PRINCIPALES RUBROS CONTABLES AFECTADOS POR LA INFLACION

The manufacturer trust is simplified as a probability of loyalty that the manufacturer agents would choose the same supplier agent as selected previously.

The trust value is determined at five levels (or scenarios) of probability: 0%, 25%, 50%, 75%, and 100%. These values are selected to represent these following degrees of manufacturer trust: extremely disloyal (extremely distrustful - 0%), disloyal (distrustful - 25%), moderately loyal (moderately trustful - 50%), loyal (trustful - 75%), and extremely loyal (extremely trustful - 100 %). These scales are chosen empirically to observe the effect of different levels of manufacturer trust on the model outputs. The variation of the variables for the scenarios is summarised in Table 6.5.

The expected outcome of this experiment is defined based on the duration of collaboration applied, with respect to short-term collaboration (4-time unit partnership) and long-term collaboration (80-time unit partnership). In short-term collaboration, it is expected that a higher manufacturer trust does not enhance the demand fulfilment rate when the firm prefers to have a short-term collaboration. In contrast, a higher manufacturer trust is expected to improve the performance of a single supply chain when the firm prefers to collaborate in long duration.

Nevertheless, with regards to the gap of the existing work, these expectations

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should turn to be opposite at market-level when all firms apply a similar trust strategy. The simulation results are provided in the next sections.

Table 6.5 The scenarios for the manufacturer trust

Probability of the

manufacturer trust Scale representation Scenario T_M-1 0% Extremely disloyal/distrustful

Scenario T_M-2 25% Disloyal/distrustful

Scenario TM-3 50% Moderately loyal/trustful

Scenario TM-4 75% Loyal/trustful

Scenario T_M-5 100% Extremely loyal/trustful

In short-term collaboration

Figure 6.17 shows the boxplots of the supply chain fill rate of manufacturer trust that is simulated under short-term collaboration (4-time unit partnership). As shown in the figure, both median and mean of supply chain fill rate have a slight U pattern as the probability of the manufacturer trust increases. Furthermore, the boxplots indicate that the 100% manufacturer trust (scenario 5) generates the highest supply chain fill rate and number of supply chains in the market, and the 0% manufacturer trust (scenario TM -1) provides the second highest outputs. Meanwhile, scenario TM

-2 (-25%), scenario TM-(50%), and scenario TM-4 (75%) provide no significant difference effect, particularly on the supply chain fill rate.

The inferential analysis of the results also concludes that scenario TM-5 (100%) is significantly different from other scenarios. It provides the highest value of supply chain fill rate (Appendix J, Table J.9). Scenario TM-1 (0%) also has a significant difference from the others, but it is not different significantly with scenario TM -2 (25%). It has higher supply chain fill rate comparing to scenario TM -3 (50%) and TM-4 (75%), but it is lower than scenario TM-5. Scenario TM-2 (25%) is significantly different from scenario TM-4 and scenario TM-5, but it is insignificant with scenario TM-1 and scenario TM-3. It provides higher supply chain fill rate than scenario 4, but it is lower than scenario TM-5. Scenario TM-3 (50%) is

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only significantly different from scenario TM-1 and scenario TM-5. It has lower supply chain fill rate than scenario TM-1 and scenario TM-5. Lastly, the supply chain fill rate in scenario TM-4 (75%) is significantly lower comparing to scenario TM-1, scenario TM-2, and scenario TM-5.

Figure 6.17 Boxplots of the supply chain fill rate with a line of mean values for all scenarios of the manufacturer trust

Meanwhile, the median and the mean of the number of supply chains in the market also depict a slight U shape, as shown in Figure 6.18. Both the median and the mean of the output decrease from 3 supply chains to 2 supply chains, from scenario TM-1 to scenario TM-2 (the manufacturer trust is 25%). The values do not change until the manufacturer trust is 75% in scenario TM-4. In the last scenario, both values increase to 4 supply chains.

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0 5 10 15 20 25 30

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Supply!chain! fill!rate!(%)

Scenario T_M

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Figure 6.18 Boxplots of the number of supply chains in the market with a line of mean values for all scenarios of the manufacturer trust with short-term collaboration

The Mann-Whitney U test concludes that scenario 5 (100%) provides a significantly higher number of supply chains in the market compared to other scenarios, particularly when it is contrasted to scenario TM-2, scenario TM-3, and scenario TM-4 (Appendix J, Table J.10). It is considered to be not different significantly when it is compared to scenario TM-1. Scenario TM-1 (0%) is only significantly different from scenario TM-3. It generates number of supply chains in the market than scenario TM-3. Finally, an insignificant difference between scenarios is concluded for the remaining comparisons.

