Keywords

Customer Perceived Ethicality, Brand Loyalty, Service Brands, Brand Equity, Structural Equation Modelling

Introduction

Consumers have been demanding ethical behaviour as a hygiene factor while making intelligent choices (Schlegelmilch et al., 2009). Increasingly, firms have been trying to incorporate ethical brand attributes in addition to the conventional features. In this context, CPE is receiving exclusive attention, as different from firm and marketing ethics where studies abound (Lu e al., 2010; Sierra et al., 2017; Hutchinson et al., 2013). Alongside, ‘Ethics in branding’ has been an increasingly researched topic, with branding as a social construct. The relationship between CPE and brand related outcomes and the implications of this relationship have received considerable attention (Singh et al., 2012; Iglesius et al., 2017).

All these studies call for research to be replicated in Asian geographies, given the importance and significantly varying effects on ethical perceptions (Swaidan, 2012; Rawwas et al., 2005; Shang et al., 2016; Belk et al., 2005) and to conduct rigorous exploratory as well as quantitative studies in these geographies.

Accordingly, this research draws from extant research, and studies various relationships that CPE has on a set of brand related outcomes, and draws comparisons between the results so obtained. The study is carried out exclusively in the Service sector in India.

Literature Review

The Service Brand and the Indian context

The share of Services in the Indian National Income has grown significantly and exceeds 50 percent of National Income (Indian Services Industry Report, 2019). Hence it is of paramount importance to conduct studies exclusively in this sector.

In the case of packaged goods the product is the primary brand. In the case of Services (Berry, 2000), the Company is the primary brand as the concept enlarges from a pure service to a brand and then to the level of the organization. Customer experience is an essential constituent of a Service brand. The risks associated with perceived monetary, social and safety risks in buying Services are difficult to evaluate prior to purchase. In the case of Services, there are multiple contact points involving many more (Riley et al., 2000), than just the seller or the agent.

Hence branding is critical in the case of Services and is a principal success driver for service brands. Brodie et al. (2006) provides a two pronged definition of the service brand as both an entity and a process. Both the ‘making of promises’ and the ‘delivery of promises’ in creating customer value and customer loyalty are important (Parasuraman et al., 1988).

A Service Firm needs to ensure that every aspect of the Firm’s Operations is in line with the intended brand communication. The brand promise incorporates the strategic agenda of the Firm as part of brand building (Chernatony, 2001).

The Importance of Brands and the Role of Ethics In Branding

Ethical branding has emerged as a subject of interest as it seeks to integrate business ethics and brand related agenda. Honesty and reliability of a Service Firm leads to customer satisfaction while unethical practices will create dissatisfaction (Thomas et al., 2002, Rawwas et al., 1994). Such brands will get rewarded by discerning consumers (Maxfield, 2008; Viriyavidhayavongs et al., 2002). An ethical brand enhances the firm’s reputation and reinforces the brand in turn (Fan 2005; Page et al., 2005). Huber et al. (2010) define brand misconduct as a disappointing behaviour in the way inside processes take place and investigate how it affects the relationship with the consumer, e.g., the use of child labour in the town of Sivakasi in TN, India for manufacturing crackers in the festive season.

Chahal et al. (2012) find that Service Brand Equity in the healthcare sector is greatly influenced by Brand Loyalty and Perceived Quality. Elbeltagi & Agag (2016) research consumer perceptions of online retailing ethics (CPORE), a second-order construct and composed of five constructs (security, privacy, non-deception, fulfilment/reliability, and service recovery), and find it is strongly predictive of online consumer satisfaction.

Despite so much evidence that CPE of a brand is a critical feature of brand outcomes, not much is known about how to create positive brand CPE (Klink et al., 2017).

Thus there is a growing need for research to understand a brand as consisting of social attributes in addition to economic and utilitarian criteria and establish the relationship that CPE has on brand related outcome variables.

Theoretical Framework

This study draws upon previous research in identifying the relationship of CPE with brand related variables (Singh et al., 2012; Markovic et al., 2018; Sierra et al., 2017). While the cited studies each analyse a single model, in this research multiple relationships of CPE with a set of brand related variables is explored and comparisons are drawn, with Brand equity and Brand Loyalty as the final outcome variables, and Brand Trust, Brand Affect and Perceived Service Quality as intervening as well as dependent variables. Multiple paths are identified and structural equation modelling is deployed to identify the strength and direction of relationships that CPE as an exogenous variable exhibits with these dependent variables. Mediation Analysis is also carried out to test the direct and indirect effects of these relationships. Comparisons are drawn between the multiple sets of relationships and a slew of learnings emerge.

The Basis for A Conceptual Framework and Identifying Mediating Variables

Extant literature mentions that attitude is made up of three components: 1. Cognitive-the thoughts and beliefs one has about the object/decision; 2. Affective-feelings and emotions about the object; 3. Behavioural-the behaviour one exhibits when faced with the object/decision (Breckler, 1984).

Thus it is necessary to determine how the cognition of CPE leads to emotional Affect, described as the construct ‘Brand Affect (BA)’ (Bloemer et al., 2003; Fullerton, 2005, Perez, 2009), and to the more calculated, discerned outcome of ‘Brand Trust (BT)’ (Gurviez et al., 2003; Keh et al., 2009; Morgan et al., 1994; Akbar et al., 2009). In a service context in particular, literature has dealt with the criterion of ‘quality of service’ and perceptions regarding quality of service as an essential determinant of subsequent behaviour (Parasuraman et al., 1985; Mende et al., 2011; Lien et al., 2014; Garcia de los Salmones et al., 2005; Chao-Chan Wu. 2011; Roostika, R, 2011; Shriedeh et al., 2017). Hence perceived service quality (PSQ) is a likely outcome/intervening variable. Brand Loyalty (BL) and Brand Equity (BE) are two important final outcome variables, even though CPE may or may not have a direct relationship with these outcomes.

