Many programs in entrepreneurship education (EE) offer modules or training in networking as a way for entrepreneurs to gather advice or co-create novel ideas with other people in their business networks. Unfortunately, the role of the diverse actors of those networks, such as family, friends and very close advisors, is taken for granted, or not explained when being applied to business. It seems that in EE, having a networks is assumed to naturally exist and there is little to be done except of expanding it. Yet, because students are in the process of forming their business, networks keep changing and strong ties need to be combined with weak ties to provide support for growth, and even more to provide a listening ear or unpaid support when it comes to early warning signals of potential business crisis.In this paper, we argue that students are better equipped for business when they pay attention to the composition of their networks, especially when it comes to deal with a potential failure. Based on interviews of students with entrepreneurs who experienced business crisis, the episode of failure become a unique case to look at those networks that provide the support and strength to keep the business. Having business networks signaling when the business was not going well led to seek external help to mitigate the impact of the crisis and recover. From these insights, we formulate the following question: How can entrepreneurship students be better equipped in terms of using business networks, especially to counteract signals of business crisis?
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Many programs in entrepreneurship education (EE) offer modules or training in networking as a way for entrepreneurs to gather advice or co-create novel ideas with other people in their business networks. Unfortunately, the role of the diverse actors of those networks, such as family, friends and very close advisors, is taken for granted, or not explained when being applied to business. It seems that in EE, having a networks is assumed to naturally exist and there is little to be done except of expanding it. Yet, because students are in the process of forming their business, networks keep changing and strong ties need to be combined with weak ties to provide support for growth, and even more to provide a listening ear or unpaid support when it comes to early warning signals of potential business crisis.In this paper, we argue that students are better equipped for business when they pay attention to the composition of their networks, especially when it comes to deal with a potential failure. Based on interviews of students with entrepreneurs who experienced business crisis, the episode of failure become a unique case to look at those networks that provide the support and strength to keep the business. Having business networks signaling when the business was not going well led to seek external help to mitigate the impact of the crisis and recover. From these insights, we formulate the following question: How can entrepreneurship students be better equipped in terms of using business networks, especially to counteract signals of business crisis?
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The main purpose of this dissertation is to identify the factors that explain success and failure in SME business transfers. Three key concepts have been defined in the research framework: firm resources, capabilities (of predecessor and successor) and (successor’s) strategic renewal. Altogether these three key concepts serve as predictors for the transfer outcomes: exit choice, transfer duration, obtained price, satisfaction and the post-transfer firm performance. Testing reveals that both firm resources and owner capabilities are of importance for exit choice. Results indicate further that especially “acquisition experience” and “years of ownership” predict the exit choice in well performing firms. In poorly performing firms, firm resources prevail as the predictors for exit choice. Most consistently, owner capabilities like “familiarity with the successor” and “flexibility” and not firm resources predict success during a transfer. The firm resource “succession planning” predicts only the level of satisfaction with the transfer. Regarding owner capabilities, a distinction is made between generic and specific human capital. Results indicate the importance of specific human capital (owner competencies and experience) rather than generic human capital (level of education). All types of renewal (i.e. product/market innovation, organizational change or a combination of the two) after succession show better post-transfer firm performance compared to no changes in the first two years.
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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.
