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The purpose of this study is to explore the relationship of gamification design elements on social play habit and we-intention to continue playing in a mobile multiplayer game context. The study further intends to reveal the mediating role of social play habit in the relationship between gamification design elements and we-intention to continue playing.

The proposed model was empirically evaluated using survey data collected from 292 PUBG users based in Malaysia. PLS-SEM analysis was used to assess the model since it includes formative and reflective constructs.

The results indicated that gamification design elements significantly affect social play habit in a positive direction. In the simultaneous condition, social play habit also significantly affects the we-intention to continue playing the mobile multiplayer game. However, these three elements of gamification design did not significantly affect the formation of we-intention to continue playing in the context of mobile multiplayer games. Notably, social play habit was found to fully mediate the relationships between immersive-related interaction, achievement-related interaction, social-related interaction and we-intention to continue playing.

This study highlights the importance of social play habits as a factor linking the relationship between gamification design elements and we-intention to continue playing. In addition, this study also provides significant insights for the game creators to emphasise the gamification design elements so that the sustainability of the game can be secured from the perspective of retaining the current users through the social play habit element.

The study is noteworthy because it is the first attempt to use gamification design elements to explain how social play habit affect the formation of we-intention to continue playing in the setting of a mobile multiplayer game environment. In addition, the findings may add to the body of knowledge in the field of gamification theory.

This study aims to explore the use of gamification elements by micro and small e-tailers to enhance customer loyalty. Additionally, this research seeks to identify the most promising gamification elements that can be utilised for this purpose.

The authors adopt a qualitative approach to examine the impact of gamification on online customer loyalty to micro and small e-tailers. Data were gathered using a combination of two types of expert interviews. Semi-structured interviews were held with micro and small e-tailers while large e-tailers served as the control group. Structured interviews based on multi-criteria decision analysis (MCDA) models were conducted to determine the most promising gamification elements.

The content analysis reveals that gamification has significant potential for fostering customer loyalty and offering various other benefits. However, small e-tailers often refrain from implementing gamification solutions due to the resource requirements in terms of finances, time, information technology and human capital. By assigning weights as an essential step in MCDA models, the authors determined that badges, medals, quests, avatars and competitions are the most promising gamification options for small e-tailers’ efforts to enhance customer loyalty.

The study makes a unique contribution to the understanding of the usefulness of gamification in augmenting customer loyalty and identifying essential gamification elements for micro and small e-tailers.

This study is about the expression of sketches in Steven Holl's architectural works. Holl shares his architectural ideas as watercolors with his staff, and he has established an original notational expression for the design process. This study investigates the elements of sketches as a notation method and examines the timeline changes.

Classification will be conducted using KJ method (Kawakita Jiro method), a method for organizing information developed by the Japanese cultural anthropologist Kawakita Jiro. Using the KJ method, this study compiled a list as a table about the pictures, letters, etc. in the sketches and grouped them together in the same attributes. The attributes that were grouped together were identified as elements of the sketches.

As a result, in the early 1970s, Holl used only line drawings for sketches, but since the 1980s, watercolor sketches have been increasingly used. Extracting the elements of sketches, it can divide them into drawing and describing expressions and classify them into three main types of pictorial expressions: Overview, Plan and Concept.

This study has shown that the closer the sketches were to the present, the more they combined elements of a more complex sketch with letters and symbols as well as pictorial expressions. This is the first study to investigate about sketch representations established as notations by Steven Holl. This study identified the elements that make the architectural concept visible through sketches.

Among different types of engineering structures, plates play a significant role. Their analysis necessitates numerical modeling with finite elements, such as triangular, quadrangular or sector plate elements, owing to the intricate geometrical shapes and applied loads. The scope of this study is the development of a new rectangular finite element for thin plate bending based on the strain approach using Airy's function. It is called a rectangular plate finite element using Airy function (RPFEUAF) and has four nodes. Each node had three degrees of freedom: one transverse displacement (w) and two normal rotations (x, y).

Equilibrium conditions are used to generate the interpolation functions for the fields of strain, displacements and stresses. The evolution of the Airy function solutions yielded the selection of these polynomial bi-harmonic functions. The variational principle and the analytical integration approach are used to evaluate the basic stiffness matrix.

