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The purpose of this study is to develop and empirically test a theoretical framework that captures the impact of corporate branding on customer emotional attachment and brand loyalty in the luxury fashion market.

Cross‐sectional data were collected from 282 customers who purchased luxury brands. Structural equation modelling was used to test the hypotheses of the framework developed for the study.

Findings found limited effect of corporate branding on customer emotional attachment and brand loyalty. Among the six corporate branding dimensions examined, only corporate association, functional benefits, and symbolic benefits were found to have a significant impact on emotional attachment. Further, the impact of corporate branding on brand loyalty was only evident through functional benefits and corporate associations.

This study offers new empirical support for the proposition that corporate branding efforts have a role, thought limited, in building customer emotional attachment and loyalty towards luxury brands. As such, findings from this study can provide managers with a guide to managing their branding strategies so that customer emotional attachment and brand loyalty can be built in the most cost‐effective manner.

This is the first study to examine the relationship between corporate branding, emotional attachment, and brand loyalty in the luxury fashion context. The examination of the differential effects of corporate branding dimensions on emotional attachment and loyalty has contributed to a better understanding of the mechanism that underlies the operation of an effective corporate branding strategy.

The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.

Introduces and annotates periodical articles, monographs, and audiovisual material examining library instruction and information literacy.

Provides information about each source, discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.

The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.

The purpose of this paper is to explore future directions in E-learning research by analysing data from Scopus indexed publications in order to have a comprehensive overview of the trends and thematic focus post COVID-19 in Asian context.

The paper uses Vos viewer and Biblioshiny software packages to analyse the bibliometric data. This software helped in identifying the anatomy of E-learning and their themes which were instrumental in forecasting future trends.

The paper depicts the trends in post COVID-19 E-learning research in Asian context. It identifies key publications, authors and journals in the field, with a focus on numerous networks of collaboration between writers and nations, identifying keyword clusters and co-citation analysis clusters. This study also explored that China and the USA are having maximum number of collaborations, whereas, countries like India, the United Kingdom, Singapore and New Zealand have comparatively weaker collaboration networks. So there is lot of potential for these countries for such collaborations. India is the most cited country globally and China is having maximum number of scientific productions per year.

The paper has been written by exclusively referring to Scopus database papers. Collecting data from different databases would significantly improve the study. Future researchers can also focus on papers from psychology, computer science and engineering fields as current work is based on open access articles on social business, business and arts and humanities.

This research will be useful to educational institutions that use these platforms to offer E-learning content and match future trends. This study will help researchers in understanding the new dimensions in the field of E-learning.

The current study uses bibliometric analysis to examine the association between E-learning, higher education and COVID-19. It aids in the identification of new difficulties within the complex and expanding study fields in the world of E-learning. Newly published studies on E-learning trends can improve understanding and bridge the knowledge gap. As a result, recommendations can be made to improve and implement newer strategies in field of education.

Sustainable success of group-buying web sites implies that consumers not only accept them initially but also use them continuously. Most group-buying web sites, however, are unable to achieve such sustainable success. Drawing on expectation-confirmation model (ECM), the purpose of this paper is to examine the factors that influence group-buying web sites continuance.

In total, 605 valid responses were collected via a survey of a leading group-buying web site in China. Structural equation modeling was used to test the research model. This study also compared the three competing models of continued use behavior, namely, ECM, the research model and the integrated model.

The results show that perceived web site quality, perceived price advantage and confirmation are important determinants of consumer satisfaction, while perceived web site quality, perceived reputation, satisfaction and perceived critical mass significantly influence consumers’ continuance intention. The research model accounts for more variance in satisfaction and continuance intention than ECM and is the best-fitting model among the competing models.

Drawing on ECM, this research proposes a model by incorporating three online group-buying characteristics (perceived price advantage, perceived reputation and perceived web site quality) and two social influence factors (subjective norm and perceived critical mass). Specially, this study uses these three online group-buying characteristics to represent perceived usefulness in ECM. These constructs are found to influence consumer satisfaction and continuance intention. This study extends ECM and provides a better explanation of consumers’ post-purchase behavior in the online group-buying context.

