2017
DOI: 10.1108/jkm-12-2016-0522
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Big data investments in knowledge and non-knowledge intensive firms: what the market tells us

Abstract: Purpose This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not. Design/methodology/approach This study is based on an event study using data from two stock markets in China. Findings The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included … Show more

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Cited by 31 publications
(20 citation statements)
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“…These capabilities allow firms to not only excel in forecasting, production and quality control management but also provide access to novel information for improved decision-making to gain a competitive advantage. The association between innovation performancemeasured by the number of patent applicationspatent quality and technological investments and BDA has been a cumbersome issue, as the quantification of the amount of the big data used by organizations is challenging (Zhang et al, 2017). However, previous studies used a wide range of measuresincluding information on investments for implementing big data, the size of data analyzed and patents using BDAto investigate these associations (Braganza et al, 2017).…”
Section: Impact Of Big Data Analytics On Patent Applicationsmentioning
confidence: 99%
“…These capabilities allow firms to not only excel in forecasting, production and quality control management but also provide access to novel information for improved decision-making to gain a competitive advantage. The association between innovation performancemeasured by the number of patent applicationspatent quality and technological investments and BDA has been a cumbersome issue, as the quantification of the amount of the big data used by organizations is challenging (Zhang et al, 2017). However, previous studies used a wide range of measuresincluding information on investments for implementing big data, the size of data analyzed and patents using BDAto investigate these associations (Braganza et al, 2017).…”
Section: Impact Of Big Data Analytics On Patent Applicationsmentioning
confidence: 99%
“…The next step was to assess the adequacy of the survey data using the Kaiser-Meyer-Olkin (KMO) and Bartlett's test of specificity for squared correlation between variables [26,29]. Following Tabachnick and Fidell [25], the KMO with a value close to 1 relates to relative compactness, distinct and reliable at a minimum value of 0.05 [27].…”
Section: Methodsmentioning
confidence: 99%
“…Therefore, big data is an important input or resource for knowledge creation (Côrte‐Real, Oliveira, & Ruivo, 2017). This knowledge can then be transferred among employees and be used for decision making (Zhang et al, 2017). Consequently, from an RBV standpoint, big data may be treated as an important organisational resource (Côrte‐Real et al, 2017; Kwon, Lee, & Shin, 2014; Opresnik & Taisch, 2015; Wamba et al, 2017).…”
Section: Conceptual Backgroundmentioning
confidence: 99%
“…Increasing the volume of data elevates knowledge generation potential (Ghasemaghaei, 2019; Intezari & Gressel, 2017; Pauleen, 2017). This is especially true if firms integrate multiple data sources (Arora & Rahman, 2016; Baboo & Kumar, 2013; Zhang et al, 2017). It also means that more effort is likely invested in generating knowledge from voluminous data compared to lower‐volume data and that sharing such knowledge may be more effortful (Jagadish et al, 2014; Shollo & Galliers, 2016).…”
Section: Hypotheses Developmentmentioning
confidence: 99%
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