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We demonstrate how complex fields, such as cybersecurity, have the need for a skilled workforce that continues to rapidly outpace supply from universities. IS researchers partnering with practitioners can use this research as an exemplar of a method to design, build, and evaluate these innovative co-curricular IS programs. Moreover, we find these co-curricular IS programs are essential to upskilling students, integrating training on the latest tools, systems, and processes in these rapidly evolving disciplines.",{"EN":201},"RQ Labs: A Cybersecurity Workforce Skills Development Framework",{"VOID":203},"[\"3267004356637752880\"]",{"VOID":205},"(ISC)2. (2021). A Resilient Cybersecurity Profession Charts the Path Forward, (ISC)2 Cybersecurity Workforce Study, 2021. (ISC)2.\nAddiscott, R., & Olyaei, S. (2021). Emerging Cybersecurity Leaders Are Needed Now to Sustain Security Program Effectiveness. Gartner, Inc.\nBaker, M. (2016). Striving for effective cyber workforce development. Software Engineering Institute, 1–26.\nBeuran, R., Chinen, K.-i., Tan, Y., & Shinoda, Y. (2016). Towards Effective Cybersecurity Education and Training. School of Information Science, Graduate School of Advanced Science and Technology. Japan Advanced Institute of Science and Technology.\nBureau of Labor Statistics. (2021). Occupational Outlook Handbook. (U.S. Department of Labor) Retrieved December 2021, from Information Security Analysts: https:\u002F\u002Fwww.bls.gov\u002Fooh\u002Fcomputer-and-information-technology\u002Finformation-security-analysts.htm\nBurg, D., Maddison, M., & Watson, R. (2021). Cybersecurity: How do you rise above the waves of a perfect storm? Retrieved December 2021, from EY Building a better working World: https:\u002F\u002Fwww.ey.com\u002Fen_us\u002Fcybersecurity\u002Fcybersecurity-how-do-you-rise-above-the-waves-of-a-perfect-storm\nCabaj, K., Domingos, D., & Respicio, A. (2018). Cybersecurity education: Evolution of the discipline and analysis of masters programs. Computers & Security, 75, 24–35.\nCaulkins, B. D., Badillo-Urquiola, K., Bockelman, P., & Leis, R. (2016). Cyber Workforce Development Using a Behavioral Cybersecurity Paradigm. 2016 International Conference on Cyber Conflict (CyCon U.S.) (pp. 21–23). Washington, DC: IEEE.\nConklin, W., Cline, R. E., & Roosa, T. (2014a). Re-engineering Cybersecurity Education in the US: An Analysis of the Critical Factors. 2014a Hawaii International Conference on System Science (pp. 2006–2014a). IEEE Computer Society.\nConklin, W., Cline, R., & Roosa, T. (2014b). Re-engineering Cybersecurity Education in the US: An Analysis of the Critical Factors. 47th Hawaii International Conference on System Science, 2006–2014b.\nDaniel, C., Mullarkey, M., Agrawal, M. (2022). RQ Labs: A Cybersecurity Workforce Talent Program Design. In: Krishnan, R., Rao, H.R., Sahay, S.K., Samtani, S., Zhao, Z. (eds) Secure Knowledge Management In The Artificial Intelligence Era. SKM 2021. Communications in Computer and Information Science, vol 1549. Springer, Cham.\nEndicott-Popovsky, B. E., & Popovsky, V. M. (2014). Application of Pedagogical Fundamentals for the Holistic Development of Cybersecurity Professionals. Cybersecurity Education, 5(1), 57–68.\nFurnell, S. (2021). The cybersecurity workforce and skills. Computers & Security, 100, 1–7.\nGonzalez-Manzano, L., & de Fuentes, J. M. (2019). Design recommendations for online cybersecurity courses. Computers & Security, 80, 238–256.\nHevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design Science in Information Systems Research. MIS Quarterly, 28(1), 75–105.\nISACA. (2019). State of Cybersecurity 2019, Part 1: Current Trends in Workforce Development. ISACA.\nISACA. (2020). State of Cybersecurity 2020, Part 1: Global Update on Workforce Efforts and Resources. ISACA.\nISACA. (2021). State of Cybersecurity 2021, Part 1: Global Update on Workforce Efforts, Resources and Budgets. ISACA.\nKatz, F. H. (2018). Breadth vs. Depth: Best Practices Teaching Cybersecurity in a Small Public University Sharing Models. The Cyber Defense Review, 3(2), 65–72.\nKnapp, K. J., Maurer, C., & Plachkinova, M. (2017). Maintaining a Cybersecurity Curriculum: Professional Certifications as Valuable Guidance. Journal of Information Systems Education, 28(2), 101–114.\nMorelli, K. (2018, October). USF\u002FReliaquest Partnership Aims to Fill the Talent Gap in the Emerging Cybersecurity Field. Retrieved December 2021, from USF Muma College of Business Newsroom Articles: https:\u002F\u002Fwww.usf.edu\u002Fbusiness\u002Fnews\u002Farticles\u002F181002-reliaquest-partnership.aspx\nMullarkey, M. T., & Hevner, A. R. (2019). An elaborated action design research process model. European Journal of Information Systems, 28(1), 6–20.\nMurphy, D. R., & Murphy, R. H. (2013). Teaching Cybersecurity: Protecting the Business Environment. Curriculum Development Conference 2013 (pp. 88–93). Kennesaw: ACM.\nNewhouse, W., Keith, S., Scribner, B., & Witte, G. (2017). National Initiative for Cybersecurity Education (NICE) Cybersecurity Workforce Framework. U.S. Department of Commerce. National Institute of Standards and Technology.\nPeterson, R., Santos, D., Smith, M. C., Wetzel, K. A., & Witte, G. (2020). Workforce Framework for Cybersecurity (NICE Framework). U.S. Department of Commerce. National Institute of Standards and Technology.\nSahay, S. K., Goel, N., Jadliwala, M., & Upadhyaya, S. (2021). Advances in Secure Knowledge Management in the Artificial Intelligence Era. Information Systems Frontiers, 23, 807–810.\nSein, M. K., Henfridsson, O., Purao, S., Rossi, M., & Lindgren, R. (2011). Action Design Research. MIS Quarterly, 35(1), 37–56.\nSpidalieri, F., & McArdle, J. (2016). Transforming the Next Generation of Military Leaders into Cyber-Strategic Leaders: The role of cybersecurity education in US service academies. The Cyber Defense Review\nSusman, G. I., & Evered, R. D. (1978). An assessment of the scientific merits of action research. Administrative science quarterly, 582-603\nTang, D., Pham, C., Ken-ichi, C., & Razvan, B. (2017). Interactive Cybersecurity Defense Training Inspired by Web-based Learning Theory. 2017 IEEE 9th International Conference on Engineering Education (ICEED) (pp. 90–95). IEEE.\nTang, C., Tucker, C., Servin, C., Geissler, M., Stange, M., Jones, N., …, Schmelz, P. (2020). Cybersecurity Curricular Guidance for Associate-Degree Programs. Association for Computing Machinery (ACM), Committee for Computing Education in Community Colleges (CCECC).\nWard, P. (2021). Constructing a Methodology for Developing a Cybersecurity Program. Proceedings of the 54th Hawaii International Conference on System Sciences (pp. 44–53). Honolulu, HI: University of Hawaii at Manoa, Hamilton Library.\nWilson, P. (2021). The Security Profession, 2020–2021. Chartered Institute of Information Security.",{"VOID":207},"10.1007\u002Fs10796-022-10332-y","PUBLICATION","VERIFIED","2024-06-24T17:38:11.033+00:00","Auto Verify","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10796-022-10332-y",[214,232,247],{"id":215,"sortIndex":23,"researcher":22,"roles":216,"affiliations":218,"properties":227,"displayName":229,"givenName":22,"familyName":22},"3f01b2b5-3bbb-409c-9a74-383102a71f29",[217],"AUTHOR",[219],{"id":220,"sortIndex":23,"affiliation":221,"properties":22},"1f594923-8db1-43c6-9f67-b6169f2fc61f",{"id":220,"createTime":22,"updateTime":22,"relativeEntities":222,"slug":22,"properties":223,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":226,"statistic":22},[],{"title":224},{"VI":225},"School of Information Systems and Management, University of South Florida, Tampa, USA",[],{"title":228,"gsAuthor":230},{"VI":229},"Clinton 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supply chains evolve beyond the confines of individual organizations, information sharing has become the holy grail in supply chain technology. Although the value of information sharing is well recognized, there is little research on how to use it to configure supply chains. This paper proposes a parameterized model to capture information sharing in a supply chain. By changing the parameters of this model, we actually adjust the degree of information sharing and create new supply chain configurations. Configurations are the means of responding to events or changes in supply chains in a timely manner. A complete example is used to demonstrate this methodology. We also perform simulation experiments to compare configurations and to understand the effect of information sharing on supply chain performance. Thus, we show how to achieve supply chain configurability by leveraging information sharing. A supply chain architecture which allows agility, adaptability and alignment of partner interests is also proposed based on this methodology.",{"EN":341},"Leveraging information sharing to configure supply chains",{"VOID":343},"[\"5893157112943297686\"]",{"VOID":345},"van der Aalst, W. M. P. (1999). Formalization and verification of event-driven process chains. Information and Software Technology, 41(10), 639–650.