Do Awards Incentivize Non-Winners to Work Harder on CSR?

Curated on Posted on by Stefaan Verhulst

Article by Jiangyan Li, Juelin Yin, Wei Shi, And Xiwei Yi: “As corporate lists and awards that rank and recognize firms for superior social reputation have proliferated in recent years, the field of CSR is also replete with various types of awards given out to firms or CEOs, such as Fortune’s “Most Admired Companies” rankings and “Best 100 Companies to Work For” lists. Such awards serve to both reward and incentivize firms to become more dedicated to CSR. Prior research has primarily focused on the effects of awards on award-winning firms; however, the effectiveness and implications of such awards as incentives to non-winning firms remain understudied. Therefore, in the article of “Keeping up with the Joneses: Role of CSR Awards in Incentivizing Non-Winners’ CSR” published by Business & Society, we are curious about whether such CSR awards could successfully incentivize non-winning firms to catch up with their winning competitors.

Drawing on the awareness-motivation-capability (AMC) framework developed in the competitive dynamics literature, we use a sample of Chinese listed firms from 2009 to 2015 to investigate how competitors’ CSR award winning can influence focal firms’ CSR. The empirical results show that non-winning firms indeed improve their CSR after their competitors have won CSR awards. However, non-winning firms’ improvement in CSR may vary in different scenarios. For instance, media exposure can play an important informational role in reducing information asymmetries and inducing competitive actions among competitors, therefore, non-winning firms’ improvement in CSR is more salient when award-winning firms are more visible in the media. Meanwhile, when CSR award winners perform better financially, non-winners will be more motivated to respond to their competitors’ wins. Further, firms with a higher level of prior CSR are more capable of improving their CSR and therefore are more likely to respond to their competitors’ wins…(More)”.

Conceptual and normative approaches to AI governance for a global digital ecosystem supportive of the UN Sustainable Development Goals (SDGs)

Curated on Posted on by Stefaan Verhulst

Paper by Amandeep S. Gill & Stefan Germann: “AI governance is like one of those mythical creatures that everyone speaks of but which no one has seen. Sometimes, it is reduced to a list of shared principles such as transparency, non-discrimination, and sustainability; at other times, it is conflated with specific mechanisms for certification of algorithmic solutions or ways to protect the privacy of personal data. We suggest a conceptual and normative approach to AI governance in the context of a global digital public goods ecosystem to enable progress on the UN Sustainable Development Goals (SDGs). Conceptually, we propose rooting this approach in the human capability concept—what people are able to do and to be, and in a layered governance framework connecting the local to the global. Normatively, we suggest the following six irreducibles: a. human rights first; b. multi-stakeholder smart regulation; c. privacy and protection of personal data; d. a holistic approach to data use captured by the 3Ms—misuse of data, missed use of data and missing data; e. global collaboration (‘digital cooperation’); f. basing governance more in practice, in particular, thinking separately and together about data and algorithms. Throughout the article, we use examples from the health domain particularly in the current context of the Covid-19 pandemic. We conclude by arguing that taking a distributed but coordinated global digital commons approach to the governance of AI is the best guarantee of citizen-centered and societally beneficial use of digital technologies for the SDGs…(More)”.

When Governance Theory Meets Democratic Theory: The Potential Contribution of Cocreation to Democratic Governance

Curated on Posted on by Stefaan Verhulst

Paper by Christopher Ansell, Eva Sørensen, Jacob Torfing: “Building on recent public administration research on service coproduction and cocreation, this article draws out the democratic potential of new forms of collaborative governance between the democratic state and civil society. Within democratic theory, cocreation has many similarities with the concept of deliberative mini-publics, but it goes beyond a “talk-centric” view to emphasize the active role of civil society in creative problem-solving and public innovation. The article argues that combining insights and perspectives from both democratic theory and governance theory can provide stronger foundations for a participatory democracy that complements rather than replaces representative democracy. The article concludes with an exploration of some of the legitimation challenges that democratic cocreation might face in practice…(More)”.

