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1 – 10 of over 95000
Article
Publication date: 6 September 2023

Abeer M. Abdelhalim

This study aims to investigate the relationships between big data analytics, management accounting practices and corporate sustainability and, more precisely, the impact of the…

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Abstract

Purpose

This study aims to investigate the relationships between big data analytics, management accounting practices and corporate sustainability and, more precisely, the impact of the integration between big data analytics and management accounting on corporate sustainability performance development.

Design/methodology/approach

A qualitative case study approach is used in this study with multiple collecting data tools as in-depth interviews and observations, in addition to the content analysis used of the annual reports for the year 2021, of Almarai manufacturing corporate (one of the leaders of food and beverage manufacturing corporates in Saudi Arabia and other countries).

Findings

Research findings provide good insights about the significant impact of the effective integration between big data analytics and management accounting on corporate sustainability performance development, big data can assist management accounting to form corporate value-added strategies and activities.

Research limitations/implications

The study is limitedly applied to one manufacturing corporate as a study case; therefore, the findings cannot be generalized. Thus, future research can examine the association between the current study variables with wide-scale applications and with different approaches and in different contexts to enrich the findings. Moreover, future research may focus on the integration between big data analytics and management accounting reports in the meta-verse environment to explore the benefits that corporates could gain from the features and capabilities of meta-verse technology.

Originality/value

There is a research gap regarding the impact of the integration between big data analytics and management accounting practices on corporate sustainability development, as most of the previous studies focused on two variables only of the current study variables; therefore, this study tries to investigate and give important insights about it.

Details

Journal of Financial Reporting and Accounting, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1985-2517

Keywords

Article
Publication date: 28 October 2022

Franziska Franke and Martin R.W. Hiebl

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

2172

Abstract

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.

Details

International Journal of Accounting & Information Management, vol. 31 no. 1
Type: Research Article
ISSN: 1834-7649

Keywords

Open Access
Article
Publication date: 10 May 2022

Simone Fanelli, Lorenzo Pratici, Fiorella Pia Salvatore, Chiara Carolina Donelli and Antonello Zangrandi

This study aims to provide a picture of the current state of art in the use of big data for decision-making processes for the management of health-care organizations.

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Abstract

Purpose

This study aims to provide a picture of the current state of art in the use of big data for decision-making processes for the management of health-care organizations.

Design/methodology/approach

A systematic literature review was carried out. The research uses two analyses: descriptive analysis, describing the evolution of citations; keywords; and the ten most influential papers, and bibliometric analysis, for content evaluation, for which a cluster analysis was performed.

Findings

A total of 48 articles were selected for bibliographic coupling out of an initial sample of more than 5,000 papers. Of the 48 articles, 29 are linked on the basis of their bibliography. Clustering the 29 articles on the basis of actual content, four research areas emerged: quality of care, quality of service, crisis management and data management.

Originality/value

Health-care organizations believe strongly that big data can become the most effective tool for correctly influencing the decision-making processes. Thus, more and more organizations continue to invest in big data analytics, and the literature on this topic has expanded rapidly. This study seeks to provide a comprehensive picture of the different streams of literature existing, together with gaps in research and future perspectives. The literature is mature enough for an analysis to be made and provide managers with useful insights on opportunities, criticisms and perspectives on the use of big data for health-care organizations. However, to date, there is no comprehensive literature review on the big data analysis in health care. Furthermore, as big data is a “sexy catchphrase,” more clarity on its usage may be needed. It represents an important tool to be investigated and its great potential is often yet to be discovered. This study thus sheds light on emerging issues and suggests further research that may be needed.

Article
Publication date: 14 May 2018

Morten Brinch, Jan Stentoft, Jesper Kronborg Jensen and Christopher Rajkumar

Big data poses as a valuable opportunity to further improve decision making in supply chain management (SCM). However, the understanding and application of big data seem rather…

3436

Abstract

Purpose

Big data poses as a valuable opportunity to further improve decision making in supply chain management (SCM). However, the understanding and application of big data seem rather elusive and only partially explored. The purpose of this paper is to create further guidance in understanding big data and to explore applications from a business process perspective.

Design/methodology/approach

This paper is based on a sequential mixed-method. First, a Delphi study was designed to gain insights regarding the terminology of big data and to identify and rank applications of big data in SCM using an adjusted supply chain operations reference (SCOR) process framework. This was followed by a questionnaire-survey among supply chain executives to elucidate the Delphi study findings and to assess the practical use of big data.

