University of Agder

Researchers have explored the benefits and applications of virtual reality (VR) in different scenarios. VR possesses much potential and its application in education has seen much research interest lately. However, little systematic work currently exists on how researchers have applied immersive VR for higher education purposes that considers the usage of both high-end and budget head-mounted displays (HMDs). Hence, we propose using systematic mapping to identify design elements of existing research dedicated to the application of VR in higher education. The reviewed articles were acquired by extracting key information from documents indexed in four scientific digital libraries, which were filtered systematically using exclusion, inclusion, semi-automatic, and manual methods. Our review emphasizes three key points: the current domain structure in terms of the learning contents, the VR design elements, and the learning theories, as a foundation for successful VR-based learning. The mapping was conducted between application domains and learning contents and between design elements and learning contents. Our analysis has uncovered several gaps in the application of VR in the higher education sphere—for instance, learning theories were not often considered in VR application development to assist and guide toward learning outcomes. Furthermore, the evaluation of educational VR applications has primarily focused on usability of the VR apps instead of learning outcomes and immersive VR has mostly been a part of experimental and development work rather than being applied regularly in actual teaching. Nevertheless, VR seems to be a promising sphere as this study identifies 18 application domains, indicating a better reception of this technology in many disciplines. The identified gaps point toward unexplored regions of VR design for education, which could motivate future work in the field.

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 will positively impact people in their work, leisure, and social interaction. The potential impact on the way we conduct business, interact with brands and others, and develop shared experiences is likely to be transformational as the distinct lines between physical and digital are likely to be somewhat blurred from current perceptions. However, although the technology and infrastructure does not yet exist to allow the development of new immersive virtual worlds at scale - one that our avatars could transcend across platforms, researchers are increasingly examining the transformative impact of the metaverse. Impacted sectors include marketing, education, healthcare as well as societal effects relating to social interaction factors from widespread adoption, and issues relating to trust, privacy, bias, disinformation, application of law as well as psychological aspects linked to addiction and impact on vulnerable people. This study examines these topics in detail by combining the informed narrative and multi-perspective approach from experts with varied disciplinary backgrounds on many aspects of the metaverse and its transformational impact. The paper concludes by proposing a future research agenda that is valuable for researchers, professionals and policy makers alike.

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 construction and somewhat precise outcome testing. This article offers a detailed step-by-step guide on how to employ fsQCA by using as an example an already published study. We analyze the same dataset and present all the details in each step of the analysis to guide the reader onto how to employ fsQCA. The article discusses differences between fsQCA and variance-based approaches and compares fsQCA with those from structured equation modelling. Finally, the article offers a summary of thresholds and guidelines for practice, along with a discussion on how existing papers that employ variance-based methods are extendable and complemented through fsQCA.

Design research (DR) positions information technology artifacts at the core of the Information Systems discipline. However, dominant DR thinking takes a technological view of the IT artifact, paying scant attention to its shaping by the organizational context. Consequently, existing DR methods focus on building the artifact and relegate evaluation to a subsequent and separate phase. They value technological rigor at the cost of organizational relevance, and fail to recognize that the artifact emerges from interaction with the organizational context even when its initial design is guided by the researchers’ intent. We propose action design research (ADR) as a new DR method to address this problem. ADR reflects the premise that IT artifacts are ensembles shaped by the organizational context during development and use. The method conceptualizes the research process as containing the inseparable and inherently interwoven activities of building the IT artifact, intervening in the organization, and evaluating it concurrently. The essay describes the stages of ADR and associated principles that encapsulate its underlying beliefs and values. We illustrate ADR through a case of competence management at Volvo IT.

Design research (DR) positions information technology artifacts at the core of the Information Systems\ndiscipline. However, dominant DR thinking takes a technological view of the IT artifact, paying scant attention\nto its shaping by the organizational context. Consequently, existing DR methods focus on building the artifact\nand relegate evaluation to a subsequent and separate phase. They value technological rigor at the cost of\norganizational relevance, and fail to recognize that the artifact emerges from interaction with the\norganizational context even when its initial design is guided by the researchers’ intent. We propose action design research (ADR) as a new DR method to address this problem. ADR reflects the premise that IT artifacts are ensembles shaped by the organizational context during development and use. The\nmethod conceptualizes the research process as containing the inseparable and inherently interwoven activities\nof building the IT artifact, intervening in the organization, and evaluating it concurrently. The essay describes\nthe stages of ADR and associated principles that encapsulate its underlying beliefs and values. We illustrate ADR through a case of competence management at Volvo IT.

