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Over the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.

First, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).

The results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.

The findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.

To the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.

The purpose of this study is to identify segments in the Gen Z population (born between 1996 and 2010) in Europe, the USA and Australia, based on brand- and lifestyle-related variables and perceptions about their online activities. This study explores how these segments differ and provide insights into cross-country similarities and differences.

An online survey was conducted with 4,304 participants, and cluster analysis and analysis of variance were used to identify and profile Gen Z segments in each of three geographical areas.

Five segments in Europe and four segments in the USA and in Australia were identified. Segments differ in terms of the importance they attach to exclusivity, inclusivity and sustainability of brands, how Gen Z members perceive money issues and stand in life and how they perceive their online activities. Similar segments are found in the three geographical areas.

This study proposes a conceptual and analytical approach for exploring intra-cohort diversity. Future research can apply this approach to different generational cohorts and use it to study intra-cohort diversity in other parts of the world.

This study provides input for marketing practitioners to create better focused and more effective campaigns.

Cross-country generational cohort research is scarce, and especially intra-cohort diversity is under-researched. This study offers a deep and fine-grained insight into the diversity of the Gen Z cohort across three geographical areas, based on representative samples in these areas.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

In this study, we drew on the theories of social exchange and social learning and hypothesized that the online social capital (SC) and offline SC of social networking affect the online self-disclosure (OSD) of individuals through social self-efficacy (SSE).

After retrieving 514 valid questionnaires, we used structural equation modeling to analyze the data.

The results indicated that the users’ SSE affected their OSD, and that both online and offline bridging and bonding SC increased their SSE. However, online bonding SC directly affected their OSD, whereas online bridging SC did not considerably affect their OSD. Given these findings, we presented both theoretical and practical implications to elucidate SSE and OSD behavior from the perspective of online and offline bridging and bonding SC.

In this study, we drew on theories of social exchange and social learning to examine the effects of online and offline bridging and bonding SC on users’ SSE and OSD on SNSs. Given the importance of SC and SSE in social relationships and the effects of OSD on SNSs, our goal was to provide SNS marketers with a thorough understanding of how to facilitate SSE and OSD from the perspective of online and offline bridging and bonding SC.

The integration of social media and e-commerce has resulted in a rising phenomenon among individual content providers (ICPs), who used to offer free content, to provide consumers with paid content, such as online courses, Q&As or consultations. Despite the prevalence of ICPs’ content monetization, empirical research has rarely studied its underlying mechanism. This paper examines how the characteristics of free content contributed by ICPs on social media platforms influence their paid content sales, focusing on the perspective of human brand.

The empirical setting is an online knowledge exchange platform, where users are allowed to provide free content (e.g. answers) on the social media platform and launch paid content (e.g. lectures) on the e-commerce platform. A machine learning technique is employed to construct measures for the characteristics of free content, and fixed-effects estimation is presented to confirm which factors have a significant influence on the sales of paid content.

The empirical results show that the quality, diversity and expertness of free content have a significant positive impact on the sales of the ICP-paid content, with the brand popularity of ICP playing a mediating role.

This study is the first attempt to demystify the relationship between content contribution and ICPs’ content monetization from the perspective of human brand. The findings validate the effectiveness of the “Selling by Contribution” strategy and provide valuable insights for ICPs and social media platforms.

This study aims to investigate the corrosion inhibitor effect of migrating corrosion inhibitor (MCI) on Q235 steel in high alkaline environment under cathodic polarization.

This study investigated the electrochemical characteristics of Q235 steel with and without MCI by polarization curve and electrochemical impedance spectroscopy. Besides, the surface composition of Q235 steel under different environments was analyzed by X-ray photoelectron spectroscopy. In addition, the migration characteristic of MCI and the adsorption behavior of MCI under cathodic polarization were studied using Raman spectroscopy.

