HIGH-TECH/LOW-TECH INDUSTRIES AND THE STRUCTURE-PERFORMANCE RELATIONSHIP WITHIN MEXICAN MANUFACTURES

2017 ◽  
Vol 3 (5) ◽  
pp. 45
Author(s):  
Dmitri Fujii
Keyword(s):  
Discriminant Analysis ◽  
Market Structure ◽  
Recent Literature ◽  
High Tech ◽  
Technological Capabilities ◽  
Empirical Application ◽  
Empirical Results ◽  
Statistical Robustness ◽  
Analysis Technique

Recent literature on Mexican industry has emphasized its uneven sectorial development: some sectors have been successful, while the rest remain well behind. Given these circumstances, the present paper proposes a particular division for Mexican industry in High-Tech and Low-Tech sectors. This division is based on technological capabilities for a particular sample of industries during the nineties and verified for statistical robustness using the discriminant analysis technique. Finally, the division is used for an empirical application in terms of profitability and market structure. The empirical results reveal a diverse behaviour of the High-Tech and Low-Tech groups.

scholarly journals The Influence of Core Technology Capability of High-Tech Industry on Sustainable Competitive Advantage

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xi Liu ◽  
Shuai Yang
Keyword(s):  
Competitive Advantage ◽  
Organizational Innovation ◽  
Core Competencies ◽  
Theoretical Research ◽  
High Tech ◽  
Sustainable Competitive Advantage ◽  
Technological Capabilities ◽  
High Tech Industry ◽  
The Core ◽  
The Impact

In order to explore how the core technological capabilities of the high-tech industry affect the sustainable competitive advantage of an enterprise, by consulting a large number of literature studies on sustainable competition, the characteristics of high-tech enterprises were summarized through analysis and sorting and a sustainable competition model was proposed based on market, management, marketing, strategy, and organizational innovation. Through factor analysis, correlation analysis, and structural equations of 266 survey data of related companies, the effectiveness of the model based on the impact of core capabilities of high-tech companies on sustainable competitive advantage was confirmed. The results show that the core competencies of high-tech enterprises’ market recognition, strategic planning, management and operation, full-person marketing, and dynamic marketing directly affect the company’s sustainable competitive advantage. The most important influence on a company’s sustainable competitive advantage is market awareness, and the organizational innovation of the company can also influence the sustainable competitive advantage indirectly, while dynamic marketing can increase the other four capabilities to improve the sustainable competitive advantage of the enterprise. The theoretical model is established to identify the core technological capabilities of high-tech enterprises that can help enterprises effectively identify the core technological capabilities that can form a sustainable competitive advantage and then provide ideas for enterprises to build theoretical research on core technological capabilities.

scholarly journals Failure and Value Creation: A Discriminant Analysis Applied to Moroccan Industrial Companies Listed on the Casablanca Stock Exchange

2020 ◽  
Vol 3 (4) ◽  
pp. 7-28
Author(s):  
Abdelkader Derbali
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Scientific Knowledge ◽  
Value Creation ◽  
Explanatory Variable ◽  
Stock Exchange ◽  
Linear Discriminant ◽  
Empirical Results ◽  
Industrial Companies ◽  
Financial Difficulties

This article purposes to assess the contribution of shareholder value creation as an explanatory variable for the failure of Moroccan industrial companies listed on the Casablanca stock exchange. It also offers a scoring that reflects the probabilities of the financial difficulties to occur. There were used data for 30 Moroccan industrial companies listed on the Casablanca stock exchange during the period of study from 2010 to 2018. Methodologically, a linear discriminant analysis was employed. The empirical results of the discriminant analysis applied during the period of 2010-2018 show that value creation, liquidity and the size of the company are the most determining variables in classifying companies according to the degree of financial difficulties. Thus, the results received make it possible to create a relationship among recurrent scientific knowledge about forecasting the companies’ failure and empirical findings in the context of Moroccan industrial companies listed on the Casablanca stock exchange.

What does Facebook ‘afford’ do-it-yourself musicians? Considering social media affordances as sites of contestation

2019 ◽  
Vol 42 (2) ◽  
pp. 277-292 ◽  
Author(s):  
Ellis Jones
Keyword(s):  
Social Media ◽  
Recent Literature ◽  
Theoretical Work ◽  
Analytical Tool ◽  
Empirical Application ◽  
Recent Theoretical Work ◽  
User Groups ◽  
Do It Yourself ◽  
Facebook Pages ◽  
Shed Light

Recent theoretical work by Internet and social media scholars promises to offer valuable clarity to a concept which has been historically rather muddy: the affordance. Connections and shared themes within this recent literature have been thus far rather under-developed, and therefore the first contribution of this article is to strengthen those connections. It argues for a nascent conceptualisation of affordances as ‘sites of contestation’, improving on unsatisfactory applications of affordance theory to date by focusing on the specificity of user-groups, on social media’s status as both textual and material, and on power imbalances between users and platforms. The second contribution of this article is an empirical application of this analytical tool. Drawing on ethnographic work in a do-it-yourself (‘DIY’) music scene in Leeds, it considers what is ‘afforded’ to these practitioners by the Facebook Pages platform. Three key affordances are outlined – ‘digging’, ‘rallying’ and ‘surveilling’ – which shed light on the complexity and variety of contestations enacted between platforms and users.

