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Article

Examining Environmental Turbulence Intensity: A Strategic Agility and Innovativeness Approach on Firm Performance in Environmental Turbulence Situations

by
Tugkan Arici
* and
M. Sahin Gok
Faculty of Business, Gebze Technical University, Kocaeli 41400, Turkey
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(6), 5364; https://doi.org/10.3390/su15065364
Submission received: 7 February 2023 / Revised: 2 March 2023 / Accepted: 3 March 2023 / Published: 17 March 2023
Browse Figure
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Abstract

:
Environmental turbulence refers to the unpredictable changes, developments, and uncertainties in a firm’s external environment. Environmental turbulence consists of market turbulence, technological turbulence, and competition intensity. It causes a shortening of firms’ product life cycles, changes in customer demands, and rapid technological developments. Companies do not control the changes in their external environment. In addition, they cannot manage change by using traditional methods where environmental factors are constantly changing. Thus, environmental turbulence and strategic plans might be reconsidered in today’s business world. This article examines the intensity of environmental turbulence from the strategic agility and innovativeness perspective. The study was conducted using data from Turkey, including medium-high or high technology firms that were located in a technopark or had an R&D center. The survey method was used to collect data for the study and the SPSS Process macro was used to analyze the effects of moderator variables on the relationship between strategic agility and firm innovativeness. Findings indicate that strategic agility positively affects firm innovativeness and that this effect might decrease due to increases in turbulence intensity. Moreover, firm innovativeness positively affects performance, and this effect becomes more robust with increases in turbulence intensity. This study provides practical implications for companies and researchers depending on environmental turbulence diversity.

1. Introduction

Rapid and dynamic developments have occurred in the information technologies, telecommunications, electronics, and machinery sectors. Accordingly, interactions between the sectors have unexpectedly increased in recent years. All these changes and developments have increased Environmental Turbulence (ET) intensity and competition [1] and Firms have begun focusing more on R&D to compete with these challenges. With the acceleration of R&D, new technological developments have emerged in many areas, the market has become more global, and the pace of change has increased even more. As a result of the chain developments experienced, ET intensity has increased, product life cycles have been shortened, the competitive position has changed, and new industrial markets have been formed by merging different industrial markets [1].
The uncertain situations occurring around firms are called turbulence. In [2] study, turbulence is the frequency of unpredictable developments that affect value creation and maintenance activities. In [3] study, turbulence is pregnant with unpredictable changes due to its unpredictable structure. Based on the definitions in the literature, we can define ET as the rapid increase in uncertainty as a result of unpredictable change and complexity in the external environment of firms [4,5].
Firms do not have the power to control the uncertainties occurring in their external environment. In addition, it is not possible to manage the changes with traditional methods in a dynamic environment where environmental factors are constantly changing. For this reason, firms should constantly collect information about their external environment. The firm’s external environment should be analyzed thoroughly, the intensity of ET should be calculated, and strategic plans should be prepared according to the turbulence intensity [6]. Uncertainty and competition intensity affect the firm’s investment decision [7]. In addition, the rate of technology adoption and economic growth slows down in sectors with low competitive power [8].
Studies regarding the effect of the strategic agility concept on firm innovation and firm performance in turbulent situations are limited [9]. Although variables such as innovation, knowledge capacity, and intellectual capital have been examined in some studies in the literature, the interaction effect of the three subdimensions that constitute ET, separately and as a whole, has been ignored in these studies [10,11,12]. In addition, ET is considered a single factor, and subdimensions are considered independent factors.
Due to the COVID-19 epidemic, businesses faced high environmental turbulence in 2019–2021. Although we are now in the post-COVID-19 era, developments such as global trade wars show that environmental uncertainties and turbulence will continue for a while. Therefore, this study makes significant contributions to both companies and researchers on ET.
This article investigates how ET and ET’s subdimensions emerge in different times and situations in a firm’s environment. Each factor has different effects on firm innovativeness and firm performance. This study argues that strategic agility has a positive effect on firm innovativeness. In addition, firm innovativeness positively affects firm performance in ET situations. Policy recommendations for increasing performance in uncertain situations are also presented in the study.
Previous studies have demonstrated that firm performance is affected by factors such as ET type and intensity. Additionally, it has been found that strategic agility has a positive impact on firm innovation in the context of ET. These findings are significant as they may lead to the development of sustainable economic models, which has become a major challenge for firms due to the increasing globalization of markets.
This study is organized as follows. The second section gives information about the theoretical background and hypotheses. The third chapter gives information about the data used in the study, the analysis method, the variables, and the existing literature on selecting the variables. In the following section, the analysis and findings are provided. The fifth and final section presents a discussion, conclusion, and suggestions for future work.

