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In this chapter, concepts of data science definition and market business agility with strong support of digital transformation paradigm are discussed. The intention is to provide the reader with a consistent, proposedly not finished view of this powerful, actual, and potential association, which presents a new fashion for entrepreneurship, leading also to organizational changes which imply, in their way, a redefinition of professional works, technology application, risk and project management, and strategic planning. The chapter describes these concepts, develops their relationships, and leaves an “open door” for the reader to perceive not only the conceptual application for competitive scenario description, but also as an associative and integrative methodology to be used, beyond other perspectives, to appreciate the evolution of the context developed by the chapter itself, updating it in the time ahead. In the final part of the text, study cases are discussed as to affirm chapter objectives, findings, and proposed integrative base.

The appeal for new business models is at high level nowadays in all market sectors involving all economic agents. Dealing with classical, non-responsive, bureaucratic structures, traditional organizational arrangements impose delays on management, ineffective control features, and, more critical, limitations to innovate. In this chapter, the authors analyze the proposition for new business models with the consideration of two huge pressuring motivations: to innovate in the healthcare sector and adopt emerging technologies. Both dimensions brought opportune facts for business models development and application, but, with an immense and uncontrolled dynamicity, also produced a confused, turbulent scenario where the academic and scientific knowledge, always demanded, was not developed and communicated efficiently. To address this imperfect scenario, the authors present their reflections around perspectives on building and applying business models supported by emerging technologies for the healthcare sector, offering a background to foster these discussions in further studies and decision-making contexts.

In this chapter, the author aim to approach new ways to understand how emerging technologies can better be applied in organizational contexts. For this purpose, collaborative methodological approaches were addressed—multi, inter, and transdisciplinary paradigms—aiming to promote a better level both of comprehension and adoption of technologies, paying special attention to the healthcare sector and to the One Health initiative, just defined as an interdisciplinary front. As an overall goal for the chapter, the adoption of those methodological principles is advised to the reader, enabling a better understanding of those technologies and their way to be effectively implemented.

Users' personal, highly sensitive data such as photos and voice recordings are kept indefinitely by the companies that collect it. Users can neither delete nor restrict the purposes for which it is used. Learning how to machine learning that protects privacy, we can make a huge difference in solving many social issues like curing disease, etc. Deep neural networks are susceptible to various inference attacks as they remember information about their training data. In this chapter, the authors introduce differential privacy, which ensures that different kinds of statistical analysis don't compromise privacy and federated learning, training a machine learning model on a data to which we do not have access to.

Market intelligence (MI) has evolved as a strong concept in last years. After debates which produced various views, a stable conceptual base was reached. Here, MI is studied with the insertion of analytics. The influence of analytics insertion in market intelligence cycle potentializes MI dynamicity, delivering knowledge in a more prompter way for strategic marketing planning decisions, serving both as an example of organizational strategic alignment and fast tactical planning, specially resulting in a context where innovation – product, process, market and organizational types – and its associated management are improved. Reflections around competitive strengths and related perspectives are studied at the end of this text, enabling further discussions and application unfolding.

It was observed, in these last years, the consolidation of Market intelligence (MI) concept. Results from MI are now being applied in several strategic ways, serving mainly for the important relationship between strategic and marketing planning. This article intends to reinforce the conceptualization of MI process, observing specially its application in one critical sector: Healthcare. Healthcare is a dynamic sector, where strategic marketing planning fundamentals are still being disseminated and absorbed by managers and institutions. Marketing data and information must be provided from a variety of sources to produce knowledge, in a process that can be characterized as “organizational intelligence”. Collected contents from healthcare associated industrial sectors, such as chemical and pharmaceutical, have the potential to produce integrated value chain knowledge, improving analysis and decision processes. Approaching the healthcare market, a framework for an intelligence system for marketing decisions was discussed in Jamil et al. (2011) and it is now evaluated with the contribution of information architecture concepts. Literature review from that original approach is expanded, encompassing information architecture discussions, towards a more consistent framework for market intelligence system implementation and cases of MI application in Healthcare sectors are then re-evaluated, with this new theoretical contribution. Bringing this additional light, market intelligence is presented with a newer, updated and improved conceptualization for practical decisions.

