跳到主要內容

臺灣博碩士論文加值系統

(18.97.14.84) 您好!臺灣時間:2024/12/04 11:02
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:郭芳妤
研究生(外文):Fang-Yu Kuo
論文名稱:從認知反應與腦波歷程探究排隊對於消費者等候決策之影響
論文名稱(外文):The Decision of Queuing after the Witness of a Queue: A Study of the Cognitive and Brainwave Responses
指導教授:梁直青梁直青引用關係
學位類別:碩士
校院名稱:國立虎尾科技大學
系所名稱:企業管理系經營管理碩士班
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:255
中文關鍵詞:排隊現象等候決策腦波資料探勘
外文關鍵詞:Queuing PhenomenonWaiting DecisionEEGData Mining
相關次數:
  • 被引用被引用:2
  • 點閱點閱:297
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
排隊現象不僅是大眾司空見慣的消費行為,其中伴隨的管理效益也在近年來開始被服務供應商們關注著,實務上也不斷出現各種排隊管理方針來加強消費者願意加入或是留在隊伍中等候之意願。然而,排隊決策卻是有如黑箱運作般的難以去衡量其管理成效,因為決策是在經由一連串複雜的人體內部認知處理後所發生的最終行為,所以本研究決定透過腦波量測技術搭配情境模擬實驗方式來了解實務上最常被使用的「等候時間」與「排隊人數」兩種排隊資訊管理方針對於顧客等候決策歷程中所造成的影響,並同時搭配事後問卷來確認受試者對於這兩種排隊資訊的認知情況,並於等候時間實驗中納入個人時間風格、等候容忍度、決策回應類型作為分群變數,以進一步比較不同特質群組間的認知差異。
在等候時間資訊實驗方面,本研究以迴歸分析發現到等候時間資訊能顯著為顧客帶來正向情緒反應,而以三個分群變數進行的探照燈分析(spotlight)顯示各群組之等候時間資訊認知對於等候正、負面情緒皆無顯著差異;而腦波訊號分析發現到純等候資訊刺激相較於時間資訊刺激有著較大的腦波訊號變化,而且人在面對純等候資訊時,前250毫秒的腦波訊號會有著較大的震盪變化,但是兩種資訊刺激皆會造成300至350毫秒間出現了高波訊號;而本研究亦嘗試透過模糊統計手法將連續值的腦波資料轉換為離散值,並透過相關分析確認十百分位數之轉換法與原始數值之相關性最高,而本研究接續以此法進行資料探勘之次序分析,並成功計算出數萬筆規則,並進一步於純等候資訊及等候時間資訊刺激下的比較發現到兩者有著不一的腦波變換規則。
另一方面,在排隊人數資訊實驗中,本研究同樣透過迴歸分析了解到等候人數資訊能顯著減弱顧客的負向情緒反應,但其正面情緒影響則未達顯著。但多位受試者會是呈現先偵測到頂葉、顳葉上方頭皮表層訊號較強的狀態,爾後是接續為額葉上方之頭皮表層訊號較強,並持續在二或三以上的區域間移轉;而當受試者面對「排隊人數資訊」與「純排隊場景資訊」時的腦波歷程變換亦有所差異。
Queuing behavior is a universal consumption phenomenon to service industry. Many companies attend to the management issues about the unavoidable waiting situation and establish many management policy to make consumer willing to wait or stay. However, consumer decision making is the ultimate behavior that occurs after a series of complex human cognitive processes, so it’s hard to observe as usual. This study was apply braiwave experiment with two kinds of queueing situation simulation and to detection the real reaction of comsumers. On the other hand, this paper also used questionnaires to understand the consumers’ queuing perception and include personal time style, waiting tolerance and decision type as grouping variables.
The analytical results of questionnaire showed providing waiting time information will bring consumer positive emotion, but no significant difference in three grouping variables. However, when providing the information of queuing people will decrease the consumer negative emotion.
In addition, the analytical results of brainwave response showed that consumer will had high wave from 300 to 350ms on FP1 after consumer receive waiting time information, but the waiting information without time will make consumer brainwave had larger change at 0 to 250ms. This study convert the continuous value of brainwave data into discrete values by fuzzy statistical techniques and confirm the LN10H method had the highest correlation with the raw data. Then, use sequence pattern analysis of data mining to find the tens of thousands of rules of brainwave. Otherwises, this study used 32 channel to observer the effect of queuing information of waiting line in front of store. The analytical results showed the stronger signals from scalp surface near paterial and temporal lobe first, than the power would transfer from the scalp surface near frontal lobe.
摘要.....................................................i
英文摘要 ...............................................iii
誌謝....................................................iv
目錄.....................................................v
表目錄...................................................ix
圖目錄...................................................xi
第一章 緒論...............................................1
1.1 研究背景與動機........................................1
1.2 研究目的..............................................3
1.3 研究流程..............................................3
第二章 文獻探討...........................................5
2.1 排隊現象..............................................5
2.2 排隊理論..............................................6
2.2.1 輸入來源(input source)..............................7
2.2.2 系統容量(system capacity)...........................7
2.2.3 服務規則(service discipline)........................7
2.2.4 服務設施(service facility)..........................7
2.3 等候決策..............................................9
2.3.1 Nicosia模型........................................9
2.3.2 EKB與EBM模型.......................................11
2.3.3 Howard-Sheth模型..................................15
2.3.4 CDM模型...........................................17
2.3.5 刺激─反應模型......................................18
2.4 排隊管理.............................................24
2.4.1 排隊環境...........................................25
2.4.2 排隊隊形管理.......................................26
2.4.3 排隊資訊...........................................28
2.5 排隊心理.............................................29
2.5.1 排隊經驗...........................................30
2.5.2 等候時間知覺.......................................31
2.5.3 等候情緒...........................................33
2.5.4 個人時間風格.......................................36
2.5.5 等候容忍度.........................................38
2.6 腦部結構.............................................41
2.7 情境模式.............................................54
2.8 本章小結.............................................55
第三章 研究方法..........................................56
3.1 研究架構及假設.......................................56
3.2 研究變數.............................................57
3.2.1 問卷架構變數之操作型定義............................57
3.2.2 腦波實驗架構變數之操作型定義.........................59
3.3 問卷設計.............................................59
3.4 問卷前測.............................................64
3.4.1等候歷程認知問卷之前測...............................64
3.4.2 個人時間風格問卷之前測..............................77
3.5 研究方法.............................................89
3.5.1 等候時間資訊實驗...................................89
3.5.2 排隊人數資訊實驗...................................90
3.6 實驗對象.............................................90
3.7 實驗一:等候時間資訊實驗..............................92
3.7.1 實驗情境設計.......................................92
3.7.2 實驗環境...........................................93
3.7.3 硬體設備...........................................95
3.7.4 實驗軟體...........................................96
3.7.5 實驗情境預試.......................................98
3.7.6 正式實驗之實驗設計..................................99
3.7.7 正式實驗前測......................................101
3.7.8 實驗流程..........................................105
3.7.9 實驗問卷..........................................106
3.8 實驗二:排隊人數資訊實驗.............................106
3.8.1 實驗設計..........................................106
3.8.2 實驗環境..........................................108