2. Literature Review and Hypothesis Development

As a result of the developments in information technologies, changes in customer demands and expectations, and increasing competition, the lifespan of products has shortened, and customer demands have become more complex [13,14,15,16]. Firms should be innovation-oriented and quickly respond to the changes to survive in this environment [17,18,19]. However, it is challenging to manage this situation today. Due to rapidly changing ET, firms have become unable to predict and follow changes in their external environment.
There is no generally accepted definition of environmental turbulence (ET). Ref. [20] defines ET as the degree of growth of the complexity and density of the external environment. Ref. [21] define ET as the rate of innovation in sectors where competition is unpredictable. According to [22], ET might be described as the rate of change within the industry and technology. While Ref. [23] defines ET as a dynamic, unpredictable, expanding, and fluctuating environment. Considering the definitions above, we might define ET as the chaotic situations arising due to chaos and disorder in the external environment. ET causes the shortening of product life cycles, rapid obsolescence of existing products, rapid increase in demands for products and services, and rapid change in technology and information [24].
ET is divided into three subdimensions in the literature (I) market turbulence, (ii) technological turbulence, and (iii) competition intensity [25,26]. Market turbulence (MT) refers to changes in customers’ requests and expectations, demands, market preferences, and product-production technologies [4,5,22,27,28,29,30]. Technological turbulence (TT) is defined as firms’ technology development rate and technology diversity [10,22,31,32]. Competition intensity (CI) expresses the degree of competition in the market and the predictability rate of competition [22,33,34]. Refs. [22,35] defined MT and TT as the most critical types of uncertainty in their studies while Ref. [34] define MT and CI as the most critical types of turbulence experienced by businesses. In this sense, it can be claimed that the types of turbulence occurring in the external environment of the firms are critical according to the structure, sector, size, and competitive situation. These turbulences should be simultaneously taken into consideration by firms.
Therefore, companies exposed to high ET factors should manage uncertainty, minimize risks, internalize proactive perspectives, and rapidly implement all kinds of strategies that will strengthen their creativity [16,36,37]; firms exposed to high environmental turbulence will only be successful by focusing on their strategic and operational efficiency [37].
The wind of change and uncertainty factors, which are difficult to predict, hinder the implementation of long-term strategic plans and highlight the concept of strategic agility [38]. The concept of strategic agility, first used in [39], was defined as “the ability to create the right products in the right place, at the right time and the right price”. Strategic agility allows one to be more sensitive to environmental factors in the planning phase of firm strategies and reorganize the firm in the face of uncertainties by making quick decisions [38,40]. Strategic agility can be briefly defined as the dynamic change of the resources and competencies of the firm [9].
Firms adapt to changes and improve competitiveness through strategic agility [41]. The concept of strategic agility has been accepted in the literature thanks to its structure, and it has recently become one of the most emphasized topics [41,42,43]. Strategic agility has emerged as a concept that can handle changes [44,45]. Many studies in the literature show that strategic agility positively affects firm performance [42,43,46,47]. In contrast, some studies show that strategic agility negatively affects firm performance. For example, Ref. [48] found in his study that there is a negative relationship between strategic agility and firm performance. [49] also stated that there was no effect between strategic agility and firm performance. It is thought that this situation arises from the uncertainty factors experienced in the external environment of the firms. In this study, we first hypothesize that strategic agility has an impact on firm performance:
Hypothesis 1 (H1):
There is a relationship between strategic agility and firm performance.
Due to technological and scientific developments, the world trade market is becoming more globalized at an increasing pace every day. While the global market allows consumers to access products with diverse features at affordable prices, it has also made the trade market more competitive and uncertain. Firms operating in such uncertain markets are under significant pressure, and this can affect the sustainability of their businesses. Firms facing the risk of losing their competitive advantage at any moment may struggle to develop sustainable income models [15].
To remain sustainable in markets where uncertainty and competition are high, companies must offer their customers products with the best features at the most affordable prices before their competitors. This requires a strong emphasis on innovation. Companies that cultivate a culture of innovation will be better equipped to adapt to new ideas, uncover hidden talents, and increase their innovation capacity over time. By increasing their innovation capacity, companies can achieve sustainable success by improving their speed of innovation [17].
Firms might focus on innovation and offer innovative products and services to the market to gain competitiveness [17]. Firms operating in highly competitive and uncertain markets need to prioritize innovation to stay sustainable. However, focusing solely on innovation is not enough. Responding quickly to changes is just as crucial [50]. Strategic agility is the capacity to respond quickly and accurately to rapid changes in uncertain environments and deliver in-demand products to customers in a complete and timely manner and might be a critical factor that responds most appropriately to customer requests in uncertain environments. While agility is crucial, it must be combined with a sound strategy to avoid confusion. On the other hand, a strategy without agility can lead to delayed implementation of planned actions. Therefore, to achieve sustainable success in highly competitive and uncertain markets, companies need to cultivate both strategic thinking and agility in their operations. Therefore, we hypothesize that strategic agility impacts firm innovativeness and that firm innovativeness has an impact on firm performance.
Hypothesis 2 (H2):
There is a relationship between strategic agility and firm innovativeness.
Hypothesis 3 (H3):
There is a relationship between firm innovativeness and firm performance.
Another issue missing in the literature is the lack of a comprehensive study examining whether ET is advantageous or disadvantageous. ET has been seen to increase pressure and negatively affect firms [51,52]. In accordance, Refs. [53,54] argued that CI weakens the relationship between firm performance and market trends and Ref. [55] stated that ET negatively affects the relationship between export orientation and export performance. Ref. [56] stated that a high ET will increase the level of uncertainty and cause a decrease in innovation activities. Furthermore, Ref. [5] stated that TT reduces the usability of new technologies and Ref. [57] stated that when TT is severe, product development teams lose their ability to make healthy decisions.
Another school of thought states that ET has positive effects on competitive advantage. Refs. [58,59] stated that ET causes an increase in innovation capacity and performance to provide a competitive advantage for firms. Ref. [60] stated that TT mediates the effect of product innovation and new product performance and argued that MT positively affects new product performance. Ref. [4] stated that ET pulls companies out of their comfort zones and causes new talents and firms to grow by specializing in technology and Ref. [61] stated that TT encourages technology teams to be more creative. Additionally, Ref. [24] claimed that ET increases organizational change capacity and Ref. [62] found a positive effect of MT on innovation.
Accordingly, ET and its subdimensions are both an opportunity and a threat for firms. In addition, thanks to strategic agility, firms might gain flexibility, predict the future, and consider uncertainty and risk factors [36,63,64]. Strategic agility emerges as a critical success factor for performance in high uncertainty [16,41,64,65,66]. However, Ref. [9] stated that low and medium ET factors do not significantly affect the relationship between strategic agility and firm performance and that high ET factors reduce the relationship.
There is no obvious indication that ET is an advantage or a disadvantage for firms. In addition, there is no consensus on what strategic steps should be taken to turn uncertainty into opportunity in cases of ET. For example, Ref. [34] stated that the CI weakens the relationship between firm innovativeness and business performance under increasing MT; turbulence might create a threat or opportunity depending on the situation and the severity of the turbulence.
It has been suggested in the literature that firms with high ET should be flexible, adaptable, and innovative [3,10]. Ref. [67] found that firms need innovation less in a stable external environment; on the contrary, they need a high level of differentiation in a dynamic external environment. Considering these findings in the literature, firms should focus on innovative products to gain a competitive advantage in environments with high uncertainty and unpredictability. Therefore, within the scope of this study, we hypothesize that each of the ET’s subdimensions affects firm performance differently. Furthermore, strategic agility, firm innovativeness, and firm performance positively affect the uncertainty event caused by ET.
Hypothesis 4 (H4):
All ET’s subdimensions have a moderator effect on the relationship between strategic agility and firm innovativeness.
Hypothesis 4a (H4a):
Market turbulence has a moderator effect on the relationship between strategic agility and firm innovativeness.
Hypothesis 4b (H4b):
Technological turbulence has a moderator effect on the relationship between strategic agility and firm innovativeness.
Hypothesis 4c (H4c):
Competitive intensity has a moderator effect on the relationship between strategic agility and firm innovativeness.
Hypothesis 5 (H5):
All ET’s subdimensions have a moderator effect on the relationship between firm innovativeness and firm performance.
Hypothesis 5a (H5a):
Market turbulence has a moderator effect on the relationship between firm innovativeness and firm performance.
Hypothesis 5b (H5b):
Technological turbulence has a moderator effect on the relationship between firm innovativeness and firm performance.
Hypothesis 5c (H5c):
Competition intensity has a moderator effect on the relationship between firm innovativeness and firm performance.
We aim to provide a contribution to the field in several aspects. First, we examine the relationship between firm innovativeness and performance in situations where ET occurs with different probabilities. We plan to analyze the effect of strategic agility on innovativeness and firm performance under ET conditions. Similar studies in the literature were generally carried out in developed countries, so we also aimed to conduct a model on developing countries and lead the studies in this field. Secondly, policy recommendations will be presented for sectors where technology, competition, and market dynamics are changing, uncertainty is high, and the current market conditions cannot be predicted. Third, a contribution to the literature will be made by analyzing the effects of interactions on firm innovativeness and firm performance if ET and its subdimensions occur with different possibilities, which is a subject that has not been studied before in the literature. Furthermore, we contribute to the existing literature by comprehensively analyzing environmental turbulence and company performance.

