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This study aims to frame the authenticity–standardisation relationship in international gastronomy retailing and explores how and to what extent the food place of origin and the urban context in which the gastronomy stores are located shape customers' in-store experience.

This paper analyses the case of Eataly, which combines specialty grocery stores and restaurants disseminating the Italian eating style, quality food and regional traditions internationally. Facebook reviews (1,018) of four Eataly stores – New York City, Rome, Munich and Istanbul were analysed, adopting a web content mining approach.

Place of origin, quality and hosting city categories frame the gastronomic in-store experience. Standardisation elements (shared across the four analysed stores) and authenticity elements (specific to a single store) are identified towards defining three archetypical authenticity–standardisation relationships, namely originated authenticity, standardised authenticity and localised authenticity.

This study proposes original modelling that disentangles the authenticity–standardisation paradox in international gastronomy retailing. It provides evidence of the intertwining of the place of origin and the city brand in customers' in-store experience.

This paper aims to provide an overview of the application of blockchain to agri-food supply chains, including key issues and trends. It examines the state of the art and conceptual structure of the field and proposes an agenda to guide future research.

This article performs a bibliometric analysis using VOSviewer software on a sample of 205 articles from the WoS database to identify research trend topics.

The number of publications in this area has increased since 2020, which shows a growing research interest. The research hotspots are related to the integration of blockchain technology in the agri-food supply chain for traceability, coordination between all actors involved, transparency of operations and improvement of food safety. Furthermore, this is linked to sustainability and the achievement of the sustainable development gtoals (SDGs), while addressing key challenges in the implementation of blockchain-based technologies in the agri-food supply chain.

The application of blockchain in the agri-food supply chain may consider four key aspects. Firstly, the implementation of blockchain can improve the traceability of food products. Secondly, this technology supports sustainability issues and could avoid disruptions in the agri-food supply chain. Third, blockchain improves food quality and safety control throughout the supply chain. Fourthly, the findings show that regulation is needed to improve trust between stakeholders.

The paper provides a comprehensive overview of the blockchain phenomenon in the agri-food supply chain by optimising the search criteria. Moreover, it serves to bridge to future research by identifying gaps in the field.

This paper reviews the literature, foundational works and current trends related to the adoption of open innovation (OI) practices in the food industry, with a particular focus on the food value chain, using a bibliometric and content analysis approach.

This study is based on 84 published documents in the field of food OI obtained using the Scopus database. First, a bibliometric analysis was conducted using a bibliographic coupling and co-citation analysis approach to understand the common themes and key clusters of food OI research. It further highlighted authors, countries, journals, years of publication and subject areas to comprehend the scope of the established literature. Second, a content analysis was undertaken to examine the titles and abstracts of the documents to explore the intersection of OI and the food value chain.

This study provides an integrated framework of the intersection of OI and the food value chain, including information about under-researched and emerging areas in the field of food innovation. It also highlights the critical challenges associated with OI food research and practices.

Practitioners can use the findings to uncover areas with limited open innovation adoption in the food value chain. They can identify extended research areas to explore the food value chain using an open innovation perspective, in different contexts within the food and beverage (F&B) industry. The framework can also be used for conducting comparative studies of current food innovation trends across different contexts within the F&B industry.

By adopting a multi-step approach involving a computer-assisted bibliometric examination complemented by a manual review undertaken through the lens of the food value chain, this literature review provides fresh and unique insights into past and present research on OI in the food industry and paves the way for future studies by laying out specific research avenues.

Efficient traffic incident management is needed to alleviate the negative impact of traffic incidents. Accurate and reliable estimation of traffic incident duration is of great importance for traffic incident management. Previous studies have proposed models for traffic incident duration prediction; however, most of these studies focus on the total duration and could not update prediction results in real-time. From a traveler’s perspective, the relevant factor is the residual duration of the impact of the traffic incident. Besides, few (if any) studies have used dynamic traffic flow parameters in the prediction models. This paper aims to propose a framework to fill these gaps.

This paper proposes a framework based on the multi-layer perception (MLP) and long short-term memory (LSTM) model. The proposed methodology integrates traffic incident-related factors and real-time traffic flow parameters to predict the residual traffic incident duration. To validate the effectiveness of the framework, traffic incident data and traffic flow data from Shanghai Zhonghuan Expressway are used for modeling training and testing.

Results show that the model with 30-min time window and taking both traffic volume and speed as inputs performed best. The area under the curve values exceed 0.85 and the prediction accuracies exceed 0.75. These indicators demonstrated that the model is appropriate for this study context. The model provides new insights into traffic incident duration prediction.

The incident samples applied by this study might not be enough and the variables are not abundant. The number of injuries and casualties, more detailed description of the incident location and other variables are expected to be used to characterize the traffic incident comprehensively. The framework needs to be further validated through a sufficiently large number of variables and locations.

The framework can help reduce the impacts of incidents on the safety of efficiency of road traffic once implemented in intelligent transport system and traffic management systems in future practical applications.

This study uses two artificial neural network methods, MLP and LSTM, to establish a framework aiming at providing accurate and time-efficient information on traffic incident duration in the future for transportation operators and travelers. This study will contribute to the deployment of emergency management and urban traffic navigation planning.

The study aims to propose an instrument for measuring product-centeredness (i.e. the extent to which comment content is related to a product) using word embedding techniques as well as explore its determinants.

The study collected branded posts from 205 Instagram influencers and empirically examined how four factors (i.e. authenticity, vividness, coolness and influencer–product congruence) influence the content of the comments on branded posts.

Post authenticity and congruence are shown to have positive effects on product-centeredness. The interaction between coolness and authenticity is also significant. The number of comments or likes on branded posts is not correlated with product-centeredness.

