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International Journal of Information Management
Journal Prestige (SJR): 1.373
Citation Impact (citeScore): 6
Number of Followers: 310  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0268-4012
Published by Elsevier Homepage  [3155 journals]
  • A systematic examination of knowledge loss in open source software
           projects
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Mehvish Rashid, Paul M. Clarke, Rory V. O’Connor Context Open Source Software (OSS) development is a knowledge focussed activity which relies heavily on contributors who can be volunteers or paid workers and are geographically distributed. While working on OSS projects contributors acquire project related individualistic knowledge and gain experience and skills, which often remains unshared with others and is usually lost once contributors leave a project. All software development organisations face the problem of knowledge loss as employees leave, but this situation is exasperated in OSS projects where most contributors are volunteers with largely unpredictable engagement durations. Contributor turnover is inevitable due to the transient nature of OSS project workforces causing knowledge loss, which threatens the overall sustainability of OSS projects and impacts negatively on software quality and contributor productivity.ObjectiveThe objective of this work is to deeply and systematically investigate the phenomenon of knowledge loss due to contributor turnover in OSS projects as presented in the state-of-the-art literature and to synthesise the information presented on the topic. Furthermore, based on the learning arising from our investigation it is our intention to identify mechanisms to reduce the overall effects of knowledge loss in OSS projects.MethodologyWe use the snowballing methodology to identify the relevant literature on knowledge loss due to contributor turnover in OSS projects. This robust methodology for a literature review includes research question, search strategy, inclusion, exclusion, quality criteria, and data synthesis. The search strategy, and inclusion, exclusions and quality criteria are applied as a part of snowballing procedure.Snowballing is considered an efficient and reliable way to conduct a systematic literature review, providing a robust alternative to mechanically searching individual databases for given topics.ResultKnowledge sharing in OSS projects is abundant but there is no evidence of a formal strategy or practice to manage knowledge. Due to the dynamic and diverse nature of OSS projects, knowledge management is considered a challenging task and there is a need for a proactive mechanism to share knowledge in the OSS community for knowledge to be reused in the future by the OSS project contributors. From the collection of papers found using snowballing, we consolidated various themes on knowledge loss due to contributor turnover in OSS projects and identified 11 impacts due to knowledge loss in OSS projects, and 10 mitigations to manage with knowledge loss in OSS projects.ConclusionIn this paper, we propose future research directions to investigate integration of proactive knowledge retention practices with the existing OSS practices to reduce the current knowledge loss problem. We suggest that there is insufficient attention paid to KM in general in OSS, in particular there would appear to an absence of proactive measures to reduce the potential impact of knowledge loss. We also propose the need for a KM evaluation metric in OSS projects, similar to the ones that evaluate health of online communities, which should help to inform potential consumers of the OSS of the KM status on a project, something that is not existent today.
       
  • The rise of motivational information systems: A review of gamification
           research
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Jonna Koivisto, Juho Hamari Today, our reality and lives are increasingly game-like, not only because games have become a pervasive part of our lives, but also because activities, systems and services are increasingly gamified. Gamification refers to designing information systems to afford similar experiences and motivations as games do, and consequently, attempting to affect user behavior. In recent years, popularity of gamification has skyrocketed and manifested in growing numbers of gamified applications, as well as a rapidly increasing amount of research. However, this vein of research has mainly advanced without an agenda, theoretical guidance or a clear picture of the field.To make the picture more coherent, we provide a comprehensive review of the gamification research (N = 819 studies) and analyze the research models and results in empirical studies on gamification. While the results in general lean towards positive findings about the effectiveness of gamification, the amount of mixed results is remarkable. Furthermore, education, health and crowdsourcing as well as points, badges and leaderboards persist as the most common contexts and ways of implementing gamification. Concurrently, gamification research still lacks coherence in research models, and a consistency in the variables and theoretical foundations. As a final contribution of the review, we provide a comprehensive discussion, consisting of 15 future research trajectories, on future agenda for the growing vein of literature on gamification and gameful systems within the information system science field.
       
  • Financial crisis prediction model using ant colony optimization
    • Abstract: Publication date: Available online 13 December 2018Source: International Journal of Information ManagementAuthor(s): Uthayakumar J, Noura Metawa, K. Shankar, S.K. Lakshmanaprabu Financial decisions are often based on classification models which are used to assign a set of observations into predefined groups. Different data classification models were developed to foresee the financial crisis of an organization using their historical data. One important step towards the development of accurate financial crisis prediction (FCP) model involves the selection of appropriate variables (features) which are relevant for the problems at hand. This is termed as feature selection problem which helps to improve the classification performance. This paper proposes an Ant Colony Optimization (ACO) based financial crisis prediction (FCP) model which incorporates two phases: ACO based feature selection (ACO-FS) algorithm and ACO based data classification (ACO-DC) algorithm. The proposed ACO-FCP model is validated using a set of five benchmark dataset includes both qualitative and quantitative. For feature selection design, the developed ACO-FS method is compared with three existing feature selection algorithms namely genetic algorithm (GA), Particle Swarm Optimization (PSO) algorithm and Grey Wolf Optimization (GWO) algorithm. In addition, a comparison of classification results is also made between ACO-DC and state of art methods. Experimental analysis shows that the ACO-FCP ensemble model is superior and more robust than its counterparts. In consequence, this study strongly recommends that the proposed ACO-FCP model is highly competitive than traditional and other artificial intelligence techniques.
       
  • Mobile cloud-assisted paradigms for management of multimedia big data in
           healthcare systems: Research challenges and opportunities
    • Abstract: Publication date: Available online 10 December 2018Source: International Journal of Information ManagementAuthor(s): Irfan Mehmood, Zhihan Lv, Yu-Dong Zhang, Kaoru Ota, Muhammad Sajjad, Amit Kumar Singh
       
  • Business intelligence and analytics for value creation: The role of
           absorptive capacity
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Katerina Božič, Vlado Dimovski Firms continuously report increased competitive value gains from the use of business intelligence and analytics (BI&A), however, little is known about how insights from BI&A are transformed to added value to date. We have conducted fourteen in-depth, semi-structured interviews with a sample of informants in CEO positions, IT managers, CIO, Heads of R&D, as well as Market Managers from nine medium or large-sized European firms. Applying the absorptive capacity’s theoretical lens, we have provided evidence that absorptive capacity’s capabilities are an underlying foundation in the process of transforming BI&A triggered insights into valuable knowledge. Moreover, this process is supported by technological, human, and relationship assets.
       
  • Exploring the influence of excessive social media use at work: A
           three-dimension usage perspective
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Xiongfei Cao, Lingling Yu Pervasive social media has resulted in technology dependency and excessive usage, which can lead to negative outcomes in organizations. This paper aims to investigate the effects of social media’s different excessive usage patterns on employee job performance and the corresponding underlying mechanism. Specifically, we propose three dimensions of excessive social media use at work (i.e., excessive social, hedonic, and cognitive). These dimensions are related to technology-work conflict and strain, which in turn decrease employee job performance. An empirical study of 305 social media users in organizations reveals that excessive social media use for socialization and entertainment can generate conflict between technology use and work demand, whereas excessive social media use for information-sharing reduces employees’ psychological strain. In addition, technology-work conflict and strain negatively influence job performance. The theoretical and practical implications of this study are also discussed.
       