3.8.3 硬體設備..........................................108
3.8.4 實驗軟體..........................................110
3.8.5 實驗前測..........................................112
3.8.6 實驗流程..........................................114
3.8.7 實驗問卷..........................................115
3.9 資料分析方法........................................115
3.9.1 敘述性統計分析....................................115
3.9.2 常態檢定..........................................115
3.9.3 信度分析..........................................116
3.9.4 兩階段集群分析....................................116
3.9.5 鑑別度分析........................................117
3.9.6 迴歸分析..........................................117
3.9.7 探照燈分析........................................118
3.9.7 腦波資料前處理....................................119
3.9.8 單通道腦波資料離散計算方法.........................121
3.9.9 相關分析..........................................122
3.9.10 資料探勘之次序分析................................123
第四章 資料分析.........................................125
4.1 等候時間資訊實驗之問卷分析...........................125
4.1.1 敘述性統計........................................125
4.1.2 常態檢定..........................................127
4.1.3 信度分析..........................................128
4.1.4 個人時間風格之樣本分組結果.........................129
4.1.5 等候容忍度之樣本分組結果...........................130
4.1.6 迴歸分析..........................................131
4.1.7 探照燈分析........................................133
4.2 等候時間資訊實驗之腦波分析...........................136
4.2.1 等候時間資訊之腦波歷程分析.........................137
4.2.2 離散計算與原始腦波數值之相關性檢定..................138
4.2.3 資料探勘之次序分析檢定結果.........................138
4.3 排隊人數資訊實驗之問卷分析...........................140
4.3.1 敘述性統計........................................140
4.3.2 常態檢定..........................................142
4.3.3 信度檢定..........................................143
4.3.4 迴歸分析..........................................143
4.4 排隊資訊實驗之腦波分析...............................145
4.4.1 排隊人數資訊之腦波歷程分析.........................146
第五章 結論與建議.......................................152
5.1 研究結論............................................152
5.2 管理意涵............................................153
5.3 研究限制與建議......................................153
參考文獻................................................155
附錄一 台灣產業發展現況..................................175
附錄二 第二章補充內容....................................176
附錄三 CFA分析說明......................................206
附錄四 等候歷程認知前測問卷..............................211
附錄五 等候歷程認知問卷各問項之相關矩陣表..................213
附錄六 個人時間風格問卷前測..............................215
附錄七 個人時間風格問項之相關矩陣表.......................217
附錄八 受試者篩選用問卷..................................218
附錄九 腦波遊戲測試參與同意書.............................220
附錄十 排隊人數資訊實驗同意書.............................223
附錄十一 腦波遊戲體驗調查問卷.............................226
附錄十二 排隊人數資訊實驗問卷.............................228
附錄十三 等候時間資訊實驗可用腦波資料統計表................234
附錄十四 等候人數資訊實驗之受試者決策統計表................237
附錄十五 ICA分析結果....................................241
附錄十六 成功大學人類研究倫理審查通過證明..................249
Extended Abstract......................................250
簡歷(CV)...............................................255
中文文獻
[1]王信文與何巧齡(2006)。影響網路購物行為之關鍵因素分析。經營管理論叢,2(1),1-28。
[2]王苡嫣(2016年8月12日)。超人氣日本鐵路便當進軍台灣 民眾清晨6點排隊搶購。今日新聞網。取自http://www.nownews.com/n/2016/08/12/2202596
申冀治(2006)。座位需求導入等候理論之設施規劃改善研究。工業科技與管理學刊,1,91-109。
[3]白?芸(2014)。服務失誤歸因與補救滿意度─消費經驗之干擾效果。品質學報,21(1),57-72。
[4]吳佳華(2012)。檢驗量表分析餐廳美食客之消費行動。商業現代化學刊,6(4),167-181。
[5]周逸衡、黃毓瑩、陳華寧與楊俊明(2006)。情緒類別及等待發生時點對等待時間知覺的影響。中山管理評論,14(2),487-516。
[6]林吉仁(2014)。作業研究(五版)。高立:台北。
[7]林美蘭、方妙玲與張瑞淳(2015)。餐廳背景音樂的速度與音量影響消費者等待時間知覺之研究。觀光休閒學報,21(1),55-77。
[8]林真真、周怡婷與余長義(2014)。多樣測驗之統計分析-以國小六年級數學科試題為例。統計與資訊評論,(16),1-18。
[9]張菀珍、葉榮木、蔡俊明、林詠翔(2011)。結合多尺度主成分分析法與支持向量機在想像彩色圖像與中文文字之腦電波差異分析。資訊科學應用期刊,7(1),1-28。
[10]梁直青、郭文甄與蔡佩舒(2016)。腦波與排隊決策之探究。東吳經濟商學學報,92,1-36。
[11]郭建良與白玫莉(2015)。結合方法─目的鏈及消費者決策模型進行新興服務體驗流程設計的可行性研究。電子商務學報,17(3),345-374。
[12]郭峰淵、黃瑜峰(2009)。擴充認知適配論以研究情緒在決策中的角色—眼動儀之應用。資訊管理學報,16,1-19。
[13]程炳林、陳正昌、陳新豐與劉子鍵(2003)。多變量分析方法-統計軟體應用。臺北:五南。
[14]黃允成與周家漢(2015)。異質母體適應性最適服務站數之研究。台灣管理學刊, 15(2),49-70。
[15]黃君瀚(2015年11月7日)。台南這間珍奶名店百人排隊 網友驚:比搶iPhone還誇張!。ETtoday東森新聞雲。取自http://www.ettoday.net/
[16]楊仁壽、俞慧芸、李怡穎與李瑞敏(2010)。情緒浸染之資訊整合行爲:理論建構與實證。臺大管理論叢,20(2),97-133。
[17]廖慧伶、洪一仁、黃惠珠與李明輝(2016)。創新門診候藥時間管理-「具等候量語音提示機制之門診領藥時間提醒系統」─以豐原醫院為例。醫學與健康期刊,5(1),101-110。
[18]廖慶榮(2009)。作業研究(2版)。華泰文化:台北。
[19]榮泰生(2015)。消費者行為。台北:五南圖書出版股份有限公司。
[20]劉世雄(2007)。瀏覽超媒體教材的訊息處理策略與訊息理解之研究。屏東教育大學學報,27,29-64。
[21]劉雅甄(2014)。棒球選手打擊之視覺焦點策略分析。華人運動生物力學期刊,11, 13-19。
[22]蕭至惠、蔡進發與吳思韻(2011)。等待時間資訊、人格特質與服務屬性對消費者等待時間知覺的影響。中原企管評論, 9(2), 113-138.
[23]蕭至惠、蔡進發與林健名(2012)。期盼模式與修正型等待觀點下,探討等待發生時點、情緒類別、個人時間風格對等待時間知覺之影響。輔仁管理評論,19(2), 29-58。
[24]蕭至惠、謝玉君與蔡進發(2010)。排隊隊形與電視節目類型對消費者等待時間知覺的影響。輔仁管理評論,17(1),55-77。
[25]賴文祥與李涵恕(2013)。以沉浸理論與排隊等待結構探討顧客之等待時間知覺。 東亞論壇,479,65-84。
[26]鍾燕宜、紀乃文與陳景元(2008)。銷售工作價值觀量表之發展與評量。臺大管理論叢,19(1),51-81.
[27]顏真真(2016年5月24日)。臨櫃免排隊 銀行推出雲端預約服務 存提匯3分鐘搞定。今日新聞網。取自http://www.nownews.com/n/2016/05/24/2111570

英文文獻
[1]Aboalayon, K. A., Ocbagabir, H. T., & Faezipour, M. (2014, May). Efficient sleep stage classification based on EEG signals. In Systems, Applications and Technology Conference (LISAT), 2014 IEEE Long Island (pp. 1-6). IEEE.
[2]Abo-Zahhad, M., Ahmed, S. M., & Abbas, S. N. (2015). A new EEG acquisition protocol for biometric identification using eye blinking signals. International Journal of Intelligent Systems and Applications, 7(6), 48.
[3]Adams, R. (2013). Active queue management: a survey. Communications Surveys and Tutorials, IEEE, 15(3), 1425-1476.
[4]Agarwal, S., & Dutta, T. (2015). Neuromarketing and consumer neuroscience: current understanding and the way forward. Decision, 42(4), 457-462.
[5]Ahmadlou, M., Adeli, H., & Adeli, A. (2010). New diagnostic EEG markers of the Alzheimer’s disease using visibility graph. Journal of Neural Transmission, 117(9), 1099-1109.
[6]Ainsworth, S. E., Baumeister, R. F., Ariely, D., & Vohs, K. D. (2014). Ego depletion decreases trust in economic decision making. Journal of Experimental Social Psychology, 54, 40-49.
[7]Altieri, N., Stevenson, R. A., Wallace, M. T., & Wenger, M. J. (2015). Learning to associate auditory and visual stimuli: behavioral and neural mechanisms. Brain Topography, 28(3), 479-493.
[8]Ancona, D. G., Okhuysen, G. A., & Perlow, L. A. (2001). Taking time to integrate temporal research. Academy of Management Review, 26(4), 512-529.
[9]Antonides, G., Verhoef, P. C., & Van Aalst, M. (2000). Consumer perception and evaluation of waiting time. Journal of Consumer Psychology, 12(3), 193-202
[10]Ashman, R., Solomon, M. R., & Wolny, J. (2015). An old model for a new age: Consumer decision making in participatory digital culture. Journal of Customer Behaviour, 14(2), 127-146.
