Information Systems Literature Research Articles

Recognition in Personal Data: Data Warping, Recognition Concessions, and Social Justice

Data-related harm and injustice are commonly viewed through instrumental, procedural, distributional, or representational theories of social justice. These theories do not account for the social injustice that occurs through the lack of recognition of individuals when data are first conceptualized. We explore the recognition of individuals in data conceptualization by drawing from information systems (IS) literature on data artifacts that acknowledges the fact that data are comprised of semantics and formats. Guided by recognition theory, we studied a project to expand sexual orientation and gender identity (SOGI) data collection at a public, U.S.-based LGBTQ+ welcoming university. We found that while the actors involved worked towards recognizing in SOGI data the fact that identities are layered, non-binary, plural, and fluid, the data themselves still misrecognized individuals due to data warping. We argue that data warping occurs because of recognition concessions between social recognition through data semantics and systems recognition through data formats. Such concessions are both necessary for some recognition but accessory to misrecognition. Our findings have implications for recognition theory, data justice, and information systems research, as well as for personal data in practice.

Navigating the digital classroom: a qualitative content analysis of MOOC discourses in Indian e-newspapers

PurposeThis paper aims to explore and unravel the contents portrayed in online news discourses on massive open online courses (MOOCs). Considering sociological dimensions and journalistic strategies, this study examines how online news media reflects, shapes and informs narratives about the social acceptance and use of the MOOC model of learning.Design/methodology/approachUsing the Gioia methodology as the overarching framework, this study adopted a two-staged qualitative content analysis of 1,162 online news items from the websites of the top seven online English newspapers of India, published between May 2012 and September 2023. In subsequent semi-structured interviews with subject matter experts, broad themes were identified. In addition, this study integrated Van Dijk’s ideological square model with media content theories to comprehensively analyze the intricate complexities in media depictions of MOOCs.FindingsWhile manifest content analysis revealed the emergence of 25 categories, latent content analysis unveiled six broad themes: “announcements, user stages, characteristics, benefits, changing facets, and educational inequalities,” which are associated with the MOOC model. Application of Van Dijk’s model evidenced the usage of a positive self-representation strategy by Indian online news media until mid-2020. The application of media content theories underscored the predominant usage of reframing as a journalistic strategy to maintain reader interest in MOOC-related content in online news items, emphasizing the dynamic nature of media portrayals of social phenomena such as MOOCs.Practical implicationsThe depth of MOOC-related coverage and the increasing number of news articles discussing MOOCs in Indian online media signify a growing acceptance of this educational innovation in society. Insights from emergent themes can aid administrators and platforms to effectively design and deliver future courses. In addition, understanding these themes can guide the development of media strategies to address contextual issues such as educational inequalities arising from MOOCs. This study also focuses on the necessity of upholding journalistic ethics in content dissemination.Originality/valueThis study provides a comprehensive synthesis of various themes and journalistic strategies adopted by online news media over the last decade in MOOC-based narratives in India. Given the distinctive Indian context, wherein MOOCs are growing rapidly amid widening digital inequalities, this research addresses calls within information systems literature to explore this phenomenon. It pioneers the integration of communication and mass media theories to analyze the complex sociological dynamics in news discourses on MOOCs, offering a novel perspective on the intersection of media representation and educational innovation.

Providing organizations with a validated instrument for an Enterprise Service Management capability

In light of new digital opportunities, enterprises require modernization also with regard to intra-organizational business and IT management. Enterprise Service Management (ESM) is an organizational capability aimed at a more efficient and effective IT and business service management in organizations. Although ESM has been recognized as an approach to improve customer and employee satisfaction and to create digital competitive advantage, there is a methodological and analytical void for organizations in how to measure their ESM capability. Motivated by this lack of measurability and tangibility, we aim to empirically validate the ESM capability model. Our contribution to this paper is empirical, as we provide a measurable instrument for further ESM studies. We aim to initiate a broader debate on ESM and thereby add to the scholarly establishment of the concept in the Information Systems and IT Management literature. Practically, we contribute by offering companies a validated and actionable set of ESM characteristics.

