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Under the background of continuous sluggishness of the real economy and expansion of asset sectors, the Chinese economy exists a trend of “from the real to the virtual.” Managing the corporate financialization is the key to prevent the real economy “from real to virtual.” The paper explores the influence of family involvement on corporate financialization since family firms are an important proportion of real sectors.

Based on Socioemotional Wealth Theory, this paper makes empirical study using the data of Chinese A-share listed companies from 2008 to 2022 to explore the influence of family involvement on corporate financialization, mainly from the perspectives of family engagement, family identity of CEO and family control power.

These are the findings: (1) Family engagement will inhibit corporate financialization; (2) Compared with employing external managers, family members acting as CEOs will decrease corporate financialization; (3) The proportion of family ownership is negatively correlated with the level of corporate financialization.

The originality of this paper include these: (1) Analyzing the differences in the financialization of real enterprises with different characteristics and attributes; (2) Expanding the research on the internal motivation of the financialization of the real enterprises, and supplementing the research literature on family firms and corporate financialization; (3) Exploring the internal influence mechanism of financialization of family firms under the background of Chinese culture.

The worldwide imposition of lockdown measures to control the 2020 coronavirus disease 2019 (COVID-19) outbreak has shifted most executive communications with external stakeholders online, resulting in quick responses from stakeholders. This study aims to understand how presentational styles exhibited in online communication induce immediate audience responses and empirically test the effectiveness of reactive impression management tactics.

The authors analyze presentational styles using MP3 files containing executive utterances during earnings call conferences held by S&P 100-listed firms after June 2020, the quarter after the World Health Organization declared the COVID-19 outbreak a pandemic on March 11, 2020. Using timestamps, the authors link each utterance to a 1-minute interval change in the ask/bid prices of the stocks that occurs a minute after the corresponding utterance begins.

Exhibiting an informational presentation style in earnings calls leads to positive and immediate audience responses. Managers tend to increase their reliance on promotional presentation styles rather than on informational ones when quarterly earnings exceed market forecasts.

Drawing on organizational genre theory, this research identifies the discrepancy between the presentation styles that audiences positively respond to and those that managers tend to exhibit in earnings calls and provides a reactive impression management typology for immediate responses from online audiences.

Artificial intelligence (AI) offers many benefits to improve predictive marketing practice. It raises ethical concerns regarding customer prioritization, market share concentration and consumer manipulation. This paper explores these ethical concerns from a contemporary perspective, drawing on the experiences and perspectives of AI and predictive marketing professionals. This study aims to contribute to the field by providing a modern perspective on the ethical concerns of AI usage in predictive marketing, drawing on the experiences and perspectives of professionals in the area.

The study conducted semistructured interviews for 6 weeks with 14 participants experienced in AI-enabled systems for marketing, using purposive and snowball sampling techniques. Thematic analysis was used to explore themes emerging from the data.

Results reveal that using AI in marketing could lead to unintended consequences, such as perpetuating existing biases, violating customer privacy, limiting competition and manipulating consumer behavior.

The authors identify seven unique themes and benchmark them with Ashok’s model to provide a structured lens for interpreting the results. The framework presented by this research is unique and can be used to support ethical research spanning social, technological and economic aspects within the predictive marketing domain.

La Inteligencia Artificial (IA) ofrece muchos beneficios para mejorar la práctica del marketing predictivo. Sin embargo, plantea preocupaciones éticas relacionadas con la priorización de clientes, la concentración de cuota de mercado y la manipulación del consumidor. Este artículo explora estas preocupaciones éticas desde una perspectiva contemporánea, basándose en las experiencias y perspectivas de profesionales en IA y marketing predictivo. El estudio tiene como objetivo contribuir a la literatura de este ámbito al proporcionar una perspectiva moderna sobre las preocupaciones éticas del uso de la IA en el marketing predictivo, basándose en las experiencias y perspectivas de profesionales en el área.

Para realizar el estudio se realizaron entrevistas semiestructuradas durante seis semanas con 14 participantes con experiencia en sistemas habilitados para IA en marketing, utilizando técnicas de muestreo intencional y de bola de nieve. Se utilizó un análisis temático para explorar los temas que surgieron de los datos.