[11]Atalay, A. S., & Meloy, M. G. (2011). Retail therapy: A strategic effort to improve mood. Psychology & Marketing, 28(6), 638-659.
[12]Aydın, E. A., Bay, Ö. F., & Güler, İ. (2016). Implementation of an embedded web server application for wireless control of brain computer interface based home environments. Journal of Medical Systems, 40(1), 1-10.
[13]Babin, B. J., & Attaway, J. S. (2000). Atmospheric affect as a tool for creating value and gaining share of customer. Journal of Business Research, 49(2), 91-99.
[14]Bailey, N., & Areni, C. S. (2006). When a few minutes sound like a lifetime: Does atmospheric music expand or contract perceived time?. Journal of Retailing, 82(3), 189-202.
[15]Baker, J., & Cameron, M. (1996). The effects of the service environment on affect and consumer perception of waiting time: An integrative review and research propositions. Journal of the Academy of Marketing Science, 24(4), 338-349.
[16]Baker, J., Parasuraman, A., Grewal, D., & Voss, G. B. (2002). The influence of multiple store environment cues on perceived merchandise value and patronage intentions. Journal of Marketing, 66(2), 120-141.
[17]Bang, J. W., Lee, E. C., & Park, K. R. (2011). New computer interface combining gaze tracking and brainwave measurements. Consumer Electronics, IEEE Transactions on, 57(4), 1646-1651.
[18]Beaudry, A., & Pinsonneault, A. (2010). The other side of acceptance: studying the direct and indirect effects of emotions on information technology use. MIS Quarterly, 689-710.
[19]Bernat, E. M., Williams, W. J., & Gehring, W. J. (2005). Decomposing ERP time–frequency energy using PCA. Clinical Neurophysiology, 116(6), 1314-1334.
[20]Bielen, F., & Demoulin, N. (2007). Waiting time influence on the satisfaction-loyalty relationship in services. Managing Service Quality: An International Journal, 17(2), 174-193.
[21]Blakemore, S. J., & Frith, U. (2005). The learning brain: Lessons for education. Blackwell publishing.
[22]Borges, A., Herter, M. M., & Chebat, J. C. (2015). “It was not that long!” : The effects of the in-store TV screen content and consumers emotions on consumer waiting perception. Journal of Retailing and Consumer Services, 22, 96-106.
[23]Brann, D. M., & Kulick, B. C. (2002, December). Simulation of customer-focused business processes: simulation of restaurant operations using the restaurant modeling studio. In Proceedings of the 34th conference on winter simulation: exploring new frontiers (pp. 1448-1453). Winter Simulation Conference.
[24]Buckner, R. L. (2013). The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron, 80(3), 807-815.
[25]Cameron, M. A., Baker, J., Peterson, M., & Braunsberger, K. (2003). The effects of music, wait-length evaluation, and mood on a low-cost wait experience. Journal of Business Research, 56(6), 421-430.
[26]Caldwell, C., & Hibbert, S. A. (2002). The influence of music tempo and musical preference on restaurant patrons’ behavior. Psychology and Marketing, 19(11), 895-917.
[27]Casado Diaz, A. B., & Más Ruíz, F. J. (2002). The consumer''s reaction to delays in service. International Journal of Service Industry Management, 13(2), 118-140.
[28]Chien, S. Y., & Lin, Y. T. (2015). The effects of the service environment on perceived waiting time and emotions. Human Factors and Ergonomics in Manufacturing & Service Industries, 25(3), 319-328.
[29]Choi, C., & Sheel, A. (2012). Assessing the relationship between waiting services and customer satisfaction in family restaurants. Journal of Quality Assurance in Hospitality & Tourism, 13(1), 24-36.
[30]Choi, S. J., & Kang, B. G. (2014). Prototype design and implementation of an automatic control system based on a BCI. Wireless Personal Communications, 79(4), 2551-2563.
[31]Chung-Herrera, B. G. (2007). Customers'' psychological needs in different service industries. Journal of Services Marketing, 21(4), 263-269.
[32]Conroy, M. A., & Polich, J. (2007). Normative variation of P3a and P3b from a large sample: Gender, topography, and response time. Journal of Psychophysiology, 21(1), 22-32.
[33]Cozolino, L. (2014). The Neuroscience of Human Relationships: Attachment and the Developing Social Brain (Norton Series on Interpersonal Neurobiology). WW Norton & Company.
[34]Cronin Jr, J. J., & Taylor, S. A. (1992). Measuring service quality: a reexamination and extension. The Journal of Marketing, 55-68.
[35]Cui, S., & Veeraraghavan, S. (2016). Blind queues: The impact of consumer beliefs on revenues and congestion. Management Science, 62(12), 3656-3672.
[36]Curin, S. A., Vosko, J. S., Chan, E. W., & Tsimhoni, O. (2005, December). Reducing service time at a busy fast food restaurant on campus. In Proceedings of the 37th conference on Winter simulation (pp. 2628-2635). Winter Simulation Conference.
[37]Dabholkar, P. A., & Sheng, X. (2008). Perceived download waiting in using web sites: a conceptual framework with mediating and moderating effects. Journal of Marketing Theory and Practice, 16(3), 259-270.
[38]Davis, R., Rogers, T., & Huang, Y. (2016, January). A Survey of recent developments in queue wait time forecasting methods. In Proceedings of the International Conference on Foundations of Computer Science (FCS) (p. 84). The Steering Committee of the World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp).
[39]De Koning, B. B., & van der Schoot, M. (2013). Becoming part of the story! Refueling the interest in visualization strategies for reading comprehension. Educational Psychology Review, 25(2), 261-287.
[40]Demoulin, N. T., & Djelassi, S. (2013). Customer responses to waits for online banking service delivery. International Journal of Retail & Distribution Management, 41(6), 442-460.
[41]Dreher J. & Tremblay L. (2016). Decision Neuroscience: An Integrative Perspective. Academic Press, New York.
[42]Duffy, F. H. (Ed.). (2013). Topographic mapping of brain electrical activity. Butterworth-Heinemann.
[43]Duncan, C. C., Barry, R. J., Connolly, J. F., Fischer, C., Michie, P. T., Näätänen, R., ... & Van Petten, C. (2009). Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clinical Neurophysiology, 120(11), 1883-1908.
[44]Duysens, J., Schaafsma, S. J., & Orban, G. A. (1996). Cortical off response tuning for stimulus duration. Vision Research, 36(20), 3243-3251.
[45]Engel, J.F., Blackwell R.D., & Miniard, P.W. (1995). Consumer Behavior(8th ed). Fort Worth: Dryden Press, Texas.
[46]Engel, J.F., Kollat, D.J., & Blackwell, R.D. (1973). Consumer Behavior, (2nd ed). New York: Holt Rinehart and Winston.
[47]Farwell, L. A., & Smith, S. S. (2001). Using brain MERMER testing to detect knowledge despite efforts to conceal. Journal of Forensic Science, 46(1), 135-143.
[48]Ferreira, M. A. M., Andrade, M., Filipe, J. A., & Coelho, M. P. (2012). Statistical queuing theory with some applications. International Journal of Latest Trends in Finance and Economic Sciences, 1(4), 190-195.
[49]Ferstl, E. C., Rinck, M., & Von Cramon, D. Y. (2005). Emotional and temporal aspects of situation model processing during text comprehension: An event-related fMRI study. Journal of Cognitive Neuroscience, 17(5), 724-739.
[50]Fetsch, C. R., Pouget, A., DeAngelis, G. C., & Angelaki, D. E. (2011). Neural correlates of reliability-based cue weighting during multisensory integration. Nature Neuroscience, 15(1), 146.
[51]Fink, R., & Gillett, J. (2006). Queuing theory and the Taguchi loss function: The cost of customer dissatisfaction in waiting lines. International Journal of Strategic Cost Management, 17.
[52]Fitzsimons, G. J. (2008). Death to dichotomizing. Journal of Consumer Research, 35(1), 5–8.
[53]Fleischmann, M., Amirpur, M., Grupp, T., Benlian, A., & Hess, T. (2016). The role of software updates in information systems continuance—An experimental study from a user perspective. Decision Support Systems, 83, 83-96.
