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\title{Competitive Strategy Orientation and Innovative Success: Mediating Market Orientation a Study of Small-Medium Enterprises}
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             \author[1]{Chalchissa Amentie  Kero}

             \affil[1]{  JIMMA UNVERSITY AND UNIVERSITY OF ABOMEY-CALAVI}

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\date{\small \em Received: 12 December 2016 Accepted: 2 January 2017 Published: 15 January 2017}

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\begin{abstract}
        


In this paper, we investigate the mediating effects of market orientation in the competitive strategy orientation -product innovative success relationship. Quantitative approach was employed in the investigation. Instruments used to collect data was self-administered questionnaires. Finally, a series of hypotheses are posited to explore the relationships of the variables and to test the effects of mediator. A field survey administered to 425 workers of small to medium enterprise in the manufacturing and services sector were used to gather the data. Out of the 425 surveys sent, hypotheses were empirically tested using structural equation modelling software's AMOS to analysis regression and confirmatory factors of variables on a data set of 388participants.The various hypotheses posited in the study were empirically tested and found to be positively significant. According to the findings of this study shows that competitive orientation has significant positive effect on products innovative success.

\end{abstract}


\keywords{market orientation, mediation, competitive strategy oriented, product innovative success and small to medium enterprise.}

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\section[{Introduction}]{Introduction}\par
he role of small and medium scale enterprises (SME) has been critical and the sector is considered as "backbone" of much of economies (Wymengaet al.;2012).However, the sector of SME in the developing countries faces many constraints such as the technological backwardness, and entrepreneurial capabilities, unavailability informationand insufficient use of information technology and poor product quality.Consequently, the economic contribution of SMEs in the developing if far behind compared to developed countries \hyperref[b2]{(Altenburg and Eckhardt, 2006} ; Asian Productivity Organization, 2011; \hyperref[b12]{Emine, 2012)}.\par
Though Ethiopian Government has tried to create an environment that supports entrepreneurship since 1991, Micro, Small and Medium Enterprise (MSMEs) are still at their infancy stage regarding their economic contribution \hyperref[b7]{(Berihu, Abebaw and Biruk, 2014)}. Despite the efforts made by Ethiopian government to support Micro and Small Enterprises, transition from Micro to Small and then to Medium Enterprises is rarely happening which makes the onlooker to vacillate the success of the Micro and Small Scale Enterprises development strategy \hyperref[b7]{(Berihu, Abebaw and Biruk, 2014;} {\ref Amare and Raghurama,2017)}. Because the Growth and Transformation Plans (GTP I \& II) of Ethiopia is seek to transform the economy toward an industrialized economy and to increase per capita income of its citizens by 2025. To this effect, the government has adopted policy focused on the development of the manufacturing sector through the use of industrial parks to attract Foreign Direct Investment and to support SMEs (FDREMI, 2013). Targeting SMEs is important, as they are an engine for jobs creation and blooming of economy. With this regard however, Ethiopia has not made significant progress in pulling labor out of agriculture into more productive and industrial jobs  {\ref (FDREMI, 2013)}. The share of employment in the manufacturing sector has changed only slightly and is virtually unchanged since 1999 at below 5\% of total employment (World Bank Group, 2015). Furthermore, the result of studies on small and medium enterprise in Ethiopia by \hyperref[b0]{Abebe, Million and Ridgewell (2009)} concluded the following problem in SMEs; low profitability, the quality and range of products produced were extremely low and majority of SMEs were entirely unaware of demand and did not attempt to advertise their products. But also, the result of study on innovation and barriers to innovation: small and medium enterprises in Ethiopia \hyperref[b55]{(Silashi, 2014)} shows; lack of cooperation (network ties), lack of competitive strategic orientation \&market information, inadequate R\&D were obstacle to SMEs' technological and product innovation success.\par
Consequently, different studies have suggested that competitor orientation is critical for the long-term survival of the firm with higher level of innovative success \hyperref[b26]{(Hakala, 2011;}\hyperref[b32]{Herath and Rosli, 2014;} {\ref Henri, 2015)}.\par
A competitor orientation described as the ability and the will to identify, to analyze and to respond to competitors' actions \hyperref[b37]{(Kerin et al., 1990}; \hyperref[b40]{Kohli and Jaworski, 1990)}. This includes the identification and construction of competitive advantages in terms of quality or specific functionalities, and allows the firm to position the new product well. Firms producing radical innovations perform better than firms producing mainly imitative innovations \hyperref[b22]{(Gatignon and Xuereb, 1997)}. Another factor which characterizes the competitive position of a product is its cost \hyperref[b52]{(Porter ,2000)}.The lower the cost, the greater the potential for profits, either by setting higher margins or by penetrating the market with a lower price which has positive effect on product innovation success (Muhammad, 2010; \hyperref[b44]{Mohammad, 2013)}.\par
Product innovation is the introduction of a good or service that is new or significantly improved with respect to its characteristics or intended uses  {\ref (OECD, 2005)}. Examples of product innovation by a business might include a new product's invention; improvements in features, materials and components of an existing product, the development of new product and other aspects  {\ref (OECD, 2005)}.\par
While product innovation success measured by various indicators, \hyperref[b25]{(Griffin and Page, 1993)} identified 75 different measures of new product success used by academics or practitioners. Moreover, the research force identified 75 different measures, experts have found 16 common measures and these were considered to be core success measure \hyperref[b13]{(Erik, 2008;}\hyperref[b21]{Fu, 2010)} and Product Development Management Association (PDMA) uses the 16 criteria.However, for this study we have taken market and financial success. Because of the financial and market share objectives both were considered measures of commercial success \hyperref[b13]{(Erik, 2008)}.\par
Market success (its market share size in the market, acceptance of new product by customers) and financial success (sales volume and net profit growth) \hyperref[b13]{(Erik, 2008}\hyperref[b21]{, Fu, 2010}\hyperref[b44]{,Mohammad, 2013;}\hyperref[b59]{Theresia, 2015)}. Product innovation is probably one of the most important processes for many firms as it influences the revenues and margins that a firm can achieve and it has a positive impact on firm value(e.g. on growth and survival of individual firms) \hyperref[b21]{(Fu, 2010)}. One of the recent best practice study showed that, among the best performing firms, 48\% of sales are derived from new products introduced in the last five years. Actually, there are lots of studies in the literature concerning product innovation success. For instance, successful innovation can be achieved through an integrated development of a firm's business strategy and market positioning, organization of work, technology and people \hyperref[b11]{(Ebru, Fulya and Sinan, 2014)}.\par
Furthermore, several studies have shown that the use ofexternal informationaffect the competitive strategy of firms and has a positive effect on the successof new products  {\ref (Atuahene-Gima, 1995;} {\ref Ottum and Moore, 1997;} {\ref Joshua, 2007)}. Effective market orientations has been identified as a sources of new knowledge \hyperref[b13]{(Erik et al.;}\hyperref[b46]{,Muhammad, 2010;;}\hyperref[b59]{Theresia, 2015)}, but many firms did not actively incorporate market information into their new products  {\ref (Ottum and Moore, 2007)}.\par
In this study, to test the mediating effects of the market orientation in the competitive strategy and product innovative success relationship, we examine the relationship between (1) market orientation and competitive strategy, (2) competitive strategy and product innovative success, and (3) market orientation and product innovative success.\par
An additional problem has been that previous research on competitive strategy and market orientation was mostly conducted in western/developed countries. Recent studies have called for research of market orientation in non-western or developing countries settings. In particular, countries in transition to marketbased economies are good candidates for market orientation research as customer sovereignty issues become increasingly important \hyperref[b23]{(Gloria and} {\ref Daniel, 2005, Erik, 2008)}.\par
Therefore, the main objective of this study is to investigate the effects of competitive strategies on product innovation success: mediating market orientations of small to medium enterprises in context of Ethiopia. 
