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This study aims to present the development and validation of a scale to measure the attitudes of Latin American business students toward sustainable management practices in the economic, social and environmental dimensions.

Using a nonprobabilistic sample, the appreciation for sustainable practices in students (ASP-S) scale was administered to a total of 653 undergraduate and graduate business students in Argentina, Colombia, Mexico and Peru. A range of psychometric validity (construct, convergent and discriminant) and reliability criteria were applied.

Construct, convergent and discriminant validity was obtained from the ASP-S scale across all samples. During the internal validation process, two factors were found: systemic consciousness (ten items) and sustainable business leadership (nine items), both of which obtained acceptable reliability indices. The resulting structure is equivalent in all four countries.

The instrument can be applied by educators and learning assurance areas to diagnose and measure the effectiveness of pedagogical strategies used in sustainability courses taught at Latin American business schools. As a result, it has applications for curriculum design. As a valid and reliable instrument set in the context of regional business praxis, it can promote an understanding of sustainable behaviors and practices in future Latin American leaders.

This paper aims to present a case study on how the strong relationships with multiple stakeholder groups can benefit educational programs through the curriculum redesign process by using the experience of Marshall University and Intuit.

This paper highlights how Marshall’s faculty used Intuit’s Design Thinking process to engage with stakeholders to innovate a curriculum that is sustainable and socially responsible and transfers workforce skills and concepts. This case describes how to: involve stakeholders to discover their pain points and desired outcomes, develop prototype curriculums from stakeholders’ feedback and test and iterate prototype curriculums on stakeholders until their expectations (e.g. quality, innovation and value) of the curriculum are exceeded.

Faculty applied Design Thinking to engage with stakeholders to infuse contemporary knowledge and skills that positively impact their workforce development and societal goals into the curriculum. This process promoted critical thinking and a “stakeholder-centered” orientation with various groups including AACSB and employers. These curriculum changes ultimately provide greater experiences to students while providing relevant skills of interest to employers and society.

Stakeholders are often consulted on educational programs; however, it is unusual for an industry stakeholder to provide their best innovative practices to assist colleges with the transformation of academic curriculums. Moreover, it is unusual for higher education institutions to fully embrace these industry processes and integrate these experiences within their collective culture. Finally, the detailing of this case allows for other colleges to apply these concepts to their curriculums.

The purpose of this research is two-fold: first, the researchers will create a reliable and valid hospitality senior exit survey by conducting a Delphi panel of experts and second, the researchers will pilot-test the instrument with students from a four-year university. The data will be (a) assessed to determine the retention of knowledge by four-year students, (b) used by academicians to make changes to course material and (c) used to help with the accreditation assessment process.

A Delphi panel of hospitality educators was used to validate the items, and graduating hospitality students were used to calculate reliability.

By embracing the hospitality exit survey (HES), institutions can effectively evaluate and enhance their programs. With its ability to gauge students' knowledge retention, the study findings serve as a powerful tool for shaping the future of hospitality education.

The study's findings might be somewhat limited in representing a broader range of perspectives within hospitality programs. Another limitation stems from the structure of the survey itself. The survey included numerous items requiring two inputs for each item. This format has the potential to introduce certain biases among participants.

In a positive statement, organizations can use this information to discover why employees stay and then continue to develop goals/strategies to ensure this process stays up to date. Academia is no different. Academia also wants to produce the best product, and since the students are to become the next set of leaders, these programs need to know what is successful and what needs to be adjusted.

A strategic exit interview program should 1)Uncover issues relating to human resources/students; 2) understand employees'/students' perception of the work; 3) managers'/directors' leadership style and effectiveness; 4) human resource/college/departments benchmarks and 5) improve the organization.

This research holds significant importance as it focuses on developing the senior HES and its potential utilization within hospitality programs. The HES serves as a valuable tool for these programs to evaluate the knowledge levels of their graduating students and collect data necessary for assessment and accreditation purposes.

Students pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.

Predictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.

The results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.

The entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.

The responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.

Furthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.

Comparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.

The study aims to explore and classify the key enablers of the Association to Advance Collegiate Schools of Business (AACSB) implementation in business schools.

