博碩士論文 107322075 詳細資訊




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姓名 方宣又(Hsuan-Yu Fang)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 電動機車共享服務之行為意向與關鍵因素間的交互影響關係—以台北市地區為例
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摘要(中) 電動機車共享服務是「電動機車」與「共享經濟」概念的結合,其特色在於無固定式站點(甲地租賃乙地歸還),且利用第一哩路及最後一哩路的概念來達到「人本交通、與民同行」的願景目標。
本文是結合了情境式問卷進行簡單隨機抽樣,於台北市地區蒐集424個有效樣本,並以計劃行為理論(theory of planned behavior, TPB)及科技接受模式(technology acceptance model, TAM)為基礎並加入環境意識及節約成本兩個構面,設計本研究之理論框架,並利用偏最小平方結構方程模式(partial least squares structural equation modeling, PLS-SEM)來檢驗關鍵因素間的路徑顯著性,以調查使用電動機車共享服務各因素間的交互影響關係。
本研究內容包括:(1)計劃行為理論及科技接受模式的因子以及其他關鍵因素(例如:環境意識及節約成本)是否會影響行為意向。實證結果顯示,各路徑之直接與間接效果皆呈現顯著性影響;(2)異質性分析利用多群組分析(partial least squares multi-group analysis, PLS-MGA)發現性別及用戶類型存在部分路徑的調節效果,亦即可觀測異質性 (性別及用戶類型不同群體間)呈現顯著效果;另外不可觀測異質性分析透過PLS-POS找出樣本存有兩個潛在類別,即「先驅者」與「晚期大眾」,不可觀測異質性也呈現顯著效果。最後針對分析結果探討電動機車共享服務的管理意涵策略,並提出結論與建議。
摘要(英) Sharing electric scooter service is the combination of " electric vehicle " and "sharing economy", the corresponding characteristics include two main categories: (1)dockless sites (pick up in A and return in B), (2) using the concept of the last mile and the first mile , to achieve the gaol of " human oriented traffic, moving forward hand in hand ". The research applied simple random sampling by using scenario-based questionnaire with the framework is constructed mainly based on theory of planned behavior (TPB), technology acceptance model (TAM), and the additional factor called environmental awareness and cost saving. The research framework is then analyzed with (1) partial least squares structural equation modeling (PLS-SEM) for exploring path relationships of influential factors of sharing electric scooter, (2) partial least squares multi-group analysis (PLS-MGA) for elaborating observed heterogeneity, like gender and user types. This study looks forward to: (1) Whether or not the factors of TPB and TAM affects the behavioral intention. (2) Whether or not other factors such as environmental awareness and cost saving will affect behavioral intentions. (3) In the heterogeneity analysis results, there was a partial adjustment of the effect of the gender and users type, and two potential categories were found by PLS-POS. To conduct the empirical study, we collected a sample of 424 respondents from both users and nonusers for sharing electric scooter service in Taipei. The result shows that all factors of the TPB and TAM have significant influence on behavioral intention of using sharing electric scooter, and there exist heterogeneity between different groups (gender and user types). In the end of the research, management implications for future research are given.
關鍵字(中) ★ 電動機車共享服務
★ 共享經濟
★ 計劃行為理論
★ 科技接受模式
★ 偏最小平方結構方程模式
★ 異質性分析
關鍵字(英) ★ Sharing electric scooter service
★ sharing economy
★ theory of planned behavior (TPB)
★ technology acceptance model(TAM)
★ partial least squares structural equation modeling
★ heterogeneity analysis
論文目次 中文摘要 i
Abstract ii
誌謝 iv
圖目錄 vii
表目錄 viii
第一章 緒論 1
第二章 研究背景及架構與假設 8
2.1 研究背景 8
2.2 研究架構與假設 10
2.2.1 計劃行為理論 10
2.2.2 科技接受模式 12
2.2.3 整合TPB跟TAM模式 13
2.2.4 環境意識 16
2.2.5 成本節約 17
