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5
THE IMPACT OF CORPORATE STRATEGY AND ORGANIZATIONAL SLACK ON CORPORATE PERFORMANCE: EVIDENCE FROM PAKISTAN
MUHAMMAD SIDDIQUE1, ABDUL RASHEED2, WALEED KHALID3
1PhD Scholar, Khwaja Fareed University of Engineering & Information Technology, Pakistan 2Assistant Professor, Khwaja Fareed University of Engineering & Information Technology, Pakistan 3Assistant Professor, Khwaja Fareed University of Engineering & Information Technology, Pakistan 1siddiqlaghari@gmail.com, 2abdul.rasheed@kfueit.edu.pk, 3rajawaleedkhalid@yahoo.com
Abstract: This study investigates the impact of organizational slack on the relationship between firm performance and Miles and Snow's (1978) typology. We examine a sample of 274 non-financial companies listed on the Pakistan Stock Exchange between 2006 and 2021 using panel data. In order to control auto correlation and endogeneity issues, the generalized method of moments estimation (GMM) is used to get the results. Our findings demonstrate that available or potential organizational slack strengthens the already-existing positive association between prospector, analyzer, and defender strategies and a firm's financial performance, whereas recoverable slack weakens the relationship. After taking into account endogeneity, and serial correlation, the results are robust. These findings contribute to the body of knowledge on existential dilemmas relating to the use of slack resources in the company and outline the theoretical and empirical implications of Miles and Snow's typologies.
Keywords: Prospector Strategy, Analyzer Strategy, Defender Strategy, Available Slack, Potential Slack, Recoverable Slack, Financial Performance.
Table of Contents
Introduction
1. Review of the Literature
2. Methodology
3. Results and Discussion
4. Conclusion of the Study
Introduction
There are several ideas and concepts that describe how firms go about gaining a long-lasting competitive edge. Miles and Snow (1978) proposed strategic typology has gained widespread recognition in the organizational theory and strategic management communities over the past three decades to achieve above average performance and long-lasting competitive edge (Hambrick, 1983). Based on their pattern of strategic decisions, organizations are classified into four archetypes under this paradigm. Defenders, on the other hand, prefer to focus on a small area by establishing premium niches in their industry. Prospectors, on the other hand, focus on seizing fresh chances in new markets. Analyzers, the third archetype, have traits of both the Defender (risk minimization) and the Prospector (opportunity maximization). Finally, the Reactor exhibits an uneven and frequently unstable pattern of environmental adaptations (Sollosy et al., 2019). According to Miles et al. (1978) three of the four recognized strategic archetypes—Prospector, Analyzer, and Defender—should perform well and should outperform the fourth type, Reactor, because it lacks a consistent approach.
The majority of strategy-based research is concerned with strategy execution and the organizational process through which strategies are integrated. For example, Miles and Snow's strategic typology and firm performance are put to the test pure and hybrid strategy consistency and inconsistency impact on firm performance is explored by (Anwar, 2017), firm strategy and investment efficiency put to test by (Lin et al., 2021; Navissi et al., 2017). Despite the typology has gained substantial attention, conflicting results and insufficient methodology highlight a number of factors that this study takes into account.
The importance of a firm's resources as the cornerstone of its strategy has recently attracted renewed focus. For instance, Jalilvand & Min (2013) posited that businesses make an effort to align the kind of spare resources with the parameters of their investment strategy, and to counteract the effects of economic uncertainty, firms may accumulate cash during unstable market environments. From the implementation point of view of business strategy, organisational theory and management literature conceptualized that organisational slack are necessary for strategic orientation and responsiveness to environmental changes. Management literature views organisational slack in two aspects: as a fund for innovation and expansion and, second, as a buffer for response to environmental changes (Gul et al., 2022; Karacay, 2017; Kraatz & Zajac, 2001). Available resources are allocated differently as the strategy needs to perform activities. A business strategy choice is the production of invested resources. The use of resources and the adoption of a strategic decision are two linked aspects of the same issue. In this sense, it is possible to say that strategies develop from resources, and then strategies produce additional resources in various ways and may be useful. Therefore, business strategy is seen as the process of the resources investment process (Bowman & Hurry, 1993). From the mid to late 1980s, research moved to resource-based views (RBVs), emphasizing organisational factors. Resources can be considered as the strengths or weaknesses of a particular strategy (Ogot, 2014). Viewing to generate the organisational resources through business operations, investing in business strategy, and slack ability to strengthen and weaken the business strategy influences investment efficiency.
Despite the typology receiving a lot of attention, there are still certain gaps that our study takes into account because of inconsistent results and a methodology that isn't perfect. First, despite the fact that research has looked at the typology's antecedents in a variety of ways (DeSarbo et al., 2005; Song et al., 2007), none that we are aware of has looked at the typology in light of more recent understandings of dynamic capabilities, a dynamic strength that is frequently rewarded in a world that is becoming more competitive (D'Souza et al., 2017). Dynamic capabilities are the routines and procedures that businesses continually reorganize (i.e., shed, acquire, integrate, and deploy) their resource base around in order to produce value-creating strategies that seize both current and future possibilities (Grant, 1996; Holmqvist, 2004; Pisano, 1994). The capacity of a company to use its current assets simultaneously for strategic advantages and investigate new technology and markets is essential to this approach. Prior research emphasis to align the corporate strategy with organizational slack for superior performance and strategy change, but neglected the issue of resource heterogeneity that how differences in organisational slack effect to change the business strategy financial outcome? How and why differences in organizational slack might moderate the relationship between corporate strategy and performance? Primary objectives of the study are: (1) to research the different business strategies employed in Pakistan to improve corporate financial performance. (2) To research how corporate strategy affects financial results. (3) To investigate the moderating role of organizational slack between business strategy and firm financial performance.
