Identification of Competitiveness Variable for Manufacturing Industries with SEM Model Approach

Competitiveness increasing for manufacturing industry needs to get attention because it is one of the main sectors driving economic growth. This study aims to determine the variables forming the competitiveness of the manufacturing industry and create a model of structural equations. The approach used is the SEM model that is able to analyze the relationship patterns among the variables used in the model. The results show that all constructs used in confirmatory factor analysis have fulfilled the predetermined goodness of fit. The probability value of the goodness of fit test shows the value of 0.071 with the feasibility tests of the eligible model as a good model. Thus, the suitability of the model predicted by the observed values adequately satisfies the model’s suitability. This shows that simultaneously the influence for target of development variables to manufacturing industry and manufacturing industry characteristic variable to model of industrial competitiveness development is 20.1%. *Corresponding author: Lukmandono, Department of Industrial Engineering, Adhi Tama Institute of Technology Surabaya, Arif Rahman Hakim Street Number 100 Surabaya 60117, East Java, Indonesia, Tel: 0315994620; E-mail: lukmandono@itats.ac.id Received February 28, 2018; Accepted March 21, 2018; Published March 27, 2018 Citation: Lukmandono, Basuki M, Purnama J (2018) Identification of Competitiveness Variable for Manufacturing Industries with SEM Model Approach. Ind Eng Manage 7: 252. doi:10.4172/2169-0316.1000252 Copyright: © 2018 Lukmandono, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Introduction
The World Economic Forum [1] defines competitiveness as a condition of institutions, policies, and factors that determine the level of economic productivity of a country. High productivity reflects high competitiveness, and high competitiveness has the potential to enable high economic growth, which will further improve the welfare of the population. The issue of industrial competitiveness is always associated with competitive strategy [2]. A competitive advantage arises when a company can produce the same product that its competitors produce at a lower cost as cost advantage, or produce different and better products/ services produced by competitors as differentiation advantage.
The competitiveness of a nation is determined by the competitiveness of the development actors or the business actors, the competitiveness of their communities and the competitiveness of the state. The competitiveness of enterprises means the ability of companies to compete [3]. The company has its own strategy to lower costs, improve product quality, and gain network marketing. Industrial development requires increased competitiveness in both domestic and international markets [4].
Companies need to deploy two forces of competitiveness as well as to compete. First, comparative advantage, attached to the low costs of factors of production, such as labor, raw materials, capital or physical infrastructure, and scale of business. Second, competitive advantage, which is in the ability of creativity, productivity, and innovation that includes technological innovation, marketing innovation, product position innovation among competitor's products, and service quality innovation. The strength of competitiveness that relies on comparative advantage is a strength that is merely physical or tangible. Meanwhile, the power of competitive competitiveness is the strength of intangible competitiveness.
Avella et al [5] and Miltenburg [6] emphasized the importance of manufacturing strategy as a determinant of corporate competitiveness. The four competitive key manufactures used are cost, quality, delivery and flexibility. Sohn et al. [7] conducted a study on 246 respondents using Maximum Likelihood Estimation (MLE), and Partial Least Square (PLS) with structural equation model to evaluate R&D performance through three aspects: output, outcome and impact given by adopting the MBNQA criterion (Malcolm Baldrige National Quality Award).
Research in the field of industrial competitiveness, especially manufacturing industry has been done by many researchers from various countries. These studies are generally focused on the problems associated with the influence of several variables on the performance of the company. The competitiveness of the industry is described as a level of performance with an overall indicator of customer, satisfaction and market performance. The influencing variables are technology and strategy interaction and competitive capabilities [8].
In another study, industry competitiveness is described as firm performance measured through market share and sales growth. Two influencing variables are competitive strategy and manufacturing strategy [9]. This model confirms that there is a relationship between competitive strategy and manufacturing strategy to firm performance firm. In general, the competitive strategy used in this model believes that a company can only create higher value for customers at high cost or create a fair value at a lower cost. Conversely, companies that seek to create blue oceans pursue differentiation and low cost simultaneously [10].
The purpose of this study is to determine the variables that affect the competitiveness of the manufacturing industry and create a model of structural equations through the SEM approach. The results of this study are expected to provide input for industry players about the determinant variables that affect the competitiveness of the manufacturing industry so as to increase the potential competitiveness. With the model produced in the research industry actors can also make

