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International Journal of Information Management
Journal Prestige (SJR): 1.373
Citation Impact (citeScore): 6
Number of Followers: 319  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0268-4012
Published by Elsevier Homepage  [3161 journals]
  • Analytics-based decision-making for service systems: A qualitative study
           and agenda for future research
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): Shahriar Akter, Ruwan Bandara, Umme Hani, Samuel Fosso Wamba, Cyril Foropon, Thanos Papadopoulos While the use of big data tends to add value for business throughout the entire value chain, the integration of big data analytics (BDA) to the decision-making process remains a challenge. This study, based on a systematic literature review, thematic analysis and qualitative interview findings, proposes a set of six-steps to establish both rigor and relevance in the process of analytics-driven decision-making. Our findings illuminate the key steps in this decision process including problem definition, review of past findings, model development, data collection, data analysis as well as actions on insights in the context of service systems. Although findings have been discussed in a sequence of steps, the study identifies them as interdependent and iterative. The proposed six-step analytics-driven decision-making process, practical evidence from service systems, and future research agenda, provide altogether the foundation for future scholarly research and can serve as a step-wise guide for industry practitioners.
       
  • Understanding the formation mechanism of high-quality knowledge in social
           question and answer communities: A knowledge co-creation perspective
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): Yan Zhang, Mingli Zhang, Nuan Luo, Yu Wang, Tao Niu The social question and answer (Q&A) community provides people with an effective tool to obtain high-quality information. From the perspective of reciprocal determinism and value co-creation, this study aims to investigate the formation mechanism of high-quality knowledge in the community. We develop a model to investigate how cognitive factors and community technological factors influence users’ knowledge co-creation behavior, thereby influencing knowledge quality in the community. A survey of 382 knowledge contributors in a social Q&A community shows that knowledge self-efficacy, topic richness, personalized recommendation, and social interactivity have a positive impact on users' knowledge sharing and integration behavior, which subsequently affect the community’s knowledge quality. Moreover, users' ratings moderate the influence of knowledge sharing on knowledge quality. This research demonstrates the synergistic effect of people and technology in knowledge co-creation, thus advances literature about value co-creation and content quality in online communities.
       
  • Artificial intelligence for decision making in the era of Big Data –
           evolution, challenges and research agenda
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): Yanqing Duan, John S. Edwards, Yogesh K Dwivedi Artificial intelligence (AI) has been in existence for over six decades and has experienced AI winters and springs. The rise of super computing power and Big Data technologies appear to have empowered AI in recent years. The new generation of AI is rapidly expanding and has again become an attractive topic for research. This paper aims to identify the challenges associated with the use and impact of revitalised AI based systems for decision making and offer a set of research propositions for information systems (IS) researchers. The paper first provides a view of the history of AI through the relevant papers published in the International Journal of Information Management (IJIM). It then discusses AI for decision making in general and the specific issues regarding the interaction and integration of AI to support or replace human decision makers in particular. To advance research on the use of AI for decision making in the era of Big Data, the paper offers twelve research propositions for IS researchers in terms of conceptual and theoretical development, AI technology-human interaction, and AI implementation.
       
  • Facebook usage and mental health: An empirical study of role of
           non-directional social comparisons in the UK
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): Tahir M. Nisar, Guru Prabhakar, P. Vigneswara Ilavarasan, Abdullah M. Baabdullah The present paper explores the relationship between nature of Facebook usage, non-directional comparisons and depressive syndromes. The extant research on linkage between social media usage and mental health is inconclusive. The paper uses data collected through an online survey of 399 Facebook users in the UK. A Facebook frequency rating scale was developed and validated as a part of the study. The Iowa-Netherlands Comparison Orientation Measure was modified and used to measure social comparison. The depressive syndromes were captured by the modified Center for Epidemiological Studies Depression Scale. The Rank Theory of Depression was used a guiding framework. The data collection had focused on the 20–29 year olds, as justified by the literature.The study found a negative relationship between active Facebook use and non-directional social comparisons. The relationship was reversed in the case of passive usage. There is small but significant causal linkage between increased non-directional social comparisons and depressive symptoms among the users.
       
