In recent years, with the rise of e-shopping and e-marketing, a phenomenon known as ‘Shopping Lies’ has become a cause for concern. All these strategies lie between outrageous offers and unattainable return policies solely for the purpose of altering the perception of consumers. Such strategies may work in creating an environment, which makes the consumer to buy even though he or she may not have intended to, but the long-term effects are likely to have a negative impact to the consumer as far as their trust and loyalty to the brand is concerned. Thus, the nature and role of false information in digital marketplaces is becoming more relevant to analyze how it influences customers and if such deception will help companies become more successful or on the contrary, contribute to the decline in consumer trust in the long term.

Consumers are able to receive and read different kinds of false advertisements, fake reviews and even concealed fine print. These are tactics take advantage of psychological effects: therefore, they appeal to the consumers’ decisions based on scarcity or perceived value. Existing literature indicates that while some forms of deception lead to impulse buying, there is a negative effect on consumer trust leading to decreased likelihoods of repeat purchases. The corresponding question is whether shopping lies are helpful for sales or are counterproductive due to their negative impact on the consumer-brand ties. Solving this problem is highly essential in the current era aiming at establishing a healthy corporate profitability and consumer responsible and legal engagement.

Consequently, there is an agreement among scholars that trust plays an important role in consumers’ decision-making process regarding brand loyalty. In essence, one can determine that trust is created by being as open as possible, providing good service and offering clear communication to the client. However, if consumers feel that the company is being deceptive they flow away from the brand and spread negative word of mouth and retain the company for a short period. Past research shows that trust is a moderator of the connection between marketing practices and customer loyalty, but few Of them has empirically measured the degree of shopping mall on these variables. This research attempts to fill this gap by analyzing cross-sectionally data of consumers, perceived deception, trust, purchasing intentions and brand loyalty towards the use of Deceptive marketing techniques.

This paper uses a survey-based approach in order to gain understanding of perception that consumers have towards shopping lies as well as their behavior when shopping. A self-developed and verified survey was sent to various online consumers to get their perceptions of manipulation techniques. To analyse the shopping lies, factor analysis was used to determine the underlying factors which were followed by the Structural Equation Modeling (SEM) in establishing the relationship between deception, trust and consumer loyalty. To this respect, the paper contributes to the advancement of knowledge in the area of marketing ethics through empirical findings of risk connected to the use of deceptive techniques and the potential implications of the trade-off between organisational revenues and brand equity maintenance.

However, regulation of the effects of shopping lies not only among the businessman but also among the regulatory authorities who are charged with the responsibility of protecting consumers. Today, there is more pressure to justify advertising, pricing policies or the lack of them, and consumer protection mechanisms for numerous e-commerce platforms. Due to the growing consumer awareness, it becomes difficult to manipulate the market for the purpose of maintaining a competitive edge. Thus, this research provides useful recommendations to marketers: do not take advantage of the consumers and the biases in question; instead, build trust with the consumers.

Given the current discussions about the ethical aspects of marketing, this work aims at giving insight into the phenomenon of the shopping lies and discuss its effect on consumers. The outcomes are valuable to the business entities as a way of marketing that can help encourage the consumer to purchase, but at the same time can also be continued in the long run.

There are challenges that are more visible in the contemporary society, specifically due to the rise of the internet, regarding consumer trust, and necessary deception from consumers, particularly in the shopping sector. Consumer trust and deceptive practices in the context of e-commerce are verified in this literature review article as a many-faceted phenomenon.

Trust in Internet purchasing decisions is considered as a key determinant that is influenced by perceived risk. This study also supported the conclusions made by Handoyo and colleagues (2024) that trust, perceived security, and e-WOM have a positive impact on consumers’ decision to engage in online transactions. This is in line with research carried out by Peña-García et al. (2024) where they reveal that security measures have an influence on the level of confidence of users of the interface.

