The external expectations of organizational accountability force organizational leaders to find solutions and answers in organizational (and information) governance to assuage the feelings of doubt and unease about the behaviour of the organization and its employees that continuously seem to be expressed in the organizational environment. Organizational leaders have to align the interests of their share– and stakeholders in finding a balance between performance and accountability, individual and collective ethical approaches, and business ethics based on compliance, based on integrity, or both. They have to integrate accountability in organizational governance based on a strategy that defines boundaries for rules and routines. They need to define authority structures and find ways to control the behaviour of their employees, without being very restrictive and coercive. They have to implement accountability structures in organizational interactions that are extremely complex, nonlinear, and dynamic, in which (mostly informal) relational networks of employees traverse formal structures. Formal processes, rules, and regulations, used for control and compliance, cannot handle such environments, continuously in ‘social flux’, unpredictable, unstable, and (largely) unmanageable. It is a challenging task that asks exceptional management skills from organizational leaders. The external expectations of accountability cannot be neglected, even if it is not always clear what is exactly meant with that concept. Why is this (very old) concept still of importance for modern organizations?In this book, organizational governance, information governance, and accountability are the core subjects, just like the relationship between them. A framework is presented of twelve manifestations of organizational accountability the every organization had to deal with. An approach is introduced for strategically govern organizational accountability with three components: behaviour, accountability, and external assessments. The core propositions in this book are that without paying strategic attention to the behaviour of employees and managers and to information governance and management, it will be extremely difficult for organizational leaders to find a balance between the two objectives of organizational governance: performance and accountability.
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The vast literature on accountability in the public sector (usually called ‘public accountability’originating from political science and public administration tends to emphasize the positive dimension of holding authorities to account. As formulated by one prominent scholar in the field, ‘[a]ccountability has become an icon for good governance’: it is perceived as ‘a Good Thing, and, so it seems, we can’t have enough of it’ (Bovens, 2005: 182, 183). Accountability has, thus, become one of the central values of democratic rule – varying on a well-known American slogan one could phrase this as ‘no public responsi bility without accountability’.
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This chapter offers a working definition of social accountability as any citizen-led action beyond elections that aims to enhance the accountability of state actors. We view social accountability as a broad array of predominantly bottom-up initiatives, aimed at improving the quality of governance (especially oversight and responsiveness) through active citizen participation. We also trace the evolution of SA as a concept in the literature over the past decades and, then, discuss some influential theoretic approaches to SAIs, pointing out strengths and weaknesses of each model. Finally, we suggest organising Arab SAIs into one of three categories: (1) transparency; (2) advocacy; or (3) participatory governance and we review each of these existing action formats by discussing their main strengths and flaws.
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The DPP4CD project, “Digital Product Passport(s) for Circular Denim: From Pilot to Practice,” focuses on delivering pilot and scalable Digital Product Passports (DPPs) in the circular denim industry. This aligns with the upcoming European Ecodesign for Sustainable Products Regulation (ESPR), making DPPs mandatory for textiles from 2027. A DPP for circular denim should clearly detail material composition, production methods, repair records, and recycling options to meet EU rules like ESPR, Corporate Sustainability Reporting Directive (CSRD) and European Sustainability Reporting Standards (ESRS). It combines dynamic lifecycle data into a standard, interoperable system that boosts traceability, cuts SME admin burdens, and supports sustainable, circular practices. Led by Saxion and HvA, the multidisciplinary project is based on a real-world Dutch use case with MUD Jeans, a leader in circular denim. The project combines circular economy principles with existing digital technologies, working with partners such as tex.tracer, Tejidos Royo, bAwear, Denim Deal, MODINT, EuFSI and, GS1 Netherlands. Instead of developing new tools, the project applies scalable technologies (augmented DPP extension) and methods e.g. blockchain, life cycle assessments, and traceability standards to denim supply chains. The project defines legal, environmental, technical, and user requirements for DPPs in circular denim and designs a modular, data-driven, and ESPR-compliant system that integrates offline and online components while ensuring interoperability, affordability, reliability, accountability, and scalability. It develops a data framework for material tracking, supported by interoperable digital solutions to improve data-sharing and transparency. A pilot DPP with MUD Jeans will cover the full lifecycle from production to recycling, enabling scalable DPP. The project aims to address societal challenges related to circularity, ensure scalable and implementable solutions, and create a digital platform where knowledge can be developed, shared, and utilised. By combining circular practices with digital technologies, DPP4CD will help textile businesses transition towards sustainable, transparent, and future-proof supply chains.
Moderatie van lezersreacties onder nieuwsartikelen is erg arbeidsintensief. Met behulp van kunstmatige intelligentie wordt moderatie mogelijk tegen een redelijke prijs. Aangezien elke toepassing van kunstmatige intelligentie eerlijk en transparant moet zijn, is het belangrijk om te onderzoeken hoe media hieraan kunnen voldoen.
Moderatie van lezersreacties onder nieuwsartikelen is erg arbeidsintensief. Met behulp van kunstmatige intelligentie wordt moderatie mogelijk tegen een redelijke prijs. Aangezien elke toepassing van kunstmatige intelligentie eerlijk en transparant moet zijn, is het belangrijk om te onderzoeken hoe media hieraan kunnen voldoen.Doel Dit promotieproject zal zich richten op de rechtvaardigheid, accountability en transparantie van algoritmische systemen voor het modereren van lezersreacties. Het biedt een theoretisch kader en bruikbare matregelen die nieuwsorganisaties zullen ondersteunen in het naleven van recente beleidsvorming voor een waardegedreven implementatie van AI. Nu steeds meer nieuwsmedia AI gaan gebruiken, moeten ze rechtvaardigheid, accountability en transparantie in hun gebruik van algoritmen meenemen in hun werkwijzen. Resultaten Hoewel moderatie met AI zeer aantrekkelijk is vanuit economisch oogpunt, moeten nieuwsmedia weten hoe ze onnauwkeurigheid en bias kunnen verminderen (fairness), de werking van hun AI bekendmaken (accountability) en de gebruikers laten begrijpen hoe beslissingen via AI worden genomen (transparancy). Dit proefschrift bevordert de kennis over deze onderwerpen. Looptijd 01 februari 2022 - 01 februari 2025 Aanpak De centrale onderzoeksvraag van dit promotieonderzoek is: Hoe kunnen en moeten nieuwsmedia rechtvaardigheid, accountability en transparantie in hun gebruik van algoritmes voor commentmoderatie? Om deze vraag te beantwoorden is het onderzoek opgesplitst in vier deelvragen. Hoe gebruiken nieuwsmedia algoritmes voor het modereren van reacties? Wat kunnen nieuwsmedia doen om onnauwkeurigheid en bias bij het modereren via AI van reacties te verminderen? Wat moeten nieuwsmedia bekendmaken over hun gebruik van moderatie via AI? Wat maakt uitleg van moderatie via AI begrijpelijk voor gebruikers van verschillende niveaus van digitale competentie?