[54]Folkman, S., & Moskowitz, J. T. (2004). Coping: Pitfalls and promise. Annu. Rev. Psychol., 55, 745-774.
[55]Fonseca, L. C., Tedrus, G. M., Prandi, L. R., Almeida, A. M., & Furlanetto, D. S. (2011). Alzheimer''s disease: relationship between cognitive aspects and power and coherence EEG measures. Arquivos de Neuro-Psiquiatria, 69(6), 875-881.
[56]Forehand, C. J. (2009). Integrative functions of the nervous system. Medical physiology: Principles for Clinical Medicine, 122-139.
[57]Fraga, F. J., Falk, T. H., Kanda, P. A., & Anghinah, R. (2013). Characterizing Alzheimer’s disease severity via resting-awake EEG amplitude modulation analysis. PLoS One, 8(8), e72240.
[58]Fraiman, D., Saunier, G., Martins, E. F., & Vargas, C. D. (2014). Biological motion coding in the brain: analysis of visually driven EEG functional networks. PloS one, 9(1), e84612.
[59]Friedman, N. P., & Miyake, A. (2000). Differential roles for visuospatial and verbal working memory in situation model construction. Journal of Experimental Psychology: General, 129, 61-83.
[60]Friman, M. (2010). Affective dimensions of the waiting experience. Transportation Research Part F: Traffic Psychology and Behaviour, 13(3), 197-205.
[61]Fullerton, G., & Taylor, S. (2015). Dissatisfaction and violation: two distinct consequences of the wait experience. Journal of Service Theory and Practice, 25(1), 31-50.
[62]Fuster, J. M. (2004). Upper processing stages of the perception–action cycle. Trends in Cognitive Sciences, 8(4), 143-145.
[63]Fuster, J. M., & Bressler, S. L. (2012). Cognit activation: a mechanism enabling temporal integration in working memory. Trends in Cognitive Sciences, 16(4), 207-218
[64]Gajewski, P. D., Drizinsky, J., Zülch, J., & Falkenstein, M. (2016). ERP correlates of simulated purchase decisions. Frontiers in Neuroscience, 10.
[65]Giebelhausen, M. D., Robinson, S. G., & Cronin Jr, J. J. (2011). Worth waiting for: increasing satisfaction by making consumers wait. Journal of the Academy of Marketing Science, 39(6), 889-905.
[66]Goodrich, J. N. (1978). The relationship between preferences for and perceptions of vacation destinations: Application of a choice model. Journal of Travel Research, 17(2), 8-13.
[67]Gorn, J. G., Chattopadhyay, A., Sengupta, J., Tripathi, S. (2004). Waiting for the web: How screen color affect time perception. Journal of Marketing Research, 41(2), 215-225.
[68]Grewal, D., Baker, J., Levy, M., & Voss, G. B. (2003). The effects of wait expectations and store atmosphere evaluations on patronage intentions in service-intensive retail stores. Journal of Retailing, 79(4), 259-268.
[69]Grönroos, C. (2007). Service management and marketing: customer management in service competition. New York: John Wiley & Sons.
[70]Gruber, R. P., & Block, R. A. (2013). The flow of time as a perceptual illusion. The Journal of Mind and Behavior, 91-100.
[71]Gutek, B. (2000). Service relationships, pseudo-relationships, and encounters. In T. Swartz & D. Iacobucci (Eds.), Handbook of services marketing and management: 371–379. Thousand Oaks, CA: Sage.
[72]Hassin, R., & Haviv, M. (2003). To queue or not to queue: Equilibrium behavior in queueing systems. Springer Science & Business Media.
[73]Hayes, A. F. (2016). PROCESS: a versatile computational tool for observed variable mediation, moderation, and conditional process modeling. 2012. Acesso em, 2.
[74]Hayes, A. F., & Rockwood, N. J. (2016). Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. Behaviour Research and Therapy.
[75]Haykin, S. (2012). Cognitive dynamic systems: perception-action cycle, radar and radio. Cambridge University Press.
[76]He, J., Hashikawa, T., Ojima, H., & Kinouchi, Y. (1997). Temporal integration and duration tuning in the dorsal zone of cat auditory cortex. Journal of Neuroscience, 17(7), 2615-2625.
[77]Herbst, S. K., Penney, T. B., Chaumon, M., & Busch, N. A. (2014). Signatures of subjective time perception in the ERP during Stimulus Encoding. Procedia-Social and Behavioral Sciences, 126, 227-228.
[78]Hernandez-Maskivker, G., Ryan, G. A., del Mar Pàmies, M., & Chicu, D. (2014, January). Make me wait: When waiting is not always negative. In Academy of Management Proceedings, 2014(1), 11695.
[79]Herrmann, C. S., & Mecklinger, A. (2001). Gamma activity in human EEG is related to highspeed memory comparisons during object selective attention. Visual Cognition, 8(3-5), 593-608.
[80]Heung, V. C. S., & Gu, T. (2012). Influence of restaurant atmospherics on patron satisfaction and behavioral intentions. International Journal of Hospitality Management, 31(4), 1167-1177.
[81]Heyman, D. P. (2013). Queueing Theory. In Encyclopedia of Operations Research and Management Science (pp. 1234-1244). Springer US.
[82]Holloway, B. B., Wang, S., & Parish, J. T. (2005). The role of cumulative online purchasing experience in service recovery management. Journal of Interactive Marketing, 19(3), 54-66.
[83]Homan, R. W., Herman, J., & Purdy, P. (1987). Cerebral location of international 10–20 system electrode placement. Electroencephalography and Clinical Neurophysiology, 66(4), 376-382.
[84]Howard, J. A. (1989). Consumer behavior in marketing strategy. Prentice Hall.
[85]Howard, John A. & J. N. Sheth. (1969). The theory of buyer behavior. New Yourk: John wiley & Sons.
[86]Hsee, C. K. and Y. Rottenstreich (2004). “Music, pandas, and muggers: On the affective psychology of value.?Journal of Experimental Psychology: General 133(1): 23-30.
[87]Hubert, M., & Kenning, P. (2008). A current overview of consumer neuroscience. Journal of Consumer Behaviour, 7(4-5), 272-292.
[88]Hui, M. K., & Tse, D. K. (1996). What to tell consumers in waits of different lengths: An integrative model of service evaluation. The Journal of Marketing, 60(2), 81-90.
[89]Hui, M. K., Tse, A. C., & Zhou, L. (2006). Interaction between two types of information on reactions to delays. Marketing Letters, 17(2), 151-162.
[90]Hwang, J. (2008). Restaurant table management to reduce customer waiting times. Journal of Foodservice Business Research, 11(4), 334-351.
[91]Hyytiä, E., Penttinen, A., & Aalto, S. (2012). Size-and state-aware dispatching problem with queue-specific job sizes. European Journal of Operational Research, 217(2), 357-370.
[92]Ibrahim, F., Harun, W. M., & Samad, M. H. (2010). The waiting space environment: perception by design. American Journal of Engineering and Applied Sciences, 3(3), 569-575.
[93]Iman, R., & Borimnejad, V. (2017). Analysis of quality of services for checkout operation in Refah chain stores using queuing theory. Journal of Foodservice Business Research, 20(1), 106-115.
[94]Jisana T. K.(2014). Consumer Behaviour Models: An Overview. Sai Om Journal of Commerce & Management, 1(5), 34-43.
[95]Johnson, A. R., & Stewart, D. W. (2005). A reappraisal of the role of emotion in consumer behavior. In Review of marketing research (pp. 3-34). Emerald Group Publishing Limited.
[96]Jones Jr, H. R., Srinivasan, J., Allam, G. J., & Baker, R. A. (2011). Netter''s Neurology. Elsevier Health Sciences.
[97]Jurcak, V., Tsuzuki, D., & Dan, I. (2007). 10/20, 10/10, and 10/5 systems revisited: their validity as relative head-surface-based positioning systems. Neuroimage, 34(4), 1600-1611.
[98]Kahneman, D. (2003). “Maps of Bounded Rationality: Psychology for Behavioral Economics.?American Economic Review 93(5), 1449-1475.
[99]Kaiser, D. A. (2010). Cortical cartography. Biofeedback, 38(1), 9-12.
