Impact of Corporate Reputation on Customers’ Sustainable Usage Intention: The Mediating Role of Satisfaction ()
1. Introduction
The reputation of an organization is an intangible asset that produces extra earning capacity over normal earnings. It is achieved by an organization inherently through providing quality services, gaining customers’ belief, trustworthiness, and faith in the services. In relationship marketing, the main aim is to build a prolonged relationship with valued customers. Reputation is the customers’ recognition of a few features or overall qualities of an organization (Su et al., 2016) . So, corporate reputation could be considered as the keen strategic resource which contributes to the organization’s sustainable competitive benefits (Capozzi, 2005) . The strength of corporate reputation, especially for banks, has become a fundamental leverage for distinction and success (Phong & Anh, 2023) .
Customers are generally preferring to choose the services of an organization for reputation in the market. Mobile financial service (MFS) is a digital financial service in which a customer can easily do banking activities by using an electronic device or digital assistance like a mobile phone, Tab, etc., from anywhere anytime (Uddin & Nasrin, 2023) . MFS facilitates customers to deposit, withdraw, transfer, add & send money, pay utility & merchant bills, send remittances, mobile recharge, etc. through agent points or the customer himself from his device or apps (Afroze & Rista, 2022; Lan & Giang, 2021) . If MFS providers ensure safe and secured financial services or the settlement of financial transactions promptly, this spreads out their reputation among the users in the market. As a result, customers could trust themselves for operating financial transactions in MFS.
Customers’ positive attitude towards mobile financial services generates customer satisfaction and intention to reuse for a long time. They also recommend to their relatives, friends & family, colleagues, and others for using the services. This positive word-of-mouth improves the corporate reputation of the MFS providers. There are 71.23 million customers actively receiving mobile financial services from thirteen MFS providers in Bangladesh despite of the number of registered customers 209.58 million at the end of July 2023 (Bangladesh Bank, 2023) . In the era of digitization, more customers are opting for mobile financial services in their daily life due to the offering of faster services (Sarwar, 2019) . But customers have a lot of complaints against MFS providers on its services, for example, fraudulent activities, password hacking, threats of losing personal information, money laundering, etc. For example, New Age Bangladesh a daily newspaper heading, “bKash customers face increasing number of defrauding” published in October 2022 where highlighted that a huge number of complaints of bKash users are lodged to the cybercrime unit of detective branch in Bangladesh for swindling their money by the fraudsters (NewAge, 2022) . Another online news portal in Bangladesh namely Newsbangla 24 on August 2021 made a report on, “terrible deception in the name of development” regarding bKash in which a Senior Assistant Commissioner of the Cyber Crime Unit stated that a lot of unauthorized e-transactions are happening through bKash but customers are not stepping to complaints against the fraudulent activities for avoiding legal complications (Amin & Nuruzzaman, 2021) . Bangladesh Financial Intelligence Unit (BFIU) had provided a list of suspected mobile banking agents of bKash, Rocket, and others to the CID in Bangladesh. BFIU had claimed that MFS agents are directly involved with illegal financial transactions for smuggling, hundi, and narcotics (Sarwar, 2019) . But these reports in newspapers, online portals or social media are creating a negative reputation for the MFS providers that may affect their business performance and growth in the long run. It leads to customer dissatisfaction and results in refraining themselves from the services. Thus, the number of customers is increasing over the years but the actual users are decreasing and they are leaving to alternative services in the market. It means customers are not intent to use services continuously for a long time. This indicates that there is a close relationship between corporate reputation, satisfaction, and customers’ sustainable usage intention.
A lot of studies had taken place previously on service quality and customer satisfaction, or the effect of perceived usefulness, ease of use, security and trust, risk and privacy, but to the best of authors’ knowledge no study found on the effect of corporate reputation on customers’ sustainable usage intention of mobile financial services with mediating role of satisfaction. To fill this gap, the study aims at investigating the effect of corporate reputation on the customers’ sustainable usage intention of MFS with an intervening impact of customer satisfaction. The remaining part of the study covers in section 2 literature review, section 3 research methodology, section 4 results, section 5 discussion of the results, section 6 contribution of the study, and in last section includes the conclusion, limitations, and future research directions.
