showing 35 related works from this author
Organizational Culture Challenges of Adopting Big Data: A Systematic Literature Review
2019
Part 2: Big Data Analytics; International audience; The interest of adopting big data (BD) in organizations has emerged in recent years. Even though many organizations have attempted to adopt BD, the benefits gained by this investment has been limited, and organizations struggle to fully utilize the potential of BD. There has been done several studies on the different challenges and benefits that may occur during the process of adopting and using BD. One major factor that has been discussed in the literature to overcome such challenges has been organizational culture. This paper aims to provide a systematic literature review that reports the organizational culture’s impact on BD adoption th…
Correction to: Digital Transformation for a Sustainable Society in the 21st Century
2019
Developing human/AI interactions for chat-based customer services: lessons learned from the Norwegian government
2022
Advancements in human/AI interactions led to smartification of public services via the use of chatbots. Here, we present findings from a clinical inquiry research project in a key public service organisation in Norway. In this project, researchers and practitioners worked together to generate insights on the action possibilities offered to human service agents by chatbots and the potential for creating hybrid human/AI service teams. The project sensitised service agents to discover affordances based on their actual practices, rather than on the predefined use of chatbots. The different affordances identified can be useful for practitioners who design and deploy chatbot-based services. The a…
Seeking Information on Social Commerce: An Examination of the Impact of User- and Marketer-generated Content Through an Eye-tracking Study
2021
Following the growing popularity of social commerce sites, there is an increased interest in understanding how consumers decide what products to purchase based on the available information. Consumers nowadays are confronted with the task of assessing marketer-generated (MGC) as well as user-generated information (UGC) in a range of different forms to make informed purchase-related decisions. This study examines the information types and forms that influence consumers in their decision-making process on social commerce. Building on uses and gratifications and dual-process theories, we distinguish between marketer and user generated content, and differentiate formats into informational and no…
Understanding Civic Engagement on Social Media Based on Users’ Motivation to Contribute
2021
Social media offer various opportunities for civic engagement by, e.g., liking, sharing, or posting relevant content. Users’ motivation to contribute to relevant topics is quite divers and can stem from an intrinsic motivation to do good or external incentives such as being recognised and rewarded by other users. In our study, we adopt self-determination theory, which defines motivation as broad continuum ranging from intrinsic motivation to external regulation. We conducted a quantitative survey with 667 Facebook users to identify how the different kinds of motivation impact the users’ behaviour in terms of reading, liking, sharing, commenting, and posting topics relevant to civic engageme…
AI-enabled adaptive learning systems: A systematic mapping of the literature
2021
Abstract Mobile internet, cloud computing, big data technologies, and significant breakthroughs in Artificial Intelligence (AI) have all transformed education. In recent years, there has been an emergence of more advanced AI-enabled learning systems, which are gaining traction due to their ability to deliver learning content and adapt to the individual needs of students. Yet, even though these contemporary learning systems are useful educational platforms that meet students’ needs, there is still a low number of implemented systems designed to address the concerns and problems faced by many students. Based on this perspective, a systematic mapping of the literature on AI-enabled adaptive le…
Big data and business analytics: A research agenda for realizing business value
2020
Author's accepted version (post-print). Available from 19/11/2022.
Identifying the combinations of motivations and emotions for creating satisfied users in SNSs: An fsQCA approach
2020
Social Networking Sites (SNSs) play an important role in our daily lives and the number of their users increases regularly. To understand how users can be satisfied in the complex digital environment of SNSs, this study examines how motivations and emotions combine with each other to explain high satisfaction. Users’ motivations comprise four attributes, entertainment, information, social-psychological, and convenience. Emotions are divided into their two main categories, that is positive and negative emotions. We draw on complexity and configuration theories, present a conceptual model along with propositions and perform a fuzzy-set qualitative comparative analysis (fsQCA). Through an empi…
Correction to: Responsible Design, Implementation and Use of Information and Communication Technology
2020
Key Influencing Factors in Early-Stage Hardware Startups: A Trilateral Model of Speed, Resource, and Quality
2020
Hardware startups, i.e., wearable devices, robotics, and Internet of Things, are a significant sector of technology startups, in which software development is relevant and needed. Compared to pure software startups, hardware development in startup contexts lacks a systematic approach and guidelines. This chapter describes an empirical model that captures common elements in product development approaches among many hardware startups. Grounded from insights of 18 active hardware startups, we constructed a trilateral model of resource, speed, and quality in early-stage product development. For startups with relevant contexts, the work suggests the preparation of internal, external resources, a…
Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing
2021
Abstract The increasing interest in fuzzy-set Qualitative Comparative Analysis (fsQCA) in Information Systems and marketing raises the need for a tutorial paper that discusses the basic concepts and principles of the method, provide answers to typical questions that editors, reviewers, and authors would have when dealing with a new tool of analysis, and practically guide researchers on how to employ fsQCA. This article helps the reader to gain richer information from their data and understand the importance of avoiding shallow information‐from‐data reporting. To this end, it proposes a different research paradigm that includes asymmetric, configurational‐focused case‐outcome theory construc…
