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Regular version of the site

Article

Resource-based model for small innovative enterprises

Management Decision. 2020. Vol. 58. No. 8. P. 1525-1541.
Maiti M., Krakovich V., Shams R., Vukovic D.

Purpose – The paper introduces a resource-based linear programming model for resource optimization in
small innovative enterprises (SIE).
Design/methodology/approach – The model is grounded on resource-based view on the firm and dynamic
capabilities approach. Linear programming technique is used to provide the actual framework to the resourcebased
model.
Findings – The paper introduces a new resource-based linear programming model for resource
optimization in small innovative enterprises. The conceptual model is grounded on resource-based view
(RBV) and dynamic capabilities strategy. The RVB of firm and firm strategy is based on the concept of
economic rent. Linear programming technique is used to provide the actual framework to the resourcebased
model. In developing the versatility concept, study suggests a distinct sight regarding resource
fungibility. Study classifies resources into multipliable, rentable and expendable resources to increases
adequacy of the model. The developed model includes both tangible and intangible assets such as human
capital. The survival rate of SIE in the early stages of life cycle is very low due to the competition among
SIEs. In this regard, the greatest advancement of the developed resource-based linear programming model
is its simplicity and versatility which is much desirable for the SIE especially in their initial stages of the
life cycle. Kelliher and Reinl (2009) argued that micro firms have unique advantage over bigger firms in
following term: rate of learning or redeployment of strategy in micro firms is faster than the rate of change
in their environment. One very significant feature of the developed resource-based linear programming
model is that mathematically the proposed model could easily be transformed into mixed integer or
stochastic linear programming models to meet the time variant requirement of small firms especially when
it expands its operation.
Research limitations/implications – The survival rate of SIE in the early stages of life cycle is very low due
to the competition among SIEs. In this regard, the greatest advancement of the developed resource-based linear
programming model is its simplicity and versatility which is much desirable for the SIE especially in their
initial stages of the life cycle. Kelliher and Reinl (2009) argued that micro firms have unique advantage over
bigger firms in following term: rate of learning or redeployment of strategy in micro firms is faster than the rate
of change in their environment. One very significant feature of the developed resource-based linear
programming model is that mathematically the proposed model could easily be transformed into mixed integeror stochastic linear programming models to meet the time variant requirement of small firms especially when it
expands its operation.
Originality/value – One very significant contribution of the present study is that the study develops a new
resource-based model for SIE especially for the SIE in the initial stages of the life cycle, to gain competitive
advantages. Furthermore, the present study contributes to the existing literature in strategy at least in three
senses as mentioned below: 1. further addition of SIE research based on the RBV and dynamic capabilities in
the strategy literature 2. in developing the versatility concept, the study suggests a distinct sight regarding
resource fungibility and it classifies resources into three categories as follows: multipliable, rentable and
expendable resources to increases adequacy of the model. 3. Finally, the study introduces a new resource-based
linear programming model for SIE resources allocation. To the best of author’s knowledge, no such similar
model is introduced by any previous studies for small firm. The greatest advancement of the developed
resource-based linear programming model is its simplicity and versatility.