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International Journal of Information Management
Journal Prestige (SJR): 1.373
Citation Impact (citeScore): 6
Number of Followers: 367  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0268-4012
Published by Elsevier Homepage  [3177 journals]
  • Leveraging Deep Learning and SNA approaches for Smart City Policing in the
           Developing World
    • Abstract: Publication date: Available online 30 November 2019Source: International Journal of Information ManagementAuthor(s): Saeed-Ul Hassan, Mudassir Shabbir, Sehrish Iqbal, Anwar Said, Faisal Kamiran, Raheel Nawaz, Umar SaifAbstractIs it possible to identify crime suspects by their mobile phone call records' Can the spatial-temporal movements of individuals linked to convicted criminals help to identify those who facilitate crime' Might we leverage the usage of mobile phones, such as incoming and outgoing call numbers, coordinates, call duration and frequency of calls, in a specific time window on either side of a crime to provide a focus for the location and period under investigation' Might the call data records of convicted criminals' social networks serve to distinguish criminals from non-criminals' To address these questions, we used heterogeneous call data records dataset by tapping into the power of social network analysis and the advancements in graph convolutional networks. In collaboration with the Punjab Police and Punjab Information Technology Board, these techniques were useful in identifying convicted individuals. The approaches employed are useful in identifying crime suspects and facilitators to support smart policing in the fight against the country's increasing crime rates. Last but not least, the applied methods are highly desirable to complement high-cost video-based smart city surveillance platforms in developing countries.
       
  • "Why pay premium in freemium services'" A study on perceived value,
           continued use and purchase intentions in free-to-play games
    • Abstract: Publication date: Available online 26 November 2019Source: International Journal of Information ManagementAuthor(s): Juho Hamari, Nicolai Hanner, Jonna KoivistoAbstractFreemium has become de facto business model for games and many other online services. We investigate how consumers' perceived value is associated with their intention to use freemium services and to purchase premium content. We employ data gathered through an online survey (N=869) among players of freemium/free-to-play games. Firstly, we find support for the "Demand Through Inconvenience" -hypothesis proposed in this study, indicating that the higher the enjoyment of the freemium service, the lower the intentions to purchase premium content but higher intention to use the service overall. Secondly, social value is found to positively affect freemium use and premium purchases. Thirdly, the quality of the freemium service does not seem to be associated with premium purchases although it has a positive association with freemium use. Fourthly, the economic value of freemium services is positively associated with freemium service use and via increased use also has a positive effect on premium purchases. The findings of the present study highlight the peculiarity of the freemium business model: increasing perceived value of the freemium service (i.e. enjoyment) may both add to and retract from future profitability via increased retention on one hand, reduced monetization on the other.
       
  • Deep strategic mediatization: Organizational leaders’ knowledge and
           usage of social bots in an era of disinformation
    • Abstract: Publication date: Available online 25 November 2019Source: International Journal of Information ManagementAuthor(s): M. Wiesenberg, R. TenchAbstractWe identified a lack of theoretical concepts and empirical knowledge about the perception and usage of social bots from the organizational and communication management perspective. Therefore, we first introduce social bots in the realm of communication and information management by using a profound literature review. Second, by building on mediatization theory and strategic communication, we introduce the concept of deep strategic mediatization. By surveying the attitudes towards and usage of social bots of leading European communication professionals (n = 2,247) from 49 European countries, we thirdly offer first indications how diverse European organizations in different European regions use social bots. Results indicate, that leading communication professionals in Central and Western Europe as well as Scandinavia perceive highly ethical challenges, while in Southern and Eastern Europe professionals are less skeptical regarding the usage of social bots. Only 11.5 percent (n = 257) declare their organization uses or are making plans to use social bots for strategic communication. They are used primarily for identifying and following social networks users. This refers specifically to the usage of digital traces for strategic communication purposes e.g., to identify topic area opinion leaders or social media influencers. However, this represents only a small minority of the sample – leading to the conclusion that only a small minority of organizations already practice deep strategic mediatization.
       
  • Improving high-tech enterprise innovation in big data environment: A
           combinative view of internal and external governance
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Runhui Lin, Zaiyang Xie, Yunhong Hao, Jie WangAbstractThe 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.
       
  • Financial crisis prediction model using ant colony optimization
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Uthayakumar J, Noura Metawa, K. Shankar, S.K. LakshmanaprabuAbstractFinancial 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.
       
  • Measuring extreme risk of sustainable financial system using GJR-GARCH
           model trading data-based
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Xiaomeng Ma, Ruixian Yang, Dong Zou, Rui LiuAbstractThis 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.
       
  • Intelligent decision-making of online shopping behavior based on internet
           of things
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Hanliang Fu, Gunasekaran Manogaran, Kuang Wu, Ming Cao, Song Jiang, Aimin YangAbstractThe development of big data and Internet of things (IoT) have brought big changes to e-commerce. Different kinds of information sources have improved the consumers’ online shopping performance and make it possible to realize the business intelligence. Grip force and eye-tracking sensors are applied to consumers' online reviews search behavior by relating them to the research approaches in IoT. To begin with, public cognition of human contact degrees of recycled water reuses with grip force test was measured. According to the human contact degrees, 9 recycled water reuses presented by the experiment are classified into 4 categories. Based on the conclusion drawn from grip force test, purified recycled water and fresh vegetable irrigated with recycled water are regarded as the drinking for high-level human contact degree and the irrigation of food crops for low-level human contact degree respectively. Several pictures are designed for eye-tracking test by simulating an on-line shopping web page on Taobao (the most popular online shopping platform in China). By comparing the fixation time participants spent on the areas of interest (AOIs), we justify that consumers' online reviews search behavior is substantially affected by human contact degrees of recycled products. It was found that consumers rely on safety perception reviews when buying high contact goods.
       
  • Does government information release really matter in regulating
           contagion-evolution of negative emotion during public emergencies'
           From the perspective of cognitive big data analytics
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Wei Zhang, Meng Wang, Yan-chun ZhuAbstractThe breeding and spreading of negative emotion in public emergencies posed severe challenges to social governance. The traditional government information release strategies ignored the negative emotion evolution mechanism. Focusing on the information release policies from the perspectives of the government during public emergency events, by using cognitive big data analytics, our research applies deep learning method into news framing framework construction process, and tries to explore the influencing mechanism of government information release strategy on contagion-evolution of negative emotion. In particular, this paper first uses Word2Vec, cosine word vector similarity calculation and SO-PMI algorithms to build a public emergencies-oriented emotional lexicon; then, it proposes a emotion computing method based on dependency parsing, designs an emotion binary tree and dependency-based emotion calculation rules; and at last, through an experiment, it shows that the emotional lexicon proposed in this paper has a wider coverage and higher accuracy than the existing ones, and it also performs a emotion evolution analysis on an actual public event based on the emotional lexicon, using the emotion computing method proposed. And the empirical results show that the algorithm is feasible and effective. The experimental results showed that this model could effectively conduct fine-grained emotion computing, improve the accuracy and computational efficiency of sentiment classification. The final empirical analysis found that due to such defects as slow speed, non transparent content, poor penitence and weak department coordination, the existing government information release strategies had a significant negative impact on the contagion-evolution of anxiety and disgust emotion, could not regulate negative emotions effectively. These research results will provide theoretical implications and technical supports for the social governance. And it could also help to establish negative emotion management mode, and construct a new pattern of the public opinion guidance.
       
  • Considering the influence of queue length on performance improvement for a
           new compact robotic automated parking system
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Guangmei Wu, Xianhao Xu, Xinyuan LuAbstractWith the development of the BI (Business intelligence) applications, robots and robot-based technology appear in various fields. Compact robotic automated parking system will facilitate the informatization and modernization of urban development and environmental protection. Compact robotic automated parking (CRAP) system is a new system with higher storage utilization and rapid response to store and handle cars. This system has double storage rings, instead of one storage ring in old compact automated parking (CAP) system for storing cars in each tier, and each tier is equipped with inner rotating ring and tier-captive automated guided vehicle for horizontal transport. The CRAP system has one elevator with vertical automated guided vehicle in the outer ring instead of the center part in the old CAP system for vertical transport. We first estimate the system performance using queuing network models. Second, we validate the analytical models through simulation and a real case. The simulation results show that we make an accurate estimation. Third, we optimize system configurations by minimizing the car retrieval time. Finally, given the same storage capacity, we compare the car retrieval time based on a real application and footprint area of CRAP system with CAP system. The results show that the car retrieval time can be reduced by at least 29.7% when the system capacity C is 400, and the space utilization can be improved by at least 32.0%.
       
  • Can the development of a patient’s condition be predicted through
           intelligent inquiry under the e-health business mode' Sequential
           feature map-based disease risk prediction upon features selected from
           cognitive diagnosis big data
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Xin Liu, yanju zhou, Wang ZongrunAbstractThe data-driven mode has promoted the researches of preventive medicine. In prediction of disease risks, physicians’ clinical cognitive diagnosis data can be used for early prevention of diseases and, therefore, to reduce medical cost, to improve accessibility of medical services and to lower medical risk. However, researches involved no physicians’ cognition of patients’ conditions in intelligent inquiry under e-health business mode, offered no diagnosis big data, neglected the values of the fused text information generated by joint activities of online and offline medical data, and failed to thoroughly analyze the phenomenon of redundancy-complementarity dispersion caused by high-order information shortage from the online inquiry data-driven perspective. Besides, the risk prediction simply based on offline clinical cognitive diagnosis data undoubtedly reduces prediction precision. Importantly, relevant researches rarely considered temporal relationships of different medical events, did not conduct detailed analysis on practical problems of pattern explosion, did not offer a thought of intelligent portrayal map, and did not conduct relevant risk prediction based on the sub-maps obtained from the map. In consequence, the paper presents a disease risk prediction method with the model for redundancy-complementarity dispersion-based feature selection from physicians’ online cognitive diagnosis big data to realize features selection from the cognitive diagnosis big data of online intelligent inquiry; the obtained features were ranked intelligently for subsequent high-dimensional information shortage compensation; the compensated key feature information of the cognitive diagnosis big data was fused with offline electronic medical record (EMR) to form the virtual electronic medical record (VEMR). The formed VEMR was combined with the method of the sequential feature map for modelling, and a sequential feature map-based model for disease risk prediction was presented to obtain online users’ medical conditions. A neighborhood-based collaborative prediction model was presented for prediction of an online intelligent medical inquiry user’s possible diseases in the future and to intelligently rank the risk probabilities of the diseases. In the experiments, the online intelligent medical inquiry users’ VEMRs were used as the foundation of the simulation experiments to predict disease risks in chronic obstructive pulmonary disease (OCPD) population and rheumatic heart disease (RHD) population. The experiments demonstrated that the presented method showed relatively good metric performances in the VEMR and improved disease risk prediction.
       
  • Big data analytics for financial Market volatility forecast based on
           support vector machine
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Rongjun Yang, Lin Yu, Yuanjun Zhao, Hongxin Yu, Guiping Xu, Yiting Wu, Zhengkai LiuAbstractHigh-frequency data provides a lot of materials and broad research prospects for in-depth research and understanding on financial market behavior, but the problems solved in the research of high-frequency data are far less than the problems faced and encountered, and the research value of high-frequency data will be greatly reduced without solving these problems. Volatility is an important measurement index of market risk, and the research and forecasting on the volatility of high-frequency data is of great significance to investors, government regulators and capital markets. To this end, by modelling the jump volatility of high-frequency data, the short-term volatility of high-frequency data are predicted.
       