  • Impact of corporate social responsibility on reputation—Insights from
           tweets on sustainable development goals by CEOs
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): Purva Grover, Arpan Kumar Kar, P. Vigneswara Ilavarasan Social media had been extensively used for communication and networking purposes among corporates. Literature indicates social media platforms had also been used by the firms for building relationship with different stakeholders (i.e. customers, employees, investors and neighbouring communities). But there exists a gap in literature, whether social capital present on social media can be used for building corporate reputation (CR) in the society. Literature indicates corporate social responsibility (CSR) impacts CR. Therefore this study explores how CSR messages on social media impacts CR. For this study assumption was made that all the concerns and issues raised by Sustainable Development Goals (SDGs) are the social responsibilities of the CEOs. The study tries to explore this gap by analysing the tweets posted by two group of CEOs, i.e. CEOs in top 200 fortune companies and top 100 social influencer CEOs. Top 100 social influencer CEOs on social media were identified from the Hootsuite.com. Social influencer CEOs are having tremendous amount of influence on Twitter. The statistically test performed on the two group of the CEOs depicts there is significant difference in the number of CSR messages posted by fortune CEOs and social influencer CEOs. Results reveals social influencer CEOs had posted 5.97 times more CSR messages on Twitter as compared to fortune CEOs, which in turn may had led to better CR, in terms of shares and likes by social capital present on Twitter. The study reveals may be social influencer CEOs through CSR messages are trying to engage stakeholders strategically on Twitter. This is an open question at present, therefore future researchers can explore this in more details. The managerial implication of the study for CEOs and firms had been highlighted in the study.
       
  • RFID technology-enabled Markov reward process for sequencing care
           coordination in ambulatory care: A case study
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): Yi-Chin Kato-Lin, Rema Padman Care coordination is vital for patient-centered care delivery. While communication is key to sharing information, sequencing the critical activities associated with care delivery is key to process efficiency and safety. The “communication” aspect has been often addressed by computer systems, but very limited attention has been paid to the “sequencing” aspect. Alongside, although real-time location systems (RTLS) are widely used for tracking purposes, they have not been used to develop analytical models for decision making, thus advancing the role and value of information technologies (IT). This paper proposes a data driven solution for developing prescriptive policies regarding the sequencing of care delivery activities in ambulatory care such that the goal of well-coordinated care may be achieved. Specifically, we propose a Markov Reward Process model to find the optimal care delivery sequence that minimizes patient waiting time using empirical data collected by Gen2IR/RFID technology in an outpatient clinic. We demonstrate improved sequencing of care delivery activities in comparison to status quo. The application of RFID in this study elevates the value of RTLS in healthcare from just tracking and identifying objects/persons to guiding and changing operational activities. Our method is generalizable to a variety of care coordination problems in different care delivery settings, and can be embedded in decision support systems for better operational sequencing of care delivery activities.
       
  • Calculating trust in domain analysis: Theoretical trust model
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): Jamal Al Qundus, Adrian Paschke, Sameer Kumar, Shivam Gupta In recent decades, more information has become increasingly available on the Web. Every user can actively participate in the generation and exchange of information. Investigating the quality of user-generated content (UGC) has therefore become a necessity and an ever-increasing challenge. In collaborative environments where users collect, share and build a knowledge base, trust is an important factor. If, for example, we as users trust UGC on the Web, this influences our interaction with this content. The aim of our research is to propose a model for the evaluation of trust in UGC. Based on the available research results, we define a model for measuring trust in collaborative environments. Our approach is based on three dimensions: stability, credibility and quality. These three concerns are combined to create a trusted translator. We use a real-world data set of the social annotation platform Genius to calculate the value of our trust in an annotation. Based on this case study, we show which insights can be gained by calculating the trust in such an environment. When information has specific qualities, our approach will enable the user to better determine which information offers the highest level of trust.
       