The numerical findings for thin plates quickly approach the Kirchhoff solution. The results obtained are compared to the analytical solution based on Kirchhoff theory.

The efficiency of the strain based approach using Airy's function is confirmed, and the robustness of the presented element RPFEUAF is demonstrated. Because of this, the current element is more reliable, better suited for computations and especially intriguing for modeling this kind of structure.

This paper aims to investigate the performance of two novel numerical methods, the face-based smoothed finite element method (FS-FEM) and the edge-based smoothed finite element method (ES-FEM), which employ linear tetrahedral elements, for the purpose of strength assessment of a high-speed train hollow axle.

The calculation of stress for the wheelset, comprising an axle and two wheels, is facilitated through the application of the European axle strength design standard. This standard assists in the implementation of loading and boundary conditions and is exemplified by the typical CRH2 high-speed train wheelset. To evaluate the performance of these two methods, a hollow cylinder cantilever beam is first used as a benchmark to compare the present methods with other existing methods. Then, the strength analysis of a real wheelset model with a hollow axle is performed using different numerical methods.

The results of deflection and stress show that FS-FEM and ES-FEM offer higher accuracy and better convergence than FEM using linear tetrahedral elements. ES-FEM exhibits a superior performance to that of FS-FEM using linear tetrahedral elements, showing accuracy and convergence close to FEM using hexahedral elements.

This study channels the novel methods (FS-FEM and ES-FEM) in the static stress analysis of a railway wheelset. Based on the careful testing of FS-FEM and ES-FEM, both methods hold promise as more efficient tools for the strength analysis of complex railway structures.

This paper aims to amplify the retrieval and utilization of historical newspapers through the application of semantic organization, all from the vantage point of a fine-grained knowledge element perspective. This endeavor seeks to unlock the latent value embedded within newspaper contents while simultaneously furnishing invaluable guidance within methodological paradigms for research in the humanities domain.

According to the semantic organization process and knowledge element concept, this study proposes a holistic framework, including four pivotal stages: knowledge element description, extraction, association and application. Initially, a semantic description model dedicated to knowledge elements is devised. Subsequently, harnessing the advanced deep learning techniques, the study delves into the realm of entity recognition and relationship extraction. These techniques are instrumental in identifying entities within the historical newspaper contents and capturing the interdependencies that exist among them. Finally, an online platform based on Flask is developed to enable the recognition of entities and relationships within historical newspapers.

This article utilized the Shengjing Times·Changchun Compilation as the datasets for describing, extracting, associating and applying newspapers contents. Regarding knowledge element extraction, the BERT + BS consistently outperforms Bi-LSTM, CRF++ and even BERT in terms of Recall and F1 scores, making it a favorable choice for entity recognition in this context. Particularly noteworthy is the Bi-LSTM-Pro model, which stands out with the highest scores across all metrics, notably achieving an exceptional F1 score in knowledge element relationship recognition.

Historical newspapers transcend their status as mere artifacts, evolving into invaluable reservoirs safeguarding the societal and historical memory. Through semantic organization from a fine-grained knowledge element perspective, it can facilitate semantic retrieval, semantic association, information visualization and knowledge discovery services for historical newspapers. In practice, it can empower researchers to unearth profound insights within the historical and cultural context, broadening the landscape of digital humanities research and practical applications.

Adopting a brand prominence perspective, this study aims to examine how textual and visual brand elements influence the success of crowdfunding campaigns for aftermarket offerings.

A Python-based Web scraper was used to collect data from 620 crowdfunding campaigns for aftermarket offerings hosted on Kickstarter. The linguistic inquiry and word count application programing interface was then used to analyze the linguistic aspects of these campaigns. A fixed effects regression model was used to evaluate the hypotheses.

Textual and visual brand prominence are positively associated with campaign success. Further, with some variations, both types of brand prominence augment the positive effects of narrative and graphic design elements on campaign success.

This study makes novel theoretical contributions to the literature on branding, crowdfunding and aftermarket products. The results also provide practical insights to aftermarket enterprises on creating compelling crowdfunding campaigns.