[100]Kartz, K., Larson, B., & Larson, R. (1991). Prescriptions for the waiting in line blues: entertain, enlighten, and engage. Sloan Management Review, 32, 44-53.
[101]Kasturi Nirmala & Shahnaz Bathul (2013). A case study of bank queueing model. International Journal of Engineering Research and Development, 5(10), 11-18.
[102]Kaufman-Scarborough, C. (2006). Time use and the impact of technology examining workspaces in the home. Time & Society, 15(1), 57-80.
[103]Kaur, C., & Singh, P. (2015). EEG derived neuronal dynamics during meditation: progress and challenges. Advances in preventive medicine, 2015.
[104]Kc, D.S, Terwiesch, C. (2011). The effects of focus on performance: evidence from California hospitals. Management Science, 57(11), 1897-1912.
[105]Keil, A., Müller, M. M., Gruber, T., Wienbruch, C., Stolarova, M., & Elbert, T. (2001). Effects of emotional arousal in the cerebral hemispheres: a study of oscillatory brain activity and event-related potentials. Clinical Neurophysiology, 112(11), 2057-2068.
[106]Khurana, I. (2006). Textbook of medical physiology. Kundli, India: Elsevier.
[107]Khushaba, R. N., Wise, C., Kodagoda, S., Louviere, J., Kahn, B. E., & Townsend, C. (2013). Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking. Expert Systems with Applications, 40(9), 3803-3812.
[108]Kim, S., Miao, L., & Magnini, V. P. (2016). Consumers’ emotional responses and emotion regulation strategies during multistage waiting in restaurants. Journal of Hospitality and Tourism Research, 40(3), 291-318.
[109]Koessler, L., Maillard, L., Benhadid, A., Vignal, J. P., Felblinger, J., Vespignani, H., & Braun, M. (2009). Automated cortical projection of EEG sensors: anatomical correlation via the international 10–10 system. Neuroimage, 46(1), 64-72.
[110]Kotler, P. (2000). Marketing Management, 10th Edition, Upper Saddle River, New Jersey: Prentice Hall.
[111]Krain, A. L., Wilson, A. M., Arbuckle, R., Castellanos, F. X., & Milham, M. P. (2006). Distinct neural mechanisms of risk and ambiguity: a meta-analysis of decision-making. Neuroimage, 32(1), 477-484.
[112]Kramer, R. S., Weger, U. W., & Sharma, D. (2013). The effect of mindfulness meditation on time perception. Consciousness and Cognition, 22(3), 846-852.
[113]Krebs, C. (2011). Neuroscience (pp. 31). Lippincott Williams & Wilkins.
[114]Kuan, K. K., Zhong, Y., & Chau, P. Y. (2014). Informational and normative social influence in group-buying: Evidence from self-reported and EEG data. Journal of Management Information Systems, 30(4), 151-178.
[115]Kuder, G. F., & Richardson, M. W. (1937). The theory of the estimation of test reliability. Psychometrika, 2(3), 151-160.
[116]Künzel, H. E., Murck, H., Stalla, G. K., & Steiger, A. (2011). Changes in the sleep electroencephalogram (EEG) during male to female transgender therapy. Psychoneuroendocrinology, 36(7), 1005-1009.
[117]Ladipo, P. K., Olufayo, T. O., & Bakare, R. D. (2012). Learning construct: Its implication for marketing and buyer’s perception of product stimulus. American Journal of Business and Management, 1(3), 119-123.
[118]Lake, J. I., LaBar, K. S., & Meck, W. H. (2016). Emotional modulation of interval timing and time perception. Neuroscience & Biobehavioral Reviews, 64, 403-420.
[119]Lakshmi, C., & Iyer, S. A. (2013). Application of queueing theory in health care: A literature review. Operations Research for Health Care, 2(1), 25-39.
[120]Lam, S. S. W., & Ong, M. E. H. (2013). Application of queuing analytic theory to decrease waiting times in emergency department: Does it make sense?. Archives of Trauma Research, 2(3), 136.
[121]Leclerc, F., Schmitt, B. H., & Dube, L. (1995). Waiting time and decision making: Is time like money?. Journal of Consumer Research, 22(1), 110-119.
[122]Lee, L. Y., & Li, L. Y. (2014). Effects of servicescape, waiting motivation and conformity on time perception and behavioral intentions. International Journal of Marketing Studies, 6(4), 83.
[123]Lee, N., Broderick, A. J., & Chamberlain, L. (2007). What is ‘neuromarketing’? A discussion and agenda for future research. International Journal of Psychophysiology, 63(2), 199-204.
[124]Lees-Miller, J. D. (2016). Minimising average passenger waiting time in personal rapid transit systems. Annals of Operations Research, 236(2), 405-424.
[125]Li, X., & Ling, W. (2015). How framing effect impact on decision making on Internet shopping. Open Journal of Business and Management, 3(1), 96-108.
[126]Liang, C. C. (2016). Queueing management and improving customer experience: empirical evidence regarding enjoyable queues. Journal of Consumer Marketing, 33(4), 257-268.
[127]Lin, J. S., & Yang, W. C. (2012). Wireless brain-computer interface for electric wheelchairs with EEG and eye-blinking signals. Int. J. Innov. Comput. Inf. Control, 8(9), 6011-6024.
[128]Lin, Y. T., Xia, K. N., & Bei, L. T. (2015). Customer''s perceived value of waiting time for service events. Journal of Consumer Behaviour, 14(1), 28-40.
[129]Liu, Y., Jang, S. (2009). The effects of dining atmospherics: an extended Mehrabian-Russell model. International Journal of Hospitality Management, 28(4), 494-503.
[130]Lotrakul, M., Sumrithe, S., and Saipanish, R. (2008). Reliability and validity of the Thai version of the PHQ-9. BMC Psychiatry, 8(46), 1-7.
[131]Lovelock, C. (2011). Services marketing: People, technology, strategy. Pearson Education India.
[132]Lovelock, C., & Gummesson, E. (2004). Whither services marketing? In search of a new paradigm and fresh perspectives. Journal of Service Research, 7(1), 20-41.
[133]Lu, Y., Musalem, A., Olivares, M., & Schilkrut, A. (2013). Measuring the effect of queues on customer purchases. Management Science, 59(8), 1743-1763.
[134]Luck, S. J., Woodman, G. F., & Vogel, E. K. (2000). Event-related potential studies of attention. Trends in Cognitive Sciences, 4(11), 432-440.
[135]Lui, M. A., Penney, T. B., & Schirmer, A. (2011). Emotion effects on timing: Attention versus pacemaker accounts. PLoS ONE, 6(7), e21829.
[136]Machleit, K. A., & Eroglu, S. A. (2000). Describing and measuring emotional response to shopping experience. Journal of Business Research, 49(2), 101–111.
[137]Maister, D. H. (1984). The psychology of waiting lines. Harvard Business School.
[138]Malmivuo, J., & Plonsey, R. (1995). Bioelectromagnetism: principles and applications of bioelectric and biomagnetic fields. Oxford University Press, USA.
[139]Mansor, W., Rani, M. S. A., & Wahy, N. (2011). Integrating neural signal and embedded system for controlling small motor. INTECH Open Access Publisher.
[140]Marsh, H. W., Dowson, M., Pietsch, J., & Walker, R. (2004). Why multicollinearity matters: a reexamination of relations between self-efficacy, self-concept, and achievement. Journal of Educational Psychology, 96(3), 518.
[141]Martini, N., Menicucci, D., Sebastiani, L., Bedini, R., Pingitore, A., Vanello, N., Milanesi, M., Landini, L. & Gemignani, A. (2012). The dynamics of EEG gamma responses to unpleasant visual stimuli: From local activity to functional connectivity. NeuroImage, 60(2), 922-932.
[142]Mattila, A. S., & Hanks, L. (2012). Time styles and waiting in crowded service environments. Journal of Travel & Tourism Marketing, 29(4), 327-334.
[143]Mayer, R. E. (2005). Principles for reducing extraneous processing in multimedia learning: Coherence, signaling, redundancy, spatial contiguity, and temporal contiguity principles. In Mayer, R. E. (ed). The Cambridge handbook of multimedia learning. 183-200. New York: Cambridge University Press.
