THE INFORMATION GAP PROBLEM AND THE SYNTHETIC MEASURE IN THE DECISION-MAKING PROCESS OF THE ORGANIZATION
The development of the global information society means that information is treated as an economic good, a basic resource and a basic economic category. The subject of the article is internal diversification and assessment of the commune's competitiveness in the aspect of regional differentiation of the financial situation on the example of synthetic evaluation of the Świętokrzyskie voivodeship communes. Synthetic measures based on a non-standard method and distance in real space with the Euclidean metric were used to achieve this goal. The value of the measure ranged from 0.28 (Tarłów, the weakest unit) to 0.69 (Ożarów, the best unit) in 2010 and from 0.35 (Imielno, the weakest) to 0.70 (Połaniec; the best) in 2015 for the non-standard method. In the case of a measure based on the distance in real space with the Euclidean Meter from 0.35 (Ożarów, best) to 0.77 (Dwikozy, the weakest) in 2010 and from 0.36 (Połaniec; best) to 0.70 (Imielno the weakest) in 2015.
The assessment of the competitiveness of local government units and information needs should take into account social and economic characteristics shaping the potential of the region. Internaldifferentiation in the context of the competitiveness of municipalitiesis a naturalphenomenon.
However, it should be remembered that these disproportions must reach a level that is acceptable in a given economic and social situation.
The method used in the article allows for the comparison of the competitiveness of one unit with the other. The value of the measure depends on the number and type of adopted variables to be tested. It can be used by the local government authorities of the region to assess the effectiveness of past development instruments or financial management. It allows to prioritize objects and assess the disproportions between individual cities of the Świętokrzyskie Province.
In the case of low spatial aggregations, we encounter data deficits most often caused by the lack of representativeness of the data resulting from insufficient sample research or simply the lack of research in this field. Therefore, inference should always be cautious and final assessments supported by additional research.