Peren-Clement Index
The Peren-Clement-Index , named after Franz Wilhelm Peren and Reiner Clement, is a risk index for assessing country risks in direct investments . It is one of two established indices for country risk analysis.
The risk index is determined by the following three factors, which are weighted differently:
- Cross-company factors
- Cost and production-oriented factors and
- Sales-oriented factors.
Cross-company factors include:
- Political and social stability
- State influence on company decisions and bureaucratic obstacles,
- General economic policy ,
- Investment incentives,
- Enforceability of contractual agreements and
- Compliance with property rights in technology and know-how transfer.
The cost and production-oriented factors include:
- Legal restrictions on production,
- Capital costs in the country of location and possibilities of capital import ,
- Availability and costs of purchasing land and real estate,
- Availability and cost of work,
- Availability and costs of capital goods, raw materials, consumables and supplies in the country of location,
- Trade barriers in importing goods and
- Availability and quality of infrastructure and government services.
The sales-oriented factors include:
- Size and dynamics of the market,
- Competitive situation ,
- Reliability, quality of local contract partners,
- Quality and opportunities of sales and
- Trade barriers when exporting from the host country.
Depending on the type of investment or motives of the respective company, there are other location factors or different weightings of the various factors. For the cost-oriented foreign investment , the factors of the cost and production -oriented factors are given greater weight and the choice of location will be decided accordingly. On the other hand, factors such as the competitive situation and the size of the market will become more important for sales-oriented investments.
method
First of all, the selected factors are individually weighted, which can be between 1.5 and 3 depending on the importance of the individual factors. See the following example:
| Cross-company factors | Points | weighting | Result |
|---|---|---|---|
| * Political and social stability | ....... | 2 | ....... |
| * State influence on company decisions and bureaucratic obstacles | ....... | 2 | ....... |
| * General economic policy | ....... | 2 | ....... |
| * Investment incentives | ....... | 1.5 | ....... |
| * Enforceability of contractual agreements | ....... | 3 | ....... |
| * Compliance with property rights in technology and know-how transfer | ....... | 2.5 | ....... |
| Cost, production-oriented factors | Points | weighting | Result |
|---|---|---|---|
| * Legal restrictions on production | ....... | 2.5 | ....... |
| * Capital costs in the country of location and possibilities of capital import | ....... | 2 | ....... |
| * Availability and cost of purchasing land and real estate | ....... | 1.5 | ....... |
| * Availability and cost of work | ....... | 3 | ....... |
| * Availability and costs of capital goods, raw materials, consumables and supplies in the country of location | ....... | 2 | ....... |
| * Trade barriers for importing goods | ....... | 2 | ....... |
| * Availability and quality of infrastructure and government services | ....... | 2 | ....... |
| Sales-oriented factors | Points | weighting | Result |
|---|---|---|---|
| * Size and dynamics of the market | ....... | 3 | ....... |
| * Competitive situation | ....... | 2.5 | ....... |
| * Reliability, quality of local contract partners | ....... | 2 | ....... |
| * Quality and opportunities of sales | ....... | 2 | ....... |
| * Trade barriers when exporting from the host country | ....... | 2.5 | ....... |
In a further step, points are awarded for the analyzed country for each individual factor. The range extends from 0 (extremely unfavorable) to 3 (extremely favorable). These are then entered in the table above and multiplied by the weighting specified in each case. This then results in a total number of points achieved for the respective country. How the total score can be interpreted is explained in the following section.
By multiplying the maximum number of points 3 by the weighting of the individual factors selected in each case, a maximum number of points that can be achieved results. The above example results in a maximum total number of points of 120 points. In a further step, the foreign risk is then classified. This can look like this:
| Gradation of country risks (with a maximum of 120 points): |
|---|
| Over 90 points = no discernible risk |
| 80 - 89 points = low risk |
| 70 - 79 points = moderate risk and obstacles in daily operation, risk protection recommended |
| 60 - 69 points = relatively high risk, poor investment climate, risk protection essential |
| below 60 points = location is not recommended for direct investments |
The total number of points achieved for the respective country can now be classified in the model described above. In this way, the respective country risks can be divided into classes and a risk assessment can be given.
The use of critical variables, the so-called knock-out variables, is extremely useful. If certain key factors are previously defined as knock-out variables and a country receives a score below 2 in them, direct investment must be rejected. This also applies in the event that all other factors have received positive values and the total number of points shows a good result and thus makes the location appear positive.
Individual evidence
- ↑ S. Beer: China Sourcing. Shopping in the Middle Country. Hamburg 2012, p. 56.
- ↑ A. Schneider, R. Schmidpeter: Corporate Social Responsibility: Responsible corporate management in theory and practice. 2nd Edition. Berlin / Heidelberg 2015, p. 1095.
- ↑ G. Apfelthaler: Market segmentation in the international area. In: W. Pepels: Market segmentation - methods for successful market segment processing. 3. Edition. Düsseldorf 2013, p. 272.
literature
- Christina Pakusch, Franz W. Peren, Markus Arian Shakoor: The PCI - A Global Risk Index for the Simultaneous Assessment of Macro and Company Individual Investment Risks. In: Journal of Business Strategies. Vol. 33, No. 2, 2017, pp. 154-173.
- Christina Pakusch, Franz W. Peren, Markus Arian Shakoor: Peren-Clement-Index - An exemplary case study. In: A. Gadatsch et al. (Ed.): Sustainable business in the digital age. A guide for innovative leaders. Springer Gabler, Wiesbaden 2017, pp. 105–118.
- Reiner Clement, Franz W. Peren: Global location analysis. In: Harvard Business Manager. 6/1998, pp. 70-77.
- Reiner Clement, Franz W. Peren: Peren-Clement-Index. Assessment of direct investments through a simultaneous recording of macro level and company level. Springer Gabler, Wiesbaden 2017, ISBN 978-3-658-17022-6 .
- Rolf-Dieter Reineke, Friedrich Bock (Hrsg.): Gabler Lexikon Unternehmensberatung. Wiesbaden 2007, ISBN 978-3-409-12008-1 , pp. 248-249.
- C. Wankel: Encyclopedia of Business in Today's World. 2009, p. 137.
- K. Roebuck: Risk Management Standards. 2011, ISBN 978-1-74304-826-9 , pp. 472-475.
- EC Hiram (Ed.): Peren-Clement Index. Plac Publishing, 2012, ISBN 978-613-8-82565-4 .
- Franz W. Peren: Assessment Tool to Measure and Evaluate the Risk Potential of Gambling Products: ASTERIG. In: The Journal of Gambling Business and Economics. Vol. 5, No. 2, 2011, pp. 54-66.
- Springer Fachmedien Wiesbaden (Ed.): 333 Keywords market research: basic knowledge for managers. 2013, ISBN 978-3-658-03540-2 , p. 137.
- Springer Fachmedien Wiesbaden (Ed.): Compact Lexicon Marketing Practice: Look up, understand, use 2,200 terms. 2014, ISBN 978-3-658-03184-8 .
- Franz W. Peren, Reiner Clement: Peren-Clement Index - PCI 2.0: Evaluation of Foreign Direct Investments through Simultaneous Assessment at the Macro and Corporate Levels. Passau: MUR-Verlag, 2019. ISBN 978-3-945939-19-2
Web links
- Peren-Clement-Index , Gabler Lexicon
- Country risk