本論文分為三篇研究，第一篇本文研究目的在探討當電子商務市場上出現不誠信供應商時，對市場會產生有何影響？而且在不同條件之下，消費者對於產品預期品質可以透過不同程度的個人學習，社會學習與社會網路連線程度下受到影響，本研究利用代理人基模擬，並且參考Izquierdo and Izquierdo (2007)所提出的品質不確定性市場模型，本文加入信任度賽局模型(Wierzbicki et al., 2014)中設定供應商誠信與不誠信比率設定與供應商聲譽參數進行模擬實驗。本文所得結論是當消費者掌握資訊愈多，受不實商品影響愈少，消費者的預期品質相對會比較高，網路電商的收入也比較高和穩定，無論在哪種誠實比例下的市場，網路連線數和社會比較能力比較高的市場環境下的消費者都較能克服不實商品影響購買信心的問題。不實商品在網路連線數和社會比較能力低下的市場環境中，其負影響的力量較大，反之亦然。
第二篇本研究蒐集臺灣與中國大陸兩個地區的調查資料，探討消費者對於多層次傳銷保健食品消費知覺區域性差異。研究結果可以提供多層次傳銷保健食品業者與經營者市場策略調整的參考依據。本研究將分兩階段分析多層次傳銷公司之行銷刺激、品牌信任、消費者知覺風險三構面的關聯性。研究表明，不同地區的消費者，對於行銷刺激與品牌信任關鍵因素的確存在差異性同時對消費者知覺風險具有顯著影響。
第三篇由於品牌眾多且產品同質性高，許多公司提供不同的行銷策略來刺激消費，企圖影響消費者的購買決策，本研究將以臺灣與中國大陸兩個地區為分析對象，考量經濟環境、文化與多層次傳銷發展程度差異性，首先利用結構方程模型的因素分析方法檢視問卷設計的信度；由於人格特質具多面向性而且型態之間無法明顯界定。本文利用消費者「五大人格特質」進行消費者人格特質集群分析，探討多層次傳銷保健食品公司「行銷刺激」、「品牌信任」此二構面對「消費者知覺風險」的影響。為避免消費者類型分類內的樣本數過低，因此。本文進一步採用集群分析法，將問卷受訪者類型分類簡化為「安逸樂活」、「樂觀保守」、「盡責務實型」三集群人格特質特徵。同時，導入臺灣與中國大陸兩地人口特性，找出消費者輪廓，綜合研究結果，本研究發現不論是「行銷刺激」、「品牌信任」亦或是「消費者知覺風險」，構面內各觀察變數對不同人格特質集群的差異性影響，研究發現，區域性消費者對構面內各觀察變數的確存在相當大的差異，不但如此，相對重要性與相對強度都具有顯著差異。

    This paper develops three research directions with empirical and theoretical methods. Firstly, we apply the agent-based method to infer the effect of dishonest suppliers on the market under the condition of quality uncertainty and information asymmetry. Research has found that consumer trust in manufacturers helps reduce consumers' perceived risk. Both e-commerce and multi-level marketing are based on trust in the market. Dishonest suppliers lead to the main reason for the decline in market volume, price and expected quality. Research shows that individual and social experience and information exchange under social networks can improve market resilience. Finally, the influence of social network, trust, marketing stimulus, consumer individual and social perception differences under different regions on multi-level marketing (MLM) market is studied. We further study the consumer personality traits and consumption characteristics in the multi-level marketing market to understand the differences under different regions.

Essay1：This paper studies dishonest sellers in the e-commerce market, specifically their impact on the market under different conditions. We consider the role of consumers’ social and individual learning and social network branches on the market. We rely on a quality uncertainty market model (Izquierdo et al., 2007) and a trust game model (Wierzbicki et al., 2014) to establish an agent-based model. Our approach considers the proportion of honest and dishonest sellers, the reputation of sellers, and the expectation of quality among consumers after purchasing the goods. The results of the study reveal that when dishonest sellers appear in a market with a high degree of quality uncertainty, there is a negative impact on the market, including a decline in consumer expected quality of products in the market, a decrease in commodity transaction volume and market price, and a decrease in seller income. The impact is more pronounced in markets with a higher proportion of dishonest sellers.

