Research Article: 2022 Vol: 25 Issue: 1
Maher Hourani, Al-Ahliyya Amman University
Yacoub Hamdan, Al-Ahliyya Amman University
Citation Information: Hourani, M., & Hamdan, Y. (2022). Exploring the link between strategic planning and financial performance: a case of Jordan-based SMEs. Journal of Management Information and Decision Sciences, 25(1), 1-8.
The research aims to explore the relationship between strategic planning (SP) and the financial performance of Jordanian SMEs. A quantitative approach with correlation design was implemented, alongside an online questionnaire survey for data collection from 92 senior employees. The study found a significant link between managerial factors and financial performance and SP intensity and financial performance. It recommends using more factors in future research to understand better the dynamics of the link between the two constructs.
Strategic planning; Financial performance; Business; Jordan.
Strategic planning (SP) is a continuing and explicit organisational procedure that includes various components, comprising the generation and assessment of different strategies and establishing objectives (Aldehayyat & Twaissi, 2011). The process of SP is deliberate, systematic, and analytical (Aldehayyat et al., 2011). Its advantages, as suggested in previous research by Sadeghifar et al. (2015), includes increasing co-ordination (aligning strategies of business units in an overall organisational strategy), increasing internal communication between employees, managing and reviewing progress, and performance toward an objective; for exploiting and highlighting future marketing process, and encouraging an employee in a positive to change, thus enhancing corporate performance. Some strategy experts, i.e. Cragg et al. (2002), claimed that the SP process is largely inappropriate for small firms as they lack financial and management resources. Nevertheless, the outcome of few empirical studies (Wijetunge & Pushpakumari, 2014; Stonehouse & Pemberton, 2002) gave significant evidence that small businesses and firms implementing SP are increasing significantly due to their trust in its advantages, particularly related to the increase in financial performance (FP).
Most of the research concerning SP in small and medium-sized enterprises (SMEs) and its association with performance were conducted in the US, and limited studies were performed in other developed economies like the UK (French et al., 2004; Falshaw et al., 2006; Kraus; 2006). Besides, little attention and focus are devoted to the research of SP and FP in SMEs in the Middle East, particularly in the context of Jordan. Although Dincer et al. (2006), Elbanna (2007), and Aldehayyat (2011) and have explored the link between SP and FP in the Middle East, not much emphasis was given to SMEs. In addition, none of these studies investigated the impact of SP on organisational performance in detail. Rather, only a few studies are worth mentioning that emphasised such a relationship in the context of the Middle East (Elbanna, 2008; Glaister et al., 2008), yet small firms were ignored their research. Hence, the present research aims to address the gap found in the literature, offer new empirical insight regarding the characteristic of SP in Jordan-based SMEs, and assess their link with FP. The current research is the newest in its type in the context of the Middle East, and its findings will be assessed in light of previous literature.
The following are the main research question:
1. What is the link between strategic planning and financial performance?
2. Which of the factors/components of strategic planning are correlated with the financial performance of Jordanian SMEs?
The literature on SP and FP is not recent; rather, previous empirical studies have contributed significantly. For instance, Gică and Negrusa (2011) assessed the link between the elements of SP and the FP of SMEs in Romania. The research emphasised SP with FP and limited influence on every element of SP to performance. The results showed and confirmed that the link between strategic and SP was weak, and a negative correlation was found. Similalry, Kraus et al. (2006) examined the characteristics of SP such as (control of plans, use of planning tools, formality, and time horizon) and performance relation of 200 plus SMEs in Austria. The results revealed a significantly positive link. Additionally, it was concluded the high the level of planning, the better the chance of SME's performance.
Other scholars assert that SP is amongst the key salient determinants responsible for contributing to the FP of firms. Nevertheless, literature in this regard provided contradictory results of the link between performance and SP. For instance, Wijetunge and Pushpakumari (2014) examined the link between SP and SMEs' FP. The findings showed that SMEs were temperately linked in the process of SP, and there was a positive link between business performance and SP.
Aldehayyat and Twaissi (2011) explored the elements of SP in Jordanian SMEs and assessed its link with corporate performance. The research found a significantly positive link between corporate performance and SP, and the survey results gave rich data regarding the number of practices linked with strategic sources in Jordanian SMEs. Furthermore, Alosani et al. (2019) empirically examined the joint impact of SP and innovation on Dubai's law enforcement performance. The outcome of the study confirmed the effect of innovation and SP on organisational performance. Organizational readiness for change, information technology capabilities and people management have significant positive impacts on organizational performance (Hameed et al., 2021).
