Publications
OUR RESEARCH
Scientific Publications
Here you can find the comprehensive list of publications from the members of the Research Center on Computer Vision and eXtended Reality (xRAI).
Use the tag cloud to filter papers based on specific research topics, or use the menus to filter by year, type of publication, or authors.
For each paper, you have the option to view additional details such as the Abstract, Links, and BibTex record.
Research is formalized curiosity. It is poking and prying with a purpose
Zora Neale Hurston
2024
Recupito, Gilberto; Pecorelli, Fabiano; Catolino, Gemma; Lenarduzzi, Valentina; Taibi, Davide; Nucci, Dario Di; Palomba, Fabio
Technical debt in AI-enabled systems: On the prevalence, severity, impact, and management strategies for code and architecture Journal Article
In: Journal of Systems and Software, vol. 216, pp. 112151, 2024, ISSN: 0164-1212.
Abstract | Links | BibTeX | Tags: Artificial Intelligence, Software Engineering, Technical Debt Management
@article{recupitoTechnicalDebtAIenabled2024,
title = {Technical debt in AI-enabled systems: On the prevalence, severity, impact, and management strategies for code and architecture},
author = {Gilberto Recupito and Fabiano Pecorelli and Gemma Catolino and Valentina Lenarduzzi and Davide Taibi and Dario Di Nucci and Fabio Palomba},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0164121224001961},
doi = {10.1016/j.jss.2024.112151},
issn = {0164-1212},
year = {2024},
date = {2024-10-01},
urldate = {2024-07-07},
journal = {Journal of Systems and Software},
volume = {216},
pages = {112151},
abstract = {Context: Artificial Intelligence (AI) is pervasive in several application domains and promises to be even more diffused in the next decades. Developing high-quality AI-enabled systems — software systems embedding one or multiple AI components, algorithms, and models — could introduce critical challenges for mitigating specific risks related to the systems' quality. Such development alone is insufficient to fully address socio-technical consequences and the need for rapid adaptation to evolutionary changes. Recent work proposed the concept of AI technical debt, a potential liability concerned with developing AI-enabled systems whose impact can affect the overall systems' quality. While the problem of AI technical debt is rapidly gaining the attention of the software engineering research community, scientific knowledge that contributes to understanding and managing the matter is still limited. Objective: In this paper, we leverage the expertise of practitioners to offer useful insights to the research community, aiming to enhance researchers' awareness about the detection and mitigation of AI technical debt. Our ultimate goal is to empower practitioners by providing them with tools and methods. Additionally, our study sheds light on novel aspects that practitioners might not be fully acquainted with, contributing to a deeper understanding of the subject. Method: We develop a survey study featuring 53 AI practitioners, in which we collect information on the practical prevalence, severity, and impact of AI technical debt issues affecting the code and the architecture other than the strategies applied by practitioners to identify and mitigate them. Results: The key findings of the study reveal the multiple impacts that AI technical debt issues may have on the quality of AI-enabled systems (e.g., the high negative impact that Undeclared consumers has on security, whereas Jumbled Model Architecture can induce the code to be hard to maintain) and the little support practitioners have to deal with them, limited to apply manual effort for identification and refactoring. Conclusion: We conclude the article by distilling lessons learned and actionable insights for researchers.},
keywords = {Artificial Intelligence, Software Engineering, Technical Debt Management},
pubstate = {published},
tppubtype = {article}
}
Context: Artificial Intelligence (AI) is pervasive in several application domains and promises to be even more diffused in the next decades. Developing high-quality AI-enabled systems — software systems embedding one or multiple AI components, algorithms, and models — could introduce critical challenges for mitigating specific risks related to the systems' quality. Such development alone is insufficient to fully address socio-technical consequences and the need for rapid adaptation to evolutionary changes. Recent work proposed the concept of AI technical debt, a potential liability concerned with developing AI-enabled systems whose impact can affect the overall systems' quality. While the problem of AI technical debt is rapidly gaining the attention of the software engineering research community, scientific knowledge that contributes to understanding and managing the matter is still limited. Objective: In this paper, we leverage the expertise of practitioners to offer useful insights to the research community, aiming to enhance researchers' awareness about the detection and mitigation of AI technical debt. Our ultimate goal is to empower practitioners by providing them with tools and methods. Additionally, our study sheds light on novel aspects that practitioners might not be fully acquainted with, contributing to a deeper understanding of the subject. Method: We develop a survey study featuring 53 AI practitioners, in which we collect information on the practical prevalence, severity, and impact of AI technical debt issues affecting the code and the architecture other than the strategies applied by practitioners to identify and mitigate them. Results: The key findings of the study reveal the multiple impacts that AI technical debt issues may have on the quality of AI-enabled systems (e.g., the high negative impact that Undeclared consumers has on security, whereas Jumbled Model Architecture can induce the code to be hard to maintain) and the little support practitioners have to deal with them, limited to apply manual effort for identification and refactoring. Conclusion: We conclude the article by distilling lessons learned and actionable insights for researchers.
Falco, Salvatore Esposito De; Montera, Raffaella; Leo, Sabrina; Laviola, Francesco; Vito, Pietro; Sardanelli, Domenico; Basile, Gianpaolo; Nevi, Giulia; Alaia, Raffaele
Trends and patterns in ESG research: A bibliometric odyssey and research agenda Journal Article
In: Corporate Social Responsibility and Environmental Management, vol. 31, no. 5, pp. 3703–3723, 2024, ISSN: 1535-3958, 1535-3966.
Abstract | Links | BibTeX | Tags: ESG, Strategy and Management, Sustainability
@article{defalcoTrendsPatternsESG2024,
title = {Trends and patterns in ESG research: A bibliometric odyssey and research agenda},
author = {Salvatore Esposito De Falco and Raffaella Montera and Sabrina Leo and Francesco Laviola and Pietro Vito and Domenico Sardanelli and Gianpaolo Basile and Giulia Nevi and Raffaele Alaia},
url = {https://onlinelibrary.wiley.com/doi/10.1002/csr.2744},
doi = {10.1002/csr.2744},
issn = {1535-3958, 1535-3966},
year = {2024},
date = {2024-09-01},
urldate = {2024-10-07},
journal = {Corporate Social Responsibility and Environmental Management},
volume = {31},
number = {5},
pages = {3703–3723},
abstract = {The paper provides a detailed analysis of the ESG literature with the aim of bringing clarity to this area of research and proposing a research agenda. An overview of the development of the literature on ESG pillars is offered through a review of 903 peer‐reviewed articles. The paper identifies four thematic clusters: impacts of ESG disclosure and practices, sustainability, accounting, and responsible investments. The main research streams and sub‐streams for each cluster are discussed, highlighting the most frequent theoretical perspectives and methodologies. Furthermore, the evolution of ESG research across time is delineated. The paper also identifies future research directions within each cluster to advance knowledge, and proposes an integrative framework based on focal themes and their reciprocal connections.},
keywords = {ESG, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
The paper provides a detailed analysis of the ESG literature with the aim of bringing clarity to this area of research and proposing a research agenda. An overview of the development of the literature on ESG pillars is offered through a review of 903 peer‐reviewed articles. The paper identifies four thematic clusters: impacts of ESG disclosure and practices, sustainability, accounting, and responsible investments. The main research streams and sub‐streams for each cluster are discussed, highlighting the most frequent theoretical perspectives and methodologies. Furthermore, the evolution of ESG research across time is delineated. The paper also identifies future research directions within each cluster to advance knowledge, and proposes an integrative framework based on focal themes and their reciprocal connections.
Falco, Salvatore Esposito De; Montera, Raffaella; Leo, Sabrina; Laviola, Francesco; Vito, Pietro; Sardanelli, Domenico; Basile, Gianpaolo; Nevi, Giulia; Alaia, Raffaele
Trends and patterns in ESG research: A bibliometric odyssey and research agenda Journal Article
In: Corporate Social Responsibility and Environmental Management, vol. 31, no. 5, pp. 3703–3723, 2024, ISSN: 1535-3958, 1535-3966.
Abstract | Links | BibTeX | Tags: ESG, Strategy and Management, Sustainability
@article{de_falco_trends_2024,
title = {Trends and patterns in ESG research: A bibliometric odyssey and research agenda},
author = {Salvatore Esposito De Falco and Raffaella Montera and Sabrina Leo and Francesco Laviola and Pietro Vito and Domenico Sardanelli and Gianpaolo Basile and Giulia Nevi and Raffaele Alaia},
url = {https://onlinelibrary.wiley.com/doi/10.1002/csr.2744},
doi = {10.1002/csr.2744},
issn = {1535-3958, 1535-3966},
year = {2024},
date = {2024-09-01},
urldate = {2024-10-07},
journal = {Corporate Social Responsibility and Environmental Management},
volume = {31},
number = {5},
pages = {3703–3723},
abstract = {The paper provides a detailed analysis of the ESG literature with the aim of bringing clarity to this area of research and proposing a research agenda. An overview of the development of the literature on ESG pillars is offered through a review of 903 peer‐reviewed articles. The paper identifies four thematic clusters: impacts of ESG disclosure and practices, sustainability, accounting, and responsible investments. The main research streams and sub‐streams for each cluster are discussed, highlighting the most frequent theoretical perspectives and methodologies. Furthermore, the evolution of ESG research across time is delineated. The paper also identifies future research directions within each cluster to advance knowledge, and proposes an integrative framework based on focal themes and their reciprocal connections.},
keywords = {ESG, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
The paper provides a detailed analysis of the ESG literature with the aim of bringing clarity to this area of research and proposing a research agenda. An overview of the development of the literature on ESG pillars is offered through a review of 903 peer‐reviewed articles. The paper identifies four thematic clusters: impacts of ESG disclosure and practices, sustainability, accounting, and responsible investments. The main research streams and sub‐streams for each cluster are discussed, highlighting the most frequent theoretical perspectives and methodologies. Furthermore, the evolution of ESG research across time is delineated. The paper also identifies future research directions within each cluster to advance knowledge, and proposes an integrative framework based on focal themes and their reciprocal connections.
