Home > Free Essays > Business > Employees Management > Global Aerospace Logistics Company: Training Evaluation

Global Aerospace Logistics Company: Training Evaluation Research Paper

Exclusively available on IvyPanda Available only on IvyPanda
Updated: Nov 4th, 2020

Executive Summary

Training is an essential component of the organization’s efficiency. When arranged in a timely and effective manner, it maintains an appropriate level of proficiency, enhances employee satisfaction, and, ultimately, increases competitive advantage of the organization. However, the process is expensive and resource-demanding. Therefore, it is necessary to establish its effectiveness and, if possible determine its benefit to cost ratio.

The following report provides evidence of the contribution of the training program at Global Aerospace Logistics, LLC (GAL) on job performance of its technicians, offers recommendations on the benefit to cost ratio of the program, and outlines the bottom line benefits provided by the program for organization’s competitiveness. The data for the research is collected through self-administered surveys and interviews. Both qualitative and quantitative analyses are used to obtain reliable results and gain in-depth understanding of the matter.

The findings suggest the overall positive effect of the program, both from the employees’ and managers’ perspective and suggest several approaches to calculating benefit to cost ratio. In addition, several barriers are identified to the effective use of obtained skills as well as the assessment of financial data, with the recommendation regarding their mitigation.


Employee training is a crucial component of a successful organization. Professional knowledge plays an important role in the ability of the staff to perform effectively and according to their workplace responsibilities. At the organizational level, this can be viewed as an important source of competitive advantage in the market. However, despite significant emphasis on obtaining the qualified workforce, maintaining a desired level of proficiency is a challenging task in the highly dynamic organizational environment. The pace of the technological advancements that permeate the modern corporate domain makes the described task a practical impossibility and require the introduction of a mechanism that would allow for timely updates of the state of employee knowledge. Thus, training becomes an absolute necessity for the organizations that aim at retaining their leading positions in the market.

Due to the fact that the process of training was determined to have a profound effect on the performance of the organization, it became clear that a certain level of control is necessary to estimate the performance and ensure the consistency of the results. However, upon closer inspection, it became clear that the process of training evaluation requires a specific, well-defined approach in order to produce valid findings. Thus, several methods of training assessment have been put forward by the scholars and adopted by the organizations.


The evaluation of the efficiency of employee training is important for several reasons. First, the process of training requires significant resource and time allocation. At this point, it is important to emphasize that the expenses created by such allocation are not to be perceived as losses – in fact, it would be more appropriate to view them as an investment in the organization’s performance. However, in order to estimate the viability of such investment, it is important to assess the outcomes of the training process and model the probable changes in organizational performance resulting from them. In other words, the evaluation process provides the organization’s management with the understanding of the effects of a training program.

By extension, it is possible to expect that the results of the evaluation can be incorporated in the strategic planning process since they offer an insight into the possible changes in performance. Second, the assessment allows for a more comprehensive understanding of the effects of a training program, namely the individual perception of its effects on participants. Specifically, the assessment may reveal the increase in self-esteem, motivation, and engagement of employees.

In some instances, these perceived benefits will have a significant effect on the productivity and efficiency of the organization as a whole. Third, the training assessment process is an important component of the evaluation of a workplace culture in the company. A consistent quality improvement is essential for achieving the desired level of performance and sustaining the competitive advantage without the constant inflow of resources. Thus, it should be viewed as an encompassing aspect of quality control tool that offers a range of opportunities at the macro level.

Purpose of the Study

The current study aims at providing a better understanding of the impact of employee training on the performance of the organization. Specifically, it intends to establish the relationship between the training delivered to the workers and a respective change in their professional performance. Next, the study is expected to outline the benefits of employee training and development expressed in several specific measurements, such as employee satisfaction level, employee retention, product quality, and the efficiency of the organization. Finally, it is expected that certain insights are gained regarding the calculation of the benefit to cost ratio of the conducted training. Overall, the results of the study are expected to provide useful data that can be utilized in the strategic planning process.

