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Examining the impacts of mental workload and task-technology fit on user acceptance of the social media search system

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Abstract

Information overload has been an important issue in today’s big data era where a huge amount of unstructured user-generated content in different languages is being created on the Web in every minute. Social media search systems could help with it by effectively and efficiently collecting, storing, organizing and presenting user-generated content across the Web in an organized and timely manner. However, little research has been done to examine factors that could influence user acceptance on this new type of systems. To address it, this study develops a research model by integrating Mental Workload (MWL), Task-Technology Fit (TTF), and the unified theory of acceptance and use of technology (UTAUT). The model is tested on a security-related social media search system. The results indicate that both MWL and TTF can significantly influence user acceptance. We also operationalize the multi-dimensional latent construct of MWL by developing survey-based measurement items for different dimensions.

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Notes

  1. There are generally two ways to measure MWL, including objective and subjective measures. In this study (please see details in Section 4.3), we used the subjective measure by creating measurement items based on NASA-TLX and asking users to provide self-assessment on those items. Therefore, the MWL concept used in this study is about the perception, which is consistent with all other constructs in the proposed research model.

  2. We used the past tense for EE and PE based on the rationale that participated had already used the system before working on the questionnaire, and their ratings on the related measures were based on this prior system usage experience. As to BI, SI, and FC, they are constructs that are not directly related to participants’ prior system usage behavior, but about their general perceptions and feelings. We understand that this is not consistent with the original UTAUT paper, in which all measurement items are in the present tense, and we acknowledge that it might be a potential limitation.

  3. We acknowledge that some correlation values are closer, and this could be a potential limitation of the study. However, as mentioned in the main text, they did not exceed the general guideline.

References

  • Artino, A. R. (2008). Cognitive load theory and the role of learner experience: an abbreviated review for educational practitioners. Association for the Advancement of Computing in Education Journal, 16(4), 425–439.

    Google Scholar 

  • Au, N., Ngai, E., & Cheng, T. (2008). Extending the understanding of end user information systems satisfaction formation: an equitable needs fulfillment model approach. MIS Quarterly, 32(1), 43–66.

    Google Scholar 

  • Averty, P., Collet, C., Dittmar, A., & Athenes, S. (2004). Mental workload in air traffic control: an index constructed from field tests. Aviation, Space, and Environmental Medicine, 75(4), 333–341.

    Google Scholar 

  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Academy of Marketing Science, 16(1), 74–94.

    Google Scholar 

  • Battiste, V., & Bortolussi, M. Transport pilot workload-a comparison between two subjective techniques. In Proceedings of the human factors and ergonomics society 32nd annual meeting Santa Monica, CA, 1988 (pp. 150–154). Human Factors & Ergonomics Society.

  • Baur, A. W. (2016). Harnessing the social web to enhance insights into people's opinions in business, government and public administration. Information Systems Frontiers. https://doi.org/10.1007/s10796-016-9681-7.

  • Bayrak, T. Performance metrics for disaster monitoring systems. In B. Van de Walle, P. Burghardt, & C. Nieuwenhuis (Eds.), Intelligent human computer systems for crisis response and management (ISCRAM 2007), Delft, the Netherlands, 2007 (pp. 125–132).

  • Bertram, D. A., Opila, D. A., Brown, J. L., Gallagher, S. J., Schifeling, R. W., Snow, I. S., et al. (1992). Measuring physician mental workload: reliability and validity assessment of a brief instrument. Medical Care, 30(2), 95–104.

    Google Scholar 

  • Boontarig, W., Chutimaskul, W., Chongsuphajaisiddhi, V., & Papasratorn, B. Factors influencing the Thai elderly intention to use smartphone for e-health services. In 2012 IEEE symposium on humanities, science and engineering research, Kuala Lumpur, Malaysia, 2012 (pp. 479–483). IEEE.

  • Brown, S. A., Dennis, A. R., & Venkatesh, V. (2010). Predicting collaboration technology use: integrating technology adoption and collaboration research. Journal of Management Information Systems, 27(2), 9–53.

