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This article deals with the evolution of customer service practices in grocery products distribution in Brazil (1994‐2001), based on a longitudinal survey of grocery retailers. Data were collected on retailers’ expectations on four relevant dimensions of customer logistics service provided by manufacturers, as well as on their perceptions of logistics service performance of the typical supplier and the best supplier. The evolution of the gaps between retailers’ expectations and manufacturers’ perceived distribution performance was investigated, as well as a trend in terms of an increase or decrease in customer satisfaction with service provided by suppliers in such dimensions. Results indicate that retailers typically tend to be satisfied with the service provided by their suppliers. In addition, there may be an adjustment of distribution performance to expectations of retailers and to the provision, in some cases, of service above customer expectations.

The article's objective is to analyze the consequent factors of Big Data Analytics Capability for firms in the competitive scenario, using different analytical models.

The research had a quantitative approach, using a survey of data from firms located in the state of São Paulo – Brazil. Structural Equation Modeling (SEM) was used to validate the model.

The results reveal that all hypotheses were accepted. Business value was the construct that had the most explanatory power in the model. It is necessary to invest more in analytical tools, as well as people trained in the analysis of these models, in addition to a change of mindset, which will dictate the bias of the firm's strategic decision-making. The Big Data analysis is evident from firms' growing investments, particularly those that operate in complex and fast-paced environments.

The proposed theoretical model makes it possible to verify firms' analytical structure and whether they are better positioned to analyze customer data and information in real-time, generate insights and implement solutions to maintain and improve their market position.

The contribution of this article is to present a proposal to expand the research models in the literature that analyzed the direct and indirect relationship between “Big Data Analytics Capability” and “Product Innovation Performance”.

The purpose of this paper is to provide a comprehensive and unified presentation of recent developments in skid-steer wheeled mobile robots (SSWMR) with regard to its control, guidance and navigation for the researchers who wish to study in this field.

Most of the contemporary unmanned ground robot’s locomotion is based upon the wheels. For wheeled mobile robots (WMRs), one of the prominent and widely used driving schemes is skid steering. Because of mechanical simplicity and high maneuverability particularly in outdoor applications, SSWMR has an advantage over its counterparts. Different prospects of SSWMR have been discussed including its design, application, locomotion, control, navigation and guidance. The challenges pertaining to SSWMR have been pointed out in detail, which will seek the attention of the readers, who are interested to explore this area.

Relying on the recent literature on SSWMR, research gaps are identified that should be analyzed for the development of autonomous skid-steer wheeled robots.

An attempt to present a comprehensive review of recent advancements in the field of WMRs and providing references to the most intriguing studies.