The research examined the underlying research questions in light of the problem statement as well as the study's objectives based on Miles and Snow (1978) strategy; (1) how do listed companies in Pakistan behave strategically to deploy pure or hybrid strategies? (2) Does the performance of the businesses fluctuate significantly depending on their strategic typology? (3) Does the difference in organisational slack moderate the relationship between organizational strategy and performance? The contribution of this study is to highlight the importance of organizational slack for developing strong relations with Miles and Snow's typology for successful organizations. These relations and coordination through interaction help to achieve strategic business performance. Similarly, the dynamic resources force businesses to adapt to required changes in strategy in stable and uncertain environments i.e. approachable when businesses are inclined towards strategic orientation. This study focuses on strategic orientation in terms of Miles and Snow's typologies to attain strategic business performance. This study is helpful for both academic research scholars and practitioners to concentrate on organizational resources and strategic orientations for uplifting businesses in Pakistan.
1. Review of the Literature
The literature review examines the interactions between strategy typology, organizational slack, and organisational performance. Theoretical Foundation
The resource-based model's proponents are quick to point out that although resources influence performance and are important building blocks in the creation of strategy, they are insufficient on their own to generate competitive advantage and above-average performance (Chandler & Hanks, 1994). According to (Eisenhardt & Martin, 2000) firm resources include, among other organizational elements, assets, competencies, competences, and specific procedures that allow the company to develop and put into action plans that are meant to improve organisational performance.
Business Strategy Typology and Firm Performance
Miles and Snow's Strategy Topology (1978) significantly influenced the strategy literature and has given theorists a solid foundation for researching adaptive methods to achieve competitive corporate performance (Hambrick, 1983; Parnell & Wright, 1993; Sarac, 2019; Sollosy et al., 2019). Prospector group companies outperform competitors on key metrics for the success of new goods, as well as in terms of sales volume and market share growth (Walker Jr & Ruekert, 1987). Given the uncertainty surrounding the creation of new goods, which may either create a low-end disruption by delivering a product with a reduced feature set at a lower price or a large interruption by offering an inventive product, Magerakis & Habib (2021) noted that prospector maintained flexibility in its strategy-making process and responded fast to new information (Christensen & Bower, 1996; Conant et al., 1990; McKee et al., 1989).
According to statistical evidence by Bortoluzzi et al. (2020) hotels that are prospectors would embrace personnel controls more firmly than hotels that are defenders. As a result, they demonstrate a fluid and dynamic work environment that stresses the requirement for varied controls to be applied to staff selection, recruiting, training, and development, as well as retention methods. Additionally, because routines vary and need for flexibility in how tasks are carried out. In order to maintain organizational commitment and product and service innovation, the controls are primarily created to involve, influence, encourage, and inspire people. Organizational dedication and new product and service development, prospector performance improved.
According to Magerakis & Habib (2021), Low-Cost Defenders strive to create, market, and promote high-quality goods and services at the lowest possible cost so they can compete on price. Instead of emphasizing effectiveness that results from innovation, defender businesses focuses on efficiency through standardised methods in both operations and marketing (Walker Jr & Ruekert, 1987). According to (Miles et al. 1978; Vorhies & Morgan, 2003), the most efficient Low-Cost Defenders include formal rules, processes, and integration tools to accomplish coordination (mechanistic) (Low-Cost Defenders). Price competitiveness is another feature of this approach (S. F. Slater & Olson, 2001). Price competition is a particularly aggressive tactic due to the possibility of price wars (Porter, 1980). Low-Cost Defenders established standards for price and cost structures by placing a strong external focus on competitors. This exterior focus and assertiveness are characteristics of a market culture.
According to Bortoluzzi et al. (2020) , hotels with defender strategies would be more strongly associated with action controls than hotels with prospector strategies. They claimed that because defender hotels provide more uniformed services, management want for tighter control on operations. This conclusion is supported by the data, which also shows that the defender has a favourable relationship with action controls, which improves firm performance.
Combining the two strategies in certain circumstances could be better for business and believed that the combination technique was both long-term feasible and frequently linked to greater performance (Buzzell et al., 1987; Hill, 1988; Murray, 1988; Parnell, 1997; Parnell & Wright, 1993). Businesses that effectively combined distinction and low costs used synergies to balance out any trade-offs. For instance, to be successful, a manufacturer may focus on the creation of new items that can be manufactured at cheaper prices than competitors' current offerings while also emphasizing first-mover advantages and production efficiency. A single company may also build its strategy on a number of competitive advantages, albeit certain combinations may be simpler to put into practice than others.