In social media influencer marketing, volume-based metrics such as the numbers of likes and comments have been researched and applied extensively. However, content-based metrics are urgently needed, as fans may ignore brands and focus on influencers. The proposed instrument for assessing comment content enables marketers to construct content-based metrics. Additionally, the authors' findings enhance the understanding of social media users' engagement behaviors.

The purpose of this paper is to investigate the key factors that explain intention to use e-wallet services (perceived usefulness, perceived ease of use, attitude, subjective norm, positive disconfirmation and perceived behavioral control). The moderating role of perceived value in the relationship between satisfaction and their intention to continue using the e-wallet is also examined.

A total of 257 e-wallet users participated in an online survey and hypotheses were tested with SPSS/PLS-SEM.

The constructs technology acceptance model (TAM), theory of planned behavior (TPB) and user satisfaction affect intention to use. However, perceived value does not strengthen the relationship between user satisfaction and e-wallet usage intention.

The TAM, TPB and expectancy disconfirmation model (EDM) constructs help explain the use of e-wallet services. These results will help the providers of these services to understand user behavior and to design their marketing strategies more appropriately to ensure consumer satisfaction and their intention to use e-wallet services.

This study adopts a holistic and integrative approach to explain the continued use of e-wallet services. The model integrates three basic adoption theories: TAM, TPB and EDM.

El propósito es investigar los factores clave que explican la intención de utilizar los servicios de monedero electrónico (utilidad percibida, facilidad de uso percibida, actitud, norma subjetiva y control conductual percibido). También se examina el papel moderador del valor percibido en la relación entre la satisfacción y su intención de seguir usando el monedero electrónico.

257 usuarios de monederos electrónicos participaron en una encuesta online y las hipótesis fueron contrastadas con SPSS/PLS-SEM.

los constructos TAM (modelo de aceptación de la tecnología), TPB (teoría del comportamiento planificado) y la satisfacción del usuario afectan a la intención de uso. Sin embargo, el valor percibido no refuerza la relación entre la satisfacción del usuario y la intención de uso del monedero electrónico.

Este estudio adopta un enfoque holístico e integrador para explicar el uso continuado de los servicios de monedero electrónico. El modelo integra tres teorías básicas de adopción: TAM, TPB y EDM (modelo de desconfirmación de expectativas).

los constructos TAM, TPB y EDM permiten explicar el uso de los servicios de monedero electrónico. Estos resultados ayudarán a los proveedores de estos servicios a comprender el comportamiento de los usuarios y diseñar sus estrategias de marketing de forma más adecuada para garantizar la satisfacción del consumidor y su intención de utilizar los servicios de monedero electrónico.

目的是研究解释使用电子钱包服务意向的关键因素（感知的有用性、感知的易用性、态度、主观规范和感知的行为控制）。此外, 还研究了感知价值在满意度和他们继续使用电子钱包的意向之间的调节作用。

257名电子钱包用户参与了一项在线调查, 用SPSS/PLS-SEM对假设进行了检验。

TAM（技术接受模型）、TPB（计划行为理论）和用户满意度影响使用意向。然而, 感知价值并没有加强用户满意度和电子钱包使用意向之间的关系。

本研究采用了一种整体和综合的方法来解释电子钱包服务的持续使用。该模型整合了三个基本的采用理论：TAM、TPB和EDM（期望不确认模型）。

TAM、TPB和EDM构造有助于解释电子钱包服务的使用。这些结果将有助于电子钱包服务提供商了解用户行为, 并更恰当地设计他们的营销策略, 以确保消费者的满意度和他们使用电子钱包服务的意向。

The alienation of megaproject environmental responsibility (MER) behavior is destructive, but its mechanism has not been clearly depicted. Based on fraud triangle theory and the fuzzy set qualitative comparative analysis (fsQCA) method, this study explored the combined effect of antecedent factors on alienation of MER behavior.

Based on the fraud triangle theory and literature review, eight influencing factors associated with the alienation of MER behavior were first identified. Subsequently, the fuzzy-set qualitative comparative analysis was used in this study to reveal configurations influencing alienation of MER behavior.

The study found nine configurations of MER behavioral alienation antecedent factors, integrated into three types of driving modes, i.e. “economic pressure + learning effect,” “institutional defect + moral rejection,” and “information asymmetry + economic pressure + expectation pressure.”

By analyzing the configuration effects of various induced conditions, this study puts forward a comprehensive analysis framework to solve the alienation of MER behavior in the megaprojects and a practical strategy to control alienation of MER behavior.

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 study is to investigate the impact of Corporate Philanthropic Donations (CPD) on the Corporate Economic Performance (CEP) of a group of Jordanian public shareholding companies.

The sample includes 94 companies listed on the Amman Stock Exchange between 2010 and 2016. Manual content analysis is employed to collect the quantitative-related data needed for this study.

Our findings show that CPD is relevant, with a significant impact on financial performance. More specifically, CPD has a positive impact on the performance indicators measured by Tobin’s Q (TQ), return on equity (ROE) and return on assets (ROA).

This study contributes to the research debate on CPD and CEP, especially in developing countries. It emphasizes the importance of such practices in increasing corporate profitability.

The study’s findings highlight the importance of CPD for Jordanian corporate managers. A greater emphasis on donations is likely to attract investor attention, government attention, media attention and humanitarian activism, all of which will enhance corporate goodwill.

This study demonstrates the positive relationship between corporate social responsibility (CSR) and CEP in an emerging economy, with a focus on one aspect of CSR, namely donation, that is underrepresented in developing countries. The study employs multiple methods for analyzing profitability as proxied by TQ, ROE and ROA, given the presence of multiple proxies to measure profitability. A further interesting aspect is examining the topic of CPD in the Jordanian context, where listed companies exhibit a uniform understanding of CPD.

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.