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Big data of big companies: A content analysis for how ISO-500 listed firms use big-data

Yıl 2020, Sayı: 49, 130 - 145, 16.12.2020

İrge Şener Halil Erman Candar Uzuner

Öz

As its name suggests, big data, which gives an idea of the data size, contains other mysteries behind it. Indeed, besides its size, its speed and diversity are also highlighted by researchers. For this reason, it is suggested that it cannot be studied with traditional statistical methods. Due to its conceptualization as a new type of fuel, it attracts attention of both businesses and researchers. In this study, statements on big data of the first 250 companies ranked by ISO-500 list for the year 2019 are examined and classified in terms of perceptions of big data and purpose of usage. However, due to limited amount of data obtained, the research has a descriptive and exploratory nature. According to the findings from the qualitative research, it can be stated that most of the big companies, except for a few, are at the stage of development or discussion phase regarding collection, use, and analysis of big data and its’ inclusion in business processes and marketing stages. The limitations of the study include limited amount of texts collected through companies' subjective self-reporting.

Anahtar Kelimeler

big-data ISO-500 list content analysis

Kaynakça

  • Abbasi A., Sarker, S., & Chiang, R.H. (2016). Big data research in information systems: toward an inclusive research agenda, Journal of the Association for Information Systems, 17(2): 1–32.
  • Akter, S., Wamba, S.F., Gunasekaran, A., Dubey, R., & Childe, S.J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113–131.
  • Altunışık, R. (2015). Büyük veri: Fırsatlar kaynağı mı yoksa yeni sorunlar yumağı mı? Yıldız Social Science Review, 1(1), 45–76.
  • Atalay, M., & Çelik, E. (2017). Artificial intelligence and machine learning applications in big data analysis (in Turkish), Mehmet Akif Ersoy University Journal of Social Sciences Institute, 22(9), 155–172.
  • Barbier G., & Liu H. (2011). Data mining in social media. In: Aggarwal C. (eds) Social Network Data Analytics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8462-3_12
  • Beyer, M.A., & Laney, D. (2012). The importance of ‘Big Data: A definition. Gartner, Stamford.
  • Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological and scholarly phenomenon. Information, Communication and Society, 15(5), 662-679.
  • Chen, H., Chiang, R.H.L., & Storey, V.C. (2012). Business intelligence and analytics: From big data to big impact, MIS Quarterly, 36(4), 1165–1188.
  • Chen, J., Chen, Y., Du, X., Li, C., Lu, J., Zhao, S., & Zhou, X. (2013). Big data challenge: a data management perspective. Frontiers of Computer Science, 7(2), 157–164.
  • Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Journal of Mobile Networks and Applications, 19, 171-209.
  • Constantiou, I.D., & Kallinikos, J. (2015). New games, new rules: Big data and the changing context of strategy, Journal of Information Technology, 30(1), 44–57.
  • Doğan, K., & Arslantekin, S. (2016). Big data: Its importance, structure and current status (in Turkish), DTCF Journal, 56(1), 15–36.
  • Driscoll, K. (2012). From punched cards to "Big Data": A social history of database populism, Communication +1: 1(1), Article 4.
  • Floridi, L. (2012). Big data and their epistemological challenge, philosophy and technology, 25(4): 435–437.
  • Gandomi, A. & Haider, M. (2015). Beyond the hype: Big data concepts, methods and analytics, International Journal of Information Management, 35(2), 137–144.
