Cross-national differences in stakeholder management: Applying institutional theory and comparative capitalism framework

Drawing upon the research in institutional theory and comparative capitalism, the present study investigates how cross-national differences in the political, business, and economic institutional contexts of the United States, Italy, and Japan are associated with the ways in which companies in each of these countries prioritize and engage in their stakeholder engagement activities (SEAs). Using Porter and Kramer's framework, which classifies corporate social responsibility (CSR) activities as falling into four categories (good citizenship, mitigating harm from value chain, transforming value chain activities, and strategic philanthropy), we investigate how companies in the United States, Japan, and Italy prioritize and engage in these four SEAs. An analysis of data collected from 340 companies across these countries reveals that while companies in each of these three countries undertake the four types of SEAs, the prioritization and prevalence of the four types of SEAs vary from one country to the other, in ways that align with the prevailing institutional contexts of each country. The results contribute to a more nuanced understanding of why and how companies' approaches to CSR differ across countries. From a practitioner's perspective, the findings highlight the cultural specificity of CSR, implying that despite the global nature of CSR, the implementation of CSR needs to be tailored to a country's context.     

Crisis leadership in economic recession: A three-barrier approach to offset external constraints

An economic recession is a type of crisis originated from external factors that may imperil an organization’s survival depending on the intensity and duration of the crisis. In peripheral European countries, such as Portugal, the recent financial crisis had devastating effects on various business activities. As a result, Portugal represents an important case study in examining how some corporate leaders have handled the economic recession successfully. I interviewed 20 corporate managers to capture their perceptions of the leadership traits and behaviors exhibited by their CEOs in guiding their companies through the recession. In economic recessions, negative constraints do not affect the most effective leaders, who instead erect barriers against the high-pressure conditions to create a supportive, positive work environment. In order to achieve maximum effectiveness, leaders must act as blocking agents against the negative social impacts of the economic crisis, including the fragility of trust in organizational life (i.e., a barrier against distrust), uncertainty of the future (i.e., a barrier against uncertainty), and toxic emotions (i.e., a barrier against toxic emotions).     

Forecasting unknown-unknowns by boosting the risk radar within the risk intelligent organisation

This theoretical perspective paper interprets (un)known-(un)known risk quadrants as being formed from both abstract and concrete risk knowledge. It shows that these quadrants are useful for categorising risk forecasting challenges against the levels of abstract and concrete risk knowledge that are typically available, as well as for measuring perceived levels of abstract and concrete risk knowledge available for forecasting in psychometric research. Drawing on cybersecurity risk examples, a case is made for refocusing risk management forecasting efforts towards changing unknown-unknowns into known-knowns. We propose that this be achieved by developing the ‘boosted risk radar’ as organisational practice, where suitably ‘risk intelligent’ managers gather ‘risk intelligence information’, such that the ‘risk intelligent organisation’ can purposefully co-develop both abstract and concrete risk forecasting knowledge. We also illustrate what this can entail in simple practical terms within organisations.     

Change within purchasing and supply management organisations – Assessing the claims from maturity models

It is a wide-held assumption that professional development and change within purchasing and supply management (PSM) organisations can be explained and guided by a maturity model. In this paper the guidance which the maturity model concept offers to understand a PSM organisation's performance is assessed. The methodology is based on the outcomes of a literature review of PSM maturity models, development of an organisational change framework and the learning from three qualitative case studies. An alternative understanding of the development of the PSM organisation is offered through an organisational change framework, composing 1) movement transitions, 2) scalability of change, 3) acceptability of change, and 4) the substantive element of change. The research found that extant PSM maturity models are too rigid for PSM managers to apply, and although maturity models are commonly accepted in PSM literature, in practice, they may produce the opposite effect of what is promised. The PSM maturity models suggest that their application will lead to increased status and influence of PSM within the organisation; expectations that may not be met. PSM organisations’ change processes are subjected to a range of situational and contextual power relations which must be considered in order to advance the specific PSM organisation roles and responsibilities.     

