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This study aims to investigate the key determinants predicting users’ behavioural intention (BI) in adopting mobile payment (m-payment) in the new normal era.

The mobile technology acceptance model (MTAM) was extended through attitudes, perceived trust, perceived risk and personal innovativeness (PI) with government support (GS) functioning as a moderator. A total of 245 valid responses were gathered from Malaysian m-payment users with purposive sampling and subsequently evaluated through partial least square-structural equation modelling.

Mobile usefulness and PI significantly predicted user BI to use m-payment. Based on the moderation analysis, GS strengthened attitude-based impacts on BI towards m-payment adoption.

The empirical outcomes provide stakeholders with pivotal implications to develop holistic policies and strategies that potentially catalyse m-payment usage in the new normal era.

This research expands the current body of knowledge by assessing the factors impacting m-payment usage intention in the new normal era. The four aforementioned MTAM elements and GS (moderator) were recommended to boost model workability and offer novel evidence from a distinct viewpoint.

El objetivo de este estudio es investigar los determinantes clave que predicen la intención de comportamiento de los usuarios a la hora de adoptar el pago por móvil (m-payment) en la nueva era normal.

El modelo de aceptación de la tecnología móvil (MTAM) se amplió a través de las actitudes, la confianza percibida, el riesgo percibido y la capacidad de innovación personal, con el apoyo gubernamental como moderador. Se recogió un total de 245 respuestas válidas de usuarios malasios de pago por móvil mediante muestreo intencionado y se evaluó posteriormente mediante modelización de ecuaciones estructurales por mínimos cuadrados parciales (PLS-SEM).

La utilidad del móvil y la capacidad de innovación personal predijeron significativamente la intención de los usuarios de utilizar el pago por móvil. Según el análisis de moderación, el apoyo gubernamental reforzó los efectos basados en la actitud sobre la intención conductual de adoptar el pago por móvil.

Los resultados empíricos proporcionan a las partes interesadas implicaciones fundamentales para desarrollar políticas y estrategias holísticas que catalicen potencialmente el uso del pago móvil en la nueva era de la normalidad.

Esta investigación amplía el corpus actual de conocimientos al evaluar los factores que influyen en la intención de uso del pago por móvil en la nueva era normal. Se recomiendan los cuatro elementos MTAM mencionados y el apoyo gubernamental (moderador) para impulsar la viabilidad del modelo y ofrecer pruebas novedosas desde un punto de vista distinto.

本研究旨在探讨新常态时代用户使用移动支付（m-payment）行为意向的主要决定因素。

通过态度、感知信任、感知风险和个人创新能力, 并以政府支持作为调节因素, 对移动技术接受模型（MTAM）进行了扩展。通过有目的的抽样, 从马来西亚移动支付用户中收集了 245 份有效回复, 随后通过偏最小二乘法结构方程模型（PLS-SEM）进行了评估。

移动实用性和个人创新性可显著预测用户使用移动支付的行为意向。根据调节分析, 政府支持加强了态度对采用移动支付的行为意向的影响。

实证研究的结果为利益相关者提供了重要的启示, 有助于他们制定全面的政策和战略, 在新常态时代促进移动支付的使用。

本研究通过评估新常态时代影响移动支付使用意向的因素, 拓展了现有的知识体系。研究推荐了上述四个 MTAM 要素和政府支持（调节器）, 以提高模型的可操作性, 并从一个独特的视角提供了新的证据。

The present research aims to examine a range of momentum trading strategies for the tourism and hospitality sector.

The paper followed the methodology of Jegadeesh and Titman (1993) to construct the portfolios. In this methodology, all portfolios were formed and evaluated by their cumulative stock returns over the past J periods and holding the position for the next K periods. In total, nine formation and holding periods were used, represented by 3, 6 and 12. For example, strategy 3–3 (that is, strategy with J = 3 and K = 3) refers to the strategy that stocks are ranked based on their previous three months and then held for the next three months.

The findings demonstrated that none of these momentum investing strategies was profitable. Most of the results, however, show positive, but insignificant momentum returns. This finding can be interpreted as price reversal over a horizon of three to twelve months in the US hospitality and tourism sector. These results are robust to size, different formation and holding combinations, beta and turnover.

Regarding the research limitations, this paper only considers the US tourism and hospitality sector. Therefore, the extension of results to other developed and developing markets should be taken carefully. Also, this paper relies only on the methodology of Jegadeesh and Titman (1993). Other methodologies could be suitable avenues for future research.

Investors and portfolio managers who seek for earning abnormal returns by investing in the US HT stocks can attain their hopes by constructing portfolios based on existing guidelines in the literature and adopting a short-term reversal trading strategy or by buying past losers and selling past winners of the US tourism and hospitality stocks.

This research contributes to the hospitality finance literature by offering the investors who are interested in the US hospitality and tourism sector an uncomplicated trading rule that uses real return data and is expected to generate actual returns. Moreover, the momentum strategy of Jegadeesh and Titman (1993) is never used in the hospitality finance literature.