  • Blockchain adoption challenges in supply chain: An empirical investigation
           of the main drivers in India and the USA
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Maciel M. Queiroz, Samuel Fosso Wamba The digitalization phenomenon is leveraging new relationship models through the entire supply chain network. In this outlook, blockchain is a cutting-edge technology that is already transforming and remodeling the relationships between all members of logistics and supply chain systems. Yet, while studies on blockchain have gained a relative pace over the recent years, the literature on this topic does not report sufficient research cases on blockchain adoption behavior at the individual level. The present study, therefore, aims to bridge this gap, notably by helping understand the individual blockchain adoption behavior in the logistics and supply chain field in India and the USA. Drawing on the emerging literature on blockchain, supply chain and network theory, as well as on technology acceptance models (TAMs), we have developed a model based on a slightly-altered version of the classical unified theory of acceptance and use of technology (UTAUT). The model being developed was then estimated using the Partial least squares structural equation modeling (PLS-SEM). As the model was eventually supported, the results obtained revealed the existence of distinct adoption behaviors between India-based and USA-based professionals. In parallel, the findings appear as a useful contribution to and a sign of progress for the literature on IT adoption, SCM, and blockchain.
       
  • A human-centric perspective exploring the readiness towards smart
           warehousing: The case of a large retail distribution warehouse
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Kamran Mahroof The explosive rise in technologies has revolutionised the way in which business operate, consumers buy, and the pace at which these activities take place. These advancements continue to have profound impact on business processes across the entire organisation. As such, Logistics and Supply Chain Management (LSCM) are also leveraging benefits from digitisation, allowing organisations to increase efficiency and productivity, whilst also providing greater transparency and accuracy in the movement of goods. While the warehouse is a key component within LSCM, warehousing research remains an understudied area within overall supply chain research, accounting for only a fraction of the overall research within this field. However, of the extant warehouse research, attention has largely been placed on warehouse design, performance and technology use, yet overlooking the determinants of Artificial Intelligence (AI) adoption within warehouses. Accordingly, through proposing an extension of the Technology–Organisation–Environment (TOE) framework, this research explores the barriers and opportunities of AI within the warehouse of a major retailer. The findings for this qualitative study reveal AI challenges resulting from a shortage of both skill and mind-set of operational management, while also uncovering the opportunities presented through existing IT infrastructure and pre-existing AI exposure of management.
       
  • Improving high-tech enterprise innovation in big data environment: A
           combinative view of internal and external governance
    • Abstract: Publication date: Available online 4 December 2018Source: International Journal of Information ManagementAuthor(s): Runhui Lin, Zaiyang Xie, Yunhong Hao, Jie Wang The emergence of big data brings both opportunities and challenges to high-tech enterprises. How to keep competitive advantages and improve innovation performance is important for enterprises in big data environment. Except from organizational learning ability and the use of advanced technology, the corporate governance also plays an important role in the process of enterprise’s innovation practice. This article creatively combines with the insights of internal and external governance, and explores how the managerial power and network centrality affects enterprise’s innovation performance in big data environment. Considering about the differences among distinct regional big data environment (strong/weak), this paper also takes classification research on it. The research findings show that managerial power has a significant positive impact on innovation performance, managerial power could enhance enterprise’s centrality in network, and the enterprise which located in network central position has more advantages in obtaining resources and significantly improves firm’s innovation performance. Network centrality plays a mediating role on managerial power and innovation performance. Further research finds that the positive effects of managerial power and network centrality are more significantly in the strong big data environment. These findings enrich the research of high-tech enterprise innovation from a combinative governance view, and contribute to the literatures on enterprise innovation in big data environment.
       
  • Cloud computing utilization and mitigation of informational and marketing
           barriers of the SMEs from the emerging markets: Evidence from Iran and
           Turkey
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Sahab Hosseini, Grahame Fallon, Vishanth Weerakkody, Uthayasankar Sivarajah This study seeks to investigate the effectiveness of Cloud Computing Utilization (CCU) in the mitigation of informational and marketing barriers for SMEs from the Emerging Market-Countries (EM-SMEs). A quantitative-research methodology was applied to collect data by using self-administered questionnaires from top managers of 227 SMEs based in Iran and Turkey. The study contributes theoretically to both small business and international business literature by developing a new classification of the internationalization barriers that EM-SMEs face, and proposing a series of cloud computing (CC) solutions for mitigating these barriers, resulting in the creation and testing of a new model. The empirical findings confirm that CCU can help EM-SMEs to mitigate a series of informational and marketing barriers. The key practical contributions of the study offer insights to both EM-SMEs and Cloud-Service-Providers (CSPs) on the extent to which CCU is effective in mitigating the internationalization barriers faced by EM-SMEs.
       
  • Application of online booking data to hotel revenue management
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Taiga Saito, Akihiko Takahashi, Noriaki Koide, Yu Ichifuji This paper presents an application of online booking data, comprised of big data crawled from a hotel booking website to hotel revenue management. It is important to build a quantitative revenue management method for online hotel booking systems incorporating overbooking strategies, because of increasing numbers of bookings through online booking websites and last-minute cancellations, which cause serious damage to hotel management. We construct a quantitative overbooking model for online booking systems combined with customers’ choice behaviors estimated from the data. Firstly, we present the overbooking model for online booking systems. Secondly, we estimate the choice behaviors of the customers from the online booking data by a discrete choice model. Thirdly, combining the estimated discrete choice model with the theoretical overbooking model, we investigate the expected sales maximization problem where we numerically solve the optimal overbooking level and room charge. Finally, we provide numerical examples of the optimal overbooking strategies and room charges using online booking data of two major luxury hotels in Shinjuku ward, Tokyo. This method, which utilizes online booking data available by crawling from booking websites, helps hotels obtain an optimal room charge and overbooking level maximizing the expected sales.
       
  • Knowledge model for emergency response based on contingency planning
           system of China
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Zi-jian Ni, Lili Rong, Ning Wang, Shuo Cao China is severely exposed to natural hazards. Currently, there are more than 5.5 million contingency plans for handling various incidents. Similar to those produced in other counties, the paper-based plans in China are limited in that emergency responders cannot easily extract helpful information for them. In this paper, a knowledge-based system will be proposed for providing different stakeholders with helpful information in the emergency response. The conceptual model is the core for the whole system, which can link plans in the physical world and the ontology in the cyber world.
       
  • The value of and myths about enterprise architecture
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Yiwei Gong, Marijn Janssen Enterprise Architecture (EA) has been embraced by many organizations to improve the value of their IT. Our systematic literature review (SLR) reveals that EA is a broad concept that is interpreted and used in many different ways. This breadth can be explained by the various starting points taken, and by the content-dependent nature of many EA efforts. Unsurprisingly, the literature presents diverse views on value creation and locates the value of EA in a broad range of areas. Only half of the articles provide empirical evidence supporting the EA value claims. Frequently, values are assumed to be the result of EA efforts, but many alternative explanations are possible. Based on the SLR findings, we identify EA myths that are attributable to an overly simplistic conceptualization of EA. These myths have their basis in the claim that EA is an instrument that can solve almost any kind of enterprise problem. This fails to acknowledge that EA in itself often does not provide value, but is an instrument enabling the creation of value. Based on our findings, we recommend demystifying EA by analysing the context-dependent mechanisms behind EA that result in value creation and developing rigorous evidence-based approaches to better understand EA.
       
