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This study addresses how algorithmic recommendations and their affordances shape everyday information practices among young people.

Thematic interviews were conducted with 20 Finnish young people aged 15–16 years. The material was analysed using qualitative content analysis, with a focus on everyday information practices involving online platforms.

The key finding of the study is that the current affordances of algorithmic recommendations enable users to engage in more passive practices instead of active search and evaluation practices. Two major themes emerged from the analysis: enabling not searching, inviting high trust, which highlights the how the affordances of algorithmic recommendations enable the delegation of search to a recommender system and, at the same time, invite trust in the system, and constraining finding, discouraging diversity, which focuses on the constraining degree of affordances and breakdowns associated with algorithmic recommendations.

This study contributes new knowledge regarding the ways in which algorithmic recommendations shape the information practices in young people's everyday lives specifically addressing the constraining nature of affordances.

This paper examines promotional practices Netflix employs via Twitter and its automated recommendation system in order to deepen our understanding of how streaming services contribute to sociotechnical inequities under capitalism.

Tweets from two Netflix Twitter accounts as well as material features of Netflix's recommendation system were qualitatively analyzed using inductive analysis and the constant comparative method in order to explore dimensions of Netflix's promotional practices.

Twitter accounts and the recommendation system profit off people's labor to promote content, and such labor allows Netflix to create and refine classification practices wherein both people and content are categorized in inequitable ways. Labor and classification feed into Netflix's production of culture via appropriation on Twitter and algorithmic decision-making within both the recommendation system and broader AI-driven production practices.

Assemblages that include algorithmic recommendation systems are imbued with structural inequities and therefore unable to be fixed by merely diversifying cultural industries or retooling algorithms on streaming platforms. It is necessary to understand systemic injustices within these systems so that we may imagine and enact just alternatives.

Findings demonstrate that via surveillance tactics that exploit people's labor for promotional gains, enforce normative classification schemes, and culminate in normative cultural productions, Netflix engenders practices that regulate bodies and culture in ways that exemplify interconnections between people, machines, and social institutions. These interconnections further reflect and result in material inequities that crystalize within sociotechnical processes.

The purpose of this paper is to develop a conceptual framework for assessing what are the possibilities and pitfalls of using algorithmic systems of news personalization – i.e. the tailoring of individualized news feeds based on users’ information preferences – for constructive conflict coverage in the context of peace journalism, a journalistic paradigm calling for more diversified and creative war reporting.

The paper provides a critical review of existing research on peace journalism and algorithmic news personalization, and analyzes the intersections between the two concepts. Specifically, it identifies recurring pitfalls of peace journalism based on empirical research on constructive conflict coverage and then introduces a conceptual framework for analyzing to what degree these pitfalls can be mediated – or worsened – through algorithmic system design.

The findings suggest that AI-driven distribution technologies can facilitate constructive war reporting, in particular by countering the effects of journalists’ self-censorship and by diversifying conflict coverage. The implementation of these goals, however, depends on multiple system design solutions, thus resonating with current calls for more responsible and value-sensitive algorithmic design in the domain of news media. Additionally, our observations emphasize the importance of developing new algorithmic literacies among journalists both to realize the positive potential of AI for promoting peace and to increase the awareness of possible negative impacts of new systems of content distribution.

The article particle is the first to provide a comprehensive conceptualization of the impact of new content distribution techniques on constructive conflict coverage in the context of peace journalism. It also offers a novel conceptual framing for assessing the impact of algorithmic news personalization on reporting traumatic and polarizing events, such as wars and violence.

The article makes an empirical and conceptual contribution to understanding the temporalities of information literacies. The paper aims to identify different ways in which anticipation of certain outcomes shapes strategies and tactics for engagement with algorithmic information intermediaries. The paper suggests that, given the dominance of predictive algorithms in society, information literacies need to be understood as sites of anticipation.

The article explores the ways in which the invisible algorithms of information intermediaries are conceptualised, made sense of and challenged by young people in their everyday lives. This is couched in a conceptual discussion of the role of anticipation in understanding expressions of information literacies in algorithmic cultures. The empirical material drawn on consists of semi-structured, pair interviews with 61 17–19 year olds, carried out in Sweden and Denmark. The analysis is carried out by means of a qualitative thematic analysis in three steps and along two sensitising concepts – agency and temporality.

