Search results

Live streaming commerce has grown rapidly in recent years. Although the way streamers communicate with viewers is the key to influencing users' purchase behaviors, little is known about the influence of streamers' communication style on purchase intention. Drawing on parasocial interaction theory and flow theory, this study examines the influence of streamers' interaction orientation on viewers' immersion and parasocial interactions, and its effect on viewers' purchase intentions. The moderating effect of streamers' expertise and attractiveness is also examined.

The authors conducted an empirical study using a structural equation modeling approach based on 407 responses to a questionnaire completed by live streaming audiences.

Results indicate that streamers' interaction orientation has a positive effect on viewers' immersion and parasocial interactions, in turn positively affecting viewers' willingness to purchase. Streamers' expertise positively moderates the effect of their interaction orientation on viewers' immersion and parasocial interactions.

This research is among the first to explore the effect of streamers' communication style and provides a framework for how their communication style affects viewers' purchase intention by enhancing immersion and parasocial interaction in live streaming commerce.

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

The purpose of this paper is to develop a new control chart using two EWMA statistics called the hybrid exponentially weighted moving average (HEWMA) chart to improve the sensitivity of EWMA chart proposed by Zhang et al. (2014). When mean and variance of process are not constants, the use of control chart using coefficient of variation (CV) is a successful approach.

The control chart using EWMA statistics has ability to detect moderate and small shifts in the process. The authors present the designing of the proposed HEWMA statistics control chart called the HEWMA_CV chart based on two hybrid EWMA (HEWMA) statistics. The proposed control chart utilizes the current information and previous information to make decision about the state of control chart.

In this paper, the authors will present the designing of HEWMA statistics control chart called the HEWMA_CV chart. The efficiency of the proposed control chart is shown using the simulated data and real data from the industry. The application of proposed chart on the real data shows that the proposed chart has ability to detect shift in the process and it is superior than existing chart in terms of average run length (ARL).

The design and implementation of the proposed control chart on a real data shows that it can be applied in several industries, such as chemical industry, biological assays, etc.

The practical application of HEWMA chart using coefficient variation is gaining extensive adequacy. The design and implementation of the HEWMA chart offers a new approach in the detection of small process mean shift.

In practice, when mean and variance of process are not constants, the use of control chart using CV is a successful approach. In this paper, the authors designed a new control chart using two EWMA statistics called the HEWMA chart to improve the sensitivity of EWMA chart. The comparison shows that the proposed chart is superior than the existing chart in terms of ARL.

In a past era, alchemists believed they could magically transmute lead into valuable gold. Science has progressed a substantial distance since then and for decades nuclear and particle physicists could change various materials into gold. When considering technology, leaders are faced with a comparable challenge: How does one leverage technology to create unique organizational value? To manage emerging technologies effectively to create organizational value, managers will need to lead the producers and practitioners of technology effectively. In the age of global interdependence, organizations must abandon old outdated perspectives.

Technology is a force which drives itself. Organizations must adopt to emerging technology or risk being obsolete. Leveraging technology to create value involves more then circumferentially managing technology. To create value, leaders must encourage staff to transmute technology. The principles and practices of quantum leadership provide for this possibility. This chapter will irradiate why simply managing technology does not offer organizations the maximum value from technology. The reader will be introduced to the four core features of quantum leadership: duality, superposition, entanglement, and observation. With this groundwork, the principles and practices of this leadership perspective will be discussed in context of transmuting technology into unique organizational value. Which lens one uses to see which possibility becomes reality are exclusively in the eyes of the viewer. Using information systems technology, artificial intelligence (AI), and 5G technology as the exemplars, readers can decide whether to accept, reject, or suspend judgement on using quantum leadership as the perspective to transmute technology into valuable organizational gold.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

Attention is one of the most important factors to affect the academic performance of students. Effectively analyzing students' attention in class can promote teachers' precise teaching and students' personalized learning. To intelligently analyze the students' attention in classroom from the first-person perspective, this paper proposes a fusion model based on gaze tracking and object detection. In particular, the proposed attention analysis model does not depend on any smart equipment.

Given a first-person view video of students' learning, the authors first estimate the gazing point by using the deep space–time neural network. Second, single shot multi-box detector and fast segmentation convolutional neural network are comparatively adopted to accurately detect the objects in the video. Third, they predict the gazing objects by combining the results of gazing point estimation and object detection. Finally, the personalized attention of students is analyzed based on the predicted gazing objects and the measurable eye movement criteria.

A large number of experiments are carried out on a public database and a new dataset that is built in a real classroom. The experimental results show that the proposed model not only can accurately track the students' gazing trajectory and effectively analyze the fluctuation of attention of the individual student and all students but also provide a valuable reference to evaluate the process of learning of students.

The contributions of this paper can be summarized as follows. The analysis of students' attention plays an important role in improving teaching quality and student achievement. However, there is little research on how to automatically and intelligently analyze students' attention. To alleviate this problem, this paper focuses on analyzing students' attention by gaze tracking and object detection in classroom teaching, which is significant for practical application in the field of education. The authors proposed an effectively intelligent fusion model based on the deep neural network, which mainly includes the gazing point module and the object detection module, to analyze students' attention in classroom teaching instead of relying on any smart wearable device. They introduce the attention mechanism into the gazing point module to improve the performance of gazing point detection and perform some comparison experiments on the public dataset to prove that the gazing point module can achieve better performance. They associate the eye movement criteria with visual gaze to get quantifiable objective data for students' attention analysis, which can provide a valuable basis to evaluate the learning process of students, provide useful learning information of students for both parents and teachers and support the development of individualized teaching. They built a new database that contains the first-person view videos of 11 subjects in a real classroom and employ it to evaluate the effectiveness and feasibility of the proposed model.