Findings

First, big data terminology seems to be more about data collection than of data management and data utilization. Second, the application of big data is most applicable for logistics, service and planning processes than of sourcing, manufacturing and return. Third, supply chain executives seem to have a slow adoption of big data.

Research limitations/implications

The Delphi study is explorative by nature and the questionnaire-survey rather small in scale; therefore, findings have limited generalizability.

Practical implications

The findings can help supply chain managers gain a clearer understanding of the domain of big data and guide them in where to deploy big data initiatives.

Originality/value

This study is the first to assess big data in the SCOR process framework and to rank applications of big data as a mean to guide the SCM community to where big data is most beneficial.

Details

The International Journal of Logistics Management, vol. 29 no. 2
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 20 June 2020

Alberto Sardi, Enrico Sorano, Valter Cantino and Patrizia Garengo

Current literature recognised big data as a digital revolution affecting all organisational processes. To obtain a competitive advantage from the use of big data, an efficient…

2318

Abstract

Purpose

Current literature recognised big data as a digital revolution affecting all organisational processes. To obtain a competitive advantage from the use of big data, an efficient integration in a performance measurement system (PMS) is needed, but it is still a “great challenge” in performance measurement research. This paper aims to review the big data and performance measurement studies to identify the publications’ trends and future research opportunities.

Design/methodology/approach

The authors reviewed 873 documents on big data and performance carrying out an extensive bibliometric analysis using two main techniques, i.e. performance analysis and science mapping.

Findings

Results point to a significant increase in the number of publications on big data and performance, highlighting a shortage of studies on business, management and accounting areas, and on how big data can improve performance measurement. Future research opportunities are identified. They regard the development of further research to explain how performance measurement field can effectively integrate big data into a PMS and describe the main themes related to big data in performance measurement literature.

Originality/value

This paper gives a holistic view of big data and performance measurement research through the inclusion of numerous contributions on different research streams. It also encourages further study for developing concrete tools.

Details

Measuring Business Excellence, vol. 27 no. 4
Type: Research Article
ISSN: 1368-3047

Keywords

Open Access
Article
Publication date: 21 August 2019

Shaikh Shamim Hasan, Yue Zhang, Xi Chu and Yanmin Teng

Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast…

2922

Abstract

Purpose

Forest as a vital natural resource in China plays an irreplaceable important role in safeguarding ecological security and human survival and development. Due to the vast territory, huge population and widespread forest landscape of China, forest management is a complex system involving massive data and various management activities. To effectively implement sustainable forest management, the big data technology has been utilized to analyze China’s forestry resources. Thus, the purpose of this paper is to clarify the role of big data technology in China’s forest management.

Design/methodology/approach

In this paper, the authors revisited the roles of big data in forest ecosystem monitoring, forestry management system development, and forest policy implementation.

Findings

It demonstrates that big data technology has a great potential in forest ecosystem protection and management, as well as the government’s determination for forest ecosystem protection. However, to deepen the application of big data in forest management, several challenges still need to be tackled.

Originality/value

Thus, enhancing modern science and technology to improve big data, cloud computing, and information technologies and their combinations will contribute to tackle the challenges and achieve wisdom of forest management.

Details

Forestry Economics Review, vol. 1 no. 1
Type: Research Article
ISSN: 2631-3030

Keywords

Article
Publication date: 6 August 2020

Qasim Ali Nisar, Nadia Nasir, Samia Jamshed, Shumaila Naz, Mubashar Ali and Shahzad Ali

This study is undertaken to examine the antecedents and role of big data decision-making capabilities toward decision-making quality and environmental performance among the…

3262

Abstract

Purpose

This study is undertaken to examine the antecedents and role of big data decision-making capabilities toward decision-making quality and environmental performance among the Chinese public and private hospitals. It also examined the moderating effect of big data governance that was almost ignored in previous studies.

Design/methodology/approach

The target population consisted of managerial employees (IT experts and executives) in hospitals. Data collected using a survey questionnaire from 752 respondents (374 respondents from public hospitals and 378 respondents from private hospitals) was subjected to PLS-SEM for analysis.

Findings

Findings revealed that data management challenges (leadership focus, talent management, technology and organizational culture for big data) are significant antecedents for big data decision-making capabilities in both public and private hospitals. Moreover, it was also found that big data decision-making capabilities played a key role to improve the decision-making quality (effectiveness and efficiency), which positively contribute toward environmental performance in public and private hospitals of China. Public hospitals are playing greater attention to big data management for the sake of quality decision-making and environmental performance than private hospitals.

