Promoting Consumers’ Sustainable Consumption of Online Retail Cold Chain Logistics Services: Extended Applications of SOR and Cognitive-Affective-Conative Theories
Abstract
:1. Introduction
2. Theoretical Background and Hypotheses
2.1. Theoretical Background
2.2. Hypotheses Development
2.3. Mediation Effects in the Three-Stage Model
3. Research Method
3.1. Sample and Data Collection
3.2. Variables Measurement
4. Data Analysis and Results
4.1. Assessment of Measurement Model
4.2. Hypothesis Test
4.3. Mediation Effect Test
5. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Su, M.; Zhao, J.; Qi, G.; Kim, J.; Park, K.S. Online retailer cold chain physical distribution service quality and consumers: Evidence from China during the COVID-19 pandemic. Int. J. Logist. Res. Appl. 2023, 26, 442–459. [Google Scholar] [CrossRef]
- Liu, G.; Hu, J.; Yang, Y.; Xia, S.; Lim, M.K. Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms. Resour. Conserv. Recycl. 2020, 156, 104715. [Google Scholar] [CrossRef]
- Wang, M.; Wang, Y.; Liu, W.; Ma, Y.; Xiang, L.; Yang, Y.; Li, X. How to achieve a win–win scenario between cost and customer satisfaction for cold chain logistics? Phys. A Stat. Mech. Its Appl. 2021, 566, 125637. [Google Scholar] [CrossRef]
- Wang, Z.; Wang, T.; Hu, H.; Gong, J.; Ren, X.; Xiao, Q. Blockchain-based framework for improving supply chain traceability and information sharing in precast construction. Autom. Constr. 2020, 111, 103063. [Google Scholar] [CrossRef]
- Lim, M.K.; Li, Y.; Song, X. Exploring customer satisfaction in cold chain logistics using a text mining approach. Ind. Manag. Data Syst. 2021, 121, 2426–2449. [Google Scholar] [CrossRef]
- Shi, Y.; Lin, Y.; Lim, M.K.; Tseng, M.L.; Tan, C.; Li, Y. An intelligent green scheduling system for sustainable cold chain logistics. Expert Syst. Appl. 2022, 209, 118378. [Google Scholar] [CrossRef]
- Li, Y.; Lim, M.K.; Tseng, M.L. A green vehicle routing model based on modified particle swarm optimization for cold chain logistics. Ind. Manag. Data Syst. 2019, 119, 473–494. [Google Scholar] [CrossRef]
- Edwin, M.; Nair, M.S.; Sekhar, S.J. A comprehensive review on impacts of COVID-19 in food preservation and cold chain: An approach towards implementing green energy technologies. Environ. Prog. Sustain. Energy 2022, 41, e13820. [Google Scholar] [CrossRef] [PubMed]
- Sánchez-Fernández, R.; Iniesta-Bonillo, M.Á.; Holbrook, M.B. The conceptualisation and measurement of consumer value in services. Int. J. Mark. Res. 2009, 51, 1–17. [Google Scholar] [CrossRef]
- Liu, A.H.; Leach, M.P.; Bernhardt, K.L. Examining customer value perceptions of organizational buyers when sourcing from multiple vendors. J. Bus. Res. 2005, 58, 559–568. [Google Scholar] [CrossRef]
- Fuchs, C.; Prandelli, E.; Schreier, M. The psychological effects of empowerment strategies on consumers’ product demand. J. Mark. 2010, 74, 65–79. [Google Scholar] [CrossRef]
- Lee, S.Y.; Kim, Y.; Kim, Y. Engaging consumers with corporate social responsibility campaigns: The roles of interactivity, psychological empowerment, and identification. J. Bus. Res. 2021, 134, 507–517. [Google Scholar] [CrossRef]
- Zhu, W.; Mou, J.; Benyoucef, M. Exploring purchase intention in cross-border E-commerce: A three stage model. J. Retail. Consum. Serv. 2019, 51, 320–330. [Google Scholar] [CrossRef]
