Value-informed pricing strategy, which focuses on determining the price level of products based on consumer value perception, is especially suitable to be applied in digital products rather than industrial ones. By carrying out 65 in-depth interviews with people involved in the Chinese Massively Multiplayer Online Role-Playing Game (MMORPG) industry, this article explores the process through which a value-informed pricing strategy is applied to determine the price level of virtual in-game accessories—exploring pricing preference through interacting with game players, swaying pricing alternatives through managing the competitive environment, and manipulating value perception through shaping the virtual marketplace. Furthermore, this article constructs a theoretical framework of value-informed pricing, including the above process, and deciphers the linkage mechanism between different segments. The findings not only enrich the theory of value-informed pricing under the application context of virtual digital products but also have implications for the practitioners in the MMORPG industry.
Understanding consumers' sentiment expressions in online reviews: a hybrid approachThis study explores consumers' sentiment and its influencing factors in the context of theme parks by analyzing online reviews. A hybrid approach is employed, including sentiment analysis, logistic regression analysis and cooccurrence network analysis. The findings provide new insights on the sentiment expression of consumers in different regions, that is, Australian consumers express significantly more positive sentiment than U.S. consumers.In addition, the results reveal the crucial experiential factors causing positive and negative sentiment. This study not only contributes to the understanding of consumers' review behavior and eWoM but provides a reference for the application of data driven approach in intelligent marketing and management.
We use pathfinder network scaling (PENETS) approach to measure and evaluate theme park visitors' online reviews. PFNETS as an effective tool of big data analytics can be used to identify unobserved meaningful interrelationships between concepts.Although there are many research analyzing online reviews, this study is the first attempt to use an analytical approach of PFNETS to explore online reviews in theme park visitor experiences. The article collects 14,142 effective reviews of the world's first Disneyland in California from TripAdvisor. Using parallel and similarity comparison in pathfinder scaling, four individually but fully connected networks were generated to reveal different visitors' experiences in different segments. The findings indicate the dissimilarity of concept relatedness between different segments and revealed the knowledge gap of marketing to different segments in theme parks. JEL classification codes: M10, M20, M30.
Statistical Process Control (SPC) is a scientific approach to quality improvement in which data are collected and used as evidence of the performance of a process, organisation or set of equipment. One of the SPC techniques, the cumulative sum (CUSUM) method, first developed by E.S. Page (1961), uses a series of cumulative sums of sample data for online process control. This paper reviews CUSUM techniques applied to financial markets in several different ways. The performance of the CUSUM method in predicting regime shifts in stock market indices is then studied in detail. Research in this field so far does not take the transaction fees of buying and selling into consideration. As the study in this paper shows, the performances of the CUSUM when taking account of transaction fees are quite different to those not taking transaction fees into account. The CUSUM plan is defined by parameters h and k. Choosing the parameters of the method should be based on studies that take transaction fees into account. The performances of the CUSUM in different stock markets are also compared in this paper. The results show that the same CUSUM plan has remarkably different performances in different stock markets.SPC, CUSUM, regime shifts, financial markets, transaction fees,
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