Xiaohong Liu, Ruiqing Sun, Shiyun Wang and Yenchun Jim Wu
In recent years, the rapid growth of big data has presented immense potential for business applications as well as raised great interest from academia. In response to this…
Abstract
Purpose
In recent years, the rapid growth of big data has presented immense potential for business applications as well as raised great interest from academia. In response to this emerging phenomenon, the purpose of this paper is to provide a comprehensive literature review of big data.
Design/methodology/approach
A bibliometric method was used to analyze the articles obtained from the Scopus database published between 2013 and 2018. A sample size of 4,070 articles was evaluated using SciVal metrics.
Findings
The analysis revealed an array of interesting findings as follows: the number of publications related to big data increased steadily over the past six years, though the rate of increase has slowed since 2014; the scope of big data research is quite broad in regards to both research domains and countries; despite a large volume of publications, the overall performance of big data research is not well presented as measured by the field-weighted citation impact metric; collaboration between different institutions, particularly in the form of international collaboration and academic–corporate collaboration, has played an important role in improving the performance of big data research.
Originality/value
To the best of the authors’ knowledge, this is the first study to provide a holistic view of the big data research. The insights obtained from the analysis are instrumental for both academics and practitioners.
Details
Keywords
Xiaohong Liu, Ying Kei Tse, Shiyun Wang and Ruiqing Sun
Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This…
Abstract
Purpose
Organisational learning plays a critical role for firms to keep abreast of a supply chain environment filled with volatility, uncertainty, complexity and ambiguity (VUCA). This study investigates the extent to which supply chain learning (SCL) affects operational resilience under such circumstances.
Design/methodology/approach
This study developed a research framework and underlying hypotheses based on SCL and information processing theory (IPT). An empirical test was carried out using secondary data derived from the “Supply Chain Policy” launched by the Chinese government and two large related conferences.
Findings
SCL positively relates to operational resilience, and several moderators influence the relationship between them. The authors argue that digital-technological diversity could weaken the role of SCL in operational resilience, whereas customer concentration, and participating in a pilot programme could enhance the effect of SCL.
Practical implications
Firms should embrace the power of SCL in building resilience in the VUCA era. Meanwhile, they should be cautious of a digital-technological diversification strategy, appraise the customer base profile and proactively engage in pilot programmes.
Originality/value
This research develops the SCL construct further in the context of China and empirically measures its power on operational resilience using a unique dataset. This contributes to the theorisation of SCL.