Literature Review

The issue of employee training assessment is a persistent issue in the industry. Despite the fact that it has been recognized as an important component in the evaluation of the organizational performance, the concept is still lacking in operational definitions and does not have an established and agreed upon framework that could be used universally. According to Brauchle and Schmidt (2004), the productivity of a training exercise is often measured by administering a questionnaire or conducting a series of interviews intended to provide the desired information.

In some cases, the consistency between the needs of the organization and the topics covered by the program are considered a sufficient confirmation of the program’s success (Brauchle & Schmidt 2004). Such an approach s clearly oversimplified and probably overlooks numerous aspects that need to be taken into account. The most relevant aspect that is not covered in such a process is the monetary value of the training expressed in the benefits derived from the improved proficiency of the workers.

The monetary component has two advantages. First, unlike the perceived value that is commonly used as a basis for assessment in the majority of questionnaires, the monetary value is universal and can be converted into a unified measure, such as a U.S. dollar. This allows for comparison of the achieved results with the outcomes reported in the academic literature. Second, the concept of financial gain associated with the increase of an intangible characteristic is attractive to managers and the administration of the organization and allows for an effective communication of the goals and benefits of the process (Brauchle & Schmidt 2004). It should be pointed out that in many instances, the inclusion of the metric is associated with significantly increased complexity.

Fletcher and Wind (2013) incorporate an example of simulation in medical training which requires the evaluation of several groups of equipment depending on a form of training: human actors for live simulation, virtual patients presented via software means, full-body manikins enhanced with electronic sensors, and simulations of specific body parts. As can be seen, the diversity of elements results in the increased complexity of the assessment.

At this point, it is important to understand that different aspects of organizational performance can be prioritized in accordance with their relative significance within the organization. For instance, Williams and Nafukho (2015) consider technical domain a more viable area for evaluation within the organization than any other functional area, mostly due to the high probability of error and the magnitude of consequences resulting from their occurrence.

The study also suggests that the majority of the organizations tend to perform the level 4 evaluation, which is considered of high degree of validity, but that only a fraction of companies utilizes the highest level of evaluation, likely due to technical difficulties and restrictions associated with its implementation (Williams & Nafukho 2015). In other words, while in the majority of instances the evaluation is performed with a sufficient degree of integrity, the complexity of evaluation poses a significant drawback for the stakeholders and thus undermines the overall quality of findings.

Arguably the most successful attempt at creating a consistent and accessible framework is the Kirkpatrick’s model. The model utilizes four levels of evaluation – reaction, learning, job performance, and organizational impact (Reio et al. 2017). The levels are positioned in a specific order that is determined by the scope of their influence on the organization. Consequently, each next level is more representative of the value of a training program under evaluation for the company.

However, it is also important to note that the complexity of the inquiry increases exponentially with each level and requires greater allocation of time and resources, which may discourage some companies from performing a complete examination. Nevertheless, according to the consensus, the increasing value of data from each stage mitigates the expenses associated with the process (Reio et al. 2017). Despite the success and widespread adoption, several weak points have been identified in the Kirkpatrick’s model, and respective adjustments have been proposed by the scholars in the field (Reio et al. 2017).

The most common criticism deals with the model’s focus on the outcome of the training process, with no account for the preceding factors. Several models were introduced in an attempt to address this drawback, including the context, input, process, and product (CIPP) model, the input, process, output (IPO) model, and context, input, reaction, and outcome (CIRO) model (Reio et al. 2017). All of the models above incorporate elements that occur during the training process and have a measureable effect on its result.

Finally, some experts suggest frameworks that prioritize certain elements intended to enhance the effectiveness of the evaluation process while at the same time diversify the potential areas of the evaluation’s implementation. Grohmann and Kauffeld (2013) emphasize the importance of psychometric parameters in the evaluation process and suggest a framework intended to comply with the psychometric standards. According to the authors, such an approach will provide more accurate results due to the reliance on psychometrically sound properties while at the same time increase the applicability of the assessment to different organizational setting (Grohmann & Kauffeld 2013).

It should be pointed out that such applicability would also provide the opportunity of comparing the results obtained in different training contexts, similar to the outcomes measured in monetary units. Barnett and Mattox (2010) stress the importance of a comprehensive plan for the assessment of training program’s efficiency and outline five essential components that need to be included in the plan in order to produce a conclusive and accurate result.

