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Digital entrepreneurship is the key to economic survival and the lantern of jobs in developing countries. The debate about the challenges facing early digital entrepreneurs (DEs) in developing countries is still ambiguous. This study attempts to fulfill the gap with an in-depth examination of Jordan.

Referring to a digital start-up database hosted by the Ministry of Digital Economy and Entrepreneurship in Jordan, the study interviews a random sample of (n = 45) early (less than one-year seniority) DEs. Thematic analysis is carried out facilitated by NVivo 20 software. E-Commerce, agriculture technology, data and artificial intelligence and entertainment were at the top of the interviewed start-ups.

Nine challenges were observed, critically analyzed and discussed. The challenges are (1) the lack of realistic funding in terms and guarantees; (2) the negligence of guidance and advisory of incubators and entrepreneurship centres; (3) the emergence of unexpected risks; (4) the stringent economic situation; (5) competition; (6) legal and legislative obstacles; (7) obstacles to accessing markets; (8) team management and finally (9) disorganization in the entrepreneurial environment. The study sets recommendations to support early DEs in their journey.

This study highlights the significant implications for aspiring DEs by focusing on some challenges that might face their start-ups such as institutional, technology and local dimensions of context and measures to develop the entrepreneurial and digital competencies. This includes sustainable funding, poor direct guidance and advisory, unexpected failures/risks, and economic obstacles. This study might be considered a road map for the decision-makers to build their strategies for eliminating the main barriers for early DEs and start-ups.

Although recent literature discussed the challenges of entrepreneurs in Jordan, this is the first that identifies early DEs’ challenges and uses 45% samples of the community.

The purpose of this study was to examine the lived experiences of working mothers during the first year of the COVID-19 pandemic and assess their perceptions of the types of training opportunities that would help advance their careers as they navigated pandemic-related challenges.

In study 1, 53 participants responded to an online survey that included open-ended questions regarding the impact COVID-19 has had on their careers and desires they have for training to ameliorate these concerns. For study 2, 10 participants completed an interview that included open-ended questions regarding workplace changes and professional development/training opportunities since the pandemic.

Thematic analysis showed mothers facing several setbacks in their careers, including delays, loss of hours and wages, childcare stressors and strained or lost relationships with colleagues and supervisors. A small number of participants also reported some surprisingly positive experiences, such as a push toward career innovation. Participants reported little to no exposure to career development opportunities and expressed a desire for training for leadership and interpersonal connection in the workplace.

Although quantitative data have been helpful in identifying and quantifying growing gender gaps in work during the pandemic, the qualitative analyses the authors used highlight how recent difficulties encountered by working mothers risk a growing gender gap in work and career mobility as women in the leadership pipeline struggle with challenges. Further, the findings suggest ways that women in management can support the working mothers on their staff, including by suggesting ways additional training may address some concerns.

The purpose of this study is to investigate how professionals learn from varying experiences with errors in health-care digitalization and develop and use negative knowledge and digital ignorance in efforts to improve digitalized health care.

A two-year qualitative field study was conducted in the context of a public health-care organization working with digital patient communication. The data consisted of participant observation, semistructured interviews and document data. Inductive coding and a theoretically informed generation of themes were applied.

The findings show that both health-care and digital communication professionals learn through experiences with digital “rule-” and “knowledge-based” errors in patient communication and develop negative knowledge and awareness of digital ignorance. In their joint efforts, they use negative knowledge to “bend the rules” and to explore digital ignorance in efforts to improve patient communication.

This study provides insight into the importance of collaboration between professionals with varying experience of errors in digitalizing patient communication. Such collaboration is required to acknowledge own shortcomings and create complementary negative knowledge to improve digital patient communication. This is particularly important when working with innovative digitalization in health care.

Path planning is an important part of UAV mission planning. The main purpose of this paper is to overcome the shortcomings of the standard particle swarm optimization (PSO) such as easy to fall into the local optimum, so that the improved PSO applied to the UAV path planning can enable the UAV to plan a better quality path.

Firstly, the adaptation function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself. Secondly, the standard PSO is improved, and the improved particle swarm optimization with multi-strategy fusion (MFIPSO) is proposed. The method introduces class sigmoid inertia weight, adaptively adjusts the learning factors and at the same time incorporates K-means clustering ideas and introduces the Cauchy perturbation factor. Finally, MFIPSO is applied to UAV path planning.

Simulation experiments are conducted in simple and complex scenarios, respectively, and the quality of the path is measured by the fitness value and straight line rate, and the experimental results show that MFIPSO enables the UAV to plan a path with better quality.

Aiming at the standard PSO is prone to problems such as premature convergence, MFIPSO is proposed, which introduces class sigmoid inertia weight and adaptively adjusts the learning factor, balancing the global search ability and local convergence ability of the algorithm. The idea of K-means clustering algorithm is also incorporated to reduce the complexity of the algorithm while maintaining the diversity of particle swarm. In addition, the Cauchy perturbation is used to avoid the algorithm from falling into local optimum. Finally, the adaptability function is formulated by comprehensively considering the performance constraints of the flight target as well as the UAV itself, which improves the accuracy of the evaluation model.

