How do CSR and perceived ethics enhance corporate reputation and product innovativeness?

Abstract

Market competitiveness is considered a core business objective besides profit-making in the current business environment, which instigates organisations to remain ethically and socially responsible. This leads to implied pressure on the organisation, whereas consumers expect to deal with ethically and socially responsible organisations. Therefore, this study explores the role of perceived corporate social responsibility (CSR) and ethics, which derives the organisational brand reputation and product innovativeness. The data was collected from 418 respondents, and partial least squares structural equation modelling (PLS-SEM) was applied for predicting the hypothesised relationships. The results revealed the positive and significant hypothesised relationships. As per findings, CSR and ethics positively correlated with product innovativeness, brand equity, and customer trust. Based on the results, organisations are advised to have transparency and higher compliance towards ethics and CSR strategies. In contrast, organisations need to have good communication of their adherence, which can further assist them in improving the customer base and maintaining the competitive advantage. These outcomes offer valuable policies.

Keywords:

• Corporate social responsibility
• ethical practices
• corporate reputation
• product innovativeness
• brand equity
• customer trust

JEL CODES:

• G3
• G30
• O3

1. Introduction

Corporate social responsibility (CSR) is being identified as an effective corporate marketing and branding tool, which leads organisations to have financial and non-financial gains by affecting customer beliefs and attitudes (Van Doorn et al., 2017). According to Carroll (1999), ‘responsibilities and obligations of the businesses to improve the community’s well-being through the use of business resources such as finance, personnel, and equipment’. There are certainly potential benefits that an organisation gets through CSR like customer satisfaction (Fatma et al., 2018), improved quality of the product (Goyal & Chanda, 2017), increased reputation (González-Rodríguez et al., 2019), and enhanced company’s performance (Latif et al., 2020). However, corporations see it as an additional financial burden in the near term and neglect the long-term advantages of CSR donations (Shahzad et al., 2020). On the other hand, by incorporating CSR in the marketing strategies, the organisations can have a competitive advantage. In contrast, it also helps them attain support from the relevant stakeholders, which eventually assist in building a sophisticated and legitimate corporate reputation (Balmer et al., 2011; Swaen et al., 2021). Further, corporate reputation (CRP) is the perceived phenomenon that is the reflection of the overall assessments, expectations, and evaluations by stakeholders by which they eventually judge the organisation as either ‘bad’ or ‘good’. In contrast, it is developed after a sufficient period in which organisations mainly take in the market while doing business (Dowling & Moran, 2012; Podnar & Golob, 2017).

For an organisation to have sound branding and market worthiness, the level of CRP is essential (Baalbaki & Guzmán, 2016); which also assist the organisation in developing their associations with the relevant and related stakeholders (Cowan & Guzman, 2020; Heinberg et al., 2018). In other words, by incorporating the CSR operations and activities as part of their marketing campaigns, organisations will be in a better position to influence the customers in terms of their preferences and perceived attributes through which they evaluate back the organisations (Gupta & Pirsch, 2008; Walsh & Bartikowski, 2013). Besides, since there is a regular number of irregularities that violates the essence of CSR like layoff of the employees to the technological advancements or reducing operational costs, employee exploitation when it comes to having the right amount of payments and decreasing the profits of the suppliers to reduce the expenses (Binninger & Robert, 2011; Monde, 2019). When such kinds of practices become part of the press and media, it will damage the overall image and reputation of the organisation in the eyes of the customers (Hoejmose et al., 2014).

In addition to this, to meet the ever-changing nature of the customers’ demands, the firm’s mission and vision should incorporate innovation so that they remain competitive (Boisvert & Khan, 2021; Morrish et al., 2010). It should be noted that a plethora of studies covered the aspect of innovation from an organisational and managerial point of view (Im et al., 2015). However, what seems innovative from the organisational and managerial point of view is not necessarily innovative from the customer’s point of view (Lee & O’Connor, 2003; Sharma et al., 2016; Szymanski et al., 2007). Furthermore, CRS is an essential tool in different aspects, such as it helps achieve organisational sustainability, green innovation, and environmental performance (Abbas, 2020; Shahzad et al., 2020; Sun et al., 2021; Zhang et al., 2021). On the other hand, there is no doubt that innovative product itself is a kind of signal to the customers that the company which is offering that product has some reputation (Sharma et al., 2016; Zhang et al., 2016), whereas it leads to developed brand equity (Sarkar & Mishra, 2017) and accordingly develop trust (Swaen et al., 2021).

