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Article
Publication date: 2 May 2022

Alaa A. Qaffas, Aboobucker Ilmudeen, Najah Kalifah Almazmomi and Ibraheem Mubarak Alharbi

The emerging attention in big data has led businesses to improve big data analytics talent capability to enrich firm performance. The big data capability pays off for some…

1778

Abstract

Purpose

The emerging attention in big data has led businesses to improve big data analytics talent capability to enrich firm performance. The big data capability pays off for some companies but not for all, and it appears that very few have achieved a big impact through big data. Rooted in the latest literature on the knowledge-based view, IT capability, big data talent capability and business intelligence, this study aims to examine how big data talent capability impact on business intelligence infrastructure to achieve firm performance.

Design/methodology/approach

The primary survey data of 272 IT managers and big data analysts from Chinese firms was analyzed by using the structural equation modeling and partial least squares (Smart PLS 3.0). The analysis uncovers a positive and significant relationship in the proposed model.

Findings

The finding shows that the big data analytics talent capability positively impacts on business intelligence infrastructure that in turn directs to achieve firm financial and marketing performance.

Originality/value

This study theorized on the multitheoretic lenses, and findings suggest the managers and industry practitioners to develop business intelligence infrastructure capabilities from big data analytics talent capability.

Details

foresight, vol. 25 no. 3
Type: Research Article
ISSN: 1463-6689

Keywords

Open Access
Article
Publication date: 20 July 2021

Rosita Capurro, Raffaele Fiorentino, Stefano Garzella and Alessandro Giudici

The purpose of this paper is to analyze, from a dynamic capabilities perspective, the role of big data analytics in supporting firms' innovation processes.

8065

Abstract

Purpose

The purpose of this paper is to analyze, from a dynamic capabilities perspective, the role of big data analytics in supporting firms' innovation processes.

Design/methodology/approach

Relevant literature is reviewed and critically assessed. An interpretive methodology is used to analyze empirical data from interviews of big data analytics experts at firms within digitally related sectors.

Findings

This study shows how firms leverage big data to gain “richer” and “deeper” data at the inter-sections between the digital and physical worlds. The authors provide evidence for the importance of counterintuitive strategies aimed at developing innovative products, services or solutions with characteristics that may initially diverge, even significantly, from established customer/user needs.

Practical implications

The authors’ findings offer insights to help practitioners manage innovation processes in the physical world while taking investments in big data analytics into account.

Originality/value

The authors provide insights into the evolution of scholarly research on innovation directed toward opportunities to create a competitive advantage by offering new products, services or solutions diverging, even significantly, from established customer demand.

Details

European Journal of Innovation Management, vol. 25 no. 6
Type: Research Article
ISSN: 1460-1060

Keywords

Article
Publication date: 29 November 2018

Yudi Fernando, Ramanathan R.M. Chidambaram and Ika Sari Wahyuni-TD

The purpose of this paper is to investigate the effects of Big Data analytics, data security and service supply chain innovation capabilities on services supply chain performance.

4462

Abstract

Purpose

The purpose of this paper is to investigate the effects of Big Data analytics, data security and service supply chain innovation capabilities on services supply chain performance.

Design/methodology/approach

The paper draws on the relational view of resource-based theory to propose a theoretical model. The data were collected through survey of 145 service firms.

Findings

The results of this study found that the Big Data analytics has a positive and significant relationship with a firm’s ability to manage data security and a positive impact on service supply chain innovation capabilities and service supply chain performance. This study also found that most service firms participating in this study used Big Data analytics to execute existing algorithms faster with larger data sets.

Practical implications

A main recommendation of this study is that service firms empower a chief data officer to establish the data needed and design the governance of data in the company to eliminate any security issues. Data security was a concern if a firm did not have ample data governance and protection as the information was shared among members of service supply chain networks.

Originality/value

Big Data analytics are a useful technology tool to forecast market preference based on open source, structured and unstructured data.

Details

Benchmarking: An International Journal, vol. 25 no. 9
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 7 June 2022

Qasim Ali Nisar, Shahbaz Haider, Irfan Ameer, Muhammad Sajjad Hussain, Sonaina Safi Gill and Awan Usama

Big data analytics capabilities are the driving force and deemed as an operational excellence approach to improving the green supply chain performance in the post COVID-19…

1255

Abstract

Purpose

Big data analytics capabilities are the driving force and deemed as an operational excellence approach to improving the green supply chain performance in the post COVID-19 situation. Motivated by the COVID-19 epidemic and the problems it poses to the supply chain's long-term viability, this study used dynamic capabilities theory as a foundation to assess the imperative role of big data analytics capabilities (management, talent and technological) toward green supply chain performance.

Design/methodology/approach

This study was quantitative and cross-sectional. Data were collected from 374 executives through a survey questionnaire method by applying an appropriate random sampling technique. The authors employed PLS-SEM to analyze the data.

