In the new manufacturing area, the Chinese textile industry is facing the opportunities and challenges under the sustainable development model and advanced manufacturing technology. It is urgent to use digital technology to realize digital transformation. In this process, digital dynamic capability and digital innovation are significant for textile firms to achieve digital transformation performance. Drawing on the data from 367 questionnaires of Chinese textile firms, we apply multiple regression to examine how a firm's digital transformation is affected by adopting digital technology. A conceptual model based on framework of resource–capability–performance is developed to examine how adoption of digital technology, digital dynamic capability, and digital innovation orientation affects a firm's digital transformation performance. The results indicate that the positive relationship between digital technology adoption and digital transformation performance is less significant; this path is fully mediated through digital dynamic capability. Digital innovation orientation has a positive moderating effect and that the efficiency digital innovation has the most significant moderating effect among all digital innovation types. In addition, compared with textile firms in the low level of digital technology adoption, the firms in the high‐level group show a significant positive relationship between digital technology adoption and digital transformation performance. These findings confirm the validity of the model and contribute to existing literature on technology efforts in firms and provide guidelines to help managers implement informed decisions about digital transformation.

In modern times, enhancing energy efficiency is one of the core agenda items for the economies to progress the world. United Nations general assembly has recommended increasing energy efficiency by considering the SDG-7 guidelines. In the contemporary period, E7 economies are deficient in producing the financial resources to ensure the availability of funds for the acquisition of energy efficiency. COVID-19 crises, lack of resilience in economies, devastating fiscal burdens, and tight monetary conditions of E7 economies are the major barriers. To resolve such issues, some innovative financing techniques, such as green financing, financial inclusion, and FinTech, were suggested to investigate. However, this research tested the empirical role of financial inclusion, green financing, and FinTech on the energy efficiency of E7 economies. Study findings have shown a significant role of such financing techniques on energy efficiency. Comparatively, green financing is found most fitting and highly supportive financing tool for energy efficiency among the three. The differences in attributes, financing mechanism, funds flow system, transection systems, and variation in support by the financial institution are the main reasons that lessen the role of financial inclusion and FinTech for energy efficiency. However, theorists must revisit the transaction system of FinTech and financial inclusion parameters like green bonds for energy efficiency attainment. Policymakers are suggested to develop viable and energy system-friendly policies to grant green finance to the energy systems of E7 economies, as conveniently as possible.

With the explosive growth of information and the increase of people’s fragmented time, the knowledge payment industry’s market size is growing. However, the heterogeneity between online knowledge payment behavior and traditional consumption gradually comes to the fore. It is of great practical significance to analyze the factors influencing users’ online knowledge payment behavior and clarify users’ online knowledge payment mechanism. Based on UTAUT theory, this study uses statistics, structural equation modeling, and mediating effect analysis to construct a theoretical model of the influencing factors of users’ payment behavior of knowledge payment platform from the user level, knowledge-provider level, and platform level. The findings show that content quality, peer influence, KOL influence, perceived interaction, effort expectation, and perceived trust significantly affect users’ willingness-to-pay and have an indirect effect on users’ paying behavior through their willingness-to-pay. Perceived cost, perceived interaction, content quality, peer influence, performance expectation, and effort expectation directly and significantly affect user paying behavior. By regulating the above elements, the improvement of customer attraction ability of online knowledge platforms can be realized.

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In recent years, the study of online consumption behavior has gradually formed its research system and analysis model based on the inheritance of traditional research paradigms, focusing on the inner mechanism of consumption models explained by consumption activities. Online consumption is based on the research scenario of social e-commerce and forms a broad research network through the extension of consumer objects, consumer psychology, and consumer concepts. Although the theoretical constructs of online consumer behavior continue to improve, the relevant studies still do not fully grasp the research frontiers due to the lagging research nature. In the context of Web 2.0, it is impossible to run through the latest developments in online consumption research. Moreover, the study of online consumer behavior has shown a trend of diversification and multiple schools of thought, and a research jungle has emerged, which in essence is the perfection and new height of the study of consumerism. This paper analyses the origins, frontiers, and prospects of online consumer behavior research to clarify the formation principles, development paths, and future directions of the online consumer behavior research jungle. Ultimately based on the economic changes in the post-pandemic context, this paper integrates and proposes an evolving mechanism for studying online consumption behavior, intending to achieve a peek into and reveal the jungle of online consumption research.