Startups as a Challenge for Management and Education

Skala, Agnieszka

doi:10.1007/978-3-030-01500-8_3

Cited by 9 publications

(11 citation statements)

References 78 publications

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“…• Resource restrictions (Lepoutre and Heene, 2006;Skala, 2019): Even if new ventures would like to assess impacts themselves or support external assessments, they are often unable to do so due to a lack of resources. Similar problems persist in larger organizations.…”

Section: Requirements For Assessing Sustainability Impacts Of New Ven...mentioning

confidence: 99%

“…This implies that the assessment targets set by new ventures and the goals themselves are likely to be much more fluid, making intertemporal comparisons difficult. • New to the market (Skala, 2019) and early phase of assessment: This leads to the challenge of measuring sustainability impact without historical performance data (Judl et al, 2015), and is related to the observation that many entrepreneurs, managers and organizations have only recently started dealing with the issue of sustainability impact assessment. Alternatively to collecting data themselves, new ventures may adopt data from third parties that are only minimally relevant or potentially incorrect, which risks creating disillusionment.…”

Section: Requirements For Assessing Sustainability Impacts Of New Ven...mentioning

confidence: 99%

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Sustainability impact assessment of new ventures: An emerging field of research

Fichter

Lüdeke‐Freund

Schaltegger

et al. 2023

Journal of Cleaner Production

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Section: Requirements For Assessing Sustainability Impacts Of New Ven...mentioning

confidence: 99%

Section: Requirements For Assessing Sustainability Impacts Of New Ven...mentioning

confidence: 99%

Sustainability impact assessment of new ventures: An emerging field of research

Fichter

Lüdeke‐Freund

Schaltegger

et al. 2023

Journal of Cleaner Production

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“…A startup life cycle is divided into three basic stages: initial, expansion, and maturity. In the [13] initial phase, a startup is an organization with limited resources which identifies a market problem, recognizes demand, or verifies its solution; at the expansion stage, it is an organization that grows rapidly (even at double-digit rates per month); and at the maturity stage it is a hyper scalable organization…”

Section: Nomentioning

confidence: 99%

Predicting Startup Success, a Literature Review

Baskoro

Prabowo

Meyliana

et al. 2022

ICoSTEC

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The development and growth of startups around the world nowadays have become a global phenomenon. Startups have become an essential element of innovation and economic growth in many countries. But literature shows that the failure rate of a startup is around 90%. Therefore it is crucial for investors, financial advisors, and the government to spot the 10% which eventually will generate higher return rates, bring in greater revenue and ensure economic growth. This research aim is to study what are the critical factors of the startup’s success that can be used to make a predictive model using a machinelearning algorithm to predict the success of a startup.

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“…As for the company characteristics, it must be an innovative and growth-oriented business. However, more recent work suggests that the startup definition depends on the actual stage of the company’s life cycle (Skala 2019 ). Therefore, the startup definition is not entirely settled, but some perspectives enable the characterization of these small companies.…”

Section: Introductionmentioning

confidence: 99%

Diachronic profile of startup companies through social media

Peixoto

Almeida

António

et al. 2023

Soc. Netw. Anal. Min.

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Social media platforms have become powerful tools for startups, helping them find customers and raise funding. In this study, we applied a social media intelligence-based methodology to analyze startups’ content and to understand how their communication strategies may differ during their scaling process. To understand if a startup’s social media content reflects its current business maturation position, we first defined an adequate life cycle model for startups based on funding rounds and product maturity. Using Twitter as the source of information and selecting a sample of known Portuguese IT startups at different phases of their life cycle, we analyzed their Twitter data. After preprocessing the data, using latent Dirichlet allocation, topic modeling techniques enabled the categorization of the data according to the topics arising in the published contents of the startups, making it possible to discover that contents can be grouped into five specific topics: “Fintech and ML,” “IT,” “Business Operations,” “Product/Service R&D,” and “Bank and Funding.” By comparing those profiles against the startup’s life cycle, we were able to understand how contents change over time. This provided a diachronic profile for each company, showing that while certain topics remain prevalent in the startup’s scaling, others depend on a particular phase of the startup’s cycle. Our analysis revealed that startups’ social media content differs along their life cycle, highlighting the importance of understanding how startups use social media at different stages of their development.

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Startups as a Challenge for Management and Education

Cited by 9 publications

References 78 publications

Sustainability impact assessment of new ventures: An emerging field of research

Sustainability impact assessment of new ventures: An emerging field of research

Predicting Startup Success, a Literature Review

Diachronic profile of startup companies through social media

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