PURPOSE: Quality of life (QOL) is an important concept in the field of health and medicine. QOL is a complex concept that is interpreted and defined differently within and between disciplines, including the fields of health and medicine. The aims of this study were to systematically review the literature on QOL in medicine and health research and to describe the country of origin, target groups, instruments, design, and conceptual issues. METHODS: A systematic review was conducted to identify research studies on QOL and health-related quality of life (HRQOL). The databases Scopus, which includes Embase and MEDLINE, CINAHL, and PsycINFO were searched for articles published during one random week in November 2016. The ten predefined criteria of Gill and Feinstein were used to evaluate the conceptual and methodological rigor. RESULTS: QOL research is international and involves a variety of target groups, research designs, and QOL measures. According to the criteria of Gill and Feinstein, the results show that only 13% provided a definition of QOL, 6% distinguished QOL from HRQOL. The most frequently fulfilled criteria were: (i) stating the domains of QOL to be measured; (ii) giving a reason for choosing the instruments used; and (iii) aggregating the results from multiple items. CONCLUSION: QOL is an important endpoint in medical and health research, and QOL research involves a variety of patient groups and different research designs. Based on the current evaluation of the methodological and conceptual clarity of QOL research, we conclude that the majority QOL studies in health and medicine have conceptual and methodological challenges.

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 chief information officers and IT managers working in Norwegian firms. By means of partial least squares structural equation modeling, results show that a strong BDAC can help firms build a competitive advantage. This effect is not direct but fully mediated by dynamic capabilities, which exerts a positive and significant effect on two types of operational capabilities: marketing and technological capabilities. The findings suggest that IS researchers should look beyond direct effects of big data investments and shift their attention on how a BDAC can be leveraged to enable and support organizational capabilities.

In 2014, the International Olympic Committee (IOC) published a consensus statement entitled “Beyond the Female Athlete Triad: Relative Energy Deficiency in Sport (RED-S)”. The syndrome of RED-S refers to: “impaired physiological functioning caused by relative energy deficiency, and includes but is not limited to impairments of metabolic rate, menstrual function, bone health, immunity, protein synthesis, and cardiovascular health.” The aetiological factor of this syndrome is low energy availability (LEA)

This paper critically reviews the outcomes of internationally-funded interventions aimed at climate change adaptation and vulnerability reduction. It highlights how some interventions inadvertently reinforce, redistribute or create new sources of vulnerability. Four mechanisms drive these maladaptive outcomes: (i) shallow understanding of the vulnerability context; (ii) inequitable stakeholder participation in both design and implementation; (iii) a retrofitting of adaptation into existing development agendas; and (iv) a lack of critical engagement with how ‘adaptation success’ is defined. Emerging literature shows potential avenues for overcoming the current failure of adaptation interventions to reduce vulnerability: first, shifting the terms of engagement between adaptation practitioners and the local populations participating in adaptation interventions; and second, expanding the understanding of ‘local’ vulnerability to encompass global contexts and drivers of vulnerability. An important lesson from past adaptation interventions is that within current adaptation cum development paradigms, inequitable terms of engagement with ‘vulnerable’ populations are reproduced and the multi-scalar processes driving vulnerability remain largely ignored. In particular, instead of designing projects to change the practices of marginalised populations, learning processes within organisations and with marginalised populations must be placed at the centre of adaptation objectives. We pose the question of whether scholarship and practice need to take a post-adaptation turn akin to post-development, by seeking a pluralism of ideas about adaptation while critically interrogating how these ideas form part of the politics of adaptation and potentially the processes (re)producing vulnerability. We caution that unless the politics of framing and of scale are explicitly tackled, transformational interventions risk having even more adverse effects on marginalised populations than current adaptation.

The past decade has seen significant progress in artificial intelligence (AI), which has resulted in algorithms being adopted for resolving a variety of problems. However, this success has been met by increasing model complexity and employing black-box AI models that lack transparency. In response to this need, Explainable AI (XAI) has been proposed to make AI more transparent and thus advance the adoption of AI in critical domains. Although there are several reviews of XAI topics in the literature that have identified challenges and potential research directions of XAI, these challenges and research directions are scattered. This study, hence, presents a systematic meta-survey of challenges and future research directions in XAI organized in two themes: (1) general challenges and research directions of XAI and (2) challenges and research directions of XAI based on machine learning life cycle’s phases: design, development, and deployment. We believe that our meta-survey contributes to XAI literature by providing a guide for future exploration in the XAI area.