Brand Equity is an all-encompassing Construct that subsumes variables such as commitment and loyalty (Aaker, 2009; Keller, 1993; Cobb-Walgren, 1995). Hence a study of the relationship that CPE has, with the ‘behavioural’ Construct of Brand Equity (Nella et al., 2014; Cronin et al., 2000; Jahanzeb et al., 2013; He et al.,2011), with Brand Affect/Brand Trust as mediating variables will be in order. Since the research is undertaken in the area of Services, the relationship that CPE has on Brand Equity through the mediating variable of Perceived Quality of Service will again be in order (Zeithaml et al., 1996). Brand Loyalty is an important constituent of Brand Equity. Thus Brand Loyalty can also be an outcome variable (Bennur et al., 2016; Upamanyu et al., 2012; Gecti et al., 2013; Li et al., 2012).

Conceptual Framework

In line with the above, four alternate Models are identified, to understand how Brand Loyalty (BL) / Brand Equity (BE) can be enhanced through enhancement of CPE. These alternate Models help in finely differentiating between the strength of the relationships depending on the variables chosen.

To summarise, the study sets out the following objectives:

1. To assess the relationships that CPE of Services brands has with a.) Brand Loyalty and b.) Brand Equity through the mediating variables of PSQ and BA.

2. To assess the relationships that CPE of Services brands has with a.) Brand Loyalty and b.) Brand Equity through the mediating variables of PSQ and BT.

3. To evaluate the direct and indirect effects in the above relationships.

4. To draw comparisons between the direction and strength of the above four relationships and to draw inferences.

The research hypotheses given alongside the relational paths in the conceptual framework (Figure 1) are to be tested using SEM methodology. The change from one Model to the next and how they relate to one another is illustrated.

Research Methodology

Sampling technique, Questionnaire Design, Administration, Data collection

To start with, psychometrically sound scales for the six Constructs CPE, PSQ, BA, BT, BL and BE were identified through a thorough examination of extant literature (Table 1). Survey was conducted using a Likert 7-point scale questionnaire, designed and tested with four experts. Respondents were identified through a snowballing approach from across the country and close to 700 responses were obtained and uploaded in Google forms. The design ensured that scope for missing data was totally eliminated. A sample size of 503 usable samples was achieved after eliminating outliers. Responder fatigue and lack of interest can be identified judging from a combination of extreme as well as uniform responses. A rigorous approach to eliminating outliers ensures soundness of data analysis and conclusions. Data was loaded onto SPSS 23 software based on a systematic coding scheme. The Demographics of the respondents revealed a uniform representation on all criteria such as Age, Gender, Education, Profession etc. and they were spread throughout the country (Table 2).

Table 1 Summary of All Six Constructs And Their Measurement Items
Construct and Items	Reference
CPE In my view, the brand is from a firm that abides by the law The brand is from a firm that is socially responsible. The brand is from a firm that is honest and transparent. In my view, the brand is from a firm that respects moral norms BA I feel good when I use this brand This brand makes me happy. This brand gives me positive feelings BT I rely on this brand I trust this brand This is an honest brand It is safe to choose this brand PSQ The offerings of the brand are of high quality The brand is from a firm whose services are reliable The firm delivers excellent overall service The firm delivers superior service in every way BL This brand would be my first choice I consider myself to be loyal to this brand If this brand is available, I will not prefer other brands I would be willing to pay a higher price for this brand over other brands BE Even if there is another brand as good as this, I prefer to choose this brand. Even if another brand offers the same services as this, I prefer to choose this brand. If another brand is not different from this in any way, it seems wise to choose this brand. Even if another brand offers the same price as this brand, I would still prefer this brand.	Brunk, K.H., 2012; Agag et al., 2016 Poolthong et al., 2009; Chaudhury and Holbrook, 2001 Chaudhury and Holbrook, 2001 Parasuraman, Zeithaml & Berry, 1988) Kumar et al., 2005; Yoo & Donthu, 2001 Yoo & Donthu, 2001

Table 2 Demographic Analysis
Respondents	503 (Nos.)	Respondents	503 (Nos.)
DEMOGRAPHICS	(Percentages)	DEMOGRAPHICS	(Percentages)
GENDER		EDUCATION
Male	71	Higher	58
Female	29	Lower	42
AGE BAND		OCCUPATION
21-30	11	Business/Executive	58
31-40	15	Other	42
41-50	24	MONTHLY INCOME IN RS.
51-60	34	Up to 50000	17
61 & above	16	50000 to 1 lac	25
		1 lac to 2.5 lacs	25
		2.5 to 5 lacs	11
		above 5 lacs	22

Choice of Categories of Service and Brands Chosen for Study

31 brands from six familiar categories, the most well-known brands are included. These constitute more than 50 percent of the sectoral Income (Table 3). The wide coverage ensured that the respondent would find it easy to make a discerned choice of a familiar service.

Table 3 Service Brands and Coding Scheme*
Category of Service	32 Health	33 Retail	34 Banking	35 Tourism	36 Insurance	37 Telecom
Brands	1 Apollo	7 Amazon	12 SBI	17 Thomas Cook	22 LIC	27 Airtel
	2 Hinduja	8 Flipkart	13 AXIS	18 MMT	23 New India	28 Vodafone
	3 MGM	9 Big Basket	14 HDFC	19 OYO	24 United	29 JIO
	4 Manipal	10 Myntra	15 ICICI	20 TAJ	25 Bajaj	30 ACT
	5 GH	11 Snapdeal	16 Canara	21 Lemontree	26 Star Health	31 BSNL
	6 Fortis

Health care: A respondent will be familiar with at least one of the six service providers including both private and Government hospitals; the wide coverage improves the heterogeneity of responses and hence the soundness of conclusions.