The components in question are resources, measurement models, strategy, cultural readiness, and measures (Barnett & Mattox 2010). According to the authors, the inclusion of these components will ensure the necessary degree of applicability of the assessment to both the large- and small-scale entities while at the same time decreasing the complexity of the evaluation process for the encompassing corporate environments (Barnett & Mattox 2010). Finally, such an approach is expected to be beneficial for the assessment of web-based and other technology-mediated programs.

As can be seen from the literature review, the majority of the sources display agreement on the importance of the employee training assessment. Another common theme is the apparent complexity of the programs, which poses a serious challenge for the companies that implement them. Finally, it is apparent that despite the popularity of some of the training programs, neither has been universally adopted. In fact, the complexity of assessment, especially at the organizational level, constitutes the most noticeable barrier to their adoption and prompts the managers to bypass them, focusing instead on the most simply measured, albeit the least representative, aspects of assessment.

Methodology Design

Research Questions

The available information about Global Aerospace Logistics highlights several needs that should be addressed by the research. These needs highlight the areas that need to be reflected in the research questions in order to be conclusively answered. In the broad terms, the inquiry focuses on the outcomes of training conducted within the company and aimed at determining its viability for the retention of a competitive advantage. The outcomes should be disaggregated by the area of influence and should thus include items such as job performance, product quality, employee retention, employee satisfaction, and benefit to cost ratio. Based on these considerations, the following research questions were suggested.

  • RQ1: How the training received by the technicians contributed to their job performance?
  • RQ2: How can the Maintenance Training Department calculate Benefit to Cost ratio for conducted training?
  • RQ3: What are the bottom line benefits that employee training and development provides to the organization and its competitiveness?

At this point, it is necessary to specify that the third question involves a range of distinct variables that need to be addressed with a high degree of specificity in order to provide findings. The most significant variables include employee satisfaction levels, employee retention, product quality in terms of reworks and scraps, and overall efficiency of the organization.

Research Design

The research at hand utilizes a case study method. The decision was prompted by several important advantages pertinent to the method. First, the identified research design is based on a close examination of a single case or phenomenon in order to reach the conclusions. This aspect was particularly suitable for the case at hand since the scope of the study was limited to a specific company and its performance within a well-defined period.

It is also worth noting that the research questions identified in the previous section require a relatively diverse set of results, some of which can only be obtained via an in-depth inquiry into the matter, characteristic for case study design. Another notable reason is a geographic localization of the case, which is confined to the Al Bateen Airport. At this point, it should be mentioned that other approaches are equally applicable to the outlined setting, such as experimental or longitudinal designs.

Nevertheless, the idiographic approach chosen by the researcher contributes to the suitability of the identified method. It is also notable that the case involves a highly specific set of criteria, including a well-defined group of participants and location, which contributes to the ease of implementation of the chosen design.

Several alternative options were considered at the stage of methodology design. The most suitable approach aside from a case study, evaluation research, was considered viable due to its compatibility with the goals of the research, particularly the ability to determine whether the needs of the organization were met as a result of the intervention. However, it was eventually rejected as it required an in-depth inquiry into the initial situation to collect baseline data and, by extension, an extended time of research, which was unacceptable under the given conditions. Next, the experimental design was considered unsuitable, mainly due to the requirements posed by the approach.

Specifically, an experiment typically involves a set of sampling practices such as randomization and the introduction of a control group. These conditions could not be fulfilled to a satisfactory degree due to the preoccupation of the stakeholders at the Al Bateen Airport with their routine operations. For this reason, experimental design is a rare occurrence in the field of organizational behavior and management research. The cross-sectional design was rejected due to the necessity of including more than one group in the study, which was outside the scope of the study. It should also be mentioned that while the method in question provides relatively reliable results and requires less time to perform, it does not illustrate the sequence of events.

In simple terms, while it would outline the job performance following the intervention, the possibility of establishing a definitive causal relationship between the training and the observed outcome would be severely limited. Next, the longitudinal design was considered inappropriate since it typically requires at least two sets of data collected from the same sample within a sufficiently large time frame between them.