Falco, Salvatore Esposito De; Montera, Raffaella; Cucari, Nicola
Deconstructing Corporate Purpose: A Conceptual Framework in an Evolutionary Perspective Journal Article
In: Academy of Management Proceedings, vol. 2024, no. 1, pp. 17207, 2024, ISSN: 0065-0668, 2151-6561.
Abstract | Links | BibTeX | Tags: Entrepreneurship, Strategy and Management, Sustainability
@article{espositodefalcoDeconstructingCorporatePurpose2024,
title = {Deconstructing Corporate Purpose: A Conceptual Framework in an Evolutionary Perspective},
author = {Salvatore Esposito De Falco and Raffaella Montera and Nicola Cucari},
url = {http://journals.aom.org/doi/full/10.5465/AMPROC.2024.17207abstract},
doi = {10.5465/AMPROC.2024.17207abstract},
issn = {0065-0668, 2151-6561},
year = {2024},
date = {2024-08-01},
urldate = {2024-10-07},
journal = {Academy of Management Proceedings},
volume = {2024},
number = {1},
pages = {17207},
abstract = {This paper introduces a novel multi-dimensional co-evolutionary framework for understanding and analysing corporate purpose, addressing its under-conceptualized nature and diverse interpretations in contemporary business studies. Grounded in the principles of coevolution and integrating Esposito De Falco’s (2012) framework on the genesis and evolution of firms, our work advances a unique theoretical typology of corporate purpose. This typology elucidates the evolutionary pathway of corporate purpose through the "3S" dimensions (structural, systemic, and strategic), offering organizations a guide to align their strategies with both their identity and public image. By examining corporate purpose through these dimensions, we highlight the interconnectedness of an organization’s intrinsic identity (structural), its engagement within its ecosystem (systemic), and the alignment of purpose with actionable strategies (strategic). This multi-dimensional approach reveals how corporate purpose guides firms through a transformative journey from their genesis to their interactions with stakeholders and broader market dynamics. To do this, the paper delineates four distinct typologies of corporate purpose: purpose washing, formal purpose, promising purpose, and deep purpose. These typologies are systematically organized within a synthesis matrix, providing a nuanced and detailed understanding of how corporate purpose manifests and evolves within different organizational contexts. Central to the study are two key propositions. The first proposition positions corporate purpose as the “metabolism of firms”, drawing a parallel with biological metabolism to underscore its crucial role in ensuring business survival, prosperity, and evolutionary adaptation. The second proposition emphasizes the importance of a sequential progression across the genetic, relational, and phenotypic stages of corporate purpose, which is critical for the design of genuinely purposeful organizations. By moving beyond a purely definitional approach, this paper contributes significantly to the ontological understanding of corporate purpose. It sheds light on the dynamics of purpose in organizations, highlighting its strategic importance and the need for alignment between a firm’s identity and actions. Our paper provides a valuable resource for academics and practitioners alike, seeking to navigate the complexities of corporate purpose in a dynamic business landscape. Keywords: Corporate purpose; evolutionary perspective; genotype; relational dimension; phenotype; corporate purpose typologies},
keywords = {Entrepreneurship, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
This paper introduces a novel multi-dimensional co-evolutionary framework for understanding and analysing corporate purpose, addressing its under-conceptualized nature and diverse interpretations in contemporary business studies. Grounded in the principles of coevolution and integrating Esposito De Falco’s (2012) framework on the genesis and evolution of firms, our work advances a unique theoretical typology of corporate purpose. This typology elucidates the evolutionary pathway of corporate purpose through the "3S" dimensions (structural, systemic, and strategic), offering organizations a guide to align their strategies with both their identity and public image. By examining corporate purpose through these dimensions, we highlight the interconnectedness of an organization’s intrinsic identity (structural), its engagement within its ecosystem (systemic), and the alignment of purpose with actionable strategies (strategic). This multi-dimensional approach reveals how corporate purpose guides firms through a transformative journey from their genesis to their interactions with stakeholders and broader market dynamics. To do this, the paper delineates four distinct typologies of corporate purpose: purpose washing, formal purpose, promising purpose, and deep purpose. These typologies are systematically organized within a synthesis matrix, providing a nuanced and detailed understanding of how corporate purpose manifests and evolves within different organizational contexts. Central to the study are two key propositions. The first proposition positions corporate purpose as the “metabolism of firms”, drawing a parallel with biological metabolism to underscore its crucial role in ensuring business survival, prosperity, and evolutionary adaptation. The second proposition emphasizes the importance of a sequential progression across the genetic, relational, and phenotypic stages of corporate purpose, which is critical for the design of genuinely purposeful organizations. By moving beyond a purely definitional approach, this paper contributes significantly to the ontological understanding of corporate purpose. It sheds light on the dynamics of purpose in organizations, highlighting its strategic importance and the need for alignment between a firm’s identity and actions. Our paper provides a valuable resource for academics and practitioners alike, seeking to navigate the complexities of corporate purpose in a dynamic business landscape. Keywords: Corporate purpose; evolutionary perspective; genotype; relational dimension; phenotype; corporate purpose typologies
Falco, Salvatore Esposito De; Montera, Raffaella; Cucari, Nicola
Deconstructing Corporate Purpose: A Conceptual Framework in an Evolutionary Perspective Journal Article
In: Academy of Management Proceedings, vol. 2024, no. 1, pp. 17207, 2024, ISSN: 0065-0668, 2151-6561.
Abstract | Links | BibTeX | Tags: Entrepreneurship, Strategy and Management, Sustainability
@article{esposito_de_falco_deconstructing_2024,
title = {Deconstructing Corporate Purpose: A Conceptual Framework in an Evolutionary Perspective},
author = {Salvatore Esposito De Falco and Raffaella Montera and Nicola Cucari},
url = {http://journals.aom.org/doi/full/10.5465/AMPROC.2024.17207abstract},
doi = {10.5465/AMPROC.2024.17207abstract},
issn = {0065-0668, 2151-6561},
year = {2024},
date = {2024-08-01},
urldate = {2024-10-07},
journal = {Academy of Management Proceedings},
volume = {2024},
number = {1},
pages = {17207},
abstract = {This paper introduces a novel multi-dimensional co-evolutionary framework for understanding and analysing corporate purpose, addressing its under-conceptualized nature and diverse interpretations in contemporary business studies. Grounded in the principles of coevolution and integrating Esposito De Falco’s (2012) framework on the genesis and evolution of firms, our work advances a unique theoretical typology of corporate purpose. This typology elucidates the evolutionary pathway of corporate purpose through the "3S" dimensions (structural, systemic, and strategic), offering organizations a guide to align their strategies with both their identity and public image. By examining corporate purpose through these dimensions, we highlight the interconnectedness of an organization’s intrinsic identity (structural), its engagement within its ecosystem (systemic), and the alignment of purpose with actionable strategies (strategic). This multi-dimensional approach reveals how corporate purpose guides firms through a transformative journey from their genesis to their interactions with stakeholders and broader market dynamics. To do this, the paper delineates four distinct typologies of corporate purpose: purpose washing, formal purpose, promising purpose, and deep purpose. These typologies are systematically organized within a synthesis matrix, providing a nuanced and detailed understanding of how corporate purpose manifests and evolves within different organizational contexts. Central to the study are two key propositions. The first proposition positions corporate purpose as the “metabolism of firms”, drawing a parallel with biological metabolism to underscore its crucial role in ensuring business survival, prosperity, and evolutionary adaptation. The second proposition emphasizes the importance of a sequential progression across the genetic, relational, and phenotypic stages of corporate purpose, which is critical for the design of genuinely purposeful organizations. By moving beyond a purely definitional approach, this paper contributes significantly to the ontological understanding of corporate purpose. It sheds light on the dynamics of purpose in organizations, highlighting its strategic importance and the need for alignment between a firm’s identity and actions. Our paper provides a valuable resource for academics and practitioners alike, seeking to navigate the complexities of corporate purpose in a dynamic business landscape. Keywords: Corporate purpose; evolutionary perspective; genotype; relational dimension; phenotype; corporate purpose typologies},
keywords = {Entrepreneurship, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
This paper introduces a novel multi-dimensional co-evolutionary framework for understanding and analysing corporate purpose, addressing its under-conceptualized nature and diverse interpretations in contemporary business studies. Grounded in the principles of coevolution and integrating Esposito De Falco’s (2012) framework on the genesis and evolution of firms, our work advances a unique theoretical typology of corporate purpose. This typology elucidates the evolutionary pathway of corporate purpose through the "3S" dimensions (structural, systemic, and strategic), offering organizations a guide to align their strategies with both their identity and public image. By examining corporate purpose through these dimensions, we highlight the interconnectedness of an organization’s intrinsic identity (structural), its engagement within its ecosystem (systemic), and the alignment of purpose with actionable strategies (strategic). This multi-dimensional approach reveals how corporate purpose guides firms through a transformative journey from their genesis to their interactions with stakeholders and broader market dynamics. To do this, the paper delineates four distinct typologies of corporate purpose: purpose washing, formal purpose, promising purpose, and deep purpose. These typologies are systematically organized within a synthesis matrix, providing a nuanced and detailed understanding of how corporate purpose manifests and evolves within different organizational contexts. Central to the study are two key propositions. The first proposition positions corporate purpose as the “metabolism of firms”, drawing a parallel with biological metabolism to underscore its crucial role in ensuring business survival, prosperity, and evolutionary adaptation. The second proposition emphasizes the importance of a sequential progression across the genetic, relational, and phenotypic stages of corporate purpose, which is critical for the design of genuinely purposeful organizations. By moving beyond a purely definitional approach, this paper contributes significantly to the ontological understanding of corporate purpose. It sheds light on the dynamics of purpose in organizations, highlighting its strategic importance and the need for alignment between a firm’s identity and actions. Our paper provides a valuable resource for academics and practitioners alike, seeking to navigate the complexities of corporate purpose in a dynamic business landscape. Keywords: Corporate purpose; evolutionary perspective; genotype; relational dimension; phenotype; corporate purpose typologies
Montera, Raffaella; Nevi, Giulia; Cucari, Nicola; Falco, Salvatore Esposito De
How firms adjust their SDG adoption in response to COVID-19 outbreak: a regional perspective Journal Article
In: Corporate Governance: The International Journal of Business in Society, vol. 24, no. 3, pp. 559–575, 2024, ISSN: 1472-0701, 1472-0701.
