Search results

This study aims at building a framework for the electronic word-of-mouth (eWOM) response under the social media environment. The elaboration likelihood model was adopted to explain how message source credibility and message appeal jointly influence the eWOM response process, while source credibility provides a central route and message appeal plays a peripheral route for information processing.

This study used a scenario design to test the decision behavior in the Facebook environment through message content manipulation. A convenience sampling method was adopted in this study. We collected 203 valid questionnaires and tested this research model with LISREL 8.8. This study used a two-stage structural equation modeling data analysis method with LISREL 8.8, by which the measurement model was assessed through confirmatory factor analysis for the reliability and validity of the research model, and the causal relationship among factors was assessed through exploratory factor analysis .

The results showed that 53% variance of eWOM responses could be explained by message source credibility and emotional message appeal from the elaboration likelihood model perspective. Message source credibility plays a central role in the social media environment. The model was further tested with a demographic profile analysis for both gender and age. It is found that a female user is influenced by both source credibility and emotional appeal, but a male user is only influenced by message source credibility. The mature age group is more responsive to eWOM messages.

The sample might not represent all social networking sites (SNS) users. The participants represent a small segment of the Facebook population around the globe. Secondly, this research design could be improved by using more recreational messages to test the effects of message appeal and message source credibility. Thirdly, the mobile phone is a type of physical product rather than an experiential product. Future studies could try to identify the same eWOM determinants with different SNS functions, for example, the inbox message function. Similarly, Facebook users are allowed to use both text and pictures to disseminate promotional messages.

This study provides an insight for SNS administrators regarding the determinants of driving more customer responses toward a message. Message source credibility and message appeal are identified as the antecedents for eWOM responses in SNS. Companies could make use of this finding to improve their marketing communication strategy in SNS. The finding can inform administrators of the importance of focusing on both customers’ psychological state and message attributes during the dissemination of promotional messages to improve the efficiency of the promotional effort. Companies aimed at receiving different types of eWOM responses in SNS may need to consider other factors for creating their promotional messages.

Previous studies have mainly identified factors influencing eWOM responses from the people-centered variables such as personal traits and social relationships. This study proposes that the eWOM response is a dual information processing process that can be explained by the ELM. When a user processes information in SNS, he follows both the central route and the peripheral route (i.e. source credibility and message appeal) which can influence the eWOM response. It is the first time that the source credibility is investigated as the central route in ELM model.

Although scholars argue that artificial intelligence (AI) represents a tool to potentially smoothen the bullwhip effect in the supply chain, only little research has examined this phenomenon. In this article, the authors conceptualize a framework that allows for a more structured management approach to examine the bullwhip effect using AI. In addition, the authors conduct a systematic literature review of this current status of how management can use AI to reduce the bullwhip effect and locate opportunities for future research.

Guided by the systematic literature review approach from Durach et al. (2017), the authors review and analyze key attributes and characteristics of both AI and the bullwhip effect from a management perspective.

The authors' findings reveal that literature examining how management can use AI to smoothen the bullwhip effect is a rather under-researched area that provides an abundance of research avenues. Based on identified AI capabilities, the authors propose three key management pillars that form the basis of the authors' Bullwhip-Smoothing-Framework (BSF): (1) digital skills, (2) leadership and (3) collaboration. The authors also critically assess current research efforts and offer suggestions for future research.

By providing a structured management approach to examine the link between AI and the bullwhip phenomena, this study offers scholars and managers a foundation for the advancement of theorizing how to smoothen the bullwhip effect along the supply chain.

This study aims to support researchers and practitioners in finding suitable instruments for future research studies and organizational quality assessments.

Employees’ success of learning at work is strongly influenced by the quality of the workplace learning environment. In the recent decades growing effort has been given to the development of surveys to measure the quality of workplace learning, resulting in a large number of available survey instruments. This study conceptually draws on a 3-P model and uses a qualitative metasynthesis to collect and categorize n = 94 surveys that intend to measure the quality of workplace learning (WPL).

The results underline that research on WPL environments is a highly interdisciplinary endeavor, where every discipline enriches the field by a new perspective and own foci. Overall, this study finds a focus on learning culture and working conditions, on social and functional inclusion of the learner and on support and feedback during training. Products of WPL such as professional competences or career aspirations play a minor role.

With the integration of quality measurement instruments from various research studies, this study produces an interactive online instrument map that gives a broad, yet organized overview of available quality measures in the WPL field.

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.

The purpose of this study was to analyze the effectiveness of simulation learning techniques within both face-to-face and online courses. The specific objective for this study was to answer two questions: (1) What are the specific benefits the simulation learning component adds to the course(s)? (2) How do students perceive the usefulness of the simulation learning component to their prepared readiness to enter the industry?

