Types Of Players Research Articles

Mechanisms of identification and social differentiation in player–avatar relations

The connection between player and avatar is central to digital gaming, with identification assumed to be core to this connection. Often, scholarship engages single dimensions of identification, yet emerging perspectives reveal that identification is polythetic (PID) – comprising at least six sufficient (but not necessary) mechanisms. The current study investigates the intersections of polythetic identification mechanisms and two different approaches to player–avatar sociality (as a marker of differentiation): general types of player–avatar relationships (PARs) and discrete dimensions of player–avatar interaction (PAX). Secondary analysis of an existing dataset of gamers revealed two main findings: (1) players reported overall diminished identification when they engaged in non-social relations with their avatar, and (2) increased liking and perspective-taking were most likely with human-like social relations, which require differentiation from rather than identification as the avatar. These findings are interpreted to suggest that player–avatar identification and differentiation are conceptually independent relational phenomena that are experientially convergent – some relational orientations and dynamics are associated with distinct combinations of identification mechanisms.

A Conceptual Framework for Integrating Gamification in eLearning Systems Based on Instructional Design Model

The current paper aims to introduce a proposed framework for gamification in the e-learning system at Saudi Arabia universities, by reviewing and analyzing the concept of gamification and its components, and types of players, as well as conditions for designing successful gamification, and the technical capabilities of Saudi Arabia universities, and also by reviewing and analyzing many designing models for gamification and e-learning systems that were introduced by the other researchers. Then incorporate all of these previous considerations into the general stages of instructional design, which is represented in analysis, design, development, implementation, and evaluation. The paper also deals with a review of the difference between gamification, games, and game-based learning, in addition to the benefits for students from employing gamification in the e-learning system.

Physical Demands and Internal Response in Football Sessions According to Tactical Periodization.

The objectives of the present study were (1)to analyze the internal and external load profile of training and competition carried out by semiprofessional football players during a 27-week period and (2)to examine the possible link between this type of periodization and players' fitness status and their readiness to compete. Training and match data were obtained from 26 semiprofessional football players belonging to the reserve squad of a Spanish La Liga club during the 2018/19 season. For the purpose of this study, the distribution of external and internal load during a typical training microcycle, with 6 or 7 days between matches, was analyzed. Five types of sessions were considered: strength, duration, velocity, preofficial match, and official match. The results showed a different internal and external load profile for each type of session, with the load being consistently higher during matches when compared with training sessions (28.9%-94% higher), showing significant differences in all the variables. There was a clear tapering strategy in the last days of the week to arrive with enough freshness to compete, shown by the decrease of the values in the 2 days before the match (15%-83% reduction, depending on the variable). Furthermore, the horizontal alternation of the load allowed the players to maintain their fitness level during the 27-week period. Our findings suggest that this weekly periodization approach could help achieve a double conditional target, allowing a short tapering strategy to face the match with enough freshness and serving as a strategy for maintaining or optimizing players' physical performance during the season.

Beyond ‘is it true?’: the ‘playframe’ in historical fiction

ABSTRACT Historical fiction is frequently judged solely on its historical accuracy, often leading authors of the genre to internalise this expectation and pre-emptively defend themselves with ‘author’s notes’. This narrow emphasis on accuracy leaves unexamined the importance of the fictional element the author has chosen to include. In this paper, I propose approaching historical fiction as a playful exploration set within the frame of the historical record, thus creating a ‘playframe’ which acknowledges the importance of both elements. This paper showcases three author player types: the Ventriloquist, the Mosaic-Maker and the Magician.

Design and development of a novel type of table tennis aerial robot player with tilting propellers

Table tennis has long fascinated roboticists as a particularly difficult task which requires fast movements, accurate control and adaptation to task parameters. In addition, the development of such devices is useful for educating the undergraduate students. Up to now, several groups have developed robotic manipulators playing table tennis and other commercial interactive robots. Moreover, drones are booming right now, and they can cover a larger workspace than manipulators, for a lower device volume and at a lower price. In this context, this paper aims to propose a drone playing table tennis to analyze the benefits and the disadvantages for this task. Most vertical takeoff and landing (VTOL) vehicles are not fast enough to reproduce hitting motions. The proposed prototype is an innovative quadrotor combining a tilting propeller and a state-dependent iterative linear quadratic control (iLQR). The performance of the proposed solution is evaluated with real experiments that show the success of the approach, reaching hitting rates of 40%.