\section[{II.}]{II.} 
\section[{Literature Review and Conceptual}]{Literature Review and Conceptual}\par
Hypothesis Development 
\section[{a) MSMEs definition and enterprises characterization in Ethiopia}]{a) MSMEs definition and enterprises characterization in Ethiopia}\par
Though Micro, Small and Medium Enterprises (MSMEs) constitute the major share in terms of number in Ethiopia, there is no consistently placed definition for the sub sector by different bodies. In 1997,the Ethiopian Ministry of Trade and Industry (MoTI) defined MSEs in terms of capital investment and on the bases of establishment -micro enterprises are those small business enterprises with a paid-up capital of not exceeding Ethiopian Birr (ETB) 20,000, and excluding high tech consultancy firms and other high tech establishments.\par
While small enterprises are those business enterprises with a paid-up capital of and not exceeding ETB 500,000, and excluding high tech consultancy firms and other high tech establishments  {\ref (MoTI and FeMSEDA,2004}).However, it did not incorporates othersattributes used by other countries and international organizations also it did not tell the size of the total asset for the MSE and did not differentiate between manufacturing (industry) and services.\par
As the revised definition in 2011, some of the attributes used by other countries and international organizations are addressed. In addition, the definition has segregated sectors as service and manufacturing. However, there is still confusion among different governmental organizations (e.g. Ministry of Trade, Central Statistics Agency, \& Federal Micro and Small Enterprises Development Agency (FeMSEDA) in defining MSEs \hyperref[b3]{(Amare and Raghurama, 2017)}. According to FeMSEDA, the classification of enterprises into small, medium and large scale depends on a number of variables such as level of employment, turnover, capital investment, production capacity, level of technology and subsector.\par
However, sinceit only focus on Micro and Small Enterprises, the new definition does not put any demarcation between Small and Medium; and Medium and large Enterprises. Current definition considers human capital and asset as the main measures of micro and small enterprise to addresses the limitations of the old definition. Accordingly, the following scales are referred to the classification of enterprises in the Ethiopian context.\par
As Federal micro and small enterprises development,establishment councils of ministers of regulation No.201/2011: Micro enterprises is enterpriseshaving a total capital excluding building cost not exceeding 50,000 Birr in case of Service sector or not exceeding 100,000 Birr in case of industrial and engages 5 workers including owner and his family members and other employees.\par
Small enterprises is enterprise having a total capital excluding building cost 501,000 to 500,000 Birr in case of Service sector or 1001,000 Birr to 1,500,00 Birr in case of industrial and engage workers 6 to 30 including owner and his family members and other employees (FeMSEDA, 2011 cited in Negarit \hyperref[b47]{Gazeta, 2011)}.\par
Thus, there is no clear and agreed definition of a small firm. For the purposes of this study, the common criteria for both service and industrialdefinitionterm 'Number of Employees' has been taken to refer small enterprises with 6 to 30 workers in the context of study area Ethiopian definition. 
\section[{b) Competitive strategy oriented, market orientation and product innovative success}]{b) Competitive strategy oriented, market orientation and product innovative success}\par
A competitor orientation can be defined as the ability and the will to identify, to analyze, and to respond to competitors' actions. This includes the identification and construction of competitive advantages in terms of quality or specific functionalities, and allows the firm to position the new product well \hyperref[b22]{(Gatignon and Xuereb, 1997)}. Such an orientation makes it possible for the firm to understand "the short term strengths and weaknesses and the long term capabilities and strategies of both the key current and key potential competitors" (Narver and Slater 1990) and to react adequately.\par
A competitor orientation is both proactive (when, for example, a firm is looking for a "highly attractive market") and reactive (when it responds to a competitor's action). In a study of innovation processes in the computer industry, Xuereb  {\ref (1993)} shows that a large number of new product developments starts in response to a competitor's action and that product development is subject to the influence of competitors' innovation processes. Competitors do not remain passive when confronted by a competitive innovation but react in order to maintain their relative position  {\ref (Gatignon, Anderson and} {\ref Helsen 1989, Robinson 1988)}. Also, most successful innovative firms select certain types of new products as a function of market competitive characteristics  {\ref (Cooper 1984)}. Following the portfolio analysis literature, successful firms avoid the "highly competitive markets" and prefer the "highly attractive markets" characterized by a large market potential, rapid growth, no dominant competitor, and a large number of customers (Cooper 1984). Consequently, a competitor orientation is required for the commercial performance of innovations.\par
In a particular target market, a firm can adopt innovation, quality enhancement or cost leadership strategies. The competitive strategies adopted by a firm reflect the positional advantages that the firm enjoys compared to its competitors \hyperref[b23]{(Gloria and Daniel, 2005)}. Atuahene-Gima (1995) found that market orientation has impacts that are more significant on incremental innovation than radical innovation, because the latter is more likely to be a function of technological expertise. Therefore, in this study product innovation strategy refers to those incremental product improvements or modifications that firms implement to satisfy changing customers' needs and to differentiate themselves from competitors. A quality enhancement strategy is considered to focus on enhancing and improving product and/or service quality. In a cost leadership strategy, firms typically attempt to gain competitive advantage by being the lowest cost producer.\par
Different researchers have identified many different aspects of the strategy construct \hyperref[b37]{(Kerin et al., 1990)}. In this study, strategy refers to the determination of the basic goals of the firm and identification of the long-term courses of action necessary to reach these goals \hyperref[b33]{(Hofer and Schendel, 1978)}. In this usage, strategy focuses on the allocation of resources and the development of organizational processes necessary to achieve the competitive advantage of firm. As a result, strategic competitive oriented is viewed as the process by which management analyses the environment, including competitive and customer-related factors and designs a strategy to achieve the firm's long-term goals  {\ref (Day,1994)}. Firms that achieve this strategic ability are said to have established a coherent strategy \hyperref[b9]{(Day, 1994)}. Two commonly seen strategies are the differentiation strategy and the cost leadership strategy \hyperref[b52]{(Porter, 1980)}. The differentiation strategy requires producing and marketing a superior product appealing to relatively price-insensitive buyers. The value created by this strategy stems from meeting customer needs better than non-differentiated rivals.\par