Abstract | Links | BibTeX | Tags: SDG, Strategy and Management
@article{monteraHowFirmsAdjust2024,
title = {How firms adjust their SDG adoption in response to COVID-19 outbreak: a regional perspective},
author = {Raffaella Montera and Giulia Nevi and Nicola Cucari and Salvatore Esposito De Falco},
url = {https://www.emerald.com/insight/content/doi/10.1108/CG-04-2023-0171/full/html},
doi = {10.1108/CG-04-2023-0171},
issn = {1472-0701, 1472-0701},
year = {2024},
date = {2024-04-01},
urldate = {2024-10-07},
journal = {Corporate Governance: The International Journal of Business in Society},
volume = {24},
number = {3},
pages = {559–575},
abstract = {Purpose
This paper aims to examine the COVID-19 pandemic’s impacts on the regional progression toward the Sustainable Development Goals (SDGs) through the lens of the adoption of 2030 Agenda by firms from different Italian regions.
Design/methodology/approach
Mixed methods were adopted. First, a content analysis was performed on 330 nonfinancial declarations released in the 2019–2021 period by a sample of 110 Italian listed companies from different regional macroareas. Second, regression analyses were run to test the impact of regional localization of businesses on SDGs adoption over pre-/during/post-COVID era.
Findings
The regional localization of businesses does not affect the SDGs adoption in the pre-COVID-19 era because Italian firms mainly address social goals. Instead, SDGs adoption is affected by regional localization of businesses both during and post-COVID-19 age, when Northern firms prioritize economic and social goals, whereas Southern firms shift from social to environmental goals.
Originality/value
This study fills the need of considering the subnational specificities in literature on sustainable development by capturing connections between firms, belonging territory, SDGs and COVID-19 crisis.},
keywords = {SDG, Strategy and Management},
pubstate = {published},
tppubtype = {article}
}
Purpose
This paper aims to examine the COVID-19 pandemic’s impacts on the regional progression toward the Sustainable Development Goals (SDGs) through the lens of the adoption of 2030 Agenda by firms from different Italian regions.
Design/methodology/approach
Mixed methods were adopted. First, a content analysis was performed on 330 nonfinancial declarations released in the 2019–2021 period by a sample of 110 Italian listed companies from different regional macroareas. Second, regression analyses were run to test the impact of regional localization of businesses on SDGs adoption over pre-/during/post-COVID era.
Findings
The regional localization of businesses does not affect the SDGs adoption in the pre-COVID-19 era because Italian firms mainly address social goals. Instead, SDGs adoption is affected by regional localization of businesses both during and post-COVID-19 age, when Northern firms prioritize economic and social goals, whereas Southern firms shift from social to environmental goals.
Originality/value
This study fills the need of considering the subnational specificities in literature on sustainable development by capturing connections between firms, belonging territory, SDGs and COVID-19 crisis.
This paper aims to examine the COVID-19 pandemic’s impacts on the regional progression toward the Sustainable Development Goals (SDGs) through the lens of the adoption of 2030 Agenda by firms from different Italian regions.
Design/methodology/approach
Mixed methods were adopted. First, a content analysis was performed on 330 nonfinancial declarations released in the 2019–2021 period by a sample of 110 Italian listed companies from different regional macroareas. Second, regression analyses were run to test the impact of regional localization of businesses on SDGs adoption over pre-/during/post-COVID era.
Findings
The regional localization of businesses does not affect the SDGs adoption in the pre-COVID-19 era because Italian firms mainly address social goals. Instead, SDGs adoption is affected by regional localization of businesses both during and post-COVID-19 age, when Northern firms prioritize economic and social goals, whereas Southern firms shift from social to environmental goals.
Originality/value
This study fills the need of considering the subnational specificities in literature on sustainable development by capturing connections between firms, belonging territory, SDGs and COVID-19 crisis.
Montera, Raffaella; Nevi, Giulia; Cucari, Nicola; Falco, Salvatore Esposito De
How firms adjust their SDG adoption in response to COVID-19 outbreak: a regional perspective Journal Article
In: Corporate Governance: The International Journal of Business in Society, vol. 24, no. 3, pp. 559–575, 2024, ISSN: 1472-0701, 1472-0701.
Abstract | Links | BibTeX | Tags: SDG, Strategy and Management
@article{montera_how_2024,
title = {How firms adjust their SDG adoption in response to COVID-19 outbreak: a regional perspective},
author = {Raffaella Montera and Giulia Nevi and Nicola Cucari and Salvatore Esposito De Falco},
url = {https://www.emerald.com/insight/content/doi/10.1108/CG-04-2023-0171/full/html},
doi = {10.1108/CG-04-2023-0171},
issn = {1472-0701, 1472-0701},
year = {2024},
date = {2024-04-01},
urldate = {2024-10-07},
journal = {Corporate Governance: The International Journal of Business in Society},
volume = {24},
number = {3},
pages = {559–575},
abstract = {Purpose
This paper aims to examine the COVID-19 pandemic’s impacts on the regional progression toward the Sustainable Development Goals (SDGs) through the lens of the adoption of 2030 Agenda by firms from different Italian regions.
Design/methodology/approach
Mixed methods were adopted. First, a content analysis was performed on 330 nonfinancial declarations released in the 2019–2021 period by a sample of 110 Italian listed companies from different regional macroareas. Second, regression analyses were run to test the impact of regional localization of businesses on SDGs adoption over pre-/during/post-COVID era.
Findings
The regional localization of businesses does not affect the SDGs adoption in the pre-COVID-19 era because Italian firms mainly address social goals. Instead, SDGs adoption is affected by regional localization of businesses both during and post-COVID-19 age, when Northern firms prioritize economic and social goals, whereas Southern firms shift from social to environmental goals.
Originality/value
This study fills the need of considering the subnational specificities in literature on sustainable development by capturing connections between firms, belonging territory, SDGs and COVID-19 crisis.},
keywords = {SDG, Strategy and Management},
pubstate = {published},
tppubtype = {article}
}
Purpose
This paper aims to examine the COVID-19 pandemic’s impacts on the regional progression toward the Sustainable Development Goals (SDGs) through the lens of the adoption of 2030 Agenda by firms from different Italian regions.
Design/methodology/approach
Mixed methods were adopted. First, a content analysis was performed on 330 nonfinancial declarations released in the 2019–2021 period by a sample of 110 Italian listed companies from different regional macroareas. Second, regression analyses were run to test the impact of regional localization of businesses on SDGs adoption over pre-/during/post-COVID era.
Findings
The regional localization of businesses does not affect the SDGs adoption in the pre-COVID-19 era because Italian firms mainly address social goals. Instead, SDGs adoption is affected by regional localization of businesses both during and post-COVID-19 age, when Northern firms prioritize economic and social goals, whereas Southern firms shift from social to environmental goals.
Originality/value
This study fills the need of considering the subnational specificities in literature on sustainable development by capturing connections between firms, belonging territory, SDGs and COVID-19 crisis.
This paper aims to examine the COVID-19 pandemic’s impacts on the regional progression toward the Sustainable Development Goals (SDGs) through the lens of the adoption of 2030 Agenda by firms from different Italian regions.
