Vol. 6, No. 2, 47-59 doi:10.17708/DRMJ.2017.v06n02a04 CORPORATE STRATEGY AND INDUSTRY 4.0: BIBLIOMETRIC ANALYSIS ON FACTORS OF MODERNIZATION Petra Ajdovec Faculty of Economics, University of Ljubljana, Slovenia ajdovec.p@gmail.com Robert Kovačič Batista Faculty of Economics, University of Ljubljana, Slovenia robert.kovacic.batista@gmail.com Matjaž Vidmar Faculty of Economics, University of Ljubljana, Slovenia vidmar93@gmail.com - Abstract - The fourth industrial revolution has produced several new fields of research, yet the areas of management and business are lagging behind. The aim of the present paper is to show connections and common thoughts within various literature areas, identify the main theoretical influxes into the field, and make informed suggestions for its future development. The analysis is conducted through the use of bibliometric methods, specifically co-citation analysis (Small, 1973) and bibliographic coupling (Kessler, 1963). Co-citation is defined as the frequency with which two units are cited together while bibliographic coupling uses the number of references shared by two documents as a measure of the similarity between them (Zupic & Čater, 2015). This enables us to identify relevant clusters that will show which scientific areas are most commonly connected with our chosen keywords. Furthermore, we will elaborate the advantages, disadvantages, effects and possible implications of the new robotization era processes on companies' business model transformation and changes in organizational structures, with an emphasis on the strategy of firms and the management behind it. Keywords: industry 4.0, bibliometrics, co-citation analysis, bibliographic coupling, robotization, corporate strategy 1. introduction Industry 4.0 or the so called fourth industrial revolution refers to the current and upcoming changes occurring in the industry development. Zhou et al (2015) noted that industry 4.0 includes future industry development trends to achieve more intelligent manufacturing processes. Radical changes have an impact on companies and their business models, and contemporary firms are faced with having to change their cor- porate strategies and organizational structures in order to adapt to the changes and survive on the market. The extant research has to some extend touched upon trends in the field of corporate strategy and industry 4.0; studies foresee large-scale changes in societal and business model transformations (Loebbecke and Picot, 2015), virtualization and decentralization in the manufacturing landscape (Brettel et al., 2014) and in the field of cloud computing, big data and intelligent manufacturing (Zhou et al., 2015). Dynamic Relationships Management Journal, Vol. 6, No. 2, November 2017 11 Petra Ajdovec, Robert Kovačič Batista, Matjaž Vidmar: Corporate Strategy and Industry 4.0: Bibliometric Analysis on Factors of Modernization Nevertheless, due to the rapid occurrence of events, new fields for scientific discovery and analysis emerge on a regular basis which implies that there is still room for additional research of the fields that have not been covered yet. There has been plenty of research regarding the industry 4.0 trends within the field of informational technology, but much less has been done within the field of management, business and economics. We have found out that the analysis of explicitly showing the correlations between all relevant literature is lacking. In addition, the extant research has not yet examined the positive and negative potential consequences of robotization overall, especially within the field of strategic management. The aim of this paper is to show connections and common thoughts within various literature areas, identify the main theoretical influxes into the field, and make informed suggestions for its future development. The analysis will be conducted through the use of bibliometric methods, specifically co-citation analysis (Small, 1973) and bibliographic coupling (Kessler, 1963). Co-citation is defined as the frequency with which two units are cited together while bibliographic coupling uses the number of references shared by two documents as a measure of the similarity between them (Zupic & Cater, 2015). This will enable us to identify relevant clusters that will show which scientific areas are most commonly connected with our chosen keywords. Furthermore, we will elaborate the advantages, disadvantages, effects and possible implications of the new robotization era processes on companies' business model transformation and changes in organizational structures, with an emphasis on the strategy of firms and the management behind it. We will show the weights of common literature by using Web of Science and VOSviewer programme analytics to graphically show the trends and inclinations of robotization in near future. Easily accessible online databases with citation data -such as Web of Science - have attracted widespread attention of bibliometric methods, write Zupic and Cater (2015), and VOSviewer is a program that has been developed for constructing and viewing bibliometric maps (Van Eck and Waltman, 2009). Even though there are many speculations that exist within our topic, we will also touch the impact of robotization on management, strategy, and labour area. This paper will try to deepen the view on the matter by summing up many different aspects and apply them on today's situation vis-a-vis a forecast impact. 