Considering the prevailing literature gap and the critical role of targeted variables, the present study explores the effect of various dimensions of CSR and ethics on corporate reputation. In contrast, the current study also intends to examine the role of CRP and INN in deriving brand equity and customer trust. One of the benefits of the present study is that it fills the research gap by assessing the correlation between CSR, ethics, corporate reputation, brand equity, product innovativeness, and customer trust in an encompassing model through the novel structural equation modelling methodology (SEM). The outcome of this study will provide valuable insights into managers and experts to incorporate CSR and ethics for enhancing corporate reputation and product innovativeness in deriving brand equity and customer trust. The remainder of the study is organised as the next section discusses the relevant literature for hypothesis development followed by the methodology, results, and in the last study is concluded, and recommendations are proposed.

2. Literature review and hypotheses developemnt

2.1. CSR and corporate reputation

Corporate Reputation (CRP) has been explained as the cognitive reflection of an organisation which is an outcome of its operations and actions and is also derived from the difference of what is expected from it and what it actually delivers while providing value to the respective stakeholders (Fombrun et al., 2000). In addition to this, different authors have defined this concept in different ways. For instance, according to Balmer (2009), CRP is the outcome of ‘facts, beliefs, images, and experiences encountered by an individual over time’, whereas according to Fombrun and van Riel (1997), CRP is the cognitive evaluation of the quality of performance that the organisation is delivering over the period of time. Nevertheless, in order to have a good, sophisticated, and sound CRP, organisations are involved in marketing their legitimacy, trustworthiness, reliability, and promoting themselves. For that particular reason, organisations also incorporate some aspects of CSR in their marketing campaigns to have an attractive and good reputation in the market (Balmer et al., 2011; Swaen et al., 2021). Moreover, among the most recommended determinants of CRP, CSR is the most prominent (Ali et al., 2015). CSR revolves around the philosophy of providing welfare to the stakeholders, including employees, customers, and society. In contrast, it should incorporate all of the elements of ‘Triple Bottom Line’, which are social, financial, and economic aspects.

Multiple studies have explored the association between CSR and CRP (El Akremi et al., 2018; Brammer & Pavelin, 2006; Rothenhoefer, 2019; Rupp et al., 2013; Swaen et al., 2021). However, there are certain limitations of those studies. One of the major limitations among such studies includes exploring the customer element of CSR only, whereas there are other stakeholders to whom organisations need CSR. Nevertheless, based on this, the current study also explores CSR towards other stakeholders perceived by the customers in the banking sector. Hence it is assumed that:

H1: Customer Related CSR (CST) has a significant relationship with Corporate Reputation (CRP)

H2: Employee and Supplier Related CSR (ENS) has a significant relationship with Corporate Reputation (CRP)

H3: Environment and Community Related CSR (ENC) has a significant relationship with Corporate Reputation (CRP)

2.2. Ethics and corporate reputation

The term Ethics (ETH) reflects the philosophy of being right, just, fair, and equitable (Carroll, 1991; Freeman & Gilbert, 1988). It has also been explained as the actions and values by an individual in accordance with the principles of society’s right and wrong (Raiborn & Payne, 1990). In organisational settings, the decisions by which an organisation can be judged as wrong or right are termed ETH (De George, 2000). It has been stated that the assessment of ETH and CSR is being done normatively (Ferrell et al., 2013, 2019). The major focus is being done in improving the level of ethics in the workplace (Laczniak & Kennedy, 2011). Moreover, Markovic et al. (2018) stated that consumers perceived ETH as the reflection of organisational morality, which is an outcome of its image, reputation, and quality. In other words, ETH tends to improve the CRP. In the context of the current study, when a bank has just a level of ethics, they are more likely to have sound CRP. Hence it is assumed that:

H4: Ethics has a significant relationship with Corporate Reputation (CRP)

2.3. Corporate reputation and product innovativeness

Product Innovativeness (INN) has been referred to as newness, novelty, originality, and uniqueness, which emerge as an innovation in the latest product offerings and makes that particular product inimitable by the competitors to fulfil the required value of the customers (Henard & Szymanski, 2001; Martín, 2021). When an organisation’s perceived reputation excels in the market, it tends to continue it and strive for its further betterment (Swaen et al., 2021). While doing this, there is a need to have innovation in the product offerings, which can help the organisation the legacy of its reputation in the market (Ahmed et al., 2020). A reputed organisation will be motivated and encouraged to bring in innovation by deploying sufficient resources to outshine the quality of the product (Martín, 2021). In the context of the current study, a high level of CRP of the banks encourages them to have higher INN. Hence it is assumed that:

