Content

Gizem ATAK, Ferhan ÇEBİ, Techno-Parks on the Digital Transformation in:

Alptekin Erkollar (Ed.)

Enterprise & Business Management, page 179 - 204

A Handbook for Educators, Consultants, and Practitioners

1. Edition 2020, ISBN print: 978-3-8288-4255-7, ISBN online: 978-3-8288-7230-1, https://doi.org/10.5771/9783828872301-179

Series: Enterprise & Business Management

Tectum, Baden-Baden
Bibliographic information
Gizem ATAK, Ferhan ÇEBİ Techno-Parks on the Digital Transformation Learnign Objectives The objectives of this chapter are to investigate and present current issues and trends of techno-park companies with regard to digital transformation. Once you have mastered the materials in this chapter, you will be able to: – Explain the developments brought about by each industrial revolution. – Understand the importance of techno-park companies in developing new technology. – Identify the concept of Industry 4.0. – Explain the cyber-physical production systems, their features and the triggers of Industry 4.0. – Understand the effects of firm characteristics, number of employees and establishment year, on the company’s awareness levels regarding Industry 4.0. – Understand the effects of firm characteristics, number of employees and establishment year, on the selection of Industry 4.0 technologies to be developed. Chapter Outline Today's world is in the fourth industrial revolution, which has a crucial role in the economies and industries of the countries. With this revolution, it is expected that all of the tools used in the industry will be selflearning, smart and more efficient hardware and software products will be able to produce. Therefore, industrial production speed, volume, and productivity will step up, and social and economic life will improve. If we are not ready for this revolution as a country, we will have 179 to face huge devastating effects besides its advantages, just as it is in every industrial revolution. To be able to transform the new industrial revolution into an advantage, there is a need for measures to be taken in this direction and studies to shed light on what needs to be done. Thus, the purpose of this chapter is to investigate and discuss some of the issues of techno-park companies in terms of Industry 4.0 after introducing the concept of Industry 4.0 and its technologies. Keywords Industry 4.0, digital transformation, techno-parks, developing technology. Introduction Industry conception is in our lives for many centuries. Today, we are in a new industrial revolution or, in other words, a period of digital transformation. With the first industrial revolution which was begun in the late 18th century, only the industrial period did not begin. With this revolution, a lot of major changes, that directly affect our lives, have also brought about such as the development of living standards, new branches of industry-economic activities, cultural changes etc. (Ozdogan 2017). The fourth industrial revolution is comparatively different from the other revolutions. The new industrial revolution, which is also called as Industry 4.0, is a digital transformation of production systems, as developed by information and communication technologies. Digital transformation of the production chain’s every stage is the development of 'Intelligent Manufacturing Systems' through the provision of machine-human-infrastructure interaction (TÜBİTAK 2016). With this, all machines and industrial devices used in the industry will generate data and will have meaningful intelligence from these data. In this way, factories will be smart and able to manage themselves. In addition to that, techno-parks have an undeniable role in technology production and development. So, the study is conducted to analysis the status of techno-parks with regard to Industry 4.0. The purpose of this study is to investigate current issues and trends of techno-park companies with regard to digital transformation in Turkey. More specifical- 1 Techno-Parks on the Digital Transformation 180 ly, the study aims to find answers for the following questions: 1) What is the level of awareness about Industry 4.0 at the national level? 2) Which Industry 4.0 technologies have been used by techno-park firms on their solutions for customers in the last 5 years? 3) What is the usage level of these Industry 4.0 technologies by techno-park firms on the solutions of customers in the last 5 years? 4) What are the application areas in which they offer their products under Industry 4.0? 5) Do the awareness levels, types of Industry 4.0 technologies developed for customer solutions, their usage level and application areas that they offer their products regarding Industry 4.0 differ with respect to the firm size, which is measured as the number of employees? 6) Do the awareness levels, types of Industry 4.0 technologies developed for customer solutions, their usage level, and application areas that they offer their products regarding Industry 4.0 differ with respect to the firm’s establishment year? In this pursuit, the study is conducted in six sections. After the introduction, section 2 covers the brief explanation of industrial revolutions. Section 3 includes a brief explanation of Industry 4.0 and Industry 4.0 technologies. Section 4 has information about techno-parks. Section 5 consists of a methodology covering exploratory factor analysis and measures the effect of company size and establishment year on the company’s Industry 4.0 activities. Finally, the last section provides a summary and a conclusion. Industrial Revolutions The concept of “revolution” means instantaneous and radical transformation. During history, revolutions have taken place every time that new technologies and new perceptions of the world have brought about profound changes in economic systems and social structures (Schwab 2017). Three major industrial revolutions have taken place in the world up to now. In today’s world, we are in a fourth industrial revolution which is also called as Industry 4.0. These revolutions and their features are explained in detail in the following section. 