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The purpose of this study was to explore the leadership competencies of the National Collegiate Athletic Association (NCAA) college athletes and assess the potential differences between domestic and international college athletes.

A quantitative, non-experimental research design was employed, including the use of an electronic survey to collect data. Survey research allows for extensive data management and a quick data collection method (Creswell & Creswell, 2018). The survey was conducted using online Qualtrics software, which allowed convenience in administration, maintenance, nationwide distribution and data export and analysis.

The findings of this study suggest that domestic college athletes develop greater leadership competencies than their international peers.

The study implications include both practical and academic contributions. The research in the area of leadership development in college athletes has been growing. Previous research has focused on the benefits of the leadership development (Lewis, 2023); however, minimal research has been dedicated to exploring actual leadership constructs within the college athlete population. Moreover, this study focused on the differences between domestic and international college athletes’ leadership constructs. International college athletes go through additional challenges while balancing the academic part of being college athletes (Ridpath, Rudd, & Stokowski, 2020).

Minimal research has been dedicated to exploring actual leadership constructs within the student-athlete population. This study is the first study that explored leadership constructs from the quantitative lens and focusing on both domestic and international student-athletes. The literature on international student-athletes mainly focuses on the motivation arriving to the United States of America (Love & Kim, 2011) and their transitional experiences (Popp, Pierce, & Hums, 2011; Jolly, Stokowski, Paule-Koba, Arthur-Banning, & Fridley, 2022). However, limited literature focuses on the preparation of international student-athlete for life beyond their sport.

Working arrangements’ hybridity has become paramount, particularly after the coronavirus disease 2019 pandemic. A remote working environment has indubitable advantages (e.g. the ability to work from anywhere and at any time). However, such flexibility comes at the cost of being virtually always connected. This duality poses challenges for talent management (TM) in determining who can thrive under these specific conditions and how. This study explores how employees respond to this extended connectivity – namely, work connectivity behaviour after-hours (WCBA) – and its influence on proactive talent behaviour by constructing and testing a theoretical model that differentiates employees’ reactions to this condition.

This study collected data from 400 mainland Chinese employees using online and offline methods. Owing to the potentially varied effects of working in digital environments on employees, a dual mediation regression model was employed to test the hypotheses.

Remote and hybrid work and, specifically, the increased connectivity experienced by employees can be a “double-edged sword” in influencing their proactive behaviour (PB). While employees experience increased organisation-based self-esteem, which positively correlates with more intense PB, this prolonged exposure may also cause emotional exhaustion (EE), which has a negative correlation with PB. Jointly considering both mediation effects revealed that WCBA’s total effect on PB remained negative.

This study enriches the debate regarding the development of TM practices specifically designed for remote work. It recommends paying greater attention to how employees react to increased connectivity experienced in remote and hybrid working environments. Increased self-esteem or passive EE are possible elements for identifying employees’ talent potential. The separation between work and after-work is becoming blurred in the digital age, which reduces employees’ motivation and ability to exploit their inner talents. Therefore, organisations must find alternatives to preserve their talent pools. This study enriches theoretical research on WCBA, promoting an in-depth application of the theory of job-demand resources in the digital age.

Even after establishing their business successfully, many business owners get demotivated, and it leads to unwillingness to grow. This study aims to propose a comprehensive model that represents interrelationships among various personal factors affecting “unwillingness to grow.”

The personal factors for unwillingness to grow were identified by extant literature, and expert interviews were conducted to establish the contextual relationships among these factors. The interrelationships among the filtered variables have been done using interpretive structural modeling (ISM) and MICMAC analysis was done to determine the importance of each factor in influencing “unwillingness to grow.”

In total, 30 personal attributes were identified from previous literature, out of which 15 were selected for the final study. The result identifies 7 variables having a strong impact on “unwillingness to grow.” These attributes are “absence of strong network,” “lack of vision,” “lack of proactiveness,” “reluctance to involve external consultants,” “absence of/small founding team,” “lack of ambition” and “improper attitude.”

