for Journals by Title or ISSN
for Articles by Keywords
Followed Journals
Journal you Follow: 0
Sign Up to follow journals, search in your chosen journals and, optionally, receive Email Alerts when new issues of your Followed Journals are published.
Already have an account? Sign In to see the journals you follow.
Similar Journals
Journal Cover
International Journal of Information Management
Journal Prestige (SJR): 1.373
Citation Impact (citeScore): 6
Number of Followers: 343  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0268-4012
Published by Elsevier Homepage  [3185 journals]
  • 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 Raymond Taking 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
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Ali E. Akgün While 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.
  • Modeling the blockchain enabled traceability in agriculture supply chain
    • Abstract: Publication date: Available online 15 June 2019Source: International Journal of Information ManagementAuthor(s): Sachin S. Kamble, Angappa Gunasekaran, Rohit Sharma Blockchain Technology (BT) has led to a disruption in the supply chain by removing the trust related issues. Studies are being conducted worldwide to leverage the benefits provided by BT in improving the performance of the supply chains. The literature reveals BT to offer various benefits leading to improvements in the sustainable performance of the agriculture supply chains (ASC). It is expected that BT will bring a paradigm shift in the way the transactions are carried in the ASC by reducing the high number of intermediaries, delayed payments and high transaction lead times. India, a developing economy, caters to the food security needs of an ever-growing population and faces many challenges affecting ASC sustainability. It is therefore essential to adopt BT in the ASC to leverage the various benefits. In this study, we identify and establish the relationships between the enablers of BT adoption in ASC. Thirteen enablers were identified from the literature and validated by the experts before applying a combined Interpretive Structural Modelling (ISM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology to envision the complex causal relationships between the identified BT enablers. The findings from the study suggest that, among the identified enablers, traceability was the most significant reason for BT implementation in ASC followed by auditability, immutability, and provenance. The findings of the study will help the practitioners to design the strategies for BT implementation in agriculture, creating a real-time data-driven ASC. The results will also help the policymakers in developing policies for faster implementation of BT ensuring food safety and sustainable ASCs.
  • Big data analytics in health sector: Theoretical framework, techniques and
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Panagiota Galetsi, Korina Katsaliaki, Sameer Kumar Clinicians, 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 Eldabi Organizations 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-Cabanillas Potential 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 Papadopoulos In 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
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Anneke Zuiderwijk, Helen Spiers Open 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.
  • Boundary conditions for traceability in food supply chains using
           blockchain technology
    • Abstract: Publication date: Available online 14 June 2019Source: International Journal of Information ManagementAuthor(s): Kay Behnke, M.F.W.H.A. Janssen Traceability of ingredients in food supply chains has become paramount in a world in which markets become global, heterogeneous, and complex and in which consumers expect a high level of quality. The food supply chain consists of many organizations having different interests and are often reluctant to share traceability information with each other. Blockchain has been advocated for improving traceability by providing trust. Yet, practice proved to be more stubborn. The goal of this paper is to identify boundary conditions for sharing assurance information to improve traceability. Four cases in the food supply chain have been investigated using a template analysis of 16 interviews. Eighteen boundary conditions categorized in business, regulation, quality and traceability categories have been identified. Some boundary conditions were found in all supply chains, whereas others were found to be supply chain specific. Standardization of traceability processes and interfaces, having a joint platform and independent governance were found to be key boundary conditions before blockchain can be used. Our findings imply that supply chain systems have first to be modified and organizational measures need to be taken to fulfill the boundary conditions, before blockchain can be used successfully.
  • Emotional Text Mining: Customer profiling in brand management
    • Abstract: Publication date: Available online 14 June 2019Source: International Journal of Information ManagementAuthor(s): Francesca Greco, Alessandro Polli The widespread use of the Internet and the constant increase in users of social media platforms has made a large amount of textual data available. This represents a valuable source of information about the changes in people’s opinions and feelings. This paper presents the application of Emotional Text Mining (ETM) in the field of brand management. ETM is an unsupervised procedure aiming to profile social media users. It is based on a bottom-up approach to classify unstructured data for the identification of social media users’ representations and sentiments about a topic. It is a fast and simple procedure to extract meaningful information from a large collection of texts. As customer profiling is relevant for brand management, we illustrate a business application of ETM on Twitter messages concerning a well-known sportswear brand in order to show the potential of this procedure, highlighting the characteristics of Twitter user communities in terms of product preferences, representations, and sentiments.
