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This study aims to explore the antecedent factors that directly and indirectly influence electronic word of mouth (eWoM) for social commerce (s-commerce) in two developing countries (e.g. Kuwait and the United Arab Emirates [UAE]) by extending social cognitive theory.

This study uses a previous robust model (Rouibah et al., 2021) as theoretical background to investigate and compares the antecedents (trust in Instagram, perceived risks) on eWoM for s-commerce through the mediation of three mediators (perceived enjoyment, perceived value and customer satisfaction) among two Arab countries. Data was collected from Kuwait (n = 1,132) and the UAE (n = 190). Different statistical analyses and structured equation modeling-based analysis of moment structure are used to test the robustness of the research model.

This study found customer satisfaction to be most important factor that mediates the effect independent factors on eWoM for s-commerce in both countries. Surprisingly, perceived enjoyment has no effect, and trust in Instagram and perceived risks are the most important factors that are considered imperative for customer satisfaction and positive feedback.

One limitation of this study is that the author does not focus on the difference between the effects of textual and graphical information on customers’ decisions and trust in buying merchandise. Another limitation is that this study focuses on Kuwait and the UAE. Other Gulf Cooperation Council countries are also growing exponentially, and mobile and internet penetration rates are booming; they could be a trigger for more studies on whether differences occur among all of them.

The first implication is that it is the first in its field to extend the effects of eWoM. To the best of the author’s knowledge, compared to the online research this study is unique because the authors examine six factors for eWoM in s-commerce using the Instagram platform as opposed to other platforms.

The third implication of this study is that the previous ones have applied eWoM to different subjects of e-commerce such as tourism and marketing but have concentrated less on s-commerce, where in-depth research is needed much more to explore factors and theories that explain human behavior.

Furthermore, most of these studies have focused on the intention to use (Dincer and Dincer, 2023; X. Hu, Chen, Davison, and Liu, 2022; Zhou et al., 2023). However, the attention in this research is on the actual use.

This research article aims to systematically explore the association between digitalisation and individual investors’ behavioural biases. Through an extensive exploration of digitalisation modes and their various serviceable avenues in the investment arena, the study aims to elucidate the impact of behavioural biases on individual investors’ investment decision-making processes.

The study employs Interpretative Phenomenological Analysis (IPA) to gain insights into behavioural finance and the associated behavioural biases of investors in digitalisation. IPA, a qualitative method grounded in heuristic, phenomenological, and idiographic elements, facilitates the exploration of individual investor experiences and the role of digitalisation and behavioural biases within.

Investors are categorised into two groups – decision seekers and decision makers – based on their digital inclination and the purpose behind using digital tools. The attributes of these segments are detailed under the sub-themes of Digital Inclination, Market Cognizance, Sophistication and Maturity, Sophomorism and Perception of Digitalisation. The study also identifies the specific behavioural biases pertinent to each segment. Additionally, it introduces a novel section on the insights related to human emotions, behaviour and sentiment within financial markets.

The essence of the current article is the application of the IPA method to the field of behavioural finance. To the best of the authors’ knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive understanding of both, digitalisation and behavioural biases that affect the individual investor’s decision-making. It offers valuable insights for researchers, academicians and scholars in behavioural finance, enhancing the understanding of how behavioural biases influence investment decisions.