Strategic opportunities (and challenges) of algorithmic decision-making: A call for action on the long-term societal effects of ‘datification’

Newell, Sue; Marabelli, Marco

doi:10.1016/j.jsis.2015.02.001

Cited by 339 publications

(252 citation statements)

References 47 publications

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“…In this vein, the PAYD model provides a valuable context for exploring the business and societal implications of technology-enabled business model innovation (Loebbecke & Picot, 2015;Markus, 2015;Newell & Marabelli, 2015). A focus on sensor adoption and use in the automotive insurance industry is relevant because it is driving a variety of changes affecting organizations and individuals across the automotive sector and beyond, including auto manufacturers, automotive sensor and OBD technology makers, automotive maintenance services, financing entities, information security standards, and public policy makers.…”

Section: Novel Business Models and Their Impact To Societymentioning

confidence: 99%

“…In Section 4.2, we consider these issues in greater depth by formulating additional research questions around the degree to which companies can establish a win-win situation that balances the interests of both businesses and consumers (Newell & Marabelli, 2015).…”

Section: Payd Model and Legal/cultural Systemsmentioning

confidence: 99%

“…In so doing, we draw and build on Newell and Marabelli's (2015) framework on the consequences of algorithmic decision making. The Newell and Marabelli (2015) framework comprehensively addresses broad issues associated with digital devices. Here, we narrow our focus to sensor-based technologies and look into the light and dark side of automotive insurance companies' PAYD models.…”

Section: Obd and Society: Cui Bono?mentioning

confidence: 99%

“…In other words, even if the initial choice is voluntary-a state of "informed control" (Newell & Marabelli, 2015)-the long-term use of such systems could engender a shift towards what one could label "semiinformed control". Such control could potentially create a situation where the initial decision to save money on a car insurance premium leads to constant monitoring with insured drivers giving away their driving data or leaving digital traces of the minutiae of their everyday (driving) lives with little awareness (Kehr, Kowatsch, Wentzel, & Fleisch, 2015;Keith, Thompson, Hale, Lowry, & Greer, 2013).…”

Section: Freedom Vs Controlmentioning

confidence: 99%

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The Light and Dark Side of The Black Box: Sensor-Based Technology in the Automotive Industry

Marabelli¹,

Hansen²,

Newell³

et al. 2017

CAIS

Self Cite

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Abstract:Diverse aspects of our everyday lives increasingly feature sensor-based technologies. Despite the importance of understanding how business and consumers exploit and adopt these technologies, the information systems (IS) community has thus far devoted relatively little attention to the topic. Accordingly, in this paper, we foster an exploration of the issue among IS scholars by focusing on the emergent use of sensor-based technologies in the automotive insurance industry. Insurance providers have increasingly begun to turn to such technologies to gain competitive advantage around risk assessment and behavior-based pricing. To investigate this phenomenon, we consider the experiences of two organizations operating distinct national contexts: Progressive Insurance (US) and Generali (Italy). These two insurance providers have been first movers in adopting sensor-based technologies for risk assessment and policy pricing. First, we highlight the key similarities and differences between the cases with regard to the technologies adopted, business models pursued, and anticipated benefits and pitfalls for the companies and their consumers. Second, in a more holistic way, we discuss the implications and unintended consequences of sensorbased technologies in the automotive insurance industry. We formulate several research questions that provide opportunities and encourage more research in this emerging area of study.

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Section: Novel Business Models and Their Impact To Societymentioning

confidence: 99%

Section: Payd Model and Legal/cultural Systemsmentioning

confidence: 99%

Section: Obd and Society: Cui Bono?mentioning

confidence: 99%

Section: Freedom Vs Controlmentioning

confidence: 99%

See 2 more Smart Citations

The Light and Dark Side of The Black Box: Sensor-Based Technology in the Automotive Industry

Marabelli¹,

Hansen²,

Newell³

et al. 2017

CAIS

Self Cite

View full text Add to dashboard Cite

show abstract

“…Researchers and practitioners alike face various types of challenges when using big data analytics for prediction, for instance, privacy and security of big data (Newell & Marabelli, 2015), platform scalability, integration, etc. However, for our purposes we only focus on key challenges that might hinder the ability of BDA to elucidate knowledge from digital archives.…”

Section: Bda Challengesmentioning

confidence: 99%

Opening Digital Archives and Collections with Emerging Data Analytics Technology: A Research Agenda

Elragal¹,

Päivärinta²

2017

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In the public sector, the EU legislation requires preservation and opening of increasing amounts of heterogeneous digital information that should be utilized by citizens and businesses. While technologies such as big data analytics (BDA) have emerged, opening of digital archives and collections at a large scale is in its infancy. Opening archives and collections involve also particular requirements for recognizing and managing issues of privacy and digital rights. As well, ensuring the sustainability of the opened materials and economical appraisal of digital materials for preservation require robust digital preservation practices. We need to proceed beyond the state-of-the-art in opening digital archives and collections through the means of emerging big data analytics and validating a novel concept for analytics which then enables delivering of knowledge for citizens and the society. We set out an agenda for using BDA as our strategy for research and enquiry and for demonstrating the benefit of BDA for opening digital archives by civil servants and for citizens. That will -eventually -transform the preservation practices, and delivery and use opportunities of public digital archives. Our research agenda suggests a framework integrating four domains of inquiry, analytics-enhanced appraisal, analytics-prepared preservation, analytics-enhanced opening, and analyticsenhanced use, for utilizing the BDA technologies in the domain of digital archives and collections. The suggested framework and research agenda identifies initially particular BDA technologies to be utilized in each of the four domains, and contributes by highlighting a need for an integrated "public understanding of big data" in the domain of digital preservation.

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Use Advanced Information Technology to Transform Organizations

KIM,

ALAVI, AND,

YOO,

2023

Principles of Organizational Behavior

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Strategic opportunities (and challenges) of algorithmic decision-making: A call for action on the long-term societal effects of ‘datification’

Cited by 339 publications

References 47 publications

The Light and Dark Side of The Black Box: Sensor-Based Technology in the Automotive Industry

The Light and Dark Side of The Black Box: Sensor-Based Technology in the Automotive Industry

Opening Digital Archives and Collections with Emerging Data Analytics Technology: A Research Agenda

Use Advanced Information Technology to Transform Organizations

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