  • Big data analytics for financial Market volatility forecast based on
           support vector machine
    • Abstract: Publication date: Available online 13 June 2019Source: International Journal of Information ManagementAuthor(s): Rongjun Yang, Lin Yu, Yuanjun Zhao, Hongxin Yu, Guiping Xu, Yiting Wu, Zhengkai Liu High-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.
  • 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. Treku Abuse 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.
  • Land records on Blockchain for implementation of Land Titling in India
    • Abstract: Publication date: Available online 8 June 2019Source: International Journal of Information ManagementAuthor(s): Vinay Thakur, M.N. Doja, Yogesh K. Dwivedi, Tanvir Ahmad, Ganesh Khadanga This paper explores the usage of Blockchain Technology for Land Records Management in India. It highlights issues, such as minimal transparency, accountability, incoherent data sets with different Government Departments pertaining to the same piece of land and delays in the current Land Records management process and how to overcome these problems using Blockchain Technology. The paper describes the current process of land records maintenance and land registration in the country, and discusses various challenges encountered during the implementation of Blockchain Technology like public key infrastructure and Internet, privacy rules and security issues. Finally, the paper illustrates a system design using Blockchain Technology for the implementation of Land Titling system in the country, so that land titles are tamper-proof, and provides authentic and conclusive rights on ownership.
  • Considering the influence of queue length on performance improvement for a
           new compact robotic automated parking system
    • Abstract: Publication date: Available online 6 June 2019Source: International Journal of Information ManagementAuthor(s): Guangmei Wu, Xianhao Xu, Xinyuan Lu With 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%.
  • A network-based concept extraction for managing customer requests in a
           social media care context
    • Abstract: Publication date: Available online 3 June 2019Source: International Journal of Information ManagementAuthor(s): Michelangelo Misuraca, Germana Scepi, Maria Spano Web 2.0 changed everyday life in many aspects, including the whole system that orbits around the purchase of products and services. This revolution necessarily involved also companies, because customers became increasingly demanding. The diffusion of social media platforms pushed customers to prefer this channel for quickly obtaining information and feedback about what they want to buy, as well as for asking help after the selling. In this framework, many organisations adopted a new way of providing assistance known as social customer care. A direct link to companies allows customers to obtain real-time solutions. In this paper, we introduce a new strategy for automatically managing the information listed in the requests that customers send to the social media accounts of companies. Our proposal relies on the use of network techniques for extracting high-level structures from texts, highlighting the different concepts expressed into the customers’ written requests. The texts can be then organised on the basis of this new emerging information. An application to the requests sent to the AppleSupport service on Twitter shows the effectiveness of the strategy.
  • 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 Wang Digital 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-Khoei There 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
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Spyridon Samonas, Gurpreet Dhillon, Ahlam Almusharraf Organizational 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 Barua mHealth 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 Mukerji Extensive 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.
  • 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: Available online 28 May 2019Source: International Journal of Information ManagementAuthor(s): Xin Liu, yanju zhou, Wang Zongrun The 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.
  • 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 Ilavarasan The 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 Mentzas Business 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.
    • Abstract: Publication date: February 2020Source: International Journal of Information Management, Volume 50Author(s): Sanjai Kumar Shukla, Sushil The 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.
  • Analysing the impact of blockchain-technology for operations and supply
           chain management: An explanatory model drawn from multiple case studies
    • Abstract: Publication date: Available online 22 May 2019Source: International Journal of Information ManagementAuthor(s): Stefan Tönnissen, Frank Teuteberg Blockchain technology is said to have a high disruptive potential and can do without an intermediary. Numerous contributions deal with its impact on and possibilities for logistics and supply chains. In this article, we use a multiple case analysis to develop an explanatory model for the interaction of actors in an operational supply chain involving blockchain technology. In addition, we show which intermediary tasks the blockchain could replace and what impact this would have on the industry logic. For this purpose, we analyze the status quo in practice based on a multiple case study with real use cases and find answers to our research questions. The findings of the paper include (1) insights into the impact of blockchain technology on the logistics industry, and (2) the implications and research questions related to blockchain technology and the impact of blockchain technology on business models.
