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    Title: 產品資訊搜尋之介面選擇：購買意圖、產品特性、電子商務涉入程度與行動裝置自我效能之影響
    Interface Selection of Information Search: the Effect of Intention to Purchase, Product Characteristics, E-Commerce Involvement and Mobile Device Self-Efficacy
    Authors: 朱峻毅
    Chu, Chung Yi
    Contributors: 管郁君
    朱峻毅
    Chu, Chung Yi
    Keywords: 購買意圖
    搜尋介面
    行動裝置自我效能
    intention to purchase
    search interface
    mobile device self-efficacy
    Date: 2013
    Issue Date: 2014-08-12 14:02:17 (UTC+8)
    Abstract: 當行動裝置逐漸改變人們的生活習慣，消費者的行為模式跟著產生變化，網路內容提供商也必須改變提供商品資訊的方式以吸引消費者的目光，因此若能掌握消費者對於搜尋介面的使用習慣，便能提供消費者更好的搜尋體驗。本研究首先探討在行動網路的環境下影響購買前搜尋介面之選擇的因素，即購買意圖與產品特性。除此之外，本研究彙整影響消費者做出不同決策的內在因素，即電子商務網站的涉入程度與行動裝置之自我效能，作為探討上述關係的調節效果。本研究發現消費者會因為購買不同特性的產品，而選擇不同的資訊搜尋介面進行產品資訊搜尋。電子商務涉入程度會間接的影響產品特性與搜尋介面的選擇，當消費者的電子商務涉入程度高時，消費者會傾向使用非行動裝置搜尋介面，而且會使用行動裝置尋找搜尋性產品的消費者比尋找經驗性產品的消費者多。當消費者的電子商務涉入程度低時，使用行動裝置尋找搜尋性產品的消費者比使用非行動裝置的消費者多，但幾乎沒有人會使用行動裝置尋找經驗性產品的資訊。行動裝置的自我效能可分為熟練度和焦慮感，消費者在選擇行動裝置搜尋介面時，會受到行動裝置熟練度和行動裝置焦慮感直接影響。除此之外，行動裝置焦慮感也會間接的影響產品特性與搜尋介面的選擇。當消費者對於行動裝置不感覺到焦慮時，會使用行動裝置尋找搜尋性產品的消費者比尋找經驗性產品的消費者多。而當消費者對於行動裝置感到焦慮時，比起搜尋性產品，消費者反而會更容易使用行動裝置進行經驗性產品的資訊搜尋。
    The increasing use of mobile devices has changed the patterns of consumer behavior. Organizations that provide digital content have to transform themselves if they want to attract consumers’ attention. To enhance consumers’ search experience, it is critical to understand the ways in which they use search interfaces. In this study, we first explored and summarized the factors that affect consumers’ search behavior, including purchase intention and product characteristics, in the mobile network environment. We investigated how these factors influence consumers’ choice of search interfaces. When consumers have the intention to purchase something, both their intention to shop and the product characteristics may affect their choice of search interfaces. In addition, this study investigated the mediating effect of consumers’ intrinsic factors, e-commerce involvement and mobile device self-efficacy, on the relationships described above.
    The study found that product characteristics affected consumers’ choice of search interfaces for a product information search. E-commerce involvement indirectly affected interface selection. When the consumers had high e-commerce involvement, they tended to use search interfaces on non-mobile devices; however, the number of consumers using mobile devices to seek information on search goods was higher than the number seeking information on experience goods. Among consumers with low e-commerce involvement, the number using mobile devices to seek information on search goods was higher than the number using non-mobile devices, but almost none used mobile devices to seek information on experience goods.
    Mobile device self-efficacy includes mobile skillfulness and anxiety. When the consumers chose mobile devices as search interfaces, they were directly affected by their mobile device self-efficacy. In addition, anxiety indirectly affected interface selection. Among consumers who were not anxious about using mobile devices, the proportion using mobile devices to seek search goods’ information was higher than the proportion seeking experience goods’ information. When the consumers felt anxious about using mobile devices, they preferred to use the mobile devices’ information search interfaces to search for experience goods’ information rather than to search for goods’ information.
    Reference: Andrews, J. C., Durvasula, S., & Akhter, S. H. (1990). A Framework for Conceptualizing and Measuring the Involvement Construct in Advertising Research. Journal of Advertising, 19(4), 27–40.
    Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-225.
    Bandura, A. (1982). Self-efficacy mechanism in human agency. American Psychologist, 37(2), 122.
    Bandura, A. (1997). Self-efficacy: the exercise of control.
    Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, N.J: Prentice-Hall, 523–582.
    Bandura, A. (1986). Social foundations of thought and action: a social cognitive theory. Englewood Cliffs, N.J: Prentice-Hall.
    Barbeite, F. G. & Weiss, E. M. (). Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales. Computers in Human Behavior, 20(1), 1–15, 2004.
    Barling, J., & Beattie, R. (1983). Self-efficacy beliefs and sales performance. Journal of Organizational Behavior Management, 5(1), 41-51.
    Barki, H., & Hartwick, J. (1989). Rethinking the Concept of User Involvement. MIS Quarterly, 13(1), 53–63.
    Bedard, J. C., Jackson, C., Ettredge, M. L., & Johnstone, K. M. (2003). The effect of training on auditors’ acceptance of an electronic work system. International Journal of Accounting Information Systems, 4(4), 227–250.
    Behe, B. K., Campbell, B. L., Hall, C. R., Khachatryan, H., Dennis, J. H., & Yue, C. (2013). Smartphone Use and Online Search and Purchase Behavior of North Americans: Gardening and Non-gardening Information and Products. HortScience, 48(2), 209–215.
    Bentler, P. M., & Speckart, G. (1981). Attitudes ‘cause’ behaviors: A structural equation analysis. Journal of Personality and Social Psychology, 40(2), 26.
    Bentler, P. M., & Speckart, G. (1979). Models of attitude–behavior relations. Psychological review, 86(5), 452.
    Bettman, J.R. (1979), An Information Processing Theory of Consumer Choice, reading, MA: Addison-Wesley.
    Blackwell, R. D., Miniard, P. W., & Engel, J. F. (2001). Consumer Behavior. Harcourt College Publishers.
    Bloch, P. H., Sherrell, D. L., & Ridgway, N. M., (1986). Consumer Search: An Extended Framework. Journal of Consumer Research, 13(1), 119–126.
    Breitenbach, C. S., & Van Doren, D. C. (1998). Value-added marketing in the digital domain: enhancing the utility of the Internet. Journal of consumer marketing, 15(6), 558-575.
    Butler, P., & Peppard, J. (1998). Consumer purchasing on the Internet: Processes and prospects. European Management Journal, 16(5), 600–610.
    Carlson, J. R., George, J. F., Burgoon, J. K., Adkins, M., & White, C. H. (2004). Deception in Computer-Mediated Communication. Group Decision and Negotiation, 13(1), 5-28.
    Case, D. O. (2012). Looking for Information: A Survey of Research on Information Seeking, Needs and Behavior, 3rd ed. Emerald Group Publishing.
    Castañeda, J. A., Frías, D. M., & Rodríguez, M. A. (2007). The influence of the Internet on destination satisfaction. Internet Research, 17(4), 402–420.
    Celsi, R. L., & Olson, J. C. (1988). The Role of Involvement in Attention and Comprehension Processes. Journal of Consumer Research, 15(2), 210–224.
    Chang H. H., & Chen, S. W. (2008). The impact of online store environment cues on purchase intention: Trust and perceived risk as a mediator. Online Information Review, 32(6), 818–841.
    Chao, P.-C. (2010). Online information search behavior vs. experience goods. ETD Collection for Purdue University), 1–54.
    Chau P. Y., & Hu, P. J.-H. (2002). Investigating healthcare professionals’ decisions to accept telemedicine technology: an empirical test of competing theories. Information & management, 39(4), 297–311.
    Cheema, A., & Papatla, P. (2010). Relative importance of online versus offline information for Internet purchases: Product category and Internet experience effects. Journal of Business Research, 63(9), 979-985.
    Chen L.-D., & Tan, J. (2004). Technology Adaptation in E-commerce: Key Determinants of Virtual Stores Acceptance. European Management Journal, 22(1), 74–86.
    Cheung, C. M., Chan, G. W., & Limayem, M. (2005). A critical review of online consumer behavior: Empirical research. Journal of Electronic Commerce in Organizations (JECO), 3(4), 1–19.
    Choi, S.-Y., Stahl, D. O., & Whinston, A. B. (1997). The economics of electronic commerce. Macmillan Technical Publishing Indianapolis.
    Church, K., Smyth, B., Cotter, P., & Bradley, K. (2007). Mobile information access: A study of emerging search behavior on the mobile Internet. ACM Trans. Web, 1(1, May.
    Compeau, D., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158.
    Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS quarterly, 19(2), 189-211.
    Deng, X., Doll, W. and Truong, D. (2004), Computer self-efficacy in an ongoing use context, Behaviour and Information Technology, 23(6), 395-412.
    Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers` product evaluations. Journal of marketing research, 307-319.
    Dowling, G. R. (1986). Perceived risk: the concept and its measurement. Psychology & Marketing, 3(3), 193–210.
    Eastlick, M. A. (1996). Consumer intention to adopt interactive teleshopping.
    Eastin, M. S., & LaRose, R. (2000). Internet Self-Efficacy and the Psychology of the Digital Divide. Journal of Computer-Mediated Communication, 6(1), 0–0.
    M. A. Eastlick & S. Lotz, (1999). Profiling potential adopters and non-adopters of an interactive electronic shopping medium. International Journal of Retail & Distribution Management, 27(6), 209–223.
    Engel, J. F., Blackwell, R. D., & Miniard, P. W. (1995). Consumer Behaviour. Dryden Press.
    Fagan, M. H., Neill, S., & Wooldridge, B. R. (2003). An empirical investigation into the relationship between computer self-efficacy, anxiety, experience, support and usage. Journal of Computer Information Systems, 44(2), 95-104.
    Fitch, C. J. (2004). Information systems in healthcare: mind the gap. 37th Annual Hawaii International Conference on System Sciences.
    Gagnon, M.-P., Godin, G., Gagné, C., Fortin, J.-P., Lamothe, L., Reinharz, D., & Cloutier, A. (2003). An adaptation of the theory of interpersonal behaviour to the study of telemedicine adoption by physicians. International journal of medical informatics, 71(2), 103–115.
    Girard, T., & Dion, P. (2010). Validating the search, experience, and credence product classification framework. Journal of Business Research, 63(9–10), 1079–1087.
    Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated environments: conceptual foundations. The Journal of Marketing, 50-68.
    Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 1(1), 104-121.
    Huang, M.-H. (2000). Information load: its relationship to online exploratory and shopping behavior. International Journal of Information Management, 20(5), 337–347.
    Hsu, M.-H., & Chiu, C.-M. (2004). Internet self-efficacy and electronic service acceptance. Decision support systems, 38(3), 369–381.
    Hwang, R.-J., Shiau, S.-H., & Jan, D.-F. (2007). A new mobile payment scheme for roaming services. Electronic Commerce Research and Applications, 6(2), 184–191.
    Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587–605.
    Irby, T. L., & Strong, R. (2013). Agricultural Education Students’ Acceptance and Self-Efficacy of Mobile Technology in Classrooms. NACTA Journal, 57(1), 82-87.
    Islam, M. A., Khan, M. A., Ramayah, T., & Hossain, M. M. (2011). The adoption of mobile commerce service among employed mobile phone users in Bangladesh: self-efficacy as a moderator. International Business Research, 4(2), 80.
    Jamieson, L. F., & Bass, F. M. (1989). Adjusting Stated Intention Measures to Predict Trial Purchase of New Products: A Comparison of Models and Methods. Journal of Marketing Research (JMR), 26(3), 336–345.
    Keith, M. J., Babb, J. S., Furner, C. P., & Abdullat, A. (2011, January). The role of mobile self-efficacy in the adoption of location-based applications: An iPhone experiment. In System Sciences (HICSS), 2011 44th Hawaii International Conference on IEEE, 1–10.
    Klein, L. R. (1998). Evaluating the Potential of Interactive Media through a New Lens: Search versus Experience Goods. Journal of Business Research, 41(3), 195–203.
    Kiang, M. Y., Raghu, T., & Shang, K. H. M. (2000). Marketing on the Internet — who can benefit from an online marketing approach? Decision Support Systems, 27(4), 383–393.
    Krikelas, J. (1983), Information-seeking behavior: Patterns and Concepts. Drexel Library Quarterly, 19(2), 5–20.
    Krugman, H. E. (1965). The Impact of Television Advertising: Learning Without Involvement. The Public Opinion Quarterly, 29(3), 349–356.
    Kotler, Philip, & Gary Armstrong. (2013). Principles of Marketing. 15th Global Edition. Pearson.
    Kotler, P., S.H. Ang, S.M. Leong, & C.T. Tan, (2004). Marketing Management-An Asian Perpective, 3th Edition, Singapore: Prentice Hall.
    Kotler, Philip. (1997). Standing room only: Strategies for marketing the performing arts, Harvard business press.
    Koufaris, M. (2001). Consumer Behavior in Web-Based Commerce: An Empirical Study. INT. J. ELECTRON. COM, 6(2), 115–138.