\nAngulo, A., Nachtmann, H., & Waller, M. (2004). Supply chain information sharing in a vendor managed inventory partnership. Journal of Business Logistics, 25(1), 101–116.\nBensaou, M., & Venkatraman, N. (1995). Configurations of interorganizational relationshops: a comparison between U.S. and Japanese automakers. Management Science, 41(9), 1471–1492.\nChen, F. (2003). Information sharing and supply chain coordination. In A. G. de Kok & S. C. Graves (Eds.), Handbooks in operations research and management science, Vol. 11, supply chain management: Design, coordination, and operation. Amsterdam: Elsevier.\nChopra, S., & Meindl, P. (2001). Supply chain management: Strategy, planning, and operations. Upper Saddle River: Prentice Hall.\nEDI ANSI X12. (1997). EDI V4 (004010), http:\u002F\u002Fwww.disa.org\u002Fbookstore\u002Fpublic\u002Findex.cfm\nFinley, F., & Srikanth, S. (2005). 7 Imperatives for successful collaboration. Supply Chain Management Review, 9, 30–37.\nFox, M. S., Barbuceanu, M., & Teigen, R. (2000). Agent-oriented supply chain management. The International Journal of Flexible Manufacturing Systems, 12(2–3), 165–188.\nGosain, S., Malhotra, A., & El Sawy, O. A. (2004). Coordinating for flexibility in e-business supply chains. Journal of Management Information Systems, 21(3), 7–45.\nHaeckel, S. H. (1999). Adaptive enterprise: Creating and Leading Sense-and-Respond Organizations. Boston: Harvard Business School Press.\nIBM Rational XDE. Version 2003.06.12. http:\u002F\u002Fwww-306.ibm.com\u002Fsoftware\u002Fawdtools\u002Fdeveloper\u002Frosexde\u002F\nKapoor, S., Bhattacharya, K., Buckley, S., Chowdhary, P., Ettl, M., Katircioglu, K., et al. (2005). A technical framework for sense-and-respond business management. IBM Systems Journal, 44(1), 5–24.\nKelton, D., Sadowski, R., & Sturrock, D. (2004). Simulation with Arena. 3rd edition, New York: Mc Graw Hill.\nLee, H. (2004). The triple-A supply chain. Harvard Business Review, 82, 102–112.\nLi, Z., Kumar, A., & Lim, Y. (2002). Supply chain modelling—a co-ordination approach. Integrated Manufacturing Systems, 13(8), 551–561.\nLiu, R., & Kumar, A. (2003). Leveraging Information Sharing to Increase Supply Chain Configurability. In Proceedings of International Conference on Information Systems (ICIS 2003), Seattle, pp. 523–536.\nLiu, R., Kumar, A., & Aalst, W. (2007). 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Available at http:\u002F\u002Fwww.w3.org\u002FTR\u002F2007\u002FREC-xquery-20070123\u002F.",{"VOID":347},"10.1007\u002Fs10796-009-9222-8","2024-06-25T02:05:06.628+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10796-009-9222-8",[351,368],{"id":352,"sortIndex":23,"researcher":22,"roles":353,"affiliations":354,"properties":363,"displayName":365,"givenName":22,"familyName":22},"5049f2c4-4b09-4a37-a135-b4b2ffeee08e",[217],[355],{"id":356,"sortIndex":23,"affiliation":357,"properties":22},"0da879f7-9b00-49a3-ba2c-49b65d04a147",{"id":356,"createTime":22,"updateTime":22,"relativeEntities":358,"slug":22,"properties":359,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":362,"statistic":22},[],{"title":360},{"VI":361},"IBM T.J. Watson Research Center, Hawthorne, USA",[],{"title":364,"gsAuthor":366},{"VI":365},"Rong Liu",{"VOID":367},"[\"Ty92mQgAAAAJ\"]",{"id":369,"sortIndex":141,"researcher":22,"roles":370,"affiliations":371,"properties":380,"displayName":382,"givenName":22,"familyName":22},"ae9614b1-382e-4de0-ba44-9b578622004f",[217],[372],{"id":373,"sortIndex":23,"affiliation":374,"properties":22},"e0ca174c-eba3-40a2-80e4-581879f48c82",{"id":373,"createTime":22,"updateTime":22,"relativeEntities":375,"slug":22,"properties":376,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":379,"statistic":22},[],{"title":377},{"VI":378},"Department of Supply Chain and Information Systems, Penn State University, University Park, USA",[],{"title":381,"gsAuthor":383},{"VI":382},"Akhil Kumar",{"VOID":384},"[\"KnrkzkEAAAAJ\"]",{"url":349,"publisher":386,"properties":440},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":387,"slug":10,"properties":388,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":392,"manageAffiliations":409,"indexDatabases":420,"url":22,"thumbnailPath":22,"statistic":435,"gsStatistic":22,"type":186,"analyzePriority":22},[],{"issn":389,"title":390,"eissn":391},{"VOID":15},{"EN":17},{"VOID":13},[393,397,401,405],{"id":26,"createTime":22,"updateTime":22,"relativeEntities":394,"label":395,"description":396,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":29},{},{"id":32,"createTime":22,"updateTime":22,"relativeEntities":398,"label":399,"description":400,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":35},{},{"id":38,"createTime":22,"updateTime":22,"relativeEntities":402,"label":403,"description":404,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":41},{},{"id":44,"createTime":22,"updateTime":22,"relativeEntities":406,"label":407,"description":408,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":47},{},[410,415],{"id":51,"createTime":22,"updateTime":22,"relativeEntities":411,"slug":22,"properties":412,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":414,"statistic":22},[],{"title":413},{"EN":55},[57],{"id":59,"createTime":22,"updateTime":22,"relativeEntities":416,"slug":22,"properties":417,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":419,"statistic":22},[],{"title":418},{"EN":63},[],[421,428],{"id":67,"indexDatabase":422,"url":78,"indexYears":79,"academicFieldIds":427,"indexDatabaseRanking":85},{"id":69,"createTime":22,"updateTime":22,"relativeEntities":423,"label":424,"description":425,"key":75,"publicationTags":426,"standard":22},[],{"EN":72,"VI":72},{"EN":72,"VI":74},[77],[81,82,83,84],{"id":87,"indexDatabase":429,"url":100,"indexYears":22,"academicFieldIds":434,"indexDatabaseRanking":22},{"id":89,"createTime":22,"updateTime":22,"relativeEntities":430,"label":431,"description":432,"key":96,"publicationTags":433,"standard":22},[],{"EN":92,"VI":92},{"EN":94,"VI":95},[98,99],[102],{"impactFactor":23,"impactFactorByYear":436,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":437,"totalCitation":139,"totalCitationByYear":438,"totalCitationPerPublication":162,"totalCitationPerPublicationByYear":439,"hindexLast5Year":185,"hindex":185},{"2012":105,"2013":106,"2014":107,"2015":108,"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"1999":121,"2000":122,"2001":123,"2002":123,"2003":124,"2004":125,"2005":122,"2006":126,"2007":124,"2008":127,"2009":128,"2010":129,"2011":130,"2012":131,"2013":132,"2014":129,"2015":127,"2016":133,"2017":118,"2018":127,"2019":134,"2020":135,"2021":136,"2022":137,"2023":134,"2024":138},{"2003":141,"2004":142,"2005":143,"2006":144,"2007":145,"2008":146,"2009":147,"2010":148,"2011":149,"2012":150,"2013":151,"2014":152,"2015":153,"2016":154,"2017":155,"2018":156,"2019":157,"2020":158,"2021":159,"2022":160,"2023":161,"2024":134},{"2003":164,"2004":165,"2005":166,"2006":167,"2007":168,"2008":169,"2009":170,"2010":109,"2011":171,"2012":172,"2013":173,"2014":174,"2015":175,"2016":176,"2017":177,"2018":178,"2019":179,"2020":180,"2021":181,"2022":182,"2023":183,"2024":184},{"pages":441,"volume":443},{"VOID":442},"139-151",{"VOID":444},"13",{"total":23,"publishYear":446,"statisticByYear":447},2009,{},"2009-10-20","DONE_ANALYZE_CITATION","2026-07-28T20:26:26.198+00:00",[85,98],{"id":453,"createTime":454,"updateTime":455,"relativeEntities":456,"slug":457,"properties":458,"entityType":208,"verifyStatus":209,"verifyTime":469,"verifyNote":211,"languages":22,"translateLanguages":22,"viewCount":23,"primaryUrl":470,"fullTextUrl":22,"authors":471,"publicationType":263,"publisherRelationship":529,"citationCount":23,"citationInfo":589,"publishDate":592,"publishYear":590,"citationAnalyzeStatus":449,"lastCitationAnalyze":593,"indexDatabases":594,"openAccess":22,"references":22,"isForceReanalyzing":330},"6f4a49b4-6384-403f-8166-082ecba7c7f7","2024-01-11T09:21:44.436+00:00","2026-07-25T21:58:15.759+00:00",[],"Breaking-the-Privacy-Kill-Chain-Protecting-Individual-and-Group-Privacy-Online",{"abstract":459,"title":461,"gsPaper":463,"references":465,"doi":467},{"EN":460},"Online social networks (OLSNs) are electronically-based social milieux where individuals gather virtually to socialize. The behavior and characteristics of these networks can provide evidence relevant for detecting and prosecuting policy violations, crimes, terrorist activities, subversive political movements, etc. Some existing methods and tools in the fields of business analytics and digital forensics are useful for such investigations. While the privacy rights of individuals are widely respected, the privacy rights of social groups are less well developed. In the current development of OLSNs and information technologies, the compromise of group privacy may lead to the violation of individual privacy. Adopting an explorative literature review, we examine the privacy kill chain that compromises group privacy as a means to compromise individual privacy. The latter is regulated, while the former is not. We show how the kill chain makes the need for protecting group privacy important and feasible from the perspectives of social, legal, ethical, commercial, and technical perspectives. 