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journal of big data acceptance rate

2012;2(6):529–51. Agarwal A, Baechle C, Behara R, Zhu X. Unlike the existing works, this research made a niche by adapting the combined model to the technological domain. New York: Wiley; 2007. The Journal of Institutional Economics is devoted to the study of the nature, role and evolution of institutions in the economy, including firms, states, markets, money, households and other vital institutions and organisations. The definition of journal acceptance rate is the percentage of all articles submitted to IEEE Transactions on Big Data that was accepted for publication. The following section establishes the concept of OLC and its dimensions. Citation Impact 2.501 - Source Normalized Impact per Paper (SNIP) 0.925 - SCImago Journal Rank (SJR) 6.1 - CiteScore Usage 647,436 downloads 549 Altmetric mentions Google Scholar. 2008;9:1002–11. 2007;2:251–80. 3. , is the slope of tamPu of olcMcDic, olcSpDic, olcOeDic, and OlcTiDic at 0 (below average OLC), while β Computational power is also a critical point for big data analytics. In fact, big data is diverse and unstructured, therefore it requires special tools and techniques that go beyond traditional information system and relational databases solutions. The framed hypotheses are tested using multivariate regression with ordinary least square, i.e., linear regression estimation. Possible effect of IT introduction into the election process: a case study of Nigeria. Adv Comput Sci Int J. However, unstructured data is often difficult to convert to a format usable by supervised machine learning algorithms. In 2013, the same amount of data is created every 10 min. This research takes a step further and contributes to the field of technology acceptance with an expanded research model. PLoS ONE. Hospital Readmission Reductions Program formulas and probability of readmission are applied using four readmission scenarios to estimate the cost of readmission. 2017;PP(99):1–1. The factors F1 to F3 refer to the technology acceptance model (TAM) [9, 20] while factors F4 to F7 incorporate the dimensions of organizational learning capabilities (OLC) [21] into the independent variable. A leading journal selection tool is available free of charge for authors to find the best fit for their manuscript. Naïve Bayes classifiers are then used to assign a probability of readmission to each patient. Big data analytics is defined as technologies (database and data mining tools) and techniques (analytical methods) that a company can implement to analyse large scale, complex data for various applications intended to augment the performance of the firm in various dimensions. The sample size is the last column. Table 2 shows the parameters estimates for each item for the TAM. Pikkarainen T, Pikkarainen K, Karjaluoto H, Pahnila S. Consumer acceptance of online banking: an extension of the technology acceptance model. 1984;96(1):201–10. Organizational learning: the contributing processes and the literatures. However, binary classification systems often do not inherently offer this additional information. IEEE J Biomed Health Inform. S Nevertheless, less diffused and enforced systems and technologies, like big data analytics, still depend a lot on voluntary usage. Are enterprises ready for big data analytics? We hope that it will help authors navigate the journal submission process. 2016;72:72–82. Bottle A, Aylin P, Majeed A. Identifying patients at high risk of emergency hospital admissions: a logistic regression analysis. In fact, the proposed model is able to explain 44% of the technology acceptance of big data analytics, 5% more than the TAM alone. Multivariate analysis. Uwemi S, Khan HU, Fournier-Bonilla SD. The ability to compute massive quantity of information is the key feature of big data analytics. Swanson EB. in Software Engineering (12.53%). Hypothesis 3c: Managerial commitment positively moderates the relationship between perceived usefulness and intended usage of big data technologies. The limitations discussed in both the fields, academic and business, highlight significant prospects for future study. In fact, the proposed model is able to explain more variation of the technology acceptance of big data analytics than the TAM alone. Not surprisingly, the QJE, who desk rejects 62% of papers, is the fastest, with an average time of little more than two weeks. The Journal of Risk and Insurance (JRI) is the premier outlet for theoretical and empirical research on the topics of insurance economics and risk management.Research in the JRI informs practice, policy-making, and regulation in insurance markets as well as corporate and household risk management. Int J Bus Forecast Mark Intell. Mediation effect; 2014. Table 6 reports the means, standard deviations, and correlations of all variables used in this study. LACE, a popular readmission system, has been found to produce a c-statistic as low as 0.55 [7]. It is an expected outcome in the IT industry, because of the fast changing environment. Finally, the structural model is tested to confirm or reject proposed hypotheses [93, 94]. To test the hypotheses, a survey is designed for students of University of Liverpool Online in the following graduate programs pertaining to various disciplines of Masters in Science program. This study tests the reliability and validity of the constructs using confirmatory factor analysis (CFA). J Internet Commer. Table 4 depicts the number of respondents per program at the University of Liverpool Online (contCour). The study is primary data based and data is collected from the students belonging to the information technology programs at the University of Liverpool Online. Fishbein M. A theory of reasoned action: some applications and implications; 1979. Although LACE initially showed improvements over systems devised by Yale (c-statistic = 0.7), additional research has found this model to vary in quality when presented with differing hospitals. [16] also successfully used LR for predicting readmission using physical function, cognitive status, and psychosocial support. s Age Ageing. 