Deterrents of tourism business crowdfunding: Aversion decision and aversion behavior

Crowdfunding has been recently suggested as an effective means for tourism business founders to gain financial support. Yet, few business founders in tourism have employed the method to fund their business creation and development. Using the behavioral decision model in complex and uncertain business situations, this qualitative study explored the deterrents to crowdfunding adoption and the factors that shape the perception of the deterrents in tourism business founders. The data collected by in-depth and face-to-face semi-structured interviews with 22 informants. Our findings revealed a combination of perceived personal, social and contextual deterrents that avert crowdfunding adoption decision and actual behavior. More specifically, our analysis explored attitude towards crowdfunding, perceived control over using crowdfunding, social norms and perceived contextual feasibility of crowdfunding as the determinants of crowdfunding aversion decision and aversion behavior. This study contributes deeper insights into tourism business financial management and crowdfunding policy, theory, practice and research development.     

Tax Benefits of Open Individual Private Pension Plans

This article describes the open private pension plans offered in Brazil, which is one of the four pillars of the Brazilian retirement system. A framework is created to describe and analyze the impact of the transaction costs and tax advantages one can obtain from these financial products. This framework allows us to show and measure the advantages of these products versus other alternatives for long-term investment in the Brazilian financial market. It is shown that private plans are better than direct investment in funds in a high interest rate environment.     

The effectiveness of tryvertising in hotels

Advertising has been a common practice to promote products and services in the tourism and hospitality industry. Although ample research has investigated customers’ perceptions of and reactions to advertising visuals, direct experience advertising strategies, such as tryvertising have been ignored. As an emerging direct experience approach, tryvertising has been increasingly used in tourism and hospitality businesses especially in hotels. This study explores the effectiveness of tryvertising practices on customer purchase behaviors in hotel settings. Two real data sets that combine 6858 records of customers’ hotel stays and guestroom products purchase transactions were obtained from a hotel management company that uses tryvertising strategies in China. The results from a Heckit model analysis determine the potential factors that affect hotel guests’ likelihood to buy and the amount of money spent on products promoted through tryvertising. This study fills this void in the current literature that focuses on traditional mass advertisements and behavioral intentions rather than actual purchase behaviors. It contributes to the literature with empirical evidence of the impact of tryvertising strategies on consumer behaviors in a hotel context. Managerial implications are suggested for practitioners to customize their tryvertising strategies.     

Navigating through the complex transport system: A heuristic approach for city tourism recommendation

The fast development of machine learning and artificial intelligence has led to a great improvement of the smart tourism recommendation system, however many problems associated with the choice of transport modes in city tourism have yet to be solved. This research attempts to address this issue by proposing a model of customized day itineraries with consideration of transport mode choice. With improved particle swarm optimization and differential evolution algorithm, a nondominated sorting heuristic approach was devised. A case study was carried out in Chengdu, China to examine the performance of our approach. The results show that compared with extant methods, our approach achieves better performance. In addition, our approach can create more sensible, multifarious, and customized itineraries than previous methods. Tourism organizations and mobile map app providers could integrate our proposed model into their existing smart service systems, as part of their e-business or digital strategy for enhancing tourist experience.     

A credibility-based multi-objective temporary logistics hub location-allocation model for relief supply and distribution under uncertainty

Disaster response operations revolve around uncertainties. While uncertainties arising due to randomness can be avoided for post-disaster location problem, those arising because of impreciseness may persist long after the disaster's occurrence. Despite the uncertainties and lack of sufficient information about the extent of the damage, disaster response facilities must be established quickly after the occurrence of the disaster. Moreover, the decisions of whether to open, where to locate, and when to open disaster response facilities are based on the amount and quality of information available during the decision-making period. To address these issues, we develop a multi-objective location-allocation model for relief supply and distribution that accounts for the imprecise and time-varying nature of different parameters and time-varying coverage, while also accommodating the subjective attributes necessary to enable establishment and operation of the temporary logistics hubs (TLHs). A credibility-based fuzzy chance-constrained programming model is employed to account for the impreciseness inherent in predicting parameter values during disaster response. The results show where, when, and how many TLHs to open and how to allocate relief supplies. Meanwhile, the sensitivity analysis provides a broader understanding of the impact of limiting the number of TLHs as well as the confidence level and the spread of the symmetric triangular fuzzy numbers on the attainment of the model objectives.     

