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This study examines acquirers' earnings management in intragroup mergers to investigate whether stock-for-stock mergers between affiliated firms within the same family-controlled business group facilitate the controlling shareholder's rent seeking. Specifically, it investigates the acquiring firm's incentive to inflate premerger-announcement earnings in intragroup mergers given the controlling shareholder's relative equity holdings in the target and acquiring firms. The authors also examine how creditor monitoring affects premerger-announcement earnings in intragroup mergers compared to mergers between independent firms.

Using univariate analysis, panel regression based on accruals and cross-sectional regression based on discretionary accruals, the authors compare earnings management in mergers between affiliated firms with that in mergers between independent firms in the context of Korean business groups. The authors also compare the effects of creditors on earnings management in both cases.

Acquirers' premerger-announcement positive abnormal accruals are less evident in mergers between affiliated firms than in mergers between independent firms. These accruals decrease with high financial leverage only in the latter case, suggesting that creditor monitoring mitigates earnings management only in independent firm mergers.

The authors examine intragroup mergers, unlike previous studies, which focus on unaffiliated firm mergers. They also contribute to the literature on stock-for-stock mergers, showing that lender monitoring can mitigate the acquiring firm's premerger earnings management in unaffiliated firm mergers but not in intragroup mergers. These findings suggest that stock-for-stock mergers between affiliated firms may facilitate the controlling shareholders' rent seeking, which has policy implications for emerging markets with large family-controlled business groups.

The purpose of this paper is to investigate whether there is any difference across individual investors, domestic and foreign institutional investors in trading volume responses to analyst reports. The authors also examine the determinants of trading volume responses using firm as well as forecast characteristics.

The authors use trading data from the Korean equity market. The authors divide investors into three classes of investors; namely, individual investors, domestic institutional investors, and foreign institutional investors. The authors then examine whether the trading responses to analyst reports vary across investor types, and how firm characteristics and characteristics of analyst reports influence the trading activities on the release dates across investor types.

Individual investors are the most responsive investor group, being responsive to analyst reports on small, neglected firms with large inside ownership as well as to analyst reports with optimistic forecasts. Domestic institutional investors are responsive to reports on neglected firms with high return volatility while foreign institutional investors show least responses.

There are few studies that investigate whether the trading responses to analyst reports vary across investor types and how firm characteristics and characteristics of analyst reports influence the trading activities on the release dates across investor types. Taking advantage of the trading volume data for the three main investor types in the Korean stock market, the authors study the trading volume responses for each investor type and make comparisons across investor types.

Existing studies show that firms may have an incentive to use share repurchases opportunistically, thereby taking advantage of market participants’ confirmation bias that share repurchase is a signal of undervaluation. This study aims to investigate whether signaling costs and accounting transparency can serve as tools to identify opportunistic share repurchases.

The authors measure signaling costs by using two share repurchase methods (direct and indirect share repurchase) with different share repurchase costs, and measure accounting transparency using the history of earnings timeliness. The authors further measure long-term performance following share repurchases using operating performance and stock returns. Lastly, the authors compare the long-term performances between the groups defined by share repurchase method and earnings timeliness level.

The authors find that indirect share repurchase firms with a history of poor earnings timeliness experience unfavorable long-term performance, while other share repurchase firms do not. This finding reinforces the view that some share repurchases may be driven by managerial opportunism. In particular, when firms with a history of poor earnings-reporting behavior choose a low-cost repurchase method, their share repurchases may be motivated by managerial opportunism.

The findings suggest that past earnings timeliness and the signaling costs of a repurchase together are useful predictors of false signaling. Moreover, they suggest that investors can – at least in part – predict opportunistic share repurchases by using signaling costs and accounting transparency.

There is limited research on the behavior of different categories of space tourists as identified by different types of space tourism. To address this deficiency, the purpose of this study is to examine what factors make consumers participate in orbital and/or suborbital space tourism, along with three dimensions of motivation, constraint and artificial intelligence. To achieve this study’s goals, a comprehensive research model was developed that included three dimensions of intrinsic and extrinsic motivation, intrapersonal and interpersonal constraint and awareness of and trust in artificial intelligence, in comparing orbital and suborbital space tourism groups.

