Editorial Board

A Refereed Monthly International Journal of Management

Shifting Sands: An Exploration of Consumer Behavior in the Transition from Fairness to Wellbeing in the Indian Cosmetics Market

 

Author Details

1.      Dr Neerupa C, Assistant Professor, Department of Professional Accounting and Finance, Kristu Jayanti College, Autonomous, Bengaluru, Karnataka, India

2.      Dr Naveen Kumar R, Associate Professor, School of Management, Kristu Jayanti College, Autonomous, Bengaluru, Karnataka, India (Corresponding Author)

3.      Dr Nidhi Raj Gupta, Assistant Professor, Department of Professional Accounting and Finance, Kristu Jayanti College, Autonomous, Bengaluru, Karnataka, India

4.      Dr Ramadevi V, Associate Professor, School of Management, Sri Krishna College of Engineering and Technology, Autonomous, Coimbatore, Tamilnadu, India

 

 

Abstract

The Indian beauty industry has evolved significantly, shifting from a fairness-driven ideal to a more holistic, wellness-focused standard. This transformation has been influenced by changing consumer preferences, ethical awareness, regulatory developments, and the rise of social media. This study examines how emotional factors influence purchase decisions (PD) and brand loyalty (BL), considering Cultural and Social factors (CS), Market and Regulatory Changes (MRC), Social Media Influence (SMI), and Consumer Awareness and Ethical Considerations (CAE). A structured survey was conducted among 276 Indian cosmetic consumers using a quantitative research approach. Data analysis, performed through Structural Equation Modeling (SEM) via AMOS, revealed that SMI and CS significantly impacted PD, whereas MRC and CAE had minimal influence. Similarly, SMI played a crucial role in BL, while CS, MRC, and CAE showed weak direct correlations. Mediation analysis (Figure 8) highlighted that Product Perception (PWP) strongly mediated the impact of CS, SMI, and CAE on PD and BL, underscoring its role in shaping consumer trust. Additionally, Ethical Considerations (EC) moderated the relationship between SMI, CAE, and consumer behavior, linking ethical branding to long-term loyalty. For industry growth, brands must emphasize transparency in ingredients, ethical sourcing, and digital engagement while regulatory bodies should enforce stricter ethical advertising standards.

Keywords:

Consumer Behavior, Indian Cosmetics Market, Fairness to Wellbeing, Brand Loyalty, Ethical Consumerism, Social Media Influence.

1. Introduction

 

The beauty industry has witnessed a significant transformation, moving beyond traditional ideals to embrace a more holistic and wellness-focused approach. In the past, beauty standards were largely defined by external appearance, often promoting fairness as a key attribute. However, with changing societal perceptions, consumers are now prioritizing products that emphasize self-care, sustainability, and ethical sourcing. This shift has been driven by increased awareness through digital platforms, evolving cultural norms, and a growing demand for transparency in product ingredients. Additionally, social media and influencer marketing have played a crucial role in shaping beauty preferences, encouraging skincare and cosmetic choices that align with personal well-being rather than conventional beauty ideals.

 

As consumers become more conscious of ethical considerations, such as cruelty-free and eco-friendly products, brands are adapting their strategies to meet these expectations. The post-pandemic era has further reinforced this transition, with an increased focus on health, wellness, and mindful consumption. Despite these trends, there remains a need to understand the factors influencing consumer purchasing decisions and brand loyalty in this evolving landscape. This study explores the role of cultural and social influences, regulatory changes, social media impact, and consumer awareness in shaping the beauty industry.

 

The global cosmetic industry has witnessed a transformative shift from fairness-driven beauty standards to a more holistic, wellness-centric approach. This evolution reflects changing consumer perceptions, heightened ethical awareness, and regulatory interventions (Sharma et al., 2021). In India, fairness creams dominated the beauty market for decades, largely influenced by socio-cultural beliefs that associated lighter skin with social and professional success (Singh & Jha, 2013). However, recent trends indicate a growing preference for cosmetics that emphasize eco-friendliness, ethical sourcing, and sustainability (Ladhari & Tchetgna, 2017).

 

Several factors have contributed to this paradigm shift, including increased access to digital media, evolving cultural beauty standards, and rising demand for ingredient transparency (Hassan et al., 2021). Social media platforms and influencer marketing further accelerate this transition, reshaping consumer preferences towards skincare and beauty routines focused on self-care and overall well-being (Lee & Lee, 2022). The post-pandemic era has intensified this focus, with consumers actively seeking dermatologically tested, natural, and cruelty-free products as part of a broader wellness movement (Choi & Kim, 2024).

 

While the transition from fairness-based beauty ideals to wellness-oriented products has been widely acknowledged, there remains a significant gap in understanding the factors influencing consumer purchase decisions (PD) and brand loyalty (BL) in the Indian cosmetics market. Previous studies have largely examined the effects of advertisements and celebrity endorsements on fairness products (Kwon, 2023). However, limited research has explored the mediating role of Ethical Considerations (EC) and Perception of Well-being Products (PWP) in shaping consumer choices. Furthermore, the impact of Cultural & Social factors (CS), Market & Regulatory Changes (MRC), Social Media Influence (SMI), and Consumer Awareness & Education (CAE) on PD and BL has not been extensively analyzed in this evolving landscape.

