BUACC5931 Research and Statistical Methods for Business Report Sample

BUACC5931 Research and Statistical Methods for Business

This assessment involves reading and analysing a dataset to develop a research report. Working in groups, you are to design a research project. This will include using academic sources to review the relevant literature, conducting analyses, and advising the management based on the findings of the research. More specific requirements for the assignment will be discussed in lectures. You will need to apply the Excel (or SPSS) data analysis techniques for your group assignment. Some lecture time will also be allocated to the group project so that your lecturer can provide direction/make suggestions.

Report Structure: The group project should have the following:

Abstract: Purpose (research questions), method to answer the research questions (data collection and data analysis), findings, practical implications (usefulness for management) and (or) theoretical implications, and the limitations of the research,

Introduction: Background (of the case); purpose (of this report); two to three research objectives for a study that you would seek to conduct (of this report).

Literature review: Write a short literature review of at least six academic sources relevant to your topic. Any sources including books, journal articles are acceptable, as long as they are relevant. You can also use a particular website for some information. If websites are used, they will be in addition of the six academic sources.

Methodology: Describe the methodology and justify your choice. Specifically describe about the measures, sampling method, procedure of data collection.

Analyses and findings: Run some analysis to turn the data into useful information as following.

Descriptive statistics: Sample characteristics will be described with descriptive analysis.

This will include at least the following analysis: Frequency, percentage; Measures of central tendency (means, median, mode); Measures of dispersion (variance, standard deviation).

Inferential statistics: Inferential statistics will be used to analyse relationship between variables. This will include at least the following analysis (Pearson’s r, t test, ANOVA test).

Discussion and managerial advice: linking your findings to extant literature. Advise the management about the usefulness of the findings. Limitations and directions for future research. Suggestions of how the research can be improved.

References: Include a correctly constructed reference list of all sources used in the project, not just those used in the literature review section.

Appendices: Appendices should also be attached which will include all the analysis and graphs etc. that are not included in the body of the report.

* Please note that conducting both descriptive statistics and inferential statistics is required for evaluation of the task.

Solution

Introduction:

Through the present study analysis has been done to understand how ISO9000 certification influence the performance of the Chinese service sector firms. For the study here statistical data analysis has been used considering secondary empirical data from Chinese firms. Through performing literature review here data analysis methodology has been explained and then statistical analysis has been performed to produce justified outcome for the study. Lastly, through highlighting the limitation and future scope of research, this study concluded.

Literature review:

ISO9000 certification has become an increasingly popular quality management system (QMS) for businesses worldwide, including those in China (Banerjee, 2020). The certification aims to improve customer satisfaction, increase efficiency, and reduce waste, which could ultimately lead to increased profitability and competitiveness (Banerjee, 2020). Several studies have examined the relationship between ISO9000 certification and firm performance in China, particularly in terms of its impact on financial indicators such as Return on Asset (ROA), Return on Sales (ROS), equity, sales, and profit. Overall, these studies suggest that there is a positive association between ISO9000 certification and financial performance.

For instance, a study by Chen et al. (2019) found that ISO9000 certified firms in China had higher ROA and ROS compared to non-certified firms. Another study by Du et al. (2016) also reported a positive impact of ISO9000 certification on firm sales and profit in the Chinese context. Similarly, Siougle et al., (2019) found that ISO9000 certification was positively associated with firm equity in China. Moreover, ISO9000 certification has also been linked to Foreign Direct Investment (FDI) inflows and employment generation in China. A study by Beccari et al., (2019) found that ISO9000 certified firms in China attracted more FDI inflows compared to non-certified firms. Similarly, another study by Aba et al. (2016) reported that ISO9000 certification positively impacted employment generation in Chinese firms.

Despite the positive relationship between ISO9000 certification and firm performance, some studies have also reported mixed results. For example, a study by Yu and

Chen (2017) found that the impact of ISO9000 certification on financial performance in Chinese firms was contingent on certain contextual factors such as firm size, industry sector, and ownership structure (Liu et al., 2023). Another study by Luo and Potkany et al., (2022) found that the positive impact of ISO9000 certification on firm performance was weakened by the presence of high debt levels in Chinese firms that lead to fall in ROS, ROA.