- Hazen, B.T.; Ellinger, A.E. Special issue editorial: Logistics customer service revisited. Int. J. Phys. Distrib. Logist. Manag. 2019, 49, 2–3. [Google Scholar] [CrossRef]
- Mehrabian, A.; Russell, J.A. An Approach to Environmental Psychology; The MIT Press: Cambridge, MA, USA, 1974. [Google Scholar]
- Guo, J.; Li, Y.; Xu, Y.; Zeng, K. How live streaming features impact consumers’ purchase intention in the context of cross-border E-commerce? A research based on SOR theory. Front. Psychol. 2021, 12, 767876. [Google Scholar] [CrossRef]
- Abbott, R.; Sin, R.; Pedersen, C.; Harris, T.; Beck, T.; Nilsson, S.; Li, Y. The role of dark pattern stimuli and personality in online impulse shopping: An application of S-O-R theory. J. Consum. Behav. 2023, 22, 1311–1329. [Google Scholar] [CrossRef]
- Lavuri, R.; Roubaud, D.; Grebinevych, O. Sustainable consumption behaviour: Mediating role of pro-environment self-identity, attitude, and moderation role of environmental protection emotion. J. Environ. Manag. 2023, 347, 119106. [Google Scholar] [CrossRef]
- Mansoor, M.; Awan, T.M.; Paracha, O.S. Sustainable buying behaviour: An interplay of consumers’ engagement in sustainable consumption and social norms. Int. Soc. Sci. J. 2022, 72, 1053–1070. [Google Scholar]
- Lim, S.H.; Kim, D.J. Does emotional intelligence of online shoppers affect their shopping behavior? From a cognitive-affective-conative framework perspective. Int. J. Hum.-Comput. Interact. 2020, 36, 1304–1313. [Google Scholar]
- Kim, Y.H.; Kim, D.J.; Wachter, K. A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention. Decis. Support Syst. 2013, 56, 361–370. [Google Scholar] [CrossRef]
- Lavidge, R.J.; Steiner, G.A. A model for predictive measurements of advertising effectiveness. J. Mark. Am. Mark. Assoc. 1961, 25, 59–62. [Google Scholar] [CrossRef]
- Kim, B.; Chen, Y. The effects of spirituality on visitor behavior: A cognitive-affective-conative model: The effects of spirituality on visitor behavior. Int. J. Tour. Res. 2021, 23, 1151–1162. [Google Scholar] [CrossRef]
- Cao, Y.; Qin, X.; Li, J.; Long, Q.; Hu, B. Exploring seniors’ continuance intention to use mobile social network sites in China: A cognitive-affective-conative model. Univers. Access Inf. Soc. 2022, 21, 71–92. [Google Scholar] [CrossRef]
- Quoquab, F.; Mohammad, J. Cognitive, affective and conative domains of sustainable consumption: Scale development and validation using confirmatory composite analysis. Sustainability 2020, 12, 7784. [Google Scholar] [CrossRef]
- Coley, L.S.; Mentzer, J.T.; Cooper, M.C. Is “consumer orientation” a dimension of market orientation in consumer markets? J. Mark. Theory Pract. 2010, 18, 141–154. [Google Scholar] [CrossRef]
- Lee, W.I.; Chen, C.W.; Chen, T.H.; Chen, C.Y. The relationship between consumer orientation, service value, medical care service quality and patient satisfaction: The case of a medical center in Southern Taiwan. Afr. J. Bus. Manag. 2010, 4, 448. [Google Scholar]
- Liu, Y.H.; Lee, E.S.; Ding, J.M. Logistics service quality in cross-border e-commerce and consumer repurchase intention: The moderating effects of consumer ethnocentrism and cosmopolitanism. Korean Manag. Consult. Rev. 2023, 23, 179–192. [Google Scholar]
- Gil Saura, I.; Servera Francés, D.; Berenguer Contrí, G.; Fuentes Blasco, M. Logistics service quality: A new way to loyalty. Ind. Manag. Data Syst. 2008, 108, 650–668. [Google Scholar] [CrossRef]