 

The Indian beauty industry is undergoing a major transformation, yet there is a lack of empirical research addressing the key determinants driving this shift. Understanding how CS, MRC, SMI, and CAE influence consumer behavior is crucial for brands seeking to align with evolving market trends. Moreover, the role of PWP as a mediator and EC as a moderator in shaping consumer trust, purchase decisions, and long-term brand loyalty remains unexplored. This study bridges these gaps by examining the interplay between these factors, offering valuable insights for cosmetic brands, policymakers, and marketers striving to adapt to ethical, sustainable, and wellness-oriented beauty trends in India.

 

2. Review of Literature

The Indian cosmetics industry has been transitioning from fairness-driven aesthetics to wellness-focused consumption, influenced by global sustainability initiatives, regulatory frameworks, and shifting consumer expectations (Sharma et al., 2021). Traditionally, fairness creams dominated the market due to deeply rooted socio-cultural norms linking fair skin with social status and financial success (Singh & Jha, 2013). However, increasing awareness about ethical considerations, brand trust, and ingredient transparency has fueled demand for natural, organic, and dermatologically safe products (Verma & Singh, 2020).

2.1 Theoretical Frameworks: Consumer Behavior and Decision-Making Models

Understanding consumer behavior in the cosmetics industry requires examining the Theory of Planned Behavior (TPB) and the Consumer Decision-Making Model (CDM). TPB explains consumer attitudes, subjective norms, and perceived behavioral control in shaping purchase intentions (Ajzen, 1991). Meanwhile, CDM outlines the process of consumer choice, from need recognition and information search to evaluation, purchase, and post-purchase behavior (Blackwell et al., 2006). These models provide a foundation for analyzing how ethical considerations, brand loyalty, and social influence impact purchasing behavior.

2.2 Ethical Consumerism and Evolving Beauty Standards

Ethics in the cosmetics industry encompass corporate social responsibility (CSR), transparency, cruelty-free practices, and sustainability (Kwon, 2023). Consumers today are increasingly conscious of ethical sourcing, product authenticity, and environmental impact (Ladhari & Tchetgna, 2017). Skepticism towards fairness products is rising due to misleading claims, prompting a shift toward organic skincare and dermatologist-approved formulations (Mukherjee & Patel, 2022). Similarly, regulatory interventions have played a crucial role in shaping ethical industry practices by restricting misleading advertisements and enforcing ingredient transparency (Hussain & Prakash, 2020). With mandatory cruelty-free certifications and stricter guidelines, brands are being pushed toward responsible production and ethical marketing (Saha & Kumar, 2019). Additionally, cultural shifts and inclusivity movements are redefining beauty ideals. Historically, Indian beauty standards were shaped by colonial influences and Bollywood endorsements (Singh & Jha, 2013), but globalization and changing social values have encouraged a move toward personalized skincare, natural skin tones, and body positivity (Sharma et al., 2021). The demand for holistic, well-being-focused beauty products further reflects this shift, as consumers prioritize chemical-free, non-toxic, and dermatologist-tested formulations (Choi & Kim, 2024).

2.3 Brand Loyalty, Ethical Marketing, and Purchase Behavior

Brand loyalty in the cosmetics industry is driven by trust, product quality, and ethical credibility (Oliver, 1999). Consumers increasingly favor brands that emphasize ingredient safety, cruelty-free formulations, and eco-conscious packaging (Hussain & Prakash, 2020). Ethical branding plays a crucial role in enhancing perceived value, fostering customer advocacy, and ensuring long-term consumer retention (Saha & Kumar, 2019). Consumer purchase decisions are also influenced by ethical considerations, brand reputation, and product efficacy (Blackwell et al., 2006). Ethical certifications, influencer endorsements, and dermatological approvals significantly impact purchase intent and brand trust (Mukherjee & Patel, 2022). Transparency in ingredient sourcing, product labeling, and corporate responsibility further strengthens consumer confidence in ethical brands (Verma & Singh, 2020). The demand for well-being products is on the rise, with consumers increasingly assessing health benefits, dermatological safety, and natural formulations before making a purchase (Hassan et al., 2021).

2.4 Digital Influence, Social Media, and Market Transformation

Social media has transformed the beauty industry, with platforms like Instagram, YouTube, and TikTok driving real-time engagement, brand storytelling, and influencer-led endorsements (Choi & Kim, 2024). Consumers heavily rely on peer reviews, digital marketing, and influencer recommendations, increasing both brand credibility and consumer trust (Lee & Lee, 2022). Research shows that brands effectively utilizing digital platforms experience stronger audience engagement, improved conversions, and higher purchase intent (Kwon, 2023). This digital influence is reshaping market dynamics and regulatory frameworks. Regulatory shifts have mandated ingredient disclosures, ethical marketing, and cruelty-free certifications, encouraging brands to prioritize sustainable and transparent practices (Saha & Kumar, 2019). The rise of clean beauty and sustainable cosmetics reflects a broader market transformation where brands must align with consumer expectations for authenticity, safety, and ethical responsibility (Sharma et al., 2021).

This literature review integrates theoretical perspectives and empirical findings to explain the key relationships explored in this study. The shift from fairness-based beauty to well-being-centric cosmetics is driven by ethical awareness, regulatory policies, and social media influence. As consumer expectations evolve, brands must align their strategies with sustainability, ingredient transparency, and ethical branding to ensure long-term loyalty and relevance in the Indian cosmetics market. Understanding these industry trends will help businesses cater to the increasing demand for ethical, inclusive, and wellness-oriented beauty products while maintaining consumer trust and brand sustainability.