2 2 Industrial Revolutions 181 The First Industrial Revolution The first industrial revolution started with the use of steam and water power for the first time on handloom (Koçak and Diyadin 2018). This industrial revolution which is continued from 1760 to around 1840, led to mechanical production with the construction of railways and the steam engine (Schwab 2017). With this revolution, there has been a serious increase in production capacity and speed (Ozdogan 2017). In addition to that, according to many authors, steam engines have not only affected steam and textile industries but also affected the other industries such as transportation, communication, and banking, etc. More and more products are being produced and the improved the standards of living, while at the same time there has also emerged a poor and hard-working employee within the scope of this ear. Therefore, this revolution not only affected production but also affected people's lives in terms of a social and psychological perspective. The Second Industrial Revolution With electric technology and chemical techniques, the second industrial revolution expanded to Europe, the United States, and Japan. It had become possible to achieve mass production with the production band technique used by Ford company, resulting in an increase in productivity (Koçak and Diyadin 2018). The second industrial revolution, which became to rise in the late 19th and early 20th centuries, made mass production possible with the support provided by the electricity and assembly line (Schwab 2017). The production methods continued to change until the second industrial revolution, which took place in 1870, specialization in employees began, and they were separated according to their expertise field. Organizations have transformed, and all these developments have expanded to all of the worlds. (Ozdogan 2017). The most significant features that distinguish the second revolution from the first revolution are production capacities and new machines used to increase these capacities. In this period of technological production, it was not only the production elements that were affected 2.1 2.2 Techno-Parks on the Digital Transformation 182 as in the first revolution. The entire life of people was also affected (Ozdogan 2017). The Third Industrial Revolution In the third industrial revolution, automation-based manufacturing processes (in which electronic and information technologies were used) were introduced (Koçak and Diyadin 2018). The third industrial revolution, which began in the 1960s; is often referred to as a computer or digital revolution. This is because, this period was improved by the catalyses of host computers (the 1960s), personal computers (1970s-1980s) and the internet (1990s) (Schwab 2017). In this period; transistors, Enterprise Resource Planning systems, Computer Numerical Controller machines were produced for the first time under the favour of the programming language of computers and machines. In this era, all kinds of data stored on paper became stored in the computer environment. Therefore, the Industry had the production speed and capacity that it has never reached before. In addition to that, administrative costs and difficulties have been eliminated and automation needs have been met in this term. The technology that has progressed in this industrial revolution has been used to the structure of companies' strategies, designing the new business forms and increasing of the production channels (Ozdogan 2017). In the third industrial revolution, which is started in 1940 and ended in 2010, there was computers, digital products and solutions, and internet. In this revolution, the recordings were digitized, and major innovations came to exist in the field of information science, especially after 1950. Also, the rise in new technology and production capacities also created new markets (Ozdogan 2017). After the third industrial revolution, Industry 4.0, which is made up of the highest level of technology use and the cyberphysical systems that internet and information technologies combine, has been reached (Koçak and Diyadin 2018). 2.3 2 Industrial Revolutions 183 The Fourth Industrial Revolution In today’s world is in a new technological era, which will trigger the fourth industrial revolution (Industry 4.0) (Magruk 2016). Industry 4.0 is a development process (which is also called as "the fourth industrial revolution"), which has been planned for the future and is now underway (Koçak and Diyadin 2018). According to this, the webbased network will support all of the smart factories at every level of the production line such as design, servicing, and recycling, etc. (Magruk 2016). Industry 4.0 Concept Industry 4.0 is a term which is arisen from Germany in 2011. It is focused on developing smart chains based on communicating with each other parts of production such as products, components, factory, people, etc. (Magruk 2016). Industry 4.0 is regarded as the “Fourth Industrial Revolution” and is expected to bring lots of significant changes in many areas (Soysal and Pamuk 2018). Industry 4.0 concept; is based on the communication of all the shareholders that are involved in the industrial production process, all the data can be reached in real time and the acquiring the highest possible value added under the favour of this data. In addition to that, this concept usually, at every phase of the entire supply chain, starting from the purchase of raw materials, producing the products, delivering them to the consumer and recycling processes are improved by taking advantage of emerging technologies (Soysal and Pamuk 2018). Industry 4.0 can be thought as a way in which a product is produced, delivered, used, repaired and recycled entirely automatically through the internet, in other words, without human intervention. According to The Federal Ministry of Education and Research in Germany, with Industry 4.0, equipment and machines will change the information constantly and be ensured that many processes in the future will be controlled and coordinated in real time at large distances. Therefore, smart factories and products will be created (Fuchs, 2018). 