3. Methodology

3.1. Data Collection and Sampling

The medium-high and high technology sectors are at the forefront of the most affected sectors by uncertainty and unpredictability factors related to ET. Innovation is becoming more critical to companies operating in these sectors. Accordingly, environmental turbulence factors should be well analyzed within the framework of sector dynamics, and steps should be taken to alleviate these uncertainties [34].
Turkey is a member of international organizations such as the G-20, D-8, Organization for Economic Cooperation, OECD, and the Turkic Council and is defined as having an emerging market economy by the International Monetary Fund (IMF). According to nominal GDP, Turkey, one of the top 20 economies in the world, has a robust industrial system in medium-high technology sectors. In addition, Turkey has been making significant investments in advanced technology sectors in the last ten years. Turkish companies, which have a strong economic stance in the face of global economic fluctuations, especially the COVID-19 pandemic, are role models for other developing countries. Accordingly, companies located in Turkey formed the sample group within the scope of the study.
According to the OECD ISIC Rev.03 [68] technology classification, technopark firms operating in the medium-high and high technology sectors and R&D centers in Turkey were determined as the primary population within the scope of the study because firms operating in these sectors in Turkey are either located in technoparks or establishing their R&D Centers.
The data was obtained from the Ministry of Industry and Technology. According to the data: (i) There are 1229 R&D Centers in Turkey, which have worked on a total of 67,713 projects over the last 5 years (52,458 completed and 14,715 ongoing), resulting in the acquisition of approximately 32,000 patents. (ii) There are 75 active technoparks in Turkey, housing a total of 6560 firms. Technopark firms have worked on 63,550 projects over the last 10 years (49,756 completed and 13,794 ongoing), generating a total of 7.9 billion US dollars in exports and 45 billion US dollars in domestic sales from these projects.
The study used a questionnaire as the primary data collection method. The questionnaires were sent to all R&D Centers and 20% of technopark firms (1271 firms, selected at random), resulting in a total of 2500 samples (32% of the population). The top managers of the firms were surveyed, and 285 firms participated. After removing incomplete and inconsistent responses, a total of 268 valid survey results were obtained, resulting in a survey participation rate of 10.7%.

