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The purpose of this paper is to examine the use of biomimicry to inspire sustainable development in economic systems. The research purpose is to explore the link between ecological systems and economic systems to highlight applied environmental solutions. The goal is to propose some driver to develop sustainable business practices inspired on the principles of biomimicry.

This paper provides a theoretical approach that builds the basis for a better understanding of the relationship between nature and sustainable economic decisions. The premise is that in the field of sustainable development, strategies based on “learning from nature” are useful. Furthermore, the concept of biomimicry provides principles and tools specifically aimed at design practice.

The complexity of economic systems has shown that high levels of abstraction are required when conceptualising problems and explanations related with nature-inspired solutions. Stakeholder engagement and transdisciplinary collaboration are required to face long-term environmental challenges. Moreover, the exploratory analysis applied in this paper appeared suitable to compile existing literature.

The study provides some general guidelines and empirical approach through case studies that could help decision makers convert nature-inspired alternatives into valuable strategic business opportunities. Although presented practical cases are framed in the local sphere (i.e. the Basque Country), they can serve as references in other international contexts.

New business models should recognize the positive synchronization between well-managed social, environmental and economic systems.

The proposed ideas deepen the understanding on the sustainable development and the link between ecological and economic systems. In fact, the concept of biomimetic economy has not been dealt with or developed in depth in previous academic works, nor has it been published thoroughly in the field of research.

This analysis deals with the integration activities of leading Spanish assembly manufacturing firms. It is based on data from the second International Manufacturing Strategy Survey (or IMSS‐II). Results show that: there is a greater correlation between strategic goals and internal integration programs than between strategic goals and external integration programs; forward and backward external integration programs are of similar importance; and logistical integration programs do provide a competitive and economic advantage although still at a low‐potential level.

The effectiveness of alternative buffering strategies in complex multilevel assembly manufacturing systems using the Material Requirement Planning (MRP) methodology is explored and assessed. The safety stock, safety lead time, “hard” safety capacity, and forecast inflation buffering strategies are tested under uncertainties of end‐item demand, resource supply, and task control. The MRP methodology is applied for scheduling along with a complex, realistic simulation model for execution of operations. Average inventory levels for end and component items, capacity utilisation, end‐item backorders and customer undersupport are used as performance measures. Experimental results establish safety stock and “hard” safety capacity as dominant buffering strategies under all uncertainty conditions, and task control is shown as the most disruptive uncertainty source.

The service sector of the American economy is expanding very rapidly at a greater than 6 per cent annual growth rate during the 1984‐88 period. The extraordinary growth of the service sector in the last two decades has focused attention on the challenges of effective management of service organizations and operations, vastly different from those faced in classical manufacturing settings. However, while services play an increasingly significant role in society, the productivity of services is much less than that of manufacturing. Determines and describes operations‐related practices and assesses skills development requirements faced by service firms operating in a real‐life environment. Findings of the study include the degree of awareness of the importance of operations‐related tasks and of their impact or organizational performance in services, the performance drivers and allocation of responsibilities for operational decisions, and the significance of operational gaps and misalignments that need correcting to enhance the effectiveness of service firms.

This paper aims to identify the antecedents’ factors that positively and negatively influence the intention to use big data analytics (BDA) by future managers of companies.

The sample comprised 364 business students from a public university in Brazil. The methodology had a quantitative approach, with the use of structural equation modeling.

This paper presented a robust model with a high explanatory factor for the intention to use BDA, in which the elements of positive influence on the intention to use are expected performance, social influence and cost–benefit, and the negative influence factor is resistance to use.

Research on BDA has improved the understanding of the phenomenon, mostly emphasizing the technical dimensions of BDA and underestimating organizational and human dimensions. This research contributed to the literature by presenting new insights into these organizational and human aspects by presenting influencing factors for future managers. User resistance is a variable that can incorporate technology adoption theories in BDA.

The results present a positive perception of future managers in the decision on financial resources in the acquisition of new technologies and enable managers to improve planning, investment and choice of technologies while presenting insights from the next generation. Issues regarding privacy, security and ethical aspects are key to minimizing user resistance.

This paper fills a significant research gap on the adoption of BDA, presenting the perception of future managers on fundamental aspects of adoption in a developing country. In addition, the research offers a theoretical model with new latent variables for a current and relevant topic.

The main purpose of this study is to present an analysis of the dynamics of the tourism market in South America and, more specifically, in Brazil, by measuring and analyzing the growth in tourists' arrivals to the region between 1998 and 2002.

This study uses the shift‐share technique that decomposes the growth of the number of tourists into various components, enabling in‐depth diagnosis of the dynamics of the sector in the period.

Despite the fact that Brazil is the leading tourist destination in South America, the study shows that Brazil has been losing ground in relation to some of its neighbors in South America. The study also revealed the impact of 9/11 and Argentina's crises and the growing participation of the European tourist in Brazil.

Despite some limitations, this technique has the advantage of focusing on a region scarcely studied in mainstream tourism researches and offering Brazilian policy‐makers a new methodology such that they may take advantage of emerging opportunities and create competitive advantages for the country.

This paper aims to explore the possible uses of economic instruments, other than water tariffs, to assist water management policy in Brazil. In particular, the paper focuses attention toward markets for use rights.

The research is based on water resources specialists’ opinions and perceptions, collected through surveys (Delphi method) and a focus group, to understand if such an instrument is desirable and which roles could it play within Brazilian water basins.

Results suggest there is room and utility for markets for water use rights, although mostly on a temporary basis, localized, predominantly dealing with scarcity events and in conjunction with the other instruments under Brazil’s National Water Policy.

Given the persistence of scarcity events in the country, the research represents a first step to understand if new instruments for water management are politically feasible and contribute to better delineate future investigations applied to specific water basins and their local conditions.

This paper aims to analyze how decision support systems manage Big data to obtain value.

A systematic literature review was performed with screening and analysis of 72 articles published between 2012 and 2019.

The findings reveal that techniques of big data analytics, machine learning algorithms and technologies predominantly related to computer science and cloud computing are used on decision support systems. Another finding was that the main areas that these techniques and technologies are been applied are logistic, traffic, health, business and market. This article also allows authors to understand the relationship in which descriptive, predictive and prescriptive analyses are used according to an inverse relationship of complexity in data analysis and the need for human decision-making.

As it is an emerging theme, this study seeks to present an overview of the techniques and technologies that are being discussed in the literature to solve problems in their respective areas, as a form of theoretical contribution. The authors also understand that there is a practical contribution to the maturity of the discussion and with reflections even presented as suggestions for future research, such as the ethical discussion. This study’s descriptive classification can also serve as a guide for new researchers who seek to understand the research involving decision support systems and big data to gain value in our society.