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This study aims to measure the degree of innovation of micro and small industrial companies in the West and Southwest metropolitan regions of the city of São Paulo, through a survey with 203 firms in the metallurgy sector.

The research had a quantitative and descriptive focus and used as methodology the validated and international approach known as Innovation Radar.

The degree of innovation in these micro and small companies is low; thus, the authors could not characterize them as systemic innovators. Most of them are little innovative, although some were classified as occasional innovators. The dimensions organization, processes, presence, supply chain and added value were the least developed.

To carry out similar studies in other Brazilian regions, to compare results and draw new conclusions, or even check if the degree of innovation present in micro-firms of these regions would not be even lower; to monitor the evolution of companies through a longitudinal study, to detect improvements in the degree of innovation; and to conduct a qualitative research that can deepen questions on the results of our study, such as the reasons why this type of company does not adopt innovative practices, or even the real suitability of the Innovation Radar model for micro and small enterprises (MSEs). We observed that some dimensions proved to be too sophisticated for these companies, such as R&D investments and the adoption of technological advances.

The study shows that the degree of innovation measured by the Innovation Radar is a useful and initial measure to check an innovative attitude in micro and small companies. It can also drive the actions that should be prioritized to stimulate the culture of innovation in SME. However, it does not allow to answer why this type of organization does not adopt innovative practices as a management attitude. Regarding its contribution, the authors expect that the paper may bring an awareness of managers and owners of micro and small companies for the need to foster innovative practices that can help increase the competitiveness and survival of this type of organization.

In Brazil, despite the fact that MSEs represent 98 per cent of the existing companies, and are mainly responsible for job creation, their leaders have a low concern for innovative practices.

The study contributes to identify the degree of innovation of these firms, which comprise a representative and strategic segment of the city’s economy, by checking to what extent an innovative attitude is effectively present in this sector. The theoretical contribution of this study regards the appropriateness of mechanisms or methodologies created to measure the degree of innovation in large organizations. Dimensions such as technological platform, brand, innovative ambience, degree of organization or systematization of processes, which are frequently considered for companies in general, and especially for large ones, are not sufficient or, instead, too sophisticated to allow an effective measurement of the degree of innovation in MSE. Thus, this study provides information for designing more effective ways to evaluate the degree of innovation that take into account MSE’s specificities, which can be considered innovation efforts, such as simple process improvements, professional development of teams, and actions to seize ideas and opportunities, among others.

Recent studies have shown that people who attend electronic dance music events and use drug checking services (DCS) are a predominantly white male, highly educated middle-class population. However, there is still a lack of data beyond sociodemographic characteristics that must be addressed. This paper aims to describe the drug use patterns and protective behavior strategies (PBS) used by testers and nontesters at Boom Festival 2018 and analyze the relationship between these behaviors and the decision to use the DCS.

This is an exploratory research based on a cross-sectional design using baseline data collected at the Boom Festival from testers (N = 343) and nontesters (N = 115).

Nontesters presented, in general, slightly higher frequencies of use for most drugs, whereas testers tended to adopt PBS more frequently. Moreover, testers planned their drug use more often than nontesters and set more limits on the amount of drugs they used in one session. Both of these behaviors work as predictors for using the DCS.

Our data suggest that DCS might not be easily accessible to all people who use drugs, reaching almost exclusively highly educated people that already apply several harm reduction strategies. Actions should be taken to promote service accessibility.

To the best of the authors’ knowledge, this paper is the first to compare the demographics, drug use and PBS adoption of DCS users with nonusers who attended the same festival.

Although the term interpersonal leadership has been well established within the literature, there remains a dearth of theoretically derived models that specifically address the comprehensive nature of the underlying leader behaviors and activities. The intent of the present article is to attempt to synthesize the existent leadership models, behaviors, and factors to arrive at a coherent conceptual model of interpersonal leadership that can inform efficient and effective leadership education programs. The resulting model included 13 primary factors integrated within a hierarchical framework. Leadership educators are recommended to adopt or adapt the proposed model while developing educational curriculum and interventions.