[144]McGonagle, A. K., Fisher, G. G., Barnes-Farrell, J. L., & Grosch, J. W. (2015). Individual and work factors related to perceived work ability and labor force outcomes. Journal of Applied Psychology, 100(2), 376.
[145]McNerney, M. W., Goodwin, K. A., & Radvansky, G. A. (2011). A novel study: A situation model analysis of reading times. Discourse Processes, 48(7), 453-474.
[146]Mella, N., Conty, L., & Pouthas, V. (2011). The role of physiological arousal in time perception: psychophysiological evidence from an emotion regulation paradigm. Brain and Cognition, 75(2), 182-187.
[147]Merchant, H., & De Lafuente, V. (2014). Neurobiology of interval timing. Springer New York.
[148]Mihajlović, V., Grundlehner, B., Vullers, R., & Penders, J. (2015). Wearable, wireless EEG solutions in daily life applications: what are we missing?. IEEE Journal of Biomedical and Health Informatics, 19(1), 6-21.
[149]Miklós-Thal, J., & Zhang, J. (2013). (De) marketing to manage consumer quality inferences. Journal of Marketing Research, 50(1), 55-69.
[150]Miller, J. (1988). Discrete and continuous models of human information processing: Theoretical distinctions and empirical results. Acta Psychologica, 67(3), 191-257.
[151]Miller, M. M., & Strongman, K. T. (2002). The emotional effects of music on religious experience: A study of the Pentecostal-charismatic style of music and worship. Psychology of Music, 30(1), 8-27.
[152]Milner, T., & Rosenstreich, D. (2013). A review of consumer decision-making models and development of a new model for financial services. Journal of Financial Services Marketing, 18(2), 106-120.
[153]Mishalani, R. G., McCord, M. M., & Wirtz, J. (2006). Passenger wait time perceptions at bus stops: Empirical results and impact on evaluating real-time. Journal of Public Transportation, 9(2), 89-106.
[154]Mishalani, R., Lee, S., & McCord, M. (2000). Evaluating real-time bus arrival information systems. Transportation Research Record: Journal of the Transportation Research Board, (1731), 81-87.
[155]Montoya-Weiss, M., Voss, G. B., & Grewal, D. (2003). Online channel use and satisfaction in a multichannel service context. MSI Reports, 2(3), 19-35.
[156]Moreno, E. M., & Rivera, I. C. (2013). Setbacks, pleasant surprises and the simply unexpected: brainwave responses in a language comprehension task. Social cognitive and affective neuroscience, 9(7), 991-999.
[157]Moretti, D. V., Babiloni, C., Binetti, G., Cassetta, E., Dal Forno, G., Ferreric, & Rodriguez, G. (2004). Individual analysis of EEG frequency and band power in mild Alzheimer''s disease. Clinical Neurophysiology, 115(2), 299-308.
[158]Mousa, F. A., El-Khoribi, R. A., & Shoman, M. E. (2015). EEG Classification based on Machine Learning Techniques. Signal, 128(4).
[159]Moutinho, L. (2000). Strategic Management in Tourism. UK: Biddles Ltd, and Guildford and King’s Lynn.
[160]Müller, M. M., Gruber, T., & Keil, A. (2000). Modulation of induced gamma band activity in the human EEG by attention and visual information processing. International Journal of Psychophysiology, 38(3), 283-299.
[161]Munichor, N., & Rafaeli, A. (2007). Numbers or apologies? Customer reactions to telephone waiting time fillers. Journal of Applied Psychology, 92(2), 511.
[162]Murat, Z. H., Taib, M. N., Hanafiah, Z. M., Lias, S., Kadir, R. S. S. A., & Rahman, H. A. (2009). Initial investigation of brainwave synchronization after five sessions of Horizontal Rotation intervention using EEG. In Signal Processing & Its Applications, 2009. CSPA 2009. 5th International Colloquium on (pp. 350-354). IEEE.
[163]Murugappan, M., Rizon, M., Nagarajan, R., Yaacob, S., Hazry, D., & Zunaidi, I. (2008). Time-frequency analysis of EEG signals for human emotion detection. In 4th Kuala Lumpur International Conference on Biomedical Engineering 2008 (pp. 262-265). Springer Berlin Heidelberg.
[164]Mwangi, S. K., & Ombuni, T. M. (2015). An Empirical Analysis of Queuing Model and Queuing Behaviour in Relation to Customer Satisfaction at Jkuat Students Finance Office. American Journal of Theoretical and Applied Statistics, 4(4), 233-246.
[165]Nath, A. R., & Beauchamp, M. S. (2011). Dynamic changes in superior temporal sulcus connectivity during perception of noisy audiovisual speech. Journal of Neuroscience, 31(5), 1704-1714.
[166]Naumann, S., & Miles, J. A. (2001). Managing waiting patients'' perceptions: the role of process control. Journal of Management in Medicine, 15(5), 376-386.
[167]Newell, C. (2013). Applications of queueing theory (Vol. 4). Springer Science & Business Media.
[168]Nicosia, F. M. (1966). Consumer decision processes: Marketing and advertising implications. Englewood Cliffs, N.J.: Prentice-Hall. Chicago Style Citation.
[169]Nunnally, J.C., 1978. Psychometric Theory, 2nd ed. McGraw–Hill, New York, NY
[170]Nuttavuthisit, K. (2014). How consumers as aesthetic subjects co-create the aesthetic experience of the retail environment. Journal of Retailing and Consumer Services, 21(4), 432-437.
[171]Ohme, R., Reykowska, D., Wiener, D., & Choromanska, A. (2010). Application of frontal EEG asymmetry to advertising research. Journal of Economic Psychology, 31(5), 785-793.
[172]Okamoto, M., Dan, H., Sakamoto, K., Takeo, K., Shimizu, K., Kohno, S., Oda I., Isobe, S., Suzuki, T. Kohyama, K. & Dan, I. (2004). Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10–20 system oriented for transcranial functional brain mapping. Neuroimage, 21(1), 99-111.
[173]Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418-430.
[174]Osorio, I., Zaveri, H. P., Frei, M. G., & Arthurs, S. (2016). Epilepsy: the intersection of neurosciences, biology, mathematics, engineering, and physics. CRC press.
[175]Othman, M., Wahab, A., Karim, I., Dzulkifli, M. A., & Alshaikli, I. F. T. (2013). EEG emotion recognition based on the dimensional models of emotions. Procedia-Social and Behavioral Sciences, 97, 30-37.
[176]Oya, H., Kawasaki, H., Howard, M. A., & Adolphs, R. (2002). Electrophysiological responses in the human amygdala discriminate emotion categories of complex visual stimuli. Journal of Neuroscience, 22(21), 9502-9512.
[177]Palawatta, T. M. B. (2015). Waiting times and defining customer satisfaction. Vidyodaya Journal of Management, 1(1), 15-24.
[178]Panagiotidi, M., & Samartzi, S. (2013). Time estimation: Musical training and emotional content of stimuli. Psychology of Music, 41(5), 620-629.
[179]Parasuraman, A., Valarie A. Z. & Leonard B. (1994). Alternative scales for measuring service quality: A comparative assessment based on psychometric and diagnostic criteria. Journal of Retailing, 70(3), 201-230.
[180]Parker, J. R., & Lehmann, D. R. (2011). When shelf-based scarcity impacts consumer preferences. Journal of Retailing, 87(2), 142-155.
[181]Pasalar, S., Ro, T., & Beauchamp, M. S. (2010). TMS of posterior parietal cortex disrupts visual tactile multisensory integration. European Journal of Neuroscience, 31(10), 1783-1790.
[182]Pearce, P. L. (2016). Tourist Queues. Managing Tourism.
[183]Peate, I., & Nair, M. (2015). Anatomy and Physiology for Nurses at a Glance (pp. 22). John Wiley & Sons.
[184]Polich J. & Kok A. (1995). “Cognitive and biological determinants of P300: an integrative review,” Biological Psychology, 41(2), 103–146.
[185]Polich, J. (2007). Updating P300: an integrative theory of P3a and P3b. Clinical Neurophysiology, 118(10), 2128-2148.
[186]Poltavski, D. V., Biberdorf, D., & Petros, T. V. (2012). Accommodative response and cortical activity during sustained attention. Vision Research, 63, 1-8.
