Towards More Convenient Services: A Text Analytics Approach to Understanding Service Inconveniences in Digital Platforms

2023 | HICSS | Citations: 0

Authors: Amat-Lefort, N.; Barnes, S.

Abstract: In today's fast-paced world, where time is our most valuable asset, convenience ... Expand

Abstract: In today's fast-paced world, where time is our most valuable asset, convenience is on the rise. This trend has led to a huge growth in digital on-demand services, which target convenience-oriented consumers. Using big data and text analytics, we examine the impact of service inconveniences on customer satisfaction in the context of on-demand food delivery. Building on the Model of Service Convenience and Attribution Theory, we analyze 235,147 user-generated reviews via a combination of keyword-assisted topic modelling and cumulative link model analysis. We introduce the concept of Remote support inconvenience and identify the key topics related to each inconvenience. We find that all service inconveniences negatively influence satisfaction (especially cancelled orders and remote support incidences), and the effects are exacerbated when moderated by stability or controllability attributions. These insights contribute to our theoretical understanding of service inconvenience and can help platforms identify and improve critical areas of their services. Collapse

Topics: user satisfaction customer satisfaction mobile application user-generated content crowdsourcing

Methods: natural language processing topic model exploratory data analysis ANOVA parametric test

Theories: attribution theory

Sensing the Future: A Design Framework for Context-Aware Predictive Systems

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

Authors: Avital, Michel; Chatterjee, Samir; Furtak, Szymon

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ... Expand

Abstract: Sensors embedded in smart objects, smart machines, and smart buildings produce ever-growing streams of contextual data that convey information of interest about their operating environment. Although an increasing number of industries have embraced the utilization of sensors in routine operations, no clear framework is available to guide designers who aim to leverage contextual data collected from these sensors to develop predictive systems. In this paper, we applied design science research methodology to develop and evaluate a general framework that can help designers build predictive systems utilizing sensor data. Specifically, we developed a framework for designing context-aware predictive systems (CAPS). We then evaluated the framework through its application in MAN Diesel & Turbo, which served as a case company. The framework can be generalized into a class of demand-forecasting problems that rely on sensor-generated contextual data. The CAPS framework is unique and can help practitioners make better-informed decisions when designing context-aware predictive systems. Collapse

Topics: data quality evaluation criteria knowledge base systems design systems development

Methods: machine learning design science design artifact data transformation design process

From Insights to INTEL: Evaluating Process Mining Insights with Healthcare Professionals

2023 | HICSS | Citations: 0

Authors: Beerepoot, Iris; Martin, Niels; Koorn, Jelmer Jan

Abstract: As healthcare organisations are looking for ways to improve their processes, pro ... Expand

Abstract: As healthcare organisations are looking for ways to improve their processes, process mining techniques are increasingly being used. Current process mining methods do not offer support for translating process mining insights into actionable improvement ideas. By performing action research at two healthcare organisations, we introduce and illustrate the INTEL funnel, a novel three-staged method consisting of process familiarisation, domain explanation and improvement ideation. Our method complements existing process mining methods and constitutes the first attempt to open the black box regarding the path from process mining insights to actionable process improvement ideas. In this way, it can contribute to a more systematic uptake of process mining in healthcare practice. Collapse

Topics: process mining digital dashboard business process improvement Microsoft Power BI

Methods: action research event log exploratory data analysis synthesis

Incorporating evolutionary adaptions into the cognitive fit model for data visualization

2023 | Decision Support Systems | Citations: 0

Authors: Bina, Saman; Kaskela, Timothy; Jones, Donald R.; Walden, Eric; Graue, William B.

Abstract: With the proliferation of data has arisen an array of information visualization ... Expand

Abstract: With the proliferation of data has arisen an array of information visualization tools to help humans convert data to information for better decision-making. This ever-expanding visualization toolset has outrun the development of theories of data visualization usage for decision support. In the current research, we contribute to the development of visualization theories in two ways. First, we incorporate our understanding of evolutionary adaptations into the cognitive fit theory to explain why 3-D surface graphs often outperform traditional 2-D graphs in various sensemaking tasks. Drawing on geon theory to interpret the 3-D advantage, we develop the concept of geonic/non-geonic information representations and tasks. We tested and found support for our hy­ potheses that geonic representations have a speed advantage for the tasks we studied, derived from the human evolved capacity for geographic orienteering, but accuracy depends on the match of representation and task, as geonic or non-geonic. Our experiment compared the geonic representation (3-D surface graph) to non-geonic planar representations (cluster bar, heat map, and line) in geonic (integration, proportion) and non-geonic atomic (acquisition, comparison) tasks. For our second contribution, we build on this result to expand the cognitive fit model to incorporate classic human information processes and evolutionary adaptations. We suggest that the cognitive fit model can expand to include new advances in neuroscience. We discuss the theoretical and practical implications of our experiment and our expanded model. Collapse