    Google Scholar 

  • Cain, B. (2007). A review of the mental workload literature. Virtual environments for intuitive human-system interaction – human factors considerations in the design, use, and evaluation of AMVE-technology, Final Report of Task Group TR-HFM-121 (pp. 4:1–34). NATO Research and Technology Organisation.

  • Cao, G., Wang, S., Hwang, M., Padmanabhan, A., Zhang, Z., & Soltani, K. (2015). A scalable framework for spatiotemporal analysis of location-based social media data. Computers, Environment and Urban Systems, 51, 70–82.

    Google Scholar 

  • Cegarra, J., & Chevalier, A. (2008). The use of tholos software for combining measures of mental workload: toward theoretical and methodological improvements. Behavior Research Methods, 40(4), 988–1000.

    Google Scholar 

  • Chen, N., Guimbretière, F., Sun, L., Czerwinski, M., Pangaro, G., & Bathiche, S. (2009). Hardware support for navigating large digital documents. International Journal of Human Computer Interaction, 25(3), 199–219.

    Google Scholar 

  • Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: from big data to big impact. MIS Quarterly, 36(4), 1165–1188.

    Google Scholar 

  • Chin, W. W. (1998). Issues and opinions on structural equation modeling. MIS Quarterly, 22(1), 7–16.

    Google Scholar 

  • Christiansson, P., & Svidt, K. Usability evaluation of mobile ICT support used at the building construction site. In World Conference on IT in Design and Construction, New Delhi, November 15–17 2006 (Vol. 1, pp. 353–364). INCITE/ITCSED.

  • Cohen, I., den Braber, N., Smets, N. J. J. M., van Diggelen, J., Brinkman, W.-P., & Neerincx, M. A. (2016). Work content influences on cognitive task load, emotional state and performance during a simulated 520-days' Mars mission. Computers in Human Behavior, 55, 642–652.

    Google Scholar 

  • Compeau, D., Marcolin, B., & Kelley, H. (2012). Generalizability of information systems research using student subjects - a reflection on our practices and recommendations for future research. Information Systems Research, 23(4), 1093–1109.

    Google Scholar 

  • Crystal, D. (2001). Weaving a web of linguistic diversity. Guardian Weekly. http://www.guardian.co.uk/GWeekly/Story/0,3939,427939,00.html. Retrieved Febrary 18, 2011.

  • D’Ambra, J., & Rice, R. E. (2001). Emerging factors in user evaluation of the world wide web. Information Management, 38(6), 373–384.

    Google Scholar 

  • D’Ambra, J., & Wilson, C. S. (2004). Use of the world wide web for international travel: integrating the construct of uncertainty in information seeking and the task-technology fit (TTF) model. Journal of the American Society for Information Science and Technology (JASIST), 55(8), 731–742.

    Google Scholar 

  • D’Ambra, J., Wilson, C. S., & Akter, S. (2013). Application of the task-technology fit model to structure and evaluate the adoption of E-books by academics. Journal of the Amercian Society for Information Science and Technology (JASIST), 64(1), 48–64.

    Google Scholar 

  • Dang, Y., Zhang, Y., Chen, H., Brown, S. A., Hu, P. J.-H., & Nunamaker, J. F. (2012). Theory-informed design and evaluation of an advanced search and knowledge mapping system in nanotechnology. Journal of Management Information Systems (JMIS), 28(4), 99–128.

    Google Scholar 

  • Dang, Y., Zhang, Y., Hu, P. J.-H., Brown, S. A., Ku, Y., Wang, J.-H., et al. (2014). An integrated framework for analyzing multilingual content in web 2.0 social media. Decision Support Systems, 61(1), 126–135.

    Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003.

    Google Scholar 

  • Dennis, A. R., Wixom, B. H., & Vandenberg, R. J. (2001). Understanding fit and appropriation effects in group support systems via meta-analysis. MIS Quarterly, 25(2), 167–193.

    Google Scholar 

  • Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. British Journal of Management, 17(4), 263–282.