H5: Corporate Reputation (CRP) has a significant relationship with Product Innovativeness

2.4. Corporate reputation and brand equity

Brand Equity (BEQ) reflects a customer’s perceived assessment which is intangible and highly subjective. In contrast, it is an outcome of the marketing campaigns and promotions that the organisation is conducting in deriving a particular reputation and image in the mind of the customers (Keller, 1993). Based on the literature findings, it is noted that banks that have a good repute, either because of the CSR and ETH or because of their product offerings, eventually improve the BEQ in the mind of the customers (Lai et al., 2010). Studies by Hur et al. (2014) and Swaen et al. (2021) have reported supportive evidence between CRP and BEQ. In the context of the current study, a high level of CRP of the banks will also eventually improve their BEQ from the customers’ perspectives. Hence it is assumed that:

H6: Corporate Reputation (CRP) has a significant relationship with Brand Equity

2.5. Corporate reputation and customer trust

Customer Trust (CTR) is the level of reliance and confidence that a customer perceives while dealing with an organisation, especially in scenarios. In contrast, customers find themselves at a relatively higher risk. In contrast, in return, the customer believes that the organisation will not impair his rights, neither will exploit him irrespective of the vulnerable nature of the situation (Delgado-Ballester & Munuera-Aleman, 2005). There are several other scenarios where customer forms a certain level of trust based on CPR. For instance, when there are few availabilities of information, specifications, and particulars related to the service or product, the CPR of an organisation forces the customer to have enough trust to evaluate the offer of the company positively (Ponzi et al., 2011; Schnietz & Epstein, 2005). According to the literature, companies with higher CPR will not compromise at the cost of CPR and accordingly will not behave opportunistically, enhancing the CTR (Heinberg et al., 2018; Swaen et al., 2021). In the context of the current study, a high level of CRP of the banks will also eventually improve their CTR in the customers’ perspectives. Hence it is assumed that:

H7: Corporate Reputation (CRP) has a significant relationship with Customer Trust

2.6. Product innovativeness, brand equity, and customer trust

As already discussed, the reputed organisation is more encouraged towards INN; however, such INN also assists the organisation in improving their profile, market worthiness, and customer base, whereas it is also a differentiating factor that gives a competitive edge to the organisations (Keller, 1993). It helps them retain existing customers and helps attract new ones (Martín, 2021). A company offering an innovative product strengthens its brand equity, whereas it also improves the level of CTR (Torres et al., 2012; Yao et al., 2021). In the context of the current study, a high level of INN of the banks will also eventually improve their BEQ and CTR from the customers’ perspectives. Hence it is assumed that:

H8: Product Innovativeness has a significant relationship with Brand Equity

H9: Product Innovativeness has a significant relationship with Customer Trust

3. Methodology

For assessing the proposed hypothesised associations, the current study relies on the primary data collected from the consumers of the banking sector by the employment of survey methodology. For this purpose, a survey questionnaire was formed for data collection, which was later addressed to the potential banking consumers. Following the proposed framework, the measuring items of the questionnaire were adapted from the existing literature, as the literature measures have reported their consistency and robustness across different contextual scenarios. The sources of the adapted measures are shown in Table 1.

Table 1. Source of measures.

Constructs	Number of items	Sources
Customer related CSR (CST)	5	Swaen et al. (2021)
Employee and supplier related CSR (ENS)	7	Swaen et al. (2021)
Environment and community related CSR (ENC)	9	Swaen et al. (2021)
Ethics (ETH)	4	Amoako et al. (2021)
Corporate reputation (CRP)	3	Newburry (2010)
Product innovativeness (INN)	5	Rindfleisch and Moorman (2001)
Brand equity (BEQ)	4
Customer trust (CTR)	3	Gurviez and Korchia (2002)

Source: Authors Drawing.

To make the developed questionnaire self-administered, the survey form was divided into two sections. First section comprised of the questions reflecting measurement of the constructs, whereas second section comprised of the questions asked for ascertaining the demographic profile of the potential respondents. Despite being the adapted scales, the ‘Face and Content validity’ of the questionnaire was ensured by having the experts’ opinions. The experts recommended particular suggestions related to the language of the items. After incorporating the comments, the pilot study was conducted to ascertain the legitimacy of the questionnaire. After having reliable results, the questionnaire was then addressed to the respondents for ample data collection. This study used the ten times rule advocated by Hair et al. (2016) for sample size. This rule states that ‘10 times the largest number of structural paths directed at a particular latent construct in a structural model’.

