The technostress trifecta ‐ techno eustress,techno distress and design: Theoretical directions and an agenda for research

Technostress—defined as stress that individuals experience due to their use of Information Systems—represents an emerging phenomenon of scholarly investigation. It examines how and why the use of IS causes individuals to experience various demands that they find stressful. This paper develops a framework for guiding future research in technostress experienced by individuals in organizations. We first review and critically analyse the state of current research on technostress reported in journals from the IS discipline and the non‐IS disciplines that study stress in organizations (eg, organizational behaviour and psychological stress). We then develop our framework in the form of the “technostress trifecta”—techno‐eustress, techno‐distress, and Information Systems design principles for technostress. The paper challenges 3 key ideas imbued in the existing technostress literature. First, it develops the argument that, in contrast to negative outcomes, technostress can lead to positive outcomes such as greater effectiveness and innovation at work. Second, it suggests that instead of limiting the role of IS to that of being a stress creator in the technostress phenomenon, it should be expanded to that of enhancing the positive and mitigating the negative effects of technostress through appropriate design. Third, it lays the groundwork for guiding future research in technostress through an interdisciplinary framing that enriches both the IS and the psychological stress literatures through a potential discourse of disciplinary exchange.     

Remote research methods for Human–AI–Robot Teaming

This study focuses on methodological adaptations and considerations for remote research on Human–AI–Robot Teaming (HART) amidst the COVID-19 pandemic. Themes and effective remote research methods were explored. Central issues in remote research were identified, such as challenges in attending to participants' experiences, coordinating experimenter teams remotely, and protecting privacy and confidentiality. Instances of experimental design overcoming these challenges were identified in methods for recruitment and onboarding, training, team task scenarios, and measurement. Three case studies are presented in which interactive in-person testbeds for HART were rapidly redesigned to function remotely. Although COVID-19 may have temporarily constrained experimental design, future HART studies may adopt remote research methods to expand the research toolkit.     

Can crisis management teams mitigate COVID-19's effects? A comparative case study between China and the United States

The COVID-19 pandemic has been the world's greatest challenge since World War II. As an unprecedented global public health crisis, crisis management teams (CMTs) in the infected countries need to rethink to cope with the similar uncertainty and urgency of the ongoing COVID-19 pandemic. The shared context of COVID-19 allows us to explore a cross-nation study of different constructs and CMT to communicate information about crises with the public effectively. Since the pandemic affected all countries, the comparison is warranted. Can CMTs mitigate the effects of COVID-19? Based on the analysis of China and the US cases, our study explores how shared and common knowledge cognition among crisis responders plays a pivotal role in effective CMTs' communication while technological failures and inadequate information disrupt the system, worsening pandemics like COVID-19. Furthermore, organizational dysfunction, such as institutional fragmentation, regulatory hurdles and bureaucratic arrogance, impede effective communication between CMTs. However, effective coordination and decisive leadership could improve coordination effectiveness and reduce crisis costs.     

Fighting COVID-19 and Future Pandemics With the Internet of Things: Security and Privacy Perspectives

The speed and pace of the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; also referred to as novel Coronavirus 2019 and COVID-19) have resulted in a global pandemic, with significant health, financial, political, and other implications. There have been various attempts to manage COVID-19 and other pandemics using technologies such as Internet of Things (IoT) and 5G/6G communications. However, we also need to ensure that IoT devices used to facilitate COVID-19 monitoring and treatment (e.g., medical IoT devices) are secured, as the compromise of such devices can have significant consequences (e.g., life-threatening risks to COVID-19 patients). Hence, in this paper we comprehensively survey existing IoT-related solutions, potential security and privacy risks and their requirements. For example, we classify existing security and privacy solutions into five categories, namely: authentication and access control solutions, key management and cryptography solutions, blockchain-based solutions, intrusion detection systems, and privacy-preserving solutions. In each category, we identify the associated challenges. We also identify a number of recommendations to inform future research.      

Service innovation in Hong Kong organizations: Enablers and challenges to design thinking practices

East-Asian practitioners aspiring to engage in the design thinking (DT) practice—a human-centred approach to innovation developed and primarily used in Western cultures—may experience a “cultural clash” or “cultural misfit” that may inhibit the acceptance of DT logic. To tap into this still underexplored terrain, this qualitative study explores the enablers and challenges of effective DT practice in achieving service innovation in Hong Kong organizations. Based on a dozen in-depth interviews, we identified numerous sociocultural and institutional enablers and challenges, which we interpreted based on the postulates of structuration theory proposed by Giddens. Our conceptualization and empirical investigation of DT through a practice lens offers a new perspective when studying the contextual antecedents of DT. Specifically, the findings show that the choice to engage in DT practice is shaped by cultural specifics in the plurality of influences that move beyond the Western perspective and previous DT studies. From a practical point of view, our research informs policymakers and managers about the importance of being culturally sensitive and humanizing digital transformation when organizing service innovation.     