  • 30 years of intelligence models in management and business: A bibliometric
           review
    • Abstract: Publication date: October 2019Source: International Journal of Information Management, Volume 48Author(s): J.R. López-Robles, J.R. Otegi-Olaso, I. Porto Gómez, M.J. Cobo The critical factors in the big data era are collection, analysis, and dissemination of information to improve an organization’s competitive position and enhance its products and services. In this scenario, it is imperative that organizations use Intelligence, which is understood as a process of gathering, analyzing, interpreting, and disseminating high-value data and information at the right time for use in the decision-making process. Earlier, the concept of Intelligence was associated with the military and national security sector; however, in present times, and as organizations evolve, Intelligence has been defined in several ways for the purposes of different applications. Given that the purpose of Intelligence is to obtain real value from data, information, and the dynamism of the organizations, the study of this discipline provides an opportunity to analyze the core trends related to data collection and processing, information management, decision-making process, and organizational capabilities. Therefore, the present study makes a conceptual analysis of the existing definitions of intelligence in the literature by quantifying the main bibliometric performance indicators, identifying the main authors and research areas, and evaluating the development of the field using SciMAT as a bibliometric analysis software.
       
  • Information system capabilities and firm performance: Opening the black
           box through decision-making performance and business-process performance
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Arafat Salih Aydiner, Ekrem Tatoglu, Erkan Bayraktar, Selim Zaim This study contributes to the extant literature on information management by investigating the interrelationships between information systems (IS)-related capabilities and their effects on firm performance. Using the resource-based view (RBV), a set of hypotheses is formulated to examine these links, considering the role that may be played by decision-making performance and business-process performance as mediating variables. Structural equation modeling (SEM) has been applied to a sample of 204 firms in Turkey. The test results obtained confirm the proposed serially mediating model according to which decision-making performance and business-process performance play a critical mediating role in the human resource and administrative-related IS capabilities, and firm-performance relationships. No support, however, has been found concerning the serial mediation effect between infrastructure-related IS capabilities and firm performance.
       
  • Measuring extreme risk of sustainable financial system using GJR-GARCH
           model trading data-based
    • Abstract: Publication date: Available online 30 January 2019Source: International Journal of Information ManagementAuthor(s): Xiaomeng Ma, Ruixian Yang, Dong Zou, Rui Liu This paper investigates the role of gold as a safe haven for stock markets and the US dollar by examining the extreme risk spillovers. The extreme risk is measured by Value at Risk (VaR), which is estimated by GJR-GARCH model based on skewed t distribution. Two test statistics of one-way and two-way Granger causality in risk are used to detect extreme risk spillovers. In general, the empirical results show that there are negative extreme risk spillovers between gold and stock markets and between gold and foreign exchange markets of US dollar, which indicate that gold can act as an effective safe haven against extreme stock and US dollar exchange rate movements. In addition, the global financial crisis can affect the safe haven role of gold.
       
  • How to facilitate knowledge diffusion in complex networks: The roles of
           network structure, knowledge role distribution and selection rule
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Tong Qiao, Wei Shan, Mingli Zhang, Chen Liu The diffusion of knowledge within organizations provides opportunities for interpersonal co-operation, improves creative ability and therefore leads to competitive advantage. Focus of prior literature on knowledge diffusion has been on identifying factors that influence individuals' behavioral intentions to seek and share knowledge. However, knowledge diffusion as an enigmatic, emergent and organizational-level process is more than the simple aggregation of individual attributes and needs to be further investigated. Accordingly, this study focuses on three distinct system-level factors, i.e., architectures of connections among individuals, distributions of knowledge roles and designs of selection mechanisms and analyses their effects on knowledge diffusion. To be more specific, we examine three distinct knowledge roles: seekers, contributors and brokers. We also distinguish between three types of selection mechanisms: objective selection mechanisms, feedback-based selection mechanisms and random selection mechanisms. By conducting agent-based simulations on four representative networks, i.e., regular networks, random networks, small-world networks and scale-free networks, our results show that the optimal knowledge diffusion performance can be achieved on scale-free networks where all agents implement objective mechanisms and show characteristics of brokers. Moreover, our results (a) highlight the significance of brokers, (b) illustrate the superiority of objective selection rules and (c) demonstrate that scale-free networks provide an optimal framework for knowledge diffusion. Furthermore, we also find the interdependent relevance of these three factors to knowledge diffusion and propose a qualitative explanation of these findings.
       
