School Papers

1) faced by the OLI framework as it

1)     LLL Model

 

The linkage, leverage, learning (LLL) model was
originated due to the critics faced by the OLI framework as it advocates the
asset exploration motive that is seen as a springboard perspective (Matthews, 2002). Matthew (2006) developed this
model to provide pivotal understanding to the accelerated internationalization
decisions of EMNEs through resource-based analysis.

 

The first aspect is linkage, which understands
how companies decide to leverage into new markets. EMNEs are viewed as
latecomers hence linkage is a mechanism that provides them with apt and readily
access to internally lacked assets such as advanced technology or brand
reputation through collaborative partnership with foreign firms (Luo and Tung, 2007). Prevalence
of risk due to uncertainty in the market is reduced often through partnership thus
it is a popular strategic decision that is utilized by Chinese EMNEs (Morck, Yeung and Zhao, 2008). The second feature,
leverage, concentrates on the exploitation of linkage by channeling resources
and cost advantages together by overcoming impediments and barriers in order to
remain internationally competitive (Matthews, 2002). Lastly,
learning is a stage established when EMNEs acquire competitive advantages and
dynamic capabilities through linkage and leverage strategies and attain
knowledge on how to compete on international level (Matthews, 2006).

 

 

He and Fallon (2013) illustrate the application
of LLL model analysis on Tata Motors whereby through the acquisition of Jaguar
Land Rover, the company was able to enhance its brand reputation and
technological skills. Furthermore, they were able to leverage their knowledge
to evolve into global players (He and Fallon, 2013).

 

Therefore, the LLL model is able to furnish
strategic intents of EMNEs as well as providing account for the rapid rise of
EMNEs (Matthews, 2006). Hence, the theory reckoned that
any EMNEs, which lack strategic resources, have the possibility to internationalized
in an accelerated manner through integration of the LLL model (Matthews, 2002).