Methodology of analysis:

Data source:

The study has been done using deductive approach, which helped to develop research hypothesis underpinning previous literary sources. As the source of the data, secondary data has been considered from survey done by National Bureau of Statistics of China in 2008. The data has 21 variables, and they were quantitative in nature. Apart from “certification” and “FDI” all variables represented the exact value corresponding to the variable. Certification was dummy variable of ISO certification of Chinese firms; hence firms with ISO9000 certification was coded as 1 and firms which were not certified, they were coded as 0. FDI represented foreign investment in Chinese firms dummy and thus it was also coded with 0 and 1. Chinese firms with 0 FDI means they did not attract any foreign investment and Chinese firms with 1 demonstrated they attracted FDI. Data was available online under open license; hence no legal violation has taken place while capturing data.

Variable description of the dataset has been presented below:

Figure 1: Variable description

A sample dataset has been presented here.

Figure 2: Sample dataset

Data analysis:

Present study for MBA assignment expert has been done considering the statistical approach of data analysis. Considering secondary source of data, quantitative data has been analysed in Excel. Before performing in depth statistical analysis, study has considered performing descriptive analysis. Firstly, coded variables have been explored with pivot table and then inferential analysis like correlation, ANOVA, t-Test, regression has been done. To perform inferential data analysis, following hypotheses has been developed underpinning the previous literary sources:

Hypothesis 1:

H0: ISO9000 certification does no influence profitability of firm.

H1: ISO9000 certification positively increase profitability of firm.

Hypothesis 2:

H0: ISO9000 certification does not have any influence on FDI inflow to Chinese firms.

H1: ISO9000 certification positively influence the FDI inflow of Chinese firms.

Hypothesis 3:

H0: ISO9000 certification does not influence asset, equity, ROS, ROA.

H1: ISO9000 certified influence asset, equity, ROS, ROA.

Hypothesis 4:

H0: ISO9000 certification does not influence sales and employability of the Chinese firms.

H1: ISO9000 certification positively influence sales and employability of the Chinese firms.

To perform the first hypothesis analysis, t-Test has been done that compare the mean value of profit of different group based on certification. For the second hypothesis analysis, chi square test has been done that check whether FDI inflow is influenced by certification or not. For third hypothesis and fifth hypothesis correlation has been checked for independent variables against the dependent variable “certification”. For the fourth hypothesis single factor ANOVA test has been done.

For the inferential analysis, 95% confidence interval has been considered, hence the critical value is set to 0.05. In other word, if the calculated p value is lower than 0.05, null hypothesis is rejected, and alternative has been accepted. However, if p value found to be higher than 0.05, in that scenario, null hypothesis has been accepted while rejecting the alternative hypothesis.

Data Analysis:

Descriptive Analysis:

Descriptive statistical analysis presented under appendix 1 showcase, there were 3685 firms which did not have any certifications and there were 315 firms which have ISO9000 certification. Also, a descriptive analysis for coded variable showcase, out of total 4000 sample firms, 3586 Chinese firms have no FDI, whereas 112 firms gained FDI.

Age of firm:

The descriptive statistics pertain to the age of the firms in the dataset showcase that the mean age of the firms is 7.3345 years, and the median age is 6 years, indicating that the data is positively skewed with a skewness value of 2.9148. Mode of 2 years showcase that most of the firms are operating for 2 years. The standard deviation is 6.0869, which indicates that the age of the firms has a relatively large spread, and the sample variance is 37.0514. The mode of the age of the firms is 2 years, and the maximum and minimum ages are 52 and 2 years, respectively, resulting in a range of 50 years. The kurtosis value of 13.3565 indicates that the age of the firms' distribution is heavily tailed, with outliers present in the data.

