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This study aims to analyze the university environment’s role in the intention–action gap (IAG)of highly successful startup founders in an emerging market.

Using multiple regression analysis, this study analyzed data collected from 314 founders representing 99 successful startups (289 valid observations), renowned for their high funding and value operating in an emerging market, Brazil.

The results demonstrate that extracurricular activities and exchange programs lead to a reduced IAG while living in a significant economic center extends it. Computer science and industrial engineering students show reduced IAGs. Studying together with future co-founders also leads to reduced gaps.

The study contributes to the microfoundations theory by presenting new interactions between students and the university environment that influence entrepreneurial action. Limitations are related to the sample, limited to Brazilian founders and selected only through venture capital firms’ filters.

This study also provides practical insights to the universities’ leaders on how they can create programs that improve the rate of startup creation, potentially leading to successful companies.

This study investigates the association between the university role and the entrepreneur’s IAG in emerging markets. The entrepreneur’s IAG is still a relatively new phenomenon explored in entrepreneurship. Even less understanding and limited empirical data exist on successful startups from emerging markets. This study drew on the microfoundations literature to answer how universities in emerging markets could address specific resources and entrepreneurship programs to reduce the IAG among students and alumni.

Total productive maintenance consists of strategies and procedures that aim to guarantee the entire functioning of machines in a production process so that production is not interrupted and no loss of quality in the final product occurs. Planned maintenance is one of the eight pillars of total productive maintenance, a set of tools considered essential to ensure equipment reliability and availability, reduce unplanned stoppage and increase productivity. This study aims to analyze the influence of statistical reliability on the performance of such a pillar.

In this study, we utilized a multi-method approach to rigorously examine the impact of statistical reliability on the planned maintenance pillar within total productive maintenance. Our methodology combined a detailed statistical analysis of maintenance data with advanced reliability modeling, specifically employing Weibull distribution to analyze failure patterns. Additionally, we integrated qualitative insights gathered through semi-structured interviews with the maintenance team, enhancing the depth of our analysis. The case study, conducted in a fertilizer granulation plant, focused on a critical failure in the granulator pillow block bearing, providing a comprehensive perspective on the practical application of statistical reliability within total productive maintenance; and not presupposing statistical reliability is the solution over more effective methods for the case.

Our findings reveal that the integration of statistical reliability within the planned maintenance pillar significantly enhances predictive maintenance capabilities, leading to more accurate forecasts of equipment failure modes. The Weibull analysis of the granulator pillow block bearing indicated a mean time between failures of 191.3 days, providing support for optimizing maintenance schedules. Moreover, the qualitative insights from the maintenance team highlighted the operational benefits of our approach, such as improved resource allocation and the need for specialized training. These results demonstrate the practical impact of statistical reliability in preventing unplanned downtimes and informing strategic decisions in maintenance planning, thereby emphasizing the importance of your work in the field.

In terms of the originality and practicality of this study, we emphasize the significant findings that underscore the positive influence of using statistical reliability in conjunction with the planned maintenance pillar. This approach can be instrumental in designing and enhancing component preventive maintenance plans. Furthermore, it can effectively manage equipment failure modes and monitor their useful life, providing valuable insights for professionals in total productive maintenance.

This paper aims to identify the profiles of beginner and experienced consumers (BCs and ECs) of craft beer and evaluate their perception, knowledge and purchase intention.

A total of 291 craft beer consumers including 148 BCs and 143 ECs participated in the study, which was divided into 2 stages: quantitative research through a questionnaire and conjoint analysis.

BCs are mostly female, with a lower age, income and consumption frequency, presented a shallower understanding of International Bitterness Units (IBU) and considered 7.0% alcohol by volume (ABV) as a high-relative value in craft beers. Otherwise, ECs are mostly men with a higher age and consumption frequency, and they don't consider 50 IBU as high bitterness. The results of conjoint analysis indicate that both groups of consumers attribute greater relative importance to ABV and nonalcoholic beers had lower purchase intentions. Finally, the authors show that beer with 30 IBU and 4.5% ABV is preferred by both BCs and ECs.

The authors' identification about the distinct behaviors of different groups of consumers, based on their consumption time of craft beer, as managerial implications for industries producing craft beer and, as a theoretical contribution, the authors have defined “BCs” and “ECs” based on the experiences with and durations of craft beer consumption.