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Strategy and society: the link between competitive advantage and corporate social responsibility. Harvard Business Review, 84(12), 78–92.\nPosey, C., Lowry, P. B., Roberts, T. L., & Ellis, T. S. (2010). Proposing the online community self-disclosure model: the case of working professionals in France and the U.K. who use online communities. European Journal of Information Systems, 19(2), 181–195. https:\u002F\u002Fdoi.org\u002F10.1057\u002Fejis.2010.15.\nPosner, R. (1981). The economics of privacy. The American Economic Review, 71(2), 405–409.\nPost, R. C. (1989). The social foundations of privacy: community and self in the common law tort. California Law Review, 77(5), 957–1010.\nRastogi, V., Hay, M., Miklau, G., & Suciu, D. (2009). Relationship privacy: Output perturbation for queries with joins. In Proceedings of the twenty-eighth ACM SIGMOD-SIGACT-SIGART symposium on principles of database systems (pp. 107–116). ACM.\nRegan, P. M. (1995). Legislating privacy: Technology, social values, and public policy. Chapel Hill: Univ of North Carolina Pr.\nRosenblum, D. (2007). What anyone can know: the privacy risks of social networking sites. IEEE Security and Privacy, 5(3), 40–49.\nSarathy, R., & Robertson, C. J. (2003). Strategic and ethical considerations in managing digital privacy. Journal of Business Ethics, 46(2), 111–126.\nShapiro, B., & Baker, C. R. (2001). Information technology and the social construction of information privacy. Journal of Accounting and Public Policy, 20(4,5), 295–322.\nSilenzio, V. M. B., Duberstein, P. R., Tang, W., Lu, N., Tu, X., & Homan, C. M. (2009). Connecting the invisible dots: reaching lesbian, gay, and bisexual adolescents and young adults at risk for suicide through online social networks. Social Science & Medicine, 69(3), 469–474.\nSmith, H. J. (1994). Managing privacy: Information technology and corporate america. Chapel Hill: University of North Carolina Press.\nStigler, G. (1980). An introduction to privacy in economics and politics. The Journal of Legal Studies, 9(4), 623–644.\nSuchman, M. C. (1995). Managing legitimacy: strategic and institutional approaches. Academy of Management Review, 20(3), 571–610.\nTavani, H. T. (2007). Ethics and technology: Ethical issues in an age of information and communication technology. Hoboken: Wiley.\nTaylor, L. (2017). Safety in numbers? Group privacy and big data analytics in the developing world. In L. Taylor, L. Floridi, & B. van der Sloot (Eds.), Group privacy: New challenges of data technologies. Cham: Springer International.\nThomson, J. J. (1975). The right to privacy. Philosophy & Public Affairs, 4(4), 295–314.\nTow, W. N.-F. H., Dell, P., & Venable, J. (2010). Understanding information disclosure behaviour in Australian Facebook users. Journal of Information Technology, 25(2), 126–136. https:\u002F\u002Fdoi.org\u002F10.1057\u002Fjit.2010.18.\nUnited Nations (1948). Universal declaration of human rights. http:\u002F\u002Fwww.un.org\u002FOverview\u002Frights.html. Accessed 12 June 2005.\nVallor, S. (2012). Flourishing on facebook: virtue friendship & new social media. Ethics and Information Technology, 14(3), 185–199. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10676-010-9262-2.\nvan den Hoven, J., & Weckert, J. (Eds.). (2008). Information technology and moral philosophy. Cambridge: Cambridge University Press.\nVolokh, E. (2000). Personalization and privacy. Association for Computing Machinery. Communications of the ACM, 43(8), 84–88.\nWalsham, G. (1993). Ethical issues in information systems development: The analyst as moral agent. In Proceedings of the IFIP WG8. 2 working group on information systems development: human, social, and organizational aspects: human, organizational, and social dimensions of information systems development (pp. 281–294). North-Holland Publishing Co.\nWalsham, G. (2006). Doing interpretive research. European Journal of Information Systems, 15(3), 320–330.\nWarren, S. D., & Brandeis, L. D. (1890). The right to privacy. Harvard Law Review, 4(5), 193–220.\nXu, H., Dinev, T., Smith, H. J., & Hart, P. (2008). Examining the formation of individual’s privacy concerns: Toward an integrative view. Paper presented at the proceedings of international conference on information systems (ICIS), Paris.\nYang, T.-H., Ku, C.-Y., & Liu, M.-N. (2016). An integrated system for information security management with the unified framework. Journal of Risk Research, 19(1), 21–41.\nYoung, K. (2009). Online social networking: an Australian perspective. International Journal of Emerging Technologies & Society, 7(1), 39–57.\nYoung, S., Dutta, D., & Dommety, G. (2009). Extrapolating psychological insights from Facebook profiles: a study of religion and relationship status. Cyberpsychology & Behavior, 12(3), 347–350.\nZainudin, N. M., Merabti, M., & Llewellyn-Jones, D. (2011). A digital forensic investigation model and tool for online social networks. In 12th annual postgraduate symposium on convergence of telecommunications, networking and broadcasting (PGNet 2011) (pp. 27–28). Liverpool.\nZimmer, M. (2010). “But the data is already public”: on the ethics of research in Facebook. Ethics and Information Technology, 12(4), 313–325. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10676-010-9227-5.",{"VOID":468},"10.1007\u002Fs10796-018-9856-5","2024-08-31T00:32:12.380+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10796-018-9856-5",[472,489,514],{"id":473,"sortIndex":23,"researcher":22,"roles":474,"affiliations":475,"properties":484,"displayName":486,"givenName":22,"familyName":22},"6f3ee3a6-60a4-4962-83ac-ea1ca898847e",[217],[476],{"id":477,"sortIndex":23,"affiliation":478,"properties":22},"7239b368-880e-4346-8322-c96cd3323b3e",{"id":477,"createTime":22,"updateTime":22,"relativeEntities":479,"slug":22,"properties":480,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":483,"statistic":22},[],{"title":481},{"VI":482},"Department of Management Science and Information Systems, University of Massachusetts Boston, Boston, USA",[],{"title":485,"gsAuthor":487},{"VI":486},"Jongwoo Kim",{"VOID":488},"[\"rrX0F_cAAAAJ\"]",{"id":490,"sortIndex":141,"researcher":22,"roles":491,"affiliations":492,"properties":509,"displayName":511,"givenName":22,"familyName":22},"1c8606e6-eccc-4d34-956a-eec1d3cf3928",[217],[493,501],{"id":494,"sortIndex":23,"affiliation":495,"properties":22},"baeb9473-bafe-4c3c-8000-43d0f2ab9a1a",{"id":494,"createTime":22,"updateTime":22,"relativeEntities":496,"slug":22,"properties":497,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":500,"statistic":22},[],{"title":498},{"VI":499},"Department of Computer Information Systems, Georgia State University, Atlanta, USA",[],{"id":502,"sortIndex":141,"affiliation":503,"properties":22},"0b0f463e-9aa0-4a37-99a0-57aa918659ef",{"id":502,"createTime":22,"updateTime":22,"relativeEntities":504,"slug":22,"properties":505,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":508,"statistic":22},[],{"title":506},{"VI":507},"Curtin University, Bentley, Australia",[],{"title":510,"gsAuthor":512},{"VI":511},"Richard L. 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paper discusses the development of an enterprise domain model in an environment where part of the domain knowledge is vague and not yet formalised in company-wide business rules. The domain model was developed for a young company starting in the telecommunications sector. The company relied on a number of stand-alone business support systems and sought for a manner to integrate them. There was opted for the development of an enterprise-wide domain model that had to serve as an integration layer to coordinate the stand-alone applications. A specific feature of the company was that it could build up its information infrastructure form scratch, so that many aspects of its business were still in the process of being defined. The paper will highlight parts of the Enterprise Model where there was a need for co-designing business rules together with the domain model. A result of this whole effort was that the company got more insight into important domain knowledge and developed a common understanding across functional areas of the way of doing business.",{"EN":605},"Domain Modelling and the Co-Design of Business Rules in the Telecommunication Business Area",{"VOID":607},"[\"13497210012003213052\"]",{"VOID":609},"Booch G, Rumbaugh J, Jacobson I. The Unified Modeling Language User Guide. Reading, MA: Addison Wesley, 1999.