3.1. Common method biasness (CMB)

In the research especially involving primary data, there is the highest probability of arising of biases due to the methodological operationalisation and is referred to as CMB (Podsakoff et al., 2012). Podsakoff et al. (2012) have proposed several measures through which the CMB can be controlled and grouped them into two, namely procedural and statistical remedies. Procedurally, adapting the reliable items and having understandable and straightforward language controls the possibility of CMB, which is followed in the current study. Statistically, the application of Harman’s single Factor (1967) test in which the extraction of variables is made by freezing the factor to 1 is applied. The findings rule out the possibility of CMB. These tests are also involved in similar studies (Najmi et al., 2021a; Najmi & Ahmed, 2018).

3.2. Overview of partial least square-structural equation modeling (PLS-SEM)

PLS-SEM is the statistical technique that belongs to the category of second-generation and is known for explaining the maximum variance of the predictor, which other conventional regress-based techniques fail to do so (Najmi et al., 2021b). In addition to this, it is also reported to be reliable while dealing with complex models. In contrast, it is pretty lenient in multivariate statistical requirements like outliers and normality (Hair et al., 2016). PLS-SEM is capable of measuring as well as analysing structural models. Furthermore, SEM was predominantly employed for the estimate and study of endogenous variables in order to explain the greatest amount of variance (Hair et al., 2016). The application of PLS-SEM has been made in diversified topics like online purchasing (Najmi & Ahmed, 2018), new product development (Najmi & Khan, 2017), reversing behaviour (Najmi et al., 2021b), the greening of suppliers (An et al., 2021; Najmi et al., 2020) and total quality management (Najmi et al., 2021). The operationalisation of PLS-SEM is made in a two-stage procedure discussed in section 4 of the study.

4. Estimations and results

The dataset upon which the application of PLS-SEM is made is comprised of 418 respondents. The dataset consisted of 418 respondents, of which 178 were females (43% of the data), and 240 were males (57% of the data). The majority of the data belong to the age bracket of 31-40 years which leads to the number of 168 respondents (40% of the data), whereas in terms of education, the majority of having graduation which leads to the number of 173 respondents (41% of the data). A cross-sectional survey approach was used to collect data using an offline and online self-administered questionnaire to test the hypotheses. This study adopted the quantitative data collection methods and used the questionnaires to collect the data from the respondents. The demographic profile of the respondents is shown in Table 2. Figure 1 shows the overall framework of this study.

Figure 1. Framework of study.

Source: Authors Drawing.

Table 2. Descriptive statistics.

		Frequency	Percent
Gender	Female	178	43%
	Male	240	57%
	Total	418	100%
Age	20–30 years	149	36%
	31–40 years	168	40%
	41–50 years	67	16%
	51 and above	34	8%
	Total	418	100%
Education	Undergraduate	103	25%
	Graduate	173	41%
	Post graduate	85	20%
	Others	57	14%
	Total	418	100%

Source: Authors’ estimation.

4.1. Application of PLS-SEM

Following the guidelines of Hair et al. (2016), the PLS-SEM is applied in the two-staged procedure, including assessment of ‘measurement model’ and the evaluation of ‘structural model’. The ‘measurement model’ discusses the quality and reliability of the outer model, whereas the ‘structural model’ discusses the inner model’s quality and reliability, including hypothesis testing. The assessment of the application of the ‘measurement model’ and ‘structural model’ are discussed in the subsequent sections.

4.1.1. Measurement model

In the ‘measurement model’, in accordance with the guidelines of Hair et al. (2016), there is an assessment of ‘Convergent Validity’ and ‘Discriminant Validity’. ‘Convergent Validity’ reflects the tendency in which the measurement of the construct tends to behave in a way that they are strongly inter-related and eventually force themselves to form a construct (Mehmood & Najmi, 2017). In accordance with the guidelines of Hair et al. (2016), the ‘Convergent Validity’ is assessed with the help of three different criteria. Firstly, it is assessed by the value of ‘Factor Loadings’, which, according to Hair et al. (2016), should be greater than 0.7. The values of the ‘Factor Loadings’ resulted in Table 3 clearly show that all of them are greater than 0.7. Secondly, it is assessed by the values of ‘Cronbach’s Alpha’ and ‘Composite Reliability’, which reflects the level of internal consistency and, according to Hair et al. (2016), should also be more significant than 0.7. The values of the ‘Cronbach’s Alpha’ and ‘Composite Reliability’ resulted and are shown in Table 3 clearly indicates that all of them are greater than 0.7. Thirdly, it is assessed by the values of ‘Average Variance Extracted’, which, according to Hair et al. (2016), should be greater than 0.5. The values of the ‘Average Variance Extracted’ resulted in Table 3 clearly show that all of them are greater than 0.5.