2.5 Hypotheses Developed

The hypotheses are grounded in the literature reviewed in the previous section, providing a strong basis for the formulation. This study offers a fresh perspective in the field, drawing from the relatively available literature.

 

Ethical considerations, including cruelty-free testing, sustainability, and ingredient transparency, play a crucial role in consumer purchasing behavior and brand loyalty in the cosmetics industry (Verma & Tripathi, 2019; Choudhury & Das, 2020). Consumers exhibit stronger loyalty to brands emphasizing ethical values and sustainability, making brand loyalty influenced by perceptions of well-being products and ethical considerations (Oliver, 1999; Kwon, 2023; Ladhari & Tchetgna, 2017). The shift from fairness to wellness-oriented cosmetics reflects consumer preference for clean beauty and health-enhancing formulations, positively impacting purchasing decisions and mediating the role of social media (Hassan et al., 2021; Mukherjee & Patel, 2022). Digital marketing, cultural influences, and regulatory changes further shape consumer choices, with social media significantly driving awareness and trust in ethical brands (Blackwell et al., 2006; Lee & Kim, 2021). The evolving Indian beauty industry, influenced by shifting cultural narratives, stricter regulations, and social media engagement, reinforces the importance of sustainable branding and ingredient transparency (Singh & Jha, 2013; Sharma et al., 2021; Hussain & Prakash, 2020). Consequently, ethical considerations, social media influence, and perceptions of well-being products are expected to drive purchasing decisions and brand loyalty in the cosmetics market.

2.5.1 Direct Effects Hypotheses

• H1a: Cultural and social factors (CS) have a positive influence on purchasing decisions (PD).
• H1b: Cultural and social factors (CS) have a positive influence on brand loyalty (BL).
• H1c: Market and regulatory changes (MRC) have a positive influence on purchasing decisions (PD).
• H1d: Market and regulatory changes (MRC) have a positive influence on brand loyalty (BL).
• H1e: Social media influence (SMI) positively affects purchasing decisions (PD).
• H1f: Social media influence (SMI) positively affects brand loyalty (BL).
• H1g: Consumer awareness and ethical considerations (CAE) positively affect purchasing decisions (PD).
• H1h: Consumer awareness and ethical considerations (CAE) positively affect brand loyalty (BL).

2.5.2 Mediating Role of Perception of well being Products (PWP)

• H2a: Perception of well being products (PWP) mediates the relationship between cultural and social factors (CS) and purchasing decisions (PD).
• H2b: Perception of well being products (PWP) mediates the relationship between market and regulatory changes (MRC) and purchasing decisions (PD).
• H2c: Perception of well being products (PWP) mediates the relationship between social media influence (SMI) and purchasing decisions (PD).
• H2d: Perception of well being products (PWP) mediates the relationship between consumer awareness and ethical considerations (CAE) and purchasing decisions (PD).
• H2e: Perception of well being products (PWP) mediates the relationship between cultural and social factors (CS) and brand loyalty (BL).
• H2f: Perception of well being products (PWP) mediates the relationship between market and regulatory changes (MRC) and brand loyalty (BL).
• H2g: Perception of well being products (PWP) mediates the relationship between social media influence (SMI) and brand loyalty (BL).
• H2h: Perception of well being products (PWP) mediates the relationship between consumer awareness and ethical considerations (CAE) and brand loyalty (BL).

2.5.3 Mediating Role of Ethical Considerations (EC)

• H3a: Ethical considerations (EC) mediate the relationship between cultural and social factors (CS) and purchasing decisions (PD).
• H3b: Ethical considerations (EC) mediate the relationship between market and regulatory changes (MRC) and purchasing decisions (PD).
• H3c: Ethical considerations (EC) mediate the relationship between social media influence (SMI) and purchasing decisions (PD).
• H3d: Ethical considerations (EC) mediate the relationship between consumer awareness and ethical considerations (CAE) and purchasing decisions (PD).
• H3e: Ethical considerations (EC) mediate the relationship between cultural and social factors (CS) and brand loyalty (BL).
• H3f: Ethical considerations (EC) mediate the relationship between market and regulatory changes (MRC) and brand loyalty (BL).
• H3g: Ethical considerations (EC) mediate the relationship between social media influence (SMI) and brand loyalty (BL).
• H3h: Ethical considerations (EC) mediate the relationship between consumer awareness and ethical considerations (CAE) and brand loyalty (BL).

3. Methodology

This study employed quantitative research methods to assess ethical concerns and consumer preferences in the Indian cosmetics market. The target population consisted of Indian consumers aged 18 to 50, as this demographic represents the most engaged segment in the cosmetics and skincare industry (Hassan et al., 2021). To ensure diverse representation, a stratified random sampling method was applied, considering factors such as cosmetic usage frequency, gender, occupation, and age. The survey was distributed through both online platforms (Google Forms, social media, and email) and offline methods (in-person interactions at cosmetic retail stores) to enhance response validity and minimize potential sample bias. A sample size of 276 respondents was determined using G*Power analysis (Hair et al., 2017), ensuring statistical sufficiency for Structural Equation Modeling (SEM) (Haenlein & Kaplan, 2002). Following Cohen’s effect size criteria (1988), which recommends a sample of 200–300 respondents for a medium effect size (0.15) and power = 0.80, the selected sample size met the required threshold for generalizability and reliability.