Understanding Algorithmic Discrimination in Health Economics Through the Lens of Measurement Errors

Curated on Posted on by Stefaan Verhulst

Paper by Anirban Basu, Noah Hammarlund, Sara Khor & Aasthaa Bansal: “There is growing concern that the increasing use of machine learning and artificial intelligence-based systems may exacerbate health disparities through discrimination. We provide a hierarchical definition of discrimination consisting of algorithmic discrimination arising from predictive scores used for allocating resources and human discrimination arising from allocating resources by human decision-makers conditional on these predictive scores. We then offer an overarching statistical framework of algorithmic discrimination through the lens of measurement errors, which is familiar to the health economics audience. Specifically, we show that algorithmic discrimination exists when measurement errors exist in either the outcome or the predictors, and there is endogenous selection for participation in the observed data. The absence of any of these phenomena would eliminate algorithmic discrimination. We show that although equalized odds constraints can be employed as bias-mitigating strategies, such constraints may increase algorithmic discrimination when there is measurement error in the dependent variable….(More)”.

A Proposal for Researcher Access to Platform Data: The Platform Transparency and Accountability Act

Curated on Posted on by Stefaan Verhulst

Paper by Nathaniel Persily: “We should not need to wait for whistleblowers to blow their whistles, however, before we can understand what is actually happening on these extremely powerful digital platforms. Congress needs to act immediately to ensure that a steady stream of rigorous research reaches the public on the most pressing issues concerning digital technology. No one trusts the representations made by the platforms themselves, though, given their conflict of interest and understandable caution in releasing information that might spook shareholders. We need to develop an unprecedented system of corporate datasharing, mandated by government for independent research in the public interest.

This is easier said than done. Not only do the details matter, they are the only thing that matters. It is all well and good to call for “transparency” or “datasharing,” as an uncountable number of academics have, but the way government might setup this unprecedented regime will determine whether it can serve the grandiose purposes techcritics hope it will….(More)”.

Evaluating the trade-off between privacy, public health safety, and digital security in a pandemic

Curated on Posted on by Stefaan Verhulst

Paper by Titi Akinsanmi and Aishat Salami: “COVID-19 has impacted all aspects of everyday normalcy globally. During the height of the pandemic, people shared their (PI) with one goal—to protect themselves from contracting an “unknown and rapidly mutating” virus. The technologies (from applications based on mobile devices to online platforms) collect (with or without informed consent) large amounts of PI including location, travel, and personal health information. These were deployed to monitor, track, and control the spread of the virus. However, many of these measures encouraged the trade-off on privacy for safety. In this paper, we reexamine the nature of privacy through the lens of safety focused on the health sector, digital security, and what constitutes an infraction or otherwise of the privacy rights of individuals in a pandemic as experienced in the past 18 months. This paper makes a case for maintaining a balance between the benefit, which the contact tracing apps offer in the containment of COVID-19 with the need to ensure end-user privacy and data security. Specifically, it strengthens the case for designing with transparency and accountability measures and safeguards in place as critical to protecting the privacy and digital security of users—in the use, collection, and retention of user data. We recommend oversight measures to ensure compliance with the principles of lawful processing, knowing that these, among others, would ensure the integration of privacy by design principles even in unforeseen crises like an ongoing pandemic; entrench public trust and acceptance, and protect the digital security of people…(More)”.

Towards Efficient Information Sharing in Network Markets

Curated on Posted on by Stefaan Verhulst

Paper by Bertin Martens, Geoffrey Parker, Georgios Petropoulos and Marshall W. Van Alstyne: “Digital platforms facilitate interactions between consumers and merchants that allow the collection of profiling information which drives innovation and welfare. Private incentives, however, lead to information asymmetries resulting in market failures both on-platform, among merchants, and off-platform, among competing platforms. This paper develops two product differentiation models to study private and social incentives to share information within and between platforms. We show that there is scope for ex-ante regulation of mandatory data sharing that improves social welfare better than competing interventions such as barring entry, break-up, forced divestiture, or limiting recommendation steering. These alternate proposals do not make efficient use of information. We argue that the location of data access matters and develop a regulatory framework that introduces a new data right for platform users, the in-situ data right, which is associated with positive welfare gains. By construction, this right enables effective information sharing, together with its context, without reducing the value created by network effects. It also enables regulatory oversight but limits data privacy leakages. We discuss crucial elements of its implementation in order to achieve innovation-friendly and competitive digital markets…(More)”.