\nColeman D, et al. Object-oriented development: The FUSION method, Prentice Hall, 1994.\nCook S, Daniels J. Designing Object Systems: Object-Oriented Modeling with Syntropy, New York: Prentice Hall, 1994.\nD'Souza DF, Wills AC. Objects, Components and Frameworks with UML, The Catalysis Approach. Reading, MA: Addison-Wesley, 1999:785.\nGalfione P, Galdiolo A, Valerio A, Cardino G. Exploiting enterprise knowledge through domain analysis and frameworks: An experimental work. Proceedings of the Eleventh InternationalWorkshop on Database and Expert Systems Application, DomE 2000, 4–8 September, Greenwich, London, UK, IEEE Computer Societey, 2000:813–822.\nLindstr¨om C. Lessons learned from applying business modelling: Exploring opportunities and avoiding pitfalls. In: Nilsson AG, Tolis C, Nellborn C, eds., Perspectives on Business Modelling, Understanding and Changing Organisations, Berlin: Springer-Verlag, 1999.\nNellborn C. Business and systems development: Opportunities for an integrated way of working. In: Nilsson AG, Tolis C, Nellborn C, eds., Perspectives on Business Modelling, Understanding and Changing Organisations, Berlin: Springer-Verlag, 1999.\nNilsson AG. The business developer's toolbox: Chains and alliances between established methods. In: Nilsson AG, Tolis C, Nellborn C, eds., Perspectives on Business Modelling, Understanding and Changing Organisations, Berlin: Springer-Verlag, 1999.\nSnoeck M, Dedene G. Existence Dependency: The key to semantic integrity between structural and behavioral aspects of object types. IEEE Transactions on Software Engineering 1998;24:233–251.\nSnoeck M, Dedene G, Verhelst M, Depuydt AM. Object-Oriented Enterprise Modeling with MERODE. Leuven University Press, 1999.\nSnoeck M, Poelmans S, Dedene G. A layered software specifi-cation architecture. In: Laendler AHF, Liddle SW, Storey VC, eds., Conceptual Modeling-ER2000, 19th International Conference on Conceptual Modeling, Salt Lake City, UTAH, USA, Lecture Notes In Computer Science, Vol. 1920, Berlin: Springer-Verlag, 2000:454–469.",{"VOID":611},"10.1023\u002FA:1019914823229","2024-05-09T15:18:38.157+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1023\u002FA:1019914823229",[615,632],{"id":616,"sortIndex":23,"researcher":22,"roles":617,"affiliations":618,"properties":627,"displayName":629,"givenName":22,"familyName":22},"a5faae81-81da-4697-bef9-3809a64f2e97",[217],[619],{"id":620,"sortIndex":23,"affiliation":621,"properties":22},"5f10f2b9-04a2-4924-a811-a7754921b699",{"id":620,"createTime":22,"updateTime":22,"relativeEntities":622,"slug":22,"properties":623,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":626,"statistic":22},[],{"title":624},{"VI":625},"K.U. Leuven, Management Information Systems Group, Leuven, Belgium",[],{"title":628,"gsAuthor":630},{"VI":629},"Monique Snoeck",{"VOID":631},"[\"d25wDdMAAAAJ\"]",{"id":633,"sortIndex":141,"researcher":22,"roles":634,"affiliations":635,"properties":642,"displayName":644,"givenName":22,"familyName":22},"e02262e8-02dc-41c6-8790-b196706418e7",[217],[636],{"id":620,"sortIndex":23,"affiliation":637,"properties":22},{"id":620,"createTime":22,"updateTime":22,"relativeEntities":638,"slug":22,"properties":639,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":641,"statistic":22},[],{"title":640},{"VI":625},[],{"title":643},{"VI":644},"Cindy 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is usually implemented using an intermediary organization or directly coordinated by solution seekers. For those using an IT-based crowdsourcing intermediary, the important factors of intermediaries that impact the crowdsourcing outcome are yet unclear. In addition, little research was conducted on how to design a crowdsourcing intermediary that can address the combined challenges of considering different cognitive demand levels of solution providers’ contributions, combining contributions and evaluating contributions. This paper identifies three important factors and provides a novel design of crowdsourcing intermediary to cope with these challenges. This study uses a case that focuses on how to assist small and medium businesses (SMBs) to develop their service imageries in triggering service innovation and designing their service experiences as to fulfill the desired outcomes of customers. Through the case, the benefits of our crowdsourcing intermediary design are demonstrated and justified. The three important factors are the crowdsourcing intermediary knowledge base, generative networks and empowerment of crowd members. This study shows that the crowdsourcing process can facilitate achieving a higher chance of attaining creative solutions for SMBs’ innovation problems when the three factors are well incorporated and managed within the crowdsourcing intermediary design. This study also presents a novel design of crowdsourcing intermediary that can address the combined challenges of coping with different cognitive demand levels of crowd members and combining and evaluating crowd members’ contributions, in order to attain impactful crowdsourcing outcome.",{"EN":723},"An impactful crowdsourcing intermediary design - a case of a service imagery crowdsourcing system",{"VOID":725},"[\"13315163388812176490\"]",{"VOID":727},"Aaker, D. A., & Biel, A. L. (Eds.) (2013). Brand equity & advertising: Advertising’s role in building strong brands. 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New York: The Modern Library.\nVerganti, R. (2009). Design driven innovation. Boston: Harvard Business School Press.\nWhitla, P. (2009). Crowdsourcing and its application in marketing activities. Contemporary Management Research, 5(1), 15–28.\nYang, C. Y., & Yuan, S. T. (2010). Color imagery for destination recommendation in regional tourism. The 14th Pacific Asia Conference on Information Systems, Taipei, Taiwan.\nZogaj, S., & Bretschneider, U. (2014). Analyzing governance mechanisms for crowdsourcing information systems: a multiple case analysis. Proceedings of the European Conference on Information Systems (ECIS) 2014, Tel Aviv, Israel, June 9–11, 2014.\nZogaj, S., Bretschneider, U., & Leimeister, J. M. (2014). Managing crowdsourced software testing: a case study based insight on the challenges of a crowdsourcing intermediary. Journal of Business Economics, 84(3), 375–405.",{"VOID":729},"10.1007\u002Fs10796-016-9700-8","2024-06-24T03:48:14.496+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10796-016-9700-8",[733,748],{"id":734,"sortIndex":23,"researcher":22,"roles":735,"affiliations":736,"properties":745,"displayName":747,"givenName":22,"familyName":22},"d9bc5b0f-1f8b-4715-9e56-445ca5cfc425",[217],[737],{"id":738,"sortIndex":23,"affiliation":739,"properties":22},"8e09d03d-e73d-4892-80d0-2927e961ef97",{"id":738,"createTime":22,"updateTime":22,"relativeEntities":740,"slug":22,"properties":741,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":744,"statistic":22},[],{"title":742},{"VI":743},"Department of Management Information Systems, National ChengChi University, Taipei City, Taiwan",[],{"title":746},{"VI":747},"Soe-Tsyr Daphne Yuan",{"id":749,"sortIndex":141,"researcher":22,"roles":750,"affiliations":751,"properties":758,"displayName":760,"givenName":22,"familyName":22},"0a1f48db-6dbe-4b36-bd1d-54b2fcaf85ef",[217],[752],{"id":738,"sortIndex":23,"affiliation":753,"properties":22},{"id":738,"createTime":22,"updateTime":22,"relativeEntities":754,"slug":22,"properties":755,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":757,"statistic":22},[],{"title":756},{"VI":743},[],{"title":759},{"VI":760},"Ching-Fang 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intelligence (AI) has increased the ability of organizations to accumulate tacit and explicit knowledge to inform management decision-making. Despite the hype and popularity of AI, there is a noticeable scarcity of research focusing on AI's potential role in enriching and augmenting organizational knowledge. This paper develops a recursive theory of knowledge augmentation in organizations (the KAM model) based on a synthesis of extant literature and a four-year revised canonical action research project. The project aimed to design and implement a human-centric AI (called Project) to solve the lack of integration of tacit and explicit knowledge in a scientific research center (SRC). To explore the patterns of knowledge augmentation in organizations, this study extends Nonaka's SECI (socialization, externalization, combination, and internalization) model by incorporating the human-in-the-loop Informed Artificial Intelligence (IAI) approach. The proposed design offers the possibility to integrate experts' intuition and domain knowledge in AI in an explainable way. The findings show that organizational knowledge can be augmented through a recursive process enabled by the design and implementation of human-in-the-loop IAI. The study has important implications for research and practice.",{"EN":837},"The Recursive Theory of Knowledge Augmentation: Integrating human intuition and knowledge in Artificial Intelligence to augment organizational knowledge",{"VOID":839},"[\"10934603207825260618\"]",{"VOID":841},"Alavi, M., & Leidner, D. E. (2001). Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly, 25, 107–136.\nAnderson, J. R. (1983). The Architecture of cognition. Harvard University Press.\nArrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S. A., Barbado, S., García, S., Gil-López, D. M., & Benjamins, R. (2020). Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities, and challenges toward responsible AI. Information Fusion, 58, 82–115.\nBailey, D. 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Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijinfomgt.2021.102383\nDavenport, T. H., & Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press.\nDavis, E., & Marcus, G. (2015). Common-sense reasoning and common-sense knowledge in artificial intelligence. Communications of the ACM, 58(9), 92–103.\nDavison, R., Martinsons, M. G., & Ou, C. X. J. (2012). The Roles of Theory in Canonical Action Research. MIS Quarterly, 36(3), 763–786.\nDavison., R.M., Martinsons., M. G., & Kock, N., (2004). Principles of canonical action research. Information Systems Journal, 14(1), 65-86.https:\u002F\u002Fdoi.org\u002F10.1111\u002FJ.1365-2575.2004.00162.X.\nDennehy, D., Griva, A., Pouloudi, N., Mäntymäki, M., & Pappas, I. (2022). Artificial intelligence for decision-making and the future of work. International Journal of Information Management. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijinfomgt.2022.102574\nDennehy, D., Griva, A., Pouloudi, N., Dwivedi, Y. K., Pappas, I., & Mäntymäki, M. (2021). Responsible AI and Analytics for an Ethical and Inclusive Digitized Society. In Proceedings of the 20th IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2021, Galway, Ireland, September 1–3, 2021 (vol. 12896). Lecture Notes in Computer Science. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-030-85447-8\nDewhurst, F. W., & Gwinnett, E. A. (1990). Artificial Intelligence and Decision Analysis. The Journal of the Operational Research Society, 41(8), 693–701.\nDuan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71.\nEnholm, I.M., Papagiannidis, E., Mikalef, Krogstie, J. (2021). Artificial Intelligence and Business Value: a Literature Review. Information Systems Frontiers.https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10796-021-10186-w.\nFaghmous, J. A., Banerjee, S. S., Steinbach, M., Kumar, V., Ganguly, A. R., & Samatova, N. (2014). Theory-Guided Data Science for Climate Change. Computer, 47(11), 74–78.\nFaraj, S., Pachidi, S., & Sayegh, K. (2018). Working and organizing in the age of the learning algorithm. Information and Organization, 28(1), 62–70.\nFossoWamba, S., & Queiroz, M. M. (2021). Responsible Artificial Intelligence as a Secret Ingredient for Digital Health: Bibliometric Analysis, Insights, and Research Directions. Information Systems Frontiers. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10796-021-10142-8\nFurman, J. L., & Teodoridis, F. (2019). Automation, research technology, and researchers’ trajectories: Evidence from computer science and electrical engineering. Organization Science, 31(2), 245–534.\nGrønsund, T., & Aanestad, M. (2020). Augmenting the algorithm: Emerging human-in-the-loop work configurations, The Journal of Strategic Information Systems, 29(2020), 101614.\nGu, J., Wang, Z., Kuen, J., Ma, L., Shahroudy, A., Shuai, B., Liu, T., Wang, X., Wang, G., Cai, J., & Chen, T. (2018). Recent advances in convolutional neural networks. Pattern Recognition, 77, 354–377.\nHaibe-Kains, B., Adam, G. A., Hosny, A., Khodakarami, F., Waldron, L., Wang, B., McIntosh, C., Goldenberg, A., Kundaje, A., Greene, C. S., Broderick, T., Hoffman, M. M., Leek, J. T., Korthauer, K., Huber, W., Brazma, A., Pineau, J., Tibshirani, R., Hastie, T., … Aerts, H. J. W. L. (2020). Transparency and reproducibility in artificial intelligence. Nature, 586(7829), E14–E16.\nHarfouche, A., Quinio, B., Skandrani, S., Marciniak, R. 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Innovation and knowledge creation: How are these concepts related? International Journal of Information Management, 26(4), 302–312. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ijinfomgt.2006.03.011",{"VOID":843},"10.1007\u002Fs10796-022-10352-8","2024-06-23T17:48:39.760+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10796-022-10352-8",[847,864,877,894],{"id":848,"sortIndex":23,"researcher":22,"roles":849,"affiliations":850,"properties":859,"displayName":861,"givenName":22,"familyName":22},"63de6774-90c0-48fb-b48a-bd23244b3a10",[217],[851],{"id":852,"sortIndex":23,"affiliation":853,"properties":22},"b3cbaf82-508d-406a-ad63-d7c66551d11b",{"id":852,"createTime":22,"updateTime":22,"relativeEntities":854,"slug":22,"properties":855,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":858,"statistic":22},[],{"title":856},{"EN":857},"Paris Nanterre University, Nanterre, France",[],{"title":860,"gsAuthor":862},{"VI":861},"Antoine 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objective of this study is to identify the financial statement fraud factors and rank the relative importance. First, this study reviews the previous studies to identify the possible fraud indicators. Expert questionnaires are distributed next. After questionnaires are collected, Lawshe’s approach is employed to eliminate these factors whose CVR (content validity ratio) values do not meet the criteria. Further, the remaining 32 factors are reviewed by experts to be the measurements suitable for the assessment of fraud detection. The Analytic Hierarchy Process (AHP) is utilized to determine the relative weights of the individual items. The result of AHP shows that the most important dimension is Pressure\u002FIncentive and the least one is Attitude\u002Frationalization. In addition, the top five important measurements are “Poor performance”, “The need for external financing”, “Financial distress”, “Insufficient board oversight”, and “Competition or market saturation”. The result provides a significant advantage to auditors and managers in enhancing the efficiency of fraud detection and critical evaluation.",{"EN":985},"Fraud detection using fraud triangle risk factors",{"VOID":987},"[\"14144257496098379910\"]",{"VOID":989},"Agrawal, C., Knoeber, R., & Tsoulouhas, T. (2006). Are outsiders handicapped in CEO successions? Journal of Corporate Finance, 12(3), 619–644.\nAnderson, R., & Reeb, D. (2003). Founding-family ownership and firm performance: evidence from the S&P 500. Journal of Finance, 58(3), 1301–1327.\nApostolou, B. A., Hassell, J. M., Webber, S. A., & Sumners, G. E. (2001). The relative importance of management fraud risk factors. Behavioral Research in Accounting, 13(1), 1–24.\nBeasley, M. S. (1996). An empirical analysis of the relation between the board of director composition and financial statement fraud. Accounting Review, 71(4), 443–465.\nBeaver, W. H. (1966). Financial ratios as predictors of failure. 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Accessed 18 Feb 2020.","http:\u002F\u002Fwww.bousai.go.jp\u002Ftaisaku\u002Fpdf\u002Fh3003kaitei.pdf",{},{"id":22,"text":1252,"url":1253,"identifiers":1254},"Crisis Mappers Japan. (2020). Crisis Mappers Japan. (in Japanese) Available at: http:\u002F\u002Fcrisismappers.jp\u002Fabout.html. Accessed 1 Apr 2021.","http:\u002F\u002Fcrisismappers.jp\u002Fabout.html",{},{"id":22,"text":1256,"url":22,"identifiers":1257},"Curran, K., Crumlish, J., & Fisher, G. (2012). OpenStreetMap. International Journal of Interactive Communication Systems and Technologies, 2(1), 69–78.",{},{"id":1259,"text":1260,"url":1261,"identifiers":1262},"4c68646b-0035-4279-8000-0006b275d4fa","Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009) ImageNet: A large-scale hierarchical image database. In Proc. 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Accessed 1 Apr 2021.","https:\u002F\u002Fwww.gsi.go.jp\u002Fgazochosa\u002Fgazochosa41006.html",{},{"id":1276,"text":1277,"url":1278,"identifiers":1279},"4852fecf-7053-44e3-8e0e-03491bb830f8","Girres, J.