Retail: e-commerce and home delivery platforms mean a 100 percent likelihood that a respondent has used one of the brands. In the odd case, they can choose some other Category.

Banking: A mix of PSU and private banks have been included accounting for more than 50 percent banking turnover. PSU Banks and Private banks may offer differing ethical and performance attributes.

Tourism: The brands cover different segments of usage in the Tourism and Hospitality Industry.

Insurance: Brands include the oldest PSUs as well as private Insurers with a wide coverage of products and services, and reach.

Telecommunications: Internet subscription was 765.09 million as of February 2021, consisting of wired and wireless internet subscribers (Telecom Regulatory Authority of India).

Normality and Reliability

The variables should be normally distributed for all the statistical tests to be valid. Normality can be established by checking for Skewness and Kurtosis. The Kurtosis and Skewness data was well within the limits between -2 and +2. Reliability of the data was established with Cronbach Alpha values satisfying established criteria (Table 4).

Table 4 Reliability Statistics
	Item Mean/Variance				Reliability Statistics
	Mean	Variance	Std. Deviation	No. of Items	Cronbach Alpha
CPE	20	26.723	5.169	4	0.915
PSQ	19.96	30.919	5.56	4	0.942
BA	14.9	17.216	4.149	3	0.932
BT	20.09	31.117	5.578	4	0.944
BL	17.69	36.183	6.015	4	0.923
BE	17.98	37.581	6.13	4	0.949

Data Analysis and Findings

Running the Measurement Model, establishing Model Fit, Construct Validity; Conducting Path Analysis using SEM, Hypotheses Testing and Direct/Indirect Effects Analysis

Using AMOS 23 software the Measurement Model (the first part of SEM) was drawn for each of the four sets of Constructs (Figure 1) along with the items that represent each of them. Measurement Model A is shown in Figure 2 for illustration.

Goodness of fit as well as the Construct Validity of the Measurement Model had to be established before undertaking Path Analysis and Hypotheses testing. All the four measurement models (Figure 1) satisfied the criteria of model fit, convergent and discriminant validity. CMIN/DF, CFI, GFI, AGFI, RMR AND RMSEA were all well within suggested limits (Hair et al., 2018) with very good convergence of all the variables on to their respective Constructs. Composite Reliability and AVE were well above the established criteria (Tables 5 and 6).

Table 5 Model Fit Indices Measurement Models
Goodness of Fit	VALUES
	Model A	Model B	Model C	Model D
CMIN/DF GFI AGFI CFI NFI RFI RMR RMSEA	4.152 0.922 0.885 0.972 0.964 0.953 0.055 0.079	4.547 0.916 0.875 0.968 0.959 0.948 0.059 0.084	4.314 0.917 0.878 0.970 0.961 0.951 0.063 0.081	3.480 0.929 0.895 0.978 0.969 0.961 0.054 0.070

Table 6 Factor Loadings, Composite Reliability (CR), Ave
Measurement Model A					Measurement Model B
Construct	Multi Items	Factor Loadings	CR	AVE	Construct	Multi Items	Factor Loadings	CR	AVE
CPE	CPE5 <- CPE CPE3 <- CPE CPE2 <- CPE CPE1 <- CPE	0.872 0.906 0.824 0.808	0.915	0.728	CPE	CPE5 <-CPE CPE3 <- CPE CPE2 <- CPE CPE1 <- CPE	0.872 0.907 0.825 0.807	0.915	0.729
PSQ	PSQ3 <- PSQ PSQ2 <- PSQ PSQ1 <- PSQ	0.899 0.920 0.865	0.923	0.801	PSQ	PSQ3 <- PSQ PSQ2 <-- PSQ PSQ1 <- PSQ	0.901 0.919 0.864	0.923	0.801
BA	BA1 <-   BA BA2 <-   BA BA3 <-   BA	0.906 0.920 0.895	0.933	0.823	BA	BA1 <-   BA BA2 <-   BA BA3 <-   BA	0.905 0.918 0.897	0.933	0.822
BE	BE1 <-   BE BE2 <-   BE BE3 <-   BE BE4 <-   BE	0.887 0.909 0.909 0.925	0.949	0.824	BL	BL1 <-   BL BL2 <-   BL BL3 <-   BL BL4 <--   BL	0.933 0.912 0.902 0.714	0.925	0.756
Measurement Model C					Measurement Model D
Construct	Multi Items	Factor Loadings	CR	AVE	Construct	Multi Items	Factor Loadings	CR	AVE
CPE	CPE5 <- CPE CPE3 <- CPE CPE2 <- CPE CPE1 <- CPE	0.879 0.904 0.818 0.807	0.914	0.728	CPE	CPE5 <- CPE CPE3 <- CPE CPE2 <- CPE CPE1 <- CPE	.879 .903 .818 .808	0.914	0.728
PSQ	PSQ3 <- PSQ PSQ2 <- PSQ PSQ1 <- PSQ	0.896 0.929 0.857	0.923	0.800	PSQ	PSQ3 <- PSQ PSQ2 <- PSQ PSQ1 <- PSQ	.894 .932 .857	0.923	0.801
BT	BT1 <-   BT BT2 <-   BT BT4 <-   BT	0.932 0.873 0.901	0.929	0.814	BT	BT1 <-   BT BT2 <-   BT BT4 <-   BT	.934 .865 .906	0.929	0.814
BL	BL1 <-   BL BL2 <-   BL BL3 <-   BL BL4 <-   BL	0.937 0.910 0.899 0.711	0.924	0.755	BE	BE1 <-   BE BE2 <-   BE BE3 <-   BE BE4 <-   BE	.886 .908 .910 .925	0.949	0.801

It is also important to ensure there is no appreciable covariance between the Constructs, indicating Discriminant validity. Discriminant Validity as per Chi-Squared Difference tests was checked and confirmed for all four Measurement Models. While studying concepts and relationships that are closely related, it is natural to expect covariance. Hence we need to check if the model under consideration is superior to models that allow the Constructs to vary together. This is the theory behind the Chi-squared Difference Tests (Segars, A.H. 1997; Jaiswal, A et al., 2019; Zait et al., 2001).

