Mugove Mashingaidze¹, More Chinakidzwa²

Abstract: Despite the positive role played by strategy formulation on the survival of small and medium enterprises (SMEs), little research has been conducted on the mediating role of strategy formulation approaches on the relationship between strategy formulation and financial performance of manufacturing SMEs in Zimbabwe. This study fills this knowledge gap by investigating the mediating role of strategy formulation approaches on the link between strategy formulation and financial performance in Zimbabwe. The study adopted a quantitative research approach in which empirical evidence was collected through structured questionnaires from 368 SME owner/managers in the manufacturing industry. Despite a positive and significant relationship between strategy formulation and financial performance, there was a statistically insignificant influence of strategy formulation on both short term and long term financial performance through the prescriptive approach. There was also a statistically insignificant influence of strategy formulation on both short term performance and long term performance through the descriptive approach. The implication for practice was derived from the outcome of the analysed data which suggests that SMEs would enhance their financial performance by using either of the approaches as long as they have the right strategy.

Keywords: descriptive approach; prescriptive approach; financial performance; small and medium enterprises, strategy formulation.

JEL Classification: M19; C12

1. Introduction

The beginning of the 21^st Century has seen many African countries fostering economic development through indigenous entrepreneurship through SMEs (Song Ng & Hung Kee, 2017; Makanyeza & Dzvuke, 2015). Many developed economies’ success has been due to the vibrant SMEs’ sector (Qamruzzaman & Jianguo, 2018). In this respect, SMEs are the economic heart of many countries (Qamruzzaman & Jianguo, 2018) as they create employment (Sibanda, Hove-Sibanda, and Shava 2018) and eliminate poverty at grassroots levels (Mashingaidze, Phiri & Bomani, 2021; Hettihewa & Wright, 2018). Many countries, including Zimbabwe, have supported the development of the SMEs sector (Derera, Croce, Phiri & O’Neill, 2020). However, the sector’s performance still falls short of supporting meaningful economic development (Mabenge, Ngorora-Madzimure & Makanyeza, 2020). An earlier study by Makanyeza and Dzvuke (2015) concluded that many SMEs shut down before their second year, despite the government’s policy interventions. Ahmed & Mukhongo (2017) concur and add that SMEs need to employ strategic management principles to survive and prosper in the current unstable macroeconomic environment. Given this background, Majama and Magang (2017) advise SMEs to adopt strategy formulation to enhance their performance. Mattheeusen and Spontak (2018) further argued that the dynamic nature of the African business environment forces businesses of all sizes to develop and adopt strategic responses to these challenges. Strategy formulation is an indispensable management tool that cushions SMEs from the volatile operating environment (Ralph, Williams Jr., Smith, Aaron, Manley & McDowell, 2020). Considering the slow growth of Zimbabwean SMEs (Mabenge et al., 2020), SMEs need to understand the value of strategy formulation in the success of their business (Sandada & Chikwama, 2016).

