Number of students in higher education in Turkey (1985–2015).
\r\n\t
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In this new structure, the economic power, knowledge, and learning levels of the individuals and the competitiveness of the countries are often measured by the human and social capital [1]. This process has increased expectations from the universities responsible for the production and sharing of knowledge and has become a focus of attention for higher education societies in almost all countries. Hence, the demand for higher education has increased rapidly all over the world. According to the reports of international organizations such as the World Bank, United Nations Educational, Scientific and Cultural Organization (UNESCO), and the Organisation for Economic Co‐operation and Development (OECD), the number of students receiving higher education in the world is increasing rapidly. In the last 20–25 years, the expansion and promotion of higher education have become political goals in both developed and developing countries. Numerical data also indicate that efforts to reach these goals have resulted in considerable success. Worldwide, the number of higher education students, which was 13 million in 1960 (0.43% of the world population), reached 82 million in 1995 (1.43% of the world population), and 137 million in 2005 (2.11% of the world population). This number exceeded 152.5 million in 2007 (2.27% of the world population). The number of students in higher education is doubling every 15 years on a global basis. It is predicted that this number will reach 200 million students in 2020 [1, 2].
\nIncreased demand and enrolment rates in the higher education system do not indicate that all segments of society are equally able to benefit from higher education. In many countries, there is a huge difference between higher education participation rates of different social and cultural groups. Despite various projects and policies of governments, institutions and other political entities, there is still inequality in access to higher education in many countries [3–5]. The studies on higher education have revealed the existence of material and cultural inequalities and hierarchies. Researchers have explored the role of education in the production of dominant cultures and classes and its role in maintaining social and economic inequalities [6–11]. The inequality that exists in the beginning and continuing stages of higher education has been examined by many researchers starting from the 1960 s until today [3, 5, 12–21]. These studies mainly aim to reveal the effects of social stratification on higher education. The research results show that socioeconomic and sociocultural factors, especially the factors such as the income status, education level of the parents, and the living area, are determinants of the higher education attendance and continuation for young adults in many countries. The research results show that the difference between the entrance rates of individuals coming from different social classes is increasing gradually, and the problems arising from these social differences are getting deeper. Higher classes are even more represented in higher education than they have been in the past [22–24].
\nAs in many countries, higher education access and the following processes are experienced similarly in Turkey. In this article, the problem of access, which is still faced in Turkey despite the rapid expansion of the system of higher education in recent years, is evaluated on the basis of social equality. In this respect, the problem of social inequality experienced during the process of access to higher education is described with a deeper viewpoint. With the theoretical framework of social justice, the study focuses primarily on the general structure of the higher education system in Turkey and the current point reached by the expansion of higher education. The goal of this study is to show the effect of the determinants of higher education access. However, when access to higher education is considered, it is not be correct to regard the problem as only coming from the university. Because the right to have access to higher education requires a discussion beyond the problems arising from the supply‐demand imbalance, the benefiters of higher education and the effects of socioeconomic background characteristics on this process are examined.
\nWith the proclamation of the Turkish Republic in 1923, there has been rapid development in the field of higher education as in every other area such as economy, agriculture, human rights, politics, etc. [25]. The first radical changes to the higher education system in the Republic era were made with the 1933 university reform. Later, attempts were made to reform with the laws of 1946 and 1973. The last radical change in Turkey’s higher education system has come with the Law No. 2547 issued in 1981. The last radical change in the higher education system in Turkey has been put into practice with the Law Number 2547 issued in 1981 [26, 27]. In line with these reforms, the developments experienced in the field of higher education in Turkey have been summarized in four periods below.
\nFirst Period – 1933 Reform: Before the foundation of the Turkish Republic, Darülfünun was the institution that was accepted as a university in the Ottoman Empire period. Shortly after the proclamation of the Republic, in 1924, this institution bearing the name of Darülfünun‐u Osmani was named Istanbul Darülfünun with the Law Number 493. The Faculties of Medicine, Law, Theology and Science affiliated to Istanbul Darülfünun were founded, and the university was transformed into a “Supplementary Budget” administration. As a result, practitioners took an important step toward the goal of making universities independent organizations [26]. However, Istanbul Darülfünun, which was taken over from the Ottoman Empire and considered as the main higher education institution of the country, was not able to show the development expected by the Turkish society, as the society expected to witness innovations in educational practices. As a result, the necessity of a comprehensive reform toward the university began to be discussed despite the interest shown between 1923 and 1932 [28, 29].
\nIn this direction, the 1930s were the years when major breakthroughs began in higher education in Turkey. During this process, the most important of these developments in higher education was the 1933 university reform [28]. In 1933, Professor Albert Malche, who was invited from Switzerland to renovate Darülfünun, prepared a report about the university. The report contained statements on Darülfünun’s structure and functioning. The report stated that Darülfünun did not play a sufficient role in the settlement of the Turkish Revolution, opposed or resisted reforms, did not have a supervisory unit, did not conduct scientific studies, and worked in isolation from society. Based on these reasons, in the same year, Darülfünun was closed with the Law Number 2252 and reopened with the name of “Istanbul University” in November 1933 [26]. The laws and regulations envisaging fundamental changes in the administration of Istanbul University, the first university of the Republic of Turkey, have entered into force since this date, and the “university” statement in Turkish legislation was mentioned in the law 2252 for the first time [28].
\nSecond Period – 1946 University Reform: The year 1946 was a turning point for Turkey in terms of higher education. In 1946, the elections were held in Turkey through a multiparty system from a one‐party system, and the university reform was also carried out with the new law, number 4936 [30]. In 1946, universities were given a new and advanced status by linking universities and affiliated units, and linking institutions and their functioning with legal regulations in line with the aims determined by the university reform, which was established with the law number 4936. With this law, universities were organized in a structural unity. A new institution named “Inter‐University Council” was formed for the managerial dimension of this unity [26]. With this law, the definition of universities was revised. The revised version pointed out that universities should have science and management autonomy. At the same time, attention was paid to the process of scientific processes such as research and examination [31]. Universities gained autonomy in financial, scientific, and managerial terms in this period.
\nWith the change of government in 1950, the structure of the Turkish universities adopting the Continental European model underwent a significant change. The new government, which attached greater importance to the free market economy, believed that an American University model would meet the human power need of a growing economy. Hence, the government focused on spreading the university system across the country [29]. In this direction, after 1950 s, there have been significant developments in higher education in accordance with the social demand. The most important of these developments has been the dissemination of colleges and universities to regional centers [32].
\nThird Period – 1973 Reform: In 1973, the issue of reform in education came to the agenda again and the universities law numbered 1750 was put into practice [33]. A new and positive provision brought by the law number 1750 was the establishment of a “Higher Education Council” that was developed in order to conduct necessary investigations, researches and evaluations in order to direct higher education and to provide coordination among higher education institutions [28]. Apart from this, the academic, administrative, and financial structure introduced by law number 4936 in 1946 was preserved by this law [29].
\nFourth Period – 1982 University Reform: Significant developments were witnessed in higher education institutions in Turkey between 1946 and 1981. However, lack of coordination and cooperation among higher education institutions and problems in planning and supervision during this period caused the development in higher education institutions to fall behind the expectations of the society from universities. In addition, the political, social and economic problems that emerged between 1960 and 1980 further increased the deterioration in higher education. As a result, higher education institutions faced management and financial resource problems. For this reason, a radical reform at the end of the seventies became inevitable, and at the end of this process, the Higher Education Law Number 2547 was adopted on November 6, 1981, in order to plan, coordinate and supervise higher education in Turkey. Some of the articles of Higher Education Law No. 2547 were amended after a short time (20 April 1982), and the authority of the Council of Higher Education (YÖK) established in accordance with this law was expanded. YÖK was redefined as a constitutional institution in order to direct the important activities of higher education institutions such as regulation, supervision, teaching, and research [29].
\nIn the years prior to the 1981 university reform, the Turkish higher education system consisted of five types of institutions: universities, academies affiliated with the Ministry of National Education, two‐year vocational colleges and conservatories mostly affiliated with the Ministry of National Education, Annual education institutes, and Common Institution of Higher Education (YAYKUR). With this law, all the higher education institutions in the country have been united under the Higher Education Council (YÖK). Academies have been transformed into universities, educational institutes to education faculties, and conservatories and vocational colleges have been linked to universities. Also, non‐profit foundations that aim to establish higher education institutions have been permitted.
\nThe current structure and management of the higher education system in Turkey were established based on the Higher Education Law No. 2547 issued in 1981. Various changes have been made to the law in time. According to this law, higher education within the National Education System of Turkey consists of secondary education‐based associate degree (at least 2 years), undergraduate (at least 4 years) and graduate (master’s degree, doctoral degree, expertise in arts and proficiency in arts) degrees. The superior boards of higher education in Turkey are the “Higher Education Council,” “Higher Education Supervision Board,” and “Inter‐university Council.” Universities and high technology institutes and their faculties, institutes, colleges, vocational schools, conservatories, research and application centers are considered as Higher Education Institutions (Law Number 2547, Article 3). The financing of higher education, which is considered as a public service in Turkey, is carried out by two basic methods. Constitutionally, public finance has been used in state universities, and special financing system has been used in foundation universities. State universities are financed by the budget of public financing. The second largest income source of the universities is the circulating capital [2]. Although the administration of higher education, under the Law Number 2547 on higher education, is based on the Anglo‐Saxon model [34], its funding sources and budget still operate according to Continental European Model principles [34]. This can be called a mixed model application.
\nHigher education in Turkey is regarded as necessary to gain access to certain occupational fields, possess social status, and acquire the ability to realize oneself individually [35]. For this reason, in parallel with the developments around the world, the expansion of higher education in Turkey has gained momentum since the 1980 s, and the number of students and institutions in higher education has increased every year [2, 36, 37].
\nTable 1 shows the student numbers in higher education in Turkey from 1985 to 2015.
\nYear | \nAssociate degree | \nUndergraduate | \nGraduate | \nFormal education total* | \nOpen education and distance education total** | \nTotal number of registered students |
---|---|---|---|---|---|---|
1984–1985 | \n45.642 | \n287.087 | \n19.156 | \n351.885 | \n65.456 | \n417.341 |
1989–1990 | \n62.671 | \n353.869 | \n40.665 | \n457.205 | \n228.295 | \n685.500 |
1994–1995 | \n127.922 | \n502.083 | \n66.979 | \n696.984 | \n477.315 | \n1.174.299 |
1999–2000 | \n218.099 | \n713.259 | \n84.054 | \n1.015.452 | \n488.569 | \n1.503.981 |
2004–2005 | \n402.404 | \n871.091 | \n137.265 | \n1.410.760 | \n695.591 | \n2.106.351 |
2009–2010 | \n613.077 | \n1.152.265 | \n206.775 | \n1.972.117 | \n1.557.217 | \n3.529334 |
2014–2015 | \n896.031 | \n1.897.692 | \n406.817 | \n3.200.540 | \n2.862.346 | \n6.062.886 |
Number of students in higher education in Turkey (1985–2015).
Associate and undergraduate students are included in the number of secondary education students. Graduate students include postgraduate, doctoral and medical specialist students.
Total number of students in distance and open education; these programs consist of associate, undergraduate and graduate students.
The number of total higher education students, which was 2914 in 1923 (Turkey’s population was approximately 13 million people), the date of the foundation of the Republic of Turkey, increased to 346,476 in 1977–1978 (Turkey’s population was 41.02 million people). In the following years, this number decreased steadily to 237,369 in 1980–1981 (Turkey’s population was 44.73 million people) [29]. As seen in Table 1, from this date onwards, the total number of students continuously increased to 1,503,981 in 1999–2000 (Turkey’s population was 67.80 million people), 1,557,217 in 2009–2010 (Turkey’s population was 72.56 million people), and 6,062,886 in 2015 (Turkey’s population was 78.74 million people). The total number of students for the year 2015 is 6,062,886. Of these students, 5,615,293 are in state universities and 447,593 are in foundation universities. Of the students, 3,366,658 are male and 2,786,228 are females. According to 2015 data, 3,200,540 students are studying in structured programs. The total number of students in open education is 2,803,064, and the number of students studying in distance education programs is 59,282.
\nIn line with the increasing number of students in Turkey, the number of institutions in higher education has also increased, especially since 1992. There are currently 23 state and two high‐tech institutes, established during the period of 1992–1994 and 41 state and 21 foundation universities, established during the period of 2006–2009; these increases also accelerated the increase in the number of students. In addition to state universities, the number of foundation universities has also started to increase rapidly since 1996, and with the 50 universities established in 1996–2010 period, the total number of foundation universities has reached 54. As of 2008, universities were established in all major cities. In 2015, the number of institutions in higher education reached 193, of which 109 were state, 76 were foundation universities, and 8 were foundation vocational high schools [2, 38].
\nThe rate of formal higher education enrollment in Turkey increased from 5.6% in 1980 to 9.4% in 1990, to 17.9% in 2000 and to 35.6% in 2010 and to 39.5% in 2015 [2, 38, 39]. The most important indicator of the inability of the schooling rate to reach the desired level in higher education is the number of students who have applied and placed in the university for years. Table 2 lists the number of students who applied for and entered the university during the period between 1980 and 2015.
\nYear | \nThe number of applicants | \nSuccess | \nSuccess rate (%) |
---|---|---|---|
1980 | \n466,963 | \n41,574 | \n8.9 |
1985 | \n480,633 | \n156,065 | \n32.5 |
1990 | \n892,975 | \n196,253 | \n22.0 |
1995 | \n1,265,103 | \n383,974 | \n30.4 |
2000 | \n1,407,920 | \n439,061 | \n31.2 |
2005 | \n1,844,891 | \n688,840 | \n37.3 |
2010 | \n1,587,866 | \n874,306 | \n55.1 |
2015 | \n2,126,684 | \n983,090 | \n46.2 |
The number of students who applied to university entrance exam in Turkey and succeeded (1980–2015).
Source: ÖSYM [43].
The numbers in Table 2 show that 32.5% of those who applied to universities in 1985, 30.4% in 1995, 37.3% in 2005, and 46.2% in 2015 have gained access to these universities. Turkey, experiencing a rapid population growth from 1960 to 1990 s, has experienced a moderate rate of population growth since the beginning of 2000. According to TUIK data, the annual rate of population growth declined to 13 in a thousand in 2010. It is estimated that the rate of population growth will fall to 7.7 in a thousand by 2025. In Turkey, where the young population is higher compared to other countries in Europe, the school‐age population (5–24 years of age) is expected to show a slight change toward 2025 by decreasing from 34.5 to 29.5% of the total population [40]. The age population in higher education is expected to be 5.064 million in 2020 and 5.077 million in 2025.