The increasing accumulation of synthetic plastic waste in oceans and landfills, along with the depletion of non-renewable fossil-based resources, has sparked environmental concerns and prompted the search for environmentally friendly alternatives. Biodegradable plastics derived from lignocellulosic materials are emerging as substitutes for synthetic plastics, offering significant potential to reduce landfill stress and minimise environmental impacts. This study highlights a sustainable and cost-effective solution by utilising agricultural residues and invasive plant materials as carbon substrates for the production of biopolymers, particularly polyhydroxybutyrate (PHB), through microbiological processes. Locally sourced residual materials were preferred to reduce transportation costs and ensure accessibility. The selection of suitable residue streams was based on various criteria, including strength properties, cellulose content, low ash and lignin content, affordability, non-toxicity, biocompatibility, shelf-life, mechanical and physical properties, short maturation period, antibacterial properties and compatibility with global food security. Life cycle assessments confirm that PHB dramatically lowers CO₂ emissions compared to traditional plastics, while the growing use of lignocellulosic biomass in biopolymeric applications offers renewable and readily available resources. Governments worldwide are increasingly inclined to develop comprehensive bioeconomy policies and specialised bioplastics initiatives, driven by customer acceptability and the rising demand for environmentally friendly solutions. The implications of climate change, price volatility in fossil materials, and the imperative to reduce dependence on fossil resources further contribute to the desirability of biopolymers. The study involves fermentation, turbidity measurements, extraction and purification of PHB, and the manufacturing and testing of composite biopolymers using various physical, mechanical and chemical tests.

This study aims to propose an integrated model involving concepts of sustainability and social innovation (SI) in higher education institutions (HEIs).

Based on a literature review, the authors were able to systematize sustainability and SI knowledge, in an integrated manner. Hence, the authors sought to develop a theoretical model that would integrate categories, indicators and sub-indicators, to review initiatives in HEIs in the sustainability and SI domains. The results indicated four major categories: mission, vision and values; curriculum; campus; and healthy environment. The integrated model was applied and validated in a Brazilian educational group, using the main corporate reports as data sources.

For the educational group analyzed in this study, the themes of sustainability and SI are explicitly and implicitly expressed in the mission, vision and values category. In the curriculum category, these themes are presented through the contents of cross-disciplines in all undergraduate courses, and also through outreach activities, integrating sustainability and SI in a theoretical and/or practical way. Regarding the campus category, the mention is explicit and the HEI works with initiatives aimed at achieving a “green” campus. In the healthy environment category, the educational group studied gives priority to the establishment of a safe and healthy work environment, focusing on labor rights and relations with society.

This work contributes to the advancement of research on the promotion of sustainability and SI in HEIs, proposing an innovative integrated model of analysis for the topics covered.

The purpose of this study is to analyze the systematic relationships among dynamic capabilities in startups’ survival.

This study is based on a systematic literature review on dynamic capabilities related to startups’ survival, following the content analysis approach.

This study presents four different perspectives of analysis about dynamic capabilities from resources exchange and business factors that meet needs of startups' survival. It also points out new area for future research in this field. In doing so, this study differentiates itself by its approach not limiting dynamic capabilities research and enriching entrepreneurs' capability theory.

By indicating an evolution of dynamic capabilities theory among tangible and intangible resources exchange in a more favorable adaptation to startups growth, this study boosters and contributes to the society, economy in general and to the science of business management in various perspectives such as overcoming cognitive barriers, entrepreneur’s commitment, innovation capabilities and knowledge capacity of startups.

This study amplifies dynamic capabilities vision in startups’ survival as one of the main sources for growth in this type of organizations. It also develops a deeper understanding about new avenues for dynamic capabilities theory among tangible and intangible resources exchange.

This paper aim to propose a methodological mapping approach for the evaluation of dissertations and theses of graduate programs in the area of environmental sciences in Brazil in relation to the UN sustainable development goals (SDGs).

The research is characterized as exploratory with qualitative/quantitative approach. The proposed model was developed as a computational algorithm with a pilot being adopted as a professional master in national network for teaching in environmental sciences (ProfCiAmb) comprising associated courses from nine Brazilian public universities. 230 dissertations completed between 2018 and 2020 were analyzed.

A total of 266 correlations were identified between the texts and descriptors of each SDG. Correlation values between 0.100 (minimum value – Vmin) and 0.464 (maximum value – Vmax) were observed. SDG 4 – Quality Education (Vmax = 0.399) and SDG 6 – Drinking Water and Sanitation (Vmax = 0.464) were those with the highest correlation values, followed by SDG 3 – Health and Well-Being (Vmax = 0.299) and SDG 17 – Partnerships and Means of Implementation (Vmax = 0.249).