 Essay2：According to statistics from the World Federation of Direct Selling Associations (WFDSA) in 2019, health food has been incorporated into the lives of most people. Regarding the regional differences in the development of biotechnology and the aging of the population, this study collected questionnaire survey data from Taiwan and Mainland China to explore the regional differences in consumer perceptions of multi-level marketing (MLM) health food consumption. The research results provide a reference basis for MLM health food manufacturers and operators to adjust their marketing strategies. This research will be divided into two phases:  The first phase of this research focuses on consumers and operators who are in contact with MLM in Taiwan and China, explaining the research methods and hypotheses, and discussing its incentives for the marketing of healthy food. Using the questionnaire survey method, based on Structural Equation Modeling (SEM), conduct reliability and validity analysis, discuss the three aspects of MLM health food stimulating marketing, brand trust and perceived risk in different regions, and design with SEM. In the second stage, confirmatory analysis is used to obtain more evidence to discriminate the scale, which proves that consumers in different regions have a significant impact on consumer perception of MLM health food stimulating marketing and key factors of brand trust.

Essay3：According to Fair Trade Commission of Taiwan, the 2019 annual data show that the competition is quite severe in the multi-level marketing industry. Especially in health products, there are many brands and high homogeneity among them. Therefore, this study intends to explore whether the differences in the management and marketing systems of various company brands affect consumers' purchasing decisions. This research will analyze the differences between Taiwan and China, considering the economic environment and the degree of development of multi-level marketing. Firstly, the reliability of the questionnaire design is examined by factor analysis method of structural equation model; then the consumers’ "five personality traits" are used to classify consumer types. The article discusses the influence of the two constructs "company brand and trust" and "business model characteristics" on consumers' purchasing decisions. At the same time, in order to avoid insufficient sample size of consumer types, this article further adopts cluster analysis method to simplify the questionnaire respondents' types into three types: unsociable, obedient, and bellwether personality traits. Based on the results of the research, this article finds that regardless of "company brand and trust" or "business model characteristics," the key impact of various observation variables on different personality traits is their relative strength. 

第一章 緒論	1
1.1 研究動機、目的及研究流程	1
1.1.1 不誠信供應商對電子商務影響：代理人基建模方法	2
1.1.2 區域性對於消費知覺風險因素分析	3
1.1.3 利用集群分析區域性消費者知覺風險因素分析	5
1.2  本文架構	6
第二章 不誠信供應商對電子商務之影響：代理人基建模方法	7
2.1 研究動機和目的	7
2.1.1 本文架構	8
2.2 文獻回顧	8
2.2.1 集體智慧 (Collective Intelligence)	9
2.2.2 資訊不對稱 (Information Asymmetry)	10
2.2.3 不誠信供應商對電子商務影響之假說	11
2.3 代理人基建模(Agent-Based Modeling)	12
2.3.1 代理人基模型(Agent-Based Models)	12
2.3.2 品質不確定性市場效應(MEQU)模型	13
2.3.3 研究架構	13
2.4 模型與實驗設計	15
2.4.1 模型	18
2.4.2 實驗設計	22
2.5 模擬結果	22
2.5.1 市場趨勢	22
2.5.2 迴歸分析	25
2.6 結論	26
第3章 區域性對於消費知覺風險因素分析－以多層次傳銷保健食品為例	29
3.1 研究背景與目的	29
3.1.1 本文架構	29
3.2 文獻探討	30
3.2.1 行銷刺激	31
3.2.2 品牌信任	32
3.2.3 消費者知覺風險	34
3.2.4 研究假說	35
3.3 研究方法	36
3.3.1 問卷調查	36
3.3.2 問卷設計	37
3.3.3 信度與效度分析	39
3.3.4 研究架構	39
3.4 研究結果分析	41
3.4.1 構面特性分析	41
3.4.2 測量模式分析	43
3.4.3 信度分析	46
3.4.4 建構效度分析	47
3.4.5 研究假設檢定	47
3.4.6 模型評估	49
3.4.7 因素負荷量分析	53
3.5 研究結果	55
3.5.1 區域性差異對各構面觀察變數排序	55
3.5.2 區域性差異對於三構面觀察變數相異點	57
3.5.3 區域性差異對於構面觀察變數之相同點	57
3.5.4 區域性差異對構面之分析	58
3.6 結論	60
第四章 利用集群分析區域性消費者知覺風險因素分析之研究結果	62
4.1 研究背景與目的	62
4.1.1 本文架構	62
4.2文獻探討綜述與研究假說	63
4.2.1 人格特質	63
4.2.2 集群分析(Cluster Analysis)	64
4.2.3 研究假說	65
4.3 研究方法	65
4.3.1 問卷調查	66
4.3.2 結構方程模型(Structural Equation Model, SEM	66
4.3.3 集群分析法(Cluster Analysis)	67
4.3.4 研究架構	68
4.4 資料分析與結果	68
4.4.1 構面特性分析	68
4.4.2 測量模式分析	71
4.4.3 信度分析	72
4.4.4 建構效度分析	72
4.4.5 五大人格特質與構面觀察變數分析	73
4.4.6 探索性因素分析與二階驗證性因素分析	75
4.4.7 研究假設檢定	76
4.4.8 理論模型評估	79
4.4.9 整體理論模式衡量分析	79
4.5 資料評估	83
4.5.1 構面觀察變數分析	83
4.5.2 集群分析	84
4.5.3 區域性集群對「行銷刺激」差異	89
4.5.4 區域性集群對「品牌與信任」差異	90
4.5.5 區域性集群對「消費者知覺風險」差異	91
4.5.6 區域性3集群對「行銷刺激」觀察變數相對重要性排序	92
4.5.7 區域性「樂觀保守」、「盡責務實」集群對「品牌信任」觀察變數相同點	93
4.5.8 區域性「盡責務實」集群 在「品牌信任」對觀察變數的相對重要性排序	93
4.5.9 區域性「安逸樂活」、「樂觀保守」集群對「消費者知覺風險」觀察變數相同點	94
4.6 研究結果分析	97
4.6.1 「行銷刺激｣區域性差異結果影響	97
4.6.2 「行銷刺激」構面相異點與強度差異	97
4.6.3 「品牌信任」區域性差異結果影響	98
4.6.4 「品牌與信任」構面相異點與強度差異	98
4.6.5 「消費者知覺風險」區域性差異結果影響	99
4.6.6 「消費者知覺風險」構面相異點與強度差異	99
4.6.7  綜合發現	100
4.7 結論	102
第五章 結論及未來發展方向	104
5.1 結論	105
5.2 商業意涵	106
5.3 未來研究方向	108
參考文獻	110