4. Data Analysis

To establish the factor structure of the study, Exploratory Factor Analysis (EFA) was conducted, assessing factor loadings and item correlations (Costello & Osborne, 2005). While the study is based on established constructs, EFA ensured that no items exhibited significant cross-loadings onto multiple factors. The Kaiser-Meyer-Olkin (KMO) test and Bartlett’s Test of Sphericity were performed to verify the adequacy of the dataset, ensuring that the observed variables shared sufficient common variance for factor analysis. For data processing, SPSS 27.0 was used to perform data cleaning, descriptive statistics, reliability analysis, and EFA. Additionally, AMOS 24.0 was utilized for Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM), and mediation analysis to examine hypothesized relationships. These analytical tools provided robust statistical validation, ensuring reliable insights into the ethical considerations and consumer preferences influencing purchase decisions in the Indian cosmetics industry.

 

Table 1 Demographic results

 

Particulars		Count	Column N %
Gender	Male	60	21.7%
	Female	216	78.3%
Age	18 to 30 Years	47	17.0%
	30 to 40 Years	99	35.9%
	40 to 50 Years	117	42.4%
	Above 50 Years	13	4.7%
Work Experience	Less than 1 Year	123	44.6%
	1 to 5 Years	71	25.7%
	5 to 10 Years	65	23.6%
	Above 10 Years	17	6.2%
Educational Background	Bachelor's Degree	133	48.2%
	Master's	110	39.9%
	Doctorate	33	12.0%
Occupation	Employed full-time	119	43.1%
	Student,	130	47.1%
	Self-employed	27	9.8%
Marital Status	Single	145	52.5%
	Married	114	41.3%
	Divorced	17	6.2%
Importance of Ingredient composition of cosmetic products to you	Important	232	84.1%
	Neutral	24	8.7%
	Not important	20	7.2%
Preference for natural cosmetic products	Prefer	235	85.1%
	Neutral	23	8.3%
	Do not prefer	18	6.5%
Do you perceive the importance of fairness in personal beauty	Important	220	79.7%
	Neutral	26	9.4%
	Not important	30	10.9%
Have you used fairness products in the past	Yes	227	82.2%
	No	49	17.8%

 

The test results in Table 1 reveals that the majority of respondents are female (78.3%) and primarily fall within the age range of 30 to 50 years (78.3%). A significant portion has less than 1 year of work experience (44.6%) and holds at least a bachelor's degree (48.2%). The respondents are mainly full-time employees (43.1%) or students (47.1%). Most respondents are single (52.5%), with a considerable number also being married (41.3%). There is a strong emphasis on the importance of ingredient composition in cosmetic products (84.1%) and a notable preference for natural cosmetic products (85.1%). Despite the shift towards wellbeing, a large majority still perceives fairness as important in personal beauty (79.7%) and have used fairness products in the past (82.2%).

 

 

Table 2 KMO and Bartlett's Test

 

KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.923
Bartlett's Test of Sphericity	Approx. Chi-Square	11353.240
	df	1275
	Sig.	.000

The test results Table 2 of the KMO and Bartlett's Test indicate that the data is suitable for factor analysis. The Kaiser-Meyer-Olkin (KMO) Measure of Sampling Adequacy is exceptionally high at 0.923, suggesting that the sample size is adequate and the items are likely to share common factors.

Table 3 Rotated Component Matrix^a

Rotated Component Matrixa
	Component
	EC	PWP	BL	PD	CS	MRC	SMI	CAE
H_1							.783
H_3							.567
H_9							.803
H_10							.756
B_1			.682
B_2			.784
B_3			.735
B_4			.782
B_5			.766
B_6			.722
B_7			.739
B_8			.568
F_1					.760
F_2					.831
F_3					.632
F_4					.607
F_5					.808
F_6					.721
C_1		.830
C_2		.863
C_3		.859
C_4		.753
C_5		.745
C_6		.824
D_3				.650
D_4				.719
D_5				.615
D_6				.592
D_7				.678
D_8				.687
A_1	.846
A_2	.860
A_3	.885
A_4	.871
A_5	.884
A_6	.858
A_7	.759
I_2								.748
I_9								.787
I_10								.736
G_1						.852
G_2						.827
G_3						.831
G_4						.709
G_5						.778
Extraction Method: Principal Component Analysis. , Rotation Method: Varimax with Kaiser Normalization.a
a. Rotation converged in 7 iterations.

 

The test results in Table 3 shows the Rotated Component Matrix results from the Principal Component Analysis using Varimax rotation with Kaiser Normalization indicate shows the factor loadings across various components.

 

Confirmatory Factor Analysis

 

The AMOS version 18 is used for performing the Confirmatory Factor Analysis (Arbuckel, 2009). The model is assessed for testing the reliability, convergent validity, and discriminant validity. The Confirmatory factor Analysis   diagram (Figure 1) shows the relationship between various latent variables and their observed indicators in context of Indian cosmetic industry's shift from fairness to wellbeing.

 

Figure 1 CFA Model

 

Figure 1 the AMOS version 18 is used for performing the Confirmatory Factor Analysis (Arbuckel, 2009). The model is assessed for testing the reliability, convergent validity, and discriminant validity. The Confirmatory factor Analysis   diagram (Figure 1) shows the relationship between various latent variables and their observed indicators in context of Indian cosmetic industry's shift from fairness to wellbeing.