  • Role of authenticity and perceived benefits of online courses on
           technology based career choice in India: A modified technology adoption
           model based on career theory
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Arghya Ray, Pradip Kumar Bala, Shilpee A. Dasgupta In this digital era, it is important to make a wise course choice since the building blocks of a career starts from choosing the career-specific course. With the number of online courses available, it is tough to differentiate a relevant career-focused course from a mediocre one. Hence, the authenticity and validity of a particular course influence the career choice of individuals. The other important factor is perceived benefits. Additionally, an increasing number of educational businesses has already integrated or plans to integrate social media applications into their marketing plans to reach and attract future students, thus showing a shift from traditional ways of marketing. As the nature of this study is both purposive as well as probabilistic, a mixed method approach has been chosen. The study consists of two phases: the exploratory research process consisting of the literature review, the semi-structured interviews with information technology professionals to form the questionnaire and hypotheses. The researchers found that through personal inputs strongly influence the learning experiences, authenticity and perceived benefits of a course plays the most important role in the individual’s decision to adopt a technical course. The practical and research implications have also been discussed.
       
  • An empirical study on predicting cloud incidents
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Yaman Roumani, Joseph K. Nwankpa With the increasing rate of adoption and growth of cloud computing services, businesses have been shifting their information technology (IT) infrastructure to the cloud. Although cloud vendors promise high availability and reliability of their cloud services, cloud-related incidents involving outages and service disruptions remain a challenge. Understanding cloud incidents and the ability to predict them would be helpful in deciding how to manage and circumvent future incidents. In this study, we propose a hybrid model that employs machine learning and time series methods to forecast cloud incidents. We evaluate the proposed model using a sample of 2261 incidents collected from two cloud providers namely, Netflix and Hulu. Unique to this study is that our model relies solely on historical data that is independent of the underlying cloud infrastructure. Results suggest that the proposed hybrid model outperforms individual forecasting models: neural network, time series and random forest. Results also reveal important temporal insights from the proposed model and highlights the practical relevance of historical data to forecast and manage cloud incidents.
       
  • An integrated holistic model for an eHealth system: A national
           implementation approach and a new cloud-based security model
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Salah Al-Sharhan, Esraa Omran, Kamran Lari Although its structure and strategies are rapidly evolving, the impact of the eHealth on the healthcare services is evident. Implementing eHealth systems on a national level can drastically enhance the health practices and services provided to the patients and community. Hence, the engineering of a new model and a holistic framework for eHealth systems becomes a necessity in order to have an effective implementation of these systems. The vast and rapid development in computers, communication, and Internet technologies has significantly affected the contemporary health systems. However, the complexity of the healthcare environment, the abundance of information, the compatibility and the lack of unified eHealth framework creates real challenges to present efficient and attractive eHealth model that encompasses all these elements. Furthermore, the security of the health records and the secure access to the information add a new dimension of complexity. This work presents a new model and an integrated framework for an efficient implementation of eHealth systems at the national level. The proposed model and framework successfully incorporate all the success factors of efficient eHealth system along with a new security model to access the health records.
       
