Understanding the dynamics of the quality of airline service attributes: Satisfiers and dissatisfiers

This research aims to determine the relationship between the quality of airline service attributes and overall satisfaction. Although a number of relevant studies have reported a linear relationship (or symmetric effect) between the two concepts, this work suggests that attribute quality exerts heterogeneous effects on satisfaction or dissatisfaction. A total of 157,035 consumer data from online reviews have been analyzed to achieve the research objective. In accordance with Herzberg, Mausner, and Snyderman’s (1959) two-factor theory, the findings of this research have determined that the quality of certain service attributes, such as cleanliness, food and beverages, and in-flight entertainment, affects the variations of positive ratings as a satisfier. Other airline service attributes, such as customer service and check-in and boarding, influence the deviations of negative ratings as a dissatisfier. Apart from airline attributes, the individual features and types of airline products have been estimated to improve the understanding of such relationships. In this regard, this study provides important implications to customer-centric marketing in an airline marketplace.     

基于人工神经网络的互联网公司估值方法研究

资本市场认为互联网公司市值的驱动因素应包括盈利因子、运营因子、流量因子和协同因子。将协同效应指标考虑到公司估值体系中,意图构造互联网公司优化估值模型。使用美股上市的互联网企业数据建立了评价指标体系,通过因子分析实现了二级指标降维,通过实证分析确认了四个因子与公司市值的相关关系,最后构建了基于人工神经网络BP算法的互联网公司估值模型,通过预测数据的检验发现模型的准确度较高。随着2018年互联网公司美股上市潮的持续,该模型能有效为资本市场估值提供参考。     

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.     

The role of relationship quality in raising organizational change acceptance: The case of the Greek hotel industry

This study examines whether the quality of an employee's relationships, within the context of the hotel industry, has an influence on their behavioral intention towards organizational change. The researchers suggest that the quality of relationships is an important element of an individual's social capital and can be evaluated using five key dimensions: the extent to which relationships are tangible, responsive and reliable, as well as the extent to which they offer empathy and assurance. Furthermore, this research examines whether organizational commitment and job satisfaction have an effect on the association between relationship quality and an individual's behavioral intention towards organizational change. The data collected from a sample of 100 hotel employees in Thessaloniki, Greece, show that relationship quality has a positive association with an individual's behavioral intention towards change. Additional results highlight the roles of job satisfaction and organizational commitment as mediating variables. Managerial implications relevant to the findings and pathways for further research are also discussed.     

The digital transformation of business models in the creative industries: A holistic framework and emerging trends

This paper examines how digital technologies facilitate business model innovations in the creative industries. Through a systematic literature review, a holistic business model framework is developed, which is then used to analyse the empirical evidence from the creative industries. The research found that digital technologies have facilitated pervasive changes in business models, and some significant trends have emerged. However, the reconfigured business models are often not ‘new’ in the unprecedented sense. Business model innovations are primarily reflected in using digital technologies to enable the deployment of a wider range of business models than previously available to a firm. A significant emerging trend is the increasing adoption of multiple business models as a portfolio within one firm. This is happening in firms of all sizes, when one firm uses multiple business models to serve different markets segments, sell different products, or engage with multi-sided markets, or to use different business models over time. The holistic business model framework is refined and extended through a recursive learning process, which can serve both as a cognitive instrument for understanding business models and a planning tool for business model innovations. The paper contributes to our understanding of the theory of business models and how digital technologies facilitate business model innovations in the creative industries. Three new themes for future research are highlighted.     

Incorporating textual information in customer churn prediction models based on a convolutional neural network

This study investigates the value added by incorporating textual data into customer churn prediction (CCP) models. It extends the previous literature by benchmarking convolutional neural networks (CNNs) against current best practices for analyzing textual data in CCP, and, using real life data from a European financial services provider, validates a framework that explains how textual data can be incorporated in a predictive model. First, the results confirm previous research showing that the inclusion of textual data in a CCP model improves its predictive performance. Second, CNNs outperform current best practices for text mining in CCP. Third, textual data are an important source of data for CCP, but unstructured textual data alone cannot create churn prediction models that are competitive with models that use traditional structured data. A calculation of the additional profit obtained from a customer retention campaign through the inclusion of textual information can be used by practitioners directly to help them make more informed decisions on whether to invest in text mining.     

Pains and gains of environmental management system certification for the sustainable development of manufacturing companies: Heterogeneous effects of industry peer learning

Environmental sustainability is a growing global concern. Environmental management systems (EMS) could be an effective strategic tool to help firms deal with their sustainable development. However, whether EMS certification pays off financially and how it takes effect can be debated. Thus far, these questions remain largely under‐researched. In particular, the effects of EMS certification on financial performance are inconclusive, and the reasons explaining the effects are underdeveloped. This study aims to enrich the current research by exploring the mediating and moderating roles from the perspective of cost‐efficiency trade‐offs to reveal how EMS certification affects financial performance. Applying a PROCESS procedure analysis and causal mediation analysis to a sample of 1,751 Chinese listed manufacturing firms from 2008 to 2016, this study shows that the effect of EMS certification on firms' financial performance is insignificant because their operating costs burden increases while their marketing efficiency and managerial efficiency improve. For the first time, this study demonstrates the moderating role of industry peer learning, as the mediating effects decrease with the growth of industry peer learning.     

Environmental policies,national culture,and stock price crash risk: Evidence from renewable energy firms

This study investigates the impact of country‐level environmental performance and national culture on the stock price crash risk of renewable energy firms. Employing a large sample of 626 renewable energy firms across 31 countries, we find a significant nonlinear relationship between country‐level environmental performance and crash risk. National culture dimensions are found to strongly predict the crash risk of renewable energy firms, particularly after the global financial crisis. On the contrary, national culture dimensions and environmental policies are observed to not exert any significance in explaining the crash risk of fossil fuel firms. Our results are robust with respect to alternative measures of stock price crash risk and the endogeneity of national culture dimensions. Overall, the findings of this paper contribute to the environmental economics literature by providing new evidence regarding the role of societal and environmental factors in explaining the stock price crash risk of energy firms.     

基于BP人工神经网络中国光伏产业贸易摩擦预警研究

建立有效的贸易摩擦预警系统有利于中国新兴产业的健康发展,有利于中国实施制造强国战略。将警兆信号法与人工神经网络相结合,从宏观经济形势、产业供给能力、双边贸易状况、市场需求水平等四个维度切入,构建了中国光伏产品出口贸易摩擦预警系统模型。预警分析表明,模型的预警效果与现实拟合较好,具有可行性。从模型的预警结果来看,2019年~2020年中国输美光伏产品贸易摩擦警情均低于轻警级别,仍面临一定的贸易摩擦风险。     

中美贸易关系新形势下中国先进制造业升级路径研究

先进制造业是一国工业实力和竞争力的直接体现。目前,在中国先进制造业中,装备制造业竞争力明显提升、高技术制造业发展迅速、先进制造业出现集群式发展,但仍然存在创新能力较低、核心技术和零部件研发能力不强、先进制造业企业竞争力不强、缺乏有利的先进制造业发展环境等问题。应采取给予先进制造业发展更大的支持力度、坚持技术引进与自主创新融合、强化先进制造业的区域合作、引导企业提高自主创新能力等措施,推动中国先进制造业持续健康发展。