Employee:

The descriptive statistics related to the employee of the firms showcase that the mean employee total is 44.519, and the median employee total is 23, indicating that the data is positively skewed with a skewness value of 6.0145. The standard deviation is 74.6384, which implies that the employee total of firms has a relatively large spread, and the sample variance is 5570.8889. The mode of the employee total is 12, and the maximum and minimum values are 969 and 11, respectively, resulting in a range of 958. The kurtosis value of 47.7467 indicates that the distribution of employee totals is heavily tailed, and the data has many outliers.

Profit:

The descriptive statistics refer to the profit of the firms showcase that the mean profit of firms is 2027.075, and the median profit is 692, indicating that the data is positively skewed with a skewness value of 20.8791. The standard deviation is 7599.5204, which indicates that the profit of firms has a relatively large spread, and the sample variance is 57752711.07. The mode of the profit is 300, and the maximum and minimum profits are 296176 and 17, respectively, resulting in a range of 296159. The kurtosis value of 653.4408 indicates that the distribution of profits is heavily tailed, with many outliers present in the data.

Sales:

The descriptive statistics refer to the sales of the firms showcase that the mean sales of firms are 11458.578, and the median sales are 4200, indicating that the data is positively skewed with a skewness value of 11.8216. The standard deviation is 33460.4577, which indicates that the sales of firms have a relatively large spread, and the sample variance is 1119602229. The mode of sales is 1800, and the maximum and minimum sales are 869176 and 1000, respectively, resulting in a range of 868176. The kurtosis value of 201.2189 indicates that the distribution of sales is heavily tailed, with many outliers present in the data.

Asset:

The descriptive statistics refer to the assets of firms showcase that the mean assets of firms are 15926.33225, and the median assets are 3919.5, indicating that the data is positively skewed with a skewness value of 8.9581. The standard deviation is 52697.54987, which indicates that the assets of firms have a relatively large spread, and the sample variance is 2777031762. The mode of assets is 2000, and the maximum and minimum assets are 879390 and 1000, respectively, resulting in a range of 878390. The kurtosis value of 103.3931 indicates that the distribution of assets is heavily tailed, with many outliers present in the data.

Equity:

The equity statistics shows that the mean equity of the 4000 firms is $7277.83 with a standard error of $462.4, and a standard deviation of $29244.81. The median equity value is $1585.5, and the mode is $500. The data is highly skewed with a skewness value of 11.92 and a kurtosis of 186.24 indicating that the data is heavily tailed and has many outliers. The range of equity values is 677091 with a minimum value of $10 and a maximum of $677101. The sum of all the equity values is $29111323. A 95% confidence level indicates that the true mean equity value of the population lies between $6371.27 and $8184.39. The descriptive statistics show that there is a large variation in equity values among the 4000 firms.

ROS:

Descriptive statistics for ROS showcase that the mean ROS value is 0.1919, indicating that the company earns a net income of $0.1919 for every dollar of sales revenue. The standard error of 0.00196 suggests that this estimate is reliable. The median ROS value is 0.1725, meaning that half of the companies have an ROS below this value. The mode of 0.31 suggests that there is a peak at this value in the distribution. The range of 0.4925 indicates that there is significant variation in ROS values among the companies, with the minimum value being 0.0133 and the maximum being 0.5058. The kurtosis value of -0.7005 suggests that the distribution is platykurtic and flatter than a normal distribution. The skewness value of 0.5065 suggests that the distribution is positively skewed.

ROA:

The descriptive statistics for ROA show that the mean is 0.227, which indicates that the average return on assets for the sample of firms is 22.7%. The standard deviation is 0.211, which implies that there is a significant variability in the ROA values, indicating that some firms are performing much better or worse than the others. The kurtosis is greater than 1, indicating that the distribution is leptokurtic, or more peaked than a normal distribution. The skewness value is positive and greater than 1, suggesting that the distribution is positively skewed, with a long tail on the right. The range is 1.008, which indicates that the difference between the minimum and maximum values of ROA is 100.8%. The minimum value is 0.0145, while the maximum value is 1.0226, which is an outlier value. The confidence level (95%) is 0.0065, which means that the true population mean ROA value is expected to fall within the range of plus/minus 0.0065 of the sample mean.

