Impact Of Dynamic Capacities On Enterprise Performance: Case Studies Of Food Enterprises And Beverage Enterprises In Lagos, Nigeria

This study examined the impact of dynamic capacities on enterprise performance using some selected food and beverages enterprises in Lagos, Nigeria. In the study, dynamic capacity was captured with respect to strategic decision-making capacity, product innovation capacity, strategic flexibility, competitive intensity, technological turbulence, and technological capability. The performance of enterprise will be captured with sales growth, enterprise survival, enterprise efficiency and competitive advantage. The dynamic capacity for enterprise performance is estimated by adopting PLS-SEM method. SEM model is calibrated by using the Lisrel 8.70. The study found that the dynamic capacity of product innovation is the only variable that can sufficiently enhance increasing sales growth. Dynamic capacities of Competitive intensity and Technological turbulence are the only variable that can sufficiently enhance the survival of enterprise or sustain the enterprise into the unforeseeable future. Dynamic capacities of Technological capability and Competitive intensity are the only variable that could enhance the efficiency of enterprise. Finally, dynamic capacity of Strategic flexibility is the only variable that could sufficiently enhance competitive advantage of enterprise over other enterprises. This research contribute to knowledge by focusing on the impact of dynamic capacity on enterprise performance using some selected food and beverages enterprises in Lagos, Nigeria particularly the manufacturing enterprises in this trying period that is evidenced with technological change, competition, among others. estimate system of linear equations test the fit of a hypothesized “causal” model. The first step in SEM deals with the visualization of “path diagram” or hypothesized model which is usually based on prior knowledge of established theories. In path diagrams, rectangles typically represent observed or directly measured variables, and circles or ovals typically represent unobserved or latent constructs which are defined by measured variables. Unidirectional arrows represent causal paths, where one variable influences another directly, and double-headed arrows represent correlations between variables. As shown in the studies of McDonald and Ho (2002); Pearl (2000), the term “arc” was preferred than “causal path”. This study examined the impact of dynamic capacities on enterprise performance using some selected food and beverages enterprises in Lagos, Nigeria. In the study, dynamic capacity was captured with respect to strategic decision-making capacity, product innovation capacity, strategic flexibility, competitive intensity, technological turbulence, and technological capability. The performance of enterprise will be captured with sales growth, enterprise survival, enterprise efficiency and competitive advantage. The dynamic capacity for enterprise performance is estimated by adopting PLS-SEM method. SEM model is calibrated by using the Lisrel 8.70. The study found that the dynamic capacity of product innovation is the only variable that can sufficiently enhance increasing sales growth. Dynamic capacities of Competitive intensity and Technological turbulence are the only variable that can sufficiently enhance the survival of enterprise or sustain the enterprise into the unforeseeable future. Dynamic capacities of Technological capability and Competitive intensity are the only variable that could enhance the efficiency of enterprise. Finally, dynamic capacity of Strategic flexibility is the only variable that could sufficiently enhance competitive advantage of enterprise over other enterprises.