  • Emergency management in the changing world of social media: Framing the
           research agenda with the stakeholders through engaged scholarship
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Amany Elbanna, Deborah Bunker, Linda Levine, Anthony Sleigh The use of social media and Web 2.0 platforms is proliferating and affecting different formal and highly structured organisations including public safety agencies. Much of the research in the area has focussed on public use of social media during an emergency as well as how emergency agencies benefit from the data and information generated by this process. However, there is little understanding of “what are the operational implications of this public use on emergency management agencies and how does social media either positively or negatively impact these operations”' In order to progress research into this topic, we chose an engaged scholarship framework to shape a research agenda with the active participation of stakeholders. Hence, we conducted a series of workshops primarily involving over 100 public safety practitioners working in the area of disasters and emergency management who work in public safety agencies, humanitarian organisations, volunteering online platforms and volunteer groups in addition to 20 academics working on this area of enquiry. The findings highlight six different challenges that emergency responding organisations currently face in relation to social media use. We conceptualise these challenges as creating six operational tension zones for organisations. We discuss these tensions and their implications for future research and practice.
       
  • Applications of business intelligence and analytics in social media
           marketing
    • Abstract: Publication date: Available online 23 January 2019Source: International Journal of Information ManagementAuthor(s): Nick Hajli, Michel Laroche
       
  • Smart cities: Advances in research—An information systems
           perspective
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Elvira Ismagilova, Laurie Hughes, Yogesh K. Dwivedi, K. Ravi Raman Smart cities employ information and communication technologies to improve: the quality of life for its citizens, the local economy, transport, traffic management, environment, and interaction with government. Due to the relevance of smart cities (also referred using other related terms such as Digital City, Information City, Intelligent City, Knowledge-based City, Ubiquitous City, Wired City) to various stakeholders and the benefits and challenges associated with its implementation, the concept of smart cities has attracted significant attention from researchers within multiple fields, including information systems. This study provides a valuable synthesis of the relevant literature by analysing and discussing the key findings from existing research on issues related to smart cities from an Information Systems perspective. The research analysed and discussed in this study focuses on number of aspects of smart cities: smart mobility, smart living, smart environment, smart citizens, smart government, and smart architecture as well as related technologies and concepts. The discussion also focusses on the alignment of smart cities with the UN sustainable development goals. This comprehensive review offers critical insight to the key underlying research themes within smart cities, highlighting the limitations of current developments and potential future directions.
       
  • Developing customer product loyalty through mobile advertising: Affective
           and cognitive perspectives
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Chih-Cheng Lu, Ing-Long Wu, Wei-Hung Hsiao Mobile advertising is an increasingly popular marketing channel since it can present advertising in a personalized manner. This study examines the development of customer product loyalty through mobile advertising by considering the drivers from affective and cognitive perspectives. An Expectation Confirmation Model (ECM), as defined for repurchase intention, is proposed as a theoretical basis for the relationship structure of related research variables. An Elaboration Likelihood Model (ELM) identifies affective and cognitive concerns for defining the drivers of consumer behavior. Involvement and interactivity confirmation arise as affective and cognitive concerns in this context. This research model also indicates a particular mediating role of perceived usefulness and customer satisfaction from the two drivers for developing customer product loyalty. Empirical analysis shows that both affective and cognitive perspectives, i.e., involvement and interactivity, are important drivers to motivate customer product loyalty. The findings can help practitioners design more effective approaches for mobile advertising.
       
  • Digital business ecosystem: Literature review and a framework for future
           research
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Prince Kwame Senyo, Kecheng Liu, John Effah Digital innovation has radically changed how organisations collaborate and compete. Coupled with this change are new collaborative value creation networks such as digital business ecosystems (DBEs). DBE is a socio-technical network of individuals, organisations and technologies that collectively co-create value. Since the emergence of DBE over a decade ago, there have been limited attempts to critically review and synthesise the body of knowledge presented over the years. Thus, the purpose of this paper is to fill this gap in DBE research by: (1) developing a comprehensive framework that synthesises and provides an overall direction of DBE research; (2) pointing out gaps in DBE literature; and (3) providing future research directions. To address this purpose, we systematically analysed 101 research articles on DBE. The findings provide insightful revelations to address some limitations in the current DBE research. As such, this study makes important contributions and serves as a useful resource for future DBE studies and practice.
       
