Skills and Strategic Planning: Unveiling the Nexus in SMEs - A Case Study

Introduction

The contemporary economic landscape is intricately woven with the diverse threads of small and medium-sized enterprises (SMEs), forming an indispensable fabric in the tapestry of national economic development. Extensive literature attests to the pivotal role played by SMEs in driving economic growth, reducing poverty, fostering wealth creation, ensuring social stability, promoting local development, and catalyzing job creation in both developed and developing countries (Wadho & Chaudhry, 2018; Wijaya & Irianto, 2018).

The recognition of SMEs as key contributors to Gross Domestic Product (GDP) is underscored by their significant employment generation and local GDP impact. In Europe, for instance, SMEs account for almost two-thirds of employment and local GDP (Jonas, Roth, & Möslein, 2016). Japan, a stalwart in the global economic landscape, attributes a staggering 99% of its business landscape to SMEs, generating 71% of employment and contributing 55.3% to the local GDP. Similarly, China, a burgeoning economic force, hosts 99% of SMEs, contributing 60% to its local GDP and constituting 75% of total employment. In the context of Indonesia, SMEs make up 95% of domestic businesses, providing 99% of job opportunities annually and contributing 57% to the GDP (Radanliev et al., 2019; Ullah, 2017). This collective evidence underscores the substantial contributions of SMEs to economic development worldwide.

Pakistan, as one of the developing nations, has witnessed the commendable growth of its SME sector, representing approximately 90% of all businesses and contributing 40% to the national GDP (SMEDA, 2019). A closer examination reveals that 3.2 million SMEs are registered in Pakistan, with 65% of them located in Punjab, the most populous province (SMEDA, 2019). Despite the sheer magnitude of SMEs in Pakistan, the sector grapples with a disconcerting failure rate of 80% (Dar, Ahmed, & Raziq, 2017; Tehseen & Ramayah, 2015; Zafar & Mustafa, 2017). This failure rate, however, pales in comparison to the GDP contributions of neighboring countries, such as China and India, which boast 58.5% and 46%, respectively (Zafar & Mustafa, 2017). This disjuncture prompts a critical examination of the factors influencing SME performance in the Pakistani context.

The economic trajectory of any nation is intricately linked to the performance of its SMEs, aptly designated as the drivers for national development and significant contributors to domestic economic growth (Khurrum S. Bhutta, Rana, & Asad, 2008). In the Pakistani context, SMEs constitute a formidable force, representing around 90% of all businesses and contributing 40% to the national GDP (SMEDA, 2019). However, a closer inspection reveals a stark reality — the 80% failure rate among SMEs in Pakistan (Dar et al., 2017; Tehseen & Ramayah, 2015; Zafar & Mustafa, 2017). This dismal performance raises crucial questions about the factors influencing SME success in Pakistan.

Empirical studies suggest that various internal and external factors play a pivotal role in determining SME success in Pakistan. Factors such as innovation, entrepreneurial orientation, organizational culture, capabilities, market orientation, individual personality, and employee behavior have been identified as indicators of better firm performance (Dar et al., 2017; Ismail et al., 2014; Peralta-Yahya et al., 2012; Skokan et al., 2013; Syed et al., 2012). However, the empirical literature is notably silent on the role of multiple skills in the success of SMEs, creating a significant gap in understanding their impact on firm success and organizational planning.

While literature underscores the importance of physical assets, particularly skills, in organizational growth (Amir, Auzair, & Amiruddin, 2016; García-Sánchez et al., 2017), the specific role of multiple skills in the success of SMEs remains unexplored. The scarcity of research in this area poses challenges for both researchers and firms, leading to study findings based on an inaccurate allocation of resources and non-directional planning (Ahmad et al., 2018). To bridge this gap, this study focuses on linking the importance of multiple skills and strategic planning to SME performance in the context of Punjab, Pakistan.

Skills, recognized as a pivotal construct in the paradigm of business performance (Kunene, 2009), have been acknowledged by scholars and practitioners as crucial elements for organizational success (Shute, Ventura, & Ke, 2015; Singh, 2003; Teece, 2007). Multiple skills not only position organizational creativity but also contribute to the ideation of unique ways in generating vision, managing resources, and operationalizing organizational activities (Smith et al., 2006). However, the specific impact of multiple skills as a resource and competitive advantage on firm performance through strategic organizational insights remains largely unexplored.

Therefore, this study sets out to address this research gap by exploring the antecedents of SMEs in Punjab, Pakistan, focusing on the relationship between technical skills, managerial skills, entrepreneurial skills, business skills, strategic planning, and SME performance. This study also addresses the questions guiding this exploration: What is the relationship between technical skills, managerial skills, entrepreneurial skills, business skills, and strategic planning of SMEs in Punjab, Pakistan? and how does strategic planning mediate the relationship between technical skills, managerial skills, entrepreneurial skills, business skills, and the performance of SMEs in Punjab, Pakistan? However, This study examined the relationship between technical skills, managerial skills, entrepreneurial skills, business skills, and SMEs in Punjab, Pakistan, through the mediating effect of strategic planning.

The study aligns itself with the Resource-Based View (RBV) theory, a theoretical framework renowned for its emphasis on the strategic management of resources to achieve sustained competitive advantage (Barney, 1991; Peteraf, 1993; Wernerfelt, 1984). According to the RBV, firms gain a competitive advantage by acquiring and deploying valuable, rare, and non-substitutable resources that are difficult for competitors to replicate (Barney, 1991; Peteraf, 1993). In the context of this study, skills and strategic planning are considered valuable and non-substitutable resources that can contribute to SME performance.

This study contributes to both theoretical and practical domains. Theoretically, it extends the existing literature by investigating the relationship between multiple skills, strategic planning, and SME performance in the specific context of Punjab, Pakistan. The empirical evidence generated by this study adds depth to the understanding of the role played by skills and strategic planning in the success of SMEs, providing a nuanced perspective that can inform future research endeavors.

Practically, the study offers valuable insights for SME owners and managers in Punjab, enabling them to recognize the significance of cultivating diverse skills and effective strategic planning for enhanced performance. Government agencies and policymakers can benefit from the findings by formulating policies that promote skill development and strategic planning among SMEs, fostering an environment conducive to their sustained growth and contribution to the national economy.

Literature Review And Hypotheses Development

Resource-Based Theory (RBV)

Werner Felt introduced the Resource-Based Theory (RBV) in 1984, linking organizational performance to resources and capabilities (Barney, Wright, & Ketchen Jr, 2001). RBV posits that a firm's competitive advantage is derived from its unique capabilities and resources, exploring why some firms outperform others (Bharadwaj, 2000; Conner & Prahalad, 1996).

