隨著科技的蓬勃發展與消費模式的改變，智慧科技也慢慢進入零售業的生態鏈，使得全球零售業都勢必面臨改變，也推動實體零售商及智慧技術的整合。然而，在新零售領域的研究，大多探討消費者的購物行為與顧客對新零售技術的滿意度及接受度，卻很少有學者在研究零售商採用新技術的行為意圖。本研究目的是以 TOE 框架探討哪些關鍵因素會影響零售企業願意採用無人商店智慧技術進而成立無人商店。因此，本研究運用計畫行為理論(TPB)和科技-組織-環境(TOE)框架為基礎，建構出本研究模型，共包含九個構面及八條假設，研究對象為正要採用無人商店智慧技術之零售商，共收集了 127 份有效問卷來檢驗假設，透過結構方程模型(PLS-SEM)來驗證構面之間的關係，本研究提出計畫行為理論和 TOE 框架整合的研究理論與模型，可供實務上零售企業將採用新技術時的借鏡，並對學術也提供零售領域的參考。

With the development of technology and the change of consumer behaviors, smart technology has entered the retail ecosystem. While the global retail industry faces these changes, traditional retailers are compelled to implement smart retail technology. Although most of previous studies on smart store technologies focused mainly on consumer shopping behavior and customer satisfaction and acceptance of new retail technologies, few examined investigation into the behavioral intentions of retailers to adopt new technologies. The purpose of this study is to explore the key factors that influence retailers’ intention to implement smart retail technologies and establish unmanned stores. Therefore, based on the theory of planned behavior (TPB) and technology-organization-environment framework (TOE), the study develops a research model including 10 constructs and 9 hypotheses. The respondents are traditional retailers which tend to implement smart retail technologies, thus, we cooperated with Jian24 distribute questionnaires to the respondents in China. A total of 127 valid questionnaires were collected to test the hypothesis using structural equation model (PLS). This study integrates TPB and TOE framework to develop a new research model. The results can offer practical suggestions for retailers to implement smart retail technologies, as well as provide an academic contribution to the research areas.

〔1〕 Inman, J. J., & Nikolova, H. (2017). Shopper-facing retail technology: A retailer
adoption decision framework incorporating shopper attitudes and privacy
concerns. Journal of retailing, 93(1), 7-28.
〔2〕 Roy, S. K., Shekhar, V., Lassar, W. M., & Chen, T. (2018). Customer engagement
behaviors: The role of service convenience, fairness and quality. Journal of Retailing and
Consumer Services, 44, 293-304.
〔3〕 Pantano, E., & Naccarato, G. (2010). Entertainment in retailing: The influences of
advanced technologies. Journal of Retailing and Consumer Services, 17(3), 200-204.
〔4〕 Renko, S., & Druzijanic, M. (2014). Perceived usefulness of innovative technology
in retailing: Consumers ׳ and retailers׳ point of view. Journal of retailing and consumer
services, 21(5), 836-843.
〔5〕 Gartner, 2020. Forecast: Enterprise IT Spending for the Retail Market, Worldwide,
2018-2024, 1Q20Update. https://www.gartner.com/en/documents/3984885/forecastenterprise-it-spending-for-the-retail-market-wo. (Accessed 16 Feb 2022).
〔6〕 Grand View Research, (2018). Smart Retail Market Growth & Trends.
https://www.grandviewresearch.com/press-release/global-smart-retailmarket#:~:text=Smart%20Retail%20Market%20Growth%20%26%20Trends%20The%20
global,a%20CAGR%20of%2023.9%25%20during%20the%20forecast%20period.
(Accessed 20 Jan 2023).
〔7〕 Hoffman, D. L., & Novak, T. (2015). Emergent experience and the connected
consumer in the smart home assemblage and the internet of things. Available at SSRN
2648786.
43
〔8〕 Wünderlich, N. V., Wangenheim, F. V., & Bitner, M. J. (2013). High tech and high
touch: a framework for understanding user attitudes and behaviors related to smart
interactive services. Journal of Service Research, 16(1), 3-20.