2.3 異質性 17
2.3.1 可觀測異質性(性別及用戶類型) 18
2.3.2 不可觀測異質性(潛在變項) 18
2.4 研究模式的框架 19
第三章 研究方法 22
3.1 偏最小平方結構方程模式 22
3.2 考慮異質性的偏最小平方結構方程模式 23
3.2.1 偏最小平方-多群組分析 24
3.2.2 偏最小平方-預測取向區隔 24
第四章 衡量標準 26
第五章 基本資料統計與實證結果分析 28
5.1 資料蒐集 28
5.2 受訪者社經背景統計 29
5.3 共同方法變異 31
5.4 測量模式之信效度分析 31
5.4.1 信度分析 31
5.4.2 效度分析 33
5.5 結構模式的假設驗證 36
5.6 異質性分析 41
5.6.1 可觀測的異質性 41
5.6.2 不可觀測異質性 42
5.6.3 小結 48
第六章 管理意涵討論與結論建議 49
6.1 研究結論 49
6.2 管理意涵與討論 51
6.3 結論與建議 53
參考文獻 55
附錄A PLS-SEM跟PLS-POS的操作步驟 67
附錄B本研究觀測指標問項 69
附錄C本研究調查問卷 72
附錄D觀測變項的敘述性統計 80
附錄E題項刪除之原因說明 82
附錄F因素負荷量及外部權重之顯著水準 83
附錄G Sobel檢驗法 85
參考文獻 [1] 交通部統計處(2019.10),機車使用狀況調查報告。
[2] 交通部運輸研究所(2016),運輸部門年度排放清冊。
[3] 交通部運研所(2018),陸路運輸業能源消耗及溫室氣體排放推估及評估指標研析。
[4] 許志義、游晨廷(2019),電動機車商業模式之經濟效益分析:共享經濟vs.電池租賃。臺灣能源期刊,第六卷第二期,第185-205頁。
[5] 張乃瑄、温蓓章(2019.05),我國電動機車產業現況與迎戰國際競爭策略,中華經濟研究院第二研究所。
[6] 陳寬裕(2018),結構方程模型分析實務:SPSS與SmartPLS 的運用,五南圖書出版股份有限公司。
[7] 陳惠國(2019),研究分析方法課程講義,國立中央大學土木工程學系。
[8] 曾郁茜(2019.10),全球電動機車市場趨勢與關鍵議題,工研院產業科技國際策略發展所。
[9] 曾郁茜(2020.5),全球二輪車聯網趨勢與應用案例,工研院產業科技國際策略發展所
[10] 環保署(2017),環境資源資料庫,https://erdb.epa.gov.tw/
[11] 環保署(2019),國家溫室氣體排放清冊。
[12] 環保署(2019),台灣空氣汙染物排放量[TEDS 10.0]線源–排放量推估手冊
[13] 臺北市停車管理工程處(2018),臺北市汽機車停車供需調查。
[14] 臺北市停車管理工程處(2019),臺北市汽機車停車供需調查。
[15] 魏逸樺、鄧傑漢(2020.05),臺灣電動機車共享服務的發展,中華經濟研究院綠色經濟研究中心。
[16] WeMo Scooter官方網站(2019.10),WeMo Scooter智慧交通白皮書。
[17] iRent官方網站,https://www.ridegoshare.com/tw/
[18] GoShare官方網站,https://www.easyrent.com.tw/irent/web/index.html
[19] Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action Control, 11-39.
[20] Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes,50 (2):179-211.
[21] Ajzen, I., and M. Fishbein., 1980. Understanding Attitudes and Predicting Social Behavior, Englewood Cliffs.
[22] Baron, R. M., & Kenny, D. A., 1986. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173.
[23] Bollen, K. A., 1989. A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303-316.
[24] Bagozzi, R. P., & Yi, Y.,1991. Multitrait-multimethod matrices in consumer research. Journal of Consumer Research, 17(4), 426-439.
[25] Bagozzi, R. P., Baumgartner, H., & Yi, Y., 1992. State versus action orientation and the theory of reasoned action: An application to coupon usage. Journal of Consumer Research, 18(4), 505-518.
[26] Bardhi, F., & Eckhardt, G. M., 2012. Access-based consumption: The case of car sharing. Journal of Consumer Research, 39(4), 881-898.
[27] Becker, J. M., Rai, A., Ringle, C. M., & Völckner, F., 2013. Discovering unobserved heterogeneity in structural equation models to avert validity threats. MIS Quarterly, 665-694.
[28] Bjerkan, K. Y., Nørbech, T. E., & Nordtømme, M. E., 2016. Incentives for promoting battery electric vehicle (BEV) adoption in Norway. Transportation Research Part D: Transport and Environment, 43, 169-180.
[29] Bonges III, H. A., & Lusk, A. C., 2016. Addressing electric vehicle (EV) sales and range anxiety through parking layout, policy and regulation. Transportation Research Part A: Policy and Practice, 83, 63-73.
[30] Bjerkan, K. Y., Nørbech, T. E., & Nordtømme, M. E., 2016. Incentives for promoting battery electric vehicle (BEV) adoption in Norway. Transportation Research Part D: Transport and Environment, 43, 169-180.