- Mahmoud, M.A.; Hinson, R.E.; Anim, P.A. Service innovation and customer satisfaction: The role of customer value creation. Eur. J. Innov. Manag. 2018, 21, 402–422. [Google Scholar] [CrossRef]
- Keszey, T. Environmental orientation, sustainable behaviour at the firm-market interface and performance. J. Clean. Prod. 2020, 243, 118524. [Google Scholar] [CrossRef]
- Zameer, H.; Wang, Y.; Vasbieva, D.G.; Abbas, Q. Exploring a pathway to carbon neutrality via reinforcing environmental performance through green process innovation, environmental orientation and green competitive advantage. J. Environ. Manag. 2021, 296, 113383. [Google Scholar] [CrossRef]
- Gabler, C.B.; Richey, R.G., Jr.; Rapp, A. Developing an eco-capability through environmental orientation and organizational innovativeness. Ind. Mark. Manag. 2015, 45, 151–161. [Google Scholar] [CrossRef]
- Watanabe, E.A.d.M.; Alfinito, S.; Curvelo, I.C.G.; Hamza, K.M. Perceived value, trust and purchase intention of organic food: A study with Brazilian consumers. Br. Food J. 2020, 122, 1070–1184. [Google Scholar] [CrossRef]
- Carlsen, J.; Boksberger, P. Enhancing consumer value in wine tourism. J. Hosp. Tour. Res. 2015, 39, 132–144. [Google Scholar] [CrossRef]
- Gallarza, M.G.; Gil Saura, I. Consumer value in tourism: A perspective article. Tour. Rev. 2020, 75, 41–44. [Google Scholar] [CrossRef]
- Danish, M.; Ali, S.; Ahmad, M.A.; Zahid, H. The influencing factors on choice behavior regarding green electronic products: Based on the green perceived value model. Economies 2019, 7, 99. [Google Scholar] [CrossRef]
- Chen, S.Y. Green helpfulness or fun? Influences of green perceived value on the green loyalty of users and non-users of public bikes. Transp. Policy 2016, 47, 149–159. [Google Scholar] [CrossRef]
- Wu, H.C.; Cheng, C.C.; Chen, Y.C.; Hong, W. Towards green experiential loyalty: Driving from experiential quality, green relationship quality, environmental friendliness, green support and green desire. Int. J. Contemp. Hosp. Manag. 2018, 30, 1374–1397. [Google Scholar] [CrossRef]
- Ullah, S. Customer satisfaction, perceived service quality and mediating role of perceived value. Int. J. Mark. Stud. 2012, 4, 68–76. [Google Scholar]
- Hapsari, R.; Clemes, M.; Dean, D. The mediating role of perceived value on the relationship between service quality and customer satisfaction: Evidence from Indonesian airline passengers. Procedia Econ. Financ. 2016, 35, 388–395. [Google Scholar] [CrossRef]
- Han, X.; Fang, S.; Xie, L.; Yang, J. Service fairness and customer satisfaction: Mediating role of customer psychological empowerment. J. Contemp. Mark. Sci. 2019, 2, 50–62. [Google Scholar] [CrossRef]
- Ngacha, W.J.; Onyango, F.E.V. The role of a customer-oriented service culture in influencing customer retention in the hotel industry. Afr. J. Hosp. Tour. Leis. 2017, 6, 1–19. [Google Scholar]
- Wu, Y.; Huang, H. Influence of Perceived Value on Consumers’ Continuous Purchase Intention in Live-Streaming E-Commerce: Mediated by Consumer Trust. Sustainability 2023, 15, 4432. [Google Scholar] [CrossRef]
- Podsakoff, P.M.; MacKenzie, S.B.; Lee, J.Y.; Podsakoff, N.P. Common method biases in behavioral research: A critical review of the literature and recommended remedies. J. Appl. Psychol. 2003, 88, 879–903. [Google Scholar] [CrossRef] [PubMed]