〔9〕 Pantano, E., & Viassone, M. (2014). Demand pull and technology push perspective
in technology-based innovations for the points of sale: The retailers evaluation. Journal of
Retailing and Consumer Services, 21(1), 43-47.
〔10〕 Evanschitzky, H., Iyer, G. R., Pillai, K. G., Kenning, P., & Schütte, R. (2015).
Consumer trial, continuous use, and economic benefits of a retail service innovation: The
case of the personal shopping assistant. Journal of Product Innovation Management, 32(3),
459-475.
〔11〕 Roy, S. K., Shekhar, V., Quazi, A., & Quaddus, M. (2020). Consumer engagement
behaviors: do service convenience and organizational characteristics matter?. Journal of
Service Theory and Practice.
〔12〕 Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2020). The future of
technology and marketing: A multidisciplinary perspective. Journal of the Academy of
Marketing Science, 48(1), 1-8.
〔13〕 Pantano, E., & Timmermans, H. (2014). What is smart for retailing?. Procedia
Environmental Sciences, 22, 101-107.
〔14〕 Chen, S. C., & Shang, S. S. (2021). Sustaining User Experience in a Smart System in
the Retail Industry. Sustainability, 13(9), 5090.
〔15〕 Bradford, M., Earp, J. B., & Grabski, S. (2014). Centralized end-to-end identity and
access management and ERP systems: A multi-case analysis using the Technology
Organization Environment framework. International Journal of Accounting Information
Systems, 15(2), 149-165.
44
〔16〕 Zheng, X., Lu, Y., Le, Y., Li, Y., & Fang, J. (2018). Formation of interorganizational
relational behavior in megaprojects: Perspective of the extended theory of planned behavior.
Journal of Management in Engineering, 34(1), 04017052.
〔17〕 Gavetti, G., Greve, H. R., Levinthal, D. A., & Ocasio, W. (2012). The behavioral
theory of the firm: Assessment and prospects. Academy of Management Annals, 6(1), 1-40.
〔18〕 Pantano, E., & Priporas, C. V. (2016). The effect of mobile retailing on consumers'
purchasing experiences: A dynamic perspective. Computers in human behavior, 61, 548-
555.
〔19〕 Bassano, C., Piciocchi, P., & Pietronudo, M. C. (2018). Managing value co-creation
in consumer service systems within smart retail settings. Journal of Retailing and
Consumer Services, 45, 190-197.
〔20〕 Bradlow, E. T., Gangwar, M., Kopalle, P., & Voleti, S. (2017). The role of big data
and predictive analytics in retailing. Journal of Retailing, 93(1), 79-95.
〔21〕 Pantano, E., & Servidio, R. (2012). Modeling innovative points of sales through
virtual and immersive technologies. Journal of Retailing and Consumer Services, 19(3),
279-286.
〔22〕 Adapa, S., Fazal-e-Hasan, S. M., Makam, S. B., Azeem, M. M., & Mortimer, G.
(2020). Examining the antecedents and consequences of perceived shopping value through
smart retail technology. Journal of Retailing and Consumer Services, 52, 101901.
〔23〕 Kim, Y. (2021). Revitalization of Offline Fashion Stores: Exploring Strategies to
Improve the Smart Retailing Experience by Applying Mobile
Technology. Sustainability, 13(6), 3434.
45
〔24〕 Scholz, J., & Duffy, K. (2018). We ARe at home: How augmented reality reshapes
mobile marketing and consumer-brand relationships. Journal of Retailing and Consumer
Services, 44, 11-23.
〔25〕 Dacko, S. G. (2017). Enabling smart retail settings via mobile augmented reality
shopping apps. Technological Forecasting and Social Change, 124, 243-256.
〔26〕 Li, R., Song, T., Capurso, N., Yu, J., Couture, J., & Cheng, X. (2017). IoT applications
on secure smart shopping system. IEEE Internet of Things Journal, 4(6), 1945-1954.
〔27〕 Mukherjee, A., Smith, R. J., & Turri, A. M. (2018). The smartness paradox: the
moderating effect of brand quality reputation on consumers' reactions to RFID-based smart
fitting rooms. Journal of Business Research, 92, 290-299.