Table 3. Measurement model results.

Variables	Items	Factor loadings	Cronbach’s alpha	Composite reliability	AVE
Customer related CSR (CST)	CST1	0.703	0.726	0.717	0.555
	CST2	0.782
	CST3	0.699
	CST4	0.710
	CST5	0.720
Employee and supplier related CSR (ENS)	ENS1	0.721	0.787	0.716	0.629
	ENS2	0.777
	ENS3	0.721
	ENS4	0.722
	ENS5	0.756
	ENS6	0.722
	ENS7	0.730
Environment and community related CSR (ENC)	ENC1	0.767	0.771	0.710	0.604
	ENC2	0.708
	ENC3	0.711
	ENC4	0.695
	ENC5	0.794
	ENC6	0.749
	ENC7	0.779
	ENC8	0.707
	ENC9	0.750
Ethics (ETH)	ETH1	0.770	0.783	0.692	0.566
	ETH2	0.797
	ETH3	0.731
	ETH4	0.797
Corporate reputation (CRP)	CRP1	0.798	0.774	0.710	0.593
	CRP2	0.718
	CRP3	0.746
Product innovativeness (INN)	INN1	0.722	0.742	0.711	0.579
	INN2	0.749
	INN3	0.758
	INN4	0.799
	INN5	0.705
Brand equity (BEQ)	BEQ1	0.725	0.747	0.736	0.601
	BEQ2	0.739
	BEQ3	0.746
	BEQ4	0.723
Customer trust (CTR)	CTR1	0.798	0.797	0.709	0.649
	CTR2	0.788
	CTR3	0.777

Source: Authors’ estimation.

On the other hand, ‘Discriminant Validity’ reflects the tendency in which the measurement of the construct tends to behave in a way that they are strongly dissimilar with the measurement of another construct and eventually forced themselves to differentiate and lead to forming different constructs (Mehmood & Najmi, 2017). In accordance with the guidelines of Hair et al. (2016), the ‘Discriminant Validity’ is assessed with the help of three different criteria. Firstly, it is assessed by the value of ‘Cross Loadings’, which, according to Hair et al. (2016), should be highly loaded in their constructs. In contrast, according to Gefen and Straub (2005), the difference between the factor loading to a respective construct and the cross-loadings to other constructs must be greater than 0.1. The resulting values are shown in Table 4 clearly show that all of the factor loadings are highly loaded in their respective constructs, and the difference of the cross-loadings is higher than 0.1.

Table 4. Results of loadings and cross loadings.

Variable	CST	ENS	ENC	ETH	CRP	INN	BEQ	CTR
Customer related CSR (CST)	0.703	0.364	0.367	0.428	0.441	0.342	0.443	0.392
	0.782	0.323	0.316	0.432	0.324	0.340	0.334	0.408
	0.699	0.436	0.373	0.355	0.304	0.432	0.313	0.366
	0.710	0.399	0.409	0.317	0.449	0.412	0.429	0.348
	0.720	0.315	0.395	0.336	0.305	0.349	0.410	0.431
Employee and supplier related CSR (ENS)	0.364	0.721	0.421	0.439	0.358	0.338	0.404	0.398
	0.371	0.777	0.362	0.321	0.340	0.353	0.406	0.337
	0.412	0.721	0.396	0.301	0.332	0.301	0.371	0.321
	0.345	0.722	0.336	0.378	0.322	0.311	0.415	0.358
	0.376	0.756	0.413	0.345	0.398	0.320	0.358	0.394
	0.342	0.722	0.400	0.328	0.441	0.397	0.435	0.383
	0.351	0.730	0.323	0.394	0.359	0.388	0.447	0.374
Environment and community related CSR (ENC)	0.390	0.398	0.767	0.412	0.319	0.314	0.323	0.438
	0.410	0.350	0.708	0.421	0.442	0.313	0.391	0.313
	0.337	0.415	0.711	0.357	0.387	0.312	0.443	0.300
	0.356	0.448	0.695	0.402	0.444	0.367	0.423	0.343
	0.403	0.444	0.794	0.340	0.408	0.408	0.347	0.324
	0.422	0.373	0.749	0.346	0.442	0.401	0.306	0.311
	0.315	0.335	0.779	0.353	0.394	0.327	0.399	0.429
	0.431	0.423	0.707	0.404	0.418	0.382	0.417	0.325
	0.311	0.322	0.750	0.368	0.335	0.321	0.433	0.414
Ethics (ETH)	0.310	0.399	0.384	0.770	0.431	0.345	0.336	0.307
	0.303	0.421	0.360	0.797	0.319	0.406	0.376	0.366
	0.369	0.321	0.355	0.731	0.388	0.378	0.376	0.316
	0.415	0.433	0.370	0.797	0.414	0.425	0.361	0.436
Corporate reputation (CRP)	0.363	0.382	0.340	0.400	0.798	0.447	0.432	0.341
	0.424	0.355	0.310	0.430	0.718	0.420	0.438	0.352
	0.403	0.351	0.418	0.386	0.746	0.417	0.442	0.367
Product innovativeness (INN)	0.386	0.351	0.412	0.402	0.415	0.722	0.430	0.391
	0.319	0.400	0.330	0.422	0.319	0.749	0.338	0.380
	0.343	0.328	0.419	0.390	0.366	0.758	0.353	0.325
	0.400	0.359	0.368	0.446	0.310	0.799	0.314	0.395
	0.364	0.339	0.375	0.397	0.402	0.705	0.436	0.369
Brand equity (BEQ)	0.401	0.411	0.320	0.442	0.347	0.324	0.725	0.366
	0.352	0.372	0.305	0.425	0.333	0.421	0.739	0.371
	0.416	0.415	0.310	0.316	0.385	0.314	0.746	0.390
	0.382	0.448	0.429	0.396	0.333	0.356	0.723	0.328
Customer trust (CTR)	0.408	0.333	0.396	0.327	0.447	0.377	0.388	0.798
	0.370	0.321	0.310	0.348	0.332	0.328	0.370	0.788
	0.446	0.322	0.317	0.402	0.421	0.425	0.323	0.777

