The determinants of mobile game success in South Korea

Nam, Kyungjin; Kim, Hye-jin

doi:10.1016/j.telpol.2019.101855

Cited by 13 publications

(36 citation statements)

References 24 publications

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“…First type of Table 3 shows that movies or scripts are used for similarity calculation. Commercial and artistic star power Genre, age limit, country of origin, sequel, online ratings, box office performance, holdback Lee and Choeh (2018) Volume of reviews, valence of reviews, depth of reviews, review helpfulness Bae and Kim (2019) Movie titles Masih and Ihsan (2019) Genre, leading actor, director, Zee cine awards, IIFA awards, budget Steininger and Gatzemeier (2019) Overall affective response, the need to re-experience Nam and Kim (2020) Genre, awareness of IP, name value of publishers, monetization option, preregistration, seasonal release, TV advertisements and media coverage, official online forums, online videos, platform ratings, platform's market power Second type of Table 3 shows that user data is used for similarity calculation. Barbosu (2016) identified similarity between movies based on users' rental data.…”

Section: Methods To Measure Similaritymentioning

confidence: 99%

“…Steininger and Gatzemeier (2019) studied impacts of the overall affective response, the need to re-experience on success of new music. Nam and Kim (2020) obtained determinants of TSV by analyzing relationships between genre, awareness of IP, name value of publishers and so on and mobile game downloads. However, to the best of our knowledge, no study has examined methods to mine attribute relationship patterns of different groups with different TSV intervals.…”

Section: Literature Reviewmentioning

confidence: 99%

“…This attribute relationship pattern, consisting of product attributes associated and association relationships among attributes, may reflect the characteristics of consumer demand. Extant studies have focused on impacts of such attributes on the TSV of EPSLC (Karniouchina, 2011; Nelson and Glotfelty, 2012; Hofmann et al , 2017; Kim and Kim, 2017; Lee and Choeh, 2018; Bae and Kim, 2019; Masih and Ihsan, 2019; Steininger and Gatzemeier, 2019; Nam and Kim, 2020). However, no study has attempted to mine attribute relationship patterns of products with different TSV intervals.…”

Section: Introductionmentioning

confidence: 99%

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Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

Tang

Wang

Cui³

et al. 2021

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PurposeBecause of short life cycle and fluctuating greatly in total sales volumes (TSV), it is difficult to accumulate enough sales data and mine an attribute set reflecting the common needs of all consumers for a kind of experiential product with short life cycle (EPSLC). Methods for predicting TSV of long-life-cycle products may not be suitable for EPSLC. Furthermore, point prediction cannot obtain satisfactory prediction results because information available before production is inadequate. Thus, this paper aims at proposing and verifying a novel interval prediction method (IPM).Design/methodology/approachBecause interval prediction may satisfy requirements of preproduction investment decision-making, interval prediction was adopted, and then the prediction difficult was converted into a classification problem. The classification was designed by comparing similarities in attribute relationship patterns between a new EPSLC and existing product groups. The product introduction may be written or obtained before production and thus was designed as primary source information. IPM was verified by using data of crime movies released in China from 2013 to 2017.FindingsThe IPM is valid, which uses product introduction as input, classifies existing products into three groups with different TSV intervals, mines attribute relationship patterns using content and association analyses and compares similarities in attribute relationship patterns – to predict TSV interval of a new EPSLC before production.Originality/valueDifferent from other studies, the IPM uses product introduction to mine attribute relationship patterns and compares similarities in attribute relationship patterns to predict the interval values. It has a strong applicability in data content and structure and may realize rolling prediction.

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Section: Methods To Measure Similaritymentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

Tang

Wang

Cui³

et al. 2021

View full text Add to dashboard Cite

show abstract

“…According to Microsoft's Massive, mobile advertising through gaming apps has been found to increase brand recommendation by 23%, purchase intention by 24%, and overall brand rating by 32% (Khan, 2017). Nam and Kim (2020) indicate that the number of user ratings have strong impacts on both mobile game revenue and the number of downloads in South Korean gaming companies. Several companies consider in-game advertising as their pure business model (Landoni et al, 2019).…”

Section: Managerial Implicationsmentioning

confidence: 99%

Ads in gaming apps: experiential value of gamers

Naser

Bressolles

Khan

et al. 2021

IMDS

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PurposeEven though there is a noticeable market value in the mobile gaming apps industry, there has been limited research examining experiential value of gamers with respect to in-game ads in gaming apps. This study fills the void in the literature by examining factors associated with “experiential value of gamers through ads in gaming apps” as well as investigating its antecedents (cognitive and affective involvement) and consequences (positive word of mouth and intention to continue playing the mobile game).Design/methodology/approachA total of 600 valid responses from gamers was used to test the model fit, measurement and structural models, conditional probabilistic queries, and nonlinearity.FindingsThis study found that experiential value of gamers through ads in gaming apps is a second-order factor of four constructs: escapism, enjoyment, social affiliation and entertainment. Most of the structural paths between cognitive/affective involvement and dimensions of experiential value are supported. Surprisingly, only social affiliation and entertainment values predict positive word of mouth and intention to continue playing the mobile game, in a nonlinear way.Originality/valueThis study is the first to introduce “experiential value of gamers through ads in gaming apps”. The findings have important implications for companies to develop brand and communication strategies by leveraging specific advertisement formats and present their ads to the right audience in the right gaming apps and at the right time.

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“…Mobile games have become the most popular game category in the gaming industry within recent years. Nam and Kim (2020) mentioned that the top ten mobile games account for 70% of the market share. This demonstrates that the mobile game market is seriously polarized, and the success rate is low.…”

Section: Introductionmentioning

confidence: 99%

Explaining mobile game takeoff through information configuration

Tang

2021

IMDS

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PurposeThe purpose of this paper is to explore how the number and quality of games that publishers have released, popularity of game genre, age rating and package size are configured to determine the mobile game takeoff in a short time.Design/methodology/approachBased on the signaling theory, the authors present a conceptual model. Using actual data about 170 mobile games at their initial stage in the Apple App store, the authors test the conceptual model by applying fuzzy qualitative comparative analysis (fsQCA).FindingsThe findings identify four solutions that explain Mobile game takeoff in a short time. The authors highlight the role of the number and quality of games released by publishers, as well as that of popular game genres, which are always core factors when present.Originality/valueThis paper complements the previous research on the diffusion of mobile games by exploring which information combinations can lead to mobile games takeoff in a short time from the perspective of configuration. FsQCA serves as a better tool for explaining the complex relationships among variables than a regression analysis approach does. The authors extend existing knowledge on how the number and quality of games that publishers have released, popularity of game genre, age rating and package size combine to lead to takeoff of mobile games in a short time.

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The determinants of mobile game success in South Korea

Cited by 13 publications

References 24 publications

Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

Predicting total sales volume interval of an experiential product with short life cycle before production: similarity comparison in attribute relationship patterns

Ads in gaming apps: experiential value of gamers

Explaining mobile game takeoff through information configuration

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