2. Literature Review and Hypotheses Development
The relevant literatures and concept on corporate reputation, customer satisfaction and customers’ sustainable usage intention are summarized as well as developed hypotheses for the present study in this section.
2.1. Corporate Reputation
Corporate reputation refers to the impression, feelings, belief, idea, and knowledge on an organization in customers’ minds (Asnakew, 2020; Poromatikul et al., 2020; Samadou, 2018) . It is interchangeable with the brand, image, or identity of a business organization from the perspective of consumer and community (Kang & Yang, 2010; Keh & Xie, 2009) . Corporate reputation reflects by overall impression of users’ positive word of mouth and fulfilment of pre-expectation of services (Poromatikul et al., 2020) . It plays a vital role in the reduction of uncertainties and risk as perceived by the customers in the banking industry (Cintamür & Yüksel, 2018) . This is connected with customers’ overall expectation and perception. When customers regard an organization as having a positive reputation, they tend to perceive a higher value of its services. This eventually leads to customer satisfaction and reuse intention of services (Lee et al., 2016) . Organizations should focus on corporate image or reputation to achieve customer satisfaction. Nguyen et al. (2018) state that positive corporate reputation would help to hold a strong market position for the organization.
2.2. Customer Satisfaction
Customer satisfaction refers to a judgment that a service provides customers a pleasant feeling by meeting their expectations (Su et al., 2016) . The customer satisfaction level is normally assessed by the comparison between customers’ perception and expectation towards services (Nguyen et al., 2018) . The role of customer satisfaction is significant in developing business strategy and to the sustainable development of organization. Corporate reputation significantly affects customer satisfaction that was justified in prior studies of ECSI (Poromatikul et al., 2020) . The corporate reputation and customer satisfaction are run in the same way, i.e., the higher the corporate image, greater the customer satisfaction (Bernarto & Purwanto, 2022) . A bad corporate reputation negatively influences customer satisfaction and a good reputation positively affects customer satisfaction with services. So that, banks should improve corporate reputation to attain customer satisfaction (Eren, 2021) .
2.3. Effect of Corporate Reputation on Customer Satisfaction
Corporate reputation eases customers to pick the right option or comparatively better services among the banks or financial institutions. It also reflects on organizational creativity which develops customers’ trust, conveys perceived benefits, and fulfills customers’ expectation and satisfaction (Bernarto & Purwanto, 2022) . The effect of corporate reputation on customer satisfaction is proved in prior studies. Eren (2021) in a study found that corporate image positively related with customers satisfaction and significantly impacts on it. Su et al. (2016) in their research confirmed that corporate reputation had a positive impact on customer satisfaction. So, based on these literatures support, the following hypothesis is postulated for the present study:
H1: Corporate reputation has a positive and significant influence on customer satisfaction.
2.4. Customers’ Sustainable Usage Intention
An organization which ensures reputable services is able to attract new customers and retain existing customers, and equally its bad reputation loses the customers (Barnett, Jermier, & Lafferty, 2006) . Poromatikul et al. (2020) in their study had found that corporate reputation has a significant effect on customers’ continuous usage decision. If an organization has a positive corporate reputation in the eye/mind of customers, they must remember such organization and intend to use services continuously (Qalati et al., 2021) . Simbolon et al. (2020) state that corporate reputation or brand image directly or indirectly affects customers’ loyalty and continuous usage decision through customer satisfaction. C. Chen (2013) highlighted that a positive corporate reputation acts as a good risk disinclination of MFS providers and distinguishes them from competitors. It also boosts customers to continue the use of services.
2.5. Effect of Corporate Reputation on Customers’ Sustainable Usage Intention
If any service providers or banks have a positive reputation or image to the customers, they intend to visit often to get services. It plays a significant role to condense the risks and uncertainties as perceived by the customer in financial services (Cintamür & Yüksel, 2018) . Before experiencing any particular services like mobile financial services, customers rely more on organizational or corporate reputation to recognize service quality and future usage intention. Uddin and Nasrin (2023) explore that corporate image is a promising antecedent of customers’ sustainable usage intention. Samadou (2018) stated that corporate image has a direct effect on customers’ continuance intention of using services. Thus, the following hypothesis is proposed for the present study:
H2: Corporate reputation has a positive and significant impact on customers’ sustainable usage intention.