According to Jayawarna and Dissanayake (2019), the link between performance and SP is drawn from different theoretical domains, which include contingency theory, organisation theory, and resource-based view. The results on performance and SP link contrary outcomes, whereas studies have shown no, negative or even positive link between performance and strategic performance, and most of the research has not undertaken the impact of their variables on this link. Gomera et al. (2018) also examined the link performance and SP using survey responses from 225 respondents identified as managers or owners of SMEs working in the Buffalo City Metropolitan in South Africa. The results showed that SP has a significantly positive link with the FP of SMEs. Additionally, certain elements of SP such as (control, evaluation, implementation, and formulation) were positively correlated with FP. In a similar context, Arasa and Obonyo (2012) argued that SP is significant in providing direction to firms and help firms where to expand and where to head in their efforts. In addition, it significantly guides them in defining the business objectives and helps them to accomplish the set target. Thus, it is found to be positively correlated with their overall financial and corporate performance.
The present research is focused on a quantitative approach to explore the link between SP and FP of Jordanian SMEs. The purpose of considering a quantitative approach is to allow data analysis using statistical evidence. This particular approach, as per Snelson (2016), allows reliable and exact measurement and control via sample and design. The quantitative approach is repeatable, allowing complex analysis via statistical tools and can produce causality statements. In terms of the research design, the present research specifically emphasises the correlation design, which helps examine the link between more than one variable. It is a non-experimental design used to describe the link between variables (Sileyew, 2019; Gelo et al., 2008). This very design contributes to a profound understanding of basic constructs and their related relationships. The use of correlation design is to provide statistical evidence for the research hypothesis. Here, the use of correlation design evaluates the link between SP and FP. Besides correlation design, the research emphasises using descriptive design in which an online survey is performed with Jordanian SMEs to assess how SP helps improve the FP of SMEs. The survey is useful in the present research as it helps collect a large number of data and allows quantitative analysis through descriptive and inferential statistics (Saunders et al., 2009).
Considering the research question of the study, approach, and design of the study, a primary data source is preferred for collecting data from Jordanian SMEs. An online questionnaire survey is used for collecting the data from senior employees of multiple Jordanian SMEs belonging to either service or production/manufacturing industries. The primary data source is significant in collecting first-hand and new data required for this study, unlike secondary sources that rely on used and already published sources (Saunders et al., 2009). In terms of the sample size, a sample of 92 employees with complete responses was considered, which was collected with the help of a convenience sampling strategy. For data analysis, Descriptive statistics are used, which according to Saunders et al. (2009), allows research to numerical compare and explain the variables. It comprises instruments linked to central dispersion and tendency. As far as present research is concerned, descriptive statistics, percentage, and distribution analysis are considered for the evaluation of the selected variables.
Additionally, the research also includes and undertakes correlation analysis techniques for examining the link between the variables. The correlation analysis technique is a significant instrument for measuring the strength and direction of the link between more than two variables. The Pearson Correlation is applied in this research for examining the statistical association between various sets of variables and applied correlation coefficient 'r' to examine the magnitude and direction of the relationship. Similarly, the regression analysis technique is used to conduct the statistical test to examine the impact of predictors on the outcome (Saunders et al., 2009).
The collected data from Jordan-based SMEs have been statistically analysed for descriptive, independent samples, correlational and regression testing. The data has been collected from 92 respondents belonging to SMEs working in the manufacturing or services industries.
A majority sample size of the current study comes from the SMEs operating in production-manufacturing industries accounting for 63%, whereas 37% are those working in the services industries (Table 1).
| Table 1 Industries | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Production-Manufacturing Industries | 58 | 63.0 | 63.0 | 63.0 |
| Services Industries | 34 | 37.0 | 37.0 | 100.0 | |
| Total | 92 | 100.0 | 100.0 | ||
In order to identify the trends of strategic planning and financial performance within SMEs, descriptive statistics were used on the individual items of strategic planning's characteristics. These dimensions include managerial factors, environmental factors, and organisational factors, which make up for strategic planning intensity. The last variable is financial performance (Table 2).
| Table 2 Descriptive Statistics | |||||
| N | Minimum | Maximum | Mean | Std. Deviation | |
| Managerial factors | 92 | 1.00 | 5.00 | 3.6848 | 1.09122 |
| Strategic planning intensity | 92 | 2.00 | 5.00 | 3.7341 | 0.72474 |
| Environmental factors | 92 | 2.00 | 5.00 | 3.2880 | 0.75678 |
| Organizational factors | 92 | 1.00 | 5.00 | 3.4076 | 1.02424 |
| Financial performance | 92 | 1.00 | 5.00 | 3.4055 | 1.00135 |
| Valid N (list wise) | 92 | ||||
The table of descriptive statistics indicates that items that make up for strategic planning intensity have the highest mean score of 3.73, followed by managerial factors with a mean of 3.68 and a standard deviation of 1.09. The lowest average score is reflected by environmental factors of 3.28. Therefore, the results imply that strategic planning intensity is highly practised in organisations, and managerial factors are given more importance than organisational or environmental factors.