    Lee, C. C., & Hsieh, M. C. (2009, June). The influence of mobile self-efficacy on attitude towards mobile advertising. In New Trends in Information and Service Science, 2009. NISS`09. International Conference on IEEE, 1231-1236.
    Li, H., Kuo, C., & Rusell, M. G. (1999). The Impact of Perceived Channel Utilities, Shopping Orientations, and Demographics on the Consumer’s Online Buying Behavior. Journal of Computer-Mediated Communication, 5(2), 0–0.
    Lian, J.-W., & Yen, D. C. (2013). To buy or not to buy experience goods online: Perspective of innovation adoption barriers. Computers in Human Behavior, 29(3), 665–672.
    Liang, T.-P., & Huang, J.-S. (1998). An empirical study on consumer acceptance of products in electronic markets: a transaction cost model. Decision support systems, 24(1), 29–43.
    Lu, H. P., & Su, P. Y. J. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19(4), 442–458.
    Marakas, G. M., Mun, Y. Y., & Johnson, R. D. (1998). The multilevel and multifaceted character of computer self-efficacy: Toward clarification of the construct and an integrative framework for research. Information systems research, 9(2), 126–163.
    Maxham III, J. G. (2001). Service recovery’s influence on consumer satisfaction, positive word-of-mouth, and purchase intentions. Journal of Business Research, 54(1), 11–24.
    McFarland, D. J., & Hamilton, D. (2006). Adding contextual specificity to the technology acceptance model. Computers in Human Behavior, 22(3), 427-447.
    Mitchell, V.W., & Boustani, P. (1994). A preliminary investigation into pre-and post-purchase risk perception and reduction. European Journal of Marketing, 28(1), 56–71.
    Miquel, S., Caplliure, E. M., & Aldas-Manzano, J. (2002). The Effect of Personal Involvement on the Decision to Buy Store Brands. Journal of Product & Brand Management, 11(1), 6–18.
    Monroe, K. B. (2003). Pricing: Making Profitable Decisions. McGraw-Hill School Education Group.
    Murphy, C. A., Coover, D., & Owen, S. V. (1989). Development and validation of the computer self-efficacy scale. Educational and Psychological Measurement, 49(4), 893-899.
    Nelson, P. J. (1981). Consumer information and advertising. Economics of information, 42(77), 42–77.
    Nelson, P. J. (1974). Advertising as Information. Journal of Political Economy, 82(4), 729.
    Nelson, P. J. (1974). The economic value of advertising. Advertising and society, 43–66), 43–66.
    Nelson, P. J. (1970). Information and Consumer Behavior. Journal of Political Economy, 78(2), 311–329.
    Ochi, P., Rao, S., Takayama, L., & Nass, C. (2010). Predictors of user perceptions of web recommender systems: How the basis for generating experience and search product recommendations affects user responses. International Journal of Human-Computer Studies, 68(8), 472–482.
    Oliver, R. L., & Bearden, W. O. (1983). The Role of Involvement in Satisfaction Processes. Advances in consumer research, 10(1), 250–255.
    Park, D. -H., Lee, J., & Han, I. (2007). The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement. International Journal of Electronic Commerce, 11(4), 125-148.
    Peter, J. P., & Olson, J. C. (2005). Consumer behavior and marketing strategy. New York: McGraw-Hill.
    Peterson, R. A., & Merino, M. C. (2003). Consumer Information Search Behavior and the Internet. Psychology & Marketing, 20(2), 99–121.
    Peterson, R. A., Balasubramanian, S., & Bronnenberg, B. J. (1997). Exploring the implications of the Internet for consumer marketing. Journal of the Academy of Marketing Science, 25(4), 329–346.
    Phau, I., & Poon, S. M. (2000). Factors influencing the types of products and services purchased over the Internet. Internet Research, 10(2), 102–113.
    Punj, G. N., & Staelin, R. (1983). A model of consumer information search behavior for new automobiles. Journal of Consumer Research, 9(4), 366–380.
    Richard, M. O., & Chandra, R. (2005). A model of consumer web navigational behavior: conceptual development and application. Journal of business Research, 58(8), 1019-1029.
    Salisbury, W. D., Pearson, R. A., Pearson, A. W., & Miller, D. W. (2001). Perceived security and World Wide Web purchase intention. Industrial Management & Data Systems, 101(4), 165–177.
    Sarker, S., & Wells, J. D. (2003). Understanding mobile handheld device use and adoption. Commun. ACM, 46(12), 35–40.
    Schiffman, L. G., & Kanuk, L. L. (2000). Consumer behavior. 7th. edn., Prentice Hall International, New Jersey.
