Abstract
In this paper, we analyze the efforts of a public healthcare business intelligence unit to implement and disseminate their data products and thus make the healthcare organization more ...data-driven. The paper is based on ethnographic fieldwork in a healthcare business intelligence unit (the BIU) whose mission is to improve healthcare efficiency and quality by making data and data analyses available to healthcare managers and staff. Their primary products consist of a data warehouse and Data Reports, both providing curated and daily updated data for healthcare staff to analyze and visualize. We conceptualize these Data Reports and the data warehouse as boundary objects through which cooperation around data between various users is achieved. Our focus is on the BIU’s efforts to introduce and promote the use of boundary objects to healthcare staff while providing them with the competencies to use them in practice. Efforts that we conceptualize as collaborative boundary work through which a new joint field of working with data is created between the BIU and healthcare staff. Based on the analysis of the ethnographic fieldwork, we point to three important aspects in creating this new joint field: Mobilizing interest, building local capabilities, and propagating data locally. The paper makes three contributions: It adds to our understanding of how new joint fields can be cultivated through collaborative boundary work to make healthcare data-driven; it contributes to the emergent field of data work studies; and finally, it adds to the largely normative literature on business intelligence and self-service business intelligence through an ethnographic analysis of its efforts to make healthcare data-driven.
This book will provide a comprehensive overview of business analytics, for those who have either a technical background (quantitative methods) or a practitioner business background. Business ...analytics, in the context of the 4th Industrial Revolution, is the "new normal" for businesses that operate in this digital age. This book provides a comprehensive primer and overview of the field (and related fields such as Business Intelligence and Data Science). It will discuss the field as it applies to financial institutions, with some minor departures to other industries. Readers will gain understanding and insight into the field of data science, including traditional as well as emerging techniques. Further, many chapters are dedicated to the establishment of a data-driven team - from executive buy-in and corporate governance to managing and quantifying the return of data-driven projects.
New technologies and the use of the Internet of Things (IoT) play a remarkable role in the design, construction, and maintenance of Smart Cities. With the exponential increase of data generated in ...the areas of health, commerce, financial services, science, education, public administration, and society, the challenge of ensuring data security and quality is increasing. IoT and Smart Cities, are in permanent mutation and evolution, towards a new paradigm of digitalization and digital transformation. The existing literature review exposes much of the attention that is given to IoT, but a broad discussion on the characteristics, use, applications, and challenges of these technologies in Smart Cities is still needed. The main contribution of this paper is that it provides a systematic assessment and synthesis of the critical applications and challenges of IoT, in the development of Smart Cities.
The rise of information technology has transformed the business landscape, with organizations increasingly relying on information systems to collect and store vast amounts of data. To stay ...competitive, businesses must harness this data to make informed decisions that optimize their actions in response to the market. Business intelligence (BI) is an approach that enables organizations to leverage data-driven insights for better decision-making, but implementing BI comes with its own set of challenges. Accordingly, understanding the key factors that contribute to successful implementation is crucial.
This study examines the factors affecting the implementation of BI projects by analyzing the interactions between these factors using system dynamics modeling. The research draws on interviews with five BI experts and a review of the background literature to identify effective implementation strategies. Specifically, the study compares traditional and self-service implementation approaches and simulates their respective impacts on organizational acceptance of BI. The results show that the two approaches were equally effective in generating organizational acceptance until the twenty-fifth month of implementation, after which the self-service strategy generated significantly higher levels of acceptance than the traditional strategy. In fact, after 60 months, the self-service approach was associated with a 30% increase in organizational acceptance over the traditional approach. The paper also provides recommendations for increasing the acceptance of BI in both implementation strategies. Overall, this study underscores the importance of identifying and addressing key factors that impact BI implementation success, offering practical guidance to organizations seeking to leverage the power of BI in today's competitive business environment.
Small scale enterprises can improve their operations by implementing business intelligence systems. The business intelligence systems are complex and require expertise to ensure successful ...implementation, hence the need for small scale enterprises to determine their readiness before undertaking the project. To improve chances for successful implementation, this study proposed a framework to guide small scale enterprises on the requirements for business intelligence systems. The design steps defined by Edwards and Goodrich & Tamassia were followed to design the framework. The framework components were informed by the Diffusion of Innovation and Technology Organization and Environment theories, the Information Evaluation Model, and the critical success factors for BIS implementation. A small business may evaluate its resources against the framework components to determine whether to implement a business intelligence system. In future, the framework may be extended to include weights and other criteria to calculate a business’s status.
