Roberta Troisi and Gaetano Alfano
This study investigates the presence of a productivity–quality trade-off in judicial decisions from an organisational standpoint, focusing on the courts as bureaucracies. Applied…
Abstract
Purpose
This study investigates the presence of a productivity–quality trade-off in judicial decisions from an organisational standpoint, focusing on the courts as bureaucracies. Applied to the Italian context and focusing on criminal courts, the main question addressed is whether or not increasing productivity diminishes decision quality.
Design/methodology/approach
Directional distance function (DDF) models were utilised to assess productivity. Two-sample t-tests are then used to compare the quality of efficient and inefficient units in first instance and appeal, with the aim to determine whether a productivity–quality trade-off exists.
Findings
The study’s approach yields results that differ from previous studies. (1) The Italian judicial system is found less efficient. (2) The efficiency of the courts of first instance is relatively uniform. In contrast, there is a difference in efficiency between northern and southern courts of appeal, with northern courts on average being more efficient. (3) The analysis reveals a statistically significant productivity–quality trade-off when the courts of appeal are considered.
Research limitations/implications
New evidence of a judicial system is presented, suggesting reforms regarding “reasonable time” as the optimal balance between quality and productivity.
Originality/value
The organisational framework leads to evaluating the efficiency of the courts by considering the various types of proceedings based on the gravity/complexity of the cases. In light of the pyramidal structure of the justice system, the quality is then defined in terms of hierarchical control expressed as review rate.
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Roberta Troisi and Gaetano Alfano
This paper analyses emergency management in two regions of Italy – Emilia-Romagna and Veneto – in order (1) to understand whether they impact on the spread of local coronavirus…
Abstract
Purpose
This paper analyses emergency management in two regions of Italy – Emilia-Romagna and Veneto – in order (1) to understand whether they impact on the spread of local coronavirus disease 2019 (COVID-19) contagion and (2) evaluate which strategy works best.
Design/methodology/approach
A three-step method was developed consisting of (1) a regional incidence curve analysis; (2) a descriptive statistical analysis of the respective operational measures related to the COVID-19 curve stages; and (3) a dynamic Structural Equation Model.
Findings
The results show the effects of the models during the various stages of the local contagion, focussing both on the two individual regions and a comparison of the way they responded.
Practical implications
Three theoretical implications are highlighted: (1) Better results are not necessarily the outcome of increased expenditure; (2) The overall rigidity they both show does not work; (3) The decision to centralize was, to some extent, effective for both regions.
Originality/value
The article empirically tests the effectiveness of emergency management in tackling a single event. Instead of the widely-used normative approach, the authors adopted a descriptive one, which is not frequently discussed in the emergency management literature.
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Debora Sarno, Bo Enquist, Francesco Polese, Roberta Sebastiani, Samuel Petros Sebhatu and Anna Maria Viljakainen
Sustainability transitions (STs) refer to large-scale step changes in complex systems required to face sustainability issues. We aim to delineate how they can unfold in service…
Abstract
Purpose
Sustainability transitions (STs) refer to large-scale step changes in complex systems required to face sustainability issues. We aim to delineate how they can unfold in service ecosystems, especially when inspired by regenerative thinking.
Design/methodology/approach
We develop a conceptual framework based on a processual view of STs and provide a propositional inventory based on literature leveraging deductive reasoning. Moreover, we contextualize our conceptualizations by showing illustrative examples of cities coping with STs.
Findings
We connect the perception of unsustainability with the shift toward service-dominant (S-D) logic and identify them as triggers of an ST; we focus on the role of nested service ecosystems and the adoption of regenerative thinking in STs; finally, we highlight the domino effect that can drive continuous change towards sustainability in service ecosystems. Future research could be focused on (loss of) sensemaking for driving STs, practical approaches to deal with institutional tensions in nested service ecosystems and the possible fractality of ST processes in service ecosystems.