  • Estimation and maximization of user influence in social networks
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Sinjana Yerasani, Deepthi Appam, Monalisa Sarma, Manoj Kumar Tiwari Marketing companies explore several strategies with a fundamental goal of increasing sales; one such popular emerging strategy is Social Media Marketing. People are more likely to adopt a product recommended received from their acquaintances or based on product reviews. In this regard, a mixed influence model is used for studying the effect of comments on a product post. Also, a Greedy discounting technique targeting potential customers with an objective to maximize revenue as well as increase the social contagion. Here, we aim to increase the influence on people by offering the product for free to potential buyers who are capable of influencing more people and then the product is offered at increasing price, i.e., decreasing discount rates and increasing the revenue as well as the growth of the influence among customers’ acquaintances. Computational experiments are conducted on real-world networks representing different scenarios with varying complexities and tested the effectiveness of these algorithms.
       
  • Changes in roles, responsibilities and ownership in organizing master data
           management
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Riikka Vilminko-Heikkinen, Samuli Pekkola Master data management (MDM) is a data management practice, which attempts to increase data quality and data use across business processes throughout the organization. This paper observes how data ownership, responsibilities, and roles change during MDM development. The metaphor of imbrication was used as a theoretical lens to identify the factors that influenced the change, and to analyze the change as a result of the intertwined social and material factors. We derive ethnographical data from two MDM projects in a municipality over a time period of 32 months, and describe how data ownership and data governance roles and responsibilities were perceived, and how they evolved during the development. As a result, MDM data ownership is emphasized, and has distinct features in relation to roles and responsibilities. Ownership had on impact on how the development proceeded, and how the roles and responsibilities evolved.
       
  • A hybrid IT framework for identifying high-quality physicians using big
           data analytics
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Yan Ye, Yang Zhao, Jennifer Shang, Liyi Zhang Patients face difficulties identifying appropriate doctors owing to the sizeable quantity and uneven quality of information in online healthcare communities. In studying physician searches, researchers often focus on expertise similarity matches and sentiment analyses of reviews. However, the quality is often ignored. To address patients' information needs holistically, we propose a four-dimensional IT framework based on signaling theory. The model takes expertise knowledge, online reviews, profile descriptions (e.g., hospital reputation, number of patients, city) and service quality (e.g., response speed, interaction frequency, cost) as signals that distinguish high-quality physicians. It uses machine learning approaches to derive similarity matches and sentiment analysis. It also measures the relative importance of the signals by multi-criterion analysis and derives the physician rankings through the aggregated scores. Our study revealed that the proposed approach performs better compared with the other two recommend techniques. This research expands the boundary of signaling theory to healthcare management and enriches the literature on IT use and inter-organizational systems. The proposed IT model may improve patient care, alleviate the physician-patient relationship and reduce lawsuits against hospitals; it also has practical implications for healthcare management.
       
  • Lean information for lean communication: Analysis of concepts, tools,
           references, and terms
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Guilherme Alfredo Redeker, Gabriela Zucchetti Kessler, Liane Mahlmann Kipper Communication and information processes are vital in any company. The use of lean manufacturing concepts applied to the communication and information process aims to reduce waste and make the flows leaner and simpler. Lean information is a new strand of lean concepts and applications. The purpose of this study was to analyze quantitatively the publications concerning the subject, outlining an overview for the new research field of lean communication. Aiming for a deeper understanding, the concepts of lean information were applied in a real process. The quantitative analysis was carried out to find the main authors and works, as well as the main terms used in related works. We used the methods of citations works, co-citation references, and co-occurrence of words using the VOSviewer software. This software was primarily designed to analyze bibliometric networks in order to create, visualize, and assess maps based on network data generated from queries in journals. We found a lack of a methodology for the development and implementation of lean information concepts. We observed a gap which had not been addressed yet, that is, mapping communication flows and developing and implementing lean information. Moreover, there was no method for improvement, implementation, and control.
       