By applying the Interpretive Structural Model (ISM) approach, it builds a hierarchical model of the identified enablers of AACSB implementation. Additionally, the Fuzzy Matriced Impacts Croises-Multiplication Applique and Classement (FMICMAC) technique is used to classify and determine the influence of these enablers on the implementation of AACSB accreditation.

The paper presents an ISM model of the identified enablers and draws managerial insight from it. Categorization of the key enablers into four groups helps in understanding the relative influence of each group of enablers on the AACSB implementation in business schools.

The proposed model of the key enablers will help business schools that are pursuing AACSB accreditation prioritize the enablers. As the study has considered experts' opinions to establish the model, some amount of bias cannot be discounted.

The development of the ISM model of the key enablers of AACSB implementation in business schools is a unique attempt. The findings will help business schools focus on the key enablers that influence implementation of AACSB standards.

The COVID-19 pandemic was an eye-opening experience that put to the test our crisis management competencies across many institutions, including those offered by institutions of higher education. This study aims to review the literature on international business (IB) risks and IB education (IBE) to question whether business graduates are equipped to make decisions in today’s volatile, uncertain, complex and ambiguous (VUCA) marketplace.

While the IB literature has discussed the importance of various sources of risks on global business operations, IBE did not effectively adopt an integrative approach to building the needed risk management competencies related to those risks into our education. The authors argue that this integrative approach to teaching IB is critically needed to prepare future global managers for addressing crises, like that of the pandemic and others. Specifically, this study proposes that this integrated risk management competency can be developed through the building of “synergistic mindsets”.

This study presents a conceptual framework for the components of the synergistic mindset, with intelligence that directly links to present IB risks. These components are cultural intelligence (CQ), emotional intelligence (EQ), public policy intelligence (PPQ), digital intelligence (DQ) and orchestration intelligence (OQ).

Insights related to IBE effectiveness in addressing today’s VUCA market demands and IB risks are discussed.

The study aims to refine the local university’s supply chain management curriculum to meet regional industry demands, thus boosting the local economy.

Mixed-methods action research combined with neural network modeling was employed to align educational offerings with the needs of the local supply chain management industry.

The research indicates that curriculum revisions, informed by industry leaders and modeled through neural networks, can significantly improve the relevance of graduates' skills to the SCM sector.

The study is specific to one region and industry, suggesting a need for broader application to verify the findings.

Adopting the recommended curricular changes can yield a workforce better prepared for the SCM industry, enhancing local business performance and economic health.

The study supports a role for higher education in promoting economic vitality and social welfare through targeted, responsive curriculum development.

This study introduces an innovative approach, integrating neural network analysis with action research, to guide curriculum development in higher education based on industry requirements.

Career preparedness is critical to successfully transitioning from college to a full-time work environment. Being prepared means students have the technical and non-technical skills to help an organization meet its strategic goals. In many instances, students lack the requisite career competencies and collaborative skills. This study proposes designing an instructor-led, career-driven quasi-virtual internship to address this issue and improve students’ preparedness and teamwork.

Our research integrates and expands the four-step processes outlined in instructional and course redesign theories, including analysis, design and development, implementation and evaluation. In the evaluation phase, a survey is used to collect data, and natural language processing is applied to identify the emerging themes. The sample included 104 undergraduate students enrolled in an information systems degree program, which resulted in a digital corpus of 40,744 words for analysis.

Results indicate that the implementation of instructor-led quasi-virtual internships offered a comprehensive career experience comparable to an onsite or virtual company-sponsored internship in five notable areas: (1) application of technical knowledge, (2) critical thinking, (3) time management, (4) application of IT project management and (5) collaborative skills.