Topics: data visualization sensemaking decision making spreadsheet Python

Methods: experiment parametric test ANOVA exploratory data analysis descriptive statistic

Theories: cognitive fit theory

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

Trust in Online Ride-Sharing Transactions: Impacts of Heterogeneous Order Features

2023 | Journal of Management Information Systems | Citations: 0

Authors: Cheng, Xusen; Fu, Shixuan; Sun, Jianshan; Zuo, Meiyun; Meng, Xiangsong

Abstract: With the development of the sharing economy, online ride-sharing has become a pr ... Expand

Abstract: With the development of the sharing economy, online ride-sharing has become a primary form of commuting. Using secondary transaction data, this study investigates the associations between the heterogeneous features and mutual trust in sharing economy-driven online ride-sharing transactions. Based on an examination of 12,404 ride-sharing orders in Beijing, we propose a set of trust distribution maps using order location data to reveal heterogeneous spatial patterns of the relationship between online ride-sharing transactions and mutual trust. The results show that the historical order completion rate and order distance are positively associated with mutual trust in ride-sharing transactions, whereas order time and departure density negatively and significantly influence mutual trust. Furthermore, we use machine learning algorithms to predict trust. The implications for theory and practice and future research directions are discussed. Collapse

Topics: ride sharing platform sharing platform logistics management geographic information system online review

Methods: machine learning computational algorithm regression analysis method experiment exploratory data analysis

Theories: signaling theory

Teaching Case: Learning Skills of the Data Analytics Lifecycle with Microsoft Power BI and National Parks Data

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

Authors: Collier, Cassie

Abstract: Like many organizations, the U.S. National Parks Service has done an excellent ... Expand

Abstract: Like many organizations, the U.S. National Parks Service has done an excellent job of collecting and storing data for years about variables of interest. However, there are steps beyond the collection and storage of data that must be taken to transform that data into valuable information that can inform strategic business decisions. This teaching case introduces students to the data analytics lifecycle and the various processes for preparing data to make decisions. Students gain a familiarity with the leading data analytics software Microsoft Power BI as well as Microsoft Excel and SQL Server Reporting Services (SSRS) to inform data-driven decisions. This case is relevant to undergraduate and graduate students in information systems and other disciplines prioritizing data analytics. The case was not developed in conjunction with the National Parks Service; the case uses real-world data made publicly available by the National Parks Service but the narrative and questions posed are fictional. Collapse

Topics: data visualization analytical information system

Methods: exploratory data analysis

Breaking bad habits: A field experiment about how routinized work practices can be made more eco-efficient through IS for sensemaking

2023 | Information & Management | Citations: 0

Authors: Degirmenci, Kenan; Recker, Jan

Abstract: We conducted a field experiment to compare the effects of information systems (I ... Expand

Abstract: We conducted a field experiment to compare the effects of information systems (IS) supporting reflective disclosure and information democratization on the sustainability footprint of a routine organizational work practice, paper printing. We find that both sensemaking processes lead to employees reducing their printing; however, the processes are interchangeable and do not mutually reinforce each other’s effects. This finding contrasts a latent assumption of prior research about a co-dependence between reflective disclosure and infor­ mation democratization, and suggests organizations have a choice in how they can design and use IS to help employees make sense of different possibilities for more eco-efficient work. Collapse

Topics: sensemaking electronic mail environmental sustainability system support systems design

Methods: experiment survey field experiment design artifact generalized linear model

Theories: theory of organizational sensemaking

Adopting Learning Analytics to Inform Postgraduate Curriculum Design: Recommendations and Research Agenda

2023 | Information Systems Frontiers | Citations: 0

Authors: Dennehy, Denis; Conboy, Kieran; Babu, Jaganath

Abstract: Understanding student sentiment plays a vital role in understanding the changes ... Expand

Abstract: Understanding student sentiment plays a vital role in understanding the changes that could or should be made in curriculum design at university. Learning Analytics (LA) has shown potential for improving student learning experiences and supporting teacher inquiry. Yet, there is limited research that reports on the adoption and actual use of LA to support teacher inquiry. This four-year longitudinal study captures sentiment of postgraduate students at a university in Ireland, by integrating LA with the steps of teacher inquiry. This study makes three important contributions to teaching and learning literature. First, it reports on the use of LA to support teacher inquiry over four one-year cycles of a Master of Science in Business Analytics programme between 2016 and 2020. Second, it provides evidence-based recommendations on how to optimise LA to support teacher inquiry, with specific attention as to how these can improve the assimilation of LA into the curriculum design and delivery. Third, the paper concludes with a research agenda to help improve the adoption and integration of LA in the future. Collapse

Topics: innovation management Tableau software analytical information system interactive data visualization Python

Methods: qualitative interview Cross-Industry Standard Process for Data Mining sentiment analysis case study design framework

Theories: assimilation theory of learning