Purpose This study examines the post-adoption workaround behavior by organizations using blockchain in the food supply chain, focusing on how they manage tensions that arise with blockchain use. It addresses a gap in existing research, which has largely concentrated on initial adoption decisions rather than ongoing use and adjustment. Design/methodology/approach This study employs a qualitative case-study design, examining organizations from two supply chains through 23 semi-structured interviews. Iterative thematic data analysis uncovers patterns of workaround actions and learning that shape blockchain work practice. Findings This study identifies five types of workaround adjustments: data adjustments, procedural adjustments, parallel system adjustments, role adjustments and strategic design adjustments (blockchain-specific). Strategic design adjustments represent novel, architectural-level adaptations that go beyond traditional information systems contexts, emphasizing the need for ongoing workarounds in inter-organizational settings where technical architecture, governance and collaboration must be continuously aligned. The study further highlights blockchain work practices related to compatibility, complementarity and commitment, demonstrating how workarounds shape organizational learning, routines and the institutionalization of blockchain technologies. Practical implications The highlighted work practices related to compatibility, complementarity and commitment enable organizations to address post-adoption tensions, enhance adaptability and sustain effective blockchain use within a dynamic technological environment. Originality/value This study enhances the understanding of blockchain work practices by moving beyond acceptance-focused models to highlight the ongoing, tension-resolving efforts required in the post-adoption phases. It offers new insights into how organizations, particularly in inter-organizational settings, workaround to resolve emerging tensions and adapt blockchain technologies in practice.
Purpose This article examines the theoretical implications of organisational decisions being increasingly prepared, filtered, produced through or attributed to computational programmes rather than individual human actors. It asks under what conditions interactions between such programmes may be analysed as communicatively consequential and what this implies for management and organisation theory. Design/methodology/approach The article develops a conceptual analysis grounded in Luhmannian social systems theory. It uses a deliberately simplified, user-moderated exchange between two large language models, ChatGPT and Gemini, as an illustrative vignette. Their interpretations of code poems serve as a heuristic device for examining interpretive divergence, role formation and double contingency. Findings The illustrative exchange suggests that mutual responsiveness between computational programmes need not produce interpretive convergence. Instead, recursive reference to one another's outputs may stabilise distinct observational positions and patterned forms of mutual irritation. The article does not treat the vignette as an empirical test of programme–programme communication. It uses it to develop the conceptual proposition that large language models may be observed as organisationally instantiated decision programmes whose outputs become communicatively consequential when they are recursively incorporated into further organisational decisions. Originality/value The article contributes to management and organisation theory by reframing artificial intelligence not as a tool or agent but as a decision programme operating within organisational autopoiesis. By introducing programme–programme communication as an analytical lens, it shows how generative information technologies may create new decision premises, stabilise differentiated roles and reshape organisational coordination, responsibility and control in programme-rich environments.
Purpose From a conceptual perspective based on Luhmann's social systems theory, we examine how digital technologies – notably those of artificial intelligence (AI) – can reframe work-related meaning processing from which workers and organizations perceive work meaningfulness. Design/methodology/approach From a Luhmannian perspective, this research first advances a conceptual framework that considers (1) work as communication that can belong to a series of communication systems and that organizes structural couplings between these systems at the individual, organizational and societal levels and (2) digital technologies as mediums that intermediate work-related communication systems and codify work-related structural couplings. It next connects the framework with the empirical issues identified from an exploratory analysis of 137 existing studies to elucidate how digital mediums can reframe work in terms of meaning processing for workers as well as for organizations. Findings Our analysis stipulates that (1) digital mediums, doubly intermediating work-related meaning processing notably between workers and organizations, draw on and, in parallel, engender codifying references that normalize, formalize, signify and interconnect work-related communication and structure couplings; (2) the amplification of codifying references could stimulate self-referencing processes by forming coding communication technical systems that reframe different work-related meaning processing systems, which include psychic systems (e.g. workers) and social systems (e.g. organizations) and (3) the structural intermediateness afforded by digital mediums between these systems could affect the ways in which work meaningfulness is individually, organizationally and societally perceived. Originality/value This research provides a conceptual prism based on Luhmann's social systems theory to address the timely preoccupation related to the implications of AI for work. Its contributions can be mobilized, for example, to study from a systemic view (1) how to understand digitally reframed work and work meaningfulness, (2) how to specify and, if necessary, converge digitally meaningful work, psychically meaningful work and societally meaningful work, (3) how to preserve workers' meaning processing in the context of working with AI and (4) how to capture the societal effects of working with coding communication by considering the interconnection between multilevel work-related systems.