Policy leadership infiltrates the lives of citizens everywhere. Though this type of leadership is implicit and ubiquitous, a theoretically-based model specifically intended for policy leaders is not readily available in academic literature. This article serves to address this gap by proposing a conceptual model of the policy leadership framework. The model expounds upon previous literature and identifies 16 areas vital to the policy process. Implications of the model relate to equipping leadership educators in the classroom and in the community with enhanced policy leadership research and curriculum.

The paper describes patterns of study on innovation in the regional economic resilience literature regarding methods and findings.

This study is a descriptive one and it uses, as a method, the scoping review based on Scopus and Web of Science databases. Forty-eight theoretical-empirical papers were thematically coded, and analyses were conducted using R packages and MaxQDA.

Innovation has been used narrowly in the regional resilience literature, considering the variables, the types of shocks and the analyzed loci. From the sampled papers, this study suggests that, depending on the operationalization, the addressed relationship can be positive or negative, which still needs further investigation. In addition, the study identified two lines of research. The first, characterized by quantitative research, secondary sources and multivariate analyses, focuses on testing predictive regional resilience models based on innovation-related variables. The second, characterized by qualitative or multi-method approaches, is more concerned with explaining the knowledge accumulation and the learning capacity related to regional innovation.

The paper’s findings show a restricted view of the innovation–resilience relationship. Although this study does not present a meta-analysis, it reveals gaps for future research. Some suggestions can be highlighted, such as (1) expanding knowledge about innovation as a predictor of resilience, (2) the theoretical development of this relationship to guide empirical investigations and (3) studies that consider the meso or micro level, approaching the role of actors in fostering innovation in the regional resilience process.

This paper fulfills an identified need to investigate how innovation has been operationalized in regional resilience empirical research.

This study aims to seek to analyse the relationships between profitability, productivity, external debt and growth in SMEs. The authors also analyse firm size and age as explicative variables of small and medium-sized enterprise (SME) growth.

In this paper the data were collected for 3309 SMEs for the period 2010–2019. The authors estimate the model using the system generalised method of moments dynamic estimator.

The results show that after a certain level of profitability, this determinant positively impacts SME growth. Productivity influences positively the firm growth. There is a positive effect of external debt on SME growth, which can be explained by the insufficiency of internally generated funds. The authors obtained a negative signal between size and firm growth, contradicting Gibrat's Law (1931). Moreover, the results suggest that SMEs grow less after a certain age, suggesting that small firms grow less after reaching the minimum scale of efficiency.

For SME owner-managers, this study enhances the importance of profitability and labour productivity for firm growth. For policymakers, the results suggest the need for favourable conditions for SMEs in accessing external finance.

Profitability negatively impacts on SME growth. However, the authors found that above a certain level of profitability, probably, as firms accumulate retained earnings, profitability has a positive effect on SME growth. Moreover, this study shows that labour productivity and debt positively impact on SME growth, evidencing the importance of the availability of financial resources to sustain the growth of these firms.

Three Coupled Model Intercomparison Project Phase 5 models involved in the G4 experiment of the Geoengineering Model Inter-comparison Project (GeoMIP) project were used to investigate the impact of stratospheric aerosol injection (SAI) on the mean surface air temperature and precipitation extremes in Africa.

This impact was examined under G4 and Representative Concentration Pathway (RCP) 4.5 scenarios on the total precipitation, the number of rainy days (RR1) and of days with heavy rainfall (R20 mm), the rainfall intensity (SDII), the maximum length of consecutive wet (CWD) and dry (CDD) days and on the maximum rainfall in five consecutive days (Rx5day) across four regions: Western Africa (WAF), Eastern Africa (EAF), Northern Africa and Southern Africa (SAF).

During the 50 years (2020–2069) of SAI, mean continental warming is −0.40°C lower in G4 than under RCP4.5. During the post-injection period (2070–2090), the temperature continues to increase, but at a lower rate (−0.19°C) than in RCP4.5. During SAI, annual rainfall in G4 is significantly greater than in RCP4.5 over the high latitudes (especially over SAF) and lower over the tropics. The termination of SAI leads to a significant increase of rainfall over Sahel and EAF and a decrease over SAF and Guinea Coast (WAF).