- Diamantopoulos, A.; Siguaw, J.A. Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. Br. J. Manag. 2006, 17, 263–282. [Google Scholar] [CrossRef]
- Hair, J.F.; Risher, J.J.; Sarstedt, M.; Ringle, C.M. When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 2019, 31, 2–24. [Google Scholar] [CrossRef]
- Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
- Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar]
- Falk, R.F.; Miller, N.B. A Primer for Soft Modeling; University of Akron Press: Akron, OH, USA, 1992. [Google Scholar]
- Preacher, K.J.; Hayes, A.F. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav. Res. Methods 2008, 40, 879–891. [Google Scholar] [CrossRef]
Category | Items | Frequency | Percentage (%) |
---|---|---|---|
Gender | Male | 102 | 38.78% |
Female | 161 | 61.22% | |
Age | Less than 20 | 41 | 15.59% |
20–40 | 165 | 62.74% | |
41–60 | 47 | 17.87% | |
More than 60 | 10 | 3.80% | |
Educational Background | High school and below | 32 | 12.17% |
Bachelor’s degree (including college) | 186 | 70.72% | |
Master’s degree and above | 45 | 17.11% | |
Careers | Student | 78 | 29.66% |
Self-employed individual | 35 | 13.31% | |
Employee | 129 | 49.05% | |
Others | 21 | 7.98% | |
Regions | Eastern China | 94 | 35.74% |
Southern China | 47 | 17.87% | |
Western China | 29 | 11.03% | |
Northern C Prof. Dr. Rogelio Puente-Diazhina | 48 | 18.25% | |
Central China | 45 | 17.11% | |
Incomes (CNY) | Less than 3000 | 21 | 7.98% |
3000–6000 | 57 | 21.67% | |
6001–9000 | 99 | 37.64% | |
9001–12,000 | 54 | 20.53% | |
More than 12,000 | 32 | 12.17% |
Variables and Measurement | Loading |
---|---|
Customer-oriented service (α = 0.858, C.R. = 0.860, AVE = 0.701). | |
COS1. Logistics service providers should understand the needs of consumers. | 0.839 |
COS2. Logistics service providers should respond quickly to consumer needs. | 0.830 |
COS3. Logistics service providers should endeavor to maximize benefits for consumers. | 0.839 |
COS4. Logistics service providers should design and launch products and services with the consumer in mind. | 0.841 |
Environment-oriented service (α = 0.808, C.R. = 0.828, AVE = 0.721). | |
EOS1. Firms have a responsibility to protect the environment. | 0.870 |
EOS2. Firms and their employees understand the importance of protecting the environment. | 0.868 |
EOS3. Firms should have a clear policy for developing and implementing environmental management strategies. | 0.807 |
Perceived value (α = 0.835, C.R. = 0.840, AVE = 0.751). | |
PV1. Product delivery was accurate and satisfactory. | 0.880 |
PV2. The delivery person was friendly and the service was satisfactory. | 0.848 |
PV3. The services provided reflect the service provider’s concern and commitment to environmental protection. | 0.871 |
Psychological empowerment (α = 0.831, C.R. = 0.832, AVE = 0.747). | |
PE1. I am free to choose my shopping platform and service provider. | 0.880 |
PE2. I am free to choose whether or not to use reusable packaging. | 0.848 |
PE3. I am free to choose whether or not to participate in the recycling of transport packaging. | 0.866 |
Continuous use intention (α = 0.856, C.R. = 0.858, AVE = 0.776). | |
CUI1. I will prioritize this platform and logistics provider for future purchases. | 0.882 |
