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The purpose of this paper is to examine the macroscopic and microscopic fields of fiber suspensions in the non‐isothermal situations, also to examine the effect of fiber on this non‐isothermal system.

Control equations are coupled and simultaneously solved by collocated finite volume method on fully triangular meshes.

Temperature dependence and wall temperature have significant effect on both macroscopic and microscopic fields of fiber suspensions. Moreover, the influence of fiber on the non‐isothermal system is similar to that of the isothermal system.

This is the first time that the microstructures of both molecules and fibers are presented in the non‐isothermal condition and it is hoped that the results will provide more insight into the microscopics of complex flows.

Food quality and safety issues have always been imperative topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality. How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

The paper aims to analyze the differences in product quality levels and market participants’ profits before and after the use of blockchain-driven traceability technology in the food agricultural product supply chain (SC) in the dynamic game frameworks of supplier-led and retailer-led modes, respectively, and explores the willingness, social welfare and consumer surplus of each member of the agricultural product SC to participate in the blockchain. Besides, We investigate the SC performance improvement with the mechanism of central centralized decision-making and revenue-sharing contract, compared to the SC performance in dynamic games.

The results are obtained as follow: The adoption of blockchain traceability technology can help improve the quality of food agricultural products, consumer surplus and social welfare, but the application and popularization of technology is hindered by traceability technology installment costs. Compared with the supplier leadership model, retailer-led food quality level, customer surplus and social welfare are higher.

How to effectively apply blockchain traceability technology to food safety has great research significance for improving food safety and consumer quality trust.

Food quality and safety issues have always been hot topics discussed by people. The anti-tampering of blockchain technology and the transparency of information make it possible to improve food traceability and safety quality.

The research results enrich the theories related to food safety and quality, and provide a valuable reference for food enterprises involved in the decision-making exploration of blockchain technology.

Based on the characteristics of blockchain technology, the demand function is adjusted and the product loss risk of channel members is transferred through a Stackelberg game SC composed of agricultural products suppliers and retailers.

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  We introduce two features of blockchain: quality trust and product information tracking.

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  The willingness of each member of the supply chain to use blockchain for product traceability was explored.

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  The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

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  The cost of blockchain technology is a barrier to its adoption.

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  Blockchain brings higher consumer surplus and social welfare.

We introduce two features of blockchain: quality trust and product information tracking.

The willingness of each member of the supply chain to use blockchain for product traceability was explored.

The overall traceability effect of the retailer-led blockchain is better than that of the manufacturer-led blockchain.

The cost of blockchain technology is a barrier to its adoption.

Blockchain brings higher consumer surplus and social welfare.

Online reviews are regarded as a source of information for decision-making because of the abundance and ready availability of information. Whereas, the sheer volume of online reviews makes it hard for consumers, especially the older adults who perceive more difficulties in reading reviews and obtaining information compared to younger adults, to locate the useful ones. The main objective of this study is to propose an effective method to locate valuable reviews of mobile phones for older adults. Besides, the authors also want to explore what characteristics of the technology older adults prefer. This will benefit both e-retailers and e-commerce platforms.

After collecting online reviews related to mobile phones designed for older adults from a popular Chinese e-commerce platform (JD Mall), topic modeling, term frequency-inverse document frequency (TF-IDF), and linguistic inquiry and word count (LIWC) methods were applied to extract latent topics and uncover potential dimensions that consumers frequently referred to in their reviews. According to consumers' attitudes towards different popular topics, seven machine learning models were employed to predict the usefulness and popularity of online reviews due to their excellent performance in prediction. To improve the performance, a weighted model based on the two best-performing models was built and evaluated.

Based on the TF-IDF, topic modeling, and LIWC methods, the authors find that older adults are more interested in the exterior, sound, and communication functions of mobile phones. Besides, the weighted model (Random Forest: Decision Tree = 2:1) is the best model for predicting the online review popularity, while random forest performs best in predicting the perceived usefulness of online reviews.

This study’s findings can help e-commerce platforms and merchants identify the needs of the targeted consumers, predict reviews that will get more attention, and provide some early responses to some questions.

The results propose that older adults pay more attention to the mobile phones' exterior, sound, and communication function, guiding future research. Besides, this paper also enriches the current studies related to making predictions based on the information contained in the online reviews.

In order to find a way to combine traditional culture with modern living needs, taking “Chinese painting” as the breakthrough point, through the study of the development process and artistic characteristics of Chinese painting, four aspects of classical philosophy, natural landscape image, brush and ink composition artistic conception, and abstract aesthetic conception contained in Chinese painting are summed up. The results of the study provide enlightenment for contemporary residential landscape design, and summarize the methods of creating Chinese paintings in residential landscape design. Thus, a residential landscape model with the characteristics of “Chinese painting” is found out.