Findings

The findings revealed that big data analytics capabilities play a significant role in boosting up sustainable supply chain performance. It was found that big data analytics capabilities significantly contributed to supply chain risk management and innovative green product development that ultimately enhanced innovation and learning performance. Moreover, innovation and green learning performance has a significant and positive relationship with sustainable supply chain performance. In the post COVID-19 situation, organizations can enhance their sustainable supply chain performance by giving extra attention to big data analytics capabilities and supply chain risk and innovativeness.

Originality/value

The paper specifically emphasizes on the factors that result in the sustainability in supply chain integrated with the big data analytics. Additionally, it offers the boundary condition for gaining the sustainable supply chain management.

Details

International Journal of Emerging Markets, vol. 18 no. 12
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 3 August 2021

Luis Hernan Contreras Pinochet, Guilherme de Camargo Belli Amorim, Durval Lucas Júnior and Cesar Alexandre de Souza

The article's objective is to analyze the consequent factors of Big Data Analytics Capability for firms in the competitive scenario, using different analytical models.

1229

Abstract

Purpose

The article's objective is to analyze the consequent factors of Big Data Analytics Capability for firms in the competitive scenario, using different analytical models.

Design/methodology/approach

The research had a quantitative approach, using a survey of data from firms located in the state of São Paulo – Brazil. Structural Equation Modeling (SEM) was used to validate the model.

Findings

The results reveal that all hypotheses were accepted. Business value was the construct that had the most explanatory power in the model. It is necessary to invest more in analytical tools, as well as people trained in the analysis of these models, in addition to a change of mindset, which will dictate the bias of the firm's strategic decision-making. The Big Data analysis is evident from firms' growing investments, particularly those that operate in complex and fast-paced environments.

Practical implications

The proposed theoretical model makes it possible to verify firms' analytical structure and whether they are better positioned to analyze customer data and information in real-time, generate insights and implement solutions to maintain and improve their market position.

Originality/value

The contribution of this article is to present a proposal to expand the research models in the literature that analyzed the direct and indirect relationship between “Big Data Analytics Capability” and “Product Innovation Performance”.

Details

Journal of Enterprise Information Management, vol. 34 no. 5
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 23 August 2021

Shokouh Razaghi and Sajjad Shokouhyar

This study aims to show that management with big data analytics capability can achieve more advantages of the global sourcing process. Furthermore, this study using its conceptual…

1313

Abstract

Purpose

This study aims to show that management with big data analytics capability can achieve more advantages of the global sourcing process. Furthermore, this study using its conceptual attitude model aims to show that big data analytics management capability leads to an increase in firm performance by the mediating role of integration.

Design/methodology/approach

Using an online questionnaire, 158 managers from 13 Iranian companies taking advantage of the global sourcing process were surveyed. The validity of the hypotheses was evaluated using partial least squares based on structural equation modeling (PLS method).

Findings

The results of the study showed that big data analytics management capability has a positive impact on global sourcing and firm performance directly, and by the mediating role of integration.

Originality/value

Previous studies have carefully addressed the role of big data and big data analytics in firms. However, this is among a few studies addressing the role of big data analytics capability, especially management capability, in improving firms’ performance. The results of this study shed light on the fact that how global sourcing takes the best advantage of big data analytics management capability for better accomplishment of organizations’ duties. The results of this study also disclose how big data analytics management capability helps organizations with their performance and bring benefits to their units.

Article
Publication date: 11 October 2022

Ayman Wael Al-Khatib

This study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and…

1732

Abstract

Purpose

This study investigates the impact of big data analytics capabilities on green supply chain performance. Moreover, it assesses the mediating effect of the green innovation and moderating effect of technological intensity.

Design/methodology/approach

This study is based on primary data that were collected from the food and beverages manufacturing sector operating in Jordan. A total of 420 samples were used for the final data analysis. Data analysis was performed via structural equation modeling (SEM) using SmartPLS 3.3.9.

Findings

The results of the data analysis supported a positive relationship between big data analytics capabilities and the green supply chain performance as well as a mediating effect of green innovation. It was confirmed that technological intensity moderated the relationship of green innovation on green supply chain performance.

Research limitations/implications

The study faced many limitations such as the method of collecting primary data, which relied on a questionnaire only and the use of cross-sectional data, as well as studying one context and in one country.

Practical implications

The findings can guide managers and policymakers in the Jordanian food and beverage manufacturing sector on how to manage organizational capabilities related to big data analytics to enhance green supply chain performance and improve green innovation in these firms.

Originality/value

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, green innovation, technological intensity and green supply chain performance. This study offers new theoretical and managerial contributions that add value to the supply chain management and innovation literature by testing the moderated mediation model of these constructs in the food and beverages manufacturing sector in Jordan.

Details

Business Process Management Journal, vol. 28 no. 5/6
Type: Research Article
ISSN: 1463-7154

Keywords

Article
Publication date: 8 June 2022

Minseok Park and Nitya Prasad Singh

As organizations globalize, they are facing twin challenges of (1) how to develop actionable intelligence from the vast amount of data flowing into their organization and (2) how…

1447

Abstract

Purpose

As organizations globalize, they are facing twin challenges of (1) how to develop actionable intelligence from the vast amount of data flowing into their organization and (2) how to effectively manage the increasing risks to their supply chain. Therefore, the purpose of this paper is to bring these two issues on a single platform to understand how firms can effectively predict supply chain risk by developing and using BDA capabilities, through an automated risk alert tool.

