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Although recent years have shown increasing popularity of e-commerce worldwide, there is still a lack of studies comprehensively exploring trust issue in e-commerce. Based on trust transfer theory and signaling theory, the purpose of this paper is to present an integrated research model to test the relationships between trust dimensions and e-loyalty, interactions among trust dimensions, as well as antecedents of different trust dimensions.

Data were collected through a web-based survey in Chinese markets and structural equation modeling with partial least squares was used to analyze the data.

The results identified that three trust dimensions all have significant impacts on e-loyalty, and relationships existed in different trust dimensions. Moreover, information quality and security protection are important factors determining institutional trust while store reputation is the most salient factor determining interpersonal trust.

This research contributes to the body of knowledge on trust by exploring the nature of trust with a multidimensional scale. Another theoretical contribution is the provision of a comprehensive understanding of the trust antecedents in e-commerce. Furthermore, this research benefits the companies doing e-businesses by allowing them to better understand how to improve consumers’ trust in the online environment and thus to retain and attract more loyal customers and succeed in online businesses.

The purpose of this paper is to explore the relationship among the air quality index (AQI) of Beijing-Tianjin-Shijiazhuang region and find countermeasures to control the pollution situation.

This study used the grey convex relation model to calculate the grey correlation degree through the AQI of Beijing-Tianjin-Shijiazhuang region.

By analyzing the calculation results among the three cities, it was concluded that the air quality of the three cities is closely related. Therefore, the Beijing-Tianjin-Shijiazhuang region should collaboratively improve the air quality for common development.

More approaches may be adopted to calculate the grey correlation degree in the further research studies.

There exist some practical difficulties in implementing these governance measures.

The paper gives the countermeasures to control the pollution situation in Beijing-Tianjin-Shijiazhuang region.

The purpose of this paper is to develop an improved compressive sensing algorithm for solder joint imagery compressing and recovery. The improved algorithm can improve the performance in terms of peak signal to noise ratio (PSNR) of solder joint imagery recovery.

Unlike the traditional method, at first, the image was transformed into a sparse signal by discrete cosine transform; then the solder joint image was divided into blocks, and each image block was transformed into a one-dimensional data vector. At last, a block compressive sampling matching pursuit was proposed, and the proposed algorithm with different block sizes was used in recovering the solder joint imagery.

The experiments showed that the proposed algorithm could achieve the best results on PSNR when compared to other methods such as the orthogonal matching pursuit algorithm, greedy basis pursuit algorithm, subspace pursuit algorithm and compressive sampling matching pursuit algorithm. When the block size was 16 × 16, the proposed algorithm could obtain better results than when the block size was 8 × 8 and 4 × 4.

The paper provides a methodology for solder joint imagery compressing and recovery, and the proposed algorithm can also be used in other image compressing and recovery applications.

According to the compressed sensing (CS) theory, a sparse or compressible signal can be represented by a fewer number of bases than those required by the Nyquist theorem. The findings provide fundamental guidelines to improve performance in image compressing and recovery based on compressive sensing.

The purpose of this paper is to analyze the mechanism and filter efficacy of accumulation generation operator (AGO)/inverse accumulation generation operator (IAGO) in the frequency domain.

The AGO/IAGO in time domain will be transferred to the frequency domain by the Fourier transform. Based on the consistency of the mathematical expressions of the AGO/IAGO in the gray system and the digital filter in digital signal processing, the equivalent filter model of the AGO/IAGO is established. The unique methods in digital signal processing systems “spectrum analysis” of AGO/IAGO are carried out in the frequency domain.

Through the theoretical study and practical example, benefit of spectrum analysis is explained, and the mechanism and filter efficacy of AGO/IAGO are quantitatively analyzed. The study indicated that the AGO is particularly suitable to act on the system's behavior time series in which the long period parts is the main factor. The acted sequence has good effect of noise immunity.