Strategy formulation has been one of the most significant aspects within the strategy domain (Donkor, Donkor & Kwarteng, 2018; Abosede, Obasan & Alese, 2016). Academics and practitioners widely recognise the importance of strategy formulation to SMEs worldwide (Damkea, Gimenezb & Damkeca, 2018). Previous research suggests that strategy formulation explains performance variations among SMEs. For example, Donkor et al. (2018) explored the influence of strategy formulation on performance across a sample of 200 manufacturing SMEs in Ghana. The study established that high-growth SMEs were involved in strategic planning of some sort. Auka and Langat (2016)’s study of Kenyan SMEs concluded that strategy formulation enhances performance. Nwachukwu, Chladkova and Fadeyi (2017) also confirmed the relationship in a meta-analysis study. These studies suggest that SMEs with robust strategy formulation frameworks perform better than SMEs with weak structures. However, many studies argue that the connection between strategy formulation and SMEs’ performance is complex as many factors come into play (Conz, Denicolal & Zucchella, 2017; Omsa, Ridwan & Jayadi, 2017). These scholars claim that the relationship is not likely to be straightforward. More precisely, they note that researchers need to consider the strategic approaches to predict effectively the nature of the relationship (Kumar, 2015; Conz et al., 2017). Strategy formulation approaches are the various methods used to arrive at a strategy. Besides the strategy approaches, context is important (Galbreath, Lucianetti, Thomas & Tisch, 2019). Many of the studies on strategy formulation in Africa have drawn samples from Nigeria (Abosede et al., 2016; Ogunsiji, 2012; Tiemo, 2012), Ghana (Donkor et al., 2018; Auka & Langat, 2016; Amoah-Mensah, 2011), and South Africa (Dubihlela & Sandada, 2014; Nkulu, 2012). Therefore, generalising results from these countries could be misleading because countries have different cultures, idiosyncrasies, and firms respond differently to different contexts (Galbreath et al., 2019). Strategy formulation is contextual, as market-specific knowledge is required (Omsa et al., 2017; Sheth, 2020; Mom, 2018). In this respect, Shu, De Clercq, Zhou and Liu (2019) calls for scholars to research in different and new contexts.

Given these research gaps, this paper makes two significant contributions. First, the paper takes a Zimbabwean perspective. Zimbabwe is a sub-Saharan African country that has experienced political and economic instabilities since 2000. The economic turbulence partly blamed on the land reform, poor political relations with the West, policy inconsistencies, and corruption has led to some large corporates’ closure, downsizing, and relocation. This departure of large corporates created enormous opportunities for SMEs in the manufacturing sector (Chinakidzwa & Phiri, 2020). However, the mediating role of strategic approaches in the nexus between strategy formulation and financial performance in such a turbulent environment remains unknown. This study seeks to plug that gap by providing empirical evidence in the Zimbabwean context. Secondly, within Zimbabwean SMEs’ context, the paper extends previous research that explores strategy formulation contingencies. While literature within the strategy formulation stream that explores the strategy formulation contingent is increasing (Donkor et al., 2018), none has empirically tested how strategy formulation approaches mediate the strategy formulation–firm performance relationship. Given the previous calls in literature, the study reveals the conditions under which strategy formulation influences financial performance. The paper offers managerial insights into which strategy formulation approach strengthens the strategy formulation-financial performance relationship. The paper further contributes by linking strategy formulation and financial performance. The evidence is vital for SMEs managers and owners to understand their strategy formulation processes’ implications.

The remainder of the paper is structured as follows. Section 2 provides an overview of the literature on SMEs and the study variables. Section 3 discusses the development of the study hypotheses and conceptual framework. Section 4 provides the research methodology, followed by Section 5, to discuss empirical findings. Section 6 presents the discussion and conclusion, and lastly, Section 7 provides the study’s limitations and directions for future research.

2. Theoretical Foundation

2.1. Strategy formulation

Many (Auka & Langat, 2016; Majama & Magang, 2017; Ahmed & Mukhongo, 2017; Mattheeusen & Spontak, 2018) have acknowledged the importance of strategy formulation. Strategy formulation is one of the driving pillars of strategic management (David & David, 2017). Mattheeusen and Spontak (2018) note that the terms “strategy formulation”, “strategy making”, “strategy development”, and “strategic planning” are interchangeably used to mean the same thing. David (2015:17) defines strategy formulation as “a logical activity that includes identifying opportunities and threats in the company’s environment and attaching some estimate of risk to the discernible”. However, Auka and Langat (2016:2) see it as “the process of selecting the most appropriate course of action for attaining organisational goals and objectives and, thus, facilitating the realisation of both long term and short term objectives”. Strategy formulation is how business strategies are created (Pratiwi, Sutopo, Zakaria & Rasli, 2017). Five significant activities regularly observed in strategy formulation include environmental scanning, developing the strategy purpose, establishing strategic objectives, integrating external and internal environmental data, and selecting strategy (David & David, 2017; Lynch, 2015). This study operationalises strategy formulation in terms of these five activities. Pratiwi et al. (2017) assert that firms should formulate strategy as the operating environment becomes increasingly complex. Strategy formulation enables firms to identify weaknesses and create stability despite a dynamic environment (Cokins, 2017; David & David, 2017; Ralph et al., 2020; Nwachukwu et al., 2017).

