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Journal of Business and Management Sciences. 2016, 4(5), 113-124
DOI: 10.12691/JBMS-4-5-2
Original Research

Reconnaissance of University Student Sentiments towards the MIS Services

Las Johansen B. Caluza1,

1Leyte Normal University

Pub. Date: November 14, 2016

Cite this paper

Las Johansen B. Caluza. Reconnaissance of University Student Sentiments towards the MIS Services. Journal of Business and Management Sciences. 2016; 4(5):113-124. doi: 10.12691/JBMS-4-5-2

Abstract

A pragmatic understanding of a student campus life relative to the services given by the university where the Management Information Systems play a vital part in keeping all offices going during the enrollment period. Sentiments of the 173 First Year BSIT Students were carefully analyzed through text mining employing the phenomenological design in order to understand their lived experiences transacting the office. Sentiment analysis was employed using different tools such as r-programming for generating a word cloud, word association, word frequencies, word frequency graph, word tree, and phrase net. The views of the respondents revealed a negative impressions and experiences when transacting the office, which confirms the Service Gap Model theory applied in the research. These were the lack of personnels and windows to transact due to slow processing resulting to a long queue of students during the enrollment period. As a result, service is a factor to a successful management in the corporate world whether in the government institutions or business industrial institutions. Eventually, these imply the need to deliver a more systematic and easy transaction in the agency.

Keywords

text analytics, sentiments, pragmatic, exploratory data analysis, qualitative research, phenomenology research design, social science, Philippines

Copyright

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]  Ackermann, F., & Eden, C. (2011). Strategic management of stakeholders: theory and practice. Long range planning, 44(3), 179-196.
 
[2]  Amtrup, J. W., Heine, H., & Jost, U. (2013). What's in a word graph evaluation and enhancement of word lattices.
 
[3]  Antoch, J. (2008). Environment for statistical computing. Computer Science Review, 2(2), 113-122.
 
[4]  Baayen, R. H. (2001). Word frequency distributions (Vol. 18). Springer Science & Business Media.
 
[5]  Bitner, M. J., Zeithaml, V. A., & Gremler, D. D. (2010). Technology’s impact on the gaps model of service quality. In Handbook of service science (pp. 197-218). Springer US.
 
[6]  Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior research methods, 41(4), 977-990.
 
[7]  Conrath, D. W., & Mignen, O. P. (1990). What is being done to measure user satisfaction with EDP/MIS. Information & Management, 19(1), 7-19.
 
[8]  Cui, W., Wu, Y., Liu, S., Wei, F., Zhou, M. X., & Qu, H. (2010, March). Context preserving dynamic word cloud visualization. In Pacific Visualization Symposium (PacificVis), 2010 IEEE (pp. 121-128). IEEE.
 
[9]  Feldman, R., & Sanger, J. (2007). The text mining handbook: advanced approaches in analyzing unstructured data. Cambridge University Press.
 
[10]  Glanzer, M. (1962). Grammatical category: A rote learning and word association analysis. Journal of verbal learning and verbal behavior, 1(1), 31-41.
 
[11]  Grover, V., Cheon, M. J., & Teng, J. T. (1994). A descriptive study on the outsourcing of information systems functions. Information & Management, 27(1), 33-44.
 
[12]  He, Q. (1999). Knowledge Discovery Through Co-Word Analysis. Library trends, 48(1), 133-59.
 
[13]  Henderson, S. (2015). Phrase Net. Retrieved from http://betterevaluation.org/taxonomy/term/573
 
[14]  Hofmann, M., & Chisholm, A. (2015). Text Mining and Visualization: Case Studies Using Open-Source Tools. CRC Press. Business & Economics.
 
[15]  Jawahar, I. M., & McLaughlin, G. L. (2001). Toward a descriptive stakeholder theory: An organizational life cycle approach. Academy of management review, 26(3), 397-414.
 
[16]  Keyword-In-Context. Thesaurus. Retrieved from http://dictionary.reference.com/browse/keyword-in-context?s=t.
 
[17]  Kuppens, P., Tuerlinckx, F., Russell, J. A., & Barrett, L. F. (2013). The relation between valence and arousal in subjective experience. Psychological Bulletin, 139(4), 917.
 
[18]  Landauer, T. K., Foltz, P. W., & Laham, D. (1998). An introduction to latent semantic analysis. Discourse processes, 25(2-3), 259-284.
 
[19]  Mahmood, M. A., Burn, J. M., Gemoets, L. A., & Jacquez, C. (2000). Variables affecting information technology end-user satisfaction: a meta-analysis of the empirical literature. International Journal of Human-Computer Studies, 52(4), 751-771.
 