Our study only evaluated participants in our treatment group. Future research should examine the differences between students who complete sponsored versus instructor-led quasi-virtual internships. Researchers can add a control group of students who receive a theoretically based capstone course. Future research can simulate randomized controlled trials (RCT) (Chalmers et al., 1981) to measure the effectiveness of quasi-virtual internships. A benefit of this research is that an open-ended survey allows for collecting rich, multifaceted primary data. The second limitation is that the study included only single-item questions. Future authors can create and validate a survey instrument based on the themes and concepts emanating from our investigation. For example, they can operationalize team dynamics and career preparedness using a reflective model in which the underlying construct drives the indicators, requiring multiple items to examine each construct (Coltman et al., 2008). Third, the sample size in the study was relatively small. We can increase the sample size using a time-series dataset with multiple measurement periods. The fourth limitation is context; this study was conducted at a public university; other institutions may have varied teaching approaches, student demographics and resources. By expanding our study using a multi-site approach (Ballantyne et al., 2012), we can increase cross-sectional sample sizes and improve the generalizability of the study’s results.

This study provides several practical insights for educators by examining quasi-virtual internships. Academic institutions that want to offer internships but struggle to establish industry partners can implement the quasi-internship model as an alternative approach. The study highlights that students gain critical insight into their future careers during these internships by being familiar with industry concepts and tools. We also provide insights into engaging students in “meaningful collaboration.” We suggest the instructor provide some time during the class sessions for group work to improve coordination and introduce industry-level tools that provide a more applied approach to IS education.

The National Survey of College Internships (NSCI) 2021 indicates that underrepresented and first-generation students were less likely to participate in internships. Our research may positively impact diverse communities since the quasi-virtual internship allows all students to participate once they are enrolled in a capstone class.

To our knowledge, this study is the first to utilize latent semantic analysis to analyze students’ feedback to improve course design, career preparedness and team dynamics.

To determine the factors influencing the perception of undergraduate students toward research–teaching nexus and also to examine its impact on the attitude of the students.

The study used a quantitative design to examine the perceptions of students in higher education institutions in India. Descriptive and inferential statistics were used to describe the data and test the hypothesis. The data was collected using a structured questionnaire for a sample of 188 students from higher education institutions (HEIs). Further, in line with the purpose of the study and to test the hypotheses, the study used descriptive statistics, exploratory factor analysis and multivariate regression analysis.

The study demonstrates that the factors influencing the perception of undergraduate students toward research teaching nexus were identified using principal component analysis (PCA) with varimax rotation, conducted on 27 measurement items. In addition, the results of the multivariate regression analysis indicated that research-based, research-tutored and research motivation dimensions, significantly impact the graduate students' perception of research–teaching nexus.

The outcomes of this research may become valid input to HEI regulators, researchers and teachers while framing the policies and implementation of the same about the pertinent issues discussed in the paper. Further, it contributes to the existing theory that teaching–research quality and level of motivation are also the predominant factors influencing the teaching–research nexus among students. In addition, the outcome of this paper also supports HEIs to achieve the United Nations Sustainable Development Goals (UNSDGs) at large.

This study contributes to the ongoing debate and scarce literature on research–teaching nexus at the higher education level. The factors derived in this paper propose a framework for aligning teaching and research in academic programs to create high-quality human resource in the nation.

This article explores whether six broad categories of activities undertaken by Canadian business scholars’ academics: publications record, citations record, teaching load, administrative load, consulting activities, and knowledge spillovers transfer, are complementary, substitute, or independent, as well as the conditions under which complementarities, substitution and independence among these activities are likely to occur.

A multivariate probit model is estimated to take into account that business scholars have to consider simultaneously whether or not to undertake many different academic activities. Metrics from Google Scholar of scholars from 35 Canadian business schools, augmented by a survey data on factors explaining the productivity and impact performances of these faculty members, are used to explain the heterogeneities between the determinants of these activities.

Overall, the results reveal that there are complementarities between publications and citations, publications and knowledge spillovers transfer, citations and consulting, and between consulting and knowledge spillovers transfer. The results also suggest that there are substitution effects between publications and teaching, publications and administrative load, citations and teaching load, and teaching load and administrative load. Moreover, results show that public and private funding, business schools’ reputation, scholar’s relational resources, and business school size are among the most influential variables on the scholar’s portfolio of activities.

This study considers simultaneously the scholar’s whole portfolio of activities. Moreover, the determinants considered in this study to explain scholars’ engagement in different activities reconcile two conflicting perspectives: (1) the traditional self-managed approach of academics, and (2) the outcomes-focused approach of university management.