral and ethical considerations influence a seller's inclination to resell directly, with much of their impact stemming from the satisfaction derived from adhering to these values.

The model's factor loadings indicate a robust measurement model, since the majority of observed variables had substantial loadings on their latent constructs (for instance, SAT2 at 0.90 and InS1 at 0.92). Despite sMV1 exhibiting a lower loading of 0.37, the majority of the MV items demonstrated loadings over 0.60, hence affirming the construct's reliability.

Previous research indicates that satisfaction serves as a mediating factor in resale activity, consistent with our findings. Kaur and Manna (2024) found that satisfaction is a crucial element linking value judgements to behavioural intentions. Jibril et al. (2024) noted that ethical incentives enhance repeat sales mostly by fostering a sense of fulfilment and alignment with personal views among vendors.

Discussion

The validation of the "EcoEthi Sale Disposal Scale" gives strong support for include moral and ethical issues in models of resale behaviour. The results suggest that these values increase the likelihood of repeat purchases from the same seller, thereby making sellers happier. Kaur and Manna (2024) have already shown that pleasure acts as a link between perceived value and behavioural intentions. This discovery is in line with what other studies have shown. The Value-Belief-Norm Theory (Stern et al., 1999) and the Theory of Planned Behaviour (Ajzen, 1991) are the study's theoretical framework, and this fits in perfectly with both. These ideas suggest that people's moral obligations and values significantly influence their plans.

Ethical Considerations as a Basis for Seller Engagement

There is a strong link between moral or ethical ideals and merchant happiness, which supports the idea that reselling goes beyond just business transactions. It is also a behaviour based on values. People want both mental and physical benefits, according to Social Exchange Theory (Blau, 1964). In this case, stores are happy to help the environment and promote eco-friendly shopping. This fits with previous research that shows that ethical framing in resale situations makes people more interested and loyal (Guo et al., 2022; Jibril, et al. 2024). This study expands on Türe's (2013) work by putting moral and ethical ideas into a mathematical framework. It gives you a verified tool that looks at parts of vendor behaviour that aren't looked at when you only look at functional or economic value.

Satisfaction as a Means of Connection

The mediation effect seen in this study parallels findings in the broader marketing literature, where satisfaction frequently links cognitive evaluations and behavioural outcomes (Cronin, Brady, & Hult, 2000). In the realm of resale, this satisfaction derives not alone from financial gain but also from the ethical fulfilment of reducing waste and supporting the circular economy, consistent with the findings of Xiao, Zhou, and Mao (2023). Moral and ethical values can directly and indirectly influence resale intention, indicating that interventions should simultaneously address value perception and satisfaction to optimise outcomes.

Cross-Cultural and Platform-Level Implications

The results significantly impact both culture and the platform itself. Ethical considerations for resale hold global significance, however their impact varies according to regional norms. In India, deeply ingrained principles of frugality, sharing, and resource optimisation (Usha, 2012) may enhance the impact of moral and ethical ideals. Conversely, in certain markets, legislative requirements and brand-driven sustainability messages may exert a more significant influence (Özer, 2021; Kapitan & Bhargave, 2013). Incorporating sustainability metrics, such as CO₂ emissions reduced or waste diverted, into the seller experience at the platform level may enhance the seller's perception of contributing positively, hence increasing their satisfaction and loyalty.

Implications for Managers

The EcoEthi Sale Disposal Scale, which has been tested and proven to work, is a useful tool for marketers, resale sites, and lawmakers to find and use moral and ethical reasons for people to sell their things. Strategies for communicating with customers reselling should be seen of as not simply a way to protect money, but also as a way to be socially and environmentally responsible. Campaigns that focus on maximising resource utilisation, environmental protection, and pollution reduction may help people view moral and ethical ideals in a more positive light. This fits with what is happening throughout the world, as messages about sustainability inspire people to become involved again (Jibril et al., 2024; Xiao et al., 2023).

Adding features to get users more interested and growing the platform: Online marketplaces can utilise tools that measure the effects of sellers' actions, including how much trash is redirected or how much CO₂ emissions are reduced. These parts make resale more ethical, which makes customers happier and more loyal, aligning with the best techniques for long-term branding (Kapitan & Bhargave, 2013).

Loyalty programs should include both monetary rewards and appreciation of vendors' ethical contributions since happiness is a balance. "EcoSeller" and "Sustainability Leaderboards" are two examples of emblems that highlight suppliers with a significant impact. The government and businesses should be encouraged to create ecosystems and implement rules that offer incentives to promote ethical resale, such as lower GST rates on used goods or funding for infrastructure improvements. India's Sustainable Development Goals, along with these steps, could help make ethical reselling a normal part of doing business (Guo et al., 2022). The scale Cultural adaptability, initially designed for North India, but it can be modified to accommodate different cultures and regions, enabling the identification of moral reasons behind the local population's actions. Multinational platforms can adapt their methods to align with the values and goals of each region, particularly in terms of sustainability.