Analyzer could be the most competitive strategy type if prospectors are the most enterprising. They must simultaneously compete with Prospectors for the attention of early adopters by releasing more innovative, superior-quality, or more reasonably priced versions of the Prospectors' products, as well as with other Analyzer and Defenders in the mass market to protect the essential goods and markets that supply the capital required for their running a business (S. F. Slater et al., 2007). Analyzers keep a core set of competencies, goods, and clients when efficiency is a concern (D. F. Slater & Narver, 1993); they engage in high levels of exploitative learning to preserve competitiveness in their industry(s) while boosting cost efficiencies. To solve the entrepreneurial dilemma, analysts must also identify new product-market prospects. Their success depends on their capacity to react promptly to promising new discoveries and consistently build new skills (Desarbo et al., 2005). However, these talents could also strengthen the Analyzer's exploitative efforts in related fields or boost the efficacy of current exploitative operations. In light of this, the Analyzer is a prime example of the ambidextrous pursuit of both exploration and exploitation (Sollosy et al., 2019). Consequently, we predict the following: Ha!: Prospector, analyzers and defender strategy has a positive relationship with firm performance.
Organizational Slack
Slack, as described by (Nohria & Gulati, 1996, p-1246), is "the pool of resources in an organisation that is in excess of the minimum necessary to produce a certain level of organisational production." A configurationally based technique for studying slack and innovative strategy enables testing of how many slack components are bundled together and how these configurations are associated with varied degrees of firm strategic approach. An analysis of the preceding studies demonstrates that slack resources and strategic investments are two of the key factors that influence a firm's adaptive profile and long-term performance (Jalilvand & Min, 2013).
Moderating Impact of Available Slack between Business Strategy and Firm Performance
Internal, adaptable, and rapidly deployable available slack acts as a cushion against the ups and downs of firm creative outputs (Bourgeois, 1981). On the other hand, it may be argued that, eventually, constraints used to choose or finish projects may become lax due to a surplus of accessible slack (Jensen, 1993). To put it another way, managers can pursue or continue activities that would be shunned or shelved if there was little to no available slack since it is flexible and readily available to them. Managers may tolerate a less-than-ideal amount of innovation because of, the organization's available slack, and as that slack increases, innovation risks suffering (Marlin & Geiger, 2015). As a result, both too much and not enough available slack might be detrimental to innovation (Nohria & Gulat, 1996; J. Tan & Peng, 2003).
Jalilvand and Min (2013) asserting that organizations should simultaneously align their company strategy with the kind of investment opportunities, they are coming across in the market through their business strategy. According to this reasoning, businesses would fund exploration-oriented investment possibilities as prospector typology by using high amounts of flexible slack resources (i.e., low absorption and low specificity, such as financial slack). Since available slack will enable the expansion of present domains and the entry of new goods and markets, a positive effect of available slack and a prospector approach is anticipated (Ansoff, 1965; Voss et al., 2008). In contrast to recoverable slack, which gives less room for new strategies and strategic adjustments, Cyert & March (1963) contend that available slack enables companies to experiment with new tactics and creative initiatives, and as a result, a more favourable connection is predicted.
Agency theory beliefs imply that managers may use extra resources to engage in excessive diversification, interventionism, excessive budgeting, and ineffective R&D investment activities (Geiger & Cashen, 2002; Jensen & Meckling, 1976; Salge & Vera, 2013; Tan & Peng, 2003). For instance, according to Jensen (993), having more spare resources may lead a business to take bigger risks, spend excessive amounts of money on R&D initiatives, or even engage in doubtful ventures that seldom result in value-added innovation (Jiao et al., 2021; C. L. Lee & Wu, 2016). Businesses that pursue high radical innovation are linked to the Prospector strategy type (Sollosy et al., 2019). The above justifications help us to offer
the following theory based on the latitude that enterprises give to excess expenses and latitude inefficiency perspectives:
Ha2: The positive relationship between prospector, defender and analyzer strategy and firm performance influenced by available slack.
Moderating Impact of Potential Slack between Business Strategy and Firm Performance The Potential slack has been operationalized through the use of financial leverage indicators such as a company's debt to equity ratio (Marlin & Geiger, 2015). This external slack component shows a firm's capacity to access resources through debt financing. It is suggested that innovation is promoted since the risks of testing are mitigated when outside resources are available, implying a positive link between potential slack and creativity (Geiger & Cashen, 2002). When the entrepreneur in start-ups deliberately synchronizes investing strategy and potential slack, the best result is created (Symeonidou, 2013). Denis & McKeon (2012) research indicates that companies use potential slack in the form of extra financing capacity to absorb sizeable positive shocks to their investment opportunity sets. According to Jong et al. (2012) analysis of whether companies maintain their debt capacity to lessen future investment distortions, firms with higher levels of unused debt capacity spend more in the coming years than do firms with lower levels of unused loan capacity. In investigation of the relationship between financial flexibility and strategic investment abilities, discovered that organizations with greater financial flexibility make better investments that eventually provide anomalous returns Marchica & Mura (2010). Marchica & Mura (2010) discover that the performance of investments and firms are significantly and favourably impacted by financial flexibility in term of debt capacity. According to earlier studies, the relationship between slack and innovation is advantageous and remains so even as slack increases. Because the purpose of potential slack is to analyzer how it is used, it is not anticipated that it would have the same agency issues as internal slack, including information asymmetry between principals and agents (Geiger & Cashen, 2002; Ullah et al., 2019). Given this, significant amounts of potential slack are likely to be helpful to company innovation, depending on accessible and recoverable slack (Marlin & Geiger, 2015).