Design/methodology/approach
Mixed methods were adopted. First, a content analysis was performed on 330 nonfinancial declarations released in the 2019–2021 period by a sample of 110 Italian listed companies from different regional macroareas. Second, regression analyses were run to test the impact of regional localization of businesses on SDGs adoption over pre-/during/post-COVID era.
Findings
The regional localization of businesses does not affect the SDGs adoption in the pre-COVID-19 era because Italian firms mainly address social goals. Instead, SDGs adoption is affected by regional localization of businesses both during and post-COVID-19 age, when Northern firms prioritize economic and social goals, whereas Southern firms shift from social to environmental goals.
Originality/value
This study fills the need of considering the subnational specificities in literature on sustainable development by capturing connections between firms, belonging territory, SDGs and COVID-19 crisis.
Pontillo, Valeria; d'Aragona, Dario Amoroso; Pecorelli, Fabiano; Nucci, Dario Di; Ferrucci, Filomena; Palomba, Fabio
Machine learning-based test smell detection Journal Article
In: Empirical Software Engineering, vol. 29, no. 2, pp. 55, 2024, ISSN: 1382-3256, 1573-7616.
Abstract | Links | BibTeX | Tags: Artificial Intelligence, Code Smell Detection, Software Engineering, Technical Debt Management
@article{pontilloMachineLearningbasedTest2024,
title = {Machine learning-based test smell detection},
author = {Valeria Pontillo and Dario Amoroso d'Aragona and Fabiano Pecorelli and Dario Di Nucci and Filomena Ferrucci and Fabio Palomba},
url = {https://link.springer.com/10.1007/s10664-023-10436-2},
doi = {10.1007/s10664-023-10436-2},
issn = {1382-3256, 1573-7616},
year = {2024},
date = {2024-03-01},
urldate = {2024-07-07},
journal = {Empirical Software Engineering},
volume = {29},
number = {2},
pages = {55},
abstract = {Test smells are symptoms of sub-optimal design choices adopted when developing test cases. Previous studies have proved their harmfulness for test code maintainability and effectiveness. Therefore, researchers have been proposing automated, heuristic-based techniques to detect them. However, the performance of these detectors is still limited and dependent on tunable thresholds. We design and experiment with a novel test smell detection approach based on machine learning to detect four test smells. First, we develop the largest dataset of manually-validated test smells to enable experimentation. Afterward, we train six machine learners and assess their capabilities in within- and cross-project scenarios. Finally, we compare the ML-based approach with state-of-the-art heuristic-based techniques. The key findings of the study report a negative result. The performance of the machine learning-based detector is significantly better than heuristic-based techniques, but none of the learners able to overcome an average F-Measure of 51%. We further elaborate and discuss the reasons behind this negative result through a qualitative investigation into the current issues and challenges that prevent the appropriate detection of test smells, which allowed us to catalog the next steps that the research community may pursue to improve test smell detection techniques.},
keywords = {Artificial Intelligence, Code Smell Detection, Software Engineering, Technical Debt Management},
pubstate = {published},
tppubtype = {article}
}
Test smells are symptoms of sub-optimal design choices adopted when developing test cases. Previous studies have proved their harmfulness for test code maintainability and effectiveness. Therefore, researchers have been proposing automated, heuristic-based techniques to detect them. However, the performance of these detectors is still limited and dependent on tunable thresholds. We design and experiment with a novel test smell detection approach based on machine learning to detect four test smells. First, we develop the largest dataset of manually-validated test smells to enable experimentation. Afterward, we train six machine learners and assess their capabilities in within- and cross-project scenarios. Finally, we compare the ML-based approach with state-of-the-art heuristic-based techniques. The key findings of the study report a negative result. The performance of the machine learning-based detector is significantly better than heuristic-based techniques, but none of the learners able to overcome an average F-Measure of 51%. We further elaborate and discuss the reasons behind this negative result through a qualitative investigation into the current issues and challenges that prevent the appropriate detection of test smells, which allowed us to catalog the next steps that the research community may pursue to improve test smell detection techniques.
Lambiase, Stefano; Catolino, Gemma; Pecorelli, Fabiano; Tamburri, Damian A.; Palomba, Fabio; Heuvel, Willem-Jan Van Den; Ferrucci, Filomena
An Empirical Investigation Into the Influence of Software Communities' Cultural and Geographical Dispersion on Productivity Journal Article
In: Journal of Systems and Software, vol. 208, pp. 111878, 2024, ISSN: 01641212.
Abstract | Links | BibTeX | Tags: Culture Creativity and Inclusive Society, Empirical Software Engineering, Social Software Engineering, Strategy and Management
@article{lambiaseEmpiricalInvestigationInfluence2024,
title = {An Empirical Investigation Into the Influence of Software Communities' Cultural and Geographical Dispersion on Productivity},
author = {Stefano Lambiase and Gemma Catolino and Fabiano Pecorelli and Damian A. Tamburri and Fabio Palomba and Willem-Jan Van Den Heuvel and Filomena Ferrucci},
url = {https://linkinghub.elsevier.com/retrieve/pii/S016412122300273X},
doi = {10.1016/j.jss.2023.111878},
issn = {01641212},
year = {2024},
date = {2024-02-01},
urldate = {2024-07-07},
journal = {Journal of Systems and Software},
volume = {208},
pages = {111878},
abstract = {Estimating and understanding software development productivity represent crucial tasks for researchers and practitioners. Although different works focused on evaluating the impact of human factors on productivity, a few explored the influence of cultural/geographical diversity in software development communities. More particularly, all previous treatise addresses cultural aspects as abstract concepts without providing a quantitative representation. Improved knowledge of these matters might help project managers to assemble more productive teams and tool vendors to design software analytics toolkits that may better estimate productivity. This paper has the goal of enlarging the existing body of knowledge on the factors affecting productivity by focusing on cultural and geographical dispersion of a development community—namely, how diverse a community is in terms of cultural attitudes and geographical collocation of the members who belong to it. To reach this goal, we performed a mixed-method empirical study. First, we built a statistical model relating dispersion metrics with the productivity of 25 open-source communities on Github. Then, we performed a confirmatory survey with 140 practitioners. The key results of our study indicate that cultural and geographical dispersion considerably impact productivity, thus encouraging managers and practitioners to consider such aspects during all the phases of the software development lifecycle. We conclude our paper by elaborating on the main insights from our analyses and instilling implications that may drive further research.},
keywords = {Culture Creativity and Inclusive Society, Empirical Software Engineering, Social Software Engineering, Strategy and Management},
pubstate = {published},
tppubtype = {article}
}
Estimating and understanding software development productivity represent crucial tasks for researchers and practitioners. Although different works focused on evaluating the impact of human factors on productivity, a few explored the influence of cultural/geographical diversity in software development communities. More particularly, all previous treatise addresses cultural aspects as abstract concepts without providing a quantitative representation. Improved knowledge of these matters might help project managers to assemble more productive teams and tool vendors to design software analytics toolkits that may better estimate productivity. This paper has the goal of enlarging the existing body of knowledge on the factors affecting productivity by focusing on cultural and geographical dispersion of a development community—namely, how diverse a community is in terms of cultural attitudes and geographical collocation of the members who belong to it. To reach this goal, we performed a mixed-method empirical study. First, we built a statistical model relating dispersion metrics with the productivity of 25 open-source communities on Github. Then, we performed a confirmatory survey with 140 practitioners. The key results of our study indicate that cultural and geographical dispersion considerably impact productivity, thus encouraging managers and practitioners to consider such aspects during all the phases of the software development lifecycle. We conclude our paper by elaborating on the main insights from our analyses and instilling implications that may drive further research.
Montera, Raffaella
Editorial: Sustainability, digitalization, performance: What reflections on corporate governance and organizational behavior? Journal Article
In: Corporate Governance and Organizational Behavior Review, vol. 8, no. 2, special issue, pp. 253–255, 2024, ISSN: 25211889, 25211870.
Abstract | Links | BibTeX | Tags: Organizational Behavior and Human Resource Management, Strategy and Management, Sustainability
@article{monteraEditorialSustainabilityDigitalization2024,
title = {Editorial: Sustainability, digitalization, performance: What reflections on corporate governance and organizational behavior?},
author = {Raffaella Montera},
url = {https://virtusinterpress.org/Editorial-Sustainability-digitalization-performance-What-reflections-on-corporate-governance-and-organizational-behavior.html},
doi = {10.22495/cgobrv8i2sieditorial},
issn = {25211889, 25211870},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-07},
journal = {Corporate Governance and Organizational Behavior Review},
volume = {8},
number = {2, special issue},
pages = {253–255},
abstract = {This issue contains thirteen papers, each of which contributes to a rich tapestry of contemporary research and practical insights. Amidst the diversity of topics covered by a variety of theoretical frameworks and methodological approaches, three key themes stand out: sustainability, innovation through digitalization, and people and organizational performance.},
keywords = {Organizational Behavior and Human Resource Management, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
This issue contains thirteen papers, each of which contributes to a rich tapestry of contemporary research and practical insights. Amidst the diversity of topics covered by a variety of theoretical frameworks and methodological approaches, three key themes stand out: sustainability, innovation through digitalization, and people and organizational performance.