[187]Posner, J., Russell, J. A., & Peterson, B. S. (2005). The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology. Development and Psychopathology, 17(3), 715-734.
[188]Prime, N. (1994). Culture, tempts, negociation commerciale: Le cas des representation du temps et de la negociation des delais de livraison dans cinq pays (Doctoral dissertation, Doctoral Dissertation, Pierre Mendes-France University, Grenoble).
[189]Punj, G., & Stewart, D. W. (1983). Cluster analysis in marketing research: Review and suggestions for application. Journal of Marketing Research, 134-148.
[190]Radvansky, G. A., & Dijkstra, K. (2007). Aging and situation model processing. Psychonomic Bulletin & Review, 14(6), 1027-1042.
[191]Radvansky, G. A., Wyer Jr, R. S., Curiel, J. M., & Lutz, M. F. (1997). Situation models and abstract ownership relations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 23(5), 1233.
[192]Radvansky, G. A., Zwaan, R. A., Curiel, J. M., & Copeland, D. E. (2001). Situation models and aging. Psychology & Aging, 16, 145- 160.
[193]Rafaeli, A., Barron, G., & Haber, K. (2002). The effects of queue structure on attitudes. Journal of Service Research, 5(2), 125-139.
[194]Remington, N. A., Fabrigar, L. R., & Visser, P. S. (2000). Reexamining the circumplex model of affect. Journal of Personality and Social Psychology, 79(2), 286.
[195]Rick, S., Pereira, B., & Burson, K. A. (2014). The benefits of retail therapy: making purchase decisions reduces residual sadness. Forthcoming in the Journal of Consumer Psychology.
[196]Robinson, L. W., & Chen, R. R. (2011). Estimating the implied value of the customer''s waiting time. Manufacturing & Service Operations Management, 13(1), 53-57.
[197]Rozgić, V., Vitaladevuni, S. N., & Prasad, R. (2013, May). Robust EEG emotion classification using segment level decision fusion. In 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 1286-1290). IEEE.
[198]Russell J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161–1178.
[199]Sabelis, I. (2001), “Time management: paradoxes and patterns”. Time & Society, 10, 387-400.
[200]Sanchez-Franco, M. J., & Rondan-Cataluña, F. J. (2010). Virtual travel communities and customer loyalty: Customer purchase involvement and web site design. Electronic Commerce Research and Applications, 9(2), 171-182.
[201]Sauseng, P., Klimesch, W., Gerloff, C., & Hummel, F. C. (2009). Spontaneous locally restricted EEG alpha activity determines cortical excitability in the motor cortex. Neuropsychologia, 47(1), 284-288.
[202]Schiffman, L., O''Cass, A., Paladino, A., & Carlson, J. (2013). Consumer behaviour. Pearson Higher Education AU.
[203]Schirmer, A., Meck, W. H., & Penney, T. B. (2016). The socio-temporal brain: Connecting people in time. Trends in Cognitive Sciences, 20(10), 760-772.
[204]Schmeichel, B. E., Zemlan, F. P., & Berridge, C. W. (2013). A selective dopamine reuptake inhibitor improves prefrontal cortex-dependent cognitive function: potential relevance to attention deficit hyperactivity disorder. Neuropharmacology, 64, 321-328.
[205]Schnotz, W. (2005). Congnitive theory of multimedia learning. In Mayer, R. E. The Cambridge handbook of multimedia learning (ed). 49-70. NJ: Cambridge University Press.
[206]Schubotz, R. I., Friederici, A. D., & Von Cramon, D. Y. (2000). Time perception and motor timing: a common cortical and subcortical basis revealed by fMRI. Neuroimage, 11(1), 1-12.
[207]Schutte, N. M., Hansell, N. K., De Geus, E. J., Martin, N. G., Wright, M. J., & Smit, D. J. (2013). Heritability of resting state EEG functional connectivity patterns. Twin Research and Human Genetics, 16(05), 962-969.
[208]Seawright, K. K., & Sampson, S. E. (2007). A video method for empirically studying wait-perception bias. Journal of Operations Management, 25(5), 1055-1066.
[209]Semrud-Clikeman, M., & Ellison, P. A. T. (2009). Child neuropsychology: Assessment and interventions for neurodevelopmental disorders. Springer Science & Business Media.
[210]Shankle, W. R., & Amen, D. G. (2005). Preventing Alzheimer''s: Ways to help prevent, delay, detect, and even halt Alzheimer''s disease and other forms of memory loss. Penguin.
[211]Shibasaki, M., & Masataka, N. (2014). The color red distorts time perception for men, but not for women. Scientific Reports, 4, 5899.
[212]Shiv, B. & Yoon, C. (2012). Integrating neurophysiological and psychological approaches: toward an advancement of brand insights. Journal of Consumer Psychology, 22(1), 3-6.
[213]Slovic, P., Finucane, M., Peters, E., & MacGregor, D. G. (2002). Rational actors or rational fools: Implications of the affect heuristic for behavioral economics. The Journal of Socio-Economics, 31(4), 329-342.
[214]Smith, G. L., Xu, Y., Buchholz, T. A., Giordano, S. H., Jiang, J., Shih, Y. C. T., & Smith, B. D. (2012). Association between treatment with brachytherapy vs whole-breast irradiation and subsequent mastectomy, complications, and survival among older women with invasive breast cancer. Jama, 307(17), 1827-1837.
[215]Southworth, J., Munroe, D., & Nagendra, H. (2004). Land cover change and landscape fragmentation—comparing the utility of continuous and discrete analyses for a western Honduras region. Agriculture, Ecosystems & Environment, 101(2), 185-205.
[216]Stuss, D. T., & Knight, R. T. (2013). Principles of frontal lobe function. Oxford University Press.
[217]Swartz, T., & Iacobucci, D. (2000). Handbook of services marketing and management. Sage.
[218]Sztrik, J. (2012). Basic queueing theory. University of Debrecen, Faculty of Informatics, 193.
[219]Tamm, M., Uusberg, A., Allik, J., & Kreegipuu, K. (2014). Emotional modulation of attention affects time perception: Evidence from event-related potentials. Acta Psychologica, 149, 148-156.
[220]Telpaz, A., Webb, R., & Levy, D. J. (2015). Using EEG to predict consumers'' future choices. Journal of Marketing Research, 52(4), 511-529.
[221]Teo, T. S., & Yeong, Y. D. (2003). Assessing the consumer decision process in the digital marketplace. Omega, 31(5), 349-363.
[222]Teplan, M. (2002). Fundamentals of EEG measurement. Measurement Science Review, 2(2), 1-11.
[223]Terraciano, A., McCrae, R. R., & Costa Jr, P. T. (2003). Factorial and construct validity of the Italian Positive and Negative Affect Schedule (PANAS). European Journal of Psychological Assessment, 19(2), 131.
[224]Thayer, R. E. (1990). The biopsychology of mood and arousal. Oxford University Press.
[225]Tiedens, L. Z., & Linton, S. (2001). Judgment under emotional certainty and uncertainty: the effects of specific emotions on information processing. Journal of Personality and Social Psychology, 81(6), 973.
[226]Tirtiroglu, E., & Elbeck, M. (2008). Qualifying Purchase Intentions Using Queueing Theory. Journal of Applied Quantitative Methods, 3(2), 167-168.
[227]Tremblay S., Fortin C. (2003). Break expectancy in duration discrimination. J. Exp. Psychol. Hum. Percept. Perform. 29, 238–831. 10.1037/0096-1523.29.4.823
[228]Tsuzuki, D., & Dan, I. (2014). Spatial registration for functional near-infrared spectroscopy: from channel position on the scalp to cortical location in individual and group analyses. Neuroimage, 85, 92-103.
[229]Turley, L. W., & Milliman, R. E. (2000). Atmospheric effects on shopping behavior: a review of the experimental evidence. Journal of Business Research, 49(2), 193-211.
[230]Usunier, J. C., & Valette-Florence, P. (2007). The Time Styles Scale: A review of developments and replications over 15 years. Time & Society, 16(2-3), 333-366.
[231]van Ede, F., de Lange, F., Jensen, O., & Maris, E. (2011). Orienting attention to an upcoming tactile event involves a spatially and temporally specific modulation of sensorimotor alpha-and beta-band oscillations. The Journal of Neuroscience, 31(6), 2016-2024.