\nAccording to Tanrıkulu [36], if the historically continuing tendencies regarding the financing, the number of students, and teaching staff in higher education continue and if there is no policy intervention, the demand for higher education of young people in Turkey will not be met in 2025. Tanrıkulu’s research predicted that the rate of organized schooling, which is the most important indicator of access to higher education [36], would reach 53.7% in 2025, and Turkey will continue to lag behind developed countries. It is estimated that the rate of settlement of formal education, which shows the demand level of higher education supply, will reach only 38.7% in 2025. These indicators show that the demand for higher education, which cannot be met in Turkey today, will continue to exist in 2025 as well.
\nMoving from statistics for higher education, it will be correct to say that there is still an important supply‐demand imbalance regarding the level of higher education in Turkey. The demand for higher education tends to continue due to the following factors [41]:
\nTransition rates from primary education to secondary education continue to rise.
Schooling rates and number of graduates in secondary education continue to increase.
Adult demands for higher education are increasing, and the age range is expanding.
The social demand for higher education (the learning society) is continuing.
The individual benefits of higher education remain important. In this context, employment participation, relative earnings, and individual outcomes tend to rise.
The participation of females is growing faster than the participation of males.
While the demand for higher education and the number of high school graduates has been continuously increasing, the total capacity of higher education institutions in Turkey has not increased in parallel with these numbers [42]. The increasing demand for higher education has forced universities to seek student selection and placement methods. Hence, a central examination system has been used in order to solve the problem of accumulation experienced during the process of accessing higher education in Turkey [42]. Although the structure of the central examinations has changed frequently, the existence of these exams has not yet come to an end. In 1974, a decision was made for launching a center that would administer the university entrance exam. As a result, the Inter‐university Student Selection and Placement Center was established. Under the name of the Student Selection and Placement Center (OSYM), this center has been preparing central exams for secondary school graduates who wish to enter higher education institutions since 1981 [2].
\nIn Turkey, the university entrance system has been implemented in a two‐stage, 6‐exam structure since 2010. The first stage is the Higher Education Transition Examination (YGS), and the second is the Undergraduate Placement Examination (LYS), which consists of five separate examinations. In 2015, a total of 2,126,670 candidates applied for ÖSYS in order to enter higher education. Of these candidates, 1,987,484 have entered YGS. There were 1,779,850 candidates who entered the exam and passed the 140 point limit. There were 1,369,147 participants who have passed the 180‐point limit. According to the numbers revealed by OSYM [43], in 2015, 983,090 students were placed in universities (417,714 undergraduate students, 195,791 associate students, 171,445 associate students without examination and 198,140 open education students).
\nThe university placement exam aims to choose the ones who are appropriate for the quotas among many candidates [2]. A centralized exam, based on multiple‐choice questions, has been conducted in order to eliminate the possibility of student mistrust. However, the existing student placement exam takes only the score superiority among those who apply to a program into account. The candidate may ignore his/her own interests and abilities and can often turn to a profession that he will not be interested in the future. In addition, students who graduate from some public schools and private high schools in Turkey can be placed in one of their first choices according to the exam results. The share of these students in the total number of students in secondary education is below 10%. The other majority either tries to keep up with a program that they are not interested in, or tries to change their program by taking the exam multiple times in the following years. The centralized examinations objectively measure the competence and knowledge of students [2]. Obviously, it is not realistic to expect a centralized exam to solve the social and economic inequalities experienced in entering the university. However, this should not be the reason for ignoring the fact that exam results play a decisive role in the placement of students in higher education institutions and contribute to the maintenance of this disparity [2].
\nThe supply‐demand imbalance in higher education creates adverse effects especially on the functioning of secondary education and increases the demand for after‐school support; the imbalance puts the families under a financial burden and most importantly creates adverse effects on the psychology of young people and their families [40]. The inability to establish a proper balance between supply and demand also contributes to the formation of competition in the field of higher education. The imbalance between supply and demand has led to competition in some programs. The fact that the competition is so comprehensive makes it inevitable that there are winners and losers [1].
\nThe negative effect of the examination system is felt in the whole education process, starting from the elementary school level. Families whose social and economic conditions are appropriate usually make long‐term educational plans for their children. As a consequence, they look for ways to increase the chances of their children in this tough long‐lasting race [35]. For this reason, the existing examination system is effective in changing the nature of the relationship established with knowledge. Acquisition of knowledge to succeed in exams leads to its instrumentalization and therefore externalization to its subject [44]. This process that accelerates the commodification of knowledge is influential in the transformation of all relations in the educational process. Educational achievements are measured by exams and tests, and the reduction of achievement to success in the central exams creates a competitive environment among the students and the teachers [45] and makes learning associated with drudgery.
\nThe reduction of the examination system to a technical level by ignoring the economic and social influences of the entrance system makes the attempts for improving the system inefficient. For this reason, access to the university should be considered in a comprehensive way, taking into account social, economic and political consequences [46]. Otherwise, the education system supported at every stage by “student selection” processes will reproduce the differences and inequalities that the capitalist system has created and deepened in the society [47]. Rare examples, such as the placement of students from different socioeconomic classes in higher education programs that demand high scores, are the most basic arguments for advocating centralized exams. However, studies conducted in Turkey reveal that there is a relationship between exam achievement and the socioeconomic origin of students, the type of school they finish, their parents’ educational status, and the geographical region where they come from. Although inequalities in education are accepted by almost all segments of the society, the opportunity given by the exam is appealing to people from all segments of life [45].
\nEducational indicators and research in Turkey demonstrate that not all individuals benefit equally from educational services. In Turkey, there are inequalities based on socioeconomic status, gender and living area of the student in terms of education access and quality [48]. These inequalities continue to become more apparent in the higher education phase. Due to the difference between regions and school types, children of families with good income can be better prepared for higher education. There is also a difference between higher education access for females and males. This difference has not shown any significant decline in the past few years. All these points show that there are inequalities in access to higher education [49].
\nResearch in Turkey reveals that socioeconomic factors such as parents’ educational level [1, 45, 50–52] and income level [51–53] are the most important determinants of benefiting from university and test achievement. Additionally, factors such as the type of school attended before higher education, and the quality of the education received [54–56], residence type [51, 55–58], after‐school support and attendance of private courses [37, 52, 59–61] are listed as other factors affecting university access.
\nOne of the indicators that show how effective socioeconomic factors are in benefiting from the right to higher education in Turkey is the education expenditure of households. Expenditures made by the household to benefit from the education service are considered as special costs of education [62]. The share and the amount of total education expenditures in Turkey vary greatly among different income groups. Table 3 shows education expenditures in Turkey according to 20% income groups.
\nIncome group | \n2004 | \n2008 | \n2012 | \n2014 | ||||
---|---|---|---|---|---|---|---|---|
Share of total educational expenditures (%) | \nAmount of educational expenditures (1. %20 = 1) | \nShare of total educational expenditures (%) | \nAmount of educational expenditures (1. %20 = 1) | \nShare of total educational expenditures (%) | \nAmount of educational expenditures (1. %20 = 1) | \nShare in total educational expenditures (%) | \nAmount of educational expenditures (1. %20 = 1) | |
1. % 20 | \n2.3 | \n1 | \n3.3 | \n1 | \n2.3 | \n1 | \n2.2 | \n1 |
2. % 20 | \n5.4 | \n2.3 | \n6.5 | \n2.0 | \n5.6 | \n2.4 | \n5.6 | \n2.5 |
3. % 20 | \n10.2 | \n4.4 | \n14.0 | \n4.2 | \n9.0 | \n3.9 | \n10.6 | \n4.8 |
4. % 20 | \n22.5 | \n9.8 | \n19.6 | \n5.9 | \n16.3 | \n7.1 | \n16.9 | \n7.7 |
5. % 20 | \n59.6 | \n25.9 | \n56.6 | \n17.2 | \n66.8 | \n29.0 | \n64.7 | \n29.4 |
Education expenditures in Turkey according to 20% income groups (2004–2014).
Source: TUIK 2004, 2008, 2012, 2014 Household budget survey.
According to the income in 2014, the share of the first 20% group with the lowest income in total education services expenditures is 2.2%, while the share of the fifth 20% group is 64.7%. As shown in Table 3, the education expenditures of the families with the highest income group are 25.9 in 2004, 17.2 in 2008, 29.0 in 2012 and 29.4 in 2014, all much higher than the families with the lowest incomes. These ratios show that education expenditures increase as income increases in Turkey, and therefore, the families in the highest income group provide better education opportunities for their children than the families with lower incomes.
\nThe growing tendency for parents to participate in the private cost of education makes the social mobility of education inaccessible for the low‐income families [63]. Despite the large increase in student numbers in the last two decades, the university student profile is usually composed of higher income segments. This situation is even more evident at state universities that require high scores. It is striking that even a very large part of the most successful foundation universities consist of students who score lower on the university entrance examination. This gives the students who may not pass the entrance exam the chance to enter a university due to the financial power of their families. Consequently, by creating a new privileged group, the role of education in balancing the differences in different segments of society is restricted [64].
\nThe most important part of the education expenditure of the household in Turkey includes the expenditures made for central exam preparations. The increasing selectivity of central examinations in Turkey has led to efforts to obtain this opportunity in large sections of society who plan their future based on having access to higher education. Thus, parents have been making every sacrifice for their children to make them benefit from higher education. This situation has led to the formation of the “test preparation” sector that has been constantly extending [37]. Individuals wishing to achieve in this competitive environment have turned to institutions and practices that may be alternatives to schools in order to increase their success in university exams [65]. The most important institutions that emerged as an alternative to schools were after‐school support centers that underwent structural change in 2015. In addition, practices under different names such as private courses, extra study sections, student coaching have become alternatives for families who were willing to spend their incomes for the sake of making their children successful in the university placement exam [42].
\nIn 2005, the Turkish Education Association (TED) conducted a comprehensive survey to determine the size of the expenditure for after‐school support institutions. According to the survey, the expenditure made by the students who entered ÖSS in 2004 to enter the university was 8.4 billion dollars and 9.2 billion dollars in 2005. The average expenditure per person in the preparation process for the university on the side of the families was $ 4708 in 2004 and $ 5322 in 2005. In 2004, the share of budget per student in higher education was $ 1990 [37]. The results of another study carried out by the Turkish Education Association in 2010 also show that the test preparation sector has brought about a serious financial burden on families. Expenditures made by the families for the preparatory work each year are about 16 billion TL (about 5 billion dollars). The distribution of the preparatory expenditures made by the families in one year area is as follows: After‐school support center: 5,707,811,064 TL (1.7 billion dollars), expenses for test preparation, book magazines and similar materials: 2,160,968,761 TL (635 million dollars), tuition and course payments for the preparation of the test: 1,267,398,136 TL ($ 372 million), expenses for transportation, meals and other expenses 5,198,178,895 TL (1.5 billion dollars), tuition fee payments: 2,374,954,883 TL ($ 698 million).
\nBakıs et al. [66] state that after‐school support, expenditures do not create benefits for students. According to the authors, this process creates a system based on reinforcement and competition rather than qualification and creating benefits based on it. The lack of a “diploma” which is the basic feature of the educational benefit is also another reason for the ineffectiveness after‐school support process. The authors state that one of the world’s most irrational educational systems emerges in terms of economic acceptance, given the size of the expenditure that individuals make to participate in a race that only 15–20% will succeed.
\nOne of the factors affecting the higher education goals and decisions of the individuals in Turkey is the quality of the education they have received before the higher education. The quality of education that individuals receive before the higher education, especially at the level of secondary education, can directly affect the higher education goals. The level of secondary education not only affects individuals’ access to higher education, but also their preferences of universities and departments in higher education.
\nThe most important reason why the level of secondary education in Turkey is so effective in higher education access and higher education decision is the difference in qualifications between school types in secondary education. For many years, certain types of schools in secondary education have provided qualified education opportunities, so their graduates are more successful in achieving higher education. Higher education access statistics in accordance with school types support this situation [42].
\nTable 4 lists the number of candidates who applied to higher education according to various school types in 2015.
\nSchool type | \nÖSYS applicants | \nPlaced in undergraduate programs | \nPlaced in associate degree* | \nOpen education | \nTotal number of student placement | ||||
---|---|---|---|---|---|---|---|---|---|
Candidate number | \nPlacement ratio (%) | \nCandidate number | \nPlacement ratio (%) | \nCandidate Number | \nPlacement ratio (%) | \nCandidate number | \nPlacement ratio (%) | ||
General high school | \n816.179 | \n126.084 | \n15.4 | \n114.059 | \n14.0 | \n86.072 | \n10.6 | \n326.215 | \n40.0 |
Private high school | \n8.228 | \n2.286 | \n27.8 | \n971 | \n11.8 | \n491 | \n5.9 | \n3.748 | \n45.5 |
Anatolian high school | \n294.672 | \n147.391 | \n50.0 | \n19.017 | \n6.5 | \n6.183 | \n2.1 | \n172.591 | \n58.6 |
Science high school | \n16.241 | \n9.602 | \n59.1 | \n146 | \n0.9 | \n87 | \n0.5 | \n9.835 | \n60.6 |
Private science high school | \n5.471 | \n3.547 | \n64.8 | \n69 | \n1.3 | \n50 | \n0.9 | \n3.576 | \n65.4 |
Social sciences high school | \n2.706 | \n1.548 | \n57.2 | \n22 | \n0.8 | \n8 | \n0.3 | \n1.578 | \n58.3 |
Fine arts high school | \n6.276 | \n187 | \n2.3 | \n397 | \n6.3 | \n178 | \n2.8 | \n762 | \n12.1 |
Teacher high school | \n43.684 | \n25.929 | \n59.4 | \n967 | \n2.2 | \n708 | \n1.6 | \n27.604 | \n63.2 |
Religious Vocational School | \n149.727 | \n25.511 | \n17.0 | \n14.429 | \n9.6 | \n29.527 | \n19.7 | \n69.467 | \n46.4 |
Commercial vocational school | \n123.442 | \n9.474 | \n7.7 | \n42.240 | \n34.2 | \n14.609 | \n11.8 | \n66.323 | \n53.7 |
Technical high school | \n81.976 | \n11.291 | \n13.8 | \n28.665 | \n35.0 | \n4.517 | \n5.5 | \n44.473 | \n54.3 |
Industrial Vocational School | \n211.390 | \n5.937 | \n2.8 | \n61.253 | \n29.0 | \n14.774 | \n7.0 | \n81.694 | \n38.6 |
Vocational school for girls | \n158.879 | \n13.485 | \n8.5 | \n42.785 | \n26.9 | \n17.761 | \n11.2 | \n74.031 | \n46.6 |
Vocational school of health | \n53.717 | \n2.761 | \n5.1 | \n15.405 | \n28.7 | \n8.151 | \n15.2 | \n26.317 | \n49.0 |
Tourism vocational high school | \n15.320 | \n1.741 | \n11.3 | \n5.443 | \n35.5 | \n1.328 | \n8.7 | \n8.512 | \n55.6 |
The number of higher education applicants and placed candidates by school types in Turkey (2015).
