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The purpose of this paper is to explore the prospect of using neurophenomenology to understand, design and test phygital consumer experiences. It aims to clarify interpretivist approaches to consumer neuroscience, wherein theoretical models of individual phenomenology can be combined with modern neuroimaging techniques to detect and interpret the first-person accounts of phygital experiences.

The argument is conceptual in nature, building its position through synthesizing insights from phenomenology, phygital marketing, theoretical neuroscience and other related fields.

Ultimately, the paper presents the argument that interpretivist neuroscience in general, and neurophenomenology specifically, provides a valuable new perspective on phygital marketing experiences. In particular, we argue that the approach to studying first-personal experiences within the phygital domain can be significantly refined by adopting this perspective.

One of the primary goals of this paper is to stimulate a novel approach to interpretivist phygital research, and in doing so, provide a foundation by which the impact of phygital interventions can be empirically tested through neuroscience, and through which future research into this topic can be developed. As such, the success of such an approach is yet untested.

Phygital marketing is distinguished by its focus on the quality of subjective first-personal consumer experiences, but few papers to date have explored how neuroscience can be used as a tool for exploring these inner landscapes. This paper addresses this lacuna by providing a novel perspective on “interpretivist neuroscience” and proposes ways that current neuroscientific models can be used as a practical methodology for addressing these questions.

The purpose of this paper is to investigate the influence of the external environment on the strategic thinking dimensions in Malaysia and Palestine on the banking sector.

This paper focuses on dynamism and complexity in political and economic external environments. This study uses qualitative methodology through a comparative case study method. Purposive sampling was used to collect data from in-depth semistructured interviews with 33 bank executives from Malaysia and 17 from Palestine.

The findings revealed that the banking sector in both Malaysia and Palestine shared five common strategic thinking dimensions, including vision, creativity, conceptual thinking, futurism and opportunity. However, a sixth dimension, intent-focused, was unique to Palestinian bank executives. This study indicates that Palestine’s financial strategic thinking environment is more dynamic and complex than Malaysia’s. Additionally, the study highlights the significant influence of both microenvironments (such as types of banks) and the macroenvironment (such as political and economic situations). These findings hold important implications for decision-makers in the banking sector of both countries.

As with many studies, this study has some limitations. First, the analysis examines only the turbulent and stable environment in the two countries by using a qualitative approach which enables the analysis of thoughts and actions and exposes the beliefs, perceptions, mental maps and structures of belief in their perceptions (Cavana et al., 2001). As such, the results are limited to a particular time, date and geographical location; thus, opinions and perceptions might be altered due to changes in the external political and economic environment. The second limitation of this work is that the case study might not be appropriate for generalization (Stake, 1978). Finally, the limited number of female participants in Palestine shows a high level of inequality compared to Malaysian participants.

This study explores the implication of uncertain environments at the national level on executives’ cognition and actions, links the micro- and macro-environment of the banking industry to a theoretical perspective and develops a conceptual circular model to show the effect of macro environments on bank performance. The findings offer practical contributions to the current literature, providing insights for executives to navigate a dynamic and complex banking industry.

This study fills the literature gap by exploring how strategic thinking dimensions triggered by macro- and micro-environments impact banking sector performance in Malaysia and Palestine.

Financial services industry is increasingly showing interest in automated financial advisors, or robo-advisors, with the aim of democratizing access to financial advice and stimulating investment behavior among populations that were previously less active and less served. However, the extent to which consumers trust this technology influences the adoption of rob-advisors. The resemblance to a human, or anthropomorphism, can provide a sense of social presence and increase trust.

In this paper, we conduct an experiment (N = 223) to test the effect of anthropomorphism (low vs medium vs high) and gender (male vs female) of the robo-advisor on social presence. This perception, in turn, enables consumers to evaluate personality characteristics of the robo-advisor, such as competence, warmth, and persuasiveness, all of which are related to trust in the robo-advisor. We separately conduct an experimental study (N = 206) testing the effect of gender neutrality on consumer responses to robo-advisory anthropomorphism.

Our results show that consumers prefer human-alike robo-advisors over machinelike or humanoid robo-advisors. This preference is only observed for male robo-advisors and is explained by perceived competence and perceived persuasiveness. Furthermore, highlighting gender neutrality undermines the positive effect of robo-advisor anthropomorphism on trust.

