Designing research that would accurately evaluate employee performance is a challenging task since the concept is not always associated with particular numbers which can be measured. Different data collection and analysis methods are utilized for receiving meaningful results and implications. The research conducted by Budiningsih, Dinarjo, and Ashari focuses on this topic in their article “Improvement of Employees’ Performance through Training Intervention in Digital Era.” The work has been published in the European Research Studies Journal (volume XX, issue 4B, pages 637-654) in 2017.
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The purpose matches the problem statement in the article and focuses on determining how much professional training affects employee performance and whether it is still effective nowadays. Budiningsih et al. have used books on human resource management and journal articles as sources for the literature review. The Tax Court Secretariat in the Indonesian Ministry of Finance was taken as an organization for the research.
One hundred of its employees were chosen using quota sampling for completing a survey, which was designed as a non-instrument test. The results were measured with the help of descriptive and inferential analysis. The authors have concluded that training accounted for 45 percent of performance improvement, while other 55 percent were due to other factors (Budiningsih et al. 637). Moreover, the competencies acquired in the process of training could disappear if not applied.
Budiningsih et al. aimed to cover performance and training as the two main concepts in their literature review. Books on human resource management and corresponding journal articles were the basis for their source choice. Moreover, half of the latter had been printed in the European Research Studies Journal. Authors did not aim to include the latest findings, as the publication years of the chosen sources ranged from 1998 to 2017.
The first part of the literature review provides the definition and description of employee performance. There are factors like work quality and quantity, responsibility, cooperation, and initiative that influence it. They are chosen by Budiningsih et al. to draw a definition of performance as a concept. Other sources provided include additional elements like loyalty or independence. The second part of the literature review focuses on the idea of training. Apart from defining the term, authors include the reasoning and conditions for conducting it, the essential steps of the process, as well as some of the issues and solutions. Moreover, the scheme for evaluating the effectiveness of a training program is offered.
Research Aims and Objectives
The introduction of the article mentions a previous study that was conducted at the Tax Court Secretariat in 2017, which defined tree problems, being the small effect of training on increasing work quantity, developing employees’ potential, and dealing with current issues. These findings determined the objectives of the research by Budiningsih et al., who aimed to find the extent to which training could influence performance.
Moreover, the positive effect of this initiative was put under question considering the modern development of the digital sphere with all types of information, including professional, that is available for anyone. One of the objectives was to determine whether benefits from training personnel nowadays exceed its cost.
Budiningsih et al. surveyed 100 employees of the Tax Court Secretariat by using Likert scale questionnaires. The audience was chosen by the quota sampling method and included workers with various demographic identities like gender, age, education, and work experience. The questionnaires focused on several indicators that aimed to cover each concept in depth. The authors drafted the model of Y = a + bX, where Y stands for performance and X – for training (Budiningsih et al. 645).
The formula determined the linear correlation between the two factors and had a regression character. Tests of normality, homogeneity of variances, and linearity were performed to measure the accuracy of the results. Finally, the correlation and the ANOVA regression analyses were made, which helped to determine the coefficients for the model as 1.5 for a and 0.6 for b (Budiningsih et al. 651). As a result, the model showed that training accounted for 45 percent of performance growth, while other factors contributed for another 55 percent.
The discussion in the article focuses primarily on the level of correlation between the two main concepts of the research. The authors discuss earlier studies, which claimed that training raised performance by only 10-20 percent, and compared the number to their findings being 45 percent (Budiningsih et al. 651). Another point of the discussion is based on what competencies are acquired in the process and how they are used afterward. Budiningsih et al. propose that if new skills developed through training are not used, they become lost, making little contribution to employees’ performance.
The topic of the discussed research is very important as it allows answering the major managerial question of whether it is worth to input company resources in employee training to raise their performance. However, the article does little to resolve this issue since it lacks clarity and grounding behind many statements and conclusions. The research mentions several parts that do not have proper coverage or, on the contrary, have little association with the topic.
The title of the article is clear and appropriate for the study, as it mentions the two central concepts that the work is based on. However, including the digital era as one of the elements does not adequately describe the paper, as there is little information further on regarding this characteristic. The abstract can also be considered representative since it covers all the main parts of the research, including details on methodology and results. This part also contains a clearly defined purpose at the beginning, which is later restated as a problem in the introduction to the study. However, the abstract is poorly written from the grammatical point of view.