Vocational‐technical high school students who are enrolled in associate degree programs are also students who pass without examination.
Source: ÖSYM [43].
The results on Table 4 show that the school types that had higher university entrance rates in 2015 are the Science and Anatolian High Schools, as it was in the past. Again, as in past years, the number of students who are placed in undergraduate programs from vocational‐technical high schools is still very low.
\nOne of the most important evidences of the qualitative differences among school types in secondary education in Turkey is the placement rate into the university. On the other hand, there are also other national and international exams, which aim to evaluate the school types in terms of academic achievement. If the types of schools in secondary education are examined in terms of academic performance in these exams, the secondary education programs that have lower achievement rates are noticed [67]. For example, the results of all the PISA exams between 2003 and 2012 display that the schools with the best performance in all fields in Turkey are Science, Anatolian and Teacher high schools. Conversely, the average of the high schools with the lowest average scores is multi‐programmed high schools, vocational schools, and general high schools [48].
\nIn mathematics literacy, which is one of the main fields in PISA 2003, Turkey ranks first among OECD countries in terms of inter‐school inequality. This situation was not the case in PISA 2006 results. Turkey is 11th among 30 OECD countries and 19th among 57 countries in terms of school inequality in the main field of science literacy. In intra‐school success, inequality among students is below OECD average. In other words, the inequality between schools in Turkey is deep, and the inequality within the schools is relatively low. When the average mathematics achievement scores of PISA 2012 for different schools in Turkey are examined, it is obvious that serious differences between the schools still persist. When we examine how much of the variance (change) in PISA 2012 mathematics scores is caused by the difference between schools, it is seen that Turkey is one of the countries with the highest rate of differences in schools among the OECD countries. In Turkey, 62% of the difference in PISA 2012 mathematics scores is the result of differences between school types [68]. Studies conducted using PISA data in Turkey show that student achievement is related to school type [69–74].
\nIn the study conducted by Berberoğlu [69], it was found that general high school, vocational high school, and Anatolian vocational high schools showed low performance levels among the schools participating in PISA 2003. Berberoğlu found that general high schools and primary schools were well below international averages, and that the Anatolian High Schools reached high achievement levels. Using PISA 2003 data, Çifçi [71] found that school type, school district, gender, and geographical region influenced students’ achievement rates in Turkey. Yılmaz [75] investigated the variables related to the science literacy of Turkish students using PISA 2006 data and found that most of the students’ variation in science literacy scores originated from the differences between schools. Using PISA 2006 data, Dinçer and Uysal Kolasin [73] found that a student studying in Anatolian High School received 66–79 points higher than a student in general high school. However, a student who is studying in general high school had 22–27 points higher than a student who is studying in vocational high school. In a study that used student questionnaires and cognitive skill tests obtained from PISA 2003, 2006, and 2009 PISA tests, Yalçın [74] exposed the ongoing qualitative difference between high schools. Science schools were the most successful school type in these three PISA exams. The Anatolian High Schools were one of the most effective schools in the 2009 and 2006 PISA exams. They also had a successful score in the 2003 PISA exam, although it was not as high as 2009 and 2006 results.
\nIn Turkey, individuals who graduate from the same level of education can develop themselves at different levels after entering higher education as a result of the differentiation of the quality of their education [76]. For these reasons, demand for “elite” high schools is high. Because graduates of these schools are more successful at university entrance exams, students find themselves in high‐quality, “respected” universities with high demands [61]. Higher education statistics and surveys reveal that access to these schools in Turkey is more dependent on socioeconomic factors. For example, 51% of the students in Science High School in 2013 and 42% of the students in Anatolian High School come from families with the highest socioeconomic level. On the other hand, 23% of the students in the vocational high school and 30% of the students in the other secondary education institutions have the lowest socioeconomic rate of 20% [7].
\nChildren of socioeconomically better families are more likely to have access to selective schools, as well as to receive more qualified training when they have access to these more sophisticated school types. Ultimately, their academic achievements are at a higher level than their peers [77].
\nAedo et al. [78] argue that the stratification of schools in secondary education in Turkey and the central examination system applied to secondary education in transition to secondary education make large differences between the achievements of students attending these schools. Likewise, the ERG [65] report emphasizes that the reasons for schools being so separated according to socioeconomic status in Turkey are the division of schools into types in secondary education, the differences in quality among schools, and the central examination system. As pupils are placed in schools in accordance with the competitive examination systems, student achievement and quality differences between school types and schools are intensified. As the qualitative differences become more intense, the competition in examinations increases, and thus, the differences created by socioeconomic background increase as well. Over the years, these processes have become interconnected, and at school level, there has been a breakdown according to socioeconomic roots.
\nObjective and subjective evaluations of the quality of secondary education show that this teaching process has serious problems in terms of quality and does not provide sufficient basis for higher education to students. There is consensus on the drawbacks of choosing university students based on only a single university entrance exam. The university exam takes only the final scores into consideration and places students in higher education institutions regardless of their competence. The exam ignores the shortcomings of the students who achieve to pass it. Consequently, higher education has to deal with the inadequacy of secondary education [2].
\nHigher education participation is important because of opportunities for the individual’s life. Higher education has an important role in terms of collective distribution of equality and social justice within a society. Higher education also contributes to social justice for the majority of people not directly involved. Such a view takes higher education beyond the limits of individual achievement to a broader contribution it makes to the society [4].
\nThe increase in the number of students and institutions in Turkey suggests that higher education is in a trend of massification [42]. However, the massification of higher education and democratization is not synonymous concepts. The massification of higher education is a necessary but inadequate condition for democratization. For the democratization of higher education, it is necessary that the benefit of higher education does not depend on the individual’s socioeconomic background and that the university student profile reflects the general population structure of the society in a proportional manner [57]. Access to higher education is concerned with ensuring that those who wish to benefit from it can pursue education without constraints other than their personal efforts and abilities. Expansion and participation in higher education are also expected to serve this purpose [1, 79].
\nThe main determinant of access to higher education in Turkey is socioeconomic status. Socioeconomic status characteristics affect not only the educational opportunities provided, but also the ways in which students perceive themselves and their education. In this sense, the students do not decide how much they meet the requirements of the application field with their higher education decisions and at the same time decide how suitable these choices are in terms of socioeconomic characteristics [1]. In other words, students’ social and economic backgrounds determine their educational preferences [80].
\nThe socioeconomic characteristics of the students’ families still have a conclusive influence in benefiting from higher education, as the current education system is inadequate to remove the disadvantages created by the socioeconomic status of the family on student achievement and orientation. For this reason, in order to limit the effect of socioeconomic characteristics on access to higher education and to enable competence‐based student selection, establishing the distribution of similar opportunities before higher education should be one of the priorities of the educational policies [1]. Socioeconomic status features are so pivotal in education that components such as learning and teaching processes cannot diminish the role of socioeconomic status in education. Hence, social inequalities are not eliminated through education; they are even produced by it. However, education is an important tool of social mobilization. Education should be used at the highest level of potential to reduce social inequalities. This is also an important requirement of a democratic and pluralistic society order [65].
\nHigher education is an educational right and a milestone. Every secondary school graduate should benefit from it in accordance with his/her abilities and interest. In a social order that is built upon democratic, egalitarian and fair decisions, the conditions to benefit from higher education should be constructed [35]. The only condition for eliminating the problems encountered during transition to higher education is to prevent the education from creating social injustices. Thus, education can play a part in removing social inequalities and stop the reproduction of these inequalities [45]. It is not possible for the necessary remedies to be limited solely to those mentioned here. For this reason, in order for all individuals and community members to benefit from equal rights to higher education, it is necessary to inform and direct the individuals about higher education and to remove obstacles in front of them starting from primary education [17]. In particular, for Turkey, it is still important to focus on and investigate the inequalities experienced in the education levels experienced before higher education.
\nIndustry 4.0 has both expanded the possibilities of digital transformation and increased its importance to manufacturing, with an emphasis on globalization, international trade, and foreign direct investments. Industry 4.0 combines and connects digital and physical technologies including artificial intelligence, the Internet of Things, additive manufacturing, robotics, cloud computing, and others to drive more flexible, responsive, and interconnected enterprises capable of making more informed decisions [1]. The infusion of digital technologies in the value chain processes of research and development, design, production, marketing, distribution, and customer services will drive efficiency in production, thereby increasing the ambits of international trade.
Developed in Germany, currently, Industry 4.0 has become the most discussed issue in the industrial arena in the world. Both managers and policymakers from developed, emerging, and developing countries are debating this issue about how they can participate in this fourth industrial revolution as well as save them from the fallout of this advancement. The issue is still evolving, and experts from all spheres of industry and markets are debating on it. The objective of this chapter is to participate in this debate and explore how Industry 4.0 will evolve in the coming years and how it might affect international trade and the global value chain. We will take an in-depth look into what exactly is Industry 4.0 in our globalized context, what it brings to the table when it comes to international businesses and how international organizations can benefit from Industry 4.0 in their globalization strategies? As a matter of fact, Industry 4.0 outperforms the previous industrial revolutions we have gone through during the past centuries. The fourth industrial revolution is the result of the combination between the real and the virtual world, in which deep learning encourages and challenges human capacities and frontiers, particularly, with the increase of cyber-physical systems. Indeed, the new industrial revolution which develops deep learning is not limited to the use of automation systems based on machine learning, but autonomous ones that do not systematically depend on human beings and which can learn and act by themselves. Industry 4.0 refers to many concepts such as artificial intelligence, smart technologies, smart factories, smart automation, or smart management like the implementation of enterprise resource planning and automation of robotized processes. The global business environment has already started to enhance efficiency with futuristic and high-value-added technologies, from which we are not able to see the frontier clearly for now.
Firstly, we will undertake a brief literature review to explain how we structured our work. We will then be having a great detailed analysis of Industry 4.0 and its main components and how it is changing the way corporations do business in an increasingly connected world. Parallelly, we will explore the opportunities that the fourth industrial revolution brings as well as the challenges which emerged from this new revolution in order to counterbalance and give a realistic view of the latter. Finally, we will illustrate the major strategies that can enable the organization to avail opportunities emanated from Industry 4.0.
Industry 4.0 contributes to the virtualization of a physical production environment that facilitates connectivity and interaction between the machines as well as man and machines in real-time. The automation and connectivity as well as machine learning facilitate the inter-connectivity and improve the production process and bring several benefits to the organization. Some of them are presented in the following sections.
Industry 4.0 is a generator of efficiency. Indeed, the great use of technologies within the different steps in the supply chain helps with optimizing the latter. It is, therefore, cost-effective, time-effective and it globally enhances productivity as well as flexibility and quality of outputs, which also raises the overall reliability of the firm and so the value of the company and its competitiveness. Industry 4.0 is not only about using high technology machines to produce more rapidly. There is indeed much more to that. Industry 4.0 can contribute to streamlining the value chain thanks to its transformation of every aspect of the production process from the logistics, passing through the managerial issues, to the networks, and more generally, the whole structure of firms in the network.
First of all, firms can benefit from
Data is the basis of all the improvements around artificial intelligence and the comprehension of the opportunities that can be taken in the organizations. Used correctly, data and communication tools can help firms to better respond to customers’ demands and allow a better accuracy of forecasts too. Data within the industry can help to see what should be improved in terms of production methods to gain efficiency. In that sense, they can also more easily identify bottleneck products which would result in better opportunity costs. Firms can also benefit from greater management and control thanks to adapted software within the firm. Data can be used to analyze production time and costs, as well as comparisons of portfolios of suppliers and materials to get the best of their interest. It allows a rapid reaction to changes and errors. It also allows a quick adaptation when it comes to stock levels, wherever it is from the production or the purchasing teams’ perspectives. Finally, data is the base of artificial intelligence. Thanks to machine learning, data is used to learn from mistakes and successes, which is crucial to be exponentially improving.
Thanks to data, programs are elaborated to improve the business networks such as suppliers with industries or with clients, or from clients to employees when they make a requirement for a change in the process of making an order. The communication is smoother, quicker, and easier to take action. Technologies also allow better safety of work conditions. The efficiency of new technologies allows companies to be more sustainable thanks to smart production facilities, which allows a better allocation of resources and vertical networking of smart production systems. The vertical networking of smart production systems can be defined as
The most blatant of the effects of efficiency in this modern revolution is customer satisfaction. Indeed, thanks to the advanced technologies, customers demand is well –
Customization is an important issue in the global manufacturing industry, and its relevance is expected to even increase in the future. Customers want to customize the design of their products and by influencing the development and production processes at an early or even late stage. This tendency creates the need for manufacturing companies to move from the objective of better products for their customers to the objective of an individualized understanding of customer needs and specialized, industry-specific solutions [5]. That is to say, a major shift from an economy of scale to an economy of customization regardless of the location of production sites in the global value chain.
This ongoing change of customers’ needs results in more and more system complexity in system design as well as in assembly. Furthermore, commissioning can only be partially compensated by manufacturers’ standardization and modularization efforts. Nevertheless,
Assembly line production systems will also be affected by an increase in flexibility in production. Bortolini et al. [8] state that products produced in assembly lines will not only be able to be personalized but that late customization (i.e., after the order has been placed) will also be possible because real-time information on the status of the production process will be available. This means that customers will not only be involved in the definition and design of the product and its specifications, as is the case with mass customization products but will also be launched once in a late customization mode [9].
