This comprehensive document shares up-to-date knowledge on Early Warning Signals of business crisis, presents detection and intervention opportunities, and makes a clear case for their beneficial application to SME leadership and overall business resilience.
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Recent research has indicated an increase in the likelihood and impact of tree failure. The potential for trees to fail relates to various biomechanical and physical factors. Strikingly, there seems to be an absence of tree risk assessment methods supported by observations, despite an increasing availability of variables and parameters measured by scientists, arborists and practitioners. Current urban tree risk assessments vary due to differences in experience, training, and personal opinions of assessors. This stresses the need for a more objective method to assess the hazardousness of urban trees. The aim of this study is to provide an overview of factors that influence tree failure including stem failure, root failure and branch failure. A systematic literature review according to the PRISMA guidelines has been performed in databases, supported by backward referencing: 161 articles were reviewed revealing 142 different factors which influenced tree failure. A meta-analysis of effect sizes and p-values was executed on those factors which were associated directly with any type of tree failure. Bayes Factor was calculated to assess the likelihood that the selected factors appear in case of tree failure. Publication bias was analysed visually by funnel plots and results by regression tests. The results provide evidence that the factors Height and Stem weight positively relate to stem failure, followed by Age, DBH, DBH squared times H, and Cubed DBH (DBH3) and Tree weight. Stem weight and Tree weight were found to relate positively to root failure. For branch failure no relating factors were found. We recommend that arborists collect further data on these factors. From this review it can further be concluded that there is no commonly shared understanding, model or function available that considers all factors which can explain the different types of tree failure. This complicates risk estimations that include the failure potential of urban trees.
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Purpose: Preventing business failure remains a significant challenge for small businesses in the Netherlands. Given their importance for the Dutch economy, understanding the causes of business failure and equipping business owners with strategies for resilience is imperative. This dissertation seeks to address this challenge by examining the sales role of business owners, referred to as ‘Entrepreneurial Selling,’ within the context of small-scale Dutch businesses. The goal is to identify how business owners can develop effective sales behaviors to mitigate the risk of failure and enhance the long-term viability of their businesses. The research into Entrepreneurial Selling is rising, yet further advancements, including this dissertation, are required to better support business owners in their continuous sales responsibilities. The main research question, therefore, is: How do small-scale business owners in the Netherlands behave in their Entrepreneurial Selling role and how can they become more effective in their sales behavior? Methods: To address the research question, a multimethod research approach is utilized. The research design comprises a literature review, three progressively linked studies, and practical applications. The first study (Chapter 4) involves a content re-analysis of 55 interviews to underscore the pivotal nature of Entrepreneurial Selling in preventing business failure. The second study (Chapter 5) conducts 12 semi-structured interviews, employing thematic analysis to categorize business owners' sales behaviors based on their entrepreneurial motivations. In the third study (Chapter 6), quantitative methods are employed (N=276) to explore the relationship between Entrepreneurial Selling Role Orientation (ESRO) and effective sales behavior. These studies provide the foundation for the practical applications developed in collaboration with practitioners (Chapter 7).Findings: The first study found that Entrepreneurial Selling is a crucial activity for preventing business failure and one that business owners recognize. Reasons for underperformance can include business owners allocating inadequate time to selling, deficient sales skills, and procrastination of sales activities. The subsequent studies build on this foundation. The second study introduces an Entrepreneurial Selling typology, linking business owners' motivations with their sales role strategies, offering insights into how motivations influence sales behavior. The third study introduces the concept of ESRO and substantiates its impact on sales behavior. Furthermore, a positive connection is identified between sales training and effective sales practices. The findings of the studies are individually applied to Sarasvathy’s Bird-in-Hand principle of Effectuation theory and are synthesized within the Entrepreneurial Selling Matrix. Originality/Value: This dissertation contributes to the Entrepreneurial Selling field by advancing our understanding of the business owners’ sales role in enhancing business resilience. It underscores the connection between ineffective sales practices and business failure and delves deeper by investigating the interplay between entrepreneurial motives and ESRO on sales behavior. Additionally, this study bridges the gap between entrepreneurship- and sales research by applying the Bird-in-Hand principle to business owners' sales behavior. In practical terms, the research's outcomes are twofold. First, it refines the Entrepreneurial Selling Matrix, providing a pragmatic typology that aids sales training practitioners in guiding business owners toward aligning sales behaviors with entrepreneurial goals. Second, it introduces an Entrepreneurial Selling Training Program, accompanied by tools, facilitating sales trainers in evaluating and improving current and desired sales behaviors. This practical approach contributes directly to nurturing resilient and thriving businesses.
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In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
