WHAT IS THE BETTER NUMBER? INTERPRETING EVALUATIVE INTELLIGENT TECHNOLOGIES IMPLEMENTATION FROM A POWER DYNAMICS PERSPECTIVE

2023 | European Conference On Information Systems | Citations: 0

Authors: Alsaedi, Basmah; Newell, Sue; Gkeredakis, Emmanouil

Abstract: Intelligent technologies are increasingly used to evaluate and monitor performa ... Expand

Abstract: Intelligent technologies are increasingly used to evaluate and monitor performance through implementing specific metrics such as Key Performance Indicators (KPIs). Recently, scholars have called to better engage with intelligent technologies specific features and their production process, which otherwise remain black-boxed. We aim at developing greater insights into how practices enacted by different end-user's shape and reshape the production of KPIs in technological change initiatives. This research employs a critical, process oriented and performative view of power to emphasise both its negative and productive effects. We highlight the pursuing (push)-withdrawing (pull) dynamics which lie in iterative and recursive acts of power and resistance involving a range of actors who collectively, albeit inadvertently and differently, change the meanings technological outcomes perform. Finally, we show that technologies that might initially seem to fail can 'take off' through persistent and positive power effects. Collapse

Topics: technological change systems development organizational change decision making business intelligence

Methods: qualitative interview single case study triangulation field study personal interview

Does Analytics Help Resolve Equivocality in the Healthcare Context? Contrasting the Effects of Analyzability and Differentiation

2023 | Journal of the Association for Information Systems | Citations: 0

Authors: Adjerid, Idris; Angst, Corey; Devaraj, Sarv; Berente, Nicholas

Abstract: Organizations are increasingly using data analytics to help make decisions and ... Expand

Abstract: Organizations are increasingly using data analytics to help make decisions and drive positive outcomes. But organizational scholarship has warned us that the sort of information processing associated with analytic capabilities, while effective for uncertainty reduction, may be less effective in equivocal contexts. Equivocality is evident when tasks are not easily analyzable (task analyzability) or when organizational departments are highly differentiated (differentiation). We hypothesize that analytics will be less effective in driving positive outcomes when equivocality is high because of low task analyzability. However, when an organization is more differentiated, resulting in high equivocality, we anticipate that analytics will be more effective in driving positive outcomes. To test this theory, we studied how clinical healthcare analytics influenced experiential quality (akin to patient satisfaction) in over 3,000 hospitals across nine years. Our results show that analytics capabilities, on average, do improve outcomes in terms of patient experiential quality, suggesting that analytics can reduce uncertainty, but we also found evidence for the moderating role of equivocality. Specifically, as task analyzability decreases (i.e., increasing equivocality), clinical healthcare analytics becomes less effective in improving experiential quality. However, when equivocality is high because of differentiation, there is a positive relationship between clinical healthcare analytics and experiential quality but only in larger hospitals. From a managerial perspective, this study has implications for boundary conditions of data analytics in organizations. Collapse

Topics: healthcare analytics technology adoption electronic health record health information system artificial intelligence

Methods: theory development post-hoc analysis experimental group longitudinal research machine learning

Theories: organizational information processing theory

DataOps as a Prerequisite for the Next Level of Self-Service Analytics – Balancing User Agency and Central Control

2023 | International Conference on Business Informatics | Citations: 0

Authors: Baars, Henning

Abstract: The area of Business Intelligence and Analytics (BIA) has repeatedly oscillated ... Expand

Abstract: The area of Business Intelligence and Analytics (BIA) has repeatedly oscillated between more central, efficiency-oriented, professionalized approaches and decentral, agility-oriented, user-driven ones. This paper investigates whether and how to alleviate that tradeoff by combining an agility-oriented self-service analytics approach with the professionalization-driven DataOps concept: DataOps aims at transferring ideas from DevOps to the realm of analytics, namely a mutual integration of Development and Operations and a high degree of professionalization and automation. A case study with a series of interviews and a workshop led to insights into the viability of such a combination. These inspire a theoretical concept for capturing the economics behind the approaches that is considering the (opportunity) costs of the components "user agency" and "central control". The concept has been evaluated with representatives from the case study. Based on the results, I argue that the discussed combination can push BIA solutions towards fine-tuned federated environments. Collapse

Topics: devops artificial intelligence mlops data management data integration

Methods: qualitative interview case study literature study machine learning survey

Low-Coders, No-Coders, and Citizen Developers in Demand: Examining Knowledge, Skills, and Abilities Through a Job Market Analysis

2023 | International Conference on Business Informatics | Citations: 0

Authors: Binzer, Björn; Winkler, Till J.