[232]Veeraraghavan, S., & Debo, L. (2009). Joining longer queues: Information externalities in queue choice. Manufacturing & Service Operations Management, 11(4), 543-562.
[233]Verbeke, W. J., Pozharliev, R., Van Strien, J. W., Belschak, F., & Bagozzi, R. P. (2014). I am resting but rest less well with you. The moderating effect of anxious attachment style on alpha power during EEG resting state in a social context. Frontiers in human neuroscience, 8, 486.
[234]Vessey, I. (1991). Cognitive fit: A theory‐based analysis of the graphs versus tables literature. Decision Sciences, 22(2), 219-240.
[235]Vilaplana, J., Solsona, F., Teixidó, I., Mateo, J., Abella, F., & Rius, J. (2014). A queuing theory model for cloud computing. The Journal of Supercomputing, 69(1), 492-507.
[236]Vourvopoulos, A., & Liarokapis, F. (2014). Evaluation of commercial brain–computer interfaces in real and virtual world environment: A pilot study. Computers & Electrical Engineering, 40(2), 714-729.
[237]Wang, S., Noe, R. A., & Wang, Z. M. (2014). Motivating knowledge sharing in knowledge management systems a quasi–field experiment. Journal of Management, 40(4), 978-1009.
[238]Wang, X., Song, C., & Zhuang, J. (2015). Simulating a multi-stage screening network: A queueing theory and game theory application. In Game Theoretic Analysis of Congestion, Safety and Security (pp. 55-80). Springer International Publishing.
[239]Wang, Y., Guo, J., Ceder, A. A., Currie, G., Dong, W., & Yuan, H. (2014). Waiting for public transport services; Queueing analysis with balking and reneging behaviors of impatient passengers. Transportation Research Part B: Methodological, 63, 53-76.
[240]Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063.
[241]Watson, L., & Spence, M. T. (2007). Causes and consequences of emotions on consumer behaviour: A review and integrative cognitive appraisal theory. European Journal of Marketing, 41(5/6), 487-511.
[242]West, A. (2010). Strategies for older elementary students struggling with reading comprehension (Doctoral dissertation, Vanderbilt University. Peabody College).
[243]Wiener, M., Turkeltaub, P., & Coslett, H. B. (2010). The image of time: a voxel-wise meta-analysis. Neuroimage, 49(2), 1728-1740.
[244]Wiler, J. L., Bolandifar, E., Griffey, R. T., Poirier, R. F., & Olsen, T. (2013). An emergency department patient flow model based on queueing theory principles. Academic Emergency Medicine, 20(9), 939-946.
[245]Winkler, I., Jäger, M., Mihajlovic, V., & Tsoneva, T. (2010). Frontal EEG asymmetry based classification of emotional valence using common spatial patterns. World Academy of Science, Engineering and Technology, 45, 373-378.
[246]Woermann, N., & Rokka, J. (2015). Timeflow: How consumption practices shape consumers’ temporal experiences. Journal of Consumer Research, 41(6), 1486-1508.
[247]Wojciechowski, J. (2014). Detection of concealed information with of the P300 potential amplitude analysis. European Polygraph, 8(4), 167-188.
[248]Woltering, S., Jung, J., Liu, Z., & Tannock, R. (2012). Resting state EEG oscillatory power differences in ADHD college students and their peers. Behavioral and Brain Functions, 8(1), 1.
[249]Wu, X., Levinson, D. M., & Liu, H. X. (2009). Perception of waiting time at signalized intersections. Journal of the Transportation Research Board, 2135, 52–59. http://dx.doi.org/10.3141/2135-07
[250]Wyer, R. S. (2004). Social comprehension and judgment: The role of situation models, narratives and implicit theories. Mahwah, NJ: Erlbaum.
[251]Yalch, R. F., & Spangenberg, E. R. (2000). The effects of music in a retail setting on real and perceived shopping times. Journal of Business Research, 49(2), 139-147.
[252]Yan, R.N. and Lotz, S. (2006). “The Waiting Game: The Role of Predicted Value, Wait Disconfirmation, and Providers Actions in Consumers Service Evaluations.” Advances in Consumer Research, 33, 412-418.
[253]Yaveroglu, I., & Donthu, N. (2008). Advertising repetition and placement issues in on-line environments. Journal of Advertising, 37(2), 31-44.
[254]Yong, A. G., & Pearce, S. (2013). A beginner’s guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology, 9(2), 79-94.
[255]Yu, Q., Allon, G., & Bassamboo, A. (2016). How do delay announcements shape customer behavior? An empirical study. Management Science.
[256]Yue, Z., Gao, T., Chen, L., & Wu, J. (2016). Odors bias time perception in visual and auditory modalities. Frontiers in psychology, 7.
[257]Zakay, D. (2014). Psychological time as information: The case of boredom. Frontiers in Psychology, 5, 917.
[258]Zalla, T., Phipps, M., & Grafman, J. (2002). Story processing in patients with damage to the prefrontal cortex. Cortex, 38(2), 215-231.
[259]Zhang, X. & Zhou, X. L. (2007). Time perception of emotional events. Progress in Natural Science, 17(13), 150-153.
[260]Zhao, C., Zhao, M., Liu, J., & Zheng, C. (2012). Electroencephalogram and electrocardiograph assessment of mental fatigue in a driving simulator. Accident Analysis and Prevention, 45, 83-90.
[261]Zhou, R., & Soman, D. (2003). Looking back: Exploring the psychology of queuing and the effect of the number of people behind. Journal of Consumer Research, 29(4), 517-530.
[262]Zhu, B., Watts, S., & Chen, H. (2010). Visualizing social network concepts. Decision Support Systems, 49(2), 151-161.
[263]Zukerman, M. (2013). Introduction to queueing theory and stochastic teletraffic models. ArXiv preprint arXiv:1307.2968.
[264]Zurawicki, L. (2010). Neuromarketing: Exploring the brain of the consumer. Springer Science & Business Media.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
1. 申冀治(2006)。座位需求導入等候理論之設施規劃改善研究。工業科技與管理學刊,1,91-109。
2. [4] 吳佳華(2012)。檢驗量表分析餐廳美食客之消費行動。商業現代化學刊,6(4),167-181。
3. [5] 周逸衡、黃毓瑩、陳華寧與楊俊明(2006)。情緒類別及等待發生時點對等待時間知覺的影響。中山管理評論,14(2),487-516。
4. [7] 林美蘭、方妙玲與張瑞淳(2015)。餐廳背景音樂的速度與音量影響消費者等待時間知覺之研究。觀光休閒學報,21(1),55-77。
5. [10] 梁直青、郭文甄與蔡佩舒(2016)。腦波與排隊決策之探究。東吳經濟商學學報,92,1-36。
6. [12] 郭峰淵、黃瑜峰(2009)。擴充認知適配論以研究情緒在決策中的角色—眼動儀之應用。資訊管理學報,16,1-19。
7. [16] 楊仁壽、俞慧芸、李怡穎與李瑞敏(2010)。情緒浸染之資訊整合行爲:理論建構與實證。臺大管理論叢,20(2),97-133。
8. [17] 廖慧伶、洪一仁、黃惠珠與李明輝(2016)。創新門診候藥時間管理-「具等候量語音提示機制之門診領藥時間提醒系統」─以豐原醫院為例。醫學與健康期刊,5(1),101-110。
9. [21] 劉雅甄(2014)。棒球選手打擊之視覺焦點策略分析。華人運動生物力學期刊,11, 13-19。
10. [22] 蕭至惠、蔡進發與吳思韻(2011)。等待時間資訊、人格特質與服務屬性對消費者等待時間知覺的影響。中原企管評論, 9(2), 113-138.
11. [23] 蕭至惠、蔡進發與林健名(2012)。期盼模式與修正型等待觀點下,探討等待發生時點、情緒類別、個人時間風格對等待時間知覺之影響。輔仁管理評論,19(2), 29-58。
12. [24] 蕭至惠、謝玉君與蔡進發(2010)。排隊隊形與電視節目類型對消費者等待時間知覺的影響。輔仁管理評論,17(1),55-77。
13. [26] 鍾燕宜、紀乃文與陳景元(2008)。銷售工作價值觀量表之發展與評量。臺大管理論叢,19(1),51-81.