3.2. Scales

Multiple choice scales adapted from previous studies were used to test the developed hypotheses. Each variable was measured using a 1–5 type Likert scale, ranging from (1) “Strongly Disagree” to (5) “Strongly Agree”. The theoretical model of the study is presented in Figure 1. The survey questions, source, and factor loads are presented in Table 1.

4. Analysis and Findings

Firstly, the validity and reliability of the measurement were tested. A null model without any structural relationship was calculated to evaluate the psychometric properties of the measurement tools. Composite scale reliability (CR) and mean-variance subtracted (AVE) were used to calculate reliability. The PLS-based CR value for all measurements was above the threshold value of 0.70, and the AVE values exceeded the threshold value of 0.50. The convergent validity was also tested by calculating the standardized loadings of the measurements. It was found that all measurements showed a standardized loading exceeding 0.50 (see Table 2).
The hypothesis tests were measured with the SmartPLS 3.0 software program. The PLS approach [71] and resampling method were used to estimate the primary interaction and indirect effects and test the research model’s hypotheses and predictive power. T-statistics were calculated for all coefficients according to their stability in the sub-sample. The beta coefficients and their associated t-values showed the direction and effect of each assumed relationship.
Table 3 shows the results of hypothesis testing, including beta values and significance levels. The findings provided empirical evidence for the direct impact of strategic agility on firm performance and firm innovation. Therefore H1 and H2 are supported (β = 0.228, p < 0.51; β = 0.280 p < 0.01). In addition, firm innovativeness positively affects performance (β = 0.373 p < 0.01), thus H3 is supported.

4.1. Moderator Impact Analysis between Strategic Agility and Firm Innovativeness

In the second stage of the study, the SPSS Process macro was used to analyze the moderator variables’ effects on the relationship between strategic agility and firm innovativeness. The empirical results are presented in Table 4. Table 5 shows that the relationship between strategic agility and firm innovativeness changes when the moderator variable moves one standard deviation to the left (low density) and one standard deviation to the right (high density) [72].
In the first model, ET factors were included in the analysis as a moderator variable without separating. As a result of the analysis, it was determined that ET as a moderator variable affected the relationship, and the explanatory power of the established model was 51% (R2 = 0.5134; p < 0.01). It was also seen that the interaction effect (X.W) result of the model was also significant. Accordingly, ET factors have a moderator effect between strategic agility and firm innovativeness (β= −0.3445, p < 0.01), and the H4 hypothesis is accepted. In addition, the change in the effect between strategic agility and firm innovativeness was also analyzed regarding low, medium, and high ET. The results are presented in Table 5. ET, which was the moderator variable, had a low (β = 0.5957; p < 0.01) and moderate (β = 0.3120; p < 0.01) effect, while the effect of strategic agility on firm innovativeness was positive even in the decreasing trend. This finding provided evidence that, as the intensity of ET increases, the relationship between strategic agility and firm innovativeness continues, but the strength of the relationship decreases.
The second model analyzes the moderator effect of ET’s subdimensions separately. Findings indicate that (i) market turbulence (MT), (ii) technological turbulence (TT), and (iii) competition intensity (CI) significantly affected the relationship between strategic agility and firm innovativeness as a moderator variable (see Table 4). Accordingly, the H4a, H4b, and H4c hypotheses are accepted.
Furthermore, ET’s subdimensions were also studied as a moderator variable regarding the intensity degrees. These analyses aimed to understand the changing effect between strategic agility and firm innovativeness when the (i) MT, (ii) TT, and (iii) CI have low, medium, and high intensity.
Findings provided evidence that low and moderate MT intensity significantly affect the relationship between strategic agility and firm innovativeness as a moderator variable. In the case of high intensity of MT, we could not find a significant effect. Similar findings were found for TT and CI regarding the level of intensity (see Table 5). Interesting findings shed light on understanding the intensity levels of ET for practitioners and policy-makers. Thus, when the intensity of (i) MT, (ii) TT and (iii) CI increase, the relationship between strategic agility and firm innovativeness continues, but the strength of the relationship decreases.