  • Conceptualizing the impact of corruption in national institutions and
           national stakeholder service systems on e-government maturity
    • Abstract: Publication date: June 2019Source: International Journal of Information Management, Volume 46Author(s): Anupriya Khan, Satish Krishnan Research linking corruption and e-government maturity has mainly focused on the impact of e-government on corruption, and a vast majority of studies among them indicate that e-government can effectively lower the level of corruption in a country. As opposed to this well-developed stream of research, we explore and contribute to another potential but under-developed stream of research: the impact of corruption on e-government maturity. Drawing on the institutional perspective to construe corruption, we argue that corruption in three basic national institutions (political, legal, and media) and two national stakeholder service systems (business and citizen systems) in a country can hinder its e-government maturity. Specifically, we propose a holistic framework that conceptualizes the negative influence of corruption in national institutions and national stakeholder service systems on e-government maturity by drawing on five key theoretical perspectives—agency theory, control theory, theory of X-inefficiency, rent-seeking theory, and trust in institutions—grounded in corruption and information systems project management literature. The proposed conceptual framework is expected to (1) guide future empirical research on “corruption–e-government” phenomenon by providing rich theoretical explanations; and (2) offer a comprehensive strategy for practitioners and policymakers dealing with e-government projects and initiatives.
       
  • Business intelligence governance framework in a university: Universidad de
           la costa case study
    • Abstract: Publication date: Available online 27 November 2018Source: International Journal of Information ManagementAuthor(s): Harold Arturo Combita Niño, Johana Patricia Cómbita Niño, Roberto Morales Ortega Universities and companies have decision-making processes that allow to achieve institutional objectives. Currently, data analysis has an important role in generating knowledge, obtaining important patterns and predictions for formulating strategies. This article presents the design of a business intelligence governance framework for the Universidad de la Costa, easily replicable in other institutions. For this purpose, a diagnosis was made to identify the level of maturity in analytics. From this baseline, a model was designed to strengthen organizational culture, infrastructure, data management, data analysis and governance. The proposal contemplates the definition of a governance framework, guiding principles, strategies, policies, processes, decision-making body and roles. Therefore, the framework is designed to implement effective controls that ensure the success of business intelligence projects, achieving an alignment of the objectives of the development plan with the analytical vision of the institution.
       
  • How does IT affect design centricity approaches: Evidence from
           Spain’s smart tourism ecosystem
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Alvaro E. Arenas, Jie Mein Goh, Alberto Urueña Little or no prior work has examined how information technology enables the development of a design centered digital ecosystem. To examine this research question, we employ a capabilities lens and identify the pathways through which IT drives the development of a design centric smart tourism ecosystem. We analyzed archival data and data collected from interviews conducted in Spain, a country which has embarked on smart destinations projects and topped the World Economic Forum’s Travel and Competitiveness Index. From our analysis, we delineate and identify specific IT-enabled capabilities important for a country implementing smart tourism projects. We find that many of the IT resources available help develop key capabilities necessary for creating a design centric smart tourism ecosystem.
       
  • Exploring the effects of extrinsic motivation on consumer behaviors in
           social commerce: Revealing consumers’ perceptions of social commerce
           benefits
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Xuequn Wang, Xiaolin Lin, Marilyn K. Spencer The rise of social media has created a new e-commerce platform called social commerce. In social commerce, e-vendors such as Amazon may integrate social media with their traditional e-commerce sites. Based on self-determination theory and social commerce literature, we develop a model illustrating how social commerce features may impact consumer behaviors and facilitate social commerce benefits from the extrinsic motivation perspective. We identify four types of extrinsic motivation including external motivation, introjected motivation, identified motivation, and integrated motivation; and we examine their influences on consumers’ intention to contribute social commerce information, which in turn leads to their subsequent behaviors and increases the perceived benefit of social commerce. We also consider the moderating effect of gender in the formulation of social commerce benefits. Based on longitudinal survey data from Amazon consumers, we find that 1) consumers’ external and identified motivation has a positive impact on intention to contribute social commerce information; 2) consumers’ intention is positively associated with their future behaviors, which in turn facilitate their perceptions of social commerce benefits; and 3) gender moderates the impact of behavior on social commerce benefits.
       
  • Data mining of customer choice behavior in internet of things within
           relationship network
    • Abstract: Publication date: Available online 24 November 2018Source: International Journal of Information ManagementAuthor(s): Yuwei Yan, Chuanchao Huang, Qian Wang, Bin Hu Internet of Things has changed the relationship between traditional customer networks, and traditional information dissemination has been affected. Smart environment accelerates the changes in customer behaviors. Apparently, the new customer relationship network, benefitted from the Internet of Things technology, will imperceptibly influence customer choice behaviors for the cyber intelligence. In this work, we selected 298 customers' click browsing records as training data, and collected 50 customers who used the platform for the first time as research objects. and use the smart customer relationship network correspond to cyber intelligence to build the customer intelligence decision model in Internet of Things. The results showed that the MAE (Mean Absolute Deviation) of the customer trust evaluation model constructed in this study is 0.215, 45% improvement over the traditional equal assignment method. In addition, customer's consumer experience can be enhanced with the support of data mining technology in cyber intelligence. Our work indicated the key to build eliminates confusion in customer choice behavior mechanism is to establish a consumer-centric, effective network of customers and service providers, and to be supported by the Internet of Things, big data analysis, and relational fusion technologies.
       
  • Modeling user preferences using neural networks and tensor factorization
           model
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Anu Taneja, Anuja Arora With the expansion of information on the web, recommendation systems have become one of the most powerful resources to ease the task of users. Traditional recommendation systems (RS) suggest items based only on feedback submitted by users in form of ratings. These RS are not competent to deal with definite user preferences due to emerging and situation dependent user-generated content on social media, these situations are known as contextual dimensions. Though the relationship between contextual dimensions and user’s preferences has been demonstrated in various studies, only a few studies have explored about prioritization of varying contextual dimensions. The usage of all contextual dimensions unnecessary raises the computational complexity and negatively influences the recommendation results. Thus, the initial impetus has been made to construct a neural network in order to determine the pertinent contextual dimensions. The experiments are conducted on real-world movies data-LDOS CoMoDa dataset. The results of neural networks demonstrate that contextual dimensions have a significant effect on users’ preferences which in turn exerts an intense impact on the satisfaction level of users. Finally, tensor factorization model is employed to evaluate and validate accuracy by including neural network’s identified pertinent dimensions which are modeled as tensors. The result shows improvement in recommendation accuracy by a wider margin due to the inclusion of the pertinent dimensions in comparison to irrelevant dimensions. The theoretical and managerial implications are discussed.
       