Organizational resources, both tangible and intangible, include human capital, technology, marketing, and financial resources (Barbosa & Cintra, 2012; Barney et al., 2001). These resources, according to RBV, are crucial internal tools that generate competitive advantages and contribute to organizational development (J. Barney et al., 2001; Tippins & Sohi, 2003).

RBV emphasizes the alignment and utilization of resources, such as skills, capabilities, and strategic planning (Cintra & Barbosa, 2012; Kunene, 2009). Only resources that provide a competitive advantage can contribute to organizational success, highlighting the importance of valuable, rare, inimitable, and non-substitutable resources (Barney, 1991).

Human capital and skills, enabling the execution of unique strategies, play a vital role in achieving organizational performance (Barney, 1991). Porter (1980) asserts that firms must identify goals, obtain resources, and create a balance between skills, capabilities, and the strategic environment for enhanced performance (Al-Dhaafri et al., 2013; Geldermann et al., 2016).

Employees' expertise and skills are considered organizational tools that enhance credibility, facilities, and brand reputation, making them strategic resources for organizational objectives (Kunene, 2009). Tangible and intangible resources, including skills, capabilities, assets, brand reputation, and technology, contribute to organizational success (Lan & Wu, 2010; Ren et al., 2015; Snell, 2009).

This study aligns with RBV, exploring the impact of technical, managerial, entrepreneurial, and business skills on organizational performance. Skills, as primary sources of competitive advantage, are crucial for sustaining success in a competitive market (Kee-Luen et al., 2013). Strategic planning, coupled with skills, is identified as a source of extraordinary results for improved performance, solidifying RBV as the underpinning theory of this study. The following are the hypotheses developed based on the research model in this study.

Relationship between Technical Skills and Strategic Planning

Ahmad et al. (2021) concluded that Technical Skills (TS) drive innovation in product development, aligning with a strategic planning perspective. Entrepreneurial style becomes a key component of performance and innovation, especially in SMEs, where owners or managers play a pivotal role in building strategies and setting goals. Technical skills assist in strategy formulation, implementation, and achievement of objectives at the product production level (Daley, 2012; Helfat & Peteraf, 2015; Hitt, Ireland, Camp, & Sexton, 2001).

Previous studies indicate that TS is directly related to strategic product building and enhanced performance (Hysong, 2008). Technical skills enable understanding technology, engineering work, emulation, and direction of technology, fostering innovative product development and technical idea enhancement within the organization (Hysong, 2008; Wani et al., 2003; Wijaya & Irianto, 2018). Kunene (2009) emphasized the critical nature of technical skills, especially at the business's start, influencing technology's role in enhancing strategic implementation.

The better performance of an organization is reflected in achieving goals and objectives by adopting multiple technical skills, operationalizing a productive technical system, innovating quality products, and entering the market effectively (Kunene, 2009). Strategies facilitate access to supply, raw material skills, and support the development of innovative, high-quality products (W. Smith et al., 2007). The relationship between strategic practices and new ideas, creative processes, operations, and technical leadership positively impacts business operations (Smith et al., 2007; Smith, Besharov, Wessels, & Chertok, 2012). In conclusion, the hypothesis is formulated as follows:

H1 : Technical skills have a positive influence on the strategic planning of organizations.

Relationship between Managerial Skills and Strategic Planning

Managerial skills predict organizational future planning, paving the way for effective strategy implementation (Tonidandel et al., 2012). Effective management of a firm's resources contributes to achieving organizational goals and objectives (Aliyu, 2015). Strategic planning practices are crucial for performance (Arasa and K'Obonyo, 2012). The development of organizational capabilities and strategies, especially in SMEs, plays a significant role in product innovation and performance (Ahmad et al., 2021).

Managerial skills significantly impact strategy development, guiding the organization through planning, organizing, managing, marketing, legal and financial positioning, and administrative roles (Aliyu, 2015; Hysong, 2008; Pansiri & Temtime, 2008). Kunene (2009) contends that managerial skills encourage strategic practices, exhibiting a positive relationship with strategic planning. Therefore, the hypothesis is postulated as follows:

H2: Managerial skills have a positive influence on the strategic planning of organizations.

Relationship between Entrepreneurial Skills and Strategic Planning

Entrepreneurial skills vary significantly, with owners/managers considering them as strong assets (Carter & Tamayo, 2017). These skills are instrumental in turning ideas into valuable products (Peters, 2005). Ahmad et al. (2018) emphasize the significant relationship between strategic planning and organizational capabilities and skills. Turning ideas into valuable products requires planning and strategies (Mohammed & Obeleagu-Nzelibe, 2014).

Large organizations with strategic practices serve as role models for small and medium enterprises (SMEs). Entrepreneurial practices, including building strategies, setting objectives, and developing skills for finding business opportunities, risk-taking, creativity, and innovation, are crucial in SMEs (Ahmad et al., 2020). Therefore, the hypothesis is formulated as follows:

H3: Entrepreneurial skills have a positive influence on the strategic planning of organizations.

Relationship between Business Skills and Strategic Planning

Business skills are essential resources for organizations, helping in day-to-day operations (Afolabi & Macheke, 2012). These skills encompass formulating business plans, operations, goal setting, time and resource planning, plan development for resource utilization, establishing internal and external relationships, HR management, business systems, and performance (Afolabi & Macheke, 2012). Strategic planning is integral to planning development and guides daily operations in organizations (Ansah, 2017).

Literature on measuring business skills and strategic planning among SMEs is scarce, with such practices more common in large multinational organizations. Therefore, it is crucial to investigate the relationship between business skills and strategic planning. The hypothesis is postulated as follows:

H4: Business skills have a positive influence on the strategic planning of organizations.

Relationship between Strategic Planning and Performance

Strategic planning involves choosing goals, setting objectives, and deciding how to achieve them (Arasa & K'Obonyo, 2012). Strategic planning positively affects organizational performance, both financial and non-financial (Ahmad et al., 2020). SMEs can benefit from strategic planning by avoiding missteps and achieving their objectives (Ansah, 2017).

The hypothesis is formulated as follows:

H5: Strategic Planning has a significant effect on enterprise performance among SMEs in Punjab, Pakistan.

Mediating Role of Strategic Planning

Prior literature shows a positive relationship between technical, managerial, entrepreneurial, and business skills with firm performance (Ahmad & Ahmad., 2018; Ahmad et al., 2020; Smith et al., 2007). However, the black box between these variables and firm performance remains unclear and under-researched. Therefore, the study focuses on the indirect effect of multiple skills on firm performance, considering strategic planning as a mediator.

Strategic planning serves as a mediator in the relationship between technical, managerial, entrepreneurial, and business skills and firm performance (Kylaheiko et al., 2016; Lengnick-Hall & Lengnick-Hall, 1988; D. Miller et al., 2015; Mohammed & Obeleagu-Nzelibe, 2014). In the context of SMEs, where the practice of multiple skills is limited, other variables need incorporation to explain firm performance.

