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The focus of this study is on how online-only retailers, known as pure-play e-retailers, leverage e-commerce platforms to identify and pursue market opportunities. Through the perspective of entrepreneurial marketing, this study aims to explore the influence of e-commerce technologies on the decision-making process of entrepreneurial marketing. This exploration is conducted via a case study of pure-play e-retailers based in China.

This study utilised a qualitative case study methodology to examine the complex processes of entrepreneurial marketing in an online environment. The study gathered detailed insights from both owner-managers and staff members of eight pure-play e-retail businesses. Additionally, the research involved a careful review of the firms' webpages and social media pages. This holistic approach facilitated a comprehensive understanding of their marketing strategies and practices.

The case study findings indicate that while many core aspects of entrepreneurial marketing remain important, there are distinct factors influencing the entrepreneurial marketing decision-making in the online marketplace. The online EM framework can be visualised as follows: (1) trend-orientated as well as innovative-orientated (2) data-orientated and entrepreneur-orientated (3) innovative-driven customer stimulation (4) orientated towards both platforms and proactiveness.

The paper provides an initial understanding of how digitalisation is enabling and transforming entrepreneurship in companies with high level digitalisation but low level digital development. Building on current entrepreneurial marketing literature, this paper develops an online entrepreneurial marketing framework to enhance understanding of the interaction between e-commerce technology and entrepreneurial marketing decision making.

Although the impact of carbon emissions regulations is evident to upstream automakers, their influence on downstream B2C car-sharing platforms remains unclear. This article reveals the influence of carbon emission regulations on the performance of supply chain members. In particular, we focused on the decision of B2C car-sharing platforms.

We develop a three-stage dynamic game model consisting of an automaker, a B2C car-sharing platform and consumers.

The carbon emission cap has a critical threshold. Above this threshold, the regulation is ineffective for the platform’s operating model. Below it, the regulation affects the platform, moderated by customers' green awareness. The threshold initially decreases (weakly) and then increases in awareness. Effective caps reduce profits for the manufacturer, B2C car-sharing platform and supply chain, while ineffective caps see higher profits with increased awareness.

Firstly, this paper explores the impact of carbon emission caps on the operational strategies of B2C car-sharing platforms within the sharing economy, complementing existing research. Secondly, it identifies conditions where stricter caps prompt B2C car-sharing platforms to adjust their operational models and offers fresh insights for managers and departments responsible for carbon emission policy formulation. Thirdly, the study uncovers how carbon emission caps affect the performance of supply chain members, providing crucial managerial insights for sustainable operations.

This paper seeks to discuss the genealogical sources for Chinese immigrants as well as the settlement of Chinese in the USA and the historical evolution of Chinese names, their origins, arrangement and development. It aims to cover the origins of various classes of Chinese surnames, followed by the content description of a traditional genealogical book for jiapu.

The paper researches the various ways that a Chinese person can find out about their ancestry.

The paper reveals the roles of libraries, including serving the needs of patrons interested in genealogical research, preserving and interpreting information through oral and family history projects and collaborating with other libraries through interlibrary loan, document delivery, library consortia, collection management and international resource‐sharing.

The study provides information on where and how to locate the genealogical resources for researching the genealogy of a Chinese family.

The paper analyzes the value of genealogical research as a documentary source for population history, life expectancy in a clan, marriages and family connections, as well as lineage organizations and inter‐lineage relations.

The purpose of this paper is to propose a graph-based representation approach for evolutionary knowledge under the big data circumstance, aiming to gradually build conceptual models from data.

A semantic data model named meaning graph (MGraph) is introduced to represent knowledge concepts to organize the knowledge instances in a graph-based knowledge base. MGraph uses directed acyclic graph–like types as concept schemas to specify the structural features of knowledge with intention variety. It also proposes several specialization mechanisms to enable knowledge evolution. Based on MGraph, a paradigm is introduced to model the evolutionary concept schemas, and a scenario on video semantics modeling is introduced in detail.

MGraph is fit for the evolution features of representing knowledge from big data and lays the foundation for building a knowledge base under the big data circumstance.

The representation approach based on MGraph can effectively and coherently address the major issues of evolutionary knowledge from big data. The new approach is promising in building a big knowledge base.

Health-related online fake news (HOFN) has become a major social problem. HOFN can lead to the spread of ineffective and even harmful remedies. The study aims to understand Internet users' responses to HOFN during the coronavirus (COVID-19) pandemic using the protective action decision model (PADM).

The authors collected pandemic severity data (regional number of confirmed cases) from government websites of the USA and China (Studies 1 and 2), search behavior from Google and Baidu search engines (Studies 1 and 2) and data regarding trust in two online fake news stories from two national surveys (Studies 2 and 3). All data were analyzed using a multi-level linear model.