The four factor model satisfied all the criteria and was far superior to the other three models, indicating discriminant validity (In each of the models, CPE and PSQ are merged to form one construct and BA/BT; BE/BL are merged to form another, thus resulting in three factor and two factor models. Finally all constructs are merged to form a single construct and the model is run. The model with the unconstrained correlation yields significantly better fit-indexes than the constrained model (Table 7).

Table 7 Checking for Discriminant Validity (Chi SQ. Difference Tests)

Model A

Model B

Model

χ2 (df)

χ2 /df

CFI

RMSEA

SRMR

Δχ2 /Δdf1

χ2 (df)

χ2 /df

CFI

RMSEA

SRMR

Δχ2 /Δdf1

Four Factor Three factor Two factor One factor

295 (71) 510 (74) 1152 (76) 1273 (77)

4.15 6.89 15.16 16.54

0.972 0.945 0.865 0.850

0.079 0.108 0.168 0.176

0.055 0.073 0.135 0.151

215/3 857/5 978/6

323 (71) 547 (74) 833 (76) 907 (77)

4.55 7.39 10.96 11.78

0.968 0.940 0.904 0.895

0.084 0.113 0.141 0.147

0.059 0.077 0.102 0.111

224/3 510/5 584/6

Model C

Model D

Model

χ2 (df)

χ2 /df

CFI

RMSEA

SRMR

Δχ2 /Δdf1

χ2 (df)

χ2 /df

CFI

RMSEA

SRMR

Δχ2 /Δdf1

Four Factor Three factor Two factor One factor

306 (71) 540 (74) 817 (76) 889 (77)

4.31 7.30 10.75 11.55

0.970 0.939 0.903 0.897

0.081 0.112 0.139 0.145

0.063 0.083 0.105 0.112

234/3 511/5 583/6

248 (71) 453 (74) 1071 (76) 1198 (77)

3.48 6.12 14.09 15.55

0.978 0.952 0.875 0.859

0.070 0.101 0.162 0.170

0.054 0.071 0.131 0.148

205/3 823/5 950/6

With the measurement models satisfying all established criteria, using SEM methodology, path analysis and hypotheses testing was done for all the four alternate models, Model fit was obtained for the Structural Model (see Figure 3 for illustration) and the hypotheses tested. Direct/Indirect Effects analysis was carried out using the bootstrapping procedure (Table 10). The Structural Model results are shown in Tables 8 and 9. Model fit, path analysis and mediation results are summarised and discussed (Tables 10 and 11).

Table 8 Model Fit Indices SEM Models
Goodness of Fit	VALUES
	Model A	Model B	Model C	Model D
CMIN/DF GFI AGFI CFI NFI RFI RMR RMSEA	4.094 0.922 0.886 0.972 0.964 0.954 0.055 0.079	4.494 0.915 0.876 0.968 0.959 0.949 0.059 0.083	4.229 0.922 0.886 0.970 0.961 0.951 0.063 0.080	3.520 0.927 0.893 0.977 0.969 0.960 0.056 0.071

Table 9 Structural Model Parameters
Model A					Model B
Path	C.R	Beta/SRW	p-value	Comment	Path	C.R	Beta/SRW	p-value	Comment
PSQ <-CPE BA <-CPE BA <-PSQ BE <-PSQ BE <-BA	22.69 6.40 13.26 -0.91 5.28	0.875 0.314 0.689 -0.171 1.000	<0.001 <0.001 <0.001 0.362 <0.001	Supported Supported Supported Not supported Supported	PSQ <-PE BA <-CPE BA <-PSQ BL <-PSQ BL <-BA	22.75 6.33 13.32 2.06 4.10	0.874 0.312 0.691 0.304 0.606	<0.001 <0.001 <0.001 <0.05 <0.001	Supported Supported Supported Supported Supported
Model C					Model D
Path	C.R	Beta/SRW	p-value	Comment	Path	C.R	Beta/SRW	p-value	Comment
PSQ <-CPE BT <-CPE BT <-PSQ BL <-BT BL <-PSQ	18.58 8.79 13.12 4.73 3.52	.852 .409 .602 .523 .392	<0.001 <0.001 <0.001 <0.001 <0.001	Supported Supported Supported Supported Supported	PSQ <-PE BT <-CPE BT <-PSQ BE <-PSQ BE <-BT	22.78 9.68 10.98 -0.28 6.64	0.875 0.471 0.535 -.036 0.874	<0.001 <0.001 <0.001 0.784 <0.001	Supported Supported Supported Not supported Supported