  • Gantz, J., & Reinsel, D. (2012). The Digital universe in 2020: Big data, bigger digital shadows and biggest growth in the far east. IDC iView: 1–16.
  • Gerard, G., Martine R. H., & Alex Pentland, (2014). From the editors: Big data and management, Academy of Management Journal, 57(2), 321–326.
  • Johnson, J., S., Friend, S., B., & Lee, H., S. (2017). Big data facilitation, utilization, and monetization: exploring the 3vs in a new product development process. Journal of Product Innovation Management, 34(5), 640–658.
  • Kitchin, R. (2013). Big data and human geography: opportunities, challenges and risks, dialogues in human geography, 3(3), 262–267.
  • Laney, D. (2001). 3-D Data management: Controlling data volume, velocity and variety, META Group (Gartner) Research Note, 1–4.
  • LaValle, S., Lesser, E., Shockley, R., Hopkins, M., & Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 21-31.
  • Lee, I. (2017). Big data: Dimensions, evolution, impacts and challenges. Business Horizons, 60, 293-303.
  • Liu, Y. (2015). The Journal of Business Forecasting; Flushing, 33(4), 40-42.
  • Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A.H. (2011). Big data: The next frontier for innovation, competition, and productivity, McKinsey Global Institute.
  • McAfee, A. & Brynjolfsson, E. (2012). Big data: the management revolution. Harvard Business Review. 90, 60–68.
  • Opresnik, D. & Taisch, M. (2015). The Value of big data in servitization, International Journal of Production Economics, 165: 174–184.
  • Russom, P. (2011). Big Data Analytics. TDWI Best Practices Report, Fourth Quarter (pp. 1-35).
  • Schöch, C. (2013). Big? Smart? Clean? Messy? Data in the Humanities, Journal of Digital Humanities, 2(3): 2–13.
  • Schroeck, M., Shockley, R., Smart, J., Romero-Morales, D. & Tufano, P. (2012). Analytics: The real-world use of big data, IBM Global Business Services, 1–20.
  • Seddon, J.J., & Currie, W.L. (2017). A model for unpacking big data analytics in high-frequency trading, Journal of Business Research, 70: 300–307.
  • Sharda, R., Delen, D., & Turban, E. (2017), Business Intelligence, Analytics, and Data Science: A Managerial Perspective (4th Edition). Pearson Education, Upper Saddle River, New Jersey.
  • Shi, Y. (2014). Big data: History, current status, and challenges going forward. Bridge 44(4), 6–11.
  • Ularu, E., G., Puican, F., C., Apostu, A., & Velicanu, M. (2012). Perspectives on big data and big data analytics. Database Systems Journal, 3(4), 3-14.
  • Vashisht, P., & Gupta, V. (2015). Big data analytics techniques: A survey, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), Noida, 2015, 264-269, doi: 10.1109/ICGCIoT.2015.7380470.
  • Verma, J., P., Agrawall, S., Patel, B., & Patel, A. (2016). Artificial Intelligence and applications. International Journal on Soft Computing, 5(1), 41-51.
  • Wamba, S.F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study. International Journal Production Economics, 165, 234-246.
  • Wamba, S. F., Gunasekaran, A., Akter, S., Ji-fan Ren, S., Dubey, R., & Childe, S.J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356-365.
  • Wang, Y., Kung, L. & Byrd, T.A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3–13.
  • Xiang, Z. Schwartz, Z., Gardes, J., H., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management. Elsevier Ltd, 44, 120–130. doi: 10.1016/j.ijhm.2014.10.013.
  • Zeng, D., Chen, H., Lusch R., & Li, S. Social media analytics and intelligence, in IEEE Intelligent Systems, 25(6), 13-16, Nov.-Dec. 2010, doi: 10.1109/MIS.2010.151.

Büyük şirketlerin büyük verisi: ISO-500’de listelenen şirketlerin büyük veri kullanımına yönelik bir içerik analizi