  • Text mining of industry 4.0 job advertisements
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Mirjana Pejic-Bach, Tine Bertoncel, Maja Meško, Živko KrstićAbstractSince changes in job characteristics in areas such as Industry 4.0 are rapid, fast tool for analysis of job advertisements is needed. Current knowledge about competencies required in Industry 4.0 is scarce. The goal of this paper is to develop a profile of Industry 4.0 job advertisements, using text mining on publicly available job advertisements, which are often used as a channel for collecting relevant information about the required knowledge and skills in rapid-changing industries. We searched website, which publishes job advertisements, related to Industry 4.0, and performed text mining analysis on the data collected from those job advertisements. Analysis of the job advertisements revealed that most of them were for full time entry; associate and mid-senior level management positions and mainly came from the United States and Germany. Text mining analysis resulted in two groups of job profiles. The first group of job profiles was focused solely on the knowledge related to Industry 4.0: cyberphysical systems and the Internet of things for robotized production; and smart production design and production control. The second group of job profiles was focused on more general knowledge areas, which are adapted to Industry 4.0: supply change management, customer satisfaction, and enterprise software. Topic mining was conducted on the extracted phrases generating various multidisciplinary job profiles. Higher educational institutions, human resources professionals, as well as experts that are already employed or aspire to be employed in Industry 4.0 organizations, would benefit from the results of our analysis.
       
  • Business intelligence governance framework in a university: Universidad de
           la costa case study
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Harold Arturo Combita Niño, Johana Patricia Cómbita Niño, Roberto Morales OrtegaAbstractUniversities 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.
       
  • The role of positive and negative valence factors on the impact of bigness
           of data on big data analytics usage
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Maryam GhasemaghaeiAbstractThe 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: February 2020Source: International Journal of Information Management, Volume 50Author(s): Wenqi Sun, Yuanjun Zhao, Lu SunAbstractBy 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.
       
  • Data mining of customer choice behavior in internet of things within
           relationship network
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Yuwei Yan, Chuanchao Huang, Qian Wang, Bin HuAbstractInternet 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.
       
  • Advancing social media derived information messaging and management: A
           multi-mode development perspective
    • Abstract: Publication date: Available online 22 November 2019Source: International Journal of Information ManagementAuthor(s): Nigel Martin, John Rice, Damien ArthurWith global reach of over 2 billion active users, the evolution of Social Media (SM) systems has provided organizations with sophisticated tools and technologies for delivering business objectives. Importantly, while marketers and public relations experts have taken leading positions in promotion and advancement of SM, project managers are often tasked with delivering SM systems. In this study, a sample of 127 project managers were asked to evaluate and recommend modes of SM development for six diverse firms using a four-part taxonomy. The results show that firms of varying size can employ narrowly focused and low cost SM development modes to meet their business objectives, with well-resourced firms able to use experimental modes to deliver widespread and higher cost ‘listen and learn’ SM systems. Alternatively, in addition to achieving groundswell promotions and broader business marketing and sales influencing objectives, firms that engage in large scale SM developments can document and implement SM best practices and apply multi-organizational collaborations required for information exchange, customer feedback and experience sharing. These managerial perspectives expose the intrinsic connections between SM systems and information messaging and management within firms. The article builds further into cumulative studies directed at SM systems construction, deployment, and firm capability affordances.Graphical abstractGraphical abstract for this article
       
  • Towards sustainable collaborative networks for smart cities co-governance
    • Abstract: Publication date: Available online 22 November 2019Source: International Journal of Information ManagementAuthor(s): Nesrine Ben Yahia, Wissem Eljaoued, Narjès Bellamine Ben Saoud, Ricardo Colomo-PalaciosAbstractThis paper addresses the concept of collaborative governance in the context of smart cities, with a focus on supporting and recommending performing organizational structures for sustainable collaborative networks (SCN). It highlights that governing a smart city is about promoting an effective environment of collaboration in the government and implying adaptive policy-making to construct new, internal and external human collaborations. Considering the smart governance as a collaborative network of government agencies and external stakeholders including citizens and a socio-technical system, we conduct in this paper an ethnographic mixed method by combining a qualitative method that studies actors’ collaboration and engagement in co-governance with a quantitative method that is based on graph theory to provide numerical analyses of organizational structures. While the qualitative method aims to discover organizational “smart factors” that affect the performance of SCN structures or configurations, the quantitative method aims to find “smart indicators” and metrics to evaluate these organizational factors. The result of this mixed method is an analytical recommender framework of the relevant SCN organizational structures in terms of robustness, flexibility and efficiency.
       
  • Predicting semantic preferences in a socio-semantic system with
           collaborative filtering: A case study
    • Abstract: Publication date: Available online 22 November 2019Source: International Journal of Information ManagementAuthor(s): Jean-François Chartier, Pierre Mongeau, Johanne Saint-CharlesAbstractThis paper proposes collaborative filtering as a means to predict semantic preferences by combining information on social ties with information on links between actors and semantics. First, the authors present an overview of the most relevant collaborative filtering approaches, showing how they work and how they differ. They then compare three different collaborative filtering algorithms using articles published by New York Times journalists from 2003 to 2005 to predict preferences, where preferences refer to journalists’ inclination to use certain words in their writing. Results show that while preference profile similarities in an actor’s neighbourhood are a good predictor of her semantic preferences, information on her social network adds little to prediction accuracy.
       
  • Do teams need both hands' An analysis of team process ambidexterity
           and the enabling role of information technology
    • Abstract: Publication date: Available online 18 November 2019Source: International Journal of Information ManagementAuthor(s): Chanhee Kwak, Junyeong Lee, Heeseok LeeAbstractAs a core organizational resource, business processes are vital for organizational teams. To deal with today’s volatile business environment, organizations need to be ambidextrous in terms of process capabilities. However, little is known about how process ambidexterity, process standardization, and process agility, are enabled by information technology (IT) and related to team-level activities. To fill this gap in the literature, we conducted a field study based on 160 teams of 1081 individuals from seven companies in South Korea. Our results show that IT enables both process standardization and agility, and that a team’s process ambidexterity has a positive effect on inter-team coordination and team innovation, which in turn have a direct impact on team performance. Our findings highlight the importance of process ambidexterity by investigating the enabling role of IT and its outcomes in a team. Our results offer theoretical and practical implications from the perspective of team process ambidexterity.
       
  • Exploring the effect of dynamic seed activation in social networks
    • Abstract: Publication date: Available online 18 November 2019Source: International Journal of Information ManagementAuthor(s): Sinjana Yerasani, Suprabhat Tripathi, Monalisa Sarma, Manoj Kumar TiwariAbstractIn this paper, we address the problem of maximizing the influence in a social network by hiring a few users in the network to propagate the information. Considering limited budget and time, hired users (seeds) are activated dynamically at different time intervals over a time horizon. This motivates to avoid the same seed activation in consecutive time intervals that leads to deteriorating the seeds’ efficiency. The aim of this paper is to maximize the total gain obtained in the process of maximizing the influence in a social network. Total gain is obtained by earning of influencing the customers and then deducting the cost incurred for influencing the users. Therefore, an improvised memetic algorithm is developed to find the seeds that are to be activated at different time intervals to maximize the gain. Experimental results validate the effectiveness of the proposed algorithm, and it is found to perform better in identifying the potential seeds with minimum expenditure.
       
  • Extending unified theory of acceptance and use of technology with
           perceived monetary value for smartphone adoption at the bottom of the
           pyramid
    • Abstract: Publication date: Available online 16 November 2019Source: International Journal of Information ManagementAuthor(s): Kuldeep Baishya, Harsh Vardhan SamaliaAbstractThe affluent markets of developed countries have become very competitive. Therefore, companies are trying to explore market opportunities at the segment of low-income people termed as “Bottom of the Pyramid” (BOP). With the proliferation in popularity and reduction in the price of smartphones, there is a potential market opportunity for smartphone producing companies at the BOP segment. The companies need to identify the factors influencing smartphone adoption at the BOP in order to explore this market opportunity. The current study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) with “Perceived Monetary Value” to investigate the antecedents of smartphone adoption at the BOP. Empirical analysis has shown that “Performance Expectancy” (PE), “Effort Expectancy” (EE), “Social Influence” (SI), and “Perceived Monetary Value” (PMV) predict the “Behavioral Intention” (BI), and BI and “Facilitating Conditions” (FC) predict the “Use Behavior” (UB). Findings from this study can be used by the managers of the companies targeting the BOP segment in pricing, marketing, and product-specific decision-making process. The policymakers can also analyze the results of this study for successful implementation and delivery of Information and Communication Technology (ICT) based services for the BOP segment.
       
  • Operationalisation of soft skill attributes and determining the existing
           gap in novice ICT professionals
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Richa Singh Dubey, Vijayshri TiwariAbstractThe manuscript presents an analysis of the perceived importance and existing gap of soft skills for new entrants in the information technology sector. It also examines the effect of various backgrounds on the perception of soft skills. Empirical examinations are carried out through independent t-test, and MANOVA indicates substantial dissimilarity in the perception of students and practitioners. While examining the effect of the background, practitioners responded to a similarity in the perceived importance of soft skills, irrespective of gender, management level and experience. Though students showed similarity in the preparedness of soft skills regardless of the gender or medium of education up to class 12th but demonstrated substantial differences due to institute during graduation. Hence findings indicate the importance of academic institutions for the development of soft skills. The outcome also depicts that academia should take necessary action to amend the method of imparting skills for enhancing employability in students. Further, the study also sublimes essential soft skill attributes.
       
  • Integrating the theory of planned behavior and behavioral attitudes to
           explore texting among young drivers in the US
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Maranda McBride, Lemuria Carter, Brandis PhillipsAbstractThe proliferation of cell phones and the growing culture of constant connectivity has introduced a plethora of new challenges for mobile citizens. One of the major challenges transportation professionals desire to address involves the use of cell phones to text while driving, especially for less experienced drivers. In this study, the Theory of Planned Behavior (TPB) in conjunction with psycho-social factors is utilized to explore the intention to text while driving among young drivers. The results of a survey administered to 524 drivers suggest that the TPB constructs (attitude, subjective norm, and perceived behavioral control) along with the perceived disadvantages of abstention and age of the driver explain a significant amount of variance in the intention to send text messages while driving (adjusted R2 = 0.71).
       
  • The efficiency of mobile media richness across different stages of online
           consumer behavior
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Chi-Hsing Tseng, Li-Fun WeiAbstractThe popularity of mobile devices has ushered in the prosperity of mobile commerce, yet research on mobile advertising and mobile marketing remains scant. Marketing ads possessing higher media richness generally have a positive effect on consumer decision-making, because rich media conveys more information, but mobile ads with richer media imply higher costs for both the marketer and the audience. The limitations of mobile devices have further highlighted the difficulty of mobile advertising and the issue of advertising costs. Selecting which media to deliver the appropriate information is the latest research trend, but few studies have applied the media richness theory to explain mobile ads’ effect on consumer behavior. This research thus explores the impact of media richness on consumer behavior at different AISAS (attention, interest, search, action, and share) stages, adopting experimental research, convenient sampling, and online questionnaire to collect data. From a total of 424 valid questionnaires, we find that media richness has a greater influence on the three early stages of AIS while having a lower impact on the later stages of AS. This research thus suggests that firms employing mobile ads should choose high richness media for those potential customers who are at the early stage of consumer behavior (AIS). For those who at the later stage (AS), it is good enough for marketers to utilize medium richness mobile ads. Following this suggestion, marketers can place mobile ads more precisely, thus improving the likelihood of a reduction in advertising costs for both the marketer and audience. As mobile ads with high media richness are more effective for high perceived risk products, firms need to use high richness media when they are promoting high perceived risk products even when potential consumers are at the later stage of AS. This research contributes to marketers dedicated to using a mobile advertisement strategy and helps refine both online consumer behavior and the media richness theory when including the context of mobile commerce.
       