4.2. Moderator Impact Analysis between Firm Innovativeness and Firm Performance

In the third stage of the study, similar analyses were carried out to investigate the effects of moderator variables (ET’s subdimensions) on the relationship between firm innovativeness and firm performance. The analysis results of the established models are presented in Table 6. Table 7 shows that the relationship between strategic agility and firm innovativeness changes when the moderator variable moves one standard deviation to the left (low density) and one standard deviation to the right (high density).
In the first model, all ET factors were included in the analysis as moderator variables without separating them. Results indicated that ET as a moderator variable significantly affected the relationship between firm innovativeness and firm performance. Thus the H5 hypothesis is accepted (see Table 6).
The moderator effects of ET’s subdimensions were also analyzed. Findings indicated that (i) MT, (ii) TT, and (iii) CI significantly affected the relationship between firm innovativeness and firm performance as a moderator variable (see Table 6). Accordingly, H5a, H5b, and H5c hypotheses are accepted.
Correspondingly, ET’s subdimensions were also studied as a moderator variable regarding the intensity degrees. These analyses aimed to understand the changing effect between firm innovativeness and firm performance when the (i) MT, (ii) TT, and (iii) CI have low, medium, and high intensities. Findings provided evidence that all intensity levels of ET’s subdimensions significantly positively affect the relationship between strategic agility and firm innovativeness as a moderator variable (see Table 7).

5. Discussion

Environmental turbulence is defined in the literature as the unpredictable change, development, and uncertainty in a firm’s external environment. Due to its characteristics, ET causes a shortening of the product life span of the firm, intensification of competition, changes in customer demands and expectations, and formation of dynamic market structures. The environment of uncertainty created by ET causes both inefficient uses of resources and ignorance of the opportunities brought by turbulence.
Firms do not have the power to control the changes in their external environment. They want to overcome the difficulties of turbulence and need to gather information about their external environment and prepare plans for every possible situation and condition. However, it is impossible to manage changes using traditional methods in a constantly changing environment. Therefore, ET should be measured, and strategic plans should be prepared according to turbulence intensities.
In the literature, ET variables were either considered as a single factor [73,74,75] or each factor was examined separately [76,77,78,79]. However, there was no study in the literature that examined ET’s subdimensions with different intensities combined. It is worth noting that ET’s subdimensions act independently and can also affect each other. For instance, a technology firm’s ET factor may be high in TT and medium in MT, while a textile firm’s ET factor may be high in MT and CI. Therefore, this study focused only on medium-high and high technology firms to examine the impact of ET’s subdimensions on firm performance.
Findings indicated that strategic agility has a positive and significant effect on firm innovation and also supports firm performance in ET situations. The effect of strategic agility on firm innovativeness is significant and positive in the low and moderate turbulence intensity. Furthermore, the relationship’s strength decreases depending on the increase in the intensity level. Based on these results, if MT, TT, CI, or ET factors co-occur in the firm environment, the effect of strategic agility on firm innovativeness continues. However, the severity of the relationship decreases as the turbulence intensity increases. Strategic agility is critical for achieving high competitiveness and firm performance in sectors where ET occurs at a low level. However, as the severity of uncertainty increases, strategic agility intention might not be the primary goal for firms.
Based on these results, it can be concluded that strategic agility is a crucial factor for firms operating in both stable and uncertain environments. The study found that strategic agility strongly supports firm performance in stable environments and continues to support firm performance in unstable environments. This finding is significant because ET can occur at any time, with different intensities and sub-variables. In the global market, firms are likely to face environmental uncertainties, and those that have incorporated strategic agility into their structures are better equipped to improve their firm performance and remain competitive in such conditions. Therefore, strategic agility can be considered a key parameter for achieving a sustainable competitive advantage and economic growth.
Our study also examined the relationship between firm innovativeness and firm performance. The results provide evidence that firm innovativeness significantly affects firm performance. According to the results, firm innovativeness also supports firm performance in ET situations. The moderator effect of ET on this relationship was also analyzed to understand the intensity changes; the relationship between innovativeness and performance became robust when the moderator variable’s intensity increases. These results are so agreeable that when the intensity of the uncertainty situation increases by one unit, the effect of firm innovativeness on firm performance doubles, excluding technological turbulence. In the case of TT, the impact of firm innovativeness on firm performance increased by 130%. Consequently, as the uncertainty in the firm environment increases, innovativeness becomes more critical for performance. In cases where uncertainty is high, it can be clearly stated that firms might improve their performance by giving more importance to R&D and innovation-based studies.
These findings partially align with previous studies in the literature. For instance, Ref. [80] found that while MT has a positive effect on innovation speed, CI has a negative effect. Ref. [81] discovered that both MT and TT have a positive impact on innovation, while CI has no effect. Refs. [82,83,84] also found that CI has a significant impact on firm innovation to some extent.
In our study, we found that firm innovativeness positively affects firm performance up to two times, regardless of the turbulence conditions. Moreover, we conducted an additional analysis that is not present in the literature. Given that the ET factors are interrelated and affect each other, we examined the relationships between the ET factors in pairs. Ref. [80] also found a significant positive relationship between each factor, suggesting that turbulence can have an interrelated impact in the medium to long term. As a result, we grouped the ET factors into pairs, as shown in Table 8.
Under all turbulent conditions, the effect of strategic agility on firm innovation was positive and decreasing. In contrast, the effect of firm innovativeness on firm performance was positive and increasing. When these results were evaluated together, it was determined that strategic agility has a positive effect on firm innovation and firm performance under all turbulent conditions. This is an important finding because this has not been demonstrated in previous studies.
However, the findings are not consistent with the results of [34]’s study. Ref. [34] stated that the CI would increase due to MT and, as a result, the relationship between firm innovativeness and performance would weaken. On the contrary, we found that ET factors further strengthen the relationship between firm innovativeness and performance. We think that the main reason for this situation is that firms will focus more on R&D and innovation and take innovative steps rapidly in cases of uncertainty. Therefore, the study indicates the importance of innovativeness in strategic agility and performance in cases of uncertainty.
Another finding obtained from our study is that TT has a more negligible effect than the other variables. We call this situation a reflection of the indecision about technology in an environment where technological uncertainty is intense. Therefore, it can be argued that more a robust performance might be achieved by R&D and innovation as uncertainty increases. However, if the main reason for the formation of uncertainty is TT, firms should apply different strategies. In such a case, focusing on technological and R&D studies may cause companies to reach their targets more slowly, and the presence of competition might lead to negative consequences.

