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Cyber-attacks that generate technical disruptions in organisational operations and damage the reputation of organisations have become all too common in the contemporary organisation. This paper explores the reputation repair strategies undertaken by organisations in the event of becoming victims of cyber-attacks.

For developing the authors’ contribution in the context of the Internet service providers' industry, the authors draw on a qualitative case study of TalkTalk, a British telecommunications company providing business to business (B2B) and business to customer (B2C) Internet services, which was a victim of a “significant and sustained” cyber-attack in October 2015. Data for the enquiry is sourced from publicly available archival documents such as newspaper articles, press releases, podcasts and parliamentary hearings on the TalkTalk cyber-attack.

The findings suggest a dynamic interplay of technical and rhetorical responses in dealing with cyber-attacks. This plays out in the form of marshalling communication and mortification techniques, bolstering image and riding on leader reputation, which serially combine to strategically orchestrate reputational repair and stigma erasure in the event of a cyber-attack.

Analysing a prototypical case of an organisation in dire straits following a cyber-attack, the paper provides a systematic characterisation of the setting-in-motion of strategic responses to manage, revamp and ameliorate damaged reputation during cyber-attacks, which tend to negatively shape the evaluative perceptions of the organisation's salient audience.

The digital platform-based sharing economy has become ubiquitous all over the world. In this paper, we explore how market actors’ conflicting interpretations of digital platforms’ business models give form and shape value co-creation and capture practices in contexts marked by weak institutions and underdeveloped markets.

Integrating insights from the broader literature on digital platforms and the contemporary turn to “meaning-making” in social theory, we adopt a problematization method to unpack the collective contest over the interpretation of value co-creation and capture from ridesharing platforms in contexts marked by weak institutions and underdeveloped markets.

Collective contest over the interpretation of digital business models may give rise to competing meanings that may enable (or impede) digital platform providers’ ability to co-create and capture value. We present an integrative framework that delineates how firms caught up in such collective contests in contexts marked by weak institutions and underdeveloped markets may utilise such conditions as marketing resources to reset their organising logic in ways that reconcile the conflicting perspectives.

The paper presents propositions constituting a contribution to a meaning-making perspective on ridesharing digital platforms by offering insights into how digital business models could potentially be localised and adapted to address and align with the peculiarities of contexts. It goes further to present a theoretical model to extend our understanding of the different sources of contestation of meaning of digital platforms.

The meaning-making perspective on digital platforms extends our understanding of how the collective contest over interpretations of value co-creation and capture may offer a set of contradictory frames that yield possibilities for ridesharing platform providers, and their users, to assimilate the organising logic of digital business models into new categories of understanding.

This study responded to calls to investigate the behavioural and social antecedents that produce a highly positive response to AI bias in a constrained region, which is characterised by a high share of people with minimal buying power, growing but untapped market opportunities and a high number of related businesses operating in an unregulated market.

Drawing on empirical data from 225 human resource managers from Ghana, data were sourced from senior human resource managers across industries such as banking, insurance, media, telecommunication, oil and gas and manufacturing. Data were analysed using a fussy set qualitative comparative analysis (fsQCA).

The results indicated that managers who regarded their response to AI bias as a personal moral duty felt a strong sense of guilt towards the unintended consequences of AI logic and reasoning. Therefore, managers who perceived the processes that guide AI algorithms' reasoning as discriminating showed a high propensity to address this prejudicial outcome.

As awareness of consequences has to go hand in hand with an ascription of responsibility; organisational heads have to build the capacity of their HR managers to recognise the importance of taking personal responsibility for artificial intelligence algorithm bias because, by failing to nurture the appropriate attitude to reinforce personal norm among managers, no immediate action will be taken.

By integrating the social identity theory, norm activation theory and justice theory, the study improves our understanding of how a collective organisational identity, perception of justice and personal values reinforce a positive reactive response towards AI bias outcomes.