It contains numerous spelling mistakes, issues with sentence structure, and the lack of clarity in some parts. What is curious, other parts of the article do not seem to have the same problem, which raises questions about how the work has been written.
The introduction of the research successfully covers the background for the study. The data for performance achievement of the Tax Court Secretariat employees measured in 2015 reveals an issue of the average number being only about 88 percent (Budiningsih et al. 638). The in-depth interview conducted in 2017 in the same organization shared more problems, associated with training results, which have encouraged Budiningsih et al. to measure the extent of its effectiveness. Both sets of data are presented in the form of tables with clear and concise information.
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Nevertheless, there are several issues associated with this section, including the lack of clarity regarding performance indicators and the absence of a connection between the discussed surveys and the included theories. Firstly, the table showing employee productivity in 2015 offers mere numbers without adding the context. For instance, there is no clarification on what are the administrative requirements that workers should achieve. Moreover, the authors do not provide the reference for the annual report that has become the source for this data.
Secondly, there are several paragraphs that discuss theories from books and journals that would better fit under the literature review section. For instance, the authors include several contradictory opinions regarding the percentage of contribution done by training on the performance development, ranging from 10 to more than 81 percent (Budiningsih et al. 638). However, these ideas have more than twenty years between them, and there is little to no information regarding how they were created and tested.
Moreover, there is no theoretical grounding for the paragraph mentioning the benefits of the digital era for training processes. Budiningsih et al. only emphasize the cost reduction and the ease of use of technologies for learning at work (638) However, this part of the article looks more like an opinion.
The literature review has much information regarding the definition of performance and training as concepts, as well as factors essential to each of them. Budiningsih et al. have ensured an in-depth coverage of this part so that readers clearly understand what is measured in the study. For instance, there are four sets of criteria that characterize performance from the point of view of different researchers. The part describing training not only has its definition but also names the conditions required for successfully leading the process, the possible reasons for its implementing, and the structure of a potential program.
At the same time, there are issues associated with this section. Firstly, the part describing performance as a concept consists mainly of definitions from different books on human resource management. Most of the information repeats itself, having only slight differences among the provided characteristics. Secondly, the section that discusses training and its elements has many sources that may be outdated considering the time of their publication. For example, the authors use information from the article by Baldwin and Ford published in 1998 focusing on costs of personnel training. However, it has been more than twenty years since that publication, and many processes in the HR sphere have changed.
The issue is associated with another weakness of this literature review, which is the absence of discussion regarding modern technology and its effect on personnel training. On the one hand, Budiningsih et al. mention this feature in the title of the research, providing that the element is important for the study. On the other hand, there are only few notes across the article made on this matter, and there are no secondary sources supporting the given ideas.
The overall design of the study is appropriate for the purpose mentioned by the authors at the beginning of the article. The idea of questioning employees of the Tax Court Secretariat on the topic was beneficial since the similar research had been conducted two years before this work, which made it possible to mark the progress in training contribution to performance. The method of quota sampling helped to collect information from personnel with different skills and background, allowing the results to be more representative. Moreover, the total number of survey participants was almost the third of all the Tax Court Secretariat employees, which added accuracy to the study.
However, the model developed for measuring the correlation between training and performance should have been better described and grounded. Firstly, the authors do not explain why they have chosen Y = a + bX as the formula to illustrate the effect of one variable on another (Budiningsih et al. 645). Although it is intuitively understandable that training and performance have a linear character of relation, it may turn differently in practice depending on additional factors influencing the process.
Secondly, Budiningsih et al. do not explain the nature of a and b coefficients, focusing only on Y and X. Finally, the authors mention the number of items essential for the performance and training variables, being thirteen and eight correspondingly (Budiningsih et al. 646). However, there is no clear description of what these elements are. The section contains a table showing dimensions and indicators for each variable, but it is impossible to tell if any of those characteristics are the discussed items. The authors mention the validity test performed for the pilot version (Budiningsih et al. 646). However, there is no additional information on it apart from the results for variables’ elements.
The section contains a table with demographics data of the survey respondents, which is clear and representative. The only information it lacks is the employees’ positions mentioned in the abstract of the article. The descriptive analysis for each variable is also very detailed, which allows noticing trends for the responses. The mean opinions are clearly described, and the standard error rate makes it evident that the results are valid for the analysis.