While such approach could provide the necessary data as well as establish the required causal relationship, it could not be performed within a timeframe of the research at hand. Finally, the comparative design would require more than one sample to arrive at a definitive conclusion. Considering the fact that the study focused on a single organization and no comparable sample could be identified, this method was rejected.

Operational Definitions

The formulated research questions contained several variables that had to be specified as operational definitions in order to increase the reliability of the findings. The most apparent variable is the concept of employee training, which can be defined as an educational or skill enhancement intervention provided to the staff by the management with the goal of addressing a specified gap in performance or increasing the overall proficiency.

The Benefit to Cost ratio required for one of the research questions is a metric that enhances the understanding of value of a selected intervention by identifying the expenses associated with the process and comparing them to the benefits derived from it. Next, the definitions of several dependent variables should be included. Specifically, employee satisfaction is a measurement of the perceived satisfaction with a condition or a set of conditions that is typically used as a component in workplace culture assessment process. Next, employee retention is a concept that describes the determination of the organization’s staff to remain employed by the company.

Retention is typically considered closely related to the employee satisfaction. Product quality is a set of characteristics pertinent to the product offered by the company that determines its suitability to the target audience. Quality is often considered one of the main determinants of the observed demand and, by extension, a source of competitive advantage, for which reason the control mechanisms are usually incorporated into the production process. Finally, the efficiency of the organization is determined by a combination of factors that collectively contribute to its capacity to perform under optimal conditions. The set of factors is determined individually for each organization.

Data Collection

Data Collection Approach

The data for the study was obtained directly from the involved stakeholders. The research incorporated both qualitative and quantitative data in order to address the research questions consistently. The quantitative approach produced measureable, quantifiable, and reliable data, which enhanced the applicability and utility of the results. Since the majority of data reflected the intangible concepts and values, it was converted into a numerical form using established data collection tools such as Likert scale.

Such approach allowed the research team to achieve the necessary level of compatibility of the data with the findings in the related areas, produce more universal results, and compare the outcomes with the findings of similar studies available in the academic literature. The quantitative method also provided the researchers with the possibility to express the findings in an unambiguous manner and with a high degree of accuracy.

In the case of Global Aerospace Logistics case, where several measurements were planned to be conducted, such approach was especially relevant as it allowed for the comparison between several datapoints once such necessity presented itself. In addition, several elements of the assessment process, such as benefit to cost ratio, employee retention, and product quality, could be more reliably established using quantifiable values. Thus, the quantitative approach was prioritized in the course of the analysis.

The qualitative approach, on the other hand, provided an in-depth insight into the issue under inspection. This approach was especially relevant for the GAL case since it provided an opportunity to reveal important details that could not be established via survey with close-ended questions. Another reason for the selection was the relatively low sample necessary for the data collection process. It should be mentioned that the process of interpreting the data obtained through interviews (the tool chosen for the qualitative analysis) typically requires significant time and effort. However, this disadvantage was partially mitigated by a relatively small expected sample size (approximately 5 respondents), which allowed for the inclusion of qualitative analysis in the study despite the restrictive time frame.


Due to the scope of the inquiry, the sample for the study included all technicians that participated in the training exercise. In other words, the entire involved population could be considered compliant with the inclusion criteria (in the case of GAL – the participation in the training exercise) and included in the sample. In other words, non-probability sampling was used for the study at hand. Since the research team has gathered the information only form the individuals that were known to be a part of the studied population, the technique in question was purposive sampling. The selected approach had two important advantages.

First, the population in question was relatively limited and thus did not allow for a meaningful randomization without decreasing the size of the sample below a reasonable threshold. Second, the focus on details and depth of the obtained information encouraged the inclusion of the entirety of the available information in order to reach the necessary coverage. Finally, it is worth mentioning that the exclusion of randomization allowed for additional optimization of the process by speeding up the collection process.

Reliability and Validity

Several practices were incorporated into the data collection process to make the outcomes more reliable. First, the data obtained by individual researchers was reviewed for consistency in order to determine the level of agreement between the researchers, thus establishing the inter-rater reliability. Second, the inter-item correlation was established in order to determine internal consistency. Finally, the stability of the statements obtained from the respondents was ensured by collecting data at different points in time and examining the datapoints for inconsistencies and deviations.