Trust and distrust coexistence and change in the adoption of an emerging technology in organizations

Emerging technologies challenge organizations by introducing information systems that transform processes and introduce a series of risks and uncertainties for stakeholders. These conditions make trust and distrust important in the adoption and implementation of technology. Most of the trust in Information Systems literature has focused on building the constructs of trust and distrust between an artifact and the final user, but there is a gap in the analysis of changes in trust and distrust beliefs and their possible coexistence across time. This case study illustrates how trust and distrust manifest across a mobile health monitoring system implementation: the attitudes, objects of trust/distrust, and the changes they exhibit across four stages. The results point at the objects of trust/distrust corresponding to the technology frames that shift during the implementation from an artifact-centric to a more encompassing technology involving other users, programmers, and themselves. The actual technology use leads to changes in perceived risks and expectations, which are fed by the interaction of all users with the system. Behaviors are shaped by coexisting trust and distrust in technology beliefs, which usually compensate for the elements of the technology they distrust. The study concludes that the coexistence of trust and distrust in technology is a constantly shifting phenomenon, leading to a complex yet stabilized use of technology.

Non-user acceptance of autonomous technology: A survey of bicyclist receptivity to fully autonomous vehicles

Whereas the information systems literature mainly has focused on the individual user acceptance of technology, this study focuses on non-user acceptance, termed technology receptivity. Autonomous vehicles (AVs) represent an emerging technology that challenges individual technology user acceptance. Whereas AVs promise several advantages, their success is conditioned on public trust. AVs impact not only those who use them but also those who share the environment with them, such as bicyclists. Empirical research has been characterized by several competing constructs aimed at explaining AV receptivity. In this article, we (1) review extant research on the receptivity of AVs, and (2) develop and validate a model of AV receptivity. A cross-sectional survey of 219 bicyclists showed empirical support for the model. The model can be a useful tool for the AV industry and policymakers in need of assessing the likelihood of success for a wider AV diffusion and help them understand intervention strategies to address populations that may be less inclined to accept the new technology on public roads. We offer several recommendations for future research on refining the measurement instrument and enhancing our understanding of AV and autonomous technology receptivity.

Analyzing and Predicting Consumer Response to Short Videos in E-Commerce

This study analyzes the drivers of and predicts the outcome of consumer response to e-commerce short videos (ESVs) in terms of viewing duration. We first construct a large-scale ESV dataset that contains 23,001 ESVs across 40 product categories. The dataset consists of the consumer response label in terms of average viewing durations and human-annotated ESV content attributes. Relying on the constructed dataset, we employ econometric modeling and deep learning methods to comprehensively understand and predict consumer response to ESVs. First, by employing the mixed-effects model, we find that ESV content attributes for product description, product demonstration, pleasure, and aesthetics are key determinants of ESV viewing duration. Subsample analyses further show the heterogeneous effects of different content attributes on ESV viewing response across product categories. Second, we design a content-based multimodal-multitask framework to predict consumers’ viewing response to ESVs. We propose an information distillation module to extract the shared, special, and conflicted information from ESV multimodal features. Additionally, we employ a hierarchical multitask classification module to capture the feature-level and label-level dependencies. By conducting extensive experiments, we demonstrate that the prediction performance of our proposed framework is superior to that of other state-of-the-art models. Taken together, our paper provides novel theoretical and methodological contributions to the Information Systems and relevant literatures.