The hypotheses are formulated as follows:

H6: Strategic Planning mediates the relationship between technical skills and enterprise performance among SMEs in Punjab, Pakistan.

H7: Strategic Planning mediates the relationship between managerial skills and enterprise performance among SMEs in Punjab, Pakistan.

H8: Strategic Planning mediates the relationship between entrepreneurial skills and enterprise performance among SMEs in Punjab, Pakistan.

H9 : Strategic Planning mediates the relationship between business skills and enterprise performance among SMEs in Punjab, Pakistan.

These hypotheses are testable and measurable statements that will be validated through the collection of questionnaire data in this study.

Theoretical Framework

The theoretical framework integrates previous studies and research findings relevant to technical skills, managerial skills, entrepreneurial skills, business skills, strategic planning, and SMEs' performance in Punjab, Pakistan. The model explores the relationships between these variables and incorporates strategic planning as a mediator. This framework provides the theoretical foundation for the study, aiming to investigate the impact of these variables on SMEs' performance, particularly in a developing country like Pakistan. The relationships within this model will be tested using collected data to contribute new insights to the understanding of these relationships in the context of SMEs.

Figure 1.Research Framework of the Study

Methodology

Research Design

The research design serves as the blueprint for conducting a systematic and scientific study (Macdonald & Headlam, 2009). The choice of a suitable research design aligns with the study's objectives and context (Ahmad et al., 2020). In this study, focused on examining the performance of SMEs and understanding the relationship between technical skills, managerial skills, entrepreneurial skills, business skills, and SME performance with the mediating effect of strategic planning, a survey design was deemed appropriate. The survey design aligns with previous relevant studies (Kunene, 2009; Ahmad et al., 2020; Ahmad et al., 2021; Smith et al., 2006).

Data Collection

The study employed empirical research through quantitative techniques, involving the systematic empirical investigation of observable phenomena using mathematical, statistical, and computational methods (Hamann et al., 2013; Li et al., 2008; Ahmad et al., 2020). A cross-sectional research setting was chosen, involving data collection from selected respondents over a six-month period (Macdonald & Headlam, 2009). The unit of analysis was the owners/managers of SMEs in Punjab, Pakistan, representing the firms and being key participants in the study.

Population and Sample Size

The population of the study comprised small and medium enterprises (SMEs) operating in Punjab, Pakistan. The total SMEs in Pakistan were 3.2 million, with 65% located in Punjab (SMEDA, 2019). The sample size calculation, based on a confidence interval of 95%, resulted in a sample size of 384, deemed suitable for structural equation modeling (SEM) analysis (Mendenhall et al., 1993; Lei & Lomax, 2005). The sampling technique used was proportional stratified sampling, considering the different sectors (manufacturing, service, agriculture) and ensuring representation from each.

Unit of Analysis

The unit of analysis for this study was the SMEs, and the respondents were owners/managers who were invited to participate in the study. This choice was made due to their representation of the firms and their involvement in key operations (Ab Rahman & Ramli, 2014; Zahra & Covin, 1995).

Sampling Technique

A single respondent approach was employed, given its suitability for firms of all sizes (Uma Sekaran & R Bougie, 2016). The sample was collected through probability sampling using a proportionate stratified sampling technique. The strata considered were the different industry sectors, and the sample size from each sector was determined proportionately.

Questionnaire Design and Measurement of Variables

A five-point Likert scale was adopted for the questionnaire items, offering respondents a midpoint for more precise responses (Nazlina, 2016). The questionnaire, consisting of 100 items, covered six constructs: firms’ performance, technical skills, managerial skills, entrepreneurial skills, business skills, and strategic planning. The questionnaire underwent pre-testing, expert validation, and modifications for clarity and relevance.

Reliability and Validity

Reliability was assessed using Cronbach’s alpha coefficient, resulting in a high-reliability standard ranging from 0.72 to 0.95. Validity was examined through exploratory factor analysis (EFA) and face validity. The factor analysis ensured inter-item reliability and consistency, with an eigenvalue greater than 1.0 considered significant.

Data Analysis Techniques

Descriptive statistics were used for summarizing and observing the study sample, while inferential statistics involved hierarchical and multi-regressions. Data analysis utilized SPSS and PLS-SEM software, examining the relationships between technical, managerial, entrepreneurial, and business skills, SME performance, and the mediating effect of strategic planning. Data screening was conducted to check for correctness, missing data, outliers, normality, and other considerations.

Measurement Scale

his research utilized a five-point Likert scale for all items, consistent with established scholarly practices. The questionnaire, specifically designed for this research study, incorporated measurements derived from previous relevant studies within the research context (Kunene, 2009). The research model encompasses six constructs: firm performance, technical skills, managerial skills, entrepreneurial skills, business skills, and strategic planning.

Variables Construct Source Reliability
Technical Skills Operational skills, Supplies/Raw Material, Development Skills, Productive Skills Smith et al. (2006) 6
Managerial Skills Management skills, Marketing/Sale skills, Financial Skills, Legal skills, Administrative skills, High-order skills Smith et al. (2006) 23
Entrepreneurial Skills Industry/Market opportunity skills, Risk-taking Skills, Creativity skills, Innovative skills, Role Model Smith et al. (2006) 10
Business Skills Operational skills, Strategy and business planning, Networking skills, HR Skills, Business systems and processes skills, ICT skills Kunene (2009) 17
Strategic Planning Vision and values, Mission statement, Goals, Objectives, Strategies Charles P. Sitkin in (1998) 26
Firm Performance Profitability, Sales growth, Overall performance, Achieve start-up goals, Provide a secure job to employees, Satisfaction with the organization’s performance Keh et al. (2007) 18
Table 1.Measures of the Study Source: Compiled by the author

Analysis

Demographic Profile of the Respondents

The researcher describes the demographic profile of the respondent for this research study. The characteristics examined include the position of the respondents, Gender, Age of respondents, educational background, years of operations, types of the business, ownership, annual turnover, and the number of employees in the table below 2.

This descriptive analysis reveals that 47.7%, representing 126 respondents, were business owners, 28%, representing 74 respondents, were managers, 15.5%, representing 41 respondents, were chairpersons of the business, and 8.7%, representing 23 respondents, were assistant managers. Assistant managers were identified based on references made by owners or senior managers. Regarding the gender of the respondents, 95.1%, representing 251 respondents, were male, and 4.9%, representing 13 respondents, were female.

Similarly, concerning the age group of the respondents, 6.1% were below 25 years, 53.4% fell in the age group of 25-34 years, 29.9% were in the age group of 35-44 years, 8.7% were in the age group of 45-54 years, and 1.9% were above 55 years.

