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Article
Publication date: 10 August 2018

Mohammad Kamel Daradkeh

Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to…

1251

Abstract

Purpose

Visual analytics is increasingly becoming a prominent technology for organizations seeking to gain knowledge and actionable insights from heterogeneous and big data to support decision-making. Whilst a broad range of visual analytics platforms exists, limited research has been conducted to explore the specific factors that influence their adoption in organizations. The purpose of this paper is to develop a framework for visual analytics adoption that synthesizes the factors related to the specific nature and characteristics of visual analytics technology.

Design/methodology/approach

This study applies a directed content analysis approach to online evaluation reviews of visual analytics platforms to identify the salient determinants of visual analytics adoption in organizations from the standpoint of practitioners. The online reviews were gathered from Gartner.com, and included a sample of 1,320 reviews for six widely adopted visual analytics platforms.

Findings

Based on the content analysis of online reviews, 34 factors emerged as key predictors of visual analytics adoption in organizations. These factors were synthesized into a conceptual framework of visual analytics adoption based on the diffusion of innovations theory and technology–organization–environment framework. The findings of this study demonstrated that the decision to adopt visual analytics technologies is not merely based on the technological factors. Various organizational and environmental factors have also significant influences on visual analytics adoption in organizations.

Research limitations/implications

This study extends the previous work on technology adoption by developing an adoption framework that is aligned with the specific nature and characteristics of visual analytics technology and the factors involved to increase the utilization and business value of visual analytics in organizations.

Practical implications

This study highlights several factors that organizations should consider to facilitate the broad adoption of visual analytics technologies among IT and business professionals.

Originality/value

This study is among the first to use the online evaluation reviews to systematically explore the main factors involved in the acceptance and adoption of visual analytics technologies in organizations. Thus, it has potential to provide theoretical foundations for further research in this important and emerging field. The development of an integrative model synthesizing the salient determinants of visual analytics adoption in enterprises should ultimately allow both information systems researchers and practitioners to better understand how and why users form perceptions to accept and engage in the adoption of visual analytics tools and applications.

Details

Information Technology & People, vol. 32 no. 3
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 21 December 2021

Sharif Islam and Thomas Stafford

The benefits of data analytics in the internal audit function (IAF) are clear; less is known about IAF adoption of analytics. The purpose of this study is to examine the…

Abstract

Purpose

The benefits of data analytics in the internal audit function (IAF) are clear; less is known about IAF adoption of analytics. The purpose of this study is to examine the factors driving IAF adoption of analytics.

Design/methodology/approach

The Common Body of Knowledge of Internal Auditing Database (IIA, 2015) provides auditor responses on key variables of analysis.

Findings

The results of this study indicate the most critical adoption factor is data-specific IT knowledge in the IAF. Critical thinking skills and business knowledge of chief audit executive (CAEs) also contribute to adoption. IAFs with fraud risk detection responsibly are more likely to adopt. IAFs in technologically advanced cultures are more likely to adopt analytics.

Originality/value

The results of this study document the critical factors driving adoption of audit analytics, benefitting both industry and research.

Details

Managerial Auditing Journal, vol. 37 no. 2
Type: Research Article
ISSN: 0268-6902

Keywords

Article
Publication date: 5 January 2021

Hokey Min

Despite a growing interest in business analytics (BA) from the business and academic communities, it is still unknown what truly motivates and hinders the adoption of BA…

Abstract

Purpose

Despite a growing interest in business analytics (BA) from the business and academic communities, it is still unknown what truly motivates and hinders the adoption of BA. To have a clear picture of what will lead to the successful implementation of BA, this paper identifies contextual variables (e.g. user characteristics, organizational readiness and technology infrastructure/expertise) that significantly influence the BA adoption decision.

Design/methodology/approach

This paper conducted a series of classification, discriminant and logistics regressions analyses to analyze the differences in mail survey responses between adopters and nonadopters of BA and then determine what either motivate or inhibit the BA adoption.

Findings

Through a series of hypothesis testing, we discovered that large firms with a greater number of information technology (IT) staff and budget tended to adopt BA more than their smaller counterparts. Also, we found that BA skeptics, who did not fully recognize BA benefit potentials, were more concerned about BA implementation costs and experienced the greater organization resistance to BA adoption than the others did. Therefore, they were less likely to adopt BA.

Originality/value

In the era of knowledge-based economy, the firm's ability to derive actionable insights from big data can be a game changer. Such ability can be developed and nurtured by utilizing BA which is designed to help business executives and policymakers make well-thought and informed decisions. This paper is one of the first attempts to develop practical guidelines for the successful implementation of BA based on the exploratory study of BA practices among the Korean firms.

Details

American Journal of Business, vol. 36 no. 2
Type: Research Article
ISSN: 1935-5181

Keywords

Article
Publication date: 12 June 2019

Dragan Gasevic, Yi-Shan Tsai, Shane Dawson and Abelardo Pardo

The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach to advancing our…

1155

Abstract

Purpose

The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach to advancing our understanding of the learning process. This promise motivated the emergence of the field of learning analytics and supported the education sector in moving toward data-informed strategic decision making. Yet, progress to date in embedding such data-informed processes has been limited. The purpose of this paper is to address a commonly posed question asked by educators, managers, administrators and researchers seeking to implement learning analytics – how do we start institutional adoption of learning analytics?