  • How social media brand pages contribute to functional conflict: The
           central role of commitment
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Si Shi, Yu Cao, Yang Chen, Wing S. Chow Although brand pages on social media platforms are burgeoning, companies frequently have difficulty in sustaining customer relationships on their brand pages. Consequently, this study focuses on how a social media brand page develops customer commitment and encourages them to perceive that future conflicts with the company can be resolved for their mutual benefit. On the basis of a review of the literature on customer value theory and commitment, this study develops an integrative model that explores the antecedents of functional conflict and the boundary condition under which brand page commitment enhances functional conflict. The model is tested using data collected from 293 followers of brand pages on a social networking site. The results demonstrate the salient roles of customer values and commitment in determining customer perceptions of future conflicts. By shifting scholarly attention from economic outcomes characterized by purchase intention to relationship outcomes characterized by functional conflict, the findings contribute to the research of the business implications of social networking sites.
       
  • Understanding mobile health service use: An investigation of routine and
           emergency use intentions
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Fei Liu, Eric Ngai, Xiaofeng Ju This study theorizes two information systems (IS) use behaviors associated with individuals’ behavioral intention of mobile health (mHealth) services. Emergency use refers to individuals’ use of IS in emergency situations. Routine use refers to individuals’ use of IS on a basis. We adopt motivation theory as our overarching theoretical lens through which we investigate the influence of individuals’ different motivation incentives on their emergency and routine use intentions of mHealth services. We also investigate the influences of technological and psychological antecedents on extrinsic and intrinsic motivations. Based on data collected from 241 participants, we find that perceived usefulness enhances people’s emergency and routine use intentions of mHealth services and that perceived enjoyment positively influences routine use intention. In addition, we find that perceived source credibility, perceived service availability, and perceived diagnosticity influence perceived usefulness (extrinsic motivation), whereas perceived autonomy, perceived competence, perceived relatedness, and curiosity affect perceived enjoyment (intrinsic motivation). This research offers insights for IS literature regarding mHealth emergency and routine use behaviors.
       
  • Why do users resist service organization’s brand mobile apps' The
           force of barriers versus cross-channel synergy
    • Abstract: Publication date: Available online 22 November 2018Source: International Journal of Information ManagementAuthor(s): Qian Chen, Yaobin Lu, Yeming (Yale) Gong, Qing Tang Service organizations increasingly develop brand apps (mobile applications) to expand service channels to the mobile end. Attracting their customers to install the brand app is critical. But there is widespread resistance to brand apps. This resistance can be classified as postponement, opposition and rejection. This study explores consumers’ active resistance of brand app in service organization. We examine the effects of adoption barriers and knowledge of alternatives quality on the three resistance behaviors and moderating effects of satisfaction with off-line service. The results show three resistance behaviors are affected by different reasons, and cross-channel synergy exists. Our study extends the theoretical understanding of the antecedents of and cross-channel influences on resistance to brand apps, with practical implications that managers should adopt different strategies for postponers, opponents and rejecters.
       
  • Exploration into the intellectual structure of mobile information systems
    • Abstract: Publication date: Available online 22 November 2018Source: International Journal of Information ManagementAuthor(s): Wen-Lung Shiau, Chang-Ming Yan, Bang-Wen Lin The purposes of this research are two-fold: to explore the key content of the Mobile Information Systems (MobIS) field and to identify the intellectual structure within MobIS research. Although mobile technologies have developed at great speed, little research has focused on the macroscopic viewpoint to understand the core knowledge of MobIS and its intellectual structure. To fill this research gap, articles related to MobIS from the ISI Web of Knowledge database and their cited articles were collected, and then citation analysis and document co-citation analysis were applied, including factor analysis and cluster analysis. This research identified 75 highly-cited articles and yielded 6 core categories of knowledge in mobile information systems: (1) Technology Acceptance; (2) Mobile Commerce; (3) Technology Innovation; (4) Use of Mobile Technology; (5) Measurement and Evaluation of Information Technology; and (6) Information System Success. The findings demonstrate that the MobIS field is still young and evolving. The core knowledge categories will be useful for scholars from different disciplines to effectively understand the core concepts and their relevance in MobIS in order to uncover possible research directions and entry-points in this rapidly expanding research area. Practitioners can also discover trend lines for future development, as well as identify extended themes for integration into the current MobIS field. This will benefit both the maintenance of current framework and the development of new business opportunities.
       
  • Lead users of business mobile services
    • Abstract: Publication date: Available online 17 November 2018Source: International Journal of Information ManagementAuthor(s): Heli Hallikainen, Ari Alamäki, Tommi Laukkanen This study examines characteristics that relate to lead userness in using business mobile services. From a large dataset of 2306 business decision-makers, the study identifies 205 lead users who are ahead of the majority in using business mobile services, while for the majority (n = 2101), business mobile services mainly supplement desktop and laptop computers. The authors test a binary logistic regression model in which individual technology readiness, sociodemographic variables, Internet use, and perceived importance of digital touchpoints predict lead userness in relation to business mobile services. The results show that job level is a highly significant predictor for lead userness in a work-related context, with senior management and entrepreneurs having the greatest likelihood for the use of business mobile services. Innovativeness and the perceived importance of mobile applications and social media also serve as positive predictors, while the perceived importance of websites and email result in a negative effect. The findings further suggest that the odds of being a lead user decrease by 2 percent per additional year of age, and that the odds of men is over 1.4 times greater than the odds of women.
       
  • A General framework for studying the evolution of the digital innovation
           ecosystem: The case of big data
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Bongsug (Kevin) Chae This paper presents a general framework for studying the digital innovation ecosystem. The notion of complex networks offers a conceptual lens to analyze the emergence and evolution of a digital innovation ecosystem. The framework uses digital data and evolutionary community detection analysis for the empirical inquiry of the digital innovation landscape. The proposed framework is applied to the big data ecosystem. Data from Twitter, for a three year period, is processed and analyzed. This study reveals a large number of elements that are diverse in form and capacity, including organizations, concepts (e.g., #analytics, #iot), technologies (e.g., #hadoop), applications (e.g., #healthcare), infrastructures (e.g., #cloud), regulations, professional meetings and associations, tools, and knowledge. These elements and their communities have evolved in the big data ecosystem. The findings highlight the evolution of digital innovation by two mechanisms, variation and selective retention, which are nonlinear and often unpredictable. Implications are presented and potential ways to improve the proposed framework are discussed. The study aims to make both conceptual and methodological contributions to digital innovation research.
       
  • Spatial data infrastructure management: A two-sided market approach for
           strategic reflections
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Chady Jabbour, Hélène Rey-Valette, Pierre Maurel, Jean-Michel Salles The recognition of a spatial data infrastructure (SDI), as a two-sided market, leads the way to an innovative approach for analysing the strategies used to bring two groups of users into interdependent markets. The literature derived from the recent industrial organisation is rich in theoretical models, aiming at the study of price structure and product design, which maximise the participation of the groups, the profits of the firms, and the value created for the entire ecosystem. The current paper interprets and adapts the theoretical model of the two-sided market in order to fit the case of a SDI. The purpose is to highlight the relevance of a two-sided market approach for analysing a SDI dynamics. The focal research question is how spatial data infrastructure, through a platform management process, can transition from a government-funded entity to a self-sustaining operation. The analysis relies on the specific case of the GEOSUD SDI, focusing on strategies ensuring the interest of image-based application developers and satellite image users. The results show that the theory of two-sided markets brings complementary elements for SDI development strategies, by proposing a framework of reasoning, which not only allows for a better understanding of the outflows already established, but also provides tools to accompany the strategic reflection of public institutions and entrepreneurs, who tend to support the uses of data and services derived from remote sensing.
       