我国“一带一路”沿线地区风险投资时空分布及影响因素研究

深入分析我国“一带一路”沿线地区风险投资时空格局及影响因素，有助于促进创新创业与企业发展、提高区域科技创新水平。运用空间分析方法和空间计量模型，对2003-2018年我国“一带一路”沿线139个城市风险投资的时空分布特征及影响因素进行分析，结果表明：①沿线地区的风险投资发展具有不均衡性，呈现为沿海高、西部低的分异格局；②风险投资的全局自相关系数均为正，呈现出明显的空间集聚特征；③风险投资机构数、国家高新区数量、风险投资退出、政府引导基金发展、财政科技支出对区域风险投资具有显著促进作用，环境污染对风险投资有一定抑制作用。随着ESG投资理念逐渐获得认可，沿线地区可以通过提升绿色发展水平促进风险投资发展。     

中国高端装备制造业自主技术创新效率稳定性及影响因素研究

在全面实施创新驱动发展战略的时代背景下，揭示中国高端装备制造业自主技术创新效率稳定性，测度相关因素的影响强度与方向，对揭示中国高端装备制造业自主技术创新规律，制定其发展策略具有重要指导意义。聚焦中国高端装备制造业自主技术创新效率稳定性及影响因素，采用DEA-Malmquist指数方法和Tobit回归模型进行实证研究，结果表明，中国高端装备制造业自主技术创新效率存在一定波动性，且各细分行业技术创新效率内部稳定性较差，产业自主技术创新效率整体稳定性不高；自主技术创新投入因素和环境影响因素对产业自主技术创新效率的影响具有较高的异质性，其中创新资金投入和人力资源投入对自主技术创新综合效率、纯技术效率及规模效率具有正向影响，而新产品开发投入和企业规模对自主技术创新综合效率、纯技术效率和规模效率的影响具有异质性，政策因素与市场因素分别具有显著和非显著负向影响，外源性创新因素具有显著正向影响，且影响强度较大。在此基础上，提出调整政府对高端装备制造业创新支持模式、加强外源性创新与智力引进等策略建议。     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.     

异质机构持股、政府补贴与企业技术创新

机构投资者与政府补贴等优惠政策作为企业经营的重要资本来源和制度保障，势必对企业技术创新产生重要影响。以我国沪深两市战略性新兴上市企业2010-2015年面板数据为研究样本，对异质机构持股、政府补贴与企业技术创新的关系进行实证分析。结果发现：机构持股对企业技术创新没有显著影响，政府补贴可以促进机构持股对企业技术创新尤其是实质性技术创新产生显著正向影响；基金持股对企业技术创新存在显著负向影响，券商持股与QFII持股对企业技术创新分别存在不显著和显著正向影响；政府补贴能够降低基金持股对企业技术创新的负向影响，有效促进基金持股对企业技术创新的正向影响，并通过调节作用促进券商持股和QFII持股对企业技术创新产生更加显著的正向效应；政府补贴对基金持股与企业非实质性技术创新关系的正向调节作用更加显著，对券商持股和QFII持股与企业实质性技术创新关系的正向调节作用更加显著。     

Deep learning for modeling the collection rate for third-party buyers

This study evaluates a wide range of machine learning techniques such as deep learning, boosting, and support vector regression to predict the collection rate of more than 65,000 defaulted consumer credits from the telecommunications sector that were bought by a German third-party company. Weighted performance measures were defined based on the value of exposure at default for comparing collection rate models. The approach proposed in this paper is useful for a third-party company in managing the risk of a portfolio of defaulted credit that it purchases. The main finding is that one of the machine learning models we investigate, the deep learning model, performs significantly better out-of-sample than all other methods that can be used by an acquirer of defaulted credits based on weighted-performance measures. By using unweighted performance measures, deep learning and boosting perform similarly. Moreover, we find that using a training set with a larger proportion of the dataset does not improve prediction accuracy significantly when deep learning is used. The general conclusion is that deep learning is a potentially performance-enhancing tool for credit risk management.     

Twenty-Five Years after the Fall of the Berlin Wall: An Empirical Revisit of West German Consumers' Attitudes Toward Products and Brands from Former East Germany

More than 25 years after the German reunification, data show that products/brands from the eastern regions of Germany (“Neue Länder”) still do not have significant shares in the country's western part (“Alte Länder”). To analyze potential reasons for this phenomenon, our current study replicates a previous study that investigated selected attitudes of Alte Länder consumers toward products/brands from the Neue Länder. It is shown that factors such as consumer ethnocentrism, product judgment, willingness to buy, and economic animosity continue to influence consumer behavior and as such our study offers potential explanation for the failure of Neue Länder products/brands in the western regions of Germany.