The pricing of European airbnb listings during the pandemic: A difference-in-differences approach employing COVID-19 response strategies as a continuous treatment

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.     

The effect of place attachment of geographical indication agricultural products on repurchase intention

[Objective] This study aims to investigate how place attachment and the quality of experience affect consumers' intention to repurchase Geographical Indication (GI) agricultural products. [Methodology] Based on the special functional value and symbolic meaning of GI agricultural products, we constructed a five-dimensional model of place attachment for GI agricultural products consumers. Expanding on the original two-dimensional place attachment model, we introduced three connection concepts: nature, society, and emotion. We also combined this model with the quality of experience model and consumer purchase intention model to form a research model of repurchase intention for GI agricultural products. A questionnaire survey was used to collect data (n = 340), and a partial least squares structural equation model was used to test the empirical evidence. [Research results] (1) Place attachment to Geographical Indication agricultural products significantly affects the quality of experience. (2) Quality of experience significantly affects consumer trust and repurchase intention. (3) Consumer trust significantly affects repurchase intention. (4) There is a mediating effect of experience quality between place attachment and repurchase intention; there is a mediating effect of trust in the relationship between quality of experience and repurchase intention. (5) There is a chain mediating effect of “place attachment→quality of experience→consumer trust→repurchase intention” in the model.     

A “load-carrier” perspective approach for assessing tourism resource carrying capacity

To address the challenge of global tourism resources being overloaded or underutilization, there requires an adequate method for assessing the tourism resource carrying capacity (TRCC). However, the majority of previous evaluation perspectives on TRCC are limited by thresholds. This paper develops an innovative approach for assessing TRCC from the “load-carrier” perspective. TRCC is assessed by exploring the interaction between the carriers and loads of tourism resources. Chongqing city in China is employed as the case city to demonstrate the application of the established TRCC method. The conclusions are as follows: 1) This study elaborates the new connotation of TRCC from the perspective of “load-carrier”, and establishes the TRCC evaluation system based on the dynamic relationship between the carrier and load of tourism resources. 2) The proposed TRCC evaluation method is proved effective through an empirical study of Chongqing. 3) Chongqing's case unveils that the overload performance of TRCC can be dynamically monitored and predicted. By applying the TRCC evaluation methodology developed in this study, tourism managers and policymakers can identify whether it is the load or the carrier of tourism resources that affect the performance of TRCC, thereby taking targeted policy measures to eliminate potential risks of overload or underutilization.     

The impact of influencers' multi-SNS use on followers’ behavioral intentions: An integration of cue consistency theory and social identity theory

The considerable marketing potential brought by the rapid growth of social media has been extensively examined in the literature, particularly in terms of the impact of influencers' recommendations on their followers' decisions. However, little attention has been given to how the individual influencers' use of multiple social networking sites affects their followers' behavioral intentions. Hence, this academic gap warrants further exploration. Drawing on cue consistency theory, social identity theory, and stimulus-organism-response framework, this research proposes three research questions and constructs an integrated research model to explore how the influencers' cue consistency affects the social identification of their followers, subsequently influencing their behavioral intentions. A structural equation modeling technique is performed to analyze the data of 510 valid respondents. The findings show that influencers' consistent cues (i.e., information and image consistency) across social media have positive impacts on followers' cognitive and affective identification toward the influencers. Furthermore, the determinants for followers' purchase intention and electronic word-of-mouth intention are affirmed to serve as both cognitive and affective identification. Especially, the results indicate that the relationships between followers’ social identifications and behavioral intentions are moderated by the type of influencer (i.e., lifestyle vs. review). Accordingly, the results indicate how the use of multiple social networking sites by influencers impacts the behavioral intentions of their followers. The findings offer new insights into influencer marketing and provide important lessons for marketers.     

A decision support model for buying battery electric vehicles considering consumer learning and psychological behavior

Developments in battery electric vehicles (BEVs) have received more and more attentions in the last decades due to alleviating carbon emissions and energy crisis. Consequently, how to rank alternative BEVs to assist consumers make better purchasing decisions is a worthy research study. However, there are still some defects in the existing studies for ranking of BEVs: 1) the evaluation index system of BEVs is not comprehensive; 2) the determination of criteria weights cannot be well applied to the actual purchase scenarios; and 3) the psychological behavior of consumers is ignored. To address those shortcomings, this paper proposes a decision support model to assist with consumers to buy BEVs. First, a systematic evaluation criteria system of BEVs including quantitative and qualitative indicators from parameter configurations and online reviews is constructed. Then, a weight algorithm considering consumer learning is proposed to determine the criteria weights. Furthermore, a decision support process considering consumers' regret avoidance behavior is proposed. Finally, an actual BEV purchase case is given to illustrate the practicability of the decision support model. This can be seen in case studies the proposed support model can be well applied to consumers with different regret avoidance behaviours.     

The antecedents of digital collaboration through an enhanced digital platform for destination management: A micro-DMO perspective

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.     

数字经济时代会计变革及对策

随着数字经济时代的来临，以人工智能技术为代表的现代信息技术越来越多地应用到会计工作中，会计工作将进入数字会计时代，向共享会计、管理会计、智能会计发展。为了适应数字经济带来的变化，会计机构要成为企业的“数据中心”，发挥管理和服务职能。会计人员要积极学习现代信息技术和管理知识，实现由核算型向管理型转型。     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

科学与技术耦合效果评价——科技互补效应和成本效应分析

考虑到当前创新环境日益复杂化，科学与技术耦合系统已成为一个受系统内外因共同影响而发生演化的开放系统。在为耦合系统构建状态空间模型的基础上，通过求解该模型，刻画科学技术化强度和技术科学化强度，据此分析科学与技术互动产生的互补效应和成本效应，评价29个省份的科学与技术耦合效果，并测度地区科技发展所属耦合路径类型。研究表明，不同省份推进科学技术化进程和技术科学化进程的差异性显著；科学与技术耦合效果最佳并不能说明地区科技发展速度最快；绝大多数省份的科技耦合路径表现为科技中立路径，占比最小的路径为技术强势路径。基于不同省份的耦合情况差异，提出针对性建议。     

中国高端装备制造业自主技术创新效率稳定性及影响因素研究

在全面实施创新驱动发展战略的时代背景下，揭示中国高端装备制造业自主技术创新效率稳定性，测度相关因素的影响强度与方向，对揭示中国高端装备制造业自主技术创新规律，制定其发展策略具有重要指导意义。聚焦中国高端装备制造业自主技术创新效率稳定性及影响因素，采用DEA-Malmquist指数方法和Tobit回归模型进行实证研究，结果表明，中国高端装备制造业自主技术创新效率存在一定波动性，且各细分行业技术创新效率内部稳定性较差，产业自主技术创新效率整体稳定性不高；自主技术创新投入因素和环境影响因素对产业自主技术创新效率的影响具有较高的异质性，其中创新资金投入和人力资源投入对自主技术创新综合效率、纯技术效率及规模效率具有正向影响，而新产品开发投入和企业规模对自主技术创新综合效率、纯技术效率和规模效率的影响具有异质性，政策因素与市场因素分别具有显著和非显著负向影响，外源性创新因素具有显著正向影响，且影响强度较大。在此基础上，提出调整政府对高端装备制造业创新支持模式、加强外源性创新与智力引进等策略建议。