  • Content features of tweets for effective communication during disasters: A
           media synchronicity theory perspective
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Jaebong Son, Hyung Koo Lee, Sung Jin, Jintae Lee Users’ ability to retweet information has made Twitter one of the most prominent social media platforms for disseminating emergency information during disasters. However, few studies have examined how Twitter’s features can support the different communication patterns that occur during different phases of disaster events. Based on the literature of disaster communication and Media Synchronicity Theory, we identify distinct disaster phases and the two communication types—crisis communication and risk communication—that occur during those phases. We investigate how Twitter’s representational features, including words, URLs, hashtags, and hashtag importance, influence the average retweet time—that is, the average time it takes for retweet to occur—as well as how such effects differ depending on the type of disaster communication. Our analysis of tweets from the 2013 Colorado floods found that adding more URLs to tweets increases the average retweet time more in risk-related tweets than it does in crisis-related tweets. Further, including key disaster-related hashtags in tweets contributed to faster retweets in crisis-related tweets than in risk-related tweets. Our findings suggest that the influence of Twitter’s media capabilities on rapid tweet propagation during disasters may differ based on the communication processes.
       
  • Business analytics and big data
    • Abstract: Publication date: Available online 13 November 2018Source: International Journal of Information ManagementAuthor(s): José Braga de Vasconcelos, Álvaro Rocha
       
  • A case analysis of E-government service delivery through a service chain
           dimension
    • Abstract: Publication date: Available online 13 November 2018Source: International Journal of Information ManagementAuthor(s): Vishanth Weerakkody, Ramzi El-Haddadeh, Uthayasankar Sivarajah, Amizan Omar, Andreea Molnar Unlike e-business few studies have examined how information is generated and exchanged between stakeholders in an e-government service chain to generate value for citizens. This case study applies the concept of service chains to empirically explore: a) how internal and external business activities in local government authorities (LGAs) contribute to electronic service delivery, and b) the impact that internal and external stakeholders have on these activities. The case study found that the diversity of stakeholders involved and lack of appropriate mechanisms for information exchange and collaboration are posing the biggest challenges for efficient local e-government service delivery.
       
  • The non-monetary benefits of mobile commerce: Extending UTAUT2 with
           perceived value
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Norman Shaw, Ksenia Sergueeva Consumers can conduct mobile commerce via their smartphones. They can search for products and when ready, they pay and have the products delivered to their homes. By sharing personal information, they receive faster and more customized service. Because of the risk of loss of privacy, consumers need to balance their privacy concerns against the perceived value of enhanced mobile commerce. In this empirical study, the unified theory of acceptance and use of technology (UTAUT2) is modified where perceived value replaces price value to represent the value of an IT artifact that has no direct costs attributable to it. The framework is extended to include constructs from the privacy calculus. In addition, the construct of personal innovativeness is added as a moderator with the anticipation that owners of smartphones who are more personally innovative will be more willing to share information. From an empirical study of Canadian smartphone owners, the results show that perceived privacy concerns influence perceived value and that intention to use is significantly influenced by hedonic motivation and perceived value.
       
  • Determinants of master data management adoption by local government
           organizations: An empirical study
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Faizura Haneem, Nazri Kama, Nazim Taskin, David Pauleen, Nur Azaliah Abu Bakar Master Data Management (MDM) is an approach for effective management of shared master data across organizations. In the public sector, MDM initiatives have been developed; however, the adoption among local government remains slow and there has been little interest in MDM adoption in extant research. Building on a Technology-Organization-Environment (TOE) framework, a conceptual model which highlights a set of potential determinants affecting the adoption of MDM by local government was developed. To validate the model, data were collected via survey from 224 responses from Malaysian local government department units. Using SEM-PLS, the study confirmed that data quality and data governance are two determinants of MDM adoption specific to the context of Malaysian local government, and four other determinants – complexity, top management support, technological competence, and citizen demand – are found to have significant effects on MDM adoption by local government. Surprisingly, three determinants – relative advantage, data security, and government policy – are found to have non-significant relationships to the adoption of MDM by local government. In addition, top management support is revealed to be a cornerstone of MDM technological competence in local government. The study contributes to the theoretical, contextual, and practical knowledge of MDM and IT adoption in the context of local government.
       
  • Investigating the impact of cybersecurity policy awareness on employees’
           cybersecurity behavior
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Ling Li, Wu He, Li Xu, Ivan Ash, Mohd Anwar, Xiaohong Yuan As internet technology and mobile applications increase in volume and complexity, malicious cyber-attacks are evolving, and as a result society is facing greater security risks in cyberspace more than ever before. This study has extended the published literature on cybersecurity by theoretically defining the conceptual domains of employees’ security behavior, and developed and tested operational measures to advance information security behavior research in the workplace. A conceptual framework is proposed and tested using survey results from 579 business managers and professionals. Structural equation modeling and ANOVA procedures are employed to test the proposed hypotheses. The results show that when employees are aware of their company’s information security policy and procedures, they are more competent to manage cybersecurity tasks than those who are not aware of their companies’ cybersecurity policies. The study also indicates that an organizational information security environment positively influences employees’ threat appraisal and coping appraisal abilities, which in turn, positively contribute to their cybersecurity compliance behavior.
       
  • An integrated view of particularized trust in social commerce: An
           empirical investigation
    • Abstract: Publication date: April 2019Source: International Journal of Information Management, Volume 45Author(s): Xusen Cheng, Yu Gu, Jia Shen With the prevalence of social media and social networking, social commerce is becoming increasingly popular in both business and research areas. As in other types of e-commerce context, trust is also indispensable in social commerce. In this study, two types of trust have been discussed. This study represents an initial attempt to provide an integrated view of particularized trust in social commerce, including particularized trust antecedents, trust transfer and trust performance, so as to promote trust formation in social commerce. Using data collected from 614 social commerce users, we demonstrate that trust disposition, quality-assured shared information, familiarity and endorsement by other members are four antecedents of particularized trust. The results also indicate particularized trust can be transferred into system trust, and particularized trust only exerts positive effect on social WOM intention while system trust only exerts positive effect on social shopping intention. Furthermore, we prove perceived similarity can strengthen the relationship between trust disposition and particularized trust as well as the relationship between quality-assured shared information and particularized trust.
       