Competitive advantage for the differentiator arises from positioning the differentiated product to select target markets who are willing to pay a premium for superior need satisfaction  {\ref (Day and Wensley, 1994)}. In contrast, the cost leadership strategy focuses on achieving the lowest cost position within an industry. This strategy is most effective where large groups of price-sensitive customers exist, as this strategy's effectiveness depends on maximizing efficiencies through investment in process technology  {\ref (Day and Montgomery, 1994)}. Although the differentiator and cost leadership strategies are useful for theoretical purposes, recent research \hyperref[b8]{(Day, 1990}) has focused on the ability of firms to adopt elements of both strategies at the same time. This is an important development, as \hyperref[b52]{Porter (1980)} did not originally allow for this development. Firms attempting to implement both strategies were stereotyped as 'stuckin-the-middle' with the implication being that they were doomed to underperform betterpositioned rivals. To achieve success under this dual strategy the firm must create and maintain a large market share by differentiating products based on process improvements that lead to real success advantages. Furthermore, these products must be positioned appropriately, relative to competitor's products and must be offered at competitive prices.\par
The formulation of a business strategy appropriate to the demands of the business, including environmental factors, such as customer needs and competitor actions, as well as internal issues, such as process improvements and quality initiatives, is necessary to provide direction to the firm \hyperref[b8]{(Day, 1990;}\hyperref[b9]{1994)}. Based on the strategic direction provided by a coherent business strategy, marketing managers can develop functional marketing strategies and implementation plans designed to achieve the goals of the strategy. To implement these plans, resources must be allocated according to the needs of the business, particularly as they relate to customers and competitors.\par
In essence, the business strategy enables marketing managers to know how to allocate resources to create the marketing processes needed to implement the strategy \hyperref[b9]{(Day, 1994)}. As a result of these factors, the development of a coherent business strategy is seen as having a direct, positive impact on the development of product innovation success. A firm has a cost advantage if its cumulative cost of performing all value activities is lower than competitor's costs. Cost advantage leads to superior performance if the firm provides an acceptable level of value to the buyer so that its cost advantage is not nullified by the need to charge a lower price than competitors are. Differentiation will lead to superior performance if the value perceived by the buyer exceeds the cost of differentiation \hyperref[b52]{(Porter, 1980)}. Furthermore, the focus strategy is considered the most suitable entry strategy for small businesses because of resource constraints.\par
Evidence for this contention is found in the \hyperref[b39]{Kodicara (2008)} study that demonstrated that more small businesses that followed a focus strategy achieved higher growth than their counterparts that used other strategiesalso stressed the usefulness of "niche" marketing as a successful growth strategy for small businesses. Market orientation is "the organizational culture that places the highest priority on the profitable creation and maintenance of superior value while considering the interest of other key stakeholders" \hyperref[b57]{(Slater and Narver 1995)}. Marketplace heterogeneities in customer preferences and product supply \hyperref[b23]{(Gloria and Daniel, 2005)} make the information about customers and competitors more and more important for a company to survive and be superior in the market. Market orientation manifests in the abilities of a business to generate intelligence about customers and competitors, and to disseminate that intelligence widely throughout the organization and to utilize the cooperation of all the departments within the organization to create and deliver customer value (Jaworski and Kohli 1993; Narver and Slater 1990). As such, market orientation is a valuable source of competitive advantage. A market orientation leads to the market oriented behaviors of acquiring, disseminating and responding to market information  {\ref (Langerak, Hultink and Robben,2004;}\hyperref[b38]{Kirca et al. 2005;} {\ref Gotteland and Boulé 2006;} {\ref Erik,2008)}. It is the acquisition, disseminate; utilization of about both current and future customer needs as well as factors that may influence those needs in different phases of innovation processes \hyperref[b30]{(Hart et al.;}\hyperref[b30]{1999;} {\ref Erik,2008;}\hyperref[b60]{Torsti et al.;}. Knowledge and information are strategic assets for the success of enterprises and nations worldwide. The utilization of, and access to, a versatile pool of information sources is necessary in developing unique and novel ideas or inventions that differ essentially from existing and already invented ones that help to improve innovative success of firms \hyperref[b13]{(Erik et al.;} {\ref 2008, Torsti et al.;}. However, how information is utilized, as well as its nature and when it is collected (acquired) may affect the innovation success of small firms.\par
Although some researchers caution that focusing on customers and competitors can lead to inertia and can discourage groundbreaking innovations (Jaworski and  {\ref Kohli, 1996)}, others agree that focusing on changing markets gives rise to fresh ideas and innovative solutions, and that market orientation is one of the major factors distinguishing between successful and unsuccessful innovations \hyperref[b23]{(Gloria and Daniel, 2005)} and found, in general, that future-oriented firms were more innovative success. \hyperref[b61]{Vijande (2005)} investigated the relationship between market orientation and six dimensions of competitive strategy developed by Venkatraman: Aggressiveness, Analysis, Defensiveness, Futurity, Proactiveness and Riskiness. The study suggests the acceptance of all of the above hypotheses except for the impact of market orientation to encourage taking risks in the organization (Muhammed, 2010). This result indicates that market orientation is associated with risk aversion. Organizational commitment to competitive analysis has been enhanced by innovations in products and services \hyperref[b61]{(Vijande (2005)}. Using current and potential rivals as the frame of reference, competitor oriented firms seek to identify their own strengths, weaknesses and capabilities. This approach will yield helpful insights into a firm's relative standing in the marketplace and also lead the firm to emphasize product innovation success \hyperref[b23]{(Gloria and Daniel, 2005)}. Therefore, it is posited that: Hypothesis 1: The higher level of competitive strategy oriented firm is the higher product innovative success. Hypothesis 2: The competitive strategy are positively affects market orientation in SMEs. Hypothesis 3: The market orientation positively affects product innovative success Hypothesis 4: The market orientation mediating the relationships between competitive strategy and product innovative success. 
