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Any banking institution’s success depends heavily on customer satisfaction. Understanding and evaluating customer satisfaction has become crucial with the rise of small finance banks (SFBs) in India, which serve the underserved and unbanking segments of society. In the context of SFBs in India, this chapter aims to examine the variables affecting customer satisfaction as well as how it affects these banks’ overall performance and sustainability. This study will help us better understand the dynamics of customer satisfaction in the Indian financial landscape by examining the particular difficulties and opportunities that SFBs face.

The study aims to identify the determinants of customer satisfaction in the electronic commerce (e-commerce) industry in Bangladesh. It also investigates whether acceptance of IT innovation mediates the relationship between the determinants of e-commerce and customer satisfaction.

A survey questionnaire had been designed and distributed among the customers of e-commerce businesses. Data were collected from 408 respondents, who were mostly from urban areas of the country. The collected data had been analysed with the application of the partial least square approach using SmartPLS4. First, the measurement model was applied to determine the validity and reliability of the dataset. Then, the structural model was utilized to justify the hypothesis.

The results showed that customer service, perceived ease of use and customer trust in e-commerce services have a significant positive impact on customer satisfaction. The acceptance of IT innovation, which showed a positive influence on customer satisfaction, enhanced customer satisfaction when accompanied by perceived ease of use and digital literacy.

The results would have valuable insight for the e-commerce business in designing their products and services and taking policies to achieve long-term customer loyalty.

This is the first study that incorporates IT innovation acceptance as a mediating variable. Although a number of factors have been identified as the determinants of customer satisfaction, the specific mechanism of IT innovation acceptance as a mediator between predictors and customer satisfaction is unique in this study.

This study analyzed the relationship between mobile financial services (MFS) usage and customer satisfaction with MFS in Bangladesh, considering perception, purpose of use and technical challenges as the primary factors influencing customer satisfaction with MFS. The aim is to determine the factors most influencing the use of MFS.

Data were collected from 400 MFS users through a structured web survey using snowball sampling that is consistent with the nature of MFS users who are difficult to identify or locate. Structural equation modeling (SEM) was used to analyze the data and evaluate the reliability and validity of the measurement model.

The results show that customers’ perceptions and satisfaction significantly impact their intention to use MFS. Specifically, customers’ perceptions strongly influence their satisfaction with MFS, and the purpose of use significantly predicts both perception and satisfaction. Technical problems and challenges were found to have no significant impact on satisfaction levels, but other factors were more critical. Furthermore, the integration of innovative technological solutions is crucial for fostering sustainability in MFS, as it enhances reliability and efficiency while minimizing environmental footprints.

The study was conducted in a single country, relied on self-reported data, and used a cross-sectional design, which limits the ability to draw causal inferences. Future research could explore the factors that influence customer satisfaction with MFS in different countries and regions and incorporate additional variables to provide a more comprehensive understanding of the drivers of customer satisfaction with MFS.

This study significantly contributes by extending the technology acceptance model (TAM) framework with the innovation resistance theory, offering a nuanced understanding of MFS adoption. The findings challenge conventional wisdom, highlighting the limited impact of technical problems on satisfaction and emphasizing the central role of user perceptions in shaping satisfaction and intention to use.

In this study, the service quality of an automobile authorized service center was investigated based on the European Customer Satisfaction Index (ECSI) model. The ECSI model includes image, customer expectations, perceived quality, perceived value, customer satisfaction, customer complaints and customer loyalty.

In the study, an attempt was made to improve the ESCI model by adding the trust factor as a moderating variable. After an extensive literature review, measurement questions were developed to best represent the factors in the research model. Partial least squares structural equation modeling (PLS-SEM) was used to test the fit of the research model and test the hypotheses.

As a result of the analysis, only one of the 13 hypotheses tested was not supported. According to the results of hypothesis testing, the highest effect was found in the relationship between customer satisfaction customer complaints, customer expectations and perceived quality. In addition, customer expectations affect customer satisfaction indirectly rather than directly. In this case, customer expectations, perceived value and perceived quality influence customer satisfaction.

The customer satisfaction quality index score of the authorized automobile service whose service quality was measured was calculated as 72.75. Although customers were generally satisfied with the authorized service, their expectations were not fully met.

In the study, an attempt was made to improve the ECSI model by adding a trust factor. Trust, which was added to the model as a moderator variable, fit the model. As a result, it was revealed that trust has an increasing regulatory effect on the relationship between perceived quality and customer satisfaction.