Chasing Metaverses: Reflecting on Existing Literature to Understand the Business Value of Metaverses
2022
AbstractMetaverses refer to immersive virtual worlds in which people, places, and things of the physical world are represented by their digital representations. The wide adoption of metaverses is expected to widely disrupt the way we interact in the virtual world by elevating our online interactive experiences and bringing a plethora of implications for businesses. Following a structured literature review of related research published in the last decade, we shed light on our current understanding of metaverses and reflect on the potentially transformative value of metaverses for businesses in the near future. We draw on an established research framework to organize the insights of existing …
Exploring the relationship between big data analytics capability and competitive performance : The mediating roles of dynamic and operational capabil…
2020
A central question for information systems (IS) researchers and practitioners is if, and how, big data can help attain a competitive advantage. To address this question, this study draws on the resource-based view, dynamic capabilities view, and on recent literature on big data analytics, and examines the indirect relationship between a firm’s big data analytics capability (BDAC) and competitive performance. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which, in turn, positively impact marketing and technological capabilities. To test our proposed research model, we used survey data from 202…
Digital Transformation for a Sustainable Society in the 21st Century
2019
Revisiting the Trust–Commitment and Export Performance Link: A Qualitative Comparative Analysis (QCA) Approach
2020
This research revisits the role of different foci of trust (interpersonal and inter-organizational), commitment (affective and calculative) and relationship lengths (inter-organizational and interpersonal) then on export relationship performance. 142 Ecuadorian non-oil exporters completed a self-administered questionnaire. This study applies fuzzy-set qualitative comparative analysis (fsQCA) and the findings help to re-establish the need for both trust dimensions and affective commitment in exporter–importer relationships. This research found three possible configurations of achieving high export relationship performance. The managerial implications noted that export managers should nurture…
Fitbit for learning: Towards capturing the learning experience using wearable sensing
2020
The assessment of learning during class activities mostly relies on standardized questionnaires to evaluate the efficacy of the learning design elements. However, standardized questionnaires pose additional strain on students, do not provide “temporal” information during the learning experience, require considerable effort and language competence, and sometimes are not appropriate. To overcome these challenges, we propose using wearable devices, which allow for continuous and unobtrusive monitoring of physiological parameters during learning. In this paper we set out to quantify how well we can infer students’ learning experience from wrist-worn devices capturing physiological data. We coll…
Wearable Sensing and Quantified-self to explain Learning Experience
2022
Author's accepted manuscript © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The confluence of wearable technologies for sensing learners and the quantified-self provides a unique opportunity to understand learners’ experience in diverse learning contexts. We use data from learners using Empatica Wristbands and self-reported questionnaire. We compute stress, ar…
Fake news on Facebook and their impact on supply chain disruption during COVID-19
2022
AbstractSocial media (SM) fake news has become a serious concern especially during COVID-19. In this study, we develop a research model to investigate to what extent SM fake news contributes to supply chain disruption (SCD), and what are the different SM affordances that contribute to SM fake news. To test the derived hypotheses with survey data, we have applied partial least square based structural equation modelling (PLS-SEM) technique. Further, to identify how different configurations of SC resilience (SCR) capabilities reduce SCD, we have used fuzzy set qualitative comparative analysis (fsQCA). The results show that SM affordances lead to fake news, which increases consumer panic buying…
Explaining User Experience in Mobile Gaming Applications: An fsQCA Approach
2019
Purpose In the complex ecosystem of mobile applications multiple factors have been used to explain users’ behavior, without though focusing on how different combinations of variables may affect user behavior. The purpose of this paper is to show how price value, game content quality, positive and negative emotions, gender and gameplay time interact with each other to predict high intention to download mobile games. Design/methodology/approach Building on complexity theory, the authors present a conceptual model followed by research propositions. The propositions are empirically validated through configurational analysis, employing fuzzy-set qualitative comparative analysis (fsQCA) on 531 a…
Tension in the data environment: How organisations can meet the challenge
2022
Big Data is becoming ubiquitous - widely applied across organisations, industry sectors and society. However, the opportunities and risks it presents are not yet fully understood. In this paper we identify and explore the tensions that Big Data can create at multiple levels, focusing on the need for organisations to meet the challenges that can arise. We draw on insights from twelve papers published in the Special Issue of Technological Forecasting & Social Change entitled “Tension in the Data Environment: Can Organisations Meet the Challenge?” in order to build a ‘Multi-Layer Tensions Model’ that highlights key pressures and challenges in the BD environment. We find evidence of tensions of…
Big Data Analytics Affordances for Social Innovation: A Theoretical Framework
2021
This paper proposes a theoretical framework to identify the mechanisms by which actors perceive the affordances of big data analytics (BDA) and how institutional voids and supports enable or hinder the actualisation of those perceived affordances. In doing so, we contribute to identifying the missing link needed to understand the social innovation process in relation to BDA. The framework paves the ground towards understanding the institutionalization process of social innovation and its implications for research and practice.