CUI2. If all other attributes (price, product, quality, etc.) are similar, I will continue to purchase products from that platform. | 0.873 |
CUI3. I would recommend the platform to my family and friends in the future. | 0.888 |
Green engagement intention (α = 0.848, C.R. = 0.851, AVE = 0.767). | |
GEI1. I like to simplify packaging when ordering and delivering products. | 0.872 |
GEI2. I would like to use reusable bags or boxes. | 0.879 |
GEI3. I am willing to cooperate with other environmental protection strategies of the company and contribute to environmental protection. | 0.876 |
Construct | COS | CUI | EOS | GEI | PE | PV | |
---|---|---|---|---|---|---|---|
AVE | COS | 0.837 | |||||
CUI | 0.448 | 0.881 | |||||
EOS | 0.244 | 0.273 | 0.849 | ||||
GEI | 0.374 | 0.375 | 0.146 | 0.876 | |||
PE | 0.342 | 0.366 | 0.207 | 0.354 | 0.865 | ||
PV | 0.463 | 0.434 | 0.173 | 0.330 | 0.526 | 0.867 | |
HTMT | COS | ||||||
CUI | 0.522 | ||||||
EOS | 0.293 | 0.329 | |||||
GEI | 0.440 | 0.439 | 0.170 | ||||
PE | 0.405 | 0.433 | 0.247 | 0.418 | |||
PV | 0.543 | 0.508 | 0.206 | 0.390 | 0.630 |
Hypothesis | Path | Path Coefficient | p Value | Results |
---|---|---|---|---|
H1 | COS -> PV | 0.448 | <0.001 | Supported |
H2 | COS -> PE | 0.31 | <0.001 | Supported |
H3 | EOS -> PV | 0.064 | 0.12 | Not Supported |
H4 | EOS -> PE | 0.132 | 0.014 | Supported |
H5 | PV -> CUI | 0.333 | <0.001 | Supported |
H6 | PV -> GEI | 0.199 | 0.001 | Supported |
H7 | PE -> CUI | 0.191 | 0.001 | Supported |
H8 | PE -> GEI | 0.249 | <0.001 | Supported |
Effect | Path | Estimate | SE | LL | UL |
---|---|---|---|---|---|
Total indirect effect | COS -> CUI | 0.208 | 0.038 *** | 0.15 | 0.274 |
COS -> GEI | 0.166 | 0.037 *** | 0.109 | 0.232 | |
EOS -> CUI | 0.047 | 0.026 * | 0.008 | 0.093 | |
EOS -> GEI | 0.046 | 0.022 * | 0.012 | 0.085 | |
Specific indirect effect | COS -> PV -> CUI | 0.149 | 0.037 *** | 0.092 | 0.212 |
COS -> PV -> GEI | 0.089 | 0.033 ** | 0.039 | 0.147 | |
EOS -> PV -> CUI | 0.021 | 0.019 | −0.006 | 0.057 | |
EOS -> PV -> GEI | 0.013 | 0.012 | −0.004 | 0.036 | |
COS -> PE -> CUI | 0.059 | 0.025 ** | 0.024 | 0.104 | |
COS -> PE -> GEI | 0.077 | 0.029 ** | 0.034 | 0.13 | |
EOS -> PE -> CUI | 0.025 | 0.015 * | 0.005 | 0.054 | |
EOS -> PE -> GEI | 0.033 | 0.018 * | 0.008 | 0.067 |
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Ding, J.; Lee, E.-S. Promoting Consumers’ Sustainable Consumption of Online Retail Cold Chain Logistics Services: Extended Applications of SOR and Cognitive-Affective-Conative Theories. Behav. Sci. 2024, 14, 771. https://doi.org/10.3390/bs14090771
Ding J, Lee E-S. Promoting Consumers’ Sustainable Consumption of Online Retail Cold Chain Logistics Services: Extended Applications of SOR and Cognitive-Affective-Conative Theories. Behavioral Sciences. 2024; 14(9):771. https://doi.org/10.3390/bs14090771
Chicago/Turabian StyleDing, Jiangmin, and Eon-Seong Lee. 2024. "Promoting Consumers’ Sustainable Consumption of Online Retail Cold Chain Logistics Services: Extended Applications of SOR and Cognitive-Affective-Conative Theories" Behavioral Sciences 14, no. 9: 771. https://doi.org/10.3390/bs14090771
APA StyleDing, J., & Lee, E. -S. (2024). Promoting Consumers’ Sustainable Consumption of Online Retail Cold Chain Logistics Services: Extended Applications of SOR and Cognitive-Affective-Conative Theories. Behavioral Sciences, 14(9), 771. https://doi.org/10.3390/bs14090771