The purpose of this paper is to investigate postgraduate students' research behavior and requirements to come up with essential components to support research collaboration in a personal digital library (PDL).

This study was conducted using a questionnaire survey method along with a few follow up interviews. A structured questionnaire was circulated among postgraduate students of the Department of Computer Science and Information Technology (CSIT) of the University of Malaya (UM). A total of 100 participants answered the questionnaire, and 15 students participated in the follow up interview. The data collected were analyzed using SPSS statistical software.

This research presents the benefit of collaboration in research. In addition, by reviewing collaborative support tools, it was inferred that the ability to share data and resources is the most important step in developing tools to support collaboration. Moreover, the important role of a virtual research environment (VRE) and social network to support research collaboration was examined. Furthermore, a closed-ended questionnaire survey together with a follow up open-ended survey was deployed among postgraduate students of CSIT of UM, to elicit students' collaboration requirements in research.

Few attempts have been made to study about collaboration services within PDL systems and their impact on students' research. This paper proposes a prototype model of a PDL and highlights the importance of sharing e-resources as the prominent research collaboration activity among postgraduate students.

The purpose of this paper is to investigate the influence of trust and perceived risk on investment willingness considering the bidirectional relationship between trust and perceived risk in peer-to-peer (P2P) lending.

Data were collected from a leading Chinese P2P platform, PPDAI.com. In total, 328 valid responses were received and analyzed using structural equation modeling (SEM).

The results show that the influence of trust on investment willingness is significant, whereas that of perceived risk is insignificant. The results also indicate that platform reputation has a positive effect on trust, and the quality of alternatives is positively associated with perceived risk. In addition, the bidirectional perspective should be preferred to cope with the bidirectional relationship between trust and perceived risk in P2P lending.

This study extends existing research on the influence of trust and perceived risk on investment willingness from a bidirectional perspective, which has not been addressed in the P2P lending context. In addition, this research enriches the current literature about trust and perceived risk by providing more evidence that the relationship between trust and perceived risk is bidirectional and thus the bidirectional model should be preferred. For practice, the study suggests that managers can earn trust and reduce the perceived risk of lenders by continuously providing high-quality products, services and enhancing platform reputation, ultimately improving their investment willingness.

The purpose of this paper is to assist a manufacturer for determining the principal supplier development impediments (SDIs) that are affecting the supplier development programs (SDPs) and yield a basis for drawing the appropriate mitigation strategies.

The proposed approach starts with the application of fuzzy analytic hierarchy process and Pareto analysis to obtain the principal SDIs. Subsequently, the interpretive structural modeling and Fuzzy-Matrice d’Impacts Croisés-Multiplication Appliquée à un Classement analysis are applied on the principal SDIs to explore the root causes inducing ineffectiveness in the SDPs.

The outcomes of the proposed approach were demonstrated through a case study conducted in an Indian automotive components manufacturing company. The principal SDIs were identified, ranked, classified and structurally related for the said case company’s manufacturing environment. It was found that the lack of competent workforce, level of nascent relationship between manufacturer and suppliers and poor devolution of authority were the main SDIs that the case company has to primarily focus to make its SDPs effective.

Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other case situations. However, the proposed approach can be applied for analyzing the SDIs in any manufacturing environment once the set of SDIs relevant to that environment are carefully chosen.

The methodology would assist a manufacturer to proactively identify the SDIs that it has to primarily focus and subsequently devise the mitigation strategies for smooth running of its SDPs.

By utilizing the identified SDIs and applying the proposed methodology a manufacturer can find the main SDIs that are making the SDPs ineffective and accordingly fix the hindrances through certain mitigation strategies designed.