Yıl 2020, Sayı: 49, 130 - 145, 16.12.2020

İrge Şener Halil Erman Candar Uzuner

Öz

Adından da anlaşılacağı üzere verinin büyüklüğü konusunda bir fikir veren büyük veri, ardında başka gizemleri de barındırmaktadır. Nitekim büyüklüğünün yanı sıra, büyük verinin hızı ve çeşitliliği de araştırmacılar tarafından öne çıkarılmaktadır. Bu nedenle geleneksel istatistiksel yöntemler ile incelenemeyeceği ileri sürülmektedir. Büyük veri, yeni bir yakıt türü olarak kavramlaştırılması nedeniyle de hem iş dünyasının hem de araştırmacıların dikkatini çekmektedir. Bu çalışmada 2019 yılı için ISO-500 listesinde yer alan ilk 250 şirketin büyük veri konusunda yapmış oldukları açıklamalar, büyük verinin nasıl algılandığı ve şirketlerde kullanım amacı bakımından incelenmiş ve sınıflandırılmıştır. Bununla beraber elde edilen veri miktarının sınırlı olması nedeniyle, araştırma tanımlayıcı ve keşfedici bir nitelik taşımaktadır. Nitel araştırma sonuçlarına göre, büyük şirketlerin birkaçı dışında çoğunun, büyük verilerin toplanması, kullanılması ve analiz edilmesi ile bu verilerin iş süreçleri ve pazarlama aşamalarına dahil edilmesi ile ilgili olarak geliştirme veya düşünce aşamasında olduğu değerlendirilmektedir. Şirketlerin kendileri ile ilgili raporlamalarına yönelik öznel yaklaşımları ile sınırlı miktarda metinlerin toplanması çalışmanın sınırlılıklarını oluşturmaktadır.

