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Playing video gaming is one of the most popular forms of leisure activities. This study looks into a specific video game genre, under the category of Multiplayer Online Battle Arena (MOBA) games. The purpose of this research is to investigate the factors that lead to the consumption of MOBA games. Three factors, imaginal, emotional and sensory experiences, are investigated through an integration of the hedonic consumption model, Technology Acceptance Model (TAM) and Uses and Gratification Theory (UGT).

The study analyses a sample of 292 MOBA game players using the PLS-SEM model. The study comprises two stages; in the first stage, an estimation model was used to test the constructs' quality and legitimacy. In the second stage, we assessed the theoretical model to test the relationship between the principle constructs.

The study found that factors related to emotional experiences, namely enjoyment, emotional involvement, and arousal, led to greater intention to play MOBA games. Similarly, two factors related to imaginal experiences, escapism and role projection, also positively impacted while fantasy carried a negative impact. The study also found that sensory experiences had a significant positive impact on the intention to play MOBA games. Lastly, a positive correlation was also found between the intention to use and usage behavior in MOBA games.

This study contributes to the theoretical understanding of the playful-consumption experiences of pleasure-oriented information systems (I.S.) that is MOBA games that derive behavioral intention to play MOBA games, which in turn determines the usage behavior of MOBA players. The study also incorporates the uses and gratification theory to uncover the needs and experiences that trigger MOBA games' behavioral intention and its further impact on gamers' usage behavior. The study also presents useful insights for game developers and other relevant stakeholders in game development.

Deviance includes behaviors that deviate from societal norms. Scholars belonging to various disciplines have extensively studied this phenomenon. This study aims to understand the length and breadth of the deviance landscape.

Through a systematic analysis of publications, authors, journals and countries involved in research, this investigation unveils the inherently interdisciplinary nature of the subject. It unveils the prominent journals and influential authors who have made significant contributions to the field, shedding light on the evolving trends and shifting emphases over time.

The findings underscore the ever-growing relevance and importance of deviance research in contemporary society. They emphasize the pressing need for ongoing exploration to grapple with the intricate challenges posed by deviant behaviors.

This comprehensive bibliometric analysis serves as an invaluable resource, catering to the needs of researchers and practitioners with a vested interest in comprehending and advancing the study of deviance in its myriad manifestations.

This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.

Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.

The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.

This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.

Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.

This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.

This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.

The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.

Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.

The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.

The purpose of this paper is to investigate an alternative simplified analytical approach for the design of electric machines. Numerical-based finite element method (FEM) is a powerful tool for accurate modelling and electromagnetic performance analysis of electric machines. However, computational complexity, magnetic saturation, complex stator structure and time consumption compel researchers to adopt alternate analytical model for initial design of electric machine especially flux switching machines (FSMs).

In this paper, simplified lumped parameter magnetic equivalent circuit (LPMEC) model is presented for newly developed segmented PM consequent pole flux switching machine (SPMCPFSM). LPMEC model accounts influence of all machine parts for quarter of machine which helps to reduce computational complexity, computational time and drive storage without affecting overall accuracy. Furthermore, inductance calculation is performed in the rotor and stator frame of reference for accurate estimation of the self-inductance, mutual inductance and dq-axis inductance profile using park transformation.

The developed LPMEC model is validated with corresponding FEA using JMAG Commercial FEA Package v. 18.1 which shows good agreement with accuracy of ∼98.23%, and park transformation precisely estimates the inductance profile in rotor and stator frame of reference.

The model is developed for high-speed brushless AC applications.

The proposed SPMCPFSM enhance electromagnetic performance owing to partitioned PMs configuration which make it different than conventional designs. Moreover, the developed LPMEC model reduces computational time by solving quarter of machine.

This paper aims to reviewed analytical methodologies, i.e. lumped parameter magnetic equivalent circuit (LPMEC), magnetic co-energy (MCE), Laplace equations (LE), Maxwell stress tensor (MST) method and sub-domain modelling for design of segmented PM(SPM) consequent pole flux switching machine (SPMCPFSM). Electric machines, especially flux switching machines (FSMs), are accurately modeled using numerical-based finite element analysis (FEA) tools; however, despite of expensive hardware setup, repeated iterative process, complex stator design and permanent magnet (PM) non-linear behavior increases computational time and complexity.

This paper reviews various alternate analytical methodologies for electromagnetic performance calculation. In above-mentioned analytical methodologies, no-load phase flux linkage is performed using LPMEC, magnetic co-energy for cogging torque, LE for magnetic flux density (MFD) components, i.e. radial and tangential and MST for instantaneous torque. Sub-domain model solves electromagnetic performance, i.e. MFD and torque behaviour.

