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This study aims to advance knowledge of channel integration, a key feature of omnichannel retailing, by investigating the role of specific touchpoints in delivering a consistent integration perception.

Quantitative methods were adopted, by testing a model built on the stimulus-organism-response framework. Data collection used a panel survey across the grocery and fashion sectors (1,031 and 739 consumers, respectively). An ordinary least squares regression with clustered standard errors was conducted, combined with a multiple correspondence analysis, followed by a mediation analysis.

This study identifies touchpoints relevant for channel integration perception and shows that they differ across product category and customer types (first time vs repeat customers). Furthermore, it pinpoints touchpoints that are directly and indirectly related to patronage intention, thereby exposing the mediating role of channel integration. By drawing on categorization theory, it discusses individual touchpoints’ contribution to channel integration perception, at general level and on different customer targets.

This study offers a new vision of channel integration perception that highlights touchpoints’ role. It contributes to the established channel integration quality framework by showing that integrated information is concerned not only with consistency of information across channels but also with the specific touchpoints through which such information is disseminated.

This study provides directly actionable managerial implications, by through strategic insights for customer journey and customer experience design/redesign and by offering a practical methodology for retailers to identify the touchpoints they can leverage to improve their customers’ channel integration perceptions – with consequences for patronage intention.

This study comprehensively reviews the Fourth Industrial Revolution, which refers to Industry 4.0 (IR 4.0) applications in small and medium enterprises (SMEs). Multinational companies and big corporations have the capacity and resources to implement IR 4.0, but SMEs are limited due to financial constraints, expertise and lack of resources. Even so, IR 4.0 is required as technologies evolve and market demand has changed how firms do business.

To uncover the potential of IR 4.0 and critical determinants of SMEs’ adoption of IR 4.0, this study presents a bibliometric analysis to evaluate the current research streams in IR 4.0 adoption among SMEs through bibliographic coupling. Furthermore, this review provides a glimpse of the future by analyzing prospective trends on IR 4.0 in SMEs.

Bibliographic coupling produces five clusters: (1) challenges and barriers in IR 4.0 implementation among SMEs, (2) technological adoption of IR 4.0, (3) opportunities and benefits of IR 4.0, (4) business model innovation and (5) implication of IR 4.0 on SMEs technologies. On the contrary, co-word analysis produces three clusters: (1) technologies in IR 4.0, (2) strategy and management of IR 4.0 among SMEs and (3) IR 4.0 model for SMEs.

Implications are directly related to business owners, policymakers and technology developers meeting the needs of the industry and SMEs, which are the focus of this review.

The findings contribute significantly to the body of knowledge by presenting a state-of-the-art science mapping approach to uncover the knowledge structure and intellectual linkage of IR 4.0 adoption within SMEs.

This study aims to analyze the entrepreneurial intention (EI) of Colombian researchers using machine learning (ML) techniques, considering their academic activity, contexts and social norms (SN).

Unsupervised classification techniques were applied, including principal component analysis, hierarchical clustering with the Ward method and a logistic model to evaluate the classification. This was done to group researchers according to their characteristics and EI.

The methodology used allowed the identification of three groups of academics with distinct characteristics, of which two showed a high presence of EI. The results indicate that EI is influenced by the connection with the private sector (consulting, intellectual property and applied research) and by the lack of institutional support from universities. Regarding SN, only the preference for entrepreneurial activity over being an employee and the social appreciation of entrepreneurial dedication were identified as predictors of EI.

The use of ML techniques to study the EI of researchers is uncommon. This study highlights the ability of the methodology used to identify differences between two groups of academics with similar characteristics but different levels of EI. One group was identified that, despite rejecting values associated with entrepreneurs, has a high predisposition to develop a career as an entrepreneur. This provides valuable information for designing policies that promote EI among Colombian researchers.