Cherkasova & Kuzmin (2018) findings show that financially flexible businesses increase their investment spending and implement more successful investment strategies by lowering levels of over- and underinvestment. Companies that are financially flexible are better able to make wise investments during times of crisis, but there is no discernible difference between large and small businesses or between developed and developing nations in terms of financial flexibility. According to Troilo et al. (2014), analyzer businesses must invest in innovation to provide the groundwork for their long-term financial stability and performance. They depend on steady domain cash flows to sustain their innovative activities. As a result, we believe that a firm's performance in respect to its potential slack will be greatly influenced by its business strategy. We also conclude that there is a causal link between potential slack and firm performance, i.e., that reducing potential slack increases investment efficiency, which in turn improves companies' performance. In other words, potential slack influence an investment strategy its performance level. In conclusion, a number of theories, including the free cash flow theory, the pecking order theory, the resource-based perspective of the company, and the behavioural theory of the firm, show that organizational slack encourages and enables investment strategies to enhance performance. Consequently this study predict that:
Ha3: The positive relationship between prospector, defender and analyzer strategy and firm performance influenced by potential slack.
Moderating Impact of Recoverable Slack between Business Strategy and Firm Performance
Although recoverable slack is different from available slack, it still falls under the umbrella of internal slack, and as a result, its relationship with strategy and performance follows a lot of the same rationale. For instance, some companies retain more personnel than necessary to handle the peaks and valleys of demand and everyday business operations. Costs are increased, but there is a safety net to ensure effectiveness if demand increases and embedded resources to support experimentation and the
emergence of innovative companies (Ateeq et al., 2022; Cyert & March, 1963). As a result, it is suggested that recoverable slack has a favourable influence on corporate innovation. However, it might be claimed that abundant recoverable spare resources will no longer boost innovation.
Agency theorists contend that when there are recoverable surplus resources, managers are attracted to self-serving and wasteful behaviour, which increases the likelihood of weak organizational controls and poor resource decisions (Jensen & Meckling, 1976). It is believed that recoverable slack in the form of excess workers or capital embedded in overhead might be challenging to recover, and that factors like power and politics can negatively affect the recovery of this kind of slack (Herold et al., 2006). This is not the case with available slack; yet, this logic also supports a similar link in that the availability of recoverable slack should enhance innovation, but the advantages of recoverable slack will be lessened or abolished at some point. Considering the conflicting theories in the literature, both an abundance of recoverable slack and even a shortfall of it should be harmful to investing strategies (Geiger & Cashen, 2002). Consequently, the study predict the following:
Ha4: The positive relationship between prospector, defender and analyzer's strategy and firm performance weakens as the amount of recoverable slack increase.
2. Methodology
The best methodology must be chosen to provide a reliable research solution, as research quality and results might vary according to the methodology used. Population and Sample Size and Data Collection
The current study initially selected all 518 firms listed at Pakistan Stock Exchange (PSX) for the period of sixteen years over 2006- 2021 in order to establish the relationship between business strategy and the performance of the firms and to determine the moderating role of organizational slack between this established relationship. First from the selected firms, we excluded the 97 financial sector companies we initially selected because these institutions have different standards, laws, and investment philosophies. Financial companies, such as banks, insurance companies, mutual funds, etc., deal largely with financial products. Second, we excluded 74- firms that had samples of missing data, and exclude companies with negative revenues, as is standard (Magerakis & Habib, 2021). As a result, employed a final unbalanced panel data sample of 374 non-financial firms using the above techniques. Variables Measurement
This study uses four performance measures (dependent variables) as previously used by (Jamil Anwar, 2017a; Siddique et al., 2022a). In order to remove bias from the data and provide a more comprehensive and comprehensive picture of performance, many financial performance measures are utilised (Salavou, 2015).
Net Profit before tax (NPBT) ^
Net Profit befote tax (NPBT)
Total Common Shareholders Equity
Net Profit before lax (NPBT) ROS = -—" , x 100
1
ROF, =
* 100
Tnbin's Q =
Tutal Sales
Market Value of Equity + Equity Reserves + Tots I Debts Buuk Value uf All Assets
Measures of Strategy: Independent Variables
By following the previous research (Anwar & Hasnu, 2016; Bentley et al., 2013; Higgins et al., 2015; Jamil Anwar, 2017b; Siddique & Rasheed, 2023b), this study measures the strategic kinds using the four characteristics listed below:
2
3
4
MESR -
Selling, general and administrative expenses (SG &A)
Sales
Ending Value nf Sales Beginmg Value Sales ^^ Fixed Assets
3
4
According to First, we calculate each of the four variables using a rolling average of the yearly ratios for the previous five years. Then, for each industry (represented by a two-digit SIC code) and year, we group the four variables into quintiles. Therefore, variable ratio is then divided into quintiles. The highest quintile variables for each observation were given a score of 4, the second-highest group received a score of 3, and so on all the way to the lowest rank. All variables may be evaluated in this way, with the exception capital intensity ratio. Hence, capital intensity variable is used to generate the reverse ranking whose components are the opposite of those described above. Because prospectors have lower capital intensity, the observations in the highest (lowest) quintile are scored as 1, and the ratio of net PPE to total assets is reverse scored (4). The next step is to add the rankings' scores so that each observation has a minimum value of 4 and a maximum value of 16. In accordance with organizational theory, the results of the four strategy measures are added together to give each company a discrete "Strategy" score that ranges along a continuum in value from 4 to 16, with prospector, analyzers, defender and reactor firms. Higher strategy score (14-16) represents a firm pursuing a prospector strategy, and second highest score (9-13) represents an analyzer strategy, third highest strategy score (5-8) represents a defender strategy and the last lower score (o-4) represent reactor strategy.
