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This case reviews the development of Dianping. After seeing Zagat's unique business model in the United States, founder Zhang Tao found that he could bring it to China and bring about local innovation. At the beginning of its establishment, the collection and promotion of comment content was the major challenge for Dianping. At the same time, Dianping faced legal issues. To solve these problems, the review mechanism of Dianping was designed to a certain extent to ensure the fairness of the review. With the advent of the mobile Internet era, Dianping began to develop a new business model. Relying on its high-quality “word-of-mouth” content and mass basis, Dianping launched group buying, online restaurant ordering, and other businesses. Dianping has always been open to strategic partners. Since 2015, Dianping has undergone historical changes, merging with Meituan. Since then, Dianping has continuously adjusted its business and organizational structure to maintain its competitiveness. Gradually, Dianping has changed from an independent business entity into a business unit of Meituan.

Although governments have used social media platforms to interact with the public in an attempt to minimize anxiety and provide a forum for public discussion during the pandemic, governments require sufficient crisis communication skills to engage citizens in taking appropriate action effectively. This study aims to examine how the National Health Commission of China (NHCC) has used TikTok, the leading short video–based platform, to facilitate public engagement during COVID-19.

Building upon dual process theories, this study integrates the activation of information exposure, prosocial interaction theory and social sharing of emotion theory to explore how public engagement is related to message sensation value (MSV), media character, content theme and emotional valence. A total of 354 TikTok videos posted by NHCC were collected during the pandemic to explore the determinants of public engagement in crises.

The findings demonstrate that MSV negatively predicts public engagement with government TikTok, but that instructional information increases engagement. The presence of celebrities and health-care professionals negatively affects public engagement with government TikTok accounts. In addition, emotional valence serves a moderating role between MSV, media characters and public engagement.

Government agencies must be fully aware of the different combinations of MSV and emotion use in the video title when releasing crisis-related videos. Government agencies can also leverage media characters – health professionals in particular – to enhance public engagement. Government agencies are encouraged to solicit public demand for the specific content of instructing information through data mining techniques.

This research addressed online customer-to-customer (C2C) incivility during digital service recovery.

To examine the effectiveness of managerial responses to online C2C incivility post a restaurant service failure, a 2 (Managerial response: general vs specific) x 2 (Failure severity: high vs low) quasi-experimental design was employed. A pretest was conducted with 123 restaurant consumers via Amazon Mechanical Turk, followed by a main study with 174 restaurant consumers. Taking a mixed-method approach, this research first asked open-ended questions to explore how participants perceived the restaurant’s motivation for providing a generic versus a specific response. Hayes’ (2013) PROCESS procedure was then performed for hypotheses testing.

The results revealed significant interaction effects of managerial responses and failure severity on perceived online service climate and revisit intention, mediated by trust with managerial responses.

This research yielded unique insight into C2C incivility management literature and industry practices in the context of digital customer service recovery.

This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.

The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.

First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.

This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.

Family planning (FP) services through the lens of human rights are not well known in Nepal. This study aims to assess Family Planning 2020: Rights and Empowerment Principles for Family Planning and identify factors affecting contraceptive use among HIV-infected women living in rural Far Western Nepal.

This study conducted a cross-sectional survey using self-designed proforma. To assess the association between contraceptive use and independent variables, this study calculated adjusted odd ratio (AOR) with 95% confidence interval (CI) using statistical package for social sciences (SPSS) V.20.

Only 37.8% of participants had access to full range of contraceptive methods, and only 57.5% of participants received proper counseling. Agency/autonomy, transparency/accountability and voice/participation were practiced by 43.7%, 23.4% and 19.7% of participants, respectively. Husband’s support (AOR = 4.263; 95% CI: 1.640–11.086), availability of FP services in their locality (AOR = 2.497; 95% CI: 1.311–4.754), employment (AOR = 3.499; 95% CI: 1.186–10.328) and postpartum period (AOR = 0.103; 95% CI: 0.023–0.475) were significantly associated with contraceptive use.

Health-care providers’ and program managers’ perspectives were not examined.

Findings of this study will be useful for making strategic plan on human rights-based approach to FP.