Purpose The antecedents and consequences of technostress are well documented. Yet, one aspect of the technostress process that is not well understood is the role of time in shaping perceptions of technostress. This research investigates the relationships between time pressure, technostress and work outcomes in online labour markets (OLMs), a context where work accomplishment is highly dependent upon time. Design/methodology/approach This study uses transactional theory of stress as a theoretical perspective to empirically test a research model explaining the link between time pressure and challenge and hindrance technostressors. Survey data were gathered from 354 workers in a widely used OLM. Structural equation modelling was used to evaluate the research model. Findings The findings show that time pressure plays a dual role, acting as a potential catalyst for both positive and negative effects of technostress in OLMs. Time pressure is significantly related to both challenge and hindrance technostressors. The findings also show that challenge and hindrance technostressors can create a time distortion effect in OLMs. However, despite experiencing hindrance technostressors, the workers in OLMs consider their work important and meaningful. A post-hoc analysis also suggests that the experience of challenge technostressors buffers the negative effect of hindrance technostressors on meaningful work. Originality/value The study extends the prior research by theorising and validating the importance of temporal elements in the technostress process. Time pressure acts as a key environmental antecedent contributing to technostress in OLMs. This study explores how technostressors affect unique work outcomes, such as time distortion and meaningfulness of work in OLMs.
Purpose This paper examines why many small- and medium-sized enterprises (SMEs) remain excluded from the digital and green transformations known as the Twin Transition. Drawing on Niklas Luhmann's social systems theory, it reconceptualises inclusion/exclusion not as a matter of resource deficits, but as a question of programmability, understood as the ability to generate communications that are intelligible within functionally differentiated social systems. Design/methodology/approach The study employs a qualitative, social systems theoretical approach grounded in second-order observation. It analyses an empirical case from a South Baltic Interreg project that developed a digital platform to support SME transformation. Rather than evaluating outcomes in managerial terms, the analysis observes how digital platform modules operate as meta-programmes that condition organisational decision programmes and structural coupling. Findings The findings show that digital platforms can function as socio-technical infrastructures that translate societal codes into organisationally useable semantic structures. By operating as meta-programmes, platform modules enable SMEs to reprogramme decision programmes related to digitalisation and sustainability, thereby enhancing their capacity to produce communications that resonate with multiple societal subsystems. Inclusion emerges as a semantic and programmatic effect rather than a direct out-come of access to resources Originality/value The paper contributes to Information Systems research by integrating Luhmann's distinction between code and programme into the analysis of digital infrastructures. It introduces the concepts of meta-programmes and programmable inclusion, highlighting programmability as a semantic condition of communicative connectability and extending current debates on socio-technical infrastructures, digital governance and organisational observability.
Purpose Artificial intelligence (AI) has changed the way organizations interact with their customers. This has instigated a necessity for businesses to address marketing managers' concerns and perceptions of the role of AI-powered systems in marketing processes. Although managers accept the fact that AI can potentially improve marketing practices and enhance efficiency, theories of Digital Leviathan predict inherent managerial anxiety about AI's destabilizing effects. Design/methodology/approach This study employs a qualitative method based on 12 in-depth interviews with marketing practitioners in Jordan, an emerging knowledge economy, to investigate key dimensions of marketing managers' perceptions of AI. Findings Findings from the interviews reveal four dimensions that explain marketing managers' Leviathanian perceptions: (1) emotion-driven empathy, (2) algorithmic opacity and explainability, (3) encryption and privacy concerns and (4) engagement, which are subsequently organized into an integrative framework that captures managerial concerns about the AI-driven marketing systems. These findings provide important insights into managerial perceptions of AI systems. They are underscored by the attribution of automatism to an emerging market Leviathan in developing economies. Together, these four dimensions capture managerial concerns on the trade-off between efficiency and humanization arising within AI-driven marketing practices. Originality/value This study offers several strategies to enhance technological humanization to help marketing managers to tackle Leviathanian concerns.