Organizational Slack
This study follows the financial drive measure of organizational slack. Consistent with previous studies by . This study use financial data to calculate organizational slack.
Available Slack
Available slack represents the firm's resources available to use not being used yet and allow management used to develop a strategy and future flexibility Greenley & Oktemgil, 1998). It is measured by current ratio.
Current Assets
Available Slack =
Current Liabilities
(Hailu et al., 2018; Marlin & Geiger, 2015)
1
2
Potential Slack
A company's ability to raise capital and allocate resources is limited by a large debt load. Potential slack can be approximated by the debt to asset ratio (S. Lee, 2014).
l'Jrb: (S. Lee, 2014; Marlin & Geiger,
Total Assets 2015)
Potential Slack =
Recoverable Slack =
Recoverable Slack
Recoverable Slack shows the resources used by a firm as excess costs (Kim et al., 2017), such as excess skilled labour, and excess machine capacity . Slack covered staff wages, office supplies, and many administrative expenses. However, the decrease the ratio the better the to be had assets for growing destiny approach options (Greenley & Oktemgil, 1998) .
Selling, Distribution and Administrative Expenses Hailuetal.,
Sale:; 2018; Marlin &
Geiger, 2015)
Control Variables
Firm size - One of the most significant and frequently utilized contingent factors in strategy-performance research is the size of the firm. Finn Size= Proxted by Natural Logarithm of firm's total assets
Siddique & Rasheed, 2023b; R. Zhang, 2016)
Firm Age According to corporate finance literature, the age of the business is also an important predictor of the firm's success (Pastor & Pietro, 2003; Siddique et al., 2022b; Siddique & Rasheed, 2023a). A.ge = "Difference between Observation Year ¿and Year of Establishment "
Industry- Industry is taken into account as a contingency variable alongside company size due to its significance in forecasting an organization's strategy and performance (R. Zhang, 2016). It is measured as natural logarithm of total assets.
Estimation of Techniques
Many investigations (Afza & Ahmed, 2017; Habib & Hasan, 2021; Liu & Kong, 2021; Yankanna-mohan, 2018) used panel regression estimate approaches to capture the findings. Furthermore, the Ordinary Least Squares (OLS) estimate approach is used to confirm the correlations. For the panel data set, several researchers used the OLS estimation approach (Habib & Hasan, 2021; Lin et al., 2021; Y. Zhang et al., 2018). The calculated models, as well as the relationship justifications, are shown below.
Empirical Econometric Equation
Panel data is used to test the study hypothesis, which is comprised of a cross-section (across firms) and time series (over years) in nature as previously used in strategy-performance relationships (Anwar, 2017; Chiu & Liaw, 2009). Our main empirical test will be based on the econometric equation. Using multiple linear regression and the following model followed by (Rudiawarni et al., 2022). The following estimate model is developed to investigate this relationship.
FP = ß0+ ß1PSIT + ß2DSIT+ß3ASIT+ß4SIZEIT+ß5AGEIT+ß6Y1YEARIT+ß7Y1INDUSTRYIT+E
1
FP = ß0 + ß1PSIT + ß2DSIjT+ß3ASIjT+ß4SIZEIjT+ß5AGEIjT+ß6ASlackIjT + ß7PSIT x ASlackIT + 2
ß8DSIT x SAlackjj + ß9ASIT x ASlackIT + ß10YlYEARIJ+ß11YlINDUSTRYIjT+Eijt
FP = ß0+ ß1PSIJ + ß2DSIJ+ß3ASIJ+ß4SIZEIj+ß5AGEIj+ß6PSlackIj + ß7PSI T x PSlackI T + 3
ß8DSIT x PSlackIT + ß9ASIT x PSlackIT + ß10YJYEARIT+ß11YJNDUSTRYIT+Ei t
FP = p0+ P1PSIJ. + p2DSIJ+p3ASIJ+p4SIZEIJ+p5AGEIJ+p6RSlackIJ + P7PSIT x RSlackIT + 4
P8DSlT x RSlackIT + p9ASIT x RSlackIT + p10YlYEARIj+p11YlINDUSTRYIj+Eit
Where FP stands for firm performance by using financial measures ROA, ROE, ROS and Tobin's Q; PS for prospector strategy; DS for defender strategy; AS for analyzer strategy; Size for Firm size, Age for firm age, Aslack stands for available slack, Pslack for potential slack, and Rslack for recoverable slack. Year and industry dummies are included for fixed effects, i for firm, and t for time.
Data Analysis and Results Descriptive Analysis
The actual data and the discussion in light of the literature are both covered in this section. The study employed descriptive statistics to look at how organizational slack, business strategy, and firm performance characteristics were distributed generally. Table 1, explains the statistical data, which contains the variables mean, standard deviation, minimum and maximum values. According to this data, the average ROA is 4.7%, the average ROE is 11.3%, the average ROS is 1.3%, and the average Tobin's Q is 0.782. These findings are consistent with a prior study on a firm listed on the Pakistan Exchange (Jamil Anwar, 2017a). The Pakistani economy is expected to see significant growth throughout the sample period, as per Tobin's Q mean of.782 Corresponding to this, statistics demonstrate that listed firms prioritize using the analyzer strategy for growth, with a mean of 0.4410; the defender strategy receives a second priority, with a mean of 0.299; and fewer firms engage in the innovative prospector strategy, with a mean of 0.238. Moreover, data show that potential slack is second greatest in terms of available space slack with a mean of 0.583, while recoverable slack is lowest with a mean of 0.093. Based on these summary data, it may be concluded that the sample utilized in this study is comparable to those used in other studies on the strategy and slacks of the Pakistan business community (Jamil Anwar, 2017b; Javid & Saleem, 2020).