\section[{III.}]{III.} 
\section[{Methodology a) Research design and data collections method}]{Methodology a) Research design and data collections method}\par
To test the posited hypotheses, a crosssectional field study was used. For survey Quantitative approach were used. Data were collected from four hundred twenty five workers of the selected small to medium enterprises to test the hypothesis developed and model specification through self-administered questionnaires. Self-administered survey research method is an efficient approach to specify the conceptual framework empirically; are relatively inexpensive and are useful for describing the characteristics of a large number of small firms \hyperref[b13]{(Erik et al.;}\hyperref[b27]{2007)}. For these reasons, direct questionnaires distribution approach were employed for gathering data in this study. 
\section[{b) Data Analysis}]{b) Data Analysis}\par
To test the relationships between various variables of competitive strategy oriented, market orientationand innovative success, statistical technique for hypothesis testing specifically, regression analysis and structural equation modeling (SEM) were used. Structural Equation Modeling (SEM) is the one of the prominent method to fulfill the requirement of the necessary for most of the researchers nowadays. This method is performed to overcome the limitation of the previous method whereby are old version that initially are false assumption. According to \hyperref[b1]{(Afthanorhan et al.;} this application is the integrating of regression analysis and exploratory factor analysis to ascertain scholar provide surveys in a factual assumption. For an example, some of the scholars often use the computation of mean for each variable to analyze their empirical research and of course totally violate the assumption in which the mean of error should be zero.\par
In the nature of social science, the type of mediation effect is able to let the scholars identify the strength of each mediator variables and competent to capture an attention of scholars to implement particular method for their empirical study. In other words, type of mediator has become enjoyed for some researchers nowadays since this skill probable to expand the contribution of the research paper to present a good knowledge to the readers from a variety of fields and countries across the whole region. The founder namely Cohen allegation the strength of mediator variable is relies on correlation of coefficient or square multiple correlation(R) in the model developed. A square multiple correlation is exist once this variable has been exerted by other variables whereby independent or exogenous variables. In particular, the result provided in mediator variable comes upon the independent variable has a causal effect on the particular variables. In the accordance of Daniel Soper(2010), square multiple correlations (R 2 ) higher than 0.80 consider high total variation. 
\section[{c) Sampling Technique and Sample Size}]{c) Sampling Technique and Sample Size}\par
A multi stage clustering and stratified sampling were used for the survey. In the first stage, selected region was selected conveniently, in second stage, industry area/zone in region as representative of the SMEs in Ethiopia was selected. Accordingly, at the first stage Oromia region has been selected. At the second stage, in Oromia region industrial zones (particularly, Finfine area) have been selected as sample representative. The selection criteria of this area was based on high density of small to medium enterprise location in Ethiopia. For this study, more than 386 respondents (workers) from small to medium enterprises were targeted as sample size that has been determined by using the following formula \hyperref[b54]{(Saunders et al.;}.\par
Where: n = adequate number of sample size with a given amount of confidence level (95\% confidence level) which is recommendable in social science. N = population size Z = table value of the confidence level from normal distribution table E = the researcher's tolerable amount of error p= the probability of success (the proportion of the study unit who may give adequate information) q = the probability of failure (the proportion of the study unit who may not give adequate information)\par
Accordingly, 386 plus 10\% in order to offset an anticipated low response or unresponded rate percent 10\% to 20\% and to maximize the generalizability of the results \hyperref[b53]{(Remenyi et al., 1998)},totally 425 respondents were selected proportionally from both manufacturing and service sectors. This sample size is hoped to generate the required information with relatively good precision for infinite or large populations \hyperref[b54]{(Saunders et al.;}.Also it is more than recommended size for applying statistics tools such as; factor analysis, AMOS, regression etc. (Julie, 2005; Field, 2013). 
\section[{d) Sampling Frame}]{d) Sampling Frame}\par
A sample was drawn from both manufacturing and services enterprises in order to derive new empirical insight into theory and to maximize the generalizability of the results \hyperref[b43]{(Michalisin et al., 1997)}. The justification for selecting a sample of manufacturing and services firms of various sizes is the fact that innovation theory, in general, is concerned more with resource-based advantages than monopoly power or specific industries within which resources may be applied  {\ref (Fahy, 2002)}.  {\ref Fahy (2002)} argues that an important research agenda within the RBV stream should be to investigate what types of resources are associated with firm's innovation success in different contexts.\par
Furthermore, a primary purpose of this study is to generalize results beyond a particular industry or sector to the population of for-profit business firms operating in markets that are not particularly regulated, protected, or controlled by government. In this study, the unit of analysis is the product innovation success. Specifically, the small firms in Ethiopia were surveyed to assess the relationship between competitive strategy, market orientation and product innovative success of firms. To develop the sample, the necessary parameters considered are as follows; 1. Only firms with at least 6 to 30 employees; 2. At least firms that had been in business for about three years; and 3. Firms within manufacturing and services classifications.\par
The justification of the above sample parameters is as follows. First, to ensure a minimum operating structure, only firms with 6 or more employees have been included based on small to medium firm definitions of Ethiopia(,FeMSEDA, 2011 cited in Negarit Gazeta ,2011).  {\ref Fahy (2002)}, for example, argues that the EO does not emphasize discrepancies between firm sizes, as its main concern is resource-based rather than monopoly-based (i.e., size-based) advantage. Second, only firms that had been in business for about 3 years are included  {\ref (Helfat, 2000;} {\ref Fahy, 2002)}. Previous product innovation research studies have used three years in order to proximate the sustainability of firm's innovation success \hyperref[b58]{(Spanos and Lioukas, 2001}). Spanos and Lioukas argue that if researchers are going to pin-point the true sources of competitive advantage, examining only single year measurements of success may bias results. Finally, given the specific focus of the sample frame, only those firms classified as operating in either a manufacturing or services industry are included. Other organizations, such as agriculture, mining, public administration, and community services are excluded due to their lack of relevance to this study. Also, the inclusion of both manufacturing (metal and wood) and services (hotels) are considered necessary to ensure an adequate sample size and generalizability of the results (Spanos and Lioukas, 2001). 
