single-au.php

IJAT Vol.12 No.3 pp. 308-318
doi: 10.20965/ijat.2018.p0308
(2018)

Paper:

Research on Willingness to Pay of Internet of Vehicles

Zheqi Zhu and Nariaki Nishino

Department of Technology of Management for Innovation, The University of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Corresponding author

Received:
September 29, 2017
Accepted:
April 3, 2018
Online released:
May 1, 2018
Published:
May 5, 2018
Keywords:
IoV, conjoint analysis, willingness to pay, contingent value method
Abstract

This study uses two separate surveys to reveal the mean willingness to pay (WTP) for different attributes of Internet of Vehicles (IoV). It uses conjoint analysis for the first survey with 437 respondents to find the most important attribute among seven attributes of IoV. It uses the contingent value method (CVM) for second survey to reveal the mean WTP of the main attributes from the first survey. The estimated method used is the binomial logit model. The result shows significant concern among people in China about security and willingness to pay an additional CNY 1000 for an IoV product with advanced security features, when other attributes are constant. These results can guide manufacturers in managing technology investments and cost saving targets.

References
  1. [1] The Current Vehicle Situation in China 2016. Retrieved from Chinese Industry Information: http://www.chyxx.com/industry/201604/407660.html [accessed April 19, 2016]
  2. [2] How to build Internet of Vehicle, 2009. Retrieved from Chinese transformation: http://www.iicc.ac.cn/Article/hydt/ywdt/znjt/200911/55591.html [accessed November 5, 2009]
  3. [3] PricewaterhouseCoopers, The Future of Internet of Vehicle, 2015. Retrieved from cheyun: http://www.cheyun.com/content/3988 [accessed June 23, 2015]
  4. [4] L. A. Maglaras et al., “Social Internet of Vehicles for Smart Cities,” J. of Sensor and Actuator Networks, Vol.5, No.1, pp. 3-20, 2016.
  5. [5] V. Sandonis et al., “Vehicle to Internet communication using the ETSI ITS Geonetworking protocol,” Transactions on Emerging Telecommunications Technologies, Vol.27, No.3, pp. 373-391, 2016.
  6. [6] S. Yang et al., “Anomaly Detection for Internet of Vehicles: A Trust Management Scheme with Affinity Propagation,” Mobile Information Systems, Vol.2016, pp. 1-10, 2016.
  7. [7] J. A. Guerrero-ibanez et al., “Integration Challenges of Intelligent Trans. Systems with Connected Vehicles, Cloud Computing, and Internet of Things Technologies,” IEEE Wireless Communications, pp. 122-125, 2015.
  8. [8] J. Prinsloo et al., “Accurate Vehocle Location System Using RFID, an Internet of Things Approach,” Sensors, Vol.16, pp. 825-849, 2016.
  9. [9] L. Wei et al., “A Secure-Efficient Data Collection Algorithm Based on Self-Adaptive Sensing Model in Mobile Internet of Vehicles,” China Communication, pp. 121-129, Feb. 2016.
  10. [10] D. Lin et al., “Optimal Network QoS over the Internet of Vehicles for E-health Application,” Mobile Information System, Vol.2016, pp. 1-11, 2016.
  11. [11] J. Wan et al., “Mobile Crowd Sensing for Traffic Prediction in Internet of Vehicles,” Sensors, Vol.16, pp. 88-103, 2016.
  12. [12] E.-K. Lee et al., “Secured Data Sharing based on Information Centric Trust in the Internet of Vehicles,” Int. J. of Security and Its Applications, Vol.9, No.11, pp. 23-34, 2015.
  13. [13] C.-H. Wang et al., “Performance Evaluation of IEEE 802.15.4 Nonbeacon-Enabled Mode for Internet of Vehicles,” IEEE Trans. on Intelligent Transportation Systems, Vol.16, No.6, pp. 3150-3159, 2015.
  14. [14] J. Fransen et al., “What should be the cut point for classification criteria for studies in gout? A conjoint analysis,” Arthritis Care&Research, pp. 1-15, 2016.
  15. [15] W. J. Taylor, “Pros and cons of conjoint analysis of discrete choice experiments to define classification and response criteria in rheumatology,” Current Opinion in Rheumatology, Vol.28, No.2, pp. 117-121, Mar. 2016.