Table 1 Descriptive Analysis
Variable ROA ROE ROS Tobin's Q Prospector Strategy Analyzer Strategy Defender Strategy Availabl e Slack Potenti al Slack Recovera ble Firm Age Firm Size
Mean 0.047 0.113 0.013 0.782 0.238 0.441 0.299 1.352 0.583 0.093 35.351 15.138
Std. Dev. 0.102 0.254 0.181 0.776 0.426 0.497 0.458 0.937 0.203 0.077 14.755 1.598
Min 0.145 0.478 0.548 -0.374 0 0 0 0.231 0.174 0.016 13 12.308
Max 0.267 0.641 0.295 2.831 1 1 1 3.975 1.191 0.412 63 18.09
Diagnostic tests for multicollinearity were run along with regression analysis. To show the stability of the regression model, the variance inflation factor (VIF) is presented for each variable. The stability of the regression model is negatively correlated with the VIFs. Any individual VIF greater than 10 may be a sign that multicollinearity is possibly affecting the least squares estimates of the regression coefficients (Chen & Jermias, 2014). According to Table 1's column 1, all of the variables employed in this study had VIF values lower than ten, which is an indication that multicollinearity is not an issue when interpreting the study's findings.
Endogeneity
It is conceivable that reverse causality will take place and confuse the merely coincidental relationship between organizational slack, corporate strategy, and financial performance. We employ a number of generalized method of moments estimation (GMM) regressions to address potential endogeneity. We use the dependent variable's one-period lag specifically as an instrumental variable because a strategy's effects—positive or negative—on financial success could not be immediate as previously used by; Liu &
Kong, 2021; Ullah et al., 2021). The baseline regression of Liu & Kong (2021), Bentley-Goode et al. (2019), and Wiersma (2017), revealed that firm size and R&D expenses have a positive relation. The Hausman test is also used in this study for panel data, and the results show that fixed effects are appropriate with P-values around 1%. The GMM's estimated models' findings are presented in Table 3-6. Auto correlation and over identification tests are performed after each regression and values are stated against each model.
3. Results and Discussion
To examine Hypothesis 1, equation 1 is used and findings are shown in Table 3, model 1 -5, that are in line with (Bortoluzzi et al., 2020; Jamil Anwar, 2017b; Miles et al., 1978), and confirm that all three strategies are equally viable and have positive association with firm financial performance. To examine Hypothesis 2, equation 2 is used and findings are shown in Table 4, Model 1 -4, and to examine Hypothesis 3, equation 3 is used and findings are shown in Table 5, Model 1-4. The findings back up hypotheses 2-3 and are consistent with Park & Hwang (2016) , who argue that a business with a core competency may decide on the sort of strategy to use, create, and implement while presenting the direction through resource input. This allows for the efficient use of resources and promotes high performance. The emerging market businesses in our sample tend to fare better when resource-based capabilities support a cost leadership strategy (Chandler & Hanks, 1994). Moreover, by refuting the agency theory's claim that slack resources are the root of the agency problem and are redundant costs that should be minimised to improve firm performance, the result supports the RBV premise that a high degree of available and potential slack benefits the company. The results are consistent with Javid & Saleem (2020) and support the study's hypotheses 2-3 that accessible slack moderates the association between business strategy and company performance.
To examine Hypothesis 4, equation 4, is used and findings are shown in Table 6, Model 1-4, and findings confirm that recoverable slack's interaction with Miles and Snow's strategy for firm performance vary with change in performance measure and strategy types. Findings for recoverable slack interaction with business strategy are consistent with (Love & Nohria, 2005; Wiersma, 2017) mention that recoverable slack with surplus employees or capital entrenched in overhead can be difficult to recover. The findings suggest that the level of firm performance is worse for businesses with relatively high levels of recoverable slack.
Table 3 Generalized method of moments estimation (GMM)
Variables Model 1 Model 2 Model 3 Model 4
ROA ROE ROS Tobin's Q
Performance t-1 .419*** .367*** .449*** .955***
(651.23) (1034.25) (3774.39) (1499.84)
Firm Size .007*** .006*** .025*** -.005***
(64.47) (48.52) (267.28) (-237.33)
Prospector Strategy .018*** .089*** .041*** .017***
(56.93) (125.25) (120.84) (329.84)
Analyzer Strategy .006*** .062*** .026*** .017***
(20.27) (180.20) (98.32) (328.88)
Defender Strategy -.001*** .043*** Q»J *** .013***
(-5.81) (148.47) (41.10) (236.59)
Firm Age -0.0005*** .0001*** -.002*** .0003***
(-27.25) (4.70) (-112.98) (124.97)
Constant -.071*** -.076*** -.322*** .188***
(-29.83) (-29.77) (-176.61) (90.21)
Year/Industry effect Yes Yes Yes Yes
Instrument/Group 302/374 302/374 301/374 301/372
Chi-square (Prob.>Chi2) 8.64e+06 6.07e+06 3.41e+07 3.69e+06
AR (2) test (P-Value) 0.1033 0.1544 0.5751 0.1622
Sargan Test (P-Value) 0.056 0.0939 0.0334 0.0551
Number of observations 4742 4742 4742 3916
223
Notes: The GMM regression findings for the impact of Miles and Snow's typology on firm performance are presented in Table 3. The model takes year effects and industry effects into account. *1 %, **5%, and *** 10% significance. In parenthesis are the T-values. Endogeneity and auto correlation problems are addressed by using a lag-based dependent variable as an instrument variable. The number of instruments, the number of groups, the second-order auto correlation, and the endogeneity test are carried out after each regression, and the corresponding values are listed in the table next to each model.
