The role of the social and technical factors in creating business value from big data analytics: A meta-analysis

Oesterreich, Thuy Duong; Anton, Eduard; Teuteberg, Frank; Dwivedi, Yogesh K.

doi:10.1016/j.jbusres.2022.08.028

Cited by 48 publications

(26 citation statements)

References 156 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This seems all the more relevant in situations in which organizations have already amassed big data (and thus command a high Breadth of big data sources ), but not yet managed to tease out high-quality information from such data and thus need to revert to skilled humans to make sense of large volumes of big data. Our findings thus add to the more recent empirical literature examining under which conditions and on which paths big data usage may end up in increased organizational decision quality (Ghasemaghaei and Calic, 2019; Oesterreich et al , 2022a, 2022b). In particular, we add to this literature a previously understudied group of employees: management accountants.…”

Section: Discussionsupporting

confidence: 62%

“…Prior research indicates that the relationship between aspects of big data and decision quality may be influenced by further organization-level factors (Ghasemaghaei, 2019;Janssen et al, 2017). One of these factors is the influence of an organization's overall human skills (Coyne et al, 2018;Gupta and George, 2016;Oesterreich et al, 2022aOesterreich et al, , 2022b, which have already been identified as potentially directly contributing to the quality of decisions based on big data (Akter et al, 2016). However, here too, prior research has assumed a direct Big data and decision quality effect of such skills on big data capabilities, but has not investigated how such skills may interact with more technical aspects of big data such as the breadth and the quality of big data.…”

Section: Moderating Role Of Management Accountants' Data Analytics Sk...mentioning

confidence: 99%

“…Various studies have already highlighted the importance of appropriate big data capabilities (Akter et al, 2016;Gupta and George, 2016;Janssen et al, 2017;Popovic et al, 2016). For example, two recent metaanalyses by Oesterreich et al (2022aOesterreich et al ( , 2022b found that employees' analytics skills are among the most important factors in creating business value from big data and driving organizational performance. However, many studies have only generally mentioned the importance of having proper employee skills available in a given organization for reaping the benefits of big data, but have neither presented details on which group of employees are specifically prone to benefit from big data skills nor identified which exact skills may be needed.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Big data and decision quality: the role of management accountants’ data analytics skills

Franke

Hiebl²

2022

IJAIM

View full text Add to dashboard Cite

Purpose Existing research on the relationship between big data and organizational decision quality is still few and far between, and what does exist often assumes direct effects of big data on decision quality. More recent research indicates that such direct effects may be too simplistic, and in particular, an organization’s overall human skills are often not considered sufficiently. Inspired by the knowledge-based view, we therefore propose that interactions between three aspects of big data usage and management accountants’ data analytics skills may be key to reaching high-quality decisions. The purpose of this study is to test these predictions based on a survey of US firms. Design/methodology/approach The authors draw on survey data from 140 US firms. This survey has been conducted via MTurk in 2020. Findings The results of the study show that the quality of big data sources is associated with higher perceived levels of decision quality. However, according to the results, the breadth of big data sources and a data-driven culture only improve decision quality if management accountants’ data analytics skills are highly developed. These results point to the important, but so far unexamined role of an organization’s management accountants and their skills for translating big data into high-quality decisions. Practical implications The present study highlights the importance of an organization’s human skills in creating value out of big data. In particular, the findings imply that management accountants may need to increasingly draw on data analytics skills to make the most out of big data for their employers. Originality/value This study is among the first, to the best of the authors’ knowledge, to provide empirical proof of the relevance of an organization’s management accountants and their data analytics skills for reaching desirable firm-level outcomes. In addition, this study thus adds to the further advancement of the knowledge-based view by providing evidence that in contemporary big-data environments, interactions between tacit and explicit knowledge seem crucial for driving desirable firm-level outcomes.

show abstract

Section: Discussionsupporting

confidence: 62%

Section: Moderating Role Of Management Accountants' Data Analytics Sk...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Big data and decision quality: the role of management accountants’ data analytics skills

