Institutional dynamics and access to non-farm employment in rural China, 1950–1996

This article examines non-farm employment in the context of Chinese rural institutional change, based on evidence from discrete-time logistic models for event history analysis using the Life History and Social Change survey. We find the transition to non-farm sector rose rapidly during the Great Leap Forward and market reform, while the Cultural Revolution saw it reach the lowest ebb. While male advantage prevailed exclusively during the Cultural Revolution and early marketization, education possessed a stable positive effect in all historical periods. Although the returns to different kinds of political capital vary along with institutional dynamics, intergenerational reproduction was greatly reduced after the Cultural Revolution.     

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.     

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.     

Becoming a tree when I will be dead? Why not! Generation X,Y and Z,and innovative green death practices

Within the theoretical field of ethical consumption, the study focuses on consumer behavior and innovative green death practices. While scarcely investigated in the marketing and consumer behavior research domains, at least four main reasons spur to consider the funeral industry as an interesting subject of enquiry: i) the sector boasts of a significant economic relevance; ii) it is extremely impactful from an environmental and social point of view; iii) it is witnessing interesting innovative processes in the direction of social and environmental sustainability; iv) consumer movements are rising all over the world asking for more sustainable death practices. Thus, adopting an augmented version of the theory of planned behavior (TPB), which includes individuals’ environmentally responsible consumption, and egoistic and altruistic environmental concern, the study investigates behavioral intention to adopt innovative green death practices (a green funeral) of people belonging to three different generations: X, Y, and Z. A purposive sample of 627 Italian people participated in an online the survey. Collected data were analyzed adopting an ordinal logit model. The results confirm the TPB predictive power also in the field of green funeral behavioral intention. Furthermore, environmentally responsible consumption and environmental concern – even though only in its altruistic component – positively influence behavioral intention, and generation exerts a moderating effect among the examined constructs. Overall, the research attempts to enrich the literature on ethical consumption by exploring the underinvestigated phenomenon of buying behavior of unsought and end-of-life products, that of green funerals, and provide managerial recommendations to funeral service sellers.     

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.     

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。     

实现2035年发展目标的潜在增长率*

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。