2.6. Effect of Satisfaction on Customers’ Sustainable Usage Intention
Satisfied customers are enthused to continue the usage of mobile financial services. It forces the MFS providers to ensure better customer services (Avornyo et al., 2019) . There is a correlation among customers’ expectation, satisfaction and continuous usage intention. If customers’ pre-expectation meets or exceeds, they are satisfied with the services and subsequently intend to continue using such services for a long time (Wu et al., 2022) . Therefore, the following hypothesis is set for the study:
H3: Customer satisfaction positively and significantly affects sustainable usage intention.
2.7. Mediating Effect of Satisfaction on Corporate Reputation and Customers’ Sustained Usage Intention
Kristensen et al. (2000) states that corporate image plays a key role to the creation of customer satisfaction and customers’ loyalty. Samadou (2018) highlighted that corporate reputation indirectly affects customers’ continuous usage intention with the intervention of customer satisfaction. Yazid et al. (2020) studied the telecommunication sector where they found that customer satisfaction fully intervene on the relationship between corporate image and loyalty. On inspiring this output, the present study postulates the following hypothesis:
H4: Customer satisfaction has an intervening effect on corporate reputation and customers’ sustainable usage intention.
On the basis of literature reviews and purposes of the study, the following conceptual research model has been developed (Figure 1).
3. Research Methodology
3.1. Sampling and Data Collection
The convenient sampling procedure i.e., non-probability sampling technique is followed for this study. Two MFS providers namely, Dutch-Bangla Bank Ltd. and BRAC Bank Ltd. were selected purposively. These two MFS providers are the pioneers and top market leaders in MFS industry in Bangladesh. A well-structured questionnaire was administered and allocated to the respondents through Google Docs by sharing the idea about constructs and describing the purposes of data collection. The period of data collection was from April 2023 to May 2023. The questionnaire consists of two section, section one contains respondents demographic information like gender, age, occupation, education, monthly gross income, and location; and section two includes respondents’ opinion regarding corporate reputation, satisfaction, and customers sustainable usage intentions of MFS. The study area was Kushtia and Jehenaidah Districts of Bangladesh. The sample units and study area represents the same scenario in terms of facilities and features of mobile financial services all over the country. Total 400 questionnaires were distributed among the Rocket and bKash users of Dutch-Bangla Bank Ltd. and BRAC Bank Ltd., respectively in the selected areas by giving the link of Google Doc and received responses from 273 users. Out of 273 responses, 250 respondents’ (62.50 percent) data were used for the study and remaining was not considered due to incomplete or missing or duplicate answers of questions. Hair et al. (2010) suggested that the sample size for a study should be minimum five times of items in the questionnaire. Since the present questionnaire contains thirteen items, this should be required 65 respondents. On the other hand, Reinartz et al. (2009) recommended that the minimum respondents should be 100 in PLS-SEM. The present study fulfills this requirement in the selection of respondents. The ethical issue was addressed in this study by giving declaration to the respondents that their response should remain confidential and only used for academic purposes.
3.2. Measurement Scales
The conceptual research model comprises three constructs such as corporate reputation, customer satisfaction, and sustainable usage intention of mobile financial services. Each of the constructs also consists of latent items or measurement items. These latent or measurement items are adapted from the existing literature. For instance, corporate reputation has four measurement items which adapted from Poromatikul et al. (2020) ; customer Satisfaction has also four items that adapted from Bhattacherjee (2001) ; and sustainable usage intention has five measurement items which adapted from Kang, Lee, and Lee (2012) . Most of the measurement items are modified and/or reinvented in the context of the present study. Also the reliability and validity of measurement items are tested statistically which allowed to proceed the next steps. Five-point Likert scale ranging from 1 “Strongly Disagree” to 5 “Strongly Agree” is used to assess the measurement items.
