This study examines the possible impact of Generic Competitive Strategies, Cost Leadership, Differentiation, and Focus, on the financial and non-financial Performance of Internet-based entrepreneurial ventures in the MENA region. Descriptive analytical methodology and exploratory research design, consisting of qualitative then quantitative approaches, were utilized. After qualitative semi-structured interviews, a five-point Likert scale questionnaire was sent to Internet-based entrepreneurial ventures. SPSS was used to describe and analyse the data of 201 filtered and screened questionnaires. The results indicate that all of the examined generic competitive strategies have positive direct impacts on the performance of Internet-based entrepreneurial ventures. Differentiation strategies have the highest impact on the performance of Internet entrepreneurial ventures in MENA region, followed by Cost Leadership, then Focus strategies. This paper concludes with a discussion of the managerial implications of these findings, future research recommendations, and limitations of the study.
Strategy is critical to an organization’s performance and long-term survival (Zott and Amit 2008; Elias 2019). Strategy determines how firms exploit opportunities in their environment, and without a competitive strategy, businesses will fail. With sweeping Internet adoption across the globe and the ever increasing role of Internet-based business (Leeflang et al. 2014), The effective strategy implantation has materialized as the source of competitive advantage, it is important to consider how competitive strategy plays a role in the new digital environment (Porter 2001; Srivastava 2014). Parnell (2010) stated that strategy plays a significant role in business performance, and that the clearer an organization’s articulation of its strategy, the better its performance is likely to be. Porter’s generic competitive strategies are among the most established frameworks for business analysis (Ormanidhi and Stringa 2008), thus they are used in the conceptual framework of this study’s analysis of Internet-based entrepreneurial ventures in the Middle East and North Africa (MENA) region. MENA incorporates 19 countries, including Algeria, Bahrain, Egypt, Iraq, Iran, Jordan, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Saudi Arabia, Syria, Tunisia, UAE, and Yemen. MENA has a gross GDP of about $3.3 trillion, representing around 4.5% of the global GDP. The region has a relatively small population, and aside from the GCC countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and UAE), the majority of MENA states are middle-income ones. MENA produces 60% of the world’s oil and 45% of its natural gas. Saudi Arabia has the largest economy in MENA, with a GDP of about $740 billion, followed by Iran ($333 billion), then UAE ($382 billion) and Egypt ($249 billion) (Kiprop 2019).
Studying an individual firm’s strategic choices allows for greater understanding of performance variations among similar firms (Lawless et al. 1989). However, measuring performance has been a challenging area in the business management field, despite the general consensus that organizations need to have accurate holistic metrics for evaluating firms’ well-being. Businesses use a variety of interrelated financial and non-financial performance measures that are common in their industrial fields. However, financial performance measures can be difficult to accurately assess across industries (Allen and Helms 2006), particularly due to differences in buyer power, supplier power, new entrants, and threat of substitution (Porter 1980). The competitive strategy of any business affects its competitiveness and performance.
Entrepreneurial ventures are vital to healthy economies (Cristina and Suzana 2016; Dinesh and Sushil 2019; Zaheer et al. 2019), Many entrepreneurial ventures are now solely based on the Internet, with various competitive strategies options. Internet businesses face many of the same and more issues than traditional ones due to the instability of the Internet environment, as well as the speed of change (Chen 2005; Zaheer et al. 2019). While the Internet gives firms a greater reach, it also causes a high degree of fragmentation (Chaffey 2015). Building trust is more difficult for Internet entrepreneurial ventures, since they do not normally have the benefit of physical interaction with customers, with implications for brand awareness and consumer relationships (Al-Abdallah and Abou-Moghli 2012). Previous studies, mainly in developed and well-developed countries, identified conflicting conclusions on the best competitive strategy to use in relation to entrepreneurial ventures’ performance (Guo et al. 2017; Zaheer et al. 2019). In general, pure play firms, which characteristically enter new markets solely through the Internet, have significantly higher failure rates than click and mortar ones, which use the Internet as an alternative channel of distribution. Moreover, there is a 22.8% failure rate for pure plays versus 2.8% for traditional business (Leeflang et al. 2014; Orendorff 2017). There are many reasons why Internet-based businesses fail, which include industry over-saturation, lack of sustainable funding, ineffective business models, insufficient performance monitoring, single-revenue source dependence, and a poor portal or website (Hirakubo and Friedman 2002; Ching 2019). However, the central reason Internet entrepreneurial ventures commonly fail is the absence of coherent strategy (Porter 2001; Hirakubo and Friedman 2002; Chaffey 2015). Internet-based business is not just about defining how to do business in an online environment, it defines how to do business differently by applying digital technologies (Al-Abdallah et al. 2014; Chaffey 2015). Therefore, issues of firm resources, actions, and activities in an online environment are addressed through a choice of strategy (King et al. 2007; Guo et al. 2017). Accordingly, it is important to inform new entrepreneurial ventures about the best available competitive strategies for them. With the lack of related studies in the MENA region in particular and in developing countries in general, this study investigates Porter’s competitive strategies to assess their applicability for online businesses in MENA region, and the impact of chosen strategy on the performance of the Internet-based entrepreneurial ventures is evaluated to determine the best strategy among the examined competitive strategies.
