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The purpose of this paper is to understand the role of perplexity in young players’ experiences within an educational videogame and how reflective thinking can help them to get out of perplexing scenarios.

We used a constructivist grounded theory approach and the lenses of Dewey’s conceptualization of perplexity and reflective thinking to examine young players’ in-game experiences.

We find that perplexity in gameplay is an experience that occurs when players encounter uncertainty about where to go or what to do next in the game. Findings reveal that while playing an educational game players engaged in two forms of perplexity – exploration-based and puzzle-based. Additionally, we unpack how players overcome these perplexing scenarios by reflecting on the information provided in the game.

While in a state of perplexity, reflecting on the in-game information aids players to think and make meaning, thus supporting learning. We provide suggestions for how to better utilize perplexity as an in-game design mechanism to encourage young players to reflect on in-game information.

This empirical study is original in its context of studying the phenomenon of perplexity in videogames and young players’ in-game reflection experiences.

Advancements in technology require that everyone is skilled with computational thinking (CT), problem-solving and computer programming skills. This study aims to examine the development of CT in problem-solving skills (PSS) and programming learning attitude by integrating LEGO robotics kits in a project-based learning course.

This study examines the development of CT in PSS and programming learning attitude by integrating LEGO robotics kits in a project-based learning course. This study consists of a single group pre-post-test research design with 32 freshmen university students. Quantitative and qualitative data were collected by pre-post-tests and recording of classroom discussions, respectively.

Therefore, this finding implies that robotics can be used to develop CT in university students; however, there is a need for designing curricula with advanced robotic kits as artificial intelligence (AI) has become more prevalent. Hence, programming knowledge learned will help students to understand the application of robots in AI.

The study creates educators' awareness that CT skills might be developed in freshmen university students through robotics. However, many still consider them toys rather than learning aids.

The purpose of this paper is to perform experimental tests on fatigue characteristics of chip scale package (CSP) assembly under vibration. Some suggestions for design to prolong fatigue life of CSP assembly are provided.

The CSP assembly which contains different package structure modes and chip positions was manufactured. The fatigue characteristics of CSP assembly under vibration were tested. The fatigue load spectrum of CSP assembly was developed under different excitation. The fatigue life of chips can be estimated by using the high-cycle fatigue life formula based on different stress conditions. The signal–noise curve shows the relationship between fatigue life and key factors. The design strategy for improving the fatigue life of CSP assembly was discussed.

The CSP chip has longer fatigue life than the ball grid array chip under high cyclic strain. The closer to fixed point the CSP chip, the longer fatigue life chips will have. The chip at the edge of the printed circuit board (PCB) has longer fatigue life than the one in the middle of the PCB. The greater the excitation imposed on the assembly, the shorter the fatigue life of chip.

It is very difficult to set up a numerical approach to illustrate the validity of the testing approach because of the complex loading modes and the complex structure of CSP assembly. The research on an accurate mathematical model of the CSP assembly prototype is a future work.

It builds a basis for high reliability design of high-density CSP assembly for engineering application. In addition, vibration fatigue life prediction method of chip-corner solder balls is deduced based on three-band technology and cumulative damage theory under random vibration so as to verify the accuracy of experimental data.

This paper fulfils useful information about the dynamic reliability of CSP assembly with different structural characteristics and material parameters.

The purpose of this paper is to investigate toxic behaviour (TB) that significantly harms individuals’ gameplay experience in multiplayer online video games. Multiplayer online video games allow to simultaneously interact with others in real time. They can be considered as digital communities unifying a group of players within a video game. TB is characterized by spreading a bad mood (e.g. upsetting and insulting) leading to unsatisfying outcomes in team-based multiplayer environments.

Using mixed methods, the authors show that handling TB should be addressed more firmly on a level of game design. First, the authors test the explanatory power of the online disinhibition effect (ODE) and its antecedents on TB using a quantitative survey (N = 320) and structural equation modelling. Specifically, the authors show that dissociative anonymity, asynchronicity, solipsistic introjection, dissociative imagination and minimization of authority have a mediated effect through toxic disinhibition as predictors of TB. Second, the authors conduct a focus group workshop (N = 10) with experts from diverse disciplines to derive design principles on a level of game design.

The results indicate that transparency and imminent feedback are still underutilized elements in game design that can significantly buffer several forms of TB. By developing a heuristic prototype and exemplary design principles in subsequent categories, the authors address all relevant in-game scenarios. With this study, the authors provide researchers and practitioners helpful insights on how to increase the well-being and safety of gaming communities.

ODE already showed its explanatory potential in the neighbouring context of cyberbullying. Embedded in theories of negative behaviour on the internet, the authors propose a holistic and theory-driven approach to handle TB on a level of game design. The authors’ insights allow for a better understanding of an innovative entity of the dark side of technology diffusion and adverse side effects linked to it.

