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This study investigated the relationships among big data analytics capability (BDAC), low-cost advantage, differentiation advantage, market and operational performance underpinning the resource-based view (RBV) and the entanglement view of sociomaterialism (EVS) theories.

A total of 191 responses from members of the Federation of Malaysian Manufacturers were analysed using a structural equation modelling approach.

This study has conclusively demonstrated that BDAC is indeed a resource bundle comprising human skills, tangible and intangible resources. This study found that BDAC positively influences competitive advantage and firm performance. The differentiation advantage was found to be a key factor in explaining market performance. Theoretically, both RBV and EVS could be used to link BDAC, differentiation advantage and market performance to explain superior firm performance.

First, the sample is restricted to the manufacturers in Malaysia. Second, a single independent variable, BDAC, is used as a higher-order capability to influence competitive advantage, and thus, superior firm performance. Third, this study uses a self-reported survey, which means that only one respondent from each firm answered the questions. Fourth, this study excludes the focused strategy as it aims to investigate the competitive strategy used in the broader industry environment, rather than in a specific segment pursuing a focused strategy.

First, BDAC is a valuable, rare, inimitable and non-substitutable tool for manufacturers to enhance their firm performance. Second, BDAC is crucial for manufacturing firms to reduce costs and differentiate themselves. Third, a low-cost advantage may not help manufacturers achieve greater market and operational performance.

The relationship among BDAC, low-cost advantage, differentiation advantage, market and operational performance within manufacturing industry is empirically tested.

The purpose of this paper is to assess the efficiency, effectiveness and performance of logistics companies in Singapore and Malaysia which are the growing logistics hubs in Asia by using a triangular data envelopment analysis (DEA). It also identifies various factors that significantly affect the efficiency, effectiveness and performance of the Singaporean and Malaysian logistics companies and proposes ways to improve their competitiveness.

First, this study employs a triangular DEA to evaluate the efficiency and effectiveness of the companies. Second, Tobit regression is used to explore the factors that affect logistics performance. Third, the managerial decision-making matrix is addressed and suggestions made to help logistics managers improve performance.

The results reveal that small firms, on average have more potential than the large ones. The results also demonstrate that investment influences firm performance significantly.

This paper is the first attempt to apply a triangular DEA-based approach by decomposing performance into efficiency and effectiveness for logistics companies in Singapore and Malaysia.