The significance of the study lays on the fact that Internet-based entrepreneurial ventures are generally more flexible (Shalender and Yadav 2019; Shukla et al. 2019; Evans and Bahrami 2020) than other ventures, they can change their competitive strategies far easier than larger firms which can lead to performance enhancement (Zhou and Wu 2010; Yadav and Sushil 2014; Acharya 2019; Birasnav et al. 2019; Brinckmann et al. 2019; Melnik et al. 2019; Nguyen 2020), accordingly, the results of this study can actually be adopted by the examined population, and not just for future considerations.
Performance can be defined as the result of all economic activities undertaken by a firm. Enhancing performance is the primary purpose of using business strategy (Zott and Amit 2008). However, measuring performance has been a challenging area in the business management field, despite the consensus that organizations need to have accurate holistic metrics for evaluating well-being. As noted previously, businesses use a variety of financial and non-financial performance measures that vary by industry, thus measures can be difficult to assess accurately across industries, especially for entrepreneurial ventures (Allen and Helms 2006; Abou-Moghli and Al-Abdallah 2018; Gupta and Gupta 2019), due to differences in buyer power, supplier power, new entrants, and the threat of substitutions (Porter 1980). Internet-based performance measures include customer retention, customer acquisition, market share, brand awareness, customer purchase frequency, recency and monetary value, webpage quality, and privacy issues (DeLone and McLean 2004; Bremser and Chung 2005; Hinton and Barnes 2009; Torres et al. 2013; Al-Abdallah et al. 2018).
Due to the variation in performance measurements, it is difficult to bring the metrics together in a holistic way. One of the few empirically tested holistic approaches to measuring online performance is the use of balanced scorecard to develop a construct that includes financial and non-financial performance (Sushil 2009; Huang et al. 2009). Measuring financial performance across industries and markets can be very hard because of difference in standards and expectations (Allen and Helms 2006), and the increased power of consumers in e-commerce increases their expectations to unprecedented levels, indicating the need for comprehensive performance measurements (Perera et al. 1997; Al-Abdallah 2013; Tarabasz 2013). Accordingly, both financial performance (represented by sales measures) and non-financial performance (represented by customer-related measures), are used to assess the performance of Internet entrepreneurial ventures in this study. The selection of these specific measures is because they are considered the most common and accessible measures to assess performance in relevant literature (DeLone and McLean 2004; Bremser and Chung 2005; Allen and Helms 2006; Hinton and Barnes 2009; Huang et al. 2009; Torres et al. 2013; Al-Abdallah et al. 2018). The detailed dimensions of each measure are presented in Table 1.
Generic Competitive Strategies
Michael Porter’s generic competitive strategies have been among the most influential framework used in marketing, conceptualizing strategy structure in terms of viability, clarity, simplicity, and generality (Ormanidhi and Stringa 2008). Porter identified three main strategies: cost leadership, differentiation, and focus (Porter 1980). These strategies are very useful in directing business and marketing decisions and controlling performance (Parnell 2006). Many of today’s new competitive strategies approaches have been developed based on, or in response to, Porter’s generic competitive strategies (Ormanidhi and Stringa 2008). In this study, only Internet-based entrepreneurial ventures that utilize one of Porter’s generic strategies are examined, in order to understand their impact on performance and evaluate the best strategy among them (Allen and Helms 2006; Abou-Moghli and Al-Abdallah 2018). Based on analysis of related literature, this study posits the following hypothesis:
Porter’s generic competitive strategies have positive direct impacts on the performance of Internet entrepreneurial ventures at α ≤ 0.05.