The AGO/IAGO has a wonderful effect on the processing of some statistical data, e.g. most of the statistical data related to economic growth, crop production, climate and atmospheric changes are mainly affected by long period factors (i.e. low-frequency data), and most of the disturbances are short-period factors (high-frequency data). After processing by the 1-AGO, its high frequency content is suppressed, and its low frequency content is amplified. In terms of information theory, this two-way effect improves the signal-to-noise ratio greatly and reduces the proportion of noise/interference in the new sequence. Based on 1-AGO acting, the information mining and extrapolation prediction will have a good effect.

The authors find that 1-AGO has a wonderful effect on the processing of data sequence. When the 1-AGO acts on a data sequence X, its low-pass filtering effect will benefit the information fluctuations removing and high-frequency noise/interference reduction, so the data shows a clear exponential change trends. However, it is not suitable for excessive use because its equivalent filter has poles at the non-periodic content. But, because of pol effect at zero frequency, the 1-AGO will greatly amplify the low-frequency information parts and suppress the high-frequency parts in the information at the same time.

The aim of this research is to combine and synthesize the findings of previous studies search for the effects of eWom on purchase intention by meta-analysis.

The paper shows a meta-analysis process step by step. Within the scope of certain criteria, the studies in the Google Scholar and ITÜ library databases were eliminated and the results of the remaining 19 studies were analyzed in CMA (Comprehensive Meta-Analysis) program.

By conducting a meta-analysis of the research question, a common effect size was obtained from 19 studies. In addition, the effect size of 21 eWom (electronic word of mouth communication) factor on purchasing intention related to the 21 hypotheses defined in the study was obtained by means of meta-analysis separately.

With the increasing number of Internet users, the desire to share their comments and ideas on the Internet, and the increasing importance of electronic word of mouth communication in our lives, people's decisions have started to be affected by this situation. One of the decision-making movements is the purchase intention. Therefore, it is expected to see more researches on meta-analysis for the effect of eWom on purchase intention in the following years.

The purpose of this study is to identify individuals’ preferences for the information attributes of Airbnb, a representative peer-to-peer (P2P) accommodation platform. In the sharing economy, platforms are considered to be the principal intermediaries in supply and demand, and these platforms have distinctly different attributes from traditional accommodation reservation systems.

The present study used a choice experiment, which is a method for systematically identifying attributes’ preferences in the form of marginal willingness-to-pay (MWTP). Amazon Mechanical Turk, a crowdsourcing marketplace, was used for data collection, and 243 respondents ultimately participated in the survey.

Results showed that respondents’ choices were positively affected by the number of pictures of an accommodation, host experience, cancellation policy and local information but negatively affected by cost. Regarding MWTPs, host experience had the highest value (US$84.25), followed by cancellation policy (US$40), photos (US$26.67) and local information (US$10.92).

These study results could provide strategic guidance for guiding the development of P2P accommodation platforms by providing a prioritized list of preferred attributes for Airbnb.

本研究旨在识别个人对Airbnb这一代表性P2P住宿平台信息属性的偏好。在共享经济中, 平台被视为供需的主要中介, 而这些平台与传统住宿预订系统有明显不同的属性。

本研究采用选择实验法（CE）, 这是一种系统地确定属性偏好的方法, 表现为边际支付意愿（MWTP）。数据采集使用了Amazon Mechanical Turk（MTurk）, 最终有243名受访者参与了调查。

结果显示, 受访者的选择受到住宿图片数量、房东经验、取消政策和本地信息的积极影响, 而受到价格的负面影响。关于边际支付意愿, 房东经验具有最高价值（84.25美元）, 其次依次为取消政策（40美元）、照片（26.67美元）和本地信息（10.92美元）

通过提供优先考虑的 Airbnb 偏好属性列表, 本研究结果可以为引导P2P住宿平台的发展提供战略指导.

This study aims to examine the impact of online travel reviews (OTR) on tourists’ intention to travel based on the stimulus–organism–response (SOR) model. Further, it explored the mediating effects of tourist trust in OTR.

In this direction, this study proposes and empirically validates a conceptual model after collecting data from 299 Indian consumers. Proposed hypotheses were tested by applying the structural equation modelling technique. Bootstrapping method was used for mediation testing.

