Connecting big data management capabilities with employee ambidexterity in Chinese multinational enterprises through the mediation of big data value creation at the employee level

Shamim, Saqib; Zeng, Jing; Choksy, Umair Shafi; Shariq, Syed Muhammad

doi:10.1016/j.ibusrev.2019.101604

Cited by 48 publications

(47 citation statements)

References 101 publications

(139 reference statements)

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“…At present, most of the areas of business are linked to big data. It has significant influence on various perspectives of business such as business process management, human resources management, R&D management [8,63], business analytics [19,26,42,59,63], B2B business process, marketing, and sales [30,39,53,58], industrial manufacturing process [7,15,40], enterprise's operational performance measurement [20,69,81], policy making [2], supply chain management, decision, and performance [4,38,64], and so other business arenas.…”

Section: Literature Reviewmentioning

confidence: 99%

“…These are essential to realize the smart manufacturing process. Shamim et al [69] argued that employee ambidexterity is important because employees' big data management capabilities and ambidexterity are crucial for EMMNEs to manage the demands of global users. Also big data appeared as a frontier of the opportunity in improving firm performance.…”

Section: Literature Reviewmentioning

confidence: 99%

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Current landscape and influence of big data on finance

2020

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In the age of technological innovation, various types of data are available with the advance of information technologies, and data is seen as one of the most valuable commodities in managing automation systems [13, 68]. In this sense, financial markets and technological evolution have become related to every human activity in the past few decades. Big data technology has become an integral part of the financial services industry and will continue to drive future innovation [12]. Financial innovations are also considered the fastest emerging issues in financial services. More specifically, they cover a variety of financial businesses such as online peer-to-peer lending, crowd-funding platforms, SME finance, wealth management and asset management platforms, trading management, crypto-currency, money/remittance transfer, mobile payments platforms, and so on. All of these services create thousands of pieces of data every day. Therefore,

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Current landscape and influence of big data on finance

2020

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“…At present, most of the business areas are connected to big data. Big data has a critical effect on different dimensions of businesses, for example, in terms of human resources management, research, and development [27,28]; management processes [27,[29][30][31]; business to business processes, advertising, and marketing [32,33]; mechanical assembling measures [34][35][36]; enterprises' operational performance [36,37]; policy-making [38]; and supply chain management [38,39]. In particular, Rabhi, Falih [27] referenced big data as a noteworthy factor of business measure management and HR cycles to help in the decision-making process.…”

Section: Literature Reviewmentioning

confidence: 99%

Identifying Big Data’s Opportunities, Challenges, and Implications in Finance

et al. 2020

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One of the latest innovations in business and technology is the use of big data, as daily data are generated by billions of events. The big data issue is now considered in the accountants and finance professionals’ field as one of the most important sources for the analysis of financial products and services. This study is very innovative, with our research aiming to identify the opportunities, challenges, and implications of big data in the finance area. It is our purpose to find competitive advantages in terms of the extent to which big data brings visible benefits, also pointing out the challenges that a company may face in this field, such as cases of customers’ data security or customer satisfaction processes. The identification of this kind of dynamics allows us to draw conclusions on the advantages of big data based on these analyses and big data’s deep impact on finance. In particular, big data is now commonly used by financial institutions and banks for analytical purposes in financial market contexts. We conducted an exploratory survey of the existing literature to highlight such connections. In the last part of our study, we also propose directions for future research.

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“…In 2019, Saqib Shamim et al [1] worked on the connection of big data management abilities by means of employee investigative and manipulative behavior at the individual level. In addition, it examines the arbitrate function of big data value formation in the relationship of big data management abilities using investigative and manipulative activities.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Big Data needs specialized tools for their treatment to produce significant consequences which, in lesser volumes, could hardly be attained. The main aim ought not to be only in managing with a large amount of data, yet on the likelihood that these data present in the expectation of making knowledge and information which can create companies and public entities increasingly series that will let them present enhanced services for citizens and consumers [1].…”

Section: Introductionmentioning

confidence: 99%

An overview of Big Data Management and its Applications

G.Gokulkumari¹

2020

JNACS

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From a few years, big data has been growing and fashioned excitement. However, it is rather standard that 3V's (velocity, volume, and variety) are further than a more systematic debate of data method. Big Data 'is corresponding to undersized data. Big data represented in diverse algorithms, techniques, tools and architectures. It requires improving an improved manner to resolve novel issues and old issues. Moreover, this paper presents identify explanation themes up-andcoming in management studies and expand an incorporated model to relate the multiple courses of research in areas of operations, organization, information management, marketing, and other appropriate fields. Additionally, this paper contributes to be a helpful show to challenges and explanation in big data management and a reference point for forthcoming works on big data management.

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Connecting big data management capabilities with employee ambidexterity in Chinese multinational enterprises through the mediation of big data value creation at the employee level

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Cited by 48 publications

References 101 publications

Current landscape and influence of big data on finance

Current landscape and influence of big data on finance

Identifying Big Data’s Opportunities, Challenges, and Implications in Finance

An overview of Big Data Management and its Applications

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