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Establishing and developing digital science and education evaluation platforms (DSEEPs) have several practical implications for the development of China's science, technology and education. Identifying and analyzing the key factors influencing DSEEP user experience (UX) can improve the users' willingness to use the platform and effectively promote its sustainable development.

First, a literature survey, a five-element model of UX and semi-structured interviews were used in this study to develop a DSEEP UX-influencing factor model, which included five dimensions and 22 influencing factors. Second, the model validity was verified using questionnaire data. Finally, the key influencing factors were identified and analyzed using a fuzzy decision-making trial and evaluation laboratory (fuzzy-DEMATEL) method.

Fourteen influencing factors, including diverse information forms and comprehensive information content, are crucial for the DSEEP UX. Its optimization path is “‘Function Services’ → ‘Information Resources’ → ‘Interaction Design’ → ‘Interface Design’ and ‘Visual Design’.” In this regard, platform managers can take the following measures to optimize UX: strengthening functional services, improving information resources, enhancing the interactive experience and considering interface effects.

This study uses a combination of qualitative and quantitative research methods to determine the key influencing factors and optimization path of DSEEP UX. Optimization suggestions for UX are proposed from the perspective of platform managers, who provide an effective theoretical reference for innovating and developing a DSEEP.

While prior studies have explored the relationship between visual appeal and purchasing decisions, the role of bookmarking has largely been underemphasized. This research aims to address this gap by focusing on the impact of bookmarking on consumer behavior, guided by the cognitive load theory and dual-system theory.

The authors executed a controlled experiment and analyzed the results using a two-stage regression method that linked visual appeal, bookmarking and purchase intent. Further empirical analysis was conducted to authenticate the authors' proposed model, utilizing real-world mobile commerce data from a clothing company.

This study's findings suggest that visual appeal influences purchase intent primarily through the full mediation of bookmarking, rather than exerting a direct influence. Furthermore, an increase in colorfulness corresponds positively with visual appeal, while visual complexity exhibits an inverted U-shaped relationship with it.

This study provides novel insights into the choice-set formation process through the theoretical lens of dual-system theory. Additionally, the authors employed an image processing technique to quantify a product's visual appeal as depicted in a photograph. This study also incorporates a comprehensive econometric analysis to connect the objective aspects of visual appeal with subjective responses.

Social media has emerged as a prominent platform for marketers and brands to disseminate brand-related information. This study aims to investigate the impact of color congruence between themes and background on marketing effectiveness, focusing specifically on Instagram.

A laboratory experiment was conducted to investigate how color congruence between themes and background in brand posts influences flow and aesthetic experience, subsequently affecting marketing communication parameters such as brand attitude, visit intention, and eWOM on Instagram. Moreover, Adidas Originals was selected as the focal brand, and blue and white color was chosen as the primary color palette for the experimental material.

This study demonstrates that color congruence, regardless of brand layout or post, significantly influences flow and aesthetic experience, subsequently affecting marketing effectiveness.

This study contributes to the theoretical understanding of congruence theory and social media marketing, providing valuable insights for brands to enhance their communication through photographs and effectively manage their official Instagram accounts.

Design Science (DS) is a relatively new paradigm for addressing complex real-world problems through the design and evaluation of artifacts. Its constituent methodologies are currently being discussed and established in numerous related research fields, such as information systems and management (Hevner et al., 2004). However, a DS methodology that describes the “how to” is largely lacking, not only in the field of OM but in general. The Theory of Constraints (TOC) and its underlying thinking processes (TP) have produced several novel artifacts for addressing ill-structured real-world operations problems (Dettmer, 1997; Goldratt, 1994), but they have not been analyzed from a DS research standpoint. The purpose of this research is to demonstrate how TOC’s thinking process methodology can be used for conducting exploratory DS research in Operations and Supply Chain Management (OSCM).

A case study of spare parts replenishment illustrates the use of TOC’s thinking processes in DS to structure an initially unstructured problem context and to facilitate the design of a novel solution.