表目錄

表 2-1 模型參數設定說明	15
表 2-2 第500回合的預期品質迴歸(品質分佈=指數，網路連接=擇優依附)	24
表 2-3第500回合的預期品質迴歸 (品質分佈=均勻，網路連接=擇優依附)	24
表 2-4 第500回合的預期品質的迴歸(品質分佈=指數，網路連接=隨機)	25
表 2- 5 第500回合的預期品質的迴歸(品質分佈=均勻，網路連接=隨機)	25
表3-1 品牌文獻整理	33
表3-2 中國大陸問卷地區比率明細表	38
表3-3 行銷刺激 (構面一)	42
表3-4 品牌信任(構面二)	42
表3-5 消費者知覺風險(構面三)	42
表3-6 信度之評估指標	43
表3-7  適合進行因素分析之評估指標	43
表3-8 收斂效度之評估指標	44
表3-9  AMOS 模式之CFA配適度標準	45
表3-10  CFA配適度指標檢定結果	46
表3-11  信度分析結果	47
表3-12  KMO取樣適合性檢定和Bartlett球面性檢定	47
表3-13 行銷刺激、品牌信任與消費者知覺風險之路徑分析	48
表3-14 構面觀察變數與相關分析表	51
表3-15 臺灣觀察變數因素負荷量分析表	53
表3-16 中國大陸觀察變數因素負荷量分析表	54
表4-1 人格特質定義	64
表4-2 臺灣構面觀察變數與相關分析表	69
表4-3 中國大陸 構面觀察變數與相關分析表	70
表4-4 信度分析結果	72
表4-5 取樣適合性檢定和 Bartlett  球面性檢定	73
表4-6  AMOS 五大人格特質與構面分析	74
表4-7  CFA配適度指標檢定結果	75
表4-8 「行銷刺激」、「品牌信任」、「消費者知覺風險」構面路徑分析	77
表4-9 五大人格特質與構面分析	80
表4-10  CFA配適度指標檢定結果	82
表4-11   KMO取樣適合性檢定和Bartlett球面性檢定	83
表4-12 集群分析人口特性分析表	86
表4-13 行銷刺激、品牌信任、消費者知覺構面變數平均數統計分析表	88

 

圖目錄

圖1-1 不誠信供應商對電子商務影響之研究流程圖	3
圖1-2 區域性對於消費知覺風險因素分析之研究流程圖	4
圖1-3 利用集群分析區域性消費者知覺風險因素之研究流程圖	5
圖2-1 不誠信供應商對電子商務影響研究架構	14
圖2-2 本研究操作界面	17
圖2-3 買方代理人的形成過程	19
圖2-4 賣方代理人的形成過程	21
圖2-5 不誠信供應商對電子商務之影響	23
圖3-1區域性對於消費知覺風險因素分析研究架構圖	40
圖3-2 臺灣與中國大陸結構方程模型架構圖	48
圖4-1 利用集群分析區域性消費者知覺風險因素分析研究架構	66
圖4-2 臺灣與中國大陸結構方程模型架構	76
圖4-3 臺灣集群分析圖	85
圖4-4 中國大陸集群分析圖	85