2. THEORETICAL BACKGROUND Digitalization and big data analytics - or datafi-cation - penetrate all areas of life and create new ways of working communicating and cooperating (Loebbecke and Picot 2015). Holotiuk and Beim-born (2017, 991) write that digitalization fundamentally impacts firm's strategy development. For example, one of the responses of organizations when it comes to digitalization, can be seen in the uprising of the industry 4.0 which "/ .../ focuses on the establishment of intelligent products and production processes (Brettel et al., 2014)". Brettel et al. (2014) say that at the moment, "/ .../ industry 4.0 is a popular term to describe the imminent changes of the industry landscape, particularly in the production and manufacturing industry of the developed world." Furthermore, Popescu (2011, 726) presents yet another aspect and claims that virtualization solves most of the problems that occur in organizations when it comes to management applications and continues that virtualization opens vast opportunities in the business continuity. Due to the uprise of the digitalized economy, new business models and strategies have arose (Peitz et al, 2006) - a significant portion of trade now takes place online, for example. Another paradigm that Lee et al (2017, 1) refer to as a novelty that is rapidly gaining ground in scenarios for factories of the future is called smart factory. "The concept of smart factories began to be established as a combination of information and communication technologies and digital automation solutions throughout the overall production process / ... / (Lee et al 2017, 1)" and can now be found in various areas of operations of a company. Last but not least, "/ .../ robots are stronger / .../" and "/ .../ the worry is that our market economy will not, on its own, be able to create new jobs with comparable pay for those who are losing their jobs" (Stiglitz, 2017). 48 Dynamic Relationships Management Journal, Vol. 6, No. 2, November 2017 Enlisted concepts show how vast are the areas, which are covered by the formation of new technologies and changes that have developed due to the technological advancement. There is a wide range of opportunities on one side and numerous drawbacks and dilemmas on the other. According to Zhou et al. (2015) there are scientific challenges, technological challenges, economic challenges, social problems and political issues. Organizations will have to respond to those challenges in order to survive and stay competitive actors on the market. Companies will need virtual and physical structures that allow for close cooperation and rapid adaption along the whole lifecycle from innovation to production and distribution (Schumacher et al. 2016). This calls for a changed strategy that takes the challenges and changes into account. 3. METHODS Methods used in our analysis arise from the bibliometric field, meaning that it deals with a statistical analysis of scholarly communication through publications (Batistic, Cerne & Vogel, 2017). Bibliometric analysis includes two techniques - co-citation analysis and bibliographical coupling. 3.1 Keyword selection After a close overview of the basic literature, we have selected several keywords covering topics that appear most frequently and are consistently cited throughout the literature and refer to keywords connected with the terms digitalization and strategy development. For the purpose of our analysis we have chosen the following keywords: Digitalization, big data, virtualization, datafication, industry 4.0, digitalized economy, smart factory and robotization. We have looked for these keywords along with the following keywords that refer to the field of strategies in organizations: Strategy, strategic management and organizational response. 3.2 Co-citation Co-citation analysis determines the key documents or core documents, which have had the most influence on the chosen research area through the analysis of citation frequency of the documents by other literatures simultaneously (Yu & Xu, 2017). This method connects two documents that appear together in the references of the same papers into networks. It is an indication that the two papers have derived on common knowledge (Lazzeretti et al., 2017). It occures when two documents without any direct relationship are cited simultaneously by other documents. These two papers are said to be co-cited. Web of Science, scientific citation indexing service, provided us with the list of scientific papers that included the following set of keywords: "(digitalization OR big data OR virtualization OR datafication OR industry 4.0. OR digitalized economy OR smart factory OR robotization) AND (strategy OR strategic management OR organizational response)" Out of Web Science's database, 4390 primary papers were found and we have included the first 1000 documents (based on relevance, an indicator founded in citation frequency) in our analysis. The analysis was conducted in VOSviewer with the co-citation technique. Our counting method was full counting, our unit of analysis were documents. We have predetermined that the minimum number of citations of a document has to be 3 - out of the 1000 documents, 361 have met the threshold, and for all those documents, the total strength of the co-citation links with other documents will be calculated. Figure 1 shows the network of clusters that were formed with the co-citation analysis and where they lie in relation to one another. Figure 2 shows the density of the clusters and we can see where the density is the strongest as well as the outliers. Table 1 shows the analysis of the biggest eight clusters that were formed following the co-citation analysis. Name of the cluster shows which topic is dominant in the cluster, number of items indicates how many items there are in each separate cluster and the brief description gives information on the content of the documents in the clusters. Dynamic Relationships Management Journal, Vol. 6, No. 2, November 2017 11 Petra Ajdovec, Robert Kovačič Batista, Matjaž Vidmar: Corporate Strategy and Industry 4.0: Bibliometric Analysis on Factors of Modernization Figure 1: Network visualization Source: Own VOSviewer analysis. Figure 2: Density vizualization Source: Own VOSviewer analysis. 