In contrast, mass-customized production facilities typically produce large volumes of products that share a common core but may be customized to a certain degree [9], creating production process sections with repetitive larger lots (e.g., automotive press shop) and sections of high product variance (e.g., final automotive assembly). The customers of mass-customized production factories typically customize their products based on a predefined set of configuration options, which can be integrated into a common modular architecture. Mass-customized production type factories are typical in the automotive industry, automotive Tier-1 suppliers, and, to some extent, in the truck, bus, agricultural, and construction equipment sectors. Industrial equipment manufacturers – where factories simultaneously have large production volumes and accommodate an ever-increasing number of variants – run mass- customized production type factories as well.
Therefore, the strategy of providing differentiated products leads to a paradigm change in manufacturing planning, posing new challenges for industrial activities. To satisfy the new kind of markets, industries had to adopt agile models, exploiting the competitive advantages of each organization [10]. These manufacturing models intend to face the uncertainty of the market by increasing the response capability of the organization in order to satisfy the customers with similar costs to mass-production industries [11]. Handling the production of large amounts of customized products presents a tough challenge since product differentiation hampers scale economies.
However, managing the production of personalized or customized goods will be quite demanding, given their different requirements. Finally, when late customization of the customer is possible to be accepted and when it is not, it depends on the production sequence in execution, and when it is possible to apply to re-sequence to incorporate the late customizations. Moreover, the advantages of late customization processes can be achieved only if the system is autonomous and can keep running the fabrication process. The customer needs real-time information about the evolution of the production of its personalized product [12]. And, as Kietzmann et al. [13] comment in the context of additive manufacturing,
Before Industry 4.0, companies used traditional data sources such as production records, internal accounts, and market research reports with a limited range for their decision-making process. The way of data sourcing is changing. Data is more and more generated from sources like sensor-generated data from smart products and data from search engines and social media sites. This technological shift offers multinational compagnies (MNC) the opportunity to access new worldwide business-relevant information. Additionally, technical progression regarding computing power and data storage costs is taking place. This results in the development of big data analytics [14, 15, 16].
To understand the innovational power of big data analytics, it is important to understand the changed concept about time in comparison to data analytics before Industry 4.0. Big data analytics is looking into the future and tries to generate existing and new data sources. The traditional role of information technology has been more backward-looking and concerned with monitoring processes and notifying management of anomalies. Firms that have adopted big data analytics report improvements in productivity and financial performance. For example, analysis of big data can enable managers to identify defects, faults, and shortcomings in the production process at an early stage, optimize automation processes and carry out trend analyses, use resources more efficiently and carry out predictive maintenance [17].
The potential implications of big data analytics for international business are several. In particular, firms will be able to monitor emerging trends and opportunities in overseas markets without the need to make substantial resource commitments in those local marketing affiliates, and they will be able to optimize more effectively their supply, production, and distribution activities around the world [18]. But there are two major drawbacks. The first is that the availability of good-quality big data may well be a source of value for firms, but successful firms will require a range of technical and governance capabilities to analyze and operationalize that data so as to realize the potential benefits [19, 20]. The second is that individuals’ privacy will be under threat from widespread big data applications. Like Facebook knows what we like, Google knows what we browse, and Twitter knows what is on our mind [21].
New data protection laws and/or stronger industry self-regulation will need to be formulated to safeguard the privacy of individuals and companies, and to put limits on what data can be accessed, stored, and transmitted both nationally and across borders [22]; Rose et al. [23]. It has to be discussed who will have legal title over what, and who will bear legal responsibility for, products that involve consumer-generated intellectual property [24] and how will these issues be handled in cross-border settings? Some form of (transnational) governance regime will be necessary to regulate this dilemma between the benefits of big data analytics described earlier and data privacy. Finally, this may influence or even determine the abilities of firms to maximize the commercial potential of big data analytics [25, 26].
The optimization of production and logistics processes allowed by Industry 4.0 could have a major impact on the management of the environmental crisis. Indeed, the processes of Industry 4.0 that allow energy savings and waste reductions to cut costs for firms would be equally beneficial for the preservation of natural resources and biodiversity. The Sustainable Development Goals established by the United Nations include the improvement of energy efficiency and better management of waste. Therefore, the improvements brought by Industry 4.0 would be in adequation with government environmental policies and regulations, which will most probably become much stricter in the coming decades.
Industry 4.0 allows improved production management thanks to the production monitoring capabilities of Industry 4.0. Constant monitoring of production efficiency and intelligent quality control offer great opportunities in terms of production efficiency, waste reduction, and improved reliability. Consequently, firms would have a better energy efficiency [27]. Industry 4.0 allows firms to make informed decisions based on the data-mining possibilities brought by sensors and AI. Relevant statistics on production efficiency, product life cycle, and energy consumption will be available to the firms [28]. Industry 4.0 will also connect the consumer with its energy consumption thanks to the sharing of statistics made possible by smart data communication technologies [29]. Energy consumers will be informed on their consumption, and this will promote self-responsibilities.
However, these improvements could easily be counterbalanced by the fact that Industry 4.0 requires the collection and storing of massive quantities of data in data centers, which significantly contribute to global warming. But this is not a fatality, and firms should not be stopped by this challenge, as innovative solutions allow the heat produced by data centers to be reused as a heating source. This strategy is especially used in Nordic countries such as Finland or Sweden.
Research on Industry 4.0 is numerous and rapidly evolving. Many types of research have addressed the evolution of the Industry 4.0 (I4.0) phenomenon and its contribution to international business activities. Especially the major drivers of I4.0 that underlines its involvement to enhance current business practices by streamlining both the production and supply chain networks [30, 31]. Those developments in Industry 4.0 have huge implications on the way the current business activities both at home as well as across the globe (i.e., international trade) are being conducted. Mamad [2] has addressed how Industry 4.0 works and has made a broad illustration of the subject in detail through an exhaustive literature review. Deloitte [3] provided an overview of the beneficial application of Industry 4.0 to enhance organizational processes. McKinsey’s [6] study focused on customization and explained how Industry 4.0 has reshaped the manufacturing industry to fit customer demand and how companies can reap profit from these upcoming innovations by showing application opportunities. UNIDO [32] report has presented an impact analysis and showed how Industry 4.0 could contribute to environmental sustainability. Jayashree et al. [33] showed how Industry 4.0 could contribute to developing dynamic capabilities and realizing triple bottom line (TBL) sustainability. Bibby et al. [34] give some tools to assess the current level of Industry 4.0 maturity of businesses that want to transition to I4.0 and better approach the issue. Dhanpat [35] reminds us of the underlying dimensions of I4.0 as a growing need for learning capacities of smart technologies to cope with the new era of cyber-physical systems. Ahmadi et al. [36] addressed the main architecture models of value-chain structure in Industry 4.0.
Industry 4.0 brings both enormous opportunities and challenges for the industry and international trade. It helps not only to modernize the production process and self-initiated execution but also allow the managers to undertake the management of the production process across the globe by creating a flexible global supply chain.
The fourth industrialization is changing the way we perform different kinds of business activities by drawing its main components and their contribution to the business environment. Industry 4.0 is the implementation of cyber-physical systems for creating smart factories by using the IoT, big data, cloud computing, artificial intelligence (AI), and communication technologies for information communication in real-time between the man-machine and machine to machine communication which is redefining the global value chain.
According to Horvàth et al. [37], there are five key drivers of Industry 4.0: Digitalization, optimization, and customization of the production, automation, and adaptation, human and machines interactions, and collaborations, high value-added offers, and automatic exchanges of data and communication. The fourth industrialization has contributed to critical transformation to the international business environment in the different stages of an organization such as human resources, financial systems, management, organizational structure, or production processes.
Those key drivers are highly illustrated by the implementation of cyber-physical systems, the internet of things, smart factories, smart technologies, cloud computing, and big data. The latest architecture of industrialization pursues new objectives and faces completely different challenges that increase in a global perspective. Industry 4.0 offers an opportunity of restructuring declining manufacturing industry in the high-cost-country (HCC) and permit to maintain a strong industrial base in developed countries [38]. It could represent a great opportunity in the context of declining manufacturing in the developed markets. Industry 4.0 answers three key challenges: better competitiveness, flexibility, and agility by facing global offer end demand fluctuation and the regionalization of production [38]. To sum up, Industry 4.0 can be understood as multiple solutions built to change the international industrial sector to gain stronger competitive positions, market shares, especially within a risky business environment. This ambition should be realized by using smart technologies and factories that ensure efficient response to the variation of the global market by improving competitiveness and agile management, which will conduct the changes implied by Industry 4.0.
Central to the fourth industrial revolution is an interconnected network. The internet enables many small firms to participate in global trade, thus, leading to more inclusion. It makes it possible for more products to be exported to more markets, often by newer and younger firms. A 10-percent increase in internet use in the exporting country is found to increase the number of products traded between two countries by 0.4 percent. A similar increase in internet use of a country pair increases the average bilateral trade value per product by 0.6 percent [39]. The transformation implied by the fourth industrialization, Industry 4.0, might lead to significant changes in existing business models allowing new ways to create value. These changes are expected to result in the transformation of traditional value chains. Industry 4.0 affects three elements of manufacturing small and medium enterprises (SMEs): value creation, value capture, and value offer [37].
The 4th industrialization will completely change global value chains by transforming its practices and objectives. The purpose is not limited to monetary rewards but includes new trends such as the willingness to gain efficiency, to create and sustain global competitive advantages, finding new ways of producing, generating innovations, stimulating automation and learning, or even increasing customer implications in the production processes.
Several opportunities generated by Industry 4.0 are transforming the current business levels and activities through its drivers. Multiple business models are flourishing in the Industry 4.0 era. One of the fast-emerging models of them is the
Internet of things (IoT) is retained as a pillar of I4.0. This type of technology provides access to the internet by using deep learning technologies. This equipment transforms machines into smart objects that could, for instance, detect wear, control the performance of the production process, plan the capacity or even manage stocks in real-time. Cloud computing allows interconnection between computers and the internet. It can solve many issues such as Big Data storage as well as the costs and capacities linked to this storage.
Cyber-physical systems (CPS) are mechanisms that allow Humans, software, and machines to interact. It implies an aggregate level of networking. The main purposes of this technique are, by creating such virtual interconnection, to exchange key information to make better strategic decisions. It establishes strong links between production processes, machines, and the virtual world, which work and communicate thanks to computation and the internet in real-time cooperatively. The machines and physical systems will be synchronized to software, and it will allow the control and assessment in real-time production efficiency, adjusting it and making the right strategic decisions easily. Also, CPS enhances the integration of autonomous machines and the collaboration between humans and cyber work.
The result of the use of the different drivers (IoT, CPS, Internet of Service, ERP) will lead to the creation of smart factories, which brings all the smart tools and models together in its production model. This integrated system will facilitate the globalization of production and expansion of global supply chain. It is true that some of manufacturing activities might be re-shored but at the same time, the new smart technology will allow firms to reconfigure their production network overlooking the national boundaries and distance. That is the reason why it is still in the pre-paradigmatic stage of Industry 4.0. implications it is a continuous process that conducts the transformation of our current or traditional methodologies to do business and conceive industrial purposes and processes. As a result, the production model of smart factories becomes cost-effective and flexible to market changes and sustainable, which would reflect the highest level of effectiveness feasible to achieve. This newfound technological prowess will modify drivers of global production networks (GPN), reduce the importance of physical distance as well as re-configure the global value chain (GVC). The new global division of labor (NGDL) is likely to emerge and re-distribute the manufacturing activities integrating different hubs from both the developed, emerging, and developing markets.
There are no doubts about the enormous challenges that Industry 4.0 will bring to the current practice of production, consumption, and global value chain (GVC). Firms and policymakers need to take into consideration adequate strategies to better implement the Industry 4.0 systems, re-organize business activities by taking into consideration of new context and take other caution for the long-term growth of the fourth industrial revolution and reap profit from it. We will define and analyze in this section the challenges raised by Industry 4.0, starting with implementation challenges, then the challenges surrounding the management of Human resources, then the risks to data security, then the Big Data challenges, and finally, the challenges concerning the environment.
As we established earlier, the transition to Industry 4.0 brings countless opportunities for businesses to increase their efficiency and development. However, there are many barriers to the implementation of Industry 4.0, the most important lackings are the shortages of skill-sets that are required in the Industry 4.0 phenomenon. There is also a lack of experience and hindsight on the transition, the necessity to remodel the entire organization, and the coordination of data resources. Added to these challenges are the inequality between SMEs and MNCs in terms of resources, focus, and strategies in the transition to Industry 4.0. This section will present the three main difficulties faced by firms integrating Industry 4.0.
The lack of experience is certainly one of the biggest factors that hold back the businesses from transitioning to Industry 4.0. era. Indeed, the transformation of the companies is very costly, and no clear business case is available as a reference for companies. It is very difficult to justify such investments when there is no perspective, no pattern to follow, and no successful case to reproduce. Therefore, most frequently, companies will either fail in their transition (60% rate of failure) or simply lack the necessary courage to follow through the process of radically changing their organization and investing as much time and resources.
To tackle this challenge effectively, some interesting research in the field has started to emerge, building the first tools to approach the transition. According to Bibby et al. [34], firms should begin by assessing the current level of Industry 4.0 maturity in their specific context or supply network. This analysis will help them determine their strengths and weaknesses and focus their improvement on the right area. Few academic research has been done so far in this area, and many research are done by consulting firms. As an example, in order to assess the industry maturity level of firms, two Industry 4.0 assessment models have been developed in 2016 by consulting firms, IMPULS management consulting GmbH (IMPULS) and PWC. While the PWC model helps companies self-assess their level of maturity based on various criteria, the IMPULS model is focused on delivering improvement advice based on the company’s preparation. More of these models are currently developing, showing that the challenge of the lack of experience will likely be overcome with time as Industry 4.0 spreads across the manufacturing world.
The transition to Industry 4.0 from a traditional organization requires the restructuring of the entire organization, as tasks are automated and decision-making processes are programmed. Every firm that will adopt Industry 4.0 system. We will have to create new business models and define a new strategy. Indeed, this transition requires rethinking the whole organization and processes, interconnecting departments, buying new equipment or modernizing the existing one, re-assigning roles to employees, recruiting new operators, and many other disruptions of their current model. These major changes have a great cost for any business on many levels: financially, of course, but also in terms of time. Therefore, firms have to be especially careful when investing in these transitions in order to not fail its implementation of Industry 4.0.