2.4 3 Techno-Parks on the Digital Transformation 184 Technologies of Industry 4.0 The traditional manufacturing industry is trying to adapt itself by experiencing the difficulties and adversity of the industrial revolution, a digital transformation that speeds up by new technologies. The new technologies of digital transformation are demonstrated in Figure 1 (Fırat and Fırat 2017). Within the scope of Industry 4.0 technologies, there are such as: The Cyber-Physical Production Systems (CPPS), Machine-to-machine Communication (M2M), Artificial Intelligence (AI), Horizontal and vertical system integration, Internet of Things (IoT), Big Data, Cloud Services, Cyber Security, Virtual Reality, Simulation, Additive Manufacturing. The term of Industry 4.0 gains more and more global recognizability day by day. The expanding of market globalization, rapidly rising global competition and more complex products and services cause a need for new technologies, business models and methods. A rapidly changing market environment and customer demands require to operate logistics processes effectively (Gubán and Kovács 2017). Industry 4.0 is consisting of the combination of different types of technologies and factors for the common goal of advancing the performance and efficiency of production line systems (Ahuett- Garza and Kurfess 2018). In addition to that, industry 4.0 is developed in Europe to acquire perfect manufacturing productivity. It provides smarter and more competitive enterprises by gathering data from devices in real-time and converting them into meaningful information. For this reason, this data can be used to acquire much more market share and increasing profit (Leitão et al. 2016). Recent research shows that industry 4.0 will affect the business world in terms of three main areas such as digitalization and integration of vertical and horizontal value chains, the formation of customer relationships and digital business models and digitalization of services and products (Gubán and Kovács 2017). Therefore, with these new technologies, the entire production process will flexibly adapt to customer demands, the activities of each part of the supply chain, and the rapidly changing economic environment (Gubán and Kovács 2017). 3.1 3 Industry 4.0 Concept 185 The triggers for this digital transformation (Fırat and Fırat 2017) Cyber-physical systems are generally identified as a link between embedded systems (Kai-Oliver Zander and MEng 2015). In other words, cyber-physical production systems are types of equipment which are able to communicate via a network. It generates communication between IT technology and electronic or mechanic items (Gubán and Kovács 2017). With the cyber-physical systems, the whole process of the system can automatically run itself without any human intervention or extra effort, with a program to be done at the beginning of the system. Here, the "automation" term is important. Many machines which including learning robots, are involved in the production pro- Figure 1: Techno-Parks on the Digital Transformation 186 cess. In today’s world, it is known that robots and vehicles learning in the automobile industry are already presented in some production processes (Soysal and Pamuk 2018). With the help of this link, cyberphysical systems can act and react between the virtual and the real world. For instance, to integrate the employee into the system, the cyber-physical systems provide an interface that enables a human-machine interaction (Kai-Oliver Zander and MEng 2015). Sensors provide the machines keeping contact with the other production elements such as factories, networks and people (Gubán and Kovács 2017). Intelligent production robots are the parts of the entire system that are able to communicate with the production control system and the element to be processed. For this reason, they are able to optimize the whole process and obtain system-wide optimization of resources (Gubán and Kovács 2017). Cyber-physical systems are also consolidating statistics and real-time data which are received from physical systems, to model the response of a system under various cases to make decisions in real time. The main objective is to improve the performance, at overall levels of the system (Ahuett-Garza and Kurfess 2018). Machine-to-machine communication is really important for cyber-physical systems. It provides that the devices connected to the network, activate the communication without human interference. For instance, robots that work on a production line are able to provide the needs of each other or stop the whole production systems in urgent cases (Gubán and Kovács 2017). Machine-To-Machine communication provides a horizontal integration. Machines which are in the same location, as well as different enterprises, can then be communicated over the internet. (Kai-Oliver Zander and MEng 2015). Machine Learning is also identified as a computer techniques group which is centre on getting the necessary information and make proper decisions by using big data, both structured or unstructured, which can be acquired from a business or factory at any given time (Ahuett-Garza and Kurfess 2018). One of the most important technologies that are included within the scope of Industry 4.0 is artificial intelligence and machine learning (Ozdogan 2017). Artificial Intelligence is a machineability that allows machines to learn and think logically. Under favor of artificial intelligence, machines are able to fulfil complex tasks (Gubán and Kovács 2017). The technology of increasing images with informa- 3 Industry 4.0 Concept 187 tion such as sound, graphics, the animation is a long-standing technology (İçten and Bal 2017). Systems that take advantage of augmented reality, support a variety of services, such as selecting parts in the depot and sending repair instructions to mobile devices. Although these systems are still in beginning, companies will benefit from enriched reality in the future to improve the decision-making and operational processes of the companies and to allow real-time information to their employees (TÜSİAD and BCG 2016). Products communicate with the other workpieces and the machines as well to work own manufacturing. In addition to, that communication is not only within the factory, but also in a whole chain such as suppliers, producers etc. (Gubán and Kovács 2017). Most of today's information technology systems are not fully integrated each other. Firms, customers and suppliers are rarely connected to each other from end to end. A similar situation exists in engineering, design, production and service functions. But, as universal data integration networks improved on a company-wide basis, companies, units and competencies will become more and more compatible with each other (TÜSİAD and BCG 2016). Internet helps people in terms of communicating with each other despite the distance between them. It is inevitable that this