We contribute to the body of knowledge on robo-advisor design by showing the effect of robot’s anthropomorphism and gender on consumer perceptions and trust. Consequently, we offer insightful recommendations to promote the adoption of robo-advisory services in the financial sector.

This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

This study aims to explore the strategies corporations use in engaging stakeholders to sustain healthy corporate partnerships and create value for the corporate entity and the society in which they operate and their influence on the corporate manager’s cognitive abilities and decision-making.

The authors used an interpretive research approach leveraging the strengths of qualitative method of content analysis and comparative and critical analyses to report the results. Interpretive methods incorporate social theories and standpoints that view reality as the social construction of understandable events in the context of organizational communication.

The findings of this study suggest that corporations are assumed to follow and execute the principles of engaging stakeholders to achieve corporate social responsibility (CSR) claiming to manage a sustainable and responsible business practices that recognize local cultures, human rights and protect the environment. However, little attention has been paid to the cognitive reasoning of the individuals responsible for CSR and corporate sustainability (CS) as opposed to the growing concerns about strategies corporations use in engaging stakeholders to sustain healthy corporate partnerships and create value – especially the processes that take place during engagement and decision-making including cognitive offloading.

Stakeholder engagement requires practical approaches that enable corporations and individuals charged with decision-making responsibilities to understand, respond and fulfill their CSRs. To achieve CSRs, corporations and managers responsible for relevant decision-making would need to involve stakeholders in social performance planning, as social reporting/auditing has long been advocating for preventing managerial biasness, groupthink and increased information dissemination via detailed reporting practices toward more collaborative stakeholder relationships. Thus, it is crucial for corporations to implement enhanced stakeholder and managerial decision-making strategies such as integrative approaches to achieve balance in the trio elements of sustainability as well as the growing use of paradox perspective to understand the nature of the tensions being sought to balance and, in the process, provide opportunity for a better evaluation of complex sustainability issues for innovative approach to resolving them. While cognitive decision-making is at play, in practice, managers tasked with making decisions must ensure the most effective stakeholder engagement strategies that are transparent and inclusive are used.

The main contribution of this study is its argument regarding the tools corporations use in engaging key stakeholders and the cognitive reasoning of the individuals responsible for CSR and CS. The study further contributes to interpreting the integrative approach to achieving balance in the trio elements of sustainability as well as the growing use of paradox perspective to understand the nature of the tensions being sought to balance and, in the process, provide an opportunity for a better evaluation of complex sustainability issues for an innovative approach to resolving them.

The study integrated understanding by design-Internet of Things (UbD-IoT) education with design thinking and computational thinking to plan and design an IoT course. Cross-domain application examples were employed to train students in problem-understanding, deep thinking and logical design for IoT applications.

In this study, the UbD model was integrated with design thinking and computational thinking in the planning and design of an IoT course. The examples of cross-domain applications were used to train students to understand a problem by engaging themselves in deep thinking and helping them think and design logically for an IoT application.

The UbD-IoT learning design greatly decreased students' overall cognitive load. UbD-IoT learning has a significant impact on the performance of computational thinking in problem-solving and problem-understanding. The impact of UbD-IoT learning on logical thinking and program learning cognition in students needs to be verified.

The results of this study have shown that the UbD model is effective in reducing the cognitive load of a learning course and also strengthens T-competencies in the lateral skills of computational thinking, critical problem-solving, logical thinking and creative thinking.

This paper aims to explain the occurrence of sustainable entrepreneurship in the underresearched sub-Saharan Africa context and to improve the understanding of how effectuation manifests in this context.

This study uses a qualitative research approach based on multiple case studies. Responses were sourced from owners, employees, suppliers, the community and customers of sustainable entrepreneurial firms. Data collection methods included in-depth interviews, document reviews and observations. The Gioia analytical approach was used.

Overall, the authors find the concept of effectuation to be well-suited to capturing the processes through which individuals with limited means seek to engage in sustainable entrepreneurship. The authors also identify three pervasive practices that are key to understanding effectuation in the developing country context: complementation of indigenous knowledge with modern science, compassion and pluriactivity.

This study underscores the importance of co-creation, diversification of revenue sources and the role of emotional awareness and interpersonal skills in entrepreneurial endeavors.