The aggressive competition in the real estate market forces real estate developers to tackle the challenge of selecting the best project construction phasing alternative. The real estate industry is characterized by high costs, high profit and high risks. The schedules of real estate projects are also characterized by having large number of repetitive activities that are executed over a long duration. The repetitiveness, long duration of execution, the high amounts of money involved and the high risk made it desirable to leverage the impact of changes in phasing plans on net present value of amounts incurred and received over the long execution and selling duration. This also changes the project progress, and delivery time as well as their respective impact on customer degree of satisfaction. This research addresses the problem of selecting the best phasing alternative for real estate development projects while maximizing customer satisfaction and project profit.

The research proposes a model that generates all construction phasing alternatives and performs decision-making to rank all possible phasing alternatives. The proposed model consists of five modules: (1) Phasing Sequencing module, (2) Customer Satisfaction module, (3) Cash-In calculation module, (4) Cost Estimation module and (5) Decision-making module. A case study was presented to demonstrate the practicality of the model.

The proposed model satisfies the real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model generates all construction phasing alternatives and performs multi-criteria decision making to rank all possible phasing alternatives. It quantifies the score of the two previously mentioned criteria and ranks all solutions according to their overall score.

The research proposes a model that assist real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model can be used to conclude general guidelines and common successful practices to be used by real estate developers when deciding the construction phasing plan. In this study the model is based on business models where all the project units are sold, rental cases are not considered. Also, the budget limitations that might exist when phasing is not considered in the model computations.

The model can be used as a complete platform that can hold all real estate project data, process revenues and cost information for estimating profit, plotting cash flow profiles, quantifying the degree of customer satisfaction attributable to each phasing alternative and providing recommendation showing the best one. The model can be used to conclude general guidelines and common successful practices to be used by real estate developers when tackling the challenge of selecting construction phasing plans.

The purpose of the chapter was to examine the impact of customer care chatbots on customer satisfaction levels in the mobile telephony industry in Zimbabwe, with a special focus on the company Econet Wireless. This chapter shows the conceptual framework used. An online questionnaire was administered to a sample of 100 Econet Wireless subscribers who were selected using probability stratified random sampling from Zimbabwe’s 10 provinces. The research data were collected and analysed for correlation, and a multiple regression analysis was carried out to identify the relationship between customer satisfaction and the three customer service improvements brought in by the introduction of customer service chatbots. The study discovered that there is a positive relationship between customer satisfaction levels and each of the three customer service improvements brought in by customer service chatbots, namely customer service convenience, speed of response, and omnichannel strategies. This study thereby proves that the introduction of customer service chatbots in the mobile telephony industry in Zimbabwe can lead to an improvement in customer satisfaction levels. However, addressing service quality only as a determinant of customer satisfaction in isolation is not sufficient to fully improve customer satisfaction levels. Therefore, organisations that seek to improve their customer satisfaction should consider strategies that address all determinants of customer satisfaction, namely price, product quality, service quality, situational factors, and personal factors. This study contributes to the body of knowledge, particularly regarding the use of artificial intelligence (AI) for customer service in developing economies.

This study aims to extend research in marketing on two important relational constructs, customer satisfaction and brand attachment, by comparing their long-term effects on customer behaviors with different levels of performance difficulty in a relatively understudied domain of durable products.

Using a two-stage quantitative study with US customers from five durable product categories, the authors first explored the hierarchy of customers’ loyalty behaviors based on increasing effort in a pretest study (N = 675). Then, the authors tested the effectiveness of satisfaction and brand attachment for customers’ loyalty behaviors over a nine-month period in a longitudinal study (N = 2,284) with customers from the same product categories.

Compared to satisfaction, brand attachment emerges as a stronger long-term predictor of customer behaviors. The performance difficulty of customer behaviors positively moderates the impact of brand attachment and negatively moderates the impact of customer satisfaction. Brand attachment is particularly effective in predicting difficult-to-perform customer behaviors, which require customers to expend resources such as time and money. Customer satisfaction is mainly effective for predicting easy-to-perform behaviors, but its long-term impact is significantly lower for easy-to-perform behaviors than brand attachment.

The use of consumer durables in the study and samples from only one country restricts the generalizability of the findings.