The biggest issue with the provided findings is associated with the failure to describe the items essential for each variable in the previous section. Thus, the table shows that there are thirteen items for performance and eight of them for training (Budiningsih et al. 646). However, there is no explanation of what those items are. Moreover, the authors mark them as “questioner number,” which is rather confusing (Budiningsih et al. 646). Instead of using abbreviations like PQ1, it would have been more reasonable to provide the direct question or indicator measured.
The section lacks the differentiation of answers based on the demographics of the respondents. For instance, 17 percent of the employees who have been surveyed have less than five years of job tenure (Budiningsih et al. 647).
This can possibly affect the results of the study as such respondents could have little to no training at work, which is one of the central concepts of the research. Besides, more than a quarter of the participants do not have a university degree, which may affect the level of their professional skills. In other words, Budiningsih et al. should have extended the results section and included the statistics for different demographic groups to see if differences in work experience and education are the factors that influence training results.
Correlation and Regression Analysis
Before making an analysis of correlation and regression, the authors conducted a series of tests to show that the received data was accurate and suitable for applying it to the proposed model. The results provide that X and Y values were homogeneous by value, had a normal distribution and linear regression (Budiningsih et al. 649). However, there is no explanation for that part, as the authors offer only five tables with the sets of data (Budiningsih et al. 649). As a result, the conclusions will not be evident to someone who is not familiar with the classic assumption tests.
The correlation analysis provides two important results, which are the value of a determinant coefficient for X, and the percent of contribution derived from it. Thus, the authors offer the number 0.671, which shows the positive and significant influence of training on performance (Budiningsih et al. 650). The square value of the coefficient provides that this effect is measured as 45%, while other 55% are associated with other factors. The issue with this analysis is the same as with the previous section, where people that do not know the method for calculating correlation and determinants may find confusing the way by which the authors have obtained the results.
Finally, a similar problem is associated with the part describing the ANOVA test findings. The authors test the model Y = 1.5 + 0.6X without clearly explaining the way of how they have received the numerical values for a and b (Budiningsih et al. 651). The only comment they make is associated with the high level of significance for the regression constant and coefficient results. In the end, they state that every ten units of training change would cause 7.5 units of performance shift, as derived from the model (Budiningsih et al. 651). The lack of a clear description of what these units are in the previous sections does not allow readers to measure the level of accuracy of this result.
The first part of the discussion is relevant to the findings of the research, as it contains the restatement of the primary result and the comparison of it to literature sources. Thus, the authors prove their hypothesis that training is significant for increasing the level of performance and contributes by 45% to this purpose. The result contradicts with one of the theories claiming that the number does not exceed 20% (Budiningsih et al. 643).
However, the rest of the discussion does not have a direct relation to the survey results and analysis. Budiningsih et al. include the findings from other sources and develop the thought about competencies acquired as a result of training. Based on this short literature review, the authors conclude that performance is predicted by both competencies and training (Budiningsih et al. 652). However, it would be better to put this statement as a direction for future research.
The factors listed under this part of the discussion are presented as the authors’ conclusion. However, they have not been derived from the survey analysis made in this study. Neither there are any references for the information, which looks very precise and specific and does not resemble an idea or a proposal. Thus, the authors should have offered the topic of competencies to become the further development of this research work instead of adding facts to this part of the article. On the contrary, it would be better to discuss the training process and the elements of it that contribute most to performance.
Despite the serious work presented on analyzing the survey results through numerous calculations, the research does not provide enough grounding for the findings offered by its authors. The article has clear statements, but there are often little to no facts or explanation behind them. Budiningsih et al. pack the paper with numbers and fail to describe their origin. The survey structure is unclear, as are the factors of training that contribute most to the performance development.
The discussion partially relies on one of the author’s previous studies, which may be a cause of low objectivity. The methodology does not include the technology factor as one of the training options, and the benefits of the digital era mentioned in the title of the article are not tested and measured. Finally, the whole work contains numerous grammar mistakes, making it difficult to read and raising questions about the quality of the journal editing.
Budiningsih et al. “Improvement of Employees’ Performance through Training Intervention in Digital Era.” European Research Studies Journal, vol. XX, no. 4B, 2017, pp. 637-654.