Introduction conditions give confidence to the enterprise networks for the purpose of surmounting the injurious business environment when realizing sustainable intensification of enterprises (Messeni, Petruzzelli, Ardito and Savino, 2018).
Springing from the potential breakthrough in the African market with Nigeria at the core stage, several manufacturing enterprises most especially the food and beverages manufacturing are wellknown are giving room for forceful competition for precincts, market share and clients. The food and beverages enterprise that are present and domesticated in the FMCGs sector has encountered different challenges from the time when there was economic meltdown, which is in furtherance to powerful, ferocious and increasing competition in the business enterprise and other macroeconomic indices such as decreasing oil prices, devaluing Naira currency, workers' salaries that are not paid, all these result in reduced spending (Industrial Report, 2016).
At the global level, food and beverages enterprises are known to be the bedrock and engine of nation's development. According to Okere (2012), the food and beverages enterprises are noted to be the main producers of foods and beverages that are consumed in Nigeria and the biggest sub-sector in the Nigerian manufacturing that were placed on the Nigerian Stock Exchange. Osundina (2014) further revealed that the enterprise is a dynamic and growing subsector of the Nigerian manufacturing industry which is witnessing unbendable and ferocious competition (KPMG, 2015).
According to Akpan, Ikon, Chukwunonye and Nneka (2016), the frequent and persistent changing of Nigerian food and beverages enterprises opens both opportunities and threats. In fact, the overall lapses of the food and beverage manufacturer are the pitiable operating environment in Nigeria and the high cost of production and operation. This has resulted to reduced output when compared with their counterparts in other developing nations. All these challenging issues have grave impacts on the performance of food and beverages enterprises.
In the view of Sola, Obamuyi, Adekunjo, and Ogunleye (2013), varieties of approaches have been adopted by the Nigerian government towards the enhancement of efficiency, productivity, and output of the enterprise networks so as to enhance economic growth and development. In the report of CBN (2003), the import substitution industrialization strategy took off and was adopted by the Nigerian nation during the First National Development Plan (1962)(1963)(1964)(1965)(1966)(1967)(1968) with the aim of plunging the degree of finished products that were imported and the enhancement of foreign exchange savings by producing locally some of the imported consumer goods. In the same vein, the Second National Development Plan period (1970)(1971)(1972)(1973)(1974) signifies the consolidation of Nigeria's import substitution industrialization strategy during the era of oil boom. Sola et al., (2013) noted that during the wake of world oil market that was collapsed in the beginning of 1980s, there was a rigorous/severe decline in the earnings accrued from oil exportation, which further lead to the inability of the nation to uphold the emerged import-dependent industrial arrangement because of the enormous import bills.
In order to rescue the abovementioned economic challenges, a variety of policy measures in terms of context and contents were employed, which seems unsuccessful. Among the policy measures were the 1982 stabilization policy, the 1984 restrictive monetary policy and stringent exchange control.
The collapse of the policy measures resulted to the acceptance and implementation of 1986 Structural Adjustment Programme (SAP) (CBN, 2003). In order to reduce the over reliance of the nation's economy on crude oil which is the major foreign means of getting income, SAP was established by endorsing non-oil exports, most especially the enterprise networks. Sola et al. (2013) noted that the performance of the enterprise networks has been worrying the government in spite of a variety of efforts they was exerted.
Accordingly, the Federal Government of Nigeria (FGN) begin with an economic programme referred to as NEEDS (National Economic Empowerment and Development Strategy) in 2003, this was to promote private sector participation in growth strategies (Essien and Bello, 2007). Though the policy document of NEEDS tend to be more entrepreneurial, the idea was basically useful for the large scale industries.
Additionally, it was identified in the policy document that there was "ineffective nexus between industry and the research institute/universities" and "lack of engineering and technical capacity to translate and decode research results into finished products and maintain existing machinery as well as low level of entrepreneurial capacity, technological support, and paucity of trained artisan skills".
These are major impediments to the development of enterprise networks (Essien and Bello, 2007).
The document was proferring solution to the shortage of technological capabilities associated with enterprise networks which are needed to influence the level efficiency.
The performance of enterprises in their business networks is quite affected by several factors such as reduced sales, high cost of production, reduced capital utilization, shortage of foreign exchange to procure the needed inputs, pitiable and unstable power supply, reduced quality of goods and services, incessant taxation among others (Adeoye and Elegunde, 2012). Among other issues associated with enterprise networks are high import dependency, political instability, deceitful governance, and political bias with resource distribution, decentralization practices, high cost of funds, weak, defect, and unsound policies formulation and implementation, high level of fake and counterfeited goods that are imported, micro-economic instability, deformed business atmosphere, invisible governance, etc. According to Olamade, Oyebisi and Egbetokun, (2013), the penalties of these issues on the national economy include among others, the loss of enterprises 'pull effect' on other sectors of the economy, and the loss of chances to partake in global economy when participating in the value chains at international level.
In many of the enterprise networks, there is an understanding that the world's economy is passing through a period of colossal transformation alongside improbability that is full of uncertainties. In fact, incremental transformations are activated in many of the cost structure, supply chains and business models of enterprises (Dobbs, 2012). One of the chief issues that are often encountered in enterprise networks is the dimension of creating value and achieving competitive advantage in the respective industry sector. These concepts of value creation and competitive advantage are germane to business strategy. The quest and reality of creating value and competitive advantage are at the basis of organizational performance and hence the indulgence of sources to the sustenance of value creation and competitive advantage is now a crucial area and dimension of study when it comes to strategic management (Barney, 1991;Porter, 1991). Global competition has revealed the level of technological changes and the dynamics of customers demand for superior quality products/services at reduced prices (Dirisu, Iyiola and Ibidunni, 2013). As competitive advantage is becoming less valuable, the performance of Nigerian enterprise networks are highly influenced as many networks are facing drastic and unexpected transformations, The formation, rations and victuals of value created and competitive advantage is realized when enterprise networks are able to recognize new and further opportunities, resources and capabilities that are in line with recognized opportunities and change (Teece, 2009). The dominant competitions have obligated several enterprise networks for new approaches to arrive at a competitive edge. What was previously referred to as strategies has been modified in the modern era (Chirico and Salvato, 2008). Dynamic capability, according to Rehman and Saeed (2015) is a mainstay for any organization to thrive in the present dynamic environment. Enterprises that are responsive in product innovation and capability to effectively coordinate and redeploy competencies from within and without would be able to improve business performance. Such enterprises will have the power to build, join together, and renew their competencies to acclimatize to the transforming market needs (Wong, 2013).
Enterprise networks place more emphasis on the aim of providing and securing competitive advantages by reaching sustainable business intensification (Seung, 2014), and creating value. In order to deal with the drastic transformations in market dynamics, technologies, and competition, top managers mostly rely on the strategic decision making ability to deal with the changing external factors that could aid the survival of transforming environment. Enterprise networks have been able to accomplish competitive advantage over time in the course of embracing technological innovation as a strategic drive to realizing competitive advantage and creating value (Oghojafor et al., 2014). In due course, enterprise owners and managers will make strategic decisions and engage in thoughts that are innovative so as to cope with the changing dynamics of environment to realize the successfulness of enterprise networks (Ibidunni and Inelo, 2015).
According to Dreyer and Gronhaug (2004), in order for enterprise networks in a ferocious competitive environment to phizog the increasingly complex environment, growing demands from customers, changes in regulatory frameworks and technological encroachment, will catalyze strategic managers to be flexible in dealings, most especially in a complex contemporary business environment that requires a short product life cycles, swift changing preferences and increasing demand of customers, technological progression and others (Shimizu and Hitt 2004).
For this reason, it is against this background that this study seeks to examine the impact of dynamic capacities on enterprise performance using food enterprises and beverage enterprises in Lagos, Nigeria as case studies. It is important to note that the interconnections between the attributes or constructs of dynamic capacities will be tested on the attributes of enterprise performance. In the study, dynamic capacities will be captured with respect to strategic decision-making capacity, product innovation capacity, strategic flexibility, competitive intensity, technological turbulence, and technological capability. The performance of enterprise will be captured with sales growth, enterprise survival, enterprise efficiency and competitive advantage.