Misleading information or ad or false advertising has become an alarming issue that prevails in virtual markets. In their study, Ahmed et al. (2024) have found out the following notable elements: unethical advertising, false information and deceitfulness. Hussain et al., went further by demonstrating that these practices impact trust measures and credibility of the platform.

As such, the usage has evolved to be a crucial aspect that determines the believability of the online reviews. Bashir and colleagues (2024) revealed in a study that credibility of the information in the reviews improves three forms of trusts namely trust in the reviews, trust in the marketplaces and trust in the rating systems. Nivitha et al. (2024) also established that verified purchase reviews have more influence than unverified in the consumer decision-making process.

According to the work of Zhang et al. (2024), consumers’ choices in the digital environment are not based on the rational factors, but due to cognitive biases, heuristics, as well as emotions.

Research Gap

Although there are quite a lot of research done on the influence of trust in consumer behavior, fewer research is directed towards executing a wedge on shopping lies on trust, purchase intention, and brand commitment. The problem that lies in deceptive marketing has been discussed in previous literature as a factor that affects consumer choice, but the impact of this approach in the long run is not well studied. Previous research has investigated specific components of deception, including fake reviews, false claims of discounts, etc., while this article integrates all these into examining consumer trust and loyalty. In addition, the moderation role played by trust on the shopping lies and purchase behavior has not been established using advanced statistical models. These shortcomings are responded to in this work through the use of SEM to model the correlation between deceptive marketing, consumer trust, purchase intent & brand loyalty.

Conceptual Framework

The study defines shopping lies as including deception, which refers to an action or act of deception; and misrepresentation, which entails concealing or non-disclosure of information. It was assumed that these factors have influence on the level of consumers’ trust, which, in turn, affects the likelihood of their decision to purchase the goods and their fidelity to brands. This framework suggests that even though, strategic advertising or communicating can compel customers to purchase a product in the short period, consumer trust is reduced thus transforming into a non-patronizing clientele base. It is hypothesized that trust will moderate the relationship between the shopping lies and long-term consumer commitment. EFA, CFA, and SEM are used to test the conceptual model.

Hypotheses

Based on the conceptual framework, the study proposes the following hypotheses:

• H1: Shopping lies are negatively associated with consumer trust.
• H2: Shopping lies are positively associated with purchase intent.
• H3: Consumer trust is positively associated with brand loyalty.
• H4: Consumer trust mediates the relationship between shopping lies and brand loyalty.

H5: Consumer trust mediates the relationship between shopping lies and purchase intent.

For the purpose of this research, a cross-sectional survey design approach was used to determine the extent of deceptive shopping behaviours or ‘shopping lies’ and their effects on consumers’ decisions. A survey was preferred since it was believed that it could provide the best insight of the student’s behaviors and attitudes in a relatively short amount of time. This design was deemed suitable because of its success in centredness, pattern recognition in consumer deceit, quantification and impacts of psychology in client buying trend.

In the study, participants were selected through the use of the stratified random sampling to ensure that both the gender, age, income and habits of the people to be surveyed were taken into consideration. The sample of this study comprised 600 participants, and the regions were divided equally among India, the United States, and the United Kingdom. To reduce the prejudice, the participants were recruited through an online research panel service provider, which is prominent in market research. The criterion used in the inclusion process was that the respondent must have made at least one purchase in the last 3 months whether online or offline. Regarding the choice of participants, the study was conducted only with fully aware, unpaid subjects, and included the exclusion of those with professional interest in the findings.

The survey was administered online using a software known as Qualtrics. It taken 4 weeks to complete the survey and reminders were provided to increase the response rates. The survey was anonymous and self-administered, and the participants had a unique link that helped in avoiding duplication of responses. The tested questionnaire was divided into several sections such as demographic information, shopping patterns and self-generated cases of perpetrating shopping deceit. Thus, to make the answers more accurate and minimize social desirable response bias, indirect questions, and questions framed as part of scenarios were used. The completion time was about 12 minutes in average for the whole of the survey.