In terms of educational background, Table 5.4 indicates that matric education constituted 14% of the respondents, intermediate education constituted 28.8% of 76 respondents, graduation with two-year education constituted 16.7% of 44 respondents, graduation with four-year education constituted 15.5% of 41 respondents, master's level education constituted 22.3% of 59 respondents, while diploma and equivalent level education constituted 0.8% of 2 respondents. Those with postgraduate and other qualifications represented only 1.8% of the total responses. This clearly points out that most owners or managers of SMEs in Pakistan hold intermediate and master's degrees.

The descriptive statistics also show that 63.3% of SMEs have been in operation for less than 5 years, followed by 25.8% in the 5-10 years range, and finally, 11% have been in operation for over 10 years. Moreover, 50% of respondents are from the industrial sector, 23.2% from the agriculture sector, and 17.8% from the services sector. In terms of registration status, 64.4% (170 respondents) are from unregistered firms, 25% (66 respondents) from sole proprietorships, 5.3% (14 respondents) from partnerships, 0.8% (2 respondents) from close corporations, and 0.4% (1 respondent) from corporation ownerships.

Regarding annual turnover, 65.2% of respondents are from firms with an annual turnover of less than 150 million, 20.5% are from the 150-200 million annual turnover group, 8.3% are from 200-300 million annual turnover firms, 3.8% belong to the 300-500 million annual turnover firms, 1.1% are from the 500M to 800M annual turnover firms, and similarly, 1.1% of all respondents belong to the group of firms with an annual turnover above 800 million. Descriptive statistics also reveal that 53.4% of respondents have less than 100 employees, 32.6% have 100-150 employees, 11% have 151-200 employees, and lastly, 3% have 200 or more employees. Based on the above, it can be concluded that the respondents in this study provide sufficient variance in their backgrounds.

Items Frequency Percent %
Position of the respondent in the organisation
Owner 126 47.7
Manager 74 28
Chairman 41 15.5
Assistant Manager 23 8.7
Gender of respondent
Male 251 95.1
Female 13 4.9
Age of respondent
Below than 25 years 16 6.1
25-34 years 141 53.4
35-44 years 79 29.9
45-54 years 23 8.7
Above 55 5 1.9
Educational background
Matric 37 14
Intermediate 76 28.8
Graduation (2 years) 44 16.7
Graduation (4 years) 41 15.5
Master 59 22.3
Diploma and equivalent 2 0.8
Ph.D. 3 1.1
Other 2 0.8
Years of operations
Less than 5 year 167 63.3
5-10 years 68 25.8
Above 10 years 29 11
Type of business
Industrial sector 132 50
Agriculture sector 85 32.2
Services Sector 47 17.8
Ownership
Not registered 170 64.4
Sole proprietorship 66 25
Partnership 14 5.3
Close Corporation 2 0.8
Corporation 1 0.4
Annual turnover
Less than 150 million 172 65.2
150-200 million 54 20.5
200-300 million 22 8.3
300-500 million 10 3.8
500-800 million 3 1.1
800 million and above 3 1.1
Number of employees
Less than 100 141 53.4
100-150 86 32.6
151-200 29 11
200 Above 8 3
Table 2.Summary of Respondents Profile Source: Compiled by the author

Assessment of a measurement model

The measurement model is the portion of the model that specifies how the observed variables depend on the unobserved, composite, or latent variables . Each one of the constructs under consideration, includes technical skills, management skills, entrepreneurial skills, business skills, strategic planning, and firm performance. The aim of the measurement model to specify which items cross the pond to each latent variable and employ the measurement model is to access the construct and convergent validity of the construct . Similarly, a confirmatory factor analysis (CFA) using PLS-SEM, was conducted to assess the convergent and discriminant validity of the latent construct. suggested that construct validity can be established by undertaking content validity, convergent validity and discriminant validity.

Individual Item Reliability

The outer loading assessed the reliability of individual items for each construct's measure (Duarte & Raposo, 2010; F. Hair Jr et al., 2014; Hulland, 1999). According to the rule, items with outer loadings between 0.40 to 0.70 were retained (Sarstedt, Ringle, Henseler, & Hair, 2014). In this process, 3 items were deleted out of the total 106 items due to their loading being below the threshold value of 0.40. Similarly, 103 items were retained, as their loadings ranged from 0.425 to 0.90.

Internal Consistency Reliability

Internal consistency reliability ensures that all items measure the same concept on a certain scale or subscale (Bijttebier et al., 2000). The widely used techniques for gauging instrument reliability in organizational research are Cronbach's Alpha coefficient and composite reliability (Bacon, Sauer, & Young, 1995; Peterson & Kim, 2013). Both Cronbach's Alpha coefficient and composite reliability were employed in this study.

Cronbach's Alpha coefficient, though popular, tends to assume equal reliability for all items and may underestimate internal consistency (Götz, Liehr-Gobbers, & Krafft, 2010). Due to this limitation, this study, along with Cronbach's Alpha, used the coefficient of composite reliability. Composite reliability offers a more accurate estimate of reliability, acknowledging that items may contribute differently to the construct (Peterson & Kim, 2013).

Cronbach's alpha can also be prone to underestimation or overestimation of scale reliability. In contrast, the composite reliability considers divergent loadings, similar to Cronbach's alpha, and deems values between 0.70 and 0.90 as satisfactory for a reliable model (Nunnally, 1994). Values lower than 0.60 are deemed unreliable and indicate a lack of internal consistency reliability. Thus, this study employed the coefficient of composite reliability, considering the threshold value of 0.70 and above (Bagozzi & Yi, 1988; F. Hair Jr et al., 2014). Table 3 displays composite reliability, item loadings, and average variance extracted for the measurement model.

Variables Cronbach's Alpha rho_A Composite Reliability Average Variance Extracted (AVE) VIF
Business Skills 0.964 0.967 0.967 0.586 2.531
Entrepreneurial Skills 0.886 0.889 0.911 0.595 2.430
Firm Performance 0.950 0.954 0.956 0.581 2.521
Management Skills 0.968 0.969 0.971 0.635 2.978
Strategic planning 0.967 0.969 0.970 0.538 2.474
Technical skills 0.949 0.965 0.959 0.797 1.998
Table 3.Reliability coefficient and Average Variance Extracted Source: Computed by the Researcher.

Furthermore, VIF values were examined to identify multicollinearity among latent constructs. Table 5.4 reveals the absence of multicollinearity. Multicollinearity is a concern if VIF values exceed 10 or tolerance values fall below 0.10 (Hair Jr et al., 2010; Pallant & Manual, 2010; Tabachnick, Fidell, & Ullman, 2007).

