Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view

TLDR: It is suggested that big data management challenges are the key antecedents of big data decision-making capability and the latter is vital for big data Decision-making quality.

About: This article is published in Information & Management.The article was published on 2019-09-01 and is currently open access. It has received 146 citations till now. The article focuses on the topics: Big data & Talent management.

Figures

Figure 1. The conceptual framework 2

Table 1. Convergent validity 15

Table 3. Path analysis

Figure 2. Path analysis2

Table 2. Discriminant validity 10

Table 4. Formation of the construct of big data decision-making capability 2

Frequently asked questions

Q1. What are the contributions in this paper?

3 This study examines the antecedents and influence of big data decision-making capabilities 4 on decision-making quality among Chinese firms. The authors propose that such capabilities are 5 influenced by big data management challenges such as leadership, talent management, 6 technology, and organisational culture. Findings suggest that big data 9 management challenges are the key antecedents of big data decision-making capability. 10 Furthermore, the latter is vital for big data decision-making quality. 

Q2. What are the future works in this paper?

This study also presents some limitations and future research suggestions. It is a cross 12 sectional study with a single data source ; thus, future research could adopt a longitudinal 13 research design and examine the variables and their associations across both developed and 14 emerging markets. Thus, future studies need to integrate institutions-based view 19 with DCs and examine the value creation through big data across different range of firms such 20 as SMEs, family-owned enterprises, business groups, state-owned enterprises and 21 multinational enterprises. Because of its 23 quantitative research design and deductive approach, this study did not explore the 1 phenomenon in depth ; thus, future research could explore the given context in more detail 2 through a qualitative mode of enquiryねi. e. to determine how big data management 3 challenges enhance big data decision-making capabilities and quality. 

Q3. What are the main factors influencing big data decision making quality?

Janssen et al. (2017) argued that the factors influencing big data decision-2 making quality are contractual and relational governance, big data analytics capabilities, 3 knowledge exchange, collaboration, process integration and standardisation, routinising and 4 standardisation, flexible infrastructure, big data source quality, and decision-maker quality. 

Q4. What is the role of leadership in the development of a DC?

Leadership is an important influencer of 2 DC development, which is usually achieved through interactions and complementarities 3 among processes, individuals and structures (Felin, Foss, Heimeriks, & Madsen, 2012). 

Q5. How many items were used in the study?

Because of the lack of an established scale in the 20 existing literature, the items to measure the variables used in this study were developed by 21 the authors, with the exception of four, measuring decision-making effectiveness, that were 22adopted from Visinescu et al. (2017). 

Q6. What are the main reasons why decision makers should have the ability to interpret the outcomes of big data?

to enhance quality data-4 driven decision-making capabilities, decision makers should have the ability to interpret the 5 outcomes of big data analysis and understand their implications (Janssen et al., 2017). 

Q7. how many technologies can be used to gather big data?

Big data can be gathered by many technological 12 meansねe.g. ubiquitous information sensing devices, aerial sensor technologies, software 13 logs identification readers etc. 

Q8. What is the view of the dynamic capabilities (DCs)?

The dynamic capabilities (DCs) view suggests that organisations should be capable of 2 renewing and recreating their strategic capabilities to meet the requirements of changing 3 environments (Teece et al., 1997; Teece, 2007; Linden & Teece, 2018). 

Q9. Why was it excluded from the big data decision-making capabilities construct?

The big data analytics capabilities 13 variable was excluded from the big data decision-making capabilities construct because it had 14 been used as an independent capability in a number of existing studies (e.g., Gupta & George, 15 2016). 

Q10. What are the main reasons why companies are using big data to create value?

companies based in emerging economies, 11 including Chinese firms, are also utilising big data to create value (Zeng & Glaister, 2018). 

Q11. How can the use of big data be enhanced?

Keeping in view the important role of harnessing talent, McAfee et al 9 (2012) suggested that the use of big data can be enhanced by appropriate talent 10 management. 

Q12. How many ways have big data changed?

Big data have changed the 15 ways in which organisations handle data (Oliveira, Fuerlinger, & Kranzlmller, 2012); larger 16 storage and higher speeds are required to gather, store and access data (Chen & Zhang, 2014). 

Q13. how many countries are in the race for the development of AI capabilities?

Many other countries, both developing 19 and developed, are in the race for the development of AI capabilities linked to big data; thus, 20 effective talent management is vital for organisations to reap the benefits from big data and 21 digital technologies. 

Q14. How does the author argue that big data is of particular interest?

The authors argue that this environment is of particular 18 interest as it represents a strong contender to dominate the AI industry, which is powered by 19 big data.