TOC’s thinking processes are an effective methodology for problem-solving DS research, enabling the development of novel solutions in initially unstructured and wicked problem situations. Combined with structured CIMO design logic TOC’s thinking process offers a systematic method for exploring wicked problems, designing novel solutions, and demonstrating theoretical contributions.

The implication for research is that TOC’s thinking process methodology can provide important elements of the lacking “how to” methodology for DS research, not only for the field of OM but in general for the field of management.

The practical outcome of the research is a novel design for dynamic buffer-based replenishment that extends beyond organizational boundaries.

This work shows how the thinking processes can be used in DS research to develop rigorous design propositions for ill-structured problems.

This research explores the impact of classical aesthetics (e.g. order and symmetry) and expressive aesthetics (e.g. creativity and distinctiveness) on consumer green consumption.

This research conducted three studies. Study 1 explored the main effect of appearance aesthetics (appearance: plain vs classical vs expressive) on green products purchase intention through a one-factor between-subjects design. Study 2 verified the mediating role of perceived naturalness through two types of appearance aesthetics (appearance: classical vs expressive) between-subjects design. Study 3 verified the moderating role of product identity-symbolic attributes through a 2 (product identity-symbolic attributes: non-identity-symbolic vs identity-symbolic attributes) × 2 (appearance: classical aesthetics vs expressive aesthetics) between-subjects design.

Consumers will be more likely to purchase a green product that has classical aesthetics appearance (vs expressive aesthetics). Perceived naturalness mediates the effect of aesthetic appearance on consumer green consumption. Product identity symbol attributes moderate this effect. Specifically, for non-identity-symbolic green products, classical aesthetics can effectively enhance consumer purchase intention. For identity-symbolic green products, expressive aesthetics can effectively enhance consumer purchase intention.

Existing research suggests that aesthetic appearance can increase consumers’ evaluation of electronic products, beauty products and food, but the difference between aesthetics has not yet been explored. This research compares two aesthetics, contributing to the literature on aesthetic appearance in green products and offering valuable insights for managers’ green products marketing.

This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.

A new data augmentation approach that has improved the model robustness against different illumination conditions and overfitting is proposed. This study uses data augmentation at test time and adds outlier samples to training set to prevent over-fitted network training. For data augmentation at test time, five segments are extracted from each sample image and fed to the network. For these images, the network outputting average values is used as the final prediction. Then, the proposed approach is evaluated on multiple deep networks used as material classifiers. The fully connected layers are removed from the end of the networks, and only convolutional layers are retained.

The proposed method is evaluated on recognizing 11 types of building materials which include 1,231 images taken from several construction sites. Each image resolution is 4,000 × 3,000. The images are captured with different illumination and camera positions. Different illumination conditions lead to trained networks that are more robust against various environmental conditions. Using VGG16 model, an accuracy of 97.35% is achieved outperforming existing approaches.

It is believed that the proposed method presents a new and robust tool for detecting and classifying different material types. The automated detection of material will aid to monitor the quality and see whether the right type of material has been used in the project based on contract specifications. In addition, the proposed model can be used as a guideline for performing quality control (QC) in construction projects based on project quality plan. It can also be used as an input for automated progress monitoring because the material type detection will provide a critical input for object detection.

Several studies have been conducted to perform quality management, but there are some issues that need to be addressed. In most previous studies, a very limited number of material types were examined. In addition, although some studies have reported high accuracy to detect material types (Bunrit et al., 2020), their accuracy is dramatically reduced when they are used to detect materials with similar texture and color. In this research, the authors propose a new method to solve the mentioned shortcomings.

This paper aims to identify and analyze the challenges for the Varanasi handloom industry after the COVID pandemic by considering their impact on different sections of the weavers and subsequently suggest the best possible solution for the same.

A combined approach of expert opinion and in-depth literature reviews are used to identify the challenges, and a multicriteria decision-making tool is used to rank the challenges for the type of weaver.

This research provides an elaborated view of the problems faced by the handloom industry after the COVID pandemic and suggests that the success of the handloom business is subjected to the eradication of a wide number of challenges according to the type of weaver.

