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  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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

Consumer Perceptions on SST in Retail Atmosphere: An application of S-O-R framework

Consumer Perceptions on SST in Retail Atmosphere: An application of S-O-R framework

The Journal of Distribution Science(JDS) / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2020, v.18 no.3, pp.87-97
https://doi.org/https://doi.org/10.15722/jds.18.3.202003.87
BYUN, Sookeun (College of Business, Kwangwoon University)
HA, Yongsoo (College of Business, Kwangwoon University)

Abstract

Purpose: The aim of this study is to understand the internal and external responses that consumers experience when they are exposed to an innovative system in retail stores. This study considered the SST(Self-Service Technology) system in a retail setting as a type of functional environmental stimuli and selected a smart shopping cart as an example of SST system. The influences of functional environmental stimuli on consumers' emotional, cognitive, and behavioral responses were examined by applying S-O-R model. In addition, this study attempted to extend the traditional S-O-R model by (a) incorporating personal characteristics variables such as time pressure and perceived crowding and (b) considering not only emotional but also cognitive aspects of consumers' internal responses. Research Design, Data, and Methodology: This study used a video-scenario technique. Participants watched a video about grocery shopping situations using a smart shopping cart and responded to their emotional, cognitive, and behavioral responses. An online survey was conducted using Amazon's Mechanical Turk (N = 185). All participants were US consumers over 20 years old and had been shopping at the grocery store in the last month. Data were analyzed through structural equations modeling with AMOS 20. Results: Test results showed that consumers who perceived higher levels of time pressure and perceived crowding in usual shopping situations were more likely to evaluate the SST system favorably. The results showed that personal characteristics have a significant impact on consumers' evaluation of functional environmental stimuli in retail setting. As consumers evaluated the SST system favorably, they experienced more positive affect and less negative affect during their shopping behaviors. Positive affect led to good service quality inference, which further increased patronize intention. However, negative affect did not show a significant impact on service quality inference, but only on patronize intention. Conclusions: This study attempted to investigate the influence of SST system by extending the traditional S-O-R model. This study classified the SST system as functional environmental stimulus of retail stores and analyzed the effect of stimulus on consumers' internal and external responses. The results of this study showed that the introduction of innovative SST can serve as an effective store differentiation strategy in an increasingly competitive retail environment.

keywords
Self-Service Technology, S-O-R model, Environmental Stimulus, Service Quality

참고문헌

1.

Anderson, J, C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.

2.

Areni, C. S. (2003). Exploring managers‘ implicit theories of atmospheric music: comparing academic analysis to industry insight. Journal of Services Marketing, 17(2), 161-184.

3.

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.

4.

Babin, B, J., & Darden, W. R. (1996). Good and bad shopping vibes: Spending and patronage satisfaction. Journal of Business Research, 35(1), 201-206.

5.

Bagozzi, R. P. (1992). The self-regulation of attitudes, intentions, and behavior. Social Psychology Quarterly, 55(2), 178-204.

6.

Bagozzi, R. P. (1986). Principles of marketing management. Chicago, IL: Science Research Associates, Inc.

7.

Baker, J. (1986). The role of environment in marketing services:The consumer perspective. In J. A. Cepeil (Eds.) The services challenge: Integrating for competitive advantage (pp. 79–84). Chicago, IL: American Marketing Association.

8.

Baker, J., Parasuraman, A., Grewal, D., & Voss, G. (2002). The influence of multiple store environment cues on perceived merchandise value and patronage intentions. Journal of Marketing, 66, 120–141.

9.

Baker, J., Grewal, D., & Levy, M. (1992). An experimental approach to making retail store environmental decisions. Journal of Retailing, 68(4), 445-460.

10.

Becker, K., & Lee, J. W. (2019). Organizational usage of social media for corporate reputation management. Journal of Asian Finance, Economics and Business, 6(1), 231-240.

11.

Bitner, M, J. (1992). Servicescapes: The impact of physical surroundings on customers and employees. Journal of Marketing, 56(2), 57-71.

12.

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, 421 – 430.

13.

Collier, J. E., Moore, R. S., Horky, A., & Moore, M. L. (2015). Why the little things matter: Exploring situational influences on customers‘ self-service technology decisions. Journal of Business Research, 68, 703-710.

14.

Donovan, R. J., & Rossiter, J. R. (1982). Store Atmosphere: An Environmental Psychology Approach. Journal of Retailing, 58, 34-57.

15.

Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2001). Atmospheric qualities of online retailing: A conceptual model and implications. Journal of Business Research, 54, 177-184.

16.

Garaus, M., Wagner, U., & Kummer, C. (2015). Cognitive fit, retail shopper confusion, and shopping value: Empirical investigation. Journal of Business Research, 68(5), 1003-1011.

17.

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.

18.

Herrington, J. D., & Capella, L. M. (1995). Shopper reactions to perceived time pressure. International Journal of Retail &Distribution Management, 23(12), 13-20.

19.