In long-term collaboration

The data characteristics of the supply chain fill rate for this experiment is presented in Figure 6.19. In the long-term collaboration, which is set to 80 time units, the pattern of the mean and the median of supply chain fill rate for all scenarios of the manufacturer trust are no longer similar to a U-shaped. In this situation, the 0%

manufacturer trust (scenario TM-1) results in the lowest supply chain fill rate, with a mean of 9.75% and median of 7.6%. Meanwhile, scenario TM-5 is consistent resulting in the highest outcome; its mean is 14.52%, and the median is 14.6%. The

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Mann-Whitney U test also concludes that only scenario TM-5 is significantly different from other scenarios (Appendix J, Table J.11). It has a significantly higher supply chain fill rate, while the remaining scenarios are concluded to be not different significantly with each other.

Figure 6.19 Boxplots of the supply chain fill rate with a line of mean values for all scenarios of the manufacturer trust with long-term collaboration

As for the supply chain fill rate, the number of supply chains in the market of this experiment also shows an almost similar pattern. The highest output is obtained in scenario TM-5, where the mean and median are 4.1 supply chains and 4 supply chains respectively. The lowest mean and median are generated by scenario TM-1 and scenario TM-4; both scenarios have a mean of 2.66 supply chains and median of 2 supply chains. However, the analysis resulted from the Mann-Whitney U test concludes that only scenario TM-5 is significantly different from other scenarios (Appendix J, Table J.12). It significantly provides the highest number of supply chains in the market compared to other scenarios. The boxplots of this output is presented in Figure 6.20.

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0 5 10 15 20 25 30

1 2 3 4 5

Supply!chain! fill!rate!(%)

Scenario T_M

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Figure 6.20 Boxplots of the number of supply chains in the market with a line of mean values for all scenarios of the manufacturer trust with long-term collaboration

Output comparison of the manufacturer trust between short-term and long-term collaboration

Figure 6.21 presents the comparison of the manufacturer trust in different levels of duration of collaboration, with respect to short-term and long-term partnership.

Overall, the extremely loyal manufacturers (scenario TM-5 - the 100% trust) provide the highest supply chain fill rate. Surprisingly, the extremely disloyal manufacturers (scenario TM-1 - the 0% trust) results in the second highest supply chain fill rate in short-term. However, when the long-term collaboration is applied, scenario TM-1 provides the lowest supply chain fill rate, while scenario TM-5 still results in the highest outcome for this measure.

The intermediate levels of manufacturer trust (the 25%, 50%, and 75% trust) are not significantly different from the other scenarios, in terms of supply chain fill rate in short-term. Only when the manufacturers are disloyal (scenario TM-2 - the 25% loyalty) in long-term collaboration can result in a better supply chain fill rate than the zero manufacturer trust. However, this result is insignificant when it is assessed by using the Mann-Whitney U test.

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Figure 6.21 The comparison of supply chain fill rate between short-term collaboration and long-term collaboration, with different levels of duration of collaboration

Meanwhile, the comparison of the number of supply chains in the market in different levels of duration of collaboration is illustrated in Figure 6.22. As can be seen from the figure, the extreme manufacturer trust (scenario TM-5) consistently results in the highest number of supply chain in the market, while the extremely disloyal manufacturers (scenario TM-1) provides the second highest output for this measure. However, the value decreases when the long-term collaboration is applied. As for the supply chain fill rate, the intermediate levels of manufacturer trust do not provide a different number of supply chains in the market compared to extreme scenarios (scenario 1 and 5). Only the scenario of disloyal manufacturers (scenario TM-2 - the 25% loyalty) in long-term collaboration has a higher median than scenario TM-1, scenario TM-3, and scenario TM-4. However, this pattern is not significant when it is assessed by the Mann-Whitney U test.

Based on these output comparisons, it can be suggested that the manufacturer trust can only leverage the supply chains performance and survivability as a market when it is applied to the extreme high level of trust. The in-between levels of manufacturer trust do not seem to be beneficial to the supply chain over the long-term, particularly when they are compared to the situation where all manufacturers have no trust towards the supplier. Thus, the hypothesis of this experimental factor is supported by the simulation results, which is:

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Supply&chain&fill&rate&(%)

Scenario T_M

Short/term1collaborations Long/term1collaborations