communication, now carried to the size of the objects, will affect the market structure and the production and marketing strategies of the enterprises (Soysal and Pamuk 2018). The internet of things (IoT) is a network connection and data exchange of incorporated electronic devices (Gubán and Kovács 2017). Internet of things is the transfer of information from an object, for example, the device or from a human being to other systems through a network (Ozdogan 2017). In this way, the devices can be used more and more efficiently (Gubán and Kovács 2017). Today, it is possible to combine many data by using the internet. However, in spite of the fact that the data is huge and due to the increasing information pollution, the use of this information and the selection of the right information from it are really hard. Nowadays, this information is decomposed by big data applications (Soysal and Pamuk 2018). Therefore, big data has an important role in the evolution of Industry 4.0 (Ozdogan 2017). It is thought that the size of the data in existing networks will be much bigger in the coming years (Soysal and Pamuk 2018). The world is generating massive amounts of data every second. In addition to that, not Techno-Parks on the Digital Transformation 188 only the volume of the data but also the variety and velocity of the data created are rising day by day (Ozdogan 2017). Thus, large data will play a crucial role in Industry 4.0. According to the German government, it is expected that the most beneficial innovation technology of Industry 4.0 will be the big data (Soysal and Pamuk 2018). The main goal of cloud-based services is to hold software data on a cloud instead of storing data locally. For this reason, these data can be reached from any location or devices through the internet connection (Gubán and Kovács 2017). The most important feature of cloud computing is the rapid use of the desired service. In addition to that, cloud computing services have high sustainability rates and short turnaround times in case of possible destruction (Ozdogan 2017). In today’s world, firms are already using cloud-based software for some enterprise and some analytical applications. But, with the fourth industrial revolution, more data on products had to be shared between plants and firms. At the same time, the number of machines belonging to cloud platforms will rise day by day and provide more beneficial services to the production systems based on the database. Furthermore, even systems that monitor and control processes are likely to move into the cloud in the Industry 4.0 era (TÜSİAD and BCG 2016). On the other hand, this access also raises concerns about the security of stored data (Gubán and Kovács 2017). Many companies still use management and production systems that are not integrated with each other. But with increased integration, critical industrial systems and production lines will need to be protected against cybersecurity threats. For this reason, secure communication based on the identification of machines and management of access to machines will gain importance (TÜSİAD and BCG 2016). Manufacturers who are operating in some industries use robots in their operations. In the world, robot technology is now becoming more flexible, autonomous and collaborative by improving its abilities and decreasing the cost. With the Industry 4.0 era, robots will communicate with each other and work side by side with people more securely and they will be able to develop their learning abilities (TÜSİAD and BCG 2016). Nowadays, the design phase of products, 3D simulation of materials and production processes are started to use. On the other side, in the future, it is stated that simulations will become more widespread in the factories. The virtual reality of the physical world 3 Industry 4.0 Concept 189 will come together with machines, products, and people prepared by using real-time data under the favor of the simulation models. That’s way, for a product on the production line, the machine parameters will be tested in the virtual world before it is actually set. This will minimize the setup time of the machines and maximize the quality (TÜSİAD and BCG 2016). With the digital transformation, the actual and virtual reality come together during production. Virtuality has an important role in design and production. The simulation of processes also has a significant role in production to catch and measure unexpected cases and their effects (Gubán and Kovács 2017). With the fourth industrial revolution, in other words, Industry 4.0, firms have started to adopt additive manufacturing techniques, such as three-dimensional printing, prototyping, and manufacturing product parts. It is expected that this technique will be used more widely in the future, especially in the fields such as complex and light designs, to produce a small number of special products. To sum up, high performance and decentralized additive production systems will decrease logistics costs and stock levels (TÜSİAD and BCG 2016). In addition to that, raw materials are turned to final parts by digital dataflow of the additive manufacturing techniques. Techniques of additive manufacturing are such below: Firstly, the process begins with a digital 3D sample of the piece which is to be produced. Secondly, supportive pieces are added if it is necessary. Thirdly, the digital model is sliced or otherwise discretised to compose directives for the machine. Finally, the additive manufacturing machine receives these directives to produce the physical material (Ahuett-Garza and Kurfess 2018). Techno Parks Techno-parks are different from each other in terms of lots of aspects such as organization structure, purpose, and way of working and administrative structures. Therefore, it is really difficult to describe them with a single definition (Btgm.sanayi.gov.tr 2018). Thus, some various definitions are given such below: According to the International Association of Science Parks (IASP): A science park is an organization managed by specialized professionals, whose main aim is to increase 4 Techno-Parks on the Digital Transformation 190 the wealth of its community by promoting the culture of innovation and the competitiveness of its associated businesses and knowledgebased institutions. To enable these goals to be met, a Science Park stimulates and manages the flow of knowledge and technology amongst