Howard, J.A., & Sheth, J. N. (1969). The theory of buyer behavior (pp.467-487). New York, NY: Wiley.

20.

Hui, M. K., & Bateson, J. E. G. (1991). Perceived Control and the Effects of Crowding and Consumer Choice on the Service Experience. Journal of Consumer Research, 18(2), 174–184.

21.

Jain, R., & Bagdare, S. (2011). CRM in retailing: A behavioural Perspective. Journal of Marketing & Communication, 7(2), 31-37.

22.

Ji, S. G. (2006). The effects of service firm‘s CSR activities on organizational trust and service commitment. Korean Journal of Business Administration, 19(5), 1867-1893.

23.

Kerin, R. A., Jain, A., & Howard, D. J. (1992). Store shopping experience and consumer price-quality-value perceptions. Journal of Retailing, 68(4), 376-397.

24.

Kim, M. J., & Park, C. J. (2019). Does customer delight matter in the customer satisfaction-loyalty linkage? Journal of Asian Finance, Economics and Business, 6(3), 235-245.

25.

Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd Ed). New York, NY: The Guilford Press.

26.

Lazarus, R. (1991). Emotion and adaptation. Oxford, UK: Oxford University Press.

27.

Lee, J. W., Kwag, M., & Potluri, R. M. (2015). Antecedents of social networking sites in retail franchise and restaurant business. Journal of Asian Finance, Economics and Business, 2(1), 29-36.

28.

Lee, J. W. (2017). Critical factors affecting consumer acceptance of online health communication: An application of service quality models. Journal of Asian Finance, Economics and Business, 4(3), 85-94.

29.

Lin, I. Y. (2004). Evaluating a Servicescape: The effect of cognition and emotion. International Journal of Hospitality Management, 23(2), 163-178.

30.

Liu, S. (2012). The impact of forced use on customer adoption of self-service technologies. Computers in Human Behavior, 28, 1194-1201.

31.

Machleit, K. A., Kellaris, J. J., & Eroglu, S. A. (1994). Human versus spatial dimensions of crowding perceptions in retail environments: A note on their measurement and effect on shopper satisfaction. Marketing Letters, 5(2), 183-194.

32.

Machleit, K. A., Eroglu, S. A., & Mantel, S. P. (2000). Perceived retail crowding and shopping satisfaction: What modifies this relationship? Journal of Consumer Psychology, 9(1), 29-42.

33.

Marmorstein, H., Grewal, D., & Fishe, R. P. H. (1992). The value of time spent in price-comparison shopping: Survey and experimental evidence. Journal of Consumer Research, 19(1), 52-61

34.

McDonald, W. J. (1994). Time in shopping: The role of personal characteristics. Journal of Retailing, 70(4), 345-365.

35.

Mehrabian, A., & Russel, J. A. (1974). An approach to environmental psychology. Cambridge, MA: Massachusetts Institute of Technology.

36.

Meuter, M. L., Bitner, M. J., Ostrom, A L., & Brown, S. W.(2005). Choosing among alternative service delivery modes:An investigation of customer trial of self-service technologies. Journal of Marketing, 69, 61–83

37.

Parasuraman, A., Zeithaml, V. A., & Berry, L, L. (1988). Servqual:A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-22.

38.

Pons, F., & Laroche, M. (2007). Cross-cultural differences in crowd assessment. Journal of Business Research, 60(3), 269-276.

39.

Roseman, I. J., Spindle, M. S., & Jose, P. E. (1990). Appraisals of emotion-eliciting events. Testing a theory of discrete emotions. Journal of Personality and Social Psychology, 59, 899–915.

40.

Schiffman, H. R. (2001). Sensation and perception (5th Ed.). New York, NY: Wiley.

41.

Sivadas, E., & Baker‐Prewitt, J. L. (2000). An examination of the relationship between service quality, customer satisfaction, and store loyalty. International Journal of Retail &Distribution Management, 28(2), 73-82.

42.

Stokols, D. S. (1972). On the distinction between density and crowding: Some implications for future research. Psychological Review, 79(3), 275-277.

43.

Sweeney, J, C., & Wyber, F. (2002). The role of cognitions and emotions in the music‐approach‐avoidance behavior relationship. Journal of Services Marketing, 16(1), 51-69.

44.

Wakefield, K. L., & Blodgett, J. G. (1999). Customer response to intangible and tangible service factors. Psychology &Marketing, 16(1), 51–68.

45.

Walsh, G., Shiu, E., Hassan, L. M., Michaelidou, N., & Beatty, S.E. (2011). Emotions, store-environmental cues, store-choice criteria, and marketing outcomes. Journal of Business Research, 64(7), 737-744.

46.

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.

47.

ZeithamI, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60, 31-46.

48.

Zhang, X., Li, S., Burke, R. R., & Leykin, A. (2014). An examination of social influence on shopper behavior using video tracking data. Journal of Marketing, 78(5), 24–41.

The Journal of Distribution Science(JDS)