Mobilising information systems scholarship for a circular economy: Review,synthesis, and directions for future research

One of today's grand societal challenges is to replace the current ‘take‐make‐waste’ economic model with a circular economic model that allows a gradual decoupling of economic activities from the consumption of finite virgin resources. While circular economy (CE) scholars have long lauded digital technologies such as sensors, distributed ledgers, or platforms as key enablers, our own community has not fully explored the potentials of information systems (IS) for a CE. Considering recent technological advances in software and hardware and our history of helping address wicked challenges, we believe the time is ripe to mobilise IS scholarship for a CE. Our findings from an interdisciplinary literature review show that research has primarily examined IS potentials for increasing efficiency of isolated intra‐organisational processes while neglecting the larger sustainability potential of IS to establish circular material flows—that is, slow down and close material loops across entire product lifecycles. In response, we propose directions for IS research that develop our knowledge of how IS can help understand and enact circular material flows to intensify and extend use of products and components and recycle waste materials. Our directions offer pathways to building and evaluating the problem‐solution pairing that could characterise a prolific CE‐IS relationship.     

Configuration information system architecture: Insights from applied action design research

One of the critical information systems that enables service resilience is the service configuration information system (CiS). The fundamental challenge for organisations is the effective designing and implementation of the CiS architecture. This paper addresses this important research problem and reports insights from a completed applied action design research (ADR) project in an Australian financial services organisation. This paper aims to provide guidance to researchers and practitioners contemplating ADR, rooted in the organisational context, for practice-oriented academia-industry collaborative research. This research also contributes in terms of the CiS reference architecture design knowledge and demonstrates the applicability of the ADR method.     

Towards a framework for energy-aware information systems in manufacturing

Environmental concerns, stricter legislation and inflated energy costs, together yield energy efficiency as an important pillar for virtually every industrial sector. Mindful of this challenge, ISs can act as enablers of energy-based management and intelligent decision support. Based on empirical evidence through two case studies combined with the design of a system prototype, this paper identifies those major functionalities that suffice to characterize an IS as ‘energy-aware’ in manufacturing. The functionalities are classified into two broad categories: (a) energy monitoring and (b) energy-aware analytics and are then combined into a high-level architecture. As a prerequisite for deploying such functionalities, this research presents also an approach integrating energy and operational information flows. Beyond that, the technologies that support the real-time and large-scale handling of energy data are provided. Our effort scales up to introduce a generic framework of a case-independent energy-aware IS.     

Developing design concepts in a cloud computing environment: creative interactions and brainstorming modalities

Abstract

This article presents the key components required to properly understand remote creative interactions associated with three collective design stages: co-definition; the ideas co-production; and the co-evaluation in the formulation of a design concept. We compare five brainstorming modalities: traditional brainstorming—graphical interaction, reverse brainstorming, brainwriting and brainsketching—adopted by six delocalised teams working through a cloud computing environment. We analyse: co-authoring production; the ratio of ideas production according to task-goal; and the variation of brainstorming modalities. Our results show that designers work on brainstorming modalities according to the task-goal assigned, and we see that task content and the verbal and graphical communicative modes are supported by the proposed computational environment; as well as all brainstorming modalities. Because co-authoring or collective sketching are hardly possible without verbal communication support in graphical production, we propose the use of these new cloud computing functionalities to enhance the distributed design work.     

Deep learning based detection of COVID-19 from chest X-ray images

The whole world is facing a health crisis, that is unique in its kind, due to the COVID-19 pandemic. As the coronavirus continues spreading, researchers are concerned by providing or help provide solutions to save lives and to stop the pandemic outbreak. Among others, artificial intelligence (AI) has been adapted to address the challenges caused by pandemic. In this article, we design a deep learning system to extract features and detect COVID-19 from chest X-ray images. Three powerful networks, namely ResNet50, InceptionV3, and VGG16, have been fine-tuned on an enhanced dataset, which was constructed by collecting COVID-19 and normal chest X-ray images from different public databases. We applied data augmentation techniques to artificially generate a large number of chest X-ray images: Random Rotation with an angle between ??10 and 10 degrees, random noise, and horizontal flips. Experimental results are encouraging: the proposed models reached an accuracy of 97.20?% for Resnet50, 98.10?% for InceptionV3, and 98.30?% for VGG16 in classifying chest X-ray images as Normal or COVID-19. The results show that transfer learning is proven to be effective, showing strong performance and easy-to-deploy COVID-19 detection methods. This enables automatizing the process of analyzing X-ray images with high accuracy and it can also be used in cases where the materials and RT-PCR tests are limited.