Franke

Hiebl²

2022

IJAIM

View full text Add to dashboard Cite

show abstract

“…We consider that the use of BDA can be useful in this respect by helping identify such use cases. Recent studies have shown that BDA can be employed to: support organizations to prioritise and coordinate activities on specific projects (Dennehy et al, 2021 ; Zamani et al, 2021 ), sense and respond to changes in the business environment (Barlette & Baillette, 2022 ; Zamani et al, 2022 ), and create business value (Oesterreich et al, 2022 ; Papadopoulos et al, 2022 ). We thus posit that BDA can be both the instrument that helps identify a problem and be part of the solution that addresses that problem in the context of supply chain resilience.…”

Section: Current Challengesmentioning

confidence: 99%

Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review

et al. 2022

View full text Add to dashboard Cite

Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to significantly improve resilience of supply chains and to facilitate more effective management of supply chain resources. Despite such potential benefits and the increase in popularity of AI and BDA in the context of supply chains, research to date is dispersed into research streams that is largely based on the publication outlet. We curate and synthesise this dispersed knowledge by conducting a systematic literature review of AI and BDA research in supply chain resilience that have been published in the Chartered Association of Business School (CABS) ranked journals between 2011 and 2021. The search strategy resulted in 522 studies, of which 23 were identified as primary papers relevant to this research. The findings advance knowledge by (i) assessing the current state of AI and BDA in supply chain literature, (ii) identifying the phases of supply chain resilience (readiness, response, recovery, adaptability) that AI and BDA have been reported to improve, and (iii) synthesising the reported benefits of AI and BDA in the context of supply chain resilience.

show abstract

“…The DC view helps to comprehend firms' strategic direction and response to external changes through an adaptive process. Second, this study also attempts to answer recent calls (Ghasemaghaei, 2021;Oesterreich et al, 2022) to understand how BDA is associated with firm performance outcomes. Particularly, we focus upon the firms' internal activitiesmarketing ambidexterity (exploration and exploitation)as an underlying mechanism that has been ignored in the extant literature.…”

Section: Introductionmentioning

confidence: 99%

Big data analytics-enabled dynamic capabilities and firm performance: examining the roles of marketing ambidexterity and environmental dynamism

Saeed

Adıgüzel

Shafique

et al. 2023

BPMJ

View full text Add to dashboard Cite

PurposeDrawing from dynamic capability (DC) theory, this study aims to investigate how big data analytics (BDA)-enabled dynamic capabilities (DCs) prompt firm performance. This study proposes that BDA-enabled DCs lead firms toward simultaneous exploration and exploitation of new knowledge about markets and products (i.e. marketing ambidexterity) which in turn improves firms' market and financial performance. This study also examines if environmental dynamism strengthens the aforementioned relationship.Design/methodology/approachThis study uses survey questionnaire and data were collected in the form of two heterogeneous samples from Turkey and Pakistan. Partial least square-structural equation modeling (PLS-SEM) was used to test the hypotheses.FindingsResults reveal that BDA-enabled DCs positively affect both dimensions of marketing ambidexterity (exploration and exploitation). Marketing exploration and exploitation have positive effects on firms' market and financial performance. Results also demonstrate that environmental dynamism moderates the link between BDA-enabled DCs and firms' marketing exploitation. The moderating effect for BDA-enabled DCs and firms' marketing exploration was not consistent across both samples.Research limitations/implicationsThis study contributes to the literature of BDA and marketing ambidexterity in the light of DC theory in a way that when and how the marketing ambidexterity, derived from BDA-enabled DCs, has a positive impact on firm performance. Moreover, findings imply that the development and enhancement of BDA-enabled DCs facilitate firms to calibrate marketing exploitation and exploration to seek new knowledge about markets and products and using such knowledge to achieve superior performance.Originality/valueThe novelty of present study is development of dynamic capabilities-based framework which sheds light on the role of big data for sensing, seizing and (re)configuring firms' resources to develop marketing ambidextrous capabilities in order to stay successful. From methodological perspective, this study uses two heterogeneous samples to assess robustness of results for ensuring greater generalizability and theoretical resonance.

show abstract

The role of the social and technical factors in creating business value from big data analytics: A meta-analysis

Cited by 48 publications

References 156 publications

Big data and decision quality: the role of management accountants’ data analytics skills

Big data and decision quality: the role of management accountants’ data analytics skills

Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review

Big data analytics-enabled dynamic capabilities and firm performance: examining the roles of marketing ambidexterity and environmental dynamism

Contact Info

Product

Resources

About