2017;39(1):147–65. [6] reviewed many HRPS using c-statistic as the primary performance metric and few perform better than 0.7. It is worth mentioning that a general purpose computer needs more than three instructions to process a byte [52–54]. MIS Q. 2011. Co-Senior Editors: J. Efrim Boritz University of Waterloo, School of Accounting and Finance, Waterloo, Ontario, Canada P: 519.888.4567 E: Even though, any technology adoption presents a learning curve, the dimensions of OLC in technology adoption are often overlooked by the literature. A cost sensitive approach to predicting 30-day hospital readmission in COPD patients. While big data holds a lot of promise, it is not without its challenges. Khan HU, Adediji OA. in Information Systems and Management (36.8%) followed by M.Sc. Hypothesis 6a: Transfer and integration positively moderates the relationship between perceived ease of usage and intended usage of big data technologies. For the next dimension, openness and experimentation the hypotheses are. Correspondence to Information technology and organizational learning: a review and assessment of research. Ability and hurdle to provide Banking online services: a case study of banking employees in Nigeria, 2015 IEEE 2nd International conference on cyber security and cloud computing, New York, USA, 03–05 November 2015; 2015. 2017;25(2):256–77. Baechle, C., Agarwal, A. 2015;13(6):670–89. CiteScore: 8.6 ℹ CiteScore: 2019: 8.6 CiteScore measures the average citations received per peer-reviewed document published in this title. However, though TAM can explain a significant portion of system adoption, the framework does not account for human capabilities. 15 Ways To Beat Big Data in College Admissions (According To Those Who Make Admissions Decisions) Aviva Legatt Contributor Opinions expressed by … It is an expected result as the TAM framework has been largely tested with a variety of technologies [64], and it is not expected to have a different outcome. Typeform online survey and form builder; 2014. Lewis DD. Risk adjustment is the fraction of actual readmissions between [0,1] for which a hospital is responsible. OLC requires four conditions to work efficiently. ERR is defined as follows, Expected readmissions rate is the target readmissions rate which CMS has assigned a given hospital. System perspective refers to the understanding of organizational objectives and according to Jerez-Gomez et al. 4. The Center for Health Information and Analysis estimates unplanned readmissions to cost $26 billion annually [1]. Khan HU, Awan MA, Ho HC. This is because today organizations collect data from different sources, such as machine data, application logs, clickstream logs, whether data, emails, contracts, geographic information systems and geospatial data, survey data, reports, spreadsheets, and social media [41, 50]. The first baseline uses the NB classifier ignoring cost and performing traditional classification. Am J Manag Care. Big data solutions need different processing capabilities that are not present in traditional databases to process text, image, video, audio, geo-spatial data, etc. If ERR ≤ 0, no additional HRRP penalties are incurred and resources for preventing readmission can be diverted elsewhere. $$, $$ ERR = \frac{{\omega \left( {\frac{{R + \mathop \sum \nolimits_{i = 1}^{N} p_{r} }}{P + N}} \right)}}{\rho } - 1. 185.5 days from submission to acceptance 29 days from acceptance to publication. Methods. West J Nurs Res. The last regression aims to test the moderation Hypotheses 3a, 4a, 5a, 6a, 3c, 4c, 5c, and 6c. That is, data from different domains are virtually impossible to translate into a structured form [41]. Stratified tenfold cross validation is performed on all comparative methodologies. To avoid over fitting or misspecification, both regression and the Monte Carlo simulation controlled important variables such as company size, IT department’s size, investments in technology, etc. The moderation method is one of the most popular approaches to study the influence of external variables in a causal model [99]. Information technology in the maritime industry past, present and future: focus on lng carriers, 7th IEEE International advance computing conference, Hyderabad, India, 5–7 January 2017; 2017. The field of natural language processing (NLP) can often be of assistance in structuring natural language to a usable format. Compared to binary NB classification, MinCost significantly lowers net cost when all factors are taken into consideration (shown in Fig. Automated identification and predictive tools to help identify high-risk heart failure patients: Pilot evaluation. Inf Manag. The journal is edited by Kate Moles, Dawn Mannay, Tom Hall, Robin Smith and Book Reviews Editor Jaimie Lewis. Halabi AE, Hachem A, Al-Akhrass L, Artail H, Khan HU. Overall, respondents’ answers are positive in regards of their system perspective. MIS quarterly 2004;28:283–322. Springer Nature. Big data typically