Table 4 Generalized method of moments estimation (GMM)
Variables Model 1 Model 2 Model 3 Model 4
ROA ROE ROS Tobin's Q
Performance t-1 .33*** .342*** .393*** .639***
(277.75) (436.84) (277.75) (1457.74)
Firm Size .004*** .005*** .024*** .009***
(13.80) (24.42) (115.06) (42.71)
Prospector -.016*** .065*** -.006*** -.133***
(-7.64) (31.57) (-4.48) (-50.66)
Analyzer -.013*** .067*** .016*** -.109***
(-5.71) (35.17) (13.31) (-55.89)
Defender -.071*** .013*** .001 -.062***
(-28.80) (5.5) (0.79) (-25.48)
Available Slack .015*** .047*** .06*** .114***
(5.77) (20.08) (60.63) (40.69)
Prospector x Available Slack .086*** .075*** .029*** 122***
(35.3) (32.73) (35.03) (35.72)
Analyzer x Available Slack .023*** -.003 .006*** .113***
(9.3) (-1.46) (9.30) (41.27)
Defender x Available Slack .018*** -.014*** .002*** .06***
(7.26) (-6.08) (7.26) (19.40)
Firm Age 0.0001*** 0.0003*** -.001*** .006***
(4.58) (15.17) (-49.54) (166.92)
Constant -.067*** -.135*** -.396*** -.267***
(-12.45) (-32.20) (-118.58) (-69.34)
Instrument/Group 306/374 346/374 346/374 346/374
Chi-square 1.83e+06 5.13e+06 4.23e+07 6.23e+07
(000) (0.000) (0.000) (0.000)
AR (2) test (P-Value) 0.0960 0.1725 0.3795 0.4777
Sargan Test (P-Value) 0.6826 0.5566 0.2264 0.3773
Number of observations 4496 4496 4496 4496
Notes: The GMM regression findings for the impact of available slack interaction with business strategies on firm performance are presented in Table 4. The model takes year effects and industry effects into account. *1%, **5%, and *** 10% significance. In parenthesis are the T-values. Endogeneity and auto correlation problems are addressed by using a lag-based dependent variable as an instrument variable. The number of instruments, the number of groups, the second-order auto correlation, and the endogeneity test are carried out after each regression, and the corresponding values are listed in the table next to each model.
Table 5 Generalized method of moments estimation (GMM)
Variables Model 1 Model 2 Model 3 Model 4
ROA ROE ROS Tobin's Q
Performance t-i .381*** .341*** .377*** .631***
(584.06) (392.67) (2729.11) (2809.96)
Firm Size -0.0001 .009*** .016*** -.007***
(-0.75) (30.86) (261.36) (-41.28)
Prospector -.003*** -.052*** -.055*** -.213***
(-3.11) (-30.46) (-169.25) (-258.49)
Analyzer .001* .001 -.029*** -.183***
(1.94) (0.57) (-173.77) (-281.97)
Defender -.002** .006*** -.043*** -. 141 ***
(-2.38) (7.68) (-323.16) (-198.17)
Potential Slack .053*** -.042*** .095*** .175***
(46.84) (-53.00) (537.16) (338.15)
Prospector x Potential Slack .045*** .126*** .073*** .206***
(33.97) (105.89) (306.78) (188.55)
Analyzer x Potential Slack .008*** .05*** .035*** Q***
(6.82) (64.77) (411.28) (304.04)
Defender x Potential Slack .005*** .037*** .038*** .141***
(3.65) (64.44) (306.30) (220.63)
Firm Age -0.0002*** .001*** -.002*** .007***
(-13.46) (19.06) (-167.22) (338.
15)
Constant .029*** -.126*** -.233*** .028***
(12.95) (-24.69) (-237.99) (12.92)
Instrument/Group 348/374 294/374 345/374 345/374
Chi-square 1.27e+07 6.48e+06 1.49e+09 4.49e+08
AR (2) test (P-Value) 0.06 0.1967 0.3277 0.5335
Sargan Test (P-Value) 0.4023 0.1019 0.2791 0.4386
Number of observations 4742 4496 4496 4496
Notes: The GMM regression findings for the impact of potential slack interaction with business strategies on firm performance are presented in Table 5. The model takes year effects and industry effects into account. *1%, **5%, and *** 10% significance. In parenthesis are the T-values. Endogeneity and auto correlation problems are addressed by using a lag-based dependent variable as an instrument variable. The number of instruments, the number of groups, the second-order auto correlation, and the endogeneity test are carried out after each regression, and the corresponding values are listed in the table next to each model.
