4 resultados citaram: Development and validation of attitudes measurement scales: fundamental and practical aspects

ABSTRACT Purpose: This research aims to validate two scales to measure growth intentions and respective inhibiting factors for individual microentrepreneurs (MEI). Originality/value: The study proposes scales to measure the growth intentions of MEI. It brings an instrument to analyze growth intentions and barriers to growth in a specific context that has not yet been explored. Design/methodology/approach: Two scales were constructed following Hair et al. (2019). They were validated with 134 MEI. Then, exploratory factor and reliability analyses were performed. Findings: The scales were validated and characterized as a multidimensional growth intentions scale consisting of the following dimensions: personal interest, social status, and family background. The growth intentions inhibiting factors scale is composed of the items: personal interest, market assessment, and financial resources. Both scales can be used in education programs and policies for MEI training. Further studies may explore the longitudinal character of growth intentions and focus on measuring growth intentions in segments of high growth potential.

ABSTRACT Context: exploratory factor analysis (EFA) is one of the statistical methods most widely used in administration; however, its current practice coexists with rules of thumb and heuristics given half a century ago. Objective: the purpose of this article is to present the best practices and recent recommendations for a typical EFA in administration through a practical solution accessible to researchers. Methods: in this sense, in addition to discussing current practices versus recommended practices, a tutorial with real data on Factor is illustrated. The Factor software is still little known in the administration area, but is freeware, easy-to-use (point and click), and powerful. The step-by-step tutorial illustrated in the article, in addition to the discussions raised and an additional example, is also available in the format of tutorial videos. Conclusion: through the proposed didactic methodology (article-tutorial + video-tutorial), we encourage researchers/methodologists who have mastered a particular technique to do the same. Specifically about EFA, we hope that the presentation of the Factor software, as a first solution, can transcend the current outdated rules of thumb and heuristics, by making best practices accessible to administration researchers.

RESUMO Contexto: a análise fatorial exploratória (AFE) é um dos métodos estatísticos mais utilizados em administração. No entanto, sua prática corrente coexiste com regras de bolso e heurísticas proferidas há meio século. Objetivo: o propósito deste artigo é apresentar as melhores práticas e recomendações recentes para uma AFE típica em administração através de uma solução prática acessível aos pesquisadores. Métodos: nesse sentido, além de serem discutidas as práticas correntes versus as práticas recomendadas, ilustra-se um tutorial com dados reais no Factor, um software ainda pouco conhecido na área de administração, porém freeware, fácil de usar (point and click) e poderoso. O passo a passo ilustrado no artigo, além das discussões levantadas e de um exemplo adicional, também é disponibilizado no formato de vídeos tutoriais. Conclusão: através da metodologia didática proposta (artigo-tutorial + vídeo-tutorial), incentivamos os pesquisadores/metodologistas que dominam alguma técnica particular a fazerem o mesmo. Especificamente sobre a AFE, esperamos que a apresentação do software Factor, como uma primeira solução, possa transcender as regras de bolso e heurísticas correntes ultrapassadas, ao tornar acessíveis as melhores práticas para os pesquisadores da administração.

ABSTRACT Objective: errors are inevitable in the scholarly pursuit of truth, yet they are often seen as flaws rather than growth opportunities. This paper examines the tension between scholars’ inherent fallibility and rigorous academic research standards, particularly concerning quantitative methods such as exploratory factor analysis (EFA) and partial least squares structural equation modeling (PLS-SEM). The focus is on whether the academic community effectively balances the acceptance of errors as part of the learning process, with the relentless pursuit of truth and how this balance influences the advancement of knowledge within the context of evolving statistical tools needed to improve our understanding of complex global relationships. Provocations: if errors are fundamental to scientific progress, why does the academic community approach them with apprehension? This fear of mistakes may inhibit innovation, especially in fields such as quantitative methods research, where the stakes are high. Another question is whether the accessibility of user-friendly statistical software has led to a superficial understanding of complex methodologies, prioritizing convenience over depth. Conclusions: we advocate for a shift in how the academic community perceives errors toward viewing them as essential to the research process rather than as fatal flaws. Embracing a humble approach to pointing out mistakes and limitations, particularly with quantitative methods such as EFA and SEM, can create a more innovative and progressive research environment. We call for a cultural shift where constructive critiques are balanced with understanding our collective fallibility, with the ultimate goal of producing more impactful scholarship.