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This study aims to investigate the micro mechanism of macro rheological characteristics for composite modified asphalt.Grey relational analysis (GRA) was used to analyze the correlation between macro rheological indexes and micro infrared spectroscopy indexes.

First, a dynamic shear rheometer and a bending beam rheometer were used to obtain the evaluation indexes of high- and low-temperature rheological characteristics for asphalt (virgin, SBS/styrene butadiene rubber [SBR], SBS/rubber and SBR/rubber) respectively, and its variation rules were analyzed. Subsequently, the infrared spectroscopy test was used to obtain the micro rheological characteristics of asphalt, which were qualitatively and quantitatively analyzed, and its variation rules were analyzed. Finally, with the help of GRA, the macro-micro evaluation indexes were correlated, and the improvement efficiency of composite modifiers on asphalt was explored from rheological characteristics.

It was found that the deformation resistance and aging resistance of SBS/rubber composite modified asphalt are relatively good, and the modification effect of composite modifier and virgin asphalt is realized through physical combination, and the rheological characteristics change with the accumulation of functional groups. The correlation between macro rutting factor and micro functional group index is high, and the relationship between macro Burgers model parameters and micro functional group index is also close.

Results reveal the basic principle of inherent-improved synergistic effect for composite modifiers on asphalt and provide a theoretical basis for improving the composite modified asphalt.

Benefiting from the development and innovation of artificial intelligence and affective computing technology, social chatbots that integrate cognitive analysis and affective social services have flooded into the consumer market. For cognition and emotion-oriented tasks, social chatbots do not always receive positive consumer responses. In addition, consumers have a contradictory attitude toward the anthropomorphism of chatbots. Therefore, from the perspective of mind perception and the two dimensions of social judgment, this research explores the mechanism of consumer responses to anthropomorphic interaction styles when social chatbots complete different service tasks.

This paper utilizes three behavior experimental designs and survey methods to collect data and the ANOVA, t-test and bootstrap analysis methods to verify the assumed hypotheses.

The results indicate that when the service task type of a social chatbot is cognition-oriented, compared to a warm anthropomorphic interaction style, a competent anthropomorphic interaction style can improve consumer responses more effectively. During this process, agent-mind perception plays a mediating role. When the service task type of a social chatbot is emotion-oriented, compared with a competent anthropomorphic conversation style, a warm anthropomorphic conversation style can improve consumer responses. Experience-mind perception mediates this influencing relationship.

The research results theoretically enrich the relevant research on the anthropomorphism of social chatbots and expand the application of the theory of mind perception in the fields of artificial intelligence and interactive marketing. Our findings provide theoretical guidance for the anthropomorphic development and design of social chatbots and the practical management of service task scenarios.

Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers.

We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers.

The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers.

This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

The study examines the impact of various aspects of channel integration quality, personalisation and perceived warmth on behavioural outcomes through customer engagement in omnichannel retailing.

This study is based on the responses of 458 participants, gathered using purposive and snowball sampling methods. PLS-SEM and FIMIX-PLS have been used to examine the heterogeneity in respondents’ views.

The findings emphasise the favourable influence of various facets of omnichannel strategy on customer engagement, which enhances brand affection, leading to stickiness and willingness to pay price premium. Furthermore, identifying three separate customer categories provides detailed insights into how omnichannel aspects appeal to consumer preferences.

The findings underscore the need to use customised approaches to cultivate lasting relationships with consumers, emphasising the potential of omnichannel retailing in harmonising business success and consumer sentiments. Retailers can identify areas of dissatisfaction within specific segments and eventually focus on improving these areas to provide a seamless experience and increase engagement.

This paper offers a distinctive contribution to the domain of omnichannel retailing by employing structural equation modelling (SEM) along with FIMIX-PLS to explore respondent heterogeneity. In addition to the transactional aspects, this study investigates the crucial elements, including warmth and personalisation strategies and how these influence the holistic customer journey, including their emotional connection with the brand in the omnichannel retailing environment, thereby advancing knowledge in the field and providing relevant implications for industry practice.

This paper aims to explore the effect of teacher–student collaboration on academic innovation in universities in different stages of collaboration.

Based on collaboration life cycle, this paper divided teacher–student collaboration into initial, growth and mature stages to explore how teacher–student collaboration affects academic innovation.

Collecting data from National Science Foundation of China, the empirical analysis found that collaboration increases the publication of local (Chinese) papers at all stages. However, teacher–student collaboration did not significantly improve the publication of international (English) papers in the initial stage. In the growth stage, teacher–student collaboration has a U-shaped effect on publishing English papers, while its relationship is positive in the mature stage.

The results offer suggestions for teachers and students to choose suitable partners and also provide some implications for improving academic innovation.

This paper constructed a model in which the effect of teacher–student collaboration on academic innovation in universities was established.

This study provides a comprehensive overview of the research landscape of Kansei engineering (KE) within the domain of emotional clothing design. It explores the pivotal technologies, challenges and potential future directions of KE, offering application methodologies and theoretical underpinnings to support emotional clothing design.

This study briefly introduces KE, outlining its overarching research methodologies and processes. This framework lays the groundwork for advancing research in clothing Kansei. Subsequently, by reviewing literature from both domestic and international sources, this research initially explores the application of KE in the design and evaluation of clothing products as well as the development of intelligent clothing design systems from the vantage point of designers. Second, it investigates the role of KE in the customization of online clothing recommendation systems and the optimization of retail environments, as perceived by consumers. Finally, with the research methodologies of KE as a focal point, this paper discusses the principal challenges and opportunities currently confronting the field of clothing Kansei research.

