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What drives entrepreneurial action to create a lasting impact? The creation of new ventures that aim at having an impact beyond their financial performance face additional challenges: achieving economic sustainability and at the same time addressing social or environmental issues. Little is known on how these new hybrid organizations, aiming for multiple impact dimensions, manage to be congruent with their blended values. A dataset of 4,125 early-stage ventures is used to gain insights into how blended values are converted into financial, social and environmental impacts, giving shape to different types of hybrid organizations. Our findings suggest new hybrid organizations might opt to sacrifice financial impact to achieve social impact, yet this is not the case when they aim to generate environmental or sustainable impact. Therefore, the tensions and sacrifices related to holding blended values are not homogeneous across all types of new hybrid organizations.
Evaluation of tech ventures’ evolving business models: rules for performance-related classification
(2022)
At the early stage of a successful tech venture's life cycle, it is assumed that the business model will evolve to higher quality over time. However, there are few empirical insights into business model evolution patterns for the performance-related classification of early-stage tech ventures. We created relevant variables evaluating the evolution of the venture-centric network and the technological proposition of both digital and non-digital ventures' business models using the text of submissions to the official business plan award in the German State of Baden-Württemberg between 2006 and 2012. Applying a principal component analysis/rough set theory mixed methodology, we explore performance-related business model classification rules in the heterogeneous sample of business plans. We find that ventures need to demonstrate real interactions with their customers' needs to survive. The distinguishing success rules are related to patent applications, risk capital, and scaling of the organisation. The rules help practitioners to classify business models in a way that allows them to prioritise action for performance.
Validity of the business model is a key indicator for buying into ventures in the early-stage. Business models of early-stage ventures decrease in validity when developing the business over the progressing stages of the business life-cycle. By doing so, the ventures are validating their business model when building transaction relationships to the surrounding value network. In prior research, we developed a research design based on existing business innovation proposals (onepager, pitch decks, business plans) that is assumed to evaluate the status of business model validation. The core hypothesis of the research design is that transaction relations represent a strong anchor between the business model and the business reality, thus providing information on the business model validity. In this research, we test this hypothesis by designing and analyzing a survey that was directed to founders taking part in a business plan competition. We compared the relationships described in the submitted business plans to the relations explicitely stated in the follow-up questionnaire. We identified that the described relations to customers, investors, and people (human resources) match the relationships expressed in questionnaires quite well. A significant disagreement, however, exists in the relationships to suppliers. We conclude that there is still a theoretical and empirical gap that leads to disagreement between business plans and reality in the group of suppliers.
New Technology-Based Firms (NTBFs) learn their business in the early-stages of their life-cycle. As a central element of the entrepreneurial learning process, the business model describes the value-creation functions that are conceptualized in different stages of the NTBF’s life-cycle. Transaction relations connect the model with the business reality and ideally mature in strength over time to a functioning value-network. This chapter describes the development of a research design that determines, extracts, and evaluates semantics constructs of this entrepreneurial learning out of a convenient sample and three cohorts of business plans submitted to a business plan award between 2008 and 2010. The analysis shows empirical evidence for the survival and growth of those NTBFs that exhibit a balanced status of entrepreneurial learning in the maturity of the value-network that can be characterized as early startup-stage. The empirical findings of the network theory based business plan analysis will allow for a better explanation of the performance in the entrepreneurial process that is discussed for NTBFs based on theory of organizational learning.
The business model canvas (BMC) and the lean start-up manifesto (LSM) have been changing both the entrepreneurial education and, on the practical side, the mindset in setting up innovative ventures since the burst of the dot-com bubble. However, few empirical insights on the business model implementation patterns that distinguish between digital and non-digital innovative ventures exist. Connecting practical management tools to network theory as well as to the theory of organizational learning, this paper investigates evolution patterns of digital and non-digital business models out of the deal flow of an innovation intermediary. For this purpose, a multi-dimensional quantitative content analysis research design is applied to 242 ventures' business plans. The measured strength of transaction relations to customers, suppliers, people, and financiers has been combined with performance indicators of the sampled ventures. The results indicate that in order to succeed, digital ventures iterate their business on the market early and search for investment afterwards. Contrariwise, non-digital ventures already need financial investments in the early stages to set up a product ready to be tested on the market. In both groups we found strong evidence that specific evolutionary patterns relate to higher rates of success.
The business plan is one of the most frequently available artifacts to innovation intermediaries of technology-based ventures' presentations in their early stages [1]–[4]. Agreement on the evaluations of venturing projects based on the business plans highly depends on the individual perspective of the readers [5], [6]. One reason is that little empirical proof exists for descriptions in business plans that suggest survival of early-stage technology ventures [7]–[9]. We identified descriptions of transaction relations [10]–[13] as an anchor of the snapshot model business plan to business reality [13]. In the early-stage, surviving ventures are building transaction relations to human resources, financial resources, and suppliers on the input side, and customers on the output side of the business towards a stronger ego-centric value network [10]–[13]. We conceptualized a multidimensional measurement instrument that evaluates the maturity of this ego-centric value networks based on the transaction relations of different strength levels that are described in business plans of early-stage technology ventures [13]. In this paper, the research design and the instrument are purified to achieve high agreement in the evaluation of business plans [14]–[16]. As a result, we present an overall research design that can reach acceptable quality for quantitative research. The paper so contributes to the literature on business analysis in the early-stage of technology-based ventures and the research technique of content analysis.
We have analyzed a pool of 37,839 articles published in 4,404 business-related journals in the entrepreneurship research field using a novel literature review approach that is based on machine learning and text data mining. Most papers have been published in the journals ‘Small Business Economics’, ‘International Journal of Entrepreneurship and Small Business’, and ‘Sustainability’ (Switzerland), while the sum of citations is highest in the ‘Journal of Business Venturing’, ‘Entrepreneurship Theory and Practice’, and ‘Small Business Economics’. We derived 29 overarching themes based on 52 identified clusters. The social entrepreneurship, development, innovation, capital, and economy clusters represent the largest ones among those with high thematic clarity. The most discussed clusters measured by the average number of citations per assigned paper are research, orientation, capital, gender, and growth. Clusters with the highest average growth in publications per year are social entrepreneurship, innovation, development, entrepreneurship education, and (business-) models. Measured by the average yearly citation rate per paper, the thematic cluster ‘research’, mostly containing literature studies, received most attention. The MLR allows for an inclusion of a significantly higher number of publications compared to traditional reviews thus providing a comprehensive, descriptive overview of the whole research field.