By analyzing the direct and synergistic effects of branding, narrative and graphic design elements on crowdfunding success, this study extends various literature streams and identifies several future research opportunities.

Prior literature has long argued that knowledge networks contain great opportunities for innovation, and researchers can identify these opportunities using the properties of knowledge networks (PKNs). However, previous studies have examined only the relationship between structural PKNs (s-PKNs) and innovation, ignoring the effect of qualitative PKNs (q-PKNs), which refer to the quality of the relationship between two elements. This study aims to further investigate the effects of q-PKNs on innovation.

Using a panel data set of 2,255 patents from the Chinese wind energy industry, the authors construct knowledge networks to identify more PKNs and examine these hypotheses.

The results show that q-PKNs significantly influence recombinant innovation (RI), reflecting the importance of q-PKNs analysed in this study. Moreover, the results suggest that the combinational potential of an element with others may be huge at different levels of q-PKNs.

This study advances the understanding of PKNs and RI by exploring how q-PKNs impact RI. At different levels of PKNs, the potential of the elements to combine with others and form innovation are different. Researchers can more accurately identify the opportunities for RI using two kinds of PKNs. The findings also provide important implications on how government should provide support for R&D firms.

Thermal protection of a flange is critical for preventing tower icing and collapse of wind turbines (WTs) in extremely cold weather. This study aims to develop a novel thermal protection system for the WTs flanges using an electrical heat-tracing element.

A three-dimensional model and the Poly-Hexacore mesh structure are used, and the fluid-solid coupling method was validated and then deployed to analyze the heat transfer and convection process. Intra-volumetric heat sources are applied to represent the heat generated by the heating element, and the dynamic boundary conditions are considered. The steady temperature and temperature uniformity of the flange are the assessment criteria for the thermal protection performance of the heating element.

Enlarging the heating area and increasing the heating power improved the flange's temperature and temperature uniformity. A heating power of 4.9 kW was suitable for engineering applications with the lowest temperature nonuniformity. Compared with continuous heating, the increased temperature nonuniformity was buffered, and the electrical power consumption was reduced by half using pulse heating. Pulse heating time intervals of 1, 3 and 4 h were determined for the spring, autumn and winter, respectively.

The originality of this study is to propose a novel electrical heat-tracing thermal protection system for the WTs flanges. The effect of different arrangements, heating powers and heating strategies was studied, by which the theoretical basis is provided for a stable and long-term utilization of the WT flange.

Gas metal arc-based directed energy deposition (GMA-DED) process experiences residual stress (RS) developed due to heat accumulation during successive layer deposition as a significant challenge. To address that, monitoring of transient temperature distribution concerning time is a critical input. Finite element analysis (FEA) is considered a decisive engineering tool in quantifying temperature and RS in all manufacturing processes. However, computational time and prediction accuracy has always been a matter of concern for FEA-based prediction of responses in the GMA-DED process. Therefore, this study aims to investigate the effect of finite element mesh variations on the developed RS in the GMA-DED process.

The variation in the element shape functions, i.e. linear- and quadratic-interpolation elements, has been used to model a single-track 10-layered thin-walled component in Ansys parametric design language. Two cases have been proposed in this study: Case 1 has been meshed with the linear-interpolation elements and Case 2 has been meshed with the combination of linear- and quadratic-interpolation elements. Furthermore, the modelled responses are authenticated with the experimental results measured through the data acquisition system for temperature and RS.

A good agreement of temperature and RS profile has been observed between predicted and experimental values. Considering similar parameters, Case 1 produced an average error of 4.13%, whereas Case 2 produced an average error of 23.45% in temperature prediction. Besides, comparing the longitudinal stress in the transverse direction for Cases 1 and 2 produced an error of 8.282% and 12.796%, respectively.

To avoid the costly and time-taking experimental approach, the experts have suggested the utilization of numerical methods in the design optimization of engineering problems. The FEA approach, however, is a subtle tool, still, it faces high computational cost and low accuracy based on the choice of selected element technology. This research can serve as a basis for the choice of element technology which can predict better responses in the thermo-mechanical modelling of the GMA-DED process.