-F., & Touya, G. (2010). Quality assessment of the French OpenStreetMap dataset. Transactions in GIS, 14(4), 435–459.","https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002F10.1111\u002Fj.1467-9671.2010.01203.x",{"doi":1280},"10.1111\u002Fj.1467-9671.2010.01203.x",{"id":1259,"text":1282,"url":1261,"identifiers":1283},"He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 770–778).",{"doi":1263},{"id":1259,"text":1285,"url":1261,"identifiers":1286},"Hezaveh, M. M., Kanan, C., & Salvaggio, C. (2017). Roof damage assessment using deep learning, 2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR).",{"doi":1263},{"id":22,"text":1288,"url":22,"identifiers":1289},"Horie, K., Shigekawa, K., Maki, N., Tanaka, S., & Hayashi, H. (2005). Application of Damage Assessment Training System (DATS) to Ojiya City following the 2004 Niigata-ken Chuetsu Earthquake -through a disaster response support activity for issuing victim certificate- (in Japanese). Journal of Social Safety Science, 7, 123–132.",{},{"id":22,"text":1291,"url":22,"identifiers":1292},"Hu, J., Shen, L., & Sun, G. (2017). Squeeze-and-excitation networks. arXiv preprint arXiv:1709.01507.",{"arxiv":1293},"arXiv:1709.01507",{"id":22,"text":1295,"url":1296,"identifiers":1297},"IMAGENET Large Scale Visual Recognition Challenge. (2012). ImageNet large scale visual recognition competition 2012 (ILSVRC2012). Available at: http:\u002F\u002Fimage-net.org\u002Fchallenges\u002FLSVRC\u002F2012\u002Fresults.html. Accessed 1 Apr 2021.","http:\u002F\u002Fimage-net.org\u002Fchallenges\u002FLSVRC\u002F2012\u002Fresults.html",{},{"id":22,"text":1299,"url":22,"identifiers":1300},"Inoue, M., Suetomi, I., Fukuoka, J., Onishi, S., Numada, M., & Meguro, K. (2018). Development of estimation formula of disaster response-work volume based on the Kumamoto earthquake (in Japanese). Monthly Journal of the Institute of Industrial Science, University of Tokyo, 70(4), 289–297",{},{"id":1259,"text":1302,"url":1261,"identifiers":1303},"Ji, M., Liu, L., Du, R., & Buchroithner, M. F. (2019). A comparative study of texture and convolutional neural network features for detecting collapsed buildings after earthquakes using pre- and post-event satellite imagery. Remote Sensing, 11, 1202.",{"doi":1263},{"id":22,"text":1305,"url":22,"identifiers":1306},"Kamagatani, Y., & Matsuoka, M. (2017). Damaged building recognition of the 2016 Kumamoto earthquakes using deep learning with aerial photographs (in Japanese). Tono Research Institute of Earthquake Science “the report of Disaster Prevention Research Committee 2017”. pp. 49–57.",{},{"id":1259,"text":1308,"url":1261,"identifiers":1309},"Kashani, A. G., & Graettinger, A. J. (2015). Cluster-Based roof covering damage detection in ground-basedlidar data. Automation in Construction, 58, 19–27.",{"doi":1263},{"id":1311,"text":1312,"url":1313,"identifiers":1314},"f7fbd20b-5340-43e2-a0df-bd846bd7bcc5","Krizhevsky, A., Sutskever, I., Hinton, G. E. (2012). ImageNet classification with deep convolutional neural networks. Advances in Neural Information Processing Systems 25 (NIPS 2012).","https:\u002F\u002Fdl.acm.org\u002Fdoi\u002F10.1145\u002F3065386",{"doi":1315},"10.1145\u002F3065386",{"id":22,"text":1317,"url":22,"identifiers":1318},"Matsuoka, Y., Fujiu, M., Takayama, J., Nakayama, S., Suda, S., & Sakaguchi, H. (2017). Development of new hazard map after a disaster using unmanned aerial vehicle (in Japanese), 54th Research Presentation of Infrastructure Planning and Management.",{},{"id":22,"text":1320,"url":1321,"identifiers":1322},"Ministry of Internal Affairs and Communications. (2018). Study about the issue of damage certification in large scale earthquakes-focus on the 2016 Kumamoto Earthquake-. (in Japanese) Available at: https:\u002F\u002Fwww.soumu.go.jp\u002Fmain_content\u002F000528758.pdf. Accessed 1 Apr 2021.","https:\u002F\u002Fwww.soumu.go.jp\u002Fmain_content\u002F000528758.pdf",{},{"id":22,"text":1324,"url":22,"identifiers":1325},"Murakami, S., Hayashi, H., Tamura, K., Maki, N., Higashida, M., Horie, K., Hamamoto, R., & Komatsu, R. (2012). Analysis for effective operation of victim’s certificate -in case of 2012 Kyoto-fu Nanbu flood disaster (in Japanese). Journal of Social Safety Science, 23, 1–10.",{},{"id":22,"text":1327,"url":1328,"identifiers":1329},"National Network for Emergency Mapping. (2020). National Network for Emergency Mapping. (in Japanese) Available at: https:\u002F\u002Fwww.n2em.jp. Accessed 18 Feb 2020.","https:\u002F\u002Fwww.n2em.jp",{},{"id":1259,"text":1331,"url":1261,"identifiers":1332},"Nex, F., Duarte, D., Tonolo, F. G., & Kerle, N. (2019). Structural building damage detection with deep learning: assessment of a state-of-the-Art CNN in operational conditions. Remote Sensing, 11, 2765.",{"doi":1263},{"id":22,"text":1334,"url":22,"identifiers":1335},"Ogawa, N., & Yamazaki, F. (2000). Photo-interpretation of building damage due to earthquakes using aerialphotographs, Proceedings of the 12th World Conference on Earthquake Engineering.",{},{"id":22,"text":1337,"url":1338,"identifiers":1339},"Open Aerial Map. (2020). Open Aerial Map. Available at: https:\u002F\u002Fopenaerialmap.org. Accessed 1 Apr 2021.","https:\u002F\u002Fopenaerialmap.org",{},{"id":1341,"text":1342,"url":1343,"identifiers":1344},"8eff8776-27d4-4cb2-b657-40118e739712","Prechelt, L. (1998). Automatic early stopping using cross validation: quantifying the criteria. Neural Networks, 11(4), 761–767.","https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS0893608098000100",{"doi":1345},"10.1016\u002Fs0893-6080(98)00010-0",{"id":22,"text":1347,"url":22,"identifiers":1348},"Sharan, C., Woolley, C., Vandermersch, P., Cohen, J., & Tran, J. (2014). cuDNN: efficient primitives for deep learning, arXiv preprint, arXiv:1410.0759.",{"arxiv":1349},"arXiv:1410.0759",{"id":22,"text":1351,"url":22,"identifiers":1352},"Shimizu, S., Komaru, Y., Wakaura, M., Tokizane, Y., Nakamura, H., & Fujiwara, H. (2019). Fragility function of wooden house considering the roofing type (in Japanese). Journal of social safety science, 34 , 63–73.",{},{"id":1354,"text":1355,"url":1356,"identifiers":1357},"6c8e6c5c-53f3-4721-8e6f-059aae94b05e","Suppasri, A., Mas, E., Charvet, I., Gunasekera, R., Imai, K., Fukutani, Y., Abe, Y., & Imamura, F. (2013). Building damage characteristics based on surveyed data and fragility curves of the 2011 Great East Japan tsunami. Natural Hazards, 66(2), 319–341.","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11069-012-0487-8",{"doi":1358},"10.1007\u002Fs11069-012-0487-8",{"id":1259,"text":1360,"url":1261,"identifiers":1361},"Szegedy, C., Liu, W., Jia, Y., Sermanet, P., Reed, S., Anguelov, D., Erhan, D., Vanhoucke, V., & Rabinovich, A. (2015)Going deeper with convolutions. In CVPR.",{"doi":1263},{"id":22,"text":1363,"url":1364,"identifiers":1365},"Zeiler, M. D., & Fergus, R. (2014). Visualizing and understanding convolutional networks. ECCV. 818–833. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-319-10590-1_53.","https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-319-10590-1_53",{"mag":1366,"openalex":1367,"doi":1368},"1849277567","W1849277567","10.1007\u002F978-3-319-10590-1_53",{"id":1370,"createTime":1371,"updateTime":1372,"relativeEntities":1373,"slug":1374,"properties":1375,"entityType":208,"verifyStatus":209,"verifyTime":1386,"verifyNote":211,"languages":22,"translateLanguages":22,"viewCount":23,"primaryUrl":1387,"fullTextUrl":22,"authors":1388,"publicationType":263,"publisherRelationship":1406,"citationCount":1465,"citationInfo":1466,"publishDate":1469,"publishYear":1467,"citationAnalyzeStatus":449,"lastCitationAnalyze":1470,"indexDatabases":1471,"openAccess":22,"references":22,"isForceReanalyzing":330},"ba79e6b6-7b13-4eab-8124-bb6eea161329","2024-01-01T08:34:59.331+00:00","2026-07-17T16:47:11.272+00:00",[],"The-role-of-civil-society-groups-in-improving-access-to-the-DC-CAN",{"abstract":1376,"title":1378,"gsPaper":1380,"references":1382,"doi":1384},{"EN":1377},"This study addresses the role that civil society groups play in improving access to a high – profile middle mile network infrastructure project in Washington D.C, namely the District of Columbia - Community Access Network (DC-CAN). The District of Columbia (D.C.) received a grant through the American Recovery and Reinvestment Act’s Broadband Technology Opportunities Program to build and operationalize the DC-CAN. The District was one of the few cities to receive federal funding for broadband infrastructure. This paper utilizes a document\u002Ftextual analysis technique to study the efforts of the three main civil society groups to empower the city’s citizens to take greater agency over local broadband infrastructure. Moreover the article provides a theoretically grounded narrative that explains the role of these groups on behalf of the DC-CAN using Kingdon’s framework of multiple policy streams as a conceptual foundation.",{"EN":1379},"The role of civil society groups in improving access to the DC-CAN",{"VOID":1381},"[\"5466388097363015915\"]",{"VOID":1383},"Anderson, G., & Whalley, J. (2015). Public library internet access in areas of deprivation: the case of Glasgow. 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Accessed 15 January 2015.\nBroadband Bridge. (2011). Interim report of the broadband bridge to the internet society D.C. chapter. http:\u002F\u002Fwww.internetsociety.org\u002Fsites\u002Fdefault\u002Ffiles\u002FInterim%20Report_Broadband%20Bridge%20DC.pdf. Accessed 15 January 2015.