Using a survey of 324 small and medium-sized enterprises (SMEs) of the Yangtze River Delta in China, this study discusses the relationship between entrepreneurial orientation, absorptive capacity, environmental dynamism, and corporate technological innovation performance. The results based on a moderated moderation model show that the relationship between entrepreneurial orientation and innovation performance is significantly positive. The absorptive capacity can positively moderate this relationship. When the external environment is in high dynamism, the moderating effect of absorptive capacity will be stronger than when the environment is in low dynamism.

Green innovation is a key way for firms to establish competitive advantage and contribute to sustainable development, but it often suffers from financing constraints. In this regard, environmental, social, and governance (ESG) practices allow firms to have a wider investor base, face lower risk, and generate positive market reactions, ultimately leading to a lower cost of capital, which may potentially alleviate financing constraints and provide strong motivation for green innovation. Combining stakeholder theory with the resource-based view (RBV), this study investigated how ESG substantially affects corporate green innovation. Based on a zero-inflated Poisson regression analysis of 1577 listed Chinese manufacturing firms, we found that better ESG could significantly induce better corporate green innovation, and financing constraints acted as a mediator in the relationship between ESG and green innovation.Our findings contribute to a more detailed understanding of the mechanisms by which corporate pro-social decision-makings initiate and boost green innovation.

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The Chinese government is committed to ensuring separation of municipal solid waste (MSW), promoting the integrated development of the MSW management system with the renewable resource recovery system, and achieving construction of ecological civilization. Guided by the methods in Intergovernmental Panel on Climate Change (IPCC) guidelines, the greenhouse gas (GHG) emissions under five waste disposal scenarios in Beijing under the life cycle framework were assessed in this research. The study included collection and transportation, as well as three end disposal methods (sanitary landfill, incineration, and composting), and the emission reduction benefits of electricity generation from incineration and recycling of renewable resources were taken into account. The results show that an emission reduction benefit of 70.82% could be achieved under Scenario 5 in which kitchen waste and recyclables are sorted and recycled and the residue is incinerated, and the selection of the optimal strategy was not affected by changes in the separation rate. In addition, landfill would emit more GHG than incineration and composting. The results of this study are helpful for the government to make a decision on MSW management considering the goal of GHG emission reduction.

After the Chinese reform and opening up, the construction of economic zones, such as Special Economic Zones, Hi-tech Zones and Bonded Zones, has played an irreplaceable role in China’s economic development. Currently, against the background of Chinese economic transition, research on development evaluation of economic zones has become popular and necessary. Similar research usually focuses on one specific field, and the methods that are used to evaluate it are simple. This research aims to analyse the development evaluation of zones by synthesis. A new hybrid multiple criteria decision making (MCDM) model that combines the DEMATEL technique and the DANP method is proposed. After establishing the evaluation criterion system and acquiring data, the influential weights of dimensions and criteria can be calculated, which will be a guide for forming measures of development. Shandong Peninsula Blue Economic Zone is used in the empirical case analysis. The results show that Transportation Conditions, Industrial Structure and Business Climate are the main influencing criteria and measures based on these criteria are proposed.

Purpose Digital technologies, such as big data and artificial intelligence, significantly impact entrepreneurial activities worldwide. However, research on entrepreneurial activities enabled by digital technologies is fragmented, divergent and delayed. This study aims to provide a structured review of digital entrepreneurship (DE) to identify status, hotspots, knowledge structure, dynamic trends and future developments in this field. Design/methodology/approach The bibliometric analysis was applied to offer a technological review on DE. In total 704 publications and their 34,083 references from Web of Science were retrieved as the sample set. Basic characteristics of publications, including the most influential documents, authors, journals and countries, were obtained. Then, co-citation and co-occurrence analyses were conducted to sketch the contours of the structure and evolution of DE. Findings DE has attracted increasing attention in the past three decades, especially after 2013. There are dozens of countries, hundreds of journals and more than 1,000 authors that have contributed to this field. Based on keyword co-occurrence clustering and co-citation clustering, the authors proposed a 3E (empower, evolution and ecosystem) framework of DE to facilitate an interdisciplinary dialogue for evidence-based policymaking and practice. In the future, researchers need to pay more attention to theoretical research and study DE from a holistic and dynamic perspective with consideration to the negative impact of digital technology on entrepreneurial activities. Originality/value This study draws an outline of the global advance on DE research. It presents an opportunity to comprehensively understand the contemporary achievements, the march of knowledge and the logical venation underlying academic developments as well as foundations for policymaking.

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Product testing is a critical step in tablet PC manufacturing processes. Purchases of testing equipment and on-site testing personnel increase overall manufacturing costs. In addition, to improve manufacturing capabilities, manufacturers must also produce products with higher quality and at a lower cost than their competitors if they are to attract consumers and gain a competitive edge in their industry. The Mahalanobis-Taguchi System (MTS) is a novel technique proposed by Genichi Taguchi for performing diagnoses and forecasting with multivariate data. The MTS can be used to select important factors and has been applied in numerous engineering fields to improve product and process quality. In the present study, the MTS, logistic regression, and a neural network were used to improve the tablet PC product testing process. The results indicated that the MTS attained 98% predictive power after insignificant test items were eliminated. The MTS performance was superior to those of the conventional logistic regression and neural network, which attained 93.3% and 94.7% predictive power, respectively. After the testing process was improved using the MTS, the number of test items in the tablet PC product testing process was reduced from 56 to 14. This facilitated the development of more stable test site configurations and effectively reduced the testing time, number of testers required, and equipment costs.