[31] Barnes, S. J., & Mattsson, J., 2017. Understanding collaborative consumption: Test of a theoretical model. Technological Forecasting and Social Change, 118, 281-292.
[32] Comrey, A. L., & Lee, H. B., 2013. A first course in factor analysis.
[33] Chin, W. W. 1998., The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.
[34] Chin, W. W., & Newsted, P. R., 1999. Structural equation modeling analysis with small samples using partial least squares. Statistical Strategies for Small Sample Research, 1(1), 307-341.
[35] Cervero, R., & Tsai, Y., 2004. City CarShare in San Francisco, California: second-year travel demand and car ownership impacts. Transportation Research Record, 1887(1), 117-127.
[36] Chang, H. L., & Yeh, T. H., 2007. Motorcyclist accident involvement by age, gender, and risky behaviors in Taipei, Taiwan. Transportation Research Part F: Traffic Psychology and Behaviour, 10(2), 109-122.
[37] Chen, C. F., & Chao, W. H., 2011. Habitual or reasoned? Using the theory of planned behavior, technology acceptance model, and habit to examine switching intentions toward public transit. Transportation Research Part F: Traffic Psychology and Behaviour, 14(2), 128-137.
[38] Carley, S., Krause, R. M., Lane, B. W., & Graham, J. D., 2013. Intent to purchase a plug-in electric vehicle: A survey of early impressions in large US cites. Transportation Research Part D: Transport and Environment, 18, 39-45.
[39] Chen, S. Y., & Lu, C. C., 2016. A model of green acceptance and intentions to use bike-sharing: YouBike users in Taiwan. Networks and Spatial Economics, 16(4), 1103-1124.
[40] Coffman, M., Bernstein, P., & Wee, S., 2017. Electric vehicles revisited: a review of factors that affect adoption. Transport Reviews, 37(1), 79-93.
[41] Chen, H. K., Chou, H. W., & Hung, S. C., 2019. Interrelationships between behaviour intention and its influential factors for consumers of motorcycle express cargo delivery service. Transportmetrica A: Transport Science, 15(2), 526-555.
[42] Davis, F. D., 1986. A technology acceptance model for empirically testing new end-user information systems: Theory and results. (Doctoral dissertation, Massachusetts Institute of Technology).
[43] Davis, F. D., 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 319-340.
[44] 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.
[45] Dishaw, M. T., & Strong, D. M., 1999. Extending the technology acceptance model with task–technology fit constructs. Information & Management, 36(1), 9-21.
[46] Efron, B., & Tibshirani, R. J., 1994. An introduction to the bootstrap.
[47] Eccarius, T., & Lu, C. C., 2020. Powered two-wheelers for sustainable mobility: A review of consumer adoption of electric motorcycles. International Journal of Sustainable Transportation, 14(3), 215-231.
[48] Fishbein, M., & Ajzen, I., 1977. Belief, attitude, intention, and behavior: An introduction to theory and research.
[49] Fornell, C., & Larcker, D. F., 1981. Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18, 39-51.
[50] Fellows, N. T., & Pitfield, D. E., 2000. An economic and operational evaluation of urban car-sharing. Transportation Research Part D: Transport and Environment, 5(1), 1-10.
[51] Gefen, D., Straub, D., & Boudreau, M. C., 2000. Structural equation modeling and regression: Guidelines for research practice. Communications of The Association for Information Systems, 4(1), 7.
[52] Gay, L. R., Mills, G. E., & Airasian, P. W. (2009). Educational Research: Competencies for Analysis and Applications.
[53] Graham-Rowe, E., Gardner, B., Abraham, C., Skippon, S., Dittmar, H., Hutchins, R., & Stannard, J., 2012. Mainstream consumers driving plug-in battery-electric and plug-in hybrid electric cars: A qualitative analysis of responses and evaluations. Transportation Research Part A: Policy and Practice, 46(1), 140-153.
[54] Giang, P. T., Trang, P. T., & Yen, V. T., 2017. An examination of factors influencing the intention to adopt ride-sharing applications. A Case Study in Vietnam. Imperial Journal of Interdisciplinary Research (IJIR), 3(10), 618-623.
[55] Harman, H. H., 1976. Modern factor analysis.
[56] Hui, B. S., & Wold, H., 1982. Consistency and consistency at large of partial least squares estimates. Systems Under Indirect Observation, Part II, 119-130.
[57] Haenlein, M., & Kaplan, A. M., 2004. A beginner′s guide to partial least squares analysis. Understanding Statistics, 3(4), 283-297.