Signaling in the ‘Before’ Model of Final Offer Arbitration

We develop a signaling model of final offer arbitration (FOA) in which the informed party makes the final settlement demand to the uninformed party. In FOA, each party submits a proposal to an arbitrator and if no agreement is reached, the arbitrator must select one of the two submitted proposals. We analyze a “before” model of FOA in which all settlement activity occurs prior to the exchange of proposals. We characterize the pure strategy separating, equilibrium associated with this game. Relative to a model of conventional arbitration (CA), the pure strategy separating equilibrium is associated with a higher dispute rate because weak player types have an enhanced incentive to bluff in this setting. This result continues to hold in semi-pooling equilibria. Thus our model is consistent with a higher dispute rate in FOA compared to CA. Results on the incentive to engage in costly voluntary disclosure are mixed across the two models. In contrast with CA, costly discovery can occur in this model of FOA. The analysis of out of equilibrium beliefs and actions is considerably more complex than in the standard litigation model.

A model of signed network formation with heterogeneous players

This paper proposes a model of formation of signed networks that comprise both positive (friendly/cooperative) and negative (antagonistic) social ties between players who differ intrinsically in strength. Friendships/alliances serve to increase one’s power over their intrinsic strength; in the determination of power it matters not how many allies one has, but who these allies are. The model proposed here is suited to any context where players derive power from friendships/alliances with stronger players and payoffs are extracted from less powerful enemies. The structure of ties across various types of players is studied in Nash equilibria along with a characterization of Nash equilibria under various parametric conditions.

A Typology of Esport Players

In recent years, esports have grown from a small number of local gaming activities undertaken by a few recreational participants to a multi-billion dollar industry with professional leagues, franchises, teams and players. While the industry has grown, our collective understanding of some of the most fundamental questions such as who plays esports and why, have received scant attention from academics. In an effort to further understand, profile and categorize players, the purpose of this research is to create a typology of esports players and to cross-validate previous research findings. Using hierarchical and k-clustering techniques, six psychographic factors (socialization, positive affect, competition, fantasy/escape, coping, pass/waste time) and additional demographic and behavioral characteristics are used to create a typology of esports players. Based on a large, diverse and international sample of respondents (n = 1165), five types of players, including (1) Competitive, (2) Casual, (3) Casual-Social, (4) Casual-Fun, and (5) Casual-Competitive esports players, are identified. In-depth examination and discussion of the five types of players are provided. The implications of this research suggest the importance of considering demographic, psychographic and behavioral characteristics when attempting to identify, understand and classify different types of esports players.

All-pay auctions with private signals about opponents’ values

We study all-pay auctions where each player observes her private value as well as a noisy private signal about the opponent’s value, following Fang and Morris’s (J Econ Theory 126(1):1–30, 2006) analysis of winner-pay auctions with multidimensional private signals. A unique symmetric monotonic equilibrium exists if the signal is not informative enough. When the signal is sufficiently informative, there exists a symmetric non-monotonic equilibrium in which all types of players randomize in overlapping supports. The revenue is lower than that in the standard independent private value setting. Fixing the signal’s informativeness, the all-pay auction raises lower revenue than the second-price auction, whereas the revenue ranking between the all-pay and the first-price auction is ambiguous.

Trust and betrayals: Reputational payoffs and behaviors without commitment

I study a repeated game in which a patient player wants to win the trust of some myopic opponents, but can strictly benefit from betraying them. His benefit from betrayal is strictly positive and is his persistent private information. I characterize every type of patient player's highest equilibrium payoff and construct equilibria that attain this payoff. Since the patient player's Stackelberg action is mixed and motivating the lowest‐benefit type to play mixed actions is costly, every type's highest equilibrium payoff is strictly lower than his Stackelberg payoff. In every equilibrium where the patient player approximately attains his highest equilibrium payoff, no type of the patient player plays stationary strategies or completely mixed strategies.