     

A four-step model for diagnosing knowledge transfer challenges from operations into engineering design

Knowledge gained from operations can help optimize the design of new installations in terms of system performance, health, and safety. Transferring such knowledge to engineering design teams makes it available for use in projects. However, the transfer involves different challenges. To better understand and identify these challenges, we combine a knowledge transfer model with a work systems model into the development of a conceptual four-step model for knowledge transfer from operations to engineering design. Knowledge transfer implies that the knowledge must be captured, transformed into an engineering design context, transferred to the appropriate individuals, and finally, applied to the design of new facilities. In this paper, we 1) present the development of this model, 2) illustrate its application in an empirical case study in an offshore oil company, and 3) propose a generic diagnostic tool to be applied in companies to diagnose and identify the existing challenges within knowledge transfer from operations to engineering design.Relevance to industryThe proposed diagnostic tool allows for better understanding of design problems to be faced and for developing design solutions that improve health, safety, and production effectiveness. This benefits knowledge management and engineering design professionals in industries with geographically dispersed organizations.     

Managing Transboundary Crises: Identifying the Building Blocks of an Effective Response System

In recent years, crises have become increasingly transboundary in nature. This exploratory paper investigates whether and how the transboundary dimensions of crises such as pandemics, cyber attacks and prolonged critical infrastructure failure accentuate the challenges that public and private authorities confront in the face of urgent threats. We explore the transboundary dimensions of crises and disasters, discuss how an increase in ‘transboundedness’ affects traditional crisis management challenges and investigate what administrative mechanisms are needed to deal with these compounded challenges. Building on lessons learned from past crises and disasters, our goal is to stimulate a discussion among crisis management scholars about the political‐administrative capabilities required to deal with ‘transboundary’ crises.     

Organizational decision-making during COVID-19: A qualitative analysis of the organizational decision-making system in the United States during COVID-19

This study sought to understand COVID-19-related organizational decisions were made across sectors. To gain this understanding, we conducted semi-structured interviews with organizational decision-makers in North Carolina about their experiences responding to COVID-19. Conventional content analysis was used to analyse the context, inputs, and processes involved in decision-making. Between October 2020 and February 2021, we interviewed 44 decision-makers from the following sectors: business (n = 4), community non-profit (n = 3), county government (n = 4), healthcare (n = 5), local public health (n = 5), public safety (n = 7), religious (n = 6), education (n = 7) and transportation (n = 3). We found that during the pandemic, organizations looked to scientific authorities, the decisions of peer organizations, data about COVID-19, and their own experience with prior crises. Interpretation of inputs was informed by current political events, societal trends, and organization mission. Decision-makers had to account for divergent internal opinions and community behaviour. To navigate inputs and contextual factors, organizations decentralized decision-making authority, formed auxiliary decision-making bodies, learned to resolve internal conflicts, learned in real time from their crisis response, and routinely communicated decisions with their communities. In conclusion, aligned with systems and contingency theories of decision-making, decision-making during COVID-19 depended on an organization's ‘fit’ within the specifics of their existing system and their ability to orient the dynamics of that system to their own goals.     

Important characteristics of software development team members: an empirical investigation using Repertory Grid

An information system is typically developed by a team of information systems (IS) professionals. Research shows that teams staffed with the right people are more likely to be effective and efficient. There is a paucity of study that examines the important traits of IS professionals in team contexts. The objective of this research is to identify and understand the important characteristics of good team members in software development projects. We applied an established psychological technique (Repertory Grid) to guide our interviews with 21 experienced IS professionals, who have had extensive experience in software development teams. The comprehensive list of important characteristics was analysed qualitatively using open coding method of grounded theory. Fifty‐nine unique characteristics were identified and classified into eight categories. Among them, attitude/motivation, knowledge, interpersonal/communication skills, and working/cognitive ability were perceived by research participants to be the most important categories. Our study provides a context‐specific (i.e. software development team) evaluation of important characteristics of IS professionals. The results have significant implications for IS recruiting, IS training, IS staffing, and IS human resource management. Our study also supplements the research on management of IS development teams.     