  • A meta-analysis of antecedents and consequences of trust in mobile
           commerce
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Subhro Sarkar, Sumedha Chauhan, Arpita KhareAbstractAwareness of antecedents and consequences of trust in m-commerce can enable m-commerce service providers to design suitable marketing strategies. Present study conducted a meta-analysis of 118 related empirical studies. The results indicate that antecedents namely perceived usefulness, perceived ease of use, system quality, information quality, service quality, user interface, perceived risk, perceived security, structural assurance, ubiquity, and disposition to trust, while consequences namely attitude, user satisfaction, behavioral intention, and loyalty have significant relationship with trust in m-commerce. Further, all the relationships were found to be moderated by culture except perceived ease of use, disposition to trust, and attitude.
       
  • Spillover of workplace IT satisfaction onto job satisfaction: The roles of
           job fit and professional fit
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Wei Wang, Yi Wang, Yi Zhang, Jing MaAbstractWith information technology (IT) increasingly penetrating in workplaces, employee satisfaction with workplace IT becomes an integral part of work and significantly influences work-related outcomes. Scant attention, however, has been paid to whether and how employees’ IT satisfaction plays a role in generating job-related attitudinal changes among employees. Drawing upon satisfaction spillover theory, we developed and empirically tested a model to examine the relationship between individual satisfaction with workplace IT and job satisfaction. Specifically, we introduced two elements of user-task-technology fit—namely, job fit and professional fit—to examine the transition in employees’ satisfaction from the technological domain to overall satisfaction with work. We found that job fit not only mediated but also strengthened the effect of workplace IT satisfaction on job satisfaction, whereas professional fit did not play a moderating role in the relationship between workplace IT satisfaction and job satisfaction. The findings suggest that practitioners should emphasize workplace IT as a crucial ingredient of the work context and improve employee experiences with using IT. More importantly, the fit of IT with employees’ job and professional requirements is critical for this transition in satisfaction.
       
  • Conceptualization of omnichannel customer experience and its impact on
           shopping intention: A mixed-method approach
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Si Shi, Yi Wang, Xuanzhu Chen, Qian ZhangAbstractAdvances in information and communication technologies (ICT) have led to the revolution in retail industry through integrating multiple available channels to enhance seamless customer experience, promoting a shift from multichannel to omnichannel business. This phenomenon has gained increasing attention in both academia and industry due to growing challenges to serve customers effectively. This study adopted a mixed-method approach to firstly conceptualize omnichannel customer experience and develop a survey instrument. Then, this study draws on the innovation diffusion theory to develop a nomological model that posits perceived compatibility and perceived risk as key linking mechanisms between omnichannel experience and omnichannel shopping intention. To achieve our research objective, we collected two data sets including pretest (n = 141) and model test (n = 377). We found that the constructs that represented our omnichannel experience conceptualization were good predictors of perceived compatibility and perceived risk, which further impact customers’ shopping intention. This study provides a rich conceptualization of an instrument for omnichannel customer experience that can serve as a springboard for future research to investigate the antecedents and impacts of omnichannel experience and can be used as a guide to design effective omnichannel retailing strategy.
       
  • Transition from web to mobile payment services: The triple effects of
           status quo inertia
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Xiang Gong, Kem Z.K. Zhang, Chongyang Chen, Christy M.K. Cheung, Matthew K.O. LeeAbstractDrawing from status quo bias theory and coping theory, this study examines how the inertial use of incumbent web payment (WP) services influences users’ intention to use new mobile payment (MP) services. By conducting an online survey (n = 491), this study reveals that inertia demonstrates triple effects on intention to use MP services: direct, bias, and moderating. The direct effect suggests that inertia directly decreases intention to use MP. The bias effect means that inertia leads to biased assessment of perceived value and perceived threat, thereby decreasing intention to use MP. The moderating effect denotes that inertia strengths the relationship between perceived controllability and intention to use MP. We expect that these findings can provide noteworthy insights for the intervention and prevention of inertia in the web-mobile payment transition context.
       
  • A framework for analysing blockchain technology adoption: Integrating
           institutional, market and technical factors
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Marijn Janssen, Vishanth Weerakkody, Elvira Ismagilova, Uthayasankar Sivarajah, Zahir IraniAbstractThe adoption of blockchain technologies require the consideration of a broad range of factors, over and above the predominantly technology focus of most current work. Whilst scholarly literature on blockchain technology is only beginning to emerge, majority are focused on the technicalities of the technology and tend to ignore the organizational complexities of adopting the technology. Drawing from a focused review of literature, this paper proposed a conceptual framework for adoption of blockchain technology capturing the complex relationships between institutional, market and technical factors. The framework highlights that varying outcomes are possible, and the change process is focal as this shapes the form blockchain applications take. Factors presented in the framework (institutional, market and technical) interact and mutually influence each other. The proposed framework can be used by organisations as a reference point for adopting blockchain applications and by scholars to expand, refine and evaluate research into blockchain technology.
       
  • ERDMAS: An exemplar-driven institutional research data management and
           analysis strategy
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Matthew I. BellgardAbstractDevising fit-for-purpose research data management strategies within a university is challenging. This is because the five ‘Vs’ for generated research data; its Volume, Variety, Velocity, Veracity and its Value must be constantly considered. Invariably, a combination of data V’s for any given research endeavour determine how best to manage it appropriately addressing archiving, compliance, security, privacy, sharing, reuse and so forth. As such, institutions are faced with defining, shaping and refining strategies and practicies to ensure there are consistent and adequate research data management polices and guidelines in place for their researchers. FAIR data principles are very important for embracing open data opportunities, but more broadly, research data management practices need to be established in a comprehensive way. Additionally, new ICT options have rapidly become available where institutions can make considered choices on whether to continue to use ‘on prem’, private Cloud or public Cloud infrastructure. If a hybrid approach is adopted, then the potential impact on existing institutional research data management strategies must be continually assessed and revised accordingly. Getting the balance right between developing a relevant institutional policy on the one hand yet also dynamically catering for the eclectic research data management and analytics needs of researchers and their evolving interactions with external collaborators on the other, must be continually navigated. In this manuscript, an exemplar-driven research data management and analytics conceptual framework is introduced. A key feature of this framework is that it is couched in two dimensions. On one axis is the ‘standard’ linear approach of developing the research data management policy, guidelines, procedures, audit and risk assessment and an options matrix. Importantly, a second axis comprising a researcher-driven focus is introduced where exemplar research activities are used to define ‘classes’ of research data management and analysis requirements. This exemplar-driven dimension enables an ongoing system-wide comparative review to occur in parallel that can continually inform policy and guidelines refinement.
       
  • Special issue on cognitive big data analytics for business intelligence
           applications: Towards performance improvement
    • Abstract: Publication date: Available online 21 September 2019Source: International Journal of Information ManagementAuthor(s): Mohamed Elhoseny, M. Kabir Hassan, Amit Kumar Singh
       
  • An empirical study on business analytics affordances enhancing the
           management of cloud computing data security
    • Abstract: Publication date: Available online 17 September 2019Source: International Journal of Information ManagementAuthor(s): Zhiying Wang, Nianxin Wang, Xiang Su, Shilun GeAbstractThe mechanism of business analytics affordances enhancing the management of cloud computing data security is a key antecedent in improving cloud computing security. Based on information value chain theory and IT affordances theory, a research model is built to investigate the underlying mechanism of business analytics affordances enhancing the management of cloud computing data security. The model includes business analytics affordances, decision-making affordances of cloud computing data security, decision-making rationality of cloud computing data security, and the management of cloud computing data security. Simultaneously, the model considers the role of data-driven culture and IT business process integration. It is empirically tested using data collected from 316 enterprises by Partial Least Squares-based structural equation model. Without data-driven culture and IT business process integration, the results suggest that there is a process from business analytics affordances to decision-making affordances of cloud computing data security, decision-making rationality of cloud computing data security, and to the management of cloud computing data security. Moreover, Data-driven culture and IT business process integration have a positive mediation effect on the relationship between business analytics affordances and decision-making affordances of cloud computing data security. The conclusions in this study provide useful references for the enterprise to strengthen the management of cloud computing data security using business analytics.
       
  • Application of soft computing and machine learning in the big data
           analytics for smart cities and factories
    • Abstract: Publication date: Available online 16 September 2019Source: International Journal of Information ManagementAuthor(s): Christian Esposito, Florin Pop, Jun Huang
       
  • The relationships among community experience, community commitment, brand
           attitude, and purchase intention in social media
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Xiao-Wu Wang, Yu-Mei Cao, Cheol ParkAbstractThe brand community built by social networking sites (SNSs) promotes efficiency in modern marketing. However, building consumer-brand relationships through an SNS brand community to improve marketing performance has always presented a challenge. Thus, this study aims to identify and test the main factors related to SNS brand communities that can predict purchase intention. The conceptual model includes community experience, community commitment, brand attitude, and purchase intention. The results of the structural equation modeling (SEM) using a sample of 278 Korean consumers reveals that in addition to information experience, other experiences (entertainment, homophily, and relationship-based) have a positive influence on community commitment. Relationship-based experience as constructed in this study has the largest impact on community commitment. SNS brand community commitment has a positive influence on brand attitude. However, SNS brand community commitment has no significant impact on purchase intention. Finally, the results show that SNS brand community commitment has a partial mediation effect on the relationship between SNS brand community experience and brand attitude. This study suggests that companies should strategically manage consumers’ SNS brand community experiences and commitment. Other theoretical implications and managerial implications are also discussed.
       
  • Is it a tool or a toy' How user conceptions of a system’s purpose
           affect their experience and use
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Dicle Berfin Köse, Benedikt Morschheuser, Juho HamariAbstractThe boundary between hedonic and utilitarian information systems has become increasingly blurred during recent years due to the rise of developments such as gamification. Therefore, users may perceive the purpose of the same system differently, ranging from pure utility to pure play. However, in literature that addresses why people adopt and use information systems, the relationship between the users conception of the purpose of the system, and their experience and use of it has not yet been investigated. Therefore, in this study we investigate the interaction effects between users’ utility-fun conceptions of the system and the perceived enjoyment and usefulness from its use, on their post-adoption intentions (continued use, discontinued use, and contribution). We employ survey data collected among users (N = 562) of a gamified crowdsourcing application that represents a system affording both utility and leisure use potential. The results show that the more fun-oriented users conceive the system to be, the more enjoyment affects continued and discontinued use intentions, and the less ease of use affects the continued use intention. Therefore, users’ conceptions of the system prove to be an influential aspect of system use and should particularly be considered when designing modern multi-purposed systems such as gamified information systems.
       
  • Digital platforms and the changing nature of physical work: Insights from
           ride-hailing
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Matti Mäntymäki, Abayomi Baiyere, A.K.M Najmul IslamAbstractThe rise of digital platforms has enabled new forms of work, but the nature of these new forms, particularly the role of the digital platform in shaping work relations, is not well understood. This study explores how the presence of the digital platform manifests itself in workers’ perceptions of their work in the context of ride-hailing. We draw on the literature on work relations and theorize how the dimensions of work relations manifest themselves in work done for a digital platform. We employ the Gioia method to analyze 39 interviews conducted with Uber and Lyft drivers, and we identify six key mechanisms of platform-enabled work, namely self-employment, time management, income, information control, pricing, and rating. Our results illustrate that from workers’ perspective, flexibility in work relationships is a key positive element of platform-enabled work. The stark power disparity between workers and the platform is, in turn, a major source of discontent among workers. As a result, we put forward two key dimensions of work relations in the context of platform-enabled work: digital temporality and algorithmic administrativity. The study furthers understanding of the implications from the platform economy and sharing economy on work relations.
       
