Determinants of Self-Service Analytics Adoption Intention

Daradkeh, Mohammad

doi:10.4018/joeuc.2019100102

Cited by 23 publications

(16 citation statements)

References 63 publications

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“…Previous studies on this topic are mainly technical and acritical, and overemphasise the instrument's benefits (Elbashir et al, 2008;Dilla, 2013;Kowalczyk, 2015;Schlesinger and Rahman, 2016;Daradkeh and Moh'd Al-Dwairi, 2017;Daradkeh, 2019). Furthermore, they are not framed within an accounting perspective, thereby the broader organisational impact of the adoption is widely overlooked, and indeed this angle is only now being glanced at in a few studies (Riggins and Klamm, 2017;Moll and Yigitbasioglu, 2019).…”

Section: Discussionmentioning

confidence: 99%

“…Academic research also supports this over-positive representation. Contributions on selfservice BI are mainly technical, concentrating on the specific benefits or features (Elbashir et al, 2008;Dilla, 2013;Kowalczyk, 2015;Schlesinger and Rahman, 2016;Daradkeh and Moh'd Al-Dwairi, 2018;Daradkeh, 2019). This lack of research and narrow vision is highlighted by Rikhardsson and Yigitbasioglu (2018), who, in discussing future open issues, pointed to the need for more critical studies where technical issues linked to information systems are coupled to an organisational perspective.…”

Section: Self-service Business Intelligence and Accounting In The Digital Agementioning

confidence: 99%

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On the relevance of self-service business intelligence to university management

Arnaboldi

Robbiani

Carlucci

2020

JAOC

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Purpose Nearly 40 years since they first appeared, there is renewed interest in dashboards, engendered by the diffusion of business intelligence (BI) desktop software, such as Power BI, QlikView and Tableau, denoted collectively as “self-service” BI. Using these commodity software tools, the work to construct dashboards apparently becomes easier and more manageable and no longer requires the intervention of specialists. This paper aims to analyse the implementation of this kind of commodity dashboard in a university, exploring its role in performance management processes and investigating whether the dashboard affects the organisation (or not). Design/methodology/approach This paper focusses on an action research project developed by the authors, where the objective was to design and implement a dynamic performance measurement tool fitting the needs of department directors. The three authors were all involved in the project, respectively, as project manager, dashboard implementation manager and accounting manager of the studied organisation. Findings The results reveal a specific but complex change to the procedures and outcomes in the organisation studied, where the dashboard becomes a boundary infrastructure, thereby reviving technical and organisational problems that had been latent for years. Originality/value In this paper, the authors contribute to the debate on the digital age and the role of accounting with their exploration into the “revolution” of self-service BI tools. The democratisation and flexibility of these instruments put into discussion two core and somewhat controversial functions of accounting: data integration and personalised reporting.

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Section: Discussionmentioning

confidence: 99%

Section: Self-service Business Intelligence and Accounting In The Digital Agementioning

confidence: 99%

On the relevance of self-service business intelligence to university management

Arnaboldi

Robbiani

Carlucci

2020

JAOC

View full text Add to dashboard Cite

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“…Data visualization and decision support: this article visualized the analysis results and presents them in an intuitive form to farmers and agricultural experts (Daradkeh, 2019). In this way, they can more easily understand and utilize data to make scientific decisions.…”

Section: System Analysis Layermentioning

confidence: 99%

Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images

Yao,

Zhang

2024

Int. Food Agribus. Manag. Rev.

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With the modernization of agricultural production and the acceleration of urbanization, agricultural landscape planning and ecological balance control have become important issues in promoting sustainable development. Traditional agricultural production methods have problems such as resource waste, environmental pollution, and ecological damage. This article aimed to achieve scientific planning and management of agricultural landscapes, and promote the efficiency of agricultural production, rational utilization of resources, and protection of the ecological environment, thereby promoting sustainable agricultural development. This study first focused on denoising and feature extraction of agricultural remote sensing data images, using remote sensing technology to obtain agricultural landscape information. After that, artificial intelligence was adopted to achieve intelligent agricultural landscape planning, with the goal of maintaining ecological balance and promoting efficient, eco-friendly, and sustainable agricultural production. This study took the landscape of a certain city as an example to test the processing effect of remote sensing images, and it was proved that the effect was good. We tested the performance of an intelligent agricultural landscape planning and ecological balance control system based on remote sensing images. According to the experimental results, it can be concluded that the resource utilization efficiency of farmland A monitored by the intelligent agricultural landscape planning system using remote sensing image technology was 82%, while the traditional one was only 60%. This indicated that the collection effect of remote sensing image technology was much better than that of traditional technology. This article comprehensively and timely monitored and evaluated farmland through remote sensing image technology, including crop growth status, soil moisture, nutritional status, etc. The system can provide precise planting and management suggestions for farmers based on this information, and help them optimize farmland layout, crop selection, and irrigation management, thereby improving the production efficiency of farmland and crop yield.

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“…Some of commercial self-service business analytics tools, such as Tableau 1 , QlikView 2 , and Microsoft Power BI 3 can be used for creating sharable data-driven stories via data visualizations and interactive dashboards and reports. These platforms lay the foundations for constructing narrative elements and exploratory visuals of data storytelling (Daradkeh, 2019b(Daradkeh, , 2019c. However, business analytics platforms with dedicated features for developing data stories are not yet as advanced and still used less frequently than the aforementioned alternatives (Tischler et al, 2017).…”

Section: Data Storytelling In Business Analytics Practicesmentioning

confidence: 99%

“…In today's business environment, organizations accumulate massive amounts of data, and their ability to make informed decisions and drive business performance depends in a part on their acumen and competency in analyzing these data and converting them into actionable insights (Daradkeh, 2019a(Daradkeh, , 2019b. To this end, various business analytics solutions are increasingly being leveraged by organizations to extract meaningful and relevant insights from the data they accumulate and support decision-making at both strategic and operational levels (Delen & Zolbanin, 2018).…”

Section: Introductionmentioning

confidence: 99%

An Empirical Examination of the Relationship Between Data Storytelling Competency and Business Performance

Daradkeh

2021

Journal of Organizational and End User Computing

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With the proliferation of big data and business analytics practices, data storytelling has gained increasing importance as an effective means for communicating analytical insights to the target audience to support decision-making and improve business performance. However, there is a limited empirical understanding of the relationship between data storytelling competency, decision-making quality, and business performance. Drawing on the resource-based view (RBV), this study develops and validates the concept of data storytelling competency as a multidimensional construct consisting of data quality, story quality, storytelling tool quality, storyteller skills, and storyteller domain knowledge. It also develops a mediation model to examine the relationship between data storytelling competency and business performance, and whether this relationship is mediated by decision-making quality. Based on an empirical analysis of data collected from business analytics practitioners, the results of this study reveal that the data storytelling competency is positively linked to business performance, which is partially mediated by decision-making quality. These results provide a theoretical basis for further investigation of possible antecedents and consequences of data storytelling competency. They also offer guidance for practitioners on how to leverage data storytelling capabilities in business analytics practices to improve decision-making and business performance.

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Determinants of Self-Service Analytics Adoption Intention

Cited by 23 publications

References 63 publications

On the relevance of self-service business intelligence to university management

On the relevance of self-service business intelligence to university management

Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images

An Empirical Examination of the Relationship Between Data Storytelling Competency and Business Performance

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