Purpose Generative artificial intelligence (AI) is making its way into our working lives. Previous research has explored topics such as AI-related fears among working people and AI technology adoption in companies, but people's perceptions of AI in the context of AI adoption are still not well understood. This article looks at the intersection of AI technology adoption and AI-related job concerns in one company. Design/methodology/approach A rapid ethnographic case study of a Finnish energy company during its introduction of a generative AI tool was conducted. This article explores: (1) How is AI technology adoption managed? (2) How do employees perceive AI-related social risks concerning their working lives? And (3) how are perceived risks related to AI accommodated? We utilized Marx's framework on alienation to analyze employees' AI-related job concerns and future perceptions, and improvisational change management theory to analyze technology adoption strategy. Findings AI-related concerns included both job security-related and job quality-related concerns. AI-related fears also manifest in rhetorics on the alienation-reducing potential of AI and digital automation. Employees' initiative is emphasized in technology adoption, which underlines the importance of their AI acceptance. Originality/value The article illustrates how AI acceptance is constructed in work culture, and it also shows how a classic theory can be relevant for analyzing AI perceptions. It demonstrates why employees' AI acceptance is central in the context of employee-led practices in AI technology adoption.
Purpose This article develops the framework of programmed power to theorize how digital platform infrastructures transform the conditions under which organizational programmes operate and decisions become observable. Drawing on Luhmann's systems theory, it asks what happens to programmes as decision premises when their conditional logic is computationally instantiated under conditions rendering premises non-inspectable, thresholds non-negotiable and operations non-attributable. 1t introduces the concept of presets to capture this transformation. Design/methodology/approach The article is conceptual, extending Luhmann's theory of programmes, decision premises and functional differentiation through engagement with recent Luhmannian scholarship on algorithms and organizational decision-making. A three-way comparison among programmatic governance, conditional programme governance and preset governance is developed through an illustration of algorithmic management in gig platforms. Findings Programmed power operates through four cumulative mechanisms: infrastructural encoding, communicative filtering, reflexivity suppression and post-decisional closure. The article introduces opaque coupling as the mechanism through which presets constrain communicative possibility while remaining beneath the threshold of observation, and identifies a legitimacy gap between the communicative register through which platforms produce legitimacy and the infrastructural register through which they exercise governance. The EU AI Act and Digital Services Act face structural limitations when targeting preset governance. Originality/value The article specifies how computational opacity transforms programme observability, contributing a diagnostic vocabulary absent from infrastructure studies and governance-by-design accounts. Its originality lies in treating presets as transformations of programmes, not replacements for them. The concepts of presets, opaque coupling and the legitimacy gap offer analytical tools for researchers studying algorithmic governance and for policymakers seeking to restore communicative access to programme premises embedded in platform infrastructures.
