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Prior marketing and hospitality studies have largely ignored the role of corporate social responsibility (CSR) in shaping frontline employees’ customer orientation. This study aims to investigate the impacts of employee perceived CSRs on customer orientation in hotel industry.

Through an onsite data collection from 642 frontline employees of 14 hotels in China, the moderated mediation model that links frontline employees’ perceptions of internal and external CSR to person-organization fit, work engagement and customer orientation were validated with the bootstrapping procedures.

The results reveal that a higher degree of perceived internal and external CSR leads to greater customer orientation through work engagement, and these indirect effects will be stronger with comparatively higher person-organization fit levels.

By clarifying the connection between perceived CSR initiatives and customer-oriented behaviors, this study offers inspiration for hospitality managers to devise, allocate and leverage CSR investments, strategies and practices.

To the best of the authors’ knowledge, this study is the first to verify a moderated mediation model that investigates the impacts of perceived CSRs (i.e. internal vs external) on customer orientation, which not only uncovers some neglected antecedents of customer orientation but also provides a more nuanced insight into perceived CSR-customer orientation linkages.

This paper aims to conduct a meta-analysis to explore the strength of the path relationship in the proposed model for online travel service adoption and the moderating effect of country or regional economic development level.

A meta-analysis was conducted based on 46 empirical studies to verify a proposed model for users’ intention to adopt online travel service.

The relationship between technology acceptance model and theory of planned behavior variables was found to be valid for online travel scenarios; moreover, perceived trust positively correlated with attitude and adoption intention. Meanwhile, personal innovation, perceived enjoyment and cost-effectiveness positively correlated with adoption intention. Except for the correlations between subjective norms and adoption intention, the correlations between all other variables in the model were significantly moderated by the economic development level of a country or region.

This paper was conducted to obtain a unified conclusion about the research field of online travel service adoption. To the best of the authors’ knowledge, its content is original.

本研究旨在探讨所提出的在线旅游服务采用模型中路径关系的强度以及国家或地区经济发展水平的调节作用。

本论文基于 46 项实证研究进行了荟萃分析, 以验证所提出的用户采用在线旅游服务意愿的模型。

技术接受模型和计划行为理论中不同变量之间的相关性在在线旅游服务场景中依然显著。对在线旅游场景有效; 此外, 感知信任与态度和采用意愿呈正相关。同时, 个人创新、感知享受和成本效益与采用意愿正相关。除了主观规范与采用意愿之间的相关性外, 模型中所有其他变量之间的相关性均受到国家或地区经济发展水平的显着调节。

本文旨在就在线旅游服务采用的研究领域获得一个统一的结论。本研究的内容是原创的。

：在线旅游服务; 采用意向; 影响因素; 荟萃分析

As the retail banking institutions are becoming more customer centric, their focus on service quality is increasing. Established service quality frameworks such as SERVQUAL and SERVPERF have been applied in the banking sector. While these models are widely accepted, they are expensive because of the need for replication across bank branches. The purpose of this paper is to propose a novel, user friendly and cost effective approach by amalgamating the traditional concept of service quality in banks (marketing base) and sentiment analysis literature (information systems base).

In this study, the main objective is to analyze user reviews to better understand the correlation between RATER dimension sentiment scores as independent variables and user overall rating (customer satisfaction) grouping in “good” and “bad” as dependent variable through development of authors’ own logistic regression model using lexicon-based sentiment analysis. The model has been developed for three largest private banks in India pertaining to three banking product categories of loans, savings and current accounts and credit cards.

The results show that the responsiveness and tangibles dimensions significantly impact the user evaluation rating. Even though the three largest private banks in India are concentrating on the tangibles dimension, not all of them are sufficiently focused on the responsiveness dimension. Additionally, customers looking for loan products are more susceptible to negative perceptions on service quality.

This study has highlighted two types of scores whereby user provided overall evaluation scores help provide validation to the sentiment scores. The developed model can be used to assess performance of a bank in comparison to its peers and to generate in depth insights on point of parity (POP) and point of difference (POD) fronts.

The purpose of this paper is to present a comprehensive self‐adaptive genetic algorithm (GA) based on fuzzy mechanism, aiming to improve both the optimizing capability and the convergence speed.