2.1.1. Strategy Formulation Approaches

The following sections present the two broad strategy formulation approaches.

2.1.2. Prescriptive Approach

The prescriptive approach, also known as the “rational”, the “deliberate”, the “planned” approach, is the traditional approach to strategy formulation (Kruger, 2018). The prescriptive approach mirrors Wheelen and Hunger (2014)’s Strategic Planning Model (SPM). According to Lynch (2015), deliberate planning makes uncertainties clear. It implies that the planning process is well thought out, and managers act intentionally and think before they consider alternatives (Jamil & Shar, 2015). David and David (2015) criticised this approach as it fails to take cognisance of the continually changing business environment’s realities. According to Cokins (2017), a prescriptive approach is limited to more developed and stable business environments.

2.1.3. Descriptive Approach

According to the descriptive approach, strategy formulation is often a less rational process (Thompson Jnr, Peteraf, Gamble & Strickland, 2016). Mintzberg et al. (2009:12) in Cokins (2017) note that “strategy often emerges as a cumulative pattern of actions that are only retrospectively rationalised and organised as a plan”. The descriptive approach is also labelled as “logical incrementalism”, “learning perspective”, “Intuitive Learning Model”, or the “emergent approach” (Lynch, 2015). This approach is rooted in the complexity theory (Thompson Jnr et al., 2016). The complexity theory holds that the future is unpredictable; hence planning is questionable (David & David, 2017). Due to the environmental complexity, strategy formulation cannot be rational, and strategies “result from manager’s daily response to problems or opportunities that were unforeseen by those engaged in the deliberate strategy-making process, at the time they were doing their analysis and planning” (Jamil & Shar, 2015:18). According to Kruger (2018), the descriptive approach leaves the strategy formulation process open and constantly shapes it. In this way, strategy formulation becomes more real. The descriptive approach is appropriate to SMEs because of their flexibility and adaptive learning (Cokins, 2017).

2.2. Financial Performance

The financial performance dimension is unquestionably one of the performance indicators in strategic management research (Pucci, Nosi & Zanni, 2017). Finance is the ‘heart’ of any business (Mageto, 2018), and any business decision is made according to its financial worth (Pucci et al., 2017). Therefore, many SMEs commonly use financial indicators (Burugo & Owour, 2017) to measure firm performance. Financial indicators can be short term (cash flows, profits, and sales revenue) or long term (growth in turnover, growth in profits and cash flow growth). This paper uses both short-term and long-term financial performance indicators. The paper argues that financial resources are valuable resources that enable firms to satisfy other non-financial goals such as reputation, expansion, and market share (Salloum, Azzi, Suissa & Khalil, 2016). Previous studies have adopted these indicators (Mabenge et al., 2020; Makanyeza & Dzvuke, 2015; Burugo & Owour, 2017; Pucci et al., 2017).

3. Conceptual Model and Hypotheses Development

The review of existing literature led to the development of the following conceptual model. The conceptual model is a pictorial representation of the proposed hypotheses and the relationships investigated in the broader research. Figure 1 summarises the proposed theoretical relationship between the variables under study.