The questionnaire was a self-administered questionnaire of 35 items related to general shop lying, trust, intention to purchase and loyalty. Some of the questions were drawn from the existing scales employed in consumer research with a view of measuring similar phenomena but some changes were made to ensure appropriateness. Family members only participated in answers and the answers were made according to a five-point Likert scale, which accompanied by =Strongly Disagree= on one end and =Stronged Agree= at the other end. In an endeavor to validate the reliability of the collected data, the questionnaire was pre-tested on a sample of 50 respondents to check on factors such as the clarity and internal reliability of the instrument. Changes that were made to the survey from feedback obtained from the pilot tests were mostly focused on better understandability of the wordings.

Figure 1: Structural Equation Model of Shopping Lies Influence on Purchase Decisions

 Regarding ethical concerns, all findings of the study complied with the evaluate procedures without compromising the rights of any individual involved with the research. Participants voluntarily consented to participate in the study; participants’ identity was also preserved under a coded name and number. The gathered data were saved on an encrypted server with the said data being available exclusively to the research team. Concerning the volunteers’ information sheet, participants were told that they could pull out of the study at any time without any repercussions. Thus, there is no violation of the data protection acts and regulations like the General Data Protection Regulation (GDPR) or the Indian Personal Data Protection Bill.

For data cleaning and analysis, data collection and database was done with the use of IBM SPSS Statistics (Version 28). EFA and CFA were analysed using IBM SPSS AMOS (26). In order to retrieve data on the subjects’ demographic background and shopping preferences tendencies, descriptive analyses were conducted to summarize the findings. Cronbach’s Alpha test was used to analyze the reliability of the items which had been administered for the study where a higher internal consistency is indicated by alpha value which is closer to 1. EFA was used with the aim of identifying the factor structure for shopping lies and the study adopted the principal component analysis with varimax rotation. This was done to ensure that the number of factors was arrived at based on the eigenvalues greater than one and also the scree line. Next, CFA was undertaken in order to confirm the factorial validity of the measures, as well as the goodness of fit indices that included the CFI, TLI, RMSEA, and SRMR indices.

Correlation analyses were carried out too in order to compare the link between shopping lies, consumer trust and purchase intentions. Consequently, regression analysis was conducted to assess the impact of the deceptive shopping behavior on the purchase and brand loyalty. Last of all, SEM was employed in the last part in order to analyse the direct and indirect connections between the variables and to confirm the proposed theoretical model. Looking at the reasons for choosing SEM, it can be concluded that it was selected because of the fact that the model must determine relationships and also capture measurement error. The goodness-of-fit indexes Chi-square/df, RMSEA, and CFI were used to test the adequacy of structural model.

In this way, the study’s purpose was to contribute to the scientific literature a quantitative investigation of the psychological and behavioral effects of shopping lies on consumers along with a sense of the role they play in brand-consumer relationships.

Descriptive Statistics of Participants

 Participants of the study consisted of 600 subjects with an equal distribution among participants’ ages and their gender, as well as their shopping behavior. Analyzing the Table 1 that presents the demographic information of the participants, several features can be noted. With regard to the characteristics of the audience, it was comprised of 34.9% males and 52% females and their mean age was 34.2 years with a standard deviation of 7.8 years. A majority 65 % of the respondents chose online shopping as their preferred mode of shopping, 35 % preferred shopping terminals.

Table 1: Descriptive Statistics of Participants

Reliability Analysis

Cronbach’s Alpha coefficient was calculated to establish internal consistency of the shopping lies scale and the related variables. From Table 2, all the scales were values were high with values more than the threshold of 0.7 for the reliability test.

Table 2: Reliability Analysis Results (Cronbach’s Alpha)

Exploratory Factor Analysis (EFA)

In order to determine the factors contributing to the shopping lies, an Exploratory Factor Analysis (EFA) was applied with principal component analysis using varimax rotation. According to KMO, the sampling adequacy was high as it stands at 0.85, while for Bartlett’s Test of Sphericity, χ²(120) = 865.32, p < 0.001, so factor analysis was requisite. Nevertheless, factor loadings are also presented in more detail in Table 3 with items that have a loading of 0.50 and above being included.