Market intelligence (MI) is a concept that results in real opportunities for knowledge management in organizations. MI is a cyclic process to deliver knowledge for strategic marketing decisions, considering typical organizations of a defined sector as its final users. As organizations must not react to external factors or phenomena, but must also try to lead their sector proposing and executing innovative plans and differential strategic positioning, MI is a modern and cooperative approach that can produce consistent bases for such planning abilities. It is an organizational continuum to answer typical decision problems faced by firms when competing in actual business environments. This chapter details the MI concept, working from theoretical point of view, and adds a practical approach on studying real cases of its potential applications. As MI is a multidisciplinary context, its conceptualization also provokes perspectives for research from other scientific fields, as information science, systems and management, computing science, human resources management, strategy, marketing.

This chapter discusses the potentialities and limitations of metaphors, as simulation techniques applied for decision-making businesses process. A special look is given to the orchestra metaphor, as it is possible to consider one of the most cited method for decades. Approaching orchestra formation definitions, a study of orchestra characteristics and peculiarities was conducted, resulting in an interesting inside view of the orchestra. A brief theoretical analysis about modelling techniques and its application in business process is also developed, allowing, at the end, to discuss how the orchestra metaphor can be applied in a useful way, encompassing several of the aspects we pointed in the text. This results as an orientation for the reader to understand how this specific technique – orchestra metaphor – can be effectively applied in decision-making processes of any level for organizations, escaping from mistakes usually committed when simple views for musical orchestras are adopted.

Revisiting a concept is a mandatory approach when new technologies emerge. This chapter presents a reviewed study, based on a previous publication, about information quality. As it happened in the first attempt to study and develop this concept, it remains challenging, as this context contemplates both tangible and intangible observations for two unlimited parts—information and quality—researched isolated, with its own alternatives, methods and objectives for several years and from different points of view. This chapter's approach is to bring additional work published since the original one and develop conclusions reached at that time, providing a new level of comprehension, which allows the continuity of this debate of information quality, considering the emerging strong trend of analytics processing and informational service offering.

The market intelligence process has been studied from several points of view and different approaches. In this chapter, the authors discuss the perspective of market intelligence as a component of information system projects and specifications. As the results show, both from theoretical perspectives and studies, and from successful practical applications, this better comprehension results in a possibility of higher levels of knowledge production, allowing the integration of marketing strategic, tactical, and operational perspectives with also a collateral benefit to integrate other organizational processes, such as competitive intelligence. The chapter text approaches conceptual development and relationship and practical cases observation, which will compose the final scenario where market intelligence, treated as an information system active component, is a vital and strategic tool to implement competitive advantage alternatives.

This chapter discusses the critical choice for a business manager, when a business model must be considered for its posterior design and implementation. Different modalities are available today and adaptations or changes are completely admissible, as competition evolves. A solid conceptualization of business models is studied, and some typical initiatives analyzed, observing their potentialities, requirements, and risks. As a market solution, several considerations are proposed at the end, regarding BM adoption in real cases, serving as a basic motivation for a clearer decision process to be pursued by business readers. This chapter contributions reach both scholars, researchers, managers, stakeholders and investors on increasing the comprehension about business models' propositions, characteristics and implementation aspects.

It was observed, in these last years, the consolidation of the market intelligence (MI) concept as a source of competitive results in several strategic ways, impacting decision-making and entrepreneurship. This article intends to explore the conceptualization of the MI process, observing specially its application in Healthcare sector under the emergence of new technologies. Approaching the healthcare market, a framework for an intelligence system for marketing decisions was discussed and it is now evaluated with the contribution of information architecture and new technologies concepts. The review formerly produced is updated regarding the focus of the MI system under the influences and potentialities for emerging technologies application, through a lemma of “digital transformation” (DT), validating and expanding market intelligence background towards new dynamism and application in Healthcare contexts.