    Google Scholar 

  • Dow, K. E., Hackbarth, G., & Wong, J. (2013). Data architectures for an organizational memory information system. Journal of the Amercian Society for Information Science and Technology (JASIST), 64(7), 1345–1356.

    Google Scholar 

  • Erskine, M. A., Gregg, D. G., Karimi, J., & Scott, J. E. (2018). Individual decision-performance using spatial decision support systems: a geospatial reasoning ability and perceived task-technology fit perspective. Information Systems Frontiers. https://doi.org/10.1007/s10796-018-9840-0.

  • Fan, W., & Gordon, M. D. (2014). The power of social media analytics. Communications of the ACM, 57(6), 74–81.

    Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39–45.

    Google Scholar 

  • Fuller, R. M., & Dennis, A. R. (2009). Does fit matter? The impact of task-technology fit and appropriation on team performance in repeated tasks. Information Systems Research, 20(1), 2–17.

    Google Scholar 

  • Gebauer, J., & Shaw, M. J. (2004). Success factors and impacts of mobile business applications: results from a mobile e-procurement study. International Journal of Electronic Commerce, 8(3), 19–41.

    Google Scholar 

  • Gefen, D., Straub, D. W., & Boudreau, M.-C. (2000). Structural equation modeling and regression: guidelines for research practice. Communications of the AIS, 4(7), 1–77.

    Google Scholar 

  • Goette, T. (2000). Keys to the adoption and use of voice recognition technology in organizations. Library Computing, 19(3–4), 235–244.

    Google Scholar 

  • Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213–236.

    Google Scholar 

  • Gwizdka, J. (2010). Distribution of cognitive load inWeb search. Journal of the Amercian Society for Information Science and Technology (JASIST), 61(11), 2167–2187.

    Google Scholar 

  • Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Hakan, A., & Nilsson, L. (1995). The effects of a mobile telephone task on driver behaviour in a car following situation. Accident Analysis and Prevention, 27(5), 707–715.

    Google Scholar 

  • Hart, S. G. (1986). Theory and measurement of human workload. In J. Zeidner (Ed.), Human productivity enhancement: Training and human factors in systems design (Vol. 1, pp. 396–455). New York: Praeger.

    Google Scholar 

  • Hart, S. G. NASA-task load index (NASA-TLX); 20 years later. In Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting, Santa Monica, CA, 2006 (pp. 904–908). Human Factors & Ergonomics Society.

  • Hart, S. G., & Staveland, L. E. (1988). Development of NASA-TLX (task load index): Results of empirical and theoretical research. In P. A. Hancock & N. Meshkati (Eds.), Human mental workload (pp. 139–183). Amsterdam: Elsevier Science Publishers.

    Google Scholar 

  • Hill, S. G., Iavecchia, H. P., Byers, J. C., Bittner, A. C., Zaklad, A. L., & Christ, R. E. (1992). Comparison of four subjective workload rating scales. Human Factors, 34(4), 429–439.

    Google Scholar 

  • IFL Science. (2017). How much data does the world generate every minute? http://www.iflscience.com/technology/how-much-data-does-the-world-generate-every-minute/. Date Accessed 13 Jan 2018.

  • Jarupathirun, S., & Zahedi, F. M. (2007). Exploring the influence of perceptual factors in the success of web-based spatial DSS. Decision Support Systems, 43(3), 933–951.

    Google Scholar 

  • Jou, Y.-T., Yenn, T.-C., Lin, C. J., Yang, C.-W., & Chiang, C.-C. (2009). Evaluation of operators’ mental workload of human-system Interface automation in the advanced nuclear power plants. Nuclear Engineering and Design. https://doi.org/10.1016/j.nucengdes.2009.06.023.

  • Kamvar, M., & Baluja, S. Query suggestions for mobile search: Understanding usage patterns. In Proceeding of the Twenty-sixth annual SIGCHI conference on Human factors in computing systems (CHI 2008) Florence, Italy, April 5–10 2008 (pp. 1013–1016). ACM.

  • Klopping, I. M., & McKinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer E-commerce. Information Technology, Learning, and Performance Journal, 22(1), 35–48.