Purpose As virtual world games become popular avenues for emotional relief, artificial intelligence (AI)-powered non-player characters (AI-NPCs) are redefining gaming experience with their unparalleled intelligence and adaptability different from traditional NPCs. However, how AI-NPCs affect players' subjective well-being remains underexplored. This paper addresses this gap by elucidating how AI-NPCs affect players' subjective well-being, with Antecedent-Belief-Consequence framework as a guiding lens.Design/methodology/approach This paper adopts a sequential mixed-method research design. In the qualitative phase, the affordances of AI-NPCs relevant to players' subjective well-being were identified through 20 semi-structured interviews. Built upon the identified affordances, in the quantitative phase, a theoretical model was built and a total of 326 valid responses were obtained in the online survey.Findings The results have identified four technology affordances, namely interactivity affordance, emotional support affordance, aesthetic affordance and narrative affordance. Among them, interactivity and emotional support affordances are prominent antecedents of social identification, while aesthetic and narrative affordances enhance game identification. Both social identification and game identification contribute to players' subjective well-being.Originality/value Lying at the intersection of technology affordances and social identifications, our work is the first to investigate the impact of AI-NPCs design on players' subjective well-being in virtual world games. It not only extends the theory of affordances and identifications into the virtual world but also provides practical implications to facilitate effective human-AI interactions.
Purpose - Phishing is a form of social engineering attack that poses an increasingly significant risk in today's digital era. The challenges and implications associated with phishing affect both end users and organizations. However, organizations face particularly serious consequences, as a single employee's error can compromise the security and privacy of the entire organization. Design/methodology/approach - This research examines the factors influencing employees' intentions to adopt self-protective behaviors against phishing attacks using protection motivation theory (PMT). The study sample comprised 200 employees working in higher education institutions (HEIs). Findings - Perceived vulnerability, perceived risk, perceived barriers, response efficacy and self-efficacy influence behavioral intention. The findings also identify significant positive associations between conceptual knowledge and self-efficacy, procedural knowledge and self-efficacy and perceived vulnerability and information security awareness. Originality/value - This study contributes to the state of the art by extending PMT by integrating conceptual and procedural knowledge to explain employees' self-protective behaviors against phishing attacks. It also provides empirical evidence from the higher education sector, a context that has received limited attention in prior phishing research.
Purpose This study examines how Digital Care Management Technologies (DCMTs) reshape accountability and empathic care practices in UK homecare agencies. Grounded in Agency Theory and Sociotechnical Systems Theory, the study investigates how digital infrastructures interact with relational care practices in digitally mediated homecare settings. Design/methodology/approach The study draws on semi-structured interviews with managers and owners from twelve UK homecare agencies. Data were analyzed using the Gioia methodology to develop inductively grounded theoretical insights into how digital technologies reconfigure care practices and organizational accountability. Findings The findings identify two interrelated sociotechnical conditions through which digitalization reshapes homecare work: first, accountability-as-legibility, whereby DCMTs render care activities visible and auditable in real time, strengthening managerial oversight and external assurance; second, information symmetry, where shared digital access reduces informational gaps and enables more transparent coordination among managers, carers, families and regulators. These conditions give rise to an accountability-empathy paradox: while digital visibility enhances coordination and service assurance, excessive monitoring and reporting demands can constrain carers' empathic engagement. The outcomes depend on capacity of empathic care, defined as organizational conditions that preserve carers' attentional and relational resources for empathic work under digital oversight. Originality/value This study integrates Sociotechnical Systems Theory and Agency Theory to explain how digital accountability infrastructures in homecare simultaneously enable coordination and assurance while risking the crowding out of relational care, introducing capacity of empathic care as an organizationally configured outcome.
Purpose The primary objective of this research is to explore the underlying mechanisms of AI companions' emotional intelligence influencing user engagement through a dual-path model including both perceived emotional support and perceived emotional release. Design/methodology/approach An online survey of 251 users of AI companions in China was conducted to test the proposed research model and hypotheses. The partial least squares (PLS) approach was used to analyse the data. Additionally, this study provides further insights through interviews. Findings The results show that emotional intelligence of AI companions enhances users' perceived emotional support and emotional release. Perceived emotional support is positively associated with both hope agency and hope pathways, while perceived emotional release is positively associated with hope pathways but not hope agency. Emotional release tendency moderates the relationship between AI companions' emotional intelligence and users' perceived emotional release, while emotional support tendency does not moderate perceived emotional support. Originality/value This study proposes a multidimensional framework for AI companions' emotional intelligence, based on the interpersonal emotional intelligence model. It examines how emotional support and emotional release affect user behaviour simultaneously and explores the role of hope in this mechanism. Additionally, it highlights the importance of user tendencies in shaping the impact of AI companions' emotional intelligence on user emotional perception.
