The Influence of Value Innovation Strategy on the Financial Performance of Manufacturing Firms in Kenya

Value innovation is the cornerstone of blue ocean strategy. Value innovation strategy aims at making competition irrelevant. The concept of value innovation strategy is founded on the belief that a business can make its competitors irrelevant in its decision making while at the same time emerging an industry leader. The purpose of this study is to establish the influence of Value Innovation Strategy on the financial performance of manufacturing firms in Kenya. The target population was 488 manufacturing firms drawn from the 12 categories of the sector in Kenya. Descriptive and inferential statistics were used in this study. The descriptive results indicate that the manufacturing firms in Kenya have implemented value innovation strategies which positively contribute to the financial performance of the firms. The inferential results also affirm that value innovation strategy significantly affect the performance of manufacturing firms in Kenya attributing up to 14.9% of its variation in performance. The study concludes that value innovation strategies boost financial performance of a firm. Managers of manufacturing firms should therefore implement value innovation strategies in order to improve financial performance.


Introduction
Value innovation is the cornerstone of blue ocean strategy (BOS). The concept of blue ocean strategy is relatively new in the business world although its existence is not new. It was first published in 2005 by Kim and Mauborgne in the book titled "Blue Ocean Strategy". Blue ocean strategy is identified with value innovation which depicts the creation of high performance and high demand in an organization (Ebele et al., 2018). The authors of blue ocean strategy did not focus on competition as their benchmark. They instead used a different strategic logic known as value innovation. The creation of blue ocean happens when companies achieve value innovation which creates value simultaneously for the company and the customer (Papazov and Mihaylova, 2016).
The concept of value innovation strategy is founded on the belief that a business can make its competitors irrelevant in its decision making while at the same time emerging an industry leader. The unfolding of value innovation is considered an exciting occurrence in the field of strategy in the last two decades (Leavy, 2018). Value innovation considers both the cost structure of the company and its value proposition to the customers (Kim, 2005). The goal of value innovation strategy aims at making competition irrelevant (Leavy, 2018). In the value innovation framework, cost savings are made by eliminating and reducing the elements the industry considers as competition. Additionally, the customer's value is improved by raising and creating factors the industry has never offered. Rouse (2015), considers value innovation as a technique designed to create new markets rather than competing for existing market share.
Value innovation creates value for both buyers and the company (Amit and Zott, 2012). Kim (2005), developed a four action framework in which value innovation can be used both for customers and organizations. The four actions include; Eliminate, Reduce, Create and Raise (Borgianni et al., 2012). Value innovation strategy eliminates the factors that the firm takes for granted, reduces the factors that are way below the industry standards, raises factors well above the industry standard and creates factors that the firm has never offered (Kim, 2005). In comparison competition focuses on the existing market found in the red ocean (Leavy, 2005). In contrast, successful firms emphasize on making competition irrelevant by creating new demand instead of looking for opportunities from the existing competition (Bourletidis, 2014).

Statement of the Problem
The manufacturing sector plays an important role in the economic development of Kenya. It is the third leading sector in terms of contribution to the GDP. The Kenya Vision 2030 identifies the sector as one of the key drivers for realizing a sustained annual Gross Domestic Product (GDP) growth of 10%. Additionally, the Kenyan government has identified the sector as one of the Big Four Agenda to spur economic growth by the year 2022. The government aspires to raise the sector's contribution to GDP from 9% to 15% and create 1.3 million jobs by 2022. The government of Kenya has devised policy strategies to spur the growth of the manufacturing sector. Despite the government interventions aimed at improving the performance of the manufacturing sector, no major changes have been achieved (KAM, 2017).
Since 2015 some manufacturing firms have closed their business due to poor performance while others have relocated to other countries (KAM, 2016). Kenya Vision 2030 emphasizes the need for appropriate manufacturing strategy for efficient and sustainable practices as a way of making the country globally competitive and a prosperous (Republic of Kenya, 2007). Therefore, this study sought to establish the influence of value innovation strategy on the performance of manufacturing firms. Studies on value innovation strategy have focused on the adoption of value innovation, challenges of implementation of value innovation, impact of value innovation on competitive advantage and determinant of value innovation in the banking industry (Miano, 2013;Nyambane, 2012;Omboto, 2013). There is scanty research carried out on value innovation and financial performance of manufacturing firms. This study addresses this gap by investigating the influence of value innovation on the financial performance of manufacturing firms in Kenya.

Objective of the Study
To examine the influence of value innovation strategy on financial performance of manufacturing firms in Kenya.