    Google Scholar 

  • Lau, R. Y. K., Zhao, J. L., Chen, G., & Guo, X. (2016). Big data commerce. Information Management, 53(8), 929–933.

    Google Scholar 

  • Lee, G., & Xia, W. (2010). Toward agile: an integrated analysis of quantitative and qualitative field data on software development agility. MIS Quarterly, 34(1), 87–114.

    Google Scholar 

  • Li, P., Santhanam, R., & Carswell, C. M. (2009). Effects of animations in learning - a cognitive fit perspective. Decision Sciences Journal of Innovative Education, 7(2), 377–410.

    Google Scholar 

  • Lim, K. H., & Benbasat, I. (2000). The effect of multimedia on perceived equivocality and perceived usefulness of information systems. MIS Quarterly, 24(3), 449–471.

    Google Scholar 

  • Lindell, M. K., & Brandt, C. J. (2000). Climate quality and climate consensus as mediators of the relationship between organizational antecedents and outcomes. Journal of Applied Psychology, 85(3), 331–348.

    Google Scholar 

  • Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology, 86(1), 114–121.

    Google Scholar 

  • Lu, H.-P., & Yang, Y.-W. (2014). Toward an understanding of the behavioral intention to use a social networkingsite: an extension of task-technologyfit tosocial-technologyfit. Computers in Human Behavior, 34, 323–332.

    Google Scholar 

  • Lysaght, R. J., Hill, S. G., Dick, A. O., Plamondon, B. D., Linton, P. M., Wierwille, W. W., et al. (1989). Operator workload: Comprehensive review and evaluation of operator workload methodologies. Technical Report No. 851, MDA 903–86-C-0384, United States Army Research Institute for the Behavioral Sciences.

  • Malhotra, N. K., Kim, S. S., & Patil, A. (2006). Common method variance in IS research: a comparison of alternative approaches and a reanalysis of past research. Management Science, 52(12), 1865–1883.

    Google Scholar 

  • Martín, H. S., & Herrero, Á. (2012). Influence of the user’s psychological factors on the online purchase intention in rural tourism: integrating innovativeness to the UTAUT framework. Tourism Management, 33, 341–350.

    Google Scholar 

  • Maruping, L. M., & Agarwal, R. (2004). Managing team interpersonal processes through technology: a task-technology fit perspective. Journal of Applied Psychology, 89(6), 975–990.

    Google Scholar 

  • Mathieson, K., & Keil, M. (1998). Beyond the interface: ease of use and task/technology fit. Information Management, 34, 221–230.

    Google Scholar 

  • Miller, G. A. (1956). The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychological Review, 63(2), 81–97.

    Google Scholar 

  • Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.

    Google Scholar 

  • Niehaves, B., & Plattfaut, R. (2014). Internet adoption by the elderly: employing IS technology acceptance theories for understanding the age-related digital divide. European Journal of Information Systems, 23, 708–726.

    Google Scholar 

  • Noyes, J. M., & Bruneau, D. P. J. (2007). A self-analysis of the NASA-TLX workload measure. Ergonomics, 50(4), 514–519.

    Google Scholar 

  • Noyes, J. M., & Garland, K. J. (2008). Computer- vs. paper-based tasks: are they equivalent? Ergonomics, 51(9), 1352–1375.

    Google Scholar 

  • Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill.

    Google Scholar 

  • Nysveen, H., & Pedersen, P. E. (2016). Consumer adoption of RFID-enabled services. Applying an extended UTAUT model. Information Systems Frontiers, 18(2), 293–314.

    Google Scholar 

  • O’Reilly, T. (2005). What is Web 2.0? Design patterns and business models for the next generation of software. http://www.oreillynet.com/pub/a/oreilly/tim/news/2005/09/30/what-is-web-20.html.

  • Parikh, S. P., Grassi, V., Kumar, V., & Okamoto, J. (2007). Integrating human inputs with autonomous behaviors on an intelligent wheelchair platform. IEEE Intelligent Systems, 22(2), 33–41.