  • Blockchain technology and enterprise operational capabilities: An
           empirical test
    • Abstract: Publication date: Available online 22 May 2019Source: International Journal of Information ManagementAuthor(s): Xiongfeng Pan, Xianyou Pan, Malin Song, Bowei Ai, Yang Ming As a new type of disruptive internet technology, blockchain technology is widely used as a technical support for enterprises to improve production processes and reduce costs. This paper reveals that existing research has only focused on the business process modelling and technology design process of a blockchain-based solution and has neglected analysis of the relationship between blockchain technology and enterprise operational capabilities based on actual data. Hence, this paper collects 50 listed blockchain technology enterprises in China and quantitatively analyses them. The results show that the expansion of the enterprise asset scale is a significant driving factor for implementing blockchain technology. In addition, this paper proves that implementation of blockchain technology has a positive impact on improving asset turnover rate and reducing sales expense rate. Based on the results of theoretical and empirical analysis, this paper provides some constructive suggestions for constructing blockchain projects in the future.
  • The dual effects of the Internet of Things (IoT): A systematic review of
           the benefits and risks of IoT adoption by organizations
    • Abstract: Publication date: Available online 22 May 2019Source: International Journal of Information ManagementAuthor(s): Paul Brous, Marijn Janssen, Paulien Herder The Internet of Things (IoT) might yield many benefits for organizations, but like other technology adoptions may also introduce unforeseen risks and requiring substantial organizational transformations. This paper analyzes IoT adoption by organizations, and identifies IoT benefits and risks. A Big, Open, Linked Data (BOLD) categorization of the expected benefits and risks of IoT is made by conducting a comprehensive literature study. In-depth case studies in the field of asset management were then executed to examine the actual experienced, real world benefits and risks. The duality of technology is used as our theoretical lens to understand the interactions between organization and technology. The results confirm the duality that gaining the benefits of IoT in asset management produces unexpected social changes that lead to structural transformation of the organization. IoT can provide organizations with many benefits, after having dealt with unexpected risks and making the necessary organizational changes. There is a need to introduce changes to the organization, processes and systems, to develop capabilities and ensure that IoT fits the organization’s purposes.
  • 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 Wang Information 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-Carulla The 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 Alalwan Mobile 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 Wang With 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 Heikkilä Company 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.
  • Blockchain, adoption, and financial inclusion in India: Research
    • Abstract: Publication date: Available online 7 May 2019Source: International Journal of Information ManagementAuthor(s): Sebastian Schuetz, Viswanath Venkatesh The economic development of rural India requires connecting remote villages to local and global supply chains. Yet, high rates of financial exclusion inhibit rural Indians from participating in these supply networks. We review the literature on financial inclusion, adoption, and blockchain in India, and posit that to resolve financial exclusion, the four challenges of geographical access, high cost, inappropriate banking products, and financial illiteracy need to be overcome. Next, we argue that blockchain technologies hold the potential to overcome most of these challenges. However, for blockchain technologies to become the cornerstone of financial inclusion initiatives, an understanding of technology adoption in India is needed. To guide the development of such understanding, we develop a research agenda on the antecedents of adoption, adoption patterns, and outcomes of adoption. Answering these research questions will lead to a nuanced understanding of adoption of blockchain-based technologies in rural India. The practical contribution of this paper is the discussion of how blockchain can alleviate the issue of financial exclusion in rural India, thereby providing a basis for a solution that could connect rural Indians to global supply chain networks. The theoretical contribution lies in the identification of knowledge gaps that should be answered to achieve financial inclusion of rural Indians.
  • PTZ-Surveillance coverage based on artificial intelligence for smart
    • Abstract: Publication date: Available online 7 May 2019Source: International Journal of Information ManagementAuthor(s): Khalid A. Eldrandaly, Mohamed Abdel-Basset, Laila Abdel-Fatah Surveillance 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. Koh This 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.
  • Intelligent decision-making of online shopping behavior based on internet
           of things
    • Abstract: Publication date: Available online 22 April 2019Source: International Journal of Information ManagementAuthor(s): Hanliang Fu, Gunasekaran Manogaran, Kuang Wu, Ming Cao, Song Jiang, Aimin Yang The 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: Available online 18 April 2019Source: International Journal of Information ManagementAuthor(s): Wei Zhang, Meng Wang, Yan-chun Zhu The 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.