Note: Bold values significant at 5%.

Source: Authors’ estimation.

The second criteria for assessing ‘Discriminant Validity’ are proposed by Fornell and Larcker (1981). According to this criterion, the square root of the AVE of the construct must be higher than the values of the inter-construct correlations of that construct with another construct. As the generated outcome is shown in Table 5, the values at the diagonal reflect the square root of the AVE. In contrast, the values other than that reflect the correlations across the constructs. Based on the values, the criteria of Fornell and Larcker (1981) are satisfied.

Table 5. Discriminant validity Fornell-Larcker criterion.

	CST	ENS	ENC	ETH	CRP	INN	BEQ	CTR
CST	0.745
ENS	0.514	0.793
ENC	0.551	0.550	0.777
ETH	0.597	0.543	0.491	0.753
CRP	0.597	0.556	0.588	0.546	0.770
INN	0.531	0.566	0.586	0.514	0.569	0.761
BEQ	0.498	0.566	0.550	0.574	0.520	0.597	0.775
CTR	0.524	0.589	0.563	0.573	0.556	0.505	0.542	0.806

Note: Bold values significant at 5%.

Source: Authors’ estimation.

The third criteria to assess the ‘Discriminant Validity’ is newly proposed by criteria by Henseler et al. (2015), which is known as ‘Heterotrait-Monotrait ratio of correlations’ (HTMT). According to Henseler et al. (2015), the HTMT of the construct must have a value that should be less than 0.85; if satisfied, then there is the presence of ‘Discriminant Validity’ among the constructs. Based on the values shown in Table 6, the criteria of HTMT are satisfied.

Table 6. Results of HTMT ratio of correlations.

	CST	ENS	ENC	ETH	CRP	INN	BEQ	CTR
CST
ENS	0.577
ENC	0.695	0.694
ETH	0.723	0.680	0.705
CRP	0.700	0.702	0.698	0.687
INN	0.660	0.699	0.575	0.677	0.615
BEQ	0.704	0.622	0.637	0.583	0.651	0.690
CTR	0.647	0.609	0.746	0.667	0.630	0.685	0.676

Source: Authors’ estimation.

4.1.2. Structural model

After assessing the ‘Measurement Model’ in the following stage, the ‘Structural Model’ was assessed, which includes the assessment of the inner model. According to Hair et al. (2016), the ‘Structural Model’ is assessed by ‘Coefficient of Determination’ (R²) and ‘Cross-validated Redundancy’ (Q²). R² is used to assess the prediction relevancy, whereas Q² is used to check the prediction accuracy. Though the values of both of these criteria are highlighted dependent on the nature of the relationships between predictor and criterion, whereby if the model consists of predictors which are more likely to predict the criterion, then the value will be higher in such models. Nevertheless, Cohen (1988) recommends the values of R² exceeding 0.26 as substantial, whereas Hair et al. (2016) stated values acceptable when exceeds zero. The importance of both criteria is shown in Table 7.

