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In cloud computing, banking knowledge with business intelligence (BI) will be a better option for the users, and the users do not have an overall picture of the whole thing until the entire job is completed.

Although the constraints are costly, complex, inflexible and integrated BI infrastructures, it helps to combine the banking and electronic commerce (EC) application data. Furthermore, this paper explores cloud computing infrastructure as a potential remedy for data processing issues.

A modern cloud computing with artificial intelligence, environmental climate to shorten periods for BI delivery, rising the expense of BI programs relatively with traditional BI of EC applications, provide customers with the ability for quicker rollout and better flexibility to incorporate research and to improve the performance, accuracy and efficiency.

In the technological world of today, the new era of BI analytical data management has been established with certain restrictions on the adoption of BI.

The purpose of this paper is to provide an insight to the outsourcing decision-making through investigating if the old evaluation/selection criteria and methods still fit with current business priorities or not and, therefore, to identify the appropriate criteria and methods to develop a new selection framework. Since the economic recession of 2008, logistics outsourcing decisions have become more prominent to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages.

This is a focused literature review prepared after analyzing 56 articles related to the logistics service provider (LSP) evaluation and selection methods and criteria during 2008-2013. The academic articles are analyzed based on research focus/area, evaluation and selection methodology/methods and evaluation and selection criteria. Then reviewed result is compared with previous literature studies for the periods (1991-2008) to identify any possible shifts.

The review reveals that: several problems in current LSPs literature have been identified; the reviewed papers can be categorized into seven groups, the usage and importance of evaluation and selection criteria fluctuate during different periods; 12 crucial criteria have been identified, increasing the importance of specific selection methods and the integrated models and fuzzy logic in logistics literature. Then, a comprehensive LSPs’ evaluation and selection framework has been developed.

To the best of our knowledge, this is the first focused logistics outsourcing study that reviews the 2008-2013 period in detail, comparing results with previous literature studies, identifies current LSPs literature problems/gaps, new trends and shifts in the way that LSPs are evaluated and selected, identifies crucial selection criteria and proposes a new holistic LSPs evaluation and selection framework. In addition, it identifies important issues for future research.