Exploring the relationship between supplier development, big data analytics capability, and firm performance

2021 ◽  
Author(s):  
Vicky Ching Gu ◽  
Bin Zhou ◽  
Qing Cao ◽  
Jeffery Adams
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Supplier Development ◽  
The Relationship ◽  
Analytics Capability

Big data analytics capability as a mediator in the impact of open innovation on firm performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
José Arias-Pérez ◽  
Alejandro Coronado-Medina ◽  
Geovanny Perdomo-Charry
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Financial Performance ◽  
Open Innovation ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Content Type ◽  
Customer Involvement ◽  
The Relationship ◽  
Analytics Capability

PurposeBig data analytics capability (BDAC) is the ability of a firm to capture and analyze big data toward the generation of insights. The literature has mainly focused on analyzing the direct effects of BDAC on different aspects related to firm performance such as finances and innovation. However, the lack of works analyzing the intermediation role BDAC could play is noticeable, particularly in organizational situations that pose great challenges in terms of data processing. Thus, the aim of this paper is to analyze BDAC mediation in the relationship between open innovation (OI), particularly customer involvement, and firm performance (financial and non-financial).Design/methodology/approachStructural equation modeling was used to test the proposed model with survey data from a sample of 112 firms.FindingsThe results show that BDAC has a partial mediating effect on the relationship between OI and financial performance, and between OI and non-financial performance. Nevertheless, this mediation is greater in the first relationship.Originality/valueThe main contribution of the study is to offer a broader research perspective regarding the role of BDAC in the relationship between OI and firm performance. This study ultimately questions that research tradition in which this role has been reduced to that of a simple application of data analytics techniques. Instead, the results show BDAC is primarily an organizational skill that should be articulated with key processes, such as customer involvement, to maximize the financial and non-financial use of the large flow of data coming from the main OI activity of low and medium-technology companies.

Quality dominant logic in big data analytics and firm performance

2019 ◽  
Vol 25 (3) ◽  
pp. 512-532 ◽  
Author(s):  
Samuel Fosso Wamba ◽  
Shahriar Akter ◽  
Marc de Bourmont
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Data Analytics ◽  
Online Survey ◽  
Information Quality ◽  
Big Data Analytics ◽  
Firm Strategy ◽  
Theoretical Understanding ◽  
Content Type ◽  
The Relationship

Purpose Big data analytics (BDA) gets all the attention these days, but as important—and perhaps even more important—is big data analytics quality (BDAQ). Although many companies realize a full return from BDA, others clearly struggle. It appears that quality dynamics and their holistic impact on firm performance are unresolved in data economy. The purpose of this paper is to draw on the resource-based view and information systems quality to develop a BDAQ model and measure its impact on firm performance. Design/methodology/approach The study uses an online survey to collect data from 150 panel members in France from a leading market research firm. The participants in the study were business analysts and IT managers with analytics experience. Findings The study confirms that perceived technology, talent and information quality are significant determinants of BDAQ. It also identifies that alignment between analytics quality and firm strategy moderates the relationship between BDAQ and firm performance. Practical implications The findings inform practitioners that BDAQ is a hierarchical, multi-dimensional and context-specific model. Originality/value The study advances theoretical understanding of the relationship between BDAQ and firm performance under the influence of firm strategy alignment.

scholarly journals How to improve firm performance using big data analytics capability and business strategy alignment?

2016 ◽  
Vol 182 ◽  
pp. 113-131 ◽  
Author(s):  
Shahriar Akter ◽  
Samuel Fosso Wamba ◽  
Angappa Gunasekaran ◽  
Rameshwar Dubey ◽  
Stephen J. Childe
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Business Strategy ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Strategy Alignment ◽  
Analytics Capability

Impacts of big data analytics management capabilities and supply chain integration on global sourcing: a survey on firm performance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shokouh Razaghi ◽  
Sajjad Shokouhyar
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Global Sourcing ◽  
Content Type ◽  
Mediating Role ◽  
Management Capability ◽  
Analytics Capability

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.

Big data analytics capability and organizational performance measures: The mediating role of business intelligence infrastructure

2021 ◽  
pp. 026638212110553
Author(s):  
Aboobucker Ilmudeen
Keyword(s):  
Big Data ◽  
Firm Performance ◽  
Organizational Performance ◽  
Performance Measures ◽  
Business Intelligence ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Operational Performance ◽  
Marketing Performance ◽  
Analytics Capability

The growing importance of big data has headed enterprises to advance their big data analytics capability to strengthen their firm performance. This study tests how big data capability impact on business intelligence infrastructure to achieve firm performance measures such as operational performance and marketing performance. This study is based on the recent literature on the knowledge-based view, big data capability, IT capability, and business intelligence. The primary survey of 272 responses from Chinese firms’ IT managers and big data analysts are used to uncover the relationship in the proposed model. The finding shows that the big data analytics capability significantly impacts on business intelligence infrastructure that in turn positively impact on operational performance and marketing performance. Further, the business intelligence infrastructure partially mediates between big data analytics capability and operational performance, and fully mediates between big data analytics capability and marketing performance. This research contributes to the information systems literature such as big data analytic capability, business intelligence, and firm performance measures, and thus offers grounds to extend more widespread studies in this field. This study adds to the literature on the theory and practical bases for big data capability and business intelligence infrastructure.

Dave Snowden on KM and big data/analytics: interview with David J. Pauleen

2017 ◽  
Vol 21 (1) ◽  
pp. 12-17 ◽  
Author(s):  
David J. Pauleen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Theory And Practice ◽  
Content Type ◽  
Face To Face ◽  
The Relationship ◽  
A Company ◽  
Practical Implications ◽  
Scientific Officer

Purpose Dave Snowden has been an important voice in knowledge management over the years. As the founder and chief scientific officer of Cognitive Edge, a company focused on the development of the theory and practice of social complexity, he offers informative views on the relationship between big data/analytics and KM. Design/methodology/approach A face-to-face interview was held with Dave Snowden in May 2015 in Auckland, New Zealand. Findings According to Snowden, analytics in the form of algorithms are imperfect and can only to a small extent capture the reasoning and analytical capabilities of people. For this reason, while big data/analytics can be useful, they are limited and must be used in conjunction with human knowledge and reasoning. Practical implications Snowden offers his views on big data/analytics and how they can be used effectively in real world situations in combination with human reasoning and input, for example in fields from resource management to individual health care. Originality/value Snowden is an innovative thinker. He combines knowledge and experience from many fields and offers original views and understanding of big data/analytics, knowledge and management.

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