 

Table 4 Reliability and Convergent Validity

 

Items		Variables/ Constructs	Standardized Factor Loadings	Cronbach’s Alpha	Composite Reliability	Average Variance Extracted	Maximum Shared Variance
A_1	<---	Ethical consideration (EC)	0.93	0.9234	0.976	0.854	0.364
A_2	<---		0.948
A_3	<---		0.955
A_4	<---		0.942
A_5	<---		0.948
A_6	<---		0.903
A_7	<---		0.838
C_1	<---	Brand Loyalty (BL)	0.928	0.8903	0.959	0.795	0.544
C_2	<---		0.946
C_3	<---		0.94
C_4	<---		0.837
C_5	<---		0.835
C_6	<---		0.856
B_1	<---	Perception of well being Products (PWP)	0.714	0.755	0.916	0.583	0.384
B_2	<---		0.878
B_3	<---		0.83
B_4	<---		0.862
B_5	<---		0.755
B_6	<---		0.773
B_7	<---		0.742
B_8	<---		0.486
D_3	<---	Purchasing Decision (PD)	0.857	0.8328	0.933	0.703	0.544
D_4	<---		0.898
D_5	<---		0.913
D_6	<---		0.65
D_7	<---		0.925
D_8	<---		0.754
F_1	<---	Cultural and Social Factors (CS)	0.718	0.6846	0.843	0.478	0.091
F_2	<---		0.831
F_3	<---		0.578
F_4	<---		0.557
F_5	<---		0.762
F_6	<---		0.662
G_2	<---	Market and Regulatory Changes(MRC)	0.821	0.7362	0.827	0.546	0.022
G_3	<---		0.773
G_4	<---		0.651
G_5	<---		0.7
H_1	<---	Social Media Influence (SMI)	0.794	0.7052	0.820	0.536	0.233
H_3	<---		0.576
H_9	<---		0.787
H_10	<---		0.752
I_2	<---		0.697
I_9	<---		0.674
I_10	<---		0.657
Model Fitness: X2=1565.775, df=875, X2/df= 1.792, RMSEA=.054, CFI=.931, NFI= 0.858, RFI= 0.839, IFI= 0.952, PNFI= 0.757, PCFI= 0.822

 

The test results in Table 4 shows in a single-model study, model fitness needs to be assessed to ensure that the relationships hypothesized align with real-world data (Kline, 2015). The result of CFA model (Figure 1) shows that model had good fit statistics including X2/df= 1.792, RMSEA=.054, CFI=.931, NFI= 0.858, RFI= 0.839, IFI= 0.952, PNFI= 0.757, PCFI= 0.822.  The recommended values are based on Hu and Bentler (1999) and Browne and Cudeck (1992) guidelines (RMSEA<.08, RMR<.05, CFI>.90). Even there is only one model, CFI helps determine how well the theoretical model represents the actual data (Bentler, 1990). A CFI value above 0.90 indicates a good fit, suggesting that the hypothesized relationships are well-supported by the data (Hu & Bentler, 1999). All items standardized factor loading was above 0.60 and AVE is also above 0.50 so it is an indication of good convergent validity (Hair et al., 2017). The Cronbach alpha and composite reliability for all variables are above 0.70 so it shows that our variables had good reliability.

Table 5 Divergent validity

 

	EC	BC	PWP	PD	CS	MRC	SMI	CAE1
EC	0.924							0.161*
BC	0.549*	0.892						0.106
PWP	0.572*	0.551*	0.764					0.134
PD	0.603*	0.738*	0.620*	0.839				0.148*
CS	0.156*	0.287*	0.118	0.301*	0.691			0.047
MRC	0.150*	0.103	0.077	0.077	0.135	0.739		0.148
SMI	0.301*	0.318*	0.434*	0.483*	0.294*	0.130	0.732	0.157*
CAE								0.676

* < 0.050

The divergent validity analysis in Table 5 highlights the correlations among the latent variables, confirming that each construct is distinct from the others (Hu & Bentler (1999), Malhotra & Dash (2011)).

 

Hypotheses Testing (Structural Model)

 

To examine the relationship between Social Media Influence (SMI), Consumer Awareness and Education (CAE), Cultural and Social Factors (CS), Market and Regulatory Changes (MRC) and Purchasing Decisions (PD) and Brand Loyalty (BL), we used the structural equation modelling using the AMOS path analysis.  Figure 2 shows the graphical representation of structural model without mediation. Further, we have tested. Whereas, Figure 3 and 4 shows the graphical representation of structural model with Perception of wellbeing Products (PWP) and Ethical Considerations (EC) as a mediators. 

 

 

 

SEM Model without Mediation

Figure 2: SEM Measurement Model without Mediation-Results

 

Table 6a- Model Summary^b

 

Table 6a- Model Summaryb
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	.538a	.290	.279	.45416	.290	27.659	4	271	.000
a. Predictors: (Constant), CAE, CS, MRC, SMI
b. Dependent Variable: PD

 

Table 6b- ANOVA^a

 

Table 6b- ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	22.820	4	5.705	27.659	.000b
	Residual	55.896	271	.206
	Total	78.716	275
a. Dependent Variable: PD
b. Predictors: (Constant), CAE, CS, MRC, SMI

 

The Model Summary (Table 6a) reveals that the independent variables (CS, MRC, SMI, and CAE) collectively explain 29.0% of the variance in PD (R² = 0.290, Adjusted R² = 0.279, p < 0.001). R² value suggest that the selected predictors account for a moderate proportion of the variation in purchasing decisions (Figure 2). The ANOVA results (Table 6b) confirm that the regression model for PD is statistically significant (F = 27.659, p < 0.001), indicating that CS, MRC, SMI, and CAE collectively influence consumer purchasing behavior.

