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  • P-ISSN1738-3110
  • E-ISSN2093-7717
  • SCOPUS, ESCI

Role of Online Social Decision When Purchasing NP : The Moderating Effect of NP Innovation

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2018, v.16 no.7, pp.57-65
https://doi.org/https://doi.org/10.15722/jds.16.7.201807.57
Han, Sang-Seol

Abstract

Purpose - Recently, internet access and social network utilization using smart phone are increasing. In such a smart environment, interactive activities such as information generation, information searching and information sending are increasing rapidly on-line environment. Therefore, consumers tend to purchase something according to eWOM and also meet the social consensus online environment. In connectivity society, consumers became accessible and engaged in the opinions of others easily. Many decisions that seem like personal decisions are actually social decisions on online connectivity. This paper seeks to explore factors that can help generate a social decision on purchasing of new products in an online environment. Research design, data, and methodology - The process of collecting a lot of wisdom and making an agreement online is called social decision. The purpose of this paper is to examine empirically the influence of factors such as online ties, online eWOM expectancy and online information behavior on online social decision. In addition, We studied online social decision by analyzing the moderating effect of new product innovation. To understand this structural relationship, research hypotheses and research models were set up and empirical analysis was conducted. In order to verify the hypothesis, 208 questionnaires were collected from the residents of Seoul city/Gyeonggi province. The answered questionnaire verifies reliability and validity using SPSS/AMOS and test hypotheses through path analysis and multiple regression analysis. Results - According to the research results, First, online ties don't have a positive impact on online social decision, Second, online eWOM expectancy have a positive impact on online social decision. Third, online information behaviors have a positive impact on online social decision. The degree of innovation of new products have a moderating effect between Independent variables of three factors and dependent variable of social decision. Conclusions - Social decisions have a positive impact on purchasing decisions about new product. There is a great significance in the fact that the online social influence and online social decision have been studied academically. It is meaningful that we have studied in depth the changing phenomenon of consumer purchase decision process in smart environment. The results of these studies provide academic and practical implications.

keywords
Ties, Information Behavior, eWOM Expectancy, Online Social Decision, New Product

Reference

1.

Andrew, T. S., & Donal, R. L. (2016). How Word-of-Mouth Transmission Encouragement Affects Consumers’Transmission Decision, Receiver Selection, and Diffusion Speed. International Journal of Research in Marketing, 33(4), 755-766.

2.

Bone, F. P. (1992). Determinants Of Word-Of-Mouth Communications During Product Consumption. Advances in Consumer Research, 19(1), 579-583.

3.

Bronjarczyk, S. M., & Alba, J. W. (1994). The Role of Consumer’ Intuitions in Inference Making. Journal of Consumer Research, 21(3), 393-407.

4.

Brown, J. J., & Peter, H. R. (1987). Social Ties And Word-Of-Mouth Referral Behavior. Journal Of Consumer Research, 14(3), 350-362.

5.

Cannoy, S. D., & Salam, A. E. (2010). A Framework for Health Care Information Assurance Policy and Compliance. Communications of the ACM, 53(3), 126-131.

6.

Christy, M., Cheung, K., & Dimple R. T. (2012). The Impact of Electronic Word-of-Mouth Communication:A Literature Analysis and Integrative Model, Decision Support Systems, 54(1), 461-470.

7.

Chiu, C. M., Meng, H. H., & Eric, T. W. (2006). Understanding Knowledge Sharing in Virtual Communities: An Integration of Social Capital and Cognitive Theories. Decision Support System, 42(3), 1872-1888.

8.

Chu, S. C., & Kim, Y. J. (2011). Determinants Of Consumer Engagement In Electronic Word-Of-Mouth (Ewom) In Social Networking Sites. International Journal Of Advertising, 30(1), 47-75.

9.

Deighton, J., & Kent, G. (1995). Marketing and Seduction:Building Exchange Relationships by Managing Social Consensus. Journal of Consumer Research, 21(4), 660-676.

10.

Devinder, P. S. (2014). Online Shopping Motivations, Information Search, and Shopping Intention in an Emerging Economy. East Asian Journal of Business Management, 14(3), 5-12.

11.

