Strategic Management Accounting And Decision-Making In Small Medium Enterprises In Malaysia

Literature Review and Hypotheses Development

Population and Sample

Population is defined as a society of people, occasions or things that captures the interest of researcher who wants to investigate (Sekaran & Bougie, 2016). Based on data released by the Department of Statistics Malaysia (Department of Statistics [DOSM], 2019), SMEs registered a growth of 6.2% in 2018 (2017: 7.1%), slightly above the long-term average growth of 6.0% (2001 - 2017). SMEs for Service sector registered a growth of 8.1% compared to 7.2 % in 2017 which was accelerated by wholesale and retail trade, food and beverages and accommodation which grew to 8.6% (2017: 7.5%). The population of this study is SMEs in food and beverages industry selected as the population because this industry is among the prime mover of SMEs in services sector (DOSM, 2019; Malaysian Investment Development Authority [MIDA], 2017). Therefore, this research focused on SMEs in food and beverage industry. On top of that, food and beverages industry is among the top three most numbers of firms among all industries in Selangor (SME Corp. Malaysia, 2019). Due to that reason, this research has specifically selected SMEs in the food and beverage industry located in Selangor due to major SMEs in food and beverage industry is concentrated in Selangor compared to other states in Malaysia (SME Corp. Malaysia, 2019).

Judgement sampling is being used which distributed to top management of SMEs since the top managements have the most advantages and in the best position to provide the information which they will represent their SMEs/company. Top management is referred as key manager who accountable for strategy formulation, planning, execution, making strategic decisions and the relationship between those decisions and business performance. In addition, the characteristics for this top management refer to their age, level of education/ professional background and company position (Wu et al., 2017). A total of 384 were distributed and 113 usable questionnaires collected for further analysis giving a response rate of 29.43%. The unusable responses were due to the top management of the SMEs refused to take part and uncompleted questionnaires.

Measurement of variables

The research questionnaire used is adopted from Julius et al. (2016), Ahmad (2012), Al-Sayyed (2015) and Alnawaiseh (2013). The questionnaire consists of four parts. Part A covers demographic factors consisting of gender, age group, education and position in the company. The measurement use for the gender factor is male =1 and female =2, and nominal scale is used to measures the other three elements. Part B consist of business characteristic of the SMEs, for example the years of operation/business, form of business, number of employees as well as annual sales turnover. Nominal scale is used for the first element whereas the remaining three element used ordinal scale in this section. As for Part C of the questionnaire is all about the SMA tools used in the business that comprised of the usage of strategic pricing, the usage of target costing and life cycle costing. Part D is the decision making section consisting of questions regarding the effects of decision-making process from the usage of SMA tool. For the Section C and D, each questions are measured using a 5 point Likert scale (1= Strongly Disagree to 5= Strongly Agree). All data gathered from the questionnaires, examined with the Statistical Package for Social Science version 24.

Normality Test and Reliability Test

Normality test is used to investigate whether the data is normally distributed. The indicator for normal distribution of data is, the p-value must be more than 0.05 but for non-normal distribution of data, the p-value must be less than 0.05. (Sekaran & Bougie, 2016). The result shows that all significance value is less than 0.05 which indicate the data is not normally distributed. Thus, non-parametric tests are used to analyse the data. The reliability test assesses the stability of the multi-item scales and internal consistency. Reliability range differently where 0.6 and below demonstrate low in reliability, in the range of 0.6 to 0.7 is commonly accepted as a moderate reliable scale and score above 0.8 indicates high reliability of items (Sekaran & Bougie, 2016). The Cronbach’s Alpha value for strategic pricing, target costing, life cycle costing and decision-making are 0.945, 0.754, 0.969 and 0.765 respectively. The Cronbach’s Alpha for strategic pricing and life cycle costing indicate to be good and acceptable because it is more than 0.8. Meanwhile, as for the target costing and decision-making, the Cronbach’s Alpha indicate to be acceptable because it is within the range of 0.7.

Descriptive Result Test

Table 01 show the descriptive analysis among the respondent. With regards on gender, most of the respondents were female with a total of 59 respondents (52.2%) and the male were 54 respondents (47.8%). In term of the age of respondents, 40.7 % is for the age of 30-39 years old representing 46 respondents, 38.1% within the age range of less than 29 years old and 15.9% respondents whom are in the range of 40-49 years old. The lowest is respondent in the age of 50 years old and above. Most of the respondents possess Diploma, which represent 79 respondents (69.9%) and only one respondent (0.9%) who holds Master/PhD and professional certificate respectively. Majority of the respondents are managers with a total 79 respondents (69.9%), followed by owners of 34 respondents (30.1%). Most of the respondents’ company operated within the range 4-10 years with a total 52 respondents (46%). The second highest are in the range of 1-3 years which represented by 34 respondents (30.1%). The lowest are the in the range of more than 10 years with a total of 27 respondents (23.9%). The highest number of employees among the respondents’ company is in the range 5 to 29 employees with a total 55 respondents (48.7%). The second highest are in the range of less than five employees which represented by 42 respondents (37.2%). The companies that consist of employees in the range of 30 to 75 employees have the least number of respondents with 16 respondents (14.2%). The majority of annual sales turnover among the respondents’ company is in the range less than RM300,000 with a total 71 respondents (63%). Then, it follows with turnover in the range of RM300,000 to RM2.9 million which represented by 36 respondents (32%). The lowest are the in the range of RM 3 million to RM 20 million with 6 respondents (5%).

