Authors : Yang Hengran

Volume/Issue : Volume 10 - 2025, Issue 1 - January

Google Scholar : https://tinyurl.com/yvbfhyub

Scribd : https://tinyurl.com/yckcxw7a

DOI : https://doi.org/10.5281/zenodo.14651270

Abstract : Cross-platform support is considered an important aspect of the development of multi-platform video games. This research aims to determine the effect of the consistency of multi-platform game experiences on users' perceived experiences in terms of player satisfaction. Using conjoint analysis, we collect gamers' multi-criteria evaluation ratings to proceed with this research. Our results show that game experience consistency has a greater impact on players' purchasing intentions compared to the price of a game. We propose that the dramatic impact of consistency on player satisfaction demonstrates the importance of game experience quality more generally. Our research contributes to the literature about video games and psychology and offers insights that can aid game developers in making better decisions concerning multi- platform video game development and enable developers to provide better game experiences to their target gamers.

Keywords : Cross-Platform Gaming, Gaming Industry Insights, Game Experience Consistency, Platform Compatibility, Expectancy-Disconfirmation Model.

References :

1. Cha, E., Wood, J., & Finkelstein, J. (2012, January). Using gaming platforms for telemedicine applications: A cross-platform comparison. In Proceedings of 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics (pp. 918-921). IEEE. https://doi.org/10.1109/BHI.2012.6211737
2. Fahy, R., & Krewer, L. (2012, September). Using open source libraries in cross platform games development. In 2012 IEEE International Games Innovation Conference (pp. 1-5). IEEE. https://doi.org/10.1109/IGIC.2012.6329835
3. Landoni, P., Dell’era, C., Frattini, F., Petruzzelli, A. M., Verganti, R., & Manelli, L. (2020). Business model innovation in cultural and creative industries: Insights from three leading mobile gaming firms. Technovation, 92, 102084. https://doi.org/10.1016/j.technovation.2019.102084
4. Vong, F., & Wong, I. A. (2013). Corporate and social performance links in the gaming industry. Journal of Business Research, 66(9), 1674-1681. https://doi.org/10.1016/j.jbusres.2012.12.014
5. Savery, C., Graham, N., Gutwin, C., & Brown, M. (2014, February). The effects of consistency maintenance methods on player experience and performance in networked games. In Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing (pp. 1344-1355). https://doi.org/10.1145/2531602.2531616
6. Phan, M. H., Keebler, J. R., & Chaparro, B. S. (2016). The development and validation of the game user experience satisfaction scale (GUESS). Human factors, 58(8), 1217-1247. https://doi.org/10.1177/0018720816669646
7. Johnson, D., Gardner, M. J., & Perry, R. (2018). Validation of two game experience scales: the player experience of need satisfaction (PENS) and game experience questionnaire (GEQ). International Journal of Human-Computer Studies, 118, 38-46. https://doi.org/10.1016/j.ijhcs.2018.05.003
8. Johnson, D., Nacke, L. E., & Wyeth, P. (2015, April). All about that base: differing player experiences in video game genres and the unique case of moba games. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 2265-2274). https://doi.org/10.1145/2702123.2702447
9. Liu, H., Amit, R., Qiao, H., & Wang, S. (2024). Digital platform compatibility strategies in platform co-opetition. Journal of Business Research, 174, 114489. https://doi.org/10.1016/j.jbusres.2023.114489
10. Liang, Y., Liu, W., Li, K. W., Dong, C., & Lim, M. K. (2023). A co‐opetitive game analysis of platform compatibility strategies under add‐on services. Production and Operations Management, 32(11), 3541-3558. https://doi.org/10.1111/poms.14049
11. Van Ryzin, G. G. (2006). Testing the expectancy disconfirmation model of citizen satisfaction with local government. Journal of Public Administration Research and Theory, 16(4), 599-611. https://doi.org/10.1093/jopart/mui058
12. Grimmelikhuijsen, S., & Porumbescu, G. A. (2017). Reconsidering the expectancy disconfirmation model. Three experimental replications. Public Management Review, 19(9), 1272-1292. https://doi.org/10.1080/14719037.2017.1282000
13. Van Ryzin, G. G. (2013). An experimental test of the expectancy‐disconfirmation theory of citizen satisfaction. Journal of Policy Analysis and Management, 32(3), 597-614. https://doi.org/10.1002/pam.21702
14. Yüksel, A., & Yüksel, F. (2001). The expectancy-disconfirmation paradigm: a critique. Journal of hospitality & tourism research, 25(2), 107-131. https://doi.org/10.1177/109634800102500201
15. Sarkar, A. ., Islam, S. A. M., & Bari, M. S. . (2024). Transforming User Stories into Java Scripts: Advancing Qa Automation in The Us Market With Natural Language Processing. Journal of Artificial Intelligence General Science (JAIGS) ISSN:3006-4023, 7(01), 9–37. https://doi.org/10.60087/jaigs.v7i01.293.