Improving Order Fulfillment Performance through Integrated Inventory Management in a Multi-Item Finished Goods System

Effective inventory management is fundamental to order fulfillment excellence and supply chain success. In this paper, we develop a strategic inventory management decision tool that integrates inventory classification and inventory control policy decisions for maximizing order fulfillment performance, while accounting for a constraint on inventory budget and the profit expectation of a firm. This inventory solution tool provides critical enhancements to current inventory planning software, which is developed upon the traditional inventory classification scheme and where practitioners have to balance service levels and safety stock decisions through trial-and-error. The model allows firms to assess whether the current inventory performance is Pareto optimal, quantify the trade-offs between various performance measures, and identify the right inventory level according to the firms' strategic goals. In computational results, we demonstrate the trade-off and positive relationships between key item- and order-based inventory performance measures and short-term profitability under different levels of inventory budget in a multi-item finished goods inventory system.     

Expectile CAPM

Conventional wisdom suggests that the uncertainty of uninformed noise-traders’ sentiment deters rational traders’ arbitrage activities. However, nowadays, social media have made the public sentiment highly predictable, whereas the CAPM-motivated beta-return relation still does not hold in practice. This study advances an argument that the sentiment can also be brought about by rational, sophisticated investors’ use of psychological insight; resultantly, the arbitrage activities are demotivated by their own sentiment, rather than deterred by noise-traders’ sentiment risk. The proposed expectile CAPM provides a parsimonious way to account for this claim, and leads to a sentiment-based functional form of pricing kernel.     

新形势下优化工程施工企业财务管理的对策分析

伴随着我国社会经济的发展和城市化进程的加快,越来越多的建筑工程项目投入施工建设。当前工程施工企业在进行财务管理时还存在一定的问题和不足,尤其是在新收入准则颁布和实施之后,对工程施工企业财务管理提出了新的要求,需要规范收入管理。论文主要针对工程施工企业财务管理的现状,着重探讨新准则模式下优化工程施工企业财务管理的对策。     

生育、劳动人口福利与机制设计

通过建立动态优化模型，进行模拟发现：在没有配套性政策下按照政策生育会降低劳动人 口的福利水平。这意味着，如果自愿进行生育，全面二孩政策下民众很可能不会有效地响应政策。 进一步模拟发现：养老制度转轨和降低生育成本的政策，如果与生育政策调整同时进行，可以增 加社会资源，补偿生育对劳动人口福利的挤占，但是政策具有生育效应的关键在于转轨带来社会 资源增量须用于生育支持，降低家庭生育成本的关键在于提高社会照看与提供孩子产品和服务企 业的社会生产率。政策启示在于，尽快出台与生育政策配套性的措施，特别是生育支持性政策。     

Smoothing and Benchmarking for Small Area Estimation

Small area estimation is concerned with methodology for estimating population parameters associated with a geographic area defined by a cross-classification that may also include non-geographic dimensions. In this paper, we develop constrained estimation methods for small area problems: those requiring smoothness with respect to similarity across areas, such as geographic proximity or clustering by covariates, and benchmarking constraints, requiring weighted means of estimates to agree across levels of aggregation. We develop methods for constrained estimation decision theoretically and discuss their geometric interpretation. The constrained estimators are the solutions to tractable optimisation problems and have closed-form solutions. Mean squared errors of the constrained estimators are calculated via bootstrapping. Our approach assumes the Bayes estimator exists and is applicable to any proposed model. In addition, we give special cases of our techniques under certain distributional assumptions. We illustrate the proposed methodology using web-scraped data on Berlin rents aggregated over areas to ensure privacy.