The paper aims to develop a new method for potential relations retrieval. It aims to find common aspects between co-occurrence analysis and ontology to build a model of semantic information retrieval based on co-occurrence analysis.

This paper used a literature review, co-occurrence analysis, ontology build and other methods to design a model and process of semantic information retrieval based on co-occurrence analysis. Archaeological data from Wuhan University Library's bibliographic retrieval systems was used for experimental analysis.

The literature review found that semantic information retrieval research mainly concentrates on ontology-based query techniques, semantic annotation and semantic relation retrieval. Moreover most recent systems can only achieve obvious relations retrieval. Ontology and co-occurrence analysis have strong similarities in theoretical ideas, data types, expressions, and applications.

The experiment data came from a Chinese university which perhaps limits its usefulness elsewhere.

This paper constructed a model to understand potential relations retrieval. An experiment proved the feasibility of co-occurrence analysis used in semantic information retrieval. Compared with traditional retrieval, semantic information retrieval based on co-occurrence analysis is more user-friendly.

This study is one of the first to combine co-occurrence analysis with semantic information retrieval to find detailed relationships.

This study aims to examine how dynamic pricing impacts customer perceptions of restaurants and sentiment toward prices via online reputation metrics. In addition, to deepen the debate on dynamic pricing, a novel definition is drawn by exploring the specific forms of discrimination that can manifest in different industries.

Leveraging a comprehensive data set of restaurant reviews sourced from TripAdvisor, the study focuses on restaurants affiliated with one of the largest groups of restaurants in Spain. We used a quasi-experimental method (difference-in-differences), to study how dynamic pricing strategies influence customers’ perceptions of value based on numerical ratings. Meanwhile, we used a Bidirectional Encoder Representations from Transformers model on the textual component of reviews to dissect the emotional nuances of dynamic pricing.

Results did not reveal a causal impact of dynamic pricing strategies on customers’ perceptions. Moreover, the sentiment analysis shows no heightened negative view after introducing dynamic pricing in restaurants compared to the control group. Contrary to what previous literature suggests, our findings indicate that implementing dynamic pricing does not adversely affect customers’ perceptions or sentiments regarding prices in restaurants.

The quasi-experimental setting of the study presents inherent challenges in establishing causality that require further investigation using controlled experimental settings. Nevertheless, our study reveals that restaurant customers do not perceive dynamic pricing as unfair. This finding is critical for restaurant managers when considering the implementation of dynamic pricing and revenue management strategies. In addition, our study highlights the importance of considering not only numerical ratings but customer sentiment analysis as well. This more holistic approach to assessing the impact of pricing strategies can give restaurant managers a deeper understanding of customer reactions. In addition, a more rigorous definition of dynamic pricing is provided, clarifying its nature and its distinction in using different price discrimination.

This study contributes to the evolving understanding of dynamic pricing strategies’ impact on customers’ perceptions and sentiments in the restaurant industry. It aims to fill the gap in understanding customer reactions to algorithmically determined prices (via revenue management systems such as DynamEat) in this industry. The combination of causal inference and sentiment analysis offers a novel perspective, shedding light on the nuanced connections between dynamic pricing implementation and customers’ emotions.

本研究考察动态定价如何通过在线声誉指标影响顾客对餐厅的感知和对价格的情绪。此外, 为了深化对动态定价的讨论, 通过探索不同行业中可能表现出的具体歧视形式, 提出了一个新的定义。

利用从TripAdvisor获取的餐厅评论的全面数据集, 研究聚焦于与西班牙最大的餐厅集团之一相关联的餐厅。我们采用了准实验方法（差异中的差异）, 研究动态定价策略如何根据数值评分影响顾客对价值的感知。同时, 我们运用BERT模型对评论的文本成分进行分析, 以解析动态定价的情感细微差别。

结果没有揭示动态定价策略对顾客感知产生因果影响。此外, 情绪分析显示, 在餐厅引入动态定价后, 与对照组相比, 没有增加消极观点。与以往文献所述相反, 我们的发现表明, 实施动态定价并不会对顾客对价格的感知或情绪产生负面影响。