Review of Literature
The notion of value creation has remained a topic of importance ever since the ancient Greeks Ramirez (2009). Discussions on the theory of value creation have been propounded by economists, sociologists and scholars for more than two centuries and also in today's literature (Beckmann and Hielscher, 2010;Parsons, 1956;Priem and Butler, 2001;Say;Weber, 1947). They argue that the central purpose of firms is value creation. The firms create value through their superior ability to organize and coordinate activities. Firms need to learn and cooperate with customers to generate values that meet their individual and dynamic essentials (Prahalad and Venkatram, 2014). Competitive advantage can only occur when firms implement a value creating strategy unique from the current or potential competitors (Fahy, 2000).
Studies conducted in the past have suggested some positive influence of value innovation strategy on the performance of the firms (Kim, 2005;Kiptoon, 2014;Miano, 2013;Mwende, 2016). These studies show evidence that value innovation strategy influences the financial performance of the firms. Kim (2005), established that market winners followed a strategic logic called value innovation strategy. Mwende (2016), established that value innovation strategy influenced the competitive advantage of microfinance institutions in Kenya. The current study will replicate these factors in the manufacturing sector to establish their influence on the financial performance of the firms.

Research Methodology
Mixed methods approach involving both quantitative and qualitative data was used in this study. Cross-sectional survey was adopted because the data was collected at one point in time. Qualitative data was analyzed through content analysis to establish the relationship between each of the independent variable and the dependent variable. Quantitative data was analyzed using descriptive statistics, the measure of central tendency, the measure of dispersion and inferential statistics.
The following multiple regression model was used to test the influence of value innovation strategies on financial performance: y = a + β 1 X 1 + β 2 X 2 + β 3 X 3 + β 4 X 4 + e ….

Population
The target population was 488 manufacturing firms drawn from the 12 categories of the sector and located in Nairobi County as indicated in the Kenya Association of Manufacturers directory (2016). Simple random sampling technique was used to determine the manufacturing firms to be sampled. The sample size was determined using the Slovin's Formula. This method is preferred because it samples the population with degree of accuracy and precision (Kalimba et al., 2016). Therefore, the questionnaires were administered to 220 operations managers of the sampled manufacturing firms determined using Slovin's formula as follows: n= N 1+ Ne 2 Where: n=sample size, N=total population, e= confidence level/error tolerance The level of confidence is 0.05 n= 488/1+488(0.05x0.05) n=220 A total of 171 questionnaires were filled and returned which gives a response rate of 77%. The response rate was deemed appropriate for further analysis in view of recommendation by Babbie (2004) that a 60% return rate is good and a 70% return rate is very good. Similar studies by Mwende (2016) and Miano (2013) had a response rate of 78% and 58% respectively.

Research Instrument
Questionnaires were used to collect primary data from the respondents. Before administering the questionnaires to the respondents, pretesting of the instrument was conducted to determine the reliability and validity. The research instruments were administered to 22 operation managers of the manufacturing companies which is 10% of the population as recommended by Cooper and Schindler (2011). The 22 manufacturing companies were not included in the final study.
The reliability of the study was assessed by computing Cronbach's Alpha coefficient for all items per section of the questionnaire. The coefficient should range between 0 and 1 with higher alpha coefficient values of 0.7 and above being more reliable (Sekaran and Bougie, 2010). The findings showed that the Cronbach's reliability coefficients ranged between 0.814 and 0.963. The Composite Cronbach's Alpha Reliability Coefficient for all the variables is 0.885 which is more than 0.7 threshold recommended (Cronbach, 1951;Sekaran and Bougie, 2010).
To establish the validity of the research instruments, content validity was used. Validity test assists in establishing the extent to which the research instruments measures what it is expected to measure (Kothari and Armstrong, 2011). The questionnaires were reviewed by five randomly selected experts in the field of study. The views and recommendations were then analyzed and the questionnaire was revised in order to enhance validity.

Results
Descriptive and inferential statistics were used to analyze the data in this study. This section presents the descriptive and inferential results.

Descriptive Statistics
This section outlines the descriptive statistics of value innovation strategy. The respondents were required to respond to statements relating to implementation of value innovation strategies.The results are shown in Table 1.

4.2339
.523806 The company ensures that the production time for the products is reduced well below the industry's standards.

.640723
The company ensures that wastage in the departments is reduced well below the industry's standards.

.500017
The company ensures that the employee's morale is raised above the industry standards.

.60703
The company ensures that the quality of products is continuously raised above the industry standards.