A questionnaire was carried out with respondents who wanted to participate in orbital (n = 332) and suborbital (n = 332) space tourism in the future. Partial least squares-structural equation modeling, fuzzy-set qualitative comparative analysis, multi-group analysis and deep learning were used to understand potential space tourist behavior.

Extrinsic motivation has the greatest positive impact on behavioral intention, followed by awareness of and trust in artificial intelligence, while intrapersonal constraint strongly negatively affects behavioral intention. Surprisingly, interpersonal constraint is insignificant by partial least squares-structural equation modeling but is still one of sufficient causal configurations by fuzzy-set qualitative comparative analysis. Interestingly, the two types of space tourism have very distinct characteristics.

This study created a comprehensive integrated research model with three dimensions of motivation, constraint and artificial intelligence, along with potential orbital and suborbital space tourist groups, to identify future consumer behavior. Importantly, this study used multi-analysis methods using four different approaches to better shed light on potential orbital and suborbital space tourists.

对不同类型太空旅游所识别的不同类别太空游客行为的研究有限。 为了解决这一缺陷, 这项工作研究了哪些因素使消费者参与轨道和/或亚轨道太空旅游, 以及动机、约束和人工智能三个维度。 为了实现研究目标, 在比较轨道和亚轨道太空旅游群体时, 开发了一个综合研究模型, 包括内在和外在动机、内在和人际约束以及对人工智能的认识和信任三个维度。

对希望在未来参与轨道 (n = 332) 和亚轨道 (n = 332) 太空旅游的受访者进行了问卷调查。 利用偏最小二乘法 (PLS)-结构方程模型 (SEM)、模糊集定性比较分析 (fsQCA)、多组分析和深度学习来了解潜在的太空游客行为。

外在动机对行为意图的积极影响最大, 其次是对人工智能的认识和信任, 而内在约束对行为意图有强烈的负面影响。 令人惊讶的是, 人际约束对于 PLS-SEM 来说是微不足道的, 但对于 fsQCA 来说仍然是充分的因果配置之一。 有趣的是, 这两类太空旅游具有非常鲜明的特点。

这项工作创建了一个全面的综合研究模型, 具有动机、约束和人工智能三个维度, 以及潜在的轨道和亚轨道太空旅游群体, 以确定未来的消费者行为。 重要的是, 这项研究采用了多种分析方法, 使用四种不同的方法来更好地揭示潜在的轨道和亚轨道太空游客。

existe una investigación limitada sobre el comportamiento de las diferentes categorías de turistas espaciales identificados por diferentes tipos de turismo espacial. Para abordar esta deficiencia, este trabajo examina qué factores hacen que los consumidores participen en el turismo espacial orbital y/o suborbital, junto con tres dimensiones de motivación, restricción e inteligencia artificial. Para lograr los objetivos del estudio, se desarrolló un modelo de investigación integral que incluía tres dimensiones de motivación intrínseca y extrínseca, restricción intrapersonal e interpersonal, y conocimiento y confianza en la inteligencia artificial, al comparar grupos de turismo espacial orbital y suborbital.

se realizó un cuestionario con los encuestados que querían participar en el turismo espacial orbital (n = 332) y suborbital (n = 332) en el futuro. Se utilizaron modelos de ecuaciones estructurales (SEM) de mínimos cuadrados parciales (PLS), análisis comparativo cualitativo de conjuntos borrosos (fsQCA), análisis multigrupo y aprendizaje profundo para comprender el comportamiento potencial del turista espacial.

la motivación extrínseca tiene el mayor impacto positivo en la intención de comportamiento, seguida de la conciencia y la confianza en la inteligencia artificial, mientras que la restricción intrapersonal afecta negativamente la intención de comportamiento. Sorprendentemente, la restricción interpersonal es insignificante por PLS-SEM, pero sigue siendo una de las configuraciones causales suficientes por fsQCA. Curiosamente, los dos tipos de turismo espacial tienen características muy distintas.

este trabajo creó un modelo de investigación integral integral con tres dimensiones de motivación, restricción e inteligencia artificial, junto con posibles grupos de turistas espaciales orbitales y suborbitales para identificar el comportamiento futuro del consumidor. Es importante destacar que este estudio empleó métodos de análisis múltiple utilizando cuatro enfoques diferentes para arrojar mejor luz sobre los posibles turistas espaciales orbitales y suborbitales.

