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To consider how quality should be conceptualized to improve understanding for researchers and practitioners, some researchers have discussed quality in terms of an essence or necessary condition. Others have regarded quality as individual and experiential, based on differences in actors’ conceptions of quality. This paper aims to resolve the tension caused by these competing views and propose an appropriate method for future research in the area of quality.

In many studies, researchers have attempted to understand quality in terms of necessary conditions or through a dualistic ontology. At the same time, an increasing number of researchers have emphasized its experiential nature while discussing quality in conjunction with meeting customers’ expectations. This study investigates how quality can be understood using a conceptual framework based on family resemblances.

There is no necessary condition or essence by which quality may be conceptualized or defined. This finding resolves the tension that has arisen from the simultaneous search for a common feature and the assertion that quality is experientially created by individuals. The research also highlights that the nature of quality may differ between people, time and place, or some aspects of it may be the same. Regarding quality in terms of family resemblances accommodates actors’ different conceptions of quality. Phenomenography is proposed as an appropriate research approach with its focus on the qualitatively different ways in which actors make sense of phenomena in their lifeworld.

Understanding quality as a family of attributes, and using phenomenography as method, provides methodological clarity to long-standing research issues. Using the approaches outlined in this study will enable empirical studies of quality, in any context, to be conducted soundly and relatively quickly. It will also provide a more inclusive and holistic set of meanings based on the experiences of individuals.

The research provides important insights for researchers and practitioners through clearer conceptions of quality. These include the ability to plan and deliver business outcomes that are more closely aligned with customers’ expectations. Understanding the conceptions of quality, as experienced and determined through family resemblances, has clear implications for researchers and practitioners.

Understanding actors’ conceptions of quality through the lens of family resemblances resolves long-standing research issues. Using phenomenography as method is innovative, as it is an emerging research approach in the business domain.

The establishment of free trade zones (FTZs) is an important experiment as part of the reform and opening up policy. This paper aims to focus on the issue of production efficiency of environmental protection enterprises in FTZs. Changes in the external and internal environments of enterprises can easily lead to changes in the production efficiencies of enterprises. The establishment of FTZs can change the external environment of enterprises. Knowledge accumulation changes the internal environment of enterprises. However, traditional efficiency analysis has usually ignored the internal and external heterogeneity of decision-making units, resulting in the distortion of the evaluation results.

This paper examines the relationship between knowledge accumulation and development potential based on financial data of environmental protection enterprises that were listed in Shanghai and Shenzhen A stocks, from 2009 to 2016. Then, through data envelopment analysis cross-efficiency analysis of the listed environmental protection enterprises from external heterogeneity, BP neural network model is set up.

The results show that the model set up in this paper is stable and reliable. The paper makes policy suggestions such as stimulating trade inside industry, quickening technological progress and enhancing environmental protection.

This paper analyzes the economy, environmental protection, science and technology and education to simulate the external environment of enterprises. Based on the experience data from the completion of Shanghai FTZ, this paper predicts the future development potential of Hainan FTZ enterprises.

The purpose of this paper is to analyze the influence that the financial restrictions of Chinese enterprises exert on their green innovation abilities with their increased integration into the global supply chain (GSC).

This study uses customs, import, and export data for 222,773 Chinese enterprises and examined them by ownership type, capital density, and degree of pollution.

The results show that the deeper the integration into the GSC, the looser the financing environment would be, and the stronger the green innovation abilities of the enterprises.

The findings suggest that China should step up privatization of state-owned enterprises, increase government subsidies to private enterprises, and loosen their financing restrictions to address the recent economic decline in the country and ensure smooth and fast economic growth.

This paper is one of the first of its kind to develop and empirically analyze the relationship between the GSC and the financing restrictions and their determinant factors in China. It uniquely contributes to help the authors find approaches to constructing China’s green innovation and has far-reaching implications for other developing countries.

Technical progress is an important technique within improving China’s comparative advantages, as new and renewable technologies will be beneficial for energy security. Productive technical progress and green technical innovation are necessary to improve working conditions and productivity of industries. Therefore, the purpose of this paper is to study technical progress in China under such harsh competitive circumstances, as well as types of technical progress that can be promoted, productive technical progress or green technology progress, and how technical progress will affect China’s competitive advantages.

The authors perform a multi-index multi-factor constitutive model based on a sample of 468 Chinese industries, and divide the industries into four categories.

The results indicate that there is a “U”-shape relationship between green technology progress and comparative advantages and an inverted “U”-shape relationship between the intensity of market competition and comparative advantages.

China has crossed the inflection point of the “U”-shaped curve. This, coupled with the slowing of economic growth, demonstrates the need for advocating green technology in China to decrease the pollutant discharge. Establishing Chinese national brands within overseas markets and earning a profit through the downstream of production chain enhance China’s international competitiveness.

One of the most original findings of this paper points out that China is faced with a situation in which exports are severely decreased and domestic environment pollution is increased. Vigorous promotion of green technology progress, improvement of the quality and the technical content of exported products, the establishment of national brand within the overseas market, as well as enhancement of China’s international competitiveness, is needed.

Non-fossil fuels are receiving increasing attention within the context of addressing global climate challenges. Based on a review of non-fossil fuel consumption in major countries worldwide from 1985 to 2015, the purpose of this paper is to analyze trends for global non-fossil fuel consumption, share of fuel consumption and inequality.

The similarities were obtained between the logarithmic mean divisia index and the mean-rate-of-change index decomposition analysis methods, and a method was proposed for complete decomposition of the incremental Gini coefficient.