\section[{IV.}]{IV.} 
\section[{Empirical Results}]{Empirical Results} 
\section[{a) Reliability and validity tests of a construct}]{a) Reliability and validity tests of a construct}\par
In this study, to test the reliability of the constructs, Cronbach's alpha was used. One of the most commonly used indicators of internal consistency is Cronbach's alpha coefficient (Juile, 2005). Reliability can be measured with Cronbach's coefficient alpha which should surpass the .70 threshold  {\ref (Nunnally,1978} {\ref ,Field,2013)}.High Cronbach's alphas refer to patterns of high inter-correlations among the items in a scale, indicating that they constitute a coherent whole in measuring a construct. However, other scholars \hyperref[b56]{(Slater, 1995} = = = E pq z n\par
In the current study the Cronbach alpha coefficient of all constructs are greater than 0.7 except extra cluster ties 0.607 which exceed the 0.60 minimum threshold and acceptable. This shows almost all constructs of current studies have good the internal consistency (inter--correlations) scale with the exception of few extra cluster ties are acceptable for hypothesis testing. Furthermore, to obtain unidimensionality of constructs , we checked the inter-item correlation for all the scale items by using the confirmatory factor analysis; the values of item to total correlation of all items are greater than 0.3 here indicated that the items have strong inter-correlation with their constructs and then factor analysis is appropriate  {\ref (Juile,2005;} {\ref Field,2013)}. Moreover, two statistical measures are also generated by SPSS to help assess the factorability of the data (i.e. suitability of the dataset for factor analysis): Bartlett's test of sphericity should be significant (p<0.05) for the factor analysis to be considered appropriate and Kaiser Meyer Olkin (KMO)measure of sampling adequacy the value of KMO should be greater than 0.5 if sample is adequate \hyperref[b27]{(Hair et al., 2007;}\hyperref[b50]{Pallant, 2011;}\hyperref[b18]{Field, 2005;}\hyperref[b19]{Field, 2013)} and to proceed with factor analysis.\par
For current study,the KMO test values for all of the factors was greater than 0.6 and the Bartlett's test was significant (p=0.000)as mentioned in table 2, indicated that the data were suitable for factor analysis. Initial communalities are estimates of the variance in each variable accounted for by all components or factors. Principal component analysis works on the initial assumption that all variance is common therefore, before the extraction the communalities are all 1. After extraction some of the factors are disregarded and so some information is lost.\par
The amount of variance in each variable that can be explained by the retained factors is represented by the communalities after extraction. Small values (average <0.60 at cases >250) indicate variables that do not fit well with the factor solution, and should possibly be dropped from the analysis.Average communality are found by adding communality after extraction and dividing by the numbers of communalities.\par
The Kaiser Criterion is said to be reliable when: a) the averaged extracted communalitiesis at least more than .70 and when there are less than 30 variables, or b) the averaged extracted communalities is equal or above Table \hyperref[tab_1]{1} Displays each construct, item to total correlation and its associated reliability coefficient.\par
.60 and the sample size is above 250 cases  {\ref (Field, 2009}\hyperref[b19]{(Field, , 2013))}.\par
For current study, the communalities test values for all of the factors was greater than 0.6 of the recommended value as mentioned in table 2 above, indicated that the data were suitable for factor analysis. 
\section[{b) Convergent Validity}]{b) Convergent Validity}\par
Factor loadings are significant and greater than 0.5 and Average Variance Extracted (AVE) for each of the factors > 0.5 indicates good convergent validity assumption.Carmines and Zeller (1979) and Muhammed (2010, p.162) suggest that factor analysis provides a suitable means to examine convergent validity. In factor analysis, loadings are used to detect whether or not an item appropriately loads on its predicted construct. It shows the reliability of individual items (indicators).Typically, loadings of 0.50 or greater are considered to be very significant \hyperref[b19]{(Field, 2013)}. KMO values >.60 indicated that the data were suitable for factor analysis. Then, Principal components analysis explored the unidimensionality of each scale using an eigenvalue of 1.0 as the cutoff points \hyperref[b19]{(Field, 2013)}. Using SPSS, all constructs have been forced into three factors and rotated using the VARIMAX rotation method to assess their loadings.\par
Accordingly, as result of current final study in table-3 below shows; all of items have greater than 0.50 load on their predicted construct that demonstrate a higher degree of association betweenthe latent items and that constructs; thus, convergent validity is confirmed. For this data set, the evidence suggests support for convergent validity. 
\section[{Table 3: Convergent Validity based on loading factors on constructs (Using SPSS)}]{Table 3: Convergent Validity based on loading factors on constructs (Using SPSS)}\par
In addition, Average Variance Extracted (AVE) is used as measure of convergent validity in AMOS method.AVE was proposed by  {\ref Fornell and Larker (1981)} as a measure of the shared or common variance in a Latent Variable (LV), the amount of variance that is captured by the LV in relation to the amount of variance due to its measurement error (Dillon and Goldstein, 1984; \hyperref[b24]{Gounaris and Dimitriadis, 2003)}. Their average variance extracted(AVE) for X with indicators x 1 , x 2 ,..., x n is Thus, acompelling demonstration of convergent validity would be an AVE of 0.5 or above \hyperref[b48]{(Nunnally 1993;}\hyperref[b24]{Gounaris and Dimitriadis, 2003)}.\par
The details of the current studies'results areprovided in table \hyperref[tab_3]{4} below. According to this data the AVE of all latent variables are greater than 0.5 (AVEs>0.5) that shows the convergent validity is good (; \hyperref[b24]{Gounaris and Dimitriadis, 2003)}. In other word, there is no violation of convergent validity for this data. Generally, by loading factors and AVE the convergent validity assumption is confirmed.All predicted constructs' factor loadings are significant and greater than 0.5 and the Average Variance Extracted (AVE) of MO that close to 0.5 and indicatesthat approximately good convergent validity assumption is achieved. 
