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The purpose of this paper is to examine the artificial intelligence (AI) methodologies to fight against money laundering crimes in Colombia.

This paper examines Colombian money laundering situations with some methodologies of network science to apply AI tools.

This paper identifies the suspicious operations with AI methodologies, which are not common by number, quantity or characteristics within the economic or financial system and normal practices of companies or industries.

Access to financial institutions’ data was the most difficult element for research because affect the implementation of a set of different algorithms and network science methodologies.

This paper tries to reduce the social and economic implications from money laundering (ML) that result from illegal activities and different crimes against inhabitants, governments, public resources and financial systems.

This paper proposes a software architecture methodology to fight against ML and financial crime networks in Colombia which are common in different countries. These methodologies complement legal structure and regulatory framework.

The contribution of this paper is how within the flow already regulated by financial institutions to manage the ML risk, AI can be used to minimize and identify this kind of risk. For this reason, the authors propose to use the graph analysis methodology for monitoring and identifying the behavior of different ML patterns with machine learning techniques and network science methodologies. These methodologies complement legal structure and regulatory framework.

In the present chapter, we present the case study of the only woman film director who has ever won an Academy Award for Best Director, Kathryn Bigelow. We analyzed 43 written interviews of Kathryn Bigelow that have appeared in the popular press in the period 1988–2013 and outlined eight main themes emerging regarding her exercise of leadership in the cinematic context. We utilize three theoretical frameworks: (a) paradoxical leadership theory (Lewis, Andriopoulos, & Smith, 2014; Smith & Lewis, 2012); (b) ambidextrous leadership theory (Rosing, Frese, & Bausch, 2011), and (c) role congruity theory (Eagley & Karau, 2002) and show how Bigelow, as a woman artist/leader working in a complex organizational system that emphasizes radical innovation, exercised paradoxical and ambidextrous leadership and challenged existing conventions about genre, gender, and leadership. The case study implications for teaching and practice are discussed.

This chapter studies how entrepreneurship research has evolved at the Latin American level. Using the database available in the Web of Science Core Collection, a period-by-period bibliometric analysis is carried out to identify possible changes in research trends over time. On the one hand, the results show that in the period 2000–2006, research focuses mainly on rural development, community development and financial resources. On the other hand, in the period 2007–2013, the research priority is related to international entrepreneurship, private capital raising and studies based on the Global Entrepreneurship Monitor (GEM). Finally, during the period between 2014 and 2020, research focused mainly on self-employment, family businesses, promotion of angel investor networks, venture capital, and female entrepreneurship. The results of this study may be of interest to academics, researchers, and policymakers to understand the evolution of this topic in recent decades and to promote entrepreneurship and innovation in the region.

The purpose of this chapter is to illustrate the contribution made by migrants in the territory that hosts them, particularly when they transfer their knowledge to members of the community. In the specific case of the sea urchin fishery, it is described how the Morishita family in Baja California undertakes the sea urchin value chain, from the location of population banks to the commercialization of the product in the Japanese market and, by therefore, the promotion of development in rural places while starting a culture of export and currency generation. An adventure of opportunities that has been successful for more than 50 years, whose origin is the sustainable use of “a plague” that today is a delicacy for many.

The objective of the work is to show the way in which creativity can influence entrepreneurial activity in Latin America. To do this, a review was made of the work related to: the mechanisms and contexts that stimulate creativity in business activities both internationally and in the region; and those that account for the contextual frameworks that favor or inhibit the development of business activity. Based on the above, it was reviewed in a more specific way, to what extent the link between creativity and entrepreneurship works or does not work in different types of companies such as small rural companies, women's businesses, and informal ones. In the last section of the chapter, with data constructed from the GEM, the impact of the context is shown to understand the geographical, historical, cultural, and institutional variations in the actions of entrepreneurship and creativity in the region, and with it, qualify the global studies on their relation.

This chapter considers the process of entrepreneurial activity to deploy financial technologies (fintech) through mandate-specific new companies in Latin America. We deal with important historical issues such as defining the term, establishing temporal and industrial activity boundaries, positioning this particular process within other organizational forms typical of the region, the role of women, and other relevant issues such as the modernization of retail payments and personal lending. A central question is whether fintech start-ups have had a “scissor” effect in the entrepreneurial process of Latin America: at the base of the pyramid (i.e., reducing frictions to support overall entrepreneurial activity, increasing financial inclusion, etc.) and near the top (by creating new business leaders). As a result, this chapter provides an initial assessment of gender disparities and barriers enabling women entrepreneurs in the fintech ecosystem.

Taking as reference a sample of around a hundred biographical materials on entrepreneurs in Mexico and Colombia, the purpose of this chapter is dual. Both to show the relevance and varied modalities that the biographical approach has enjoyed in business history research since the 1990s, and to display the intrinsic potential this modality of scholarship entails for entrepreneurship endeavors. In particular, it discusses the prospects to incorporate this body of empirical works into the large Latin American audience attending undergraduate, graduate and executive education programs in business, economic history and related fields. The chapter is organized into three sections. The first two are devoted to illustrate relevant patterns in the entrepreneurial trajectory of individuals and entrepreneurial families studied in each of the two countries under consideration. The last section identifies some conceptual issues that may impact current debates on Latin American business development as exemplified in recent business and economic history journal venues and scholarly conferences.

The purpose of this paper is to distinguish clearly between industry (ILC) and product lifecycle (PLC) models and to elucidate their different ramifications for organizational learning and knowledge.

The authors examine existing knowledge on ILCs and PLCs to highlight the differences and similarities and develop a framework with implications for learning and innovation in digital manufacturing industries.

The authors identify and associate one dominant type of learning with each phase of the ILC: learning-by-participating in the introduction phase, learning-by-feedback in the growth phase, vicarious learning in the maturity phase and learning-by-memory in the decline phase. The study also provides insight into how different types of learning influence PLC in digital innovation. From this perspective, learning-by-feedback is crucial to co-creation, co-production and open innovation. Similarly, learning-by-doing and learning-by-memory are essential to production and usage stages, respectively.

The conceptual development in this paper follows a somewhat critical but ultimately elucidative analysis that highlights important research avenues in the interplay of PLC/ILC, organizational learning and digital innovation.

This paper clarifies a perennial theoretical problem by differentiating two concepts often conflated in the literature. More importantly, it contributes to the knowledge management literature by shedding light on the connection of ILC and PLC theories to different types of organizational learning.

Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications. In the literature, several approaches have been proposed to solve this problem. However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k), and point sample size (r) on the optimized curve reconstruction measured by a penalty function (f). The paper aims to discuss these issues.

A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed. Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored.

It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m. Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks. The authors were able to detect the presence of such spurious features with spectral analysis. Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample.

The authors have addressed important voids of previous works in this field. The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how. Also, the authors performed a characterization of the curve fitting problem from the optimization perspective. And finally, the authors devised a method to detect spurious features in the fitting curve.

This paper provides a methodology to select the important tuning parameters in a formal manner.

Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.).