Literature Study: Competitiveness Analysis of Manufacturing Industry
The manufacturing industry is the main sector driving economic growth, contributing almost 30 percent to gross domestic product (GDP). In addition to the large share of exports in the manufacturing industry, the absorption of manpower in the manufacturing industry also ranks above so that the performance of the manufacturing sector will have a real impact on exports, labor absorption as well as the overall economy (BPS, 2010). Increased competitiveness, especially the competitiveness of the manufacturing industry should continue to be pursued, in order to increase industrial growth more easily achieved.
The four competitive key manufactures that include cost, quality, delivery and flexibility show the importance of manufacturing strategy as a determinant of corporate competitiveness [11]. The existence of manufacturing strategy also contributes to enhance the competitiveness of enterprises [12]. Porter's value chain model is used to prove that there is a relationship between knowledge management activities and competitiveness. The Porter's value chain model illustrates the role of each activity towards increasing value added for the organization to enhance competitiveness through increased productivity, agility, reputation and innovation [13].
In order to support the strengthening of the competitiveness of the manufacturing industry it is necessary to develop a competitive model capable of identifying the variables that affect its competitiveness. The fundamental difference of this study with other research is the use of modeling variables and their methods of completion. The settlement method used to create flowcharts is a structural equation model (SEM). This model can be used as a basis for planning the development strategy of the manufacturing industry.

Determination of Thinking Framework and Dimensional Variables
Based on the study of the theory that has been done to produce a research flow to solve the problem. The existing problem is how to determine the variables that affect the competitiveness of the manufacturing industry. The framework of thinking generates the concept of developing the research model.

Preparation of measuring instruments
The measuring tool used is a questionnaire that reflects the performance of latent variables through its indicators. This questionnaire is used to determine the effect of industry target development variables and industry characteristics on the model of industrial competitiveness development. The number of respondents used is 160 respondents manufacturing industry. Respondents who fill out the questionnaires come from elements of government and business actors in the field of manufacturing industry. With estimation models using maximum likelihood (ML), the minimum required sample size is 100 [14]. The SEM method is the preferred method for obtaining structural models that can be used for predictive purposes. This is because the SEM method can test the relationship of causality, validity and reliability. SEM can also be used for recursive and reciprocal models, and their outputs are determinants, structural models and measurement models [14].

Structural equation modeling analysis
The model development uses theoretical framework that the manufacturing industry competitiveness model is determined by two latent variables namely industrial development target and manufacturing industry characteristic. Based on the framework, a model framework is constructed using several indicators. The objective of developing the manufacturing industry is to use 3 indicators, as:

Interpretation of manufacture competitiveness model
The measurement model of the confirmatory factor analysis is a modeling process directed to investigate the existing indicators being perfectly capable of defining a construct. From Table 2 it can be seen that industry market indicator is unable to define construct model of competitiveness development of manufacture industry because its value is -1.536. Therefore, the indicators to be used in the manufacturing industry competitiveness development model are technological

Conclusion
From the results of this study can be concluded that the model of structural equation of manufacturing industry competitiveness is formed from two variables, namely the target of industrial development and industry characteristics. With probability value of goodness of fit test that has fulfilled the minimum limit of 0.05 on the measurement of confirmatory analysis, the proposed industry competitiveness model has been able to define the constructor of the variable of competitiveness. Thus, technology indicators, partnerships, manufacturing strategies and competitive strategies can be used as variables that affect the competitiveness of the manufacturing industry.