Conclusion and Future Research Directions

This study developed and validated the "EcoEthi Sale Disposal Scale" to measure the moral and ethical value of selling pre-owned goods, addressing a critical gap in resale and sustainable marketing research. Findings confirm that moral/ethical value significantly enhances seller satisfaction, which in turn promotes repeat resale intentions, partially mediating the value-intention relationship. The research offers both theoretical and practical contributions. Theoretically, it extends perceived value literature by operationalising moral and ethical value in a measurable, context-specific scale, aligning with recent calls for integrating ethical dimensions into consumer behaviour models. Practically, it provides marketers and policymakers with a diagnostic tool to design interventions that strengthen ethical motivations and improve resale engagement.

Future research can extend this work by testing the scale in diverse cultural and economic contexts to evaluate cross-cultural applicability. Incorporating additional variables such as trust in resale platforms, perceived product authenticity, and price fairness. Applying longitudinal designs to assess how moral/ethical value perceptions evolve over repeated resale experiences. Exploring the interplay between buyer and seller ethical perceptions to understand bilateral value creation in pre-owned markets. By recognising resale as both an economic and ethical transaction, this research aligns with India's circular economy vision and contributes to the growing body of literature that positions sustainable consumption at the core of marketing strategy.

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Indexed at, Google Scholar, Cross Ref

Blau, P. M. (1964). Exchange and power in social life. John Wiley & Sons.

Byrne, B. M. (2016). Structural equation modelling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.

Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.

Indexed at, Google Scholar, Cross Ref

Cronin, J. J., Jr., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality, value, and customer satisfaction on consumer behavioural intentions in service environments. Journal of Retailing, 76(2), 193–218.

Indexed at, Google Scholar, Cross Ref

Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. Chapman & Hall/CRC.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

Cross Ref

Guo, F., Zheng, X., Wang, C., & Zhang, L. (2022). Sharing matters: Household and urban economies of scale in sustainable consumption. Resources, Conservation and Recycling, 184, 106410.

Indexed at, Google Scholar, Cross Ref

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.

Indexed at, Google Scholar, Cross Ref

Hu, L., & Bentler, P. M. (1999). Cut-off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.

Cross Ref

Iacobucci, D. (2010). Structural equations modelling: Fit indices, sample size, and advanced topics. Journal of Consumer Psychology, 20(1), 90–98.

Cross Ref

Jibril, A. B., Amoah, J., Egala, S. B., & Odei, M. A. (2024). Understanding the determinants of secondhand goods purchase intention: A developing country perspective. Service Science, 16(4), 319–335.

Cross Ref

Kapitan, S., & Bhargave, R. (2013). Navigating residue sensitivity in the used goods marketplace. Psychology and Marketing, 30(4), 305–316.

Indexed at, Google Scholar, Cross Ref

Kaur, M., & Manna, R. (2024). Sale of second-hand goods by consumers: Mediating role of satisfaction between perceived value and behavioural intentions. The International Review of Retail, Distribution and Consumer Research, 35(3), 291–312.

Indexed at, Google Scholar, Cross Ref

Kline, R. B. (2015). Principles and practice of structural equation modelling (4th ed.). Guilford Press.

Malhotra, N. K., & Dash, S. (2015). Marketing research: An applied orientation (7th ed.). Pearson Education India.

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

Özer, A. H. (2021). A fair, preference-based posted price resale environment for used goods. Applied Soft Computing, 106, 107308.

Cross Ref

Sánchez-Fernández, R., & Iniesta-Bonillo, M. Á. (2007). The concept of perceived value: A systematic review of the research. Marketing Theory, 7(4), 427–451.

Indexed at, Google Scholar, Cross Ref

Stern, P. C., Dietz, T., Abel, T., Guagnano, G. A., & Kalof, L. (1999). A value-belief-norm theory of support for social movements: The case of environmentalism. Human Ecology Review, 6(2), 81–97.

Indexed at, Google Scholar

Türe, M. (2013). Value-in-disposition: Exploring how consumers derive value from the disposition of possessions. Marketing Theory, 14(1), 53–72.

Google Scholar, Cross Ref

Usha, S. (2012, August). The contribution of frugality and material values to product disposition: An exploratory study. In Management Issues in Emerging Economies (ICMIEE), Conference Proceedings (pp. 144–148).

Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806–838.

Google Scholar, Cross Ref

Xiao, X., Zhou, C., & Mao, H. (2023). What can satisfy customers in servitization? Second-hand goods market perspectives. Journal of Business & Industrial Marketing, 38(10), 2030–2044.

Cross Ref

Received: 11-Aug-2025, Manuscript No. AMSJ-25-16139; Editor assigned: 12-Aug-2025, PreQC No. AMSJ-25-16139(PQ); Reviewed: 16-Sep-2025, QC No. AMSJ-25-16139; Revised: 22-Sep-2025, Manuscript No. AMSJ-25-16139(R); Published: 30-Sep-2025