Has COVID-19 been the making of Open Science?

Curated on Posted on by Stefaan Verhulst

Article by Lonni Besançon, Corentin Segalas and Clémence Leyrat: “Although many concepts fall under the umbrella of Open Science, some of its key concepts are: Open Access, Open Data, Open Source, and Open Peer Review. How far these four principles were embraced by researchers during the pandemic and where there is room for improvement, is what we, as early career researchers, set out to assess by looking at data on scientific articles published during the Covid-19 pandemic….Open Source and Open Data practices consist in making all the data and materials used to gather or analyse data available on relevant repositories. While we can find incredibly useful datasets shared publicly on COVID-19 (for instance those provided by the European Centre for Disease Control), they remain the exception rather than the norm. A spectacular example of this were the papers utilising data from the company Surgisphere, that led to retracted papers in The Lancet and The New England Journal of Medicine. In our paper, we highlight 4 papers that could have been retracted much earlier (and perhaps would never have been accepted) had the data been made accessible from the time of publication. As we argue in our paper, this presents a clear case for making open data and open source the default, with exceptions for privacy and safety. While some journals already have such policies, we go further in asking that, when data cannot be shared publicly, editors/publishers and authors/institutions should agree on a third party to check the existence and reliability/validity of the data and the results presented. This not only would strengthen the review process, but also enhance the reproducibility of research and further accelerate the production of new knowledge through data and code sharing…(More)”.

The AI Localism Canvas: A Framework to Assess the Emergence of Governance of AI within Cities

Curated on Posted on by Stefaan Verhulst

Paper by Verhulst, Stefaan, Andrew Young, and Mona Sloane: “AI Localism focuses on governance innovation surrounding the use of AI on a local level….As it stands, however, the decision-making processes involved in the local governance of AI systems are not very systematized or well understood. Scholars and local decision-makers lack an adequate evidence base and analytical framework to help guide their thinking. In order to address this shortcoming, we have developed the below “AI Localism Canvas” which can help identify, categorize and assess the different areas of AI Localism specific to a city or region, in the process aid decision-makers in weighing risk and opportunity. The overall goal of the canvas is to rapidly assess and iterate local governance innovation about AI to ensure citizens’ interests and rights are respected….(More)”.

Information Disorder in the Glam Sector: The Challenges of Crowd Sourced Contributions

Curated on Posted on by Stefaan Verhulst

Paper by Saima Qutab, Michael David Myers and Lesley Gardner: “For some years information systems researchers have looked at crowdsourcing as a way for individuals, organizations and institutions to co-create content and generate value. Although there are many potential benefits of crowdsourcing, the quality control of crowd contributions stands out as one of the most significant challenges. Crowds can create the information contents but at the same time can facilitate information disorder: misinformation, disinformation and mal-information.

Crowd created information is a dominant element in what is sometimes called the post-truth era. A small piece of misleading information can constitute significant challenges to the information sharing group or society. This misinformation can reshape in various ways how information-driven communities make sense of their world. As information disorder and its effects have recently started to be recognised as a potential problem in IS research, we need to explore this phenomenon in more detail, to understand how it happens and why. This multiple case study is aimed at appraising information disorder through crowd-created contents in the knowledge and cultural heritage organisations such as Galleries, Libraries, Archives and Museums (GLAM). We intend to investigate the quality control mechanisms that might be used to prevent and minimise the effects of information disorder from crowdsourced contributions….(More)”.