The final effectiveness of employee voice largely depends on voice endorsement. This study aims to review, assess, analyze and synthesize the emerging literature on voice endorsement by focusing on its antecedents to promote future research from a comprehensive perspective.

Based on an integrative review of the literature, the authors conducted a content analysis of 53 peer-reviewed journal articles.

Building on the Shannon–Weaver communication model, this paper summarizes that factors influencing voice endorsement can be classified into five prominent aspects: voicer, voiced idea, contextual factors and noises, voice channel (medium) and voice receiver.

This research holds important implications for practice, providing practical guidelines for employees to speak up, for leaders to endorse voice and for organizations to maintain sustainable development by making full use of employee voice.

This review enriches voice endorsement research by introducing a communication framework to synthesize its antecedents and extends the application of the communication model in organization research. Additionally, the authors offer directions for future research.

Involvement plays a crucial role in understanding consumer behavior. In recent years, the concept of social innovation has gained momentum, resulting in the development of eco-friendly products and initiatives to tackle societal issues. This trend is driven by consumers, who are increasingly aware of the social benefits of the products they buy. The present study aims to investigate how socially innovative, environmentally conscious consumers can influence their engagement with eco-friendly products.

Researchers aimed to investigate the “impact of social innovation on involvement in environmentally friendly products.” They selected active members of various environmental organizations operating in the country to conduct the study. Convenience sampling was used to reach out to these members, and the managers of these organizations sent an electronic questionnaire to all members' email addresses.

The study found that socially innovative, environmentally conscious consumers tend to be more interested in the symbolic meaning and pleasure of products, leading to a decrease in perceived risk and risk importance.

There are limited studies examining the relationship between social innovation and product innovation. Therefore, the novelty of this research lies in its exploration of the relationship between these two concepts. Unlike previous studies, this research found a negative relationship between the dimensions of risk importance and risk probability. This result was interpreted as environmentally friendly products being sensitive to public welfare and not being perceived as risky by environmentalists.

Despite the increasing use of home delivery (HD) in e-commerce, no studies have explicitly examined consumer perceptions of the convenience of the last-mile delivery of goods by cargo bike (CB). Therefore, this study aims to identify the dimensions of HD convenience and to develop a reliable and valid measurement tool, namely the Home-Delivery Convenience via Cargo Bike (HDCCB) scale.

The methodology of this scale development study is premised on a review of the existing literature, which identifies differences in consumer perceptions of the convenience of services. The authors conducted semi-structured interviews with 10 online consumers and validated the content with 3 experts on marketing in the retail and services sectors in order to develop the items for the scale. Thereafter, the authors identified the main dimensions through an exploratory factor analysis that the authors applied to an online survey with 116 respondents. Finally, the scale was validated through a confirmatory factor analysis of an online survey with 300 respondents.

Following the original work of Brown (1990), the authors define consumer perceptions of HD convenience as a multidimensional construct and measure each facet of its four dimensions, which are time, use, execution and acquisition. E-retailers and last-mile logistics providers could use the authors' proposed measurement tool to assess consumer perceptions of the convenience of HD. That assessment could generate a competitive advantage.

This study is original as the study deepens the existing understanding of consumer perceptions of the convenience of HD by CB in last-mile logistics. This study also develops a multidimensional measure that is based on an empirical study.

The purpose of this paper is to present research in detecting and identifying abrupt faults in controlled auto‐regressive (CAR) processes.

Model‐based approach is adopted in this paper. Two series of fault‐tolerant iterative estimators are set up to estimate online the coefficients in a CAR process. Based on these fault‐tolerant estimators, the detailed detecting and identifying algorithms are obtained for not only the pulse‐type faults but also the step‐type faults in CAR process.

This paper illustrates the useful information that can be obtained from residuals and that can be used to detect pulse‐type faults as well as step‐type faults. A fault‐tolerant recursive estimator for the coefficients of the CAR process is put forward. Using a simple transformation from step‐ to pulse‐type faults, all kinds of diagnosis methods to detect and identify step‐type faults can be used.

Fault‐tolerant estimators and fault detection and identification algorithms are aimed at abrupt faults in CAR processes.

Most of the algorithms given in this paper can be used in many different fields, such as process monitoring, safety control and change detection, etc.

This paper contributes to research of abrupt faults and abrupt changes in a CAR process and emphasizes identification of magnitudes of abrupt faults. The fault‐tolerant estimators are effective not only to detect faults but also to identify safely the coefficients CAR model.

This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.

Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.

The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.

The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.