3.3. Statistical Techniques
Structural equation modeling (SEM) is used in the study to evaluate the causal-effect relationship between exogenous and endogenous variables. The variables used in the study are corporate image (CI), customer satisfaction (CS), and sustainable usage intention (SIU). In PLS-SEM, firstly used a measurement model to examine the reliability and validity of data. Secondly, the structural model is used to test the hypotheses of the study.
4. Results
4.1. Analysis of Respondents’ Demographic Profile
Respondents’ demographic statistics presented in Table 1 that contains gender, age, educational qualification, profession, monthly gross income, and residential areas. The results represent that in the case of gender, male respondents were much higher than females. Among the five age groups of respondents, a higher number from the range of 31 - 40 years followed by 41 - 50 years, below 20 years and so on. From the educational qualification perspective, 91 percent respondents held Bachelor and Master degree, and only 9 percent from secondary and below secondary level. From the professional point of view of the respondents, almost one-third of the respondents were in service and the rest were in business, students, unemployed and others. In terms of monthly gross income of the respondents, 33 percent of respondents’ monthly gross income were above Tk. 50,000 and 33 percent were in between Tk. 30,000 to 50,0000, and 13 percent respondents’ income were under Tk. 10,000. For the residential area status of the respondents, 68 percent were located in urban areas followed by rural (17 percent) and semi-urban (15 percent) areas respectively.
4.2. Assessment of Measurement Model
The measurement model is used to examine the reliability of data and validity of
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Table 1. Respondents demographic profile.
constructs in the research model. This model is presented in Figure 2 showing the indicator loadings. Chen et al. (2022) suggested that a loading value lower than 0.50 should be deleted, and the value more than 0.90 should leave to achieve the data reliability in the model. Hair et al. (2019) also recommended that items loading value should be greater than 0.708 as it implies that the construct explains higher than 50 percent of the indicator’s variance. But, the items
loading value more than 0.50 is also acceptable for further steps. The corresponding value of the indicator loading of the observed variable CR1, CR2, CR3, and CR4 are 0.712, 0.887, 0.844 and 0.804 respectively. Likewise, the indicator loading value of the observed variable CS1, CS2, CS3, and CS4 are 0.825, 0.899, 0.887, 0.894 respectively. Similarly, the outer loading matrix of the observed variable SIU1, SIU2, SIU3, SIU4, and SIU5 are 0.744, 0.650, 0.765, 0.787, and 0.715 respectively. All the indicators loading value (as presented in Figure 2) were found to be an acceptable threshold for the study.
4.2.1. Test of Reliability
In the measurement model, firstly determine the reliability of data through Cronbach’s alpha technique and Composite reliability parameters (Henseler et al., 2009) . The Cronbach’s Alpha value of each construct is 0.7 threshold and above acceptable for further analysis of data (Hair et al., 2019) .
Besides, Cronbach’s Alpha, Composite reliability is another measure to ascertain the accuracy of data (Hair Jr. et al., 2017) . The value of composite reliability in between 0.60 and 0.70 is considered acceptable for further study. Also the value ranging from 0.70 to 0.90 indicates “satisfactory to good”, but if the output of the composite reliability is over 0.95 of any construct it is problematic and would decay the validity of the construct. Table 2 represents the results of Cronbach’s alpha and composite reliability test where all the values are within the acceptable range and permit further study.
4.2.2. Validity Analysis
The next to the reliability test is the assessment of validity of constructs in the
Source: Output of SmartPLS 4. Note: CR—Corporate Reputation; CS—Customer Satisfaction; SIU—Sustainable Intention.
measurement model. Convergent and discriminant validity are the two measures of testing the validity of constructs. Convergent validity deals with a construct convergence for explaining the variance of the measurement items of constructs. Convergent validity is measured by the static value of AVE (average variance extracted) for each construct item. Hair et al. (2019) recommended that the AVE value should be greater than 0.50 for achieving the convergent validity.