  • Data analysis and feature selection for predictive maintenance: A
           case-study in the metallurgic industry
    • Abstract: Publication date: Available online 30 October 2018Source: International Journal of Information ManagementAuthor(s): Marta Fernandes, Alda Canito, Verónica Bolón-Canedo, Luís Conceição, Isabel Praça, Goreti Marreiros Proactive Maintenance practices are becoming more standard in industrial environments, with a direct and profound impact on the competitivity within the sector. These practices demand the continuous monitorization of industrial equipment, which generates extensive amounts of data. This information can be processed into useful knowledge with the use of machine learning algorithms. However, before the algorithms can effectively be applied, the data must go through an exploratory phase: assessing the meaning of the features and to which degree they are redundant. In this paper, we present the findings of the analysis conducted on a real-world dataset from a metallurgic company. A number of data analysis and feature selection methods are employed, uncovering several relationships, which are systematized in a rule-based model, and reducing the feature space from an initial 47-feature dataset to a 32-feature dataset.
       
  • An approach for planning and deploying gamification concepts with social
           networks within educational contexts
    • Abstract: Publication date: Available online 26 October 2018Source: International Journal of Information ManagementAuthor(s): Armando M. Toda, Ricardo M.C. do Carmo, Alan P. da Silva, Ig I. Bittencourt, Seiji Isotani Gamification planning has been a topic of discussion in the last years since it can be used to increase performance, engagement, and motivation of end users. When properly applied in educational settings, gamification can lead to better learning. Furthermore, it can be boosted when tied to social networks. However, according to the literature, there are three main concerns regarding this topic: (a) instructors and teachers does not have the resources to plan and develop gamification strategies into their classes; (b) gamification needs a systematic approach to achieve the desired positive results; and (c) inexistence of systematic approaches that connect and help in the design of gamification and social network tasks within these contexts. Thus, this work proposes a solution to help instructors and teachers to plan and deploy gamification concepts with social network features in learning environments. In this paper, we detailed our approach depicting the set of items to analyze and compare it with other solutions that are focused on education. Then, it was conducted a case study over a programming course (N = 40) to analyze the planning and deployment phases. Our results demonstrated that our approach is the first to consider the stakeholders (i.e. instructors and teachers) as part of the process. Moreover, even though there are still some obstacles to overcome, the gamified strategies that were created achieved positive acceptance among the students and professor.
       
  • Mobile cloud computing based stroke healthcare system
    • Abstract: Publication date: Available online 12 October 2018Source: International Journal of Information ManagementAuthor(s): Yeliz Karaca, Majaz Moonis, Yu-Dong Zhang, Caner Gezgez Information technology has recently seen a huge progress in innovative healthcare technologies that rendered healthcare data bigger. Connectivity on 7/24 basis between human to device and device to device have a crucial role in individuals’ lives. Therefore, Mobile Cloud System (MCC) has become an indispensable tool. Parallel with the rapid developments in the Internet of Things, convergence has become an important issue. Our proposed method, accordingly, can be converged with mobile-cloud environments with cloud computing in handling healthcare information. This study uses Virtual Dedicated Server (VDS) as 4 VCPU and 8 GB RAM and proposes a model based on the Android based mobile phones for stroke patients with cardioembolic (689) and cryptogenic (528) subtypes. The system set up through this study has two basic application elements which are mobile application and server application. Artificial Neural Network (ANN) module is beneficial for classifying the two stroke subtypes while server application is used for saving the data from the patients. Accordingly, our model guarantees availability, security, and scalability as a system for stroke patients applying Stroke dataset for ANN algorithm, Multilayer Perceptron Algorithm (MLP), which has been done for the first time in literature with big data in this scope. The main contributions are: (1) The outcomes will display an individual unique social insurance framework. (2) The outcomes will be utilized for the distinguishing proof of stroke-related data to be gathered by cell phones that are Android based. (3) Stroke patients will find out about their condition of well-being through an ANN application programming interface, which will provide a sort of organization for the patients. Overall, an efficient and user-friendly stroke determination human services framework has been presented through this Healthcare System for patients.Graphical abstractMLP in Stroke Diagnosis Healthcare System seems to be crucial concerning the use of mobile cloud computing for the management of stroke data in healthcare systems. In general, life quality of the patients will be improved since they will have more agency over their disease. Once they enter the analysis results on the system set up, they can have direct access to the relevant data so they can have agency over their course of disease, which render them more aware and informed patients. The secondary benefit would be concerned with the psychological aspect since agency and more awareness would help reduce anxiety and concerns regarding the disease.
       
  • Adoption of O2O food delivery services in South Korea: The moderating role
           of moral obligation in meal preparation
    • Abstract: Publication date: Available online 11 October 2018Source: International Journal of Information ManagementAuthor(s): Minjung Roh, Kiwan Park Most studies on O2O services have focused solely on the technological merits of mobile applications, overlooking the role of the value systems that underlie people’s lifestyles.In contrast, this research sheds light on how people’s value systems influence their decision to adopt food delivery applications. Particularly, it proposes that people’s moral obligation in meal preparation can change the mode of thinking that guides their adoption decision. Namely, moral obligation is assumed to restrict people from acting on their basic convenience orientation in meal preparation. Empirical results have supported this assumption by showing that people with a high moral obligation (or married people) are more reluctant to convert their basic convenience-seeking tendencies into actual adoption intention than those with a low moral obligation (or single people). The important theoretical and managerial implications of these results are also discussed.
       
  • A reversible and secure patient information hiding system for IoT driven
           e-health
    • Abstract: Publication date: Available online 11 October 2018Source: International Journal of Information ManagementAuthor(s): Javaid A. Kaw, Nazir A. Loan, Shabir A. Parah, K. Muhammad, Javaid A. Sheikh, G.M. Bhat Internet of things (IoT) coupled with mobile cloud computing has made a paradigm shift in the service sector. IoT-assisted mobile cloud based e-healthcare services are making giant strides and are likely to change the conventional ways of healthcare service delivery. Though numerous approaches for preventing unauthorized access to information exchanged between a mobile phone and cloud platform do exist, but there is no security mechanism to prevent unauthorized access by the cloud administrators. With an aim to ensure security of client data such as Electronic Patient Records (EPR), we propose a novel high-capacity and reversible data hiding approach for securely embedding EPR within the medical images using Optimal Pixel Repetition (OPR). OPR converts every pixel of the input image to a 2 × 2 block to facilitate reversibility by ensuring all the pixels in a 2 × 2 block to have different values. Since a 2 × 2 block is comprised of 4-pixel elements, which could be arranged in sixteen possible ways; we generate a lookup table corresponding to sixteen possible positions of pixels. EPR hiding in each block is achieved by permuting the pixels of a block according to the four-bit word of secret data, resulting in a histogram invariant stego image. The histogram invariance improves the robustness of the proposed scheme to statistical attacks. A stego image is said to hide embedded data securely, when it provides better imperceptivity for an appreciably high payload. Thus, while using information embedding approach for securing client data on a mobile-cloud platform, high imperceptivity is a desirable feature. Experimental results show that average PSNR obtained is 42 dB for payload 1.25 bpp by our scheme, showing its effectiveness for preventing unauthorized access to client’s sensitive data.
       