Textual information about restaurants, such as online reviews and food categories, is essential for consumer purchase decisions. However, previous restaurant recommendation studies have failed to use textual information containing essential information for predicting consumer preferences effectively. This study aims to propose a novel restaurant recommendation model to effectively estimate the assessment behaviors of consumers for multiple restaurant attributes.

The authors collected 1,206,587 reviews from 25,369 consumers of 46,613 restaurants from Yelp.com. Using these data, the authors generated a consumer preference vector by combining consumer identity and online consumer reviews. Thereafter, the authors combined the restaurant identity and food categories to generate a restaurant information vector. Finally, the nonlinear interaction between the consumer preference and restaurant information vectors was learned by considering the restaurant attribute vector.

This study found that the proposed recommendation model exhibited excellent performance compared with state-of-the-art models, suggesting that combining various textual information on consumers and restaurants is a fundamental factor in determining consumer preference predictions.

To the best of the authors’ knowledge, this is the first study to develop a personalized restaurant recommendation model using textual information from real-world online restaurant platforms. This study also presents deep learning mechanisms that outperform the recommendation performance of state-of-the-art models. The results of this study can reduce the cost of exploring consumers and support effective purchasing decisions.

关于餐厅的文本信息, 如在线评论和食品分类, 对于消费者的购买决策产生至关重要。然而, 先前的餐厅推荐研究未能有效利这些文本信息去预测消费者喜好。本研究提出了一种新颖的餐厅推荐模型, 以有效估计消费者对多个餐厅属性的评估行为。

我们从 Yelp.com 收集了来自25,369名消费者对 46,613 家餐厅的 1,206,587 条评论。利用这些数据, 我们通过结合消费者身份和在线消费者评论生成了消费者偏好向量。然后, 我们结合了餐厅身份和食品分类来生成餐厅信息向量。最后, 考虑到餐厅属性向量, 本研究调查了消费者偏好和餐厅信息向量之间的非线性交互关系。

我们发现, 所提出的推荐模型相比于之前最先进的模型表现出更优秀的性能, 这表明结合消费者和餐厅的各种文本信息是预测消费者喜好的基本因素。

据我们所知, 这是第一项利用来自真实在线餐厅平台的文本信息开发个性化餐厅推荐模型的研究。本研究还提出了胜过最先进模型的深度学习机制。本研究的结果可以降低探索消费者行为的成本并支持有效的购买决策。

This paper aims to investigate travelers’ intentions to use ChatGPT and the influential factors affecting their decision-making.

Four studies were conducted to test three hypotheses. Four groups of respondents totaling 593 (Study 1), 337 (Study 2), 374 (Study 3) and 385 (Study 4) survey participants were used for data analyses.

Overall, the findings confirmed the impacts of technology usage experience and ChatGPT’s mistakes and provided additional information on travelers’ intentions to use ChatGPT. The four hypotheses were supported.

The findings can help researchers and industry to understand travelers’ intentions to use ChatGPT and their responses to its functions.

这项研究调查了旅行者使用ChatGPT的意图, 以及影响其决策的重要因素。

通过进行四项研究来验证三个假设。四组受访者总共593名（研究1）、337名（研究2）、374名（研究3）和385名（研究4）参与了数据分析。

总体而言, 研究结果证实了技术使用经验的影响、ChatGPT的错误并提供了有关旅行者使用ChatGPT意图的更多信息。四个假设均得到了支持。

研究结果可以帮助研究人员和业界了解旅行者使用ChatGPT的意图, 以及他们对其功能的反应。

Este trabajo investiga la intención de los viajeros en el uso de ChatGPT y su influencia en el proceso de decisión de viaje de los viajeros.

Se han desarrollado cuatro estudios para probar tres hipótesis. Cuatro grupos de participantes: 593 (Estudio 1), 337 (Estudio 2), 374 (Estudio 3), y 385 (Estudio 4) participantes respondieron la encuesta y sus respuestas utilizadas para el análisis de datos.