\nCarothers, T. (1999). Civil society: think again. http:\u002F\u002Fcarnegieendowment.org\u002Fpdf\u002FCivilSociety.pdf. Accessed 4 May 2015.\nCherry, B. (2000). The irony of telecommunications deregulation: Assessing the role reversal in U.S. and E.U. policy. Vogelsang, I., & Compaine, B.M. (Eds.). The internet upheaval. Cambridge: MIT Press, 355–385.\nCohen, M. (2014). Why do D.C. residents pay the highest internet costs in the country? http:\u002F\u002Fdcist.com\u002F2014\u002F01\u002Fdc_residents_pay_the_highest_intern.php. Accessed 15 January 2015.\nCourt, J., Mendizabal, E., Osborne, D., and Young, J. (2006). Policy engagement how civil society Can be more effective. http:\u002F\u002Fwww.odi.org\u002Fsites\u002Fodi.org.uk\u002Ffiles\u002Fodi-assets\u002Fpublications-opinion-files\u002F200.pdf. Accessed 4 May 2015.\nCrawford, S., Connolly, J., Nally, M., and West, T. (2014). Community fiber in Washington, D.C., Seattle, WA, and San Francisco, CA: Developments and lessons learned. http:\u002F\u002Fcyber.law.harvard.edu\u002Fpublications\u002F2014\u002Fcommunity_fiber. Accessed 15 January 2015.\nDePillis, L. (2012). Meet the new-ish boss: chief technology officer Rob Mancini. http:\u002F\u002Fwww.washingtoncitypaper.com\u002Fblogs\u002Fhousingcomplex\u002F2012\u002F01\u002F11\u002Fmeet-the-new-ish-boss-chief-technology-officer-rob-mancini\u002F. Accessed 15 January 2015.\nDistrict of Columbia Government, Office of the Chief Technology Officer. (2013). Dc-can pricing guide. http:\u002F\u002Fdcnet.dc.gov\u002Fsites\u002Fdefault\u002Ffiles\u002Fdc\u002Fsites\u002Fdcnet\u002Fpublication\u002Fattachments\u002FDC- CAN_Pricing_Guide_v1.1.8b.pdf. Accessed 15 January 2015.\nDistrict of Columbia Government, Office of the Chief Technology Officer. (2012). Dc-can services contract – community anchor institution. http:\u002F\u002Fdcnet.dc.gov\u002Fsites\u002Fdefault\u002Ffiles\u002Fdc\u002Fsites\u002Fdcnet\u002Fpublication\u002Fattachments\u002FDC-CAN_CAI_Contract.pdf. Accessed 15 January 2015.\nDistrict of Columbia Government. (2010). Dc-can. http:\u002F\u002Fdcnet.dc.gov\u002Fpage\u002Fdc-can. Accessed 15 January 2015.\nEssia, U., & Yearoo, A. (2009). Strengthening civil society organizations\u002Fgovernment partnership in Nigeria. International NGO Journal, 4(9), 368–374.\nFrieden, R. (2013). Identifying best practices in financing next generation networks. The Information Society., 29(4), 234–247.\nFuentes-Bautista, M. (2014). Rethinking localism in the broadband era: a participatory community development approach. Government Information Quarterly, 31(1), 65–77.\nGalperin, H. (2004). Beyond interests, ideas and technology: an institutional approach to communication and information policy. The Information Society, 20(3), 159–168.\nGhaus-Pasha, A. (2004). The role of civil society organizations in governance. http:\u002F\u002Funpan1.un.org\u002Fintradoc\u002Fgroups\u002Fpublic\u002Fdocuments\u002Fun\u002Funpan019594.pdf. Accessed 4 May 2015.\nGonzalez, L. (2012). New videos from dc-net and dc-can highlights benefits all over the city. http:\u002F\u002Fmuninetworks.org\u002Fcontent\u002Fnew-videos-dc-net-and-dc-can-highlights-benenfits-all-over-city. Accessed 15 January 2015.\nGreeley, B. (2014). 10-year experiment in broadband investment has failed. Bloomberg Businessweek, http:\u002F\u002Fwww.businessweek.com\u002Farticles\u002F2014-02-20\u002Famericas-10-year-experiment-in-broadband-investment-has-failed. Accessed 15 January 2015.\nHasan, S. (2012). Why wireless mesh networks won’t save us from censorship. http:\u002F\u002Fsha.ddih.org\u002F2011\u002F11\u002F26\u002Fwhy-wireless-mesh-networks-wont-save-us-from-censorship\u002F. Accessed 15 January 2015.\nHsieh, J. J. P., Keil, M., Holmstrom, J., & Kvasny, L. (2012). The bumpy road to universal access: an actor-network analysis of a U.S. municipal broadband internet initiative. The Information Society, 28(4), 264–283.\nHudson, H.E. (2010). Municipal wireless broadband: lessons from san francisco and silicon Valley. Telematics and Informatics, 27(1), 1–9.\nJain, R. (2014). The Indian broadband plan: a review and implications for theory. Telecommunications Policy, 38(3), 278–290.\nKesharwani, A., & Bisht, S. S. (2012). The impact of trust and perceived risk on internet banking adoption in India: an extension of technology acceptance model. The International Journal of Bank Marketing, 30(4), 303–322.\nKhorasani, G., & Zeyun, L. (2014). Implementation of technology acceptance model (tam) in business research on web based learning system. International Journal of Innovative Technology and Exploring Engineering, 3(11), 112–116.\nKing, J., Gurbaxani, V., Kraemer, K., McFarlan, F., Raman, K., & Yap, C. (1994). Institutional factors in information technology innovation. Information Systems Research, 5, 139–169.\nKingdon, J. W. (2003). Agendas, Alternatives, and Public policies (Second ed., ). New York: Longman.\nKoebler, J. (2014). Hundreds of cities are wired with fiber—but telecom lobbying keeps it unused. Motherboard, http:\u002F\u002Fmotherboard.vice.com\u002Fread\u002Fhundreds-of-cities-are-wired-with-fiberbut-telecom-lobbying-keeps-it-unused. Accessed 15 January 2015.\nKovacs, A.-M. (2013). Telecommunications competition: the infrastructure-investment race, http:\u002F\u002Finternetinnovation.org\u002Fimages\u002Fmisc_content\u002Fstudy-telecommunications-competition-09072013.pdf. 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Journal of Information Policy, 4, 228–249.\nNational Telecommunications and Information Administration (2010a). Broadband USA connecting America’s communities: District of Columbia government, http:\u002F\u002Fwww2.ntia.doc.gov\u002Fgrantee\u002Fdistrict-of-columbia-government. Accessed 4 May 2015.\nNational Telecommunications and Information Administration (2010b). National broadband map: About> > technical overview> > assembling the data, http:\u002F\u002Fwww.broadbandmap.gov\u002Fabout\u002Ftechnical-overview\u002Fassembling-the-data. Accessed 4 May 2015.\nNational Telecommunications and Information Administration (2010c). Broadband USA connecting America’s communities: District of Columbia government, http:\u002F\u002Fwww2.ntia.doc.gov\u002Fgrantee\u002Fdistrict-of-columbia-government. Accessed 4 May 2015.\nNorth, D. (1990). Institutions, institutional change and economic performance. New York: Cambridge University Press.\nPowell, W., & DiMaggio, P. (Eds.) (1991). The new institutionalism in organizational analysis. Chicago: University of Chicago Press.\nRhea, P. (2012). Notes from broadband bridge community wireless meeting, sept. 25 2012, http:\u002F\u002Fprestonrhea.org\u002Fnotes-from-broadband-bridge-community-wireless-meeting-sept-25-2012\u002F. Accessed 15 january 2015\nRhea, P., and Breitbar, J. (2011). Washington dc broadband bridge gains momentum, http:\u002F\u002Fwww.isoc-dc.org\u002F2011\u002F03\u002Fwashington-dc-broadband-bridge-regains-momentum\u002F. Accessed 15 January 2015.\nRich, S. (2011). D.C. fiber network waiting for isps to join. Government Technology, http:\u002F\u002Fwww.govtech.com\u002Fwireless\u002FDC-Fiber-Network-Waiting-for-ISPs-to-Join.html?utm_source=related&utm_medium=direct&utm_campaign=DC-Fiber-Network-Waiting-for-ISPs-to-Join. Accessed 15 January 2015.\nRogers, E. (2003). Diffusion of innovation (5th ed., ). New York: Free Press.\nRoy, P.R. (2003), August 1. DC’s private telecommunications networks. HighBeam Research, http:\u002F\u002Fwww.highbeam.com\u002Fdoc\u002F1P3-412310751.html. Accessed 4 May 2015\nRusso, N., Morgus, R., Morris, S., & Kehl, D. (2014). The cost of connectivity, https:\u002F\u002Fstatic.newamerica.org\u002Fattachments\u002F229-the-cost-of-connectivity-2014\u002FOTI_The_Cost_of_Connectivity_2014.pdf. Accessed 4 May 2015.\nStrover, S., Waters, J., & Chapman, G. (2004). Beyond community networking and CTCs: access, development, and public policy. Telecommunications Policy, 28(7–8), 465–485.\nTeppayayon, O., & Bohlin, E. (2009). Government intervention: Why is competition not sufficient for broadband deployment? Paper presented at the 37th Research Conference on Communications. Information and Internet Policy.\nTroulos, C., & Maglaris, V. (2011). Factors determining municipal broadband strategies across Europe. Telecommunications Policy, 35(9–10), 842–856.\nVenkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.\nWiener, A. (2013). Fiber-optical illusion. http:\u002F\u002Fwww.washingtoncitypaper.com\u002Fblogs\u002Fhousingcomplex\u002F2013\u002F05\u002F01\u002Ffiber-optical-illusion\u002F. Accessed 15 January 2015.