includes structured data, which is the organized information obtained from relational databases, spreadsheets and machines. The hypotheses formulated after the literature review and research model are tested using quantitative research methods with mathematical modelling and statistical analysis. According to Dumbill [51] some level of analysis is necessary during the data inbound in order to keep storages levels practical. : Princeton; 2013. The equation describing the OLS model to be estimated is. C R Phys. Khan HU, Ejike AC. Nwankpa J, Roumani Y. Before processing begins, patients must have readmission probability assigned using NB, then sorted by probability of readmission. Kwon O, Lee N, Shin B. As expected, the perceived usefulness (tamPu) and perceived ease of use (tamPeou) have a positive and significant relationship with the use and intended usage of big data analytics (tamUse), thus supporting Hypotheses 1 and 2. MIS Q. O’reilly Media. IBM commercial the road: intelligent data management and analytics; 2010. This system consists of a simple questionnaire to be completed by medical staff. 2016;0:1–6. 2016;6(10):e921. Boston: Addison Wesley; 2009. , is the change of slope for olcMcDic, olcSpDic, olcOeDic, and OlcTiDic at 1 (above average OLC). Apart from these, another component veracity is also identified. Marakas GM, O’brien JA. 2006;27:235–63. Inf Comput Secur Inf Comput Secur. Mayo clinical text analysis and knowledge extraction system (cTAKES): architecture, component evaluation and applications. An extension of the technology acceptance model in an ERP implementation environment. doi:10.1109/JBHI.2017.2684121. Schlögl C. Information and knowledge management: dimensions and approaches. N 1996;119(1):166–75. This aspect of the proposed model can be a source of attraction for applying this to other academic domains. If resources are available to send a home healthcare professional to a single patient, but there are two patients classified as potential readmissions, additional information is required. 2011;332:60–5. This shortcoming limits the use of a HRPS within a CDSS. New York: Guilford Press; 2005. This trend is independent of the trend documented by Ellison (2002) toward longer delays in the adjudication and revision process, and in fact has largely emerged in the decade since Ellison’s original investigation. 2015. The questionnaire is designed using Type form, online survey tool designed to collect data [90]. Kutner M, Neter J, Nachtsheim C, Li W. Applied statistical linear models. Journal information Editor-in-Chief. 2014;67:692–7. The second baseline method assumes to intervene on all patients using a home healthcare professional. 2012;1(3):81–8. About this journal. A technology acceptance model for empirically testing new end-user information systems: theory and results. These models are built once and may predict readmission for any patient at any hospital. Hospital discharge summaries are structured using clinical natural language processing techniques. Hosseinzadeh A, Izadi MT, Verma A, Precup D, Buckeridge DL. Additionally, intervening in only high-risk patients saved an average of 90.07% compared to providing all patients with costly aftercare. Fourth, the company must have an open mind to test new ideas and raise awareness for continuous learning and experimentation [82, 83]. Structured data is generally stored in a relational database and contains information such as demographics and ICD-9 or ICD-10 codes. AA made substantial contributions to the conception and design of this research as well as critically reviewing and interpreting results. Though many supervised machine learning algorithms have the ability to coerce classification distribution, the NB machine learning algorithm naturally produces posterior probabilities without coercion [19]. These models are applied on the construct, intended usage of big data and also the mediation effect of the OLC constructs is assessed. Followed by the M.Sc. Even though the four dimensions identify different aspects of OLC, they are closely related to each other. Data sources for readmission models can be categorized into structured and unstructured data [25]. MathSciNet  This system is considered to have poor discriminative ability, but has been popular with clinical staff due to its simplicity. Due to sampling methods, these costs are relative and meant to be compared with baseline methods. Das A, Khan HU. Volumes 1, 2, 3, and 4 SpringerOpen is proud to publish the Journal of Organization Design from Volume 5 onward. Bagozzi RP. According to Swanson [29], perceived ease of use and perceived usefulness are amongst important elements for users’ involvement in system implementation and information perspective. J Bus Res. Measuring the Natural Rates of Interest of OECD and BRICS Economies: A Time Varying Perspective Bin Wang, Yum K. Kwan In Press, Journal Pre-proof, Available online 29 November 2020 Although cost as a performance metric may offer a clear alternative to c-statistic, its use in HRPS has been limited. Each issue of the journal reaches over 8,000 academics, finance professionals, libraries, government and financial institutions around the world. 2015;65(2):89–96. Figure 1 shows the theoretical model for this study. Hassan IM, Khan HU, Zaitun R, Mardini G. Pedagogical potentials of IEEE 802.11 WLAN to higher educational institutions: a case study of Nigerian based University, IEEE 9th International conference on semantic computing (IEEE ICSC 2015), Anhaim, CA, USA, 7–9 Feb 2015; 2015. 