Discriminant validity measures whether the constructs are theoretically discriminant to each other or unrelated. Chin (1998) stated that every indication loading must be larger than the sum of all cross loading for it to be valid. The output of convergent and discriminant validity as per the Fornell-Larcker criterion is presented in Table 3. The AVE value for each construct is greater than 0.50 indicating the establishment of convergent validity. Likewise, the value of discriminant validity for each construct is diagonal and larger than the beneath value. So, it is justified that this study has no discriminant value and confirmed the discriminant validity.
The Hetrotrait-Montrait Ratio Matrix (HTMT) is another measure of testing the discriminant validity. Table 4 shows the result of HTMT where the constructs corresponding value is lower than 0.90. Hair et al. (2019) suggested that the HTMT value should be lower than 0.90 at the upper bound of 95% confidence interval for establishing the discriminant validity. Thus, the output in Table 4 implies that there is no discriminant issue among the constructs and the discriminant validity is achieved.
The factor loading is also the key measure of discriminant validity. The construct items loading should be higher than the cross loading value (Chin, 1998) . Table 5 explains the discriminant validity output-cross loading where it indicates that the factor loadings are larger than the available cross loading. It implies the establishment of discriminant validity for the study.
4.3. Structural Model
The next step after the measurement model in PLS-SEM is the structural model. Structural model is used to test the hypothesis of the study as well as preferable to examine the mediating effect of the study (Chin, 1998) . The VIF (Variance Inflation Factor) value for the construct items ranges 1.207 to 2.403 indicating that the study does not have any multicollinearity problems. The latent structure
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Table 3. Validity test output (fornell-larcker criterion).
Source: Output of SmartPLS 4.
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Table 4. Discriminant validity-HTMT output.
Source: Output of SmartPLS 4.
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Table 5. Discriminant validity output-cross loading.
Source: Output of SmartPLS 4.
is allied with a structural model in PLS-SEM (Sohaib et al., 2019) that determines the relationship between the models (Hair Jr. et al., 2017) . Under the structural model, the sample size was explained by using the observed bootstrapping process and ascertained the significance with t-statistics and p-value. This study has used a normal bootstrapping with a range of 5000 bootstraps and 100 cases to determine the value of direction of coefficient.
Figure 3 demonstrates the structural model of this study. The model represents the causal-effect relationship between exogenous and endogenous variables.
The study examined the intervening effect of customer satisfaction on corporate image and customers’ sustainable usage intention of MFS. Figure 3 indicates that all the relationship between observed variables (CR1, CR2, CR3, CR4, CS1, CS2, CS3, CS4, SIU1, SIU2, SIU3, SIU4, SIU5) and latent variables (CR, CS, SIU) are significant as the p-value is less than 0.05 (at 5% level of significance). The casual effect relationship between corporate reputation (CR) and customer satisfaction (CS) is significant as the p-value is lower than 0.05. Similarly, the relationship between customer satisfaction (CS) and sustainable usage intention (SIU) is also significant at 5% level of significance. Moreover, the casual effect relationship between corporate reputation (CR) and customers’ sustainable usage intention (SIU) is insignificant since the p-value is higher than 0.05 i.e., at 5% level of significance.
Table 6 presents the path coefficient value of the relationship between the constructs. Based on Table 6, the result depicted that corporate reputation has a positive relationship (beta value 0.598) and significant influence on customer satisfaction (t-value > 1.96 and p-value < 0.05 at 5% level of significance). So, hypothesis 1 is accepted. Hypothesis 2 specifies that corporate reputation has a positive and significant influence on customers’ sustainable usage intention. The inferential output revealed that corporate reputation has a positive relationship with customers’ sustainable intention as the beta value is 0.166. The inferential statistics of t-value is 1.464 that is lower than 1.96 at 5% level of significance and p-value is 0.143 which is higher than 0.05 significance level. It means that the hypothesis is not supported. Hence, corporate reputation has no direct effect on sustainable usage intention. Hypothesis 3 explained that customer satisfaction
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Table 6. Path coefficients and hypothesis testing.