Methodology
The research design in the study is a survey research design. This similar design was been adopted in the studies of Ziolkowska (2014). Frankfort-Nachmias and Nachmias (2008) noted that the survey design enhances better possibilities of unfolding existing phenomenon, situations and dynamics by which primary data are collected. It will enable the researcher to seek out the opinions of individual so as to reveal answers to or justify pertinent and specific questions that are comprehensive in the questionnaire instrument concerning the topic under consideration.
In the year 2014, the Nigerian Stock Exchange (NSE) listed fourteen companies which comprises of multinational and indigenous companies. The population adopted in this study will comprise the categories of staff in the top and middle management cadre of the six (6) selected quoted food and beverages companies located in Lagos State. Six quoted food and beverages companies will be purposively selected (non probability sampling) for the study as they are noted to be major players and stakeholders in the Food and Beverages industry in Nigeria (Akpan, et al., 2016;Udemba, 2015).
From previous studies, it was revealed that the other eight companies were difficult to educing information from them.
According to Zikmund (2003), the various error allowances will be determined and the suitable one will be chosen based on the discretion of the researcher. The chosen error allowance of 0.04 will be employed to establish the sample size as shown in the equation below: The formulae for achieving sample size where; n = Sample size; Z = Z score for the confidence interval (2.05); E = Error allowance (0.04) When inserted into the formula, Sample Size will be 656.6406, and approximately 657. It is therefore crucial that the questionnaire distribution will target six hundred and fifty seven respondents whom are middle and top managers in the six food and beverage manufacturing companies.
Structural Equation Modelling (SEM) of Partial Least Square (PLS) was adopted to determine the relationship that exists between competitive advantage, product innovation, and performance of food and beverage enterprises.
Structural equation modelling (SEM) is a multivariate statistical framework that is used to model complex relationships between directly and indirectly observed (latent) variables. It is a general framework which simultaneously solves the systems of linear equations and encompasses other techniques through the incorporation and integration of regression, factor analysis, path analysis, and latent growth curve modelling (Bollen, 1989; Catherine, Nathan, and Nora, 2012). SEM is used to estimate a system of linear equations to test the fit of a hypothesized "causal" model. The first step in SEM deals with the visualization of "path diagram" or hypothesized model which is usually based on prior knowledge of established theories. In path diagrams, rectangles typically represent observed or directly measured variables, and circles or ovals typically represent unobserved or latent constructs which are defined by measured variables. Unidirectional arrows represent causal paths, where one variable influences another directly, and double-headed arrows represent correlations between variables. As shown in the studies of McDonald and Ho (2002); Pearl (2000), the term "arc" was preferred than "causal path".
SEMs comprises of two sub-models, they are: 1.
The measurement model estimates relationships between the observed variables, also referred to as indicator variables, and latent variables; this is the same framework used in factor analysis. In regression and other statistical theories, "indicator variable" implies a binary yes/no sort of variable. Here, as is customary for SEM, "indicator variable" refers to a variable that is directly associated with a latent variable such that differences in the values of the latent variable mirror differences in the value of the indicator (Bollen, 2001).