  • Uncovering unobserved heterogeneity bias: Measuring mobile banking system
           success
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Luvai F. Motiwalla, Mousa Albashrawi, Hasan B. KartalAbstractMobile banking (MB) involving the use of mobile devices to access bank accounts for conducting financial transactions has proliferated in recent years but inconsistently among banking customers. This diversity of use increases the complexity of uncovering unobserved heterogeneity bias in the success of MB systems. This research, first, uses a study of objective measures to cluster 4478 MB users into three homogeneous segments based on the system utilization behaviors captured in the log data. The users were, then, surveyed using a field study of subjective measures based on the information systems (IS) success model. A priori sample segmentation used for facilitating the discovery of unobserved heterogeneity bias in the full sample. The analysis of the subset with 445 users who responded indicated that the path coefficient and explained variances (R2) of the IS model were higher in the segments compared to the full sample; and the influence of success factors on satisfaction and intention to use varied significantly among the segments. Our study, consisting of objective and subjective measures, has theoretical and practical implications for MB usage. It contributes to the IS success model by confirming the existence of unobserved bias in full sample and inconsistent effects of the quality factors on satisfaction and continued usage in the segmented samples. It also assists the banks in identifying MB features that are more appealing to the varying user groups, which could help them with customer retention.
       
  • Data governance: A conceptual framework, structured review, and research
           agenda
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Rene Abraham, Johannes Schneider, Jan vom BrockeData governance refers to the exercise of authority and control over the management of data. The purpose of data governance is to increase the value of data and minimize data-related cost and risk. Despite data governance gaining in importance in recent years, a holistic view on data governance, which could guide both practitioners and researchers, is missing. In this review paper, we aim to close this gap and develop a conceptual framework for data governance, synthesize the literature, and provide a research agenda. We base our work on a structured literature review including 145 research papers and practitioner publications published during 2001-2019. We identify the major building blocks of data governance and decompose them along six dimensions. The paper supports future research on data governance by identifying five research areas and displaying a total of 15 research questions. Furthermore, the conceptual framework provides an overview of antecedents, scoping parameters, and governance mechanisms to assist practitioners in approaching data governance in a structured manner.Graphical abstractGraphical abstract for this article
       
  • Business analytics adoption process: An innovation diffusion perspective
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Dalwoo Nam, Junyeong Lee, Heeseok LeeAbstractAlthough business analytics (BA) have been increasingly adopted into businesses, there is limited empirical research examining the drivers of each stage of BA adoption in organizations. Drawing upon technological-organizational-environmental framework and innovation diffusion process, we developed an integrative model to examine BA adoption processes and tested with 170 Korean firms. The analysis shows data-related technological characteristics derive all stages of BA adoption: initiation, adoption and assimilation. While organizational characteristics are associated with adoption and assimilation stage, only competition intensity in environmental characteristics is associated with initiation stage. Our findings help practitioners and researchers to understand what factors can enable companies to adopt BA in each stage.
       
  • Unveiling the interplay between blockchain and loyalty program
           participation: A qualitative approach based on Bubichain
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Lu Wang, Xin (Robert) Luo, Frank LeeAbstractKeeping motivated customers partaking in point exchange activities is a major challenge in extant loyalty program (LP) studies. In the literature, IT or its applications play a paramount role in enabling firms to offer superior services and consequently deepen the relationships with their customers. Although already applied to augment customer experience and increase participation in practice, how blockchain applications interact with the LP context is still largely unknown in IS research. The objective of this research is to explore how blockchain, as an IT artifact on the rise, influences value creation in a LP context. Drawing on self-determination theory (SDT), this paper considers both intrinsic and extrinsic motivations in a LP context guided by SDT regulation: meeting the needs of Economy, Autonomy, Competence and Relatedness, and explores the effects of blockchain application on customers’ motivations, which influence value perception and participative behaviors. By using an exploratory case study of BubiChain in China, we collected data through semi-structured interviews and extracted from the raw data of BubiChain-based loyalty point exchange platform, including real-time, multi-brands, peer-to-peer, and secure, traceable and fraud-proof exchange. We found that these features of blockchain applications not only improve customers’ economic perceived value by meeting their extrinsic motivation but also enhance their social interaction and psychological self-fulfillment value perception by satisfying their intrinsic motivations, thus increasing customers’ experience and participative behaviors. We also synthesized the results and theorized the findings into 4 formal testable propositions, which would offer testable hypotheses for future empirical studies. This paper reveals an innovative breakthrough on SDT theory and LP research, and is an early attempt to analyze how the blockchain is applied to LPs. We endeavor to establish a theoretical overview of how the key features of blockchain-driven point exchange platform influence customers’ motivations, which affect value perception and consequently induce participative behaviors in a loyalty point context.
       
  • Insight into hackers’ reaction toward information security breach
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Siew H. Chan, Suparak JanjarasjitAbstractThis study provides insight into hackers’ reaction toward an information security breach perpetuated either with an ill or good intention. To our knowledge, limited research is available for promoting understanding of whether intent induces different perceived moral affect (i.e., a perpetrator should have feelings of regret, sorrow, guilt, and shame) which explains the effect of perceived intensity of emotional distress on responsibility judgment. Further, research is sparse on enhancing understanding of whether the nature of a perpetrator’s intent affects the moderating role of consideration of the consequences in the relationship between perceived moral affect and responsibility judgment. Increased understanding of the relationships among perceived moral affect, perceived intensity of emotional distress, consideration of the consequences, and responsibility judgment of an information security breach from the hackers’ perspective may shed light on their continued engagement in the act despite society’s disapproval. Analyzes of the responses of 166 hackers recruited at two major hacker conferences reveal that perceived moral affect mediates the effect of perceived intensity of emotional distress on responsibility judgment only in an ill intention breach, and consideration of the consequences strengthens the relationship between perceived moral affect and responsibility judgment only in a good intention breach.
       
  • Recipes for success: Conditions for knowledge transfer across open
           innovation ecosystems
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Emily Bacon, Michael D. Williams, Gareth H. DaviesAbstractOpen innovation ecosystems involve the transfer of knowledge between multiple stakeholders to contribute toward product and service innovation, and to an extent, have superseded network-level approaches to co-creation. Effective management of the knowledge and information transferred between ecosystem partners is crucial for the process of open innovation. However, to date, limited research has focused on ascertaining the conditions required for knowledge transfer success, particularly where the context involves collaboration between diverse organizational actors. Correspondingly, this study extends existing knowledge by presenting an exploration of conditions for knowledge transfer success between ecosystem partners. Semi-structured interviews were conducted with thirty key stakeholders in order to acquire their perceptions of the presence of specific conditions within their ecosystem partnerships. Empirical data were analyzed using a fuzzy-set Qualitative Comparative Analysis approach, resulting in the production of success recipes from multinational, small and medium-sized enterprise, and academic institution perspectives. Results indicate that combinations of knowledge, relationship, and organizational characteristics contribute to knowledge transfer success. However, these combinations are found to be dependent on the type of ecosystem partnership involved. Theoretical and practical implications of the study are presented, along with acknowledged limitations and suggestions for further work.
       
  • The role of digital influencers in brand recommendation: Examining their
           impact on engagement, expected value and purchase intention
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): David Jiménez-Castillo, Raquel Sánchez-FernándezAbstractDespite the growing interest in digital influencers as a brand communication tool in recent years, much remains to be explored to understand how they can build a bond with their followers that shapes their perceptions and behaviors towards the endorsed brands. This study aims to determine how effective digital influencers are in recommending brands via electronic word-of-mouth by examining whether the potential influence they have on their followers may affect brand engagement in self-concept, brand expected value and intention to purchase recommended brands. The results from a sample of 280 followers show that the perceived influential power of digital influencers not only helps to generate engagement but also increases expected value and behavioral intention regarding the recommended brands. Moreover, brand engagement in self-concept raises brand expected value and both variables also affect the intention to purchase recommended brands. The study contributes to a deeper understanding of the persuasive power of digital influencers, which is still limited. It can be also useful for companies when developing their own social media communication strategy.
       
  • Mobile apps and employee behavior: An empirical investigation of the
           implementation of a fleet-management app
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Michal Levi-Bliech, Polina Kurtser, Nava Pliskin, Lior FinkAbstractWhereas implementing a mobile application (app) in support of organizational processes is quite common in contemporary organizations, only few empirical studies have investigated the impact of app implementation in an organizational context. This study explores the association between the driving behavior of employed drivers and pre-driving app use of a fleet-management app. Users can get from the app not only real-time notifications while driving but can also take advantage of a unique app capability, that more traditional driving technologies do not provide, and receive feedback about their driving before their next drive. We hypothesize that pre-driving app use is associated with reduced risky driving behavior, and that this association is mitigated by real-time notifications and enhanced by experience with the app. The supportive results of the study confirm the organizational impact of implementing a fleet-management app via better driving behavior of employees who engage in pre-driving app use.
       
  • The effects of e-business processes in supply chain operations: Process
           component and value creation mechanisms
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Zhen Zhu, Jing Zhao, Ashley A. BushAbstractUsing a process component lens, this paper decomposes an e-business process into technical, relational, and business components. We then draw on resource orchestration theory to identify two managerial actions, resources structuring and capabilities leveraging in using e-business process components, to explain how these three components work together to improve competitive performance in supply chain operations. Two interesting insights emerge from our empirical research corresponds to value creation mechanisms. First, we identify the critical three portfolio effects to promote platform architecture flexibility and partner engagement to develop e-business operations capabilities (EBOCs) in three major e-business processes. Second, we reveal the transformation effect of EBOCs in different e-business processes in obtaining competitive performance. The notion of portfolio and transformation mechanisms of e-business process components offers theoretical and practical implications for developing successful digital supply chain platform.
       
  • Autonomic machine learning platform
    • Abstract: Publication date: Available online 11 July 2019Source: International Journal of Information ManagementAuthor(s): Keon Myung Lee, Jaesoo Yoo, Sang-Wook Kim, Jee-Hyong Lee, Jiman HongAbstractAcquiring information properly through machine learning requires familiarity with the available algorithms and understanding how they work and how to address the given problem in the best possible way. However, even for machine-learning experts in specific industrial fields, in order to predict and acquire information properly in different industrial fields, it is necessary to attempt several instances of trial and error to succeed with the application of machine learning. For non-experts, it is much more difficult to make accurate predictions through machine learning.In this paper, we propose an autonomic machine learning platform which provides the decision factors to be made during the developing of machine learning applications. In the proposed autonomic machine learning platform, machine learning processes are automated based on the specification of autonomic levels. This autonomic machine learning platform can be used to derive a high-quality learning result by minimizing experts’ interventions and reducing the number of design selections that require expert knowledge and intuition. We also demonstrate that the proposed autonomic machine learning platform is suitable for smart cities which typically require considerable amounts of security sensitive information.
       
  • A systems approach for modeling health information complexity
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Caitlin Champion, Craig Kuziemsky, Ewan Affleck, Gonzalo G. AlvarezAbstractInformation complexity issues such as poor data integration and quality and timely access to information can impair the implementation of information artifacts. Clinical practice guidelines (CPGs) are an information artifact used to guide a patient’s care delivery over time. Despite evidence on the effectiveness of CPGs, they remain underutilized in certain contexts of medicine. One such example is colorectal cancer screening where disparities in screening rates and incidences of colorectal cancer are particularly prevalent between rural and urban populations. To address that issue, we need to better understand the information complexity factors that impact CPG implementation. This paper addresses the above shortcoming and uses a case study of colorectal cancer screening in remote and rural Northern Canada to develop a systems approach for modeling health information complexity. We describe a set of health information system components and interrelationships and a method for system mapping using the system components and interrelationships. We then provide exploratory system models from our case study and use them to characterize health information complexity according to interaction complexity and information behavior complexity. Our results highlight that information artifacts such as CPGs are not complex per se, but rather confounding factors is what causes information complexity. Our findings have implications for modeling information complexity and the design of policy and technological solutions to address health information complexity.
       