\section[{c) Discriminant Validity}]{c) Discriminant Validity}\par
There are two methods used to assess discriminant validity of data. One cross-factor loading method that expected each of block of indicators load higher on its respective latent variable than indicators for another latent variables  {\ref (Churchill, 1991)}. If indicators has high correlations with other latent variables then the appropriateness of model may be reconsidered. This implies that if two or more constructs are unique, then valid measures of each should not correlate too highly.\par
The other method is Average variance extracted (AVE) also used to assess the discriminant validity of the constructs. For this, a construct must have more variance with its indicators than with other constructs of the model. It is when square root of AVE (?AVE) between each pair of factors greater than estimated correlation between those factors (?AVE>r) in other word AVE>r 2  {\ref (Fornell and Larcker,1981;}\hyperref[b24]{Gounaris and Dimitriadis, 2003)} it is the more recommended method.\par
So for this study to assess discriminant validity, Average variance extracted is used. The details of the current studies' results are provided in table 5 below. We assessed the discriminant validity of each construct by AMOS. The values of all of the average variance extracted in table 5 are greater than all corresponding square of correlations. According to this data, the discriminate validity is good. In other word, there is no violation of discrimination validity.In general, the overall evidence suggests the existence of discriminant validity. Multicollinearity exists if there is a high correlation between independent variables when regressed against each other i.e the correlation coefficients are below the level considered to be serious/harmful, which is generally accepted as 0.80 or higher as harmful  {\ref (Field,2005)}. It was tested using tolerance value and Variance Inflation Factor (VIF)  {\ref (Field,2005)}. The results revealed tolerance values ranging from .645 and above which were supported by VIF values below 10. Thus, there is non-multicollinearity among the study variables.\par
The Model Fit Indices shows the chi-square result (?²= 13.003, DF = 23, P= .952 ) is not significant that indicates a good model fit \hyperref[b34]{(James, 2011)}. In addition, the fit statistics for this model indicated a good fit: ?²/df = .565; RMSEA = .000 that shows that exact fit (Kaplan, 2000; James, 2011); GFI = .995; AGFI=.980; NFI = .984; CFI = .997; IFI = .997; TLI=.991 all of them are above the recommended 0.9. Also, the value of all constructs' squared multiple correlation are greater than zero (R²>0.00). Therefore, that the model is goodness fit is very well.\par
In general, from all of the validity and reliability tests there is no violation of validity and reliability. Therefore, the data is valid and reliable. 
\section[{d) Correlations}]{d) Correlations}\par
A zero order correlation was conducted to test whether or not associations existed between the study variables as hypothesized from the literature review. The correlation results indicated a positive significant relationship between competitive strategy and market orientation (r=0. \hyperref[b55]{56}  
\section[{e) Mediation Tests}]{e) Mediation Tests}\par
To establish mediation, the following three conditions must hold: First, the independent variable (IV) (tested at step1) must affect the mediator (M); second, the independent variable (tested at step2) must be shown to affect the dependent variable (DV) and third, the mediator must affect the dependent variable.If effect of independent variable (CO)on DV significantalso after IV+M (eg.MO in this study) has significant, the mediatorpartially mediates the relationship between IVand DV but if effect of independent variable (CO)on DVnot significant and after IV+M has significant, the mediation fully mediates the relationship between IVand DV  {\ref ( Baron \& Kenny,1986)}. When these conditions for mediation proposed by Baron and Kenny were examined, it appeared that the three conditions were met. Testing mediation effect using SEM requires significant correlations between independent variable, mediating variable, and the ultimate dependent variable  {\ref (Hair et al.2010}).In the accordance of Baron \& Kenny which inherits the Sobel (1982) technique, indirect effect should be higher than direct effect to indicate the mediator effect is occurs in a structural modeling.\par
For current study as finding of regression weight of unstandardized (in tables 7b and 7c) shows that competitive orientation has significant positive (?=.262, p<0.001) direct effect on products innovative success. This when competitive oriented goes up by 1, product innovative success approximately goes up by 0.26. So, this supports hypothesis-1 that the higher level of competitive strategy oriented firm is the higher product innovative success. In addition, market orientation positively significantly (?=.76, p<0.001) affects competitive strategy in SMEs. Similarly, market orientation positively significantly (?=.31, p<0.001) affects product innovative success. Additionally, hypothesizes 2and3 are also supported.Overall, the regression results support the conditions for mediation to be realized. It can be concluded that market orientation mediates the relationship between competitive oriented on product innovative successes.\par
Further analysis using AMOS, SEM was performed to establish the significance level of the mediation effect. Therefore, we can analysis hypothesis-4that examines the effect of mediator (market orientation)on the relationships between competitive strategy and product innovative success.Hence, to determine the mediator effect of MO, the model is run by SEM (AMOS). As the result, in regression equation without mediator the estimate of causal pathfrom competitive oriented to product innovation was positively significant (r=.30; p<.001).In addition, the effects of competitive oriented on market orientation were statistically positively significant (r=0.68, p<0.001).The path diagram of Figure \hyperref[fig_0]{1} of the mediation model includes the standardized estimates(r) for the causal paths for the indirect (r =.24, p<0.001) and direct (r=0.30, p<0.001) effects of CO on product innovative success. Both estimated paths for the direct and indirect effectof CO on product innovative success were statistically significant but also the estimate of the direct effect (r=.39, p<0.001) of market orientation on product innovation success statistically significant (Table7b. and Fig. \hyperref[fig_0]{1}).The indirect (mediated) effect of competitive orientation on product innovative success is .24. That is, due to the indirect (mediated) effect of competitive oriented on product innovative success that shows when competitive oriented goes up by 1standard deviation, product innovative success goes up by 0.24standard deviation. This is in addition to any direct (unmediated) effect that competitive orientation may have on product innovative success.\par