The purpose of this research is to address the existing gap in the study of construction and demolition waste (C&DW) by focusing on its impact on human health throughout the entire life cycle. And this research provides a comprehensive assessment model that incorporates the release of gaseous pollutants and particulate matter during the whole life cycle of C&DW, thereby contributing to a more holistic understanding of its impact on human health.

The research was conducted in two stages. Firstly, the quantitative model framework of pollutants emitted by C&DW was established. Three types of pollutants were considered, namely nitrogen dioxide (NO₂), sulfur dioxide (SO₂) and inhalable particulate matter (PM10). Second, disability-adjusted life year (DALY) and willingness to pay (WTP) assessments were used to provide a monetary quantified health impact for pollutants released by C&DW.

The results show that the WTP value of PM10 is the highest among all pollutants and 8.68E+07 dollars/a, while the WTP value in the disposal stage accounts for the largest proportion compared to the generation and transportation stage. These findings emphasize the importance of PM10 and C&DW treatment stage for pollutant treatment.

The results of this study are of great significance for the management department to optimize the construction management scheme to reduce the total amount of pollutants produced by C&DW and its harm to human health. Meanwhile, this study fills the gap in existing research on the impact assessment of C&DW on human health throughout the whole life cycle, and provides reference and basis for future research and policy formulation.

Agriculture and cultivation firms are facing severe competition in the saturated market. Due to the characteristics of heavy assets, low investment return, long cycle and high price fluctuation, agri-food firms require innovations for capital support. The purpose of this paper is to provide valuable insights on how firms in the food/agricultural industry approach innovations and reinforce their advantages through functional and structural innovations by adopting supply chain finance (SCF).

This research adopts a single-case study methodology to investigate the innovations and mechanisms taking place at H Corp Agriculture Group (H Corp hereafter), a Chinese egg company.

The findings of this paper indicate that SCF could have a great impact on supply chain management through functional and structural innovations throughout the supply chain and solve the capital constraint problems in the agricultural development process, promoting the implementation of the integration strategy as well as innovation in the agricultural industry chain. The research also shows that supply chain structural and functional innovations could promote corporate social responsibility (CSR) and creating shared value (CSV).

The research contributes to the application of SCF mechanisms and the realization of CSV and CSR jointly – both in the literature and in firms’ practices. It also contributes to the extension of structural and functional innovations and vertical integration of the supply chain. However, generalizability and universality are insufficient for a single case study in the specified industry. Data collection and quantitative analysis could be extended for further research.

The study addresses the need for comprehensive research on SCF and its applications. It proposes effective and efficient strategies for agri-food firms applying SCF to overcome industry capital constraints and develop competitiveness. It also provides a balanced and positive circulation between economic value and social value, realizing CSR and CSV.

The authors aim to measure the effects of ambidextrous innovation and its mix strategy on organizational obsolescence with the moderating roles of environmental turbulence.

Hierarchical regression analysis was used to test the hypotheses on the basis of the survey data of 198 firm employees in China.

Both exploratory and exploitative innovations significantly restrain organizational obsolescence. The complementary strategy of ambidextrous innovation is negatively correlated to organizational obsolescence, but the impact of balanced strategy is not significant. Environmental turbulence negatively moderates the relationship between exploratory innovation and organizational obsolescence, whereas it cannot moderate the effect of exploitative innovation.

The empirical and conceptual findings have important implications for organizations countering obsolescence through the construction of a mix strategy of ambidextrous innovation. This study enriches and extends obsolescence theory by introducing the joint mechanism of ambidextrous innovation and environmental turbulence.

Carbon trading mechanism has been adopted to foster the green transformation of the economy on a global scale, but its effectiveness for the power industry remains controversial. Given that energy-related greenhouse gas emissions account for most of all anthropogenic emissions, this paper aims to evaluate the effectiveness of this trading mechanism at the plant level to support relevant decision-making and mechanism design.

This paper constructs a novel spatiotemporal data set by matching satellite-based high-resolution (1 × 1 km) CO₂ and PM_2.5 emission data with accurate geolocation of power plants. It then applies a difference-in-differences model to analyse the impact of carbon trading mechanism on emission reduction for the power industry in China from 2007 to 2016.

Results suggest that the carbon trading mechanism induces 2.7% of CO₂ emission reduction and 6.7% of PM_2.5 emission reduction in power plants in pilot areas on average. However, the reduction effect is significant only in coal-fired power plants but not in gas-fired power plants. Besides, the reduction effect is significant for power plants operated with different technologies and is more pronounced for those with outdated production technology, indicating the strong potential for green development of backward power plants. The reduction effect is also more intense for power plants without affiliation relationships than those affiliated with particular manufacturers.

This paper identifies the causal relationship between the carbon trading mechanism and emission reduction in the power industry by providing an innovative methodology for identifying plant-level emissions based on high-resolution satellite data, which has been practically absent in previous studies. It serves as a reference for stakeholders involved in detailed policy formulation and execution, including policymakers, power plant managers and green investors.

