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1 – 3 of 3Dezhi Li, Lugang Yu, Guanying Huang, Shenghua Zhou, Haibo Feng and Yanqing Wang
To propose a new investment-income valuation model by real options approach (ROA) for old community renewal (OCR) projects, which could help the government attract private…
Abstract
Purpose
To propose a new investment-income valuation model by real options approach (ROA) for old community renewal (OCR) projects, which could help the government attract private capital's participation.
Design/methodology/approach
The new model is proposed by identifying the types of options private capital has in the OCR project, selecting the option model most suitable for private capital investment decisions, improving the valuation model through the triangular fuzzy numbers to take into account the uncertainty and flexibility, and demonstrating the feasibility of the calculation model through an actual OCR project case.
Findings
The new model can valuate OCR projects more accurately based on considering uncertainty and flexibility, compared with conventional methods that often underestimate the value of OCR projects.
Practical implications
The investment-income of OCR projects shall be re-valuated from the lens of real options, which could help reveal more real benefits beyond the capital growth of OCR projects, enable the government to attract private capital's investment in OCR, and alleviate government fiscal pressure.
Originality/value
The proposed OCR-oriented investment-income valuation model systematically analyzes the applicability of real option value (ROV) to OCR projects, innovatively integrates the ROV and the net present value (NPV) as expanded net present value (ENPV), and accurately evaluate real benefits in comparison with existing models. Furthermore, the newly proposed model holds the potential to be transferred to various social welfare projects as a tool to attract private capital's participation.
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Dezhi Li, Huan Zhou, Shenghua Zhou, Guanying Huang, Xiaoming Ma, Yongheng Zhao, Wentao Wang and S. Thomas Ng
The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously…
Abstract
Purpose
The study aims to pioneer an innovative approach for the evaluation of government portal websites (GPWs) by introducing an eye-tracking-based method. The research meticulously pinpoints and analyses the distinct usability issues and challenges that users encounter while navigating and interacting with GPWs.
Design/methodology/approach
This study devises an eye-tracking-based GPW usability evaluation approach, which focuses on the major functions (i.e. government information disclosure, government services and interactive responses) of GPWs. An Entropy Weighted Technique for Order Preference by Similarity to an Ideal Solution (EW-TOPSIS) method is employed to process eye-tracking indicator results for deriving GPW usability results.
Findings
The proposed approach is demonstrated to assess the usability of 12 GPWs in pilot smart cities in China, and it is found that most GPWs have lower-than-average usability. GPWs with low usability require more cognitive load that exhibit increased fixation and saccade. The comparisons among the GPW usability results from (1) the eye-tracking experiment, (2) questionnaire surveys and (3) the ready-made performance evaluation report validate the effectiveness of eye-tracking-based GPW usability evaluation.
Originality/value
The work contributes to shifting the GPW usability evaluation approach from a subjective judgment paradigm to an objective paradigm, as well as provides implications for enhancing GPW usability, including improving search function, reducing website complexity and prioritizing user needs.
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Kanapot Kalnaovakul, Kandappan Balasubramanian and Stephanie Hui-Wen Chuah
This study investigates the service quality dimensions of hotel resorts in renowned beach destinations of Thailand. It also explores the relationship between review text sentiment…
Abstract
Purpose
This study investigates the service quality dimensions of hotel resorts in renowned beach destinations of Thailand. It also explores the relationship between review text sentiment expressed in online platforms and the satisfaction ratings provided for those reviews.
Design/methodology/approach
The study employs a two-step analysis approach: first, supervised and unsupervised machine learning via support vector machine (SVM) and latent Dirichlet allocation (LDA) are used to identify service quality dimensions, and second, SmartPLS with PROCESS macro is applied to analyze the moderating roles of quality signals and reviewer’s experience on the relationship between sentiment and satisfaction rating. The dataset comprises 102,179 online reviews from TripAdvisor, focusing on 187 selected hotels rated from 3 to 5 stars.
Findings
Eight service quality dimensions were identified, including leisure activities, tangibles and surroundings, reliability, responsiveness, service process, food, empathy and ambience. The study underscores that the service process stands as the sole dimension exhibiting negative sentiment. Furthermore, the analysis revealed a robust positive association between sentiment of review texts and satisfaction, and reviewers’ experience and brand affiliation influenced the relationship between customer sentiment and satisfaction.
Practical implications
Hotel managers should focus efforts on maintaining tangible aspects while enhancing existing service quality level of other dimensions, particularly those related to intangible elements. Independent hotels might implement quality audit to ensure that service quality gaps are monitored.
Originality/value
This study contributes an examination of the moderating roles of quality signals and reviewer’s experience on the relationship between review sentiment and satisfaction rating in online reviews.
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