Internet of Things (IoT) devices are rapidly becoming ubiquitous while IoT services are becoming pervasive. Their success has not gone unnoticed and the number of threats and attacks against IoT devices and services are on the increase as well. Cyber-attacks are not new to IoT, but as IoT will be deeply interwoven in our lives and societies, it is becoming necessary to step up and take cyber defense seriously. Hence, there is a real need to secure IoT, which has consequently resulted in a need to comprehensively understand the threats and attacks on IoT infrastructure. This paper is an attempt to classify threat types, besides analyze and characterize intruders and attacks facing IoT devices and services.

The circular economy (CE) has the potential to capitalise upon emerging digital technologies, such as big data, artificial intelligence (AI), blockchain and the Internet of things (IoT), amongst others. These digital technologies combined with business model innovation are deemed to provide solutions to myriad problems in the world, including those related to circular economy transformation. Given the societal and practical importance of CE and digitalisation, last decade has witnessed a significant increase in academic publication on these topics. Therefore, this study aims to capture the essence of the scholarly work at the intersection of the CE and digital technologies. A detailed analysis of the literature based on emerging themes was conducted with a focus on illuminating the path of CE implementation. The results reveal that IoT and AI play a key role in the transition towards the CE. A multitude of studies focus on barriers to digitalisation-led CE transition and highlight policy-related issues, the lack of predictability, psychological issues and information vulnerability as some important barriers. In addition, product-service system (PSS) has been acknowledged as an important business model innovation for achieving the digitalisation enabled CE. Through a detailed assessment of the existing literature, a viable systems-based framework for digitalisation enabled CE has been developed which show the literature linkages amongst the emerging research streams and provide novel insights regarding the realisation of CE benefits.

Purpose In this article the authors aim to investigate the moderating effects of gender in explaining intention to use mobile chat services. Design/methodology/approach An extended adoption model based on the technology acceptance model and theory of reasoned action is applied for pin‐pointing the antecedents of intention to use mobile chat services and for revealing cross‐gender differences. The hypotheses are tested on data from a survey of 684 users of mobile chat services. Findings The study results suggest that social norms and intrinsic motives such as enjoyment are important determinants of intention to use among female users, whereas extrinsic motives such as usefulness and – somewhat surprisingly – expressiveness are key drivers among men. Research limitations/implications The findings put renewed focus on non‐utilitarian motives and illuminate the role of gender in technology adoption. Practical implications The cross‐gender differences observed give several guidelines for mobile service developers and marketers in how to accommodate female versus male users. Originality/value The paper provides important and new insights both into mobile services adoption and into gender as an important segmentation variable in marketing.

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 learning systems was performed in this work. A total of 147 studies published between 2014 and 2020 were analysed. The major findings and contributions of this paper include the identification of the types of AI-enabled learning interventions used, a visualisation of the co-occurrences of authors associated with major research themes in AI-enabled learning systems and a review of common analytical methods and related techniques utilised in such learning systems. This mapping can serve as a guide for future studies on how to better design AI-enabled learning systems to solve specific learning problems and improve users’ learning experiences.

This study was designed to quantify the daily distribution of training intensity in a group of well-trained junior cross-country skiers and compare the results of three different methods of training intensity quantification. Eleven male athletes performed treadmill tests to exhaustion to determine heart rate and VO2 corresponding to ventilatory thresholds (VT1, VT2), maximal oxygen consumption (VO2max), and maximal heart rate. VT1 and VT2 were used to delineate three intensity zones. During the same time period, all training sessions (N=384, 37 strength training, 347 endurance) performed over 32 consecutive days were quantified using continuous heart rate registration and session Rating of Perceived Exertion (RPE). In addition, a subset of 60 consecutive training sessions was quantified using blood lactate measurements. Intensity distribution across endurance training sessions (n=318) was similar when based on heart rate analysis (75+/-3%, zone 1; 8+/-3%, zone 2; 17+/-4%, zone 3) or session RPE (76+/-4%, zone 1; 6+/-5%, zone 2; 18+/-7%, zone 3). Similarly, from measurements of 60 consecutive sessions, 71% were performed with <or=2.0 mM blood lactate, 7% between 2 and 4 mM, and 22% with over 4 mM (mean=9.5+/-2.8 mM). In this group of nationally competitive junior skiers, training was organized after a polarized pattern, with most sessions performed clearly below (about 75%) or with substantial periods above (15-20%) the lactate accommodation zone, which is bounded by VT1 and VT2. The pattern quantified here is similar to that reported in observational studies of elite endurance athletes across several sports. It appears that elite endurance athletes train surprisingly little at the lactate threshold intensity.