Rethinking Learning Design in IT Education During a Pandemic
2021
Maintaining high-quality teaching and learning in the times of a pandemic poses a huge challenge to education systems. To scaffold adequate practices in our courses during the pandemic, more advanced, and fine-grained “learning design” is needed than providing the learning objectives and learning materials of the course and defining the deliverables and assignments. In this paper, we leverage on our experience with putting into practice different learning designs and technologies, in various information technology (IT) contexts and discuss how IT educators can further reflect on the learning design of their courses and scaffold fully remote or blended learning approaches to accommodate thei…
Systematic literature review of E-learning capabilities to enhance organizational learning
2021
AbstractE-learning systems are receiving ever increasing attention in academia, business and public administration. Major crises, like the pandemic, highlight the tremendous importance of the appropriate development of e-learning systems and its adoption and processes in organizations. Managers and employees who need efficient forms of training and learning flow within organizations do not have to gather in one place at the same time or to travel far away to attend courses. Contemporary affordances of e-learning systems allow users to perform different jobs or tasks for training courses according to their own scheduling, as well as to collaborate and share knowledge and experiences that res…
Affordances in Human-Chatbot Interaction: A Review of the Literature
2021
The present study advances our understanding of human-AI interactions, by identifying and analyzing chatbot affordances in prior research. The results of this review consolidate research findings on chatbots’ affordances, which must be taken into consideration when chatbot-based services are designed and deployed. Specifically, the review of state-of-the-art literature led to the identification of nine high level affordances: Human Like Conversing, Assistance Provision, Facilitation, Distilling Information, Enriching Information, Context Identification, Personalization, Fostering Familiarity and Ensuring Privacy. Our contribution is twofold. First, we map the chatbot affordances identified …
Technology-Enhanced Organizational Learning: A Systematic Literature Review
2019
Part 9: Learning and Education; International audience; E-Learning systems are receiving ever increasing attention in, academia, businesses as well as in public administrations. Managers and employee who need efficient forms of training as well as learning flow within the organization, do not have to gather in a place at the same time, or to travel far away for attending courses. Contemporary affordances of e-learning systems allow them to perform different jobs or tasks for training courses according to their own scheduling, as well as collaborate and share knowledge and experiences that results rich learning flow within the organization. The purpose of this article is to provide a systema…
Investigating Aid Effectiveness in Developing Countries: The Case of Nepal
2020
Foreign aid serves as an important source of capital for any developing or under-developed country. It is very important to see how the recipient country can utilize this aid in the economic upliftment of the nation. Taking a case of Nepalese economy, this paper investigates the effectiveness of foreign aid in developing countries. The result from Johansen’s cointegration test reveals that foreign aid independently is not adequate for the economic growth. Increased capital and technological infrastructures, improved skills on human capital, on the other hand, significantly changes the result for the positive aid impact on growth in the long run. Therefore, we can conclude that a good policy…
Achieving agility and quality in product development -an empirical study of hardware startups
2020
Context: Startups aim at scaling their business, often by developing innovative products with limited human and financial resources. The development of software products in the startup context is known as opportunistic, agility-driven, and with high tolerance for technical debt. The special context of hardware startups calls for a better understanding of state-of-the-practice of hardware startups’ activities. Objective: This study aimed to identify whether and how startups can achieve product quality while maintaining focus on agility. Method: We conducted an exploratory study with 13 hardware startups, collecting data through semi-structured interviews and analysis of documentation. We pro…
Learning Environments in the 21st Century: A Mapping of the Literature
2020
Education has been transformed by significant breakthroughs in AI, mobile internet, cloud computing and Big Data technologies. More personalized educational settings are developed by increasingly integrating contemporary learning environments with new technologies. However, few examples of executed AI enabled learning interventions have been identified. Therefore, a mapping of literature on AI enabled learning systems was done. 121 studies published in the last five years were analyzed. This paper presents a discussion regarding on what mainly AI enabled contemporary learning environments are designed to achieve. The major contribution of the study is bringing awareness to researchers and s…