The complementary roles of customer satisfaction and brand attachment are highlighted. Only satisfying customers is not enough to engage customers in behaviors that require resources such as money, time and energy for the brand.

A comparative study on the long-term effectiveness of two established relational metrics in explaining different customer behaviors varying in their performance difficulty in an understudied domain of durable products.

In the era of Industrial Revolution (IR) 4.0, the integration of digital technologies, automation and data-driven insights has generated a broad wave of transformation across all industries, including the insurance sector. The study focuses on determining how the adoption of these technologies (InsurTech) is changing the life insurance industry, ultimately enhancing the level of customer satisfaction.

The data analysis has been performed with 304 useable responses from the policyholders of life insurance in the north-west region of India. The methodology adopted for this study is partial least squares (PLS) structural equation modeling (SEM). To investigate the predictive relevance of customer satisfaction, the PLS predict technique has been used. Also, importance performance map analysis (IPMA) has been applied to assess the important and performing dimensions of customer satisfaction.

The outcomes show that the adoption of InsurTech has a positive impact on customer satisfaction. Customer service management and policy management are among the strongest predictors of customer satisfaction, and the predictive relevance is reported to be moderate. IPMA results have suggested that improvements in online distribution of insurance services and customer service management lead to higher customer satisfaction.

The conceptual model can be tested with the moderating effect of different demographic factors (age, gender etc.), and future research can be done to analyze the mediating role of customer satisfaction between InsurTech adoption and customer loyalty.

The study offers valuable contributions to the marketing literature, shedding light on the influence of InsurTech adoption on customer satisfaction within the Indian life insurance sector. The research offers a practical approach that could help marketing professionals and policymakers comprehend the utilization of online insurance services, and this understanding can help industry experts to develop customer-oriented products and services.

This research is the first of its kind to test the association between InsurTech adoption and customer satisfaction in the life insurance sector in the Indian context. Research also provides novel insights for policymakers to enhance the satisfaction of customers towards using online insurance services in the near future in developing countries like India.

This study aims to examine the effect of e-customer relationship management (e-CRM) on customer e-loyalty through e-service quality and e-satisfaction. This study also examines how customers’ e-loyalty affects their willingness to recommend a banking service.

A total of 372 private bank customers from Chattogram, the second largest and only port city of Bangladesh, were chosen using a convenience sampling technique. Structured equation modelling was used to analyse the data.

E-CRM positively impacts e-service quality, customer e-satisfaction and customer e-loyalty. The association between e-CRM and customer e-loyalty is sequentially mediated by e-service quality and e-satisfaction. E-loyalty has a significant influence on willingness to recommend a banking service.

The findings will help Bangladeshi banks boost the number of prospective customers implementing e-CRM. In addition, mediators between e-CRM and e-loyalty provides managers a new insight on willingness to recommend a banking service.

The sequential mediation effect of e-service quality and customer e-satisfaction on the connection between e-CRM and e-loyalty represents the unique contribution and enriches the present e-CRM literature, particularly in the Bangladeshi private banking sector.

This study investigates the key factors that influence customer satisfaction when interacting with augmented reality shopping assistance applications (ARSAPs). ARSAPs grant consumers the capability to experience products in a virtually simulated user environment before product acquisition. With the development of mobile e-commerce due to breakthroughs in smartphone and augmented reality (AR) technologies, there is an increasing potential for these emergent AR mobile services, yet there is a need for further improvement.

This study initially explored the key satisfaction factors for ARSAPs by utilizing topic modeling of a collection of actual user reviews. These factors are subsequently revisited and complemented by existing literature, and finally verified through logistic regression analysis supported by sentiment analysis.

This study identified the key factors that influence customer satisfaction with ARSAPs, including visuality, sense of reality, credibility, format, completeness, understandability, relevance, flexibility, response time, reliability, availability, ease of use and privacy. In particular, two additional factors (i.e. visuality and sense of reality) were newly identified as important in the context of AR, despite their previous omissions in existing literature.

This study is the first to investigate the key factors that influence customer satisfaction with ARSAPs from users' perspectives, utilizing topic modeling of a large amount of real-world data on actual user feedback. By identifying new factors (i.e. visuality and sense of reality) that were not identified in previous literature, this study provides important academic implications for a broader understanding of AR and related technologies that are essential elements of the metaverse. This study also provides valuable insights for developers and companies in the e-commerce industry on how to optimize AR applications and develop more targeted and effective marketing strategies in this field.