Dinet, J., Chevalier, A., & Tricot, A. (2012). Information Search Activity: An Overview. Revue Europeenne de Psychologie Appliquee, 62(2), 49-62.

12.

Godes, D., & Dina, M. (2004). Using Online Conversations to Study Word-Of-Mouth Communication. Marketing Science, 23(4), 545-560.

13.

Granovetter, M. (1983). The Strength of Weak Ties: A Network Theory Revisited. Sociological Theory, 1(6), 201-233

14.

Habibollah, J., Ali, I., & Sorayya B. B. (2014). New Clothing Adoption in an Islamic Market. International Journal of Industrial Distribution &Business, 15(4), 13-22.

15.

Hoeffler, S. (2003). Measuring Preferences for Really New Products. Journal of Marketing Research, 40(4), 406-420.

16.

Huang, M., Cai, F., Alex, S. L. T., & Zhou, N. (2011). Making Your Online Voice Loud: the Critical Role of WOM Information. European Journal of Marketing, 45(7/8), 1277-1297.

17.

Jaakko, P., Hannu, S., Mark T. S., & Mika, Y. (2017). From Electronic WOM to Social eWOM: Bridging the Trust Deficit. Journal of Marketing Theory and Practice, 25(3), 340-356.

18.

Jillian, C. S., Geoffrey, N., & Soutar, T. M. (2008). Factors Influencing Word of Mouth Effectiveness:Receiver Perspectives. European Journal of Marketing, 42(3/4), 344-364.

19.

Kalwani, M. L., Yim, C. K., Rinne, H. J., & Sugita, Y. (1990). A Price Expectations Model of Customer Brand Choice. Journal of Marketing Research, 27(3), 251-262.

20.

Kim, N. E., Song, G. S., & Kim, M. S. (2018). The Relationship among Narcissism, Usage Motive, and Information Diffusion of Social Media. International Journal of Industrial Distribution & Business. 19(1), 99-110.

21.

Kim, J. N., & Grunig, J. E. (2011). Problem Solving and Communicative Action: A Situational Theory of Problem Solving. Journal of Communication, 61(1), 120-149.

22.

Kotler, P., Kartajaya, H., & Iwan, S. (2016). Marketing 4.0. New Jersey: Wilet.

23.

Moriarty, R. T., & Thomas, J. K. (1989). High-Tech Marketing: Concepts, Continuity, and Change. MIT Sloan Management Review, 30(4), 7-17.

24.

Moreau, C. P., Arthur, B. M., & Donald, R. L. (2001). What is It? Categorization Flexibility and Consumers' Responses to Really New Products. Journal of Consumer Research, 27(4), 489-498.

25.

Raassens, N., Wuyts, S., & Geyskens, I. (2012). The Market Valuation of Outsourcing New Product Development. Journal of Marketing Research, 49(5), 682-695.

26.

Smith, A. N., Eileen, F., & Chen, Y. J. (2012). How Does Brand-related User-generated Contents Differ across YouTube, Facebook, and Twitter?. Journal of Interactive Marketing, 26(2), 102-113.

27.

Steffes, M. S., & Lawrence, E. B. (2009). Social Ties And Online Word of Mouth. Internet Research, 19(1), 42-59.

28.

Sweeney, J., Soutar, G., & Mazzarol, T. (2014). Factors Enhancing Word-of-Mouth Influence: Positive and Negative Service-related Messages. European Journal of Marketing, 48(1/2), 336-359.

29.

Tan, W. K. (2017). The Effect Of Temporal Psychological Distance On Reliance On Word-Of-Mouth For Information About Destination Image Attributes. Behaviour and Information Technology, 36(11), 1101-1110.

30.

Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model:Four Longitudinal Field Studies. Management Science, 46(2), 186-204.

31.

Wilson, E. J., & Sherrell, D. L. (1993). Source Effects in Communication and Persuasion Research: A Meta-Analysis of Effect Size. Journal of the Academy of Marketing Science, 21(2), 101-112.

32.

Zao, Y., & Kim, S. B. (2018). Effect of Directionality and Type of Online e-WOM on Purchase Intention and Moderating Role of Regulatory Focus. Asia-pacific Journal of Multimedia Service Convergent with An Humanities and Sociology, 8(1), 121-131.

The Journal of Distribution Science