〔28〕 Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation.
Lexington, MA: Lexington Books.
〔29〕 Rogers, E. M. (1995). Diffusion of Innovations: modifications of a model for
telecommunications. Die diffusion von innovationen in der telekommunikation, 25-38.
〔30〕 Baker, J. (2012). The technology–organization–environment framework. Information
systems theory, 231-245.
〔31〕 Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in
small businesses using a technology–organization–environment framework. Information &
management, 38(8), 507-521.
〔32〕 Pan, M. J., & Jang, W. Y. (2008). Determinants of the adoption of enterprise resource
planning within the technology-organization-environment framework: Taiwan's
communications industry. Journal of Computer information systems, 48(3), 94-102.
〔33〕 Lian, J.W., Yen, D.C. and Wang, Y.T. (2014), “An exploratory study to understand
46
the critical factors affecting the decision to adopt cloud computing in Taiwan hospital”,
International Journal of Information Management, Vol. 34 No. 1, pp. 28-36.
〔34〕 Ghobakhloo, M., Arias‐Aranda, D., & Benitez‐Amado, J. (2011). Adoption of e‐
commerce applications in SMEs. Industrial Management & Data Systems.
〔35〕 Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and
human decision processes, 50(2), 179-211.
〔36〕 Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An
introduction to theory and research. Philosophy and Rhetoric, 10(2).
〔37〕 Bandura, A. (1977). Self-efficacy: toward a unifying theory of behavioral
change. Psychological review, 84(2), 191.
〔38〕 Mishra, D., Akman, I., & Mishra, A. (2014). Theory of reasoned action application
for green information technology acceptance. Computers in human behavior, 36, 29-40.
〔39〕 Trafimow, D. (2009). The theory of reasoned action: A case study of falsification in
psychology. Theory & Psychology, 19(4), 501-518.
〔40〕 Chatzisarantis, N. L., Hagger, M. S., & Brickell, T. (2008). Using the construct of
perceived autonomy support to understand social influence within the theory of planned
behavior. Psychology of Sport and Exercise, 9(1), 27-44.
〔41〕 Lu, H., & Lin, J. C. C. (2002). Predicting customer behavior in the market-space: a
study of Rayport and Sviokla’s framework. Information & Management, 40(1), 1-10.
〔42〕 Dodor, J. B. K., & Rana, D. S. (2009). Investigating business schools' intentions about
offering e‐commerce education using an extended theory of planned behavior. Decision
Sciences Journal of Innovative Education, 7(1), 195-220.
47
〔43〕 Veronese, D., & Kensler, L. (2013). School leaders, sustainability and green school
practices: An elicitation study using the theory of planned behavior. Journal of
Sustainability Education, 4(1), 1-21.
〔44〕 Souitaris, V., Zerbinati, S., & Al-Laham, A. (2007). Do entrepreneurship
programmes raise entrepreneurial intention of science and engineering students? The effect
of learning, inspiration and resources. Journal of Business venturing, 22(4), 566-591.
〔45〕 Miranda, F. J., Chamorro-Mera, A., & Rubio, S. (2017). Academic entrepreneurship
in Spanish universities: An analysis of the determinants of entrepreneurial
intention. European research on management and business economics, 23(2), 113-122.
〔46〕 Khalifa, M., & Shen, K. N. (2008). Drivers for transactional B2C m-commerce
adoption: Extended theory of planned behavior. Journal of Computer Information
Systems, 48(3), 111-117.
〔47〕 Nanath, K., & Pillai, R. R. (2021). Individual and organizational factors affecting the
implementation of Green IT: a case study of an Indian business school. The Electronic
Journal of Information Systems in Developing Countries, 87(3), e12163.
〔48〕 Awa, H. O., Ojiabo, O. U., & Emecheta, B. C. (2015). Integrating TAM, TPB and
TOE frameworks and expanding their characteristic constructs for e-commerce adoption by
SMEs. Journal of Science & Technology Policy Management, 6(1), 76-94.
〔49〕 Agarwal, R., & Prasad, J. (1998). The antecedents and consequents of user
perceptions in information technology adoption. Decision support systems, 22(1), 15-29.