Both the survey and the interview were reviewed by the research team members. The identified potential drawbacks were discussed, and solutions for their minimization were incorporated. The benchmark tests were performed prior to the launch of the data collection process. In this way, face validity and concurrent validity of the data was established. The researchers also familiarized themselves with the findings of the similar studies in the field of quality management in order to establish construct validity of the data.


The data collection process resulted in two datasets. The first set was based on the results of a close-ended survey that utilized Likert scale and was analyzed using the quantitative approach. The second set contained the findings of an interview and was coded in accordance with the qualitative methods used in case studies.

Quantitative Data

In order to perform a quantitative analysis of the results of the survey, it is first necessary to establish the nature of data represented by the responses. In the case of GAL, the questions were focused on the positive effects of the training sessions. The effects ranged from workplace productivity to the favorability of the environment to different aspects of employee satisfaction, such as tangible and intangible rewards. In all cases, the response “strongly agree,” situated as a first option, was considered the most favorable response and confirmed the positive impact of the training, whereas “strongly disagree” (situated in the end of the list) was associated with unfavorable outcome, either for the company or for the employees.

Based on this assertion, it is possible to incorporate at least two descriptors, mean and mode. The latter is the most straightforward in terms of calculations since it can be performed by relying on raw data or through the examination of bar charts generated from the responses. For example, the majority of responses to question one (9) agree with the notion that the knowledge received during training was applicable to their work. This suggests that the second option is the mode in this case. As can be seen in appendix 1, this response is the mode in the overwhelming majority of cases (16 out of 20), followed by the first and third option, each being the mode in one case. It is also worth noting that in two instances (question 10 and 15) two options receive an equal number of responses (first and second and second and third, respectively).

The mean would require an interpretation of response options into a quantifiable format. Considering the favorability criterion explained above, it would be reasonable to assign the values of 5 to 1 to the options from “strongly agree” to “strongly disagree.” With this assertion on hand, it becomes possible to calculate the mean of each set of responses, with a higher resulting number representing greater favorability of training session outcomes.

For example, the mean for question one will be calculated as follows: (8 * 5) + (9 * 4) + (1 * 3) + (2 * 2) + (0* 1) / 20 = 4.15. In this case, the value of 4.15 indicates that the number of negative responses is negligible since the average response is above the second most favorable result (agree), represented by the value of 4. As can be seen from appendix 2, the mean for the majority of answers is between 3 and 4, with the lowest score of 3 for question 16 and the highest score of 4.3 for questions 3, 5, 10, and 11. It is also important to establish standard deviation in order to determine the spread of the results from the mean. As can be seen from appendix 3, standard deviation ranges from 0.57 (q5) to 0.99 (q9).

Considering that for the purpose of the study the difference between options is 1, it is reasonable to assert that the numbers in each response are close to the mean of the dataset. However, it is necessary to acknowledge that in the survey at hand, the Likert scale provides ordinal data, which does not allow to conclusively establish the distance between the consequent responses. In other words, from the strictly scientific point of view, there is no definitive way of establishing that the difference between “strongly agree” and “agree” equals the distance between “agree” and “neither agree nor disagree.” Thus, the numerical values can be considered close approximations and, by extension, both mean and mode are presented to corroborate the data obtained from median and interquartile range.

The median can be obtained by arranging the responses in a descending or ascending order and determining the number in the middle (or, in the case of the dataset at hand, two numbers). As can be seen, the overwhelming majority of the responses indicate “agree” (the second favorable answer) as a median. The two exceptions are questions 15 and 16, both of which indicate “neither agree nor disagree” as a median. The responses to question 9 place both “agree” and “neither agree nor disagree” as a median.

The interquartile range can be calculated using the values assigned to the responses in the process of calculating the mean. For the second response, both the first and the third quartile would be represented by the value of 4 (indicative of the “agree” response). Thus the interquartile range will be 4 – 4 = 0, indicating the greatest possible consensus. As can be seen in appendix 4, the consensus is generally high throughout the survey, with only two sets of responses (questions 9 and 16) displaying minor disagreement.