Los resultados revelan que el uso de la IA en marketing podría tener consecuencias no deseadas, como perpetuar sesgos existentes, violar la privacidad del cliente, limitar la competencia y manipular el comportamiento del consumidor.

El estudio identifica siete temas y los comparan con el modelo de Ashok para proporcionar una perspectiva estructurada para interpretar los resultados. El marco presentado por esta investigación es único y puede utilizarse para respaldar investigaciones éticas que abarquen aspectos sociales, tecnológicos y económicos dentro del ámbito del marketing predictivo.

人工智能（AI）为改进预测营销实践带来了诸多益处。然而, 这也引发了与客户优先级、市场份额集中和消费者操纵等伦理问题相关的观点。本文从当代角度深入探讨了这些伦理观点, 充分借鉴了人工智能和预测营销领域专业人士的经验和观点。旨在通过现代视角提供关于在预测营销中应用人工智能时所涉及的伦理观点, 为该领域做出有益贡献。

本研究采用了目的性和雪球抽样技术, 与14位在人工智能营销系统领域具有丰富经验的参与者进行为期六周的半结构化访谈。研究采用主题分析方法, 旨在深入挖掘数据中显现的主要主题。

研究结果表明, 在营销领域使用人工智能可能引发一系列意外后果, 包括但不限于加强现有偏见、侵犯客户隐私、限制竞争以及操纵消费者行为。

本研究通过明确定义七个独特的主题, 并采用阿肖克模型进行基准比较, 为读者提供了一个结构化的视角, 以解释研究结果。所提出的框架具有独特之处, 可有效支持在跨足社会、技术和经济领域的预测营销中展开的伦理研究。

The media is described as a fourth estate of the realm due to its ability to frame and shape discussions on governance and provide a stimulus for fighting corruption. But is the media really an effective tool for fighting corruption? This question arises due to the possibility of the media being used for propaganda, biased reporting and media owners’ and journalists’ engagement in corruption. The current study addresses the question by exploring the relationship between the media and corruption from the perspectives of Ghanaian justice and anti-corruption officials.

The study adopts a qualitative approach by interviewing justice and anti-corruption officials across three administrative regions in Ghana.

The results show that while justice officials describe the media as a medium for accusing officials unjustifiably and exaggerating the scale of corruption, anti-corruption officials believe the media helps to fight corruption. In addition to uncovering and exposing public officials’ corruption, the media is also a double-edged sword characterised by intra-vigilance: the media hold “their own” (i.e. journalists fighting corruption) accountable through criticism and exposure of wrongdoings.

The double-edged nature of the media can strengthen and enhance the fight against corruption because anti-corruption actors and journalists will be cautious as misjudgements or errors committed will not be overlooked or concealed by the media. Therefore, anti-corruption agencies in Ghana can collaborate with the media to uncover and expose corruption committed by public officials and even journalists or media owners.

This study is the first in Ghana to explore the relationship between the media and corruption from the perspectives of justice and anti-corruption officials. The approach, frameworks and methodology adopted in this study can be applied in similar studies in other countries on the African continent and beyond.

The authors’ goal is to investigate variations in the writing style of book reviews published on different social reading platforms and referring to books of different genres, which enables acquiring insights into communication strategies adopted by readers to share their reading experiences.

The authors propose a corpus-based study focused on the analysis of A Good Review, a novel corpus of online book reviews written in Italian, posted on Amazon and Goodreads, and covering six literary fiction genres. The authors rely on stylometric analysis to explore the linguistic properties and lexicon of reviews and the authors conducted automatic classification experiments using multiple approaches and feature configurations to predict either the review's platform or the literary genre.

The analysis of user-generated reviews demonstrates that language is a quite variable dimension across reading platforms, but not as much across book genres. The classification experiments revealed that features modelling the syntactic structure of the sentence are reliable proxies for discerning Amazon and Goodreads reviews, whereas lexical information showed a higher predictive role for automatically discriminating the genre.