Successful endurance training involves the manipulation of training intensity, duration, and frequency, with the implicit goals of maximizing performance, minimizing risk of negative training outcomes, and timing peak fitness and performances to be achieved when they matter most. Numerous descriptive studies of the training characteristics of nationally or internationally competitive endurance athletes training 10 to 13 times per week seem to converge on a typical intensity distribution in which about 80% of training sessions are performed at low intensity (2 mM blood lactate), with about 20% dominated by periods of high-intensity work, such as interval training at approx. 90% VO2max. Endurance athletes appear to self-organize toward a high-volume training approach with careful application of high-intensity training incorporated throughout the training cycle. Training intensification studies performed on already well-trained athletes do not provide any convincing evidence that a greater emphasis on high-intensity interval training in this highly trained athlete population gives long-term performance gains. The predominance of low-intensity, long-duration training, in combination with fewer, highly intensive bouts may be complementary in terms of optimizing adaptive signaling and technical mastery at an acceptable level of stress.

This article provides a systematic review of existing research on problematic smartphone use (PSU) to guide other researchers in search of relevant studies, and to propose areas for future research. In total, 293 studies were analyzed leading to the development of an overview model in the field of PSU, presenting findings on demographic factors, explanations for smartphone use and why this use becomes problematic, consequences of PSU, and how such use can be corrected. In addition, we considered in which contexts, with which methods, and with which theoretical lenses this stream of research has been studied to date. Smartphone use is most often explained by the smartphone design, and users' emotional health and their ability to control smartphone use. Our review suggests that people who are young, female, and highly educated are more prone to PSU. Emotional health issues are the most frequently identified consequence of PSU. Strategies for correcting PSU fall into three categories: information-enhancing, capacity-enhancing, and behavior reinforcement strategies. The studies on PSU are most often conducted using quantitative surveys with university and college participants considering their personal smartphone use. Whereas a variety of theoretical frameworks have been adopted to investigate PSU, they are often related to identifying factors explaining use and problematic use, and more seldom to analyze the findings. A future research agenda for PSU is proposed consisting of seven key research questions which can be investigated by researchers going forward.

Scholars have speculated that the metaverse will alter the way in which the hospitality and tourism industry operates. Efforts to understand this new phenomenon in both academia and industry are at a crossroads. In this opinion piece, we first attempt to explain the concept of the metaverse in general and in the context of the hospitality and tourism industry. Next, we propose a conceptual framework for creating metaverse experiences, identifying research gaps, and proposing agenda items with the potential to significantly benefit hospitality and tourism industry players. Finally, we classify future research agendas into three broad categories: staging experiences in the metaverse, understanding possible changes in the consumer behavior, and marketing and operations strategies in the metaverse.学者们推测，metaverse将改变酒店业和旅游业的运作方式. 学术界和工业界对这一新现象的理解正处于十字路口. 在这篇评论文章中，我们首先试图在酒店业和旅游业的背景下解释metaverse的概念. 接下来，我们提出了一个概念框架，用于创建metaverse体验、确定研究差距，并提出有可能使酒店业和旅游业参与者受益的议程项目. 最后，我们将未来的研究议程分为三大类在metaverse中展示体验、了解消费者行为的可能变化，以及metaverse中的营销和运营策略.

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Markus and Kitayama's (1991) theory of independent and interdependent self-construals had a major influence on social, personality, and developmental psychology by highlighting the role of culture in psychological processes. However, research has relied excessively on contrasts between North American and East Asian samples, and commonly used self-report measures of independence and interdependence frequently fail to show predicted cultural differences. We revisited the conceptualization and measurement of independent and interdependent self-construals in 2 large-scale multinational surveys, using improved methods for cross-cultural research. We developed (Study 1: N = 2924 students in 16 nations) and validated across cultures (Study 2: N = 7279 adults from 55 cultural groups in 33 nations) a new 7-dimensional model of self-reported ways of being independent or interdependent. Patterns of global variation support some of Markus and Kitayama's predictions, but a simple contrast between independence and interdependence does not adequately capture the diverse models of selfhood that prevail in different world regions. Cultural groups emphasize different ways of being both independent and interdependent, depending on individualism-collectivism, national socioeconomic development, and religious heritage. Our 7-dimensional model will allow future researchers to test more accurately the implications of cultural models of selfhood for psychological processes in diverse ecocultural contexts. (PsycINFO Database Record