Another challenge of the implementation of Industry 4.0 is how to connect all data efficiently. Industry 4.0 requires the cooperation of all organizational units, from manufacturing, R&D, IT, to sales and finance departments. Sometimes the walls separating these departments are very hard to break, adding to the difficulty of the transition. But the coordination of functions is only part of the issue: Industry 4.0 requires the management of the large quantities of data generated by diverse sources in the company. For example, production data will have to be processed and coordinated along with data from customer information systems. Data Integration is, therefore, a very difficult task, and the firms need to have the necessary talent from data scientists that will be able to process and model this data.
More than 98% of firms in the developed markets are considered as SMEs, and they are increasingly participating in the global value chains and global trades of goods, services, and components. Introducing the new I4.0 paradigm may have varying levels of difficulty depending on the size and available resources of the targeted firms. Starting conditions between Small and Medium Enterprises (SMEs) and larger firms are obviously very different and bring different challenges. According to Matt et al. [43], SMEs need specific strategies to properly implement I4.0 to their business model.
Large companies will usually follow the higher maturity level in the technological domain faster and more easily than SMEs because of the resources. Indeed, they have more money, expertise, and time to invest in this project. As a consequence, I4.0 is spreading more quickly across large companies which are investing and working intensively on introducing and enabling the necessary technologies. SMEs, however, are lagging behind because they lack the financial and human resources to research into the risks and potential of implementing I4.0. These difficulties further enlarge the gap between SMEs and large multinational companies. However, SMEs have an advantage over large companies, which have a much more complex organizational structure and production processes. Therefore, it is much easier to implement the necessary changes to the organization and culture of SMEs.
According to the study made by Glass et al. [44], across 176 SMEs and 71 large enterprises, numerous barriers to Industry 4.0 must be underlined across business processes and models. The most important challenges include, of course, the multiple issues which arise from Industry 4.0 strategy modeling and the growing need for highly skilled workers with specific know-how, particularly oriented in high technologies, smart engineering, automation, and digitalization competencies and expertise, etc.
We can easily understand that, beyond such technical and future-oriented subjects applying to industries, which is already developed in multiple kinds of business corporations, human resources remain a major challenge for the spread of Industry 4.0 concepts, methodologies, models, and tools. For instance, Mubarak and Petraite [45] have raised a fundamental HR component of Industry 4.0 implementation: The concept of digital trust. Digital trust is situated between trust and Industry 4.0 implementation and implies HR issues. We can identify major human resources issues related to Industry 4.0 as the followings:
When digital trust refers to a new working environment where technology and Humans interact for the welfare of a company and to answer the stakeholder’s needs, a danger of this approach would be the growth of technocentric businesses. In fact, in this model, the stakeholders will give more confidence to technologies, artificial intelligence, and automation to run their business activities and corporations rather than human beings. Indeed, The Deloitte reports questioned the preparedness of HR in an era of Industry 4.0 and the global value chain. Among the 32% of firms that are ready to face technological challenges, only 12% are ready to face the challenges emanating from the Industry 4.0 ecosystem [46]. This statistic illustrates the new trends for companies to focus on efficiency with the highest technological implementation rather than hiring people and maintaining their position through retention policies.
The information systems of human resources (ISHR) illustrate the Industry 4.0 impact upon Human resource function. Indeed, the ISHR technologies permit to automate, standardize with the intervention of smart technologies, activities that belong to HR functions as the following ones: Administrative procedures, training, payrolls management, recruitments, talents management, or even career development of employees within a company [47, 48]. The different systems like automation of robotic processes (ARP) and enterprise resource planning (ERP) were conduct to rethink the HR function. Those different tendencies push HR workers to acquire new competencies geared towards smart technologies and which are transforming their workstation, and which are implying news risks. On the one hand, we can identify the complexity of adaptation to the rapid change of HR function but also the risks linked to the security of information systems and the possibility to lose sensitive data to the benefit of the competition. As a reminder, ISHR systems such as the one proposed by the SAP software can contain confidential data such as the wages, the positions, the personal data of each employee, their curriculum vitae, the annual reports, information posted on the different job board and the main partners of the company, etc.
The fourth revolution required a highly-skilled workforce to be implemented, developed, used and maintained. As a result, a wide range of industries needs a certain level of cooperation between machines and workers. If Industry 4.0 implies this tendency, it also underlines the growing trend of Google, Apple, Facebook, Amazon, Microsoft (GAFAM) to conquer traditional industries in which they have the necessary knowledge and capacities to become undisputable competitors in multiple fields [49]. As an example, we can remember the creation of the Google autonomous car, the collaboration between the Volkswagen group with Amazon web services to collect and analyze its industrial data and becoming a major global leader of the automotive industry, and even the collaboration between Apple and General Electric (GE) to create new applications for the internet of things (IoT) platforms that benefit to GE industries purposes thanks to IOS (exploitation system owned by Apple) opportunities. Industry 4.0 increases competition, in traditional industries and markets (but not only), which seems to be overwhelmed regarding the fast spread of the fourth industrial revolution. To overcome these challenges, companies must recruit high skilled workers, implementing continuous reskilling, learning, and training programs in their HR policies [44]. Besides, one of the major HR issues is constituted by the launch of retention practices which will reduce the diffusion of confidential business information and enhance efficiency and profitability by staying competitive at the same time. We can understand that the rise of high skilled workers’ demand would create a danger if it is not associated with HR policies to enhance workforce abilities to work in a new smart and autonomous workplace.
One major issue to face urgently for HR function is the resistance to change. According to Deloitte [50] report, 17% of their interviewees are ready to manage working environments composed of people, robots, and AI interacting together when 60–70% will fail because they do not manage the adaptation to change properly. Also, Dhanpat et al. [35] confirmed this problem. They have shown that some employees can be resistant to change by being afraid of losing their jobs and being replaced by machines. Bonekamp et al. [51] also agree on the fact that the introduction of Industry 4.0 led to the suppression of standardized tasks by smart and autonomous systems. As a consequence, strong pressure is put on HR managers who require highly skilled people, to train employees and manage to dismiss workers for whom their tasks will be replaced by smart technologies to gain efficiency and competitiveness in the global market. In 2016, The World Economic Forum (WEF) already raised awareness by making an announcement before the opening of the Davos forum: around 5 million jobs in 5 years will be suppressed within 5 years in the main global economies [52]. It is necessary for the HR function globally to answer and react to the exponential expectations of the fourth industrial revolution by taking into account its effect on the global workforce demand and its impact on the global economy and competitiveness.
The fourth industrialization reveals new challenges in business activities such as the management of Bigdata and cybersecurity. Multiple obstacles to Industry 4.0 remain redundant: The constraints are numerous because the digitization of the industry poses formidable problems of standardization and cybersecurity [52].
Indeed, through their researches, one of the major challenges implied by this concept in the working environment is the deployment of Big Data, which creates a growing need to provide a legal framework for the protection of personal data and private life. Among the different cyber issues reported in Industry 4.0, the Deloitte report [50] identifies the top 10 cyber threats and their major data protection concerns.
Indeed, if legal restrictions increase to manage big data challenges, the different issues persist. In terms of an international legal framework, the ISO norm ISO/IEC 27001 defines the data security management for sensitive subjects such as financial, intellectual proprietary, employees, or even data entrusted to another company in the context of business activities. This norm is also called “Management systems of Information security” [53]. In addition, the European Union has implemented the General Data Protection Regulation (GDPR) to mitigate different kinds of challenges affiliated with the management of Big Data. GDPR regulations refer to “imposing a legal framework on the processing of personal data” [54].
However, despite the willingness to build an international legal framework to reduce risk related to Big data cybersecurity, there are still a long-ways to go for a proper framework of Industry 4.0. For instance, Deloitte report has shown that one out of four firms is not developing, implementing, or documenting the industrial cybersecurity (ICS) specific policies and procedures, and more than 33% of manufacturers have not performed any cyber risk assessments specifically focused on the ICS operating on their shop floors, resulting in a potentially significant risk to their operations [55].
In terms of internal management, other issues can arise when a company starts using big data analytics in order to grow. The challenges to take into account include the lack of proper understanding of big data, and therefore, proper usage of the latter; data growth issues, or, “what do I do with this much information?” because the collection of such an amount of data must be useful for something. But what, exactly? Another issue is the confusion when selecting a Big Data tool. There is an increasing number of tools available on the market for firms to have reports and data concerning their businesses. However, it is often not very precise and easy when one is not really aware of what is best for them. This last point brings us to another issue which is the lack of professional expertise in the field of Big Data. Indeed, more and more companies are recruiting professionals and experts in the field of data, such as data scientists, engineers, and analysts. These professions are rare, and as the demand and supply rule confirms, it is quite costly for a firm to recruit, though it is a must when expecting to grow, especially in our current globalized market.
Concerning the international strategies of Industry 4.0 applied to firms, we can find key references in terms of Smart Manufacturing architectures: Reference Architecture Model or Industry 4.0 (RAMI 4.0), Smart manufacturing ecosystem (SME), Intelligent manufacturing system architecture (IMSA). In Smart manufacturing, the architecture corresponds to the designing of the arrangement and connectivity of the organizational structure. The Smart manufacturing ecosystem (SME) provides a standard overview of Smart Manufacturing Systems (SMS). It has three dimensions: product, production, and business. It allows information circulation, in order to follow the production of products through its entire life-cycle. It focuses on the entire value chain and the interaction between the three dimensions.
According to a BGC report on Industry 4.0, related to the German manufacturing industry, Industry 4.0 will be used by an increasing number of firms and generate significant productivity gains of this industry sector (90 to 150 billion EUR). The productivity will improve by 15 to 25%. If material costs are considered, productivity upgrades of 5 to 8% are realistic. Individual effect size depends on the specific manufacturing industry. E.g. industrial component manufacturers will see the largest productivity gains (20 to 30%), while automotive manufacturers may assume 10 to 20% [56]. Furthermore, Industry 4.0 will impact the revenue growth of the German industry. Need from manufacturers for improved devices and new data applications, as well as customer demand for a greater range of increasingly customized products, will provide further revenue growth of around 30 billion euros per year, equivalent to around 1% of German GDP.
The BCG study predicts that the growth and productivity increase described above will also positively impact the employment growth of 6% over the next decade. The need for mechanical engineering workers could increase even more – by up to 10 percent over the same period. In the next few years, the automation trend will replace some low-skilled workers in repetitive and monotonous tasks. However, the increasing use of big data analytics will increase the demand for workers with ICT skills. This shift of needed skills transformation is one of the most important challenges of future growth and innovation. Making the mandatory steps to be economically successful in the world of Industry 4.0 will cost manufacturers about 1 to 1.5 percent of their sales in absolute value over the next decade. Finally, it can be concluded that Industry 4.0 will transform the global value chain, labor market, and logistics.
Global trades are going through lots of volatility from geopolitical instability and natural disasters. The current situation requires businesses to develop their strategic goals for growth, risk management, and global supply chain for the short term, mid-term as well as long term. Manufacturing firms need to develop multi-pronged and multi-disciplinary approaches to address challenges facing current and future supply chain disruptions. The use of advanced technologies like artificial intelligence (AI) and Business analytics can be helpful to analyze large-scale data and keep track of supply chain movements in real-time and develop the ability to re-configure the Supply chain on short notice. A firm’s ability to succeed in global markets will depend on the capacity of the industry to adapt to a rapidly changing business landscape.
To sum up, Industry 4.0 seems to have reached heights when it comes to the organization of enterprises at a global level. We described how international organizations could benefit from Industry 4.0 doing international business. We explained how the components of Industry 4.0 had enhanced many aspects of SMEs and MNCs, by analyzing the evolution of the different phases of the historical context to come to such a strong, advanced stage. We, therefore, defined the industry and its key components to explain its contribution to the organization.
Managers need to develop the ability to identify the opportunities and the strengths brought up by this industrial revolution. We took a look into its efficiency features, and opportunities to satisfy the varied demands thanks to capabilities of customization, and the power of the use of Big Data Analytics, as well as the great impact that this evolution has on the environment. Nevertheless, all these benefits do not come without some challenges. Indeed, Industry 4.0 has full of potentialities of innovation and quite complex transformations to simplify and adapt organizations, especially in terms of human resources because robotics and automation will have huge a repercussion on the social aspect. Most especially, developing and emerging countries that participate in the global value chain by offering advantageous manufacturing production locations will face stiff competition between Industry 4.0 based technologies with those of cheap and abundant labor force in those countries. There is no option other than up-grading the workforce and integrating into the 4.0 era to face these new challenges in the era of Industry 4.0. Finally, as valuable as Big Data can be for the industry, we have found out that it is still a domain that requires particular attention since its use remains quite laborious.
Nonetheless, this modern revolutionary phase is not the last of its category. In fact, the very recent rise of Industry 5.0, a solution provider for people and the planet has flipped the script. Indeed, the new revolution of Industry 5.0 puts an emphasis on the well-being of the workers and captures all the added-value components of Industry 4.0 with the aim of prosperity in the new industry as an ambition for a better future.