Table 7. Predictive power of construct.

	R-square	Q-square
CRP	0.264	0.125
INN	0.108	0.040
BEQ	0.156	0.088
CTR	0.086	0.055

Source: Authors’ estimation.

After the assessment of the ‘Structural Model’, the next step is hypothesis testing. By the hypothesised associations proposed in Section 2, the results reported positive and significant associations. Precisely, CSR related to the customer was reported to have a positive effect which is also statistically significant$\mathrm{ }(\beta =0.198,\mathrm{ }p<0.01).$ It reflects that an increase in the CSR related to the customer will increase the reputation of the organisation by 19.8%. In other words, in the context of the current study, it is evident from the empirical findings that when the banks strive towards customer-oriented CSR, they are more likely to enhance the reputation across the banking sector in the eyes of the customers. Such a relationship benefits the banks as it improves their reputation level and for the customer side, as it encourages banks to have sufficient CSR activities for customers. These findings are also justified from the existing literature that has reported similar associations among the variables above (for instance, see Swaen et al., 2021).

Secondly, CSR related to suppliers and employees was reported to have a positive effect which is also statistically significant$\mathrm{ }(\beta =0.215,\mathrm{ }p<0.01).$ It reflects that an increase in the CSR related to suppliers and employees will increase the reputation of the organisation by 21.5%. In other words, in the context of the current study, it is evident from the empirical findings that when the banks strive towards supplier and employee-oriented CSR, they are more likely to enhance the reputation across the banking sector in the eyes of the customers. Such a relationship benefits not only the banks as it improves their reputation level but also for the supplier and employees, as it encourages banks to have sufficient CSR activities for supplier and employees, which leave a positive image of the banks in the eyes of the customers. These findings are also justified from the existing literature that reported similar associations among these variables (Öberseder et al., 2013; Swaen et al., 2021).

Thirdly, CSR related to community and environment was reported to have a positive effect which is also statistically significant$\mathrm{ }(\beta =0.164,\mathrm{ }p<0.01).$ It reflects that increased CSR related to community and environment will increase the organisational reputation by 16.4%. In other words, in the context of the current study, it is evident from the empirical findings that when the banks strive towards community and environment-oriented CSR, they are more likely to enhance the reputation across the banking sector in the eyes of the customers. Such kind of relationship benefits the banks as it improves their reputation level and for the community and environment, as it encourages banks to have sufficient CSR activities for the community and environment, which leave a positive image of the banks in the eyes of the customers. These findings are also justified from the existing literature that has reported similar associations among the aforementioned variables (El Akremi et al., 2018; Öberseder et al., 2014; Swaen et al., 2021).

Fourthly, Ethics was reported to have a positive effect which is also statistically significant$\mathrm{ }(\beta =0.247,\mathrm{ }p<0.01).$ It reflects that an increase in the level of ethics and the respective ethical practices across the Banks’ operations will increase the reputation of the organisation by 24.7%. This beta coefficient is the highest among the predictors of reputation in the present study. In other words, in the context of the current study, it is evident from the empirical findings that when the banks prevail and enhance the level of ethics and the respective ethical practices across the operations like avoiding exaggeration in marketing the products and communicating in terms of possible hidden expenses (if any), they are more likely to enhance the reputation across the banking sector in the eyes of the customers. Such kind of relationship benefits the banks as it improves their reputation level and for the customers and stakeholders, as it encourages banks to have sufficient ethical practices across their operations, which leave a positive image of the banks in the eyes of the customers. These findings are also justified from the existing literature that reported similar associations (Amoako et al., 2021; Mella & Gazzola, 2015).

In addition to this, while considering the next phase of the framework, the reputation of the corporate is also reported to have a positive and significant association with Brand Equity$\mathrm{ }(\beta =0.169,\mathrm{ }p<0.01),$ product innovativeness$\mathrm{ }(\beta =0.185,\mathrm{ }p<0.01),$ and trust of the customers $\left(\beta =0.228,\mathrm{ }p<0.01\right)\mathrm{ }$ respectively. It reflects that an increase in the level of reputation of the bank will increase the brand equity of the organisation by 16.9%, increase the product innovativeness by 18.5%, and increase the trust of the customers by 22.8%, respectively. In other words, when the image of the bank is improved in the market, which creates the worthiness and reputation while compared with the other banking institutions in the market, it will improve the brand equity, which will eventually help the bank in improving the level of customer base and in retaining the existing the customers. Moreover, such reputation will also encourage the banks to work on the innovativeness through which they can offer unique and innovative banking products to the customers which can fulfil the requirement of the customers from time to time whereas having a reputed bank which has sufficient market worthiness improve the level of trust of the customers which will further encourage customers to enhance their financial dealings with the same bank. These findings are also justified from the existing literature that reported similar associations among the variables, as mentioned earlier (Hur et al., 2014; Swaen et al., 2021; Torres et al., 2012).