Diethanolamine (DEA) and N, N-dimethylethanolamine (DMEA) can inhibit the increase of Fe(II) in the oxide film of Q235 steel under cathodic polarization. The adsorption stability of DMEA film was higher under cathodic polarization potential, showing a higher corrosion inhibition ability. The corrosion inhibition mechanism of DEA and DMEA under cathodic polarization potential was proposed.

The MCI has a broad application prospect in the repair of damaged reinforced concrete due to its unique migratory characteristics. The interaction between MCIs, rebar and concrete with different compositions has been studied, but the passivation behavior of the steel interface in the presence of both the migrating electric field and corrosion inhibitors has been neglected. And it was investigated in this paper.

This study aims to introduce and evaluate a model of host community support for sustainable tourism development (SSTD) based on the influential factors contributing to community support in a biosphere reserve.

Partial least squares structural equation modeling using SmartPLS 3 software is applied to analyze data collected from 473 residents of the Miankaleh Biosphere Reserve, Iran.

The findings reveal that the locals’ community support is affected by their level of environmental awareness, opportunity and attitudes toward SSTD. However, the results do not reveal an influence of environmental knowledge and community attachment on SSTD. The findings enrich the existing literature on community attitude predictors by showing that locals’ SSTD level is not consistently based on common predictors. Such support strongly depends on host communities’ attitudes toward supporting tourism, which is definitely not the same among residents. It is imperative to know whether people’s attitudes arise from a desire to protect the area or for reasons of self-interest.

The findings provide further support for the tenets of the segmentation approach and challenge existing knowledge on host communities’ attitudes about factors influencing residents toward SSTD. The findings have several practical implications regarding community participation for regional and national authorities and destination policymakers.

采用SmartPLS3软件建立偏最小二乘结构方程模型, 对从伊朗米安卡莱生物圈保护区的473名居民获得的数据进行分析。

本研究旨在介绍和评估基于影响促进生物圈保护内社区支持的可持续旅游发展(SSTD)的东道社区支持模型。

结果表明, 本地社区的环境意识水平、机会和对SSTD的态度影响着社区支持。然而, 研究结果并没有揭示环境知识和社区依恋对SSTD的影响。

这一发现丰富了现有的关于社区态度预测因子的文献, 表明当地人的SSTD并不一致基于共同的预测因子。这种支持很大程度上取决于东道社区对支持旅游的态度, 这在居民中肯定是不一样的。有必要了解人们的态度是出于保护该地区的愿望还是出于自身利益的原因。此外, 研究结果为细分方法的原则提供了进一步的支持, 并挑战了关于东道社区对影响居民SSTD态度的现有认知。

Se aplica un modelo de ecuaciones estructurales por mínimos cuadrados parciales con el programa SmartPLS 3 para analizar los datos recogidos de 473 residentes de la reserva de la biosfera de Miankaleh (Irán).

Esta investigación pretende introducir y evaluar un modelo de apoyo de la comunidad anfitriona al desarrollo del turismo sostenible (SSTD) basado en los factores que contribuyen al apoyo de la comunidad en una reserva de la biosfera.

Los resultados revelan que el apoyo de la comunidad local se ve afectado por su nivel de concienciación medioambiental, sus oportunidades y sus actitudes hacia el desarrollo del turismo sostenible. Sin embargo, los resultados no muestran una influencia del conocimiento medioambiental y el apego de la comunidad sobre el desarrollo turístico sostenible.

Los resultados enriquecen la literatura existente sobre predictores de la actitud de la comunidad al mostrar que el nivel de desarrollo turístico sostenible de los autóctonos no se basa únicamente en factores tradicionales. Dicho apoyo depende en gran medida de las actitudes de las comunidades anfitrionas hacia el apoyo al turismo y éste no es el mismo entre los residentes. Es necesario conocer si la actitud de los individuos surge de un deseo de proteger la zona o por razones de interés propio. Además, los resultados corroboran los principios del enfoque de segmentación y retan los conocimientos existentes sobre las actitudes de las comunidades anfitrionas acerca de los factores de los residentes sobre el desarrollo turístico sostenible.