Source: Output of SmartPLS 4.
significantly and positively impacts customers’ usage intention to use mobile financial services. The statistical output displayed that customer satisfaction is positively related with sustainable usage intention (beta value 0.457). It also significantly affects customers’ sustainable usage intention since the calculated t-value (4.686) is higher than 1.96 and the p-value (0.00) is lesser than 0.05 significant level. Thus, the hypothesis 3 (H3) is supported.
The r-square value in coefficient of determination represents the predictive accuracy of the conceptual research model. It is recognized to explain the variances in the endogenous constructs of the model. The R-square value denoted 0.327 in customers’ sustainable usage intention describing 32.70 percent of the total variance. That means, customers’ sustainable intention is explained 32.70 percent by corporate reputation and customer satisfaction but the remaining 67.30 percentage is explained by other variables. This shows the moderating predicting power of the research model. Likewise, the R-square value of 0.357 in customer satisfaction denotes 35.70 percent variances explained by corporate image in the model and rest percentage by others. This also indicates the moderating predicting power.
4.4. Analysis of Mediating Effect
Under this study, customer satisfaction has been used as a mediator between the corporate reputation and customers’ sustainable usage intention of mobile financial services. In the mediation analysis, the study followed path analysis (CI -> CS -> SIU) in PLS-SEM and focused on the output of the indirect effect concerning the relationship among corporate reputation, customer satisfaction, and sustainable usage intention. Based on the inferential statistics of mediation analysis in Table 7, customer satisfaction mediates the relationship between corporate reputation and customers’ usage intention because the beta value is 0.273, t-value is greater than 1.96 (calculated value 4.073), and p-value is lower than 0.05 (0.00). Hypothesis 4 (H4) indicated that customer satisfaction has an intervening effect on corporate reputation and customers’ usage intention. So, the inferential statistics revealed that hypothesis 4 is supported.
4.5. Assessment of Full or Partial Mediation
After finding the intervening or mediating effect, it is relevant to assess whether
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Table 7. Mediating or indirect effect of customer satisfaction and hypothesis testing.
Source: Output of SmartPLS 4.
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Table 8. Direct effect and indirect effect.
Source: Output of SmartPLS 4.
it is partial or full mediation. Carrión, Nitzl, and Roldán (2017) suggested that if the direct effect of independent variable on dependent variable is insignificant but the indirect is significant in the presence of mediator, it is treated as full mediation. They pointed out that if both the direct and indirect effects are significant, it indicates partial mediation. Table 8 describes that the direct effect of corporate reputation on customers’ sustainable usage intention is insignificant (β = 0.116, t-Value = 1.464, and p-Value > 0.05) but the indirect effect of corporate reputation on it with the presence of customer satisfaction is significant (β = 0.273, t-Value = 4.073, and p-Value < 0.05). The total effect of corporate image on customers’ sustainable usage intention is also significant (β = 0.439, t-Value = 4.979, and p-Value < 0.05). Consequently, the statistical output shows that customer satisfaction fully mediates the relationship between corporate reputation and customers’ sustainable usage intention.
5. Discussion
Corporate reputation is surely intimated to the business success. This study provides underlying insights into which corporate reputation affects customers’ sustained usage intention. MFS providers with positive reputation benefits to build a quality relationship with customers which in turn positively influences customers’ sustained usage intention. The findings revealed that corporate reputation is a significant antecedent of customer satisfaction. Similarly, satisfaction is an important antecedent of customers’ sustained usage intention. This is similar to Su et al. (2016) who also revealed corporate reputation as an important variable of customer satisfaction, and corporate reputation is influenced by customer satisfaction.
The conceptual research model in this study has shown corporate reputation and customer satisfaction as the two antecedents of customers’ sustainable usage intention. Corporate reputation in the present model is also an antecedent of customer satisfaction. The result explored that corporate reputation has a positive and significant effect on customer satisfaction. This is similar to prior research work done by Poromatikul et al. (2020) ; Eren (2021) ; and Nguyen et al. (2018) where they found that corporate reputation has a positive relationship and significant impact on customer satisfaction. This study also revealed that corporate reputation has no direct effect on customers’ sustained usage intention of mobile financial services. This output is matched with Poromatikul et al. (2020) who found in their study that corporate image has no effect on the continuous usage intention of mobile banking applications. But this study differs from Lan and Giang (2021) who denoted that a bank’s brand image has a significant effect on customers’ usage decisions. The findings also demonstrate that satisfaction has a significant effect on customers’ sustainable usage intention. This result supports Poromatikul et al. (2020) where it was explored that customer satisfaction significantly influenced customers’ continuous usage intention of mobile banking.
