Modeling customer satisfaction and revisit intention in Bangladeshi dining restaurants

A user satisfaction model for mobile government services: a literature review

User satisfaction is essential for the success of an organisation. With the development of government service delivery through mobile platforms, a compatible measurement model must be found to measure user satisfaction with performing such services through a mobile government portal. Measuring user satisfaction with mobile government services is necessary nowadays due to the increasing popularity of smart devices. Research on mGovernment users' satisfaction is lacking, leading to difficulties in understanding users' expectations. In the present study, systematic literature reviews have been used to analyze users' satisfaction with mGovernment portals and propose a comprehensive model compatible with such contexts. The results show that government agencies can evaluate users' satisfaction using the proposed model of six quality constructs: usability, interaction, consistency, information, accessibility, and privacy and security. The study recommends improving the evaluation strategies of mGovernment portals regularly to ensure they fit with challenges. Measuring user satisfaction at mGovernment services encourages the user to perform the transactions through such online platforms, increasing the digitalization process and reducing the cost and efforts for both the service provider and end-users.

Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis

Restaurant research has received significant attention globally. This article aims to examine the evolution and the knowledge structure of restaurant research over the past decades. We also investigate the restaurant research hotspots and knowledge diffusion paths based on 1489 articles extracted from the Web of Science database. Furthermore, we conduct a keyword co-occurrence network analysis and four different types of main path analyses to scrutinize the historical formation of the restaurant research. Results revealed that restaurant research mainly focused on five research themes: consumer behavior, consumer satisfaction, social media, green restaurants, and authenticity. While consumer behavior has been the mainstream topic, the focus of this line of research has recently shifted from traditional to luxury and ethnic restaurants. Furthermore, our analysis has detected several recent changes in response to the COVID-19 pandemic. By examining the knowledge structure of restaurant research, we reveal its knowledge diffusion paths and provide avenues for future research in this vast and interdisciplinary research field.

Exploring Recreationist-Environment Fit Hospitality Experiences of Green Hotels in China

To develop the hotel industry’s competitiveness, research on satisfaction and revisit intentions has always been important. More research has recently focused on guests’ pro-environmental behaviors and low-carbon management in the hotel industry. This research creates a recreationist-environmental fit satisfaction-revisit intention model based on the recreationist-environmental fit theory. This study surveyed seven green-standard hotels in Sanya, China, and tested the moderating effect of guests’ environmental behavior on their satisfaction and willingness to revisit. Self-administered questionnaires were distributed to respondents who had visited the surveyed green-standard hotels. Two hundred and forty-five valid questionnaires were collected with the hypotheses developed and examined using the SEM and HMR methods. The results indicated that the suitability of a leisure environment could positively impact guest satisfaction, which positively affected their willingness to revisit. In addition, this study proved the moderating effect of guests’ pro-environmental behaviors between satisfaction and revisit intentions.

Developing and validating e-retailing satisfaction scales with text-mining

Purpose

The purpose of this study includes two parts. First, it introduces a machine-based method for model and instrument development and updating that integrates large sample qualitative data. Second, a new model and instrument for e-commerce customer satisfaction are developed.

Design/methodology/approach

The research occurs in two phases. In Phase 1, data collection occurs with a literature-based quantitative model and instrument that includes at least one qualitative scale item per construct. Data analysis of the resulting data includes factor analysis (FA) and latent semantic analysis text mining to generate an updated model and instrument. In Phase 2, data collection uses the new model and instrument. Data analysis in Phase 2 includes exploratory data analysis with FA, exploratory structural equation modeling and partial least square modeling.

Findings

As a result of the information gained by the integration of qualitative scales in the literature-based survey, the final model departs substantially from the initial research-based research model. It integrates many of the constructs known to impact a website and software usability from information systems research into a new e-retail satisfaction model.

Originality/value

The research method, as presented here, offers a strategy for integrating large scale qualitative data for refinement of models and the development of instruments. It is essentially a method of gaining the wisdom of crowds economically while simultaneously reducing the biases and laborious effort commonly associated with qualitative research.