    Google Scholar 

  • Park, J., & Jung, W. (2006). A study on the validity of task complexity measure of emergency operating procedures of nuclear power plants-comparing with a subjective workload. IEEE Transactions on Nuclear Science, 53(5), 2962–2970.

    Google Scholar 

  • Petter, S., Straub, D., & Rai, A. (2007). Specifying formative constructs in information systems research. MIS Quarterly, 31(4), 623–656.

    Google Scholar 

  • Qin, J., Zhou, Y., Chau, M., & Chen, H. (2006). Multilingual web retrieval: an experiment in English–Chinese business intelligence. Journal of the Amercian Society for Information Science and Technology (JASIST), 57(5), 671–683.

    Google Scholar 

  • Ringle, C. M., Wende, S., & Will, A. (2005). SmartPLS 2.0 (M3) beta. Hamburg: http://www.smartpls.de.

  • Roberts, J. (2011). We have the data - now what??!! A few examples of social media analytics. http://www.collectiveintellect.com/blog/we-have-the-data-now-what-a-few-examples-of-social-media-analytics. Retrieved Febrary 18, 2011.

  • Robinson, S. J., & Brewer, G. (2016). Performance on the traditional and the touch screen, tablet versions of the Corsi block and the tower of Hanoi tasks. Computers in Human Behavior, 60, 29–34.

    Google Scholar 

  • Rubicon Consulting Inc. (2009). Online communities and their impact on business: Ignore at your peril. http://thenkbank.files.wordpress.com/2009/03/onlinecommunitiesandtheirimpactonbusinessignoreatyourperil.pdf.

  • Rubio, S., Díaz, E., Martín, J., & Puente, J. M. (2004). Evaluation of subjective mental workload: a comparison of SWAT, NASA-TLX, and workload profile methods. Applied Psychology: An International Review, 53(1), 61–86.

    Google Scholar 

  • Saleem, J. J., Patterson, E. S., Militello, L., Anders, S., Falciglia, M., Wissman, J. A., et al. (2007). Impact of clinical reminder redesign on learnability, efficiency, usability, and workload for ambulatory clinic nurses. Journal of the American Medical Informatics Association, 14(5), 632–640.

    Google Scholar 

  • Schmutz, P., Heinz, S., Métrailler, Y., & Opwis, K. (2009). Cognitive load in eCommerce applications-measurement and effects on user satisfaction. Advances in Human-Computer Interaction, 2009, 1–9. https://doi.org/10.1155/2009/121494.

    Article  Google Scholar 

  • Seethamraju, R., Diatha, K. S., & Garg, S. (2018). Intention to use a mobile-based information technology solution for tuberculosis treatment monitoring – applying a UTAUT model. Information Systems Frontiers, 20(1), 163–181.

    Google Scholar 

  • Shibl, R., Lawley, M., & Debuse, J. (2013). Factors influencing decision support system acceptance. Decision Support Systems, 54(2), 953–961.

    Google Scholar 

  • Speier, C., & Morris, M. G. (2003). The influence of query interface design on decision-making performance. MIS Quarterly, 27(3), 397–423.

    Google Scholar 

  • Stanton, N., Salmon, P., Walker, G., Baber, C., & Jenkins, D. (2005). Human factors methods: A practical guide for engineering and design. Hampshire: Ashgate Publishing.

    Google Scholar 

  • Stevens, J. (2017). Internet Stats & Facts for 2017.

    Google Scholar 

  • Sweller, J. (1988). Cognitive load during problem solving: effects on learning. Cognitive Science, 12(2), 257–285.

    Google Scholar 

  • Sweller, J., Van-Merriënboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296.

    Google Scholar 

  • Takao, H., Sakai, K., Osugi, J., & Ishii, H. (2002). Acoustic user Interface (AUI) for the auditory displays. Displays, 23(1–2), 65–73.

    Google Scholar 

  • Teo, T. (2011). Factors influencing teachers’ intention to use technology: model development and test. Computers & Education, 57, 2432–2440.