Analysis for first hypothesis:

First objective was aimed to analyse whether profitability of the Chinese firms is influenced by certification or not. As per the t-Test, it was observed that there were 3685 firms which did not have any certifications and there were 315 firms which have ISO9000 certification. As it was aimed to determine whether profitability of certified firms is higher than non-certified firm, thus one tail test results has been considered from statistical test. As per the output presented in appendix 2, it can be observed that p value is much lower than 0.05; hence here null hypothesis is rejected, and alternative hypothesis is accepted. This infer that the profitability of the Chinese firms increases with the ISO9000 certification.

Analysis for second hypothesis:

Second objective was aimed to determine whether ISO9000 certification influence the FDI inflow of the firm or not. For this, chi square test has been done using excel and p value found to be 0.1369 (Appendix 3). This value is much higher than 0.05, hence the null hypothesis has been accepted while rejecting the alternative. This signifies that there is no association between FDI inflow of firm and ISO9000 certification.

Analysis for Third Hypothesis:

Third hypothesis was aimed to determine whether there is any association between ISO9000 certification and asset generation, equity growth, ROS generation, ROA generation. For this correlation test has been done and the output is presented under appendix 4. As per the outcome, it was observed that ISO9000 certification significantly increase asset generation and equity. However, it also needs to note that the association is very weak with .0928 and .0945 correlation respectively. As the association is positive, it means, change in certification lead to change in asset value and equity in same direction. In case of ROS and ROA, there is a negative association with ISO9000 certification. This means ISO9000 certification would lead to fall in ROS and ROA for the firm. This finding is aligned with the previous literary sources which showcase ISO certification led to higher investment in product development, causing ROA and ROS to fall (Aba et al. 2016). However, in long term, both ROS and ROA are supposed to rise with product quality development and international sales generation with ISO9000 certification (Aba et al. 2016). Here, due to absence of valid evidence, null hypothesis neither rejected nor accepted.

Analysis for Fourth Hypothesis:

Fourth objective was aimed to analyse whether ISO9000 certification influence the employability generation and sales generation. To analyse the same, ANOVA has been used and the finding presented in appendix 5 showcase that p value if 0. Hence, with p value lower than critical value of 0.05, it is valid to reject null hypothesis and tell that ISO9000 certification significantly influence the sales and employee number growth.
Analysis of factors that influence ISO9000 certification:

To check which factors significantly influence the ISO9000 certification of Chinese firms, a regression has been done. As per the regression output presented in appendix 6, regression model is significantly valid with F value lower than 0.05. However, R square value showcase, independent variables can explain only 5.8% variability in the dependent variable. As per the outcome, age of firm, total employee number, ROA and sales influence the ISO9000 certification. Coefficients terms showcase that, with each year rise in age of the firm, probability of getting ISO certification increase by .3% rate. On the other hand, when the employee number and sales increase by one unit probability of Chinese firm getting ISO9000 certification is increased by .05% and .000076%. For ROA, unit increase in the same decrease the probability of getting ISO9000 certification by -6.1%.

Discussion and Managerial Advises:

Finding of the analysis and managerial implication:

From the above analysis it is found that the data considered have 4000 sample firm of different size and age. However, descriptive statistics showcase that most of the firm are having operation age of 2 years. Upon analysis of hypothesis, it was signified with statistical validity that ISO9000 certification increase profitability of Chinese firms. Moreover, ISO9000 certification can increase the sales and employment generation of the firm. Although the hypothesis analysis failed to significantly determine change in equity and asset value due to ISO9000 certification; yet correlation demonstrated a positive association among these factors. Meaning, when the firm become ISO9000 certified, it increases the asset value of firm and enhance equities too. Study also found that ROS and ROA are supposed to fall due to the ISO certification. This is valid because when new firm get certified with ISO, it needs to invest heavily on product quality enhancement for meeting international standards. Thus, the additional cost led to fall in ROS and ROA at initial period, although it becomes positive over time with higher sales and revenue generation. Study showcased that FDI inflow is not influenced by the ISO certification; however, it is not in line with previous literary source that showcase firms with ISO certification tends to fain higher FDI inflow (Beccari et al., 2019).