Business intelligence systems (BIS) are considered a potential source of competitive advantage but their benefits can be fully realized only when using BIS and the information provided by BIS become ...fully embedded into the routines of decision makers. This study thus adds to previous research of IS acceptance by investigating diverse post-adoptive use behaviors, which are the intensity, extent of use and embeddedness of BIS. We followed an exploratory approach to conceptualize a business intelligence extended use model. The findings show that personal innovativeness and readiness for change boost the transition to the embeddedness of BIS into workers routines. The relevance of the information provided by BIS is crucial for the deep structural usage of BIS, which has not been highlighted in previous models of IT acceptance. Besides taking pre- and post-implemental issues that address acceptance determinants into consideration, for the success of BIS we must consider trans-implemental issues.
Purpose
The purpose of this paper is to provide a better understanding of how post-adoption use of business intelligence system (BIS) affects firm performance. It develops and empirically tests a ...conceptual model for assessing the impact of BIS routine and innovative usage on firm performance the context of small and medium enterprises (SMEs).
Design/methodology/approach
Drawing on the data collected from 181 SMEs we analyzed how BIS usage influences firm performance using the PLS-SEM method.
Findings
The paper provides empirical insights about how BIS routine and innovative usage affect firm performance.
Practical implications
The results provide instrumental insights for managers and solution providers to help them understand the influence of various determinants to more effectively conclude the post-adoption process in SMEs.
Originality/value
This study represents important progress in the authors’ theoretical understanding of the role of BIS routine and innovative usage across different BIS partial impacts on firm performance dimensions.
•We examined the interrelated role of compatibility in predicting IS use intentions in the context of BI&A.•Compatibility perceptions have a positive impact on use intentions and mediate the impact ...of performance perceptions on use intentions.•Results demonstrability and social influence strengthen the perceived relevance of compatibility in impacting use intentions.•Findings contribute to the understanding of the influential drivers of BI&A use intention.
Research shows that data-driven decision-making using Business Intelligence and Analytics (BI&A) can create competitive advantages for organizations. However, this can only happen if users successfully accept BI&A and use it effectively. Analytical decision processes are often characterized by non-routine and ill-structured tasks and decisions, making individuals’ work styles more pronounced. Aligning on one hand what a BI&A solution can offer and, on the other, the changing needs and expectations of users, the way they like to work – their work style, can thus be difficult. This illustrates the importance of compatibility evaluations in the BI&A context, including perceptions of the technology fit with the user’s work needs and style, along with the fit with the organizational decision processes and organizational values when deciding to use BI&A. These issues have not yet been thoroughly researched in the existing BI&A literature. In response, we conduct a quantitative survey-based study to examine the interrelated role of compatibility in predicting BI&A use intentions. The model is empirically tested with the partial least squares (PLS) approach through to structural equation modeling (SEM). Our results show that compatibility perceptions have a direct positive impact on use intentions, mediate the impact of performance perceptions on use intentions, while the socio-organizational considerations of result demonstrability and social influence have interaction effects by positively strengthening the perceived relevance of compatibility in impacting use intentions.
There is a problem with collecting information in healthcare services as it is scattered among various sources. This leads to potential impact on patient care focus. To address this issue, a Business ...Intelligence platform was developed and implemented at the Centre for Surgical Treatment of Obesity at Centro Hospitalar do Tâmega e Sousa. The platform developed enables knowledge extraction and aids healthcare professionals to easily access helpful information and perform better decisions, specifically in regards to the growing global concern of obesity and the increasing prevalence of bariatric surgery.
Self-service Business Intelligence (SSBI) allows non-technical users to use Business Intelligence in a self-reliant manner without the support of technical users. Many organizations struggle to ...utilize the potential of SSBI and experience implementation challenges. This study aims to explore user-related SSBI challenges by conducting 30 qualitative interviews with 2 SSBI implementation projects. Analysis revealed challenges that can help practitioners to avoid unnecessary obstacles when implementing and using SSBI, and guide researchers in simplifying the implementation process.
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