    Google Scholar 

  • Terman, E. (2011). Five Top Challenges of Integrating Social Media Data with Business Applications. Enterprise Applications, Guest Opinion, http://www.ctoedge.com/content/five-top-challenges-integratingsocial-media-data-business-applications. (Retrieved January 18, 2012).

  • Torre, G. G. D. l., Ramallo, M. A., & Cervantes, E. (2016). Workload perception in drone flight training simulators. Computers in Human Behavior, 64, 449–454.

    Google Scholar 

  • Umanath, N. S., & Vessey, I. (1994). Multiattribute data presentation and human judgment: a cognitive fit perspective. Decision Sciences, 25(5/6), 795–824.

    Google Scholar 

  • Van-Merriënboer, J. J. G., & Ayres, P. (2005). Research on cognitive load theory and its design implications for E-learning. Educational Technology Research and Development, 53(3), 5–13.

    Google Scholar 

  • Vargas, J. A. (2012). Spring awakening: How an Egyptian revolution began on Facebook. The New York Times. http://www.nytimes.com/2012/02/19/books/review/how-an-egyptian-revolution-began-on-facebook.html?pagewanted=all&_moc.semityn.www.

  • Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.

    Google Scholar 

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186–204.

    Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: towards a unified view. MIS Quarterly, 27(3), 425–478.

    Google Scholar 

  • Venkatesh, 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.

    Google Scholar 

  • Vessey, I. (1991). Cognitive fit: a theory-based analysis of the graphs versus tables literature. Decision Sciences, 22(2), 219–240.

    Google Scholar 

  • Vessey, I., & Galletta, D. (1991). Cognitive fit: an empirical study of information acquisition. Information Systems Research, 2(1), 63–84.

    Google Scholar 

  • Wachter, S. B., Johnson, K., Albert, R., Syroid, N., Drews, F., & Westenskow, D. (2006). The evaluation of a pulmonary display to detect adverse respiratory events using high resolution human simulator. Journal of the American Medical Informatics Association, 13(6), 635–642.

    Google Scholar 

  • Wilson, E. V., & Addo, T. B. (1994). An investigation of the relative presentation efficiency of computer-displayed graphs. Information Management, 26, 105–115.

    Google Scholar 

  • Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67, 221–232.

    Google Scholar 

  • Yang, Z., Sun, J., Zhang, Y., & Wang, Y. (2018). Peas and carrots just because they are green? Operational fit between green supply chain management and green information system. Information Systems Frontiers. https://doi.org/10.1007/s10796-016-9698-y.

  • Yen, D. C., Wu, C.-S., Cheng, F.-F., & Huang, Y.-W. (2010). Determinants of users' intention to adopt wireless technology: an empirical study by integrating TTF with TAM. Computers in Human Behavior, 26, 906–915.

    Google Scholar 

  • Zhou, Y., Qin, J., & Chen, H. (2006). CMedPort: an integrated approach to facilitating Chinese medical information seeking. Decision Support Systems, 42(3), 1431–1448.

    Google Scholar 

  • Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26, 760–767.

    Google Scholar 

  • Zhuhadar, L. (2015). A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines. Computers in Human Behavior, 51, 1107–1115.

    Google Scholar 

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Authors and Affiliations

  1. Information Systems, The W. A. Franke College of Business, Northern Arizona University, Flagstaff, AZ, 86011, USA

    Yan (Mandy) Dang & Yulei (Gavin) Zhang

  2. Department of Management Information Systems, Eller College of Management, University of Arizona, Tucson, AZ, 85721, USA

    Susan A. Brown & Hsinchun Chen

Authors
  1. Yan (Mandy) Dang
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  2. Yulei (Gavin) Zhang
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  3. Susan A. Brown
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  4. Hsinchun Chen
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Corresponding author

Correspondence to Yan (Mandy) Dang.

Appendices

Appendix 1. The seven tasks used in the experiment

Scenario 1: Please login the system using the provided user name and password, and then click the forum “IslamicNetwork” (i.e., the 3rd forum) under “Forums in English.” The following two questions are about this forum.