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Vellecco",authors:[{id:"118072",title:"Dr.",name:"Immacolata",middleName:null,surname:"Vellecco",slug:"immacolata-vellecco",fullName:"Immacolata Vellecco"},{id:"118597",title:"Dr.",name:"Giulio",middleName:null,surname:"Maggiore",slug:"giulio-maggiore",fullName:"Giulio Maggiore"}]},{id:"35715",title:"The Role and Importance of Cultural Tourism in Modern Tourism Industry",slug:"the-role-and-importance-of-cultural-tourism-in-modern-tourism-industry",totalDownloads:41023,totalCrossrefCites:29,totalDimensionsCites:56,abstract:null,book:{id:"2298",slug:"strategies-for-tourism-industry-micro-and-macro-perspectives",title:"Strategies for Tourism Industry",fullTitle:"Strategies for Tourism Industry - Micro and Macro Perspectives"},signatures:"Janos Csapo",authors:[{id:"118766",title:"Dr.",name:"János",middleName:null,surname:"Csapó",slug:"janos-csapo",fullName:"János Csapó"}]},{id:"71088",title:"Public Sector Organizational Culture: Experience from Frontline Bureaucracies",slug:"public-sector-organizational-culture-experience-from-frontline-bureaucracies",totalDownloads:864,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This chapter discusses the practice of organizational culture by the frontline bureaucrats in Bangladesh. Culture scholars argue that organizational culture—commonly defined as the beliefs, values, attitudes, and practices of the members of an organization—is a powerful force in determining the health and well-being of an organization. Scholars also suggest the existence of different dimensions of organizational culture. Although they do not agree in naming these dimensions, commonalities are found in their understanding. How organizational culture is practiced by the frontline bureaucrats in Bangladesh has not been studied much. A study was designed to know how the frontline public bureaucrats practice organizational culture and how they differ in their practices along their service lines. Four dimensions of organizational culture—power distance, uncertainty avoidance tendency, participation, and team orientation—were considered. The chosen culture dimensions impact the overall management of any public sector organization. Three hundred and twenty-six frontline public bureaucrats were studied using a survey questionnaire. Both descriptive and inferential statistics have been used for analyzing the collected data. Findings from independent samples t-tests revealed that the frontline bureaucrats significantly differ along their service lines in practicing the culture dimensions.",book:{id:"7807",slug:"a-closer-look-at-organizational-culture-in-action",title:"A Closer Look at Organizational Culture in Action",fullTitle:"A Closer Look at Organizational Culture in Action"},signatures:"Md. Morshed Alom",authors:[{id:"314259",title:"Ph.D.",name:"Md. Morshed",middleName:null,surname:"Alom",slug:"md.-morshed-alom",fullName:"Md. Morshed Alom"}]},{id:"72449",title:"Communication and Organizational Culture",slug:"communication-and-organizational-culture",totalDownloads:748,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"When people in an organization understand themselves and their context of interaction from very different perspectives, there is an increased risk of poor organizational dialogue. The reason is not only that individuals’ social interpretations of others are influenced by their idiosyncratic perspectives. In interactions involving a significant diversity of individual perspectives, there is also a risk that communicators form radically different interpretations of goals and processes in the organization. It is therefore of crucial importance that people have a sufficiently similar understanding of action-guiding information, communicative acts and the workplace itself. The chapter focuses on the importance of creating shared organizational culture on the basis of four communication conditions from social interaction theory. (1) In communicative processes, senders need to secure the attention of audiences. (2) Senders and audiences need to have a sufficiently similar understanding of the language that is used. (3) Senders and audiences need to interpret communicative acts in a sufficiently similar way. (4) The attitudes and values that audiences ascribe to senders must correspond to the values and attitudes that senders actually have. After having clarified these conditions, the chapter applies them to analyse fundamental organizational challenges. The final part of the chapter argues that the conditions can, typically on management levels, constitute conceptual tools for creating unifying communicative cultures. Furthermore, using the conditions (1)–(4) actively as a means for securing communication across a diversity of individual perspectives can contribute to reaching organizational goals, no matter how they are defined.",book:{id:"7807",slug:"a-closer-look-at-organizational-culture-in-action",title:"A Closer Look at Organizational Culture in Action",fullTitle:"A Closer Look at Organizational Culture in Action"},signatures:"Halvor Nordby",authors:[{id:"212169",title:"Prof.",name:"Halvor",middleName:null,surname:"Nordby",slug:"halvor-nordby",fullName:"Halvor Nordby"}]},{id:"72534",title:"Effects of Information Technologies on Organizational Culture: A Discussion Based on the Key Role of Organizational Structure",slug:"effects-of-information-technologies-on-organizational-culture-a-discussion-based-on-the-key-role-of-",totalDownloads:1063,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"This chapter discusses the influences of information technologies on cultural features of organizations with an emphasis on the concept of “organizational structure” because research shows that organizational culture and organizational structure are in a very close relationship. In this regard, it argues that information technologies can have direct and indirect effects on organizational cultures based on the information technologies’ influences on organizational structures and the processes, activities, and human relations within these structures. Underlining different and controversial approaches and findings in the literature, this study makes some deductions by referring to important features of information technologies and organizational culture. 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Radiotherapy and Nuclear Medicine Technology has always been my aspiration and my life. As years passed I accumulated a tremendous amount of skills and knowledge in Radiotherapy and Nuclear Medicine, Conventional Radiology, Radiation Protection, Bioinformatics Technology, PACS, Image processing, clinically and lecturing that will enable me to provide a valuable service to the community as a Researcher and Consultant in this field. My method of translating this into day to day in clinical practice is non-exhaustible and my habit of exchanging knowledge and expertise with others in those fields is the code and secret of success.",institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"313277",title:"Dr.",name:"Bartłomiej",middleName:null,surname:"Płaczek",slug:"bartlomiej-placzek",fullName:"Bartłomiej Płaczek",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/313277/images/system/313277.jpg",biography:"Bartłomiej Płaczek, MSc (2002), Ph.D. (2005), Habilitation (2016), is a professor at the University of Silesia, Institute of Computer Science, Poland, and an expert from the National Centre for Research and Development. His research interests include sensor networks, smart sensors, intelligent systems, and image processing with applications in healthcare and medicine. He is the author or co-author of more than seventy papers in peer-reviewed journals and conferences as well as the co-author of several books. He serves as a reviewer for many scientific journals, international conferences, and research foundations. Since 2010, Dr. Placzek has been a reviewer of grants and projects (including EU projects) in the field of information technologies.",institutionString:"University of Silesia",institution:{name:"University of Silesia",country:{name:"Poland"}}},{id:"35000",title:"Prof.",name:"Ulrich H.P",middleName:"H.P.",surname:"Fischer",slug:"ulrich-h.p-fischer",fullName:"Ulrich H.P Fischer",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/35000/images/3052_n.jpg",biography:"Academic and Professional Background\nUlrich H. P. has Diploma and PhD degrees in Physics from the Free University Berlin, Germany. He has been working on research positions in the Heinrich-Hertz-Institute in Germany. Several international research projects has been performed with European partners from France, Netherlands, Norway and the UK. He is currently Professor of Communications Systems at the Harz University of Applied Sciences, Germany.\n\nPublications and Publishing\nHe has edited one book, a special interest book about ‘Optoelectronic Packaging’ (VDE, Berlin, Germany), and has published over 100 papers and is owner of several international patents for WDM over POF key elements.\n\nKey Research and Consulting Interests\nUlrich’s research activity has always been related to Spectroscopy and Optical Communications Technology. Specific current interests include the validation of complex instruments, and the application of VR technology to the development and testing of measurement systems. He has been reviewer for several publications of the Optical Society of America\\'s including Photonics Technology Letters and Applied Optics.\n\nPersonal Interests\nThese include motor cycling in a very relaxed manner and performing martial arts.",institutionString:null,institution:{name:"Charité",country:{name:"Germany"}}},{id:"341622",title:"Ph.D.",name:"Eduardo",middleName:null,surname:"Rojas Alvarez",slug:"eduardo-rojas-alvarez",fullName:"Eduardo Rojas Alvarez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/341622/images/15892_n.jpg",biography:null,institutionString:null,institution:{name:"University of Cuenca",country:{name:"Ecuador"}}},{id:"215610",title:"Prof.",name:"Muhammad",middleName:null,surname:"Sarfraz",slug:"muhammad-sarfraz",fullName:"Muhammad Sarfraz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/215610/images/system/215610.jpeg",biography:"Muhammad Sarfraz is a professor in the Department of Information Science, Kuwait University, Kuwait. His research interests include optimization, computer graphics, computer vision, image processing, machine learning, pattern recognition, soft computing, data science, and intelligent systems. Prof. Sarfraz has been a keynote/invited speaker at various platforms around the globe. He has advised/supervised more than 110 students for their MSc and Ph.D. theses. He has published more than 400 publications as books, journal articles, and conference papers. He has authored and/or edited around seventy books. Prof. Sarfraz is a member of various professional societies. He is a chair and member of international advisory committees and organizing committees of numerous international conferences. He is also an editor and editor in chief for various international journals.",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"32650",title:"Prof.",name:"Lukas",middleName:"Willem",surname:"Snyman",slug:"lukas-snyman",fullName:"Lukas Snyman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/32650/images/4136_n.jpg",biography:"Lukas Willem Snyman received his basic education at primary and high schools in South Africa, Eastern Cape. He enrolled at today's Nelson Metropolitan University and graduated from this university with a BSc in Physics and Mathematics, B.Sc Honors in Physics, MSc in Semiconductor Physics, and a Ph.D. in Semiconductor Physics in 1987. After his studies, he chose an academic career and devoted his energy to the teaching of physics to first, second, and third-year students. After positions as a lecturer at the University of Port Elizabeth, he accepted a position as Associate Professor at the University of Pretoria, South Africa.\r\n\r\nIn 1992, he motivates the concept of 'television and computer-based education” as means to reach large student numbers with only the best of teaching expertise and publishes an article on the concept in the SA Journal of Higher Education of 1993 (and later in 2003). The University of Pretoria subsequently approved a series of test projects on the concept with outreach to Mamelodi and Eerste Rust in 1993. In 1994, the University established a 'Unit for Telematic Education ' as a support section for multiple faculties at the University of Pretoria. In subsequent years, the concept of 'telematic education” subsequently becomes well established in academic circles in South Africa, grew in popularity, and is adopted by many universities and colleges throughout South Africa as a medium of enhancing education and training, as a method to reaching out to far out communities, and as a means to enhance study from the home environment.\r\n\r\nProfessor Snyman in subsequent years pursued research in semiconductor physics, semiconductor devices, microelectronics, and optoelectronics.\r\n\r\nIn 2000 he joined the TUT as a full professor. Here served for a period as head of the Department of Electronic Engineering. Here he makes contributions to solar energy development, microwave and optoelectronic device development, silicon photonics, as well as contributions to new mobile telecommunication systems and network planning in SA.\r\n\r\nCurrently, he teaches electronics and telecommunications at the TUT to audiences ranging from first-year students to Ph.D. level.\r\n\r\nFor his research in the field of 'Silicon Photonics” since 1990, he has published (as author and co-author) about thirty internationally reviewed articles in scientific journals, contributed to more than forty international conferences, about 25 South African provisional patents (as inventor and co-inventor), 8 PCT international patent applications until now. Of these, two USA patents applications, two European Patents, two Korean patents, and ten SA patents have been granted. A further 4 USA patents, 5 European patents, 3 Korean patents, 3 Chinese patents, and 3 Japanese patents are currently under consideration.\r\n\r\nRecently he has also published an extensive scholarly chapter in an internet open access book on 'Integrating Microphotonic Systems and MOEMS into standard Silicon CMOS Integrated circuitry”.\r\n\r\nFurthermore, Professor Snyman recently steered a new initiative at the TUT by introducing a 'Laboratory for Innovative Electronic Systems ' at the Department of Electrical Engineering. The model of this laboratory or center is to primarily combine outputs as achieved by high-level research with lower-level system development and entrepreneurship in a technical university environment. Students are allocated to projects at different levels with PhDs and Master students allocated to the generation of new knowledge and new technologies, while students at the diploma and Baccalaureus level are allocated to electronic systems development with a direct and a near application for application in industry or the commercial and public sectors in South Africa.