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This paper aims to examine the impact of problem-solving activities, emotional experiences and contextual and personal factors on learning from dealing with software-related problems in everyday office work.

To measure the use of problem-solving activities, emotional experiences and the contextual factors of problem characteristics and learning in situ, a research diary was used. To measure team psychological safety (contextual factor) and personal factors, including the Big Five personality traits, occupational self-efficacy and technology self-efficacy, the authors administered a self-report questionnaire. In sum, 48 students from a software company in Germany recorded 240 diary entries during five working days. The data was analysed using multilevel analysis.

Results revealed that asking others and using information from the internet are positive predictors of self-perceived learning from a software-related problem, while experimenting, which was the most common activity, had a negative effect on learning. Guilt about the problem was positively related to learning while working in the office (as opposed to remote work), and feeling irritated/annoyed/angry showed a negative effect. Surprisingly, psychological safety had a negative effect on perceived learning.

Major limitations of the study concern the convenience sample and the disregard for the sequence of the activities.

This study contributes to the limited empirical evidence on employees’ problem-solving activities and informal workplace learning in the software context. To overcome the shortcomings of previous studies using retrospective assessments and in-lab observations, this study uses the diary method to investigate in situ.

The study aims to optimize truck routes by minimizing social and economic costs. It introduces a strategy involving diverse drones and their potential for reusing at DNs based on flight range. In HTDRP-DC, trucks can select and transport various drones to LDs to reduce deprivation time. This study estimates the nonlinear deprivation cost function using a linear two-piece-wise function, leading to MILP formulations. A heuristic-based Benders Decomposition approach is implemented to address medium and large instances. Valid inequalities and a heuristic method enhance convergence boundaries, ensuring an efficient solution methodology.

Research has yet to address critical factors in disaster logistics: minimizing the social and economic costs simultaneously and using drones in relief distribution; deprivation as a social cost measures the human suffering from a shortage of relief supplies. The proposed hybrid truck-drone routing problem minimizing deprivation cost (HTDRP-DC) involves distributing relief supplies to dispersed demand nodes with undamaged (LDs) or damaged (DNs) access roads, utilizing multiple trucks and diverse drones. A Benders Decomposition approach is enhanced by accelerating techniques.

Incorporating deprivation and economic costs results in selecting optimal routes, effectively reducing the time required to assist affected areas. Additionally, employing various drone types and their reuse in damaged nodes reduces deprivation time and associated deprivation costs. The study employs valid inequalities and the heuristic method to solve the master problem, substantially reducing computational time and iterations compared to GAMS and classical Benders Decomposition Algorithm. The proposed heuristic-based Benders Decomposition approach is applied to a disaster in Tehran, demonstrating efficient solutions for the HTDRP-DC regarding computational time and convergence rate.

Current research introduces an HTDRP-DC problem that addresses minimizing deprivation costs considering the vehicle’s arrival time as the deprivation time, offering a unique solution to optimize route selection in relief distribution. Furthermore, integrating heuristic methods and valid inequalities into the Benders Decomposition approach enhances its effectiveness in solving complex routing challenges in disaster scenarios.

The purpose of this paper is to verify how distributed cognition enhances collaborative problem-solving in the context of projects.

Using qualitative research and in-depth interviews, a sample of 32 project managers with experience in traditional and agile methods acting in Brazil and internationally participated in the research process. The analysis process, utilising coding techniques, involved stages: open, axial, coding and selective coding. These stages encompassed the evaluation of categories based on a hierarchy, in order to determine an appropriate level of abstraction that properly explains theoretical findings.

The results indicate that distributed team cognition is significant for collaborative problem-solving. The data from the interviews allowed the proposal of a model of cognition, and the identification of the elements that support it.

Understand how aspects of distributed team cognition can impact the behaviours of the project professional and contribute to problem-solving in the project environment.

The elements observed affects the collaborative problem-solving by presenting a model of distributed cognition, which is composed by directed communication, collective interaction, trust building and collaborative behaviour.

This study compared the results of self-report and ability-based tests of problem-solving abilities of 144 hospitality managers working at hotels and restaurants through an online survey. In the first stage of the study, the managers were asked to fill in the self-report problem-solving ability scale by Tesone et al. (2010). In the second stage of the study, the managers were asked to respond to questions in a case-study-based problem-solving test.

Problem-solving is a key aspect of business process management. This study aims to investigate and compare hospitality managers' actual and claimed (self-report) problem-solving abilities. A lack of unawareness of the actual level of skills may be an important problem as managers who tend to have inflated self-efficacy beliefs are less likely to allocate resources, e.g. time, money and effort, to develop a particular skill or ability they lack. They are also more likely to take risks regarding that skill or ability.