Examining Behavioral Intention to Use Mobile Government Services in Bangladesh: An Empirical View

Purpose: This study aims to identify factors influencing users’ behavioural intentions towards mobile government services. Methodology: We develop a research model with information quality, interaction quality, perceived value, power distance, and perceived compatibility. The structural equation modeling method was used to analyze the data collected through an online survey of 301 participants who are mobile government service users in Bangladesh. Findings: The results of this study show that information quality, interaction quality, perceived value, and perceived compatibility have significant and positive influences on behavioural intention to use mobile government services. Practical Implications: This research identified users' specific requirements and expectations about government services, and the necessary actions that the government should take in the event of dissatisfaction among the public. Moreover, the results indicate that giving users succinct and uncomplicated information suitable for standard mobile phones will motivate them to use mobile government services. Originality/Value: This study significantly contributes to information systems literature, particularly in the domain of mobile government services. Researchers developed an integrated model with the relevant dimensions of mobile government services, explaining the variation in the behavioural intention of mobile government services. Limitations: This research has some limitations. Initially, this investigation was confined only to the geographical boundaries of Bangladesh. Furthermore, the study model considers a limited number of factors that impact individuals' behaviour about their intention to use mobile government services. Most of the respondents are under the 20-30 age range; hence, the conclusions may not be relevant for older individuals.

From resistance to acceptance: developing health task measures to boost mHealth adoption among older adults: mixed-methods approach and innovation resistance

PurposeThere are two main objectives in this study. First, we aim to develop a set of constructs for health task management support (HTMS) features to evaluate which health-related tasks are supported by mobile health application (mHealth app) functions. Second, drawing on innovation resistance theory (IRT), we examine the impacts of the newly developed HTMS dimensions on perceived usefulness, alongside other barrier factors contributing to technology anxiety.Design/methodology/approachUsing a mixed-method research design, this research seeks to develop new measurement scales that reflect how mHealth apps support older adults’ health-related needs based on interviews. Subsequently, data were collected from older adults and exploratory factor analysis was used to confirm the validity of the new scales. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data from 602 older adults.FindingsThe PLS-SEM results indicated that medical management task support, dietary task support, and exercise task support were positively associated with perceived usefulness, while perceived complexity and dispositional resistance to change were identified as antecedents of technology anxiety. Perceived usefulness and technology anxiety were found to positively and negatively influence adoption intention, respectively.Originality/valueThis study enriches the information systems literature by developing a multidimensional construct that delineates how older adults’ health-related needs can be supported by features of mHealth apps. Drawing on IRT, we complement the existing literature on resistance to innovation by systematically examining the impact of five types of barriers on technology anxiety.

Review of Federated Learning and Machine Learning-Based Methods for Medical Image Analysis

Federated learning is an emerging technology that enables the decentralised training of machine learning-based methods for medical image analysis across multiple sites while ensuring privacy. This review paper thoroughly examines federated learning research applied to medical image analysis, outlining technical contributions. We followed the guidelines of Okali and Schabram, a review methodology, to produce a comprehensive summary and discussion of the literature in information systems. Searches were conducted at leading indexing platforms: PubMed, IEEE Xplore, Scopus, ACM, and Web of Science. We found a total of 433 papers and selected 118 of them for further examination. The findings highlighted research on applying federated learning to neural network methods in cardiology, dermatology, gastroenterology, neurology, oncology, respiratory medicine, and urology. The main challenges reported were the ability of machine learning models to adapt effectively to real-world datasets and privacy preservation. We outlined two strategies to address these challenges: non-independent and identically distributed data and privacy-enhancing methods. This review paper offers a reference overview for those already working in the field and an introduction to those new to the topic.

“You are you, and I am me”: investigating inter-organisational collaboration between multiple emergency services

PurposeIn the past decade, financial austerity has brought significant pressure upon emergency services in the UK. For the British Government, one approach to alleviate this pressure was to increase collaborative efforts in core functions (e.g. information systems and technology) between multiple organisations. Despite the consensus that collaborations are key in addressing complex problems, the majority fail or become discontinued. This research explores the development of collaborative information infrastructures between one Police Force and two Fire and Rescue Services in the UK, with a specific focus on how the difference in culture, identities and rules and norms, can work in a collaborative emergency service environment.Design/methodology/approachThis study investigated an example of successful development of a collaborative information infrastructure within the context of public safety and, specifically, the technology-based structures that underpin information management. A case study approach was taken, combining semi-structured interviews, document analysis and site visits. The study used activity theory as a theoretical and analytical framework.FindingsThe research revealed that creating a shared identity is not essential in emergency services collaboration, and organisations may maintain their separate identity, given they address other elements of the activity system (e.g. leadership, motivated subjects). However, pursuing this strategy will create multiple tensions throughout the collaboration process.Originality/valueThe study contributes to the information systems literature concerning inter-organisational collaborations in the public sector providing a novel view to the implications of maintaining separate identities, and the significance of misalignment between interacting activity systems.