The reviewed analytical methodologies are validated with globally accepted FEA using JMAG Commercial FEA Package v. 18.1 which shows good agreement with accuracy. In comparison of analytical methodologies, analysis reveals that sub-domain model not only get rid of multiples techniques for validation purpose but also provide better results by accounting influence of all machine parts which helps to reduce computational complexity, computational time and drive storage with overall accuracy of ∼99%. Furthermore, authors are confident to recommend sub-domain model for initial design stage of SPMCPFSM when higher accuracy and low computational cost are primal requirements.

The model is developed for high-speed brushless AC applications.

The SPMCPFSM enhances electromagnetic performance owing to segmented PMs configuration which makes it different than conventional designs. Moreover, developed analytical methodologies for SPMCPFSM reduce computational time compared with that of FEA.

This study aims to examine the relationship between managerial supportive communication, CEO relational communication and symmetrical internal communication. It specifically investigates the mediating role of symmetrical internal communication and employee advocacy, as well as the moderating influence of proactive personality on the link between employee advocacy and employee creativity.

A survey was conducted involving 290 full-time employees, and a Partial Least Square Structural Equation Modeling (PLS-SEM) statistical approach was used to assess the proposed relationships.

Both managerial supportive communication and CEO relational communication were found to be positively associated with symmetrical internal communication. Furthermore, results indicated that symmetrical internal communication and employee advocacy acted as strong mediators in the hypothesized relationships. Notably, the study also found that the impact of employee advocacy on employee creativity was significantly amplified in cases where employees exhibited a higher degree of proactive personality.

By emphasizing managerial supportive communication, enhancing CEO relational communication and promoting symmetrical internal communication and employee advocacy, organizations can create an environment conducive to innovation and creativity among employees. Additionally, recognizing the buffering effect of proactive personality on employee advocacy's impact on creativity enables organizations to better tailor their strategies for fostering creativity.

This research presents a novel contribution to the field by exploring the less-explored relationships between these critical communication factors and employee creativity. It uncovers the mediating and moderating mechanisms, shedding new light on how internal communication dynamics influence creativity. This unique approach provides an original perspective on the role of communication in promoting creativity at workplace.

The study aims to examine the relationship between personality traits and investor risk behavior of the individuals trading in stock markets. Furthermore, this study establishes the association of financial literacy on the relationship between personality traits and investor risk behavior.

The authors analyze cross-sectional survey method data by using moderated multiple regression analysis, a standard method of determining the moderation effect. PROCESS Model method has been used in this study to check the robustness of the results.

The findings reveal that personality traits significantly influence investor risk behavior and financial literacy modifies the fundamental relationships between personality traits and investor risk behavior. The findings also conclude that behavioral impact was predetermined by individuals' genetic traits and is influenced by financial literacy.

The current study provides valuable insights for investors and adamant grounds for future research. The two-fold role of individuals' personalities in case of gains and losses can be of interest to the researchers in future.

Investors currently facing the complex financial choices which are far beyond the day-to-day financial advice. This study guides rational investment behavior for portfolio managers and investors for advanced investment options.

Most of the prior literature is based on developed markets, whereas the current study focuses on less literate society (i.e. Pakistan) to protect the investors from scams and fraud. The current study supports the vital role of investors in the socio-economic development of emerging markets.

The authors believe this study expands the boundaries of personality theories, especially in the context of risk behavior and financial literacy. The study also contributes to advancing the personality theory trimmed with financial literacy and investor behavior while making important theoretical inroads for future research.

This study aims to examine the environmental impact of fossil fuel use in newly industrialized countries (NICs), focusing on the relationship between economic growth, energy consumption and environmental sustainability from 1971 to 2020.

The research uses pool mean group autoregressive distributive lag, fully modified ordinary least squares and dynamic ordinary least squares econometric models to analyze long-run data. These methods enable a detailed assessment of how economic and industrial factors affect environmental pollution.

The study finds that nonrenewable energy consumption is positively linked to environmental pollution, with a 1% increase leading to a 6.25% rise in pollution. Industrialization, urbanization and globalization also significantly increase pollution, with increments of 2.51%, 3.97% and 2.11%, respectively. Conversely, economic growth has a beneficial effect, reducing pollution by 2.59% for every 1% increase in growth.

Policymakers should balance economic growth with environmental sustainability by reducing nonrenewable energy consumption and supporting renewable energy adoption.

This research provides fresh insights into the dynamics between economic growth and environmental pollution in NICs. By using advanced econometric techniques over an extended period, it offers a view of how economic and industrial activities influence environmental outcomes, highlighting the dual role of economic growth in both promoting development and reducing pollution.