Many key factors that affect the performance of GAs are identified and analyzed, and their influences on the optimizing capability and the convergence speed are further elaborated, which prove to be very difficult to be described with explicit mathematical formulas. Therefore, a set of fuzzy rules are used to model these complicated relationships, in order to effectively guide the online self‐adaptive adjustments, such as changing the crossover and mutation probabilities, and thus to improve the optimizing capability and convergence speed.

Simulation results illustrates that, compared with a normal GA and another self‐adaptive GA based on explicit mathematical modeling of the key factors, the new GA is more advanced in terms of the optimizing capability and the convergence speed.

This paper develops a fuzzy‐rule‐based approach to describe the relationships between multiple GA parameters and online states, and the approach is useful in the design of a comprehensive self‐adaptive GA.

The purpose of this paper is to establish the damage alarming indexes for ancient wood structures and study the damage sensitivity and noise robustness of these indexes under random excitation.

Xi’an Bell Tower is taken as a case in this paper to simulate the damage of ancient wood structures through finite element (FE) simulation and determine the satisfactory damage alarming indexes with wavelet packet energy spectrum.

The results of this paper show that: 1) the damage alarming indexes can effectively identify the damage of ancient wood structures, each index with a different damage sensitivity; 2) the energy ratio deviation is greater than the energy ratio variance and is close to the maximum variation of energy ratio; 3) the energy ratio deviation has a better alarming effect than the energy ratio variance during the initial period of the damage. With the accumulation of the damage, the energy ratio variance outperforms the energy ratio deviation; 4) the sensitivity of the energy ratio deviation and variance varies from positions, changing from the highest to lowest at the mortise-and-tenon joints, the beam mid-span and the plinth; 5) if signal to noise ratio (SNR) is 40db or larger, the indexes can accurately identify the damage of ancient wood structures. As SNR increases, the indexes will have an increasingly higher sensitivity and certain ability to resist noise.

The FE model is simpiy, it does not completely reflect Xi’an Bell Tower.

It will provide a theoretical basis for the damage alarming of Xi’an Bell Tower.

It makes structural health monitoring through structural vibration response under ambient excitation a new research field in damage detection as well as a positive way of ancient architecture protection.

This paper studies the damage alarming effect on ancient wood structures from different wavelet functions and wavelet packet decomposition levels. To study the effect under white noise environment, this paper adds Gaussian white noise with a SNR of 10, 20, 30, 40 and 50 db to the acceleration response signal of intact structure and damaged structure.

This study aims to conceptualise the panic buying behaviour of consumers in the UK during the novel COVID-19 crisis, using the assemblage approach as it is non-deterministic and relational and affords new ways of understanding the phenomenon.

The study undertakes a digital ethnography approach and content analysis of Twitter data. A total of 6,803 valid tweets were collected over the period when panic buying was at its peak at the beginning of the first lockdown in March 2020.

The panic buying phase was a radical departure from the existing linguistic, discursive, symbolic and semiotic structures that define routine consumer behaviour. The authors suggest that the panic buying behaviour is best understood as a constant state of becoming, whereby stockpiling, food waste and a surge in cooking at home emerged as significant contributors to positive consumer sentiments.

The authors offer unique insights into the phenomenon of panic buying by considering DeLanda’s assemblage theory. This work will inform future research associated with new social meanings of products, particularly those that may have been (re)shaped during the COVID-19 crisis.

The study offers insights for practitioners and retailers to lessen the intensity of consumers’ panic buying behaviour in anticipation of a crisis and for successful crisis management.

Panic buying took on a somewhat carnivalesque hue as consumers transitioned to what we consider to be atypical modes of purchasing that remain under-theorised in marketing. Using the conceptual lenses of assemblage, the authors map bifurcations that the panic buyers’ assemblages articulated via material and immaterial bodies.

This research proposes a text analytics–based framework that examines the utility of online customer reviews in evaluating automobile manufacturers and discovering their consumer-perceived weaknesses.

The proposed framework integrates aspect-level sentiment analysis with the house of quality (HoQ), TOPSIS, Pareto chart and fishbone diagram. While sentiment analysis mines and quantifies review-embedded consumer opinions on various automobile attributes, the integrated HoQ-TOPSIS analyzes the quantified opinions and evaluates the manufacturers. The Pareto charts assist in discovering consumer-perceived weaknesses of the underperforming manufacturers. Finally, the fishbone diagram visually represents the results in the form with which the manufacturing community is acquainted.