研究的准实验设置存在确立因果关系的固有挑战, 需要通过控制实验设置进一步调查。尽管如此, 我们的研究揭示了餐厅顾客不认为动态定价不公平。这一发现对餐厅经理在考虑实施动态定价和收入管理策略时至关重要。此外, 我们的研究强调, 考虑顾客情绪分析和数值评分的重要性。这种更全面的方法评估定价策略的影响, 可以让餐厅经理更深入地理解顾客反应。此外, 提供了一个更严格的动态定价定义, 澄清了其性质及其在使用不同价格歧视中的区别。

本研究对于理解动态定价策略对餐厅行业顾客感知和情绪影响的不断发展有所贡献。它旨在填补对客户对算法确定的价格（通过收入管理系统（RMS）例如DynamEat）在此行业中反应的理解空白。因果推断与情绪分析的结合提供了新的视角, 揭示了动态定价实施与顾客情绪之间微妙的联系。

Este estudio examina cómo la fijación dinámica de precios impacta en las percepciones de los clientes de los restaurantes y en el sentimiento hacia los precios a través de métricas de reputación en línea. Además, para profundizar en el debate sobre la fijación dinámica de precios, se propone una definición novedosa explorando las formas específicas de discriminación que pueden manifestarse en diferentes industrias.

Utilizando un conjunto de datos exhaustivo de reseñas de restaurantes obtenidas de TripAdvisor, el estudio se centra en los restaurantes afiliados a uno de los mayores grupos de restaurantes en España. Empleamos un método cuasiexperimental (diferencias en diferencias) para estudiar cómo las estrategias de precios dinámicos influyen en las percepciones de valor de los clientes basándonos en las calificaciones numéricas. Mientras tanto, empleamos un modelo BERT en el componente textual de las reseñas para desentrañar los matices emocionales de la fijación dinámica de precios.

Los resultados no revelaron un impacto causal de las estrategias de precios dinámicos en las percepciones de los clientes. Además, el análisis de sentimiento no muestra una visión negativa aumentada después de introducir la fijación dinámica de precios en los restaurantes en comparación con el grupo de control. Contrariamente a lo que sugiere la literatura previa, nuestros hallazgos indican que la implementación de precios dinámicos no afecta negativamente las percepciones o los sentimientos de los clientes respecto a los precios en los restaurantes.

La configuración cuasiexperimental del estudio presenta desafíos inherentes para establecer la causalidad que requieren una investigación más profunda utilizando entornos experimentales controlados. Sin embargo, nuestro estudio revela que los clientes de restaurantes no perciben la fijación de precios dinámica como injusta. Este hallazgo es crítico para los gerentes de restaurantes al considerar la implementación de la fijación de precios dinámica y estrategias de gestión de ingresos. Además, nuestro estudio resalta la importancia de considerar no solo las calificaciones numéricas sino también el análisis del sentimiento del cliente. Este enfoque más holístico para evaluar el impacto de las estrategias de precios puede dar a los gerentes de restaurantes una comprensión más profunda de las reacciones de los clientes. Además, se proporciona una definición de fijación de precios dinámica más rigurosa, aclarando su naturaleza y su distinción en el uso de diferentes discriminaciones de precios.

Este estudio contribuye a la comprensión en evolución del impacto de las estrategias de fijación de precios dinámicos en las percepciones y sentimientos de los clientes en la industria restaurantera. Su objetivo es llenar el vacío en la comprensión de las reacciones de los clientes a los precios determinados algorítmicamente (a través de sistemas de gestión de ingresos (RMS) como DynamEat) en esta industria. La combinación de inferencia causal y análisis de sentimientos ofrece una perspectiva novedosa, arrojando luz sobre las conexiones matizadas entre la implementación de la fijación de precios dinámicos y las emociones de los clientes.