The table above displays the reliability coefficients of Cronbach’s alpha and composite reliability for the constructs in this research study. Table 5.6 shows composite reliability values ranging from 0.927 to 0.971 for each construct, and similarly, the rho_A coefficient ranges from 0.916 to 0.969 for each construct. All constructs exceed the threshold value of 0.70, indicating sufficient internal consistency for each measure in this study (Bagozzi & Yi, 1988; F. Hair Jr et al., 2014).Convergent Validity

Convergent validity, defined as the extent to which items represent the study construct and correlate with other items of the same construct, was assessed using Average Variance Extracted (AVE) (Fornell & Larcker, 1981). AVE for each construct must exceed 0.50 for significant convergent validity (Chin, 1998). Table 5.6 shows that AVE values are not less than 0.50 for all study constructs.

Discriminant Validity

Discriminant validity, indicating the degree to which a specific measure positively correlates with other constructs of the same construct, was assessed using the AVE square roots and cross-loadings (Joseph F Hair, Ringle, & Sarstedt, 2013). AVE values must exceed 0.50, and the square root of AVE must surpass construct correlations (Fornell and Larcker, 1981). Table 5.6 displays AVE values ranging from 0.537 to 0.797, signifying sufficient validity as values below 0.50 are not acceptable. Table 5.7 shows the square root values of AVE (in boldface), which exceed construct correlations, indicating acceptable discriminant validity (Fornell and Larcker, 1981).

Variables Business Skills Entrepreneurial Skills Firm Performance Managerial Skills Strategic Planning Technical Skills
Business skills 0.765
Entrepreneurial Skills 0.676 0.733
Firm performance 0.406 0.455 0.762
Managerial Skills 0.546 0.499 0.399 0.797
Strategic Planning 0.702 0.708 0.569 0.374 0.733
Technical Skills 0.171 0.187 0.173 0.076 0.145 0.893
Table 4.Correlation of the variance and Square roots of average variance Extracted.Note: bold entries represent the Square root of AVE.Source: Computed by the researcher by using PLS-SEM 3.2.

Assessment of Significance of the Structural Model

After ascertaining the constructed measures are reliable and validate, this study will compute the structural model. The standard bootstrapping was used with a number of 5000 boost strap samples and 264 respondents to evaluate the significance of the path . Table 5 depict the relationship with the mediator of the structural model in this study.

Hypothesis Relation Beta Sample Mean (M) SE T-Value P Values Findings
H1 TS -> SP -0.007 0.000 0.037 0.186 0.853 Not Supported
H2 MS -> SP -0.096 -0.091 0.047 2.030** 0.042 Supported
H3 ES -> SP 0.456 0.451 0.061 7.447** 0.000 Supported
H4 BS -> SP 0.446 0.448 0.056 8.020** 0.000 Supported
H5 SP -> FP 0.597 0.600 0.064 9.321** 0.000 Supported
H6 TS -> SP -> FP -0.004 0.000 0.022 0.185 0.854 Not Supported
H7 MS -> SP -> FP -0.057 -0.054 0.028 2.054** 0.040 Supported
H8 ES -> SP -> FP 0.272 0.271 0.048 5.707** 0.000 Supported
H9 BS -> SP -> FP 0.267 0.268 0.040 6.637** 0.000 Supported
Table 5.Structural Model Assessment (Full Model with mediator included)Note: ***Significant at 0.01, **Significant at 0.05, *Significant at 0.1Source: Computed by smart PLS 3.2.8.

From the inspection, Hypothesis 1 reveals that technical skills are not related to Strategic planning. Table 5 also display the insignificant negative relationship between technical skills and strategic planning (β= -0.007, t = 0.186, P < 0.853), which does not support hypothesis 1.

Hypothesis 2 indicated that managerial skills are significant in strategic planning. Table 5 also indicated a positive relationship between managerial skills and strategic planning (β= -0.096, t = 2.030, P < 0.042). Hypothesis 2 is supported. Similarly, the results of hypothesis 3 showed a significant relationship between entrepreneurial skills and strategic planning. Results (Table 5 and Figure 5.5) indicated entrepreneurial skills have a significant positive relationship with strategic planning (β= 0.597, t = 7.447, P < 0.000). Hypothesis 3 is supported.

Hypothesis 4 predicted that business skills had a significant relationship with strategic planning. Results from Table 5 also indicated that a significant positive relationship exists between business skills and strategic planning (β= 0.446, t = 8.020, P < 0.000). The hypothesis was supported. As presented in Table 5, strategic planning had a significant positive relationship with firm performance (β= 0.550, t = 9.321, P < 0.000). So, the hypothesis is supported.

The mediating effect of strategic planning on technical skills and firm performance was predicted in hypothesis 6. Results in Table 5 (β= -0.004, t = 0.185, P < 0.854) show that the hypothesis was not supported. Similarly, the mediating effect of strategic planning on managerial skills and firm performance is indicated by hypothesis 7; the results of Table 5 and Figure 5.5 showed a significant effect (β= -0.057, t = 2.054, P < 0.040). Hypothesis 7 is supported. Contrarily, results for the mediating effect of strategic planning on the relationship between entrepreneurial skills and firm performance, which was predicted in hypothesis 8, revealed a positively significant effect (β= 0.272, t = 5.707, P < 0.000). Thus, hypothesis 8 was supported. Finally, the proposed mediating effect of strategic planning on business skills and firm performance in hypothesis 9 was fully supported. The results in table 5 for Hypothesis 9 were (β= 0.267, t = 6.637, and P < 0.000) respectively.

Figure 2.Measurement Model

Figure 3.PLS-SEM Bootstrapping with mediator (Full Model)

Assessment of Variance/ Coefficient of determination (R 2 )

Assessment of variance or the coefficient of determination (R²) is a crucial criterion for evaluating the PLS-SEM structural model (Hair et al., 2012; Hair at al., 2011; Henseler et al., 2009). R² represents the proportion of variation in the endogenous variable(s) explained by the single or multiple predictor variable(s) (Elliott & Woodward, 2007; Hair, Black, Babin, Anderson, & Tatham, 2006; Hair Jr et al., 2010). The adequacy of the R² value depends on the research context, with a minimum acceptable value of 0.10 . For PLS-SEM, R² values of 0.19, 0.33, and 0.67 are considered weak, moderate, and substantial, respectively (Chine, 1998). Table 6 presents the predicted R² values for firm performance and strategic planning.

Latent Variable Variance Explained R- Square
Firm Performance 0.357
Strategic Planning 0.599
Table 6.Variance Explained in the Endogenous Latent VariablesSource: Computed by Researcher by using Smart PLS 3.2.8.

Table 6 reveals that the study model accounts for 36% of the overall variance in firm performance and 60% of the overall variance in strategic planning. This indicates that the four independent variables (Technical Skills, Managerial Skills, Entrepreneurial Skills, and Business Skills) collectively explain 36% and 60% of the variance in firm performance and strategic planning, respectively. Consequently, the R² values for this study can be deemed moderate, meeting the acceptable criteria outlined by Chin (1998) and Falk and Miller (1992).