2.
The structural model develops the relationships between the latent variables. For clarity of presentation, the system of equations will be described. The measurement model consists of the following equations, using standard notation used by Bollen (1989): x 1 = λ 1 ζ 1 + δ 1 y 1 = λ 3 ƞ 1 + Ɛ 1 x 2 = λ 2 ζ 2 + δ 2 y 2 = λ 4 ƞ 1 + Ɛ 2 x 3 = λ 3 ζ 3 + δ 3 y 3 = λ 5 ƞ 1 + Ɛ 3 Where the x' s and y' s are observed indicators for latent variables, ζ' s and ƞ' s are latent variables, the λ' s are the factor loadings, and Ɛ' s and δ' s are the errors or disturbance terms. In general matrix notation, the measurement model is written as x = Ʌ x ζ + δ y = Ʌ y ƞ + Ɛ From the path diagram, the arrows point to the x' s and y' s , so they are modelled as dependent variables. Also, the factor loadings for x 1 and y 1 can be set to 1, which can be done for two reasons: For instance, the direct effect of ƞ 1 on ƞ 2 is estimated by β 21 , and the indirect effect of ζ 1 on ƞ 2 is estimated by γ 11 . Alternatively, one could model the direct effect of ζ 1 on ƞ 2 with the model depicted in Fig. 2, with corresponding coefficient γ 12 .
These models are estimated using the variance-covariance matrix of the data. Usually, maximum likelihood estimation fitting functions are used to fit the system of equations to the data, but this method requires that the data be normally distributed and the observations be independent.
Variations that relax the assumption of multivariate normality have been developed, including the robust weighted least squares estimator (WLSMV), which allows for binary and categorical dependent variables (Muthe ´n, 1984). To assess the overall model fit, there are a number of fit statistics, including the root mean squared error (RMSEA) and comparative fit index (CFI) (Bollen, 1989), and for categorical data, the weighted root mean square residual (WRMR) is appropriate (Hancock and Mueller, 2006). Hu and Bentler (1999) categorize these fit statistics as "comparative" or "absolute." One could also compare nested models, as is done with traditional regression models and segregation analysis models, using a likelihood ratio test (LRT) and non-nested models using Akaike's AIC; by contrast, the aforementioned fit statistics (RMSEA, CFI, WRMR, etc.) do not require the models being compared to be nested. By so doing, it will examine the relationship between the constructs of dynamic capacities and enterprise performance, and the conforming constructs' indicators with a structural model. This study will incorporate the PLS-SEM for data screening, analysis and the underline assumptions will be taken critically in order to compute loadings, path coefficients and weights, the study will also employ the bootstrapping method to determine the significance levels as evidenced in the study of Hair, Hult,

Ringle and Sarstedt (2013).
Reasons for adopting PLS-SEM are: i. PLS can be applied to both small and large samples; ii.
It can be adopted in the situation whereby there is no theory or theoretical basis; iii. It is applicable for both probability and non-probability sampling distribution; iv. It allows for both reflective and formative latent variables; v. It requires only the formation of indices or indicators; The approach will be based on creating latent factors from the questionnaire based on an exploratory factor analysis. The resulting factors will then be evaluated in terms of their influence on the where I rn is the value of an indicator r of the latent construct Z * ln will be perceived by respondent n,Z * ln will be the value of latent construct l for respondent n, S ln will be the vector of M respondents' observed individual characteristics, and Y in will be the vector of enterprise performance levels. Error terms will be presented as elements ω ln , ν rn , ξ in of the vectors following a normal distribution with respective covariance matrix Σ ω , Σ ν , Σ ξ , while parameters to be estimated are α r , β l , β i , and β z .
Considering R indicators translates into writing R measurement equations and estimating an (R × 1) vector α of parameters (i.e., one parameter is estimated for each equation), while considering L latent constructs translates into writing L structural equations and estimating an (M × L) matrix of β parameters (i.e., M parameters will be estimated for each equation). The model to be estimated is shown in Fig. 3.