Similarly, from (table7b) the unstandardized estimate shows,the indirect (mediated) effect of competitive oriented on product innovative success is .23. That is, due to the indirect (mediated) effect of competitive oriented on product innovative success, when competitive oriented goes up by 1, product innovative success goes up by 0.23. This is in addition to any direct (unmediated) effect that competitive oriented may have on product innovative success.\par
The total (direct and indirect) effect of competitive oriented on product innovative success is .50. That is, due to both direct (unmediated) and indirect (mediated) effects of competitive oriented on product innovative success, when competitive oriented goes up Further, the results showed the index ratio of 48\% with partial mediation effect of market orientation, suggesting that without market orientation, competitive orientedcould influence product innovative success in SMEs.This statement is far from (Hair et al.; 2010, Eugenie, John and Laura, 2016) who stated that in case of full mediation, the predictor variable loses its power to influence the dependent variable except through a mediator.Despite a full mediation, the index of mediation indicated that product innovative success received only 48\% of the indirect effect from competitive oriented through MO, leaving 52\% unaccounted for. Therefore, it can be presumed that the balance of 52\% may be accounted for by other mediating factors not considered in this study that necessitate further investigation.\par
Here after MO considered as mediator the effect of competitive oriented on product innovative success still exist but in smaller magnitude, therefore, potentially, market orientation partially mediates the path between competitive oriented and product innovative success. Therefore, hypothesis4 is supported. In general, all of the hypothesizes were accepted as follows: 
\section[{Hypothesis}]{Hypothesis}\par
Findings Decision     
\section[{Conclusions, Implications and Limitations of the Study}]{Conclusions, Implications and Limitations of the Study}\par
Following the foregone finding, that competitive orientation has significant positive effect on products innovative success. Similarly, competitive orientation has significant positive effect on market orientation. In addition, market orientation has significant positive effect on products innovative success and mediates the relationship competitive orientation and products innovative success.So, it can be concluded that market orientation is pertinent to enhance product innovative success.\par
Furthermore, competitive orientation strategy remains a fundamental factor for market orientation since competitive oriented positively affects market orientation. The findings therefore contributes to the existing literature on market orientation and product innovative success by providing empirical evidence that market orientation is a powerful mediator in the relationship between competitive orientation and product innovative success.\par
The practical implications of this study are that owner/manager of SMEs should focus on competitive oriented strategy and response (utilize) MO to improve their product innovative success (to increase sales volume and profits) in the short term. This can be achieved by utilizing well-gathered market information. Besides, information-sharing culture within an enterprise must be strengthened. Finally, the acquired new market information must be effectively used to generate the best competitive strategy that will result in increased their product innovative success.\par
For policy makers the findings of this study will help them to formulate sound policies and support programmes which are necessary to enhance the product innovative success of SMEs especially in developing countries particularly Ethiopia.\par
This study provides also important information on SMEs for academic researchers working at higher learning institutions and other researchers involved in the business sector. However, the study has some limitations and further suggestions for future researchers. As this study used a cross-sectional research design combined with a quantitative research approach, future researchers should employ a longitudinal method to compare any variations in the results. Alternatively, qualitative studies could be conducted to supplement the quantitative findings because through methodological triangulation, it may be possible to gain a better understanding of the mediating effect of market orientation on competitive orientation and product innovative success.The index of mediation indicated that product innovative success received only 48\% of the indirect effect from competitive oriented through MO, leaving 52\% unaccounted for. From this, it can be presumed that the balance of 52\% may be accounted for by other mediating factors not considered in this study that necessitate further investigation.Therefore, it is advisable for future researchers to incorporate other external and internal factors that can mediate the relationship between competitive orientation and product innovative success. Lastly, this study focused on service and manufacturing SMEs. Other studies might include other types of business. 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XVII Issue III Version I Year ( )\begin{figure}[htbp]
\noindent\textbf{1}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Figure 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.4913043478260869\textwidth}P{0.05217391304347826\textwidth}P{0.12391304347826088\textwidth}P{0.1826086956521739\textwidth}}
Constructs\tabcellsep No. of Items\tabcellsep Item to Total Correlation\tabcellsep Chronbach Alpha (Reliability)\\
Market orientation\tabcellsep 12\tabcellsep \tabcellsep 0.824\\
Information acquisition\tabcellsep 4\tabcellsep .494\tabcellsep 0.707\\
Information dissemination\tabcellsep 4\tabcellsep .585\tabcellsep 0,753\\
Information utilization\tabcellsep 4\tabcellsep .471\tabcellsep 0.743\\
Competitive strategy oriente\tabcellsep 9\tabcellsep \tabcellsep 0.889\\
Differentiation\tabcellsep 3\tabcellsep .558\tabcellsep 0.760\\
Cost leadership\tabcellsep 3\tabcellsep .630\tabcellsep 0.743\\
Scope market\tabcellsep 3\tabcellsep .619\tabcellsep 0.818\\
Product Innovative Success\tabcellsep 5\tabcellsep \tabcellsep 0.760\\
Market success\tabcellsep 3\tabcellsep .469\tabcellsep 0.872\\
Financial success\tabcellsep 2\tabcellsep .495\tabcellsep 0.865\end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.07083333333333333\textwidth}P{0.425\textwidth}P{0.09444444444444444\textwidth}P{0.25972222222222224\textwidth}}
KMO\tabcellsep P-value Bartlett's\tabcellsep Sig.\tabcellsep Communality\end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.2883592017738359\textwidth}P{0.13569844789356983\textwidth}P{0.06031042128603104\textwidth}P{0.23181818181818178\textwidth}P{0.06031042128603104\textwidth}P{0.05088691796008869\textwidth}P{0.02261640798226164\textwidth}}