This study aims to explore the hidden connectivity among words by semantic network analysis, further identify salient factors accounting for customer satisfaction of coffee shops through analysis of online reviews and, finally, examine the moderating effect of business types of coffee shops on customer satisfaction.

Two typical major procedures of big data analytics in the hospitality industry were adopted in this research: one is data collection and the other is data analysis. In terms of data analysis, frequency analysis with text mining, semantic network analysis, CONCOR analysis for clustering and quantitative analysis with dummy variables were performed to dig new insights from online customer reviews both qualitatively and quantitatively.

Different factors were extracted from online customer reviews contributing to customer satisfaction or dissatisfaction, and among these factors, the brand-new factor “Sales event” was examined to be significantly associated with customer satisfaction. In addition, the moderating effect of business types on the relationship between “Value for money” and customer satisfaction was verified, indicating differences between customers from different types of coffee shops.

The present study broadened the research directions of coffee shops by adopting online customer reviews through relative analytics. New dimensions such as “Sales event” and detailed categorization of “Coffee quality”, “Interior” and “Physical environment” were revealed, indicating that even new cognition could be generated with new data source and analytical methods. The industry professionals could develop their decision-making based on information from online reviews.

The present study used online reviews to understand coffee shop costumer experience and satisfaction through a set of analytical methods. The textual reviews and numeric reviews were concerned simultaneously to unearth qualitative perception and quantitative data information for customers of coffee shops.

本研究的目的在于通过网络评论分析了解网络评论中关键词之间的隐含联系, 然后探究影响咖啡店顾客满意度的因素, 最后验证不同咖啡店经营类型的调节作用。

本研究使用文本挖掘的频率分析、语义网络分析、聚类分析和通过虚拟变量进行的定量分析, 从网络评论中挖掘对咖啡店行业的新见解。此外, 还检验了咖啡店经营类型的调节作用。

从网络评论中提取影响顾客满意度的不同因素, 探索出“销售活动”对顾客满意度的显著影响。同时, 相较于连锁咖啡店, 独立经营咖啡店对“物有所值”到顾客满足度的关系具有调节作用。  

本研究通过使用相关的分析方法对顾客网络评论进行分析, 拓宽了咖啡店研究的方向。研究结果发现“销售活动”和“咖啡品质”的细分等新方面, 揭示了利用新的数据源和分析方法可以为相关产业提供全新的认知。本研究的研究结果表明行业从业者可以根据顾客网络评论来制定相应的营销策略。

本研究利用网络顾客评论及相关分析方法, 了解顾客咖啡店体验及满意度。本研究同时利用文本评论和数字评论来挖掘和分析咖啡店顾客的定性感知和定量数据信息。

关键词咖啡店 在线顾客评论 文本挖掘 语义网络分析 经营类型

文章类型： 研究型论文

Este estudio intenta explorar las relaciones encubiertas de palabras, mediante el análisis de redes semánticas, pero aún más, identificar los factores destacados que explican la satisfacción de los clientes de las cafeterías a través del análisis de reseñas online y, por último, examinar el efecto moderador de los tipos de negocios de cafeterías en la satisfacción al cliente.

En esta investigación se adoptaron dos procedimientos principales de análisis de “Big Data” en la industria hotelera, uno es la recopilación de datos y el otro es el análisis de datos. En términos de análisis de datos, se efectuó un análisis de frecuencia con minado de texto (text mining), análisis de red semántica, análisis CONCOR para agrupamiento y análisis cuantitativo con variables ficticias para extraer nuevas perspectivas de las reseñas de los clientes online, tanto cualitativa como cuantitativamente.

Diferentes factores fueron extraídos de las reseñas de clientes online que contribuyen a la satisfacción o insatisfacción de estos y, entre estos factores, se examinó que el nuevo factor “Evento de Ventas” está significativamente asociado con la satisfacción al cliente. Además, se verificó el efecto moderador de los tipos de negocios entre la relación de “Valor por Dinero” y la satisfacción del cliente, indicando las diferencias entre los clientes de distintos tipos de cafeterías.

El presente estudio amplia la perspectiva de investigación de las cafeterías, al adoptar las reseñas de clientes online a través de un análisis relativo. Se revelaron nuevas dimensiones como “Evento de Ventas” y la categorización detallada de la “Calidad del Café”, “Interior” y “Entorno Físico”, lo que indica que se podría generar una nueva cognición con una nueva fuente de datos y métodos analíticos. Los profesionales de la industria podrían llevar a cabo la toma de decisiones en función de la información obtenida a través de las reseñas en línea.

El presente estudio utilizó reseñas de clientes online para comprender la experiencia y satisfacción de los clientes de las cafeterías a través de un conjunto de métodos analíticos. Las revisiones numéricas y de texto se tomaron en cuenta simultáneamente para revelar la percepción tanto cualitativa como cuantitativa de la información de los clientes de las cafeterías.

Cafetería, Reseñas de clientes online, Minado de texto, Análisis de redes semánticas, Tipos de negocios

Trabajo de investigación