  16. [16] J. V. Cauwenberg et al., “Street characteristics preferred for transportation walking among older adults: a choice-based conjoint analysis with manipulated photographs,” Int. J. of Behavioral Nutrition and Physical Activity, Vol.13, No.6, pp. 1-17, 2016.
  17. [17] C. Breidert, “Estimation of Willingness-to-Pay: Theory, Measurement, Application,” Deutscher Universitats-Verlag, 2006.
  18. [18] J. M. Gibson et al., “Discrete Choice Experiments in Developing Countries: Willingness to Pay Versus Willingness to Work,” Environ Resource Econ, pp. 697-721, 2016.
  19. [19] C. Torres et al., “Waiting or acting now? The effect on willingness-to-pay of delivering inherent uncertainty information in choice experiments,” Ecological Economics, pp. 231-240, 2017.
  20. [20] G. V. Lombardi et al., “Environmental friendly food. Choice experiment to assess consumer’s attitude toward “climate neutral” milk: the role of communication,” J. of Cleaner Production, pp. 257-262, 2017.
  21. [21] K. E. Lewis et al., “U.S. consumers’ preferences for imported and genetically modified sugar: Examining policy consequentiality in a choice experiment,” J. of Behavioral and Experimental Economics, pp. 1-8, 2016.
  22. [22] Y. Matthews et al., “Using virtual environments to improve the realism of choice experiments: A case study about coastal erosion management,” J. of Environmental Economics and Management, pp. 193-208, 2017.
  23. [23] C.-Y. Lee et al., “Estimating willingness to pay for renewable energy in South Korea using the contingent valuation method,” Energy Policy, pp. 150-156, 2016.
  24. [24] I. R. Vieira et al., “A contingent valuation study of buriti (Mauritia flexuosa L.f.) in the main region of production in Brazil: is environmental conservation a collective responsibility?,” Acta Botanica Brasilica, pp. 532-539, 2016.
  25. [25] J. Jianjun et al., “Measuring the willingness to pay for drinking water quality improvements: results of a contingent valuation survey in Songzi, China,” J. of Water and Health, pp. 504-512, 2016.
  26. [26] K. Page et al., “What is a hospital bed day worth? A contingent valuation study of hospital Chief Executive Officers,” BMC Health Services Research, pp. 17-25, 2017.
  27. [27] A. Báez-Montenegro et al., “Contingent valuation and motivation analysis of tourist routes: Application to the cultural heritage of Valdivia (Chile),” Tourism Economics, pp. 558-571, 2016.
  28. [28] M. Verbic, “Contingent valuation of urban public space: A case study of Ljubljanica riverbanks,” Land Use Policy, pp. 58-67, 2016.
  29. [29] Mar. wenjuanxing, 2016. Retrieved from wenjuanxing: http://www.sojump.com/ [accessed September 10, 2016]
  30. [30] Zhuzheqi, the survey on price distribution of Internet of Vehicle, Dec. 2016. Retrieved from wenjuanxing: https://sojump.com/jq/11721770.aspx [accessed December 24, 2016]
  31. [31] W. M. Hanemann, “Welfare evaluations in contingent valuation experiments with discrete responses,” American J. of Agricultural Economics, Vol.66, pp. 332-341, 1984.
  32. [32] G. Kerr, “Dichotomous choice contingent valuation probability distributions,” Aust. J. Agric. Resour. Econ, pp. 233-252, 2000.
  33. [33] R. C. Bishop, “Measuring Values of Extra-Market Goods: Are Indirect Measures Biased?,” Amer. J. Agr. Econ, pp. 926-930, 1979.
  34. [34] N. Zhuzheqi, “Research on the attributes of internet of vehicle with conjoint analysis,” 5th Int. Conf. on Serviceology, July 2017 (pending).
Cite this article as:
Zheqi Zhu and Nariaki Nishino, “Research on Willingness to Pay of Internet of Vehicles,” Int. J. Automation Technol., Vol.12, No.3, pp. 308-318, 2018
Zheqi Zhu and Nariaki Nishino, Int. J. Automation Technol., Vol.12, No.3, pp. 308-318, 2018

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, IE9,10,11, Opera.

Last updated on May. 19, 2018