The items of each of these characteristics are also tested separately to identify which of them is more important in the Jordanian SMEs. See the following Table 3 for results.
| Table 3 Descriptive Statistics | |||||
| N | Minimum | Maximum | Mean | Std. Deviation | |
| Strategic planning expertise | 92 | 1.00 | 5.00 | 3.7283 | 1.12028 |
| Planning–performance beliefs | 92 | 1.00 | 5.00 | 3.6413 | 1.13468 |
| Mission | 92 | 2.00 | 5.00 | 3.6522 | 0.89485 |
| Objectives | 92 | 2.00 | 5.00 | 3.8043 | 0.78781 |
| Internal analysis | 92 | 2.00 | 5.00 | 3.9130 | 0.84713 |
| External analysis | 92 | 2.00 | 5.00 | 3.7283 | 0.93882 |
| Implementation | 92 | 1.00 | 5.00 | 3.5978 | 0.96145 |
| Alternatives | 92 | 2.00 | 5.00 | 3.6739 | 1.10054 |
| Control | 92 | 1.00 | 5.00 | 3.7717 | 1.02821 |
| Environmental change | 92 | 2.00 | 5.00 | 3.3370 | 0.84225 |
| Environmental complexity | 92 | 1.00 | 5.00 | 3.2391 | 0.99857 |
| Structural complexity | 92 | 1.00 | 5.00 | 3.4130 | 1.07061 |
| Business size | 92 | 1.00 | 5.00 | 3.4022 | 1.01700 |
| Income | 92 | 1.00 | 5.00 | 3.2717 | 1.09045 |
| Deposit growth | 92 | 1.00 | 5.00 | 3.3043 | 1.03498 |
| Return on equity | 92 | 1.00 | 5.00 | 3.6413 | 1.20968 |
| Valid N (list wise) | 92 | ||||
According to the results of descriptive statistics, internal analysis and objectives have the highest average (mean) score of 3.91 and 3.80, showing that these activities as a part of strategic planning intensity are given more importance in the companies of Jordan. Other factors that seem important include external analysis, control, and strategic planning expertise, which are a diverse mix of environmental, organisational and managerial factors with a mean score of 3.72 and higher. However, it should be noted that the items that make up for financial performance, such as income, deposit growth and returns on equity (ROE), have a fairly low average; however, out of the three, ROE has the highest average of 3.64.
The study performs an independent samples t-test to test whether strategic planning intensity differs between types of industries (Tables 4 & 5).
| Table 4 Group Statistics | |||||
| Industries | N | Mean | Std. Deviation | Std. Error Mean | |
| Strategic planning intensity | Production-Manufacturing Industries | 58 | 3.9874 | 0.55152 | 0.07242 |
| Services Industries | 34 | 3.3021 | 0.78607 | 0.13481 | |
| Table 5 Independent Samples Test | ||||||
| Levene's Test for Equality of Variances | t-test for Equality of Means | |||||
| F | Sig. | t | df | Sig. (2-tailed) | ||
| Strategic planning intensity | Equal variances assumed | 7.670 | 0.007 | 4.901 | 90 | 0.000 |
| Equal variances not assumed | 4.479 | 52.274 | 0.000 | |||
The mean scores reveal that production-manufacturing industries have greater strategic planning intensity on average than the services industries in Jordan. It could be due to higher scores in strategy planning expertise, planning-performance-beliefs, mission, objectives and other strategic planning intensity factors.
The independent samples t-test confirms that results that strategic planning intensity significantly differs between the two types of industries in Jordan, suggesting a greater focus required by service-based firms on strategic planning and decision-making.