Phase Transitions in Kyle's Model with Market Maker Profit Incentives

We consider a stochastic game between three types of players: an inside trader, noise traders and a market maker. In a similar fashion to Kyle's model, we assume that the insider first chooses the size of her market-order and then the market maker determines the price by observing the total order-flow resulting from the insider and the noise traders transactions. In addition to the classical framework, a revenue term is added to the market maker's performance function, which is proportional to the order flow and to the size of the bid-ask spread. We derive the maximizer for the insider's revenue function and prove sufficient conditions for an equilibrium in the game. Then, we use neural networks methods to verify that this equilibrium holds. We show that the equilibrium state in this model experience interesting phase transitions, as the weight of the revenue term in the market maker's performance function changes. Specifically, the asset price in equilibrium experience three different phases: a linear pricing rule without a spread, a pricing rule that includes a linear mid-price and a bid-ask spread, and a metastable state with a zero mid-price and a large spread.

Evolutionary Random Access Game With Objective and Subjective Players

We consider an evolutionary game on a graph under the condition that players perception of uncertainty and decision making can follow either an objective expected utility theory (EUT) model or a subjective prospect theory (PT) model. Each player chooses one of two strategies with probabilities $x$ and $1-x$ , where the subjective players bias their choices of the probabilities to be $w(x)$ and $w(1-x)$ to reflect the probability weighting effect of PT. We derive the conditions to achieve a locally asymptotically stable Nash equilibrium (NE) and the necessary conditions to achieve an evolutionary stable strategy (ESS). We illustrate these results through a simple random access channel game. We find that players’ behavior is affected by the total number of players as well as the number of each type of players (objective or subjective). We show that increasing the number of interacting players induces an aggressive transmission strategy and the behavior becomes similar for both types of players. Moreover, we let the objective and subjective players adjust their transmission under throughput rewards, delay penalties, and energy costs. The EUT players’ throughput is higher than the PT players’ throughput for a small number of interacting players and equal to if the number of interacting players increases.

Demand monotonicity of a pavement cost function used to determine Aumann-Shapley values in highway cost allocation

Pavement thickness and traffic lanes are two essential requirements affecting the cost of a highway design project. The traffic loadings on a pavement are typically measured in 18-kip equivalent single axle loads (ESALs). In this paper, both ESALs and lanes are treated as two types of players and a pavement cost function is developed to determine the average marginal cost for each type of players. These averages are known as the Aumann-Shapley (A-S) values and are used to allocate the highway cost among all vehicle classes. The proposed pavement cost function is proved to be monotonically increasing as the traffic loadings (ESALs) are increased, a necessary condition for the function to be acceptable for computing Aumann-Shapley values. A severe limitation of the procedure to calculate marginal costs for the traffic-loading players is the extremely large number of permutations since the number of players is enormously high. To overcome this limitation, this article derives a compact form for the discrete A-S values of ESALs and lanes that allows the Aummann-Shapely values to be calculated in a computationally effective manner.

Implementation and Analytics of the Distributed Eco-Driving Simulation iCO2

We describe iCO2, a simulation platform for collecting driving behavior data. It is designed as the first massively multiplayer online game for mobile devices to practice eco-friendly driving. It facilitates the collection of large-scale data on driving behavior to better understand compliance and incentive mechanisms for eco-driving and users' preferences. We present the results of a campaign with iCO2 that used a game promoter to attract 2455 users. The results are described from three angles: (1) types of drivers are identified by clustering driving behavior; (2) types of players are identified by relating players' interaction with game elements and their driving behavior; (3) by looking at longer sessions, we demonstrate that players who show eco-unfriendly behavior at the beginning of the session improve their eco-driving behavior throughout their playtime.

Gamification as the human resources management tool

There is a huge number of different methods created to increase employee motivation, while they are constantly being improved and new ones appear. The manager must not only choose the right one, but also be able to implement it. One of the methods is gamification. The basics of HR management processes using this method are just beginning to form, so it is necessary to develop mechanisms for implementing gamification in the organization. Based on the research, the main provisions aimed at including elements of gamification in the company and recommendations for their implementation are formulated. The purpose of the article is to study gamification in the organization’s personnel management in detail and to formulate practical recommendations for its application. The research used methods of the theoretical level, such as: study and generalization, analysis and synthesis, deduction and induction, as well as the study of literature, the regulatory framework and other sources of information. On the basis of the study, the types of games and players, the main provisions aimed at including elements of gamification in the company, as well as recommendations for their implementation to improve the organization’s activities are formulated.