In the theoretical framework of this study, there was a mediating role of satisfaction between the corporate reputation and customers’ sustainable usage intention. It specified that customer satisfaction intervenes in the relationship between corporate reputation and customers’ sustainable usage intention of MFS. The statistical output has shown that satisfaction fully mediates the relationship between corporate reputation and customers’ sustained usage intention. This finding is consistent to Samadou (2018) who showed that corporate image significantly impacts customers’ usage intention to use mobile banking services in the presence of customer satisfaction. Under this study, corporate reputation did not affect directly customers’ sustainable usage intention but had an indirect impact on it in the presence of satisfaction. So, customer satisfaction plays a significant role in the corporate reputation and sustainable usage intention of mobile financial services in Bangladesh. The MFS providers should take initiatives like the orientation of fraud prevention awareness programs, the building of social awareness by publishing services security features in media, to improve their positive reputation and gain customer satisfaction that might lead to the customers’ sustainable usage intention.
6. Innovation and Contribution of the Study
Usually, customers like to value the organization’s reputation before experiencing or the initial adoption of its product or services. After experiencing if they are satisfied, they intend to reuse or repurchase the product or services for a long time. This is obvious that there is a casual-effect relationship among corporate reputation, satisfaction and sustainable usage intention. The current study newly presents customer satisfaction as mediator between corporate reputation and customers’ sustainable usage intention and investigates the mediating effect of customer satisfaction on corporate reputation and customers’ sustainable usage intention in the context of mobile financial services. This study theoretically contributes to the current body of knowledge in mobile banking services. The key contribution is providing the quantitative and analytical output of the intervening effect of customer satisfaction on corporate reputation and customers’ sustainable usage intention of MFS. The theoretical framework or the conceptual model offers an important insight in MFS literature in customers’ sustainability and services marketing studies. The output of this research may be used as a reference or empirical evidence for further studies in the financial sector in a distinct culture or regional context. This study also practically contributes to the policymakers, customers, and stakeholders in respect of making decisions on mobile financial services. The findings of the research will be useful for the bank to enhance its image, reputation, and positive belief in customers’ minds.
7. Conclusion, Limitations and Future Directions
7.1. Conclusion
Customers keep faith in corporate reputation in selecting financial services to a greater extent. Corporate reputation grows positivity in the customers’ minds leading to their satisfaction and bringing sustainability to the usage of services. The main aim of the study was to investigate the intervening effect of customer satisfaction on the relationship between corporate reputation and customers’ sustainable usage intention of MFS. The output of the study reveals that corporate reputation positively and significantly affects customer satisfaction. Similarly, customer satisfaction positively impacts customers’ sustainable usage intention. The empirical result also explores that corporate reputation has no direct effect on customers’ sustainable usage intention in MFS but has an indirect effect on it. The findings in mediation analysis show that customer satisfaction intervenes in the relationship between corporate reputation and customers’ sustainability in usage decisions. If the corporate reputation of MFS providers/banks is positive, this creates customer satisfaction which leads to sustainability in users’ decisions to use or reuse the services. MFS providers should focus on developing their corporate reputation among the users for creating customer satisfaction and bringing sustainability to their usage decision.
7.2. Limitations and Future Directions
This study has some limitations that might cause the concern of generalizability. The main limitation of the study was the selection of the study area because it covered only two district in Bangladesh. Also, the number of respondents was small and followed a cross-sectional basis in data collection from such respondents. So there is a further scope to broaden the study area or other distinct cultures by following a longitudinal approach. There was only one independent variable like corporate reputation in the conceptual model but adding more variables, for instance, perceived benefit, social influence, hedonic motivation, and word-of-mouth, to the model may improve the predicting power of the conceptual model in MFS contexts or across the banking industry.