Purpose This study investigates how the design characteristics of artificial intelligence (AI)-powered chatbots influence user performance in mobile banking, focusing on the mediating role of synchronous service quality. Understanding how consumers collaborate with AI chatbots in real time is increasingly critical as service interactions become more automated.Design/methodology/approach Data were collected from 263 mobile banking users with prior experience using AI-powered chatbots; 230 valid responses were retained. Partial least squares structural equation modeling (PLS-SEM) was employed to examine both the antecedents and outcomes of synchronous service quality in AI-human collaboration.Findings The results show that all three chatbot characteristics - anthropomorphic design, perceived intelligence and perceived safety - significantly shape users' perceptions of synchronous service quality, which in turn affects task-oriented performance outcomes in terms of both emotional and cognitive responses. Perceived synchronicity emerges as a key mechanism enabling effective AI-human collaboration.Research limitations/implications The study was conducted within a single digital service context using a cross-sectional design. Future research should examine other service domains and cultural contexts, and apply longitudinal methods to improve generalizability.Practical implications Emphasizing human-likeness, cognitive responsiveness and safety in chatbot design can enhance synchronous communication, thereby improving user engagement and service efficiency in mobile banking.Originality/value This study makes a novel theoretical contribution by integrating Media Synchronicity Theory with the Computers Are Social Actors paradigm to explain how chatbot design drives real-time interaction quality. It shifts the analytical focus from user attitudes and adoption to the dynamics of interaction effectiveness - addressing a critical and underexplored dimension of intelligent service systems.
Purpose The widespread adoption of Information and Communication Technologies (ICT) for both work and personal use significantly impacts employees' professional and private lives, drawing considerable academic interest. Despite extensive research, existing studies often fail to integrate these distinct uses into a cohesive framework, hindering a complete understanding of their varying effects on employee work and life outcomes. To address these gaps, this study introduces the concept of “boundary-crossing ICT use (BCU)”, offering a unified framework for fragmented existing concepts and proposing a new classification model. Design/methodology/approach We followed established construct measurement and validation procedures (MacKenzie et al., 2011; Shiau and Huang, 2023). Study 1 specified the construct domain and dimensionality; Study 2 generated and refined items through expert screening, EFA, and CFA; and Study 3 examined nomological validity. Notable, drawing on Conservation of Resources Theory and effort-recovery logic, Study 3 employed this scale to investigate the differentiated impacts of proactive and reactive BCU on employees' mental health, also examining the moderating role of polychronicity (the preference for engaging in multiple tasks simultaneously). Findings This study rigorously developed and validated a 20-item BCU scale, encompassing four distinct dimensions: proactive life-related, proactive work-related, reactive life-related, and reactive work-related BCU. The results demonstrate that the BCU scale exhibits strong psychometric properties, making it a reliable tool for predicting health outcomes. Originality/value This study advances research on ICT-enabled work-life boundaries by integrating previously fragmented ICT-boundary constructs into a coherent BCU framework and by developing and validating a rigorous four-dimensional BCU scale. Importantly, the scale is not only a measurement contribution, but also an enabling one: by operationalizing direction and enacted agency simultaneously, it sharpens the conceptual understanding of BCU and provides a common framework for future research to examine when and why ICT-mediated boundary crossing becomes adaptive or maladaptive.