[20]  Mineo, A. M., & Pontillo, A. (2006). Using R via PHP for Teaching Purposes: R-php. Journal of Statistical Software, 17(4), 1-20.
 
[21]  Monitoring Emotions. (2013). Monitoring Emotions-Valence VS Arousal. The Thinking Zygote. Retrieved from http://www.thinkingzygote.com/2013/06/monitoring-emotions-valence-vs-arousal.html.
 
[22]  Murphy, C. (2013). Term Frequency Analysis. Retrieved from https://www.revinate.com/blog/2013/08/tfa/
 
[23]  Nelson, D. L., McEvoy, C. L., & Schreiber, T. A. (2004). The University of South Florida free association, rhyme, and word fragment norms. Behavior Research Methods, Instruments, & Computers, 36(3), 402-407.
 
[24]  Oatley, K., Keltner, D., & Jenkins, J. M. (2006). Understanding emotions. Blackwell publishing.
 
[25]  Omer, A. (2012). What are the roles of MIS in the fields of Education? Researchgate. Retrieve from https://www.researchgate.net/post/What_are_the_roles_of_MIS_in_the_fields_of_education.
 
[26]  Open Learning World. (2011). Role of the Management Information System. Retrieved from http://www.openlearningworld.com/books/Fundamentals%20of%20MIS/Introduction%20to%20 Management%20Information%20Systems/Role%20of%20the%20Management%20information%20 system.html.
 
[27]  Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis.Foundations and trends in information retrieval, 2(1-2), 1-135.
 
[28]  Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. The Journal of Marketing, 41-50.
 
[29]  R-programming. (nd). What is R? Retrieved from https://www.r-project.org/about.html
 
[30]  Rouse, M. (2013). Text mining (text analytics) definition. TechTarget. Retrieved from http://searchbusinessanalytics.techtarget.com/definition/text-mining.
 
[31]  Sakthivel, RS. (2014). Role Impact and Importance of MIS. Retrieved from https://www.linkedin.com/pulse/20140901121616-270946654-role-impact-and-importance-of-mis.
 
[32]  Service [Def. 1]. (n.d.). Merriam-Webster Online. In Merriam-Webster. Retrieved 11/25/2015, from http://www.merriam-webster.com/dictionary/service.
 
[33]  Shah, M. (2014). Impact of management information systems (MIS) on school administration: What the literature says. Procedia-Social and Behavioral Sciences, 116, 2799-2804.
 
[34]  Sinclair, S. and G. Rockwell (2015). Cirrus. Voyant. Retrieved November 25, 2015 from http://voyant-tools.org/tool/Cirrus/.
 
[35]  Sinclair, S. and G. Rockwell (2015). Collocate Clusters. Voyant. Retrieved 11/24/2015 from http://voyant-tools.org/tool/Links/.
 
[36]  Stebbins, R. A. (2001). Exploratory research in the social sciences (Vol. 48). Sage.
 
[37]  Text Mining. (2015). Text Mining. Statistics. Retreived from http://documents.software.dell.com/Statistics/Textbook/Text-Mining.
 
[38]  Thaicharoen, S. (2009). Text association mining with cross-sentence inference, structure-based document model and multi-relational text mining. ProQuest.
 
[39]  Thong, J. Y., & Yap, C. S. (1996). Information systems effectiveness: A user satisfaction approach. Information Processing & Management, 32(5), 601-610.
 
[40]  Visa, A. (2001). Technology of text mining. In Machine Learning and Data Mining in Pattern Recognition (pp. 1-11). Springer Berlin Heidelberg.
 
[41]  Wattenberg, M., & Viégas, F. B. (2008). The word tree, an interactive visual concordance. Visualization and Computer Graphics, IEEE Transactions on, 14(6), 1221-1228.
 
[42]  Western Washington University. (nd). Management Information Systems Concentration. Retrieved from http://cbe.wwu.edu/dsci/management-information-systems.shtml.
 
[43]  Word Cloud. (2015). Word Cloud. Retrieved from http://betterevaluation.org/evaluation-options/wordcloud.
 
[44]  Ye, F., Xiong, J., & Xu, L. (2013). A Text Association Rules Mining Method Based on Concept Algebra. In Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing (pp. 2153-2158). IEEE.
 
[45]  Zhang, S., Huang, Q., Lu, Y., Wen, G., & Tian, Q. (2010). Building pair-wise visual word tree for efficent image re-ranking. In Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on(pp. 794-797). IEEE.