Cost leadership strategies purposely try to produce products at lower cost in order to offer products to consumers at lower or equal value to those of competitors. Ideally, this can be achieved through operational efficiency, economies of scale, resources capacity utilization, and improved access to raw materials, technologies, and product designs (Allen and Helms 2006). Cost leadership strategies are dictated to maintain or even enhance cost-cutting activities (Porter 1980). All activities performed by this strategy are aimed at reducing the cost of producing the product. Therefore, if necessary, cost leaders must discontinue products, or outsource certain processes to enhance cost reductions (Allen and Helms 2006). Due to this constant focus on price reduction, cost leaders tend to prefer and blossom in stable environments (Miller 1988).
Nonetheless, some studies suggested that cost leadership strategies have the worst performance of all competitive strategies when situated in a dynamic environment (Pertusa-Ortega et al. 2008). According to Block et al (2015) entrepreneurial ventures that utilize cost leadership typically do so out of immediate necessity, and this does not provide the best profit-generating platform for long-term growth. as they distract cost leaders from exploiting new market opportunities, as they are focused on protecting their current market share (Karagozoglu and Lindell 2004). In addition, cost leaders can face difficulty regarding research and development and innovation (Allen and Helms 2006). Larger, well-established firms can benefit from trimming their operational costs by cost leadership strategies, but entrepreneurial ventures are typically smaller and nimbler in their resource deployment, thus they tend to favor more straightforward, less complicated strategies aimed at aggressive market penetration by offering new or exciting products (Block et al. 2015). On the other hand, some studies found that Internet-based business using cost leadership strategies performed significantly better than any of the firms using other competitive strategies. Cost leadership strategies can utilize the reach of the Internet to gain a large market share (Zhuang and Lederer 2003). Once established with a critical mass of customers, it is much more difficult for cost leaders such as e-bay and Amazon to be displaced (Hirakubo and Friedman 2002).
Cost leadership strategies have positive direct impacts on the Performance of Internet entrepreneurial ventures at α ≤ 0.05.
Differentiation strategies seek to increase the perceived or actual value of a product to a customer through marketing, distribution, quality, efficiency, reliability, or style (Porter 1980; Miller 1988; Allen and Helms 2006; Agrawal et al. 2016). The primary aim of differentiation is to create a unique product that drives consumers to believe that there is no suitable alternative replacement for the product on offer. To achieve this, intense marketing campaigns and extreme branding activities are used to create a distinct position. This leads to loyalty, price inelasticity, and higher profit margins, because of the shifting of power from the buyer to the seller (Miller 1988). Differentiation strategies seek and combine characteristics that are important to customers, and pay special attention to customer service, commensurately charging higher prices in exchange (Allen and Helms 2006).
Differentiation has been proven to be more applicable in dynamic environments (Pertusa-Ortega et al. 2008; Su et al. 2017). Unlike cost leadership strategies, differentiation strategies are associated with higher performance in intensely competitive environments. Business that pursue experimentation, risk-taking, and encourage innovation should be more inclined to use a differentiation strategy (Su et al. 2017). Smaller firms like entrepreneurial ventures are more motivated to pursue differentiation strategies due to their inability to exploit economies of scale and scope (Karagozoglu and Lindell 2004). On the other hand, some studies concluded that business using differentiation strategies in the online environment had the worst performance out of Porter’s three competitive strategies, which is largely attributable to online consumers being less loyal (Zhuang and Lederer 2003). Additionally, providing valuable and detailed information on products to consumers might help the competition, as consumers may purchase the products elsewhere for less, after knowing what they need to know.
Differentiation strategies have positive direct impacts on the Performance of Internet entrepreneurial ventures at α ≤ 0.05.