  • Mobile users’ information privacy concerns and the role of app
           permission requests
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Kenan DegirmenciAbstractRecent privacy-related incidents of mobile services have shown that app stores and providers face the challenge of mobile users’ information privacy concerns, which can prevent users from installing mobile apps or induce them to uninstall an app. In this paper, we investigate the role of app permission requests and compare the impact on privacy concerns with other antecedents of information privacy concerns, i.e., prior privacy experience, computer anxiety, and perceived control. To test these effects empirically, we conducted an online survey with 775 participants. Results of our structural equation modeling show that prior privacy experience, computer anxiety, and perceived control have significant effects on privacy concerns. However, concerns for app permission requests have approximately twice as much predictive value than the other factors put together to explain mobile users’ overall information privacy concerns. We expect that our findings can provide a theoretical contribution for future mobile privacy research as well as practical implications for app stores and providers.
       
  • Building resilience and managing post-disruption supply chain recovery:
           Lessons from the information and communication technology industry
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Hsi Yueh Chen, Ajay Das, Dmitry IvanovAbstractIn recent years, major local and global disruptions have had significant adverse effects on corporate performance, particularly for businesses with long, global supply chains. Managing disruption and its effects has therefore become a key focus for firms. While the process of disruption management has attracted considerable research attention, much of it has been directed at the pre-disruption stage. This study investigates the post-disruption stage, and its management. The unpredictability of disruption magnitude and nature suggests that the post-disruption management process may be as important, if not more so, than pre-determined pre-disruption strategies. An effective post-disruption management process would directly affect actual ability to recover from sudden and serious disruptions. This study analyzes six companies, variously positioned upstream and downstream in the supply chain of the information and communications technology (ICT) industry in Taiwan. Specific factors and strategies relating to the post-disruption management process were collected by conducting in-depth interviews with the managers and executives of the firms. The information was categorized into distinct disruption management process stages: discovery, recovery, and supply chain redesign. The study findings are interesting and at times, new and counter-intuitive, including the surprising positive effects of clustering in disruptions, and the role of back-up supplier and material verification in disruption recovery. The study emerges with an integrated framework that can be utilized to establish an effective post-disruption management process. The framework is used to develop research propositions for future research.
       
  • Reconceptualizing information quality as effective use in the context of
           business intelligence and analytics
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Russell Torres, Anna SidorovaAbstractDespite a significant body of knowledge related to BI&A success, questions remain regarding the mechanism through which BI&A contributes to organizational benefits. In this paper, we build on the representation theory of effective use in order to enrich the current understanding of BI&A success informed by the IS success model. The theoretical model proposed here casts an integrated construct, information-quality-as-effective-use, as the mediator between system quality, data quality, and BI&A personnel expertise and performance benefits. The results of the empirical testing support the propositions of the theoretical model. Implications for theory and practice are discussed.
       
  • Healthcare big data processing mechanisms: The role of cloud computing
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Lila Rajabion, Abdusalam Abdulla Shaltooki, Masoud Taghikhah, Amirhossein Ghasemi, Arshad BadfarAbstractRecently, patient safety and healthcare have gained high attention in professional and health policy-makers. This rapid growth causes generating a high amount of data, which is known as big data. Therefore, handling and processing of this data are attracted great attention. Cloud computing is one of the main choices for handling and processing of this type of data. But, as far as we know, the detailed review and deep discussion in this filed are very rare. Therefore, this paper reviews and discusses the recently introduced mechanisms in this field as well as providing a deep analysis of their applied mechanisms. Moreover, the drawbacks and benefits of the reviewed mechanisms have been discussed and the main challenges of these mechanisms are highlighted for developing more efficient healthcare big data processing techniques over cloud computing in the future.
       
  • Role of real-time information-sharing through SaaS: An industry 4.0
           perspective
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Arsalan Mujahid Ghouri, Venkatesh ManiAbstractMiddle-level managers’ role in business success is crucial, and the perception of middle-level managers regarding operations-related technologies is imperative. However, previous studies have not addressed middle-level managers’ perceptions of modern technologies and relative aspects such as the effects of real-time information sharing (RTIS) and software as a service (SaaS). This study analyzes middle-level managers’ perceptions regarding RTIS with customers through SaaS technology and its impact on purchase behaviors. The analysis is based on primary data collected from 207 middle-level managers from 151 small businesses operating in wholesale and retail, food and beverages, and accommodation sectors. We also develop a theoretical framework with the relational view (RV) and theory of information-sharing (ToIS). Our results from path modelling indicate that RTIS is the key determinant of customer purchase behavior (CPB). Further, the results illustrate that customer orientation mediates the correlation between RTIS and CPB. Consequently, our findings provide a deeper understanding of RTIS and CPB, rooted in RV and ToIS. We then discuss theoretical and practical implications and provide suggestions for future research.
       
  • A non-linear business process management maturity framework to apprehend
           future challenges
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Manon Froger, Frederick Bénaben, Sébastien Truptil, Nicolas Boissel-DallierAbstractIn a context where enterprises and organizations aim to optimise their behaviour, obtain certifications and labels, and benefit from the smart use of information systems and technology, two considerations drive this research: (1) the weak maturity level of worldwide Business Process Management (BPM), which exposes the need to reconcile academic theories with industrial contexts, and (2) the need for upcoming software functionalities that prioritize removing the barriers frequently encountered by industrialists when trying to implement the method. To reach such goals, this research work has developed a conceptual framework to represent the BPM implementation state. It is built along three axes: the BPM Cycle (Design, Enact, Maintain), the Field (Culture, Business, IT) and the Abstraction Level (Data, Jobs, Behaviour). An organization’s overall BPM maturity can thus be evaluated by positioning its capabilities along the framework’s axes. It is also suggested that the framework be used to track the implementation of new procedures in an organisation. The framework is presented and detailed before being applied to a complete case study.
       
  • The role of stakeholders in the effective use of e-government resources in
           public services
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Olusoyi Richard Ashaye, Zahir IraniWith the global evolution of information and communication technology (ICT), organisations need to keep up-to-date with the trends. Whilst most countries are able to respond to these technological changes by drawing on the resources available to them, organisations tend to find it more difficult to keep up. This paper thus attempts to analyse critically the influencing factors regarding e-government implementation and the roles of the key stakeholders in driving successful implementation within public sector organisations in developing countries. Based on the extant literature review and empirical studies, the researchers have developed a conceptual framework stemming from a unification of the concepts, factors, theories and models for e-government implementation. Qualitative analysis was adopted using a multiple case study strategy, and focusing on the three-tiers of government – Federal, Government Agency and Local levels. This conceptual framework has re-affirmed the external and internal influencing factors and the key stakeholder’ and their roles. The e-government stakeholders include the government (ministry/agency), technologically-advanced country, companies and users (employers/citizens).
      Authors further discussed that the stakeholders’ roles and tasks vary from ‘pre-implementation’ (initiation) to ‘during implementation’ (planning and implementation), and ‘post-implementation’ (monitoring and evaluation) phases. From the analysis and findings, authors have recommended that public organisations would need to strategise their relationships with stakeholders in order to achieve a collective interest for successful e-government implementation. This study contributes to the body of knowledge in information systems by broadening the theoretical foundations of e-government field especially within the stakeholders’ perspective.
       
  • Would you like to play' A comparison of a gamified survey with a
           traditional online survey method
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Tamilla Triantoro, Ram Gopal, Raquel Benbunan-Fich, Guido LangAbstractUsing the stimulus-organism-response (S-O-R) framework and signaling theory, we evaluated the signaling effect of gamification in online survey systems. Based on the Big Five personality assessment instrument, we developed an experimental study with two surveys – a traditional online survey with Likert scales, and a gamified survey powered by game mechanics. Then we evaluated the effect of both surveys on the users’ cognitive and affective reactions, as well as their preference toward the signaler. We also identified game elements that influence the individuals’ reactions when interacting with gamified surveys. The results suggest that gamification serves as a positive signal and increases affective reactions. These findings have theoretical and practical implications to improve the design of existing online surveys.
       
  • Enabling innovation in the face of uncertainty through IT ambidexterity: A
           fuzzy set qualitative comparative analysis of industrial service SMEs
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Ana Ortiz de Guinea, Louis RaymondAbstractTaking a configurational approach, this paper investigates the causal configurations of IT ambidexterity (i.e., IT capabilities for exploitation and exploration), dynamic capabilities (i.e., innovation and networking capabilities) and environmental uncertainty that are associated to service innovation performance in small and medium-sized enterprises (SMEs). Results from a fuzzy set qualitative comparative analysis (fsQCA) of 63 industrial service SMEs show that these firms attain high service innovation performance with three different configurations under conditions of high uncertainty. Two configurations highlight the importance of IT exploration capabilities (combined with the absence of innovation and networking capabilities in one configuration and with the absence of networking capabilities and IT capabilities for exploitation in another), whereas another configuration accentuates the importance of IT exploitation capabilities (combined with the presence of innovation and networking capabilities). Our study contributes to the literature in multiple ways. For instance, due to the equifinal properties of the configurational approach, our results suggest that SMEs can attain high innovation performance through both sequential and simultaneous IT ambidexterity, thus providing a starting point for reconciling competing views of IT ambidexterity. Other contributions to theory and practice and avenues for future research are also discussed.
       
  • Team wisdom in software development projects and its impact on project
           performance
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Ali E. AkgünAbstractWhile the concept of wisdom, which refers to how people make right use of their knowledge through their practical actions, judgments, and ethical decisions, in general attracts researcher interest in a variety of disciplines, such as philosophy, psychology and management studies, little is known about how wisdom is conceptualized and then operationalized in the software development project team context. Based on the frameworks for philosophical, group and organizational wisdom, this paper identifies software development project team wisdom as a process for how team members best use the stock and flow of their knowledge through collective judgment, virtue-ethics, emotions/feelings, and effective decision-making during their project-related efforts. Adapting the efforts and functional similarities of both group and organizational wisdom practices, this effort determines that wisdom-related mechanisms (e.g., team diversity, networking with other teams and people, and their past experiences), joint epistemic actions (e.g., team reasoning, intuition, and aesthetic capacity), and team virtue and prudence become the different faces of the software development team wisdom process. We then propose how these different faces interrelate and how they also relate to project process effectiveness, such as team learning and speed-to-users, both of which have been rarely addressed empirically in the context of software development project teamwork.By examining 210 in-house software development project teams in a field study and using structural equation modeling analysis, our results empirically show the following: (a) software development wisdom-related mechanisms positively relate to software development team prudence and virtue and their joint epistemic actions, (b) software development team prudence and virtue are positively associated with software development team joint epistemic actions, and further (d) software development team joint epistemic actions are positively associated with software development project process effectiveness. We conclude by discussing our findings as they relate to the wisdom framework of software development project teams and suggest the key managerial implications for different types of software development projects.
       
  • Big data analytics in health sector: Theoretical framework, techniques and
           prospects
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Panagiota Galetsi, Korina Katsaliaki, Sameer KumarAbstractClinicians, healthcare providers-suppliers, policy makers and patients are experiencing exciting opportunities in light of new information deriving from the analysis of big data sets, a capability that has emerged in the last decades. Due to the rapid increase of publications in the healthcare industry, we have conducted a structured review regarding healthcare big data analytics. With reference to the resource-based view theory we focus on how big data resources are utilised to create organization values/capabilities, and through content analysis of the selected publications we discuss: the classification of big data types related to healthcare, the associate analysis techniques, the created value for stakeholders, the platforms and tools for handling big health data and future aspects in the field. We present a number of pragmatic examples to show how the advances in healthcare were made possible. We believe that the findings of this review are stimulating and provide valuable information to practitioners, policy makers and researchers while presenting them with certain paths for future research.
       