1, p. 604–10. The raw scores of the factor scales are converted in summated scales by the arithmetic mean of the items of each construct. Vast majority of the respondents “somewhat agree”, “agree”, or “completely agree” with the statement of each question. However, data velocity not only challenges communication networks but also processing capabilities of a constant inflow of data streams [59]. This model examines the relationship of OLC dimensions over TAM. These penalties often exceed potential reimbursement and have motivated hospitals to work towards readmission reduction [3]. Askoul R, Khan HU, Madhavi Lalitha VV. Ejike AC, Khan HU, Fournier-Bonilla SD. 2012;41(6):784–9. 2005;58:715–25. As expected managerial commitment (olcMc) does have a positive and significant relationship with the use and intended usage of big data analytics (tamUse), thus supporting Hypothesis 4a. BMC Cardiovasc Disord. 1982;10:157–65. J Parallel Distrib Comput. Although simple methods have been found to be effective, the number of hospitals penalized for excess readmissions has held steady for several years [5]. The model reliability for each construct, measured by CR and AVE are also above the expected minimum (CR > 0.75; AVE > 0.60) [95]. Due to the direct effect on the revenues of the companies, especially in the telecom field, companies are seeking to develop means to predict potential customer to churn. 1986;51:1173–82. Khan HU, Bankole OA, Alomari MK. Hand DJ. Templeton GF, Lewis BR, Snyder CA. The data for this research consists of 1248 discharge summaries containing chronic obstructive pulmonary disease (COPD) as a primary diagnosis. Predicting early psychiatric readmission with natural language processing of narrative discharge summaries. Likewise, variance inflation factor (VIF) of centralized variables (shown with suffix Cent: tamUseCent, tamPuCent, and tamPuCent, in the output, Appendix E) are below the cut point proposed by Kutner et al. Dierkes M, Nonaka I, Child J, Antal AB. Springer Nature. 2014;4(1/2):5–17. are constrained to zero to test the Hypotheses 3b, 4b, 5b, and 6b. Thus, the model does not support Hypotheses 4b, 5b, and, 6b. Millions of Americans are admitted to hospitals each year. A critical review of the technology acceptance model. in Computer Security (15.21%) and M.Sc. Scientific Journal Selector (2018-2019), we collect latest information of SCI journals, include ISSN, h-index, CiteScore, online submission URL, research area, subject area, submission experience, etc. E-commerce, challenges, and developing countries, 2016 DSI Annual Meeting in Austin, TX, USA. Researchers have argued that c-statistic is often used inappropriately to measure the performance of classification systems [23]. s An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record data. System perspective (olcSp) does not provide significant moderation on the perceived usefulness (tamPu) but does provide a significant moderation effect on perceived ease of use (β = 0.59; p < 0.05), thus supporting Hypothesis 4a but not 4c. TAM has its origin in the theory of reasoned action [27] and the theory of planned behaviour [28]. Another contribution is the validation of measurement scales and the statistical analysis program. If resources are available to send a home healthcare professional to a single patient, but there are two patients classified as potential readmissions, additional information is required. To read the latest Editor Report, click the DOI link below: Alexander Kogan and Patrick Wheeler. This study provides relevant academic insights as it integrates two technology adoption frameworks to explain the adoption of big data analytics. Likewise, with the advent of diffusion of the internet, government entities, public companies, statistics bureaus, weather stations, financial institutions and many others have also made a significant contribution to the data that is publicly available for public consumption. The IEEE Big Data 2019 (regular paper acceptance rate: 18.7%) was held in Los Angeles, CA, Dec 9-12, 2019 with close to 1200 registered participants from 54 countries. Using the LACE index to predict hospital readmissions in congestive heart failure patients. Structured data is generally stored in a relational database and contains information such as demographics and ICD-9 or ICD-10 codes. Even when there is no significant mismatch in the data type, the static nature of relational database schemas is not suitable for a dynamic and exploratory environment ([51], p. 13). Unstructured data is dynamic information not made available in a fixed place, such as emails, texts and voicemails. 5, baseline classification selects many more patients than necessary for readmission intervention. s used SVM to predict readmission for intensive care patients, while Sushmita et al. Yousafzai SY, Foxall GR, Pallister JG. ), IT security, big data, cloud computing, etc. CiteScore values are based on citation counts in a range of four years (e.g., DOI: 2016;6(4):256–61. Computing. to β For example, all dimensions emphasize the engagement of executives, managers and employees in the knowledge creation. 1985;10(4):803–13. California Privacy Statement, The research model adapts and expands the original technology acceptance model (TAM) [9, 19, 20] by incorporating the dimensions of organisational learning capabilities (OLC) [21]. Daniel B. Structural equation models. A leading journal selection tool is available free of charge for authors to find the best fit for their manuscript.

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