Intended learning outcomes: Disclose a model for systematic reduction of possible locations / partners. Produce an overview on steps in location selection and evaluation of a concrete case, namely a joint venture partner in China. Present in detail factors for location selection used in this case. Explain the results of factor rating and the sensitivity analysis in this case.
This is primarily concerned with the location selection of a production network. Instead of listing all possible criteria for location selection, in the next section below we will discuss a specific case, namely, the evaluation of a joint venture in China by a European company that constructs plants.
It is best to conceive of location selection as a project, with the associated tasks of project initiation, project management, and project realization. Figure 3.2.1.1 shows the steps in the concrete case mentioned above. Noticeable in this specific case is the long time period for location selection. Almost two years were required for the evaluation.
In practice, there are many location factors critical to success, and each factor has criteria. For a comprehensive view, a complete set of factors with individual criteria is required. Evaluating the degree to which the criteria are fulfilled is then dependent on the strategy chosen in the specific case. Figure 3.2.1.2 shows the location factors examined in this case.
In addition to four factors that relate to the actual location, three factors are shown that relate to the contemplated joint venture partner. The individual criteria in these three factors can implicitly also characterize — although not only — the location of the partner.
To proceed effectively and also efficiently, whereas as many locations as possible are considered, they are reduced as rapidly as possible to a few candidates through examination of an appropriate sequence of location factors. One model for this is shown in Figure 3.2.1.3.
Fig. 3.2.1.1 Steps in location selection and evaluation of a joint venture partner in China.
Fig. 3.2.1.2 Factors for location selection.
This funnel was based on an idea in [AbNu08]. The location factors are considered in an order that allows systematic reduction of locations. The final step in Figure 3.2.1.3 is discussed in the following. The figures show the criteria for each location factor that a European plant manufacturer rated in the concrete case of evaluating joint venture partners in China. The criteria were rated in the order shown in Figure 3.2.1.2. Each criterion was rated. Of course, the range of values for the factors chosen here are just examples; in other cases, a different range of values might be used.
Fig. 3.2.1.3 Systematic reduction of possible locations / partners.
Figure 3.2.1.4 shows the criteria of the factor “political and economic business environment.”
Fig. 3.2.1.4 Evaluation of a JV candidate in China: Criteria of the location factor “political and economic business environment.”
As a further criterion for the location factor “political and economic business environment,” political stability (unrest, corruption, and strikes) could be evaluated, for example.
Figure 3.2.1.5 shows the criteria of the location factor “cultural and infrastructure aspects.”
Fig. 3.2.1.5 Evaluation of a JV candidate in China: Criteria of the location factor “cultural and infrastructure aspects.”
Other criteria under “cultural and infrastructure aspects” could also be work ethic, availability and skills of workers, and the telecommunications infrastructure or water availability.
Figure 3.2.1.6 shows the criteria of the location factor “regional customer structure.”
Fig. 3.2.1.6 Evaluation of a JV candidate in China: Criteria of the location factor “regional customer structure.”
Further criteria under “regional customer structure” can be the proportion of customers in the region that already are being supplied by the home base, the market power of customers, purchasing power of customers, customer and buying behavior, and the specific product and delivery time requirements of the customers.
Figure 3.2.1.7 shows the criteria of the factor “medium-term attractiveness of the market.”
Fig. 3.2.1.7 Evaluation of a JV candidate in China: Criteria of the location factor “medium-term attractiveness of the market.”
Further criteria under “medium-term attractiveness of the market” can also be examined: the expected market position, the origins of the competitors (possibly from home), the market segments, the company’s own potential for exporting products (transport, customs duties, and so on), and possible substitution products by competitors.
Figure 3.2.1.8 shows the criteria of the location factor “internal company evaluation of a joint venture candidate.”
Fig. 3.2.1.8 Evaluation of a JV candidate in China: Criteria of the location factor “internal company evaluation of a JV candidate.”
Figure 3.2.1.9 shows the criteria of the factor “general positioning as joint venture candidate.”
Fig. 3.2.1.9 Evaluation of a JV candidate in China: Criteria of the location factor “general positioning as joint venture candidate.”
Further criteria of the location factor “general positioning as joint venture candidate” that can be rated are: regional presence (production / distribution / sales / service), innovation behavior, and strategic orientation.
Figure 3.2.1.10 shows the criteria of the location factor “performance program of the potential joint venture partner.”
Fig. 3.2.1.10 Evaluation of a JV candidate in China: Criteria of the location factor “performance program of the potential joint venture partner.”
