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  • 1
    Online Resource
    Online Resource
    Shared Minds: How Patients Use Collaborative Information Sharing via Social Media Platforms
    Wiley ; 2019
    In:  Production and Operations Management Vol. 28, No. 1 ( 2019-01), p. 9-26
    Details
    In: Production and Operations Management, Wiley, Vol. 28, No. 1 ( 2019-01), p. 9-26
    Abstract: Despite our understanding that social media and online healthcare communities can help to eliminate health information asymmetry and improve patients’ self‐care engagement, we have yet to understand what happens when patients have access to others’ health data and how patients’ access to these shared experiences and opinions influence their health knowledge and perceived treatment outcome. In this study, we apply social information processing theory and incorporate (1) uncertainty of a treatment, (2) information exposure, and (3) credibility of the information source into patients’ information evaluation function to assess how patients utilize shared health information and experiences. An empirical model, which combines various aspects of patients’ firsthand experiences about treatments into a single construct, yields empirical evidence that patients’ perceived treatment outcome is prone to social influence from other patients’ shared experiences. By disaggregating the sources of social influence, we find that social influence created by generalized others in the community outweighs that by familiar others of one's intimate social group. In addition, we find that other factors, such as positive sentiment in comments and patients’ prior experiences, also affect patients’ perceived treatment outcome. Based on our findings, implications for health promotion and health behaviors are presented.
    Type of Medium: Online Resource
    ISSN: 1059-1478 , 1937-5956
    URL: Issue
    URL: Article
    DOI: 10.1111/poms.2019.28.issue-1
    DOI: 10.1111/poms.12895
    RVK:
    QA 10000
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2151364-8
    detail.hit.zdb_id: 1108460-1
    SSG: 3,2
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  • 2
    Online Resource
    Online Resource
    Contract Disputes by Individually Owned Small Businesses
    Informa UK Limited ; 1988
    In:  Chinese Economic Studies Vol. 21, No. 2 ( 1988-01), p. 115-119
    Details
    In: Chinese Economic Studies, Informa UK Limited, Vol. 21, No. 2 ( 1988-01), p. 115-119
    Type of Medium: Online Resource
    ISSN: 0009-4552
    URL: Article
    DOI: 10.2753/CES1097-14752102115
    RVK:
    QA 10000
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 1988
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    Online Resource
  • 3
    Online Resource
    Online Resource
    The Optimized Anomaly Detection Models Based on an Approach of Dealing with Imbalanced Dataset for Credit Card Fraud Detection
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-4-25), p. 1-10
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-4-25), p. 1-10
    Abstract: Credit card fraud is a major problem in today’s financial world. It induces severe damage to financial institutions and individuals. There has been an exponential increase in the losses due to fraud in recent years. Hence, effectively detecting fraudulent behavior is of vital importance for either financial institutions or individuals. Since credit fraud events account for a small proportion of all transaction events in real life, the datasets about credit fraud are usually imbalanced. Some common classifiers, such as decision tree and naïve Bayes, are unable to detect fraud. Furthermore, in some cases, traditional strategies for dealing with an imbalanced problem, such as the synthetic minority oversampling technique (SMOTE), are not effective for the fraud detection datasets. To accurately detect fraud behavior, this study uses anomaly detection on imbalanced data, as well as Isolation Forest (IForest) with kernel principal component analysis. A one-class support vector machine (OCSVM) with AdaBoost is used as two models to detect outliers which significantly improves detection accuracy and efficiency. The model achieved 96% accuracy, 100% precision, 96% recall, and 98% F 1 score, respectively. The proposed model is expected to become a helpful tool for finding credit card fraud detection, and the analysis presented in this study will provides useful insights into credit card fraud detection mechanisms.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/8027903
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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  • 4
    Online Resource
    Online Resource
    Constructing the Web of Events from Raw Data in the Web of Things
    Hindawi Limited ; 2014
    In:  Mobile Information Systems Vol. 10, No. 1 ( 2014), p. 105-125
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 10, No. 1 ( 2014), p. 105-125
    Abstract: An exciting paradise of data is emerging into our daily life along with the development of the Web of Things. Nowadays, volumes of heterogeneous raw data are continuously generated and captured by trillions of smart devices like sensors, smart controls, readers and other monitoring devices, while various events occur in the physical world. It is hard for users including people and smart things to master valuable information hidden in the massive data, which is more useful and understandable than raw data for users to get the crucial points for problems-solving. Thus, how to automatically and actively extract the knowledge of events and their internal links from the big data is one key challenge for the future Web of Things. This paper proposes an effective approach to extract events and their internal links from large scale data leveraging predefined event schemas in the Web of Things, which starts with grasping the critical data for useful events by filtering data with well-defined event types in the schema. A case study in the context of smart campus is presented to show the application of proposed approach for the extraction of events and their internal semantic links.