Assessment of Effect Size (f 2 )

This study assessed the effect size of all endogenous constructs using the f² statistic, measuring the influence of specific exogenous latent variables on endogenous latent variables through changes in R-square (Chin, 1998). Calculated by the recommended , the effect size (f²) values (0.35, 0.15, and 0.02) are categorized as strong, moderate, and weak effects, respectively. Table 7 presents the effect sizes of latent variables based on Cohen’s recommendations:

Variables f- Square Effect Size
Technical Skills -> Strategic Planning 0.003 small
Managerial Skills-> Strategic Planning 0.020 Small
Entrepreneurial Skills -> Strategic Planning 0.284 Moderate
Business Skills -> Strategic Planning 0.262 Moderate
Strategic Planning -> Firm Performance 0.205 Moderate
Technical Skills -> Firm Performance 0.020 Small
Managerial Skill -> Firm Performance 0.076 small
Entrepreneurial Skills -> Firm Performance 0.006 Small
Business Skills -> Firm Performance 0.019 small
Table 7.Effect Sizes of the Latent variables on Cohen’s (1988) recommendationSource: Computed by the Researcher.

The effect size values in Table 7 indicate that the impact of latent constructs (Technical Skills, Managerial Skills, Entrepreneurial Skills, Business Skills) on Strategic Planning ranges from small (0.003, 0.020) to moderate (0.284, 0.262). Similarly, the effect size of Strategic Planning on Firm Performance is moderate (0.205). Conversely, the effect size of endogenous latent constructs (Technical Skills, Managerial Skills, Entrepreneurial Skills, Business Skills) on Firm Performance is small (0.020, 0.076, 0.006, 0.019).

Assessment of Predictive Relevance (Q 2 )

Apart from evaluating effect size, the predictive relevance capacity of a model is another crucial aspect. Stone-Geisser’s Q2 values are utilized to assess the predictive accuracy of the model (Hair et al., 2013). This measure gauges the model's ability to offer predictive evidence for the indicators of the independent variable (Henseler et al., 2009). The assessment of predictive accuracy using Q2 is conducted through Stone-Geisser’s test, involving a blindfolding process (Hair et al., 2013; Henseler et al., 2009). This study employs a reflective measurement model, and the blindfolding process was applied to cross-validate the effect size using Stone-Geisser’s method (Hair et al., 2013). Table 8 presents the cross-validated values for firm performance and strategic planning.

Total SSO SSE Q² (=1-SSE/SSO)
Firm Performance 4,224 3,380.31 0.200
Strategic Planning 7,392 5,221.14 0.294
Table 8.Predictive Relevance (Q2) Source: Computed by the Researcher.

Table 8 indicates that the Q2 values for this study are above zero for both latent variables: firm performance (0.200) and strategic planning (0.294). These values signify an acceptable level of predictive relevance for the study model. This aligns with the recommendation of various researchers (Joseph F. Hair et al., 2013; J. Henseler et al., 2009), stating that Q2 values above zero indicate predictive relevance, while values below zero do not. Thus, the Q2 values in this study indicate that all endogenous latent constructs have predictive relevance for the study model.

Discussion

The findings of this study are discussed in the discussion section and presented based on the study objectives.

Technical, managerial, entrepreneurial , and business skills have a positive influence on the strategic planning of organisations.

The initial objective of this study was to examine the relationship between technical skills, managerial skills, entrepreneurial skills, business skills, and the strategic planning of SMEs in Punjab, Pakistan. Consequently, four hypotheses were proposed to examine the significance of the effect of all these skills on an organization’s strategic planning.

To start, the first hypothesis, H1, stated that technical skills (TS) have a significant effect on the strategic planning (SP) of the organization. The t-value of 0.186 was lower than the cut-off value of 1.960, indicating a statistically insignificant relationship between technical skills and corporate strategic planning (β= -0.007, t = 0.186, P < 0.853). All steps in the methodology were considered, and there were no methodological issues. This finding contradicts some other research (De Toni & Tonchia, 2003; Huault, 1996; Kunene, 2009; Ouakouak & Ouedraogo, 2013; Skokan, Pawliczek, & Piszczur, 2013).

The population of the study, the occupations of the participants, and the sample characteristics in Pakistan may explain the insignificance of this result. Moreover, the highest sample of respondents came from the industrial sector, more related to production and manufacturing. It is also unsurprising that technical skills have no effect on strategic planning, as they are unrelated to building strategies and focus on the vision of the organization. Another explanation may be that the organization was relaxed and held fewer concerns about the serious competition present in the market. Additionally, these insignificant findings support the problem statement, indicating deficient output due to the lack of strategic planning within SMEs in Pakistan.

The second hypothesis, H2, posited that managerial skills have a significant effect on the strategic planning of the organization. This relationship was consistently found to be significant, as the t-value of 2.030 was higher than the cut-off value of 1.960, supporting H2 (β= -0.096, t = 2.030, P < 0.042). Therefore, H2 is supported. This finding will help owners and managers use these important skills in their organizational planning. Moreover, firms should develop strategies that enable the utilization of organizational resources and enhance performance. Theoretically, this relationship supports the RBV theory, according to which organizations can improve their performance by building effective strategies .

Similarly, managerial skills as organizational capabilities and resources are crucial for an organization because these abilities mostly relate to organizational management covering all aspects of the company, such as handling, developing, planning, supervising, and focusing on the corporate vision. Thus, owners and managers can consider these important managerial capabilities as an essential competitive advantage of the firm. Additionally, these resources also assist in developing plans following market situation assessments and setting long-term strategies. Hence, the results of this study are congruent with the arguments in which hypothesis H2 was grounded (Clardy, 2008; Daley, 2012; Devanna, Fombrun, & Tichy, 1981; King, Fowler, & Zeithaml, 2001; Pansiri & Temtime, 2008; Radipere & Van Scheers, 2005). Similarly, the results from this research also offer support for the theoretical explanation of strategic planning and managerial skills from the perspective of policy building.

Managerial skills help owners and managers to build organizational policies and utilize their resources according to their strategies . In this view, the findings of the study will also enable them to consider how these resources are so crucial for their businesses and allow the SMEs to participate in raising the national GDP. However, SMEs in Pakistan need SP to utilize their resources when designing organizational strategies.