The quasi-sorting equilibrium and incentive effects in parallel contests with multiple types of players

The quasi-sorting equilibrium and incentive effects in parallel contests with multiple types of players

An Optimal Decision Method for Intrusion Detection System in Wireless Sensor Networks With Enhanced Cooperation Mechanism

When it comes to selecting an optimal defense strategy for an intrusion detection system of a wireless sensor network, such challenges as those brought about by the diversification of the attack methods and the expanded database of the attack patterns have to be dealt with. To overcome those challenges, this paper combines realistic bounded rationality with the incomplete information of the attack-defense players by employing evolutionary game theory as a tool. Firstly, an attack-defense evolutionary game model considering three types of population, in which attackers are subdivided by the source of the threat into external attackers and selfish nodes, is proposed. The sets of player types and the game strategies in our model can be extended from 2×2 to n× m × l. The sensitivity of the evolutionary population to similar strategies, which reflects the efficiency change in the multi-agent learning process, is depicted by a replicator dynamic equation especially optimized for this purpose by the introduction of an enhanced cooperation mechanism. In essence, an optimal defense strategy selection algorithm is provided by calculating the evolutionary stable equilibrium and a description of the evolutionary trajectory of the players over time is obtained. Moderate security and proactive defense in the form of support decisions have been provided by our method for wireless sensor networks. Experimental results have verified the validity of our method. Moreover, the optimized algorithm has solved the problem that an excessively large database of attack patterns affects the speed of switching to the optimal defense decision strategy and the learning efficiency of the evolutionary game replicator dynamic mechanism is not fast enough.

Upper body injuries and Key Performance Indicators in professional basketball players

ntroduction: Upper body injuries are less common than lower body injuries in basketball, but there is still a lack of knowled-ge about the relationship among their occurrence and the performance profile of professional basketball players. This study aimed to analyse the relationships between upper-body injuries and Key Performance Indicators (KPIs) of basketball players. Material and method: Statistical variables of 554 professional basketball players (age: 26.97±4.86 years, height: 199.23±8.80 cm, minutes per season: 441.18±301.41) in Spanish ACB (Asociación de Clubes de Baloncesto) professional competition were analysed for two seasons (2012-13 and 2013-14). Besided, injury reports were registered and injuries were categorized with OSICS-10 classification. The players who played the most minutes during the season were more likely to suffer lumbar spine, head, wrist, and hand injuries. The players injured in the thoracic spine obtained a better average in steals per minute. The players injured in the head or the elbow had better +/- performance per minute. The players injured in the neck had better means per minute in received fouls, free throws made and attempted. Results: The players injured in the lumbar spine had better means, per minute played, in assists, probably by their continuous column twists to protect the ball with the body to avoid bumps. Players injured in the shoulder had more blocked shots per minute than those not injured, probably because the realization of a block involves a shoulder flexion and rotation. It would be interesting to carry out a specific follow-up in this type of player, for this type of injury. This information could be helpful to improve injury prevention with the use of KPIs of basketball.

Sustainable society based on social gamification using Nova Empire ecology mining

In recent years, with the development of social app, the Internet has created a different interactive mode from the previous daily life, which makes the development of society gradually presents the trend of “gamification”. “Social gamification” makes the life systematically integrated into the competition activities. Therefore, we propose a new idea for the realization of a sustainable society under the trend of “social gamification” by combining strategy game ecology mining for the first time. Specifically, we use big data mining to analyze the attributes of the smurf (subsidiary account), and then extract discriminative features and compute a score for each attribute using machine learning, which could accurately locate all the smurf in the game. By banning the smurf, the game ecology is optimized to improve the player’s game experience. Meanwhile, this paper proposes appropriate operation strategies for players at different stages based on multi-level clustering. In the real society, smurf represents the citizens who disturb social order, and different types of players represent the pyramid structure of social classes. The measures in the game provide references for the construction of a sustainable society.

Determination of Player Types according to Digital Game Playing Preferences: Scale Development and Validation Study

ABSTRACT The aim of this study was to develop a player type determination scale based on Bartle’s taxonomy. In this study, player type determination tests prepared for Bartle’s player types were translated into Turkish by two English experts. The Turkish version of the items was revised by two field experts to best express the point of each item. Next, a scale consisting of 50 items was formed in accordance with the purpose of the study and the level of secondary school students. The scale was administered to 505 secondary school students, and validity and reliability studies were conducted. As a result of a factor analysis, it was decided to remove some items from the test, leading to a measurement instrument of 32 items in total. It was concluded that the scale developed to determine the player type for digital gaming environments was valid and reliable.