The research attempts to create a bricolage of all the important personal factors affecting “unwillingness to grow.” Previous researches have used few attributes, but with the help of ISM, a graphical modeling technique, it became possible to draw interrelationship between 15 attributes. Further, with the help of MICMAC, the importance of each attribute was determined.

The case is designed to be used with the digital business model framework developed by Peter Weill and Stephanie Woerner of Massachusetts Institute of Technology (MIT) (Weill and Woerner, 2015) and is referred to as the W & W framework. This approach provides a useful structure for thinking through the strategic options facing environments ripe for digital transformation.

Research for this case was conducted through face-to-face interviews with the protagonist, as well as through a review of their business planning documents and other data and documentation provided by the founder. Some of the market and industry data were obtained using secondary research and industry reports. Interviews were digitally recorded and transcribed to ensure accuracy.

The case follows the story of Kurt Waltenbaugh, a Minnesota entrepreneur who shared the dream of using data analytics to reduce costs within the US health-care system. In early 2014, Waltenbaugh and a physician colleague founded Carrot Health to bring together their personal experience and expertise in both consumer data analytics and health care. From the beginning, they focused on how to use data analytics to help identify high-risk/high-cost patients who had not yet sought medical treatment. They believed that they could use these insights to encourage early medical interventions and, as a result, lower the long-term cost of care.

Carrot’s initial success found them in a consultative role, working on behalf of insurance companies. Through this work, they honed their capabilities by helping their clients combine existing claims data with external consumer behavioral data to identify new potential customers. These initial consulting contracts gave Carrot the opportunity to develop its analytic tools, business model and, importantly, to earn some much-needed cash flow during the start-up phase. However, they also learned that, while insurance companies were willing to purchase data insights for one-off market expansion projects, it was much more difficult to motivate them to use data proactively to eliminate costs on an ongoing basis. Waltenbaugh believed that Carrot’s greatest potential lay in their ability to develop predictive models of health outcomes, and this case explores Carrot’s journey through strategic decisions and company transformation.

This case is intended for either an undergraduate or graduate course on entrepreneurial strategy. It provides an effective introduction to the unique structure and constraints which apply to an innovative start-up within the health-care industry. The case also serves as a platform to explore the critical criteria to be considered when developing a digital transformation strategy and exposing students to the digital business model developed by Weill and Woerner (2015) at MIT (referred to in this instructor’s manual as the W&W framework). The case was written to be used in an advanced strategy Master of Business Administration (MBA) class, an undergraduate specialty health-care course or as part of a health-care concentration in a regular MBA, Master of Health Care Administration (MHA) or Master of Public Health (MPH). It may be taught toward the end of a course on business strategy when students are building on generic strategy frameworks and adapting their strategic thinking to the characteristics of specific industries or sectors. However, the case can also be taught as part of a course on health-care innovation in which case it also serves well as an introduction to the health-care payments and insurance system in the USA. Finally, the case can be used in a specialized course on digital transformation strategy in which case it serves as an introduction to the MIT W&W framework.

The case is particularly well-suited to students who are familiar with traditional frameworks for business strategy and business models. The analysis builds on this knowledge and introduces students interested in learning about the opportunities and challenges of digital strategy. Equally, the case works well for students with clinical backgrounds, who are interested in how business strategy can influence changes within the health-care sphere. Finally, an important aspect of the case design was to develop students’ analytical confidence by encouraging them to “get their hands dirty” and to carry out some basic exploratory data analytics themselves. As such, the case requires students to combine and correlate data and to experience the potentially powerful combination of clinical and consumer data. Instructors should find that the insights from these activities give students unique insights into the potential for of data analytics to move health care from a reactive/treatment ethos to a proactive/intervention ethos. This experience can be particularly revealing for students with clinical backgrounds who may initially be resistant to the use of clinical data by commercial organizations.