  • The role of a digital engineering platform in appropriating the creation
           of new work-related mind-set and organisational discourse in a large
           multi-national company
    • Abstract: Publication date: Available online 8 October 2018Source: International Journal of Information ManagementAuthor(s): Zahid I. Hussain, Uthayasankar Sivarajah, Naveed Hussain This paper reports on a case study involving a strategic and innovative approach to creation of an in-house multifaceted digital engineering platform (the DEP) in overcoming a number of organisational problems at a multinational engineering company. The DEP was to be used strategically for simplifying the operational complexity and to create and appropriate new work-related mind-set and new organisational discourse to achieve homogenous working across the organisation, which is a huge challenge. The need for this system emerged from the need to resolve many organisational services related problems that carried phenomenal amount of processes, health and safety risks and to regulate, and, control the running of engineering project. Research data were collected using a longitudinal case study approach over a period of six months. In order to make sense of how the DEP helped the organisation, the study used certain elements of Extended Structuration Theory as a lens to assess the case study. This research discovered that the DEP succeeded in creating and appropriating work-related mind-set and organisational discourse. It also had real influence on working processes and employees at all levels while encouraging transparency, responsiveness, agility and accountability. It continues to help the organisation to govern, manage and maintain good standard of service but many barriers still remain.
       
  • Cross-company customer churn prediction in telecommunication: A comparison
           of data transformation methods
    • Abstract: Publication date: Available online 27 September 2018Source: International Journal of Information ManagementAuthor(s): Adnan Amin, Babar Shah, Asad Masood Khattak, Fernando Joaquim Lopes Moreira, Gohar Ali, Alvaro Rocha, Sajid Anwar Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).
       
  • Mobile edge computing based QoS optimization in medical healthcare
           applications
    • Abstract: Publication date: Available online 25 September 2018Source: International Journal of Information ManagementAuthor(s): Ali Hassan Sodhro, Zongwei Luo, Arun Kumar Sangaiah, Sung Wook Baik Emerging trends in mobile edge computing for developing the efficient healthcare application such as, remote monitoring of the patients with central electronics clouds (e-Clouds) and their increasing voluminous multimedia have caught the attention of everyone in industry and academia. So, clear visualization, big sensing level, and better quality of service (QoS) is the foremost priority. This paper proposes the window-based Rate Control Algorithm (w-RCA) to optimize the medical quality of service (m-QoS) in the mobile edge computing based healthcare by considering the network parameters for instance, peak-to-mean ratio (PMR), standard deviation (Std.dev), delay and jitter during 8 min medical video stream named “Navigation to the Uterine Horn, transection of the horn and re-anastomosis’ transmission over 5 G networks. The performance of the proposed w-RCA is evaluated and compared with the conventional battery smoothing algorithm (BSA) and Baseline by using MPEG-4 encoder for optimizing m-QoS at the source or the server side. The experimental results demonstrate that the w-RCA outperforms the BSA and Baseline by optimizing QoS in remote healthcare application i.e., Tele-surgery. Besides, it is observed and analyzed that w-RCA produces better and effective results at small buffer and window sizes unlike BSA and Baseline by adopting large buffer size during QoS optimization.
       
  • A lossless DNA data hiding approach for data authenticity in mobile cloud
           based healthcare systems
    • Abstract: Publication date: Available online 25 September 2018Source: International Journal of Information ManagementAuthor(s): Mohammad Saidur Rahman, Ibrahim Khalil, Xun Yi We present a lossless Deoxyribonucleic Acid (DNA) sequence hiding method that can be used for ensuring authenticity of DNA sequence in the context of Mobile Cloud based healthcare systems. Hiding data within DNA sequence results in permanent information loss in DNA sequence. Therefore, providing DNA sequence authenticity using data hiding is challenging. Moreover, existing works on DNA data hiding require a reference DNA sequence data to retrieve hidden data. Hence, current methods are not blind approaches and inappropriate for ensuring authenticity of DNA sequence in the Mobile Cloud. The proposed method hides authentication data within DNA sequence, extracts authentication data, and reconstructs the DNA sequence without any loss of information. From there, our proposed approach guarantees DNA sequence authenticity and integrity in Mobile Cloud based healthcare systems. We present a security analysis of our method to show that the method is secured. We conduct several experiments to demonstrate the performance of our proposed method.
       
  • How perceived value drives the use of mobile financial services apps
    • Abstract: Publication date: Available online 25 September 2018Source: International Journal of Information ManagementAuthor(s): Heikki Karjaluoto, Aijaz A. Shaikh, Hannu Saarijärvi, Saila Saraniemi Mobile information services have revolutionized business models and service delivery methods by facilitating consumer access to information and order placement via mobile apps. In developed markets, mobile banking (m-banking) and mobile payment (m-payment) applications have replaced text-based mobile services. However, extant research has not addressed these mobile financial services apps (MFSAs) adequately from the perspective of consumer behavior. Thus, the present study developed and tested a series of hypotheses related to the antecedents of perceived value of MFSA use; it also examined how such use affects the development of customers’ overall relationships with banks. Our hypotheses were tested using two samples (N = 992; N = 524) comprising different types of MFSA end-users in one of the leading countries in digital banking, Finland. The results supported most of the hypotheses and revealed that self-congruence and new product novelty are the principal drivers of perceived MFSA value. In addition, the findings show that the perceived value of MFSAs yields strong positive effects on customers’ overall satisfaction and commitment to their bank. The present study’s key managerial implication is that banks’ investments in developing MFSAs result in improved relationships with customers and increased business.
       
  • Measuring the impact of spammers on e-mail and Twitter networks
    • Abstract: Publication date: Available online 24 September 2018Source: International Journal of Information ManagementAuthor(s): Andrea Fronzetti Colladon, Peter A. Gloor This paper investigates the research question if senders of large amounts of irrelevant or unsolicited information – commonly called “spammers” – distort the network structure of social networks. Two large social networks are analyzed, the first extracted from the Twitter discourse about a big telecommunication company, and the second obtained from three years of email communication of 200 managers working for a large multinational company. This work compares network robustness and the stability of centrality and interaction metrics, as well as the use of language, after removing spammers and the most and least connected nodes. The results show that spammers do not significantly alter the structure of the information-carrying network, for most of the social indicators. The authors additionally investigate the correlation between e-mail subject line and content by tracking language sentiment, emotionality, and complexity, addressing the cases where collecting email bodies is not permitted for privacy reasons. The findings extend the research about robustness and stability of social networks metrics, after the application of graph simplification strategies. The results have practical implication for network analysts and for those company managers who rely on network analytics (applied to company emails and social media data) to support their decision-making processes.
       
  • Real-time big data processing for anomaly detection: A Survey
    • Abstract: Publication date: Available online 8 September 2018Source: International Journal of Information ManagementAuthor(s): Riyaz Ahamed Ariyaluran Habeeb, Fariza Nasaruddin, Abdullah Gani, Ibrahim Abaker Targio Hashem, Ejaz Ahmed, Muhammad Imran The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifically in the domain of anomaly detection in network, which is considered crucial for network security. However, preliminary investigations have revealed that the existing approaches to detect anomalies in network are not effective enough, particularly to detect them in real time. The reason for the inefficacy of current approaches is mainly due the amassment of massive volumes of data though the connected devices. Therefore, it is crucial to propose a framework that effectively handles real time big data processing and detect anomalies in networks. In this regard, this paper attempts to address the issue of detecting anomalies in real time. Respectively, this paper has surveyed the state-of-the-art real-time big data processing technologies related to anomaly detection and the vital characteristics of associated machine learning algorithms. This paper begins with the explanation of essential contexts and taxonomy of real-time big data processing, anomalous detection, and machine learning algorithms, followed by the review of big data processing technologies. Finally, the identified research challenges of real-time big data processing in anomaly detection are discussed.
       