Originality/value
This study supports the understanding of STs in cities and other systems such as industries, markets and organizations. It contributes to ST literature by suggesting the adoption of S-D logic and system lenses to identify, drive and cope with system changes toward sustainability, showing implications for policymakers and practitioners. Furthermore, it contributes to S-D logic by unfolding the self-adjustment of service ecosystems and the focus of sustainability initiatives on nested service ecosystems to sustain the broader systems. Finally, it contributes to transformative service research by identifying how the procedural and inspirational principles characterizing regenerative thinking can support design for STs.
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Martina Toni, Maria Francesca Renzi, Maria Giovina Pasca, Roberta Guglielmetti Mugion, Laura di Pietro and Veronica Ungaro
This paper aims to study the automotive 4.0 context to understand the consumers’ propensity towards high-tech automated cars. The paper analyses the antecedents that lead to the…
Abstract
Purpose
This paper aims to study the automotive 4.0 context to understand the consumers’ propensity towards high-tech automated cars. The paper analyses the antecedents that lead to the use of innovative vehicles. Theory of planned behaviour (TPB) is adopted and extended by including further constructs, such as environmental aspects and inhibitors.
Design/methodology/approach
The advent of smart technologies and the internet of things has given rise to several contributions that look at consumers’ intention towards innovation adoption in the automotive industry. Furthermore, this study rises from the growing interest that sustainable mobility achieved. Based on the previous technology acceptance models and particularly TPB, this paper develops a structured questionnaire. After a pilot survey, the final questionnaire was administered online through email and social media in the Italian context. Structural equation modelling technique has been used for analysing data and testing the conceptual model.
Findings
The number of questionnaires filled out was 310, with a sample composed of young adults, characterised by different addiction levels towards technology. The results explain the drivers that lead to accept and adopt high-tech automated vehicles. This topic is still under investigation and offers potential research opportunities, considering the evolution of the market and the consumers’ habits and needs. Future research studies in this area should focus on generalising the present findings in other countries. Moreover, once this technology starts to be adopted, other constructs could be discovered, investigated and included in the model.
Originality/value
Mobility has raised a growing interest with the fast increasing demand for sustainability and growth of innovative solutions embedded in mobility. This research explores the TPB model’s application and the relation between its constructs, environmental aspects, inhibitors and intention to adopt automated vehicles. On this strength, it is possible to identify each construct’s relevance for obtaining social consensus on the market.
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Luca Carrubbo, Silvia Cosimato and Anna Roberta Gagliardi
Service organizations operate in an increasingly complex and uncertain context that makes decision-making challenging. Despite well-recognized changes in the operational context…
Abstract
Purpose
Service organizations operate in an increasingly complex and uncertain context that makes decision-making challenging. Despite well-recognized changes in the operational context of government as service organization, service literature has given surprisingly limited attention to what these changes imply for organizational decision-making. This study aims to face with the lack of fit of decision-making theorizing with the reality, within which most service practitioners operate, in order to foster the relevance of decision-making in service research and properly approach the false assumptions and misguided instructions for action.
Design/methodology/approach
To rectify the situation, the purpose of this paper is to advance a more holistic understanding of decision-making in government as service organization. The authors do so by reviewing the sparse, though insightful, prior literature on decision-making in service research and identifying four foundational assumptions of decision-making in the service context, that radically differ from the traditional assumptions of decision-making within the wider management literature.
Findings
The authors contribute to service research by further advancing the emerging dynamic understanding of decision-making by developing eight systems thinking-informed research propositions and a connected research agenda. In doing so, the paper offers the essential ground work that can revitalize the field of service management and equip it for facing the challenges that government as service organization is encountering in the 21st century.
Originality/value
The formulated eight research propositions demonstrate that decision-making in a government as service organization occurs within complex adaptive systems composed of multiple subsystems and is characterized by a high degree of unpredictability. It is a process influenced by multiple actors part of the system and subsystems, through multiple feedback loops, where the implications of prior decisions inform the future decisions.