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1.
The COVID-19 pandemic has been a major shock to the global tourism industry. Given its peculiarity, this paper analyzes one of the most intriguing questions in the Airbnb literature – the pricing of Airbnb listings – by taking advantage of a difference-in-differences methodology that largely draws on variations in country-level policy responses to the pandemic. Relying on a dataset containing weekly information from 130,999 continuously active listings across 27 European countries from 2019 to 2020, this study first investigates the exogenous impact of response policies (proxied by the COVID-19 Stringency Index) on demand. Secondly, accounting for the endogeneity of both demand and prices, this research analyzes pricing responses to demand variations. Results show that: i) increases in the COVID-19 Stringency Index cause significant declines in Airbnb demand; ii) increases in demand cause, on average, increases in Airbnb prices; and iii) pricing strategies between commercial and private hosts differ substantially.  相似文献   
2.
While the tourism sector shifts towards digital transformation, Destination Management Organisations (DMOs) often struggle to adapt to their changing technological environment. This study explores the antecedents of digital collaboration and develops a framework for micro-DMOs to enhance effective destination management through digital technologies. An integrated sequential qualitative approach was adopted by conducting multi-phase interviews, in addition to designing and trialling a real-world trial digital platform. The research provides empirical evidence that digital collaboration is essential for micro-DMOs, necessitating them to transform their current “websites” into digital platforms which act as a hub for business stakeholders to actively be involved in. Antecedents of successful digital collaboration include mutuality, trust, control, and leadership which may be manifested differently from non-digital collaboration. Additionally, the study identifies three aspects for digital collaboration; marketing, networking and knowledge sharing that demands specific attention. Our results have theoretical, methodological, and practical implications for academia, industry and policymakers.  相似文献   
3.
党的十九届五中全会提出了到2035年人均GDP达到中等发达国家水平的远景目标,因此测算和回答能否和如何如期实现该目标,对于我国实现第二个百年奋斗目标和坚持“四个自信”具有重要的意义。为此,本文根据跨越和陷入“中等收入陷阱”经济体的发展经验,对2021—2035年我国潜在增长率变化进行了测算。一是参照跨越和陷入“中等收入陷阱”经济体在我国相同发展阶段时各主要生产要素的变化,模拟设定我国未来各主要生产要素的增长率;二是通过运用附加人力资本的增长核算模型测算基准、乐观和悲观三种不同情境下未来我国经济的潜在增长率,验证我国2035年发展目标实现的可能性;三是依据主要要素对潜在增长率的贡献度,提出我国如期实现2035年发展目标的相应政策建议。  相似文献   
4.
Machine learning (ML) methods are gaining popularity in the forecasting field, as they have shown strong empirical performance in the recent M4 and M5 competitions, as well as in several Kaggle competitions. However, understanding why and how these methods work well for forecasting is still at a very early stage, partly due to their complexity. In this paper, I present a framework for regression-based ML that provides researchers with a common language and abstraction to aid in their study. To demonstrate the utility of the framework, I show how it can be used to map and compare ML methods used in the M5 Uncertainty competition. I then describe how the framework can be used together with ablation testing to systematically study their performance. Lastly, I use the framework to provide an overview of the solution space in regression-based ML forecasting, identifying areas for further research.  相似文献   
5.
This paper investigates why the upsurge of top income shares has coincided with economic slowdowns in the US since the late 1970s. I argue that a fast-growing unearned income from ‘wealth residual’ – the unexplained increase in wealth that is not accompanied by any increase in real output – lies behind them. To support this hypothesis, I measure wealth residual from the national accounts and associated statistics, and then perform a set of panel regressions using a comprehensive panel dataset of the US at the state level. The estimation results demonstrate that the rapid growth of wealth residual during the last four decades has contributed to a co-evolution of fast-growing inequality and falling growth.  相似文献   
6.
This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.  相似文献   
7.
While the customer-to-manufacturer (C2M) business model has received increasing attention as a new business model for e-commerce and retail industry, little is still known about it and the effect of its approach. This study aims to understand how brand-related stimuli in C2M environments affect customer responses as the worldwide COVID-19 pandemic. The outcomes reveal that the Sensory, affective, and intellectual aspects of brand experience positively influence brand authenticity. Brand authenticity has a positive effect on behavioral intention, such as reuse intention and word-of-mouth. Additionally, this research finds that social presence moderates the association between the sensory aspect of brand experience. Thus, this study can suggest a C2M business model as a means of sustainable operation of the retail industry to both researchers and practitioners in relation to the retail industry.  相似文献   
8.
科学技术是第一生产力,科技投入无论是在推动经济增长还是促进社会发展方面,都有着举足轻重的重要作用。通过协整检验、格兰杰因果检验等方法,研究2006年-2020年西部地区财政科技支出对区域经济增长的作用。实证结果表明,西部地区的财政科技支出与经济增长之间存在着长期的均衡关系。因此,应进一步加大及合理安排政府财政科技资金的投入,加强资金监管,提高资金使用效率,更好地促进经济发展与社会进步。  相似文献   
9.
This work presents key insights on the model development strategies used in our cross-learning-based retail demand forecast framework. The proposed framework outperforms state-of-the-art univariate models in the time series forecasting literature. It has achieved 17th position in the accuracy track of the M5 forecasting competition, which is among the top 1% of solutions.  相似文献   
10.
Digital marketing communication, that is, communication through digital or electronic media among businesses and consumers, is growing rapidly, especially during the COVID-19 era. We propose a framework for analyzing digital marketing communication along four major dyads, business-to-consumer (B2C), business-to-business (B2B), consumer-to-consumer (C2C), and consumer-to-business (C2B). We review and summarize, for researchers and practitioners, the literature during 2000–2021 in these dyads along four major components: goals; channels, media, and platforms; content; and responses. We find that extant research in digital marketing communication pertains mostly to a specific, national level rather than a global level, despite the porousness of national boundaries for digital marketing. We derive important insights, identify key research gaps and questions in each of the dyads along these dimensions. We suggest approaches to address these research questions under three major components: substantive issues, data, and methods. These approaches can offer the insights that managers need to better formulate digital marketing strategies in local and global contexts.  相似文献   
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