‘Table 10 Direct and Indirect Effects
Model A
Hypotheses	Direct effect	Indirect effect	Remarks	Mediation
CPE → PSQ → BA	0.314***	0.513***	Both direct and indirect effect are significant with p<0.001	Partial mediation
CPE → PSQ → BA → BE	Negative NS	0.767***	indirect effect is significant with p<0.001; direct effect is implausible (negative)	Full mediation
PSQ → BA → BE	Negative NS	0.689***	Direct effect is (implausible) negative and not significant; indirect effect significant with p<0.05	Full mediation
Model B
Hypotheses	Direct effect	Indirect effect	Remarks	Mediation
CPE → PSQ → BA	0.312***	0.604***	Both direct and indirect effect are significant with p<0.001	Partial mediation
CPE → PSQ → BA → BL	0.000	0.821***	indirect effect is significant with p<0.001; direct effect is implausible (negative)	Full mediation
PSQ → BA→ BL	0.304 NS	0.418*	Direct effect not significant; indirect effect significant with p<0.05	Full mediation
Model C
Hypotheses	Direct effect	Indirect effect	Remarks	Mediation
CPE → PSQ → BT	0.409***	0.513***	Both direct and indirect effects are significant with p<0.001	Partial mediation
CPE → PSQ → BT → BL	0.000	0.815***	indirect effect is significant with p<0.001; direct effect is implausible (negative)	Full mediation
PSQ → BT → BL	0.392*	0.315*	Both direct and indirect effects are significant with p<0.05	Partial mediation
Model D
Hypotheses	Direct effect	Indirect effect	Remarks	Mediation
CPE → PSQ → BT	0.471***	0.468***	Both direct and indirect effect are significant with p<0.001	Partial mediation
CPE → PSQ → BT → BE	0.000	0.790***	indirect effect is significant with p<0.001; direct effect is implausible (negative)	Full mediation
PSQ → BT → BE	-0.36 NS	0.468***	direct effect is implausible (negative); indirect effect is significant with p<0.001	Full mediation

Table 11 Comparative Summary
	Model A		Model B
Measurement model
Constructs	CPE PSQ BA BE		CPE PSQ BA BL
Reliability	Yes		Yes
Validity	Yes		Yes
Model fit	Yes		Yes
Path Analysis
Model fit	Yes		Yes
Hypotheses	PSQ --> BE not supported; rest 4 paths supported at 1 percent		All five supported. PSQ --> BL at 5 percent significance
Mediation results	CPE -> PSQ -> BA	Partial mediation	CPE -> PSQ -> BA	Partial mediation
	CPE -> PSQ -> BA -> BE	Full mediation	CPE -> PSQ -> BA -> BL	Full mediation
	PSQ -> BA -> BE	Full mediation	PSQ -> BA -> BL	Full mediation
	Model C		Model D
Measurement model
Constructs	CPE PSQ BT BL		CPE PSQ BT BE
Reliability	Yes		Yes
Validity	Yes		Yes
Model fit	Yes		Yes
Path Analysis
Model fit	Yes		Yes
Hypotheses	All five supported at 1 percent significance		PSQ --> BE not supported; rest 4 paths supported at 1 percent
Mediation results	CPE -> PSQ ->BT	Partial mediation	CPE -> PSQ -> BT	Partial mediation
	CPE -> PSQ -> BT ->BL	Full mediation	CPE -> PSQ -> BT -> BE	Full mediation
	PSQ -> BT -> BL	Partial mediation	PSQ -> BT -> BE	Full mediation

Summary of Findings

Note: 1.Models A and D have BE as the final Outcome Variable; Models B and C have BL as the final Outcome Variable.

Discussion and Findings

Refer to ‘Summary findings’ (Table 11).

Models A and D have BE as the final Outcome Variable; Models B and C have BL as the final Outcome Variable. The measurement models of all the four Models are reliable and valid and the structural models of all the four Models demonstrate Model fitness. Path Analysis shows the results of the tested hypotheses: All five hypotheses of Model C are supported at 1 percent significance. All hypotheses of Model B are supported at 1 percent significance, but one at 5 percent significance. In the case of Models A and D, the hypothesis ‘Perceived Service Quality is positively related to Brand Equity’ is not supported. The balance four hypotheses are supported at 1 percent significance.

The results of the Path Analysis clearly establish the importance of CPE with significant positive effects on brand related variables. The Beta coefficients are positive and significant (Table 9). All the threshold values of C.R, Beta as well as the p-values are significant for four out of five hypotheses indicating that these four hypotheses are supported. At each stage the succeeding outcome variable has a positive outcome from the preceding exogenous or endogenous variable as the case may be. It is the same as saying that at each stage the exogenous or endogenous variable has a positive significant impact on the succeeding outcome variable; however the hypothesis 4 is not supported for Models A and D. PSQ is not directly positively related to Brand Equity.

Direct and Indirect Effect Analysis

In the case of all the four models, PSQ is a partial mediator between CPE and BA (or BT) as both the direct and indirect effects are significant. Similarly, PSQ and BA (or BT) fully mediate the relationship between CPE and BE/(or BL as the case may be) and the relationship is significant.

While CPE and Brand Equity/Brand Loyalty are correlated, the direct effect of CPE on Service Brand Equity/Brand Loyalty is negative. This may be due to multicollinearity with the other explanatory variables. The path from CPE to BL or BE as the case may be is fully mediated by the intervening variables of PSQ, BA or BT as the case may be. This shows that CPE does not directly result in loyalty to a brand, or for that matter long term Brand Equity. But there is a significant indirect effect of CPE on Brand Equity/Brand Loyalty, with CPE exhibiting a positive effect on PSQ; and in turn PSQ exhibiting a positive effect on BA (or BT as the case may be), and finally BA or BT exhibiting a positive effect on BE/BL. The sum of the indirect effects from CPE through PSQ and Brand Affect (or Brand Trust as the case may be) as intervening (mediating) variables is significant. These are very important findings of this research. The coefficients with the p-values are shown in the mediation results tables at the end of each path.

Another interesting finding is with respect to the direct effect of PSQ on BE and PSQ on BL.

In the case of models A and D, BA (or BT) is a full mediator between PSQ and BE as the direct effect is not supported while indirect effect is supported.

Whereas in the case of Models B and C,

While BA is a full mediator between PSQ and BL as the direct effect is not supported while indirect effect is, BT is a partial mediator between PSQ and BL as both the direct and indirect effects are significant. (BE is a second order construct while BL, being a constituent of BE, a more immediate positive response to positive perceptions on quality is a result. The effect of PSQ on BE is still significant through the addition of all the indirect effects resulting in the correlations being positive and significant. In short, achieving positive Brand Equity takes time and long term effort.