Abstract: The emergence of low-code/no-code (LCNC) platform technologies and the resultin ... Expand

Abstract: The emergence of low-code/no-code (LCNC) platform technologies and the resulting increase in citizen development programs are facilitating the democratization of the design, development, and deployment of digital solutions. Citizen developers, non-technical employees who leverage LCNC platforms, are at the heart of this trend. While many firms perceive LCNC and citizen development as a crucial component of their digital transformation strategy, little is known about the evolving roles in this field or the necessary knowledge, skills, and abilities (KSA). To address this knowledge gap, we processed 113,106 job postings published on Indeed.com. Our topic modeling methodology identified 34 KSA topics and classified them into the three domains platform, business, and technology. We contribute to research by empirically demonstrating which competencies are required to successfully work in the LCNC field. Our findings can guide individual professionals and organizations alike. Collapse

Topics: online labor market Indeed.com low code development platform Python project management

Methods: topic model natural language processing computational algorithm latent dirichlet allocation NLTK

Exploring the value of IoT data as an enabler of the transformation towards servitization: an action design research approach

2023 | European Journal of Information Systems | Citations: 0

Authors: Chen, Kuan-Lin; Lassen, Astrid; Li, Chen; Møller, Charles

Abstract: Servitization is a well-recognised phenomenon in the manufacturing industry. Bus ... Expand

Abstract: Servitization is a well-recognised phenomenon in the manufacturing industry. Business potentials are demonstrated mainly from the marketing perspective on servitization. However, increased digitalisation makes servitization interesting to other research areas. This paper applies the resource-based view (RBV) to argue how to value the data and explore its potential and impact on servitization. We examine the evolving role of information technology (IT), particularly of the Internet of Things (IoT), and the role of data in the servitization journey. This research is based on a longitudinal study of a product-oriented manufacturing company’s transformation towards servitization. The engagement with the company also includes the development of an IT platform that consolidates IoT and enterprise data, which enables managers to explore new data-based insights. Our goal is to investigate the organisation and in particular cross-functional effects of data-based insights and their impact on supporting strategic decision-making. The action design research (ADR) approach is applied to unfold the servitizing activities inside the organisation and extract the lesson learned into the joint domains of servitization and information systems research. First, we argued that exploring the value of data is becoming a more complex process. Rather than having one design perspective, technical concerns, business considerations, and operational purpose must be aligned to frame the value of data to support decision-making. Second, we discuss the emerging managerial implications, especially the role of IT in the transformation. A cross-functional team is a prerequisite to exploring complex transformation projects. Thus, managers must recognise the problematic situation and bootstrap the available organisational resources. Finally, we provide empirical evidence on how scholars and practitioners can address mutual interests by applying the ADR approach to a transformation project. In summary, servitizing a product-centric manufacturing firm to have a digital services business model is a transformation involving complex social and organisational relations. This study advocates resource-based analysis as a lens and demonstrates how IT and data as heterogeneous and imperfectly mobile resources create value for a product-oriented manufacturing company. However, a critical question remains on how to manage the expanding operational condition of a servitizing organisation and its business system to sustain its competitive advantage and win the digital market. Collapse

Topics: mobile system internet of things enterprise information system enterprise resource planning smart device

Methods: action design research experiment qualitative interview longitudinal research design artifact

Theories: resource based view of the firm

Beyond Dashboards? Designing Data Stories for Effective Use in Business Intelligence and Analytics

2023 | European Conference On Information Systems | Citations: 0

Authors: Gunklach, Jonas; Jacob, Katharina; Michalczyk, Sven

Abstract: With the proliferation of Business Intelligence and Analytics, data storytellin ... Expand

Abstract: With the proliferation of Business Intelligence and Analytics, data storytelling has gained increasing importance to improve communicating analytical insights to business users and support decision-making. While conceptual research on data storytelling suggests that these techniques can help improve decisionmaking, there is a lack of prescriptive knowledge on how to design data stories in Business Intelligence and Analytics. Moreover, it is not understood how data stories can facilitate effective use and support decision-making of business users. To address this challenge, we conduct a Design Science Research (DSR) project. Drawing on the theory of effective use and data storytelling techniques, we propose three design principles that we instantiate in a prototype. The results of two focus groups indicate that enhancing dashboards with data storytelling techniques increases transparent interaction and representational fidelity. Our DSR project contributes novel design knowledge for data stories that facilitate effective use. Collapse

Topics: digital dashboard data visualization analytical information system database system decision making

Methods: literature study focus group qualitative interview literature sample design principle

Theories: theory of effective use

Guidance in Business Intelligence & Analytics Systems: A Review and Research Agenda

2023 | European Conference On Information Systems | Citations: 0

Authors: Gunklach, Jonas; Nadj, Mario

Abstract: While the data amount grows exponentially, the number of people with analytical ... Expand