Empirical analysis showed that: global non-fossil fuel consumption accounts for a small share of the total energy consumption, but presents an increasing trend; the level of global non-fossil fuel consumption inequality is high but has gradually declined, which is mainly attributed to the concentration effect; inequality in global non-fossil fuel consumption is mainly due to the difference between nuclear power and hydropower consumption, but the contributions of nuclear power and hydropower to per capita non-fossil fuel consumption are declining; and population has the greatest influence on global non-fossil fuel consumption during the sampling period.

The main contribution of this study is its analysis of global non-fossil fuel consumption trends, disparities and driving factors. In addition, a general formula for complete index decomposition is proposed and the incremental Gini coefficient is wholly decomposed.

The purpose of this paper is to measure Chinese industries’ eco-efficiency during 2006-2013. The Chinese industry attained rapid achievement in recent decades, but meanwhile, overconsumption of energy and environmental pollution have become serious problems. To solve these problems, many research studies used the data envelopment analysis (DEA) to measure the Chinese industry’s eco-efficiency. However, because the target set by these works is usually the furthest one for a province to be efficient, it may hardly be accepted by any province.

This paper builds a new “closest target method” based on an additive DEA model considering the undesirable outputs. This method is a mixed-integer programming problem which can measure the ecological efficiency of provinces and more importantly guide the province to perform efficiently with minimum effort.

The results show that the eco-efficiency of Chinese provinces increased at the average level, but the deviations remained at a larger value. Compared to the “furthest” target methods, the targets by the approach proposed by this study are more acceptable for a province to improve its performance on both economy and environment counts.

This study is the first attempt to introduce the closest targets concept to measure the eco-efficiency and set the target for each provincial industry in China.

As the functions of environmental regulations cannot be quantified while assessing their environmental efficiency, there has been no comprehensive evaluation of environmental efficiency. The purpose of this paper is to evaluate environmental regulations based on triangular and trapezoidal fuzzy numbers.

This paper uses L-R fuzzy numbers to transform the evaluation language into triangular fuzzy numbers, and adopts an α-level flexible slacks-based measurement model to evaluate the performance of these regulations. Trapezoidal fuzzy numbers are combined with a data envelopment analysis model, and an α-slack-based measurement (SBM) model is used to evaluate the environmental efficiency. The α-SBM model is confirmed to be stable and sustainable.

Relevant index data from 16,375 enterprises were collected to test the proposed model, and models corresponding to triangular fuzzy numbers and trapezoidal fuzzy numbers were used to evaluate their environmental efficiency. Comparative results showed that the proposed model is feasible and stable.

The main contributions of this study are twofold. First, this paper provides a valuable evaluation method for environmental regulation. Second, our research improves the practical performance of trapezoidal fuzzy data envelopment analysis and enhances its feasibility and stability.

This paper aims to examine the impact and mechanism of digital development on enterprise labor productivity. In addition, this study empirically analyzes the nonlinear impact of digitalization on labor productivity.

This paper uses a fixed effect model, a mediation effect model and a panel threshold model to test the theoretical hypothesis of this study.

The results demonstrated that digitalization had a promotional effect on labor productivity, with approximately 18% of this effect achieved through transmission and influence on human capital. In addition, the novelty of this study lies in the discovery that digitization has an obvious nonlinear positive effect on corporate labor productivity. The results suggest that companies should increase investment in data-driven innovation capabilities, improve the implementation of digital talent training plans, improve their financing capacity and strengthen corporate internal management, while the government should provide appropriate policy support differently for various enterprises.

This study takes China’s Shanghai and Shenzhen A-share listed companies as the research object, systematically examines the impact and mechanism of digital development on enterprise labor productivity and explores the nonlinear relationship between digitalization and enterprise labor productivity, which is a new angle.

本文旨在探讨数字化发展对企业劳动生产率的影响及其机制。此外, 本研究实证分析了数字化对劳动生产率的非线性影响。

本文采用固定效应模型、中介效应模型和面板门槛模型来检验本研究的理论假设。

结果表明, 数字化对劳动生产率有促进作用, 其中约 18% 是通过对人力资本的传导和影响来实现的。此外, 本文的新颖之处在于发现了数字化对企业劳动生产率具有显著的非线性正效应。结果表明, 企业应加大对数据驱动创新能力的投入, 完善数字化人才培养计划的实施, 提高融资能力, 加强企业内部管理, 政府应针对各类企业提供差异化的政策支持。

本研究以中国沪深A股上市公司为研究对象, 系统考察了数字化发展对企业劳动生产率的影响和机制, 探讨了数字化与企业劳动生产率之间的非线性关系, 这是一个新的研究角度。

Logistics capability is an important enabler of supply chain resilience (SCR). However, few studies have analyzed the underlying influence mechanism of logistics capability on SCR in extreme conditions, such as those of the COVID-19 pandemic. The purpose of this study is to increase understanding of the role of logistics capabilities in constituting a resilient supply chain.

Drawing upon the dynamic capability perspective and contingency theory, the proposed conceptual framework aims to demonstrate the relationship between a firm's logistics capabilities and SCR. Furthermore, the conceptual framework is illustrated by empirical evidence from a case study of a Chinese manufacturing company, which focuses on extracting practical lessons from the COVID-19 pandemic.

The findings suggest that digitalization, innovativeness, and modularization comprise potential mediating pathways for firm logistics capability to affect SCR and government policies, risk management culture, trust and cooperation moderate the effect positively. The potential associations are identified and elucidated by detecting the corresponding strategies and practices of a Chinese manufacturer that performed well amid the COVID-19 pandemic.

This study provides specific guidelines for logistics managers to enhance SCR during the COVID-19 pandemic. Seeing SCR as a dynamic capability, the framework is also instructive for manufacturers, supply chain members, and policymakers to achieve the sustained competitive advantage of supply chains.

The findings expand the understanding of enhancing SCR in a logistics approach. The empirical validation of propositions in the case study reveals a new vista for research on SCR.