中文部分
陳俊峰 (2005)。影響消費者購買保健食品決策因素之研究-以多層次傳銷為例，成功大學高階管理碩士在職專班(EMBA)學位論文.
陳欽春 (2009)。何信任如此重要: 政治信任的下滑與美國自由主義的隕落. 公共行政學報, (30), 149–153.
郭欣易 (2000)。人格特質與激勵偏好, 工作態度, 工作表現之相關性研究, 世新大學，觀光學系碩士論文。
公平交易委員會 (2019)。報告資料，http://www.ftc.gov.tw
張春興 (1998)。張氏心理學辭典 (二版). 臺北市: 東華.
張琪玲 (2012)。多層次傳銷組織領導者管理職能之硏究, 國立中山大學，人力資源管理研究所碩士論文。


英文部分
Aaker, D. A. (1996). Measuring brand equity across products and markets. California Management Review, 38(3), 102–120.
Akerlof, G. A. (1978). The market for “lemons”: Quality uncertainty and the market mechanism. In Uncertainty in economics (pp. 235–251). Academic Press.
Allport, G. W. (1937). Personality: A psychological interpretation. Henry Holt.
Allport, G. W. (1961). Pattern and growth in personality. Harcourt College Publishers.
Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. Journal of marketing, 58(3), 53–66.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
Bandura, A., & Walters, R. H. (1977). Social learning theory (Vol. 1). Prentice Hall: Englewood cliffs.
Barnes, J. A. (1954). Class and committees in a Norwegian island parish. Human relations, 7(1), 39-58.
Belch, G. E., & Belch, M. A. (2004). Advertising and promotion: An integrated marketing communications perspective 6th. New York: McGraw-Hill.
Biel, A. L. (1993). How brand image drives brand equity. Journal of Advertising Research, 32(6), 6–13.
Byrne, B. M. (2001). Structural equation modeling with AMOS, EQS, and LISREL: Comparative approaches to testing for the factorial validity of a measuring instrument. International Journal of Testing, 1(1), 55–86.
Chaudhury, A., & Rao, H. R. (1997). Introducing client/server technologies in information systems curricula. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 28(4), 20–32.
Chin, W. W. (1998). Commentary: Issues and Opinin on Structural Equation Modeling. Management information Systerms Quarterly, 22(1), 7-16AVE。
Chow, S., & Holden, R. (1997). Toward an understanding of loyalty: The moderating role of trust. Journal of Managerial Issues, 275–298.
Cox, D. F. (1967), Risk‐taking and information handling in consumer behavior, Harvard University, Boston, MA.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.
Dobni, D., & Zinkhan, G. M. (1990). In search of brand image: A foundation analysis. Advances in Consumer Research, 17 (1990), 110–119.
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 28(3), 307–319.
Elfenbein, D. W., Fisman, R., & McManus, B. (2015). Market structure, reputation, and the value of quality certification. American Economic Journal: Microeconomics, 7(4), 83–108.
Erciş, A., Ünal, S., Candan, F. B., & Yıldırım, H. (2012). The effect of brand satisfaction, trust and brand commitment on loyalty and repurchase intentions. Procedia-Social and Behavioral Sciences, 58, 1395–1404.
Festinger, L. (1954). A theory of social comparison processes. Human relations, 7(2), 117–140.
Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal of Marketing, 56(1), 6–21.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388.
Granovetter, M., & Soong, R. (1986). Threshold models of interpersonal effects in consumer demand. Journal of Economic Behavior & Organization, 7(1), 83–99.
Gregg, D. G., & Walczak, S. (2008). Dressing your online auction business for success: An experiment comparing two eBay businesses. Mis Quarterly, 653–670.
Hair, J. F. J., Anderson, R. E., Tatham, R. L., & Black, W. C. (1992). Factor analysis In: Easter F, editor. Multivariate data analysis.
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Factor analysis. Multivariate data analysis. NJ Prentice-Hall, 3, 98-99.
Hayek, F. A. (1946). Individualism, True and False: The Twelfth Finlay Lecture Delivered at University College, Dublin, on December 17, 1945. Hodges, Figgis.
Hirsh, J. B. (2010). Personality and environmental concern. Journal of Environmental Psychology, 30(2), 245–248.
Homburg, C., & Giering, A. (2001). Personal characteristics as moderators of the relationship between customer satisfaction and loyalty—an empirical analysis. Psychology & Marketing, 18(1), 43-66.
Hoyer, W. D., & Brown, S. P. (1990). Effects of brand awareness on choice for a common, repeat-purchase product. Journal of Consumer Research, 17(2), 141–148.
