Jose Ramon Saura

This study introduces a conceptual framework that reframes predictive personalization as a recursive cognitive process shaped by algorithms, social media platforms, and artificial intelligence (AI), based on a systematic literature review. Although predictive personalization has been widely examined as a tactical tool to increase engagement, existing research lacks an integrative theoretical framework explaining how it recursively interacts with consumer cognition across fragmented literatures. In this model, digital cognition interprets behavioral traces as data‐driven representations of cognitive processes. Through AI‐driven algorithmic prediction, behavioral data are used to personalize digital exposure that influence users' attention, memory, and decision processes, gradually reshaping how cognition operates within digital environments. As a result, predictive marketing personalization enables the modeling of a closed‐loop system that may support more effective digital marketing strategies. What begins as digitally extended cognitive activity is rendered into streams of behavioral data. These data fuel predictive models, which generate outputs that subsequently reshape mental states and influence future behaviors. The outcome is a self‐modifying system in which human cognition and machine logic evolve in tandem. The loop then restarts. The study relies on qualitative synthesis and theory mapping rather than on primary empirical data analysis. Positioned within the predictive marketing personalization and algorithmic decision‐making research stream, the study theoretically maps this loop across two interdependent layers (behavioral traces and algorithmic interventions) and integrates them with established theories. It further introduces the concept of cognitive equilibrium marketing as a conceptual perspective that aligns algorithmic precision with cognitive and ethical balance. The results analyze how personalization not only reacts to user behavior but transforms how individuals attend, remember, decide, and learn in digital environments. The study concludes with 7 research propositions linked to boundary conditions and 30 future research questions, highlighting the psychological, ethical, and managerial implications of cognition‐aware personalization systems in contemporary digital marketing. From a practical perspective, the framework offers actionable guidance for managers and practitioners designing AI‐driven personalization systems, helping them align algorithmic precision with users' cognitive capacities, ethical constraints, and long‐term engagement outcomes.

Purpose: The rapid integration of Artificial Intelligence (AI) and robotics into digital strategies has significantly transformed business operations, enhancing efficiency, decision-making, and connectivity. The purpose of this study is to explore how emerging economies can leverage these technologies to drive economic growth while addressing distinct challenges related to privacy, ethical considerations, and data security. Design/methodology/approach: To investigate the complexities of AI robotics adoption in emerging economies, this study uses a two-step methodology. First, a systematic literature review synthesizes key contributions to the field, identifying relevant theoretical frameworks. Following this, a Multiple Correspondence Analysis (MCA) based on homogeneity analysis of variance using alternating least squares is conducted in the R programming language. Findings: The main findings suggest that the successful adoption of AI-driven digital strategies in emerging economies requires balancing innovation with robust privacy protections, ensuring that user trust is cultivated through transparent and user-centered practices for the adoption of AI robotics applications. Furthermore, ethical considerations, such as adaptability to local values and regulatory readiness, emerge to aligning technological advancements with societal needs. The presence of outlier variables, such as the impact on employment and the risk of data leakage, highlights possible research gaps in the literature. Research limitations/implications: The MCA analysis in R, though effective for exploring relationships between variables, is sensitive to data quality and may not capture all dimensions of real-world applications. Practical implications: For successful AI robotics adoption in emerging economies, companies should focus on AI robotics systems that prioritize data security, fostering user trust and ensuring compliance with diverse regulatory environments, prioritize digital literacy initiatives and create user-friendly technologies that accommodate varying levels of digital skills. Social implications: The outlier variables, such as “Impact on Employment” and “Data Leakage,” have implications for socio-technical systems theory, which examines the interaction between technology, people and social systems. The separation of these variables from the main clusters suggests that certain socioeconomic impacts of AI robotics, like job displacement and privacy risks, are distinct concerns in emerging economies. Originality/value: This study’s originality contributes to the field by addressing an area where limited research exists, the intersection of AI robotics in digital strategies, ethical considerations and privacy in the emerging market context.