Comparison of the Research Findings with Cited Research

Sierra et al. (2017) studied the relationship between CPE and BE through PSQ and BA. This is similar to Model A in this Research. Similar to this research, the direct relationship between CPE and BE was not supported. All other relationships were supported. In this research, however, the direct relationship between PSQ and BE was not supported, while the indirect relationship through BA was supported. As far as the mediation effects are concerned, in the cited research, CPE -> BA -> BE was fully mediated while CPE -> PSQ - >BE was partially mediated. In this research, both the above mediation paths were fully mediated. This is an interesting insight which shows that in the Indian example, the strength of relationship between Perceived Service Quality and Brand Equity occurs only through intervening variables and quality perception does not guarantee a direct causal effect on enhancement of customer based Brand Equity.

Singh et al. (2012) studied the relationship between CPE and BL, with BT and BA as mediators. The context was not Services but consumer goods. Notwithstanding that, while all immediate relationships were supported, the direct relationship between CPE and Brand Loyalty was not, just similar to the Service context. Further, in that study, the sum of the indirect effects from CPE to Brand Loyalty through Brand Trust and Brand Affect as intervening (mediating) variables is significant, and hence CPE does influence Brand Loyalty albeit through mediating variables.

Managerial Implications

Learning from the path analysis is that loyalty in the short run is necessary to get commitment. That commitment and loyalty will lead to strengthening of the Brand Equity in the long run. By looking at the comparative results and seeing what gets supported and what does not, managers can prioritise. Further, managers should not adopt shortcuts in defining ethical agenda and brand communication. In the service sector customer touch points are vital to satisfaction. The study confirms the importance of this by the positive relationship between CPE and perceived serviced quality. Choice of Affect and Trust, the two aspects of a customer’s relationship with a brand and the positive findings in the study, signify the importance of practicing ethical agenda from the consumers’ points of view. Firms can use the same approach to understand ethical perceptions of various groups of customers, suppliers, business associates, and further drill down those findings to understand how these perceptions of CPE as well as its relationship with outcome variables can be improved in their organizations. These exercises will enable budgets to be sharply focused to corporate objectives.

Limitations and Scope for Future Research

A fundamental limitation arose from the snowball approach to choose respondents for the quantitative studies. However, the fact that the participants were largely unknown, and distributed through a wide geography, with significantly varied demographics enhances the chances for randomness. Giving 31 brand choices should further address this limitation. Individual brand wise relationships could not be studied. At the same time, this limitation presents an opportunity for future research. Larger samples can be obtained, and the brand-specific responses can be subjected to analysis, to study the differences. Using paired sample ‘t’ tests, the CPE scales of brands can be compared to study the scale’s ability to distinguish between specified groups of services as well as specified brands. These findings can then be correlated with otherwise learnt opinions. Incidentally, the data analysis structure and coding scheme facilitate these efforts. Likewise, using brand specific data, path analysis can be constructed to study relationships that are specific to a category. Comparisons can then be drawn between these relationships and specific recommendations can be given to each category. Using SEM, the direction and strength of the relationship that CPE is likely to exhibit with various other brand related outcomes such as word-of-mouth etc., can be studied.

Conclusion

Ethics related agenda is becoming increasingly important in managing brands and this had to be tested out in different geographies to understand the variable priorities. This research places it in perspective by studying the Indian Service sector with four alternate sets of hypotheses. While most of the relationships are positive, some are implausible and some are not supported. These are important sets of findings in this research. Invariably, CPE does not exhibit a direct relationship with either Brand Loyalty or Brand Equity. This is yet another significant finding. However, the indirect relationships of CPE with both Brand Loyalty and Brand Equity are highly significant. In addition, Perceived Service quality does not have a direct effect on Brand Equity as different from the European context. The findings also indicate the strength of these various relationships. The reason for testing out four Models was to enable comparisons between various relationships. When one looks at comparative data it becomes clearer as to which is more or less important.

The referred research work from Europe and other countries do not necessarily demonstrate similar results. There are agreements as well as variations. All these varied findings, comparisons between the four models, comparisons with the overseas contexts, point out as to how much important it is to conduct studies in each geography. Thus the entire set of findings and comparisons are useful additions to existing knowledge.

References

Aaker, D.A. (2009). Managing brand equity. simon and schuster.

Indexed at, Google Scholar

Agag, G., El-Masry, A., Alharbi, N.S., & Almamy, A.A. (2016). Development and validation of an instrument to measure online retailing ethics: Consumers’ perspective. Internet Research.

Indexed at, Google Scholar, Cross Ref

Akbar, M.M., & Parvez, N. (2009). Impact of Service quality, trust and customer satisfaction on customer loyalty. ABAC Journal,  29(1), 24-38.

Google Scholar

Belk, R.W., Devinney, T., & Eckhardt, G. (2005). Consumer ethics across cultures. Consumption, Markets and Culture, 8(3), 275–289.

Indexed at, Google Scholar, Cross Ref

Bennur, S., & Jin, B. (2016). The mediating role of Brand Trust and affect in clothing Brand Loyalty formation: a cross-cultural examination of U.S. and India. The Journal of The Textile Institute, Taylor & Francis. http://dx.doi.org/10.1080/00405000.2015.1133105.

Google Scholar, Cross Ref

Berry, L.L. (2000). Cultivating service brand equity. Journal of the Academy of Marketing Science, 28(1), 128–137.

Indexed at, Google Scholar, Cross Ref

Bloemer, J., & Schröder, G.O. (2003). Antecedents and Consequences of Affective Commitment. Australasian Marketing Journal, 11 (3), 33-43.

Indexed at, Google Scholar, Cross Ref

Breckler. (1984). Empirical Validation of Affect, Behaviour, and Cognition as Distinct Components of Attitude. Journal of Personality and Social Psychology, 47(6), 1191-1205.