Most preferable SMA tools use by SMEs in Malaysia

Table 02 shows the univariate analysis conducted for strategic pricing, target costing and life cycle costing. The highest average mean is target costing and can be concluded that the target costing is most preferable SMA tool used by SMEs. This is on contrary with the study by Ahmad and Zabri (2016) in which their finding that strategic pricing is the most preferable SMA tools in SMEs.

Table 03 reveals the descriptive analysis conducted for every question that falls under strategic pricing. The highest mean for strategic pricing was 4.06 refer to the question “ We analyse the effect of competitor price in pricing decision process ” which indicated majority respondents take account on price set by competitors in pricing decision process.

Table 4 shows the descriptive analysis conducted for every question that falls under target costing. The result for target costing portray that the question “ Price of the products is affected by the costs of raw materials storage, supplies and prices of the production process cost ” has the highest mean of 4.25 and standard deviation of 0.77. This demonstrated that respondents agree that the cost of raw materials storage, supplies and prices of the production process costs will affect the product price.

For life cycle costing, the result shows that the highest mean is 3.14 for both question on “assigning a qualified staff to identify and measure the costs incurred at each stage” and “measure all the costs incurred as part of the product cost”. Table 5 shows the descriptive analysis for every questions in the life cycle costing as one of the strategic management tools.

Relationship between between the use of the SMA tools (strategic pricing, target costing and life cycle costing) and the decision-making process

Spearman’s Rank Order Correlation was run to test correlation between the independent variables and the dependent variable. The result of the correlation test is used to analyse the relationship between the independent variables and the dependent variable. Table 6 shows the correlation between strategic pricing and the decision-making process. The result shows a significant relationship which indicate by correlation coefficient, r = 0.212 at the p-value = 0.024. Hence, the result supports the findings made by Oboh and Ajibolade (2017), Ahmad and Zabri (2016) and Cohan and Jacquillat (2017). Oboh and Ajibolade (2017) stated that the strategic pricing will contribute to a better pricing decision. Moreover, Ahmad and Zabri (2016) found that most of the manufacturing firm in SMEs use strategic pricing. Moreover, Cohan and Jacquillat (2017) stated that the revenue will increase by using strategic pricing. Thus, it can be concluded that there is a significant relationship between the usage of strategic pricing and the decision making process. Hence, the hypothesis, H1 is supported.

The result for target pricing and the decision-making process shows a significant relationship which indicate by correlation coefficient, r = 0.526 at the p-value = 0.000. The result obtained is consistent with the findings of Ghafeer et al. (2014) and Ahmad and Zabri (2016). Ghafeer et al. (2014) find out that there is a positive relationship between the cost target method and decision making process. Moreover, Ahmad and Zabri (2016) declared target costing as the second most used SMA tools in the manufacturing firms in SMEs sectors in Malaysia. However, the result of this research in not consistent with Mustafa and Kasa (2016) that found no single manufacturing firms in Albania use target costing in decision making. Thus, it can be concluded that there is a significant relationship between the usage of target costing and the decision making process. Hence, the hypothesis, H2 is supported.

The final correlation testing is the relationship between life cycle costing and decision making process. The result shows no significant relationship which indicate by correlation coefficient, r = 0.007 at the p-value = 0.941. The result is not consistent with the study by Charavarty and Debnath (2014), Spickova and Myskova (2015) and Ahmad and Zabri (2016). Charavarty and Debnath (2014) proves that life cycle costing is important decision making tools to evaluate the choices for capital investment planning. Besides, Spickova and Myskova (2015) stated that the usage of life cycle costing is good because the tools take measures the system boundaries and future costs. In manufacturing firms, Ahmad and Zabri (2016) found that the life cycle costing is the top three strategic management accounting tools being used. Thus, it can be concluded that there is no significant relationship between the usage of life cycle costing and the decision making process. Hence, the hypothesis, H3 will not be supported.

Limitations of study

This study has following limitations. First, the result might only generalise for food and beverages SMEs only. Thus, the result may not reflect the overall sector population of SMEs in Malaysia. Since the respondent of this study in only focus on SMEs in food and beverages sector in Selangor. Since this study have small samples and limited to respondents in particular geographic regions. Hence, if the scope is increased to include more sectors of SMEs, the findings will be different. Other than that, some SMEs have trouble to understand the questionnaire given even though the researcher apply face to face interview with SMEs respondent by giving explanations in each items of the questionnaire. Thus, the respondent will refuse the questionnaire because of lack of knowledge regarding the SMA tools. Finally, another limitation of this study is only focus on top management to fill up the questionnaire, which limit the qualified respondent to respond. In some cases, the top management are not always available which the respondent reluctant to answer the questionnaire given.

Recommendations

Firstly, the research only focus on food and beverages SMEs. As the result might only generalised in the food and beverages industry of SMEs, future research is recommended to expand the study in other sectors in order to reflect the overall sector population of SMEs in Malaysia. In addition, the research is conducted within the Selangor state only hence it is recommended for the research to be conducted in other regions that has high number of SMEs such as Pahang and Terengganu. The data collected shows that the top management of SMEs majorly use the strategic management accounting (SMA) tools in order to facilitate their decision-making. However, a number of respondents is lacking knowledge about SMA tools. Hence, the SME Corporation is recommended to educate the top management of SMEs on the use of SMA tools in facilitating decision making by introducing courses or providing information in their official website. Future researcher could conduct their research with more independent variables. They may identify more SMA tools that will influence the decision-making among SMEs in Malaysia. Additionally, future researcher could use larger sample size to widen their scope of research. Increase sample size would lead to higher reliability on the data collected, hence the data obtained could be normally distributed.