Design/methodology/approach

The authors used a questionnaire-based survey methodology supported by secondary data to collect information related to managerial perceptions on how firms can develop a risk alert tool by improving BDA capabilities. A database of 213 senior and middle-level managers was developed and used to test the proposed hypothesis. Using econometric techniques, the authors identify the conditions necessary for such an automated risk management tool to be effective.

Findings

The results suggest that if organizations focus on developing an effective IT infrastructure supported by a strong BDA capability, they will be able to leverage these capabilities to develop an effective risk management tool. Moderating influences of Upstream and Downstream Supply Chain IT Infrastructure capabilities were also observed on different types of BDA capabilities within a firm. In conclusion, it was argued that the effectiveness of a risk alert tool is dependent on how well firms harness big data analytics capability.

Originality/value

The value of the research stems from the fact that it uses managerial surveys to identify specific BDA capabilities that can enable firms to develop risk resilience capabilities. In addition, the article is one of the few empirical studies that aims to identify how firms can use BDA capabilities within a supply chain context to develop an automated risk alert tool. The article, therefore, contributes to the literature that identifies the value of BDA capabilities within the context of supply chain risk management.

Details

Benchmarking: An International Journal, vol. 30 no. 5
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 3 October 2019

Samuel Fosso Wamba and Shahriar Akter

Big data-driven supply chain analytics capability (SCAC) is now emerging as the next frontier of supply chain transformation. Yet, very few studies have been directed to identify…

3382

Abstract

Purpose

Big data-driven supply chain analytics capability (SCAC) is now emerging as the next frontier of supply chain transformation. Yet, very few studies have been directed to identify its dimensions, subdimensions and model their holistic impact on supply chain agility (SCAG) and firm performance (FPER). Therefore, to fill this gap, the purpose of this paper is to develop and validate a dynamic SCAC model and assess both its direct and indirect impact on FPER using analytics-driven SCAG as a mediator.

Design/methodology/approach

The study draws on the emerging literature on big data, the resource-based view and the dynamic capability theory to develop a multi-dimensional, hierarchical SCAC model. Then, the model is tested using data collected from supply chain analytics professionals, managers and mid-level manager in the USA. The study uses the partial least squares-based structural equation modeling to prove the research model.

Findings

The findings of the study identify supply chain management (i.e. planning, investment, coordination and control), supply chain technology (i.e. connectivity, compatibility and modularity) and supply chain talent (i.e. technology management knowledge, technical knowledge, relational knowledge and business knowledge) as the significant antecedents of a dynamic SCAC model. The study also identifies analytics-driven SCAG as the significant mediator between overall SCAC and FPER. Based on these key findings, the paper discusses their implications for theory, methods and practice. Finally, limitations and future research directions are presented.

Originality/value

The study fills an important gap in supply chain management research by estimating the significance of various dimensions and subdimensions of a dynamic SCAC model and their overall effects on SCAG and FPER.

Details

International Journal of Operations & Production Management, vol. 39 no. 6/7/8
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 5 March 2021

Jukka Hallikas, Mika Immonen and Saara Brax

This study aims to investigate digitalization as a performance driver in supply chains, especially the role of data analytics in the digitalization of procurement. The study…

7167

Abstract

Purpose

This study aims to investigate digitalization as a performance driver in supply chains, especially the role of data analytics in the digitalization of procurement. The study investigates how digital procurement capabilities are linked to data analytics capabilities and supply chain operational performance and how this links to business success.

Design/methodology/approach

Using operational and dynamic capabilities as foundations for data analytics capabilities, this paper studied the digital procurement capabilities and proposed the conceptual model and hypotheses for empirical testing. The collected industry survey data and structural equation method are then applied to test the hypotheses.

Findings

The study confirms positive and significant relationships among digital procurement capabilities, data analytics capabilities and supply chain performance. Digital procurement capabilities mediate the positive relationship between external data analytics capabilities and supply chain performance.

Research limitations/implications

This study has some limitations that should be addressed. The empirical study was based on survey data from a questionnaire that was probably challenging for some respondent companies with low levels of digital procurement and data analytics. Also, it is necessary to adopt secondary data to measure business performance in future studies which reduces the effect of subjective bias.

Practical implications

From the managerial point of view, the findings highlight the importance of gaining knowledge from gathered data and digitalized processes. Managers must focus on data utilization capabilities to improve the operational performance expected from the digitalization of supply chain activities. In addition, managers need to consider exploiting of data through new creative approaches as part of standardized operations.

Originality/value

The present study contributes to existing knowledge by investigating the mediating role of data analytics capabilities between the digitalization of procurement and supply chain performance. The findings support a positive relationship between the data analytics capabilities and supply chain performance in digital upstream supply chain procurement processes. The present study also clarifies the impact and role of data analytics capabilities in digital supply chain development and success.

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