.46619
The company ensures continuous creation of new products for customers that are not offered by the industry.
3.8655 .552569 The company regularly creates new manufacturing processes that are not offered by the industry. The results in Table 1 shows that the respondents agreed with the statement that the company ensures that all the costs that could be avoided are eliminated (mean = 4.2749, std = 0.44775). The respondents also agreed that the company ensures any duplication of processes in the departments is eliminated (mean = 4.2339, std = 0.5238). Similarly, the respondents agreed that the company ensures the production time for the products is reduced well below the industry's standards (mean = 4.0351, std = 0.640723), the company ensures wastage in the departments is reduced well below the industry's standards (mean = 4.4620, std = 0.5000) and the company ensures the employee's morale is raised above the industry standards (mean = 4.2339, std = 0.60703). The findings also show that the respondents agreed that the company ensures the quality of products is continuously raised above the industry standards (mean = 4.3158, std = 0.46619), the company ensures continuous creation of new products for customers that are not offered by the industry (mean = 3.8655, std = 0.5525) and the company regularly creates new manufacturing processes that are not offered by the industry (mean = 4.1520, std = 0.6947). The findings also show that the respondents agreed with the statement that value innovation strategy positively influences sales growth (mean = 4.6023, std = 1.1297), value innovation strategy has greatly improved the ROA (mean = 4.7661, std = .84937) and greatly improved the ROE (mean = 4.7426, std = 1.18986). The results imply that the manufacturing firms have implemented value innovation strategies which positively contribute to the financial performance of the firms.

Testing of Hypothesis
The objective of the study was to establish the influence of value innovation on the performance of manufacturing firms in Kenya. The following hypothesis was therefore tested using multiple linear regression models.
H o1 : Value innovation strategy does not influence the financial performance of manufacturing firms in Kenya.
The results are presented in Table 2, 3 and 4. The results in Table 2 show that the coefficient of determination (R 2 ) is 0.149 meaning that the model estimated explains 14.9% of the variations in the performance of manufacturing firms in Kenya. The results of the Analysis of Variance (ANOVA) indicated in Table 3 show that the relationship between the independent variables and the dependent variable is significant (F = 7.247, sig <.05). This implies that the value innovation strategies significantly affect the performance of manufacturing firms in Kenya. Factors to eliminate, factors to reduce, factors to raise and factors to create are therefore statistically acceptable as useful in predicting the performance of manufacturing firms in Kenya.

Discussion
The descriptive results indicate that the manufacturing firms in Kenya have implemented value innovation strategy which positively contributes to the financial performance of the firms. The inferential results affirm that value innovation strategy significantly affect the performance of manufacturing firms in Kenya attributing up to 14.9% of its variation in performance. The inferential results also show that the constant term for value innovation strategy is -2.431; implying that holding the variables under consideration to zero could result in -2.431 units of returns to manufacturing firms. The regression coefficient for the factors to eliminate is (0.489, p<.05), meaning that holding other independent variables to zero, an increase in factors to eliminate variable by 1 unit results in an increase of 0.489 units on returns. This implies that eliminating some factors like avoidable costs and duplication of processes would positively affect the performance of manufacturing companies in Kenya.
The coefficient for factors to reduce is (.360, p<.05). This indicates that holding other independent variables to zero, an increase of factors to reduce variable by 1 unit results in an increase of 0.360 units on returns of manufacturing firms. This implies that reducing factors like production time and wastages positively affect performance of manufacturing firms. The coefficient for factors to raise is (.265, p<.05) indicating that holding other independent variables to zero, an increase in factors to raise variable by 1 unit results in an increase of 0.265 units on returns of manufacturing firms. The results imply that raising factors such as employee's morale and quality of products above the industry standards influences positively the performance of manufacturing firms.
The coefficient for factors to create is (.301, p<.05). This indicates that holding other independent variables to zero, an increase of factors to reduce variable by 1 unit results in an increase of 0.301 units on returns of manufacturing firms. This implies that creating factors like new products and new manufacturing processes that are not offered by the industry positively influence the performance of manufacturing firms.

Conclusions and Recommendations
Value innovation is a strategy that is gaining popularity in manufacturing firms and others sectors. Organizations could be successful if they embraced value innovation by offering value proposition that is superior to competition. Value innovation enhances the strategic position of firms. This study sought to establish the influence of value innovation strategy on the performance of manufacturing firms in Kenya. The indicators of the value innovation strategy were factors to eliminate, factors to reduce, factors to raise and factors to create. The null hypothesis tested was that value innovation strategy does not influence the performance of manufacturing firms in Kenya. The findings were R 2 = 0.149, F = 7.427, P=0.00˂0.05. The null hypothesis was therefore rejected and the study concludes that value innovation strategy has a statistically significant influence on the performance of manufacturing firms in Kenya.
The study recommends that managers of manufacturing firms should implement value innovation strategies in order to improve financial performance. The study also recommends that a further study be carried to determine the influence of value innovation strategy on the performance of other sectors in Kenya.