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This paper aims to collect the energy consumption data and carry out energy consumption analysis of chemical enterprises, which is helpful to grasp the working conditions of each equipment accurately and to perfect the demand side management (DSM) for the user in the terminal.

The paper proposes a load monitoring system of chemical enterprises to collect the energy consumption data and carry out energy consumption analysis. An Elman neural network based on sparrow search algorithm is proposed to predict the power consumption change and distribution trend of enterprises in the future production cycle. The calculation efficiency and prediction accuracy have been significantly improved.

The paper analyzes the energy saving effect of energy efficiency management as well as “avoiding peak and filling valley” measures, and reasonable control requirements and assumed conditions are put forward to study the operability of enterprise energy saving measures from the DSM.

Because of the chosen enterprise data, the prediction accuracy needs to be further improved. Therefore, researchers are encouraged to test the proposed methodology further.

The paper includes implications for the development of energy consumption analysis and load forecasting of chemical enterprises and perfects the DSM for the user.

This paper fulfills an identified need to study how to forecast the power load and improve the management efficiency of energy consumption.

This study reveals the trigger of innovative behavior from the perspective of intrinsic and extrinsic spiritual inspiration and provides a new research idea for the formation mechanism of innovative behavior. The purpose of this study is to provide certain guidance and implications for enterprises to cultivate and enhance employees’ innovative behavior.

We conducted three studies, collected multi-source data (N = 1,175) from different countries longitudinally, as well as used hierarchical regression analysis and fuzzy-set quantitative comparative analysis to verify the theoretical model.

According to the findings, both spiritual leadership and career calling have a positive impact on employees’ innovative behavior through the mediating effect of autonomous motivation and the moderating effect of person-vocation fit.

Innovative behavior is the positive professional pursuit of employees, which is difficult to form without the motivation of spiritual factors. Spirituality is a complex concept that contains intrinsic and extrinsic spiritual factors, both of which could stimulate employees’ innovative behavior. Although many discussions have been held on this topic in recent years, little attention has been paid simultaneously to the motivating effects of the two perspectives. Drawn from self-determination theory, this study explores the mechanisms of two spiritual motivation paths (i.e. the intrinsic and extrinsic spiritual motivation paths) in the improvement of employees’ innovative behavior.

Hanfu has been the Han ethnic costume in Chinese history. This study explores the travel motivation and experience of Hanfu tourists by conducting qualitative research on Hanfu tourists through photo-elicitation interviews with 25 participants covering four study regions, including the mainland of China, Taiwan, Malaysia, and Singapore. The results reveal seven motivations drive Hanfu tourists: (1) personal hobby, (2) seeking cultural identity, (3) social belonging, (4) Hanfu tourist photography, (5) career need, (6) influence on Hanfu movement, and (7) free space for wearing Hanfu created by tourism. Additionally, the seven types of Hanfu tourist experiences are (1) social experience, (2) cultural experience, (3) Hanfu performance experience, (4) nonvisual sensual experience, (5) learning experience, (6) challenge experience, and (7) pilgrimage experience. This study further furnishes theoretical and managerial implications as a reference for destination marketing targeting Hanfu tourists.

Collaboration is significant but difficult for the development of youth organizations, this research aims to explore whether the online collaboration process is suitable for youth organizations' collaboration and improve their effectiveness and efficiency.

This research has applied a design approach using the collaboration engineering method, to design an online collaboration process for youth organizations to improve their effectiveness and efficiency. Using a self-developed group support systems (GSS) tool, the authors have tested the new collaboration process through an experiment among four youth organizations and conducted a survey afterwards.

The new process improves the collaboration effectiveness and efficiency. The research also identifies the detailed relationships among influencing factors in the online collaboration process.

There is little research in the context of computer mediated youth organization collaboration. This research designs an online collaboration process for the effective and efficient collaboration of youth organizations and has it tested among representative youth organizations, providing practical instructions for digital youth organization collaboration in the context of global pandemic.

This study aims to examine whether corporate stconcerns on social responsibility issues pressurize corporate managers to act in a socially responsible way and how this affects corporate value.

This study follows previous studies such as Wu et al. (2008) and Jiang and Huang (2011) in using the research model.

The analysis shows that in regions where large attention paid to demolitions, corporate managers are under great pressure from corporate stakeholders and they thus act in more socially responsible ways; this, in turn, results in higher corporate values. Furthermore, in regions in which demolition events attract more attention, the increase in corporate value is relatively small for state-owned enterprises and unprofitable listed enterprises.

The findings demonstrate that internet governance heightens corporate stakeholders’ awareness of social responsibility, and this leads to pressure on corporate relative behaviors to satisfy the requests of corporate stakeholders, leading to an increase in corporate value and improvement in social welfare.

The purpose of this study is to propose and test a model that is composed of immersion, perceived attractiveness, happiness, satisfaction and behavioral intention in light of the extended cognitive-affective-conative model.

To test the suggested research model, 271 genuine on-site questionnaires were gathered.