    Shao, C. Y., Baker, J. A., & Wagner, J. (2004). The effects of appropriateness of service contact personnel dress on customer expectations of service quality and purchase intention: The moderating influences of involvement and gender. Journal of Business Research, 57(10), 1164–1176.
    Sherif, C. W., Sherif, M., & Nebergall, R. E. (1965). Attitude and Attitude Change: The Social Judgment-involvement Approach. Greenwood Publishing Group, Incorporated.
    Shim, S., Eastlick, M. A., Lotz, S. L., & Warrington, P. (2001). An online prepurchase intentions model: The role of intention to search: Best Overall Paper Award—The Sixth Triennial AMS/ACRA Retailing Conference, 2000☆ 11☆ Decision made by a panel of Journal of Retailing editorial board members.. Journal of retailing, 7(3), 397–416.
    Solomon, Michael R. Consumer behavior: buying, having, and being. Pearson Education, 2009.
    Sutton, S., & Hallett, R., (1989). Understanding Seat-Belt Intentions and Behavior: A Decision-Making Approach1. Journal of Applied Social Psychology, 19(15), 1310–1325.
    Swaminathan, V., Lepkowska-White, E., & Rao, B. P. (1999). Browsers or Buyers in Cyberspace? An Investigation of Factors Influencing Electronic Exchange. Journal of Computer-Mediated Communication, 5(2), 0–0.
    Swinyard, W. R. (1993). The Effects of Mood, Involvement, and Quality of Store Experience on Shopping Intentions. Journal of Consumer Research, 20(2), 271–280.
    Taylor, M. S., Locke, E. A., Lee, C., & Gist, M. E. (1984). Type A behavior and faculty research productivity: What are the mechanisms?. Organizational Behavior and Human Performance, 34(3), 402-418.
    Torkzadeh, R., Pflughoeft, K., & Hall, L. (1999). Computer self-efficacy, training effectiveness and user attitudes: An empirical study. Behaviour & Information Technology, 18(4), 299-309.
    Torkzadeh, G., & Koufteros, X. (1994). Factorial validity of a computer self-efficacy scale and the impact of computer training. Educational and psychological Measurement, 54(3), 813-821.
    Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information systems research, 11(4), 342–365.
    Venkatesh, V. (1999), Creation of favorable user perceptions: exploring the role of intrinsic motivation, MIS Quarterly, (23)2, 239-60.
    Venkatesh, V. and Davis, F.D. (1996), A model of the antecedents of perceived ease of use: development and test, Decision Sciences, 27(3), 451-81.
    Wang, Y.-S. (2003). The adoption of electronic tax filing systems: an empirical study. Government Information Quarterly, 20(4), 333–352.
    Weathers, D., Sharma, S., & Wood, S. L. (2007). Effects of online communication practices on consumer perceptions of performance uncertainty for search and experience goods. Journal of Retailing, 83(4), 393–401.
    Weber, K., & Roehl, W. S. (1999). Profiling people searching for and purchasing travel products on the World Wide Web. Journal of Travel Research, 37(3), 291–298.
    Wilkie, William L., and Peter R. Dickson. Shopping for appliances: Consumers` strategies and patterns of information search. Marketing Science Institute, 1985.
    Woodside, A. G., Frey, L. L., & Daly, R. T. (1989). Linking Service Quality, Customer Satisfaction, and Behavioral Intention. Journal of Health Care Marketing, 9(4), 5–17.
    Wu, J.-H., Chen, Y.-C., & Lin, L.-M. (2007). Empirical evaluation of the revised end user computing acceptance model. Computers in Human Behavior, 23(1), 162–174.
    Wu, J.-H., Wang, S.-C., & Lin, L.-M. (2007). Mobile computing acceptance factors in the healthcare industry: A structural equation model. International Journal of Medical Informatics, 76(1), 66–77.
    Xiao, B. & Benbasat, I. (2011). Product-related deception in e-commerce: A Theoretical Respective. MIS Quarterly, 35(1), 169-195.
    Zaichkowsky, J. L. (1994). Research Notes: The Personal Involvement Inventory: Reduction, Revision, and Application to Advertising. Journal of Advertising, 13(4), 59-70.
    Zaichkowsky, J. L. (1985). Measuring the Involvement Construct. Journal of Consumer Research, 12(3), 341–352.
    Zaichkowsky, J. L. (1943). The Personal Involvement Inventory: Reduction, Revision, and Application to Advertising. Journal of advertising, 23(4), 59–70.
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