The amount of expenditure required to scale up smart infrastructure projects is often enormous. Public–private partnership (PPP) is one of the proposed and viable solutions for addressing the financial issues of smart infrastructure projects. However, the most important criterion in choosing PPP over other procurement methods is that the project under the PPP method should deliver the best value for money (VFM) while also including defined economic and social objectives, rather than relying exclusively on efficiency factors. While PPP provides a variety of advantages for developing infrastructure, significant challenges may arise as a result of smart infrastructure initiatives. Diverse PPP approaches have been used to build smart infrastructure around the world, with varying degrees of success. The purpose of this study is to identify the VFM factors that are suitable for smart infrastructure projects and to examine the impact of their interrelationships.

The methodology for this study consisted of three stages: identifying VFM factors in PPP for smart cities based on an extensive literature review, analyzing data from a sample of 90 PPP practitioners using a Likert scale questionnaire and estimating interrelationships among VFM factors using structural equation modeling (SEM).

After performing a SEM analysis on the gathered data, the best fitted measurement model consisted of 11 VFM factors acting as indicators of three latent variables for smart infrastructure projects (clear output specification for measuring performance, efficient dispute resolutions, optimized risk allocation and business models, improved and integrated community services, economic sustainability, appropriate capital structure and collaterals, smart asset management, diffusion of smart technologies, technical innovation, Ince) and three clusters of their interrelations (economic sustainability, integration drive, optimization and smart technology).

This research has resulted in a useful and readily applicable list of factors and clusters of value for money criteria for the implementation of PPP in smart infrastructure projects, assisting public sector management by providing a measure of pre-conditions that can be used as an assessment tool when determining whether a PPP should be used instead of conventional methods.

In addition to the theoretical and methodological contributions, this study produced a usable and readily adaptable list and clusters of value for money factors for the implementation of PPP in smart infrastructure projects.

Academic coaching (AC) has gained a significant attention to support student success and achievement in higher education, management and psychology. This study aimed to conduct a comprehensive bibliometric analysis of AC literature to identify the top authors, research patterns, hotspots and research topics in the field.

The study utilized a bibliometric analysis of articles published between 1987 and 2023, using descriptive and network analysis methods with tools such as RStudio, Biblioshiny, Excel and VOSviewer. The study also conducted functional, mapping and content analysis, to identify AC literature's key themes and research areas.

The results revealed an increasing interest in AC, with increased publications. However, there are gaps in geographical diversity and authorship. Most studies were conducted in the United States of America and the UK, and were published in education, psychology and coaching journals. Common themes included coaching, professional development, higher education and mentoring. Emerging research areas include: coaching efficacy in education, AC as an online learning support and professional learning communities. More studies are needed in different contexts and with larger sample sizes.

This comprehensive bibliometric analysis adds to the existing literature by presenting a detailed analysis of the field of AC, filling a gap in the current literature. The study's unique contribution is its examination of emerging research areas and themes in AC literature, providing directions for future research. This study is particularly relevant for researchers, practitioners and policymakers interested in understanding AC's state of the art and identifying promising areas for future research.

This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

This paper aims to explore how researchers in general, and field researchers in particular, might respond to systems of governance of the researchers' activity in ways that can support rather than distort the quality of the research.

We draw upon literature on serendipity to develop a framework for engaging with the positive and negative potentials of systems of governance. We ground our analysis in discussion of participation in the field comprising two parts: first, the examination of our own activities and second, the accounts of participation found in two career-autobiographical interviews with emeritus professors of management accounting from Japan.

We highlight the potential for a productive tension between two contrasting perspectives that researchers might take on governance of their activity. A contractual perspective sees the value of targets and detailed pre-planning. A reflexive perspective sees the value of exploring the unexpected and considering many alternatives. We offer a framework for considering serendipity and the conditions that facilitate serendipity to help researchers maintain a productive tension between these perspectives.

We build upon retrospective accounts of two successful individuals whose careers evolved in a specific context. The intention is not to set out what might be generally achievable in a research career, nor to propose specific lines of action or planning in relation to specific systems of governance, since these vary across countries and over time. Rather, the paper draws on these materials to illuminate the more general challenge of preparing for serendipity in a way that goes beyond simple opportunism.

We analyse how researchers' mindfulness of serendipity and the nature of contexts that facilitate serendipity can encourage a productive tension between contractual and reflexive perspectives on governance of academic activity.

This paper attempts to document the effect of economic uncertainty on financing constraints faced by private firms.

Ordered logistic regression is used to analyze the data of private firms from 101 developing countries. The data was provided by the World Bank's Enterprise Surveys and was gathered during the period between 2006 and 2019.

The findings show that firms headquartered in countries with high economic uncertainty face more financing constraints than firms headquartered in countries with low economic uncertainty. The authors argue that the increase in economic uncertainty allows capital providers to adjust their lending decisions by reducing the provision of capital to firms. The paper also shows that firms headquartered in countries with strong institutional infrastructure and well-functioning firms are less likely to be affected by economic uncertainty while accessing finance.

The findings would help managers, investors, regulators, and policymakers better understand the implication of economic policy uncertainty on the real economy. This study also sheds the light on the importance of minimizing volatility, ambiguity, and randomness in governmental decisions and policies. Regardless of the pertinence of these policies, arbitrariness surrounding their development and communication can limit their effectiveness and produce unwanted effects.

This paper is closely related to prior literature that documents the behavior of credit providers and investors (the supply side) during the periods of economic uncertainty. The authors differ from this strand of literature by taking the perspective of firms – the demand side.