〔50〕 Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in
rural small businesses. Omega, 27(4), 467-484.
〔51〕 Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology
adoption across time: A cross-sectional comparison of pre-adoption and post-adoption
beliefs. MIS quarterly, 183-213.
48
〔52〕 Mahakittikun, T., Suntrayuth, S., & Bhatiasevi, V. (2020). The impact of
technological-organizational-environmental (TOE) factors on firm performance:
Merchant’s perspective of mobile payment from Thailand’s retail and service
firms. Journal of Asia Business Studies, 15(2), 359-383.
〔53〕 De Bellis, E., & Johar, G. V. (2020). Autonomous shopping systems: Identifying and
overcoming barriers to consumer adoption. Journal of Retailing, 96(1), 74-87.
〔54〕 Lee, Y., & Kozar, K. A. (2008). An empirical investigation of anti-spyware software
adoption: A multitheoretical perspective. Information & Management, 45(2), 109-119.
〔55〕 Plouffe, C. R., Hulland, J. S., & Vandenbosch, M. (2001). Richness versus parsimony
in modeling technology adoption decisions—understanding merchant adoption of a smart
card-based payment system. Information systems research, 12(2), 208-222.
〔56〕 Moon, K. L., & Ngai, E. W. T. (2008). The adoption of RFID in fashion retailing: a
business value‐added framework. Industrial Management & Data Systems, 108(5), 596-
612.
〔57〕 Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer
technology: A comparison of two theoretical models. Management science, 35(8), 982-
1003.
〔58〕 Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance
of information technology: Toward a unified view. MIS quarterly, 425-478.
〔59〕 Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A
test of competing models. Information systems research, 6(2), 144-176.
〔60〕 Van der Heijden, G. A., Schepers, J. J., Nijssen, E. J., & Ordanini, A. (2013). Don’t
just fix it, make it better! Using frontline service employees to improve recovery
performance. Journal of the Academy of marketing Science, 41, 515-530.
49
〔61〕 Al-Jabri, I. M., & Roztocki, N. (2015). Adoption of ERP systems: Does information
transparency matter?. Telematics and Informatics, 32(2), 300-310.
〔62〕 Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the
perceptions of adopting an information technology innovation. Information systems
research, 2(3), 192-222.
〔63〕 Choi, J., Lee, A., & Ok, C. (2013). The effects of consumers' perceived risk and
benefit on attitude and behavioral intention: A study of street food. Journal of Travel &
Tourism Marketing, 30(3), 222-237.
〔64〕 Oliveira, T., & Martins, M. F. (2010). Understanding e‐business adoption across
industries in European countries. Industrial Management & Data Systems.
〔65〕 Chang, Y. W., Hsu, P. Y., Huang, S. H., & Chen, J. (2020). Determinants of switching
intention to cloud computing in large enterprises. Data Technologies and
Applications, 54(1), 16-33.
〔66〕 Chwelos, P., Benbasat, I., & Dexter, A. S. (2001). Empirical test of an EDI adoption
model. Information systems research, 12(3), 304-321.
〔67〕 Ifinedo, P. (2011). Internet/e‐business technologies acceptance in Canada's SMEs: an
exploratory investigation. Internet Research, 21(3), 255-281.
〔68〕 Chong, A. Y. L., & Chan, F. T. (2012). Structural equation modeling for multi-stage
analysis on Radio Frequency Identification (RFID) diffusion in the health care industry.
Expert Systems with Applications, 39(10), 8645-8654.
〔69〕 Chen, C. D., Fan, Y. W., & Farn, C. K. (2007). Predicting electronic toll collection
service adoption: An integration of the technology acceptance model and the theory of
planned behavior. Transportation Research Part C: Emerging Technologies, 15(5), 300-311.
50
〔70〕 Ordanini, A., & Rubera, G. (2010). How does the application of an IT service
innovation affect firm performance? A theoretical framework and empirical analysis on ecommerce. Information & Management, 47(1), 60-67.