En resumen, los resultados confirman el impacto de la experiencia de uso de la tecnología, los errores de ChatGPT, proveyendo información adicional sobre la intención de uso de ChatGPT por los viajeros. Las cuatro hipótesis de investigación fueron aceptadas.

Los resultados pueden ser útiles para la academia y la industria sobre la comprensión en la intención de uso de ChatGPT, tanto por los viajeros, como sus respuestas sobre su función.

According to the conventional wisdom, trade is not a zero-sum game, but a positive-sum game. By allowing countries to focus on producing the goods that they can produce relatively efficiently, free trade is largely beneficial for everyone involved. Then, why are the world’s two largest economies (i.e. the USA and China) currently engaged in a trade war, which is likely to hurt their own economies? What is the driving force for the trade war between the two economic giants? The purpose of this paper is to offer an explanation of the underlying cause of the US–China trade war.

In an effort to make sense of the trade war between the USA and China, the paper draws the insights from the two international relations theories – i.e. hegemonic stability theory and power transition theory.

As China continues to threaten US hegemony in the world in general and East Asia in particular, the Sino–US competition for hegemony will intensify over time. As a result, the trade war between the two countries may persist longer than many anticipate. Further, even if the trade war between the two superpowers ends soon, a similar type of conflict is likely to occur later as long as the Sino–US hegemonic rivalry continues.

The central thesis of this paper is that “US fear” about its declining hegemony and China’s rapid rise as a challenger of US hegemony is driving a US-launched trade war with China. Since the underlying cause of the trade war between the world’s two largest economies is political (i.e. the Sino–US hegemonic rivalry) rather than economic (e.g. US attempts to improve the trade balance with China by imposing tariffs on Chinese goods), the paper contends that the full understanding of the trade war requires close attention to the importance of power competition between the two superpowers.

From 1953 to 1961, the South Korean economy grew slowly; the average per capita GNP growth was a mere percent, amounting to less than $100 in 1961. Few people, therefore, look for the sources of later dynamism in this period. As Kyung Cho Chung (1956:225) wrote in the mid‐1950s: “[South Korea] faces grave economic difficulties. The limitations imposed by the Japanese have been succeeded by the division of the country, the general destruction incurred by the Korean War, and the attendant dislocation of the population, which has further disorganized the economy” (see also McCune 1956:191–192). T.R. Fehrenbach (1963:37), in his widely read book on the Korean War, prognosticated: “By themselves, the two halves [of Korea] might possibly build a viable economy by the year 2000, certainly not sooner.”

The purpose of this paper is to examine the role of playfulness on innovative consumers’ pre-order behavior for new products.

Drawing upon self-congruity theory and early adoption literature, the effects of playfulness and innovativeness on pre-order behavior and the role of self-congruity are tested using four experimental studies that are analyzed using generalized linear model (GLM) and structural equation modeling.

Results indicate that playfulness amplifies the advance-purchasing propensity, especially when the pre-launch information cues come from a credible source.

This paper refines playfulness measurement scales and proposes how both enjoyment- and creativity-based playfulness amplify the purchase intention among innovative consumers. The results assist product managers in developing advanced marketing plans before a new product is launched.

Although Leader-Member Exchange (LMX) has been studied within the domain of organizational psychology, it has not received major attention from information systems literature and researchers. Drawing on LMX theory and the theory of reasoned interaction, this study investigates the roles of LMX, individual member's attitude toward system adoption, supervisor influence and goal commitment on mandatory system implementation. Specifically, our model investigates the moderating role of LMX and how it can be interpreted for an individual member's system adoption in an organization.

Partial least square (PLS) technique with the field survey of 148 participants was used for this analysis.

The empirical test results in the field setting show that attitude and supervisor influence positively affect goal commitment in the system implementation. Furthermore, LMX is a significant moderator between attitude and goal commitment within organizations, but this moderating effect is not valid in the relationship between supervisor influence and goal commitment since it is a more complex process influenced by variables other than supervisor influence.

The results showed that the model in this research has high explanatory and predictive power and is valuable in offering insights and guidance for implementers initiating technology-related changes within organizations.