Addressing the research objectives, the study performs a Pearson correlation between strategic planning and financial performance characteristics (Table 6).
| Table 6 Correlations | ||||||
| MF | EF | OF | FP | SPI | ||
| Managerial factors | Pearson Correlation | 1 | .460** | 0.065 | .524** | .466** |
| Sig. (2-tailed) | 0.000 | 0.541 | 0.000 | 0.000 | ||
| N | 92 | 92 | 92 | 92 | 92 | |
| Environmental factors | Pearson Correlation | .460** | 1 | .375** | 0.166 | .281** |
| Sig. (2-tailed) | 0.000 | 0.000 | 0.114 | 0.007 | ||
| N | 92 | 92 | 92 | 92 | 92 | |
| Organizational factors | Pearson Correlation | 0.065 | .375** | 1 | 0.042 | 0.020 |
| Sig. (2-tailed) | 0.541 | 0.000 | 0.688 | 0.848 | ||
| N | 92 | 92 | 92 | 92 | 92 | |
| Financial performance | Pearson Correlation | .524** | 0.166 | 0.042 | 1 | .355** |
| Sig. (2-tailed) | 0.000 | 0.114 | 0.688 | 0.001 | ||
| N | 92 | 92 | 92 | 92 | 92 | |
| Strategic planning intensity | Pearson Correlation | .466** | .281** | 0.020 | .355** | 1 |
| Sig. (2-tailed) | 0.000 | 0.007 | 0.848 | 0.001 | ||
| N | 92 | 92 | 92 | 92 | 92 | |
| **. Correlation is significant at the 0.01 level (2-tailed). | ||||||
The Pearson correlation exhibits that managerial factors and strategic planning intensity are highly correlated with a financial performance at 0.01 level. Further, the correlation value of positive 0.524 between managerial factors and financial performance indicates that the direction of this relationship is positive and moderate. In contrast, the relationship between strategic planning intensity and financial performance is positive but weak, with a correlation value of 0.355. It should also be noted that organisational factors and environmental factors have an insignificant relationship with financial performance as the p-value (sig value) is greater than the assumed level of significance.
Finally, based on the results of the correlation analysis, the study examines the influence of managerial factors and strategic planning intensity on financial performance. The overall regression model is significant at 0.01 level, F = 18.238, p < 0.01 (Table 7).
| Table 7 Anova | ||||||
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | Regression | 26.525 | 2 | 13.262 | 18.238 | 0.000b |
| Residual | 64.721 | 89 | 0.727 | |||
| Total | 91.245 | 91 | ||||
Moreover, the model exhibits an r-square of 0.291. That is, the strategic planning model is able to explain 29.1% of the variance in the performance of Jordanian firms. The adjusted R-square value is equal to 0.275, showing 27.5% of explained variance (Table 8).
| Table 8 Model Summary | ||||
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | 0.539a | 0.291 | 0.275 | 0.85276 |
| a. Predictors: (Constant), Strategic planning intensity, Managerial factors | ||||
The two independent variables, which were significant in the correlation analysis, are tested again in the regression analysis. According to the results, managerial factors are statistically significant at 0.01 level after controlling strategic planning. On the other hand, SP intensity, which was significantly associated with financial performance in the correlation results, has an insignificant impact on financial performance when controlled by managerial factors. It may also suggest that managerial factors mediate the link between SP intensity and FP (Table 9).
| Table 9 Coefficients | ||||||
| Model | Unstd. Coefficients | Std. Coefs | T | Sig. | ||
| B | Std. Error | Beta | ||||
| 1 | (Constant) | 1.124 | 0.479 | 2.345 | 0.021 | |
| Managerial factors | 0.420 | 0.093 | 0.458 | 4.541 | 0.000 | |
| Strategic planning intensity | 0.196 | 0.139 | 0.142 | 1.407 | 0.163 | |
| a. Dependent Variable: Financial performance | ||||||
Previous literature also suggests that strategic planning has a significant and positive impact on business performance in Jordan (Aldehayyat & Twaissi, 2011). Strategic planning provides a direction to organisations to expand and improve their performance (Arasa & Obonyo, 2012). However, previous research has also assessed a weak and limited influence of strategic planning on performance (Gică & Negrusa, 2011). It highlights the importance of other factors, such as managerial factors, which supports strategic planning.
The objective of the research study is to examine the link between SP and FP. For this purpose, the research studies the link between relevant SP-related factor and firm performance. These factors include managerial, organisational, and environmental factors and SP intensity. Based on the sample 92 respondents, the study finds a significant link between managerial factors and financial performance and SP intensity and financial performance. The regression analysis further confirms the influence of managerial factors, which also fully mediate the link between SP intensity and FP. Future research in the context of Jordan may consider more factors related to SP and greater sample size from the Jordan-based firms to find more accurate estimates.
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