Qualitative Data

The qualitative data available to the researchers was in the form of the responses to the personal interviews. The interviews were conducted with the managers who were expected to possess relevant knowledge regarding the outcomes of training and sufficient understanding of benefit to cost analysis. Three responses were available to the research team. The analysis was based on a case study approach. Prior to processing the responses, a number of preset codes were formed that were expected to cover the topics identified in the research questions.

The codes for the first research question centered on the identification of the improvement in job performance associated with training. No codes corresponding to specific areas of improvement were formed at this stage. The codes related to the second research question focused on the reported possibility of calculating benefit to cost ratio and included a reference to the Kirkpatrick model, which was identified in the literature review as relatively common and thus was expected to be used or suggested as an option. Due to the sample’s area of proficiency, only one aspect of the third research question was expected to be covered in the interviews – that of the overall efficiency of the organization. Thus, it was included as a preset code.

The examination of the data revealed that two of the three responses to the first question were consistent with the codes confirming a positive impact of training on technicians’ job performance. Both responses to question 2 demonstrated the same result, describing training as “worthwhile” and “valuable” and referring to its risk mitigating effect as “vital.” All three responses to question 5 confirmed the possibility to calculate benefit to cost ratio. However, only one response referred to the Kirkpatrick model.

The analysis also determined the need for the introduction of additional codes. Specifically, it was discovered that question 3 dealt solely with the existing and proposed methods of training evaluation, which was not related directly to any of the research questions. However, it can be indirectly linked to research question 3 by identifying the existing barriers to the facilitation of benefits received from training. In a similar manner, the responses to question 4 identify the obstacles that hinder the benefits of training and are thus indirectly related to RQ1 and, partially, R3.

In order to address these issues, a set of emergent codes was introduced. The emergent codes specified the benefits according to the reported outcomes, introduced the factor of evaluation practices, outlined the common obstacles, and focused on the perceived barriers to benefit to cost ratio evaluation. The use of these codes provided the following results. The positive effects of training received by technicians included the improved speed, confidence, and reliability of their performance and increased their capacity for responsible decision making.

The main barriers to the facilitation of these benefits included the transfer of the staff to the areas where the acquired knowledge and skills could not be applied and the restrictions imposed by the need for supervision. The benefit to cost ratio can be calculated by determining the direct and indirect costs of the training program and comparing it to the benefits obtained from training. The Kirkpatrick model can be used for this purpose. The most apparent expected challenge to such approach is the inability to obtain financial data from the responses of the participants, and the greatest current barrier is the lack of robust formal means of evaluation of training outcomes, as shown by the responses to interview questions 5 and 3, respectively.

Conclusions and/or Recommendations

As can be seen from the analysis above, the first and second research questions were answered primarily through interview responses whereas the third one was covered in detail by the results of a self-administered survey. The results suggest that the training received by the technicians contribute to multiple aspects of their job performance, including faster completion of tasks, increased confidence, improved responsibility and reliability, greater autonomy in a decision-making process, and optimized time allocation.

However, the identified results are reported to vary greatly depending on the individual characteristics of the workers, with employee motivation being the most significant factor determining the success of the program. The most apparent barriers to the implementation of the knowledge obtained during the training are the deployment of the technicians to the locations where the knowledge becomes irrelevant and the inability to perform certain tasks due to the lack of supervision. In other words, the increase in job performance is both apparent and positive but is hindered by the lack of coordination at the organizational level.

The majority of respondents agreed that it is both possible and recommended to calculate benefit to cost ratio of the received training. Only one responded offered specific models suitable for the assessment and provided the information on their limitations. The majority of the responses pointed to the evaluation of financial data necessary for obtaining the ratio as the most apparent challenge in the process. All respondents reported the absence of methods for determining the viability of the received training due to the lack of qualification and dedicated staff. Thus, the most appropriate approach to establishing a benefit to cost analysis method would be to introduce financial measurement tools.

Finally, the responses to the overwhelming majority of the survey questions indicate a strong positive impact of training on the competitiveness of the organization. Specifically, the training was reported to improve employee satisfaction levels and increase employee retention (Q3, Q4, Q9, Q11, Q12, Q15, Q20), product quality (Q5, Q7, Q8, Q13, Q14, Q16, Q17, Q19), and overall efficiency of the organization (Q1, Q2, Q6, Q10, Q18). It is worth mentioning that Q9, Q15, and Q16 showed lower results (Mdn = 3-4, IRQ 2, Mdn = 3, IRQ = 2, and Mdn = 3, IRQ 2, respectively). However, as can be seen, two of three results are also characterized by high interquartile range.

