| ranks_antifragility {MSmix} | R Documentation |
Antifragility Data (complete rankings with covariates)
Description
The Antifragility dataset came up from an on-line survey conducted during spring 2021 by Sapienza University of Rome in collaboration with the Italian incubator Digital Magics, to investigate the construct of antifragility in innovative startups. Antifragility reflects the capacity of a company to adapt and improve its activity in the case of stresses, volatility and disorders triggered by critical and unexpected events, such as the COVID-19 outbreak which motivated the survey. On the basis of their experience and knowledge, a sample of N=99 startups provided their complete rankings of n=7 desirable antifragility properties in order of importance. The antifragility features are: 1 = Absorption, 2 = Redundancy, 3 = Small stressors, 4 = Non-monotonicity, 5 = Requisite variety, 6 = Emergence and 7 = Uncoupling.
Usage
data(ranks_antifragility)Format
A data frame gathering N=99 complete rankings of the n=7 antifragility features in each row (rank 1 = most preferred item). The definition of the antifragility aspects is detailed below:
- Absorption
Ability to absorb stress and shocks while remaining in the planned state.
- Redundancy
Overcapacity to defend from risks and prevent faults.
- Small_stressors
Ability to exert low levels of stress on the organization.
- Non_monotonicity
Capacity to learn from failures and errors.
- Requisite_variety
Need for regulatory agents (i.e., government agency) to monitor and control organization’s outcomes and behaviors.
- Emergence
Existence of cause-effect relationships between organization’s activity at micro level and its outcomes at macro level.
- Uncoupling
Existence of strong interconnection between agents inside and outside the organization.
- Industry_sector
Industry sector of the startup.
- Market
Market type in which the startup operates.
- Innovation_type
Main innovation type of the startup.
- Approach_to_crisis
Main approach implemented by the startup during Covid-19 outbreak.
- Crisis_impact
Impact of Covid-19 outbreak on the startup.
- Age
Age of the startup (years).
- N_employees
Number of employees in the startup.
- Region
Italian region of the startup.
- Job_title
Job title of the startup participant in the survey.
- Experience
Years of job experience of the startup participant in the survey.
References
Ghasemi A and Alizadeh M (2017). Evaluating organizational antifragility via fuzzy logic. The case of an Iranian company producing banknotes and security paper. Operations research and decisions, 27(2), pages 21–43, DOI: 10.5277/ord170202.
Examples
str(ranks_antifragility)
head(ranks_antifragility)