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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.

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.

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.

This research aims (i) to assess the level of customer satisfaction and loyalty to self-service technologies and Auchan Retail Portugal, (ii) to identify the determinants of customer satisfaction and loyalty to these technologies and also, (iii) to identify their influence on customer loyalty to this modern distribution retailer operating in Portugal.

A conceptual model was defined to meet the research objectives and to carry out the quantitative analysis applied to the random sample (n = 483) of customers. The data used where gathered via an online questionnaire survey, which covered all dimensions of the conceptual model, applied in 2021 in Portugal. To validate the hypotheses, Cronbach’s alpha and multiple linear regression models were used.

The results reveal that customer satisfaction with self-service technologies has a direct and positive effect on customer loyalty to Auchan Retail Portugal. Furthermore, results reveal that the technology utility factors significantly influence the customer technology experience which has an impact on perceived service quality and perceived risk. The findings of this research provide data on how to improve customer adoption and satisfaction with self-service technology and highlight that these technologies should be part of firm’s competitive strategy.

This study presents itself as a novelty for science, while granting important contributions to the retailer. It presents an innovative conceptual model that delivers to Auchan the basis for it to move toward smart retail technologies, aiming at the market trend of personalization. For future research, this study can be used as an instrument to evaluate the customer experience with self-service technology and to examine the determinants and effects of self-service technology separately.

This study proposes a model that influences customer citizenship behavior during COVID-19, and empirically tests the effects of fast-food restaurant customers' perceptions of justice (price and procedural justice) on trust; trust on satisfaction and loyalty; and trust, satisfaction and loyalty on customer citizenship behavior. Furthermore, it was questioned whether there was a disparity between customer expectations based on the restaurant's image and consumption experience.

The data were gathered from customers of fast-food restaurants in the shopping centers in Turkey. The data set, which included 437 valid questionnaires, was subjected to CFA for validity and reliability, SEM analysis for hypothesis and paired sample t-Tests for the research questions.

The findings of the study indicate that perceived justice affects customer trust, which, consequently, affects customer loyalty and satisfaction during the COVID-19 period. Findings also demonstrate that, while customer loyalty and trust increase customer citizenship behavior, customer satisfaction alone is insufficient to increase customer citizenship behavior. The study also shows that during the COVID-19 period, fast-food restaurants should have raised awareness of employees’ fair behaviors toward the customers and provided additional services to differentiate themselves in the market. Also, it indicates that customer expectations related to price, cleanliness and professional appearance of staff are not met after taking service.

No research has been found in the literature focusing on the expectations, justice, trust, satisfaction, loyalty and citizenship behaviors of fast-food restaurant customers in the COVID-19 pandemic process. Therefore, the results can fill the gap in relevant literature by testing the relationships between justice, trust, satisfaction, loyalty and citizenship during the pandemic and provide inferences for fast-food business owners.

This research aims to analyze the customer satisfaction associated with experiences from 14 ecological hotels in Ecuador by exploring online guest reviews and classifying the most influential factors.

This study applied big data exploration, semantic network analysis, EFA and linear regression. It processed 22,629 online reviews from Google/travel, extracting 100 words with the highest frequency. In addition, CONCOR analysis built a comprehensive structural model gathering essential keywords. Furthermore, exploratory factor analysis and regression were conducted to explore the elements that best express customer satisfaction in ecological hotels.

The words such as green, sustainable, recycle, environment and ecological were not found among the main attributes extracted. Nonetheless, the keywords obtained reflect customer satisfaction, revealing that green practices do not affect comfort and the guests' experience. CONCOR analysis displayed four categories associated with satisfaction: tangibles, experience, location and empathy. Then, EFA restructured and revealed the factors: facilities feature, assurance, reliability, location and experience. Lastly, the regression disclosed location, assurance and facilities features as the most significant factors for customer satisfaction in the 14 ecological hotels. The terms related to the hotel area, staff care and hotel amenities were decisive for guests.

This study demonstrated that employee courtesy and location are the keys to enhancing customer experience and satisfaction. Hotel managers must promote green attributes and practices to increase customer awareness through constant staff training and information disclosure in common areas.

These findings provide insight and empirical evidence for hoteliers to understand how and what guest perceive to be green practices. By identifying the main features or concepts associated with satisfaction in Ecuador's green hotels, hoteliers could address new strategies to respond to expectations, effectively satisfy customers and provide a superior experience.

This study empirically investigated the different attributes (i.e. convenience, online reviews, online ratings, visual appeal and various food choices) of food delivery applications (FDAs) that impacted customers' perceived benefits, satisfaction and loyalty. Price consciousness was positioned as the moderator while customer satisfaction was positioned as the mediator.

Utilizing the purposive sampling technique, 360 useable respondents were gathered from existing FDAs' customers in China. Partial least squares structural equation modelling (PLS-SEM) was employed to verify the interrelationships among variables.

The results confirmed the significant impact of four FDA attributes (i.e. convenience, online ratings, visual appeal and various food choices) on perceived benefits. Customer satisfaction positively influenced loyalty. Moreover, the mediating role of customer satisfaction and the moderating role of price consciousness were confirmed.

FDA operators should engage in providing more benefits to stimulate satisfaction and loyalty among customers. Promotion discounts remain a key factor in enhancing the satisfaction and loyalty of price-conscious customers.

This study extends the applicability of the stimulus–organism–response (SOR) framework and enriches FDA literature by assessing the external stimuli, organisms and moderating factors that trigger customer loyalty.