Table 6 Generalized method of moments estimation (GMM)
Variables Model 1 Model 2 Model 3 Model 4
ROA ROE ROS Tobin's Q
Performance t-1 .373*** .353*** 722***
(203.09) (196.12) (447.91) (362.30)
Firm Size .108*** .017*** .027*** -.026***
(147.59) (45.27) (78.46) (-28.12
Prospector .088*** .138*** .072*** .065**
(17.37) (9.58) (7.97) (2.51)
Analyzer .057*** .065*** .049*** .028
(11.13) (3.96) (5.42) (1.14)
Defender .049*** .049*** .042*** .031
(9.53) (5.86) (4.73) (1.25)
Recoverable Slack .009 -.555*** -.839*** .361*
(0.25) (-3.37) (-12.17) (1.68)
Prospector x Recoverable Slack -.435*** -.426*** -.216*** -.683***
(-12.57) (-2.54) (-3.14) (-3.23)
Analyzer x Recoverable Slack -.282*** .033 -.115* -.078
(-8.16) (0.20) (-1.66) (-0.37)
Defender x Recoverable Slack -.241*** .101 -.083 -.539**
(-6.92) (0.62) (-1.20) (-2.54)
Firm Age 0.0005*** -.001*** -.001*** .008***
(16.33) (-37.04) (-30.13) (90.50)
Constant -.007 -.051*** -.234*** .249***
(-1.16) (-3.02) (-24.94) (9.27)
Instrument/Group 262/372 305/372 305/372 276/372
Chi-square 4.10e+06 4.52e+04 1.41e+06 2.82e+06
AR (2) test (P-Value) 0.56 0.52 0.80 0.6513
Sargan Test (P-Value) 0.0853 0.1109 0.2240 0.0811
Number of observations 4280 4280 4280 4280
Notes: The GMM regression findings for the impact of recoverable slack interaction with business strategies on firm performance are presented in Table 6. The model takes year effects and industry effects into account. *1%, **5%, and *** 10% significance. In parenthesis are the T-values. Endogeneity and autocorrelation problems are addressed by using a lag-based dependent variable as an instrument variable. The number of instruments, the number of groups, the second-order autocorrelation, and the endogeneity test are carried out after each regression, and the corresponding values are listed in the table next to each model.
4. CONCLUSION OF THE STUDY
This study's objective was to determine a connection between organizational slack, Miles and Snow's typology; prospector, defender, and analyst, and financial performance as determined by ROA, ROE, ROS, and Tobin's Q. The GMM (generalized method of moments estimation) methodology was used in this study by controlling auto correlation and endogeneity to test the hypothesis using a sample of 374 firms that are listed on the Pakistan Stock Exchange. The data spans 16 years, from 2006 to 2021. Tobin's Q, ROA, ROE, and ROS are used as the dependent variables, while prospector, analyst, and defender are developed as dummy variables to assess the business strategy. Organizational slack, which includes available, potential, and recoverable slack, mediates the relationship between the dependent and independent variables.
The findings back up the hypothesis that a business with a core competency may decide on the sort of strategy to use, create, and implement while presenting the direction through resource input. This allows for the efficient use of resources and promotes high performance (Park & Hwang, 2016). The link between Miles and Snow's archetypes and economic success is strengthened by the moderating impact of organizational slack, both available and potential. The conclusion drawn from the results is that the potential and available slack interaction with Miles and Snow's typology (1978) has a significant and favourable impact on firm performance. Second, in the context of Pakistan, the agency issue appears immaterial. Findings for recoverable slack interaction with business strategy mentioned that recoverable slack with surplus employees or capital entrenched in overhead can be difficult to recover. The findings suggest that the level of firm performance is worse for businesses with relatively high levels of recoverable slack.
In contrast to this recoverable slack interaction with prospector, analyzer, and defender strategies, relationships differ depending on strategy and financial performance metric. The statistical findings show that organizational slack capability has an impact on the prospector, analyzer, and defender strategies at the business level. Prospector and defender strategies exhibit strengthened relationships with financial performance when available, and potential slack types interact with them. This is true for both low-cost as defender and innovative strategies like prospector as well as a combination of both analyzer tactics. Also, the defender approach, the capacity to produce, and the inventive or hybrid strategy are all negatively impacted by the recoverable slacks capabilities. This suggests that performance is increased when a strategy is only chosen based on the strength of available resources.
These findings demonstrate that a key factor in venture enterprises' excellent success is the strategic and resource alignment.
Theoretically and practically, this theoretical integration guide that joint efforts of organization resources (available slack, recoverable and potential slack) and business strategy influence firm performance. Findings suggest that recoverable slack should be lower as they are not easily recoverable to reuse to enhance performance. Second, the study findings will benefit practitioners and managers, particularly those working in emerging markets. As well many managers desire to enhance the firm performance and have a variety of strategies and a variety of organizational slack but do not understand to choose the strategy and adjustment of slack, which can enhance the investment efficiency and firm performance. Finally, the study findings will lead investors by imparting value to the allocation of resources to maximize the return to investors, as it is the quality of investment decisions that maximize the investors' financial positions. Therefore, investors will be able to understand better these factors (business strategy, resources, and economic periods) for making investment decisions. There are certain limitations to the current study. First, regardless of the type of firm, every firm registered on PSX is included in the sample. The current analysis overlooks the sample's division based on variations in industries. Yet doing so closes gaps brought on by variances in the industries and other business strategies with various levels of organizational slack, for investment efficiency and performance. Because of this, the study's analysis of the whole business is constrained, which makes it inappropriate and illogical for generalization. Last but not least, the study's foundation is a developing nation like Pakistan. As a result, the conclusions cannot be applied generally.
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