An exploratory study on risk identification of cross‐boundary innovation of manufacturing enterprises based on grounded theory

Unlocking green innovation and environmental performance: the mediated moderation of green absorptive capacity and green innovation climate

This study extends the foundations of the natural resource-based view (NRBV) by introducing a mediation-moderation framework by analyzing the influence of green intellectual capital (GIC) on both green innovation performance (GIP) and environmental performance (EP) while simultaneously considering the mediating role of green absorptive capacity (GAC) and the moderating influence of the green innovation climate (GICL). The data for this study was gathered from a sample of 575 participants employed within small and medium enterprises' (SMEs') manufacturing firms. This dataset was utilized to evaluate the proposed model; this study uses the PLS-SEM approach to comprehensively examine the complex interactions among these variables. This model adds to the theoretical understanding of NRBV and enhances its practical applicability. The findings of this study reveal a positive relationship between GIC, GAC, GIP, and EP within organizations. Furthermore, our investigation reveals a positive correlation between a GICL and the relationships involving GIC, GAC, GIP, and EP. Importantly, this research introduces a novel perspective by clarifying the complex relations among these variables and highlighting the positive correlation between a GICL and the relationships involving GIC, GAC, GIP, and EP. This novel approach enhances the theoretical understanding of NRBV and its practical applicability in fostering GIP and EP within manufacturing SMEs operating in Pakistan.

Constructing big data prevention and control model for public health emergencies in China: A grounded theory study

Big data technology plays an important role in the prevention and control of public health emergencies such as the COVID-19 pandemic. Current studies on model construction, such as SIR infectious disease model, 4R crisis management model, etc., have put forward decision-making suggestions from different perspectives, which also provide a reference basis for the research in this paper. This paper conducts an exploratory study on the construction of a big data prevention and control model for public health emergencies by using the grounded theory, a qualitative research method, with literature, policies, and regulations as research samples, and makes a grounded analysis through three-level coding and saturation test. Main results are as follows: (1) The three elements of data layer, subject layer, and application layer play a prominent role in the digital prevention and control practice of epidemic in China and constitute the basic framework of the “DSA” model. (2) The “DSA” model integrates cross-industry, cross-region, and cross-domain epidemic data into one system framework, effectively solving the disadvantages of fragmentation caused by “information island”. (3) The “DSA” model analyzes the differences in information needs of different subjects during an outbreak and summarizes several collaborative approaches to promote resource sharing and cooperative governance. (4) The “DSA” model analyzes the specific application scenarios of big data technology in different stages of epidemic development, effectively responding to the disconnection between current technological development and realistic needs.

A Grounded Theory Construction of the eSports Endogenous Drive Model

E-sports attracts a lot of time and energy from adolescents, making them happy to actively participate and even become addicted to the Internet. In order to reveal the mechanism of e-sports addiction and the mechanism of action, a model of e-sports internal drive was constructed by rooting qualitative analysis of interview data from 30 e-sports players, and the results of the study showed that the e-sports internal drive model consists of incentive setting (continuous incentive, variety of incentives, incentive can be redeemed, and incentive odds), task setting (can start over, flexible and free, can be completed, and specific goals), program setting (forming a team, simple interpersonal relationship, specific rules, timely feedback, fairness, simple operation, goal focus, quantified indicators, challenge difficulty, and training guidance), 3 dimensions, and 18 categories. The three dimensions are interrelated and synergistic eSports influencing factors. The establishment of this model enriches the relevant theories on the study of eSports endogamy and provides a reference basis for revealing the current social phenomenon of eSports game addiction among eSports players.

Influencing factors for effective teaching evaluation of massively open online courses in the COVID-19 epidemics: An exploratory study based on grounded theory

Many factors affect the teaching of massively open online courses (MOOCs). In this study, to explore the factors that influence the effective teaching of MOOCs, a large number of relevant studies are analyzed. Based on grounded theory, semi-structured interviews were conducted with 30 students and teachers who used MOOCs for online teaching. The interview data were subjected to four research processes –open coding, axial coding, selective coding, and saturation testing– to explore the factors influencing MOOCs’ effective teaching and the interactions between them. The results demonstrate that: (1) Effective teachers, effective tuition, effective communication, active online learning, social support guarantees, and online course design have important positive effects on effective teaching, while only certain online learning behaviors will seriously affect the teaching effectiveness of MOOC, resulting in negative effects. (2) Effective communication is essential for effective teaching in MOOCs; effective teachers are the leading factor, thus teachers should take the initiative to study and understand the students to understand their various learning needs and difficulties. (3) Reasonable and effective classroom teaching design is key to improving MOOCs’ teaching efficiency. (4) E-learning is respected, cared for, and valued by society, including cognition, emotion, and learning platform support from family, school, teachers, and classmates, and has an important impact on students’ motivation and the effects of online learning. The results of this study further clarify factors influencing effective teaching of MOOCs, thus helping to enrich and supplement the theory of effective teaching and evaluation and providing theoretical guidance for teachers to effectively implement MOOC teaching.