Focus is similar to differentiation, but the latter is more general, while the former is targeted to a narrow market segment, mainly in terms of resource investment to enter or expand narrow market or industry segments, considering the factors of cost, quality, or both (Allen and Helms 2006; Porter 1980). Businesses pursuing focus strategies believe that by honing in on a particular type of customer, product (or product range), or geographical area, they will be able to outcompete others who are not as focused. Focus strategy is usually utilized when firms know their segments and have products to competitively satisfy the needs of those segments. Generally, focus strategies tend to avoid competition, because of firms’ limited market penetration and share (Johnson et al. 2016).
Many studies found that focus strategies presented the most effective strategy for increasing business performance in click and mortar businesses (Chul Mo et al. 2004; Bertels 2019). Focus strategies seem to be associated with high-growth entrepreneurial ventures. In an online environment, focus strategies are second to cost leadership strategies in overall performance in USA. Furthermore, Internet-based businesses are able to improve customer service and internal efficiency through focus strategies (Zhuang and Lederer 2003; Bertels 2019).
On the other hand, focus strategies may limit entrepreneurial ventures’ capability to grow (Karlof and Loevingsson 2005; Allen and Helms 2006). Some empirical investigations suggest that focus strategies contributed the least to entrepreneurial ventures’ performance (Chul Mo et al. 2004). Furthermore, some studies that did not even consider focus strategies, considering them to be beyond the purview of entrepreneurial ventures (Li and Li 2008; Torres et al. 2014; Su et al. 2017).
Focus strategies have positive direct impacts on the Performance of Internet entrepreneurial ventures at α ≤ 0.05.
Internet Entrepreneurial Ventures
Entrepreneurial ventures are typically considered small, young organizations in a rapid growth phase, with limited resources. However, it is possible for some firms to start off well-resourced, depending on the obligations of the industry in which they compete, and their access to capital (Bhide 1992). Entrepreneurial ventures are credited with developing robust economies, jobs and wealth creation (King et al. 2007). Entrepreneurial ventures are also known to be more agile and responsive to the economic changes (Norris 2014). According to Tülüce and Yurtkur (2015), and based on creative destruction theory, entrepreneurial ventures are agents of wealth creation in a capitalist society, as new ventures bring increased value to the market by destroying old, economically lagging firms that were a drag on the economy. The literature emphasizes the role of the entrepreneur along with the characteristics of the environment in determining entrepreneurial ventures’ success, failure, and performance (Marco et al. 2006). Modern entrepreneurial ventures face the increasing challenges and opportunities of globalization, digitization, and deregulation to address, in addition to the standard challenges historically faced by entry firms (Chen 2005). According to the US Department of Labor (2018), for every three start-up businesses, two die in the same time period (when seasonally adjusted).
Internet entrepreneurial ventures face many of the same and more issues than traditional ones due to the instability of the Internet environment, as well as the speed of change in markets and technology. There are other critical issues pure play firms deal with, such as how to effectively compete in a global marketplace. While the Internet gives firms greater reach to potential clients, it also causes a high degree of consumer fragmentation (Leeflang et al. 2014). Other issues, such as building trust (i.e. branding and consumer relationships) and security, are more difficult for Internet entrepreneurial ventures, since these businesses have impaired physical interactions with customers relative to traditional firms. Pure play firms have significantly higher failure rates than click and mortar firms, specifically a 22.8% failure rate for the former versus 2.8% for the latter (Chen 2005).
There are many reasons why Internet businesses fail, but they have remained broadly similar in the decades since the dot com crash, including industry over-saturation, lack of sustainable funding, scaling too quickly, ineffective business models, insufficient performance monitoring, single-revenue source dependence, and a poor website as an analysis of failed e-commerce firms in the dot.com crash (c. 2000–2002) (Hirakubo and Friedman 2002). However, most previous studies found that the primary cause for Internet businesses failure is the lack of coherent strategy (Porter 2001; Hirakubo and Friedman 2002; Chaffey 2015).
Chaffey (2015) stated that Internet business is not about defining an online business model; it is rather about how to do business differently by employing digital technologies. Therefore, issues of firm resources, actions, and activities in an online environment are addressed through a choice of strategy (Sydney 2001). Special benefits of the Internet space, such as network capabilities and information accessibility, are also leveraged through strategy (Carrier et al. 2004). Porter’s competitive strategies could be applied to a variety of contexts to help Internet entrepreneurial ventures improve performance and thrive (Ormanidhi and Stringa 2008).