本研究旨在探討各種可應用於旅遊及酒店業的動量交易策略。

本文按照 Jegadeesh 和 Titman（1993）的研究方法來建造投資組合。使用這研究方法時，所有投資組合均以它們在過去J 時期的累積股票收益和在未來K 時期的持倉來建立及評價的。九個組成方式及持有期被使用，以3、6、12來表示。例如，策略3-3（那就是說，該策略以J = 3和 K = 3）指的策略是以有關的股票基於過去三個月而被分等級，繼而在未來三個月被持有。

研究結果顯示，這些投資策略全沒帶來利潤；唯大部分結果顯示正動能策略報酬，雖報酬是微不足道的。這研究結果或許可理解為在美國酒店及旅遊業為期三至十二個月的價格逆轉。這些結果就規模、不同組成方式和持有組合、beta 和成交量而言是強而有力的。

就研究的局限而言，本文只是考慮美國的酒店及旅遊業；因此，如把研究結果伸延至其它已開發或發展中的市場，則需小心處理。另外，本文只依賴 Jegadeesh 和 Titman（1993）的研究方法，就此，使用其它研究方法會是日後相關研究的適當途徑。

欲透過投資於美國酒店及旅遊股票而尋求賺取異常收益的投資者和投資組合經理可如願以償，方法是基於文獻內現存的準則建造投資組合，以及採用短期的逆轉交易策略，或買入美國酒店及旅遊業過去輸家及賣出過去贏家。

本研究為酒店金融文獻作出貢獻，因研究為對美國酒店及旅遊業有興趣的投資者提供了使用實際收益數據及預期可創造實際回報的簡單交易規則；而且， Jegadeesh 和 Titman（1993）的動量策略從未在酒店金融文獻內被使用過。

The purpose of this paper is to address the opposing views of the relationship between directors’ and officers’ liability insurance (D&O insurance) and stock price crash risk in a major Asian emerging stock market.

This paper finds an endogenous relationship between D&O insurance and stock price crash risk. Hence, the two-stage least squares regression analysis is used to address the endogeneity issue when the relationship is examined. Moreover, this paper further controls the quality of other corporate governance mechanisms to investigate whether D&O insurance still has an effect on stock price crash risk.

The effect of D&O insurance coverage is significantly negatively related to firm-specific stock price crash risk in Taiwan. More importantly, even when the quality of other corporate governance mechanisms is controlled, the negative relationship between D&O insurance coverage and firm-specific stock price crash risk remains significant. The evidence supports that D&O insurance serves as an effective external monitoring mechanism, strengthens corporate governance, and thus reduces stock price crash risk.

Emerging Asian markets suffer a dearth of research on the relationship of D&O insurance coverage and the firm-specific stock price crash risk. Investigating the relationship in Taiwan, the present study fills the research void. The findings show that D&O insurance plays an important role in reducing stock price crash risk of Taiwanese firms even when other corporate governance mechanisms are in place.

The purpose of this paper is to develop a proof-of-concept (POC) Forward Collision Warning (FWC) system for the motorcyclist, which determines a potential clash based on time-to-collision and trajectory of both the detected and ego vehicle (motorcycle).

This comes in three approaches. First, time-to-collision value is to be calculated based on low-cost camera video input. Second, the trajectory of the detected vehicle is predicted based on video data in the 2 D pixel coordinate. Third, the trajectory of the ego vehicle is predicted via the lean direction of the motorcycle from a low-cost inertial measurement unit sensor.

This encompasses a comprehensive Advanced FWC system which is an amalgamation of the three approaches mentioned above. First, to predict time-to-collision, nested Kalman filter and vehicle detection is used to convert image pixel matrix to relative distance, velocity and time-to-collision data. Next, for trajectory prediction of detected vehicles, a few algorithms were compared, and it was found that long short-term memory performs the best on the data set. The last finding is that to determine the leaning direction of the ego vehicle, it is better to use lean angle measurement compared to riding pattern classification.

The value of this paper is that it provides a POC FWC system that considers time-to-collision and trajectory of both detected and ego vehicle (motorcycle).

The Incheon Region has numerous assets that fall within a Pentaport model.' These include the Incheon International Airport, the Port of Incheon, a coastal industrial park, free economic zones, a leisure port, and Songdo new town designed to be the future Silicon Valley of Korea. This paper looks at how Northeast Asia trade flows between China and Korea might be enhanced by application of the Pentaport model in making the Incheon region a North East Asian Hub. It looks also at their trade and logistics systems as well as their water borne commerce. It proposes an integrated transportation system for the Yellow Sea Region being beneficial to the economies of the Northeast Asia. It also stresses that innovative technologies for ships, terminals and cargo handling systems should be introduced to develop a competitive short sea shipping system in the region and cooperation among the regional countries will be essential to achieve the final goal. The potential of methods of container shipping is discussed as it might apply to short sea shipping in the Yellow Sea Region that could greatly facilitate Incheon's situation with respect to the broader region in application of the Pentaport model.