6. Conclusions

This study examined the relationship between strategic agility, innovativeness, and performance under different ET factors. This issue has become even more important as local firms gain more presence in global markets. Unfortunately, firms do not have the power to control or alter the changes that occur in their external environment. Therefore, traditional management theories may not be effective in managing firms in dynamic competitive environments. As a result, firms should prepare alternative plans for dealing with external changes.
ET and its subdimensions were examined as separate moderator variables within the scope of the study. Consequently, it was found that strategic agility positively affects firm innovativeness and, this effect might decrease with the increases in turbulence intensity. Another finding is the relationship between firm innovativeness and firm performance. According to the findings, firm innovativeness positively affects firm performance, and this effect becomes more robust by the increases in turbulence intensity.
The findings obtained within the scope of the study contain important implications for firms. Contrary to popular belief, ET is not a disadvantage but an advantage for firms. The results showed that both strategic agility and firm innovation strengthen firm success in ET situations. When strategic agility and firm innovation are managed correctly, firm success will increase as turbulence increases. In particular, firms that need to improve performance should attach more importance to R&D and innovation-based studies. In addition, they should reconsider methods to support this innovation activity based on the TT intensity. At the same time, firms with strategic agility might improve innovativeness and performance. However, the power of strategic agility decreases with the intensity of uncertainty. In such cases, firms might incorporate an open innovation strategy or strengthen intellectual capital to improve their innovation performance.
Strategic agility is another important factor that can benefit firms operating in ET conditions. Research has shown that firms with strategic agility can increase both innovation and performance. However, it is worth noting that while strategic agility is more effective in low and moderate uncertainty situations, its impact on firm performance is lower in high uncertainty situations. Therefore, strategic agility can contribute more to firm performance in low and medium uncertainty situations. In high uncertainty situations, the use of strategic agility in combination with firm innovation can further enhance firm performance. Additionally, firms can adopt an open innovation strategy or strengthen their intellectual capital to boost innovation performance, ultimately leading to higher firm performance in high uncertainty situations.
The findings obtained provide important results for policymakers. Natural disasters such as earthquakes, floods, and tsunamis can cause great turbulence for companies. For instance, when two earthquakes with a magnitude of 7.6 and 7.8 consecutively occurred in Turkey, companies faced great uncertainty in the market and competition areas. It is evident that companies located in natural disaster-prone areas face high market and competition turbulences. In such cases, strategic agility can be used to make the companies’ assets and economic income models sustainable. In this way, companies can enhance their performance by making quick strategic plans. Therefore, the results obtained in this study help policymakers by shedding light on how to develop economic sustainability in regions affected by natural disasters.

7. Suggestions for Future Research

As in all research, there are some limitations to our study. The first is that ET factors were not handled with different intensities. Considering the dynamic structure of firms, the subdimension factors affecting the ET of each sector may have different intensities. We believe this could be another research topic for future studies. In addition, the characteristic features of the companies in our research were not included in the analysis. In future studies, research models might be expanded by including control variables such as the size of the firms.

Author Contributions

Conceptualization, T.A.; Methodology, T.A. and M.S.G.; Analysis, T.A.; Resources, M.S.G.; Writing, T.A. and M.S.G.; Review and Editing, M.S.G. All authors have read and agreed to the published version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article. We declare no financial or personal conflicts of interest.

Institutional Review Board Statement

The authors declared that there was no potential unethical behavior related to the research, authorship, and/or publication of this article.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the presence of proprietary information belonging to the firm.

Acknowledgments

This paper was supported by Gebze Technical University Scientific Research Projects (BAP) (No: 2022-A-102-19).

Conflicts of Interest

The authors declared no potential conflict of interest with respect to the research, authorship, and/or publication of this article.