Table 3: Factor Loadings from Exploratory Factor Analysis

Figure 2 presents the scree plot, which was used to determine the number of retained factors. The plot shows a clear break at two factors, confirming a two-factor solution.

Figure 2: Scree Plot for Factor Retention in Exploratory Factor Analysis
The scree plot illustrates the eigenvalues for each factor, indicating that two primary factors explain most of the variance in shopping lies.

Confirmatory Factor Analysis (CFA)

 To ensure that the factor structure obtained in EFA was appropriate, CFA was performed next. Table 4 shows the indices for the model fit The indices show that the model fit is excellent (CFI = 0.92, RMSEA = 0.05, TLI = 0 .91).

Table 4: Confirmatory Factor Analysis Model Fit Indices

Figure 3 provides the path diagram from CFA, visualizing the relationships between observed variables and latent constructs.

Figure 3: Path Diagram from Confirmatory Factor Analysis
The path diagram represents factor loadings and error terms associated with shopping lies and consumer trust, confirming the construct validity.

Correlation Analysis

 Correlation analysis was used in order to test the associations between major study factors. An analysis carried in Table 5 revealed that while shopping lies have a negative relationship with consumer trust r= -.58 (p < 0.01) it has a positive association with purchase intention r =. 42(p < 0.0001) which underlines the fact that deceiving shoppers still generate consumer sales.

Table 5: Correlation Matrix of Key Variables

(p < 0.01)

Regression Analysis

 In order to investigate the degree, to which the shopping lies have an effect on purchase intention and brand consciousness, regression analyses were compared. From table 6, it was found that; shopping largely influences purchase intent positively ( β = 0.39, p < 0.001) while it negatively impacted on brand loyalty (β = – 0.25, p < 0.001).

Table 6: Regression Analysis Results for Shopping Lies and Consumer Behavior

(*p < 0.001)

 Figure 4 exhibits a scatter plot for shopping lies and purchase intent proving that even if there is lack of trust due to lies, people are drawn in to make a purchase.

Figure 4: Scatter Plot of Shopping Lies vs. Purchase Intent
The scatter plot highlights the moderate positive correlation between shopping lies and purchase intent, supporting the regression results.

This paper sought to establish the moderating role of consumer trust between shopping lies and brand loyalty through using the Structural Equation Model (SEM). The above diagram (figure 1) is supporting that the relation exists through consumer trust and it is a partial mediating variable.

Data Analysis and Interpretation

To achieve the above objective of analyzing the shopping lies and their impact on consumer behavior, the following methodologies were applied; Exploratory, reliability coefficient testing, exploratory factor analysis, correlation analysis, regression analysis and structural equation modeling. The study gives information on the impact of the type of deceptive marketing practices on consumers’ trust, their willingness to buy products, and adoption of the specific brand.

The first table with demographic data yields that the provided sample is quite balanced in terms of age and the majority of participants prefers online shopping (65%). Table 2 shows that all the study’s constructs have good internal consistency according to the Cronbach’s alpha coefficients which are all greater than 0.7.

To determine the number of factors that represent shopping lies, Exploratory Factor Analysis (EFA) was conducted. As reflected on the scree plot (Figure 2), the number of factors was found to be two based on the cut-off point where eigenvalues dropped after the second factor. Table 3 presents the rotated factor loadings and also two factors are clearly defined: Deception and Misrepresentation. To confirm this factor structure, a Confirmatory Factor Analysis (CFA) was conducted and it was observed that the model-fit indices given in table 4 are within acceptable range (Chi-square = 12.14, Df = 10, p = 0.20, CFI = 0.92, RMSEA = 0.05). The path diagram from CFA depicted in Figure 3 below also reveals more of the factor loadings thus making the overall model more valid.