Compared to RCP4.5, SAI will contribute to reducing significantly regional warming but with a significant decrease of rainfall in the tropics where rainfed agriculture account for a large part of the economies. After the SAI period, the risk of drought over the extratropical regions (especially in SAF) will be mitigated, while the risk of floods will be exacerbated in the Central Sahel.

To meet the Paris Agreement, African countries will implement mitigation measures to contribute to keep the surface air temperature below 2°C. Geoengineering with SAI is suggested as an option to meet this challenge, but its implication on the African climate system needs a deep investigation in the aim to understand the impacts on temperature and precipitation extremes. To the best of the authors’ knowledge, this study is the first to investigate the potential impact of SAI using the G4 experiment of GeoMIP on temperature and precipitation extremes of the African continent.

This paper reviews the current literature on theoretical and methodological issues in discrete choice experiments, which have been widely used in non-market value analysis, such as elicitation of residents' attitudes toward recreation or biodiversity conservation of forests.

We review the literature, and attribute the possible biases in choice experiments to theoretical and empirical aspects. Particularly, we introduce regret minimization as an alternative to random utility theory and sheds light on incentive compatibility, status quo, attributes non-attendance, cognitive load, experimental design, survey methods, estimation strategies and other issues.

The practitioners should pay attention to many issues when carrying out choice experiments in order to avoid possible biases. Many alternatives in theoretical foundations, experimental designs, estimation strategies and even explanations should be taken into account in practice in order to obtain robust results.

The paper summarizes the recent developments in methodological and empirical issues of choice experiments and points out the pitfalls and future directions both theoretically and empirically.

Halal integrity assurance is the primary objective of Halal supply chain management. Several halal-related risks are present that have the potential to breach halal integrity. Therefore, this study aims to develop the framework for the assessment of halal-related risk from a supply chain perspective.

Risk related to halal is identified through the combined approach of the systematic literature review and experts’ input. Further, these risks are assessed using the integrated approach of intuitionistic fuzzy number (IFN) and D-number based on their severity score. This integrated approach can handle fuzziness, inconsistency and incomplete information that are present in the expert’s input.

Eighteen significant risks related to halal are identified and grouped into four categories. These risks are further prioritised based on their severity score and classified as “high priority risk” or “low priority risks”. The findings of the study suggests that raw material status, processing methods, the wholesomeness of raw materials and common facilities for halal and non-halal products are more severe risks.

This study only focusses on halal-related risks and does not capture the other types of risks occurring in the supply chain. Risks related to halal supply chain management are not considered in this study. Prioritisation of the risks is based on the expert’s input which can be biased to the experts' background.

The proposed risk assessment framework is beneficial for risk managers to assess the halal related risks and develop their mitigation strategies accordingly. Furthermore, the prioritisation of the risks also assists managers in the optimal utilisation of resources to mitigate high-priority risks.

This study provides significant risks related to halal integrity, therefore helping in a better understanding of the halal supply chain. To the best of the authors' knowledge, this is the first comprehensive study for developing a risk assessment model for the halal supply chain.

To address requirements and specifications of construction project, academics need to build a project classification model. In recent years, project success concept, particularly on large-scale construction projects, has been a controversial issue, especially in developing countries. Hence, in this paper, after introducing a sustainable success index (SSI), a novel method called “rough set approach” had been adopted to induce decision rules and to classify construction projects. The paper aims to discuss these issues.

At first, 20 effective success factors and 15 success criteria based on three pillars of sustainability of economy, society and environment had been categorized. The research data used for analysis had been collected from 26 large-scale construction projects in Iran and five other countries. After collecting data collection, observations had been analyzed and 51 decision rules were generated, and the projects were classified. Eventually, in order to evaluate the performance of the generated rules, confusion matrix was applied, and the model was validated.

The results of the present study show that rough set theory (RST) can be an effective and valuable tool for building expert systems. Practical applications of these results along with limitations and future research are described.

Perhaps for the first time, in the present study, a number of large-scale construction projects are classified based on SSI. Applying RST for building rule-based system and classifying projects in construction project area are novel attempts undertaken in this paper. The rules induced in this study can be applied to develop a sustainable success prediction model in the future studies.