Montera, Raffaella; Ciasullo, Maria Vincenza; Cucari, Nicola; Bianco, Rosario
The Customer Experience with Fashion Sale Robots: A Psycho-interpretative Framework Book Section
In: Ozuem, Wilson; Ranfagni, Silvia; Willis, Michelle (Ed.): Digital Transformation for Fashion and Luxury Brands, pp. 207–223, Springer International Publishing, Cham, 2024, ISBN: 978-3-031-35588-2 978-3-031-35589-9.
Abstract | Links | BibTeX | Tags: Management of Technology and Innovation, Strategy and Management
@incollection{monteraCustomerExperienceFashion2024,
title = {The Customer Experience with Fashion Sale Robots: A Psycho-interpretative Framework},
author = {Raffaella Montera and Maria Vincenza Ciasullo and Nicola Cucari and Rosario Bianco},
editor = {Wilson Ozuem and Silvia Ranfagni and Michelle Willis},
url = {https://link.springer.com/10.1007/978-3-031-35589-9_10},
doi = {10.1007/978-3-031-35589-9_10},
isbn = {978-3-031-35588-2 978-3-031-35589-9},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-07},
booktitle = {Digital Transformation for Fashion and Luxury Brands},
pages = {207–223},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {This chapter aims to conceptually examine how perceptions of a customer experience with service robots are formed in a fashion retail context. The theoretical backbone is the integration of managerial and marketing view of human-machine interaction through Variety Information Model (VIM) and a psychological approach to the user adoption of new technologies according to Cognitive-Affective-Conative (CAC) model. The existing body of knowledge on humans’ reactions to service robots in a fashion retail context is enriched by proposing a new and multidisciplinary framework in which information units are the antecedents of customers’ experiences; synthesis schemes affect the cognitive experience; general schemes impact the conative experience; and categorical values are linked to the affective experience. The factors, from the customer’s side, conditioning the customer experience with fashion sale robots are thereby highlighted.},
keywords = {Management of Technology and Innovation, Strategy and Management},
pubstate = {published},
tppubtype = {incollection}
}
This chapter aims to conceptually examine how perceptions of a customer experience with service robots are formed in a fashion retail context. The theoretical backbone is the integration of managerial and marketing view of human-machine interaction through Variety Information Model (VIM) and a psychological approach to the user adoption of new technologies according to Cognitive-Affective-Conative (CAC) model. The existing body of knowledge on humans’ reactions to service robots in a fashion retail context is enriched by proposing a new and multidisciplinary framework in which information units are the antecedents of customers’ experiences; synthesis schemes affect the cognitive experience; general schemes impact the conative experience; and categorical values are linked to the affective experience. The factors, from the customer’s side, conditioning the customer experience with fashion sale robots are thereby highlighted.
Montera, Raffaella
I controlli ispirati dall’Environmental (E), Social (S), Governance (G) Book Section
In: Corporate governance. Teorie, attori e sistemi di controllo nelle imprese, pp. 561–603, McGrow Hill, 2024, ISBN: 978-88-386-1219-0.
BibTeX | Tags: Corporate Governance, Strategy and Management, Sustainability
@incollection{monteraControlliIspiratiDallEnvironmental2024,
title = {I controlli ispirati dall’Environmental (E), Social (S), Governance (G)},
author = {Raffaella Montera},
isbn = {978-88-386-1219-0},
year = {2024},
date = {2024-01-01},
booktitle = {Corporate governance. Teorie, attori e sistemi di controllo nelle imprese},
pages = {561–603},
publisher = {McGrow Hill},
keywords = {Corporate Governance, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {incollection}
}
Montera, Raffaella
Il management e i suoi rapporti con la proprietà Book Section
In: Corporate governance. Teorie, attori e sistemi di controllo nelle imprese, pp. 329–370, McGrow Hill, 2024, ISBN: 978-88-386-1219-0.
BibTeX | Tags: Corporate Governance, Ownership, Strategy and Management
@incollection{monteraManagementSuoiRapporti2024,
title = {Il management e i suoi rapporti con la proprietà},
author = {Raffaella Montera},
isbn = {978-88-386-1219-0},
year = {2024},
date = {2024-01-01},
booktitle = {Corporate governance. Teorie, attori e sistemi di controllo nelle imprese},
pages = {329–370},
publisher = {McGrow Hill},
keywords = {Corporate Governance, Ownership, Strategy and Management},
pubstate = {published},
tppubtype = {incollection}
}
Montera, Raffaella; Falco, Salvatore Esposito De
Reaching the SDGs by 2030: At what point is Italy? Evidence from firms at the regional clusters’ level Journal Article
In: Sinergie Italian Journal of Management, vol. 42, no. 1, pp. 189–213, 2024, ISSN: 0393-5108, 2785-549X.
Abstract | Links | BibTeX | Tags: ESG, Strategy and Management, Sustainability
@article{monteraReachingSDGs20302024,
title = {Reaching the SDGs by 2030: At what point is Italy? Evidence from firms at the regional clusters’ level},
author = {Raffaella Montera and Salvatore Esposito De Falco},
url = {https://ojs.sijm.it/index.php/sinergie/workflow/index/1741/5},
doi = {10.7433/s123.2024.08},
issn = {0393-5108, 2785-549X},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-07},
journal = {Sinergie Italian Journal of Management},
volume = {42},
number = {1},
pages = {189–213},
abstract = {Framing of the research. The implementation of the SDGs, one of the most urgent and current challenges, requires adaptation to sub-national contexts and the involvement of many actors, including firms. Purpose of the paper. The paper examines the Italian situation regarding the achievement of the SDGs through the lens of the adoption of the 2030 Agenda by firms from different Italian regions. Methodology. The research involved 30 Italian listed companies from Northern and Central-Southern Italy, selected from the CONSOB’s list of firms providing a non-financial declaration. An integral reading of the documents with subsequent interpretation was performed. Results. Regional localization does not affect the overall contribution to the SDGs, which is limited for all firms. Instead, the geographic localization of firms at the regional scale differentiates the prioritized SDGs: Northern firms are more oriented towards social and economic SDGs, while Central-Southern firms focus more on environmental ones. Research limitations. The paper represents a preliminary exploration of Italian firms’ advancements towards the SDGs over a regional space. Future research developments could focus on sample enlargement and the exploration of sub-national specificities in other countries around the world. Managerial implications. Italian firms should enhance their commitment to the 2030 Agenda in all its ambitions by incorporating the sustainable goals within their corporate culture and strategic posture. Originality of the paper. The study responds to the need to consider sub-national specificities in the literature on sustainable development by capturing the connections between firms, their territory of operation, and the SDGs.},
keywords = {ESG, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
Framing of the research. The implementation of the SDGs, one of the most urgent and current challenges, requires adaptation to sub-national contexts and the involvement of many actors, including firms. Purpose of the paper. The paper examines the Italian situation regarding the achievement of the SDGs through the lens of the adoption of the 2030 Agenda by firms from different Italian regions. Methodology. The research involved 30 Italian listed companies from Northern and Central-Southern Italy, selected from the CONSOB’s list of firms providing a non-financial declaration. An integral reading of the documents with subsequent interpretation was performed. Results. Regional localization does not affect the overall contribution to the SDGs, which is limited for all firms. Instead, the geographic localization of firms at the regional scale differentiates the prioritized SDGs: Northern firms are more oriented towards social and economic SDGs, while Central-Southern firms focus more on environmental ones. Research limitations. The paper represents a preliminary exploration of Italian firms’ advancements towards the SDGs over a regional space. Future research developments could focus on sample enlargement and the exploration of sub-national specificities in other countries around the world. Managerial implications. Italian firms should enhance their commitment to the 2030 Agenda in all its ambitions by incorporating the sustainable goals within their corporate culture and strategic posture. Originality of the paper. The study responds to the need to consider sub-national specificities in the literature on sustainable development by capturing the connections between firms, their territory of operation, and the SDGs.
Montera, Raffaella
Editorial: Sustainability, digitalization, performance: What reflections on corporate governance and organizational behavior? Journal Article
In: Corporate Governance and Organizational Behavior Review, vol. 8, no. 2, special issue, pp. 253–255, 2024, ISSN: 25211889, 25211870.
Abstract | Links | BibTeX | Tags: Organizational Behavior and Human Resource Management, Strategy and Management, Sustainability
@article{montera_editorial_2024,
title = {Editorial: Sustainability, digitalization, performance: What reflections on corporate governance and organizational behavior?},
author = {Raffaella Montera},
url = {https://virtusinterpress.org/Editorial-Sustainability-digitalization-performance-What-reflections-on-corporate-governance-and-organizational-behavior.html},
doi = {10.22495/cgobrv8i2sieditorial},
issn = {25211889, 25211870},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-07},
journal = {Corporate Governance and Organizational Behavior Review},
volume = {8},
number = {2, special issue},
pages = {253–255},
abstract = {This issue contains thirteen papers, each of which contributes to a rich tapestry of contemporary research and practical insights. Amidst the diversity of topics covered by a variety of theoretical frameworks and methodological approaches, three key themes stand out: sustainability, innovation through digitalization, and people and organizational performance.},
keywords = {Organizational Behavior and Human Resource Management, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
This issue contains thirteen papers, each of which contributes to a rich tapestry of contemporary research and practical insights. Amidst the diversity of topics covered by a variety of theoretical frameworks and methodological approaches, three key themes stand out: sustainability, innovation through digitalization, and people and organizational performance.