When the factors of influence for ISO9000 certification was assessed, it was found that age of firm, sales, employment generation and ROA influence it significantly. These are all in line with previous literary sources. With rise in age of firm, sales and employment increase that led the firms ROA, and it aims for global expansion (Aba et al. 2016). With aim of global expansion firm opts for ISO certification to match the global standards.

Limitation of the study:

There are various limitations in the study. Firstly, in terms of the data, it was taken from the 2008 which is pretty old considering the analysis made in present date. Secondly, here only quantitative data analysis has been taken based on empirical data without understanding human perspectives towards ISO9000 certification. Thirdly, in absence of human psychological perspectives, study has failed to capture the real change in operation, business performance, quality assurance of the firm. Thus, though the study has statistically showcase use of ISO9000 certification is beneficial for Chinese firms, however, it failed miserably to understand qualitative influence of the same.

Future scope of study:

Considering qualitative information and introducing human psychological perspectives into the present study is highly suggested for future study on current research phenomenon. With capturing latest information related to ISO certification of Chinese firm, market trend and behaviour can be assessed in future study. It will provide essential guidance to the policymakers in shaping norms for ISO certification that can enhance global acceptance of Chinese products (Banerjee, 2020). Future study can perform mixed method of study which will have both the empirical evidence and qualitative information. This will make the study more acceptable to larger audience as it will have higher validity and reliability with statistical justification and qualitative confirmation.

Reference:

Aba, E. K., Badar, M. A., & Hayden, M. A. (2016). Impact of ISO 9001 certification on firms financial operating performance. International Journal of Quality & Reliability Management, 33(1), 78-89. https://sci-hub.se/https://www.emerald.com/insight/content/doi/10.1108/IJQRM-02-2014-0021/full/html

Banerjee, T. (2020). Assessment of the impact of iso standards–a study of Chinese firms. https://www.researchgate.net/profile/Trishit-Banerjee-4/publication/344416011_ASSESSMENT_OF_THE_IMPACT_OF_ISO_STANDARDS_-A_STUDY_OF_CHINESE_FIRMS/links/5f73440d299bf1b53efe2672/ASSESSMENT-OF-THE-IMPACT-OF-ISO-STANDARDS-A-STUDY-OF-CHINESE-FIRMS.pdf

BECCARI, G., PISICOLI, B., & VOCALELLI, G. Barbarians at the gate? FDI and target firms’ management quality. https://www.freit.org/WorkingPapers/Papers/ForeignInvestment/FREIT1794.pdf

Chen, Y. Y., Wu, L., & Zhai, Q. G. (2019). Does ISO9000 certification benefit service firms?. Sustainability, 11(21), 5886. https://www.mdpi.com/2071-1050/11/21/5886/pdf

Du, Y., Yin, J., & Zhang, Y. (2016). How innovativeness and institution affect ISO9000 adoption and its effectiveness: evidence from small and medium enterprises in China. Total Quality Management & Business Excellence, 27(11-12), 1315-1331. https://sci-hub.se/https://www.tandfonline.com/doi/full/10.1080/14783363.2015.1075874?scroll=top&needAccess=true&role=tab&aria-labelledby=full-article

Liu, Y., Farooque, M., Lee, C. H., Gong, Y., & Zhang, A. (2023). Antecedents of circular manufacturing and its effect on environmental and financial performance: A practice-based view. International Journal of Production Economics, 260, 108866. https://www.sciencedirect.com/science/article/pii/S0925527323000981

Potkany, M., Zavadsky, J., Hlawiczka, R., Gejdos, P., & Schmidtova, J. (2022). Quality Management Practices in Manufacturing Enterprises in the Context of Their Performance. Journal of Competitiveness, 14(2), 97-115. https://www.cjournal.cz/files/446.pdf

Siougle, E., Dimelis, S., & Economidou, C. (2019). Does ISO9000 certification matter for firm performance? A group analysis of Greek listed companies. International Journal of Production Economics, 209, 2-11. https://www.sciencedirect.com/science/article/abs/pii/S0925527318301907