\r\n\r\nProfessor Snyman received the WIRSAM Award of 1983 and the WIRSAM Award in 1985 in South Africa for best research papers by a young scientist at two international conferences on electron microscopy in South Africa. He subsequently received the SA Microelectronics Award for the best dissertation emanating from studies executed at a South African university in the field of Physics and Microelectronics in South Africa in 1987. In October of 2011, Professor Snyman received the prestigious Institutional Award for 'Innovator of the Year” for 2010 at the Tshwane University of Technology, South Africa. This award was based on the number of patents recognized and granted by local and international institutions as well as for his contributions concerning innovation at the TUT.",institutionString:null,institution:{name:"University of South Africa",country:{name:"South Africa"}}},{id:"317279",title:"Mr.",name:"Ali",middleName:"Usama",surname:"Syed",slug:"ali-syed",fullName:"Ali Syed",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/317279/images/16024_n.png",biography:"A creative, talented, and innovative young professional who is dedicated, well organized, and capable research fellow with two years of experience in graduate-level research, published in engineering journals and book, with related expertise in Bio-robotics, equally passionate about the aesthetics of the mechanical and electronic system, obtained expertise in the use of MS Office, MATLAB, SolidWorks, LabVIEW, Proteus, Fusion 360, having a grasp on python, C++ and assembly language, possess proven ability in acquiring research grants, previous appointments with social and educational societies with experience in administration, current affiliations with IEEE and Web of Science, a confident presenter at conferences and teacher in classrooms, able to explain complex information to audiences of all levels.",institutionString:null,institution:{name:"Air University",country:{name:"Pakistan"}}},{id:"75526",title:"Ph.D.",name:"Zihni Onur",middleName:null,surname:"Uygun",slug:"zihni-onur-uygun",fullName:"Zihni Onur Uygun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/75526/images/12_n.jpg",biography:"My undergraduate education and my Master of Science educations at Ege University and at Çanakkale Onsekiz Mart University have given me a firm foundation in Biochemistry, Analytical Chemistry, Biosensors, Bioelectronics, Physical Chemistry and Medicine. After obtaining my degree as a MSc in analytical chemistry, I started working as a research assistant in Ege University Medical Faculty in 2014. In parallel, I enrolled to the MSc program at the Department of Medical Biochemistry at Ege University to gain deeper knowledge on medical and biochemical sciences as well as clinical chemistry in 2014. In my PhD I deeply researched on biosensors and bioelectronics and finished in 2020. Now I have eleven SCI-Expanded Index published papers, 6 international book chapters, referee assignments for different SCIE journals, one international patent pending, several international awards, projects and bursaries. In parallel to my research assistant position at Ege University Medical Faculty, Department of Medical Biochemistry, in April 2016, I also founded a Start-Up Company (Denosens Biotechnology LTD) by the support of The Scientific and Technological Research Council of Turkey. Currently, I am also working as a CEO in Denosens Biotechnology. The main purposes of the company, which carries out R&D as a research center, are to develop new generation biosensors and sensors for both point-of-care diagnostics; such as glucose, lactate, cholesterol and cancer biomarker detections. My specific experimental and instrumental skills are Biochemistry, Biosensor, Analytical Chemistry, Electrochemistry, Mobile phone based point-of-care diagnostic device, POCTs and Patient interface designs, HPLC, Tandem Mass Spectrometry, Spectrophotometry, ELISA.",institutionString:null,institution:{name:"Ege University",country:{name:"Turkey"}}},{id:"246502",title:"Dr.",name:"Jaya T.",middleName:"T",surname:"Varkey",slug:"jaya-t.-varkey",fullName:"Jaya T. Varkey",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/246502/images/11160_n.jpg",biography:"Jaya T. Varkey, PhD, graduated with a degree in Chemistry from Cochin University of Science and Technology, Kerala, India. She obtained a PhD in Chemistry from the School of Chemical Sciences, Mahatma Gandhi University, Kerala, India, and completed a post-doctoral fellowship at the University of Minnesota, USA. She is a research guide at Mahatma Gandhi University and Associate Professor in Chemistry, St. Teresa’s College, Kochi, Kerala, India.\nDr. Varkey received a National Young Scientist award from the Indian Science Congress (1995), a UGC Research award (2016–2018), an Indian National Science Academy (INSA) Visiting Scientist award (2018–2019), and a Best Innovative Faculty award from the All India Association for Christian Higher Education (AIACHE) (2019). She Hashas received the Sr. Mary Cecil prize for best research paper three times. She was also awarded a start-up to develop a tea bag water filter. \nDr. Varkey has published two international books and twenty-seven international journal publications. She is an editorial board member for five international journals.",institutionString:"St. Teresa’s College",institution:null},{id:"250668",title:"Dr.",name:"Ali",middleName:null,surname:"Nabipour Chakoli",slug:"ali-nabipour-chakoli",fullName:"Ali Nabipour Chakoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/250668/images/system/250668.jpg",biography:"Academic Qualification:\r\n•\tPhD in Materials Physics and Chemistry, From: Sep. 2006, to: Sep. 2010, School of Materials Science and Engineering, Harbin Institute of Technology, Thesis: Structure and Shape Memory Effect of Functionalized MWCNTs/poly (L-lactide-co-ε-caprolactone) Nanocomposites. Supervisor: Prof. Wei Cai,\r\n•\tM.Sc in Applied Physics, From: 1996, to: 1998, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Determination of Boron in Micro alloy Steels with solid state nuclear track detectors by neutron induced auto radiography, Supervisors: Dr. M. Hosseini Ashrafi and Dr. A. Hosseini.\r\n•\tB.Sc. in Applied Physics, From: 1991, to: 1996, Faculty of Physics & Nuclear Science, Amirkabir Uni. of Technology, Tehran, Iran, Thesis: Design of shielding for Am-Be neutron sources for In Vivo neutron activation analysis, Supervisor: Dr. M. Hosseini Ashrafi.\r\n\r\nResearch Experiences:\r\n1.\tNanomaterials, Carbon Nanotubes, Graphene: Synthesis, Functionalization and Characterization,\r\n2.\tMWCNTs/Polymer Composites: Fabrication and Characterization, \r\n3.\tShape Memory Polymers, Biodegradable Polymers, ORC, Collagen,\r\n4.\tMaterials Analysis and Characterizations: TEM, SEM, XPS, FT-IR, Raman, DSC, DMA, TGA, XRD, GPC, Fluoroscopy, \r\n5.\tInteraction of Radiation with Mater, Nuclear Safety and Security, NDT(RT),\r\n6.\tRadiation Detectors, Calibration (SSDL),\r\n7.\tCompleted IAEA e-learning Courses:\r\nNuclear Security (15 Modules),\r\nNuclear Safety:\r\nTSA 2: Regulatory Protection in Occupational Exposure,\r\nTips & Tricks: Radiation Protection in Radiography,\r\nSafety and Quality in Radiotherapy,\r\nCourse on Sealed Radioactive Sources,\r\nCourse on Fundamentals of Environmental Remediation,\r\nCourse on Planning for Environmental Remediation,\r\nKnowledge Management Orientation Course,\r\nFood Irradiation - Technology, Applications and Good Practices,\r\nEmployment:\r\nFrom 2010 to now: Academic staff, Nuclear Science and Technology Research Institute, Kargar Shomali, Tehran, Iran, P.O. Box: 14395-836.\r\nFrom 1997 to 2006: Expert of Materials Analysis and Characterization. Research Center of Agriculture and Medicine. Rajaeeshahr, Karaj, Iran, P. O. Box: 31585-498.",institutionString:"Atomic Energy Organization of Iran",institution:{name:"Atomic Energy Organization of Iran",country:{name:"Iran"}}},{id:"248279",title:"Dr.",name:"Monika",middleName:"Elzbieta",surname:"Machoy",slug:"monika-machoy",fullName:"Monika Machoy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248279/images/system/248279.jpeg",biography:"Monika Elżbieta Machoy, MD, graduated with distinction from the Faculty of Medicine and Dentistry at the Pomeranian Medical University in 2009, defended her PhD thesis with summa cum laude in 2016 and is currently employed as a researcher at the Department of Orthodontics of the Pomeranian Medical University. She expanded her professional knowledge during a one-year scholarship program at the Ernst Moritz Arndt University in Greifswald, Germany and during a three-year internship at the Technical University in Dresden, Germany. She has been a speaker at numerous orthodontic conferences, among others, American Association of Orthodontics, European Orthodontic Symposium and numerous conferences of the Polish Orthodontic Society. She conducts research focusing on the effect of orthodontic treatment on dental and periodontal tissues and the causes of pain in orthodontic patients.",institutionString:"Pomeranian Medical University",institution:{name:"Pomeranian Medical University",country:{name:"Poland"}}},{id:"252743",title:"Prof.",name:"Aswini",middleName:"Kumar",surname:"Kar",slug:"aswini-kar",fullName:"Aswini Kar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252743/images/10381_n.jpg",biography:"uploaded in cv",institutionString:null,institution:{name:"KIIT University",country:{name:"India"}}},{id:"204256",title:"Dr.",name:"Anil",middleName:"Kumar",surname:"Kumar Sahu",slug:"anil-kumar-sahu",fullName:"Anil Kumar Sahu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204256/images/14201_n.jpg",biography:"I have nearly 11 years of research and teaching experience. I have done my master degree from University Institute of Pharmacy, Pt. Ravi Shankar Shukla University, Raipur, Chhattisgarh India. I have published 16 review and research articles in international and national journals and published 4 chapters in IntechOpen, the world’s leading publisher of Open access books. I have presented many papers at national and international conferences. I have received research award from Indian Drug Manufacturers Association in year 2015. My research interest extends from novel lymphatic drug delivery systems, oral delivery system for herbal bioactive to formulation optimization.",institutionString:null,institution:{name:"Chhattisgarh Swami Vivekanand Technical University",country:{name:"India"}}},{id:"253468",title:"Dr.",name:"Mariusz",middleName:null,surname:"Marzec",slug:"mariusz-marzec",fullName:"Mariusz Marzec",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/253468/images/system/253468.png",biography:"An assistant professor at Department of Biomedical Computer Systems, at Institute of Computer Science, Silesian University in Katowice. Scientific interests: computer analysis and processing of images, biomedical images, databases and programming languages. He is an author and co-author of scientific publications covering analysis and processing of biomedical images and development of database systems.",institutionString:"University of Silesia",institution:null},{id:"212432",title:"Prof.",name:"Hadi",middleName:null,surname:"Mohammadi",slug:"hadi-mohammadi",fullName:"Hadi Mohammadi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/212432/images/system/212432.jpeg",biography:"Dr. Hadi Mohammadi is a biomedical engineer with hands-on experience in the design and development of many engineering structures and medical devices through various projects that he has been involved in over the past twenty years. Dr. Mohammadi received his BSc. and MSc. degrees in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, and his PhD. degree in Biomedical Engineering (biomaterials) from the University of Western Ontario. He was a postdoctoral trainee for almost four years at University of Calgary and Harvard Medical School. He is an industry innovator having created the technology to produce lifelike synthetic platforms that can be used for the simulation of almost all cardiovascular reconstructive surgeries. He’s been heavily involved in the design and development of cardiovascular devices and technology for the past 10 years. He is currently an Assistant Professor with the University of British Colombia, Canada.",institutionString:"University of British Columbia",institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"254463",title:"Prof.",name:"Haisheng",middleName:null,surname:"Yang",slug:"haisheng-yang",fullName:"Haisheng Yang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/254463/images/system/254463.jpeg",biography:"Haisheng Yang, Ph.D., Professor and Director of the Department of Biomedical Engineering, College of Life Science and Bioengineering, Beijing University of Technology. He received his Ph.D. degree in Mechanics/Biomechanics from Harbin Institute of Technology (jointly with University of California, Berkeley). Afterwards, he worked as a Postdoctoral Research Associate in the Purdue Musculoskeletal Biology and Mechanics Lab at the Department of Basic Medical Sciences, Purdue University, USA. He also conducted research in the Research Centre of Shriners Hospitals for Children-Canada at McGill University, Canada. Dr. Yang has over 10 years research experience in orthopaedic biomechanics and mechanobiology of bone adaptation and regeneration. He earned an award from Beijing Overseas Talents Aggregation program in 2017 and serves as Beijing Distinguished Professor.",institutionString:"Beijing University of Technology",institution:null},{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255757/images/system/255757.jpg",biography:"Lakhno Igor Victorovich was born in 1971 in Kharkiv (Ukraine). \nMD – 1994, Kharkiv National Medical Univesity.\nOb&Gyn; – 1997, master courses in Kharkiv Medical Academy of Postgraduate Education.\nPhD – 1999, Kharkiv National Medical Univesity.