Anahtar Kelimeler

büyük veri ISO-500 içerik analizi

Kaynakça

  • Abbasi A., Sarker, S., & Chiang, R.H. (2016). Big data research in information systems: toward an inclusive research agenda, Journal of the Association for Information Systems, 17(2): 1–32.
  • Akter, S., Wamba, S.F., Gunasekaran, A., Dubey, R., & Childe, S.J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113–131.
  • Altunışık, R. (2015). Büyük veri: Fırsatlar kaynağı mı yoksa yeni sorunlar yumağı mı? Yıldız Social Science Review, 1(1), 45–76.
  • Atalay, M., & Çelik, E. (2017). Artificial intelligence and machine learning applications in big data analysis (in Turkish), Mehmet Akif Ersoy University Journal of Social Sciences Institute, 22(9), 155–172.
  • Barbier G., & Liu H. (2011). Data mining in social media. In: Aggarwal C. (eds) Social Network Data Analytics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8462-3_12
  • Beyer, M.A., & Laney, D. (2012). The importance of ‘Big Data: A definition. Gartner, Stamford.
  • Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological and scholarly phenomenon. Information, Communication and Society, 15(5), 662-679.
  • Chen, H., Chiang, R.H.L., & Storey, V.C. (2012). Business intelligence and analytics: From big data to big impact, MIS Quarterly, 36(4), 1165–1188.
  • Chen, J., Chen, Y., Du, X., Li, C., Lu, J., Zhao, S., & Zhou, X. (2013). Big data challenge: a data management perspective. Frontiers of Computer Science, 7(2), 157–164.
  • Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Journal of Mobile Networks and Applications, 19, 171-209.
  • Constantiou, I.D., & Kallinikos, J. (2015). New games, new rules: Big data and the changing context of strategy, Journal of Information Technology, 30(1), 44–57.
  • Doğan, K., & Arslantekin, S. (2016). Big data: Its importance, structure and current status (in Turkish), DTCF Journal, 56(1), 15–36.
  • Driscoll, K. (2012). From punched cards to "Big Data": A social history of database populism, Communication +1: 1(1), Article 4.
  • Floridi, L. (2012). Big data and their epistemological challenge, philosophy and technology, 25(4): 435–437.
  • Gandomi, A. & Haider, M. (2015). Beyond the hype: Big data concepts, methods and analytics, International Journal of Information Management, 35(2), 137–144.
  • Gantz, J., & Reinsel, D. (2012). The Digital universe in 2020: Big data, bigger digital shadows and biggest growth in the far east. IDC iView: 1–16.
  • Gerard, G., Martine R. H., & Alex Pentland, (2014). From the editors: Big data and management, Academy of Management Journal, 57(2), 321–326.
  • Johnson, J., S., Friend, S., B., & Lee, H., S. (2017). Big data facilitation, utilization, and monetization: exploring the 3vs in a new product development process. Journal of Product Innovation Management, 34(5), 640–658.
  • Kitchin, R. (2013). Big data and human geography: opportunities, challenges and risks, dialogues in human geography, 3(3), 262–267.
  • Laney, D. (2001). 3-D Data management: Controlling data volume, velocity and variety, META Group (Gartner) Research Note, 1–4.
  • LaValle, S., Lesser, E., Shockley, R., Hopkins, M., & Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 21-31.
  • Lee, I. (2017). Big data: Dimensions, evolution, impacts and challenges. Business Horizons, 60, 293-303.
  • Liu, Y. (2015). The Journal of Business Forecasting; Flushing, 33(4), 40-42.
  • Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A.H. (2011). Big data: The next frontier for innovation, competition, and productivity, McKinsey Global Institute.
  • McAfee, A. & Brynjolfsson, E. (2012). Big data: the management revolution. Harvard Business Review. 90, 60–68.
  • Opresnik, D. & Taisch, M. (2015). The Value of big data in servitization, International Journal of Production Economics, 165: 174–184.
  • Russom, P. (2011). Big Data Analytics. TDWI Best Practices Report, Fourth Quarter (pp. 1-35).
  • Schöch, C. (2013). Big? Smart? Clean? Messy? Data in the Humanities, Journal of Digital Humanities, 2(3): 2–13.
  • Schroeck, M., Shockley, R., Smart, J., Romero-Morales, D. & Tufano, P. (2012). Analytics: The real-world use of big data, IBM Global Business Services, 1–20.
  • Seddon, J.J., & Currie, W.L. (2017). A model for unpacking big data analytics in high-frequency trading, Journal of Business Research, 70: 300–307.
  • Sharda, R., Delen, D., & Turban, E. (2017), Business Intelligence, Analytics, and Data Science: A Managerial Perspective (4th Edition). Pearson Education, Upper Saddle River, New Jersey.
  • Shi, Y. (2014). Big data: History, current status, and challenges going forward. Bridge 44(4), 6–11.
  • Ularu, E., G., Puican, F., C., Apostu, A., & Velicanu, M. (2012). Perspectives on big data and big data analytics. Database Systems Journal, 3(4), 3-14.
  • Vashisht, P., & Gupta, V. (2015). Big data analytics techniques: A survey, 2015 International Conference on Green Computing and Internet of Things (ICGCIoT), Noida, 2015, 264-269, doi: 10.1109/ICGCIoT.2015.7380470.
  • Verma, J., P., Agrawall, S., Patel, B., & Patel, A. (2016). Artificial Intelligence and applications. International Journal on Soft Computing, 5(1), 41-51.
  • Wamba, S.F., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study. International Journal Production Economics, 165, 234-246.
  • Wamba, S. F., Gunasekaran, A., Akter, S., Ji-fan Ren, S., Dubey, R., & Childe, S.J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356-365.
  • Wang, Y., Kung, L. & Byrd, T.A. (2018). Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations. Technological Forecasting and Social Change, 126, 3–13.
  • Xiang, Z. Schwartz, Z., Gardes, J., H., & Uysal, M. (2015). What can big data and text analytics tell us about hotel guest experience and satisfaction? International Journal of Hospitality Management. Elsevier Ltd, 44, 120–130. doi: 10.1016/j.ijhm.2014.10.013.
  • Zeng, D., Chen, H., Lusch R., & Li, S. Social media analytics and intelligence, in IEEE Intelligent Systems, 25(6), 13-16, Nov.-Dec. 2010, doi: 10.1109/MIS.2010.151.
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular İşletme
Bölüm Makaleler / Articles
Yazarlar

İrge Şener 0000-0002-1876-9411

Halil Erman 0000-0002-2363-1767

Candar Uzuner 0000-0002-1012-6227

Yayımlanma Tarihi 16 Aralık 2020
Gönderilme Tarihi 26 Ekim 2020
Kabul Tarihi 2 Aralık 2020
Yayımlandığı Sayı Yıl 2020 Sayı: 49

Kaynak Göster

APA Şener, İ., Erman, H., & Uzuner, C. (2020). Big data of big companies: A content analysis for how ISO-500 listed firms use big-data. Erciyes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(49), 130-145.
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ERCİYES AKADEMİ | 2021 | sbedergi@erciyes.edu.tr Bu eser Creative Commons Atıf-Gayri Ticari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.