  • Q1. Please choose the menu tab “By Member” and then use this search function to find the messages posted by user “catalyst.” Please write down the total number of messages posted by user “catalyst.”

  • Q2. Please choose the menu tab “By Time” and then use this search function to find the messages posted during March, 2008 (i.e., from March 01, 2008 to March 31, 2008). Please choose and write down one of the messages returned by the search function as your answer to this question. If the message is very long, write down the first 30 words as your answer. Please also write down the date when this message was posted. (The search function may return more than one message. Please choose any one of them.)

Scenario 2: Please choose the menu tab “Home” to go back to the home page of the system. Then click the forum “Alokab” (i.e., the 2nd forum) under “Forums in Arabic.” The following two questions are about this forum.

  • Q3. Please choose the menu tab “By Topic” and then use the “Search for Terms in Thread Names” to find the threads talking about “nuclear.” Please use the English word “nuclear” to conduct the search. For the returned thread titles, please use the embedded translation function to get their English translations by clicking the button “Translate Titles” at the bottom of the result list. Please choose and write down one of them as your answer to this question. (The search function may return more than one thread. Please choose any one of them and write down its English translation.)

  • Q4. Please choose the menu tab “By Topic” and then use the “Search for Terms in Message Bodies” to find the messages talking about “Iraq.” Please use the English word “Iraq” to conduct the search. For the returned message bodies, please use the embedded translation function to get their English translations by clicking the button “Translate” at the bottom of the result list. Please choose one of the messages and write down the English translation of the sentence in this message that has the word “Iraq.” (The search function may return more than one message. Please choose any one of them and write down the English translation of the sentence in the message that has the word “Iraq.”)

Scenario 3: Please choose the menu tab “Home” to go back to the home page of the system. Then click “Cross Forum Search” under “Search all forums” at the bottom of the home page. The following three questions are about this cross forum search function.

  • Q5. Please use this function to find the threads talking about “bomb” in different forums. Please use the English word “bomb” to conduct the search. Please write down the number of threads identified for each forum. Then click the Arabic forum “AlFirdaws” (i.e., the 1st forum in the result list) to view all the threads talking about “bomb” in this forum in a pop-up webpage. Please use the embedded translation function to get the English translations of these threads by clicking the button “Translate Titles” at the bottom of the result list. Please choose and write down one of them as your answer to this question. (The search function may return more than one thread. Please choose any one of them and write down its English translation.)

  • Q6. Please close the pop-up result webpage of the previous question Q5. Then choose the menu tab “By Topic (Cross Forum)” to start a new search session. Please find the threads talking about “extremist” in different forums. Please use the English word “extremist” to conduct the search. Then click any one of the Arabic forums to view all the threads talking about “extremist” in that forum in a pop-up webpage. Please write down the name of the forum that you choose. Then use the embedded translation function to get the English translations of these threads by clicking the button “Translate Titles” at the bottom of the result list. Please choose and write down one of them as your answer to this question. (The search function may return more than one thread. Please choose any one of them and write down its English translation.)

  • Q7. Please close the pop-up result webpage of the previous question Q6. Then choose the menu tab “By Topic (Cross Forum)” to start a new search session. Please find the threads talking about “peace” in different forums. Please use the English word “peace” to conduct the search. Then click any one of the Arabic forums to view all the threads talking about “peace” in that forum in a pop-up webpage. Please write down the name of the forum that you choose. Then use the embedded translation function to get the English translations of these threads by clicking the button “Translate Titles” at the bottom of the result list. Please choose and write down one of them as your answer to this question. (The search function may return more than one thread. Please choose any one of them and write down its English translation.)

Appendix 2. An example of the screenshot of the search function

Fig. 3
figure 3

A screenshot of the search function of the system

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Dang, Y.(., Zhang, Y.(., Brown, S.A. et al. Examining the impacts of mental workload and task-technology fit on user acceptance of the social media search system. Inf Syst Front 22, 697–718 (2020). https://doi.org/10.1007/s10796-018-9879-y

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