At present, studies in the domain of clothing KE have achieved partial progress, but there are still some challenges to be solved in the concept, technical methods and area of application. In the future, multimodal and multisensory user Kansei acquisition, multidimensional product deconstruction, artificial intelligence (AI) enabling KE research and clothing sales environment Kansei design will become new development trends.

This study provides significant directions and concepts in the technology, methods and application types of KE, which is helpful to better apply KE to emotional clothing design.

This study aims to investigate the impact of ResearchGate (RG) scores on the scientific indicators of Qur’anic productions in Scopus.

This research is fundamental in method, created in a descriptive method and a scientometric approach. The statistical society includes 4,105 records produced by writers in the field of Qur’an during the time period of 2011–2020 indexed in the Scopus database. In this study, Pearson correlation coefficient test is used with aid of Excel and SPSS software.

Countries such as Malaysia, the USA and Indonesia, respectively, hold the highest number of scientific productions in the field of Qur’an. Iran holds the fourth place with a 544 record difference in comparison to Malaysia (866 documents). There is a positive and meaningful relation between measures of RG, readers, followers, citations and the H-index score regarding writers with received citations and the H-index score of scientific productions in the field of Qur’an in Scopus. However, no relation can be observed between the mentioned measures and indicators of the number of documents with cowriting.

Because of some authors not using the same name in their articles, it was not possible to access their profile in RG. For this reason, the information of these authors was not accessible in RG.

The activity of researchers in social networks will receive feedback from readers. This will result in more citations. Contrary to expectations, the research results showed that Iran does not have a good position in publishing Qur’anic works. Therefore, researchers should publish their findings in international journals.

Iranian writers should try to publish their scientific productions in international publications and also widely spread their content and research results across social networks to increase feedback and gain the attention of readers. This process leads to receiving reader feedback and publication of the Islamic teachings.

The relationship between the number of citations of Qur’anic works in Scopus and altmetric indicators in RG has not been investigated in previous researches. Therefore, this research is innovative in this field.

The purpose of this study is to explore the interplay between the selection of selling formats of remanufactured products for a third-party remanufacturer (TPR) and the quality decision of an original equipment manufacturer (OEM).

This study considers a remanufacturing supply chain, where the OEM sells new products through a platform retailer, but the products remanufactured by the TPR can be sold via a direct or indirect channel. The authors model a Stackelberg game and explore the optimal quality decision of the OEM and selling format choice of the TPR.

The OEM's optimal decision depends mainly on consumers' discounted utility coefficient and cost-scale factor of remanufactured products. A higher consumers' valuation of the remanufactured product will not result in a higher retail price, but may lead to an increase in new product's sales. Given the cost-scale factor, the TPR prefers to sell directly no matter what the value of consumers' discounted utility coefficient is. An all-win situation is achieved with selling directly when consumers' discounted utility coefficient is sufficiently large.

These results provide some support to the operational strategies of the OEM and TPR.

This study firstly endogenizes the quality decision and combines the selling format selection of the TPR and the quality decision of the OEM to explore the interplay between these two important decisions.

Improving the diversity of recommendation information has become one of the latest research hotspots to solve information cocoons. Aiming to achieve both high accuracy and diversity of recommender system, a hybrid method has been proposed in this paper. This study aims to discuss the aforementioned method.

This paper integrates latent Dirichlet allocation (LDA) model and locality-sensitive hashing (LSH) algorithm to design topic recommendation system. To measure the effectiveness of the method, this paper builds three-level categories of journal paper abstracts on the Web of Science platform as experimental data.

(1) The results illustrate that the diversity of recommended items has been significantly enhanced by leveraging hashing function to overcome information cocoons. (2) Integrating topic model and hashing algorithm, the diversity of recommender systems could be achieved without losing the accuracy of recommender systems in a certain degree of refined topic levels.

The hybrid recommendation algorithm developed in this paper can overcome the dilemma of high accuracy and low diversity. The method could ameliorate the recommendation in business and service industries to address the problems of information overload and information cocoons.

Previous studies have rarely integrated the financing modes of a capital-constrained manufacturer with the choices of online sales strategies. To address this gap, the authors study how a manufacturer selects optimal financing modes under different sales strategies in three dual-channel supply chains.

This paper considers three sales strategies, namely, combining a traditional retailer channel with one of the direct selling, reselling and agency selling channels, and two common financing modes, namely, bank financing and retailer financing. The authors obtain equilibrium outcomes of the manufacturer and traditional retailer and then provide the conditions for them to select optimal financing modes under three sales strategies.

The results indicate that the manufacturer’s financing decisions rely on the initial capital and interest rates, and the manufacturer selects retailer financing only if the initial capital is relatively larger. In terms of financing mode options, the retailer financing mode is more beneficial for the manufacturer under the three sales strategies. From the perspective of sales strategies, the direct selling model is more beneficial. In addition, the higher the consumer acceptance of the online channel, the more profits the manufacturer obtains.

This paper provides suggestions on how the capital-constrained manufacturer chooses financing modes and sales strategies.

This paper integrates the financing mode and different sales strategies to investigate the manufacturer’s optimal operational decisions. These sales strategies allow us to investigate the manufacturer’s optimal financing modes in the presence of both different financing modes and sales strategies.