[58] Hair, J. F., Ringle, C. M., & Sarstedt, M., 2011. PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
[59] Henseler, J., 2012. PLS-MGA: A non-parametric approach to partial least squares-based multi-group analysis. In Challenges at the Interface of Data Analysis, Computer Science, and Optimization , 495-501.
[60] Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A., 2012. An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433.
[61] Hayes, A. F., & Scharkow, M., 2013. The relative trustworthiness of inferential tests of the indirect effect in statistical mediation analysis: Does method really matter?. Psychological Science, 24(10), 1918-1927.
[62] Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G., 2014. Partial least squares structural equation modeling (PLS-SEM).
[63] Hayes, A. F., & Preacher, K. J., 2014. Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67(3), 451-470.
[64] Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M., 2016. A primer on partial Least Squares Structural Equation Modeling (PLS-SEM).
[65] Huang, F. H., 2016. Exploring information needs of using battery swapping system for riders. In International Conference on Human Interface and the Management of Information, 531-541.
[66] Hamari, J., Sjöklint, M., & Ukkonen, A., 2016. The sharing economy: Why people participate in collaborative consumption. Journal of the Association for Information Science and Technology, 67(9), 2047-2059.
[67] Henseler, J., Hubona, G., & Ray, P. A., 2016. Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems.
[68] Haldar, P., & Goel, P., 2019. Willingness to use carsharing apps: an integrated TPB and TAM. International Journal of Indian Culture and Business Management, 19(2), 129-146.
[69] Jöreskog, K. G., 1978. Structural analysis of covariance and correlation matrices. Psychometrika, 43(4), 443-477.
[70] Keil, M., Tan, B. C., Wei, K. K., Saarinen, T., Tuunainen, V., & Wassenaar, A., 2000. A cross-cultural study on escalation of commitment behavior in software projects. MIS Quarterly, 299-325.
[71] Lohmöller, J. B., 1989. Predictive vs. structural modeling: Pls vs. ml. In Latent Variable Path Modeling with Partial Least Squares, 199-226.
[72] Lieven, T., Mühlmeier, S., Henkel, S., & Waller, J. F., 2011. Who will buy electric cars? An empirical study in Germany. Transportation Research Part D: Transport and Environment, 16(3), 236-243.
[73] Lamberton, C. P., & Rose, R. L., 2012. When is ours better than mine? A framework for understanding and altering participation in commercial sharing systems. Journal of Marketing, 76(4), 109-125.
[74] MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V., 2002. A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7(1), 83.
[75] Mattila, A. S., & Enz, C. A., 2002. The role of emotions in service encounters. Journal of Service Research, 4(4), 268-277.
[76] May, A., Ross, T., Grebert, J., & Segarra, G., 2008. User reaction to car share and lift share within a transport ‘marketplace’. IET Intelligent Transport Systems, 2(1), 47-60.
[77] Moan, I. S., & Rise, J., 2011. Predicting intentions not to “drink and drive” using an extended version of the theory of planned behaviour. Accident Analysis & Prevention, 43(4), 1378-1384.
[78] Mayer, K. J., & Sparrowe, R. T., 2013. From the editors—Integrating theories in AMJ articles. Academy of Management Journal, 56(4), 917–922.
[79] Mattia, G., Mugion, R. G., & Principato, L., 2019. Shared mobility as a driver for sustainable consumptions: The intention to re-use free-floating car sharing. Journal of Cleaner Production, 237, 117404.
[80] Nunnally, J. C., 1994. Psychometric Theory 3E.
[81] Norberg, P. A., Horne, D. R., & Horne, D. A., 2007. The privacy paradox: Personal information disclosure intentions versus behaviors. Journal of Consumer Affairs, 41(1), 100-126.
[82] O′Fallon, C., Sullivan, C., & Hensher, D. A., 2004. Constraints affecting mode choices by morning car commuters. Transport Policy, 11(1), 17-29.
[83] Ong, D. L. T., Tee, S. Y. V., & Lim, M. Y. H., 2017. Uber-nization of transport: An investigation into the sustainability of ride-sharing applications in Malaysia.
[84] Oyedele, A., & Simpson, P., 2018. Emerging adulthood, sharing utilities and intention to use sharing services. Journal of Services Marketing.
[85] Podsakoff, P. M., & Organ, D. W., 1986. Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531-544.
[86] Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P., 2003. Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879.
[87] Preacher, K. J., & Hayes, A. F., 2004. SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717-731.
[88] Preacher, K. J., & Hayes, A. F., 2008. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879-891.