  • Measuring creolization in IT outsourcing: Instrument development and
           validation
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Shizhong Ai, Rong Du, Detmar W. Straub, Likoebe M. Maruping, Yumeng Miao This research describes the development and validation of an instrument of creolization. Creolization, which reflects how partnering firms manage a variety of cross-cultural processes, is particularly important for both clients and vendors to successfully engage in IT outsourcing contracts. Unfortunately, empirical research on this cross-cultural issue is currently under-developed because there are no adequate measures for the construct. We developed and validated a 13-item instrument via a sample of 317 knowledge workers working for 23 IT-enabled service-provisioning companies in Beijing, Shanghai, and Xi’an, China. Results from the present research reveal that the instrument has acceptable psychometric properties. The instrument should contribute to advancing quantitative research on creolization and for operationalizing the conceptualization of creolization in practice. Suggestions for adopting and improving the instrument are discussed and implications for practitioners are provided.
       
  • The role of business analytics capabilities in bolstering firms’
           agility and performance
    • Abstract: Publication date: August 2019Source: International Journal of Information Management, Volume 47Author(s): Amir Ashrafi, Ahad Zare Ravasan, Peter Trkman, Samira Afshari Many companies invest considerable resources in developing Business Analytics (BA) capabilities to improve their performance. BA can affect performance in many different ways. This paper analyses how BA capabilities affect firms’ agility through information quality and innovative capability. Furthermore, it studies the moderating role of environmental turbulence, both technological and in the market. The proposed model was tested using statistical data from 154 firms with two respondents (CEO and CIO) from each firm. The data were analysed using Partial Least Squares (PLS)/Structured Equation Modelling (SEM). Our results indicate that BA capabilities strongly impact a firm’s agility through an increase in information quality and innovative capability. We also discuss that both market and technological turbulence moderate the influence of firms' agility on firms' performance.
       
  • The role of positive and negative valence factors on the impact of bigness
           of data on big data analytics usage
    • Abstract: Publication date: Available online 28 December 2018Source: International Journal of Information ManagementAuthor(s): Maryam Ghasemaghaei The number of firms that intend to invest in big data analytics has declined and many firms that invested in the use of these tools could not successfully deploy their project to production. In this study, we leverage the valence theory perspective to investigate the role of positive and negative valence factors on the impact of bigness of data on big data analytics usage within firms. The research model is validated empirically from 140 IT managers and data analysts using survey data. The results confirm the impact of bigness of data on both negative valence (i.e., data security concern and task complexity), and positive valence (i.e., data accessibility and data diagnosticity) factors. In addition, findings show that data security concern is not a critical factor in using big data analytics. The results also show that, interestingly, at different levels of data security concern, task complexity, data accessibility, and data diagnosticity, the impact of bigness of data on big data analytics use will be varied. For practitioners, the findings provide important guidelines to increase the extent of using big data analytics by considering both positive and negative valence factors.
       
  • Big Data Analytics for Venture Capital Application:Towards
           Innovation Performance Improvement
    • Abstract: Publication date: Available online 20 December 2018Source: International Journal of Information ManagementAuthor(s): Wenqi Sun, Yuanjun Zhao, Lu Sun By using the panel date of Chinese enterprises, this paper analyzes the influence of venture capital on innovation performance. In this paper, the number of patent application and the patent quality(invention patent applications, number of effective patents, IPC number of international patent classification, and patent claims) are used to measure the innovation performance of enterprises, and the regression results show that the innovation performance is significantly promoted by the venture capital; for industries with higher dependence on external financing and high technology intensity and areas with better protection of property rights, venture capital promotes innovation performance more significantly. In this paper, it further distinguishes the characteristics of venture capital institutions, and finds that the promotion effect of non-state-owned venture capital on innovation performance is significantly greater than that of state-owned venture capital; the venture capital institutions with high reputation and high network capital play a more significant role in promoting innovation performance.
       
  • 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
       
  • 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.
       
  • 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.
       
  • 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.
       
  • 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.
       
  • 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.
       
  • 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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