An open-ended survey was administered at the end of the course to conduct a content analysis of student perspectives of the incorporation of cloud-based, educational simulation learning into educational courses. A discussion of the students' perspective of the SIM labs benefits, ease of use and perceived usefulness of this trending learning component has been reviewed, along with the comparison of the online and face-to-face viewpoints.

Some of the identified successes were the ability to collaborate between online and face-to-face classes. Another was the ability to incorporate the application and decision-making components of the textbook into their virtual position of the simulation (SIM) learning lab from an owner's/general manager's perspective. Finally, the SIM labs provided the instructor with a measurable tool to have students compete in a healthy environment.

Valuable insights were gained into the student's perspective and helped in needed adjustments to better utilize this type of active learning. By studying a specific simulation learning component of this type of electronic learning (e-learning,) valuable contextual explanations to support the other types of active learning techniques mentioned above can be gained.

This study intended to bridge this gap by investigating the perspectives of international students regarding Taiwan’s bilingual education policy and its impact on their willingness to enroll in graduate programs in Taiwan. Additionally, the comparisons among international students from diverse backgrounds were examined.

Employing a qualitative research design, the study included nine participants from three countries, with each country contributing three students. Three sessions of semi-structured interviews were conducted, supplemented by the analysis of 15 documents from 8 organizations and universities.

Results indicated predominantly negative views toward Taiwan’s bilingual education policy, with little impact reported by two participants and none by others. Furthermore, themes derived from document analysis deviated from participants' viewpoints.

A focus on students from southern Asia, which was the major source of international students in Taiwan, becomes critical. In the same vein, little literature has been found concerning graduate students' perceptions toward bilingual education policy, which should be thoroughly explored as well.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

The purpose of this study is to chart the development of Makerspaces in higher education (MIHE), by building a map of existing research work in the field. Based on a corpus of 183 manuscripts, published between January 2014 and April 2021, it sets out to describe the range of topics covered under the umbrella of MIHE and provide a holistic view of the field.

The approach adopted in this research includes development of the 2014–2021 MIHE corpus; literature overview and initial coding scheme development; refinement of the initial coding scheme with the help of a focus group and construction of the MIHE map version 1.0; refinement of the MIHE map version 1.0 following a systematic approach of content analysis and development of the MIHE map version 2.0; evaluation of the proposed structure and inclusiveness of all categories in the MIHE map version 2.0 using card-sorting technique; and, finally, development of the MIHE map version 3.0.

The research trends in the categories of the MIHE map are discussed, as well as possible future directions in the field.

This paper provides a holistic view of the field of MIHE guiding both junior MIHE researchers to place themselves in the field, and policymakers and decision-makers who attempt to evaluate the current and future scholar activity in the field. Finally, it caters for more experienced researchers to focus on certain underinvestigated domains.

This study investigates a novel educational strategy in science, technology, engineering and mathematics (STEM) teaching that integrates the engineering design process (EDP) as a framework. The strategy aims to help teachers explain STEM concepts in a simplified way. We employed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology to enable a systematic review that evaluated the effectiveness of this approach in improving both teaching and learning in STEM subjects.

In order to fulfill the objectives of the review, key data were extracted from each of the 400 articles that were reviewed from three databases: Scopus, ProQuest Central and EBSCO. Two types of analysis were conducted, namely descriptive analysis and literature classification.

This systematic review analyzed 44 articles on the EDP, focusing on 18 detailed studies mainly from ProQuest, SCOPUS and EBSCO. It revealed a limited focus on gender’s impact on EDP and a trend toward interdisciplinary use and integrated research approaches. The study underscores the need for further exploration of demographic influences and preparation programs in EDP across various disciplines, aiming to inform future research and educational policies.

The study’s value lies in its comprehensive assessment of engineering design (ED) research over the past decade, serving as a key reference point. It highlights progress in the field, consolidates findings and provides insights into the field’s evolution, guiding future research directions in ED.

Listening is often considered the cornerstone of the communication process, with feedback being a crucial skill for effective management. The primary objective of this article was to investigate the relationship between managers’ listening skills and feedback skills from their subordinates’ perspectives. Moreover, it explores the mediating effect of message-sending skills and the ability to deal with interference in this relationship.

This article deployed a quantitative, descriptive research design. The authors developed and distributed a self-administered questionnaire via non-probability convenience sampling, resulting in 304 useable responses.

The results of the main direct effect test (model 1) indicate that listening is positively associated with feedback. Model 2 established that message-sending skills did not directly mediate that relationship. On the other hand, the ability to deal with interference was found to mediate the relationship. Finally, model 4 showed the multi-mediating effect of message-sending skills and the ability to deal with interference in the relationship between listening and feedback.

As far as the researchers are aware, this paper is the first of its kind to show the ability to deal with interference as a mediating factor in a statistical model. Moreover, this study is the first to present a continuous intermediary role played by message-sending skills and the ability to deal with interference in the relationship between listening and feedback.