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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.

Following the Supreme Court’s 1988 decision in Basic, securities class plaintiffs can invoke the “rebuttable presumption of reliance on public, material misrepresentations regarding securities traded in an efficient market” [the “fraud-on-the-market” doctrine] to prove classwide reliance. Although this requires plaintiffs to prove that the security traded in an informationally efficient market throughout the class period, Basic did not identify what constituted adequate proof of efficiency for reliance purposes.

Market efficiency cannot be presumed without proof because even large publicly traded stocks do not always trade in efficient markets, as documented in the economic literature that has grown significantly since Basic. For instance, during the recent global financial crisis, lack of liquidity limited arbitrage (the mechanism that renders markets efficient) and led to significant price distortions in many asset markets. Yet, lower courts following Basic have frequently granted class certification based on a mechanical review of some factors that are considered intuitive “proxies” of market efficiency (albeit incorrectly, according to recent studies and our own analysis). Such factors have little probative value and their review does not constitute the rigorous analysis demanded by the Supreme Court.

Instead, to invoke fraud-on-the-market, plaintiffs must first establish that the security traded in a weak-form efficient market (absent which a security cannot, as a logical matter, trade in a “semi-strong form” efficient market, the standard required for reliance purposes) using well-accepted tests. Only then do event study results, which are commonly used to demonstrate “cause and effect” (i.e., prove that the security’s price reacted quickly to news – a hallmark of a semi-strong form efficient market), have any merit. Even then, to claim classwide reliance, plaintiffs must prove such cause-and-effect relationship throughout the class period, not simply on selected disclosure dates identified in the complaint as plaintiffs often do.

These issues have policy implications because, once a class is certified, defendants frequently settle to avoid the magnified costs and risks associated with a trial, and the merits of the case (including the proper application of legal presumptions) are rarely examined at a trial.

The accepted wisdom is that Northern Ireland is a traditional society within which women’s primary role is defined as homemaker and mother. Examines data on the labour market participation of women in Northern Ireland, drawing comparisons with the UK, the Republic of Ireland and the European Union. Examines four hypotheses as possible explanations for mothers continuing in paid employment. Concludes that, despite living in a society seemingly more traditional than that in many other European Union countries, mothers of young children in Northern Ireland may be more likely to be in employment because they can call on a network of family support to provide informal child care.

The purpose of this paper is to identify sensing, seizing and reconfiguring routines of dynamic capabilities that enable digital transformation in firms.

A qualitative approach is used. Representatives from a firm going through digital transformations are interviewed, and focus groups have been carried out with a consultancy firm experienced in giving advice to firms going through digital transformation.

Six routines identified as relevant specifically for digital transformation are identified. These are cross-industrial digital sensing, inside-out digital infrastructure sensing, digital strategy development, determination of enterprise boundaries, decomposition of digital transformation into specified projects and creation of a unified digital infrastructure.

The authors provide direction for managers on how to approach digital transformation. In relation to previous research, the authors provide more specific guidance regarding how to reconfigure the organization in digital transformation.

The paper uses a novel context for digital transformation and complements the very few studies available using dynamic capabilities to understand digital transformation.

The purpose of this study is to empirically investigate the role of dynamic capabilities, specifically the sequence of sensing, seizing, and transforming capabilities, in highly uncertain, emerging technology environments. Focusing on the extended reality industry, the study aims to understand the antecedents to these dynamic capabilities, their sequential nature, and their subsequent impact on innovation and company performance.

Based on a survey of 130 German companies in the extended reality sector, we built a structural equation model that explores the relationship between dynamic capabilities, their antecedents, and their effect on innovation and company performance.

The analysis suggests that sensing capabilities positively influence seizing and transforming capabilities, while seizing directly contributes to transforming. Transforming capabilities are linked to improved innovation performance, which in turn boosts company performance. Organizational ambidexterity, market orientation, and technology orientation are found to be crucial antecedents, accounting for 33.1% of the variance in sensing capabilities.

This research illuminates the interdependence of dynamic capabilities in highly uncertain business environments, such as emerging technology markets. It contributes original insights by elucidating the sequential nature of dynamic capabilities and identifying their vital antecedents. It also enlarges the understanding of how dynamic capabilities impact firms’ innovation performance.