COVID TCL: A Joint Metric Loss Function for Diagnosing COVID-19 Patient in the Early and Incubation Period

Convolution Neural Networks (CNN) can quickly diagnose COVID-19 patients by analyzing computed tomography (CT) images of the lung, thereby effectively preventing the spread of COVID-19. However, the existing CNN-based COVID-19 diagnosis models do consider the problem that the lung images of COVID-19 patients in the early stage and incubation period are extremely similar to those of the non-COVID-19 population. Which reduces the model’s classification sensitivity, resulting in a higher probability of the model misdiagnosing COVID-19 patients as non-COVID-19 people. To solve the problem, this paper first attempts to apply triplet loss and center loss to the field of COVID-19 image classification, combining softmax loss to design a jointly supervised metric loss function COVID Triplet-Center Loss (COVID-TCL). Triplet loss can increase inter-class discreteness, and center loss can improve intra-class compactness. Therefore, COVID-TCL can help the CNN-based model to extract more discriminative features and strengthen the diagnostic capacity of COVID-19 patients in the early stage and incubation period. Meanwhile, we use the extreme gradient boosting (XGBoost) as a classifier to design a COVID-19 images classification model of CNN-XGBoost architecture, to further improve the CNN-based model’s classification effect and operation efficiency. The experiment shows that the classification accuracy of the model proposed in this paper is 97.41%, and the sensitivity is 97.61%, which is higher than the other 7 reference models. The COVID-TCL can effectively improve the classification sensitivity of the CNN-based model, the CNN-XGBoost architecture can further improve the CNN-based model’s classification effect.     

Integration of human factors and ergonomics during medical device design and development: It's all about communication

Manufacturers of interactive medical devices, such as infusion pumps, need to ensure that devices minimise the risk of unintended harm during use. However, development teams face challenges in incorporating Human Factors. The aim of the research reported here was to better understand the constraints under which medical device design and development take place. We report the results of a qualitative study based on 19 semi-structured interviews with professionals involved in the design, development and deployment of interactive medical devices. A thematic analysis was conducted. Multiple barriers to designing for safety and usability were identified. In particular, we identified barriers to communication both between the development organisation and the intended users and between different teams within the development organisation. We propose the use of mediating representations. Artefacts such as personas and scenarios, known to provide integration across multiple perspectives, are an essential component of designing for safety and usability.     

Information system professionals’ knowledge and application gaps toward Web design guidelines

Web design guidelines are adopted by many usability evaluation methods as one of the criteria for success, while usability is proven to significantly impact Website performance. Since Web design guidelines cover a broad range of system and interface design solutions, knowledge of them can be considered as a prominent indicator of Web design skills for information systems (IS) professionals. This study empirically assessed how much IS professionals know and apply Web design guidelines via a survey to 500 randomly selected companies from Taiwan’s Fortune 2000 corporations. As expected, the knowledge–application gaps of IS professionals were statistically significant in all Web design guideline categories. Meanwhile, certain guideline categories were proven to be more difficult to acquire or apply than others. Finally, degree, gender, experience, training hours, and courses taken were also proven to be determining factors for Web design guideline skills. Implications for developing Web design guideline skills are also discussed.     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Information system artefact or information system application: that is the question

Lee et al. ( 2015 ) suggest the concept of information system (IS) artefact as an alternative to information technology (IT) artefact, defining the former as a system of an IT artefact, an information artefact and a social artefact. This paper assesses this suggestion, contrasting it with the concepts of IT artefact and IS application as introduced in the prior IS literature. After this conceptual analysis, the paper discusses the relationships between an IS artefact and design and between an IS artefact and design science. The analysis concludes that an IS artefact is problematic as a unit of design because of the great differences in the designability of its constituent parts. Instead, the paper maintains that an IS application is more appropriate as a unit of design, but an IS artefact may be fruitful as an analytical concept to be used in behavioural science research on the interplay of IT artefact, information artefact and social artefact, or – especially if including IS application design – in action research‐oriented design science research. © 2016 John Wiley & Sons Ltd     

Reconfiguring and ramping-up ventilator production in the face of COVID-19: Can robots help?

As the COVID-19 pandemic expands, the shortening of medical equipment is swelling. A key piece of equipment getting far-out attention has been ventilators. The difference between supply and demand is substantial to be handled with normal production techniques, especially under social distancing measures in place. The study explores the rationale of human-robot teams to ramp up production using advantages of both the ease of integration and maintaining social distancing. The paper presents a model for faster integration of collaborative robots and design guidelines for workstations. The scenario is evaluated for an open source ventilator through continuous human-robot simulation and amplification of results in a discrete event simulation.