Purpose Previous research presents conflicting findings on how disclosing AI identity affects user responses. This meta-analysis quantifies the overall impact of AI identity disclosure on user responses (evaluations, attitudes, intentions and behaviors). It further explores how these effects are moderated by nine variables across four dimensions. Design/methodology/approach A systematic literature search identified 33 relevant articles comprising 44 independent studies. From these, 67 effect sizes from 25,208 participants were synthesized using a three-level random-effects model to account for nested data structures. We further employed a series of univariate three-level mixed-effects meta-regression models to examine subgroup differences, followed by exploratory analyses to test interaction effects among moderators, complemented by publication bias assessments and a series of robustness and sensitivity analyses. Findings AI identity disclosure has a small, statistically significant negative overall effect on user responses. High heterogeneity was observed, with no significant publication bias indicated. Negative effects were stronger for objective responses (vs. subjective responses), non-HCI tasks (vs. HCI tasks) and knowledge-oriented (vs. experience-oriented) applications. Furthermore, exploratory interaction analyses suggested significant interaction effects between sample types and experimental methods, cultural backgrounds and task forms and cultural backgrounds and application scenarios. Originality/value This meta-analysis systematically quantifies the impact of AI identity disclosure across diverse user responses, addressing prior inconsistencies by identifying significant contextual moderators. The findings inform context sensitive AI identity disclosure strategies, advance AI ethics and guide human-AI interaction design.
Purpose This study examines how multichannel digital information environments shape user decision-making in disposition-prone contexts within China's T+1 market. Grounded in coping theory and dual-system theory, we specify how channel attributes—issuer disclosures, third-party analyses, social networks, and artificial intelligence (AI)-based tools—affect decision quality through problem- and emotion-focused coping. Design/methodology/approach We adopt an exploratory sequential mixed-methods design. Study 1 develops the framework through grounded theory interviews with experienced Chinese investors who use digital trading platforms. Study 2 tests the dual-path model with a survey (N = 713) analyzed using partial least squares structural equation modeling (PLS-SEM) to evaluate how information quality, information overload, and channel-specific cues transmit effects to decision quality through the two coping routes. Findings Information quality strengthens both coping routes, while information overload weakens them. In social channels, perceived infollution reduces emotion regulation, whereas informational influence enhances analytic engagement. In AI channels, social influence and perceived technology acceptability reinforce both routes, while perceived algorithmic bias is nonsignificant. Mediation analyses confirm that problem- and emotion-focused coping jointly transmit channel effects to decision quality in a regulated, time-lagged market. Originality/value This paper integrates coping theory with information systems research by articulating a process-level, dual-path mechanism linking multichannel digital information and decision quality in T+1 setting. It advances technostress/information-behavior work by separating channel attributes (quality, load, social and AI cues) from coping responses. Furthermore, it extends prior single-channel studies by situating dual coping in an emerging digital market.
Purpose Artificial intelligence (AI) has enhanced mobile banking by improving user value and user experience. Success depends on user stickiness, but few studies have explored how AI-specific features (perceived intelligence and anthropomorphism) affect user stickiness or how technology readiness (optimism, innovativeness, discomfort, and insecurity) moderates these effects in the context of AI-enabled mobile banking. Design/methodology/approach This study develops a research model to examine the impacts of perceived intelligence and anthropomorphism on user stickiness, as well as the moderating role of technology readiness. Data were collected from a sample of 428 users with prior experience using AI-enabled mobile banking applications and were analyzed using the partial least squares (PLS) method. Findings The results reveal that both intelligence and anthropomorphism positively influence user stickiness in AI-enabled mobile banking applications, highlighting their essential role in encouraging more frequent usage of and extended usage time on these applications. In addition, optimism and innovativeness significantly strengthen the positive effects of both perceived intelligence and perceived anthropomorphism on user stickiness. In contrast, discomfort and insecurity do not significantly moderate the relationships between perceived intelligence or perceived anthropomorphism and user stickiness. Originality/value This study introduces user stickiness as a behaviorally grounded outcome to better explain user adoption behavior in AI-enabled mobile banking. The findings show that perceived anthropomorphism outweighs intelligence in driving user stickiness, and only optimism and innovativeness moderate these effects. Moreover, optimism proves more influential than innovativeness does, thereby refining the TRI framework and advancing the understanding of AI adoption in intelligent financial services.