The results of the study showed that there was a major difference between the results of the self-report test and the actual test. This meant that the managers who participated in the study had inflated self-efficacy beliefs regarding their problem-solving abilities, i.e. they operated under the influence of the Dunning–Kruger effect. The study showed that self-report tests that are commonly used in businesses in recruitment and promotion may not provide a correct level of people's abilities. In general, managers who have inflated self-efficacy beliefs are less likely to be interested in developing a particular skill due to the overconfidence arising from their inflated self-efficacy beliefs. The study showed that managers were less likely to allocate resources, e.g. time, money and effort, to develop a particular skill they lack and are more likely to take risks regarding that particular skill.

Managers in the hospitality industry appear to lack problem solving-abilities. While the hospitality managers assigned high marks for their problem-solving abilities in a self-report problem-solving scale and appeared to be performing significantly good overall in problem-solving, they performed poorly in an actual problem solving exercise. It is recommended that businesses rather than depending on self-report problem-solving scales, they should resort to ability-based scales or exercises that actually measure managers' problem-solving abilities. Also, as managers who had formal tourism and hospitality education performed poorly, tourism and hospitality programme managers at universities are recommend to review their syllabi and curriculum so as to help support their graduates' problem-solving abilities.

The study is original as no previous study compared managers' problem-solving abilities by using self-report and ability-based tests. The study has implications for researchers in terms of developing knowledge, ability and skill-based scales in the future. The study has also significant practical implications for the practitioners.

The author aims to develop an employee competency framework for a volatility, uncertainty, complexity and ambiguity (VUCA) environment and propose learning and development (L&D) interventions for organisations and employees to develop competencies for thriving in a VUCA environment.

The framework synthesis method was used to determine employee competencies that are essential in a VUCA world.

The author identified 10 competencies that are essential for employee development in a VUCA world. The author categorised these employee competencies as cognitive (cognitive flexibility, agility mindset and personal ambidexterity), cross-cultural (cross-cultural intelligence and cross-cultural collaboration), analytical (creativity and complex problem solving) and personal effectiveness competencies (personal resilience, continuous learning and adaptive mindset).

The proposed competencies could be used for the personal development of employees and organisations. The VUCA competency framework developed in this study includes behavioural dimensions for each competency, which could be used in self-assessment, recruitment and selection and talent and performance management. Furthermore, the author proposes L&D interventions required for developing these competencies. Overall, this study contributes to human resources (HR) development in the VUCA era by proposing the development of specific individual competencies as necessary conditions for survival and growth.

VUCA competencies empower employees to not only survive but also thrive in an unpredictable and rapidly changing world. By incorporating these competencies in L&D interventions, organisations can help employees develop the necessary competencies to thrive in a VUCA environment, thus contributing to their personal and organisational success.

This work compares the performance of the three boundary element techniques for solving Helmholtz problems: dual reciprocity, multiple reciprocity and direct interpolation. All techniques transform domain integrals into boundary integrals, despite using different principles to reach this purpose.

Comparisons here performed include the solution of eigenvalue and response by frequency scanning, analyzing many features that are not comprehensively discussed in the literature, as follows: the type of boundary conditions, suitable number of degrees of freedom, modal content, number of primitives in the multiple reciprocity method (MRM) and the requirement of internal interpolation points in techniques that use radial basis functions as dual reciprocity and direct interpolation.

Among the other aspects, this work can conclude that the solution of the eigenvalue and response problems confirmed the reasonable accuracy of the dual reciprocity boundary element method (DRBEM) only for the calculation of the first natural frequencies. Concerning the direct interpolation boundary element method (DIBEM), its interpolation characteristic allows more accessibility for solving more elaborate problems. Despite requiring a greater number of interpolating internal points, the DIBEM has presented higher-quality results for the eigenvalue and response problems. The MRM results were satisfactory in terms of accuracy just for the low range of frequencies; however, the neglected higher-order primitives impact the accuracy of the dynamic response as a whole.

There are safe alternatives for solving engineering stationary dynamic problems using the boundary element method (BEM), but there are no suitable comparisons between these different techniques. This paper presents the particularities and detailed comparisons approaching the accuracy of the three important BEM techniques, aiming at response and frequency evaluation, which are not found in the specialized literature.

The study aims to assess students' perceived mastery of reasoning-for-complexity competency and its sub-competencies in a sample of students in a Latin American university. The intention was to identify statistically significant differences between a population of men and women with similar sociocultural characteristics, assessing whether gender could be a factor for educational institutions to consider when implementing strategies to develop this competency.