\nZorina, A., and Dutton, W.H. (2014). Building broadband infrastructure from the grassroots: The case of home lans in Belarus. Journal of Community Informatics, 10, 2, http:\u002F\u002Fci-journal.net\u002Findex.php\u002Fciej\u002Farticle\u002Fview\u002F949. Accessed 15 January 2015.",{"VOID":1385},"10.1007\u002Fs10796-015-9602-1","2024-05-27T16:50:51.969+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10796-015-9602-1",[1389],{"id":1390,"sortIndex":23,"researcher":22,"roles":1391,"affiliations":1392,"properties":1401,"displayName":1403,"givenName":22,"familyName":22},"88164f6f-fd52-4f28-be61-f7596219ed3c",[217],[1393],{"id":1394,"sortIndex":23,"affiliation":1395,"properties":22},"1ad32bef-900a-41b0-8594-b277129ff08d",{"id":1394,"createTime":22,"updateTime":22,"relativeEntities":1396,"slug":22,"properties":1397,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1400,"statistic":22},[],{"title":1398},{"VI":1399},"Washington, USA",[],{"title":1402,"gsAuthor":1404},{"VI":1403},"Siddhartha Menon",{"VOID":1405},"[\"i2HyCyYAAAAJ\"]",{"url":1387,"publisher":1407,"properties":1461},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1408,"slug":10,"properties":1409,"entityType":20,"verifyStatus":21,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":23,"subjectFields":1413,"manageAffiliations":1430,"indexDatabases":1441,"url":22,"thumbnailPath":22,"statistic":1456,"gsStatistic":22,"type":186,"analyzePriority":22},[],{"issn":1410,"title":1411,"eissn":1412},{"VOID":15},{"EN":17},{"VOID":13},[1414,1418,1422,1426],{"id":26,"createTime":22,"updateTime":22,"relativeEntities":1415,"label":1416,"description":1417,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":29},{},{"id":32,"createTime":22,"updateTime":22,"relativeEntities":1419,"label":1420,"description":1421,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":35},{},{"id":38,"createTime":22,"updateTime":22,"relativeEntities":1423,"label":1424,"description":1425,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":41},{},{"id":44,"createTime":22,"updateTime":22,"relativeEntities":1427,"label":1428,"description":1429,"parentId":22,"standard":22,"scholarHubFieldId":22},[],{"EN":47},{},[1431,1436],{"id":51,"createTime":22,"updateTime":22,"relativeEntities":1432,"slug":22,"properties":1433,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1435,"statistic":22},[],{"title":1434},{"EN":55},[57],{"id":59,"createTime":22,"updateTime":22,"relativeEntities":1437,"slug":22,"properties":1438,"entityType":22,"verifyStatus":22,"verifyTime":22,"verifyNote":22,"languages":22,"translateLanguages":22,"viewCount":22,"url":22,"parentIds":1440,"statistic":22},[],{"title":1439},{"EN":63},[],[1442,1449],{"id":67,"indexDatabase":1443,"url":78,"indexYears":79,"academicFieldIds":1448,"indexDatabaseRanking":85},{"id":69,"createTime":22,"updateTime":22,"relativeEntities":1444,"label":1445,"description":1446,"key":75,"publicationTags":1447,"standard":22},[],{"EN":72,"VI":72},{"EN":72,"VI":74},[77],[81,82,83,84],{"id":87,"indexDatabase":1450,"url":100,"indexYears":22,"academicFieldIds":1455,"indexDatabaseRanking":22},{"id":89,"createTime":22,"updateTime":22,"relativeEntities":1451,"label":1452,"description":1453,"key":96,"publicationTags":1454,"standard":22},[],{"EN":92,"VI":92},{"EN":94,"VI":95},[98,99],[102],{"impactFactor":23,"impactFactorByYear":1457,"i10Index":117,"i10IndexLast5Year":118,"totalPublication":119,"totalPublicationByYear":1458,"totalCitation":139,"totalCitationByYear":1459,"totalCitationPerPublication":162,"totalCitationPerPublicationByYear":1460,"hindexLast5Year":185,"hindex":185},{"2012":105,"2013":106,"2014":107,"2015":108,"2016":109,"2017":110,"2018":111,"2019":112,"2020":113,"2021":114,"2022":115,"2023":116},{"1999":121,"2000":122,"2001":123,"2002":123,"2003":124,"2004":125,"2005":122,"2006":126,"2007":124,"2008":127,"2009":128,"2010":129,"2011":130,"2012":131,"2013":132,"2014":129,"2015":127,"2016":133,"2017":118,"2018":127,"2019":134,"2020":135,"2021":136,"2022":137,"2023":134,"2024":138},{"2003":141,"2004":142,"2005":143,"2006":144,"2007":145,"2008":146,"2009":147,"2010":148,"2011":149,"2012":150,"2013":151,"2014":152,"2015":153,"2016":154,"2017":155,"2018":156,"2019":157,"2020":158,"2021":159,"2022":160,"2023":161,"2024":134},{"2003":164,"2004":165,"2005":166,"2006":167,"2007":168,"2008":169,"2009":170,"2010":109,"2011":171,"2012":172,"2013":173,"2014":174,"2015":175,"2016":176,"2017":177,"2018":178,"2019":179,"2020":180,"2021":181,"2022":182,"2023":183,"2024":184},{"pages":1462,"volume":1464},{"VOID":1463},"361-375",{"VOID":1118},10,{"total":1465,"publishYear":1467,"statisticByYear":1468},2015,{},"2015-10-14","2026-07-17T16:47:11.271+00:00",[85,98],{"id":1473,"createTime":1474,"updateTime":1475,"relativeEntities":1476,"slug":1477,"properties":1478,"entityType":208,"verifyStatus":209,"verifyTime":1489,"verifyNote":211,"languages":22,"translateLanguages":22,"viewCount":23,"primaryUrl":1490,"fullTextUrl":22,"authors":1491,"publicationType":263,"publisherRelationship":1524,"citationCount":23,"citationInfo":1582,"publishDate":1585,"publishYear":1583,"citationAnalyzeStatus":449,"lastCitationAnalyze":1586,"indexDatabases":1587,"openAccess":22,"references":22,"isForceReanalyzing":330},"a389290d-7aca-40fd-80fc-a4d16d0deef0","2024-01-10T16:19:40.819+00:00","2026-07-17T01:54:02.013+00:00",[],"ICT-Gender-Inequality-and-Income-Inequality-A-Panel-Data-Analysis-Across-Countries",{"abstract":1479,"title":1481,"gsPaper":1483,"references":1485,"doi":1487},{"EN":1480},"ICT has been long recognized as a driver of sustainable development goals (SDGs). This study examines the relationship between ICT, gender (in)equality (SDG 5), and income inequality (SDG 10). We conceptualize ICT as an institutional actor and use the Capabilities Approach to theorize the relationships between ICT, gender inequality and income inequality. This study uses publicly available archival data to conduct a cross-lagged panel analysis of 86 countries from 2013 to 2016. The key contributions of the study include the establishment of the relationship between (a) ICT and gender inequality and (b) gender inequality and income inequality. We also make methodological contributions to the field by employing cross-lagged panel data analysis to further our understanding of the links between ICT, gender equality, and income inequality over time. Our findings have implications for both research and practice, which are discussed.",{"EN":1482},"ICT, Gender Inequality, and Income Inequality: A Panel Data Analysis Across Countries",{"VOID":1484},"[\"13490659786168663667\"]",{"VOID":1486},"Akande, A., Cabral, P., & Casteleyn, S. (2019). Assessing the gap between technology and the environmental sustainability of European cities. Information Systems Frontiers, 21(3), 581–604. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10796-019-09903-3\nAker, J. C., & Mbiti, I. M. (2010). Mobile phones and economic development in Africa. Journal of Economic Perspectives, 24(3), 207–232. https:\u002F\u002Fdoi.org\u002F10.1257\u002Fjep.24.3.207\nAmeen, N., Madichie, N. O., & Anand, A. (2021). Between handholding and hand-held devices: Marketing through smartphone innovation and women’s entrepreneurship in post conflict economies in times of crisis. Information Systems Frontiers. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10796-021-10198-6\nAndres, A. R., Amavilah, V. H. S., & Asongu, S. A. (2016). Linkages between formal institutions, ICT adoption and inclusive human development in Sub Saharan Africa. SSRN Electronic Journal. https:\u002F\u002Fdoi.org\u002F10.2139\u002Fssrn.2822104\nAntonelli, C., & Gehringer, A. (2017). Technological change, rent and income inequalities: A Schumpeterian approach. Technological Forecasting and Social Change, 115, 85–98. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.techfore.2016.09.023\nAnyanwu, J. C., & Augustine, D. (2013). Gender Equality in employment in Africa: Empirical analysis and policy implications. African Development Review, 25(4), 400–420. https:\u002F\u002Fdoi.org\u002F10.1111\u002F1467-8268.12038\nAsongu, S. A., Orim, S.-M.I., & Nting, R. T. (2019). Inequality, information technology and inclusive education in sub-Saharan Africa. Technological Forecasting and Social Change, 146, 380–389. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.techfore.2019.06.006\nAsteriou, D., Dimelis, S., & Moudatsou, A. (2014). Globalization and income inequality: A panel data econometric approach for the EU27 countries. Economic Modelling, 36, 592–599. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.econmod.2013.09.051\nAvgerou, C. (2003). IT as an Institutional Actor in Developing Countries. The Digital Challenge: Information Technology in the Development Context, 46–62.\nAvgerou, C. (2010). Discourses on ICT and development. Information Technologies and International Development, 6(3), 1–18.\nBagozzi, R. P., & Cha, J. (1997). Partial least squares. In Advanced methods of marketing research (1. publ., Repr, pp. 52–78). Blackwell.\nBaller, S., Dutta, S., & Lanvin, B. (2016). The Global Information Technology Report 2016: Innovating in the Digital Economy. https:\u002F\u002Fwww.deslibris.ca\u002FID\u002F10090686. 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