Digital transformation is a foundational change in how firms operate and deliver value to customers by using digital technologies to create new business opportunities. The purpose of this study is to offer a conceptual framework by reorganizing the elements of digital transformation, including resources, technology, capabilities and performance, into a workable process and investigating how firms integrate these resources, build new capabilities and transform them into enhanced performance.

This framework builds three blocks: resource integration, organizational capabilities and outcomes, exploring the impact of resource integration on outcomes through organizational capabilities. For resource integration, this study adopts a resource-based view (RBV) and service-dominant logic (SDL) to integrate organizational resources, including information technology (IT)-based resources, which play a role in moderating the effect of resource integration. Moreover, the author argues that firms’ capabilities have two levels: higher-order capabilities and lower-order capabilities, which will convert these resources through the capabilities into organizational performance.

This framework is built to understand the process of digital transformation and its antecedents for firms’ performance in business environments. Drawing on RBV, it provides a more holistic perspective that has been linked to resource integration, organizational capabilities and outcomes at the firm level. In this way, the theoretical basis for diminishing implicitness associated with the current perspective of digital transformation can be strengthened.

This paper offers a coherent discussion of digital transformation and explains the process of digital transformation, thus advancing prior work. The major contribution is connecting the process of digital transformation through which firms integrate resources, i.e. digital technologies and valuable, rare, inimitable and nonsubstitutable (VRIN) and nonVRIN resources as well, to build organizational dynamic capabilities based on RBV and SDL.

Amidst growing concerns about environmental sustainability, brands face the challenge of upholding authenticity in their green marketing efforts. While existing research primarily focuses on understanding and preventing greenwashing, there is a critical need to explore its consequences and mitigation strategies. This study aims to investigate the effects of greenwashing across varying levels of severity on consumer forgiveness and brand attitude, with growth beliefs and apology sincerity serving as moderators.

This study conducted a between-subjects online experiment in two phases: Phase 1 examined the effects of greenwashing severity on brand attitude, mediated by consumer forgiveness and moderated by their growth beliefs, whereas Phase 2 tested the moderating role of apology sincerity.

This study identifies different types of greenwashing and reveals that higher perceived severity of active greenwashing worsens brand attitude through reduced consumer forgiveness. However, consumers with stronger growth beliefs show greater forgiveness, moderating the negative impact of greenwashing severity. Crucially, a sincere apology effectively mitigates the detrimental effects of greenwashing severity on brand attitude.

This study offers actionable insights for brand managers, highlighting that fostering growth beliefs and offering sincere apologies can mitigate the negative impacts of greenwashing.

This study advances the greenwashing literature by highlighting the negative consequences of greenwashing on consumer forgiveness and brand attitude, and underscoring the role of growth beliefs and apology sincerity as effective mitigation strategies.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

Inscrutable machine learning (ML) models are part of increasingly many information systems. Understanding how these models behave, and what their output is based on, is a challenge for developers let alone non-technical end users.

The authors investigate how AI systems and their decisions ought to be explained for end users through a systematic literature review.

The authors’ synthesis of the literature suggests that AI system communication for end users has five high-level goals: (1) understandability, (2) trustworthiness, (3) transparency, (4) controllability and (5) fairness. The authors identified several design recommendations, such as offering personalized and on-demand explanations and focusing on the explainability of key functionalities instead of aiming to explain the whole system. There exists multiple trade-offs in AI system explanations, and there is no single best solution that fits all cases.

Based on the synthesis, the authors provide a design framework for explaining AI systems to end users. The study contributes to the work on AI governance by suggesting guidelines on how to make AI systems more understandable, fair, trustworthy, controllable and transparent.

This literature review brings together the literature on AI system communication and explainable AI (XAI) for end users. Building on previous academic literature on the topic, it provides synthesized insights, design recommendations and future research agenda.

The purpose of this study was to create a more balanced, comprehensive and valid illustration of the relationships between casino gaming volume and employment during economic downturns in urban and rural locations in nondestination gaming states.

This study analyzes gaming volumes and employment prior, during and after the recession of 2007–2009, using a time series with intervention analysis on a monthly coin in, table drop and regression analysis on employment impacts of casinos.

Findings indicate that while there was a slight drop in gaming revenue and employment figures during the economic downturn, nondestination gaming locations such as Indiana proved relatively resilient to an economic downturn.

The Great Recession had no significant impact on gaming volume because gamblers chose to spend their more limited entertainment dollars on less expensive gaming options; in other words, casinos closer to home requiring the expenditure of fewer dollars on travel and/or hotel rooms. The current pandemic and pressures of the macro-environment again threaten the US gaming and casino market with an economic downturn and the results of this study are as timely as ever for hospitality professionals and social scientists to understand the behavior of casinos in recessionary environments.