  • 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 Nunkoo This 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 Paul The 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 Akella The 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.
  • Put your money where your mouth is: Using deep learning to identify
           consumer tribes from word usage
    • Abstract: Publication date: Available online 2 April 2019Source: International Journal of Information ManagementAuthor(s): Peter Gloor, Andrea Fronzetti Colladon, Joao Marcos de Oliveira, Paola Rovelli Internet and social media offer firms novel ways of managing their marketing strategy and gain competitive advantage. The groups of users expressing themselves on the Internet about a particular topic, product, or brand are frequently called a virtual tribe or E-tribe. However, there are no automatic tools for identifying and studying the characteristics of these virtual tribes. Towards this aim, this paper presents Tribefinder, a system to reveal Twitter users’ tribal affiliations, by analyzing their tweets and language use. To show the potential of this instrument, we provide an example considering three specific tribal macro-categories: alternative realities, lifestyle, and recreation. In addition, we discuss the different characteristics of each identified tribe, in terms of use of language and social interaction metrics. Tribefinder illustrates the importance of adopting a new lens for studying virtual tribes, which is crucial for firms to properly design their marketing strategy, and for scholars to extend prior marketing research.
  • Process fragmentation and port performance: Merging SNA and text mining
    • Abstract: Publication date: Available online 1 April 2019Source: International Journal of Information ManagementAuthor(s): Davide Aloini, Elisabetta Benevento, Alessandro Stefanini, Pierluigi Zerbino This paper investigates the role of process coordination dynamics and information exchanges in maritime logistics. To this aim, a case study in a mid-sized port supported by a Port Community System (PCS) was developed. Exploiting data retrieved from the PCS, the methodology combined three data-driven techniques – Process Mining (PM), Social Network Analysis (SNA) and Text Mining – to draw handover social networks among the port logistics players, and to assess the export process efficiency and significant process deviations. Then, two sets of regression models were developed to explore the effects of network dynamics on process performances. Preliminary results point out that the process fragmentation and the frequent communication switching among the port actors could negatively affect the export process efficiency and effectiveness. Finally, the study proposes practical solutions for reducing process fragmentation and improving information exchange among port actors.
  • Connecting circular economy and industry 4.0
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Shubhangini Rajput, Surya Prakash Singh The 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 Ivanov There 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-Bryson In 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 Azuri Despite 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
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): A. Mohammed Abubakar, Elaheh Behravesh, Hamed Rezapouraghdam, Selim Baha Yildiz Drawing 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 Chen Telehealth 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 Deng Knowledge 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
    • Abstract: Publication date: December 2019Source: International Journal of Information Management, Volume 49Author(s): Tiago Oliveira, Ricardo Martins, Saonee Sarker, Manoj Thomas, Aleš Popovič In 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.
  • Special section on mobile information services
    • Abstract: Publication date: Available online 27 February 2019Source: International Journal of Information ManagementAuthor(s): Tommi Laukkanen
  • Measuring extreme risk of sustainable financial system using GJR-GARCH
           model trading data-based
    • Abstract: Publication date: Available online 30 January 2019Source: International Journal of Information ManagementAuthor(s): Xiaomeng Ma, Ruixian Yang, Dong Zou, Rui Liu This paper investigates the role of gold as a safe haven for stock markets and the US dollar by examining the extreme risk spillovers. The extreme risk is measured by Value at Risk (VaR), which is estimated by GJR-GARCH model based on skewed t distribution. Two test statistics of one-way and two-way Granger causality in risk are used to detect extreme risk spillovers. In general, the empirical results show that there are negative extreme risk spillovers between gold and stock markets and between gold and foreign exchange markets of US dollar, which indicate that gold can act as an effective safe haven against extreme stock and US dollar exchange rate movements. In addition, the global financial crisis can affect the safe haven role of gold.
  • Applications of business intelligence and analytics in social media
    • Abstract: Publication date: Available online 23 January 2019Source: International Journal of Information ManagementAuthor(s): Nick Hajli, Michel Laroche
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
Home (Search)
Subjects A-Z
Publishers A-Z
Your IP address:
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-