The results are presented through three themes, anticipating personalisation, divergences and interventions. These highlight how articulating an anticipatory stance works towards connecting individual responsibilities, collective responsibilities and corporate interests and thus potentially facilitating an understanding of information as co-constituted by the socio-material conditions that enable it. This has clear implications for the framing of information literacies in relation to algorithmic systems.

The notion of algo-rhythm awareness constitutes a novel contribution to the field. By centring the role of anticipation in the emergence of information literacies, the article advances understanding of the temporalities of information.

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’ approval of AI certification entities is vital for its effectiveness and companies’ choice of certification. This study aims to generate important insights into the consumer perspective of AI certifications and stimulate future research.

A literature and status-quo-driven search of the AI certification landscape identifies entities and related concepts. This study empirically explores consumer approval of the most discussed entities in four AI decision domains using an online experiment and outline a research agenda for AI certification in marketing/social media.

Trust in AI certification is complex. The empirical findings show that consumers seem to approve more of non-profit entities than for-profit entities, with the government approving the most.

The introduction of AI certification to marketing/social media contributes to work on consumer trust and AI acceptance and structures AI certification research from outside marketing to facilitate future research on AI certification for marketing/social media scholars.

For businesses, the authors provide a first insight into consumer preferences for AI-certifying entities, guiding the choice of which entity to use. For policymakers, this work guides their ongoing discussion on “who should certify AI” from a consumer perspective.

To the best of the authors’ knowledge, this work is the first to introduce the topic of AI certification to the marketing/social media literature, provide a novel guideline to scholars and offer the first set of empirical studies examining consumer approval of AI certifications.

Artificial intelligence (AI) is transforming consumers' experiences and how firms identify, create, nurture and manage interactive marketing relationships. However, most marketers do not have a clear understanding of what AI is and how it may mutually benefit consumers and firms. In this paper, the authors conduct an extensive review of the marketing literature, develop an AI framework for understanding value co-creation in interactive buyer–seller marketing relationships, identify research gaps and offer a future research agenda.

The authors first conduct an extensive literature review in 16 top marketing journals on AI. Based on this review, an AI framework for understanding value co-creation in interactive buyer–seller marketing relationships was conceptualized.

The literature review led to a number of key research findings and summary areas: (1) an historical perspective, (2) definitions and boundaries of AI, (3) AI and interactive marketing, (4) relevant theories in the domain of interactive marketing and (5) synthesizing AI research based on antecedents to AI usage, interactive AI usage contexts and AI-enabled value co-creation outcomes.

This is one of the most extensive reviews of AI literature in marketing, including an evaluation of in excess or 300 conceptual and empirical research. Based on the findings, the authors offer a future research agenda, including a visual titled “What is AI in Interactive Marketing? AI design factors, AI core elements & interactive marketing AI usage contexts.”

The rapid development of information and communication technologies (ICTs) has facilitated consumers’ involvement in firms’ value creation processes through increasingly near real-time information exchanges. This strategic opportunity configures new forms of ICT-enabled collaboration between firms and consumers. Firms can now immediately react to consumers’ requests/complaints, having gained real-time visibility of consumers’ actions and behaviors. Despite the increasing deployment of ICT-enabled value co-creation projects, managers still poorly apprehend them as high-potential strategic initiatives.

This paper investigates this gap through a multiple qualitative case study based on 17 organizations that successfully implement ICT-based value co-creation initiatives, including Lego, Netflix and Blablacar.

This study identifies two dimensions of the ICTs’ value co-creation process, namely, the firms’ involvement and customers’ role, in this co-creation process. Through these dimensions, four ICT-based co-creation initiatives are observed and defined: community, customers’ contributions create the firms’ value proposition (FVP); customization, customers’ service consumption personalize FVP; reputation, customers’ contributions about the offered services completes the FVP; and sense, an algorithmic approach, designed to focus on learning from customers’ consumption tailors FVP.

This study advances a framework supporting managerial decision-making concerning the aptitude of co-creation initiatives to meet organizational goals. Managers may gain insight from its use especially in assessing emerging opportunities to engage consumers in the value creation process.