A relationship between project management and knowledge management was observed with a detailed level of analysis in this chapter, as analytics tools and methods were presented to define new perspectives for these dynamics. After a theoretical review that advanced the level reached by a previous paper on the same topic a new theoretical background was completely worked, resulting in a base where a deeper way of analysis allowed, at the end, to study practical cases of rich association for PM and KM in practical, ready to apply situations. As a trend for next competitive cycles, tools, methods, and techniques that focus knowledge production for decision making are to be increasingly defined and applied, on one hand enabling organizations to propose new competitive structures and positioning, and on the other hand, presenting a more aggressive, faster, and demanding competitive environment.

This article analyses the concept of business models and their main dimensions and elements for global economy competitive scenarios. The issue studied in this research identifies disruptive business models, and builds a practical model to help the implementation of a business model for private individual transportation services, based on the case of Uber. To accomplish this research, articles were searched based on the keywords “business models concepts” and “business models elements.” The period considered was from 2013 to 2017. The goal was to identify elements of business models and strategies adopted by the company, products and services, corporate image, models and management systems: human resource management, financial management, and marketing, among others, and the formal and informal structure of the companies. The empirical case is based on the Uber business model and the new competitive scenario on personal transportation.

This chapter aims to contribute to evaluate market options for business models to be adopted by industrial agents. To achieve this object, a methodological approach for a critical observation was pursued. First, it was conducted a theoretical review, regarding the business model (BM) concept and related definitions, as its relationship with strategy, tactical, and operational level of a generic company, innovation, innovation management, structure, and components, among others. Then an analysis of experiences of practical business model adoption by economy actors, typical industrial arrangements or those related to industrial actions, productive chains or practices, were studied, to produce an overlook of its classical, traditional and influential aspects. Finally, in this analysis, reflections around these findings are presented, contributing for BM practice for industrial organizations and associated value-aggregation partners, as from service sectors, which, nowadays, even pressure industries to adopt or adapt to their business models.

This paper aims to analyze digital transformation in a Brazilian perspective, aiming to understand it for Industry 4.0. Starting from academic researches, from Brazilian companies, a model based on dimensions to define a construct—digital maturity—was suggested, allowing a definite starting point to analyze it for industry 4.0 future scenario. To strengthen these definitions, results of a research about digitalization efforts in Brazilian companies, held by the innovation and entrepreneurship research group of Fundacao Dom Cabral, a major Brazilian player on executive education, is presented, where opportunities and limitations for digital transformation in Brazilian companies were analyzed.

Inovar e uma condicao Sine qua non para qualquer empresa que queira sobreviver no mercado dinâmico dos dias atuais. E importante conhecer as mudancas do mercado, as necessidades e expectativas de seus clientes, visando adequar seus produtos e/ou servicos a elas e, com isso, prestar um servico de qualidade na busca de melhores resultados. Nesse intuito, e imprescindivel adotar em sua estrategia a gestao da informacao que forneca aos gestores a informacao correta, no momento correto. Somente assim e possivel inovar, criando solucoes que atendam as demandas exatas.Esse trabalho tem por objetivo apresentar como a gestao da informacao se insere no contexto da gestao de inovacao das organizacoes. Para tal, foi feita um estudo de multiplos casos na area de engenharia. Apresenta um modelo teorico que auxilia os gestores na adocao de uma gestao de informacoes que levara a inovacao nas organizacoes.

What is innovation? In this chapter, an objective search for the basics on innovation concept is held, allowing its definition, but also producing a background covering its relationships with other management concepts. This study, which starts with a theoretical search for innovation and innovation management concepts, evolving to practical observation of cases and market aspects—such as the startups phenomenon—aims to allow a better comprehension on how innovation can be achieved by small and medium-sized enterprises, regarded as dynamic market agents, active in practically every open economy model in the world. As a result, a conceptual network is proposed, serving both SMEs, to comprehend how innovation is reached and developed for the market, and also contributing to the discussion around its perspectives, as it was approached by other authors in this book.