Expanding access to contraceptive information and services and strengthening autonomy, accountability and participation are key to human rights-based approach to FP.

This study identified that inadequate counselling, nonavailability of full range of contraceptive methods, low level of autonomy, accountability and participation were key bottlenecks in fulfilling human rights-based approach to FP.

Research on the effects of feedback frequency has reported mixed findings. To tackle this problem, the current study focuses on specific feedback signs (i.e. negative feedback). By integrating the face management theory and attribution theory, this study examined the mediating effect of trust in supervisors and the moderating effect of employee-attributed performance promotion motives for negative feedback.

A field study with 176 participants and two supplemental experiments with 143 and 100 participants, respectively, were conducted to test the theoretical model.

Results revealed that the frequency of supervisory negative feedback negatively influenced employees’ trust in supervisors, which in turn influenced employees’ perceptions of feedback utility and learning performance. These indirect effects can be alleviated when employees have high degrees of performance promotion attribution for supervisor motives.

This research extends feedback research by integrating feedback frequency with a specific sign of feedback and revealing a moderated mediation effect of the negative feedback frequency.

The purpose of this paper is to explore carbon emission reduction of electric vehicles from the perspective of electricity consumption.

Electric vehicles (EVs) consume large amounts of electricity, thereby generating large amounts of carbon dioxide (CO2) emissions, so there is an urgent need to consider whether EVs have greater potential for reducing carbon emissions than other modes of transport. In this paper, the carbon emission reduction potential (CERP) coefficients of EVs are examined under three different scenarios from an interprovincial electricity trading perspective. Scenario analysis was used to quantify the CERP of EVs in 18 provinces in China.

The results show the following: (1) The higher the proportion of general-fuel vehicles in all transportation, the higher the CERP of EVs. (2) Interprovincial power trading affects the proportion of coal power consumed in a province, and the higher the proportion of clean power in the purchased power, the lower the proportion of coal power consumed in that province. (3) The proportion of coal power in the electricity consumption of a province is correlated negatively with the CERP of EVs in that province.

This paper quantifies the CERP of EVs compared with other modes of transport and gives provinces a more intuitive understanding of the CERP of EVs. Furthermore, we derive the carbon emission shift out of each province via the electricity trading paths among provinces, analyzing the impacts of the variability between different provinces on EV carbon emissions.

This study investigates how the complexity of sentiment in online reviews affects perceived helpfulness. Analyzed over 730,000 reviews from Tripadvisor.com, the research explores how information overload and increased cognitive load impact consumer decision-making.

This study applied the BERT deep learning model to analyze sentiment complexity in online reviews. Based on cognitive load theory, we examined two key factors: the number of attributes mentioned in a review and the variation in sentiment valence of across attributes to evaluate their impact on cognitive load and review helpfulness.

The results show that a higher number of attributes and greater variation in sentiment valence increase cognitive load, reducing review helpfulness. Reviewers’ expertise and review readability further moderate these effects, with complex or expert-written reviews worsening the negative impact.

This research introduces a method for measuring attribute-level sentiment complexity and its impact on review helpfulness, emphasizing the importance of balancing detail with readability. These findings provide a foundation for future studies on review characteristics and consumer behavior.

This paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.

Publications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.

The annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.

This paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.

Step length is a key factor for pedestrian dead reckoning (PDR), which affects positioning accuracy and reliability. Traditional methods are difficult to handle step length estimation of dynamic gait, which have larger error and are not adapted to real walking. This paper aims to propose a step length estimation method based on frequency domain feature analysis and gait recognition for PDR, which considers the effects of real-time gait.

The new step length estimation method transformed the acceleration of pedestrians from time domain to frequency domain, and gait characteristics of pedestrians were obtained and matched with different walking speeds.

Many experiments are conducted and compared with Weinberg and Kim models, and the results show that the average errors of the new method were improved by about 2 meters to 5 meters. It also shows that the proposed method has strong stability and device robustness and meets the accuracy requirements of positioning.

A sliding window strategy used in fast Fourier transform is proposed to implement frequency domain analysis of the acceleration, and a fast adaptive gait recognition mechanism is proposed to identify gait of pedestrians.