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The present study aims to construct ensemble machine learning (EML) algorithms for groundwater potentiality mapping (GPM) in the Teesta River basin of Bangladesh, including random forest (RF) and random subspace (RSS).

The RF and RSS models have been implemented for integrating 14 selected groundwater condition parametres with groundwater inventories for generating GPMs. The GPM were then validated using the empirical and bionormal receiver operating characteristics (ROC) curve.

The very high (831–1200 km²) and high groundwater potential areas (521–680 km²) were predicted using EML algorithms. The RSS (AUC-0.892) model outperformed RF model based on ROC's area under curve (AUC).

Two new EML models have been constructed for GPM. These findings will aid in proposing sustainable water resource management plans.

This study aims to examine the mediating effect of four antecedents of competitive advantage on the linkage of risky strategy to firm performance, measured by revenue dynamics. It considers the roots of competitive advantage to highlight different patterns and foundations of achieving superior performance. It investigates whether pursuing a risky strategy fosters revenue dynamics growth and whether different mediators are included in that relationship.

Path analysis (structural equation modeling) method is used to analyze data from 122 companies of various sizes and industries. All respondents were responsible for executing strategic management processes. The paper used the subjective perspective, which is based on the individual opinion of senior company managers and owners.

The authors find a positive relationship between risky strategy and firm performance, but no evidence of a mediating role of competitive advantage and dynamic growth in this relationship. Competitive advantage should be perceived as a set of integrated factors that can be analyzed from an aggregated perspective. Integrating all antecedents requires a holistic and systematic approach and the development of a particular mindset. Aggregated competitive advantage is related to setting dynamic growth as a priority. However, no relationship between risky strategy and achieving competitive advantage, or between implementing a risky strategy and setting dynamic growth as a priority, is observed, which was assumed to explain the revenue dynamics growth.

Secondary data should be analyzed to explore how risky strategies are manifested, and which managerial decisions are reflected in high-level risk. A multidimensional scale could be developed to check how risk shapes the constructs’ interdependence. Therefore, the dynamic capabilities approach could be further expanded.

This research offers insights into the short-term relationship between risky strategy and revenue dynamics, although competitive advantage does not mediate that relationship. Special attention should be paid to the selected antecedents of competitive advantage, as they influence dynamic growth.

This work provides insights into different antecedents of competitive advantage, which is not necessarily based on making risky decisions, and into factors that facilitate firm performance measured by revenue dynamics.

The transition to omnichannel retail is the recognized future of retail, which uses digital technologies (e.g. augmented reality shopping assistants) to enhance the customer shopping experience. However, retailers struggle with the implementation of such technologies in brick-and-mortar stores. Against this background, the present study investigates the impact of a smartphone-based augmented reality shopping assistant application, which uses personalized recommendations and explainable artificial intelligence features on customer shopping experiences.

The authors follow a design science research approach to develop a shopping assistant application artifact, evaluated by means of an online experiment (n = 252), providing both qualitative and quantitative data.

Results indicate a positive impact of the augmented reality shopping assistant application on customers' perception of brick-and-mortar shopping experiences. Based on the empirical insights this study also identifies possible improvements of the artifact.

This study's assessment is limited to an online evaluation approach. Therefore, future studies should test actual usage of the technology in brick-and-mortar stores. Contrary to the suggestions of established theories (i.e. technology acceptance model, uses and gratification theory), this study shows that an increase of shopping experience does not always convert into an increase in the intention to purchase or to visit a brick-and-mortar store. Additionally, this study provides novel design principles and ideas for crafting augmented reality shopping assistant applications that can be used by future researchers to create advanced versions of such applications.

This paper demonstrates that a shopping assistant artifact provides a good opportunity to enhance users' shopping experience on their path-to-purchase, as it can support customers by providing rich information (e.g. explainable recommendations) for decision-making along the customer shopping journey.

This paper shows that smartphone-based augmented reality shopping assistant applications have the potential to increase the competitive power of brick-and-mortar retailers.