Descriptive statistics of perceptions (Table 5) show that there is students’ negative perception of the role of shopping lies towards consumer trust which indicates that negative correlation (mean = – 0.58, p < 0.01) means trust is negatively affected by deceptive practices. Nevertheless, there is the positive correlation between shopping lies and the purchase intention where ri = 0.42, p < 0.01, Hence, it is apparent that despite the lit eros in trust, people are still influenced by deceptive marketing strategies. In line with this, a moderate positive correlation is evidenced in the scatter plot layout depicted in Figure 4 between the variable of shopping lies and the construct of purchase intent.

Table 6 below also shows regression analysis to get a better understanding of the relationships between the variables. The results show that shopping influences the purchase intent positively (β = 0.39, p < 0.001) and brand loyalty, conversely (β = -0.25, p < 0.001). This implies that while deception leads to short-term consumers’ purchase, it actually deters the long-term relationships with those customers.

At last, in the Structural Equation Model (SEM), as indicated in the figure 1 below, consumer trust has been posited to mediate the relationship between the various antecedents and brand loyalty. This means that shopping takes a toll on trust negativly (-0.58); using this the research established that brand loyalty (-0.60). The above mediation diagram (Figure 5) also supports this by showing that trust indeed helps to moderate the negative relationship between deceptive practices and long-term consumer loyalty.

The study provides an insight that though there are short-term benefits in leading the consumer to the purchase, shopping lies undermine the trust that consumers develop for the brand and in the process hamper its long-term potential. This is shown through the short term benefits but long term losses of unethical advertising and how it is crucial to practice ethical advertisement to maintain long term customer relations.

This paper sought to understand the effects of shopping lies which highlighted some of the effects that can be attributed to such misleading advertising. Thus, relationship between self-esteem and positive affect as bom, settles the research hypothesis, shoppers negatively influence consumer trust (H1 proved) while at the same enhancing purchase intention (H2 proved). Nevertheless, trust is quite important when it comes to consumer loyalty, which can be explained by the fact that it has a positive effect on brand loyalty (H3). Moreover, as stated by H4, trust plays a moderating role in the relationship between shopping lies and brand loyalty level; also, the moderating effect of trust was supported in the relationship between shopping lies and purchase intent (H5). These results raise a pertinent issue about making money truthfulness: as the manipulative tactics increase sales, they decrease customer faith, which affects the brand equity.

Limitations of the Study

Nonetheless, the following are the limitations of this study. First, the data was collected through self-reported surveys and people might not honestly answer the questions due to some reasons which will lead to social desirability bias. Secondly, the current study mainly targets online customers and, therefore, generalizing the findings of the research to offline retail settings may be somewhat restricted. Third limitation: There was no clear attention to the fact that consumers in different cultures have different perception of deception depending on the region. Future research should also focus on the cultural differences that exist and make use of panel data in order to assess the effects of deception in advertising in the long run.

Implications of the Study

The implications of the findings can be for businesses, policy makers, and the consumer protection agencies. Marketers should avoid using such short-term deceptive strategies as they are likely to have an adverse effect of customers’ churn in the long run. Instead, organizations should learn more on how to practice and engage the public in proper communication in order to gain the trust of the public which is essential and key in the consumers being loyal to the particular brand. Overall, it is recommended that regulatory bodies enhance some measures of scrutiny and ensure more proper tackling of the corresponding deceptive advertisements.

Future Recommendations

Further studies must be conducted on how the CA can be used to reduce the impact of the deceptive marketing practices. Such empirical research could examine how increased levels of transparency impact the consumer’s behavior in their purchases. The paper also suggests supplementing the present information about deceptive advertising based on neurocientific and behavioral economics models. Another research proposal that could be pursued in the future is the analysis of the effectiveness of the global CSR initiatives toward restoration of the trust breached by a firm.

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