  • The role of organisational climate in managing knowledge sharing among
           academics in higher education
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Osama F. Al-Kurdi, Ramzi El-Haddadeh, Tillal EldabiAbstractOrganizations have often implemented Knowledge Management programs to connect employees better and promote knowledge sharing (KS). In the context of Higher Education Institutions (HEIs), this is particularly valid as knowledge creation and dissemination direct their mission and vision. Academics are one of the pillars of HEIs, where knowledge is created and shared. Nonetheless, as HEIs strive to promote academics’ knowledge sharing culture, the actual behaviour of academics might remain inhibited by numerous issues, namely the organizational. Prior research has been focused primarily on individual, technological and scarce aspects of organizational elements. Therefore, this study assesses the role of organizational climate operationalized by organizational leadership and trust in academics’ KS in HEIs. Partial Least Square (PLS) method where variance-based Structural Equation Modelling (SEM) was applied in this study. Results from 257 surveyed academics indicate that organizational climate has an exceptionally strong influence on academics’ KS practices. Additionally, organizational leadership and trust had a positive relationship with academics’ KS behaviour. These findings indicate that it is necessary to consider organizational elements and their interactions when understanding and fostering academics’ knowledge sharing behaviour in HEIs context.
       
  • Determining factors in the adoption and recommendation of mobile wallet
           services in India: Analysis of the effect of innovativeness, stress to use
           and social influence
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Nidhi Singh, Neena Sinha, Francisco J. Liébana-CabanillasAbstractPotential for the use of mobile wallet is enormous and it is drawing attention as an alternative mode of payment worldwide. The present research aims to provide important insights into the TAM (Technology Acceptance Model) and UTAUT2 (Unified Theory of Acceptance and Use of Technology) models. This study develops a conceptual model to determine the most significant factors influencing user's intention, perceived satisfaction and recommendation to use mobile wallet. The research model included 206 responses from an online and manual survey in India. Our study tested the moderating effect of innovativeness, stress to use and social influence on user's perceived satisfaction and recommendation to use mobile wallet services. We found that ease of use, usefulness, perceived risk, attitude, to have significant effect on user's intention, which further influenced user's perceived satisfaction and recommendation to use mobile wallet services. We also determined the significant moderating effect of stress to use and social influence on user's perceived satisfaction and recommendation to mobile wallet services. This study provides an integrated framework for academicians to measure the moderating effect of psychological, social and risk factors on technology acceptance. It can also help practitioners by identifying important factors affecting user's decision, which further affects user's perceived satisfaction and recommendation to use mobile wallet services.
       
  • The role of temporal coordination for the fuzzy front-end of innovation in
           virtual teams
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Petros Chamakiotis, Achilleas Boukis, Niki Panteli, Thanos PapadopoulosAbstractIn this paper, we study the role of temporal coordination in managing the early stages of innovation (aka fuzzy front-end) in the context of virtual teams. Following a comparative case study approach, we detail the role of temporal coordination through the study of two contrasting virtual teams—one with a 24-h lifespan, and one with a five-month lifespan—from two Industry-Academia collaboration projects. Our approach was longitudinal capturing virtual team activities from start to end of each project, and involved multiple data collection methods, including observations and interviews. The findings reveal that the virtual team lifespan influences the type of temporal coordination that emerges. In virtual teams with short lifespans, tight coordination with frequent communication can help to reduce the uncertainty characterizing the fuzzy front-end. On the other hand, in virtual teams with longer lifespans, loose coordination allows dispersed members to work simultaneously on different, complementary aspects of the task at hand. These findings extend scholarly understanding around how innovation activities are coordinated in technology-mediated environments, such as virtual teams. Finally, we discuss theoretical and managerial implications.
       
  • Sharing and re-using open data: A case study of motivations in
           astrophysics
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Anneke Zuiderwijk, Helen SpiersOpen data sharing and re-use is currently more common in some academic disciplines than others. Although each discipline has unique challenges and characteristics which can influence data sharing and re-use behavior, it may be possible to gain transferable insight from disciplines where these practices are more common. Several studies of the motivations underlying data sharing and re-use have been conducted, however these studies often remain at a high level of abstraction rather than providing in-depth insight about discipline-specific challenges and opportunities. This study sought to provide in-depth insight about the complex interaction of factors influencing motivations for sharing and re-using open research data within a single discipline, namely astrophysics. We focused on this discipline due to its well-developed tradition of free and open access to research data. Eight factors were found to influence researchers’ motivations for sharing data openly, including the researcher’s background, personal drivers, experience, legislation, regulation and policy, data characteristics, performance expectancy, usability, and collaboration. We identified six factors that influence researchers’ motivations to re-use open research data, including the researcher’s background, facilitating conditions, expected performance, social and affiliation factors, effort and experience. Finally, we discuss how data sharing and re-use can be encouraged within the context of astrophysics research, and we discuss how these insights may be transferred to disciplines with low rates of data sharing and re-use.
       
  • Effect of penitence on social media trust and privacy concerns: The case
           of Facebook
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Emmanuel W. Ayaburi, Daniel N. TrekuAbstractAbuse of information entrusted to organizations can result in a variety of privacy violations and trust concerns for consumers. In the event of violations, a social media brand or organization renders an apology – a form of social account – to alleviate users’ concerns and maintain user membership and engagement with the platform. To explore the link between apology offered by a social media brand or organization and the users’ trust dynamics in the brand’s services, we study how organizational integrity can contribute to reducing individuals’ privacy concerns whiles increasing or repairing their trust. Drawing on organizational behavioral integrity literature, our proposed research model suggests that the persuasiveness of an apology following a data breach affects users’ trust or spillover trust through their perceptions of the degree of alignment between the words in the apology and the actions of the violating entity. Based on a survey of Facebook users, our findings show that persuasiveness of an apology has a significant impact on users’ perceptions of the alignment between the social media brand’s (i.e. Facebook) words and subsequent actions. These perceptions impact social media brand trust (i.e. users’ trust in Facebook and allied services such as Instagram). We also find that, post data breach incidence, while integrity of the social media organization partially mediates the relationship between persuasive apology and users’ trust, it fully mediates the relationship between the persuasive apology and the privacy concerns expressed by the users. However, users’ privacy concerns do not contribute much to the repair of trust needed to maintain their membership.
       
  • Machine Learning based Digital Twin Framework for Production Optimization
           in Petrochemical Industry
    • Abstract: Publication date: Available online 31 May 2019Source: International Journal of Information ManagementAuthor(s): Qingfei Min, Yangguang Lu, Zhiyong Liu, Chao Su, Bo WangAbstractDigital twins, along with the internet of things (IoT), data mining, and machine learning technologies, offer great potential in the transformation of today’s manufacturing paradigm toward intelligent manufacturing. Production control in petrochemical industry involves complex circumstances and a high demand for timeliness; therefore, agile and smart controls are important components of intelligent manufacturing in the petrochemical industry. This paper proposes a framework and approaches for constructing a digital twin based on the petrochemical industrial IoT, machine learning and a practice loop for information exchange between the physical factory and a virtual digital twin model to realize production control optimization. Unlike traditional production control approaches, this novel approach integrates machine learning and real-time industrial big data to train and optimize digital twin models. It can support petrochemical and other process manufacturing industries to dynamically adapt to the changing environment, respond in a timely manner to changes in the market due to production optimization, and improve economic benefits. Accounting for environmental characteristics, this paper provides concrete solutions for machine learning difficulties in the petrochemical industry, e.g., high data dimensions, time lags and alignment between time series data, and high demand for immediacy. The approaches were evaluated by applying them in the production unit of a petrochemical factory, and a model was trained via industrial IoT data and used to realize intelligent production control based on real-time data. A case study shows the effectiveness of this approach in the petrochemical industry.
       
  • An empirical study of the antecedents of data completeness in electronic
           medical records
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Caihua Liu, Didar Zowghi, Amir Talaei-KhoeiAbstractThere is a body of research that highlights the role of data management to improve the quality of data, which in return improves organizational performance. The literature in data management has indicated the five theoretical constructs used to understand the factors influencing data quality, including top management support, capability on the regulation and process management, business-IT alignment, staff participation, and integration of information systems. However, it is unclear how these theoretical constructs can be utilized to understand the antecedents of data completeness as a dimension of data quality. Following that stream of research, the current paper examines the factors influencing data completeness in electronic medical records (EMR). The scope of this study is by only surveying medical professionals at healthcare settings in northern Nevada. The empirical results reveal that resources should be added as one of the antecedents of data completeness in EMR.
       
  • Stakeholder perceptions of information security policy: Analyzing personal
           constructs
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Spyridon Samonas, Gurpreet Dhillon, Ahlam AlmusharrafAbstractOrganizational stakeholders, such as employees and security managers, may understand security rules and policies differently. Extant literature suggests that stakeholder perceptions of security policies can contribute to the success or failure of policies. This paper draws on the Theory of Personal Constructs and the associated methodology, the Repertory Grid technique, to capture the convergence and divergence of stakeholder perceptions with regards to security policy. We collected data from the employees of an e-commerce company that had developed five information security sub-policies. Our study highlights the practical utility of the Repertory Grid analysis in helping information security researchers and managers pinpoint a) the aspects of a security policy that are well-received by stakeholders, as well as those that are not, and b) the variance in the perceptions of stakeholders. Organizations can, then, capitalize on the well-received aspects of the policy and take corrective action for the ill-received ones.
       
  • Factors influencing the adoption of mHealth services in a developing
           country: A patient-centric study
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Mohammad Zahedul Alam, Md. Rakibul Hoque, Wang Hu, Zapan BaruaAbstractmHealth under the umbrella of eHealth has become an essential tool for providing quality, accessible and equal health care services at an affordable cost. Despite the potential benefits of mHealth, its adoption remains a big challenge in developing countries such as Bangladesh. This study aims to examine the factors affecting the adoption of mHealth services in Bangladesh by using the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model with perceived reliability and price value factors. It also examines the moderating effect of gender on the intention to use and on the actual usage behavior of users of mHealth services. A well-structured face-to-face survey was employed to collect the data. Structural equation modeling (SEM) with a partial least squares method was used to analyze the data collected from 296 generation Y participants. The results confirmed that performance expectancy, social influence, facilitating conditions and perceived reliability positively influence the behavioral intention to adopt mHealth services. However, effort expectancy and price value did not have a significance influence on the behavioral intention. Moreover, Gender has a significant moderating effect on mHealth services adoption in certain cases. Finally, the theoretical and practical implications of this study are also discussed.
       
  • Public service reformation: Relationship building by mobile technology
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Mahmud A. Shareef, Ramakrishnan Raman, Abdullah M. Baabdullah, Rafeed Mahmud, Jashim Uddin Ahmed, Humayun Kabir, Vinod Kumar, Uma Kumar, M. Shakaib Akram, Ahmedul Kabir, Bhasker MukerjiAbstractExtensive implementation of information and communication technology (ICT) in public administration has created the capacity to reengineer public service systems to develop a new service delivery channel using the continuous interactivity of the mobile phone's short messaging service (SMS). An empirical study was conducted among general citizens in Bangladesh, who are the actual users of public service. The study revealed that the critical factors which contribute to the development of attitude toward public administration for service delivery through mobile phone SMS are: time and location, relevance, and reliability.
       
