Navigating the impacts of digital transformation in waste management

Purpose This article examines how artificial intelligence (AI)-enabled digitalization changes managerial decision-making in municipal waste management. It focuses on a central paradox: digital tools improve operational visibility and efficiency, while simultaneously redefining what counts as a “good” managerial decision by introducing new accountability pressures, behavioral distortions and equity concerns. Design/methodology/approach The study adopts a practice-based mixed-method analysis of Alia Servizi Ambientali's rollout of smart-bin telemetry and digital service operations, combining container-level telemetry, service records and qualitative operational feedback. Findings Digital visibility improved route efficiency, predictive maintenance and service responsiveness, but also generated risks of contamination, dumping displacement and digital exclusion. These outcomes depended on governance choices, especially tariff design, communication and assisted access channels. Practical implications Managers should sequence implementation around four actions: validate data quality, pilot differentiated service standards, align pricing and communication and monitor dark-side indicators alongside efficiency key performance indicator (KPIs). Originality/value The article shows how managers use digitalization in essential public services not simply to optimize operations, but to reconfigure the criteria through which they prioritize problems, allocate resources, design incentives and exercise judgment under conditions of increased visibility and traceability.

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Publication Details

Journal
Management Decision
Published
2026-09-19
DOI
https://doi.org/10.1108/md-10-2025-3353
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
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article

Navigating the impacts of digital transformation in waste management

Andrea Piazzoli, Alberto Irace, Roberto Marseglia, Domenico Scamardella
Management Decision
Municipal Solid Waste Management
article

Navigating the impacts of digital transformation in waste management

Andrea Piazzoli, Alberto Irace, Roberto Marseglia, Domenico Scamardella
article en

Abstract

Purpose This article examines how artificial intelligence (AI)-enabled digitalization changes managerial decision-making in municipal waste management. It focuses on a central paradox: digital tools improve operational visibility and efficiency, while simultaneously redefining what counts as a “good” managerial decision by introducing new accountability pressures, behavioral distortions and equity concerns. Design/methodology/approach The study adopts a practice-based mixed-method analysis of Alia Servizi Ambientali's rollout of smart-bin telemetry and digital service operations, combining container-level telemetry, service records and qualitative operational feedback. Findings Digital visibility improved route efficiency, predictive maintenance and service responsiveness, but also generated risks of contamination, dumping displacement and digital exclusion. These outcomes depended on governance choices, especially tariff design, communication and assisted access channels. Practical implications Managers should sequence implementation around four actions: validate data quality, pilot differentiated service standards, align pricing and communication and monitor dark-side indicators alongside efficiency key performance indicator (KPIs). Originality/value The article shows how managers use digitalization in essential public services not simply to optimize operations, but to reconfigure the criteria through which they prioritize problems, allocate resources, design incentives and exercise judgment under conditions of increased visibility and traceability.

Management Decision
Scuola Superiore Sant'Anna (IT), Futures Group (United States) (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 11%
Municipal Solid Waste Management
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Navigating the impacts of digital transformation in waste management — Andrea Piazzoli, Alberto Irace, et al. · Management Decision (2026) | TGRS Research Map | TGRS