Figure 1. Conceptual framework

Source: Authors’ own

3.1. Effect of Strategy Formulation on Financial Performance

Strategy formulation is considered a fundamental strategic management aspect that enhances firm performance, especially in the unstable and dynamic business world (Wahyuni & Ratnatunga, 2015; Auka & Langat, 2016). Earlier research work (Jones 1982, Bracker & Pearson 1986, Bracker et al. 1988) shows that successful SMEs appreciate the role of strategy formulation and make greater use of the strategy formulation tools such as SWOT analysis. Furthermore, Mattheeusen and Spontak (2018) and Germanos (2012) investigated the effect of strategy formulation on the financial performance of SMEs. They established that strategy formulation had a significantly positive influence on firm performance. Similarly, Qehaja, Kutllovci and Pula (2017) confirmed the overall positive effect of strategy formulation on SMEs’ long-term financial and short-term financial performance. In another study, Siddique (2015) concluded that strategy formulation significantly impacts overall SMEs’ performance. In Nigeria, Muogbo (2013) confirmed that strategy formulation significantly increased SMEs’ competitiveness and performance. Therefore, the study hypothesised that:

H1_a: Strategy formulation positively affects short-term financial performance perceptions of small and medium manufacturing enterprises in Zimbabwe.

H1_b: Strategy formulation positively affects long-term financial performance perceptions of small and medium manufacturing enterprises in Zimbabwe.

3.1. Mediating Effect of Strategic Approaches on the Strategy Formulation and Short-Term Financial Performance Relationship.

Extant research (Toyin et al. 2016; Bozkurt & Kalkan, 2013; Maritz, 2010) supports the claim that successful SMEs adopt a more descriptive than prescriptive strategy formulation approach. Verreynne (2006) found that SMEs who use the emergent and individualist approach to strategy had a strong and positive relationship with the firms’ financial performance. Bozkurt and Kalkan (2013) concluded that Turkish SMEs adopting the emergent approach have better short-term financial performance than those employing a more prescriptive strategy approach. Toyin et al. (2016) suggest that an emergent approach to strategy is particularly suitable for SMEs to enhance their short-term financial returns. However, another stream of research shows that SMEs with highly sophisticated and rational planning processes show more significant growth in sales and profits than those without formalised processes (Robinson & Pearce cited in Khan & Khalique (2014). In Australia, Kraus et al. (2007) concluded that the extent to which SMEs formalised strategy formulation influenced performance. Kraus et al. (2007) observed that SMEs with highly formalised strategy systems had a chance to belong to the high-growth firms’ group. Aremu and Oyinloye (2015) confirmed the positive relationship between rational approach and financial performance in Nigeria. These competing findings leave a gap in understanding the linkage between strategic approaches and firm performances in different contexts. Therefore, the study hypothesises that:

H2_a: The prescriptive approach mediates the relationship between strategy formulation and short-term financial performance perceptions.

H2_b: The descriptive approach mediates the relationship between strategy formulation and short-term financial performance perceptions.

3.3. Mediating Effect of Strategic Approaches on the Strategy Formulation and Long-Term Financial Performance Relationship

Harshim (2016) concluded that SMEs that employ more descriptive approaches are much concerned with reality; hence they can perform better in the long run than those using more deliberate approaches. Elshamly (2013) suggest that SMEs with an emergent planning process fail to reap the benefits of these efforts in the long term, while Germanos (2012) claim that SMEs using sophisticated planning activities (including written business plans) enhance their long-term performance. In Romania, Gica and Balint (2012) concluded that the prescriptive approach to strategising enhances the long-term financial performance of SMEs. A study of UK SMEs by Kraus, Reiche and Reschke (2013) concludes that SMEs adopting more formal planning systems can witness long-term growth and performance. Therefore, this study posited that:

H3_a: The prescriptive approach mediates the relationship between strategy formulation and long-term financial performance.

H3_b: The descriptive approach mediates the relationship between strategy formulation and long-term financial performance.

4. Research Methodology

The study focused on understanding the mediating influence of the strategy approaches on the relationship between strategy formulation and financial performance perceptions among manufacturing SMEs in Harare, Zimbabwe. In this respect, a quantitative research approach was the most appropriate. This approach also used the cross-sectional design, which involved collecting data in a particular period. Data for the study was gathered in the period February to April 2019. The study drew its sample from a pool of manufacturing SMEs registered with the Small and Medium Enterprises Department of Zimbabwe. The population comprised 9 242 SMEs. The researchers used Yamane (1967) formula to determine the sample size of 368 SMEs. Despite being old, the formula is still dependable and widely acceptable in academic researches (Anyanga & Nyamita, 2016; Kowo et al., 2018). A stratified random sampling technique was used to select respondents for the study. The use of a stratified sampling technique enabled the researchers to divide the manufacturing SMEs into five strata based on their outputs: 1) food products, 2) clothing and footwear, 3) wood and furniture, 4) chemical and petroleum, and 5) metals (Mashingaidze et al., 2021).