universities, R&D institutions, companies, and markets; it facilitates the creation and growth of innovation-based companies through incubation and spin-off processes; and provides other valueadded services together with high-quality space and facilities. (IASP 2017). According to the Technology Development Zone Law No. 4691: The Technology Development Zone is a region where technology / software developed by companies using high / advanced technology or new technology, utilizing the facilities of a specific university or high technology institute, R&D centre or institute. Firms in this region operate to transform a technological invention into a commercial product, method or service, thereby contributing to the development of the region. In addition, the technology development zone also refers to the site with or integrated with the academic, economic and social structure within or near the same university, high technology institute or R&D headquarters or institute area. (Official Gazette 24454 2001). Techno-parks are really important structures of the innovation system that brings together the technology and science infrastructure of the university and the Industry (Pekol and Erbas 2011). They are established for inducing the formation and improvement of the new technology-based firms (Siegel et al. 2003). Techno-parks create an environment that helps companies in terms of to establish relationships with other companies and universities, under the favour of the structures that keep their companies in close proximity to each other and to the university. These relationships are helpful for expanding the knowledge and it leads to entrepreneurial and innovative cultures. (Pekol and Erbas 2011). There are 77 Technology Development Zone in Turkey and 56 of these are still in operation (Btgm.sanayi.gov.tr 2018). 4 Techno Parks 191 Methodology and Findings of Research As stated earlier, this study aims to measure the awareness level of techno-park companies on the Industry 4.0, Industry 4.0 technologies that have been used by techno-park firms on their solutions for customers in the last 5 years, application areas in which they offer their products related to Industry 4.0, and to determine these factors differ with respect to the establishment year of the firm and firm size which is measured as the number of employees (Atak, 2018). In this pursuit, a survey using a questionnaire form has been developed considering the opinions and sights who are expert in the field of Industry 4.0 and information gathered in the light of literature. In the questionnaire, the items related to the subjects indicated above are grouped into 3 questions. Overview of Industry 4.0, Application Area, Industry 4.0 Technologies. The participants in the responding organizations were asked to use a 5-point Likert-type scale to indicate the degree of agreement in the top two groups above. After that, the questionnaire was sent to 50 techno-park in Turkey. A total of 231 technology development centered companies participated in the survey. The prepared questionnaire study was conducted as a pilot study to several technology manufacturing companies located in Istanbul Technopark. In total, 231 of 830 respondents were answered. Thus, the questionnaire response rate is approximately 28%. The data obtained from the survey were analyzed with descriptive statistics, exploratory factor analysis, reliability analysis, and t-test by using the SPSS 25.0 statistical software program. In the study, 69.7% (n=161) of the responding organizations were in the software sector, 24.2% (n=56) were in engineering firms and 6.1% (n=14) of the participants did not state their sector group. Finally, most of the participants consist of managers with 33.3% (n=77), this is followed by the company owner with 22.9% (n=53) and the rest of the participant’s position were other. 5 Techno-Parks on the Digital Transformation 192 Measures The level of awareness about Industry 4.0 In this section, there were 23 questions. Before the factor analysis, the results of KMO and Bartlett’s tests were given in Table 1. As seen in Table 1, Barlett’s Test of Sphericity is significant (p<0.0005). Also, the anti-image correlation matrix was examined and all diagonal values were found greater than 0.50. These are enough to use the factor analysis. In addition to that, the sample size is sufficient for analysis. The value of Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) is 0.878 and 0.878 > 0.6 means that it is significant. The value of Bartlett’s test Chi-Square is 3583.792 and degree of freedom is 231. So, it is significant (p=0.000, p<0.05). Components and Cronbach's alpha coefficients of awareness level about Industry 4.0 Factors N Cronbach’s Alpha Awareness about organizational impact 8 0.948 Awareness about competitiveness impact 7 0.883 Awareness about role of techno-parks and support 3 0.835 Awareness about environmental impact 4 0.792 K.M.O: 0.878; Bartlett Test: 3583.792; p: 0.000 As seen in Table 1, the variables were collected in 4 groups. Also, communalities for each item have a value greater than 0,30. The first factor has eigenvalue 8.063, which explains 36,649 % of total variance and factor 1 represents awareness about organizational impact. The first factor which contains nine items measures whether participants have knowledge of Industry 4.0, Industry 4.0 technologies and whether they have information about how their companies’ sector that they operate in will be influenced by the digital transformation. The second factor has eigenvalue 3.584, which explains 16.291 % of total variance and factor 2 represents awareness about competitiveness impact. The second factor seven items points out participants’ sights about the effects of digital transformation on getting more market share and increasing the competitiveness of companies. The third factor has eigenvalue 5.1 5.1.1 Table 1: 5 Methodology and Findings of Research 193 2.709, which explains 12.313 % of total variance and factor 3 represents awareness about environmental impact. The third factor having tree items is related to the participants’ opinions on the issue of whether Industry 4.0 is being discussed sufficiently in Turkey by the government, academics and non-government organizations, trade unions and press. Finally, the fourth factor has eigenvalue 1.076, which explains 4.893 % of total variance and factor 4 represents