This study explores the motivations and decision-making processes of small business leaders engaging in societal commitment, using sensemaking theory as a conceptual framework. While existing research has extensively examined corporate social responsibility (CSR) strategies, the role of individual decision-makers in initiating and structuring these engagements remains underexplored. This study addresses this gap by investigating how leaders interpret, construct meaning, and integrate their personal values into their company’s societal strategy. Adopting a qualitative approach, the study draws on semi-structured interviews and shadowing conducted with 22 small business leaders, capturing their perceptions, motivations, and the strategic processes underlying their commitment. The findings highlight that the alignment between personal values and corporate societal objectives is critical in shaping authentic and impactful engagement. Leaders do not engage in societal causes solely for economic or strategic benefits, such as market differentiation and consumer expectations, but also as part of a deeply personal and retrospective process that integrates identity, past experiences, and collective sensemaking within their organizations. From a managerial perspective, the research provides practical guidance for business leaders seeking to design genuine and sustainable societal commitments in small businesses. This study contributes to theory by demonstrating how sensemaking process’s structure managerial decisions on societal engagement, bridging individual identity construction with strategic organizational outcomes. The findings challenge traditional perspectives on corporate activism by showing that commitment can be visible, discreet, or even hidden, depending on perceived risks, legitimacy concerns, and stakeholder dynamics. Given the exploratory nature of our study, it presents certain inherent limitations, which in turn open up avenues for future research. First, while the qualitative methodology adopted provides an in-depth understanding of managerial motivations, it does not allow for a comprehensive assessment of the evolution of these dynamics from a temporal perspective. Accordingly, our current research is part of a longitudinal study aimed at analyzing the evolution of executives’ societal engagement over several years. This work will deepen the understanding of the relationship between societal engagement and committed managerial practices, with a particular focus on the resilience of such engagement in the face of adversity and the strategies implemented to manage dilemmas inherent to corporate social responsibility. Second, the issue of generalizing the results represents another limitation of our work. The sample, while relevant to our analysis, is limited to executives currently in position, without considering future decision-makers, namely students in management and entrepreneurship. However, academic training plays a fundamental role in shaping values and managerial practices (Lobre-Lebraty and Heimann, 2024; Ratten and Jones, 2021; Secundo et al., 2019). A promising research avenue would thus be to examine how management students perceive and integrate societal issues into their strategic vision. Research could specifically analyze the impact of sustainable education (Wyness et al., 2015) on their future behaviors regarding societal engagement. Likewise, observing young entrepreneurs in the early stages of their ventures would help identify whether and how societal engagement is embedded in their initial strategic decisions, as well as its influence on sustainable business practices (Di Prima et al., 2023). In sum, our future research aims to provide a temporal and dynamic perspective on the role of leadership in societal engagement. Most executives perceive their company’s societal engagement as a risk factor. As founders and initiators of these commitments, their personal history often heightened this perception. This can lead them to adopt a discreet approach or even maintain a certain level of confidentiality around their societal actions. However, they must navigate between the risk of inaction, which can limit the impact of societal initiatives, and the risk of excessive discretion, which may hinder stakeholder mobilization and reduce the reach of their commitments. A too-cautious approach, driven by fear of controversy or financial consequences, can weaken the effectiveness of actions implemented within the organization. To maximize the impact of their commitments, executives must actively engage stakeholders in the definition and implementation of their societal initiatives. By co-constructing strategies with employees, customers, and suppliers, they foster collective ownership, ensuring the longevity of these commitments. This dynamic extends beyond current stakeholders to include future audiences, such as potential customers or evolving teams, contributing to embedding engagement within a sustainable and evolving perspective. Finally, the alignment between personal values and corporate social engagement creates a bridge between their individual commitment and that of their company. This alignment develops within a temporal process that connects the personal and the collective and is essential for anchoring societal engagement in a lasting and meaningful way. In terms of theoretical implications, the results of the study also enrich Weick’s social dimension of sensemaking and complement the concept of the “parliament of selves”. Historically, Weick evokes the idea of multiple aspects or facets of a person who coexist and may have different opinions or desires, like different parliament members. We develop this concept by integrating and classifying these dimensions: self in relation to its ideology (1), self in relation to other real or supposed (2), and self in relation to its individual-organizational dialectic (3). Our work reinforces the idea that there are internal discussions between leaders who are torn between the initial desire for commitment and the achievable desire, between the ideal commitment and the confrontation with economic reality and the market. The understanding of the dimension of self in relation to ideology (1) allows giving elements on the perception of the meaning of their values, of what they say they want to transmit through the societal commitment of the organization and to give a reading of the results. These results are to be read under this prism. The originality of our research lies in the fact that it explains and explores in greater depth the notion of how commitment is made. In this way, managers wishing to take part in a societal approach will be able to understand how this can be done and how it gives meaning to their actions at work.

Behavioral Economics, artificial intelligence (AI), and Entrepreneurship have emerged as critical fields reshaping contemporary management practices. This article explores the connections between these disciplines to propose an updated framework for entrepreneurship management. To achieve this, a systematic literature review was conducted, complemented by a Latent Dirichlet Allocation (LDA) topic modeling algorithm developed in Python to identify thematic patterns across the selected corpus. The findings reveal eight key topics linked to these fields, including strategic management, decision-making, and innovation, highlighting their interrelations through AI integration. Specifically, positive correlations between innovation, market dynamics, and risk management emphasize AI’s potential to enhance entrepreneurial decision-making and market adaptability. Also, behavioral insights further underpin these themes, showcasing AI’s capacity to address cognitive biases and optimize management strategies. Additionally, this study proposes eight research propositions to guide future investigations in this field that align with the identified topics, offering novel theoretical perspectives and practical applications that set an updated framework for management practices. The findings provide entrepreneurs with strategic guidance for leveraging these areas to advance innovation, enhance adaptive decision-making, and promote sustainable management practices within dynamic ecosystems shaped by the growing influence of AI and behavioral economics on managerial frameworks, which capitalize on a deeper understanding of human behavior.