Data Analysis And Results
In the study, dynamic capacity was captured with respect to strategic decision-making capacity, product innovation capacity, strategic flexibility, competitive intensity, technological turbulence, and technological capability. The performance of enterprise will be captured with sales growth, enterprise survival, enterprise efficiency and competitive advantage.  Table 5. According to the chi-squared test (χ2/df), the χ2 value is significant, where the lower the chi square value, the lower the difference between the definite matrix and input matrix, and the realistic the goodness of fit test will be. It is important to note that the goodness of fit indexes (GFI) are satisfactory between 0.72 and 0.86, the incremental fit indexes (IFI) are satisfactory between 0.82 and 0.92, and the comparative fit indexes (CFI) are satisfactory between 0.91 and 1.00.
These indicators are guided by rule that must not be more than 1.00, which gives a numerical evidence of perfect fitness. Hence, the goodness of fit test is said to be satisfactory from the holistic point of view.
Furthermore, the values of the root mean square residual indexes (RMR) ranges from 0.015 and 0.073, and the root mean square error of approximation indexes (RMSERA) ranges from 0.008 and 0.050. The values of these indicators are quite low and, can be said to be satisfactory. From the path diagram to stress the inter-connectivity of dynamic capacities and enterprise performance shown in the conceptual framework of Fig. 2.2, the analytical figures were shown in Table 6   The findings of this study is in agreement with the findings of Rajee, (2005) which points out that product innovation is the basis for competitive advantage that will enable the innovator to implement the required and at the same time could result to an increase in the enterprise's profits most especially at challenging times. This is also similar as evidenced in the study of Wang and Ahmed (2004) which reveals that innovation in process and products is observed as prerequisite for the survival and success of the organization. However, process and product innovations are concepts of technological development for enterprise.
It also agrees with the study of Jegede, Ilori, Sonibare, Oluwale and Siyanbola (2012) which conducted the study on factors that influences innovation and competiveness in the indigenous Nigeria's oil and gas servicing firms. Their study discovered that innovation of product enhances the increase in firms' sales revenue and profitability. Also, they found that majority of the important factors that have impact on innovation in the sub-sector are Research and Development expenditure and training.
The findings of this study also corroborate the findings of Mohd, Mohd and Yasuo (2013) which discover variables that have significant influence on sales growth. The variables are internal motivation for employees, employees' promotion, and retaining of talented employees. All these variables have open up investment opportunities with new equipment and technologies in the enterprise production process. Also, it was affirmed in the study that sales growth could be determined within the framework and trend of industry as well as local, national and regional economies. The finding also corroborates the findings of Ibidunni, Oluwole, and Ayodotun (2014) which investigates the impact of product innovation strategy on the survival of the small and medium enterprises in Nigeria. Their study found a significant relationship between product innovation and the survival of SMEs. The survival of SMEs is usually measured based on the degree of sales.
The study also agrees with the findings of Aw and Batra (1998), which found a relationship between technological capability and firm efficiency in Taiwan (2002) revealed that the strategic flexibility is a driver of enterprise performance which improve competitive advantage over business players in the industry.
In the study carried out by Ibidunni and Inelo (2015) on the relationship between market-oriented strategic flexibility and market performance of the furniture industry in Southwest Nigeria under fierce competitive environment, in Lagos and Ogun states. It was revealed that there was significant relationship between resource portforlio and firm's profit; deployment of resources and market share; and the greater the demand uncertainty, the stronger the positive relationship between strategic flexibility and market performance.

Conclusion
This study examined the impact of dynamic capacities on enterprise performance using some selected food and beverages enterprises in Lagos, Nigeria. In the study, dynamic capacity was captured with respect to strategic decision-making capacity, product innovation capacity, strategic flexibility, competitive intensity, technological turbulence, and technological capability. The performance of enterprise will be captured with sales growth, enterprise survival, enterprise efficiency and competitive advantage. The dynamic capacity for enterprise performance is estimated by adopting PLS-SEM method. SEM model is calibrated by using the Lisrel 8.70.
The study found that the dynamic capacity of product innovation is the only variable that can sufficiently enhance increasing sales growth.

Funding
This empirical work was supported by the National Natural Science Foundation of China (NSFC),71804061.

Availability of data and materials
Will be made available upon request. Interconnections of Dynamic capacities and Enterprise performance. Source: Authors' work (2020)