Abstract: While the data amount grows exponentially, the number of people with analytical and technical skills is only slowly increasing. This skill gap is putting pressure on the labor market and increasing the need for personnel with these skills. At the same time, companies are forced to think of alternative ways to empower their less-skilled workforce to take on Business Intelligence and Analytics (BI&A) tasks. One promising attempt to address these challenges may turn to the concept of guidance. However, the current body of research on guidance in BI&A systems is scattered and lacks a structured investigation from which future research avenues can be derived. To address this gap, this article analyzes five categories, namely BI&A phases, guidance degree, guidance generation, user roles, and interactivity form. Reviewing 82 articles, our contribution is to synopsize articles on guidance in BI&A systems and to suggest five research avenues. Collapse

Topics: analytical information system data visualization data quality business intelligence artificial intelligence

Methods: exploratory data analysis machine learning literature sample time series analysis longitudinal research

Empowering Users with Narratives: Examining the Efficacy of Narratives for Understanding Data-Oriented Conceptual Models

2023 | Information Systems Research | Citations: 0

Authors: Hvalshagen, Merete; Lukyanenko, Roman; Samuel, Binny M.

Abstract: With the ongoing digitalization of human society, regular employees (e.g., nonin ... Expand

Abstract: With the ongoing digitalization of human society, regular employees (e.g., noninformation technology experts) become increasingly autonomous and proactive in using organizational data and information technologies to facilitate data-driven actions and insights. This growing autonomy of regular employees (dubbed here, empowered users) in using information technologies creates new challenges. As most empowered users lack sophisticated information technology skills, they struggle to find and access relevant data, understand their meaning, and extract and adapt them to meet their needs. We propose a powerful way to support empowered users with a combination of conceptual models and narratives. A data narrative is a descriptive and textual representation of one or more aspects of data in a domain that is organized and presented as a connected sequence of sentences in a natural language. We assess the efficacy of narrative representations for conceptual modeling cardinality constraints, which are an essential part of understanding data. We conducted two laboratory experiments and found a positive and strong effect for narratives: cardinality constraints that were described in the narratives were better understood than constraints only represented in the model (i.e., script). This effect was robust across cardinalities, measures, script complexities, and familiarity levels with the conceptual modeling grammar. History: Manju Ahuja, Senior Editor; Choon-Ling Sia, Associate Editor. Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1141. Collapse

Topics: data management data literacy database system IT workforce analytical information system

Methods: conceptual modelling experiment entity relationship modeling design science parametric test

Theories: cognitive load theory

Getting Your RPA Priorities Straight with Process Mining: The PLOST Framework

2023 | European Conference On Information Systems | Citations: 0

Authors: Jongeling, Hilde; Lu, Xixi; Beerepoot, Iris; Weerd, Inge van de; Reijers, Hajo

Abstract: Robotic Process Automation (RPA) has gained much attention both in industry and ... Expand

Abstract: Robotic Process Automation (RPA) has gained much attention both in industry and academia. One of the main challenges for a successful implementation of RPA is selecting which tasks should be automated. While different methods exist to identify RPA candidate tasks, they lack in providing objective evidence on why to automate that task. Such objective evidence can be gathered by applying process mining techniques to gain insights into the performance of a process and its tasks. Although this has multiple advantages, it can be time-consuming to analyze all potential processes. We conducted a literature review of existing methods to identify relevant criteria and method components, based on which we designed a framework for identifying and prioritizing suitable RPA candidate tasks: the Prioritized List of Suitable Tasks (PLOST) Framework. The framework includes both qualitative and quantitative assessment criteria and guides the analyst to focus on relevant processes before zooming in on the task level. It also takes into account a customized automation strategy. We conducted a case study to evaluate the applicability and effectiveness of the PLOST Framework and performed thinking-aloud sessions to evaluate its usability, practicality, and completeness. The results show that the framework is easy to apply and feasible. Collapse

Topics: process mining business intelligence organizational value usability digital dashboard

Methods: case study cognitive walkthrough qualitative interview design science literature study

GOVERNANCE IN IMPLEMENTING WEAKLY STRUCTURED INFORMATION SYSTEMS

2023 | European Conference On Information Systems | Citations: 0

Authors: Kandaurova, Maria; Bumann, Adrian

Abstract: The implementation of information systems (IS) is a complex process that requir ... Expand

Abstract: The implementation of information systems (IS) is a complex process that requires appropriate governance to ensure that the technical capabilities of the new IS align with organizational goals. However, existing literature lacks insight into how this alignment occurs when IS are designed as openended, weakly structured systems that offer generic functions, rather than for a singular purpose. To address this gap, this study examines the implementation of a low-code AI platform in eight large companies and the governance practices they employed to align the system's capabilities with their organizational goals. The findings highlight the importance of balanced governance practices that support and constrain the generative capacity of weakly structured IS, while enabling continuous interdependent development of organizational and technical capabilities throughout implementation. This study contributes to IS literature by responding to calls to examine challenges of implementing weakly structured IS and offering practical recommendations for implementation teams and system vendors. Collapse

Topics: low code development platform information technology capability innovation management systems implementation artificial intelligence

Methods: qualitative interview chatbot personal interview computational algorithm case study

Theories: theory of affordance framing theory