The design of the questionnaire was based on literature (Singh, 2009; Sandada, 2015; Wheelen and Hunger, 2014; Yazdani, 2010; Germanos, 2012; Papulova & Papula, 2014). The questionnaire had four major sections: sample profile, strategy formulation, approaches, and financial performance. Section A collected the sample profile data on the five variables, namely gender, age, level of education, the sector in which the firm operates, and the annual revenues. Section B collected data about respondents’ attitudes towards strategy formulation. The strategy formulation constructs were measured using twenty items adapted from previous studies (Singh, 2009; Sandada, 2015; Sandada et al., 2016; Wheelen & Hunger, 2014). Section C solicited the participants’ data relating to their strategic approaches. The study further adapted ten items from Yazdani (2010), Germanos (2012) and Papulova and Papula (2014). The use of previously used items strengthened the credibility and validity of the research and its findings. Section D collected financial performance data, i.e., short-term financial performance and long-term financial performance. The study adopted subjective measures of financial data as many SMEs are reluctant to report objective and sensitive information (Makanyeza & Dzvuke, 2015; Burugo & Owour, 2017). On sections B, C and D, a five-point Likert scale was used, ranging from one (strongly disagree) to five (strongly agree) to express their level of agreement.

The researchers’ hand-delivered questionnaires to owners/managers as they held the enterprises’ overall responsibility. These managers have comprehensive information about the SME (Makanyeza & Dzvuke, 2015). A month was given to respondents to complete the questionnaires, after which follow-ups were made through telephone calls. Ultimately, 289 out of the 368 distributed questionnaires were usable, giving a response rate of 78.5 %. Baruch (1999, p. 422) in Derera (2015), “there is no u agreed norm as to what is or what may not be perceived as an acceptable and reasonable response rate”. However, Dillman (2000) suggest that 50% is the minimum level. The study’s response rate is far above the minimum of 50%.

5. Presentation of Results

A total of 289 usable questionnaires were received. The data was captured on a Microsoft Excel spreadsheet and uploaded to the SmartPLS3.2.1. A partial least squares (PLS) algorithm was run before bootstrapping. The PLS-SEM has high statistical power that is useful in a less developed or developing theory (Hair et al., 2019); therefore was ideal in the study. Bootstrapping is a nonparametric procedure used to test for mediation (Ramaya, Cheah, Chuah, & Memon, 2018). Preacher and Hayes (2008:886) add, “bootstrapping provides the most powerful and reasonable method to obtain confidence limits for specific indirect effects under most conditions”.

Two sections present the study’s results. The first section provides the measurement model assessment illustrating the results of indicator loadings, reliability tests (composite reliability), convergent validity, and discriminant validity. Lastly, the structural model assessment, collinearity tests, coefficient of determination (R²) and statistical significance are shown. This order was crucial because the measurement model must be satisfactory before assessing the structural model (Hair et al., 2019, p. 8).

5.1. Measurement Model Assessment

Results to assess the measurement model are presented in sections 5.1.1 to 5.1.4.

5.1.1. Indicator Loadings

The factor loadings (and cross-loadings) of all indicator items to their respective latent constructs are shown in Table 1.

