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The purpose of this study is to examine how social media affects luxury brand equity and purchase intention in Malaysia.

Questionnaires were distributed across shopping malls in the Klang Valley, including Kuala Lumpur and surrounding areas, targeting Malaysian citizens aged 18 and above with a history of luxury purchases. Using random sampling, the study collected and analysed 300 valid responses.

The findings demonstrate that social media has a positive effect on luxury brand equity and that brand equity significantly influences purchase intention. However, the study reveals a negative impact of social media on purchase intention.

This study explores the profound impact of social media on luxury brand equity in Malaysia, revealing its role in shaping brand awareness, associations, uniqueness, loyalty and perceived quality.

The motivation to choose an electric vehicle (EV) is guided by principles of personal values, perceived rewards and preferences. While the benefits of sustainable transportation are known, the acceptance of EVs and the motivation to purchase them is not satisfactory in India. An assessment of the motivation continuum, a range of intrinsic to extrinsic personal and societal drives that encourage specific choices, explains the lack of EV adoption in the country. This study aims to examine the effect of motivation types on EV adoption intentions and also explores the moderating role of gender in this context.

By incorporating constructs from the self-determination theory, the study expands on the technological acceptance model. It uses the structural equation modelling method to test the hypotheses and presents an analysis of responses from 351 participants.

The findings suggest that there are significant relationships between external, identified, integrated motivation and EV buying intentions. The influence of gender on EV adoption is also explored.

This study provides an in-depth analysis of varied motivational types on EV buying intentions and the moderating effects of gender on these relationships.

This study aims to investigate factors that influence individuals’ continuance intention to use massive open online courses (MOOCs) by using machine learning models.

Data was collected from 702 MOOC users from major metropolitan cities in India through a network-based sampling and recruitment via various social media outlets (e.g. LinkedIn and Facebook). Various machine learning algorithms along with explainable artificial intelligence (XAI) were employed using Python PyCaret.

Results confirm that pedagogy value, content value, interface value, ubiquity value, teacher presence and learning satisfaction have positive effects on the continuous intention of MOOCs. Furthermore, pedagogy value is a chief driving force of CI of MOOCs. XAI helps clarify intricate patterns in learner data, thus allowing more appropriate interventions.

The findings of the study would be useful for MOOC developers to formulate better value propositions for ensuring a sustainable business and higher growth rate in the market.

This study bridges the gap in the existing literature by providing a novel approach. To the best of the authors’ knowledge, this is the first study using machine learning and XAI earlier in identifying factors leading to continuous intentions of MOOCs, so this research adds value to the existing method of exploring factors enhancing retention rates among learners.

Tech start-ups (TSs) functioning in different domains have a responsibility of ensuring that domestic knowledge and capabilities are leveraged to minimize dependence on foreign organizations. Despite the growth of the ecosystem, while numerous TSs emerge, very few of them are able to survive, and of those that survive, very few scale up. The aim of this study is to identify the factors influencing the competitiveness of technological start-ups and to study the interrelationship and interdependence of these factors.

Modified total interpretative structural modeling (m-TISM) was employed for the current research. The analysis of what factors have an effect on competitiveness, how they affect it and why they affect it should be explored. The study begins by developing the list of factors through literature search, and further it is validated by expert opinion. A hierarchical model has been developed using m-TISM and MICMAC analysis to analyze the driving and dependency power of factors at each level.

Results show that the competitiveness of TSs is affected by organizational agility and internationalization. Factors present at the bottom level, namely entrepreneurial intensity, act as a strong driver for TSs. Team member commitment, transformational leadership, strategic alliances, knowledge sharing and organizational ambidexterity are middle-level factors.

This study is among the few articles that have explored competitiveness of TSs in the Indian context.