  • A health data analytics maturity model for hospitals information systems
    • Abstract: Publication date: Available online 26 July 2018Source: International Journal of Information ManagementAuthor(s): João Vidal Carvalho, Álvaro Rocha, José Vasconcelos, António Abreu In the last five decades, maturity models have been introduced as reference frameworks for Information System (IS) management in organizations within different industries. In the healthcare domain, maturity models have also been used to address a wide variety of challenges and the high demand for hospital IS (HIS) implementations. The increasing volume of data, is exceeded the ability of health organizations to process it for improving clinical and financial efficiencies and quality of care. It is believed that careful and attentive use of Data Analytics in healthcare can transform data into knowledge that can improve patient outcomes and operational efficiency. A maturity model in this conjuncture, is a way of identifying strengths and weaknesses of the HIS maturity and thus, find a way for improvement and evolution. This paper presents a proposal to measure Hospitals Information Systems maturity with regard to Data Analytics. The outcome of this paper is a maturity model, which includes six stages of HIS growth and maturity progression.
       
  • An overview of assessing the quality of peer review reports of scientific
           articles
    • Abstract: Publication date: Available online 20 July 2018Source: International Journal of Information ManagementAuthor(s): Amanda Sizo, Adriano Lino, Luis Paulo Reis, Álvaro Rocha Assuring the quality control of publications in the scientific literature is one of the main challenges of the peer review process. Consequently, there has been an increasing demand for computing solutions that will help to maintain the quality of this process. Recently, the use of Artificial Intelligence techniques has been highlighted, applied in the detection of plagiarism, bias, among other functions. The assessment of the reviewer’s review has also been considered as important in the process, but, little is known about it, for instance, which techniques have been applied in this assessment or which criteria have been assessed. Therefore, this systematic literature review aims to find evidence regarding the computational approaches that have been used to evaluate reviewers' reports. In order to achieve this, five online databases were selected, from which 72 articles were identified that met the inclusion criteria of this review, all of which have been published since 2000. The result returned 10 relevant studies meeting the evaluation requirements of scientific article reviews. The review revealed that mechanisms to rank review reports according to a score, as well as the word analysis, are the most common tools, and that there is no consensus on quality criteria. The systematic literature review has shown that reviewers’ report assessment is a valid tool for maintaining quality throughout the process. However, it still needs to be further developed if it is to be used as a resource which surpass a single conference or journal, making the peer review process more rigorous and less based on random choice.
       
  • An m-health application for cerebral stroke detection and monitoring using
           cloud services
    • Abstract: Publication date: Available online 30 June 2018Source: International Journal of Information ManagementAuthor(s): Laura García, Jesús Tomás, Lorena Parra, Jaime Lloret Over 25 million people suffered from cerebral strokes in a span of 23 years. Many systems are being developed to monitor and improve the life of patients that suffer from different diseases. However, solutions for cerebral strokes are hard to find. Moreover, due to their widespread utilization, smartphones have presented themselves as the most appropriate devices for many e-health systems. In this paper, we propose a cerebral stroke detection solution that employs the cloud to store and analyze data in order to provide statistics to public institutions. Moreover, the prototype of the application is presented. The three most important symptoms of cerebral strokes were considered to develop the tasks that are conducted. Thus, the first task detects smiles, the second task employs voice recognition to determine if a sentence is repeated correctly and, the third task determines if the arms can be raised. Several tests were performed in order to verify the application. Results show its ability to determine whether users have the symptoms of cerebral stroke or not.
       
  • Deep gesture interaction for augmented anatomy learning
    • Abstract: Publication date: Available online 28 March 2018Source: International Journal of Information ManagementAuthor(s): Ahmad Karambakhsh, Aouaidjia Kamel, Bin Sheng, Ping Li, Po Yang, David Dagan Feng Augmented reality is very useful in medical education because of the problem of having body organs in a regular classroom. In this paper, we propose to apply augmented reality to improve the way of teaching in medical schools and institutes. We propose a novel convolutional neural network (CNN) for gesture recognition, which recognizes the human's gestures as a certain instruction. We use augmented reality technology for anatomy learning, which simulates the scenarios where students can learn Anatomy with HoloLens instead of rare specimens. We have used the mesh reconstruction to reconstruct the 3D specimens. A user interface featured augment reality has been designed which fits the common process of anatomy learning. To improve the interaction services, we have applied gestures as an input source and improve the accuracy of gestures recognition by an updated deep convolutional neural network. Our proposed learning method includes many separated train procedures using cloud computing. Each train model and its related inputs have been sent to our cloud and the results are returned to the server. The suggested cloud includes windows and android devices, which are able to install deep convolutional learning libraries. Compared with previous gesture recognition, our approach is not only more accurate but also has more potential for adding new gestures. Furthermore, we have shown that neural networks can be combined with augmented reality as a rising field, and the great potential of augmented reality and neural networks to be employed for medical learning and education systems.
       
  • Business analytics use in CRM: A nomological net from IT competence to CRM
           performance
    • Abstract: Publication date: Available online 1 February 2018Source: International Journal of Information ManagementAuthor(s): Dalwoo Nam, Junyeong Lee, Heeseok Lee Business analytics (BA) becomes increasingly important under rapidly changing business environment. A research challenge is that BA use is not fully understood. We tackle this challenge from the perspective of dynamic capability by using an empirical model with the emphasis on BA use in customer relationship management (CRM). Based on 170 samples from firm-level survey, we analyze the nomological linkage from IT competence to CRM performance. The results show data management capability fully mediates between IT competence and BA use, while customer response capability partially mediates between BA use and CRM performance.
       
  • Making a case for speech analytics to improve customer service quality:
           Vision, implementation, and evaluation
    • Abstract: Publication date: Available online 10 January 2018Source: International Journal of Information ManagementAuthor(s): Scott Scheidt, Q.B. Chung Firms operating in highly competitive markets must find ways to deliver customer value beyond offering competitive prices. Providing superior customer service in such environments becomes a strategic initiative because it can create a competitive advantage by fostering customer loyalty, which can also help ease pressure on profit margins and secure continued revenue flow. In this case study we report a case of utilizing speech analytics to improve customer service quality at a call center of a pharmaceutical supply chain service provider in the U.S. We first describe the strategic rationale behind enhancing customer service quality, followed by the implementation of a quality management program using a novel approach of speech analytics. We then present a longitudinal study that evaluated customer service performance using the data gathered from a team of 120 customer service agents during an 8-month period. Two categories of key performance indicators were established and measured, namely “workforce management” metrics and “customer experience” metrics, which served as the primary indicators in the analysis of the level of success in attaining three strategically identified performance goals to improve customer service quality.
       
 
 
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