Table 7a- Model Summary^b

 

Table 7a- Model Summaryb
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics
					R Square Change	F Change	df1	df2	Sig. F Change
1	.464a	.216	.204	.46856	.216	18.623	4	271	.000
a. Predictors: (Constant), CAE, CS, MRC, SMI
b. Dependent Variable: BL

 

Table 7b- ANOVA^a

 

Table 7b- ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	16.355	4	4.089	18.623	.000b
	Residual	59.498	271	.220
	Total	75.853	275
a. Dependent Variable: BL
b. Predictors: (Constant), CAE, CS, MRC, SMI

The Model Summary (Table 7a) reveals that the independent variables collectively explain 21.6% of the variance in Brand Loyalty (R² = 0.216, Adjusted R² = 0.204, p < 0.001).  The ANOVA results (Table 7b) confirm that the regression model is statistically significant (F = 18.623, p < 0.001), indicating that the selected variables significantly impact brand loyalty (Figure 2).

Table 8:  Results of Structural Model without Mediation.

 

Hypotheses	Hypothesized Relationship			Estimate(β )	P Value	Results
H1a	PD	<---	CS	.173	***	Supported
H1b	BL	<---	CS	-.011	.822	rejected
H1c	PD	<---	MRC	-.020	.549	rejected
H1d	BL	<---	MRC	-.003	.923	rejected
H1d	PD	<---	SMI	.471	***	Supported
H1e	BL	<---	SMI	.487	***	Supported
H1f	PD	<---	CAE	.097	.070	Rejected
H1g	BL	<---	CAE	.085	.123	Rejected

 

The results of the structural model without mediation reveal the direct effects of Cultural and Social Factors (CS), Market and Regulatory Changes (MRC), Social Media Influence (SMI), and Consumer Awareness and Education (CAE) on Purchasing Decision (PD) and Brand Loyalty (BL) (Figure 2). The findings indicate that CS and SMI have significant positive effects on PD, with estimates of .173 and .471, respectively (Table 8). SMI also has a significant positive effect on BL, with an estimate of .487. However, CS has no significant effect on BL, and neither MRC nor CAE shows significant direct effects on either PD or BL.

 

 

 

 

• SEM Model with Mediation

 

Figure 3: Structure equation model with Perception of wellbeing Products (PWP) as mediator	Figure 4: Structure equation model with Ethical Consideration (EC) as mediator.

 

Table 9 Results of Structural Model with Perception of wellbeing Products (PWP) as mediator.

 

Hypothesized Relationship			Estimate	S.E.	P	Results
PWP	<---	CS	.196	.051	***	Supported
PWP	<---	MRC	.014	.035	.696	Rejected
PWP	<---	SMI	.264	.064	***	Supported
PWP	<---	CAE	.067	.056	.232	Rejected
PD	<---	PWP	.794	.040	***	Supported
BL	<---	PWP	.593	.050	***	Supported

 

The results of the structural model with Perception of well being Products (PWP) as a mediator (Figure 3, Table 9) reveal significant relationships between Cultural and Social Factors (CS) and Social Media Influence (SMI) and PWP, while Market and Regulatory Changes (MRC) and Consumer Awareness and Education (CAE) do not show significant direct effects on PWP. PWP, in turn, significantly impacts both Purchasing Decision (PD) and Brand Loyalty (BL).

 

Table 10 Results of Structural Model with Ethical Consideration (EC) as mediator.

 

Hypothesized Relationship			Estimate	S.E.	P	Results
EC	<---	SMI	.432	.105	***	Supported
EC	<---	MRC	.056	.059	.335	Rejected
EC	<---	CS	.101	.084	.229	Rejected
EC	<---	CAE	.215	.093	.021*	Supported
BL	<---	EC	.374	.030	***	Supported
PD	<---	EC	.397		***	Supported

*<.05, *** <0.001

 

Table 10 shows that Ethical Consideration (EC) mediates the relationships between Social Media Influence (SMI) (estimate = 0.432, C.R. = 4.098, p < 0.001) and Consumer Awareness and Education (CAE) (estimate = 0.215, C.R. = 2.310, p = 0.021) with other latent variables.

Ethical Consideration (EC) also directly influences Brand Loyalty (BL) (estimate = 0.374, C.R. = 12.271, p < 0.001) and Purchasing Decision (PD) (estimate = 0.397, C.R. = 13.134, p < 0.001), highlighting its direct impact on consumer behaviours. Whereas EC mediation with Market and Regulatory Changes (MRC) and Cultural and Social Factors (CS) shows no significant relationship (Figure 4).

 

Mediation Analysis

 

The mediation analysis is based on the analysis of indirect effects based on the guideline by Baron and Kenny (1986) classical approach We performed mediation analysis by using the direct and indirect effects based on bootstrap procedures (2000 samples) and bias-corrected bootstrap confidence interval (90%). The results are provided in the following table. 