Practical implications

This study provides guidelines required by hospitals to strengthen their big data capabilities to improve decision-making quality and environmental performance.

Originality/value

The proposed model provides an insight look at the dynamic capabilities theory in the domain of big data management to tackle the environmental issues in hospitals. The current study is the novel addition in the literature, and it identifies that big data capabilities are envisioned to be a game-changer player in effective decision-making and to improve the environmental performance in health sector.

Details

Journal of Enterprise Information Management, vol. 34 no. 4
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 25 August 2020

Xinyi Zhang, Yanni Yu and Ning Zhang

This study aims to provide a literature review and bibliometric analysis of sustainable supply chain management using big data. We reviewed the literature on sustainable supply…

2136

Abstract

Purpose

This study aims to provide a literature review and bibliometric analysis of sustainable supply chain management using big data. We reviewed the literature on sustainable supply chain management under big data from 2012 to 2019 and extracted 777 articles.

Design/methodology/approach

We conducted quantitative analysis and data network visualization of the chosen literature, including authors, journals, countries, research institutions and citations.

Findings

We discovered that the development of this interdisciplinary field has gained increasing popularity among researchers around the world, such as China and the US publishing the most articles and Western states having more cooperation, which indicates this research topic is growing in significance globally.

Originality/value

Scientific and technological revolutions such as big data have been incorporated in various industries. Modern supply chain management has also been combined with the advances in data science to achieve sustainability goals. No studies have reviewed the sustainable supply chain management based on big data. This study fills this gap.

Details

Journal of Enterprise Information Management, vol. 34 no. 1
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 17 December 2018

David Egan and Natalie Claire Haynes

The purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing…

2127

Abstract

Purpose

The purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions.

Design/methodology/approach

A three-stage iterative thematic analysis technique based on the approaches of Braun and Clarke (2006) and Nowell et al. (2017) and using different research instruments to collect and analyse qualitative data at each stage was used to develop an explanatory framework.

Findings

Whilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe that their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics.

Practical implications

The less a manager believes in the ability of those systems to interpret these data, the more they perceive gut instinct to increase the reliability of their decision making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information and knowledge that they believe leads to revenue growth.

Originality/value

There is currently little research explicitly investigating the role of big data in decision making within hotel revenue management and certainly even less focussing on decision making at property level and the perceptions of managers of the value of big data in increasing the reliability of revenue and pricing decision making.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 29 August 2019

Muhammad Saleem Sumbal, Eric Tsui, Irfan Irfan, Muhammad Shujahat, Elaine Mosconi and Murad Ali

The purpose of this study is twofold: to investigate the role of big data in firms’ co-knowledge and value creation and to understand the underlying drivers behind value creation…

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Abstract

Purpose

The purpose of this study is twofold: to investigate the role of big data in firms’ co-knowledge and value creation and to understand the underlying drivers behind value creation through big data in the oil and gas industry by underscoring the role of firms’ capabilities, trends and challenges.

Design/methodology/approach

Following an inductive approach, semi-structured interviews were conducted with senior managers and analysts working in oil and gas companies across eight countries. The data collected from these key informants were then analysed using the qualitative data analysis software ATLAS.ti.

Findings

Value creation through big data is an important factor for enhancing performance. It has a positive impact on both tangible (organisational performance) and intangible (societal) aspects depending on the context. Oil and gas companies understand the importance of big data to creating value in their operations. However, implementing and using big data has been problematic. In this study, a framework was developed to show that factors such as the shortage of data experts, poor data quality, the risk of cyber-attacks and unsupportive organisational cultures impede its implementation and utilisation.

Research limitations/implications

The findings from this study have implications for managers and executives implementing big data and creating value across various data-intensive industries. The research findings, are contextual, however, and should be applied cautiously.

Originality/value

This study contributes to the value creation literature in the big data context. The findings identify the key areas to be considered for the effective implementation and utilisation of big data in the oil and gas sector. This study addresses a broad but under-explored issue (i.e. knowledge creation from big data and its implementation) and strengthens the academic debate within this research stream.

Details

Journal of Knowledge Management, vol. 23 no. 8
Type: Research Article
ISSN: 1367-3270

Keywords

1 – 10 of over 95000