In addition, neither of the results is representative of the trend observed within the identified subgroup. Therefore, it would be safe to consider the overall effect of training as beneficial for the organization’s competitiveness. The results are corroborated by the mean which, in the majority of cases, is consistent with the median and confirmed by the small standard deviation values. Admittedly, the latter is only relevant for determining the overall trends, but, once corroborated by the median and IQR descriptors, can be considered a confirmation of the findings.

Considering all of the above, it is reasonable to describe training program conducted at Global Airspace Logistics beneficial for the competitiveness of the company in terms of employee satisfaction and retention, product quality, and overall organizational efficiency. Therefore, it is recommended to incorporate a systematic measurement of training outcomes and financial benefits in order to produce a meaningful benefit to cost ratio and optimize the workforce allocation to minimize waste of resources associated with deployment and lack of supervision.

Appendix 1

Mode of Responses
Mode of Responses.

Appendix 2

Responses Mean Values.
Responses Mean Values.

Appendix 3

Standard Deviations of Survey Responses
Standard Deviations of Survey Responses.

Appendix 4

Median and Interquartile Range of Survey Responses
Median and Interquartile Range of Survey Responses.

Reference List

Barnett, K & Mattox, J R 2010, ‘Measuring success and ROI in corporate training’, Journal of Asynchronous Learning Networks, vol. 14, no. 2, pp. 28-44.

Brauchle, P E & Schmidt, K 2004, ‘Contemporary approaches for assessing outcomes on training, education, and HRD programs’, Journal of Industrial Teacher Education, vol. 41, no. 3, pp. 1-14.

Fletcher, J D & Wind, A P 2013, ‘Cost considerations in using simulations for medical training’, Military Medicine, vol. 178, no. 10, pp. 37-46.

Grohmann, A & Kauffeld, S 2013, ‘Evaluating training programs: development and correlates of the questionnaire for professional training evaluation’, International Journal of Training and Development, vol. 17, no. 2, pp. 135-155.

Reio, T G, Rocco, T S, Smith, D H & Chang, E 2017, ‘A critique of Kirkpatrick’s evaluation model’, New Horizons in Adult Education and Human Resource Development, vol. 29, no. 2, pp. 35-53.

Williams, R C & Nafukho, F M 2015, ‘Technical training evaluation revisited: an exploratory, mixed‐methods study’, Performance Improvement Quarterly, vol. 28, no. 1, pp. 69-93.

This research paper on Global Aerospace Logistics Company: Training Evaluation was written and submitted by your fellow student. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.
Removal Request
If you are the copyright owner of this paper and no longer wish to have your work published on IvyPanda.
Request the removal

Need a custom Research Paper sample written from scratch by
professional specifically for you?

Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar
Writer online avatar

certified writers online

Cite This paper
Select a referencing style:


IvyPanda. (2020, November 4). Global Aerospace Logistics Company: Training Evaluation. Retrieved from https://ivypanda.com/essays/global-aerospace-logistics-company-training-evaluation/

Work Cited

"Global Aerospace Logistics Company: Training Evaluation." IvyPanda, 4 Nov. 2020, ivypanda.com/essays/global-aerospace-logistics-company-training-evaluation/.

1. IvyPanda. "Global Aerospace Logistics Company: Training Evaluation." November 4, 2020. https://ivypanda.com/essays/global-aerospace-logistics-company-training-evaluation/.


IvyPanda. "Global Aerospace Logistics Company: Training Evaluation." November 4, 2020. https://ivypanda.com/essays/global-aerospace-logistics-company-training-evaluation/.


IvyPanda. 2020. "Global Aerospace Logistics Company: Training Evaluation." November 4, 2020. https://ivypanda.com/essays/global-aerospace-logistics-company-training-evaluation/.


IvyPanda. (2020) 'Global Aerospace Logistics Company: Training Evaluation'. 4 November.

More related papers