Venture investment assessment of the biotechnology industry

2017 ◽  
Vol 23 (3) ◽  
Author(s):  
Xiangli Kong
Keyword(s):  
Comprehensive Evaluation ◽  
Positive Impact ◽  
Evaluation Model ◽  
Indicator System ◽  
Biotechnology Industry ◽  
High Tech ◽  
Empirical Results ◽  
Venture Investment ◽  
Comprehensive Evaluation Model ◽  
Production Value

Abstract: The biotechnology industry has been the leading industry among various high-tech industries since the mid- and late stage of 20th century and has applied in many fields. Venture investment originates from the same stage. This study evaluated the value of venture investment programs through qualitatively analyzing the venture investment of the biotechnology industry. According to the characteristics of biotechnology industry, a biotechnology industry venture investment assessment indicator system was established firstly. Then a cluster-radial basis function (RBF) neural network comprehensive evaluation model was established. The comprehensive evaluation value of the biotechnology industry venture investment programs was obtained through analyzing the relational expression with regard to biotechnology industry production value and venture investment. The above models and relational expression were verified. The fitting coefficient of the model empirical results suggested that reached 0.912, and the error in the comprehensive evaluation model test was 0.052. The dynamic simulation result ranking was highly identical with the practical operation results. The empirical results of the relational expression suggested every 1% of increase in the logarithmic value of biotechnology industry venture investment could result in 0.727% of increase in the industry program production value. Therefore, the models and relational expression obtained were verified with practical operability and certain accuracy. Venture investment can effectively promote the development of the biotechnology industry and produce positive impact on the development of venture investment in the biotechnology industry in China.

scholarly journals PERBEDAAN KEPUTUSAN MAHASISWA DALAM MEMILIH STIE DI JAWA TIMUR

2017 ◽  
Vol 11 (3) ◽  
pp. 321
Author(s):  
Nur Handayani
Keyword(s):  
Factor Analysis ◽  
Discriminant Analysis ◽  
Learning System ◽  
Internal Factor ◽  
Analysis Technique ◽  
Clean Environment ◽  
Two Factors ◽  
Boarding House ◽  
Research Population ◽  
System 2

This research aim is to know the factors which influence student in selecting STIE in east java and to know factor differences which influence student’s decision in selecting STIESIA Surabaya,STIE Perbanas and STIE Malangkucecwara.This research population is college student in the second semester of 2003/2004. Data analysis technique uses .factor analysis and discriminant analysis. Factor analysis result indicates that proposed hypothesis is can not be rejected or there are several factors which influence the student’s decision differences in  selecting STIE (13 variables in 12 .factors).  Discriminant analysis result indicates that the variables which are differenciate the decision. The variables are divided in two factors, which are internal factor and eksternal  factor. Internal  factor consists of (1) reguler learning system, (2) school  fee credit, while eksternal factor consists of (I) health facility, clean environment and (3) boarding house location.

scholarly journals ANALISIS STRUKTUR, KONSENTRASI, DAN EFISIENSI PASAR INDUSTRI TELEKOMUNIKASI DI INDONESIA

Media Ekonomi ◽  
2016 ◽  
Vol 24 (2) ◽  
pp. 113
Author(s):  
Zulfikar Adi Satria ◽  
Tri Kunawangsih P
Keyword(s):  
Data Envelopment Analysis ◽  
Market Structure ◽  
Concentration Ratio ◽  
Telecommunications Industry ◽  
Telecommunication Industry ◽  
Data Envelopment ◽  
Total Revenue ◽  
Analysis Technique ◽  
Efficient Level ◽  
Very High

<p><em>The purpose of this study was to determine how the structure, market concentration and efficiency of the telecommunication industry in Indonesia. The analysis technique used in this research is Concentration Ratio (CR4) and Data Envelopment Analysis (DEA). Total revenue of the Indonesia telecommunication industry from 2010-2015 were used to calculate Concentration Ratio (CR4) and Data Envelopment Analysis (DEA) are input and output, the input consists of total assets, debt and equity, the output consists of total revenue and gross profits. Based on the analysis results of Concentration Ratio (CR4) is quite of very high ranging from 98,17% - 99,67%, the market structure in property industry classified within a very high concentrated oligopoly. Results from Data Envelopment Analysis (DEA) in 2010-2015 there were 1 efficient company. As a result of an oligopoly market structure is very tight, then in the telecommunications industry is a lot to make improvements to network sharing and speed the delivery of messages, telephone, and internet as well as to achieve efficient company should refer to the telecommunications industry, which reached the maximum efficient level. In order to achieve an efficient level that has not been efficient, the company must conduct debt reduction, labor usage more efficient and increase product sales.</em></p>

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