Research methodology could be descriptive or experimental for similar studies. In descriptive research, the researchers do not interfere with the examined phenome at any level, while in the experimental research, the results are obtained by observing the changes that take place due to the manipulation of study variables (Creswell et al. 2003). Since the researchers are examining the impact of the independent variable on the dependent variable without any manipulation or interference of any kind, this study employed descriptive analytical methodology. The chosen methodology was found more suitable for the nature of this research as it describes the examined phenomena as it is, while try to underline the reason behind it in the examined population.
In mixed methods research design, research can follow an explanatory design; when qualitative data are needed to explain or expand on quantitative results, or exploratory design; where the results of the qualitative stage is utilized to identifying variables in the study. Explanatory design is not normally used to provide conclusive evidence but can help better understand the examined phenomena efficiently, while exploratory design is more conclusive and more appropriate when it comes to generalizing the results (Creswell et al. 2003). An exploratory design was found more appropriate for the purpose of this research, starting with a qualitative inquiry to ascertain the type of strategy used in Internet entrepreneurial ventures in MENA, followed by quantitative research to examine the relationship between the independent variable (Porter’s generic competitive strategies) and the dependent variable (performance of Internet-based entrepreneurial ventures). The first phase was carried out using semi-structured interviews with the managers/owners of the ventures. After explaining the study aim and objectives and record the participants’ consent, the managers/owners were asked questions to describe the strategy being utilized in the firm in order to identify which of the three examined Porter’s strategies was being utilized. The interview also asked questions about the main resources available to firms. The second phase of the research design utilized a structured survey strategy, using a five-point Likert scale questionnaire, developed based on previous studies (cited below) to collect primary data. The questionnaire consisted of four main parts. The cover letter and consent form explained again the nature and aim of the study, and emphasized the voluntary nature of participation and the confidentiality of collected data. The second part collected demographic data about the respondents and their Internet entrepreneurial ventures. The third part collected data about Porter’s strategy as utilized by the firm. The fourth part collected data about the performance of the firm. The sources of the statements of parts three and four were adopted form previous studies (Sylvie et al. 2002; Kulatunga 2008; Huang et al. 2009; Nandakumar et al. 2010).
Validity of the Measurement
The validity of the research was assessed using the following procedures and tests.
First, the researcher developed the questionnaire statements based on previous studies (Sylvie et al. 2002; Kulatunga 2008; Huang et al. 2009; Nandakumar et al. 2010). Then, the final questionnaire was presented to a panel of experts from both business and academia (four from each), who reviewed and commented on the content and phrasing of the statements used. The views and opinions of the panel were taken into account and required adjustments were made based on their notes and comments.
Construct validity was analyzed using the correlation coefficients between items of the questionnaire variables and the total; the results are presented in Tables 2 and 3. Table 2 indicates the correlation that expresses the construct validity among the questionnaire’s items and its total for the independent variable (Porter’s strategies). The highest value of correlation that could be reached is 1, and a minimum value of 0.40 is considered good and acceptable correlation value between items (Laher 2010). Inspecting the provided values in Table 2, it is clear that all the mentioned correlation values were > 0.40, indicating good construct validity for each variable expressed by its related items.
Table 3 indicates the correlation that expresses the construct validity among the questionnaire items and the total for the dependent variable (performance). The highest value of correlation that could be reached is 1, while a minimum value of 0.40 is considered good and acceptable correlation value between items (Laher 2010). Inspecting the provided values in Table 3, it is clear that all the mentioned correlation values were > 0.40, indicating good construct validity for each variable expressed by its related items.
Discriminant validity refers to the extent to which factors are distinct and uncorrelated. In order to assess the discriminant validity of the questionnaire items, the factor correlation matrix between independent variable items is need. However, before being able to do this, KMO and Bartlett’s tests are needed to examine the data. Table 4 shows related results, including chi-square. KMO results of the measurement adequacy (which determines if the responses given with the statements are adequate or not) with values between 0.7–0.8 are considered acceptable, while greater than 0.5 indicates that the data are suitable for structure detection.