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Sustainability 15 05364 g001 550
Figure 1. Theoretical model.
Figure 1. Theoretical model.
Sustainability 15 05364 g001
Table
Table 1. Scales and factor load.
Table 1. Scales and factor load.
VariablesSourceF.L.
Strategic Agility
SC1 Respond to changes in aggregate consumer demand.[64]0.68
SC2 Customize a product or service to suit an individual customer.0.71
SC3 React swiftly to new product or service launches by competitors.0.71
SC4 Introduce a new pricing schedule in response to changes in competitors’ prices.0.58
SC5 Expand into new regional or new markets.0.81
SC6 Change (i.e., expand or reduce) the variety of products or services available for sale.0.73
SC7 Adopt new technologies to produce better products or services.0.83
SC8 Switch suppliers to get better benefits of lower costs or better quality or improved delivery times.0.64
Firm Innovativeness
FY1 Innovation, based on research results, is readily accepted in our company.[5]0.91
FY2 In our company, management actively seeks innovative ideas.0.96
FY3 In our company, innovation is readily accepted in management.0.97
FY4 Our company encourages and supports innovative activities.0.98
FY5 New ideas are quickly accepted in our company.0.94
Firm Performance
FP1 The new service exceeded market share objectives.[69]0.83
FP2 The new service exceeded sales growth objectives.0.85
FP3 The new service exceeded sales objectives.0.85
FP4 The new service exceeded the return of investment objectives.0.79
FP5 Rapid increase in revenue.[70]0.80
FP6 Rapid increase in sales volume.0.82
FP7 Rapid increase in market share.0.79
FP8 Rapid increase in profits.0.78
FP9 Higher amount of new products.[4]0.67
FP10 Faster speed of new product launching.0.70
FP11 Higher new product sales revenue.0.80
FP12 Increasingly higher new product market share.0.88
Environmental Turbulence
Market1 In our kind of business, customers’ product preferences change quite a bit over time.[22]0.64
Market2 Our customers tend to look for a new product all the time.0.62
Market3 Sometimes our customers are very price-sensitive, but on other occasions, price is relatively unimportant.0.66
Market4 We are witnessing demand for our products and services from customers who never bought them before.0.82
Market5 New customers tend to have product-related needs that are different from those of our existing customers.0.64
Market6 We cater to many of the same customers that we used to in the past.0.86
Tech1 The technology in our industry is changing rapidly.0.91
Tech2 Technological changes provide big opportunities in our industry.0.93
Tech3 It is very difficult to forecast where the technology in our industry will be in the next 2 to 3 years.0.53
Tech4 A large number of new product ideas have been made possible through technological breakthroughs in our industry.0.75
Tech5 Technological developments in our industry are rather minor.0.16
Compe1 Competition in our industry is cutthroat.0.84
Compe2 There are many “promotion wars” in our industry.0.69
Compe3 Anything that one competitor can offer, others can match readily.0.64
Compe4 Price competition is a hallmark of our industry.0.64
Compe5 One hears of a new competitive move almost every day.0.62
Compe6 Our competitors are relatively weak.0.66
Table
Table 2. CR and AVE reliability values.
Table 2. CR and AVE reliability values.
NoVariables123456
1SC
2FI0.547 **
3FP0.271 **0.356 **
4Market0.435 **0.325 **0.138 *
5Tech0.292 **0.239 **0.175 **0.276 **
6Compe0.164 **0.158 **0.106 **0.158 **0.207 **
CR0.8950.9820.9510.8610.8180.777
AVE0.5180.9160.6080.5130.5170.541
α0.8660.9770.9430.8210.7850.612
* p < 0.05, ** p < 0.01. Note2: SC: Strategic Agility, FY: Firm Innovativeness, FP: Firm Performance, Market: Market Turbulence, Tech: Technological Turbulence, and Compe: Competitive Intensity.
Table
Table 3. Hypothesis test results.
Table 3. Hypothesis test results.
RelationshipsPath Coefficient (β)HypothesisResults
SC→FP0.228 **H1Supported
SC→FI0.280 ***H2Supported
FI→FP0.373 ***H3Supported
Note2. SC: Strategic Agility, FP: Firm Performance, and FI: Firm Innovativeness. ** p < 0.05, *** p < 0.01.
Table
Table 4. Moderator effects on strategic agility and firm innovativeness.
Table 4. Moderator effects on strategic agility and firm innovativeness.
Model 1—Environmental Turbulence Coeff.SEtp
Constant−1.01650.2621−3.87850.0001
Strategic Agility (X)1.54810.18048.58230.0000
Environmental Turbulence (W)0.31890.07354.33630.0000
Strategic Agility X Environmental Turbulence (X.W)−0.34450.0594−5.79870.0000
R2 = 0.5134, MSE = 0.4921, F(3, 265) = 92.841, p < 0.01
Model 2—Market Turbulence Coeff.SEtp
Constant0.09350.04572.04410.0419
Strategic Agility (X)0.24220.06433.76400.0002
Market Turbulence (W)0.26380.05454.84270.0000
Strategic Agility X Market Turbulence (X.W)−0.15760.0302−5.21000.0000
R2 = 0.5310, MSE = 0.4744, F(3, 265) = 99.627, p < 0.01
Model 3—Technological Turbulence Coeff.SEtp