Design/methodology/approach

A narrative review is performed to synthesize the existing literature on learning analytics adoption in higher education. The synthesis is based on the established models for the adoption of business analytics and finding two projects performed in Australia and Europe to develop and evaluate approaches to adoption of learning analytics in higher education.

Findings

The paper first defines learning analytics and touches on lessons learned from some well-known case studies. The paper then reviews the current state of institutional adoption of learning analytics by examining evidence produced in several studies conducted worldwide. The paper next outlines an approach to learning analytics adoption that could aid system-wide institutional transformation. The approach also highlights critical challenges that require close attention in order for learning analytics to make a long-term impact on research and practice of learning and teaching.

Originality/value

The paper proposed approach that can be used by senior leaders, practitioners and researchers interested in adoption of learning analytics in higher education. The proposed approach highlights the importance of the socio-technical nature of learning analytics and complexities pertinent to innovation adoption in higher education institutions.

Details

The International Journal of Information and Learning Technology, vol. 36 no. 4
Type: Research Article
ISSN: 2056-4880

Keywords

Article
Publication date: 4 September 2019

Valeriia Boldosova and Severi Luoto

The purpose of this paper is to explore the role of storytelling in data interpretation, decision-making and individual-level adoption of business analytics (BA).

1905

Abstract

Purpose

The purpose of this paper is to explore the role of storytelling in data interpretation, decision-making and individual-level adoption of business analytics (BA).

Design/methodology/approach

Existing theory is extended by introducing the concept of BA data-driven storytelling and by synthesizing insights from BA, storytelling, behavioral research, linguistics, psychology and neuroscience. Using theory-building methodology, a model with propositions is introduced to demonstrate the relationship between storytelling, data interpretation quality, decision-making quality, intention to use BA and actual BA use.

Findings

BA data-driven storytelling is a narrative sensemaking heuristic positively influencing human behavior towards BA use. Organizations deliberately disseminating BA data-driven stories can improve the quality of individual data interpretation and decision-making, resulting in increased individual utilization of BA on a daily basis.

Research limitations/implications

To acquire a deeper understanding of BA data-driven storytelling in behavioral operational research (BOR), future studies should test the theoretical model of this study and focus on exploring the complexity and diversity in individual attitudes toward BA.

Practical implications

This study provides practical guidance for business practitioners who struggle with interpreting vast amounts of complex data, making data-driven decisions and incorporating BA into daily operations.

Originality/value

This cross-disciplinary study develops existing BOR, storytelling and BA literature by showing how a novel BA data-driven storytelling approach can facilitate BA adoption in organizations.

Details

Management Research Review, vol. 43 no. 2
Type: Research Article
ISSN: 2040-8269

Keywords

Article
Publication date: 18 January 2021

Amitesh Singh Parihar and Vinita Sinha

The purpose of this paper is to identify the strengths and areas of improvement for taking organizations one step ahead in terms of adopting digitalization, analytics and…

Abstract

Purpose

The purpose of this paper is to identify the strengths and areas of improvement for taking organizations one step ahead in terms of adopting digitalization, analytics and governance. Also, the paper aims to identify the organizational cultural traits that influence the adoption of digitization and technology, analytics and governance.

Design/methodology/approach

A quantitative analysis of survey questionnaire collected from working professionals of various manufacturing industries to find out the driving traits and the restraining traits and to propose which is dominating. Sector: manufacturing, sample: working professionals across functions and sample size: 80–100 people.

Findings

This research suggests the cultural traits that influence the adoption of digitization and technology, analytics and governance in any organization.

Practical implications

As organizations explore new ways of working, their organizational culture and employee perspective would play an important role in prioritizing the interventions. This research aims to suggest a strategy to strengthen the driving forces and/or weaken the restraining forces.

Originality/value

There are various papers available on the individual topics but the uniqueness of this paper is that it represents all three factors in a single research and their influencers.

Details

International Journal of Innovation Science, vol. 13 no. 2
Type: Research Article
ISSN: 1757-2223

Keywords

Article
Publication date: 14 May 2018

Yuanyuan Lai, Huifen Sun and Jifan Ren

Based on previous literature on big data analytics (BDA) and supply chain (SC) management, the purpose of this paper is to address the factors determining firms’ intention…

5691

Abstract

Purpose

Based on previous literature on big data analytics (BDA) and supply chain (SC) management, the purpose of this paper is to address the factors determining firms’ intention to adopt BDA in their daily operations. Specifically, this study classifies potential factors into four categories: technological, organizational, environmental factors, and SC characteristics.

Design/methodology/approach

Drawing on the innovation diffusion theory, a model consisted of direct technological and organizational factors as well as moderators was proposed. Subsequently, survey data was collected from 210 organizations. Then we used SPSS and SmartPLS to analyze the collected data.