    Type of Medium: Online Resource
    ISSN: 1574-017X , 1875-905X
    URL: Article
    DOI: 10.1155/2014/517486
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2014
    detail.hit.zdb_id: 2187808-0
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  • 5
    Online Resource
    Online Resource
    Understanding the Impact of Individual Users’ Rating Characteristics on the Predictive Accuracy of Recommender Systems
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2019
    In:  INFORMS Journal on Computing
    Details
    In: INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS)
    Type of Medium: Online Resource
    ISSN: 1091-9856 , 1526-5528
    URL: Article
    DOI: 10.1287/ijoc.2018.0882
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2019
    detail.hit.zdb_id: 2070411-2
    detail.hit.zdb_id: 2004082-9
    SSG: 3,2
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  • 6
    Online Resource
    Online Resource
    Impact of information technology on the performance of logistics industry: the case of Hong Kong and Pearl Delta region
    Informa UK Limited ; 2014
    In:  Journal of the Operational Research Society Vol. 65, No. 6 ( 2014-06), p. 904-916
    Details
    In: Journal of the Operational Research Society, Informa UK Limited, Vol. 65, No. 6 ( 2014-06), p. 904-916
    Type of Medium: Online Resource
    ISSN: 0160-5682 , 1476-9360
    URL: Article
    DOI: 10.1057/jors.2013.121
    RVK:
    QA 10000
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2014
    detail.hit.zdb_id: 716033-1
    detail.hit.zdb_id: 2007775-0
    SSG: 3,2
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  • 7
    Online Resource
    Online Resource
    Cluster-Based Smartphone Predictive Analytics for Application Usage and Next Location Prediction
    IGI Global ; 2018
    In:  International Journal of Business Intelligence Research Vol. 9, No. 2 ( 2018-07), p. 64-80
    Details
    In: International Journal of Business Intelligence Research, IGI Global, Vol. 9, No. 2 ( 2018-07), p. 64-80
    Abstract: Prediction of app usage and location of smartphone users is an interesting problem and active area of research. Several smartphone sensors such as GPS, accelerometer, gyroscope, microphone, camera and Bluetooth make it easier to capture user behavior data and use it for appropriate analysis. However, differences in user behavior and increasing number of apps have made such prediction a challenging problem. In this article, a prediction approach that takes smartphone user behavior into consideration is proposed. The proposed approach is illustrated using data from over 30000 users from a leading IT company in China by first converting data in to recency, frequency, and monetary variables and then performing cluster analysis to capture user behavior. Prediction models are then developed for each cluster using a training dataset and their performance is assessed using a test dataset. The study involves ten different categories of apps and four different regions in Beijing. The proposed app usage prediction and next location prediction approach has provided interesting results.
    Type of Medium: Online Resource
    ISSN: 1947-3591 , 1947-3605
    URL: Issue
    URL: Issue
    URL: Journal
    URL: Article
    DOI: 10.4018/IJBIR.2018
    DOI: 10.4018/IJBIR.20180701
    DOI: 10.4018/IJBIR
    DOI: 10.4018/IJBIR.2018070104
    RVK:
    QA 10000
    Language: English
    Publisher: IGI Global
    Publication Date: 2018
    detail.hit.zdb_id: 2566652-6
    SSG: 3,2
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  • 8
    Online Resource
    Online Resource
    Performance‐Price‐Ratio Utility: Market Equilibrium Analysis and Empirical Calibration Studies
    SAGE Publications ; 2021
    In:  Production and Operations Management Vol. 30, No. 5 ( 2021-05), p. 1442-1456
    Details
    In: Production and Operations Management, SAGE Publications, Vol. 30, No. 5 ( 2021-05), p. 1442-1456
    Abstract: In this study, as an alternative to the surplus utility, we propose a performance‐price‐ratio (PPR) utility and specialize the customer choice model with a PPR maximization criterion. With the PPR‐based choice model, we investigate a pricing game between retailers in a competitive market. Through transferring the decision variable from price to performance‐price ratio, the first‐order condition of the game becomes a linear equation system, which enables us to develop a closed‐form equilibrium solution. The solution reveals how product performance and price sensitivity affect equilibrium pricing, market share, and revenue. With the developed theoretical results, we carry out empirical studies with a rich data set obtained from the China TV market. At the individual product level and the brand level, we calibrate the PPR‐based choice model and the widely used surplus‐based model with a Bayesian information criteria‐based stepwise multivariate regression method. The regression results suggest that the PPR‐based model fits both the product‐level and brand‐level data better than the surplus‐based model. Through the stepwise selection of independent variables, we find that the leading features affecting a TV’s performance are 3D TV functionality and its screen size. Moreover, we explore how the market equilibrium evolves with the game decision sequence, market structure, and new product entry.