 

Table 11 Mediation analysis with Perception of wellbeing Products (PWP) as mediator

 

Hypothesis	Path	Total Effects	Direct Effects	Indirect Effects	Remarks
H2a	CS>PWP>PD	.155	.000	.155*	Hypothesis supported since indirect effects are statistically significant
H2b	MRC>PWP>PD	.011	.000	.011*	Hypothesis supported since indirect effects are statistically significant
H2c	SMI>PWP>PD	.210	.000	.210*	Hypothesis supported since indirect effects are statistically significant
H2d	CAE>PWP>PD	.053	.000	.053*	Hypothesis supported since indirect effects are statistically significant
H02e	CS>PWP>BL	.116	.000	.116*	Hypothesis supported since indirect effects are statistically significant
H2f	MRC>PWP>BL	.008	.000	.008*	Hypothesis supported since indirect effects are statistically significant
H2g	SMI>PWP>BL	.157	.000	.157*	Hypothesis supported since indirect effects are statistically significant
H2h	CAE>PWP>BL	.040	.000	.040*	Hypothesis supported since indirect effects are statistically significant

*<.05

These results confirm that PWP significantly mediates the effects of CS, MRC, SMI, and CAE on PD and BL (Table 11). This highlights that consumer perception of well being products plays a critical role in shaping purchasing behavior and brand loyalty.

 

Table 12 Mediation analysis with Ethical Consideration (EC) as mediator.

 

Hypothesis	Path	Total Effects	Direct Effects	Indirect Effects	Remarks
H3a	CS>EC>PD	.040	.000	.040*	Hypothesis supported since indirect effects are statistically significant
H3b	MRC>EC>PD	.022	.000	.022*	Hypothesis supported since indirect effects are statistically significant
H3c	SMI>EC>PD	.172	.000	.172*	Hypothesis supported since indirect effects are statistically significant
H3d	CAE>EC>PD	.086	.000	.086*	Hypothesis supported since indirect effects are statistically significant
H3e	CS>EC>BL	.038	.000	.038*	Hypothesis supported since indirect effects are statistically significant
H3f	MRC>EC>BL	.021	.000	.021*	Hypothesis supported since indirect effects are statistically significant
H3g	SMI>EC>BL	.080	.000	.080*	Hypothesis supported since indirect effects are statistically significant
H3h	CAE>EC>BL	.161	.000	.161*	Hypothesis supported since indirect effects are statistically significant

*<.05

Table 12 demonstrates that Ethical Considerations (EC) significantly mediate the relationships between CS, MRC, SMI, CAE, and both PD and BL. This confirms that consumer preference for ethically responsible products influences both purchasing decisions and brand loyalty. The mediation analysis results provide a comprehensive understanding of how consumer perception of well being products and ethical considerations influence purchasing decisions and brand loyalty. Both mediators show statistically significant indirect effects, emphasizing the importance of social influence, cultural factors, regulatory changes, and consumer awareness in driving ethical and wellness-oriented purchasing behavior in the Indian cosmetic industry. These findings align with previous research highlighting the role of ethical and well being-focused branding in shaping modern consumer preferences.

• Discussion of this study

Past research has largely explored the influence of fairness creams and their socio-cultural implications (Singh & Jha, 2013; Sharma et al., 2021). However, this study broadens the scope by examining the interplay of ethical considerations (EC), brand loyalty (BL), and perceptions of well-being products (PWP) in consumer behavior. While earlier studies emphasized price sensitivity and brand image as key factors in purchasing decisions (Ladhari & Tchetgna, 2017), this research highlights the growing influence of ethical transparency and digital engagement as dominant drivers of consumer choices (Hassan et al., 2021). The study provides empirical evidence that PWP and EC act as mediators in shaping the impact of social media, cultural influences, and regulatory policies on consumer behavior. The findings align with contemporary research, indicating that sustainable and ecologically responsible business practices enhance consumer trust and engagement (Kwon, 2023; Choi & Kim, 2024). These insights are crucial for cosmetic marketers, legislators, and manufacturers, helping them adapt to shifting consumer expectations. The demand for ingredient transparency, cruelty-free certifications, and dermatologically safe products is increasing, making it essential for brands to integrate ethical and wellness-focused marketing strategies (Mukherjee & Patel, 2022). Regulatory bodies can leverage these insights to strengthen consumer protection policies and address misleading claims surrounding fairness-based cosmetics (Saha & Kumar, 2019).

Unlike previous research, which often provided a limited psychological perspective on fairness consumption (Verma & Singh, 2020), this study takes a behavioral approach, integrating ethical attributes, social influence over time, and the impact of loyalty on purchasing decisions. Using Structural Equation Modeling (SEM), the study quantitatively validates these relationships, contributing to a comprehensive theory of modern consumer preferences in India’s cosmetic sector. This research significantly expands the literature by establishing an empirical framework that connects social media exposure, ethical awareness, and well-being perceptions with purchase behavior and brand loyalty. The study further explores trends in ingredient choices, sustainability, and ethical consumerism, offering valuable insights into the evolving beauty landscape. It provides strategic recommendations for marketers, policymakers, and academics, paving the way for future advancements in consumer psychology, ethical branding, and regulatory measures.