3.3 Bibliographical coupling Bibliographic coupling differs from co-citation in "/.../ describing similarities among groups of papers for information retrieval" (Youtie, Kay and Melkers, 2013, 147). Zupic and Cater (2015, 438) noted that "co-citation analysis and bibliographical coupling use citation practices to connect documents, authors or journals." Youtie, Kay and Melkers (2013, 145) define bibliographic coupling as "/.../ the appearance of a reference work in the cited references of articles from two or more center researchers." The same set of keywords as in the co-citation analysis has again been applied for the extraction of key literature. Out of Web Science's database, 4390 primary papers were found and we have included the first 1000 documents in our analysis. Analysis was done in VOSviewer with bibliographical coupling - it links papers that cite the same articles and represents the current state-of-the-art of the examined field. Our counting method was full counting, our unit of analysis were documents. We have predetermined that the minimum number of citations of a document has to be 10 - out of the 1000 documents, 598 have met the threshold and for all of those documents the total strength of the bibliographical coupling links with other documents will be calculated. The largest set of connected items consists of 312 items. 48 Dynamic Relationships Management Journal, Vol. 6, No. 2, November 2017 Table 1: Clusters from co-citation analysis Cluster N°of items Brief description 1 Bioinformatics 46 The area in the red cluster contains literature on Bioinformatics, which is an interdisciplinary application of IT on biological data for a better understanding on available information. There is some emphasis on knowledge management and new formalized approaches on the matter as well. Collins and Varmus (2015) write " / .../The initiative will encourage and support the next generation of scientists to develop creative new approaches for detecting, measuring, and analyzing a wide range of biomedical information". 2 Computer science 45 The computer science cluster includes papers that describe principles, usage, theory, design, development and application of computer and software systems. It is notable, that few papers are done on the topic of cloud computing, " / ./a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction" (Baliga et al. 2011, 150). Cloud computing systems fundamentally provide access to large pools of data and computational resources through a variety of interfaces similar in spirit to exist- ing grid and HPC resource management and programming systems. (Nurmi et al., 2009) 3 Knowledge-based view 41 The common line of the articles within KVB cluster are explaining, elaborating or proving various concepts about a specified topic. The information can help an organization, government or individuum to adopt or improve a strategy in order to obtain a needed competitive advantage. It is a learning approach which can serve for instance, as a basis for human capital involvement in an organization. As Cohen and Levinthal (1990) write " / .../ Outside sources of knowledge are often critical to the innovation process, whatever the organizational level at which the innovating unit is defined" . 4 No general topic 36 Because there cannot be find any relevant common line between the literatures, the cluster is unnamed, hence irrelevant for our paper. 5 Psychology 28 The cluster consists psychology articles that are focused on different strategic, conceptual and statistical factors as well as measures that influence the personalities of human beings. For instance, aggregation is one of " / .../ the most expected form personality measures, is a procedure that has been implicitly practiced almost since the dawn of scientific psychology" (Digman, 1990). 6 Big data, digital data 22 In this cluster, we can find articles weighting and considering the increasing impact of big data usage for different purposes. " / .../ because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance" (McAfee and Brynjolfsoon, 2012). 7 History, anthropology 20 An outlier of all cluster with literature exploring miscellaneous anthropological scope of surface. One " / ./paper presents research on the conditions under which progressive levels of burning may occur to archaeological bone" (Stiner and Kuhn, 1994). 8 Personality factors 16 The final memorable cluster has factors that influence personality, where (Ashton et al., 2009) found them " / ./as measures of broad personality factors do not necessarily imply the existence of higherorder factors". Another paper tells us " / ./that almost all of the common variance between factors can be attributed to a single general factor related to social desirability" (Backstrom et al., 2009). Dynamic Relationships Management Journal, Vol. 6, No. 2, November 2017 11 Petra Ajdovec, Robert Kovačič Batista, Matjaž Vidmar: Corporate Strategy and Industry 4.0: Bibliometric Analysis on Factors of Modernization Figure 3: Network Visualization burstein (2010) johnson(2005) liu [1013) farquhar(2005) ^Kgueredo (2007) Aoerger (2011 ) ones (2007) vickery (2003) Iii coin (1992) scherer (2000) mile/4201 í) wilh