The findings of this research will help the policymakers to make and align their policies and strategies for the upliftment of the Varanasi handloom industry efficiently and effectively.

To the best of the authors’ knowledge, this is the first kind of study that focuses on identifying and prioritizing the barriers affecting the success of the Varanasi handloom industry after the COVID pandemic. Furthermore, the uniqueness of this research lies in its ability to study all three independent sections of the handloom industry, having different capabilities and limitations.

Agricultural waste and food sources are some of the pollutants of the environment. One of these wastes is the peel of fruits that cannot be consumed as food. In this regard, walnut husk (WH) and oleaster peel (PO) are known as two important sources of tannin and are bulky wastes. Because of the high percentage of tannin, these materials can be used as a natural source for the preparation of bio-mordant in the dyeing process.

In this study, Reseda and Madder were used as natural dyes in the presence of a mixture of two bio-mordants. WH and PO were selected as bio-mordant. All natural resources are extracted to obtain the juice. The phenolic percentage of tannin-containing extracts was evaluated and then it was used for wool yarns by premordanting method. The results of evaluating the fastness properties using the ISO method.

The most important achievement of this research is the use of agricultural waste in the dyeing process to reduce environmental pollution and create added value. All compounds rich in tannin have some phenolic components, therefore the amount of phenolic content of these extracts was evaluated. The effect of mixing the mordant on the color characteristics of the yarns was investigated and the results showed that changing the ratio of the combination of two mordant is effective on the K/S values. The results of evaluating the fastness properties using the ISO method showed that the washing, rubbing and light fastness in the presence of mordant is good, good and moderate, respectively.

In this paper, to the best of the authors’ knowledge, for the first time, the combination of two natural extracts obtained from agricultural waste has been used to create a new bio-mordant on fibers and improve stability.

The South African wool industry is integral to the country's agricultural sector, particularly sheep farming and wool production. Small-scale farmers play a vital role in this industry and contribute to employment and food security in rural communities. However, these farmers face numerous challenges, including a lack of funding, poor farming practices and difficulty selling their wool at fair prices. This study aims to address these challenges, the University of Free State launched a wool value chain project for small-scale farmers.

In this project, one of the studies conducted assessed the effectiveness of different detergents suitable for traditional wool scouring methods for small-scale farmers who lack access to sophisticated machinery. The investigation was conducted by scouring 160 wool samples using three different detergents and filtered water as a control. The wool samples were then evaluated for their cleanliness, brightness and fibre properties through a combination of scanning electron microscopy, spectrophotometry and statistical analysis at different scouring times (3, 10, 15 and 20 min, respectively).

The results showed that the combination of scouring time and the type of scouring solution used could significantly impact wool quality. It was found that using a combination of standard detergent or Woolwash as a scouring solution with a scouring time of 10–15 min resulted in the best outcome in terms of fibre property, wool colour and scouring loss.

This study demonstrated that traditional wool scouring methods could be an option for small-scale farmers and anyone who want to learn how to scour wool without expensive machinery to make wool products.

Using the stimulus–organism–response (SOR) theoretical model, this empirical research aims to examine and validate how tourists’ interactions with 360-degree virtual reality (VR) videos incorporating Web navigability and visual interface design quality (stimulus) on travel websites can make tourists more engaged and then satisfied (organism), which could make them more likely to visit destinations and spread electronic word of mouth (e-WOM) (response).

Using the convenience sampling method, 975 responses were collected through a questionnaire. The data were analysed using Smart-PLS 4 software to investigate the hypothesised relationships.

The findings demonstrate that 360-degree VR videos significantly create Web user engagement, and Web user engagement is significantly associated with Web user satisfaction. The result shows that Web user engagement and satisfaction impact the intention to visit the tourist destination. Additionally, Web user satisfaction impacts e-WOM. Lastly, navigability and visual interface design quality are significantly moderated between 360-degree VR videos and Web user engagement.