Immersion was found to positively affect perceived attractiveness and happiness. It is also suggested that perceived attractiveness and happiness mediate the association between immersion and tourist satisfaction.

This study also has advantageous marketing and management implications for destination managers and marketers to improve tourist satisfaction.

As per the authors’ knowledge, this is the very first study that inspects the mechanism by which how immersion influences tourist satisfaction.

利用拓展的认知-情感-意动理论, 本研究旨在提出和测试一个将沉浸感、感知吸引力、幸福感和行为意图联系起来的模型。

本研究收集线下有效样本271份。

本研究发现沉浸对感知吸引力和幸福感有正向影响。本研究还提出感知吸引力和幸福感在沉浸感和游客满意度之间的关系中起中介作用。

本研究还为目的地营销人员提供有用的营销和管理启示, 以提高游客满意度。

这是探索沉浸感如何影响游客满意度的机制的研究首批研究之一。

Este estudio tiene como objetivo proponer y probar un modelo que vincula la inmersión, el atractivo percibido, la felicidad, la satisfacción y la intención de comportamiento basado en el modelo cognitivo-afectivo-conativo (CAC) extendido.

Se recogieron un total de 271 cuestionarios in situ válidos para probar el modelo de investigación propuesto.

Se encontró que la inmersión afecta positivamente el atractivo y la felicidad percibidos. También se propone que el atractivo percibido y la felicidad median la relación entre la inmersión y la satisfacción del turista.

Este estudio también proporciona implicaciones útiles de marketing y gestión para que los comercializadores de destinos mejoren la satisfacción del turista.

Este es el primer estudio que explora el mecanismo detrás de cómo la inmersión influye en la satisfacción del turista.

Wool, mainly composed of keratin, is a relatively high-grade clothing material. Although woollen textile has the advantages of high wearing comfort and excellent warmth retention property as we have known, its inherent disadvantage of easy pilling has easy puzzled people for a long time. Most of the existing technologies for pilling resistance are not eco-friendly or severely damaged the internal structure of wool.

In this work, a controlled and effective surface treatment method was proposed to controllable micro-dissolution the scale layers of wool with minor damage to its internal structure, thereby improving the anti-pilling property of wool. Thiourea dioxide (TD) is used as a dissolving agent to swell and dissolve wool surface flakes. After TD treatment, the morphology changes of wool fibers were observed by scanning electron microscope (SEM) and methylene blue staining. Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) were used to characterize the structural changes of TD wool. At the same time, the anti-pilling properties and wettability of wool fabrics were tested.

The results show that the wool scale layer is destroyed after TD treatment, which reduces the friction between fibers and improves the anti-pilling performance of wool fabrics. The methylene blue-stained images further demonstrate that low concentrations of TD can damage the superficial scale layer of wool without significant loss of strength.

This method is simple, eco-friendly and economical, and opens up a new direction for the surface treatment of wool fabrics.

This study aims to investigate the antecedents of design crowdsourcing decision-making, the impact of design crowdsourcing on new product performance and the moderating effect of network connectivity.

The sample (n = 104) was collected from a leading social product development website; the fuzzy-set qualitative comparative analysis and two-stage least square methods were used in the investigation.

Three design attribute feature configurations (rational, emotional and kinesthetic value configurations) are conducive to firms’ adoption of design crowdsourcing and there are two configurations in which firms do not adopt design crowdsourcing. Design crowdsourcing influences new product performance positively. Network connectivity has an inverted U-shaped effect on the relationship between design crowdsourcing and new product performance.

These findings not only enrich crowdsourcing and social network studies but also guide crowdsourcing firms to better manage their processes and community members.

Despite the extensive academic interest in social media sentiment for financial fields, multimodal data in the stock market has been neglected. The purpose of this paper is to explore the influence of multimodal social media data on stock performance, and investigate the underlying mechanism of two forms of social media data, i.e. text and pictures.

This research employs panel vector autoregressive models to quantify the effect of the sentiment derived from two modalities in social media, i.e. text information and picture information. Through the models, the authors examine the short-term and long-term associations between social media sentiment and stock performance, measured by three metrics. Specifically, the authors design an enhanced sentiment analysis method, integrating random walk and word embeddings through Global Vectors for Word Representation (GloVe), to construct a domain-specific lexicon and apply it to textual sentiment analysis. Secondly, the authors exploit a deep learning framework based on convolutional neural networks to analyze the sentiment in picture data.

The empirical results derived from vector autoregressive models reveal that both measures of the sentiment extracted from textual information and pictorial information in social media are significant leading indicators of stock performance. Moreover, pictorial information and textual information have similar relationships with stock performance.

To the best of the authors’ knowledge, this is the first study that incorporates multimodal social media data for sentiment analysis, which is valuable in understanding pictures of social media data. The study offers significant implications for researchers and practitioners. This research informs researchers on the attention of multimodal social media data. The study’s findings provide some managerial recommendations, e.g. watching not only words but also pictures in social media.