The chi-square value of 59.906 is greater than the tabulated value at the degree of freedom of 3, which equals 7.8147 at α ≤ 0.05, indicating that the data are suitable for analyses. In addition, Bartlett’s test of sphericity is significant (less than 0.05), which means that correlation matrix is not an identity matrix (Cerny and Kaiser 1977). Based on the results above, factor correlation analyses for the independent variable dimensions were conducted. The results are presented in Table 5.
Table 5 shows the factor correlation matrix between independent variable dimensions and contains the factor analyses between all pairs of items. Since the discriminant validity means the degree to which measures of different items are unrelated, the results show that all values of the correlation were smaller than 0.5, indicating a very acceptable level of shared variance. Values below 0.6 are generally considered to be acceptable (Manly and Alberto 2016).
Cronbach’s alpha test was used to assess the reliability of the research instrument. Table 6 shows results for the 31 statements of the questionnaire and the closeness of the relations between the set of items as a group (over the sample of respondents). It can be seen that the Cronbach’s alpha value for the independent variable (Porter’s generic competitive strategies: cost leadership, differentiation, and focus) is equal to 0.819. As for the dependent variable (financial and non-financial performance), the Cronbach’s alpha value is 0.863. The overall value of the questionnaire is 0.897, indicating a high level of reliability of the research tool, and reflecting relatively high internal consistency, since a reliability coefficient of 0.70 or higher is acceptable in the majority of social science research (Nunnally 1978).
Population, Sample, and Data Collection
MAGNiTT, the largest online community platform for entrepreneurial ventures across the MENA region, contains extensive data for more than 13,095 entrepreneurial ventures can be found (MAGNiTT 2020). Clear classification of the nature of each entrepreneurial venture over the past five years can be found on the platform, as only Internet ones, typically pure play, are targeted. By the time of this study’s fieldwork (2019), the total number of listed Internet entrepreneurial ventures was 1,158 for the second quarter of the year when data collection started. According to Sekaran and Bougie (2016) the sample size for the given population is 289. Following the 50% response distribution rule, 578 firms were required for a systematic random sample of Internet entrepreneurial ventures, representing almost half of the total population, thus they were selected and approached using publicly available contact information.
After initial calls and interviews of 494 managers/owners who agreed to participate in the study, and upon the determination of the strategy used by the interviewed venture, confirming that it falls within the examined strategies’ scope, the questionnaire was sent via e-mail to those who utilized one of Porter’s examined strategies. Initially, 388 questionnaires were sent; after necessary and continued follow-up, 205 questionnaires were successfully retrieved, resulting in a response rate of 52.8%, which is a very acceptable rate in online questionnaires (Fan and Yan 2010; Saleh and Bista 2017). After the filtration process four questionnaires were discarded, and 201 were subsequently subjected to statistical analyses.
SPSS version 23 was used to describe and analyse the collected data from 201 filtered and screened questionnaires. Descriptive analyses were utilized to sort and describe the data, while regression analyses were utilized to test the hypotheses and determine the possible impact of Porter’s competitive strategies on the Internet entrepreneurial venture performance. The main results are explained below.
Before starting to test the hypotheses, two basic assumptions were tested to apply linear regression: the normality of the data distribution of the independent variable, and the level of multicollinearity among the independent variables, using skewness for normality and VIF (variance inflation factor) test for multicollinearity. The results are displayed in Table 7.
The skewness values are considered to be close to the normal distribution if they lie (−2 and + 2). It is true the values are slightly left sided, but all the obtained values fall between −2 and 2, which proves that the data are considered normally distributed, with normal univariate distribution (George and Mallery 2010; Ryu 2011). The VIF values are less than 2, which means that there is no multicollinearity between the dimensions of the independent variable (Porter’s strategies). Maddala and Lahiri (2009) considered that a value of VIF more than 30 is a serious problem, a value between 10 and 30 leads to untrusted coefficients, a value between 5–10 reflects a moderate problem, and a value less than 5 is a small problem. All values are less than 2, indicating no substantive problems.
Testing the First Sub Hypothesis
Cost Leadership strategies have positive direct impacts on the Performance of Internet entrepreneurial ventures at α ≤ 0.05.
