互联网背景下工商管理模式的创新发展研究

随着信息时代的到来,互联网技术在各个行业的应用也越来越普遍,这也为我国经济的发展提供了非常有利的条件。工商管理模式的创新实践是现代企业经营管理中的核心内容,工商管理模式将直接影响企业在日常经营中解决各种管理问题的效率,是企业稳定持续发展的重要指标。因此,企业的管理者应该合理地运用现代化信息技术,提升企业工商管理的水平,实现企业的健康稳定发展。     

Exploring the use of content analysis methodology in consumer research

Content analysis is a viable way to thematise consumer experiences. The purpose of this review study is to examine the use of content analysis in consumer research (1977–2017). The authors explore how content analysis has been used. The reviewed studies address consumer experiences. The results show that qualitative content analysis is not used as a method in its own right; it is more often applied as a supplement to quantitative testing. There is also a lack of rigorous reporting of methodologies in many studies. The systematic review provides four propositions, content analysis studies: 1) vary in execution and reporting; 2) have a tendency towards methodological vagueness; 3) do not apply content analysis as a sole method; 4) are versatile. The study can also serve as point of departure for novice researchers wishing to engage with content analysis research. We suggest that further research is needed to explore the use of qualitative methodologies in consumer research.     

Nowcasting and forecasting GDP in emerging markets using global financial and macroeconomic diffusion indexes

This paper contributes to the nascent literature on nowcasting and forecasting GDP in emerging market economies using big data methods. This is done by analyzing the usefulness of various dimension-reduction, machine learning and shrinkage methods, including sparse principal component analysis (SPCA), the elastic net, the least absolute shrinkage operator, and least angle regression when constructing predictions using latent global macroeconomic and financial factors (diffusion indexes) in a dynamic factor model (DFM). We also utilize a judgmental dimension-reduction method called the Bloomberg Relevance Index (BRI), which is an index that assigns a measure of importance to each variable in a dataset depending on the variable’s usage by market participants. Our empirical analysis shows that, when specified using dimension-reduction methods (particularly BRI and SPCA), DFMs yield superior predictions relative to both benchmark linear econometric models and simple DFMs. Moreover, global financial and macroeconomic (business cycle) diffusion indexes constructed using targeted predictors are found to be important in four of the five emerging market economies that we study (Brazil, Mexico, South Africa, and Turkey). These findings point to the importance of spillover effects across emerging market economies, and underscore the significance of characterizing such linkages parsimoniously when utilizing high-dimensional global datasets.     

All of work? All of life? Reconceptualising work‐life balance for the 21st century

This paper argues that the study of work‐life balance to date has, in the main, adopted a restricted conception of both “work” and “life”, which does not take account of recent developments in life worlds, working arrangements and employment relationships. “Life” has hitherto been viewed as largely comprising caring activities for dependent children, whereas “work” has been premised largely on a traditional model of work, characterised by full‐time, permanent employment with one employer and a conventional understanding of what work involves. This means that extant research and theory only provides a partial view of the work‐life needs and experiences of the workforce. In the paper, we propose extending conceptions of both work and life to incorporate different life worlds and social groups and different working arrangements and employment relationships.     

高职院校环境监测实践教学改革探索

本文分析了高职院校环境监测实践教学中存在的问题,从实践参与教学模式、实践教学方法及考核、评价方式等方面进行了一系列的探索和尝试。     

‘I didn't feel like I was alone anymore’: evaluating self‐organised employee coping practices conducted via Facebook

The long‐term fracturing of the labour movement has led to increased attention to employee coping practices under new management practices and labour processes. However, the literature caters little for the recent rise of employees taking to social networking sites (SNSs), such as Facebook, to find ways to cope with the pressures of contemporary employment. To explore the self‐organised coping qualities of SNSs, interviews were conducted with front line workers, employed by a large anti‐trade union US retailer, who contribute to a self‐organised Facebook group set up as a place for fellow employees to deal with collective employment‐related problems. The main findings suggest employee self‐organised Facebook groups represent an important development and extension to the coping practices available to individual and groups of employees. The main implication of the findings is that Facebook groups appear to strengthen and widen the options for employee resilience in an age of continuing trade union retreat.     

A comparison of programming languages in macroeconomics

We solve the stochastic neoclassical growth model, the workhorse of modern macroeconomics, using C++14, Fortran 2008, Java, Julia, Python, Matlab, Mathematica, and R. We implement the same algorithm, value function iteration, in each of the languages. We report the execution times of the codes in a Mac and in a Windows computer and briefly comment on the strengths and weaknesses of each language.     

Repeated moral hazard and recursive Lagrangeans

This paper shows how to solve dynamic agency models by extending recursive Lagrangean techniques à la Marcet and Marimon (2011) to problems with hidden actions. The method has many advantages with respect to the promised utilities approach (Abreu et al., 1990): it is a significant improvement in terms of simplicity, tractability and computational speed. Solutions can be easily computed for hidden actions models with several endogenous state variables and several agents, while the promised utilities approach becomes extremely difficult and computationally intensive even with just one state variable or two agents.     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.     

Using CRM to Model Firm Performance in a Business-to-Business Market

Customer relationship management (CRM) is the widely accepted approach for gathering, examining, understanding and translating information related to customers into managerial action. CRM is investigated in the context of new product performance (NPP). CRM enhances NPP as well as firm performance. This study investigates the impact of CRM on NPP through the moderation of top management support and an innovative culture, as well as the impact of CRM on firm performance through the mediation of NPP. A questionnaire survey is used for data collection from marketing managers of 159 firms in Pakistan in the B-to-B market. Hypotheses were tested using SEM in SMART PLS. This research shows that CRM directly affects firm performance, while NPP partially mediates the relationship of CRM and firm performance. These findings have significant implications for the practitioner. This study delivers insights to managers and academicians about the role of CRM in enhancing NPP and improving firm performance. In general, the study provides new insights into CRM by integrating top management support and an innovative culture. The research extends our understanding that top management support and innovative culture do not moderate the relationship of CRM with new product performance in a B-to-B context.