Findings

The empirical results revealed that perceived benefits and top management support can significantly influence the adoption intention. And environmental factors, such as competitors’ adoption, government policy, and SC connectivity, can significantly moderate the direct relationships between driving factors and the adoption intention.

Research limitations/implications

Given the fact that big data (BD) usage in logistics and SC management is still in the start-up stage, the interpretations toward BDA might vary from different perspectives, thus causing some ambiguity in understanding the meaning and potential BD has. In addition, we collected data through questionnaires completed by IT managers, whose viewpoint may not fully represent that of an organization.

Practical implications

This paper tests the organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.

Social implications

This research helps top managers assess the benefits of BDA as well as how to adjust their business strategy along the changes of environment and SC maturity.

Originality/value

This paper contributes to the literature of organizational adoption intention of BDA and extends the literature streams of BD and SC management simultaneously.

Details

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

Keywords

Article
Publication date: 12 October 2021

Vaibhav S. Narwane, Rakesh D. Raut, Vinay Surendra Yadav, Naoufel Cheikhrouhou, Balkrishna E. Narkhede and Pragati Priyadarshinee

Big data is relevant to the supply chain, as it provides analytics tools for decision-making and business intelligence. Supply Chain 4.0 and big data are necessary for…

1143

Abstract

Purpose

Big data is relevant to the supply chain, as it provides analytics tools for decision-making and business intelligence. Supply Chain 4.0 and big data are necessary for organisations to handle volatile, dynamic and global value networks. This paper aims to investigate the mediating role of “big data analytics” between Supply Chain 4.0 business performance and nine performance factors.

Design/methodology/approach

A two-stage hybrid model of statistical analysis and artificial neural network analysis is used for analysing the data. Data gathered from 321 responses from 40 Indian manufacturing organisations are collected for the analysis.

Findings

Statistical analysis results show that performance factors of organisational and top management, sustainable procurement and sourcing, environmental, information and product delivery, operational, technical and knowledge, and collaborative planning have a significant effect on big data adoption. Furthermore, the results were given to the artificial neural network model as input and results show “information and product delivery” and “sustainable procurement and sourcing” as the two most vital predictors of big data adoption.

Research limitations/implications

This study confirms the mediating role of big data for Supply Chain 4.0 in manufacturing organisations of developing countries. This study guides to formulate management policies and organisation vision about big data analytics.

Originality/value

For the first time, the impact of big data on Supply Chain 4.0 is discussed in the context of Indian manufacturing organisations. The proposed hybrid model intends to evaluate the mediating role of big data analytics to enhance Supply Chain 4.0 business performance.

Details

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

Keywords

Article
Publication date: 23 February 2022

Parisa Maroufkhani, Mohammad Iranmanesh and Morteza Ghobakhloo

The study challenges the assumption of independence among Technological, Organizational and Environmental (TOE) factors and investigates the influence of TOE factors on…

1088

Abstract

Purpose

The study challenges the assumption of independence among Technological, Organizational and Environmental (TOE) factors and investigates the influence of TOE factors on Big Data Analytics (BDA) adoption among Small and Medium Enterprises (SMEs). Top management support was proposed as a mediator between technological and organizational factors and BDA adoption. Furthermore, the moderating effect of environmental factors on the association between relative advantage, compatibility, competitiveness, organizational readiness and BDA adoption was evaluated.

Design/methodology/approach

Data were collected from 171 SME manufacturing firms and analyzed using the partial least squares technique.

Findings

The findings confirmed the interrelationships among the TOE factors. The effects of compatibility, competitiveness and organizational readiness on BDA adoption were mediated by top management support. Furthermore, environmental factors moderate the influences of compatibility and organizational readiness on top management support.

Originality/value

The findings contribute to the TOE model by challenging the assumption of independence among TOE factors, and future studies should use this model with more caution and consider the potential relationships between TOE factors.

Details

Industrial Management & Data Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 27 May 2022

Mohammad Iranmanesh, Kok Hong Lim, Behzad Foroughi, Meen Chee Hong and Morteza Ghobakhloo

Present research aims to study the determinants of big data analytics (BDA) adoption intention and outsourcing in the context of small and medium-sized enterprises (SMEs).

Abstract

Purpose

Present research aims to study the determinants of big data analytics (BDA) adoption intention and outsourcing in the context of small and medium-sized enterprises (SMEs).

Design/methodology/approach

The partial least squares approach was employed to analyse data collected from 187 SMEs.

Findings

The findings indicate that relative advantage, competitive pressure and environmental uncertainty significantly influence SMEs' BDA adoption intention. Top management support moderates the association between the regulatory environment and BDA adoption intention. Furthermore, organisational readiness moderates negatively the association between BDA adoption intention and propensity to outsource BDA.

Practical implications

The findings benefit SMEs' managers/owners in making well-informed decisions in the BDA adoption process.

Originality/value

The majority of the previous research on BDA adoption intention is limited to large corporations. To address the gap on determinant factors of BDA adoption intention among SMEs, the drivers of BDA adoption intention and propensity to outsource were investigated using the technology-organisation-environment model.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

Keywords

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