Table 8 shows the relationship between the cost leadership strategies and the performance of Internet entrepreneurial ventures. It is clear that the relationship is a very strong, positive, and significant one, with an R value of 0.785. In addition, the value of determination coefficient R2 equals 0.616, which means that cost leadership strategies can explain 61.6% of the change in the performance of Internet entrepreneurial ventures, which is a strong percentage. The p-value of 0.000 is less than 5% (the significance threshold), thus the alternative hypothesis is accepted, and there is a statistically significant positive direct impact of cost leadership strategies on the performance of Internet entrepreneurial ventures at α ≤ 0.05.
Testing the Second Sub Hypothesis
Differentiation strategies have positive direct impacts on the Performance of Internet entrepreneurial ventures at α ≤ 0.05.
Table 9 shows the relationship between the differentiation strategies and the performance of Internet entrepreneurial ventures. It is clear that the relationship is very strong, positive, and significant one, with an R value of 0.895. In addition, the value of determination coefficient R2 equals 0.801, which means that differentiation strategies can explain 80.1% of the change in the performance of Internet entrepreneurial ventures, which is a very strong percentage. The p-value is 0.000, which is less than 5% (the significance threshold), thus the alternative hypothesis is accepted, concluding that there is a statistically significant positive direct impact of differentiation strategies on the performance of Internet entrepreneurial ventures at α ≤ 0.05.
Testing the Third Sub Hypothesis
Focus strategies have positive direct impacts on the Performance of Internet entrepreneurial ventures at α ≤ 0.05.
Table 10 shows the relationship between the focus strategies and the performance of Internet entrepreneurial ventures. It is clear that the relationship is a very strong, positive, and significant one, with an R value of 0.685. Also, the value of determination coefficient R2 equals 0.469, which means that focus strategies can explain 46.9% of the change in the performance of Internet entrepreneurial ventures, which is a middling percentage. The p-value equals 0.000, which is less than 5% (the significance threshold), thus the alternative hypothesis is accepted, concluding that there is a statistically significant positive direct impact of focus strategies on the performance of Internet entrepreneurial ventures at α ≤ 0.05.
Testing the Main Hypothesis
Porter’s competitive strategies have positive direct impacts on the Performance of Internet entrepreneurial ventures at α ≤ 0.05.
Table 11 shows that each of the Porter’s generic competitive strategies (cost leadership strategies, differentiation strategies, and focus strategies) have a significant, positive relationship with the performance of Internet entrepreneurial ventures. The p-value is 0.000, which is less than 5% (the significance threshold), thus the alternative hypothesis is accepted. The independent variables (Porter’s competitive strategies) can explain 50.6% of the change in the dependent variable (the performance of Internet entrepreneurial ventures), which is a middling percentage, as the value of determination coefficient R2 equals 0.506.
The highest impact among the three main strategies is for the differentiation strategies, with a Beta value of 0.553, followed by cost leadership (0.304), and then focus strategies (0.137).
Discussion and Conclusion
The literature has long debated which competitive strategies are suitable for Internet contexts, especially for start-ups (Zhuang and Lederer 2003; Kim et al.2004a; Parnell 2006; Kulatunga 2008; Guo et al. 2017; Zaheer et al. 2019). The results of this study demonstrate that Porter’s generic competitive strategies can indeed be used in the Internet environment, and the right utilization of these strategies can positively affect the performance of entrepreneurial ventures. Based on the results of the statistical analyses, all of Porter’s competitive strategies have positive direct impacts on the performance of Internet entrepreneurial ventures. This general result intersect with relevant previous studies (Hirakubo and Friedman 2002; Zhuang and Lederer 2003; Karagozoglu and Lindell 2004). This might reflect the rapid technological developments and revolution in global e-commerce since the early 2000s; regular Internet usage has grown by 82% since 2012 (KEMP 2017), with infinitely more business conducted over the Internet. The Enterprise Guide to Global E-commerce anticipates a 246.15% increase in Internet-based business in the form of direct and indirect sales, from $1.3 trillion in 2014 to $4.5 trillion in 2021 (Orendorff 2017), which might explain the difference in the best strategy to implement in compression between well-developed, developed and developing countries and markets, as differentiation strategies are more suited in strongly competitive environments (Al-Abdallah, 2015).