Lastly, while considering the final phase of the framework, product innovativeness is also reported to have a positive and significant association with Brand Equity$\mathrm{ }(\beta =0.096,\mathrm{ }p<0.01),$ and trust of the customers $\left(\beta =0.214,\mathrm{ }p<0.01\right)\mathrm{ }$ respectively. It reflects that an increase in the level of innovation in the bank’s product offerings will increase the organisation’s brand equity by 9.6% and will increase the trust of the customers by 21.4%, respectively. These findings urge the banks to have innovation in their product offerings. By doing that, they are more likely to increase their brand value, customer base, customer retention, and, accordingly, trust. Product innovation is the need of time, and to have the edge over the competitors, banks should regularly compare the products with the similar products offered in the market. By having an honest and legitimate comparison, banks can look for the options by which they can increase the customer base, whereas innovation is the key to success in such a situation. These findings are also justified from the existing literature (Ahmed et al., 2020; Kanwal & Yousaf, 2019; Martín, 2021; Seyedin et al., 2021). The outcome of the hypotheses assessment is shown in Table 8.

Table 8. Results of path coefficients.

Hypothesised path	Path coefficient	C.R.	P-value	Remarks
CRP ← CST	0.198	9.325	***	Supported
CRP ← ENS	0.215	5.092	***	Supported
CRP ← ENC	0.164	5.436	***	Supported
CRP ← ETH	0.247	5.449	***	Supported
BEQ ← CRP	0.169	9.908	***	Supported
INN ← CRP	0.185	7.236	***	Supported
CTR ← CRP	0.228	5.904	***	Supported
BEQ ← INN	0.096	7.744	***	Supported
CTR ←INN	0.214	6.547	***	Supported

*** Level of significance (1% i.e., 0.01).

Source: Authors’ estimation.

5. Conclusion and recommendations

By incorporating CSR in the marketing strategies, the organisations can have a competitive advantage over the competitors. It also helps them attain support from the relevant stakeholders, which eventually assist in building a sophisticated and legitimate corporate reputation. Moreover, by incorporating the CSR operations and activities as part of their marketing campaigns, organisations will be better positioned to influence the customers in terms of their preferences and perceived attributes through which they evaluate back the organisations.

Furthermore, to meet the ever-changing nature of demands of the customers, a firm’s mission and vision should incorporate innovation so that they remain competitive. However, there is no doubt that the innovative product itself is a kind of signal to the customers that the company offering that product has some reputation, whereas it leads to developed brand equity and accordingly develops trust. Hence, the objective of the current study is to identify the role of CSR and ethics as the determinants of CRP, whereas the present study also intends to explore the role of CRP and INN in deriving brand equity and customer trust. By employing the survey methodology, the data was collected from 418 banking customers through the help of a self-administered questionnaire, and PLS-SEM was applied. Following the guidelines of Hair et al. (2016), the results of the PLS-SEM reported positive and significant associations among the variables.

Based on the outcome, there are several managerial recommendations. Firstly, the banking industry needs to have transparency in incorporating CSR as part of its marketing campaigns to cater to legitimate benefits. Secondly, CSR should also be done on the other stakeholders other than customers, which generally focus on the firms. Thirdly, the banking sector should have transparency in terms of their product offerings which makes them ethically correct and help them in improving their CRP accordingly, whereas they should not be exaggerating while marketing their products. Lastly, innovative solution is the key to success in the current highly competitive market. Though the banking sector is highly governed and controlled by central or state banks, they can innovate to increase the market share.

In accordance with the limitations, the current study also has certain future recommendations. Firstly, the relevancy of the framework should be evaluated in other business settings like retailing; secondly, there is a need to have qualitative research in which more insights from the experts are investigated, which can broaden the phenomena of CSR. Thirdly, there is a need to have exploration of further determinants of corporate reputation, which itself is perceived and cognitive. Lastly, the data analysis insights will be improved by incorporating machine learning-based estimations techniques directed to future researchers as a possible avenue of contribution to the literature.

Disclosure statement

No potential conflict of interest was reported by the authors.