Hypothesis three, H3, postulates that entrepreneurial skills (ES) have a significantly positive effect on the SP of the organization. The results, shown in Table 5, indicate that the t-value of 7.447 is higher than the threshold value of 1.960. The result of this study shows a significant relationship between the ES and SP of the organizations, as the values in Table 5 suggest (β= 0.597, t = 7.447, P < 0.000). This finding, therefore, also corroborates the relationship between organizational resources. Hence, H3 was supported. The results of this study corroborate prior studies in concluding that entrepreneurial skills, as organizational resources, are crucial for organizational competitiveness and help companies to build strategies and long-term sustainability (Afolabi & Macheke, 2012; Berry, 1998; Boateng, Karikari, & Akafo, 2015; Carter & Tamayo, 2017; Giunipero, Denslow, & Eltantawy, 2005; Kiambati & Itunga, 2016; Leyva Carreras, Cavazos Arroyo, & Espejel Blanco, 2018). The findings also support the RBV theory that collaboration between organizational resources and organizational management in developing innovative ideas should enhance performance and further contribute to the national GDP.

Entrepreneurial skills generally refer to starting a business, turning ideas into a successful business, and then developing, planning, and growing the business. However, the findings of this study also indicate that SME owners and managers should consider these important skills as useful organizational assets, resources which can be utilized at the outset of the business and which can build long-term planning and policies. Moreover, the findings will also be helpful for the SMEs managers and owners in developing their strategy, using their resources to sustain a competitive advantage, and enhancing performance.

Finally, hypothesis four, H4, posits that business skills have a significant positive relationship with the strategic planning of the organization. These skills are essential for the company because they enable the acquisition of the conventional management area and allow the firm to sustain activities in complex and challenging market situations . As values given in Table 5 show, the t-value of 8.020 is higher than the cut-off value of 1.960. The findings also indicate that business skills have a significant relationship with organizational strategic planning (β= 0.550, t = 9.321, P < 0.000). Moreover, findings suggest that these skills are also greatly significant in the development of organizational planning and should be considered important resources for business development and enhanced performance.

Furthermore, the results also propose to owners and managers how these resources can be utilized in the development of business strategies. Therefore, SMEs need to adopt these important skills to ensure long-term sustainability and participate effectively in the national GDP. This relationship supports the outcomes of previous studies (Ajagbe, 2011; Ansah, 2017; Anwar, Saleem, Zahid, & Director, 2012; Leyva Carreras et al., 2018; Logan, 2009). Similarly, the RBV theory also supports this relationship. According to the RBV, the collaboration between organizational resources has a more effective impact on organizational performance and helps to determine future planning and corporate goals.

Strategic Planning has a significant effect on the enterprise performance of SMEs in Punjab, Pakistan.

This study examined the mediating relationship between strategic planning (the mediator variable) and corporate performance of SMEs (the dependent variable) in Punjab, Pakistan. To test the level of this mediation, hypothesis H5 was used to assess the mediation procedure provided by Preacher and Hayes (2008). This procedure examines the relationship between the independent variable and the mediator variable, as well as the relationship between the mediator variable and the dependent variable. Strategic planning is an organizational resource that can help owners and managers utilize their resources effectively. This relationship was tested through PLS-SEM to fulfill the second objective of this research.

Hypothesis H5 posits that strategic planning would have a significant mediating effect on corporate performance. This hypothesis was tested by collecting numerical data from SMEs within Punjab, Pakistan. Hence, as the t-value was 9.321, which is higher than the cut-off value of 1.960, H5 was supported, and a significantly positive relationship was found between strategic planning (SP) and firm performance (FP) (β= 0.550, t = 9.321, P < 0.000). Specifically, this result also corroborated prior studies by , , , , and .

The results following the testing of H5 further demonstrate that SMEs’ owners and managers should use mediation to leverage their resources to enhance performance through strategic planning. This study provides additional evidence of ways in which firms can perform better and contribute to the national GDP. Furthermore, the findings also support the concept of the RBV theory, suggesting that firms enhance performance by utilizing their tangible and intangible resources. The findings also provide further support for the idea that firms should adopt strategic planning as an organizational resource and work towards organizational development.

Strategic Planning mediates the relationship between technical, managerial, entrepreneurial , and business skills, and the performance of SMEs in Punjab, Pakistan.

The primary objective of the research was to examine the mediating effect of strategic planning on the relationship between technical, managerial, and entrepreneurial skills and the performance of SMEs in Punjab, Pakistan. In addressing this objective, the direct relationship between SP and FP had been previously tested. Four hypotheses were proposed to examine the mediating impact of SP on the relationship between TS, MS, ES, BS, and firm performance through bootstrapping .

Certain prerequisite conditions exist for mediation to have a significant positive effect on the relationship between the independent and mediator variables, as well as the mediator and dependent variables . The relationship between the independent and the mediator variable was also tested in a previous hypothesis. The effect of mediation on the relationship between the independent and dependent variables (H6, H7, H8, H9) will now be assessed and discussed.

Hypothesis H6 posits that SP would mediate the relationship between technical skills and firm performance. Table 5 shows that the t-value of 0.185 is less than 1.960, indicating that SP does not mediate the relationship between technical skills and firm performance (β= -0.004, t = 0.185, P < 0.854). Hence, H6 was not supported, and the researcher was bound to reject this hypothesis. It is unsurprising that the important condition for mediation, the relationship between the independent variable and mediator variable, was not significant. Hence the mediation effect was not significant . Lack of understanding among owners and executives regarding the role of strategic planning may be a probable reason for this insignificance.

Similarly, managers and owners of organizations may not consider the role of strategic planning in developing technical resources for long- or short-term planning. In addition, it is not considered a prerequisite resource for organizations in terms of sustainable development. Therefore, the role of SP in this relationship may be unimportant in the context of Pakistani SMEs. Another possible reason for this lack of a mediation effect of SP is that the sample of SMEs emphasizes other organizational resources and their financial situations more strongly, without allowing a greater focus on strategic planning. In Pakistan, the way most firms manage and operate follows traditional strategies and policies. Therefore, owners and managers tend not to accept changes that allegedly represent a risk of failure. These factors explain the insignificant effect of SP on TS and SMEs’ performance in Punjab, Pakistan which subsequently means it is necessary to revisit this in future research.

Hypothesis seven, H7, postulates that strategic planning would mediate the relationship between managerial skills and SMEs’ performance in Punjab, Pakistan. Thus, H7 is supported on the basis that the t-value 2.025 is greater than 1.960. It means that strategic planning mediates the relationship between managerial skills and firms’ performance in the context of Punjab, Pakistan (β= -0.057, t = 2.054, P < 0.040). However, findings show that strategic planning connects to the idea that organizational management should utilize its resources for the betterment of the organization. Furthermore, the study results could serve as a guide for SMEs’ owners and managers on how to use their resources to build strategies and how to use strategic planning to improve corporate performance. No matter how effective a firm is in utilizing its resources, performance cannot be enhanced without the implementation of strategic planning in its policies.

