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This study aims to examine the evolution of three science, technology and innovation parks (STIPs) located in the state of Rio de Janeiro, Brazil, from the perspective of the university–industry–government linkages.

This is a multiple case study organized in two stages: first, bibliographic and documentary research to develop a theoretical framework and description of the innovation environments; and second, interviews and forms filling with 13 managers and stakeholders, combined with participant observation. The analysis and assessment of the evolution of each environment are based on a tool named Amaral’s Model for Innovation Environment Management (AMIEM).

There are critical issues for the development of STIPs, namely, governance structure, government participation and the relationship with knowledge sources such as universities. The time of existence is not a significant factor in reaching evolution. Although common factors are present in all environments, local particularities, specific characteristics, regional vocations, management leadership and other elements have an impact on park performance.

AMIEM is an assessment tool and a technological product, useful in mapping and evaluating innovation environments.

STIPs are dynamic and maturing, requiring active management and engagement with government and companies.

The results allow a better comprehension of the evolution and management of the STIPs located in the state of Rio de Janeiro. Another contribution lies in the organization of information to design public policies.

The purpose of this paper is to explore last mile delivery (LMD) to the bottom of the pyramid in Brazilian slums, its challenges and how practitioners overcome them. Urban logistics in precarious circumstances is central to the conceptualization.

A qualitative, grounded theory methodology is developed, gathering data from companies delivering to slums in Sao Paulo and Rio de Janeiro, Brazil. Field notes, documents and interviews led to conceptual categories for LMD to slums.

The study indicates that while some standard urban logistics practices can be effective for LMD to slums, such unusual contexts often call for unusual solutions. A model is developed using grounded theory categorization, resulting in five dimensions for LMD to slums: employing locally, giving back, acknowledging criminals, vehicle and location.

The model is a qualitative proposition representing LMD to slums in two major Brazilian cities. Even though slums in different cities/countries may face similar conditions, additional studies are needed to confirm and replicate the model.

Companies that successfully engage in LMD to slums must adapt and develop idiosyncratic practices.

LMD to slums enables a larger portion of bottom of the pyramid consumers to access a wider range of products and work opportunities, contributing to their social inclusion.

The study provides an understanding of LMD in a new context. The model encourages companies to question their current practices, learning from effective LMD experiences implemented by successful practitioners.

Metaheuristic algorithms have been commonly used as an optimisation tool in various fields. However, optimisation of real-world problems has become increasingly challenging with to increase in system complexity. This situation has become a pull factor to introduce an efficient metaheuristic. This study aims to propose a novel sport-inspired algorithm based on a football playing style called tiki-taka.

The tiki-taka football style is characterised by short passing, player positioning and maintaining possession. This style aims to dominate the ball possession and defeat opponents using its tactical superiority. The proposed tiki-taka algorithm (TTA) simulates the short passing and player positioning behaviour for optimisation. The algorithm was tested using 19 benchmark functions and five engineering design problems. The performance of the proposed algorithm was compared with 11 other metaheuristics from sport-based, highly cited and recent algorithms.

The results showed that the TTA is extremely competitive, ranking first and second on 84% of benchmark problems. The proposed algorithm performs best in two engineering design problems and ranks second in the three remaining problems.

The originality of the proposed algorithm is the short passing strategy that exploits a nearby player to move to a better position.

The purpose of this paper is to introduce the development of an innovative mobile laser scanning (MLS) method for 3D indoor mapping. The generally accepted and used procedure for this type of mapping is usually performed using static terrestrial laser scanning (TLS) which is high-cost and time-consuming. Compared with conventional TLS, the developed method proposes a new idea with advantages of low-cost, high mobility and time saving on the implementation of a 3D indoor mapping.

This method integrates a low-cost 2D laser scanner with two indoor positioning techniques – ultra-wide band (UWB) and an inertial measurement unit (IMU), to implement a 3D MLS for reality captures from an experimental indoor environment through developed programming algorithms. In addition, a reference experiment by using conventional TLS was also conducted under the same conditions for scan result comparison to validate the feasibility of the developed method.

The findings include: preset UWB system integrated with a low-cost IMU can provide a reliable positioning method for indoor environment; scan results from a portable 2D laser scanner integrated with a motion trajectory from the IMU/UWB positioning approach is able to generate a 3D point cloud based in an indoor environment; and the limitations on hardware, accuracy, automation and the positioning approach are also summarized in this study.

As the main advantage of the developed method is low-cost, it may limit the automation of the method due to the consideration of the cost control. Robotic carriers and higher-performance 2D laser scanners can be applied to realize panoramic and higher-quality scan results for improvements of the method.

Moreover, during the practical application, the UWB system can be disturbed by variances of the indoor environment, which can affect the positioning accuracy in practice. More advanced algorithms are also needed to optimize the automatic data processing for reducing errors caused by manual operations.

The development of this MLS method provides a novel idea that integrates data from heterogeneous systems or sensors to realize a practical aim of indoor mapping, and meanwhile promote the current laser scanning technology to a lower-cost, more flexible, more portable and less time-consuming trend.