Google Scholar, Cross Ref

Brodie, R.J., Glynn, M.S., & Little, V. (2006). The service brand and the service-dominant logic: Missing fundamental premise or the need for stronger theory? Marketing Theory, 6(3), 363–379.

Indexed at, Google Scholar, Cross Ref

Brunk, K.H. (2012). Un/ethical Company and Brand Perceptions: Conceptualising and Operationalising Consumer Meanings. Journal of Business Ethics, 111, 551–565.

Indexed at, Google Scholar, Cross Ref

Chahal, H., & Bala, M. (2012). Significant components of service brand equity in healthcare sector. International Journal of Health Care Quality Assurance, 25(4), 343-362.

Indexed at, Google Scholar, Cross Ref

Chao-Chan Wu. (2011). The impact of hospital brand image on Service quality, patient satisfaction and loyalty. African Journal of Business Management  5(12),  4873-4882.

Indexed at, Google Scholar, Cross Ref

Chaudhury, A., & Holbrook, M.B. (2001). The chain of effects from Brand Trust and Brand Affect to brand performance: The role of Brand Loyalty. Journal of Marketing, 65(2), 81–93.

Indexed at, Google Scholar, Cross Ref

Chernatony, L., & Harris, F.J. (2001). Measuring the consumer-based equity of financial Services brands. Services Industries Journal, 24(2), 15-33.

Google Scholar

Cobb-Walgren, C.J., Ruble, C.A., & Donthu, N. (1995). Brand Equity, brand preference, and purchase intent. Journal of Advertising, 24(3), 25–40.

Indexed at, Google Scholar, Cross Ref

Cronin, J.J, Jr., Brady. M.K., & Hult, 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.

Google Scholar, Cross Ref

Elbeltagi, I., & Agag, G. (2016). E-retailing ethics and its impact on customer satisfaction and repurchase intention. Internet Research 26(1), 288-310.

Indexed at, Google Scholar, Cross Ref

Fan, Y. (2005). Ethical branding and corporate reputation. Corporate Communications: An International Journal, 10(4), 341–350.

Indexed at, Google Scholar, Cross Ref

Fullerton, G. (2005). How commitment both enables and undermines marketing relationships. European journal of marketing.

Indexed at, Google Scholar, Cross Ref

Gecti, F., & Zengin, H. (2013). The relationship between brand trust, brand affect, attitudinal loyalty and behavioral loyalty: A field study towards sports shoe consumers in Turkey. International Journal of Marketing Studies, 5(2), 111.

Google Scholar

Gurviez, P., & Korchia, M. (2003, May). Proposal for a multidimensional brand trust scale. In 32nd Emac-Conference-Glasgow, Marketing: Responsible and Relevant (pp. 438-452).

Google Scholar

Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2018). Multivariate Data Analysis (Eighth edition). Cengage, UK.

Huber, F., Vollhardt, K., Matthes, I., & Vogel, J. (2010). Brand misconduct: Consequences on consumer–brand relationships. Journal of Business Research, 63(11), 1113-1120. ]

Indexed at, Google Scholar, Cross Ref

Hutchinson, D. B., Singh, J., Svensson, G., & Mysen, T. (2013). Towards a model of conscientious corporate brands: a Canadian study. Journal of Business & Industrial Marketing.

Indexed at, Google Scholar, Cross Ref

Iglesias, O., Markovic, S., Singh, J. J., & Sierra, V. (2019). Do customer perceptions of corporate services brand ethicality improve brand equity? Considering the roles of brand heritage, brand image, and recognition benefits. Journal of business ethics, 154(2), 441-459.

Indexed at, Google Scholar, Cross Ref

Jahanzeb, S., Fatima, T., & Butt, M. M. (2013). How service quality influences brand equity: The dual mediating role of perceived value and corporate credibility. International Journal of Bank Marketing.

Indexed at, Google Scholar, Cross Ref

Jaiswal, A., & Dyaram, L. (2019). Perceived diversity and employee well-being: Mediating role of inclusion. Personnel Review.

Indexed at, Google Scholar, Cross Ref

Keh, H. T., & Xie, Y. (2009). Corporate reputation and customer behavioral intentions: The roles of trust, identification and commitment. Industrial marketing management, 38(7), 732-742.

Google Scholar, Cross Ref

Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of marketing, 57(1), 1-22.

Indexed at, Google Scholar, Cross Ref

Klink, R. R., & Wu, L. (2017). Creating ethical brands: The role of brand name on consumer perceived ethicality. Marketing Letters, 28(3), 411-422.

Indexed at, Google Scholar, Cross Ref

Kumar, S., & Advani, J. (2005). Factors affecting Brand Loyalty: A study in an emerging market on fast moving consumer goods. Journal of Customer Behaviour, 4, 251–275.

Lertwannawit, A., & Gulid, N. (2011). International tourists service quality perception and behavioral loyalty toward medical tourism in bangkok metropolitan area. Journal of Applied Business Research (JABR), 27(6), 1-12.

Google Scholar, Cross Ref

Li, X., & Jarinto, K. (2012). Service is power: exploring service quality in Hotel's business, Yunnan, China. International Business Research, 5(5).

Indexed at, Google Scholar

Lien, C. H., Wu, J. J., Chen, Y. H., & Wang, C. J. (2014). Trust transfer and the effect of service quality on trust in the healthcare industry. Managing Service Quality.

Indexed at, Google Scholar, Cross Ref

Lu, L. C., & Lu, C. J. (2010). Moral philosophy, materialism, and consumer ethics: An exploratory study in Indonesia. Journal of Business Ethics, 94(2), 193-210.

Indexed at, Google Scholar, Cross Ref

Markovic, S., Iglesias, O., Singh, J. J., & Sierra, V. (2018). How does the perceived ethicality of corporate services brands influence loyalty and positive word-of-mouth? Analyzing the roles of empathy, affective commitment, and perceived quality. Journal of Business Ethics, 148(4), 721-740.