  • Pre- and post-launch emotions in new product development: Insights from
           twitter analytics of three products
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Ashish Kumar Rathore, P. Vigneswara IlavarasanAbstractThe paper showcases the possible application of social media analytics in new product development (NPD). It compares users’ emotions before and after the launch of three new products in the market—a pizza, a car and a smart phone—for possible inputs for NPD. The user-generated content offers an alternative to conventional survey data and is cross-cultural in nature, relatively inexpensive and provides real-time information about user behaviour. A total of 302,632 tweets that mentioned the three new products before and after the launch were collected and analysed. Sentiment analysis of the tweets from two time periods was conducted and compared. The users’ responses to the pre- and post-launch of three products vary. The dissatisfaction with the new products represented by negative emotions aligns with the market performance. In the pre-launch period, trust and joy were more common for pizza, joy was more common for the car, and trust was more common for the phone. In the post-launch period, anger and disgust were more common for pizza, joy and trust were more common for the car, and joy was more common for only one aspect of the phone. Further analysis showed that for the car and the phone, firms need to focus on user attitudes towards product attributes, whereas for pizza, firms should concentrate on physiological changes, i.e., changes in product attributes, service and promotional sides. By using the proposed alternative approach, businesses can obtain real-time feedback about the expectations and experiences of the new products. The NPD process can be adjusted accordingly.
       
  • Prescriptive analytics: Literature review and research challenges
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Katerina Lepenioti, Alexandros Bousdekis, Dimitris Apostolou, Gregoris MentzasAbstractBusiness analytics aims to enable organizations to make quicker, better, and more intelligent decisions with the aim to create business value. To date, the major focus in the academic and industrial realms is on descriptive and predictive analytics. Nevertheless, prescriptive analytics, which seeks to find the best course of action for the future, has been increasingly gathering the research interest. Prescriptive analytics is often considered as the next step towards increasing data analytics maturity and leading to optimized decision making ahead of time for business performance improvement. This paper investigates the existing literature pertaining to prescriptive analytics and prominent methods for its implementation, provides clarity on the research field of prescriptive analytics, synthesizes the literature review in order to identify the existing research challenges, and outlines directions for future research.
       
  • EVALUATING THE PRACTICES OF FLEXIBILITY MATURITY FOR THE SOFTWARE PRODUCT
           AND SERVICE ORGANIZATIONS
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Sanjai Kumar Shukla, SushilAbstractThe competitive advantage offered by flexibility has drawn considerable attention from the academic and practitioner community. The existing literature primarily focuses on means to achieve flexibility through information system (IS) exploitation. There is a noticeable absence of a comprehensive flexibility evaluation and implementation framework for organizations, engaged in the delivery of software products and services. This paper proposes twenty-three practices graded in six maturity levels to fill this gap. These practices will improve the understanding, evaluation, and implementation of flexibility in the organizational setting.
       
  • Examining gender differences in people’s information-sharing decisions
           on social networking sites
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Xiaolin Lin, Xuequn WangAbstractInformation systems research provides increasing evidence that women and men differ in their use of information technology. However, research has not sufficiently explained why these differences exist. Using the theory of reasoned action and social role theory, this paper investigates gender differences in people’s decisions about information sharing in the context of social networking sites (SNSs). We developed a comparative model of the information-sharing decision process across genders and theoretically explained why these differences exist. Data was collected from an online survey taken by American SNS users. We found that privacy risks, social ties, and commitment were more important in the formation of attitudes toward information sharing for women than men. Gender significantly moderates the relationship between people’s perceptions of information sharing and their intention to share information. This paper provides an enhanced understanding of gender differences in people’s decisions about sharing information on SNSs. It advances gender differences research into the use of newly emerged information technology and provides researchers insightful views of the role that gender plays in the social media era. Being aware of the research findings, practitioners may better engage their targeted stakeholders on SNSs and collect more useful information for business purposes.
       
  • Role of visual analytics in supporting mental healthcare systems research
           and policy: A systematic scoping review
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Younjin Chung, Nasser Bagheri, Jose Alberto Salinas-Perez, Kayla Smurthwaite, Erin Walsh, MaryAnne Furst, Sebastian Rosenberg, Luis Salvador-CarullaAbstractThe availability of healthcare data has exponentially grown, both in quantity and complexity. The speed of this evolution has generated new challenges for translating complex data into effective evidence-informed policy. Visual analytics offers new capacity to analyze healthcare systems and support better decision-making. We conducted a systematic scoping review to look for evidence of visual analytics approaches being applied to mental healthcare systems and their use in driving policy. We found 79 relevant studies and categorized them in two ways: by study purpose and by type of visualization. The majority (67.1%) of the studies used geographical maps, and 11% conducted highly complex studies requiring novel visualizations. Significantly, only 15% of the studies provided information indicating high levels of usability for policy and planning. Our findings suggest that while visual analytics continues to evolve rapidly, there is a need to ensure this evolution reflects the practical needs of policy makers.
       
  • Mobile food ordering apps: An empirical study of the factors affecting
           customer e-satisfaction and continued intention to reuse
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Ali Abdallah AlalwanAbstractMobile food ordering apps (MFOAs) have been widely considered in the restaurant sector as innovative channels to reach customers and provide them with high-quality services. However, there are important questions regarding the impact of implementing MFOAs on customer satisfaction and on customers’ intention to reuse such apps. Several studies have examined the outcomes of using MFOAs from the customer’s perspective. The fundamental purpose of this study is to identify and empirically examine the main factors predicting the e-satisfaction with MFOAs and customers’ intention to reuse such apps in Jordan. This research proposes an integrated model based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and the features of MFOAs: online review, online rating, and online tracking. The data was collected from a convenience sample of Jordanian customers who have used MFOAs. The main results are based on structural equation modelling and support the role of online review, online rating, online tracking, performance expectancy, hedonic motivation, and price value on e-satisfaction and continued intention to reuse. This study provides a theoretical contribution and presents practical implications relevant to academics and practitioners working in areas related to MFOAs.
       
  • IoT data feature extraction and intrusion detection system for smart
           cities based on deep migration learning
    • Abstract: Publication date: Available online 10 May 2019Source: International Journal of Information ManagementAuthor(s): Daming Li, Lianbing Deng, Minchang Lee, Haoxiang WangAbstractWith the development of information technology and economic growth, the Internet of Things (IoT) industry has also entered the fast lane of development. The IoT industry system has also gradually improved, forming a complete industrial foundation, including chips, electronic components, equipment, software, integrated systems, IoT services, and telecom operators. In the event of selective forwarding attacks, virus damage, malicious virus intrusion, etc., the losses caused by such security problems are more serious than those of traditional networks, which are not only network information materials, but also physical objects. The limitations of sensor node resources in the Internet of Things, the complexity of networking, and the open wireless broadcast communication characteristics make it vulnerable to attacks. Intrusion Detection System (IDS) helps identify anomalies in the network and takes the necessary countermeasures to ensure the safe and reliable operation of IoT applications. This paper proposes an IoT feature extraction and intrusion detection algorithm for intelligent city based on deep migration learning model, which combines deep learning model with intrusion detection technology. According to the existing literature and algorithms, this paper introduces the modeling scheme of migration learning model and data feature extraction. In the experimental part, KDD CUP 99 was selected as the experimental data set, and 10% of the data was used as training data. At the same time, the proposed algorithm is compared with the existing algorithms. The experimental results show that the proposed algorithm has shorter detection time and higher detection efficiency.
       
  • Business continuity of business models: Evaluating the resilience of
           business models for contingencies
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Marko Niemimaa, Jonna Järveläinen, Marikka Heikkilä, Jukka HeikkiläAbstractCompany business models are vulnerable to various contingencies in the business environment that may unexpectedly render their business logic ineffective. In particular, technological advancements, such as the Internet of things, big data, sharing economy and crowdsourcing, have enabled new forms of business models that can effectively and abruptly make traditional business models obsolete. By disrupting or even diminishing companies’ revenue streams, environmental contingencies may present a significant threat to business continuity (BC). Evaluating the resilience of business models against these contingencies should therefore be a core area of BC. However, existing BC approaches tend to focus on the continuity of the resources and processes through which a particular business model is accomplished in practice but omit the business model itself. We argue that in order for BC approaches to become holistic and strategic, business models need to become a part of the BC considerations, entailing an expansion of the scope of BC from value preservation to value creation. We propose an approach of Strategic Business Continuity Management, which consists of two parts: (1) sustaining the continuity of the company business model (value preservation) and (2) evaluating and modifying the business model (value creation). We illustrate conceptually the value creation part with an example drawn from the sharing economy.
       
  • PTZ-Surveillance coverage based on artificial intelligence for smart
           cities
    • Abstract: Publication date: Available online 7 May 2019Source: International Journal of Information ManagementAuthor(s): Khalid A. Eldrandaly, Mohamed Abdel-Basset, Laila Abdel-FatahAbstractSurveillance cameras have a plethora of usages in newly born cities including smart traffic, healthcare, monitoring, and meeting security needs. One of the most famous new cites is the Egypt's new administration capital “New Cairo”. The new administration capital of Egypt mainly characterizes with the green life style via the "Green River ". In this paper, a new enhanced Artificial Intelligence (AI) algorithm is introduced for adjusting the orientation of Pan–Tilt–Zoom (PTZ) surveillance cameras in new Cairo. In other words, the new proposed algorithm is used for improving the field of view (FOV) coverage of PTZ cameras network. For validating the proposed algorithm, it is tested on many scenarios with different criterions. After that, the proposed algorithm is applied to adjust the PTZ monitoring cameras in the green river which locates on new administrative capital as an equivalent to the river Nile. In addition, it compared with several other AI algorithms through the appropriate statistical analysis. The overall experimental results indicate the prosperity of the proposed algorithm for increasing the coverage of the PTZ surveillance system.
       
  • Social media enablers and inhibitors: Understanding their relationships in
           a social networking site context
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Yulia W. Sullivan, Chang E. KohAbstractThis study extends and tests the dual factor model of technology usage (Cenfetelli, 2004, Cenfetelli and Schwarz, 2011), which recognizes enablers and inhibitors as two distinct constructs in the context of social media. We test the effect of two enablers: perceived usefulness and perceived enjoyment on perceived communication quality and social media continuance intention. We advance the understanding of the conceptualization of inhibitors from object-based, social-based, behavioral-based, and affective-based perspectives. We investigate the moderating effects of affective-based inhibitors (i.e., perceived social media distress and perceived social media anxiety) and the direct effects of object-based inhibitor (rapid change), social-based inhibitor (i.e., distorted reputation), and behavioral-based inhibitor (perceived complexity) on communication quality and continuance intention. To test the hypotheses, we collected data using an Online Crowdsourcing Markets (OCMs) technique. Using a sample of 268 Facebook users, our findings suggest perceived enjoyment is the main enabler, whereas perceived complexity is the main inhibitor of social media continuance intention. The findings also suggest that perceived social media anxiety moderates the relationships between (1) perceived complexity and perceived enjoyment, (2) perceived complexity and perceived usefulness, and (3) perceived complexity and perceived communication quality. We also find distorted reputation has a positive effect on perceived complexity but rapid change does not have a significant effect on perceived complexity. Perceived communication quality also significantly influences social media continuance intention. Our study confirms the dual factor model of technology usage and advances social media research by demonstrating that inhibitors are distinct from enablers.
       