Information Security Research in the Information Systems Discipline: A Thematic Review and Future Research Directions

Information security continues to grow in importance in all aspects of society and therefore evolves as a prevalent research area. The information systems (IS) discipline offers a unique perspective to move this stream of literature forward. Using a semiautomated thematic analysis approach based on the topic modeling technique, we review a broad range of information security literature to investigate how we may integrate and advance our understanding of information security. Our analysis reveals four major themes, including information security policy (ISP) compliance, motivations and susceptibility, software security decisions, and firm security strategy. We also identify a theme of security in broader contexts, in which studies consider the societal impacts of information security and online hacker behavior. This review contributes to IS literature by 1) synthesizing the broad range of information security research published in the top journals of the field, moving beyond prior reviews focusing on a narrower scope such as individual ISP compliance; 2) identifying major themes and proposing an overarching research framework encompassing these themes and their interconnections, allowing us to envision future research directions; and 3) enumerating a semiautomated topic modeling approach that other researchers can employ.

Sustainability with Limited Data: A Novel Predictive Analytics Approach for Forecasting CO2 Emissions

AbstractUnforeseen events (e.g., COVID-19, the Russia-Ukraine conflict) create significant challenges for accurately predicting CO2 emissions in the airline industry. These events severely disrupt air travel by grounding planes and creating unpredictable, ad hoc flight schedules. This leads to many missing data points and data quality issues in the emission datasets, hampering accurate prediction. To address this issue, we develop a predictive analytics method to forecast CO2 emissions using a unique dataset of monthly emissions from 29,707 aircraft. Our approach outperforms prominent machine learning techniques in both accuracy and computational time. This paper contributes to theoretical knowledge in three ways: 1) advancing predictive analytics theory, 2) illustrating the organisational benefits of using analytics for decision-making, and 3) contributing to the growing focus on aviation in information systems literature. From a practical standpoint, our industry partner adopted our forecasting approach under an evaluation licence into their client-facing CO2 emissions platform.

How does big data analytics capability affect firm performance? Unveiling the role of organisational resilience and environmental dynamism

ABSTRACT In a dynamic environment, organisations are increasingly compelled to utilise big data analytics (BDA) to develop organisational resilience, which will help them weather disruptions and gain competitiveness. By investigating 213 Chinese firms across a diverse array of industries, this study seeks to uncover the mechanisms and boundary conditions through which BDA capability affects firm performance. Drawing on the organisational capabilities-based theory and information technology-enabled organisational capabilities perspective, we both theoretically and empirically verify that two types of organisational resilience (i.e., proactive resilience and reactive resilience) mediate the relationship between BDA capability and firm performance. Our findings reveal that environmental dynamism positively moderates the impact of BDA capability on reactive resilience and strengthens the positive mediation effect of reactive resilience on the relationship between BDA capability and firm performance. This study contributes to the information systems literature by theoretically and empirically clarifying the pivotal roles of proactive resilience and reactive resilience as mediating mechanisms and by describing the contingent effect of environmental dynamism on the relationship between BDA capability and performance. The results provide new insights into how managers deploy BDA to achieve superior performance in a dynamic environment.