awareness about the role of techno-parks and support. Also, the total percentage of explanation is 70.146. The fourth factor has 4 items. And it measures participants’ opinions about whether participants receive adequate support for the development of Industry 4.0 technologies and whether techno-parks’ role in the diffusion and development of Industry 4.0 technologies at the national level. After conducting factor analysis, the reliability of each factor has been calculated. As seen in Table 1, all factors have Cronbach’s Alpha value greater than the 0.7. Table 2 represents the descriptive statistics of factors. The range of factors’ mean varies between 3.33 and 4.33. Here, 5 implies “strongly agree” and 1 implies “strongly disagree”. Descriptive statistics of awareness level about Industry 4.0 Factors N Mean Std. Deviation Awareness about organizational impact 219 3.66 0.99 Awareness about competitiveness impact 224 4.23 0.72 Awareness about role of techno-parks and support 223 2.51 0.91 Awareness about environmental impact 226 3.33 0.85 As seen in Table 2, awareness about competitive impact has the highest mean however, awareness about the role of techno-parks and support has the lowest mean. Technologies of Industry 4.0 In this part, participants were asked which of the technologies in Industry 4.0 were offered to their customers. These technologies are; sensor technology, big data, robot and automation, horizontal / vertical system integration, cyber security, cloud computing, augmented reality Table 2: 5.1.2 Techno-Parks on the Digital Transformation 194 technology, additive manufacturing, internet of things, machine learning and artificial intelligence, simulation and virtual reality. On the other hand, the participants were asked to indicate which frequencies they have been using these technologies for solutions to customer's problems. Participants' responses to Industry 4.0 technologies are given in Table 3. Descriptive statistics of Industry 4.0 technologies 0–4 5–9 10–14 +15 Technology Frequency (%) Frequency (%) Frequency (%) Frequency (%) Sensor Technology 91(39.4) 29 (12.6) 11(4.8) 4(1.7) Big Data 93(40.3) 37(16.0) 15(6.5) 5(2.2) Robot and Automation 65(28.1) 17(7.4) 10(4.3) 9(3.9) Horizontal / Vertical System Integration 61(26.4) 22(9.5) 10(4.3) 4(1.7) Cyber Security 71(30.7) 21(9.1) 12(5.2) 4(1.7) Cloud Computing 74(32.0) 28(12.1) 20(8.7) 12(5.2) Augmented Reality Technology 71(30.7) 17(7.4) 8(3.5) 2(0.9) Additive Manufacturing 66(28.6) 7(3.0) 5(2.2) 4(1.7) Internet of Things 79(34.2) 21(9.1) 12(5.2) 9(3.9) Machine Learning and Artificial Intelligence 82(35.5) 21(9.1) 5(2.2) 3(1.3) Simulation 74(32.0) 11(4.8) 7(3.0) 4(1.7) Virtual Reality 75(32.5) 13(5.6) 4(1.7) 3(1.3) It appears that most of the participants who answered this question offered their solutions which are related to these technologies is in the range of 0–4 predominantly. In this section, factor analysis is also applied to those 12 items related to Industry 4.0 technologies seen in Table 3. Table 3: 5 Methodology and Findings of Research 195 Results of KMO and Bartlett's test of Industry 4.0 technologies KMO and Bartlett’s Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy ,858 Bartlett’s Test of Sphericity Approx. Chi-Square 610.751 Df 66 Sig .000 Table 4 presents the results of KMO and Bartlett’s tests. As seen from the table, the value of the Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) is 0.858. So, it can be said that the sample is enough for the analysis. From the table, the value of Bartlett's test Chi-Square is seen as 610.751 and degree of freedom as 66. The significance of the test is 0.000 (p=0.000, p<0.05). These results indicate the factor analysis to be suitable. In addition, the anti-image correlation matrix was examined and all diagonal values were found greater than 0.50. These are enough to use the factor analysis. Also, the sample size is sufficient for analysis. The results of the factor analysis are given in Table 5. Components and factor loadings of technologies of Industry 4.0 Factors Factor Loading Communality Factor 1: Digital manufacturing systems technologies Sensor Technology 0.618 0.804 Robot and Automation 0.822 0.724 Horizontal / Vertical System Integration 0.731 0.680 Additive Manufacturing 0.601 0.681 Internet of Things 0.616 0.539 Factor 2: Virtualization technologies Augmented Reality Technology 0.790 0.803 Simulation 0.784 0.739 Virtual Reality 0.843 0.807 Factor 3: Data management technologies Big Data 0.758 0.643 Table 4: Table 5: Techno-Parks on the Digital Transformation 196 Cyber Security 0.639 0.710 Cloud Computing 0.734 0.575 Machine Learning and Artificial Intelligence 0.598 0.539 As seen in Table 5, communalities for each item have a value greater than 0.30. Also, the variables were collected in three groups. The first factor has eigenvalue 4.420, which explains 45.166 % of total variance and factor 1 represents digital manufacturing systems technologies. The second factor has eigenvalue 1.455, which explains 12.123 % of total variance and factor 2 represents virtualization technologies. The third factor has eigenvalue 1.174, which explains 9.780 % of total variance and factor 3 represents data management technologies. Also, the total percentage of explanation is 67.069. After conducting factor analysis, the reliability of each factor has been calculated. Table 6 represents Cronbach’s alpha internal consistency coefficients of all factors. Cronbach's alpha coefficients of technologies of Industry 4.0 Factors N Cronbach’s Alpha Digital manufacturing systems technologies 5 0,814 Virtualization technologies 3 0.886 Data management technologies 4 0.767 As seen in Table 6, all factors have Cronbach’s Alpha value greater than the 0.7. Application areas In this section, participants were asked which application area that they would like to present their solution and its degree, within the scope of Industry 4.0. Before the factor analysis results of KMO and Bartlett’s tests were given in Table 7. Table 6: 5.1.3 5 Methodology and Findings of Research 197 Results of KMO and Bartlett's Test of application area KMO and Bartlett’s Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy .906 Bartlett’s Test of Sphericity Approx. Chi-Square 1045.072 Df 45 Sig .000 The value of Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) is 0.906 and 0.906 > 0.6 means that it is significant. The value