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The Bed and Breakfast (B&B) enterprises generally lack sufficient human resources and time to conduct research on important social media marketing factors for visitors’ satisfaction and visitors’ intentions. Therefore, this study aims to provide crucial social media marketing and factors and service quality elements for improving customer satisfaction and customer loyalty in B&B sectors. This study also provides some recommendations for attracting more visitors and increasing customer satisfaction and customer loyalty through social media.

First, social media marketing factors and service quality elements were identified through the systematic literature review. Then these identified factors and elements were used to design a survey questionnaire for collecting data. The research data included responses of 64 B&B enterprises and 625 customers. The collected data was analyzed by feature selection approaches including Decision Tree algorithm and Information Gain to identify the key factors for improving customer satisfaction and customer loyalty.

The findings of this study determined that featured choice is an important social media marketing factor, and assurance is the common service quality element for both B&B enterprises and their customers in terms of satisfaction and loyalty.

This study adds a value to the growing literature on customer satisfaction and loyalty in B&B sectors by exploring key social media marketing factors and service quality elements. The study reveals several implications for theories and practices. The findings hopefully help B&B enterprises better social media marketing with less workforce and budget.

As emerging e-course providers after the COVID-19 crisis, universities (UNI) policymakers in the Mekong Delta region (MDR) have faced difficulties owing to limited clues about what factors improve student retention and recruitment. This study aims to determine important factors (IF) for student satisfaction with e-course adoption (e-satisfaction) for student retention and recruitment.

Survey data collected from 850 students of the target UNI were analyzed using the DT-fuzzy DEMATEL method. Input factor dimensions included course design, technical infrastructure, interaction, teacher-related and student-related factors. Decision Trees (DT) confirmed the final factors; fuzzy decision-making trial and evaluation laboratory (DEMATEL) was used to establish the cause-effect relationships among these factors.

DT-fuzzy DEMATEL method can identify satisfied and dissatisfied students (accuracy = 94.95%) and determine IFs successfully. The most IFs included new and useful knowledge/information provided, various effective teaching methods and motivation to read provided learning materials.

Although e-satisfaction has been the focus of theories and practices, e-satisfaction in an emerging region like MDR has been studied here for the first time. Most IFs can be used as predictors for e-satisfaction and serve as a primary reference for UNIs’ policymakers. Several practical suggestions were also provided for the sustainable and long-term development of e-programs.

Due to the high use of mobile devices, the market share of mobile advertisements (Ads) is significantly growing. Although mobile Ads can contact potential customers at any time and in any location depending on their unique demands, one of the biggest problems for advertisers is how to improve customer repurchases with their Ads. The development and empirical support of customer repurchase through mobile Ads context have not been addressed. Therefore, the purpose of this paper is to define and identify the key attributes of customer repurchase in a mobile Ads context.

In this research, the set of attributes was derived from a systematic literature review and finalized by applying the Fuzzy Delphi method. To develop a hierarchical model and classify the cause/effect groups among identified key attributes, the Fuzzy mixed approach uses a combination of Fuzzy interpretive structural modeling-decision-making trial and evaluation laboratory.

The findings suggest that language, type of website and social media are classified to as essential attributes for improving customer repurchase through mobile Ads.

The focus of the current research is limited to identify and develop the hierarchical interrelationships between customer repurchase attributes that are unique to the mobile Ads business context. Additional research may be conducted for various media contexts and other products/services categories.

This study illustrated how multicriteria decision-making techniques could be used effectively using Fuzzy theory to explore the research area of customer repurchase in mobile Ads concept.

This study aims to simultaneously examine customer complaints through the proposed novel Design for Six Sigma (DFSS) model which incorporates of creating the new insurance services to win customers' hearts and mind for the insurance industry.

A novel DFSS research methodology which includes the theory of inventive problem solving (TRIZ), Pugh concept selection, creative product analysis matrix and importance–satisfaction model (I–S Model) was proposed. In addition, a real insurance company case was studied to illustrate the effectiveness of the proposed DFSS model.

The results of a novel DFSS model not only can establish new services, but also can dramatically reduce the cost of resolving customer complaints.

The findings of this study are useful for insurance companies and other related service providers in devising tailored strategies to offer quality and suitable services to their customers.

This study addresses the paucity of research and marketing gaps through the proposed novel DFSS model for the first time in the insurance industry. These study findings would enable researchers and practitioners to formulate strategies for solving customer complaints effectively and develop new services from time to time.