  • Consumers acceptance of artificially intelligent (AI) device use in
           service delivery
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Dogan Gursoy, Oscar Hengxuan Chi, Lu Lu, Robin NunkooAbstractThis study develops and empirically tests a theoretical model of artificially intelligent (AI) device use acceptance (AIDUA) that aims to explain customers’ willingness to accept AI device use in service encounters. The proposed model incorporates three acceptance generation stages (primary appraisal, secondary appraisal, and outcome stage) and six antecedents (social influence, hedonic motivation, anthropomorphism, performance expectancy, effort expectancy, and emotion). Utilizing data collected from potential customers, the proposed AIDUA model is tested. Findings suggest that customers go through a three-step acceptance generation process in determining whether to accept the use of AI devices during their service interactions. Findings indicate that social influence and hedonic motivation are positively related to performance expectancy while anthropomorphism is positively related to effort expectancy. Both performance and effort expectancy are significant antecedents of customer emotions, which determines customers’ acceptance of AI device use in service encounters. This study provides a conceptual AI device acceptance framework that can be used by other researchers to better investigate AI related topics in the service context.
       
  • Does digital footprint act as a digital asset' – Enhancing brand
           experience through remarketing
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Vikas Arya, Deepa Sethi, Justin PaulAbstractThe purpose of this paper is to examine the utilization of the marketing adaptability of branded mobile applications (apps) in order to understand the relationship between consumers and their attachment to branded apps. We develop a model grounded in the purchaser-brand relationship theory of remarketing in order to develop the consumer-brand relationship through mediator brand experience (BE) and moderator digital footprint. A survey was conducted with 421 participants from different regions in India. AMOS 21.0 and SPSS plugin called “Process Analysis System” proposed by Hayes (2013) were used to analyze the hypotheses. The results corroborate the proposed research model. It approves brand association with brand connection for those brands that are easily identifiable. The result also confirms that the comprehensive consumption values are the major influencing factors in the adoption of branded apps. The study enhances the comprehension of the impact of brand connotation on consumer behavior in terms of the usage of various branded apps and the practical and non-useful esteem attached to them.
       
  • Blockchain research, practice and policy: Applications, benefits,
           limitations, emerging research themes and research agenda
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Laurie Hughes, Yogesh K. Dwivedi, Santosh K. Misra, Nripendra P. Rana, Vishnupriya Raghavan, Viswanadh AkellaAbstractThe blockchain has received significant attention from technology focussed researchers, highlighting its perceived impact and emerging disruption potential, but has been slow to engender any significant momentum within the Information Systems (IS) and Information Management (IM) literature. This study approaches the subject through an IS/IM lens developing the key themes from the blockchain based research via a comprehensive review. This analysis of the body of literature highlights that although few commercial grade blockchain applications currently exist, the technology demonstrates significant potential to benefit a number of industry wide use cases. This study expands on this point articulating through each of the key themes to develop a detailed narrative on the numerous potential blockchain applications and future direction of the technology, whilst discussing the many barriers to adoption. The study asserts that blockchain technology has the potential to contribute to a number of the UN Sustainability Development Goals and engender widespread change within a number of established industries and practices.
       
  • Connecting circular economy and industry 4.0
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Shubhangini Rajput, Surya Prakash SinghAbstractThe purpose of this paper is to understand the hidden connection between Circular Economy (CE) and Industry 4.0 in the context of supply chain. The factors responsible for linking CE and Industry 4.0 are studied from two angles viz. from the enablers’ side and barriers’ side. In the paper, twenty-six significant enabling and fifteen challenging factors are identified which are further factorized using Principal Component Analysis (PCA). DEMATEL approach is applied on the factors constructed from PCA. Here, the DEMATEL is applied for three different sets of data termed as Optimistic, Pessimistic and Most Likely. The paper identified Artificial Intelligence, Service and Policy Framework, and Circular Economy are significant enablers connecting CE and Industry 4.0. Similarly, paper reports Interface Designing and Automated Synergy Model as the most significant challenges to link CE and Industry 4.0 in a supply chain.
       
  • A supervised machine learning approach to data-driven simulation of
           resilient supplier selection in digital manufacturing
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Ian M. Cavalcante, Enzo M. Frazzon, Fernando A. Forcellini, Dmitry IvanovAbstractThere has been an increased interest in resilient supplier selection in recent years, much of it focusing on forecasting the disruption probabilities. We conceptualize an entirely different approach to analyzing the risk profiles of supplier performance under uncertainty by utilizing the data analytics capabilities in digital manufacturing. Digital manufacturing peculiarly challenge the supplier selection by the dynamic order allocations, and opens new opportunities to exploit the digital data to improve sourcing decisions. We develop a hybrid technique, combining simulation and machine learning and examine its applications to data-driven decision-making support in resilient supplier selection. We consider on-time delivery as an indicator for supplier reliability, and explore the conditions surrounding the formation of resilient supply performance profiles. We theorize the notions of risk profile of supplier performance and resilient supply chain performance. We show that the associations of the deviations from the resilient supply chain performance profile with the risk profiles of supplier performance can be efficiently deciphered by our approach. The results suggest that a combination of supervised machine learning and simulation, if utilized properly, improves the delivery reliability. Our approach can also be of value when analyzing the supplier base and uncovering the critical suppliers, or combinations of suppliers the disruption of which result in the adverse performance decreases. The results of this study advance our understanding about how and when machine learning and simulation can be combined to create digital supply chain twins, and through these twins improve resilience. The proposed data-driven decision-making model for resilient supplier selection can be further exploited for design of risk mitigation strategies in supply chain disruption management models, re-designing the supplier base or investing in most important and risky suppliers.
       
  • Representation matters: An exploration of the socio-economic impacts of
           ICT-enabled public value in the context of sub-Saharan economies
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Sergey Samoilenko, Kweku-Muata Osei-BrysonAbstractIn this investigation we use a modified Networked Readiness Index (NRI) framework to investigate whether (1) ICT capabilities impact public value creation, and (2) if the public value is associated with the socio-economic impact of ICT capabilities. In the case of this study the construct Public Value is represented via two different proxies. In the first case we use a perception-based measure of public value (as represented by the World Government Indicators) and in the second case we use a surrogate objective measure (as represented by the Cost of Business Startup Procedures (CBSP)). We use a six-step multi-method methodology that involves Cluster Analysis, Correlation Analysis, Decision Trees Induction, Data Envelopment Analysis, Association Rules Mining, and Ordinary Least Squares regression to conduct the inquiry in the context of 26 Sub-Saharan (SSA) economies. Results of our data analysis include: 1) the set of economies with better developed ICT Capabilities are relatively more efficient in converting ICT Capabilities into Public Value than the relatively poorer economies with less developed ICT Capabilities; 2) High levels of ICT capabilities in the areas of Affordability Readiness, Skills Readiness, the Political & Regulatory Environment, and Business Usage allow for relatively more efficient generation of Public Value.
       
  • Mobile technology identity and self-efficacy: Implications for the
           adoption of clinically supported mobile health apps
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Ali Balapour, Iris Reychav, Rajiv Sabherwal, Joseph AzuriAbstractDespite smartphone applications (apps) being key enablers of telemedicine, telehealth, and self-monitoring, adoption issues persist for mobile healthcare (mHealth) apps. This study diverged from the traditional adoption approach and drew on more innovative theories to predict the intentions of patients for adopting apps supported by clinics. More specifically, technology identity literature was explored to make this prediction and the study surveyed 292 patients who were seated in the waiting room of a local clinic. The results suggested that perceived mobile technology identity (MTI), perceived related IT experience, and perceived self-efficacy positively influences patients’ perceived intentions to adopt mHealth apps provided by clinics or hospitals. Furthermore, the results suggested that perceived related IT experience positively influences users perceived self-efficacy and perceived MTI. However, education was found to negatively influence patients’ perceived intentions to use mHealth apps. This study contributes to the growing literature on the use of these apps in trying to elevate the quality of patients’ lives. Moreover, there are implications for mHealth-app designers who are trying to make healthcare services accessible via smartphones.
       
  • Applying artificial intelligence technique to predict knowledge hiding
           behavior
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): A. Mohammed Abubakar, Elaheh Behravesh, Hamed Rezapouraghdam, Selim Baha YildizAbstractDrawing on psychological ownership and social exchange theories, this study suggests theoretical arguments and empirical evidence for understanding employee reactions to distributive, procedural, and interactional (in)justice — three crucial bases of employees’ feelings of social self-worth. Utilizing field data and artificial intelligence technique, this paper reveals that distributive, procedural, and interactional (in)justice contribute to higher levels of knowledge hiding behavior among employees and that this impact is non-linear (asymmetric). By reuniting the discourses of organizational justice and knowledge management, this study indicates that feelings of psychological ownership of knowledge and the degree of social interaction are mechanisms that work with organizational (in)justice to influence knowledge hiding behavior. The current research may inform contemporary theories of business research and provide normative guidance for managers.
       
  • Acceptance and resistance of telehealth: The perspective of dual-factor
           concepts in technology adoption
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Juin-Ming Tsai, Min-Jhih Cheng, Her-Her Tsai, Shiu-Wan Hung, Ya-Ling ChenAbstractTelehealth can be used to develop innovative healthcare services for promoting medical quality and efficiency. Despite previous research on users’ adoption intention of telehealth, users’ acceptance and resistance have rarely been considered at the same time. This study used a research model based on the dual-factor concepts of “enablers” and “inhibitors” to explain users’ intentions to utilize telehealth. We extended the Technology Acceptance Model and Status Quo Bias with the technology anxiety concept to explain why patients accept or reject the use of telehealth from the perceived enablers and inhibitors of intentions. The experimental results demonstrated users’ ambiguous and indecisive intentions of adopting telehealth. It was also found that availability and perceived usefulness are the main factors that encourage individuals to adopt telehealth services. Technology anxiety and transition costs are the key factors in discouraging people from using telehealth. Technology anxiety could be overcome through the perceived usefulness to promote the adoption of telehealth.
       
  • Knowledge collaboration among physicians in online health communities: A
           transactive memory perspective
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Hong Wu, Zhaohua DengAbstractKnowledge teams have emerged in online health communities (OHCs) where physicians collaborate spontaneously with others through the Internet to gather knowledge. Knowledge collaboration (KC) facilitates physicians’ communication and the provision of better services to patients in today's medical environment. However, the underlying mechanism through which KC improves team performance in OHCs is not clear. This study aims to advance understanding of the KC process by exploring the role of the transactive memory system (TMS). Real operation data from 1071 teams in a leading OHC in China used to understand both the antecedent and consequences of the TMS and the interaction effects among different dimensions of TMS. The findings have demonstrated that leader's capital was a critical factor in KC by promoting the effective TMS development and further affect both team's process and outcome performance. Positive moderating effects of coordination on the relationship between credibility and performance are also found. This study reveals for the first time the role of KC in improving performance in online health markets from the TMS perspective. The findings provide theoretical guidance to physician–physician collaborative teams with guidelines on boosting chances for higher performance.
       
  • Understanding SaaS adoption: The moderating impact of the environment
           context
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Tiago Oliveira, Ricardo Martins, Saonee Sarker, Manoj Thomas, Aleš PopovičAbstractIn the information management literature, Software-as-a-Service (SaaS) is recognized as a technology capable of providing operational and financial benefits to firms, and it is rising as the dominant IT service delivery model. Considered to be a promising solution it is garnering interest among researchers and professionals. However, SaaS can represent a vulnerability to firms due to its nature. The weighing of the pros and cons leads to firms’ uncertainty regarding SaaS adoption. Through the lenses of technology-organization-environment (TOE) framework we examine the contextual factors that influence the adoption of SaaS. Furthermore, this study explores the moderating effects of the environmental context in the adoption of SaaS and how it shapes the direct influences of technological and organizational contexts of the TOE framework. Data collected from 259 firms were used to test the proposed model. The study found the significance of the technology, organization, and environment context for SaaS adoption. Moreover, it was found the moderator influence of the environment context between the organization context and SaaS adoption. This study contributes to a deepest understanding of the determinants of SaaS adoption by providing a holistic theoretical lens, advancing newer paths of approaching the TOE framework.
       
 
 
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