of Bartlett’s test Chi-Square is 1045.072 and degree of freedom is 45. So, it is significant (p=0.000, p<0.05). The results of the factor analysis are given in Table 8. Also, the anti-image correlation matrix was examined and all diagonal values were found greater than 0.50. These are enough to use the factor analysis. Also, the sample size is sufficient for analysis. Components and factor loadings of application area Factors Factor Loading Communality Factor 1: Primary Activities Production 0.609 0.551 Purchase 0.890 0.871 Logistics 0.664 0.492 Sales 0.792 0.762 Finance/Accounting 0.831 0.755 Human Resources 0.790 0.727 Factor 2: Supportive and Service Activities Service 0.692 0.704 Information Technologies 0.814 0.727 After sales service 0.605 0.699 R and D 0.813 0.708 As seen in Table 8, communalities for each item have a value greater than 0.30. Also, the variables were collected in two groups. The first factor has eigenvalue 6.094, which explains 60.944% of total variance Table 7: Table 8: Techno-Parks on the Digital Transformation 198 and factor 1 represents primary activities. The second factor has eigenvalue 0.916, which explains 9.157 % of the total variance and factor 2 represents supportive and service activities. After conducting factor analysis, the reliability of each factor has been calculated. Table 9 represents Cronbach’s alpha internal consistency coefficients of all factors. Cronbach's alpha coefficients of application area Factors N Cronbach’s Alpha Primary Activities 6 0.909 Supportive and Service Activities 4 0.852 As seen in Table 9, all factors have Cronbach’s Alpha value greater than the 0.7. Effect of Size and Establishment Year This section investigates the effect of firm characteristics which are measured as the number of employees and establishment year on the following issue: Industry 4.0 awareness levels of Technopark, Type of Industry 4.0 technologies on customer solutions, Usage level of Industry 4.0 technologies on customer solutions, Application areas that they offer their products regarding Industry 4.0. More specifically, the study test whether the mean score of the issues mentioned above differs with regard to the number of employees and the establishment year of the firm. the t-test is selected for the analysis. In this pursuit, the mean score of each factor illustrated in Table 1, Table 5 and Table 8 is calculated. Then, the firms are divided two groups with regard to number of employments: ones having 49 or less than 49 employees and others having more than 49 employees while the firms are grouped into two with regard to establishment year: ones with earlier than 2010 of establishment year and others with 2010 or later that establishment year. The results of the t-test have shown that company’s awareness levels, types of Industry 4.0 technologies on customer solutions, their usage level, as well as application areas that they offer their products regarding Industry 4.0 do not differ with respect to number of employment and establishment year. Table 9: 5.1.4 5 Methodology and Findings of Research 199 Conclusion This chapter discusses some of the issues of techno-park companies’ Industry 4.0 activities in Turkey. The findings of the study are summarized as follows: Awareness level about Industry 4.0 is classified in four main categories, which are “awareness about the organizational impact”, “awareness about competitiveness impact”, “awareness about the role of techno-park and support” and” awareness about the environmental impact”. The mean of awareness about competitiveness impact is too high. This result is also supported by a study which is conducted by Boston Consulting Group and Turkish Industry and Business Association in manufacturing firms in 2016. According to two research, most of the companies think that Industry 4.0 technologies will contribute to getting more market share (TÜSİAD and BCG 2016). On the other hand, the mean of awareness about the role of techno-park and support is low. Industry 4.0 technologies are classified into three main categories, which are “digital manufacturing systems technologies”, “virtualization technologies” and “data management technologies”. Results showed that most of the participants who answered this question offered their solutions which are related to these technologies is in the range of 0–4 predominantly. The application area is classified into two parts, which are “primary activities” and “supportive and service activities”. Company’s awareness levels on Industry 4.0, type of Industry 4.0 technologies for customer solutions and their usage level, and application areas of Industry 4.0 technologies that they offer do not differ with respect to firm characteristics which are measured with regard to number of employees and establishment year. The t-test applied to each factor obtained in this study did not yield a statistically significant result. Although, scholars who analyzed the correlation between firm size and the ability of digital transformation found that “the relationship is stronger for newly established and smaller firms than others (Auger et al. 2003). Techno-Parks on the Digital Transformation 200 References Ahuett-Garza, H., & Kurfess, T. (2018). A brief discussion on the trends of habilitating technologies for Industry 4.0 and Smart manufacturing. Manufacturing Letters. Auger, P., Barnir, A., & Gallaugher, M. J. (2003). Business Process Digitization, Strategy, and the Impact of Firm Age and Size: The Case of the Magazine Publishing Industry. Journal of Business Venturing, (6) 18, 789–814. Atak G. (2018), The Role of Technopark Companies in the Development of the Fourth Industrial Revolution in Turkey,. Istanbul Technical University, Unpublished master’s thesis Btgm.sanayi.gov.tr (2018). Date retrieved 28.12.2018, from https://btgm.sanayi.go v . t r /DokumanGetHandler .ashx?dokumanId=c2 f 7d4c9–5cde-461eb2ee-1966309073d2. Fırat, S. Ü., & Fırat, O. Z. (2017). Sanayi 4.0 Devrimi Üzerine Karşılaştırmalı Bir İnceleme: Kavramlar, Küresel Gelişmeler ve Türkiye. Toprak İşveren Dergisi, (114), 10–23. Fuchs, C. (2018). Industry 4.0: The Digital German Ideology. tripleC: Communication, Capitalism & Critique. Open Access Journal for a Global Sustainable Information Society, 16(1), 280–289. Gubán, M., & Kovács, G. (2017). Industry 4.0 Conception. Acta Technical Corviniensis-Bulletin of Engineering, 10(1), 111. IASP (2017). Date