The eComplexity instrument was applied to 370 undergraduate students in their first to ninth semesters in a private university in Western Mexico. Descriptive statistics were analyzed to determine the mean and standard deviation indicators and were tested for statistical significance. The convenience sampling methodology ensured that there were students from all semesters and a diversity of majors. The sampling aimed for a balance of men and women, resulting in 189 women and 181 men.

The results confirmed no statistically significant evidence to indicate differences between men and women in their perceived mastery of the reasoning-for-complexity competency in general. However, statistically significant differences were found in the perceived achievements of the sub-competencies of systems, critical and scientific thinking, which comprise the overall competency. Women presented a higher average perception of systemic and critical thinking achievement, and men had a higher perception of scientific thinking. The authors concluded that social and cultural elements influence the perception of achievement that men and women develop in thinking and solving problems.

Governments and educational institutions must establish training programs that do not follow gender stereotypes and promote reasoning-for-complexity skills equitably in men and women. It is necessary to create more scientific and academic spaces and projects involving women in the sciences; countries must emphasize this to improve their scientific competency. Only in this way will it be possible to reverse the perception that men and women have of their problem-solving skills and abilities, which, as this study shows, are more a matter of culture than capabilities.

Unlike previous studies, which analyze the competency of complex thinking in a particular way among its sub-competencies, this research sought comprehensive measurement. Furthermore, beyond measuring competency development, this study aimed to measure the perception of achievement. The authors believe this is the first step towards identifying elements of the social imagination that limit the formation of scientific thinking among women in Latin America.

We develop and test an innovative approach to teaching financial statement analysis (FSA) and assessing student learning outcomes based on making complex stock investment decisions compared to professional analysts. We train students to apply FSA and emphasize interdisciplinary factors and high integrative complexity. Our innovative FSA teaching approach, which we apply in an MBA financial reporting course, involves the instructor lecturing on FSA as a tool for integrative and complex decision making, students researching and applying FSA to public companies, and presenting the rationale for individual and group stock investment decisions. The instructor gives high-quality and timely feedback on the students’ application of FSA with a focus on investment judgments involving critical thinking, problem-solving, and teamwork skills. Our detailed efficacy analysis shows that our FSA teaching approach is effective. Students who perceive a public company to have credible management, effective competitive strategy, and an acceptable level of financial flexibility make comparable individual and group stock investment decisions as professional analysts.

The challenges facing 21st-century society are becoming increasingly complex, requiring the development of new citizen competencies. This study aims to validate an educational model focused on developing complex thinking in higher education students. Current educational models lack future-ready competencies, necessitating the emergence of new models to guide future generations toward the common good.

This was an adaptation of the causal-layered analysis (CLA) applied to 415 participants from higher education institutions in Mexico, Panama and Spain. Sessions were designed to present the proposed educational model and explore participants’ perceptions of its significance and contributions to future education.

Key findings include the following: participants perceived complexity as difficult and challenging; causes of problems were linked to outdated educational models requiring replacement by those that develop students’ competencies; participants envisioned changes that would develop individuals capable of understanding and transforming society; and participants recognized the model’s transformative potential, offering a novel proposal for 21st-century education.

This research sought to gather opinions from different stakeholders using the CLA methodology, providing a deep understanding of participants’ perspectives on the proposed solution.

In the realm of education, there has been an increasing emphasis on developing analytical thinking (AT) in the past few years. This systematic review focuses on an analysis of journal publications that have explored AT within the context of science, technology, engineering and mathematics (STEM) education. This analysis investigated four primary issues: (1) the operational definition that was used; (2) the types of theories that were used; (3) the interventions that were implemented to enhance AT skills; and (4) the research designs that were used.

To ensure a comprehensive and thorough review, we used the guidelines of preferred reporting items for systematic reviews and meta-analysis.

A comprehensive review of 28 pertinent scholarly articles reveals that scholars frequently rely on the concepts proposed by Anderson (2002), Marzano and Kendall (2008), Rodrangsee and Tuntiwongwanich (2021) and Suyatman et al. (2021) to establish a framework for delineating the competencies associated with analytical thinking (AT). Quasi-experimental designs were the most frequently used research designs in the studies analysed, followed by research and development approaches and then correlational designs. Most researchers have focused on investigating the effectiveness of problem-based learning as an intervention for improving AT skills. However, most research indicates that the theories or theoretical frameworks used to guide the research must be evident.

To the extent the authors know, this study represents the initial comprehensive examination of analytical thinking in STEM education. It presents a consolidated summary of the available evidence, assessing its quality and bringing it together in a single resource.