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Alain Bouchard was born in 1949. He bought his first convenience store in 1978, when he was almost 30 years old. By then, he already had nearly 10 years of experience in the sector. He had already been involved in the start-up of more than 200 convenience stores. He understood that if he was to transform his newly acquired store into a chain and build something big, he needed to set up a team of people with complementary skills to help him make acquisitions.

In 2023, there are roughly 15,000 convenience stores operating under the Circle K/Ingo/Couche-Tard banners, employing 130,000 people in more than 30 countries. Annual sales are more than US$60 billion. Alain Bouchard officially retired from his position as President and CEO in 2014 and became Founder and Executive Chairman of the Board. He continues to be a major shareholder. He is still actively involved in strategic orientations and in identifying potential acquisitions. He has become a ‘Chief Culture Officer’ involved in executive leadership mentoring. He has never stopped communicating the importance of innovative, creative and intrapreneurial behaviour at all levels of the enterprise.

This case study presents Alain Bouchard, the man and the entrepreneur. It shows how he learned and mastered the craft of starting, acquiring, managing and developing convenience stores. It looks at how he encouraged the people around him to act as facilitators and intrapreneurs. It describes his values, how he works and learned to live with risk.

The European Union’s Digital Markets Act (DMA) calls for far-reaching changes to the way economic activity will occur in EU digital markets. Before its remedies are imposed, it is critical to assess their impacts on individual markets, the digital sector, and the overall European economy. The European Commission (EC) released an Impact Assessment in support of the DMA that purports to evaluate it using cost/benefit analysis.

An economic evaluation of the DMA should consider its full impacts on dynamic competition. The Impact Assessment neither assesses the DMA's impact on dynamic competition in the digital economy nor evaluates the impacts of specific DMA prohibitions and obligations. Instead, it considers benefits in general and largely ignores costs. We study its benefit assessments and find they are based on highly inappropriate methodologies and assumptions. A cost/benefit study using inappropriate methodologies and largely ignoring costs cannot provide a sound policy assessment.

Instead of promoting dynamic competition between platforms, the DMA will likely reinforce existing market structures, ossify market boundaries, and stunt European innovation. The DMA is likely to chill R&D by encouraging free riding on the investments of others, which discourages making those investments. Avoiding harm to innovation is critical because innovation delivers large, positive spillover benefits, driving increases in productivity, employment, wages, and prosperity.

The DMA prioritizes static over dynamic competition, with the potential to harm the European economy. Given this, the Impact Assessment does not demonstrate that the DMA will be beneficial overall, and its implementation must be carefully tailored to alleviate or lessen its potential to harm Europe’s economic performance.

Entrepreneurship education is being taught to undergraduates in tertiary institutions and fresh graduates in youth programmes to encourage start-ups and create employment as a strategy to stem youth unemployment. As such, entrepreneurship education programmes are expected to include rigorous processes of programme design, implementation and evaluation so as to achieve changes in behaviour, attitude and action of participants measureable in terms of start-up and jobs created. Two entrepreneurship education programmes implemented in Nigeria are evaluated to ascertain the level of effectiveness in design, implementation and evaluation and the outcomes in terms of start-ups and employment created. Research methods adopted in the two programmes combine observation techniques with content analyses, action research in case study and focus group interviews. In addition, test-retest techniques in a quasi-experimental design, with a structured questionnaire is adopted in programme number two only. The findings are that while it is suspected that the design stage is jumped in programme number one, in programme two, the design is poorly done. Implementation is ineffective in the two programmes because objectives did not arise from programme design as they ought to and evaluation methods are inappropriate and so ineffective. The recommendations include review of the design of the two programmes to generate appropriate and measurable objectives; adopting implementation strategies that will achieve the measurable objectives generated from revised programme designs and adopting appropriate evaluation techniques that has capacity to measure outcomes and impact in addition to outputs.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

The global financial crisis (GFC) of 2007–2008 had far-reaching consequences for the global economy, triggering widespread economic turmoil. We use the event-study method to investigate whether investors priced the effect of significant events before the Lehman Brothers' bankruptcy in European and Asia-Pacific banks. Abnormal returns on the event days range from −4.32% to 5.03% in Europe and −5.13% to 6.57% in Asia-Pacific countries. When Lehman Brothers went bankrupt on September 15, 2008, abnormal returns averaged the lowest at −4.32% in Europe and −5.13% in Asia-Pacific countries. The significant abnormal returns show that Lehman Brothers' collapse was a turning point, and investors paid attention to the precrisis events as warning signs of the oncoming crisis.

Social enterprises (SEs), part of the third sector, are hybrid organizations combining the pursuit of social scopes with commercial business solutions. In seeking for social value, they pair for-profit and non-profit features, thereby compensating for shortcomings of both the public sector and the commercial market. Therefore, the performance management of such organizations assumes a crucial relevance. Among the available tools, the balanced scorecard (BSC) aims to capture performance multidimensionality, at the same time fostering legitimacy towards stakeholders.

In general terms, the BSC has the limit to follow a linear and static logic of construction and functioning. For this reason, scholars combine it with system dynamics (SD) to create dynamic balanced scorecards (DBSCs). However, literature seems to devote scarce attention to the adoption of such analytic tools in the third sector, particularly in SEs. This chapter wants to contribute to bridging this gap by proposing a tailored application in the context of a social cooperative, active in the clothing recycle and in the re-integration of disadvantaged social categories. By referring to previous literature about DBSC, two modelling strategies are identified: the BSC-driven and the SD-driven. The latter, based on inductive reasoning, is the one privileged for the study because of its wider flexibility. The modelling outputs consider different perspectives than the ones within traditional BSCs, contain elements of circular causality and show how financial and non-financial performances interplay and co-determine each other. Insights from the proposed model can be useful to support both decision-making and stakeholder engagement.

A quick search of the headlines of major newspapers reveals a treasure trove of technology procurement gone wrong. While the private sector seems to adopt and implement new technology seamlessly and quickly to deliver for customers, the government struggles to accomplish technology purchases and integrations with the same ease. As governments in the United States are looking to retain their current workforce and attract the next generation of workers, the technological capabilities and ethos of governments will be paramount. With nearly every industry being transformed by technology and Generation T being the first generation to have an ingrained “technology first” mindset, the ability of governments to attract these workers depends, in large part, on the ability to transform their government technology culture, policies, and practices.

In this chapter, the authors examine the administrative branch and observe two key components at the root of most technology failures: poor organizational structure in the bureaucracy and the lack of an empowered Chief Information/Technology Officer. Building upon case studies from Massachusetts and California, this chapter looks at the factors related to failure or success to understand the technology procurement culture. The chapter concludes by presenting four key “best practice” principles of public policy and administration that can be implemented by almost any governmental entity to improve their acquisition and implementation of technology.