\nDSc – 2019, PL Shupik National Academy of Postgraduate Education \nLakhno Igor has been graduated from an international training courses on reproductive medicine and family planning held in Debrecen University (Hungary) in 1997. Since 1998 Lakhno Igor has worked as an associate professor of the department of obstetrics and gynecology of VN Karazin National University and an associate professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education. Since June 2019 he’s a professor of the department of obstetrics and gynecology of VN Karazin National University and a professor of the perinatology, obstetrics and gynecology department of Kharkiv Medical Academy of Postgraduate Education . He’s an author of about 200 printed works and there are 17 of them in Scopus or Web of Science databases. Lakhno Igor is a rewiever of Journal of Obstetrics and Gynaecology (Taylor and Francis), Informatics in Medicine Unlocked (Elsevier), The Journal of Obstetrics and Gynecology Research (Wiley), Endocrine, Metabolic & Immune Disorders-Drug Targets (Bentham Open), The Open Biomedical Engineering Journal (Bentham Open), etc. He’s defended a dissertation for DSc degree \\'Pre-eclampsia: prediction, prevention and treatment”. Lakhno Igor has participated as a speaker in several international conferences and congresses (International Conference on Biological Oscillations April 10th-14th 2016, Lancaster, UK, The 9th conference of the European Study Group on Cardiovascular Oscillations). His main scientific interests: obstetrics, women’s health, fetal medicine, cardiovascular medicine.",institutionString:"V.N. Karazin Kharkiv National University",institution:{name:"Kharkiv Medical Academy of Postgraduate Education",country:{name:"Ukraine"}}},{id:"89721",title:"Dr.",name:"Mehmet",middleName:"Cuneyt",surname:"Ozmen",slug:"mehmet-ozmen",fullName:"Mehmet Ozmen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/89721/images/7289_n.jpg",biography:null,institutionString:null,institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"243698",title:"M.D.",name:"Xiaogang",middleName:null,surname:"Wang",slug:"xiaogang-wang",fullName:"Xiaogang Wang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243698/images/system/243698.png",biography:"Dr. Xiaogang Wang, a faculty member of Shanxi Eye Hospital specializing in the treatment of cataract and retinal disease and a tutor for postgraduate students of Shanxi Medical University, worked in the COOL Lab as an international visiting scholar under the supervision of Dr. David Huang and Yali Jia from October 2012 through November 2013. Dr. Wang earned an MD from Shanxi Medical University and a Ph.D. from Shanghai Jiao Tong University. Dr. Wang was awarded two research project grants focused on multimodal optical coherence tomography imaging and deep learning in cataract and retinal disease, from the National Natural Science Foundation of China. He has published around 30 peer-reviewed journal papers and four book chapters and co-edited one book.",institutionString:"Shanxi Eye Hospital",institution:{name:"Shanxi Eye Hospital",country:{name:"China"}}},{id:"242893",title:"Ph.D. Student",name:"Joaquim",middleName:null,surname:"De Moura",slug:"joaquim-de-moura",fullName:"Joaquim De Moura",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/242893/images/7133_n.jpg",biography:"Joaquim de Moura received his degree in Computer Engineering in 2014 from the University of A Coruña (Spain). In 2016, he received his M.Sc degree in Computer Engineering from the same university. He is currently pursuing his Ph.D degree in Computer Science in a collaborative project between ophthalmology centers in Galicia and the University of A Coruña. His research interests include computer vision, machine learning algorithms and analysis and medical imaging processing of various kinds.",institutionString:null,institution:{name:"University of A Coruña",country:{name:"Spain"}}},{id:"267434",title:"Dr.",name:"Rohit",middleName:null,surname:"Raja",slug:"rohit-raja",fullName:"Rohit Raja",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRZkkQAG/Profile_Picture_2022-05-09T12:55:18.jpg",biography:null,institutionString:null,institution:null},{id:"294334",title:"B.Sc.",name:"Marc",middleName:null,surname:"Bruggeman",slug:"marc-bruggeman",fullName:"Marc Bruggeman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/294334/images/8242_n.jpg",biography:"Chemical engineer graduate, with a passion for material science and specific interest in polymers - their near infinite applications intrigue me. \n\nI plan to continue my scientific career in the field of polymeric biomaterials as I am fascinated by intelligent, bioactive and biomimetic materials for use in both consumer and medical applications.",institutionString:null,institution:null},{id:"244950",title:"Dr.",name:"Salvatore",middleName:null,surname:"Di Lauro",slug:"salvatore-di-lauro",fullName:"Salvatore Di Lauro",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0030O00002bSF1HQAW/ProfilePicture%202021-12-20%2014%3A54%3A14.482",biography:"Name:\n\tSALVATORE DI LAURO\nAddress:\n\tHospital Clínico Universitario Valladolid\nAvda Ramón y Cajal 3\n47005, Valladolid\nSpain\nPhone number: \nFax\nE-mail:\n\t+34 983420000 ext 292\n+34 983420084\nsadilauro@live.it\nDate and place of Birth:\nID Number\nMedical Licence \nLanguages\t09-05-1985. Villaricca (Italy)\n\nY1281863H\n474707061\nItalian (native language)\nSpanish (read, written, spoken)\nEnglish (read, written, spoken)\nPortuguese (read, spoken)\nFrench (read)\n\t\t\nCurrent position (title and company)\tDate (Year)\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. Private practise.\t2017-today\n\n2019-today\n\t\n\t\nEducation (High school, university and postgraduate training > 3 months)\tDate (Year)\nDegree in Medicine and Surgery. University of Neaples 'Federico II”\nResident in Opthalmology. Hospital Clinico Universitario Valladolid\nMaster in Vitreo-Retina. IOBA. University of Valladolid\nFellow of the European Board of Ophthalmology. Paris\nMaster in Research in Ophthalmology. University of Valladolid\t2003-2009\n2012-2016\n2016-2017\n2016\n2012-2013\n\t\nEmployments (company and positions)\tDate (Year)\nResident in Ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl.\nFellow in Vitreo-Retina. IOBA. University of Valladolid\nVitreo-Retinal consultant in ophthalmology. Hospital Clinico Universitario Valladolid. Sacyl. National Health System.\nVitreo-Retinal consultant in ophthalmology. Instituto Oftalmologico Recoletas. Red Hospitalaria Recoletas. \n\t2012-2016\n2016-2017\n2017-today\n\n2019-Today\n\n\n\t\nClinical Research Experience (tasks and role)\tDate (Year)\nAssociated investigator\n\n' FIS PI20/00740: DESARROLLO DE UNA CALCULADORA DE RIESGO DE\nAPARICION DE RETINOPATIA DIABETICA BASADA EN TECNICAS DE IMAGEN MULTIMODAL EN PACIENTES DIABETICOS TIPO 1. Grant by: Ministerio de Ciencia e Innovacion \n\n' (BIO/VA23/14) Estudio clínico multicéntrico y prospectivo para validar dos\nbiomarcadores ubicados en los genes p53 y MDM2 en la predicción de los resultados funcionales de la cirugía del desprendimiento de retina regmatógeno. Grant by: Gerencia Regional de Salud de la Junta de Castilla y León.\n' Estudio multicéntrico, aleatorizado, con enmascaramiento doble, en 2 grupos\nparalelos y de 52 semanas de duración para comparar la eficacia, seguridad e inmunogenicidad de SOK583A1 respecto a Eylea® en pacientes con degeneración macular neovascular asociada a la edad' (CSOK583A12301; N.EUDRA: 2019-004838-41; FASE III). Grant by Hexal AG\n\n' Estudio de fase III, aleatorizado, doble ciego, con grupos paralelos, multicéntrico para comparar la eficacia y la seguridad de QL1205 frente a Lucentis® en pacientes con degeneración macular neovascular asociada a la edad. (EUDRACT: 2018-004486-13). Grant by Qilu Pharmaceutical Co\n\n' Estudio NEUTON: Ensayo clinico en fase IV para evaluar la eficacia de aflibercept en pacientes Naive con Edema MacUlar secundario a Oclusion de Vena CenTral de la Retina (OVCR) en regimen de tratamientO iNdividualizado Treat and Extend (TAE)”, (2014-000975-21). Grant by Fundacion Retinaplus\n\n' Evaluación de la seguridad y bioactividad de anillos de tensión capsular en conejo. Proyecto Procusens. Grant by AJL, S.A.\n\n'Estudio epidemiológico, prospectivo, multicéntrico y abierto\\npara valorar la frecuencia de la conjuntivitis adenovírica diagnosticada mediante el test AdenoPlus®\\nTest en pacientes enfermos de conjuntivitis aguda”\\n. National, multicenter study. Grant by: NICOX.\n\nEuropean multicentric trial: 'Evaluation of clinical outcomes following the use of Systane Hydration in patients with dry eye”. Study Phase 4. Grant by: Alcon Labs'\n\nVLPs Injection and Activation in a Rabbit Model of Uveal Melanoma. Grant by Aura Bioscience\n\nUpdating and characterization of a rabbit model of uveal melanoma. Grant by Aura Bioscience\n\nEnsayo clínico en fase IV para evaluar las variantes genéticas de la vía del VEGF como biomarcadores de eficacia del tratamiento con aflibercept en pacientes con degeneración macular asociada a la edad (DMAE) neovascular. Estudio BIOIMAGE. IMO-AFLI-2013-01\n\nEstudio In-Eye:Ensayo clínico en fase IV, abierto, aleatorizado, de 2 brazos,\nmulticçentrico y de 12 meses de duración, para evaluar la eficacia y seguridad de un régimen de PRN flexible individualizado de 'esperar y extender' versus un régimen PRN según criterios de estabilización mediante evaluaciones mensuales de inyecciones intravítreas de ranibizumab 0,5 mg en pacientes naive con neovascularización coriodea secunaria a la degeneración macular relacionada con la edad. CP: CRFB002AES03T\n\nTREND: Estudio Fase IIIb multicéntrico, randomizado, de 12 meses de\nseguimiento con evaluador de la agudeza visual enmascarado, para evaluar la eficacia y la seguridad de ranibizumab 0.5mg en un régimen de tratar y extender comparado con un régimen mensual, en pacientes con degeneración macular neovascular asociada a la edad. CP: CRFB002A2411 Código Eudra CT:\n2013-002626-23\n\n\n\nPublications\t\n\n2021\n\n\n\n\n2015\n\n\n\n\n2021\n\n\n\n\n\n2021\n\n\n\n\n2015\n\n\n\n\n2015\n\n\n2014\n\n\n\n\n2015-16\n\n\n\n2015\n\n\n2014\n\n\n2014\n\n\n\n\n2014\n\n\n\n\n\n\n\n2014\n\nJose Carlos Pastor; Jimena Rojas; Salvador Pastor-Idoate; Salvatore Di Lauro; Lucia Gonzalez-Buendia; Santiago Delgado-Tirado. Proliferative vitreoretinopathy: A new concept of disease pathogenesis and practical\nconsequences. Progress in Retinal and Eye Research. 51, pp. 125 - 155. 03/2016. DOI: 10.1016/j.preteyeres.2015.07.005\n\n\nLabrador-Velandia S; Alonso-Alonso ML; Di Lauro S; García-Gutierrez MT; Srivastava GK; Pastor JC; Fernandez-Bueno I. Mesenchymal stem cells provide paracrine neuroprotective resources that delay degeneration of co-cultured organotypic neuroretinal cultures.Experimental Eye Research. 185, 17/05/2019. DOI: 10.1016/j.exer.2019.05.011\n\nSalvatore Di Lauro; Maria Teresa Garcia Gutierrez; Ivan Fernandez Bueno. Quantification of pigment epithelium-derived factor (PEDF) in an ex vivo coculture of retinal pigment epithelium cells and neuroretina.\nJournal of Allbiosolution. 2019. ISSN 2605-3535\n\nSonia Labrador Velandia; Salvatore Di Lauro; Alonso-Alonso ML; Tabera Bartolomé S; Srivastava GK; Pastor JC; Fernandez-Bueno I. Biocompatibility of intravitreal injection of human mesenchymal stem cells in immunocompetent rabbits. Graefe's archive for clinical and experimental ophthalmology. 256 - 1, pp. 125 - 134. 01/2018. DOI: 10.1007/s00417-017-3842-3\n\n\nSalvatore Di Lauro, David Rodriguez-Crespo, Manuel J Gayoso, Maria T Garcia-Gutierrez, J Carlos Pastor, Girish K Srivastava, Ivan Fernandez-Bueno. A novel coculture model of porcine central neuroretina explants and retinal pigment epithelium cells. Molecular Vision. 2016 - 22, pp. 243 - 253. 01/2016.\n\nSalvatore Di Lauro. Classifications for Proliferative Vitreoretinopathy ({PVR}): An Analysis of Their Use in Publications over the Last 15 Years. Journal of Ophthalmology. 2016, pp. 1 - 6. 01/2016. DOI: 10.1155/2016/7807596\n\nSalvatore Di Lauro; Rosa Maria Coco; Rosa Maria Sanabria; Enrique Rodriguez de la Rua; Jose Carlos Pastor. Loss of Visual Acuity after Successful Surgery for Macula-On Rhegmatogenous Retinal Detachment in a Prospective Multicentre Study. Journal of Ophthalmology. 2015:821864, 2015. DOI: 10.1155/2015/821864\n\nIvan Fernandez-Bueno; Salvatore Di Lauro; Ivan Alvarez; Jose Carlos Lopez; Maria Teresa Garcia-Gutierrez; Itziar Fernandez; Eva Larra; Jose Carlos Pastor. Safety and Biocompatibility of a New High-Density Polyethylene-Based\nSpherical Integrated Porous Orbital Implant: An Experimental Study in Rabbits. Journal of Ophthalmology. 2015:904096, 2015. DOI: 10.1155/2015/904096\n\nPastor JC; Pastor-Idoate S; Rodríguez-Hernandez I; Rojas J; Fernandez I; Gonzalez-Buendia L; Di Lauro S; Gonzalez-Sarmiento R. Genetics of PVR and RD. Ophthalmologica. 232 - Suppl 1, pp. 28 - 29. 2014\n\nRodriguez-Crespo D; Di Lauro S; Singh AK; Garcia-Gutierrez MT; Garrosa M; Pastor JC; Fernandez-Bueno I; Srivastava GK. Triple-layered mixed co-culture model of RPE cells with neuroretina for evaluating the neuroprotective effects of adipose-MSCs. Cell Tissue Res. 358 - 3, pp. 705 - 716. 2014.\nDOI: 10.1007/s00441-014-1987-5\n\nCarlo De Werra; Salvatore Condurro; Salvatore Tramontano; Mario Perone; Ivana Donzelli; Salvatore Di Lauro; Massimo Di Giuseppe; Rosa Di Micco; Annalisa Pascariello; Antonio Pastore; Giorgio Diamantis; Giuseppe Galloro. Hydatid disease of the liver: thirty years of surgical experience.Chirurgia italiana. 59 - 5, pp. 611 - 636.\n(Italia): 2007. ISSN 0009-4773\n\nChapters in books\n\t\n' Salvador Pastor Idoate; Salvatore Di Lauro; Jose Carlos Pastor Jimeno. PVR: Pathogenesis, Histopathology and Classification. Proliferative Vitreoretinopathy with Small Gauge Vitrectomy. Springer, 2018. ISBN 978-3-319-78445-8\nDOI: 10.1007/978-3-319-78446-5_2. \n\n' Salvatore Di Lauro; Maria Isabel Lopez Galvez. Quistes vítreos en una mujer joven. Problemas diagnósticos en patología retinocoroidea. Sociedad Española de Retina-Vitreo. 2018.\n\n' Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor Jimeno. iOCT in PVR management. OCT Applications in Opthalmology. pp. 1 - 8. INTECH, 2018. DOI: 10.5772/intechopen.78774.\n\n' Rosa Coco Martin; Salvatore Di Lauro; Salvador Pastor Idoate; Jose Carlos Pastor. amponadores, manipuladores y tinciones en la cirugía del traumatismo ocular.Trauma Ocular. Ponencia de la SEO 2018..\n\n' LOPEZ GALVEZ; DI LAURO; CRESPO. OCT angiografia y complicaciones retinianas de la diabetes. PONENCIA SEO 2021, CAPITULO 20. (España): 2021.\n\n' Múltiples desprendimientos neurosensoriales bilaterales en paciente joven. Enfermedades Degenerativas De Retina Y Coroides. SERV 04/2016. \n' González-Buendía L; Di Lauro S; Pastor-Idoate S; Pastor Jimeno JC. Vitreorretinopatía proliferante (VRP) e inflamación: LA INFLAMACIÓN in «INMUNOMODULADORES Y ANTIINFLAMATORIOS: MÁS ALLÁ DE LOS CORTICOIDES. RELACION DE PONENCIAS DE LA SOCIEDAD ESPAÑOLA DE OFTALMOLOGIA. 10/2014.",institutionString:null,institution:null},{id:"265335",title:"Mr.",name:"Stefan",middleName:"Radnev",surname:"Stefanov",slug:"stefan-stefanov",fullName:"Stefan Stefanov",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/265335/images/7562_n.jpg",biography:null,institutionString:null,institution:null},{id:"318905",title:"Prof.",name:"Elvis",middleName:"Kwason",surname:"Tiburu",slug:"elvis-tiburu",fullName:"Elvis Tiburu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Ghana",country:{name:"Ghana"}}},{id:"336193",title:"Dr.",name:"Abdullah",middleName:null,surname:"Alamoudi",slug:"abdullah-alamoudi",fullName:"Abdullah Alamoudi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Majmaah University",country:{name:"Saudi Arabia"}}},{id:"318657",title:"MSc.",name:"Isabell",middleName:null,surname:"Steuding",slug:"isabell-steuding",fullName:"Isabell Steuding",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"318656",title:"BSc.",name:"Peter",middleName:null,surname:"Kußmann",slug:"peter-kussmann",fullName:"Peter Kußmann",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Harz University of Applied Sciences",country:{name:"Germany"}}},{id:"338222",title:"Mrs.",name:"María José",middleName:null,surname:"Lucía Mudas",slug:"maria-jose-lucia-mudas",fullName:"María José Lucía Mudas",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}},{id:"147824",title:"Mr.",name:"Pablo",middleName:null,surname:"Revuelta Sanz",slug:"pablo-revuelta-sanz",fullName:"Pablo Revuelta Sanz",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Carlos III University of Madrid",country:{name:"Spain"}}}]}},subseries:{item:{id:"4",type:"subseries",title:"Fungal Infectious Diseases",keywords:"Emerging Fungal Pathogens, Invasive Infections, Epidemiology, Cell Membrane, Fungal Virulence, Diagnosis, Treatment",scope:"Fungi are ubiquitous and there are almost no non-pathogenic fungi. Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",hasOnlineFirst:!1,hasPublishedBooks:!1,annualVolume:11400,editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",slug:"yuping-ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",biography:"Dr. Yuping Ran, Professor, Department of Dermatology, West China Hospital, Sichuan University, Chengdu, China. Completed the Course Medical Mycology, the Centraalbureau voor Schimmelcultures (CBS), Fungal Biodiversity Centre, Netherlands (2006). 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Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. 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Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. 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