How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data
2020
This study examines how quickly we can predict users’ ratings on visual aesthetics in terms of simplicity, diversity, colorfulness, craftsmanship. To predict users’ ratings, first we capture gaze behavior while looking at high, neutral, and low visually appealing websites, followed by a survey regarding user perceptions on visual aesthetics towards the same websites. We conduct an experiment with 23 experienced users in online shopping, capture gaze behavior and through employing machine learning we examine how fast we can accurately predict their ratings. The findings show that after 25 s we can predict ratings with an error rate ranging from 9% to 11% depending on which facet of visual ae…
Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy
2022
FNEGE 3, HCERES A, ABS 2; International audience; The metaverse has the potential to extend the physical world using augmented and virtual reality technologies allowing users to seamlessly interact within real and simulated environments using avatars and holograms. Virtual environments and immersive games (such as, Second Life, Fortnite, Roblox and VRChat) have been described as antecedents of the metaverse and offer some insight to the potential socio-economic impact of a fully functional persistent cross platform metaverse. Separating the hype and “meta…” rebranding from current reality is difficult, as “big tech” paints a picture of the transformative nature of the metaverse and how it w…
Utilizing Multimodal Data Through fsQCA to Explain Engagement in Adaptive Learning
2020
Investigating and explaining the patterns of learners’ engagement in adaptive learning conditions is a core issue towards improving the quality of personalized learning services. This article collects learner data from multiple sources during an adaptive learning activity, and employs a fuzzy set qualitative comparative analysis (fsQCA) approach to shed light to learners’ engagement patterns, with respect to their learning performance. Specifically, this article measures and codes learners’ engagement by fusing and compiling clickstreams (e.g., response time), physiological data (e.g., eye-tracking, electroencephalography, electrodermal activity), and survey data (e.g., goal-orientation) to…
Multimodal data as a means to understand the learning experience
2019
Most work in the design of learning technology uses click-streams as their primary data source for modelling & predicting learning behaviour. In this paper we set out to quantify what, if any, advantages do physiological sensing techniques provide for the design of learning technologies. We conducted a lab study with 251 game sessions and 17 users focusing on skill development (i.e., user's ability to master complex tasks). We collected click-stream data, as well as eye-tracking, electroencephalography (EEG), video, and wristband data during the experiment. Our analysis shows that traditional click-stream models achieve 39% error rate in predicting learning performance (and 18% when we perf…
The Role of Big Data in Addressing Societal Challenges: A Systematic Mapping Study
2019
Part 2: Big Data Analytics; International audience; Big data has recently become the focus of academic and corporate investigation due to its high potential in generating business and social value. We have done a systematic mapping of the literature related to big data and its applications leading to social change through the lens of social innovation. The search strategy initially resulted in 593 papers, and after applying inclusion exclusion criteria a total of 156 papers were mapped; 59% of which were identified as empirical studies. This mapping investigated the publication frequency of the studies, research approach and contributions, research areas and article distribution per journal…
Goalkeeper: A Zero-Sum Exergame for Motivating Physical Activity
2021
Incentives and peer competition have so far been employed independently for increasing physical activity. In this paper, we introduce Goalkeeper, a mobile application that utilizes deposit contracts for motivating physical activity in group settings. Goalkeeper enables one to set up a physical exercise challenge with a group of peers that deposit a fixed amount of money for participating. If a peer fails to complete the challenge, Goalkeeper redistributes their deposit to those who managed to complete it (i.e., zero-sum game). We evaluated the potential of Goalkeeper in increasing physical activity with a total of 50 participants over the course of 2 months. Our findings suggest that deposi…
How Quickly Can We Predict Users’ Ratings on Aesthetic Evaluations of Websites? Employing Machine Learning on Eye-Tracking Data
2020
This study examines how quickly we can predict users’ ratings on visual aesthetics in terms of simplicity, diversity, colorfulness, craftsmanship. To predict users’ ratings, first we capture gaze behavior while looking at high, neutral, and low visually appealing websites, followed by a survey regarding user perceptions on visual aesthetics towards the same websites. We conduct an experiment with 23 experienced users in online shopping, capture gaze behavior and through employing machine learning we examine how fast we can accurately predict their ratings. The findings show that after 25 s we can predict ratings with an error rate ranging from 9% to 11% depending on which facet of visual ae…