The unique contribution of this study is the fact that differentiation strategies have the most positive direct impact on Internet entrepreneurial ventures in the MENA region, followed by cost leadership strategies, and then focus strategies. These results are in line with some previous studies (Karagozoglu and Lindell 2004; Pertusa-Ortega et al. 2008; Abderrahman et al. 2016; Su et al. 2017), but contradict several other studies (Hirakubo and Friedman 2002; Zhuang and Lederer 2003; Verhees and Meulenberg 2004; Johnson et al. 2016; Guo et al. 2017; Bertels 2019; Ching 2019; Zaheer et al. 2019). While most Internet-based entrepreneurial ventures in developed and well-developed countries utilize cost leadership strategies, through economy of scale, Internet-based entrepreneurial ventures in developing countries should pay more attention to differentiation strategies. The findings of this study address the gap found in literature about the best strategy to follow in developing countries in general and MENA region in particular.
The nature of entrepreneurial ventures’ offerings will definitely affect the choice of best strategy to implement, but generally speaking differentiation strategies have the highest impact on the performance of Internet entrepreneurial ventures, which means that this strategy should be the first choice of new Internet entrepreneurial ventures, and since established Internet entrepreneurial ventures are generally more flexible (Zhou and Wu 2010; Brinckmann et al. 2019); steering their current competitive strategies to differentiation would result in enhancing their performance. This might be because differentiation emphasizes positioning in general, rather than for a particular product, which could be imitated more swiftly (Allen and Helms 2006). In the volatile Internet environment, where price comparison is every easy (Hirakubo and Friedman 2002; Kim et al. 2004a), it would be of great value to entrepreneurial ventures to use differentiation strategies in order to set themselves apart from competition, especially for those with limited starting resources.
The study recommends that both new and running Internet entrepreneurial ventures should center their marketing strategies around differentiation, to enhance their performance and increase their success and survival rates. Such change can be take the form of business flowing stream strategy to guarantee its success (Sushil 2012a,b).
As for the policy makers, and since most governments in the examined region are trying to encourage entrepreneurial ventures in general and Internet-based entrepreneurial ventures in particular; due to the great benefits such ventures can have on the local economy (Kiprop 2019), policy makers should develop and implement training programs to educate Internet-based entrepreneurs on the main competitive strategies available to them and how differentiation is more effective in most cases, as it proven to be even more important than just providing lower cost offering. Differentiation can be achieved on several levels, specialized workshops should be planned and provided to Internet-based entrepreneurial ventures on the practical methods of achieving this competitive strategy. Assigning qualified academic mentors to help entrepreneurs implement the correct strategy should be considered (Deepali et al. 2017).
Further investigations linking each of the Porter’s competitive strategies with business categories would offer important research contributions. Conducting the same study over other databases for Internet entrepreneurial ventures to confirm the conclusions of this study would also be useful. Some previous studies discussed in the literature review suggested that Porter’s competitive strategies are not mutually exclusive, and can be blended (Kim et al. 2004b; Li and Li 2008); examining this claim would be another interesting future research area. Finally, examining the long-term impacts of Porter’s strategy dimensions on Internet entrepreneurial ventures’ performance (i.e. using a longitudinal sample) is essential to achieve a comprehensive view of the impact of the chosen strategy on long-term, sustainable performance.
The study faced some limitations in terms of determining the type of strategy used in the Internet entrepreneurial ventures, as most of them do not have a written or cohesive policy to guide them in this regard. Some of them used a mix of marketing activities, which they considered to comprise a strategy to them. The researcher used triangulation and member checking to ensure the validity of the data collected form the interviews; triangulation is the process of corroborating the information from different sources to strengthen the validity of the data (Torrance 2012). This involved collecting data from different sources and time periods. The use of subjective measures for performance in the form of Likert scale items can be seen as limitation for some researchers. To mitigate a loss of precision in measurements, multiple statements were used to measure performance (Kulatunga 2008).
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Al-Abdallah, G.M., Fraser, K.E. & Albarq, A.N. Internet-Based Entrepreneurial Ventures: An Empirical Investigation of Startup Business Strategies on Firm Performance from the MENA region. Glob J Flex Syst Manag 22, 29–41 (2021). https://doi.org/10.1007/s40171-020-00256-4
- Cost leadership strategy
- Developing countries
- Differentiation strategy
- Emerging economies
- Focus strategy
- Financial performance
- Generic strategies
- Non-financial performance
- Online entrepreneurial
- Porter’s competitive strategies