Analyzing the Decision Criteria of Software Developers Based on Prospect Theory

Kina, Kanako; Tsunoda, Masateru; Hata, Hideaki; Tamada, Haruaki; Ishiguro, Hiroshi

doi:10.1109/saner.2016.115

Cited by 5 publications

(4 citation statements)

References 18 publications

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“…Bell e et al (2018) identified how prospect theory explains cognitive biases in public policy and decision-making. Prospect theory is also applied to learn decisionmaking in software development choices (Kina et al, 2016;Peng and Yang, 2017). It has been extensively applied in political decision-making literature (Boettcher, 2004;Mercer, 2005).…”

Section: Discussionmentioning

confidence: 99%

Decision-making system for higher education university selection: comparison of priorities pre- and post-COVID-19

Nanath

Ali

Kaitheri

2021

JARHE

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PurposeUniversity selection in higher education is a complex task for aspirants from a decision-making perspective. This study first aims to understand the essential parameters that affect potential students' choice of higher education institutions. It then aims to explore how these parameters or priorities have changed given the impact of the COVID-19 pandemic. Learning about the differences in priorities for university selection pre- and post-COVID-19 pandemic might help higher education institutions focus on relevant parameters in the post-pandemic era.Design/methodology/approachThis study uses a mixed-method approach, with primary and secondary data (university parameters from the website and LinkedIn Insights). We developed a university selector system by scraping LinkedIn education data of various universities and their alumni records. The final decision-making tool was hosted on the web to collect potential students' responses (primary data). Response data were analyzed via a multicriteria decision-making (MCDM) model. Portal-based data collection was conducted twice to understand the differences in university selection priorities pre- and post-COVID-19 pandemic. A one-way MANOVA was performed to find the differences in priorities related to the university decision-making process pre- and post-COVID-19.FindingsThis study considered eight parameters of the university selection process. MANOVA demonstrated a significant change in decision-making priorities of potential students between the pre- and post-COVID-19 phases. Four out of eight parameters showed significant differences in ranking and priority. Respondents made significant changes in their selection criteria on four parameters: cost (went high), ranking (went low), presence of e-learning mode (went high) and student life (went low).Originality/valueThe current COVID-19 pandemic poses many uncertainties for educational institutions in terms of mode of delivery, student experience, campus life and others. The study sheds light on the differences in priorities resulting from the pandemic. It attempts to show how social priorities change over time and influence the choices students make.

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Section: Discussionmentioning

confidence: 99%

Decision-making system for higher education university selection: comparison of priorities pre- and post-COVID-19

Nanath

Ali

Kaitheri

2021

JARHE

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“…Risk aversion has wider generalisability towards, for example, general decision making under risk (Abdellaoui et al, 2007). Kina et al (2016) examined software engineer tool adoption practices and found they did not always maximise profit by adopting new tools, instead relying upon the known certainty of familiar tools. This suggests a certainty effect or bias in play.…”

Section: Cognitive Processing Stylesmentioning

confidence: 99%

Recognizing the known unknowns; the interaction between reflective thinking and optimism for uncertainty among software developer’s security perceptions

Ivory¹,

Towse²,

Sturdee³

et al. 2023

Preprint

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Software development is a complex process requiring aspects of social, cognitive, and technical skills. Software engineers face high levels of uncertainty and risk during functional and security decision making. This preregistered study investigates behavioural measures of cognitive reflection, risk aversion, and optimism bias among professional freelance software developers and computer science students, to expose relationships between uncertainty-associated language and risk sensitivity. We employ content analysis with a mixed-effect model to understand how psychological dimensions influence risk sensitivity in secure software development. We show an interaction between cognitive reflection and optimism bias in the proportion of uncertainty-related language used. Overly optimistic outlooks combined with higher cognitive reflection drives up expressions of uncertainty, while pessimistic or realistic individuals reduce uncertainty as cognitive reflection increases. Software engineers who hold average or pessimistic views on the security of their code are more likely to speak more intuitively about security and risk. We discuss the potential for psychological interventions to promote more secure coding behaviours in software engineers. By increasing potential risk awareness, they may consider risk in software more carefully, which may lead to better security implementation in their code.

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“…Risk aversion has wider generalizability toward, for example, general decision making under risk (Abdellaoui et al, 2007). Kina et al (2016) examined software engineer tool adoption practices and found that when new tools are not guaranteed to maximize profit and contain risks, engineers are more risk averse and instead rely upon the known familiarity of familiar tools. This suggests a certainty effect, or bias in play.…”

Section: Risk Aversionmentioning

confidence: 99%

Supplemental Material for Recognizing the known unknowns; the interaction between reflective thinking and optimism for uncertainty among software developer’s security perceptions.

Ivory,

Towse,

Sturdee

et al. 2023

Technology, Mind, and Behavior

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Software development is a complex process requiring aspects of social, cognitive, and technical skills. Software engineers face high levels of uncertainty and risk during functional and security decision making. This preregistered study investigates behavioral measures of cognitive reflection, risk aversion, and optimism bias among professional freelance software developers and computer science students, to expose relationships between uncertainty-associated language and risk sensitivity. We employ content analysis with a mixed-effect model to understand how psychological dimensions influence risk sensitivity in secure software development.We show an interaction between cognitive reflection and optimism bias in the proportion of uncertainty-related language used. Overly optimistic outlooks combined with higher cognitive reflection drives up expressions of uncertainty, while pessimistic or realistic individuals reduce uncertainty as cognitive reflection increases. Software engineers who hold average or pessimistic views on the security of their code are more likely to speak more intuitively about security and risk. We discuss the potential of our findings in relation to understanding how to leverage language used by engineers as markers of risk aversion. Encouraging increased discourse could be used as a catalyst for increased cognitive reflection and grounding optimistic behaviors, leading to more careful decisions.

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Analyzing the Decision Criteria of Software Developers Based on Prospect Theory

Cited by 5 publications

References 18 publications

Decision-making system for higher education university selection: comparison of priorities pre- and post-COVID-19

Decision-making system for higher education university selection: comparison of priorities pre- and post-COVID-19

Recognizing the known unknowns; the interaction between reflective thinking and optimism for uncertainty among software developer’s security perceptions

Supplemental Material for Recognizing the known unknowns; the interaction between reflective thinking and optimism for uncertainty among software developer’s security perceptions.

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