Montera, Raffaella; Ciasullo, Maria Vincenza; Cucari, Nicola; Bianco, Rosario
The Customer Experience with Fashion Sale Robots: A Psycho-interpretative Framework Book Section
In: Ozuem, Wilson; Ranfagni, Silvia; Willis, Michelle (Ed.): Digital Transformation for Fashion and Luxury Brands, pp. 207–223, Springer International Publishing, Cham, 2024, ISBN: 978-3-031-35588-2 978-3-031-35589-9.
Abstract | Links | BibTeX | Tags: Management of Technology and Innovation, Strategy and Management
@incollection{ozuem_customer_2024,
title = {The Customer Experience with Fashion Sale Robots: A Psycho-interpretative Framework},
author = {Raffaella Montera and Maria Vincenza Ciasullo and Nicola Cucari and Rosario Bianco},
editor = {Wilson Ozuem and Silvia Ranfagni and Michelle Willis},
url = {https://link.springer.com/10.1007/978-3-031-35589-9_10},
doi = {10.1007/978-3-031-35589-9_10},
isbn = {978-3-031-35588-2 978-3-031-35589-9},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-07},
booktitle = {Digital Transformation for Fashion and Luxury Brands},
pages = {207–223},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {This chapter aims to conceptually examine how perceptions of a customer experience with service robots are formed in a fashion retail context. The theoretical backbone is the integration of managerial and marketing view of human-machine interaction through Variety Information Model (VIM) and a psychological approach to the user adoption of new technologies according to Cognitive-Affective-Conative (CAC) model. The existing body of knowledge on humans’ reactions to service robots in a fashion retail context is enriched by proposing a new and multidisciplinary framework in which information units are the antecedents of customers’ experiences; synthesis schemes affect the cognitive experience; general schemes impact the conative experience; and categorical values are linked to the affective experience. The factors, from the customer’s side, conditioning the customer experience with fashion sale robots are thereby highlighted.},
keywords = {Management of Technology and Innovation, Strategy and Management},
pubstate = {published},
tppubtype = {incollection}
}
This chapter aims to conceptually examine how perceptions of a customer experience with service robots are formed in a fashion retail context. The theoretical backbone is the integration of managerial and marketing view of human-machine interaction through Variety Information Model (VIM) and a psychological approach to the user adoption of new technologies according to Cognitive-Affective-Conative (CAC) model. The existing body of knowledge on humans’ reactions to service robots in a fashion retail context is enriched by proposing a new and multidisciplinary framework in which information units are the antecedents of customers’ experiences; synthesis schemes affect the cognitive experience; general schemes impact the conative experience; and categorical values are linked to the affective experience. The factors, from the customer’s side, conditioning the customer experience with fashion sale robots are thereby highlighted.
Montera, Raffaella
Il management e i suoi rapporti con la proprietà Book Section
In: Corporate governance. Teorie, attori e sistemi di controllo nelle imprese, pp. 329–370, McGrow Hill, 2024, ISBN: 978-88-386-1219-0.
BibTeX | Tags: Corporate Governance, Ownership, Strategy and Management
@incollection{montera_il_2024,
title = {Il management e i suoi rapporti con la proprietà},
author = {Raffaella Montera},
isbn = {978-88-386-1219-0},
year = {2024},
date = {2024-01-01},
booktitle = {Corporate governance. Teorie, attori e sistemi di controllo nelle imprese},
pages = {329–370},
publisher = {McGrow Hill},
keywords = {Corporate Governance, Ownership, Strategy and Management},
pubstate = {published},
tppubtype = {incollection}
}
Montera, Raffaella
I controlli ispirati dall’Environmental (E), Social (S), Governance (G) Book Section
In: Corporate governance. Teorie, attori e sistemi di controllo nelle imprese, pp. 561–603, McGrow Hill, 2024, ISBN: 978-88-386-1219-0.
BibTeX | Tags: Corporate Governance, Strategy and Management, Sustainability
@incollection{montera_i_2024,
title = {I controlli ispirati dall’Environmental (E), Social (S), Governance (G)},
author = {Raffaella Montera},
isbn = {978-88-386-1219-0},
year = {2024},
date = {2024-01-01},
booktitle = {Corporate governance. Teorie, attori e sistemi di controllo nelle imprese},
pages = {561–603},
publisher = {McGrow Hill},
keywords = {Corporate Governance, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {incollection}
}
Montera, Raffaella; Falco, Salvatore Esposito De
Reaching the SDGs by 2030: At what point is Italy? Evidence from firms at the regional clusters’ level Journal Article
In: Sinergie Italian Journal of Management, vol. 42, no. 1, pp. 189–213, 2024, ISSN: 0393-5108, 2785-549X.
Abstract | Links | BibTeX | Tags: ESG, Strategy and Management, Sustainability
@article{montera_reaching_2024,
title = {Reaching the SDGs by 2030: At what point is Italy? Evidence from firms at the regional clusters’ level},
author = {Raffaella Montera and Salvatore Esposito De Falco},
url = {https://ojs.sijm.it/index.php/sinergie/workflow/index/1741/5},
doi = {10.7433/s123.2024.08},
issn = {0393-5108, 2785-549X},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-07},
journal = {Sinergie Italian Journal of Management},
volume = {42},
number = {1},
pages = {189–213},
abstract = {Framing of the research. The implementation of the SDGs, one of the most urgent and current challenges, requires adaptation to sub-national contexts and the involvement of many actors, including firms. Purpose of the paper. The paper examines the Italian situation regarding the achievement of the SDGs through the lens of the adoption of the 2030 Agenda by firms from different Italian regions. Methodology. The research involved 30 Italian listed companies from Northern and Central-Southern Italy, selected from the CONSOB’s list of firms providing a non-financial declaration. An integral reading of the documents with subsequent interpretation was performed. Results. Regional localization does not affect the overall contribution to the SDGs, which is limited for all firms. Instead, the geographic localization of firms at the regional scale differentiates the prioritized SDGs: Northern firms are more oriented towards social and economic SDGs, while Central-Southern firms focus more on environmental ones. Research limitations. The paper represents a preliminary exploration of Italian firms’ advancements towards the SDGs over a regional space. Future research developments could focus on sample enlargement and the exploration of sub-national specificities in other countries around the world. Managerial implications. Italian firms should enhance their commitment to the 2030 Agenda in all its ambitions by incorporating the sustainable goals within their corporate culture and strategic posture. Originality of the paper. The study responds to the need to consider sub-national specificities in the literature on sustainable development by capturing the connections between firms, their territory of operation, and the SDGs.},
keywords = {ESG, Strategy and Management, Sustainability},
pubstate = {published},
tppubtype = {article}
}
Framing of the research. The implementation of the SDGs, one of the most urgent and current challenges, requires adaptation to sub-national contexts and the involvement of many actors, including firms. Purpose of the paper. The paper examines the Italian situation regarding the achievement of the SDGs through the lens of the adoption of the 2030 Agenda by firms from different Italian regions. Methodology. The research involved 30 Italian listed companies from Northern and Central-Southern Italy, selected from the CONSOB’s list of firms providing a non-financial declaration. An integral reading of the documents with subsequent interpretation was performed. Results. Regional localization does not affect the overall contribution to the SDGs, which is limited for all firms. Instead, the geographic localization of firms at the regional scale differentiates the prioritized SDGs: Northern firms are more oriented towards social and economic SDGs, while Central-Southern firms focus more on environmental ones. Research limitations. The paper represents a preliminary exploration of Italian firms’ advancements towards the SDGs over a regional space. Future research developments could focus on sample enlargement and the exploration of sub-national specificities in other countries around the world. Managerial implications. Italian firms should enhance their commitment to the 2030 Agenda in all its ambitions by incorporating the sustainable goals within their corporate culture and strategic posture. Originality of the paper. The study responds to the need to consider sub-national specificities in the literature on sustainable development by capturing the connections between firms, their territory of operation, and the SDGs.
Aversano, Lerina; Bernardi, Mario Luca; Cimitile, Marta; Iammarino, Martina
Forecasting the Developer’s Impact in Managing the Technical Debt Book Section
In: Kadgien, Regine; Jedlitschka, Andreas; Janes, Andrea; Lenarduzzi, Valentina; Li, Xiaozhou (Ed.): Product-Focused Software Process Improvement, vol. 14484, pp. 35–47, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-49268-6 978-3-031-49269-3.