The purpose of this paper is to find the characteristic of entrepreneurial process for the student in free enterprise (SIFE) team in China, and to provide theoretical guidance for the entrepreneurial process of SIFE student team through a new Timmons model.

Taking an entrepreneurial project of Shantou University SIFE team as example, a Timmons model was proposed describing the SIFE student team entrepreneurial process based on the famous entrepreneurial process model established by Jeffry A. Timmons. The application value of the new Timmons model was proved by case analysis.

The paper summarized the main characteristics of the entrepreneurial model for the SIFE student team as: the nature of creation free enterprises, the excellent entrepreneurship networks, and the spirit of social entrepreneurship orientation. By case study, the paper proved the practical value of the new Timmons model by analysis of the key factors such as business opportunities, resources and entrepreneurial team, and their dynamic balance process.

The new model proposed in the paper will have theoretical value to provide a direction for student entrepreneurial practice, the analysis of the characteristics of the new model will also enrich the research on entrepreneurship theory.

This paper is the first research on SIFE student entrepreneurial process in China. In the past two years, the authors observed dozens of successful worldwide SIFE students' practical projects, but few of them appeared in the literature. It is hoped that this paper can offer some constructive advice to the entrepreneurial process of the SIFE student team and enrich the theory of general entrepreneurial education.

Purpose: This study quantitatively assesses the impact of ESG profile on equity value and risk, as well as identifies potential differences occurring in different sectors, based on the data of the Nasdaq Nordic market.

Methodology: To reach this purpose, (i) the stock return and volatility analysis is being conducted (using the methods of paired sample t-test, correlation, etc.), and (ii) panel data models with constant, fixed and random effects are being constructed. The analysis is based not only on the company’s ESG performance but also on a cross-sectoral approach.

Findings: The results revealed that although ESG factors appeared to have a significant impact in most of the constructed models, the impact of these factors varies depending on the sector.

Implications: This research provides a comprehensive and comparative approach to the importance of the ESG profile for investment performance and therefore can be useful both for impact investors making investment decisions in dynamic global financial markets and for companies developing or reforming their ESG strategies.

Limitations: Due to the problem of data availability, the cross-sectoral comparison was performed based on the limited number of sectors. In addition, the limited availability of ESG data in the analysed market did not allow the use of additional methods to assess the impact of ESG.

Future Research: Expanding the data sample and assessing the impact of a company’s ESG profile not only in different sectors but also in different phases of the economic cycle might be the direction for future research.

This article aims to provide a critical review of the articles included in this special issue and highlight their findings and contribution to events, festivals and destination management research.

The article critically reviews methodologies, findings, themes and conclusions offered by each article included in this special issue.

The articles in the special issue identify the latest thematic trends in events, festivals and destination management research and propose conceptual frameworks for event and festival life cycle trajectories. They build on previous research confirming how accessible tourism and a balanced event portfolio can increase the sustainability and competitiveness of the destination. Based on sound methodologies, they offer specific theoretical and practical implication for the successful planning, marketing and management of events, festivals and destinations. They provide suggestions on how event innovation, participatory sport events, mega sport events, food and wine festivals and meetings, incentives, conferences and events (MICE) can assist in the marketing and branding of the tourism destination.

The articles in this special issue lay the foundation for future research in events, festivals and destination management. Articles in this special issue apply various research methods and analysis, indicating the growth of event and festival research. Research methods and analysis techniques used in the special issue include content/theme analysis, case studies, qualitative studies and questionnaires. The research articles and methodologies used in this issue should help both researchers and industry practitioners.

This study highlights key findings, theoretical and practical implications and contributions of the articles included in this special issue. It provides a holistic view of events, festivals and destination management research and suggests areas for future research.

This study examines the impact of firm-level climate risk exposure (FCRE) on firm stock liquidity by using a sample of Indian-listed firms from the financial years 2003–2004 to 2022–2023. Further, it endeavors to investigate the moderating role of environmental, social and governance (ESG) disclosure in this relationship.

A novel text-based FCRE metric is introduced using a sophisticated Word2Vec model through a Python-generated algorithm for each firm and year based on the management discussions and analysis (MD&A) reports. The panel fixed effect model is used to study how FCRE affects stock liquidity.

The result shows that FCRE negatively affects firms’ stock liquidity, and the effect remains robust after addressing endogeneity concerns. In addition, we find that a high ESG disclosure rating significantly moderated the adverse effect of FCRE. Furthermore, our analysis reveals that investor sentiment, information quality, corporate life cycle and institutional holdings moderate the impact of FCRE on liquidity.

The study offers valuable insights for investors, managers and policymakers on integrating climate risk into investment strategies, improving corporate climate governance and shaping policies that incentivize sustainable corporate behavior.

To the best of our knowledge, this study is an early study to explore the relationship between firm-specific climate risk exposure and stock liquidity using advanced machine learning techniques. It contributes to the existing literature by illustrating how climate risk can lead to adverse market reactions while highlighting the critical roles of corporate ESG practices, investor sentiment and disclosure quality in influencing this relationship.