This study, therefore, contributes new knowledge about the mechanisms through which entrepreneurs faced with resource constraints use control as opposed to prediction strategies to exploit sustainable entrepreneurship opportunities. In so doing, this study contributes to entrepreneurship theory by proposing the integration of cognitive and affective dimensions in realizing sustainable entrepreneurship goals.

Seekers who visit professional virtual communities (PVCs) are usually motivated by knowledge-seeking, which is a complex cognitive process. How do seekers search for knowledge, and how is their search linked to prior knowledge or PVC situation factors? From the cognitive process and interactional psychology perspectives, this study investigated the three-way interactions between seekers’ expertise, task complexity, and perceptions of PVC features (i.e. knowledge quality and system quality) on knowledge-seeking strategies and resultant outcomes.

A field experiment was conducted with 119 seekers in a PVC using a 2 × 2 factorial design of seekers’ expertise (i.e. expert versus novice) and task complexity (i.e. low versus high).

The study reveals three significant insights: (1) For a high-complexity task, experts adopt an ask-directed searching strategy compared to novices, whereas novices adopt a browsing strategy; (2) For a high-complexity task, experts who perceive a high system quality are more likely than novices to adopt an ask-directed searching strategy; and (3) Task completion time and task quality are associated with the adoption of ask-directed searching strategies, whereas knowledge seekers’ satisfaction is more associated with the adoption of browsing strategy.

We draw on the perspectives of cognitive process and interactional psychology to explore potential two- and three-way interactions of seekers’ expertise, task complexity, and PVC features on the adoption of knowledge-seeking strategies in a PVC context. Our findings provide deep insights into seekers’ behavior in a PVC, given the popularity of the search for knowledge in PVCs.

This study examined how people assess health information from AI and improve their diagnostic ability to identify health misinformation. The proposed model was designed to test a cognitive heuristic theory in misinformation discernment.

We proposed the heuristic-systematic model to assess health misinformation processing in the algorithmic context. Using the Analysis of Moment Structure (AMOS) 26 software, we tested fairness/transparency/accountability (FAccT) as constructs that influence the heuristic evaluation and systematic discernment of misinformation by users. To test moderating and mediating effects, PROCESS Macro Model 4 was used.

The effect of AI-generated misinformation on people’s perceptions of the veracity of health information may differ according to whether they process misinformation heuristically or systematically. Heuristic processing is significantly associated with the diagnosticity of misinformation. There is a greater chance that misinformation will be correctly diagnosed and checked, if misinformation aligns with users’ heuristics or is validated by the diagnosticity they perceive.

When exposed to misinformation through algorithmic recommendations, users’ perceived diagnosticity of misinformation can be predicted accurately from their understanding of normative values. This perceived diagnosticity would then positively influence the accuracy and credibility of the misinformation.

Perceived diagnosticity exerts a key role in fostering misinformation literacy, implying that improving people’s perceptions of misinformation and AI features is an efficient way to change their misinformation behavior.

Although there is broad agreement on the need to control and combat health misinformation, the magnitude of this problem remains unknown. It is essential to understand both users’ cognitive processes when it comes to identifying health misinformation and the diffusion mechanism from which such misinformation is framed and subsequently spread.

The mechanisms through which users process and spread misinformation have remained open-ended questions. This study provides theoretical insights and relevant recommendations that can make users and firms/institutions alike more resilient in protecting themselves from the detrimental impact of misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0167

In Brazil, over 4.7 million women enrolled in university in the year 2017. However, Brazilian women have been consistently overrepresented in humanities and care majors and underrepresented in science, technology, engineering and mathematics (STEM). Given that observed gender differences in math-intensive fields have lasting effects on gender inequality in the labor market, and that observed gender variations do not necessarily associate with differences in innate ability, in this paper we explore the paths of societal gender bias and gender differences in a Brazilian university.

We conduct a social experiment at a University in Southeastern Brazil, applying the gender-STEM Implicit Association Test.

We found that women in STEM are less likely to show gender-STEM implicit stereotypes, compared to women in humanities. The results indicate a negative correlation between implicit gender stereotyping and the choice of math-intensive majors by women.

The stereotype-congruent results are indicative of the gender bias in Brazilian society, and suggest that stereotypes created at early stages in life are directly related to future outcomes that reinforce gender disparities in Brazil, which can be observed in career choices.