Evaluasi Pengelolaan Sampah Menggunakan Climate Resilient and Inclusive Cities (CRIC) Waste Assessment Tool Kota Palembang

Waste is a problem that cannot be ignored because it is always generated in all aspects of life. The Climate Resilient and Inclusive Cities CRIC Waste Assessment Tool helps in analyzing the current situation in the city and provides important and practical recommendations from both technical aspects, governance, and social issues. The research aims to evaluate urban waste management using the Climate Resilient and Inclusive Cities (CRIC) Waste Assessment Tool based on management technology in Palembang City. A quantitative strategy was used in this research, along with a descriptive and verification research method. Secondary data is taken from the national waste management information system and other literature to fill in the CRIC Waste Assessment Tool application. Data analysis using CRIC Tool covers waste management, governance, economy and knowledge of citizens, GHG emissions. The results of measuring waste management performance with CRIC show that waste management in the city is still low, most of the waste is disposed of uncontrollably, resulting in SLCPs. Waste banks and TPS3R are still lacking. Achievement of waste management to reduce greenhouse gas emissions has only reached 50% of the recommended target. Proper waste handling is still lacking, such as reduced dumping, open burning, and better composting practices. This will support modifications in waste handling from the community, which can support waste management technology development.

Ignoring and collective passivity in relation to information systems: How actors avoided engagement with data about wait times in Swedish healthcare

Although digital technology (DT) is often introduced with the aim of enhancing organizational knowledge transfer and learning, these aims often fail to materialize. The information systems (IS) literature attributes such unexpected outcomes to inappropriate technology design and implementation, as well as to overuse, misuse, and non-use of technology. However, we know little about how actors misuse or fail to use technology and data, thereby failing to acquire and act upon the knowledge necessary to achieve organizational learning. Leveraging the literature on strategic ignorance, we explore how actors expected to use technology for learning purposes justify their non-engagement with it. Studying an implementation of a DT with the purpose of facilitating organizational learning on basis of provided data in health care, we identify seven ignoring justifications through which the target users of the DT avoided key knowledge acquisition and knowledge-based action activities. These sensemaking behaviors accumulated to a state of collective passivity in relation to the DT. Our conceptualization contributes to and connects theories of organizational learning in the IS literature and strategic ignoring.

Dynamic capabilities for nimbleness and resilience in a continuous digital transformation: action design research in an Australian financial services organisation

PurposeThe research aims to understand the co-existence of nimbleness and resilience in a continuous digital transformation, along with the dynamic capabilities needed to balance the challenges of their co-existence.Design/methodology/approachThe current study draws on dialogical action design research (D-ADR) to investigate interactions among practitioners and executives. Data are collected from a major Australian financial services organisation (FSO) and many international experts.FindingsThe study presents a framework, the continuous transformation model (CTM), to describe digital transformation within an FSO context, emphasising nimbleness and resilience as its foundational pillars. This framework facilitates the identification of the critical role of organisational capabilities in managing continuous digital transformation, supported by dynamic IT capabilities. More importantly, the findings underscore how these capabilities enable managers to effectively balance the coexistence of nimbleness and resilience.Research limitations/implicationsThe CTM contributes to the enterprise information systems literature by offering a coherent understanding of balancing resilience and nimbleness to succeed in digital transformation. In particular, the research model elucidates the relationship between dynamic capabilities and continuous digital transformations.Practical implicationsDigital transformations are not a one-off exercise. Managers in the FSO context must cultivate their organisational capabilities to achieve nimbleness and resilience during their digital transformation journey.Originality/valueThe relationship between dynamic capabilities and continuous digital transformation sheds light on establishing successful management processes within FSOs.

Assessing the Impact of Recommendation Novelty on Older Consumers: Older Does Not Always Mean the Avoidance of Innovative Products.

Personalized recommendations that use digital technologies to predict user interests and preferences and give guiding conclusions have become a widely used digital marketing tool on e-commerce platforms. Given that existing consumer behavior research has not reached a consensus on the relationship between age and the adoption of innovative products, whether recommendation novelty can stimulate older consumers' acceptance of innovative products remains uncertain. Grounded in the aging and social influence literature, this experimental study investigated the moderating role of individual cognitive age on the impact of recommendation novelty on consumer perceptions regarding stereotype threat and receptiveness to innovativeness. An experiment involving 239 online shoppers was conducted to investigate the experiences of cognitively younger and older adults while using low or high levels of recommendation novelty designed for this study. Results reveal the tension for older adults when using highly recommended novelty, as they perceive these to be more of a stereotype threat, but they also have a higher level of receptiveness to innovativeness. This finding is contrary to the common belief that "the older the consumer, the less receptive to innovativeness", providing novel insight into the information systems literature. Theoretically, this research shows how increasing the level of recommended novelty affects stereotype threat and receptiveness to innovativeness (of consumers of different cognitive ages). For practitioners, the results provide important guidelines on the kind of personalized recommendations that are appropriate for consumers with different cognitive ages.