The high availability of cultural products makes information services necessary to help users navigate these resources and acquire information from unstructured data. This study contributes to a better understanding of the linguistic characteristics of user-generated book reviews, which can support the development of linguistically-informed recommendation services. Additionally, the authors release a novel corpus of online book reviews meant to support the reproducibility and advancements of the research.

This paper aims to deepen the current knowledge of seasonality by investigating visitors’ intentional and behavioural patterns during peak and off-peak seasons. It compares the variation in several key behavioural factors, namely, duration of stay, party size, revisit intention, spending and breakdown of spending in different sectors in hospitality and tourism including entertainment, restaurant, accommodation and transportation. Moreover, this research expands the understanding by examining the effectiveness of two innovative strategies of offering a digital app and organising a unique event to tackle seasonal imbalances through stimulating visitors’ intention to change their timing of visit from peak to off-peak periods.

The author initially used a Delphi approach to gather experts’ opinion on the two scenario settings: event organisation and a trip planner app. The scenarios aimed to potentially encourage visitors to change their visit time to off-peak seasons. Then, using a quantitative survey, the travel habits and spending behaviours of 310 participants were captured. Furthermore, the survey assessed their intention to travel during off-peak seasons in response to the implementation of the two innovative strategies.

The results revealed that although the number of visitors who travel in off-peak seasons may be lower, their daily spending is higher than peak season visitors. In addition to total spending per day, the duration of stay, part size, quality of accommodation and re-visit intention of visitors indicated significant variation between peak and off-peak seasons. According to the statistical analysis’ results, organising events (including festivals) proves more effective in encouraging visitors to travel during off-peak seasons compared to digital innovation (i.e. a trip planner app). This finding is in line with the tenets of the Jobs-to-be-Done Theory of innovation.

This study contributes by conceptualising the mechanism of seasonality and its impacts on subsectors of tourism and hospitality. To the best of the author’s knowledge, this is one of the few empirical research that compares the behavioural patterns of visitors including their average spending per day between peak and off-peak seasons. Previous studies focused on specific regions or sectors, whereas this research investigates visitors’ behaviour on a broader scale to provide more comprehensive view. Furthermore, this study is novel due to practising an outside-in approach through investigating the effectiveness of the two innovative strategies aimed at addressing seasonality in the hospitality and tourism industry from visitors’ point of view.

Social media networks make their services freely available to all users. Users pay for the service received with the time and attention taken by the advertisements. This chapter argues that social media platforms are a unique form of monopoly driven by “the more the merrier” effect (i.e., network effects) in users' consumption. These monopolies exercise market power, not by charging higher prices to users but by “tying” larger amounts of advertising to their content. Traditional antitrust instruments designed to address excessive pricing and reduced output by monopolies need to be reframed to tame the attention economy problems in the social media industry. This chapter discusses five antitrust instruments grouped in three categories: structural, behavioral, and market-based remedies. Market-based solutions are the least explored in the literature, despite being the most promising instruments to lower the attention costs imposed on users, while preserving the economies of scope in production and the network effects in consumption, and possibly maintaining free access to social media, as we know it today.

Transitions to and within university studies can be associated with heightened distress in students. This study focusses on the less studied transition from a bachelor’s to a master’s degree. During a master’s degree, study requirements and autonomy increase compared to bachelor’s studies. The present study examines how students’ experiences of study-related burnout, their approaches to learning and their experiences of the teaching and learning environment (TLE) change during this transition. Moreover, the study examines how approaches to learning and the TLE can affect study-related burnout.

Questionnaire data were collected from 335 university students across two timepoints (bachelor’s degree graduation and the second term of their master’s degree).

The results show that students’ overall experience of study-related burnout increases, as does their unreflective learning, characterised by struggling with a fragmented knowledge base. Interestingly, students’ experiences of the TLE seem to have an effect on study-related burnout in both master’s and bachelor’s degree programmes, irrespective of learning approaches. These effects are also dependent on the degree of context.