The proposed framework is tested on a review data set collected from CarWale, a well-known car portal in India. Selecting five manufacturers from the mid-size car segment, the authors identified the worst-performing one and discovered its weak attributes.

The proposed framework can help the manufacturers in evaluating competitor; identifying consumers' contemporary interests; discovering own and their competitors' weak attributes; assessing the suppliers and sending early warnings; detecting the hazardous defects. It can assist the component suppliers in devising process improvement strategies; improving their customer network; comparing them with competitors. It can support the customers in identifying the best available alternative.

The proposed framework is first of its kind to integrate the sentiment analysis with (1) HoQ-TOPSIS to assess the manufacturers; (2) Pareto chart to discover their weaknesses; (3) fishbone diagram to visually represent the results.

In mainstream economics and finance literature, market sentiment is considered “irrational”. This leads to significant challenges in capturing the effect of sentiment on economic relationships. Real estate is even more complex due to the fact that the sector exhibits several market inefficiencies. The purpose of this paper is to explore the literature and present a simple test for the potential of using three different sentiment indicators to improve a basic cap rate model. The authors establish the case using commercial real estate (CRE) data for London West End.

The three indicators differ in their underlying source and method. The authors used orthogonalisation and principal component analysis for a macroeconomic sentiment indicator. Furthermore, online search volume data have been used to mirror the market sentiment for the London West End market. Finally, textual analysis based on word lists has been applied to corpus of market reports.

The results indicate considerable improvement in the authors’ ability to capture the effect of sentiment. Furthermore, the consideration of a human factor leads to improvement in the basic yield model.

The methods suggest that sentiment extracted from more forward-looking sources, such as online searches, could be a significant information gain for investors, lenders or other market participants. The additional information could be used to adjust their behaviour within the market.

To the authors’ knowledge, this is the first study that applies textual analysis to market reports for the CRE market in the UK.

Online review bias research has predominantly focused on self-selection biases on the user’s side. By collecting online reviews from multiple platforms and examining their biases in the unique digital environment of “Chinanet,” this paper aims to shed new light on the multiple sources of biases embedded in online reviews and potential interactions among users, technical platforms and the broader social–cultural norms.

In the first study, online restaurant reviews were collected from Dianping.com, one of China's largest review platforms. Their distribution and underlying biases were examined via comparisons with offline reviews collected from on-site surveys. In the second study, user and platform ratings were collected from three additional major online review platforms – Koubei, Meituan and Ele.me – and compared for possible indications of biases in platform's review aggregation.

The results revealed a distinct exponential-curved distribution of Chinese users’ online reviews, suggesting a deviation from previous findings based on Western user data. The lack of online “moaning” on Chinese review platforms points to the social–cultural complexity of Chinese consumer behavior and online environment that goes beyond self-selection at the individual user level. The results also documented a prevalent usage of customized aggregation methods by review service providers in China, implicating an additional layer of biases introduced by technical platforms.

Using an online–offline design and multi-platform data sets, this paper elucidates online review biases among Chinese users, the world's largest and understudied (in terms of review biases) online user group. The results provide insights into the unique social–cultural cyber norm in China's digital environment and bring to light the multilayered nature of online review biases at the intersection of users, platforms and culture.

The purpose of this paper is to analyze the research status and outputs of information behavior in China in order to reveal its in-depth research pattern and trends.

The author collected literature during the past 29 years from China Academic Journal Network Publishing Database. Bibliometric analysis, including publication growth analysis, core authors and collaborative degree analysis, core journals analysis, and institutions distribution, was performed. The temporal visualization map of burst term was drawn, and the co-occurrence matrix of these keywords was analyzed by the hierarchical cluster analysis, strategic diagram, and social network analysis.

The earliest article on information behavior in China was published in 1987. And the number of articles has risen continually since then, which follows the logical growth law of literature. The collaborative degree of authors is on the rise in general. The distribution of these articles obeys the Bradford’s Law of Scattering. School of Information Management of Wuhan University remarkably ranks the top in most publications. In all, ten important research directions were identified, which are in the imbalanced development. And a newly appearing topic with great potential for further development, namely information seeking and information security, is identified.

This study provides important insights into the research status and trends on information behavior in China, which might provide a potential guide for the future research.