4
This study has some limitations. One of its limitations is that it used a cross-sectional research 5
design. However, necessary measures were taken to reduce common method bias (i.e., 6
randomising items, collecting data in two different waves and employing statistical 7
techniques). This study highlights the influence of big data management capabilities on big 8
data value creation and on employees’ exploratory and exploitative activities. Understanding 9
how to enhance big data management capabilities at both the employee and organisation 10
levels requires specialised research. Initially, a qualitative enquiry could be fruitful in exploring 11
the factors affecting big data management capabilities. Furthermore, as the scope of this 12
study was limited to Chinese MNEs, future research should also consider other developing 13
and underdeveloped economies to enhance understanding and generalisability. Additionally, 14
investigating the moderating effect of demographic factors – which are used by several 15
studies as control variables – is an important research direction which should be considered 16
in future studies. Following Donate and de Pablo (2015) in regard to methodological 17
parsimony, this study did not fully include the control variables, which could be considered in 18
future research. Another interesting line of enquiry for future on this topic is to investigate 19
big data management capabilities at strategic and operational level. Following the strategic 20
management literature strategic level capabilities influence operational level capabilities, and 21
operational level capabilities facilitates the strategic level capabilities to achieve the desired 22
outcomes (Witcher & Chau, 2010). Along with investigating the relationship of big data 23
36 capabilities with value creation, scholars should also explore the ways to enhance these 1
capabilities through different management practices such as data governance. Particularly 2
contractual and relational governance is also suggested by Jannsen et al. (2017). Knowledge 3
in these areas is thin and need specialized research. 4
37
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49
Appendix
1
Big data democratisation capability 1. I have the ability to access big data when it is needed at any given
time.
1 2 3 4 5 6 7
2. I have the ability to understand big data where it is needed. 1 2 3 4 5 6 7
3. The sheer volume of big data creates problems for me to deal with.* 1 2 3 4 5 6 7
4. I can convince senior management to give me access to more databases.
1 2 3 4 5 6 7
5. I have the ability to understand the data of other departments. 1 2 3 4 5 6 7
6. I can use a wide range of big data applications. 1 2 3 4 5 6 7
7. I have the ability to break down data barriers. 1 2 3 4 5 6 7 Big data contextualisation capability
8. I have the ability to interpret big data. 1 2 3 4 5 6 7 9. I can identify contextual clues in big data. 1 2 3 4 5 6 7 10. Based on the data, I can see the connection between individual
customers and their everyday lives. 1 2 3 4 5 6 7
11. Based on the data, I can understand the scenarios that drive
customers to make decisions. 1 2 3 4 5 6 7
12. It is difficult for me to understand the context of big data. 1 2 3 4 5 6 7 Big data experimentation capability
13. I conduct experiments with big data to monitor changes. 1 2 3 4 5 6 7 14. I have the ability to come up with new methods to test big data. 1 2 3 4 5 6 7 15. Trial and error with the data is a routine matter for me. 1 2 3 4 5 6 7 16. For me, data are a scary set of numbers.* 1 2 3 4 5 6 7 17. I do not know how to start experimentation with data.* 1 2 3 4 5 6 7
18. I prefer not to mess with the data.* 1 2 3 4 5 6 7
Big data execution capability
19. I can transform big data insights into actions.
1 2 3 4 5 6 7
20. I often use big data to perform my duties. 1 2 3 4 5 6 7
21. I respond to the data in a timely manner. 1 2 3 4 5 6 7 22. When I observe any abnormality emerging from the data, I react to
the situation in real time. 1 2 3 4 5 6 7
23. I monitor market trends/customer activities through data tools based
on historical and real-time data. 1 2 3 4 5 6 7
50 1
24. Exploiting the large volume of internal data for business growth is
easy for me. 1 2 3 4 5 6 7
25. My data analysis findings often lead to the identification of new
business opportunities. 1 2 3 4 5 6 7
26. I often explore new ways to increase customer willingness to use/pay. 1 2 3 4 5 6 7 27. Based on the data, I often propose future product improvements. 1 2 3 4 5 6 7 28. My data analysis often facilitates innovation processes in the firm. 1 2 3 4 5 6 7
29. My understanding of contextual clues in big data help me to gain a
holistic view of customers. 1 2 3 4 5 6 7
Exploratory activities
30. Searching for new possibilities with respect to products/services,
processes or markets 1 2 3 4 5 6 7
31. Evaluating diverse options with respect to products/services,
processes or markets 1 2 3 4 5 6 7
32. Focussing on the strong renewal of products/services or processes 1 2 3 4 5 6 7
33. Activities requiring some substantial adaptability 1 2 3 4 5 6 7
34. Activities requiring me to learn new skills or knowledge 1 2 3 4 5 6 7 Exploitative activities
35. Activities which clearly fit into existing company policy 1 2 3 4 5 6 7
36. Activities which serve existing (internal) customers with existing
services/products 1 2 3 4 5 6 7
37. Activities on the conduction of which I am clear 1 2 3 4 5 6 7
38. Activities primarily focussed on achieving short-term goals 1 2 3 4 5 6 7
39. Activities which I can properly conduct by using my present