Table 1. Factor Loadings (Bold) and Cross-Loadings

Factor loadings above 0.70 are recommended as they signify that the construct describes more than 50% of the indicator’s variance, thus providing acceptable item reliability (Hair et al., 2019, p. 8). The results in Table 1 shows all items loaded on their corresponding constructs (bolded factor loadings) from a lower bound of 0.56 to an upper bound of 0.92. Although SF12 loaded below the recommended 0.70, a loading of 0.56 was considered close to 0.60, acceptable in exploratory studies (Hair et al., 2019:15). However, loadings of 0.60 are acceptable in exploratory again; SF12 loaded higher on its respective construct than any other construct (i.e. the non-bolded factor loadings in any one row). Although SF12 was below the recommended factor loadings, it was left in the model because it satisfied other quality tests.

5.1.2. Reliability Tests

The composite reliability was adopted to test for internal consistency. The composite reliability is a better measure of reliability than the Cronbach’s alpha, a less precise measure of reliability in unweighted items (Hair et al., 2019, p. 8). In assessing composite reliability, high values show high levels of reliability. However, values above 0.95 and higher are problematic as they indicate item redundancy, reducing construct validity. High values may also indicate other problems, such as straight-lining, which trigger inflated correlations. Therefore, Hair et al. (2019, p. 8) regard values ranging from 0.60 and 0.70 as “acceptable in exploratory research” and values ranging from 0.70 and 0.90 as “satisfactory to good”.

The results for internal consistency reliability assessments are shown in Table 2.

Table 2. Composite Reliability, Correlations and Discriminant Validity

*SF= strategy formulation; PA= prescriptive approach; DA=descriptive approach; STFP=short-term financial performance; LTFP=long-term financial performance.

The results in Table 2 indicate that all items measured well on the composite reliability and the average variance extracted (AVE) tests. The composite reliabilities of the different measures in the model range from 0.70 to 0.955, which surpassed the acclaimed threshold value of 0.70 (Nunnally, 1994). However, the prescriptive approach variable fall into the problematic range of 0.95 and above (Hair et al., 2019, p. 8). The researchers did not do anything to the variable because the value marginally exceeded 0.95, satisfying the AVE test.

5.1.3. Convergent Validity

The AVE tests were conducted to provide evidence of convergent validity (Fornell & Larcker, 1981). Convergent validity refers to the model’s capacity to explain the indicator’s variance. Bagozzi and Yi (1991) suggest an AVE threshold level of 0.5 as a signal of convergent validity. This means the construct explains at least 50% of the variance of its items (Hair et al., 2019). Therefore, measures of the five constructs have high levels of convergent validity, as shown in Table 2.

5.1.4. Discriminant Validity

Discriminant validity is ‘the degree to which a construct is empirically different from other constructs in the structural model’ (Fornell and Larcker 1981). According to Fornell and Larcker (1981), “each construct’s AVE should be matched to the squared inter-construct correlation (as a measure of shared variance) of that same construct and all other reflectively measured constructs in the structural model”. The shared variance for all model constructs must not be higher than their AVEs. An acceptable AVE should be “0.50 or higher, indicating that the construct explains at least 50 per cent of the variance of its items” (Hair et al., 2019, p. 8).

The results for discriminant validity shown in Table 2 met Fornell and Larcker (1981) and Hair et al. (2019:8) recommendations that the AVE for each measure must exceed 0.50 to provide evidence of discriminant validity. In addition, all the square root values of AVE are larger than their corresponding correlations, therefore meeting the discriminant validity test, as prescribed by the Fornell-Larcker Criterion. The bolded elements in the matrix diagonals, representing the square roots of the AVEs, are larger in all cases than the off-diagonal elements in their matching row and column, supportive of the discriminant validity of the scales.

5.2. Structural Model Assessment

The results for structural model assessment are presented in the following sections.

5.2.1. Collinearity Tests

Results of analysis can be decreased when variables are highly correlated (Ryuta, et al., 2019). Collinearity can be measured using the variance inflation factor (VIF). However, there is no generally accepted classification of high VIF. For example, Hair et al. (2019:11) considered VIF values above 5 to indicate probable collinearity issues among the predictor constructs. Hair et al. (2019:11) further suggested that even lower VIF values of 3–5 may indicate collinearity problems and recommended values close to 3 or lower. However, (Chatterjee & Hadi, 2012) considered VIF above 10 problematic, whilst (Akinwande, Dikko, & Samson, 2015) view values between 5 and 10 as problematic whilst those above 10 show high multicollinearity. Therefore, low VIF values close to 1 are generally acceptable.