The research detected negative time-lagged relationships between pandemic severity and regional HOFN search behavior by three actual fake news stories from the USA and China (Study 1). Importantly, trust in HOFN served as a mediator in the time-lagged relationship between pandemic severity and search behavior (Study 2). Additionally, the relationship between pandemic severity and trust in HOFN varied according to individuals' perceived control (Study 3).

The authors' results underscore the important role of PADM in understanding Internet users' trust in and search for HOFN. When people trust HOFN, they may seek more information to implement further protective actions. Importantly, it appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.

This paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.

This paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.

A case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.

Proposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

The politically laden nature of postdisaster recovery calls for more research on its governance, especially at the micro-scale. Apart from engineering-oriented frameworks, researchers need new theoretical underpinnings. This paper aims to review the development of the evolutionary resilience theory and use it as an analytical framework to evaluate the governance of post-earthquake reconstruction planning in China.

This paper examines how reconstruction planning is governed in the epicenter town of the 2008 Great Sichuan Earthquake, highlighting three key qualities of evolutionary resilience. The authors draw on site investigations, semistructured interviews and analysis of official and unpublished documents from various sources.

This paper finds that despite the absence of specific resilience statements in reconstruction plans of the time, qualities of evolutionary resilience, including social connectedness, flexibility and innovation, were evident in a hybrid and contradictory reconstruction planning system. In this respect, resilience thinking appears in Chinese planning earlier than generally assumed. This paper suggests that this manifestation of resilience was the result of an instrumental utility in addressing socioeconomic uncertainties in the postdisaster environment and, thus, may not be systematic.

This work enriches the understanding of recovery governance from an evolutionary resilience perspective where existing research is insufficient. It also offers ample practical guidance for similar cases in China and elsewhere.

The purpose of this study is to explore the evolutionary path and stable strategy for the competitive dissemination between disinformation and knowledge on social media to provide effective solutions to curb the dissemination of disinformation and promote the spread of knowledge.

Based on the social capital (SC) theory, the benefit matrix is constructed and an evolutional game model is established in this paper. Through model solving and Matrix Laboratory (MATLAB) simulation, the factors that influence disinformation-believing users (DUs) and knowledge-believing users (KUs) to choose different strategies are analyzed.

The initial dissemination willingness, the disinformation infection probability, the knowledge infection probability and the knowledge penetration probability are proved to be crucial factors influencing the game equilibrium in the competitive dissemination process of disinformation and knowledge. Moreover, some countermeasures and recommendations for the governance of disinformation are proposed.

Currently most research interest lies in the disinformation dissemination model but ignores the interaction between disinformation and knowledge in the diffusion process. This study reveals the dynamic mechanism of social media users disseminating disinformation and knowledge and is expected to promote the formation of cleaner cyberspace.

This paper aims to anticipate the possible development direction of WAAM. For large-scale and complex components, the material loss and cycle time of wire arc additive manufacturing (WAAM) are lower than those of conventional manufacturing. However, the high-precision WAAM currently requires longer cycle times for correcting dimensional errors. Therefore, new technologies need to be developed to achieve high-precision and high-efficiency WAAM.

This paper analyses the innovations in high-precision WAAM in the past five years from a mechanistic point of view.

Controlling heat to improve precision is an effective method. Methods of heat control include reducing the amount of heat entering the deposited interlayer or transferring the accumulated heat out of the interlayer in time. Based on this, an effective and highly precise WAAM is achievable in combination with multi-scale sensors and a complete expert system.

Therefore, a development direction for intelligent WAAM is proposed. Using the optimised process parameters based on machine learning, adjusting the parameters according to the sensors’ in-process feedback, achieving heat control and high precision manufacturing.

Because of the nature of their work, frontline service employees are highly exposed to customer incivility (CI) and are required to perform surface acting (SA) in such circumstances. Both CI and SA have detrimental impact to a sustainable workforce. This study aims to investigate the psychological effects of CI and SA on emotional exhaustion (EE), organizational commitment (OC) and work–family conflict (WFC).

Data from 203 respondents who successfully completed the questionnaire is used for the analysis. Structural equation modelling and bootstrapping were performed to investigate the relationship among variables.

The study found that both CI and SA are positively related to EE. EE is negatively related to OC and positively related to WFC. EE was engaged as a mediator between CI and OC, and between CI and WFC. EE also served as a mediator between SA and OC, and between SA and WFC.

The findings advanced our knowledge of the impact of CI and SA on EE, OC and WFC. Based on the findings, theoretical and practical implications are discussed.