• Implications of the Study

The transition from fairness-focused cosmetics to well-being-centric beauty products presents significant advantages for both businesses and regulators. Findings emphasize the role of ethical considerations, social media influence, and perceived well-being aspects in shaping consumer perceptions of cosmetic brands (Hassan et al., 2021). Key factors such as sustainable sourcing, cruelty-free certifications, and ingredient transparency have become pivotal in consumer decision-making. Additionally, influencer endorsements and digital marketing serve as powerful tools, significantly influencing final purchasing choices and reinforcing brand credibility (Choi & Kim, 2024). To cater to wellness-conscious consumers, brands must shift their marketing narratives to emphasize hygiene and skincare benefits over traditional beauty ideals (Sharma et al., 2021). The study's findings have practical implications for regulatory bodies, particularly in strengthening policies related to cosmetic labeling, misleading advertisements, and ingredient disclosures. Enforcing consumer protection laws is crucial to curbing deceptive marketing tactics in fairness products while ensuring a level playing field for ethical brands (Saha & Kumar, 2019). Governments should implement stricter branding ethics to promote long-term industry commitment to sustainability and transparency (Mukherjee & Patel, 2022). Additionally, public initiatives advocating inclusive beauty and wellness-oriented consumption can contribute to the ethical transformation of the cosmetics industry (Singh & Jha, 2013).

This research underscores the growing consumer preference for ethical, sustainable, and health-conscious beauty products. Ethical branding and transparency significantly impact long-term brand loyalty, reinforcing the relevance of responsible consumerism (Verma & Singh, 2020). Moreover, consumers are encouraged to base their purchasing decisions on scientific validation, dermatological safety, and sustainability efforts rather than outdated beauty norms (Ladhari & Tchetgna, 2017). This study also fosters confidence and self-acceptance, particularly among individuals with diverse skin tones, by promoting the idea that beauty is rooted in skincare wellness rather than fairness ideals (Sharma et al., 2021). Beyond its industry implications, this research opens new avenues for academic exploration (Choi & Kim, 2024), offering a foundation for future studies on sustainability-driven branding, the effectiveness of digital marketing, and ethical consumer psychology. The results highlight that ethical branding, regulatory compliance, and digital engagement are becoming critical success factors in the cosmetics industry. Brands that align with shifting consumer values—prioritizing well-being, transparency, and ethical accountability—will gain a competitive advantage. The broader impact extends beyond business strategy to policy-making and consumer awareness, reinforcing the global movement towards sustainable and responsible beauty standards.

5. Conclusion

This study examines the evolving consumer preferences in the Indian cosmetics industry, highlighting the transition from fairness-focused products to wellness-oriented beauty solutions. It investigates the interplay between ethical considerations (EC), brand loyalty (BL), perception of well-being products (PWP), purchasing decisions (PD), cultural and social factors (CS), market and regulatory changes (MRC), and social media influence (SMI) in shaping consumer choices and brand engagement. Grounded in the Theory of Planned Behavior (Ajzen, 1991) and the Consumer Decision-Making Model (Blackwell et al., 2006), this research provides an academically supported framework explaining why modern consumers increasingly prioritize sustainability, transparency, and ethical accountability in their purchasing decisions. Findings reveal that perceptions of well-being products and ethical considerations serve as key mediators in the relationship between social media, cultural influences, and regulatory policies concerning purchasing decisions and brand loyalty. Ethical branding and sustainability efforts significantly enhance consumer trust and loyalty (Kwon, 2023; Verma & Singh, 2020). Well-informed consumers actively engaging on social media tend to favor transparent ingredient disclosures and ethical practices, leading to higher purchase intent (Choi & Kim, 2024). Regulatory shifts and changing societal views challenge traditional beauty ideals, reinforcing the preference for wellness-focused cosmetic products (Sharma et al., 2021). From a managerial perspective, brands must prioritize responsible sourcing, ingredient transparency, and sustainability certifications to maintain credibility. Influencer marketing and digital engagement should authentically communicate a brand’s ethical commitments (Mukherjee & Patel, 2022). Policymakers should enforce strict regulations on misleading advertisements and promote inclusive beauty awareness campaigns (Saha & Kumar, 2019).

Limitations of the Study

While this study provides valuable insights, it has certain limitations. The research primarily focuses on urban and digitally active consumers, which may overlook the perspectives of rural and lower-income demographics. As a result, the findings may not fully represent the diverse consumer base of the Indian cosmetics market. Additionally, the study captures consumer preferences at a single point in time, making it difficult to assess how these preferences evolve. Incorporating longitudinal data in future research could provide a deeper understanding of shifting trends. Cross-cultural comparisons could also enhance the findings by offering a broader perspective on global trends in ethical and wellness-driven beauty choices (Hassan et al., 2021).

Future Research Directions

This study contributes to both academic and industry discourse by offering empirical evidence on the shift from fairness-driven beauty standards to wellness-focused preferences in India. The findings support marketing strategy development, regulatory policymaking, and ethical consumerism, helping brands align with sustainable, ethical, and health-conscious beauty trends. As consumer awareness continues to grow, brands that embrace transparency and sustainability will gain long-term trust and market leadership (Ladhari & Tchetgna, 2017). Future research could explore the impact of digital trust in beauty marketing, personalized skincare solutions, and the psychological effects of ethical branding, further expanding knowledge in this evolving domain.

Funding

• This research did not receive any funding from external sources.

Conflict of Interests

• The authors declare no conflict of interest in conducting this study.

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