Indexed at, Google Scholar, Cross Ref

Mende, M., & Bolton, R. N. (2011). Why attachment security matters: How customers' attachment styles influence their relationships with service firms and service employees. Journal of Service Research, 14(3), 285-301.

Indexed at, Google Scholar, Cross Ref

Morgan, R. M., & Hunt, S. D. (1994). The commitment-trust theory of relationship marketing. Journal of marketing, 58(3), 20-38.

Indexed at, Google Scholar, Cross Ref

Nella, A., & Christou, E. (2014). Linking service quality at the cellar door with brand equity building. Journal of Hospitality Marketing & Management, 23(7), 699-721.

Indexed at, Google Scholar, Cross Ref

Page, G., & Fearn, H. (2005). Corporate reputation: what do consumers really care about?. Journal of Advertising Research, 45(3), 305-313.

Indexed at, Google Scholar, Cross Ref

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of marketing, 49(4), 41-50.

Indexed at, Google Scholar, Cross Ref

Parasuraman, A., Zeithaml, V.A., & Berry, L.L. (1988). SERVQUAL: A multiple item scale for measuring customer perceptions of Service quality. Journal of Retailing, 64(1), 12–40.

Indexed at

Pérez, R. C. (2009). Effects of perceived identity based on corporate social responsibility: The role of consumer identification with the company. Corporate Reputation Review, 12(2), 177-191.

Indexed at, Google Scholar, Cross Ref

Poolthong, Y., & Mandhachitara, R. (2009). Customer expectations of CSR, perceived service quality and brand effect in Thai retail banking. International Journal of Bank Marketing.

Indexed at, Google Scholar, Cross Ref

Rawwas, M. Y., Swaidan, Z., & Oyman, M. (2005). Consumer ethics: A cross-cultural study of the ethical beliefs of Turkish and American consumers. Journal of Business Ethics, 57(2), 183-195.

Indexed at, Google Scholar, Cross Ref

Riley, F.D.O., & De Chernatony, L. (2000). The Service Brand as Relationships Builder. British Journal of Management, 11, 137–150.

Roostika, R. (2011). The effect of perceived service quality and trust on loyalty: Customer's perspectives on mobile internet adoption. International journal of innovation, management and technology, 2(4), 286.

Google Scholar

Salmones, M. D. M. G. D. L., Crespo, A. H., & Bosque, I. R. D. (2005). Influence of corporate social responsibility on loyalty and valuation of services. Journal of business ethics, 61(4), 369-385.

Indexed at, Google Scholar, Cross Ref

Schlegelmilch, B. B., & Öberseder, M. (2010). Half a century of marketing ethics: Shifting perspectives and emerging trends. Journal of Business Ethics, 93(1), 1-19.

Indexed at, Google Scholar, Cross Ref

Segars, A. H. (1997). Assessing the unidimensionality of measurement: A paradigm and illustration within the context of information systems research. Omega, 25(1), 107-121.

Indexed at, Google Scholar, Cross Ref

Shang, J., & Peloza, J. (2016). Can “real” men consume ethically? How ethical consumption leads to unintended observer inference. Journal of business ethics, 139(1), 129-145.

Indexed at, Google Scholar, Cross Ref

Shriedeh, F. B., & Ghani, N. H. A. (2017). Service quality as an antecedent of brand equity: empirical evidence in the medical tourism from Jordan. International review of management and marketing, 7(1), 15-19.

Indexed at, Google Scholar

Sierra, V., Iglesias, O., Markovic, S., & Singh, J. J. (2017). Does ethical image build equity in corporate services brands? The influence of customer perceived ethicality on affect, perceived quality, and equity. Journal of Business Ethics, 144(3), 661-676.

Indexed at, Google Scholar, Cross Ref

Singh, J. J., Iglesias, O., & Batista-Foguet, J. M. (2012). Does having an ethical brand matter? The influence of consumer perceived ethicality on trust, affect and loyalty. Journal of business ethics, 111(4), 541-549.

Indexed at, Google Scholar, Cross Ref

Swaidan, Z. (2012). Culture and consumer ethics. Journal of Business Ethics, 108(2), 201-213.

Indexed at, Google Scholar, Cross Ref

Thomas, J. L., Vitell, S. J., Gilbert, F. W., & Rose, G. M. (2002). The impact of ethical cues on customer satisfaction with service. Journal of retailing, 78(3), 167-173.

Indexed at, Google Scholar, Cross Ref

Upamannyu, N. K., & Mathur, G. (2013). Effect of brand trust, brand affect and brand image on customer brand loyalty and consumer brand extension attitude in FMCG sector. In Prima (Vol. 3, No. 2, p. 1). Publishing India Group.

Google Scholar

Viriyavidhayavongs, V., & Yothmontree, S. (2002). The Impact of ethical considerations in purchase behavior: a propaedeutic to further research. ABAC Journal, 22(3).

Google Scholar

Yoo, B., & Donthu, N. (2001). Developing and validating a multidimensional consumer-based brand equity scale. Journal of business research, 52(1), 1-14.

Indexed at, Google Scholar, Cross Ref

Zai?, A., & Bertea, P. S. P. E. (2011). Methods for testing discriminant validity. Management & Marketing Journal, 9(2), 217-224.

Indexed at, Google Scholar

Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of marketing, 60(2), 31-46.

Indexed at, Google Scholar, Cross Ref

Received: 07-Mar-2022, Manuscript No. AMSJ-22-11646; Editor assigned: 09-Mar-2022, PreQC No. AMSJ-22-11646(PQ); Reviewed: 23-Mar-2022, QC No. AMSJ-22-11646; Revised: 25-Mar-2022, Manuscript No. AMSJ-22-11646(R); Published: 31-Mar-2022