Purpose The purpose of this study is to investigate how different integration strategies (i.e. internal and external integration) mediate the impacts of information technology (IT) capabilities (i.e. internally- and externally-focused) on competitive performance as well as how such mediating effects are moderated by environmental turbulence. Design/methodology/approach This study uses data collected from 179 Chinese firms for analyses using hierarchical regression analysis. Findings The results find that internally- and externally-focused IT capabilities affect competitive performance through internal and external integration, respectively. Moderated mediation analyses further reveal that the mediating effect of internal integration on the relationship between internally-focused IT capability and competitive performance is stronger under high level of environmental turbulence, while the mediating effect of external integration on the relationship between externally-focused IT capability and competitive performance is stronger under low level of environmental turbulence. Originality/value This study crystallizes the insights of resource-action-performance model and information processing theory and empirically tests how environmental turbulence moderates the mediating effects of different integration strategies on the relationships between different IT capabilities and competitive performance.
Purpose This study originates from observations and reflections on a fundamental work paradigm shift: the deep integration of artificial intelligence (AI) is driving work beyond task automation toward hybrid intelligence (HI). This reveals a profound paradigm misalignment. Traditional literacy models fail to capture the relational, generative and systemic nature of HI and lack a micro-level perspective on human-AI collaboration. This study aimed to identify and explicate digital literacies and their mechanisms within HI workflows, providing both theoretical foundations and practical architecture for a more integrated, adaptive and co-evolutionary paradigm.Design/methodology/approach An exploratory qualitative design was employed, drawing on semi-structured interviews with 24 HI practitioners in China's financial and e-commerce sectors, contexts characterized by high complexity, ambiguity and uncertainty. The data were analyzed thematically to identify key literacy practices.Findings Four core literacies were identified as forming a generative HI system: cross-border literacy (integrating heterogeneous cognitive frameworks), cognitive literacy (orchestrating generative dialogue with AI), evolve literacy (enabling bidirectional co-learning) and transformative literacy (driving architecture reconstruction). These literacies function as micro-level rules addressing challenges across HI workflow stages.Originality/value This study identifies four critical literacies that catalyze HI workflows, advancing digital literacy research toward a dynamic practice-relational paradigm. It contributes a micro-process perspective to socio-technical systems theory and offers a generative account of HI as a complex adaptive system. This study provides an actionable framework elevating digital literacy from an individual trait to an organizational design cornerstone.
Purpose This article reconceptualises interactivity as a systems-theoretical concept grounded in the distinction between form and medium. It clarifies how interactivity should be understood not as interaction or reciprocity, but as the technologically organised conditioning of communicative continuation, and analyses how this configuration is transformed under conditions of generative AI. Design/methodology/approach The article reconstructs Luhmann's sociology of communication, media and technology as an integrated analytical framework. Interactivity is reinterpreted through the interactivity typology of Bordewijk and van Kaam as programme configurations understood as condensed decision premises. On this basis, the concept of technological media formation is developed to analyse how media condition communicative form-building across sociomedia evolution, from language and inscription to digital infrastructures and generative systems. Findings Interactivity designates the relation between communicative form-building and its technologically conditioned medium. Across sociomedia evolution, decision premises progressively condense from socially enacted constraints into mechanised, automated and infrastructural configurations. Earlier digital interactivity stabilised continuation through deterministic programme architectures. Generative AI introduces a non-trivial technological media formation in which probabilistic computation conditions the generation of selectable proposals without participating in communicative meaning formation. This transformation reorganises transmission, consultation, conversation and registration by shifting programmes from deterministic stabilisation to stochastic conditioning. Interactivity increasingly approximates interaction experientially, while communicative closure remains intact. Originality/value The article contributes (1) a form-theoretical reconstruction of interactivity within systems theory, (2) a sociomedia-evolutionary account of technological media formation and (3) a conceptual clarification of generative AI as non-trivial technological automated media formation. It thereby provides a non-normative framework for analysing how probabilistic infrastructures reorganise communicative potentiality without dissolving the distinction between communication and technology.