The construction of the computational algorithm provided consistent quantitative analyses with potential to contribute to the improvement of the multidimensional evaluation of graduate studies, as well as to support public policies related to teaching and research and strategic planning of the programs.

The relevance of this study lies in the creation of a model that involves the creation of metrics and tools regarding the impact of graduate studies on society.

Owing to the dramatic rise of FinTech credit in the financial sector, this study describes its knowledge and intellectual structure and paves the way for future research.

The study employs citation analysis, keyword analysis, co-author analysis, co-citation analysis and bibliographic coupling on 268 peer-reviewed articles published during 2010–2021 and extracted from the Web of Science database.

Research on FinTech credit has picked up momentum from 2016, with majority contributions from China, followed by UK and USA. International Journal of Bank Marketing is found to be the most productive journal. Co-citation analysis reveals that past studies have focused on three dominant themes, viz. (a) factors that influence user intention to adopt technological products and services (b) borrowers' and lenders' characteristics that impact fund-raising in FinTech credit platforms and (c) evolution of FinTech market over the years. Bibliographic coupling reveals that recent trends in FinTech credit include (a) impact of emerging technologies like blockchain, artificial intelligence, big data on financial system, (b) factors that encourage consumers to adopt the FinTech products and services, (c) mechanisms by which FinTechs have transformed formal credit markets, (d) factors that lead to successful fundraising in FinTech platforms and (e) critical perspectives on digital lending platforms.

To the best of the authors' knowledge, this is a pioneering study undertaking an exhaustive analysis of FinTech credit as a research area. The study offers valuable insights on potential topics of research in FinTech credit domain like investigating Balance Sheet Lending Model, investigating the impact of FinTechs on financial system, and new markets by collaborating with scholars of other regions.

This study aims to apply for the first time in literature a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm and test the sensors' configuration found in a delamination identification case study.

This work aims to study the damage identification in an aircraft wing using the Lichtenberg and multi-objective Lichtenberg algorithms. The former is used to identify damages, while the last is associated with feature selection techniques to perform the first sensor placement optimization (SPO) methodology with variable sensor number. It is applied aiming for the largest amount of information about using the most used modal metrics in the literature and the smallest sensor number at the same time.

The proposed method was not only able to find a sensor configuration for each sensor number and modal metric but also found one that had full accuracy in identifying delamination location and severity considering triaxial modal displacements and minimal sensor number for all wing sections.

This study demonstrates for the first time in the literature how the most used modal metrics vary with the sensor number for an aircraft wing using a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm.

Entrepreneurial intention is one of the main predictors of venture creation. However, the approaches used to analyze the entrepreneurial intention and venture creation are mostly linear approaches, leaving aside the fact that new ventures arise in a context characterized by fluctuations and instability, especially in emerging economies where economic and social factors are highly variables. Nevertheless, a dynamic approach could best represent its behavior. This study aims to propose an alternative approach and a starting point for more complex dynamic models in the entrepreneurship process that surpass the limitation of the current linear methodologies and allow gathering isolated studies' contributions.

This study proposes a method to shed light on the processes related to the venture creation process and entrepreneurial intention by designing a system dynamics simulation model.

The results reveal that the delayed effect of expectations produces a growing tendency in project creation, venture establishment and venture creation. Likewise, the entrepreneurial intention is not a static variable; it changes by the system’s dynamics and disturbs the venture creation process, which produces an increase in oscillations in the model and, therefore, reduces the project’s growth and venture creation.

This model is a generic approach for the study of venture creation and entrepreneurial intention. The model can analyze entrepreneurial intention and venture creation in different contexts, adjusting the different model parameters. The authors run a sensitivity analysis to encompass deviation from the parameter established and the uncertainty about them. However, the empirical data used for the model’s testing, in this case, correspond to an approximation to the behavior of venture creation in Colombia, which is considered an emerging economy. The model proposed does not pretend to incorporate all the variables and phenomena about entrepreneurship.

The approach suggested in this work aims to conceptualize venture creation as a complex process that emerges from the occurrence and combination of simpler states, instead of activities that represent building blocks. In addition, the term “entrepreneurial process” is defined as a composite of different perspectives that use a series of multidisciplinary theories to address the topic.