This research only examined the tourists’ behavioural intentions with 360-degree VR videos during the pre-travel phase. In contrast, future research may investigate how tourists behave with VR during the on-site and post-travel phases.

Tourism marketers should not only adopt 360-degree VR but also integrate Web navigability and visual interface design to boost Web users’ engagement on tourism websites.

This study advances the study of VR from the tourists’ psychological perspective. Moreover, the SOR theory has been re-examined from the VR and technology tourism perspectives. It provides a general understanding of the behavioural aspects of tourists in developing countries.

利用刺激-有机体反应（SOR）理论模型, 本实证研究检验并验证了游客与旅游网站上结合了网络导航性和视觉界面设计质量（刺激）的360度虚拟现实(VR)视频的互动如何使游客更投入、更满意（有机体）, 这可能使他们更有可能访问目的地并传播电子口碑（响应）。

采用方便抽样法, 通过问卷调查收集了975份回复。使用Smart-PLS 4软件对数据进行分析, 以调查假设的关系。

研究结果表明, 360度虚拟现实(VR)视频显著提高了网络用户参与度, 网络用户参与与网络用户满意度显著相关。结果表明, 网络用户参与度和满意度对旅游目的地的访问意愿有影响。此外, 网络用户满意度也会影响电子口碑。最后, 在360度虚拟现实(VR)视频和网络用户参与度之间, 导航性和视觉界面设计质量显著适中。

这项研究只考察了游客在旅行前阶段使用360度虚拟现实(VR)视频的行为意图。相比之下, 未来的研究可能会调查游客在现场和旅行后阶段使用虚拟现实(VR)的行为。

旅游营销人员不仅应采用360度虚拟现实(VR), 还应将网络导航性和视觉界面设计相结合, 以提高网络用户对旅游网站的参与度。

本研究从游客的心理角度推进了虚拟现实(VR) 的研究。此外, 还从虚拟现实(VR)和科技旅游的角度重新审视了SOR 理论。它提供了对发展中国家游客行为方面的一般了解。

Utilizando el modelo teórico estímulo-organismo-respuesta (SOR), esta investigación empírica examinó y validó cómo las interacciones de los turistas con los vídeos de RV de 360 grados que incorporan la navegabilidad web y la calidad del diseño de la interfaz visual (estímulo) en los sitios web de viajes pueden hacer que los turistas se sientan más comprometidos y luego satisfechos (organismo), lo que podría hacerles más propensos a visitar los destinos y a difundir el e-WOM (respuesta).

Utilizando el método de muestreo por conveniencia, se recogieron 975 respuestas a través de un cuestionario. Los datos se analizaron mediante el software Smart-PLS 4 para investigar las relaciones hipotetizadas.

Los resultados demuestran que los vídeos de RV de 360 grados generan un compromiso significativo de los usuarios de la web y que el compromiso de los usuarios de la web se asocia significativamente con su satisfacción. El resultado muestra que el compromiso y la satisfacción del usuario web repercuten en la intención de visitar el destino turístico. Además, la satisfacción del usuario web influye en el e-WOM. Por último, la navegabilidad y la calidad del diseño de la interfaz visual son significativamente moderadas entre los vídeos de RV de 360 grados y el compromiso del usuario web.

Esta investigación sólo examinó las intenciones de comportamiento de los turistas con los vídeos de RV de 360 grados durante la fase previa al viaje. En cambio, en futuras investigaciones se podría estudiar cómo se comportan los turistas con la RV durante las fases in situ y posterior al viaje.

Los profesionales del marketing turístico no sólo deberían adoptar la RV de 360 grados, sino también integrar la navegabilidad web y el diseño de la interfaz visual para potenciar el compromiso de los internautas en los sitios web turísticos.

Este estudio avanza en el estudio de la RV desde la perspectiva psicológica del turista. Además, se ha reexaminado la teoría S-O-R desde las perspectivas de la RV y el turismo tecnológico. Proporciona una comprensión general del aspecto conductual de los turistas en los países en desarrollo.