The results of collinearity tests (Appendix 1) using the VIF criterion showed that SF, LTFP and STFP had VIF values <2, thereby satisfying the recommendations of Hair et al. (2019). However DA and PA items had VIF values <5 except PA5. Although high, these VIF values are within acceptable values (Akinwande et al., 2015; Chatterjee & Hadi, 2012; Bagozzi et al.,1991).

5.2.2. Coefficient of Determination (R²)

Further, the R² value of endogenous constructs was examined since collinearity was not a problem. The R² ranges from 0 to 1, with high values indicating a large explanatory power. Although the interpretation of R² is contextual R² values of 0.75, 0.50 and 0.25 are regarded as substantial, moderate and weak, respectively (Hair et al., 2019:11). The results indicated that all the constructs had R² values below 0.25. This means the variables had weak explanatory power.

The results further revealed a small effect size in all the variables. All f² values were <0.15. According to Cohen (1988), cited by Hair et al. (2019), f² values higher than 0.02, 0.15 and 0.35 represent small, average and big f² effect sizes. The highest (although low compared to standard) coefficient f² values were recorded on strategy formulation. Strategy formulation had an f² coefficient of 0.099 on short-term performance and an f2 value of 0.077 on long-term performance, indicating a small effect size.

5.2.3. Hypothesis Testing: Statistical Significance

Table 3 shows the results of the PLS-SEM. The table shows that strategy formulation directly influences both short term and long-term performance.

Table 3. Summary: Significance Testing Results of the Structural Model Path Coefficients.

The results in Table 3 show that strategy formulation exhibited a statistically significant influence (t=6.09, p<0.001) and (t=5.19, p<0.001) on short-term performance and long-term performance, respectively. However, there was a statistically insignificant influence of strategy formulation on short-term performance (t=0.012, p>0.991) and long-term performance (t=0.009, p>0.993) through the prescriptive approach, respectively. There was also a statistically insignificant influence of strategy formulation on both short-term performance (t=0.137, p>0.891) and long-term performance (t=0.288, p>0.774) through the descriptive approach. Therefore, the results show that only hypotheses H1a and H1b were accepted. Further, the bootstrapping analysis has shown that all the four indirect effects,  = -0.002,  = 0.000,  = 0.008,  = 0.000, are insignificant with t-values of 0.137, 0.012, 0.288 and 0.009 respectively.

6. Discussion and Conclusions

The study explains the extent to which an SME’s strategy formulation influences its short term and long term financial performance. Strategy formulation exhibited a statistically significant influence (t=6.12, p<0.001) and (t=5.19, p<0.001) on short-term performance and long-term performance, respectively. Thus, the results of the strategy formulation–financial performance (H1a-b) support the study expectations that strategy formulation enhances the financial performance of SMEs, i.e. (H1a) short-term financial performance and (H1b) long-term financial performance. These findings are broadly consistent with prior research studies that also established that strategy formulation has a significant and positive impact on the financial performance of SMEs (Auka & Langat, 2016; Adeyemi, Isaac & Olufemi, 2017; Majama & Magang, 2017; Donkor et al., 2018; Mattheeusen & Spontak, 2018). The results illustrate that Zimbabwean SMEs should prioritise strategy formulation since it enhances financial performance. The results further provided evidence that strategy formulation contributes to performance in dynamic environments (Sandada & Chikwama, 2016; Auka & Langat, 2016) such as Zimbabwe. Operating in a dynamic, unstable environment such as Zimbabwe requires the formulation of breakthrough strategies. Strategy development represents an avenue for establishing a competitive edge. In this regard, SMEs in turbulent environments are called to define their business strategy to navigate the stormy waters. The results further justify the financial value added by the five strategy formulation activities as adapted from De Wit and Meyer, (2014) study in a highly turbulent environment. This methodology, grounded in strategic management, requires SMEs to continuously search and seize new ideas and integrate and orchestrate their resources with their environs to stay competitive and yield financial growth. This is particularly crucial to SMEs because of their sensitive competitive market positions and limitations vis-a-vis their large enterprises. Our results further enrich evidence of the purported positive impact of strategy development on the financial performance of SMEs (Adeyemi et al., 2017; Majama & Magang, 2017; Mattheeusen & Spontak, 2018; Donkor et al., 2018).