Further criteria that can be examined under the location “performance program of the potential joint venture partner” are also the specific process know-how in individual areas of sales and distribution, R&D, production, and installation.
To evaluate alternative locations, a cost-benefit analysis is often performed. A simple, rather qualitative tool for this is factor rating, for example.
Factor rating [DaHe05, p. 382], is a decision method for evaluating several possible solutions to a problem that can be characterized using factors or features.
Figure 3.2.1.11 shows the results of a rough-cut factor rating in the form of a graphical summary of the criteria that were applied in the concrete case.
The overall rating can be determined qualitatively using the graphical representation in Figure 3.2.1.11 as an aid. First, starting from the rating of the individual criteria in Figures 3.2.1.4 to 3.2.1.10, simple graphical averaging, or interpolation, allows the determining of the positions in Figure 3.2.1.11. As the great majority of the values for location 2 are higher than the values for location 1 — also in both cases where better evaluations resulted for location 1, but were only insignificantly better than location 2 — the decision will be made that location 2 is the better location; in the case at hand, that was indeed the company’s decision.
Fig. 3.2.1.11 Results of factor rating.
Generally, however, it is necessary in the last step to quantify the ratings and to assign weights to both the individual criteria within a location factor and the location factors in relation to one another (reflecting their relative importance to the company) to be able to compare the alternative locations. Instead of estimating the ratings qualitatively (from minus to plus to double-plus), we can determine the degree to which a criterion is fulfilled, expressed, for example, as a percentage of maximum fulfillment of the criterion. Suppose
- n is the number of locations,
- mi is the number of criteria per location i, 1 i n,
- Fi,j is the degree of fulfillment of the criterion (i,j) of location factor i, 1 j mi, 1 i n,
- Wi,j is the weight assigned to the criterion (i,j), 1 j mi, 1 i n,
- Wi is the weight assigned to the location factor i, 1 i
Figure 3.2.1.12 shows the formula for calculating the overall benefit B for each location and thus the ranking of the locations. For greater certainty in ranking the alternative locations, in addition to determining the overall benefit, a sensitivity analysis is also necessary.
Fig. 3.2.1.12 Factor rating with degrees of fulfillment and weightings.
A sensitivity analysis determines how much an expected outcome or result will change in response to a variation of the input variables.
For an identification of locations that are close in the overall score, it is important to vary both the degree of fulfillment and the weightings.
The quantification of ratings can also be set by considering costs and investments associated with the locations. This can, for example, concern the criteria under the location factor “internal company evaluation” (see Figure 3.2.1.8). In this case, to discount the benefits and costs over time, commonly used methods of investment analysis can be applied, such as the net present value technique, NPV (see Figure 19.2.5.3).
Likewise, for location selection for both distribution and service networks, location factors with catalogues of criteria are used.
- For distribution or service processes in direct contact with the customer or the object, the main factors are criteria such as access routes (pedestrians, cars, public transportation), population density, size of families, and annual family income. See the discussion in relation to Figure 3.1.3.2.
- For distribution or service processes in indirect contact with the customer or the object, there are often additional factors, such as the availability of lower-cost temporary personnel that can be flexibly (time) employed. As an example, airlines locate call centers in Cape Town or Dublin, due to the plentiful supply of well-trained, multilingual exchange students present in these places who can provide a low priced, qualified workforce for these part-time jobs.
- For distribution or service processes with no customer or object contact, in contrast, the location factors and criteria are in principle the same as those described above for production networks.
Assessment of the various options for the location selection can be carried out using qualitative methods such as those above for production networks. Sometimes quantitative methods are also used, such as linear programming.
Course section 3.2: Subsections and their intended learning outcomes
3.2 Location Selection and Location Configuration
Intended learning outcomes: Differentiate between location selection and location configuration. Explain location selection using qualitative methods and factor rating. Describe location selection and location configuration with linear programming.
3.2.1 Location Selection Using Qualitative Methods and Factor Rating
Intended learning outcomes: Disclose a model for systematic reduction of possible locations / partners. Produce an overview on steps in location selection and evaluation of a concrete case, namely a joint venture partner in China. Present in detail factors for location selection used in this case. Explain the results of factor rating and the sensitivity analysis in this case.
3.2.2 Location Selection and Location Configuration with Linear Programming
Intended learning outcomes: Produce an overview on linear programming (LP). For the design option of “in part decentralized production for the global market”, explain the use of mixed-integer linear programming (MILP).