Constant0.15080.04873.09450.0022
Strategic Agility (X)0.34040.06275.42400.0000
Technological Turbulence (W)0.05130.04991.02770.3050
Strategic Agility X Technological Turbulence (X.W)−0.31160.0458−6.80590.0000
R2 = 0.5005, MSE = 0.5052, F(3, 265) = 88.174, p < 0.01
Model 4—Competitive Intensity Coeff.SEtp
Constant0.08640.04162.07910.0386
Strategic Agility (X)0.25260.05724.41290.0000
Competitive Intensity (W)0.34750.0288.11160.0000
Strategic Agility X Competitive Intensity (X.W)−0.22660.0358−6.33110.0000
R2 = 0.5913, MSE = 0.4134, F(3, 265) = 88.174, p < 0.01
Table
Table 5. Effect of moderator variable intensities on strategic agility and firm innovativeness.
Table 5. Effect of moderator variable intensities on strategic agility and firm innovativeness.
IntensityWEffectSEtpLLCIULCI
Environmental
Turbulence		Low2.76470.59570.048612.26080.00000.500000.6914
Moderate3.58820.31200.6165.06080.00000.19060.4334
High4.11760.12960.08521.52180.1293−0.03810.2973
Market
Turbulence		Low−0.73870.35860.05456.57410.00000.25120.4660
Moderate0.28270.19760.06962.83790.00490.06050.3348
High0.74700.12450.07961.56420.1190−0.03220.2812
Technological
Turbulence		Low−1.02410.65940.050513.05270.00000.56000.7589
Moderate0.28180.25250.07133.53980.00050.11210.3930
High0.93480.04910.09510.51650.6060−0.13810.2363
Competitive
Intensity		Low−1.02410.52460.042912.24440.00000.44040.6092
Moderate0.28180.20530.06253.28570.00120.08230.3283
High0.9348−0.00780.0901−.08660.9311−0.18510.1695
Table
Table 6. Moderator effects on firm innovativeness and firm performance.
Table 6. Moderator effects on firm innovativeness and firm performance.
Model 1—Environmental Turbulence Coeff.SEtp
Constant−22.430.0549−4.08290.0001
Firm Innovativeness (X)1.00400.090711.07480.0000
Environmental Turbulence (W)0.10900.05631.97000.0490
Firm Innovativeness X Environmental Turbulence (X.W)0.48580.05149.45230.0000
R2 = 0.3494, MSE= 0.6581, F(3, 265) = 47.2348, p < 0.01
Model 2—Market Turbulence Coeff.SEtp
Constant−0.18480.0589−3.13980.0019
Firm Innovativeness (X)0.77380.09178.44060.0000
Market Turbulence (W)0.21910.07023.11930.0020
Firm Innovativeness X Market Turbulence (X.W)0.30920.04407.02310.0000
R2 = 0.2655, MSE = 0.7429, F(3, 265) = 31.8018, p < 0.01
Model 3—Technological Turbulence Coeff.SEtp
Constant−0.12130.0555−2.18370.0299
Firm Innovativeness (X)0.60280.06758.93130.0000
Technological Turbulence (W)0.11530.05861.97750.0490
Firm Innovativeness X Technological Turbulence (X.W)0.32830.04706.97860.0000
R2 = 0.2629, MSE = 0.7455, F(3, 265) = 31.3879, p < 0.01
Model 4—Competitive Intensity Coeff.SEtp
Constant−0.24080.0630−3.82120.0002
Firm Innovativeness (X)1.06650.12258.70760.0000
Competitive Intensity (W)0.04750.06410.74020.4599
Firm Innovativeness X Competitive Intensity (X.W)0.42690.06126.97860.0000
R2 = 0.2633, MSE = 0.7451, F(3, 265) = 31,4437, p < 0.01
Table
Table 7. Effect of moderator variable intensities on firm innovativeness and firm performance.
Table 7. Effect of moderator variable intensities on firm innovativeness and firm performance.
IntensityWEffectSEtpLLCIULCI
Environmental
Turbulence		Low−1.11540.46220.05778.00420.00000.34850.5759
Moderate0.15241.07800.096911.12130.00000.88711.2689
High0.96741.47390.133311.05490.00001.21141.7364
Market
Turbulence		Low−1.02410.26670.05814.58810.00000.15220.3811
Moderate0.28180.65930.07559.21460.00050.54680.8439
High0.93480.90970.09849.24470.00000.71591.1034
Technological
Turbulence		Low−0.73870.54540.07297.47830.00000.40180.6890
Moderate0.28270.86120.10078.55030.00000.66291.0595
High0.74701.00480.11698.59190.00000.77451.2350
Competitive
Intensity		Low−1.20160.55350.07117.78140.00000.41340.6935
Moderate0.20871.15560.13358.65440.00000.89271.4185
High1.14891.55700.18618.36880.00001.19071.9234
Table
Table 8. Environmental turbulence’s subdimension groups.
Table 8. Environmental turbulence’s subdimension groups.
#Market TurbulenceTechnological TurbulenceCompetitive Intensity
1YesYesNo
2NoYesYes
3YesNoYes
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Arici, T.; Gok, M.S. Examining Environmental Turbulence Intensity: A Strategic Agility and Innovativeness Approach on Firm Performance in Environmental Turbulence Situations. Sustainability 2023, 15, 5364. https://doi.org/10.3390/su15065364

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Arici T, Gok MS. Examining Environmental Turbulence Intensity: A Strategic Agility and Innovativeness Approach on Firm Performance in Environmental Turbulence Situations. Sustainability. 2023; 15(6):5364. https://doi.org/10.3390/su15065364

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Arici, Tugkan, and M. Sahin Gok. 2023. "Examining Environmental Turbulence Intensity: A Strategic Agility and Innovativeness Approach on Firm Performance in Environmental Turbulence Situations" Sustainability 15, no. 6: 5364. https://doi.org/10.3390/su15065364

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