This study further advances the current body of the strategy development-financial performance relationship by testing the mediating effects of the firm’s strategic approaches: descriptive and prescriptive approaches. There was a statistically insignificant influence of strategy formulation on short term performance (t=0.012, p>0.991) (H2_a) and on long term performance (t=0.009, p>0.993) (H3_b) through the prescriptive approach. There was also a statistically insignificant influence of strategy formulation on both short term performance (t=0.137, p>0.891) (H2_b) and long term performance (t=2.88, p>0.774) (H3_a) through the descriptive approach. These findings mean no statistically significant evidence supports the mediation effect through either prescriptive or descriptive approaches. Findings from the study revealed that both strategic approaches do not affect the relationship between strategy formulation and SMEs’ financial performance either on a long-term or short-term basis. These findings contradict existing literature supporting the mediation effect of strategic approaches to financial performance (Toyin et al., 2016; Harshim, 2016). The study concludes that evidence on the mediation effect remains inconclusive. The inconsistencies in past research findings support this; for example, Toyin et al. (2016); Harshim (2016), Aremu and Oyinloye (2015) established that descriptive approach significantly influences the financial performance of SMEs while other researchers such as Aremu and Oyinloye (2015), Germanos (2012), Kraus, Reiche and Reschke (2013) found that prescriptive approach positively influences SMEs’ long term financial performance. The study’s findings illustrate that by combining the deliberate, prescriptive process of the design school and the adaptive, descriptive learning process of the learning school, more fertile financial results can be obtained. The study concludes that irrespective of the strategic approach employed, the financial performance of SMEs is enhanced by strategy formulation.

The study was driven by the need to understand the strategy formulation financial performance relationship among SMEs. A comprehensive understanding of this relationship is indispensable for improving the financial performance of SMEs operating in dynamic environments. In order to improve the performance of SMEs through strategising, caution must be taken when it comes to strategic decisions. The study established that strategy formulation-firm financial performance relationship is stronger irrespective of the strategic approach employed. The study concludes that enterprises should use either of the two approaches when formulating their strategies to improve financial performance. There is a statistically insignificant influence of strategy formulation approaches on the strategy formulation-financial performance relationship. In this case, the study recommends that SMEs consider contingencies that enhance strategy formulation to increase both short-term and long-term financial performance. These contingencies may include firm resources, the competitive environment, and the strategies used, among others. The significant role of contingencies needs to be addressed because of their direct impact on financial performance from a strategic perspective.

7. Limitations and Future Studies

Despite the importance of this study, the results of the current study could be biased because the mediation effect was tested using cross-sectional data. Mediated models contain causal paths that imply time passage; therefore, using cross-sectional data can produce biased results (Ramaya, Cheah, Chuah, & Memon, 2018). Therefore, a longitudinal survey would be ideal for testing the mediation effect of strategic approaches. Although examining financial performance is predominant in strategic management studies, it may not be the most appropriate construct to study the impact of strategy formulation on the performance of SMEs (Soto Acosta, Colomo-Palacios & Loukis, 2011). This is particularly crucial in the SMEs sector due to difficulties in measuring financial performance, but they might be seen through the non-financial performance indicators created for the SMEs’ stakeholders in the longer term (Rashidirad & Salimian, 2020). The study suggests that future researchers need to consider assessing firm performance using both financial and non-financial performance.

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Appendix 1