A comparative study of eight COVID-19 protective measures and their impact on Swiss tourists’ travel intentions

A comparative vignette-based experimental survey design incorporating various socio-psychological factors, linked to the Theory of Planned Behavior (TPB), the Health Belief Model (HBM) and the Domain-Specific Risk-Taking scale (DOSPERT) was carried out to test variations in eight travel-related COVID-19 protective measures on Swiss tourists’ travel intentions. Among the tested measures, vaccination passports, surgical masks and quarantining are those that stand out the most, with surgical masks having the greatest acceptance and willingness to adopt while traveling. Quarantining, on the other hand, appears to have a deterrent influence on travel intentions, and vaccination passports have the lowest perceived barriers during travel, but the highest perceived benefits in mitigating the spread of the infection. The discussion of individual differences has specific implications for tourism management against the background of our empirical findings.     

Mitigating panic buying behavior in the epidemic: An evolutionary game perspective

The panic buying behavior under public health emergencies will lead to many adverse consequences, such as material waste, price fluctuation and uneven distribution of epidemic prevention materials, which will pose a threat to the social stability and economic development. In this paper, we construct a tripartite game model to explore the strategic choices of the public, merchants and the government in order to effectively respond to the panic buying behavior in the epidemic. The results demonstrate that: (1) Eight evolutionary stable strategies emerge in the panic buying events. The worst scenario can be improved by adjusting some relevant parameters. (2) The probability of the public choosing the strategy of “not involving in panic buying” depends on the potential benefits and losses of snapping up, rather than the extent of price rising. (3) The probability of merchants choosing the strategy of “not bid up price” depends on the intangible benefits. (4) The probability of the government choosing the strategy of “active supervision” depends on the supervision costs and government credibility, rather than the amount of fines. In addition, strategic suggestions to mitigate panic buying behavior are put forward from the perspective of each stakeholder.     

Size of nested cities

Models of cities based on conventional spatial market theory are unable to replicate a realistic size distribution. The stochastic process approach to size distribution, which assumes proportionate growth, does not provide an economic foundation for spatial trades. There is an apparent irreconcilability. We propose that since there is a continuum of equilibria in models of spatial markets with endogenous location, proportionate growth can work as equilibrium selection. We present computations for an urban configuration that has not been presented in the literature before. A small city locates inside a larger city's agricultural supply zone. This generates a larger variation in city size that may include a realistic size distribution.     

Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution

This paper presents a new facility location problem variant with application in disaster relief. The problem is unique in that both verified data and unverified user-generated data are available for consideration during decision making. The problem is motivated by the recent need of integrating unverified social data (e.g., Twitter posts) with data from more traditional sources, such as on-the-ground assessments and aerial flyovers, to make optimal decisions during disaster relief. Integrating social data can enable identifying larger numbers of needs in shorter amounts of time, but because the information is unverified, some of it may be inaccurate. This paper seeks to provide a “proof of concept” illustrating how the unverified social data may be exploited. To do so, a framework for incorporating uncertain user-generated data when locating Points of Distribution (PODs) for disaster relief is presented. Then, three decision strategies that differ in how the uncertain data is considered are defined. Finally, the framework and decision strategies are demonstrated via a small computational study to illustrate the benefits user-generated data may afford across a variety of disaster scenarios.     

A Kaleckian Perspective on Financialisation and Distribution in Three Main Eurozone Countries before and after the Crisis: France,Germany and Spain

The purpose of this article is twofold. First, we examine if, and to what extent, a general Kaleckian analysis of the potential effects of financialisation on income shares in advanced capitalist economies is of relevance for the three Eurozone countries under investigation—France, Germany and Spain—in the period before the recent financial and economic crisis. Second, we study changes in the financialisation–distribution nexus that have occurred in the course of and after the financial and economic crisis. We find that the countries examined here have shown broad similarities regarding redistribution before the crisis, although there are some differences in the underlying determinants. These differences have continued during the period after the crisis and have led to different results in the development of distribution since then.     

