Management decisions regarding innovative projects at their early stages of development: An example of a methodology for assessing crypto projects

Mandryka, Vladyslav; Mandryka, Kateryna; Yevdokymova, Alona; Matsenko, Oleksandr; Melnyk, Leonid

doi:10.21511/ppm.21(4).2023.25

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…Kwilinski (2019) explored the implementation of Blockchain technology in the accounting sphere, which could affect how companies manage their financial data and reporting processes. Dzwigol (2020), Skrynnyk and Vasilyeva (2022), Dzwigol (2022), and Mandryka et al (2023) offered insights into methodological platforms and research methodologies in management science, including the concept of triangulation, which may be relevant for developing analytical approaches in the context of events after the reporting period.…”

Section: Theoretical Basismentioning

confidence: 99%

Company management decision-making based on the analysis of events after the reporting period

Aliyeva

2023

Problems and Perspectives in Management

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The study aims to discuss the impact of the analysis of events after the reporting date (subsequent events) on management decision-making. In the interval between the end of the reporting period and the publication of the annual financial report, company management may learn about events that either occurred during the reporting period but were previously unknown or occurred when the financial report was already prepared but not approved. The consequences of these events can be so serious that they require adjustments to the financial statements, changes in the company’s strategy and tactics, and radical management transformations. The paper structures such events depending on their impact on business performance and the procedure for reporting and identifies the determinants and mechanisms for their analysis and correct accounting. To assess the complex impact of events after the reporting period on the financial results of a company, an integral indicator is proposed, a set of management measures is defined in accordance with the values of this indicator, and the mechanism for its calculation and use is demonstrated on the example of a hypothetical scenario. The sensitivity analysis of this indicator to fluctuations in the weighting coefficients of its components was performed using the Monte Carlo method. In an environment where transparency, accountability, trust between key stakeholders, adaptability, and proactivity are crucial for effective management, this indicator can be used as an effective metric that is taken into account by auditors, regulators, clients, investors, company management, etc.

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Section: Theoretical Basismentioning

confidence: 99%

Company management decision-making based on the analysis of events after the reporting period

Aliyeva

2023

Problems and Perspectives in Management

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Structural and comparative analysis of R&D funding impact on the level of innovation development: The empirical evidence of GII’s leaders and Ukraine

Dobrovolska,

Sonntag,

Ortmanns

et al. 2023

Innovative Marketing

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The study aims to determine the influence of the R&amp;D expenditure structure funded by different sectors of stakeholders on the level of innovation development. The data sample involves values of GII and R&amp;D expenditure funded by business, government, higher education, private non-profit sectors, and foreign sources for 10 countries – Ukraine and 9 top countries in GII-2022 for 2011–2020. Pearson/Spearman correlation analysis considers time lags to determine the nature and strength of relationships. For GII’s top countries, the relationship with innovation development level is confirmed as direct for funding R&amp;D by business (in 8 from 9 countries), higher education (5 from 7), and foreign sources (5 from 9) with power from moderate to very high and 0-3-year lag. In Ukraine, the direct relationship is for financing by business (very high power and 3-year lag) and foreign sources (high power and 1-year lag). The regression modeling of dependences (Arellano-Bover/Blundell-Bond dynamic model for panel data and linear model for Ukraine) was also applied using STATA 18. In GII’s top countries, increasing the share of R&amp;D expenditures financed by business by 1% contributes to increasing GII’s score by 0.25%, higher education – 2.47%; government, non-profit sector, and foreign sources – decreasing by 0.89%, 1.68% and 0.81% accordingly. In Ukraine, increasing financing R&amp;D by the government by 1% leads to a similar decrease of GII estimate by 0.19% with a 2-year lag, and the business sector – an increase of 0.16% with a 3-year time lag. Vice versa, in Ukraine, R&amp;D expenditures financed by higher education lead to GII’s score decreasing.

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Management decisions regarding innovative projects at their early stages of development: An example of a methodology for assessing crypto projects

Cited by 2 publications

References 23 publications

Company management decision-making based on the analysis of events after the reporting period

Company management decision-making based on the analysis of events after the reporting period

Structural and comparative analysis of R&D funding impact on the level of innovation development: The empirical evidence of GII’s leaders and Ukraine

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Management decisions regarding innovative projects at their early stages of development: An example of a methodology for assessing crypto projects

Cited by 2 publications

References 23 publications

Company management decision-making based on the analysis of events after the reporting period

Company management decision-making based on the analysis of events after the reporting period

Structural and comparative analysis of R&amp;D funding impact on the level of innovation development: The empirical evidence of GII’s leaders and Ukraine

Contact Info

Product

Resources

About

Structural and comparative analysis of R&D funding impact on the level of innovation development: The empirical evidence of GII’s leaders and Ukraine