This paper main objective is to raise information and knowledge demands in an information technology consulting organization, aiming to prepare an information architecture project, where the information and knowledge management will contribute to the expected improvement. A descriptive research has been prepared, using an interview script that enabled to reach the desired goal. It was concluded that existing investments are isolated, without an effective planning that might allow the company to achieve results that would bring real improvements to it.

Innovation is today condition sine qua non for any company that wants to survive in a competitive environment. It is important for the company to know the changes in the market more deeply: in the expectations of the customers, aiming to adapt its products to these changes, innovating both the portfolio and the processes, and therefore seeking better results. In this sense, it is imperative to include in the company's strategy the information management, which maximize the chance to provide correct information to the managers, at the right moment, subsidizing their actions. This chapter aims to present how the information management is inserted in the context of the organizations' innovation management. To this end, it will present theoretical concepts and models that allow managers to implement effective information management, searching better operational results.

This chapter proposes the application of computer simulation models for the evaluation of software quality improvement through the implementation of policies and practices of software development processes and performing the measurement of the evolution of the quality through the Six Sigma methodology. In order to provide decision makers of process improvement, a model of dynamic simulation of systems was proposed. Model validation was performed using data collected from various projects developed in an information technology company headquartered in Belo Horizonte-MG. The models mentioned in this chapter are able to provide the decision makers a tooling of process improvement able to perform predictions, predictions, analysis of “what if” scenarios in the model. As a result of this work, a dynamic simulation model of systems capable of performing the evaluation of software quality in Sigma level is found. Also, there are comparisons and analyses of actual data of software development projects with the simulation data of the models presented. The earnings with the new version of the case exceed by more than 50% the Sigma level, the quality of software developed, and reduction of more than 55% of the time of development of the project.

In this chapter a focus on practical organizational aspects is considered: how to understand the development of concrete, objective processes such as logistics and supply chain management for fashion production and commercialization, with the help of information and knowledge management (IKM). For this study, some restrictive fundamentals are applied. The basic methodological aspect is to consider a “collection” as a line of artifacts of clothing produced according fashion concepts and propositions, resulting in several tangible products – as the clothing itself, complementary accessories, usage-oriented implementations – and intangible factors – such as image, communication messages, brand, artistic and cultural propositions, among many others (Sauro, 2009; Godart et al., 2015). It is a remarkably complex result, resulting from an intense creative process that receives internal and external influences, regarding organizational boundaries, which has to be limited to a focus for a particular study, as it is considered for this chapter. It is important also to mention that “collection” as referred here, approaches mainly clothing, although the term is also related to several other artifacts and products, such as shoes, jewelry, particular accessories, etc.

There is no doubt that nowadays internationalization is increasingly attractive for companies that want to become more competitive. However, many small and medium enterprises (SMEs) still are resource-constrained, lacking adequate information and facing problems to establish and manage relationships to operate in a sustainable way in international markets. Despite receiving some support from governments and from other institutional entities, these difficulties faced by SMEs call for a stronger support, which can be played by industrial enterprises associations (IEAs). This chapter brings the perspective of five different companies that are associated with IEAs. The main objective is to have their opinion about the role of IEAs as information managers and promoters of collaborations, mainly for internationalization processes. Another objective is to understand the acceptance by these companies regarding the use of collaborative platforms, managed by IEAs, for supporting their information and collaboration management activities.

This chapter intends to evaluate how mixed researches are significant knowledge producers for business management. A discussion is conducted about the trade-off around the success and restrictions offered by the dominance of quantitative methods, especially when there is interest to study supply management and logistics. Quantitative methods are essential for any kind of management, but, as more dynamics in market competition produces more complex scenarios, qualitative answers are needed, along its approaches to formulate new questions that will help organizational decision-makers to apply knowledge for their planning activities. This chapter will explore three main points: 1) how the excessive concentration on quantitative methods can restrict managerial views; 2) how any organization can apply qualitative methods to enrich results observed from quantitative, resulting in better, more sustainable decisions; and 3) how qualitative and quantitative methods, associated, can implement this approach in real cases, with an overview of mixed scientific research methodologies.