〔71〕 Watson, K., Hogarth‐Scott, S., & Wilson, N. (1998). Small business start‐ups:
success factors and support implications. International Journal of Entrepreneurial
Behavior & Research, 4(3), 217-238.
〔72〕 Tan, M., & Teo, T. S. (2000). Factors influencing the adoption of Internet
banking. Journal of the Association for information Systems, 1(1), 5.
〔73〕 Du, W., & Li, M. (2019). Government support and innovation for new energy firms
in China. Applied Economics, 51(25), 2754-2763.
〔74〕 Songling, Y., Ishtiaq, M., Anwar, M., & Ahmed, H. (2018). The role of government
support in sustainable competitive position and firm performance. Sustainability, 10(10),
3495.
〔75〕 Teo, H. H., Tan, B. C., & Wei, K. K. (1997). Organizational transformation using
electronic data interchange: The case of TradeNet in Singapore. Journal of Management
Information Systems, 13(4), 139-165.
〔76〕 Seiders, K., Berry, L. L., & Gresham, L. G. (2000). Attention, retailers! How
convenient is your convenience strategy?. MIT Sloan Management Review, 41(3), 79.
〔77〕 Lin, H. F. (2007). Predicting consumer intentions to shop online: An empirical test
of competing theories. Electronic Commerce Research and Applications, 6(4), 433-442.
〔78〕 Tan, Z., & Ouyang, W. (2004). Diffusion and Impacts of the Internet and E‐
Commerce in China. Electronic Markets, 14(1), 25-35.
〔79〕 Hoogland, J. J., & Boomsma, A. (1998). Robustness studies in covariance structure
modeling: An overview and a meta-analysis. Sociological Methods & Research, 26(3),
329-367.
51
〔80〕 Boomsma, A., & Hoogland, J. J. (2001). The robustness of LISREL modeling
revisited. Structural equation models: Present and future. A Festschrift in honor of Karl
Jöreskog, 2(3), 139-168.
〔81〕 Kline, T. J. (2005). Psychological testing: A practical approach to design and
evaluation. Sage publications.
〔82〕 Schumacker, R. E., & Lomax, R. G. (1996). A beginner's guide to structural equation
modeling. Lawrence Erlbaum Associates, Inc.
〔83〕 Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). Editor's comments: a critical
look at the use of PLS-SEM in" MIS Quarterly". MIS quarterly, iii-xiv.
〔84〕 Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver
bullet. Journal of Marketing theory and Practice, 19(2), 139-152.
〔85〕 Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable
variables and measurement error: Algebra and statistics.
〔86〕 Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006).
Multivariate data analysis 6th Edition.
〔87〕 Clark, L. A., & Watson, D. (2016). Constructing validity: Basic issues in objective
scale development.
〔88〕 Kline, R. B. (2011). Principles and practice of structural equation modeling. New
York: Guilford Press
〔89〕 Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An
organizational capabilities perspective. Journal of management information systems, 18(1),
185-214.
〔90〕 Teo, T. S., Srivastava, S. C., & Jiang, L. I. (2008). Trust and electronic government
success: An empirical study. Journal of management information systems, 25(3), 99-132.
52
〔91〕 Oliveira, T., Thomas, M. and Espadanal, M. (2014), “Assessing the determinants of
cloud computing adoption: an analysis of the manufacturing and services sectors”,
Information and Management, Vol. 51 No. 5, pp. 497-510.
〔92〕 Puklavec, B., Oliveira, T., & Popovič, A. (2018). Understanding the determinants of
business intelligence system adoption stages: An empirical study of SMEs. Industrial
Management & Data Systems.
〔93〕 Grewal, D., Noble, S. M., Roggeveen, A. L., & Nordfalt, J. (2020). The future of instore technology. Journal of the Academy of Marketing Science, 48(1), 96-113.
〔94〕 Workman, M. (2005). Expert decision support system use, disuse, and misuse: a study
using the theory of planned behavior. Computers in Human Behavior, 21(2), 211-231.
〔95〕 Pavlou, P. A., & Fygenson, M. (2006). Understanding and predicting electronic
commerce adoption: An extension of the theory of planned behavior. MIS quarterly, 115-
143.