Developing data analytics capabilities: integrating the information systems success model and the resource-based view

PurposeThe information systems (IS) literature has indicated the importance of data analytics capabilities (DAC) in improving business performance in organizations. The literature has also highlighted the roles of organizations’ data-related resources in developing their DAC and enhancing their business performance. However, little research has taken resource quality into account when studying DAC for business performance enhancement. Therefore, the purpose of this paper is to understand the impact of resource quality on DAC development for business performance enhancement. Design/methodology/approachWe studied DAC development using the resource-based view and the IS success model based on empirical data collected via 19 semi-structured interviews.FindingsOur findings show that data-related resource (including data, data systems, and data services) quality is vital to the development of DAC and the enhancement of organizations’ business performance. The study uncovers the factors that make up each quality dimension, which is required for developing DAC for business performance enhancement.Originality/valueUsing the resource quality view, this study contributes to the literature by exploring the role of data-related resource quality in DAC development and business performance enhancement.

Examining consumer behavior towards adoption of quick response code mobile payment systems: transforming mobile payment in the fintech industry

The quick response (QR) code-enabled mobile payment has gained large attention from academicians and policymakers due to its fast, convenience, and usefulness. However, acceptance of this technology among consumers is limited and rare in a few cases. Therefore, current research attempts to gain insight into factors that influence consumer behavior to adopt QR code-enabled mobile payment. This research has developed an integrated research framework that combines the technology acceptance model, theory of reasoned action, transaction speed, convenience, and innovativeness to investigate consumer behavior to adopt QR code mobile payment. In addition to that moderating effect of transaction speed is tested between consumer attitude and intention to adopt QR code-driven mobile payment. This study empirically investigates consumer attitudes and intention to adopt the QR mobile payment system with 216 responses. Findings of the statistical analysis have revealed that perceived usefulness, perceived ease of use, convenience, subjective norms, and innovativeness explained a substantial variance R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}^{2}$$\\end{document} 52.3% in measuring user attitude to adopt QR code-enabled mobile payment. Practically, this study suggests that policymakers should pay attention to perceived convenience, transaction speed, subjective norm, and perceived usefulness to boost consumer attitude and intention to adopt QR-enabled mobile payment. This study is unique as it integrates the technology acceptance model and theory of reasoned action to investigate consumer behavior towards the adoption of QR code mobile payment. This study is also valuable as it examines the moderating effect of transaction speed between consumer attitude to accept QR code and their intention to adopt QR code-driven mobile payment and adds a new dimension to information system literature.

A qualitative systematic review of trust in technology

Although many information systems (IS) scholars have researched the antecedents and consequences of trust in technology, the sheer amount of work published, authors’ use of inconsistent construct terms, and variations in conceptualization and measurement make it difficult to compare and aggregate findings across studies. To provide scholars with an overview of the literature, we performed a systematic qualitative review of the IS literature. The goal of our review was to identify the antecedents and consequences of trust in technology that have received frequent empirical support, as well as those for which the evidence is not yet conclusive. To that end, we curated a glossary of unique construct terms and summarized the results of 241 relationships tested in 62 empirical research articles (both quantitative and qualitative) from the AIS “Basket of Eight” journals. From these, we identified 62 unique relationships: 22 are well-supported, 6 are supported by suggestive evidence, and 34 have received little support. These relationships summarize what is well-known and less well-known within the literature. By taking stock, we prepare a path for future research on the phenomenon of trust in the context of emerging technologies (e.g., artificial intelligence and blockchain). We conclude the paper with opportunities and directions for future research.