[89] Roscoe, J. T., 1975. Fundamental research statistics for the behavioral sciences.
[90] Rhodes, N., & Pivik, K., 2011. Age and gender differences in risky driving: The roles of positive affect and risk perception. Accident Analysis & Prevention, 43(3), 923-931.
[91] Rucker, D. D., Preacher, K. J., Tormala, Z. L., & Petty, R. E., 2011. Mediation analysis in social psychology: Current practices and new recommendations. Social and Personality Psychology Compass, 5(6), 359-371.
[92] Rezvani, Z., Jansson, J., & Bodin, J., 2015. Advances in consumer electric vehicle adoption research: A review and research agenda. Transportation Research Part D: Transport and Environment, 34, 122-136.
[93] Schwab, D. P., 1980. Construct validity in organizational behavior. Res Organ Behav, 2, 3-43.
[94] Sobel, M. E., 1982. Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290-312.
[95] Spector, P. E., 1987. Method variance as an artifact in self-reported affect and perceptions at work: Myth or significant problem?. Journal of Applied Psychology, 72(3), 438.
[96] Sheppard, B. H., Hartwick, J., & Warshaw, P. R.,1988. The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15(3), 325-343.
[97] Sethi, V., & Carraher, S., 1993. Developing measures for assessing the organizational impact of information technology: A comment on Mahmood and Soon′s paper. Decision Sciences, 24(4), 867-877.
[98] Shaffer, J. P., 1995. Multiple hypothesis testing. Annual Review of Psychology, 46(1), 561-584.
[99] Shrout, P. E., & Bolger, N., 2002. Mediation in experimental and nonexperimental studies: new procedures and recommendations. Psychological Methods, 7(4), 422.
[100] Straub, D., Boudreau, M. C., & Gefen, D., 2004. Validation guidelines for IS positivist research. Communications of the Association for Information Systems, 13(1), 24.
[101] Sarstedt, M., Henseler, J., & Ringle, C. M., 2011. Multigroup analysis in partial least squares (PLS) path modeling: Alternative methods and empirical results. In Measurement and Research Methods in International Marketing.
[102] Sierzchula, W., Bakker, S., Maat, K., & Van Wee, B., 2014. The influence of financial incentives and other socio-economic factors on electric vehicle adoption. Energy Policy, 68, 183-194.
[103] Si, H., Shi, J. G., Tang, D., Wu, G., & Lan, J., 2020. Understanding intention and behavior toward sustainable usage of bike sharing by extending the theory of planned behavior. Resources, Conservation and Recycling, 152, 104513.
[104] Taylor, S., & Todd, P., 1995. Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions. International Journal of Research in Marketing, 12(2), 137-155.
[105] Taylor, S., & Todd, P., 1995. Assessing IT usage: The role of prior experience. MIS Quarterly, 561-570.
[106] Wold, H., 1966. Estimation of principal components and related models by iterative least squares. Multivariate Analysis, 391-420.
[107] Werts, C. E., Linn, R. L., & Jöreskog, K. G., 1974. Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), 25-33.
[108] Wold, H., 1982. Soft modeling: the basic design and some extensions. Systems Under Indirect Observation, 2, 343.
[109] Wold, H., 1985. Partial least squares. S. Kotz and NL Johnson (Eds.), Encyclopedia of statistical sciences (vol. 6).
[110] Wolbertus, R., Kroesen, M., van den Hoed, R., & Chorus, C. G., 2018. Policy effects on charging behaviour of electric vehicle owners and on purchase intentions of prospective owners: Natural and stated choice experiments. Transportation Research Part D: Transport and Environment, 62, 283-297.
[111] Wang, Y., Wang, S., Wang, J., Wei, J., & Wang, C., 2018. An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model. Transportation, 1-19.
[112] Wang, Y., Wang, S., Wang, J., Wei, J., & Wang, C., 2018. An empirical study of consumers’ intention to use ride-sharing services: using an extended technology acceptance model. Transportation, 1-19.
[113] Wang, N., Tang, L., & Pan, H., 2019. A global comparison and assessment of incentive policy on electric vehicle promotion. Sustainable Cities and Society, 44, 597-603.
[114] Wang, J., & Wang, X., 2019. Structural equation modeling: Applications using Mplus.
[115] Zhang, K., Guo, H., Yao, G., Li, C., Zhang, Y., & Wang, W., 2018. Modeling acceptance of electric vehicle sharing based on theory of planned behavior. Sustainability, 10(12), 4686.
指導教授 陳惠國 審核日期 2020-8-19
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