PurposeLarge cities are and will continue to become important tourism destinations in foreseeable future. Tourists' motives of the present is the prognosis for their future tourists' behavior. In respond to the longstanding critics in city tourism study, the present research aims to examine the underlying motives of tourists visiting large cities and offer insights into fashioning tourism future for visiting large cities. The identified motives inform three distinct implications fashioning tourism future of large cities.Design/methodology/approachA quantitative investigation was performed by surveying city tourists. Measurements on the survey form were derived from both scholarly and grey literature in relation to tourists' motivations. 326 valid questionnaires were netted to attain the study aim. Three-quarters of respondents were from Europe, Australia and Pacific. Descriptive analysis and exploratory factor analysis were conducted to achieve the research aims.FindingsFive underlying motives of tourists visiting large cities were revealed: shopping indulgence, urban commons, city icons, cultural and lifestyle and personal advancement. Mapping the findings with a conceptual scheme depicting tourism product in destination, the author revealed a new dimension, urbanity and offered critical reflection on three implications for the tourism future of large cities.Originality/valueLiterature examining city tourists' motives neglect the context-specific measurements while administering the investigation. The research design embraces the urban-specific measurements in the data collection tool, contributing to deeper understanding on how tourism functions in cities. A new dimension, urbanity, which illustrates tourists' motives exclusive in large cities, was identified. Furthermore, three implications fashioning tourism future of large cities are revealed with the support of empirical evidence.

Based on Maslow's hierarchy of needs, this study develops a five-factor casinoinduced satisfaction of needs scale and examines its relationship with casino customer loyalty using Macau as a study context. The findings show that the respondents' most visited casinos had only marginally met the respondents' various inner needs; there's still ample room for Macau casinos to improve the level of their customers' satisfaction regarding customers' inner needs. Among the five types of inner needs, self-actualization appears to be one need that requires more attention because it was rated as the need that was the least satisfied but contributed the second most to measuring satisfaction. Additionally, Macau casinos should continue their efforts in improving and maintaining a safe and secure casino environment, coupled with providing a variety of quality foods and beverages, for their customers. Lastly, safety and security, self-actualization and physiology needs were found to positively affect casino customer loyalty.

Purpose This study aims to understand how a community of practice (CoP) facilitates the knowledge spiral of intangible cultural heritage (ICH) in tourist destinations. Design/methodology/approach This case study focuses on Cantonese opera, a representative example of the ICH of Hong Kong. Narrative inquiry with eight CoP members was used in this study. Findings The CoP members believed that the city has unique and quality tourism knowledge. They used their professional expertise in the domains of creating, collecting and sharing both explicit and tacit knowledge. With the strategic goal of creating a sustainable competitive advantage, CoP act as a kernel in knowledge creation by converting explicit knowledge into tacit knowledge and vice versa. Originality/value This study uses the knowledge spiral model to understand knowledge creation, and it contributes to the sparse literature on knowledge management in the field of tourism, especially the role of CoP. It addressed a gap in the literature pertaining to knowledge creation and ICH.

Consumers' demand for fresh agricultural products (FAPs) and their quality requirements are increasing in the current agricultural-product consumption market. FAPs' unique perishability and short shelf-life features mean a high level of delivery efficiency is required to ensure their freshness and quality. However, consumers' demand for FAPs is contingent and geographically dispersed. Therefore, the conflicting relationship between the costs associated with the logistics distribution and the level of delivery quality is important to consider. In this paper, the authors consider a fresh agricultural-product distribution path planning problem with time windows (FAPDPPPTW). To address the FAPDPPPTW under demand uncertainty, a mixed-integer linear programming model based on robust optimization is proposed. Moreover, a particle swarm optimization algorithm combined with a variable neighborhood search is designed to solve the proposed mathematical model. The numerical experiment results show the robustness and fast convergence of the algorithm.

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