retrieved 23.10.2017, from https://www.iasp.ws/OurIndustry/D efinitions. İçten, T., & Bal, G. (2017). Artırılmış Gerçeklik Teknolojisi Üzerine Yapılan Akademik Çalışmaların İçerik Analizi. Bilişim Teknolojileri Dergisi, 10(4), 401–415. (IASP 2017) Doyduk, H. B. B., & Tiftik, C. (2017). Nesnelerin İnterneti: Kapsamı, Gelecek Yönelimi ve İş Fırsatları. Third Sector Social Economic Review, 52(3), 127–147. Kai-Oliver Zander MS, M., & MEng, K. R. (2015). An Analysis of the Potential of Company's Inter-Cooperation on Shop-Floor Level Through the Utilization of Cyber-Physical Production Systems. In Proceedings of the International Annual Conference of the American Society for Engineering Management. (p.1). American Society for Engineering Management (ASEM). Kiran, V. (2016). Trends 2016: Big Data, IoT take the plunge. Voice & Data; New Delhi. Koçak, A., & Diyadin, A. (2018). Sanayi 4.0 Geçiş Süreçlerinde Kritik Başarı Faktörlerinin DEMATEL Yöntemi ile Değerlendirilmesi. Ege Akademik Bakis, 18(1), 107–120. Leitão, P., Colombo, A. W., & Karnouskos, S. (2016). Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges. Computers in Industry, 81, 11–25. References 201 Magruk, A. (2016). Uncertainty in the Sphere of the Industry 4.0-Potential Areas to Research. Business, Management and Education, 14(2), 275. Official Gazette 24454 (2001). Date retrieved 23.10.2017, from http://www.resmig azete.gov.tr/eskiler/2001/07/20010706.htm#1. Ozdogan, O. (2017). Endüstri 4.0. Ankara: Pusula yayın. Pekol, Ö., & Erbas, B. Ç. (2011). Patent Sisteminde Türkiye'deki Teknoparkların Yeri/Technopark in Turkey: Patent System Perspective. Ege Akademik Bakis, 11(1), 1327. Schwab, K. (2017). Dördüncü Sanayi Devrimi. Istanbul: Optimist. Siegel, D. S., Westhead, P., & Wright, M. (2003). Science Parks and The Performance of New Technology-Based Firms: A Review of Recent UK Evidence and an Agenda for Future Research. Small Business Economics, 20(2), 177–184. Soysal, M., & Pamuk, N. S. (2018). Yeni Sanayi Devrimi Endüstri 4.0 Üzerine Bir İnceleme. Verimlilik Dergisi, (1), 41–66. TÜBİTAK (2016). Ar-Ge Reform Paketi Tanıtım Toplantısı Yapıldı. Türkiye Bilimsel ve Teknolojik Araştırmalar Merkezi, 14 Ocak 2016. Date retrieved: 23.04.2017, from https://www.tubitak.gov. tr /tr/haber/ar-gereform-paketi-tanitim-programi-yapildi. Türkiye Odalar ve Borsalar Birliği (2016). Akıllı Fabrikalar Geliyor. TOBB Ekonomik Forum Dergisi, 259, 16–27. TÜSİAD & BCG (2016). Türkiye’nin Küresel Rekabetçiliği için Bir Gereklilik Olarak Sanayi 4.0: Gelişmekte Olan Ekonomi Perspektifi. İstanbul: TÜSİAD. Key Terms Industry 4.0 Digital Transformation Techno-parks Application Area Industrial Revolution Awareness Level Firm Size Industry 4.0 Technologies Questions for Further Study What are the main outputs and the innovations of Industry 4.0 that will bring our lives? Compare and contrast techno-park companies and other technology development companies in terms of developing industry 4.0 technologies. What are the advantages of techno-park companies on this subject? Techno-Parks on the Digital Transformation 202 What are the main advantages of using big data? In which areas can you use this technology? Three major industrial revolutions have taken place until today and we are now experiencing a new revolution. What kind of results do you expect from the enterprises that cannot keep up with this revolution, why? Exercises Suppose that you developed a new warehouse management software and this application’s database, that holds all of your customer’s data, is on the cloud. What may be some concerns about using cloud computing and what measures can be taken against it? Suppose that you are the owner of a company that produces high technology. Which Industry 4.0 technologies would you focus on using in your products and services? Why? The technologies of Industry 4.0 are explained in this chapter. Suppose that you are a Sales Manager and you want to analyse customer behaviours and obtain the target of the customer to launch your new product. Which industry 4.0 technology can help you? Why? Further Reading Çevikcan, E. and Üstündağ, A. (2018). Industry 4.0: managing the digital transformation. Switzerland: Springer. Kiran, V. (2016). Trends 2016: Big Data, IoT take the plunge. Voice & Data; New Delhi. Prisecaru, P. (2017). The Challenges of the Industry 4.0. Global Economic Observer, 5(1), 66. Seliger, G., and Stock, T., (2016). Opportunities of Sustainable Manufacturing in Industry 4.0. Procedia CIRP, (40), 536–541. Vásquez-Urriago, Á. R., Barge-Gil, A., Rico, A. M., & Paraskevopoulou, E. (2014). The Impact of Science and Technology Parks On Firms’ Product Innovation: Empirical Evidence from Spain. Journal of Evolutionary Economics, 24(4), 835–873. Further Reading 203

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Abstract

Organizations have always been dependent on communication, information, technology and their management. The development of information technology has sped up the importance of management information systems, which is an emerging discipline combining various aspects of informatics, information technology, and business management. Understanding the impact of information on today’s organizations requires technological and managerial views, which are both offered by management information systems.

Business management is not only about generating greater returns and using new technologies for developing businesses to reach future goals. Business management also means generating better revenue performance if plans are diligently followed.

It is part of business management to have an ear to the ground of global economic trends, changing environmental conditions and preferences, as well as the behavior of value chain partners. While, until now, business management and management information systems are mostly treated as independent fields, this publication takes an interest in the cooperation of the two. Its contributions focus on both research areas and practical approaches, in turn showing novelties in the area of enterprise and business management.

Main topics covered in this book are technology management, software engineering, knowledge management, innovation management and social media management.

This book adopts an international view, combines theory and practice, and is authored for researchers, lecturers, students as well as consultants and practitioners.