LV\tabcellsep \multicolumn{4}{l}{Standardized Regression Weights Estimate(R)}\tabcellsep R 2\tabcellsep AVE\\
\tabcellsep Uti\tabcellsep <---\tabcellsep MIP\tabcellsep .633\tabcellsep .40\tabcellsep \\
\tabcellsep Diss\tabcellsep <---\tabcellsep MIP\tabcellsep .848\tabcellsep .72\tabcellsep \\
MO\tabcellsep Acqui\tabcellsep <---\tabcellsep MIP\tabcellsep .488\tabcellsep .24\tabcellsep .45\\
\tabcellsep Scope\tabcellsep <---\tabcellsep CO\tabcellsep .779\tabcellsep .61\tabcellsep \\
\tabcellsep Cost\tabcellsep <---\tabcellsep CO\tabcellsep .882\tabcellsep .78\tabcellsep \\
CO\tabcellsep Diff\tabcellsep <---\tabcellsep CO\tabcellsep .751\tabcellsep .56\tabcellsep .65\\
\tabcellsep MS\tabcellsep <---\tabcellsep PIS\tabcellsep .837\tabcellsep .70\tabcellsep \\
PIS\tabcellsep FS\tabcellsep <---\tabcellsep PIS\tabcellsep .845\tabcellsep .71\tabcellsep .50\\
\multicolumn{6}{l}{MO-market orientation: Acqui-Acquisition, Uti-utilization, Diss-dissemination,}\tabcellsep \\
\multicolumn{3}{l}{CO-competitive orientation}\tabcellsep \multicolumn{4}{l}{: Diff-Differentiation, cost-cost leadership, scope-scope/focus}\\
strategy\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{PIS-product innovation success :}\tabcellsep \multicolumn{3}{l}{MS-Market success, FS-financial success}\tabcellsep \end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.02266666666666667\textwidth}P{0.17755555555555555\textwidth}P{0.11711111111111111\textwidth}P{0.1322222222222222\textwidth}P{0.18133333333333335\textwidth}P{0.01511111111111111\textwidth}P{0.204\textwidth}}
\tabcellsep Discriminant\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep Validity 1 2\tabcellsep Factor Correlations\tabcellsep Correlation squared (r 2 )\tabcellsep \multicolumn{2}{l}{Should be AVEs>r 2 AVE 1 AVE 2}\tabcellsep Discriminant Validity\\
MO\tabcellsep <--> CO\tabcellsep .675\tabcellsep .46\tabcellsep . 45\tabcellsep . 65\tabcellsep Established\\
MO\tabcellsep <--> PIS\tabcellsep .599\tabcellsep .36\tabcellsep . 45.50\tabcellsep \tabcellsep Established\\
CO\tabcellsep <--> PIS\tabcellsep .574\tabcellsep .33\tabcellsep . 65.50\tabcellsep \tabcellsep Established\end{longtable} \par
 
\caption{\label{tab_4}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.507017543859649\textwidth}P{0.1789473684210526\textwidth}P{0.07083333333333333\textwidth}P{0.03728070175438596\textwidth}P{0.05592105263157894\textwidth}}
\tabcellsep \multicolumn{4}{l}{, p<0.05); market orientation and}\\
innovative\tabcellsep product\tabcellsep \multicolumn{2}{l}{success(r=0.491,}\tabcellsep p<0.05);\\
competitive\tabcellsep strategy\tabcellsep and\tabcellsep innovative\tabcellsep product\\
\multicolumn{5}{l}{success(r=0.513, p<0.05) respectively. Table-6}\\
\multicolumn{5}{l}{presents correlation between various constructs and}\\
\multicolumn{2}{l}{multicollinearity.}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_5}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.43294392523364483\textwidth}P{0.10724299065420559\textwidth}P{0.0794392523364486\textwidth}P{0.05560747663551401\textwidth}P{0.1350467289719626\textwidth}P{0.0397196261682243\textwidth}}
by 1\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep MO\tabcellsep CO\tabcellsep PIS\tabcellsep \multicolumn{2}{l}{Collinearity Tolerance VIF}\\
Market orientation (MO)\tabcellsep 1\tabcellsep \tabcellsep \tabcellsep .646\tabcellsep 1.549\\
Competitive orientation (CO)\tabcellsep .560 **\tabcellsep 1\tabcellsep \tabcellsep .683\tabcellsep 1.464\\
Product innovation success (PIS)\tabcellsep .491 **\tabcellsep .513 **\tabcellsep 1\tabcellsep \\
Mean\tabcellsep 42.80\tabcellsep 31.46\tabcellsep 16.01\tabcellsep \\
Standard Deviation\tabcellsep 7.704\tabcellsep 7.662\tabcellsep 4.677\tabcellsep \end{longtable} \par
 
\caption{\label{tab_6}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7a} \par 
\begin{longtable}{P{0.08652694610778443\textwidth}P{0.22395209580838324\textwidth}P{0.22904191616766467\textwidth}P{0.1781437125748503\textwidth}P{0.13233532934131736\textwidth}}
\tabcellsep Standardized total effects\tabcellsep standardized direct effects\tabcellsep standardized indirect effects\tabcellsep indirect/Total\\
CO?MO\tabcellsep .68***\tabcellsep .69***\tabcellsep \tabcellsep \\
CO?PIS\tabcellsep .56***\tabcellsep .30***\tabcellsep .27***\tabcellsep .27/.56=0.48\\
MO?PIS\tabcellsep .39***\tabcellsep .39***\tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table 7a :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7b} \par 
\begin{longtable}{P{0.09506578947368421\textwidth}P{0.25164473684210525\textwidth}P{0.3019736842105263\textwidth}P{0.2013157894736842\textwidth}}
\tabcellsep \tabcellsep \multicolumn{2}{l}{T ables 7}\\
\tabcellsep Unstandardized\tabcellsep UnstandardizedDirect\tabcellsep Unstandardized\\
\tabcellsep Total Effects\tabcellsep Effects\tabcellsep Indirect Effects\\
CO?MO\tabcellsep .76***\tabcellsep .76***\tabcellsep \\
CO?PIS\tabcellsep .50***\tabcellsep .26***\tabcellsep .23***\\
MO?PIS\tabcellsep .31***\tabcellsep .31***\tabcellsep \end{longtable} \par
 
\caption{\label{tab_8}Table 7b :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7c} \par 
\begin{longtable}{P{0.28960817717206133\textwidth}P{0.36201022146507666\textwidth}P{0.10136286201022146\textwidth}P{0.02896081771720613\textwidth}P{0.06805792163543442\textwidth}}
\tabcellsep \multicolumn{2}{l}{Maximum Likelihood Estimates}\tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \multicolumn{3}{l}{Estimate S.E. C.R. P}\\
Market orientation\tabcellsep <---Competitive oriented\tabcellsep .755\tabcellsep .061\tabcellsep 12.415 ***\\
\multicolumn{2}{l}{Product innovative success <---Competitive oriented}\tabcellsep .262\tabcellsep .074\tabcellsep 3.551 ***\\
\multicolumn{2}{l}{Product innovative success <---Market orientation}\tabcellsep .311\tabcellsep .072\tabcellsep 4.331 ***\\
Diff\tabcellsep <---Competitive oriented\tabcellsep 1.000\tabcellsep \tabcellsep \\
Cost\tabcellsep <---Competitive oriented\tabcellsep 1.000\tabcellsep \tabcellsep \\
scope\tabcellsep <---Competitive oriented\tabcellsep .953\tabcellsep .053\tabcellsep 18.127 ***\\
FS\tabcellsep <---Product innovative success\tabcellsep 1.000\tabcellsep \tabcellsep \\
MS\tabcellsep <---Product innovative success\tabcellsep 1.000\tabcellsep \tabcellsep \\
Uti\tabcellsep <---Market orientation\tabcellsep 1.000\tabcellsep \tabcellsep \\
Diss\tabcellsep <---Market orientation\tabcellsep 1.000\tabcellsep \tabcellsep \\
Acqui\tabcellsep <---Market orientation\tabcellsep .587\tabcellsep .068\tabcellsep 8.634 ***\\
\multicolumn{2}{l}{*** is significant at the p<0.001 (2-tailed), n=388}\tabcellsep \tabcellsep \tabcellsep \\
V.\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_9}Table 7c :}\end{figure}
 			\footnote{© 2017 Global Journals Inc. (US)} 			\footnote{Competitive Strategy Orientation and Innovative Success: Mediating Market Orientation a Study of Small-Medium Enterprises} 			\footnote{( ) 2017 © 2017 Global Journals Inc. (US) 1} 			\footnote{© 2017 Global Journals Inc. (US) 1} 		 		\backmatter  			  				\begin{bibitemlist}{1}
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