The study implies that students’ experiences of study-related burnout could be mitigated by developing TLE factors during both bachelor’s and master’s degree programmes. Practical implications are considered for degree programme development, higher education learning environments and student support.

The purpose of this paper is to develop a conceptual framework that examines the impacts of changing seasons on tourism.

The paper presents a conceptual process model of the impact of seasons on all aspects of in-destination tourist behaviour. The model is developed from the literature and is then tested using Cairns, Australia as a case study.

Seasons influence the actual and perceived range of products/experiences available, which dictate the pull features of a destination, that in turn, influence who comes and why they come. Combined the activity sets and visitor profile define in-destination behaviour and, ultimately, satisfaction.

The study fills a needed research gap in two ways. Firstly, it explains conceptually and then tests empirically how changes in seasons affect the delivery of tourism products and experiences. Secondly, it adds significantly to our understanding of the factors that influence in-destination behaviour.

Managerial implications for destination management organisations are identified.

This paper presents a new conceptual process model for a previously unexamined issue.

本文提出了一个季节影响目的地游客行为的过程的理论模型。该模型基于文献开发而成, 然后以澳大利亚凯恩斯作为案例进行测试。

本文的目的是开发一个研究季节变化影响旅游的理论框架。

研究发现季节会影响实际和感知的产品或体验的范围, 从而决定一个目的地的吸引力特征。他们反过来可以影响谁来旅游以及他们来旅游的原因。 结合活动和旅游者画像来定义其目的地行为。

这项研究从两个方面填补了理论空白。 首先, 它从概念上解释, 然后实证检验了季节的变化如何影响旅游产品和体验的供应。 其次, 它极大地增强了我们对影响目的地行为的因素的理解。

本文指出了对目的地管理的实践意义。

本文针对先前未经考察的问题提出了一种新的理论过程模型。

El artículo presenta un modelo de proceso conceptual del impacto de las estaciones en todos los aspectos del comportamiento en en destino turístico. El modelo se desarrolla a partir de la literatura y luego se pone a prueba usando Cairns, Australia como estudio de caso.

El propósito de este artículo es desarrollar un marco conceptual que examine los impactos de los cambios de estación en el turismo.

Las estaciones influyen en la gama, real y percibida, de productos/experiencias disponibles que condicionan las características de atracción de un destino. Las estaciones, a su vez, influyen en quién viene y por qué viene. Los conjuntos de actividades combinadas y el perfil del visitante definen el comportamiento en el destino.

El estudio llena un vacío de investigación necesario de dos maneras. Primero, explica conceptualmente y luego demuestra empíricamente cómo los cambios en las estaciones afectan la oferta de productos y experiencias turísticas. En segundo lugar, contribuye significativamente a la comprensión de los factores que influyen en el comportamiento en el destino.

Se identifican las implicaciones de gestión para las organizaciones de gestión de destinos.

Este artículo presenta un nuevo modelo de proceso conceptual para un tema no examinado previamente.

This study explores how institutional and cultural factors influence political trust among hotel employees and its impact on support for local government actions, with implications for hotel leadership and regulatory compliance.

Employing a quantitative approach and structural equation modeling (SEM-PLS), the study integrates institutional and cultural theories of trust. Data were collected from 444 frontline hotel employees via mTurk in May 2021.

The research reveals insights into the significant role of institutional and cultural factors in shaping political trust among hotel employees. Moreover, it demonstrates a positive correlation between political trust and support for local government actions.

This research has limitations to acknowledge. The sample size may restrict generalizability, and data from May 2021 might not capture long-term trends. Furthermore, relying solely on quantitative data may overlook individual nuances and complexities.

Hotel leadership can leverage these findings to prioritize building political trust among employees, leading to better support for government actions and regulatory compliance.

Fostering trust between hotel employees and governing bodies can foster more effective collaboration, benefiting the hotel industry and the broader community.

This research contributes to the existing body of knowledge by presenting a novel conceptual model that integrates institutional theory and cultural theory of trust to examine the formation of political trust in the context of hotel employees. The application of this model to the hospitality industry adds to the limited research available in this area.