Search results

Rational use of the information available to companies is one of the strategic concerns for both family businesses and non-family businesses. The aim is to make the best use of the information resulting from data analysis in order to gain strategic advantage and to be more competitive as a company in all its functional areas. Experience indicates that emotions play an important role, especially in family businesses. Many maturation models exist to analyze decision-making processes (DMPs), but none from the perspective of family business cognition. The authors start from their own “Circumplex Hierarchical Representation of Organisation Maturity Assessment” (CHROMA) model (Parra, Tort-Martorell, Ruiz-Viñals, & Alvarez-Gomez, 2017), which was created to support decision processes in family businesses. This model was proven successful in the analysis of DMPs in large family businesses. The model was simplified as CHROMA-SHADE (Parra, Tort-Martorell, Ruiz-Viñals, & Alvarez-Gomez, 2019), more adequate for the analysis of small and medium-sized family businesses. Despite being a good DMP analysis instrument, intangible aspects such as family values and emotions have not yet been included. Both entrepreneurial emotions and entrepreneurial cognition must be taken into account when analyzing the DMP of the family business. In this chapter, the authors wish to explore attributes that can be introduced into a new dimension in the CHROMA model in order to make it more specific in the analysis of DMPs of family businesses regardless of size. The resulting FAMILY-CHROMA model represents a specific maturation model to evaluate DMPs based on the use of business information of family businesses.

The nature of technologies that are recognised as Artificial Intelligence (AI) has continually changed over time to be something more advanced than other technologies. Despite the fluidity of understanding of AI, the most common theme that has stuck with AI is ‘human-like decision making’. Advancements in processing power, coupled with big data technologies, gave rise to highly accurate prediction algorithms. Analytical techniques which use multi-layered neural networks such as machine learning and deep learning have emerged as the drivers of these AI-based applications. Due to easy access and growing information workforce, these algorithms are extensively used in a plethora of industries ranging from healthcare, transportation, finance, legal systems, to even military. AI-tools have the potential to transform industries and societies through automation. Conversely, the undesirable or negative consequences of AI-tools have harmed their respective organisations in social, financial and legal spheres. As the use of these algorithms propagates in the industry, the AI-based decisions have the potential to affect large portions of the population, sometimes involving vulnerable groups in society. This chapter presents an overview of AI’s use in organisations by discussing the following: first, it discusses the core components of AI. Second, the chapter discusses common goals organisations can achieve with AI. Third, it examines different types of AI. Fourth, it discusses unintended consequences that may take place in organisations due to the use of AI. Fifth, it discusses vulnerabilities that may arise from AI systems. Lastly, this chapter offers some recommendations for industries to consider regarding the development and implementation of AI systems.

This chapter explores the evolution of a network, initially based on providing sustainable seafood through Loblaw’s supply chain, to a network that is collectively working to improve ocean health. It describes the role of the CEO and key managers, the internal changes taken by Loblaw to become a more sustainable organization, and the external partnering that resulted in a more coherent network with shared goals.

The chapter describes models and theories of sustainable organizations, issue nets, and collaboration and then applies the concepts to understand Loblaw’s sustainability journey and the creation of a network.

The model of the evolution to a sustainable organization is extended to include the journey to sustainable issue or domain networks. What Loblaw and the partnering organizations were able to create suggests that there are increasing levels of collaboration around changing a domain, if there is the courage to take a leap of faith and increase an organization’s time horizon beyond immediate financial demands.

The findings of this chapter will help senior executives with responsibility for shifting supply chains to become more sustainable. In addition, this case provides a new level of detail in describing the journey to sustainability, shifting from a company focus to an issue focus.

This chapter discusses the evolvement of the sustainability concept and its importance in the strategic management context. First, the authors review the development of the concept over the last century and presents the most commonly used sustainability definitions. Then, the three pillars of sustainability (economic, natural and social) are reviewed, highlighting the sustainability aspect of each pillar individually and the problems of their non-substitutability, irreversibility and non-linearity. Based on the literature review, this chapter discusses the main motives for integration of sustainability concept into the overall strategy of the company, namely compliance with regulation, response to public concern, expected competitive advantage and top management commitment. Furthermore, important distinctions between reactive and proactive approaches are presented, and the results and benefits (such as cost reductions, differentiation and added value) of proactive approaches to corporate sustainability are analyzed. Nevertheless, such benefits can only be achieved if corporate sustainability is understood and treated as a holistic concept, which is deeply embedded in the company’s strategy and is approached proactively from the interdisciplinary viewpoint, looking at all three dimensions simultaneously.

Higher education can offer hope and a way forward for vulnerable populations. In particular, access to internationally recognized degrees and credentials has the potential to be a key protection priority for refugee populations, opening alternative solutions to displacement through economic empowerment and increased mobility.

While innovations in online learning have opened new pathways, the delivery of higher education to refugee learners in resource-deprived settings – including camps and urban environments – remains notoriously challenging. Therefore, there is an imperative to draw upon lessons learned from existing programs in order to identify promising practices and emerging innovations.

In this chapter, we draw on our experiences of developing a higher education model for refugee and vulnerable learners to argue that successful delivery of accredited degrees to populations affected by forced displacement relies upon the following three key elements:

• 1)

  Flexible mode of degree delivery and assessment.

• 2)

  Robust blended learning model with in-person academic support.

• 3)

  Provision of adaptive and context-specific interventions and resources.

Flexible mode of degree delivery and assessment.

Robust blended learning model with in-person academic support.

Provision of adaptive and context-specific interventions and resources.

The case study for this chapter is an initiative called the Global Education Movement at Southern New Hampshire University, which delivers accredited degrees to refugee and refugee-hosting populations in five countries. Evidence from the program in Rwanda, operated in partnership with a local partner, Kepler, suggests it is possible for a full degree program to be successful in reaching vulnerable learners, including refugees.