The findings revealed that various attributes of OTR exert differential impacts on travel intention. The study also confirmed the mediating role of tourist trust in OTR.

This study offers significant practical implications for travel marketers. To capitalize on OTR, travel marketers are recommended to develop an effective and efficient online reviews management system. This will improve the quality, valence, quantity and consistency of OTR, which in turn will enhance tourist trust in OTR, leading to improved travel intention.

No empirical evidence has been traced on how OTR enhances tourist trust in OTR and their travel intention. In support of this, the present study proposes and empirically validates an extensive model to comprehend the role of various drivers of OTR in improving tourist trust in OTR, leading to enhanced travel intention based on the SOR model.

This paper has a twofold objective: (1) to examine how trust and distrust mediate the relationship between corporate social responsibility (CSR) and irresponsibility (CSI) perceptions and word of mouth recommendations; and (2) to show that moral norms moderate this mediating relationship.

Two experimental studies test the proposed model. Study 1 performs a single-factor experiment with three levels of corporate social responsibility (positive, neutral, negative) to test the mediation hypothesis (N = 180, 66% females, mean age = 22.3). Study 2 validates the mediation findings and examines the role of moral norms as moderators (N = 240, 50% females, mean age = 39.5).

Study 1 reveals that trust in the company partially mediates the effects of CSR on word of mouth (WOM) recommendations. Study 2 shows that consumers who adhere to higher moral standards follow distinct paths to negative WOM. Specifically, these consumers tend to spread negative comments when they expect the firm to behave irresponsibly. When unsure about future corporate behaviour, they are less likely to spread negative WOM.

This is the first study, to the authors' knowledge, to demonstrate how moral norms shape the effects of distrust in the corporate culprit on word of mouth recommendations. Accordingly, this research proves that conceptualising trust and distrust as separate constructs is useful in explaining consumer reactions to corporate social irresponsibility.

This study aims to examine the impact of electronic word of mouth (eWOM) on behavioural intentions of Indian urban millennials to use it when they book travel. The eWOM has been measured on the basis of four dimensions, namely, perceived credibility, quality, quantity and completeness. eWOM attitude is studied as a mediator.

The study first applies a confirmatory factor analysis to gauge validity and reliability. Then structural equation modelling was applied to test the research hypotheses after collecting responses from 288 Indian millennials from six North Indian cities. Mediation has also been examined using the bootstrapping method. The quality of the data was assured by Harman’s single-factor test.

The study reveals that millennials’ eWOM attitude fully mediates its perceived quality and its usage intentions at the time of booking travel. However, this mediation effect is partial with respect to other components of eWOM, namely, perceived credibility, perceived quantity and perceived completeness.

India has the largest millennial population (440 million) in the world out of which 33% live in urban cities. Hence, it becomes imperative for travel marketers to understand the attitude of millennials’ towards eWOM, shared on social media. They should understand that millennials prefer eWOM in social media over traditional advertising for fulfilling their informational needs. Therefore, by apprehending the impact of recipients’ perception towards various components of eWOM on their behavioural intentions to use it, market practitioners can design superior marketing campaigns that will help them to gain maximum in the changing business landscape.

The study is unique in the sense that to date no study to the limited knowledge of the researchers has investigated the attitude of Indian millennials towards eWOM on social media as a mediator to comprehend their behavioural intentions to use travel reviews when they book travel.

The purpose of this paper is to investigate the effect of formulation categories (parent brand and extension product) and research and development (R&D) cooperation types on electronic word-of-mouth (eWOM) volume for extension products.

This study uses data from 109 extension products in the Korean dessert market whose formulations were changed between 1 February 2014 and 19 February 2019. The formulation categories and R&D cooperation types are transformed into dummy variables to conduct a linear regression.

The formulation categories and R&D cooperation types play key roles in proliferating eWOM for formulation change products. The most effective way to proliferate eWOM is through product extension by changing the formulation of ice cream, beverage and snack category products. Furthermore, vertical R&D cooperation positively affects the proliferation of products' eWOM.

These findings contribute to increasing the chance of successful food product development by providing information on the formulation changes that are effective at inducing consumers' interest.