In a related development, the findings also suggest that many SMEs’ owners and managers are trying to identify more effective policies to utilize their resources and enhance their role in contributing to the national GDP. Findings also support the RBV theory concept. Using the resources in proper planning in view of the company's vision and mission will increase the firm’s performance and enable the firm to sustain growth. The findings of previous studies , , , , , also support the importance of the effect of strategic planning for organization’s performance. Therefore, SMEs in Pakistan need to promote this relationship, which enables better performance despite limited resources. It would not be accomplished until SME owners/managers adopt both strategic planning and managerial skills to build and implement strategies and policies.

Hypothesis eight H8 was formulated in order to investigate the mediating effect of strategic planning in the relationship between entrepreneurial skills and SMEs’ performance in Punjab, Pakistan. To achieve this mediation, all the necessary paths for mediation to take effect were observed to be significant (Hayes, 2009). As results in Table 5 show, the t-value of 5.707 was larger than the cut-off value of 1.960. SP was found to significantly mediate the relationship between entrepreneurial skills and corporate performance in Punjab, Pakistan (β= 0.272, t = 5.707, P < 0.000). Hence, H8 was supported. Similarly, previous literature also supports the present findings. Past research also highlights the significant role of strategic planning on organizational resources and a firm’s capabilities (Hall, 1992; Idar, Yusoff, & Mahmood, 2012; Ireland et al., 2001).

This finding indicates that strategic planning facilitates how organizations utilize their resources, which leads to better performance. Similarly, this finding also suggests to owners and managers of SMEs that entrepreneurial skills as an organizational resource are an important factor that can expedite better performance through the building of better strategies. This finding also supports the RBV theory, according to which organizations could perform better if they utilized their resources more effectively . Finally, the finding further informs firms that strategic planning is a key, valuable intangible resource, allowing the firm to enhance performance with limited resources.

Finally, the last hypothesis, H9, also posits that strategic planning would mediate the relationship between business skills and SMEs’ performance in Punjab, Pakistan. Hence, H9 is supported by analyzing the values in Table 5. The T-value of 6.637 is larger than the threshold value of 1.960. Similarly, it also indicates the significant positive effect of strategic planning on the relationship between business skills and SMEs’ performance (β= 0.267, t = 6.637, P < 0.000). This study considers business skills as an organizational resource, in which case many studies support the present findings and the view that organizational resources affect corporate performance (Devanna et al., 1981; Falshaw et al., 2006; Hin et al., 2013). However, strategic planning as an organizational resource has a strong influence and connectivity with organizational resources (Ahmad et al., 2020). Therefore, owners and managers of SMEs need to promote this relationship since it enables better performance with limited resources. This finding also expounds on the idea that utilization of resources with proper planning, in the direction of organizational strategies and to achieve the organizational goals, can lead to better performance.

Implications Of The Study

The study offers significant implications across applied, theoretical, and methodological dimensions.

The findings underscore the importance of adopting a strategic planning approach in manufacturing firms. Focusing on technical, managerial, and entrepreneurial aspects can provide valuable insights for building manufacturing strategies and optimizing resource utilization.

In the services sector, the study emphasizes the understanding of factors influencing growth through corporate strategies. The implementation of strategic planning is recommended as a key element for better resource utilization and enhanced performance.

For the agriculture sector, the study contributes to understanding the role of multiple skills in enhancing performance through the implementation of strategic planning. It advocates for comprehensive planning by identifying important skills tailored to specific business needs.

The study provides guidelines for policymakers to support SMEs through financial assistance for implementing effective strategies. Policymakers are encouraged to focus on supporting, training, and incentivizing SME owners and managers in developing specific skills and strategies.

The study is grounded in the Resource Base Theory (RBV), contributing to the literature by proposing technical, managerial, entrepreneurial, and business skills as significant independent variables influencing corporate performance. It introduces the mediating role of strategic planning, offering empirical evidence within the RBV framework. The study supports the RBV theory's contention that corporate competitive advantage is driven by organizational capabilities and resources.

The study's methodology introduces several implications. It advocates for a generic measurement of organizational performance, integrating multiple resources into the measurement of the dependent variable. The use of Partial Least Squares Structural Equation Modeling (PLS-SEM) for validation and hypothesizing linkages between variables is recommended for future research. The study suggests a systematic approach to measurements, combining quantitative and qualitative methods for more accurate and reliable results.

Limitations And Recommendations For Future Research

The study acknowledges certain limitations that warrant consideration for future research endeavors. Firstly, the cross-sectional research design, necessitated by time and cost constraints, limits the establishment of causal relationships among the study variables. To address this limitation, future research may benefit from adopting a longitudinal research design, facilitating a more nuanced exploration of the intricate relationships between variables over time.

Furthermore, the study's reliance on a sample size derived from the total population of SMEs raises a limitation related to generalizability. Subsequent research efforts should consider employing larger sample sizes to ensure more robust and widely applicable findings. Additionally, the study's exclusive use of quantitative techniques, particularly the questionnaire as the sole data collection tool, presents a limitation in terms of comprehensiveness. Future researchers are encouraged to adopt a mixed-methods approach, combining both quantitative and qualitative methodologies, to provide a more comprehensive understanding of the study variables.

Geographically, the study focuses on SMEs in the province of Punjab, Pakistan, which might limit the generalization of findings due to cultural, linguistic, and demographic variations across regions. Future studies should consider diversifying the geographical scope to capture a broader representation of the SME landscape in Pakistan.

Moreover, the unidimensional construct employed in measuring variables, such as technical, managerial, entrepreneurial, and business skills, alongside strategic planning, poses a limitation. Future research should explore the use of multidimensional scales to enhance the granularity and accuracy of measurements.

In conclusion, while the study contributes significantly to the understanding of the mediating role of strategic planning in SME performance, it is imperative to recognize these limitations. Future research endeavors should aim to address these constraints, allowing for more robust and nuanced insights into the complex dynamics of skills, strategic planning, and SME performance. Such efforts will contribute to the continuous evolution of knowledge in the fields of management, strategic management, entrepreneurship, and organizational management.

Conclusions

The study significantly contributes to the literature on the mediating role of strategic planning in the relationship between skills and SME performance. Despite acknowledged limitations, the findings offer valuable insights for scholars, practitioners, and policymakers. The study's recommendations open avenues for future research, urging scholars to explore deeper relationships, different research designs, diverse samples, and varied measurement techniques. Overall, the study provides meaningful insights into enhancing the role of SMEs in economic growth and development.

Acknowledgment statement: The authors would like to thank the reviewers for providing comments in helping this manuscript to completion.

Conflicts of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Author contribution statements: Author 1 contributed to the Conceptualization, Methodology, Formal Analysis Investigation, Writing – Original Draft, Visualization, Project Administration, and Writing – Review and editing.

Funding: The funding is no funding.

Ethical consideration statement: Not applicable. This study did not involve human and animal studies.

Data availability statement: Data is available at request. Please contact the corresponding author for any additional information on data access or usage.

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