粤港澳大湾区制造业集聚与区域创新

以2009—2020年粤港澳大湾区11个城市为研究对象，探讨制造业集聚与区域创新的关系。研究发现，制造业集聚显著提高区域创新水平，可通过提高企业竞争这一路径实现。进一步分析发现，金融业集聚对区域创新发展具有显著的正向关系，金融产业和制造业产融协同集聚显著提高区域创新水平。研究结果表明，制造业集聚加剧产业内部企业创新竞争，带动区域创新发展，且金融业在创新中起到积极的推动作用。指出应鼓励区域企业创新竞争，优化营商环境，为产业融合发展提供保障。     

土地市场扭曲如何影响制造业出口产品质量升级*——基于土地市场交易数据和制造业企业数据的实证分析

地方政府“以地谋发展”的策略在促进各地区制造业大规模集聚和出口贸易快速增长的同时，也势必会给企业出口产品质量带来深刻影响。本文综合利用中国土地市场网城市土地交易数据、中国工业企业数据、中国海关进出口产品数据和中国城市面板数据，实证检验了土地市场扭曲对企业出口产品质量升级的影响，并对其内在机制进行了探讨。研究发现：中国城市建设用地配置存在明显的工业偏向性，进而导致工业用地价格被低估，产生工业用地应得收益大于实际价格的反向扭曲问题。这种反向扭曲可通过抑制技术进步、阻碍产业结构高级化、弱化集聚经济效应等机制显著降低制造业企业出口产品质量。土地市场扭曲对企业出口产品质量升级的影响具有明显的异质性特征。具体而言，土地市场扭曲不利于一般贸易企业与混合贸易企业出口产品质量提升，但对加工贸易企业出口产品质量提升具有促进作用。土地市场扭曲对企业出口产品质量升级的抑制作用由东到西依次递增。土地市场扭曲不利于外资企业和国有企业出口产品质量提升，对集体企业及民营企业的影响不显著。     

Risk Preferences and Gender Differences in Union Membership in Late Nineteenth-Century Swedish Manufacturing

Women are generally seen as less inclined to join trade unions. This study matches firm–worker data from the Swedish cigar and printing industries around 1900 and examines information on men and women holding the same jobs; such data are rare but important for understanding gender gaps. The results explain the gender gap in union membership among compositors, but not among cigar workers. Differences in union membership varied considerably across firms, with the largest differences found in low-union-density cigar firms where indirect costs (that is, uncertainty and risk) accrued in particular to women workers. The lack of gender differences in mutual aid membership indicates that women were not hard to organize but avoided organizations associated with greater risk for employer retaliation and uncertain returns according to a cost–benefit analysis.     

A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.     

Evaluation of the green technology innovation efficiency of China's manufacturing industries: DEA window analysis with ideal window width

Data Envelopment Analysis (DEA) window analysis with ideal window width is applied to evaluate the green technology innovation efficiency of 28 manufacturing industries in China during 2006–2014. The obtained results are compared with those calculated using the traditional DEA model, and convergence analysis of the efficiency is conducted. Five years is the obtained ideal window width and DEA window analysis with ideal window produces results closer to reality for China's manufacturing industry. The overall efficiency of the green technology innovation in the manufacturing sector is low following a wave-shaped curve – first decreasing, then increasing and decreasing again, with large inter-industrial differences. There are 8 high-, 14 medium- and 6 low-efficiency industries. A convergence trend in the green technology innovation efficiency within the 28 manufacturing industries exists, implying a catch-up effect between them.     

人力资源管理实践对制造企业转型升级的影响——基于泉州企业的实证研究

构建人力资源管理实践行为策略影响制造业转型升级的理论模型，以327家泉州制造企业为研究对象，通过问卷调查和结构方程模型分析,检验人力资源管理实践对制造企业转型升级的作用机制。结果表明，人力资源管理实践行为策略对企业转型升级具有显著的影响，组织创新气氛在两者之间起到部分中介作用。说明制造企业可以通过工作设计与人力资源规划、员工招聘与选择、员工培训与开发、绩效评价及薪酬与激励等策略的调整来促进企业转型升级。     

Unfolding the impact of leadership and management on sustainability performance: Green and lean practices and guanxi as the dual mediators

This study aims to empirically evaluate the predictors that influence sustainability performance among manufacturing firms. Leadership and management, green and lean practices, and guanxi were examined to determine whether these predictors are directly and/or indirectly affecting sustainability performance; 160 valid responses were collected and partial-least-squares-structural-equation-modeling (PLS-SEM) was used to analyze the data. The results showed that leadership and management positively influenced green and lean practices and green and lean practices positively influenced sustainability performance. Leadership and management also positively influenced guanxi. Interestingly, leadership and management and guanxi do not exert a significant direct influence on sustainability performance. The findings contributed to the development of the resource-based-view theory further by empirically exploring the significance of leadership and management coupled with green and lean practices as competencies and capability to drive sustainability performance. The testing of the dual mediators' effects further added value to this study.     

Blockchain in Additive Manufacturing and its Impact on Supply Chains

Additive manufacturing (AM) appears to be a particularly attractive use case for blockchain. This research combines inductive in‐depth interviews with the Delphi method to explore what potentials blockchain technology in AM creates, which adoption barriers firms need to overcome, and how supply chains will be affected by the integration of these two potentially disruptive technologies. The results suggest opportunities that are related to intellectual property (IP) rights management, the monitoring of printed parts throughout their lifecycle, process improvements, and data security. The most important barriers for blockchain adoption in AM are an absence of blockchain‐skilled specialists on the labor market, missing governance mechanisms, and a lack of firm‐internal technical expertise. By addressing important limitations of AM, blockchain is expected to improve the competitiveness of AM in parts’ production, catalyzing the trend toward more decentralized manufacturing resulting in more agile, resilient, and flexible supply chains and reduced logistics costs. Beyond that, blockchain‐based AM platforms are expected to enhance supply chain visibility, drive supply chain digitalization, support supply chain finance, and contribute to the emergence of shared factory systems.     

Natural resources,technological progress,and economic modernization

The present inquiry focuses on the modernization perspectives of the commodity‐exporting countries through the lens of development economics. To this end, the study adopts the Kaldorian framework to address the modernization effects, epitomized in the absorption of surplus labor. To trace the process of economic modernization, the study augments Lewis’s dualistic economy model by the extractive sector. Three different scenarios for the management of resource revenues are scrutinized. An altruistic mode, which implies a pure redistribution of the revenues among the poor swaths of the population, protracts the process of economic modernization, requires a greater amount of capital stock, and harbors a greater risk of a poverty trap. This effect is less pronounced if the modern sector is more capital‐intensive. A productive mode, which elicits full reinvestment of the commodity revenues, in contrast, accelerates the pace of economic modernization. Further, predicated on the scrutiny of a more realistic scenario, a bargaining mode, the study derives the condition for a net positive (or negative) modernization effect. The study identifies technical progress alongside capital accumulation as a further important source of economic modernization.