Abstract | Links | BibTeX | Tags: Prediction, Technical Debt
@incollection{aversanoForecastingDevelopersImpact2024,
title = {Forecasting the Developer’s Impact in Managing the Technical Debt},
author = {Lerina Aversano and Mario Luca Bernardi and Marta Cimitile and Martina Iammarino},
editor = {Regine Kadgien and Andreas Jedlitschka and Andrea Janes and Valentina Lenarduzzi and Xiaozhou Li},
url = {https://link.springer.com/10.1007/978-3-031-49269-3_4},
doi = {10.1007/978-3-031-49269-3_4},
isbn = {978-3-031-49268-6 978-3-031-49269-3},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-02},
booktitle = {Product-Focused Software Process Improvement},
volume = {14484},
pages = {35–47},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {Technical debt is a collection of design decisions that, when taken together over time, make the system challenging to maintain and develop. Technical debt impacts the quality of applications by generating structural weaknesses that translate into slowness and functional deficiencies at the development level. Identifying debts in your code, architecture, and infrastructure is of paramount importance and requires an in-depth analysis that requires effort in terms of time and resources. To date, there are several reliable tools for calculating debt in code, but this study aims to forecast the impact developers have on debt in source code. We propose an approach, based on the use of different Machine Learning and Deep Learning classifiers capable of predicting just in time, if the change that the developer is making will have a low, medium, or high impact on the debt. To conduct the experiments, three open-source Java systems available on Github were selected, and for each of these, the entire history was collected in terms of changes, quality metrics and indicators strictly connected to the presence of technical debt. The results obtained are satisfactory, showing the effectiveness of the proposed method.},
keywords = {Prediction, Technical Debt},
pubstate = {published},
tppubtype = {incollection}
}
Technical debt is a collection of design decisions that, when taken together over time, make the system challenging to maintain and develop. Technical debt impacts the quality of applications by generating structural weaknesses that translate into slowness and functional deficiencies at the development level. Identifying debts in your code, architecture, and infrastructure is of paramount importance and requires an in-depth analysis that requires effort in terms of time and resources. To date, there are several reliable tools for calculating debt in code, but this study aims to forecast the impact developers have on debt in source code. We propose an approach, based on the use of different Machine Learning and Deep Learning classifiers capable of predicting just in time, if the change that the developer is making will have a low, medium, or high impact on the debt. To conduct the experiments, three open-source Java systems available on Github were selected, and for each of these, the entire history was collected in terms of changes, quality metrics and indicators strictly connected to the presence of technical debt. The results obtained are satisfactory, showing the effectiveness of the proposed method.
Aversano, Lerina; Bernardi, Mario Luca; Cimitile, Marta; Iammarino, Martina
Forecasting the Developer’s Impact in Managing the Technical Debt Book Section
In: Kadgien, Regine; Jedlitschka, Andreas; Janes, Andrea; Lenarduzzi, Valentina; Li, Xiaozhou (Ed.): Product-Focused Software Process Improvement, vol. 14484, pp. 35–47, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-49268-6 978-3-031-49269-3.
Abstract | Links | BibTeX | Tags: Prediction, Predictive Models, Technical Debt
@incollection{kadgien_forecasting_2024,
title = {Forecasting the Developer’s Impact in Managing the Technical Debt},
author = {Lerina Aversano and Mario Luca Bernardi and Marta Cimitile and Martina Iammarino},
editor = {Regine Kadgien and Andreas Jedlitschka and Andrea Janes and Valentina Lenarduzzi and Xiaozhou Li},
url = {https://link.springer.com/10.1007/978-3-031-49269-3_4},
doi = {10.1007/978-3-031-49269-3_4},
isbn = {978-3-031-49268-6 978-3-031-49269-3},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-02},
booktitle = {Product-Focused Software Process Improvement},
volume = {14484},
pages = {35–47},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {Technical debt is a collection of design decisions that, when taken together over time, make the system challenging to maintain and develop. Technical debt impacts the quality of applications by generating structural weaknesses that translate into slowness and functional deficiencies at the development level. Identifying debts in your code, architecture, and infrastructure is of paramount importance and requires an in-depth analysis that requires effort in terms of time and resources. To date, there are several reliable tools for calculating debt in code, but this study aims to forecast the impact developers have on debt in source code. We propose an approach, based on the use of different Machine Learning and Deep Learning classifiers capable of predicting just in time, if the change that the developer is making will have a low, medium, or high impact on the debt. To conduct the experiments, three open-source Java systems available on Github were selected, and for each of these, the entire history was collected in terms of changes, quality metrics and indicators strictly connected to the presence of technical debt. The results obtained are satisfactory, showing the effectiveness of the proposed method.},
keywords = {Prediction, Predictive Models, Technical Debt},
pubstate = {published},
tppubtype = {incollection}
}
Technical debt is a collection of design decisions that, when taken together over time, make the system challenging to maintain and develop. Technical debt impacts the quality of applications by generating structural weaknesses that translate into slowness and functional deficiencies at the development level. Identifying debts in your code, architecture, and infrastructure is of paramount importance and requires an in-depth analysis that requires effort in terms of time and resources. To date, there are several reliable tools for calculating debt in code, but this study aims to forecast the impact developers have on debt in source code. We propose an approach, based on the use of different Machine Learning and Deep Learning classifiers capable of predicting just in time, if the change that the developer is making will have a low, medium, or high impact on the debt. To conduct the experiments, three open-source Java systems available on Github were selected, and for each of these, the entire history was collected in terms of changes, quality metrics and indicators strictly connected to the presence of technical debt. The results obtained are satisfactory, showing the effectiveness of the proposed method.
Aversano, Lerina; Bernardi, Mario Luca; Cimitile, Marta; Iammarino, Martina
Forecasting the Developer’s Impact in Managing the Technical Debt Book Section
In: Kadgien, Regine; Jedlitschka, Andreas; Janes, Andrea; Lenarduzzi, Valentina; Li, Xiaozhou (Ed.): Product-Focused Software Process Improvement, vol. 14484, pp. 35–47, Springer Nature Switzerland, Cham, 2024, ISBN: 978-3-031-49268-6 978-3-031-49269-3.
Abstract | Links | BibTeX | Tags: Prediction, Predictive Models, Technical Debt
@incollection{kadgien_forecasting_2024-1,
title = {Forecasting the Developer’s Impact in Managing the Technical Debt},
author = {Lerina Aversano and Mario Luca Bernardi and Marta Cimitile and Martina Iammarino},
editor = {Regine Kadgien and Andreas Jedlitschka and Andrea Janes and Valentina Lenarduzzi and Xiaozhou Li},
url = {https://link.springer.com/10.1007/978-3-031-49269-3_4},
doi = {10.1007/978-3-031-49269-3_4},
isbn = {978-3-031-49268-6 978-3-031-49269-3},
year = {2024},
date = {2024-01-01},
urldate = {2024-10-02},
booktitle = {Product-Focused Software Process Improvement},
volume = {14484},
pages = {35–47},
publisher = {Springer Nature Switzerland},
address = {Cham},
abstract = {Technical debt is a collection of design decisions that, when taken together over time, make the system challenging to maintain and develop. Technical debt impacts the quality of applications by generating structural weaknesses that translate into slowness and functional deficiencies at the development level. Identifying debts in your code, architecture, and infrastructure is of paramount importance and requires an in-depth analysis that requires effort in terms of time and resources. To date, there are several reliable tools for calculating debt in code, but this study aims to forecast the impact developers have on debt in source code. We propose an approach, based on the use of different Machine Learning and Deep Learning classifiers capable of predicting just in time, if the change that the developer is making will have a low, medium, or high impact on the debt. To conduct the experiments, three open-source Java systems available on Github were selected, and for each of these, the entire history was collected in terms of changes, quality metrics and indicators strictly connected to the presence of technical debt. The results obtained are satisfactory, showing the effectiveness of the proposed method.},
keywords = {Prediction, Predictive Models, Technical Debt},
pubstate = {published},
tppubtype = {incollection}
}
Technical debt is a collection of design decisions that, when taken together over time, make the system challenging to maintain and develop. Technical debt impacts the quality of applications by generating structural weaknesses that translate into slowness and functional deficiencies at the development level. Identifying debts in your code, architecture, and infrastructure is of paramount importance and requires an in-depth analysis that requires effort in terms of time and resources. To date, there are several reliable tools for calculating debt in code, but this study aims to forecast the impact developers have on debt in source code. We propose an approach, based on the use of different Machine Learning and Deep Learning classifiers capable of predicting just in time, if the change that the developer is making will have a low, medium, or high impact on the debt. To conduct the experiments, three open-source Java systems available on Github were selected, and for each of these, the entire history was collected in terms of changes, quality metrics and indicators strictly connected to the presence of technical debt. The results obtained are satisfactory, showing the effectiveness of the proposed method.
2023
Aversano, Lerina; Bernardi, Mario Luca; Cimitile, Marta; Iammarino, Martina; Montano, Debora
Forecasting technical debt evolution in software systems: an empirical study Journal Article
In: Frontiers of Computer Science, vol. 17, no. 3, pp. 173210, 2023, ISSN: 2095-2228, 2095-2236.
