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Enterprise social media (ESM) refers to a platform built on Web 2.0 technology dedicated to online collaboration and information sharing among employees within an organization. With the advent of the information age, ESM as a kind of information tool improves the internal communication and management mode of the enterprise, which is crucial for its sustainable development. The current research on ESM affordance has a single perspective and lacks a double-edged sword perspective. Studying ESM affordance from a double-edged sword perspective enables managers to recognize the complex impact of ESM use. Based on communication visibility theory and regulatory focus theory, we used prestige-striving behavior (PSB) and quiescent silence (QS) as mediating variables. In addition, we used need for uniqueness (NFU) as the moderating variable. The impact of ESM affordance on employee creativity (EC) was explored from a double-edged sword perspective. There were 428 questionnaires collected in China from October to November of 2023. The results indicate that ESM affordance promotes EC, PSB and QS. ESM affordance positively influences employee creativity by promoting PSB. ESM affordance negatively affects employee creativity by promoting QS. The moderating effect of NFU is significant. Full article

Drawing from both enactivist and cognitivist perspectives on mind, I propose that explaining teleological phenomena may require reappraising both “Cartesian theaters” and mental homunculi in terms of embodied self-models (ESMs), understood as body maps with agentic properties, functioning as predictive-memory systems and cybernetic controllers. Quasi-homuncular ESMs are suggested to constitute a major organizing principle for neural architectures due to their initial and ongoing significance for solutions to inference problems in cognitive (and affective) development. Embodied experiences provide foundational lessons in learning curriculums in which agents explore increasingly challenging problem spaces, so answering an unresolved question in Bayesian cognitive science: what are biologically plausible mechanisms for equipping learners with sufficiently powerful inductive biases to adequately constrain inference spaces? Drawing on models from neurophysiology, psychology, and developmental robotics, I describe how embodiment provides fundamental sources of empirical priors (as reliably learnable posterior expectations). If ESMs play this kind of foundational role in cognitive development, then bidirectional linkages will be found between all sensory modalities and frontal-parietal control hierarchies, so infusing all senses with somatic-motoric properties, thereby structuring all perception by relevant affordances, so solving frame problems for embodied agents. Drawing upon the Free Energy Principle and Active Inference framework, I describe a particular mechanism for intentional action selection via consciously imagined (and explicitly represented) goal realization, where contrasts between desired and present states influence ongoing policy selection via predictive coding mechanisms and backward-chained imaginings (as self-realizing predictions). This embodied developmental legacy suggests a mechanism by which imaginings can be intentionally shaped by (internalized) partially-expressed motor acts, so providing means of agentic control for attention, working memory, imagination, and behavior. I further describe the nature(s) of mental causation and self-control, and also provide an account of readiness potentials in Libet paradigms wherein conscious intentions shape causal streams leading to enaction. Finally, I provide neurophenomenological handlings of prototypical qualia including pleasure, pain, and desire in terms of self-annihilating free energy gradients via quasi-synesthetic interoceptive active inference. In brief, this manuscript is intended to illustrate how radically embodied minds may create foundations for intelligence (as capacity for learning and inference), consciousness (as somatically-grounded self-world modeling), and will (as deployment of predictive models for enacting valued goals). Full article