    Type of Medium: Online Resource
    ISSN: 1059-1478 , 1937-5956
    URL: Article
    DOI: 10.1111/poms.13331
    RVK:
    QA 10000
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2021
    detail.hit.zdb_id: 2151364-8
    detail.hit.zdb_id: 1108460-1
    SSG: 3,2
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  • 9
    Online Resource
    Online Resource
    The Kindness of Commenters: An Empirical Study of the Effectiveness of Perceived and Received Support for Weight‐Loss Outcomes
    Wiley ; 2020
    In:  Production and Operations Management Vol. 29, No. 6 ( 2020-06), p. 1448-1466
    Details
    In: Production and Operations Management, Wiley, Vol. 29, No. 6 ( 2020-06), p. 1448-1466
    Abstract: Social media‐based online communities are becoming increasingly popular for various social interactions, including those for healthcare and health‐related activities. The benefits from these activities, however, are constrained by how a platform is designed, as a platform's design defines what activities can be done and how individuals can engage and interact on the platform. In this study, we focus on weight‐loss communities and social tools that facilitate social communication and establish a variety of relationships between users. In particular, we examine the effectiveness of one‐way and two‐way social relationships on individuals’ weight‐loss management. Drawing from theories of social support, social reciprocity, and social indebtedness, we use two‐way friendship relationships to proxy perceived support and one‐way commenting relationships to proxy received support and conjecture that they work through different pathways. We find, through empirical analyses, that both types of social relationships as well as self‐monitoring are effective in promoting weight loss, but perceived and received support have different impacts. Whereas both perceived and received support are positively related to weight‐loss outcomes, the effect of received support is found to be higher than that of perceived support and the difference is statistically significant. Moreover, we find that received support is positively associated with self‐monitoring behaviors, whereas perceived support is not. These findings provide insights for platform providers to improve the social design aspect of online services and for healthcare practitioners in their efforts to advise individuals on weight self‐management. Our results also can be used to design and implement more effective online interventions.
    Type of Medium: Online Resource
    ISSN: 1059-1478 , 1937-5956
    URL: Issue
    URL: Article
    DOI: 10.1111/poms.v29.6
    DOI: 10.1111/poms.13171
    RVK:
    QA 10000
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2151364-8
    detail.hit.zdb_id: 1108460-1
    SSG: 3,2
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  • 10
    Online Resource
    Online Resource
    Social Media for Disaster Management: Operational Value of the Social Conversation
    Wiley ; 2019
    In:  Production and Operations Management Vol. 28, No. 10 ( 2019-10), p. 2514-2532
    Details
    In: Production and Operations Management, Wiley, Vol. 28, No. 10 ( 2019-10), p. 2514-2532
    Abstract: Disaster relief organizations increasingly engage in social conversations to inform social media users about activities such as evacuation routes and aid distribution. Concurrently, users share information such as the demand for aid, willingness to donate and availability to volunteer through social conversations with relief organizations. We investigate the effect of this information exchange on social engagement during disaster preparedness, response, and recovery. We propose that the effect of information on social engagement increases from preparedness to response and decreases from response to recovery. Some of the information exchanged in social conversations is actionable as well. We propose, however, that the effect of actionable information reaches its lowest point during disaster response. To test our theory, we use Facebook data from five benchmark organizations that responded to Hurricane Sandy in 2012. We analyze all of the organizations’ posts and users’ comments during a three‐week period before, during and after Hurricane Sandy. Our findings support our theory. Furthermore, we identify an opportunity for relief organizations to improve their use of social media for disaster management. While relief organizations focus on informing disaster victims about aid distribution, most users are asking about how they as individuals can donate or volunteer. Thus, besides posting information directed to victims, organizations should post more information targeting potential donors and volunteers.
    Type of Medium: Online Resource
    ISSN: 1059-1478 , 1937-5956
    URL: Issue
    URL: Article
    DOI: 10.1111/poms.v28.10
    DOI: 10.1111/poms.13064
    RVK:
    QA 10000
    Language: English
    Publisher: Wiley
    Publication Date: 2019
    detail.hit.zdb_id: 2151364-8
    detail.hit.zdb_id: 1108460-1
    SSG: 3,2
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