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This study aims to investigate the moderating effects of brick-and-mortar (BM) store characteristics and customer satisfaction on the relationship between ship-to-store (STS) retailing and BM store performance in an emerging economy. The purpose is to explore how BM store characteristics and customer satisfaction influence online buying behaviour when customers visit the stores to pick up their products.

This study collected secondary longitudinal data from 615 BM stores from one of Brazil's largest retailers and performed a panel-data regression analysis using the following moderating variables: customer satisfaction with BM stores, BM store's size, convenience and inventory transparency.

Customer satisfaction with BM stores moderates the effect of STS transactions on the revenue per store. Results also show that BM store's convenience, size and inventory transparency moderate STS online customers' impact on BM store cross-sales.

The STS strategy can increase online and BM store performance. Some BM store characteristics and customer satisfaction influence online customers to buy more products when they visit BM stores to pick up their products, providing a more complex model for the relationship between STS strategy and BM store performance.

Companies in emerging economies can use the BM store more strategically in combination with the STS strategy to increase overall retailer performance. By managing some BM store characteristics, managers can improve retail sales.

This study demonstrates how new moderating factors expand the understanding of the relationship between online and physical retailing in emerging economies. Also, the panel data regression results control for extraneous variables and provide more robust evidence of the relationships observed.

The purpose of this paper is to explore last mile delivery (LMD) to the bottom of the pyramid in Brazilian slums, its challenges and how practitioners overcome them. Urban logistics in precarious circumstances is central to the conceptualization.

A qualitative, grounded theory methodology is developed, gathering data from companies delivering to slums in Sao Paulo and Rio de Janeiro, Brazil. Field notes, documents and interviews led to conceptual categories for LMD to slums.

The study indicates that while some standard urban logistics practices can be effective for LMD to slums, such unusual contexts often call for unusual solutions. A model is developed using grounded theory categorization, resulting in five dimensions for LMD to slums: employing locally, giving back, acknowledging criminals, vehicle and location.

The model is a qualitative proposition representing LMD to slums in two major Brazilian cities. Even though slums in different cities/countries may face similar conditions, additional studies are needed to confirm and replicate the model.

Companies that successfully engage in LMD to slums must adapt and develop idiosyncratic practices.

LMD to slums enables a larger portion of bottom of the pyramid consumers to access a wider range of products and work opportunities, contributing to their social inclusion.

The study provides an understanding of LMD in a new context. The model encourages companies to question their current practices, learning from effective LMD experiences implemented by successful practitioners.

This study aims to identify the relationship between different maintenance practices and productive efficiency in continuous process productive plants as well as the moderating effect of good training practices.

The empirical data were drawn from a database containing 609 observations of 29 productive units. Scales were validated using the Q-sort method. The panel data technique was used as the analysis methodology, with the inclusion of fixed effects for each productive plant.

Maintenance practices can effectively contribute to increasing the overall equipment effectiveness (OEE) of firms. Application of predictive maintenance practices should be considered as the primary training tool.

This study used a secondary database, limiting the research design and data manipulation.

The article provides practitioners with an analysis of maintenance practices by category (predictive, preventive and corrective), and the impact of each practice on the OEE of continuous process productive plants. Moreover, it explores the importance of training for extracting more results from maintenance practices.

Companies are investing in new technologies, but it is also essential to invest in training people. There is a demand for Industry 4.0 through the introduction of upskilling and reskilling programs.

This study used practice-based view (PBV) theory to explain how maintenance practices help firms achieve greater OEE. Furthermore, it introduced training practice as a moderating variable in the relationship between maintenance practices and OEE.