Abstract | Links | BibTeX | Tags: Artificial Intelligence, Empirical Study, Machine Learning, Software Quality, Technical Debt
@article{aversano_forecasting_2023,
title = {Forecasting technical debt evolution in software systems: an empirical study},
author = {Lerina Aversano and Mario Luca Bernardi and Marta Cimitile and Martina Iammarino and Debora Montano},
url = {https://link.springer.com/10.1007/s11704-022-1541-7},
doi = {10.1007/s11704-022-1541-7},
issn = {2095-2228, 2095-2236},
year = {2023},
date = {2023-06-01},
urldate = {2024-10-02},
journal = {Frontiers of Computer Science},
volume = {17},
number = {3},
pages = {173210},
abstract = {Technical debt is considered detrimental to the long-term success of software development, but despite the numerous studies in the literature, there are still many aspects that need to be investigated for a better understanding of it. In particular, the main problems that hinder its complete understanding are the absence of a clear definition and a model for its identification, management, and forecasting. Focusing on forecasting technical debt, there is a growing notion that preventing technical debt build-up allows you to identify and address the riskiest debt items for the project before they can permanently compromise it. However, despite this high relevance, the forecast of technical debt is still little explored. To this end, this study aims to evaluate whether the quality metrics of a software system can be useful for the correct prediction of the technical debt. Therefore, the data related to the quality metrics of 8 different open-source software systems were analyzed and supplied as input to multiple machine learning algorithms to perform the prediction of the technical debt. In addition, several partitions of the initial dataset were evaluated to assess whether prediction performance could be improved by performing a data selection. The results obtained show good forecasting performance and the proposed document provides a useful approach to understanding the overall phenomenon of technical debt for practical purposes.},
keywords = {Artificial Intelligence, Empirical Study, Machine Learning, Software Quality, Technical Debt},
pubstate = {published},
tppubtype = {article}
}
Technical debt is considered detrimental to the long-term success of software development, but despite the numerous studies in the literature, there are still many aspects that need to be investigated for a better understanding of it. In particular, the main problems that hinder its complete understanding are the absence of a clear definition and a model for its identification, management, and forecasting. Focusing on forecasting technical debt, there is a growing notion that preventing technical debt build-up allows you to identify and address the riskiest debt items for the project before they can permanently compromise it. However, despite this high relevance, the forecast of technical debt is still little explored. To this end, this study aims to evaluate whether the quality metrics of a software system can be useful for the correct prediction of the technical debt. Therefore, the data related to the quality metrics of 8 different open-source software systems were analyzed and supplied as input to multiple machine learning algorithms to perform the prediction of the technical debt. In addition, several partitions of the initial dataset were evaluated to assess whether prediction performance could be improved by performing a data selection. The results obtained show good forecasting performance and the proposed document provides a useful approach to understanding the overall phenomenon of technical debt for practical purposes.
Gigante, Domenico; Pecorelli, Fabiano; Barletta, Vita Santa; Janes, Andrea; Lenarduzzi, Valentina; Taibi, Davide; Baldassarre, Maria Teresa
Resolving Security Issues via Quality-Oriented Refactoring: A User Study Proceedings Article
In: 2023 ACM/IEEE International Conference on Technical Debt (TechDebt), pp. 82–91, IEEE, Melbourne, Australia, 2023, ISBN: 979-8-3503-1194-5.
Abstract | Links | BibTeX | Tags: Empirical Software Engineering, Software, Technical Debt Management
@inproceedings{giganteResolvingSecurityIssues2023,
title = {Resolving Security Issues via Quality-Oriented Refactoring: A User Study},
author = {Domenico Gigante and Fabiano Pecorelli and Vita Santa Barletta and Andrea Janes and Valentina Lenarduzzi and Davide Taibi and Maria Teresa Baldassarre},
url = {https://ieeexplore.ieee.org/document/10207139/},
doi = {10.1109/TechDebt59074.2023.00016},
isbn = {979-8-3503-1194-5},
year = {2023},
date = {2023-05-01},
urldate = {2024-07-07},
booktitle = {2023 ACM/IEEE International Conference on Technical Debt (TechDebt)},
pages = {82–91},
publisher = {IEEE},
address = {Melbourne, Australia},
abstract = {Software quality is crucial in software development: if not addressed in early phases of the software development life cycle, it may even lead to technical bankruptcy, i.e., a situation in which modifications cost more than redeveloping the application from scratch. In addition, code security must also be addressed to reduce software vulnerabilities and to comply with legal requirements. In this work, we aim to investigate the relationship between refactoring code quality and software security, with the purpose of understanding whether and to what extent improving software quality could have a positive impact on software security as well. Specifically, we investigate to what extent rule violations of a software quality tool such as SonarQube overlap with rule violations of a software vulnerability tool like Fortify Static Code Analyzer. We first compared the rules encoded in the quality models of both tools, to discover possible overlapping cases. Later, we compared the issues raised by both tools on a set of open source Java projects; we also investigated the cases in which a quality refactoring process impacts over software security (thus removing one or more vulnerabilities). We furthermore validated our results statistically. Our results show that resolving software quality issues might also resolve security issues but only in part: many security issues still persist in the source code; also, some quality aspects are more likely to be improved in respect to others. In addition, this empirical study uncovers rule co-occurrences between the two tools. This study confirms the need for using a security-oriented static analysis tool to enforce software security instead of relying only on a quality-oriented one. Results have highlighted important insights for practitioners.},
keywords = {Empirical Software Engineering, Software, Technical Debt Management},
pubstate = {published},
tppubtype = {inproceedings}
}
Software quality is crucial in software development: if not addressed in early phases of the software development life cycle, it may even lead to technical bankruptcy, i.e., a situation in which modifications cost more than redeveloping the application from scratch. In addition, code security must also be addressed to reduce software vulnerabilities and to comply with legal requirements. In this work, we aim to investigate the relationship between refactoring code quality and software security, with the purpose of understanding whether and to what extent improving software quality could have a positive impact on software security as well. Specifically, we investigate to what extent rule violations of a software quality tool such as SonarQube overlap with rule violations of a software vulnerability tool like Fortify Static Code Analyzer. We first compared the rules encoded in the quality models of both tools, to discover possible overlapping cases. Later, we compared the issues raised by both tools on a set of open source Java projects; we also investigated the cases in which a quality refactoring process impacts over software security (thus removing one or more vulnerabilities). We furthermore validated our results statistically. Our results show that resolving software quality issues might also resolve security issues but only in part: many security issues still persist in the source code; also, some quality aspects are more likely to be improved in respect to others. In addition, this empirical study uncovers rule co-occurrences between the two tools. This study confirms the need for using a security-oriented static analysis tool to enforce software security instead of relying only on a quality-oriented one. Results have highlighted important insights for practitioners.
Lenarduzzi, Valentina; Pecorelli, Fabiano; Saarimaki, Nyyti; Lujan, Savanna; Palomba, Fabio
A critical comparison on six static analysis tools: Detection, agreement, and precision Journal Article
In: Journal of Systems and Software, vol. 198, pp. 111575, 2023, ISSN: 01641212.
Abstract | Links | BibTeX | Tags: Empirical Software Engineering, Software, Technical Debt Management
@article{lenarduzziCriticalComparisonSix2023,
title = {A critical comparison on six static analysis tools: Detection, agreement, and precision},
author = {Valentina Lenarduzzi and Fabiano Pecorelli and Nyyti Saarimaki and Savanna Lujan and Fabio Palomba},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0164121222002515},
doi = {10.1016/j.jss.2022.111575},
issn = {01641212},
year = {2023},
date = {2023-04-01},
urldate = {2024-07-07},
journal = {Journal of Systems and Software},
volume = {198},
pages = {111575},
abstract = {Background: Developers use Static Analysis Tools (SATs) to control for potential quality issues in source code, including defects and technical debt. Tool vendors have devised quite a number of tools, which makes it harder for practitioners to select the most suitable one for their needs. To better support developers, researchers have been conducting several studies on SATs to favor the understanding of their actual capabilities. Aims: Despite the work done so far, there is still a lack of knowledge regarding (1) what is their agreement, and (2) what is the precision of their recommendations. We aim at bridging this gap by proposing a large-scale comparison of six popular SATs for Java projects: Better Code Hub, CheckStyle, Coverity Scan, FindBugs, PMD, and SonarQube. Methods: We analyze 47 Java projects applying 6 SATs. To assess their agreement, we compared them by manually analyzing – at line – and class-level — whether they identify the same issues. Finally, we evaluate the precision of the tools against a manually-defined ground truth. Results: The key results show little to no agreement among the tools and a low degree of precision. Conclusion: Our study provides the first overview on the agreement among different tools as well as an extensive analysis of their precision that can be used by researchers, practitioners, and tool vendors to map the current capabilities of the tools and envision possible improvements.},
keywords = {Empirical Software Engineering, Software, Technical Debt Management},
pubstate = {published},
tppubtype = {article}
}
Background: Developers use Static Analysis Tools (SATs) to control for potential quality issues in source code, including defects and technical debt. Tool vendors have devised quite a number of tools, which makes it harder for practitioners to select the most suitable one for their needs. To better support developers, researchers have been conducting several studies on SATs to favor the understanding of their actual capabilities. Aims: Despite the work done so far, there is still a lack of knowledge regarding (1) what is their agreement, and (2) what is the precision of their recommendations. We aim at bridging this gap by proposing a large-scale comparison of six popular SATs for Java projects: Better Code Hub, CheckStyle, Coverity Scan, FindBugs, PMD, and SonarQube. Methods: We analyze 47 Java projects applying 6 SATs. To assess their agreement, we compared them by manually analyzing – at line – and class-level — whether they identify the same issues. Finally, we evaluate the precision of the tools against a manually-defined ground truth. Results: The key results show little to no agreement among the tools and a low degree of precision. Conclusion: Our study provides the first overview on the agreement among different tools as well as an extensive analysis of their precision that can be used by researchers, practitioners, and tool vendors to map the current capabilities of the tools and envision possible improvements.