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
Izquierdo, S. S., & Izquierdo, L. R. (2007). The impact of quality uncertainty without asymmetric information on market efficiency. Journal of Business Research, 60(8), 858–867.
Jacoby, J., & Kaplan, L. B. (1972). The components of perceived risk. In Proceedings of the Third Annual Conference, Ann Arbour, MI, Association for Consumer Research.
Janssen, M. A., & Jager, W. (2001). Fashions, habits and changing preferences: Simulation of psychological factors affecting market dynamics. Journal of Economic Psychology, 22(6), 745–772.
Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services. Journal of Retailing, 76(2), 259–274.
Kotler, P. (1998). A generic concept of marketing. Marketing Management, 7(3), 48–54.
Laurent, G., Kapferer, J. N., & Roussel, F. (1995). The underlying structure of brand awareness scores. Marketing Science, 14(3), 170–179.
Macdonald, E. K., & Sharp, B. M. (2000). Brand awareness effects on consumer decision making for a common, repeat purchase product: A replication. Journal of Business Research, 48(1), 5–15.
McCrae, R. R., & Costa Jr, P. T. (1996). Toward a new generation of personality theories: Theoretical contexts for the five factor model. In J.S. Wiggins (Ed.), The five-factor model of personality: Theoretical perspectives. New York: Guilford, 51–87.
McCrae, R. R., & Costa Jr, P. T. (1999). A five-factor theory of personality. In O.P. John (Ed.), Handbook of personality theory and research, Guilford Press, New York, 139–153.
Mitchell, V. W. (1999). Consumer perceived risk: conceptualisations and models. European Journal of Marketing, 33 (1/2), 163–196.
Mittal, V., & Kamakura, W. A. (2001). Satisfaction, repurchase intent, and repurchase behavior: Investigating the moderating effect of customer characteristics. Journal of marketing research, 38(1), 131-142.
Parry, K. W. (1998). Grounded theory and social process: A new direction for leadership research. The leadership quarterly, 9(1), 85–105.
Peter, J. P., & Ryan, M. J. (1976). An investigation of perceived risk at the brand level. Journal of Marketing Research, 13(2), 184–188.
Samiee, S. (1994). Customer evaluation of products in a global market. Journal of International Business Studies, 25(3), 579–604.
Schiffman, L. G., & Kanuk, L. L. (1978). Consumer behavior. Englewood, NJ: Pretice Hall.
Sheth, J. N., Newman, B. I., & Gross, B. L. (1991). Why we buy what we buy: A theory of consumption values. Journal of Business Research, 22(2), 159–170.
Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of marketing, 66(1), 15-37.
Sondoh, S. L., Omar, M. W., Wahid, N. A., Ismail, I., & Harun, A. (2007). The effect of brand image on overall satisfaction and loyalty intention in the context of color cosmetic. Asian Academy of Management Journal, 12(1), 83–107.
Stone, R. N., & Grønhaug, K. (1993). Perceived risk: Further considerations for the marketing discipline. European Journal of Marketing, 27(3), 39–50.
Tesfatsion, L. (2021). Agent-Based Computational Economics: Overview and Brief History. Available at: https://www2.econ.iastate.edu/tesfatsi/ACEOverview BriefHistory.LTesfatsion.EconWP21004.LatestRevision.pdf
Vriend, N. J. (2002). Was Hayek an ace?. Southern Economic Journal, 811–840.
WFDSA (2019), Global Direct Selling - 2018 Retail Sales (June 1, 2019), p. 2, Available at: https://wfdsa.org/wp-content/uploads/2019/06/Sales-Seller-Report-FINAL.pdf [accessed in 19 June 2022].
Wierzbicki, A., Adamska, P., Abramczuk, K., Papaioannou, T., Aberer, K., & Rejmund, E. (2014). Studying web content credibility by social simulation. Journal of Artificial Societies and Social Simulation, 17(3), 6.
Wilensky, U. (2005). NetLogo Small Worlds model. http://ccl.northwestern. edu/netlogo/models/SmallWorlds. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL
Wilensky, U., & Rand, W. (2015). An introduction to agent-based modeling: modeling natural, social, and engineered complex systems with NetLogo. Mit Press.
Yu, T., Chen, S. H., & Wang, C. H. (2017). Information Aggregation in Big Data: Wisdom of Crowds or Stupidity of Herds. In International Symposium on Distributed Computing and Artificial Intelligence (pp. 16–27). Springer, Cham.