农村集体经营性建设用地流转模式再审视：基于产权让渡与市场化的视角

研究目的:厘清集体经营性建设用地流转模式,推进集体建设用地入市改革。研究方法:以产权让渡及市场化为视角,采用矩阵分类法划分集体经营性建设用地流转模式,剖析不同流转模式特征与演进路径。研究结果:基于本研究视角可将集体经营性建设用地流转划分为6种模式,不同模式具有不同特征、运行条件、优缺点及收益分配格局,且其存在关联并遵循一定的演进规律。研究结论:规范市场下农地发展权及使用权流转模式将是当前改革的方向,需从法律法规上明确农地发展权相关规定;不同地区需因地制宜地选择流转模式及类型,探索具体实施办法,循序渐进推进流转改革与创新。     

产学研协同创新成本分摊机制研究

产学研协同创新是推动技术创新的一条重要路径，但创新成本分摊机制是影响产学研协同合作的一个重要问题。通过构建充分竞争市场下的多阶段博弈模型，从成本分摊机制角度探究了如何有效推进产学研协同创新。通过模型扩展与求解，获得成本分摊后的帕累托改善以及产学研协同创新的可行路径。结果表明：企业和学研方基于自身收益最大化而进行的成本分摊协商无法实现帕累托最优，而轮流出价博弈模型下的成本分摊形成机制能够有效改善各方收益，并使整体收益达到帕累托最优，因此是一条现实可行的帕累托改善路径，其中，各方获得的收益增量与耐心程度的对比有关。     

“Retail is detail! Give consumers a gift rather than a bundle”: Promotion framing and consumer product returns

Retailers often use the promotion strategy of offering supplementary products (e.g., free gift, bundle) to attract consumers and increase sales. Despite the growing literature on the promotions that are differently framed but offer economically identical values, little research has examined the link between promotion framing and consumer product returns. The current article sheds light on this relationship, hypothesizing that a free gift promotion would be superior to a bundle promotion in reducing consumer product returns. The findings suggest that a gift‐framed promotion leads to a lower product return intention than an economically equivalent bundle promotion, because consumers tend to perceive more loss from giving up the gift‐framed (vs. bundle‐framed) deal. Further, this study examines a moderating role of brand familiarity (familiar vs. unfamiliar) and shows that the merits of free gift framing on product return intention via perceived loss are amplified (attenuated) when the promoted brand is familiar (unfamiliar). Overall, the investigations of this study imply that it is better to frame a promotion as a “free gift” than a “bundle” to increase perceived loss in returning the purchase and thus to decrease consumer product returns. This strategic intervention works especially when the gift is offered by familiar brands.     

Stadiums and Scheduling: Measuring Deadweight Losses in the Victorian Football League, 1920–70

Over a 50 year period, Australian Rules football's major league, the Victorian Football League, did not always use its largest and best-equipped stadium for regular season games between its most popular teams or schedule those teams to play twice in a regular season. We calculate deadweight losses from the use of capital goods (stadiums) and effects of match scheduling in this professional sports league. Such analysis has not been attempted previously because of the absence of a counterfactual. The welfare losses were significant but not sufficient to threaten the survival of a distance-protected cartel.     

Factor state–space models for high-dimensional realized covariance matrices of asset returns

We propose a dynamic factor state–space model for high-dimensional covariance matrices of asset returns. It makes use of observed risk factors and assumes that the latent integrated joint covariance matrix of the assets and the factors is observed through their realized covariance matrix with a Wishart measurement density. For the latent integrated covariance matrix of the assets we impose a strict factor structure allowing for dynamic variation in the covariance matrices of the factors and the residual components as well as in the factor loadings. This factor structure translates into a factorization of the Wishart measurement density which facilitates statistical inference based on simple Bayesian MCMC procedures making the approach scalable w.r.t. the number of assets. An empirical application to realized covariance matrices for 60 NYSE traded stocks using the Fama–French factors and sector-specific factors represented by Exchange Traded Funds (ETFs) shows that the model performs very well in- and out of sample.