Wade D. Cook

The current research makes three main contributions to the DEA (Data Envelopment Analysis) literature. First, when using DEA to derive an efficiency score for a given DMU, it is normally assumed that each and every DMU has its own unique set of inputs and outputs, there are situations whereby a DMU can have a factor that is shared with other DMUs. This means that one must view efficiency from the perspective of groups of DMUs rather than from the perspective of the individual DMU. Second, two stage problems can, in the presence of shared factors, result in different groupings of DMUs in one stage than in another. Third, in certain circumstances efficiency can be viewed from the perspective of multiple attributes (e.g. different types of tourism). Herein, we develop a model to cater for these features and illustrate the model using a data set on tourism in Mexico.

Using panel data from 2010 to 2016, this study investigates how well banking institutions perform in investing in digital technologies and utilizing their resources in the digital age. A conventional data envelopment (DEA) analysis model is first applied, followed by a Malmquist index analysis. Results suggest that bank holding companies (BHCs) have failed to benefit from technological progress due to inefficient resource management. As such, we propose a novel resource-allocation model to address the issues, particularly allowing non-homogeneous BHCs to be compared with their true peers and highlighting practical insights into the allocation and reallocation of shared resources. Aggregate efficiency scores are measured and then regressed against selected explanatory variables. The empirical findings indicate that BHCs should strengthen their innovation capabilities and improve their diversification levels to gain better performance in utilizing resources. The results also offer novel managerial implications for collaboration with financial technology (FinTech) firms. Specifically, the explanatory variable, partnership, is shown to have a moderating effect on the relationship between the size and aggregate efficiency of BHCs. Larger BHCs could benefit from collaborating with FinTech, while smaller BHCs appear to be better off acting alone.