Forecasting Austrian national elections: The Grand Coalition model

Forecasting the outcomes of national elections has become established practice in several democracies. In the present paper, we develop an economic voting model for forecasting the future success of the Austrian ‘grand coalition’, i.e., the joint electoral success of the two mainstream parties SPOE and OEVP, at the 2013 Austrian Parliamentary Elections. Our main argument is that the success of both parties is strongly tied to the accomplishments of the Austrian system of corporatism, that is, the Social Partnership (Sozialpartnerschaft  ), in providing economic prosperity. Using data from Austrian national elections between 1953 and 2008 (n=18$n=18$), we rely on the following predictors in our forecasting model: (1) unemployment rates, (2) previous incumbency of the two parties, and (3) dealignment over time. We conclude that, in general, the two mainstream parties benefit considerably from low unemployment rates, and are weakened whenever they have previously formed a coalition government. Further, we show that they have gradually been losing a good share of their voter basis over recent decades.     

Relative performance of judgmental methods for forecasting the success of megaprojects

Forecasting the success of megaprojects, such as the Olympic Games or space exploration missions, is a very difficult but important task, due to their complexity and the large capital investment they require. Typically, megaproject stakeholders do not employ formal forecasting methods, but instead rely on impact assessments and/or cost–benefit analysis; however, as these tools do not necessarily include forecasts, there is no accountability. This study evaluates the effectiveness of judgmental methods for successfully forecasting the accomplishment of specific megaproject objectives, where the measure of success is the collective accomplishment of such objectives. We compare the performances of three judgmental methods used by a group of 69 semi-experts: unaided judgement (UJ), semi-structured analogies (s-SA), and interaction groups (IG). The empirical evidence reveals that the use of s-SA leads to accuracy improvements relative to UJ. These improvements are amplified further when we introduce the pooling of analogies through teamwork in IG.     

Stability in the inefficient use of forecasting systems: A case study in a supply chain company

Computer-based demand forecasting systems have been widely adopted in supply chain companies, but little research has studied how these systems are actually used in the forecasting process. We report the findings of a case study of demand forecasting in a pharmaceutical company over a 15-year period. At the start of the study, managers believed that they were making extensive use of their forecasting system that was marketed based on the accuracy of its advanced statistical methods. Yet most forecasts were obtained using the system’s facility for judgmentally overriding the automatic statistical forecasts. Carrying out the judgmental interventions involved considerable management effort as part of a sales & operations planning (S&OP) process, yet these often only served to reduce forecast accuracy. This study uses observations of the forecasting process, interviews with participants and data on the accuracy of forecasts to investigate why the managers continued to use non-normative forecasting practices for many years despite the potential economic benefits that could be achieved through change. The reasons for the longevity of these practices are examined both from the perspective of the individual forecaster and the organization as a whole.     

Community Inclusion under Systemic Inequality: How For-Profit Businesses Pursue Social Purpose

In countries where systemic inequality is pervasive, purposeful businesses that assume wider societal responsibilities try to counteract its effects by including marginalized social groups in their value creation processes. While current research documents a variety of business approaches for community inclusion, the nature, drivers and effectiveness of these inclusionary practices are not fully understood. We develop and empirically validate a framework of community inclusion that explicates the mechanisms through which purposeful businesses generate civic wealth – or economic and social benefits – to disadvantaged community groups. We differentiate between commercial practices that recast existent firm-centric processes towards creating value for marginalized groups and collaborative practices that aim to devise novel, participatory processes for engaging marginalized groups. Analysis of primary data from a sample of 430 small businesses in seven African countries confirms that the effect of social purpose on civic wealth is partially mediated by the two inclusionary practices. Businesses are more likely to extend the scope of their inclusion through collaborative practices when they receive favourable external validation and when institutional voids are low. We contribute to the literature by documenting the role of social purpose in motivating the pursuit of community-level goals and by unpacking the specific inclusionary practices used to achieve them.     

HRM and disenfranchisement: Working beyond organizational boundaries to tackle societal barriers

From a practical perspective, employers have the potential to serve as an important societal mechanism for tackling grand challenges like disenfranchisement because they wield significant financial, social, human, and political capital. We posit that they may also have an obligation to take positive action to help solve issues in the community in which they operate. One of the main ways in which employers interact with society is through the labor market, as represented by the human resource management (HRM) function. We believe that HRM has significant capacity for addressing disenfranchisement beyond the boundaries of the organization through both functional and normative policies and programs. Based on recent ethics-HRM scholarship, we go beyond the typical business case approach to present a moral argument based in utilitarian and universal theoretical perspectives for why employers should seek to mitigate the impact of George et al.'s (2016) four societal barriers that lead to disenfranchisement. We build a 2 × 3 matrix model based on HRM's societal support role (Podgorodnichenko, Edgar, & McAndrew, 2020), as well as pictorial models, that provides practical recommendations related to the HRM responsibility areas of staffing, compensation, and training and development designed to prevent disenfranchisement.     

Incorporating sustainability criteria into credit risk management

Does a commercial debtor's economic, environmental and social performance in terms of sustainability affect its credit risk rating? Does adding criteria aimed at assessing a lender's environmental, social or sustainability practices provide added value to traditional financial rating criteria? Many analyses have reported that a correlation exists between companies' environmental and their financial performance. We checked out the assertion that it ‘pays to be sustainable’ by analyzing the role that criteria pertaining to sustainability and environmental orientation play in the commercial credit risk management process. Our results show that sustainability criteria can be used to predict the financial performance of a debtor and improve the predictive validity of the credit rating process. We conclude that the sustainability a firm demonstrates influences its creditworthiness as part of its financial performance. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment.     

现代医院财务管理工作的思考

从现代医院财务管理的重要意义及工作目标出发,分析了目前医院财务管理工作的普遍问题及原因,并结合笔者的实际工作经验,提出了加强现代医院财务工作的具体措施,以做到确立财务管理在医院管理工作中的核心地位,实现市场经济下,医院经济效益与社会效益的最大化。     

Forecasting with gradient boosted trees: augmentation,tuning, and cross-validation strategies: Winning solution to the M5 Uncertainty competition

Deep neural networks and gradient boosted tree models have swept across the field of machine learning over the past decade, producing across-the-board advances in performance. The ability of these methods to capture feature interactions and nonlinearities makes them exceptionally powerful and, at the same time, prone to overfitting, leakage, and a lack of generalization in domains with target non-stationarity and collinearity, such as time-series forecasting. We offer guidance to address these difficulties and provide a framework that maximizes the chances of predictions that generalize well and deliver state-of-the-art performance. The techniques we offer for cross-validation, augmentation, and parameter tuning have been used to win several major time-series forecasting competitions—including the M5 Forecasting Uncertainty competition and the Kaggle COVID19 Forecasting series—and, with the proper theoretical grounding, constitute the current best practices in time-series forecasting.     

Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective

Forecasting election results has been a highly attractive activity among political and social scientists. Different forecasting methods have been proposed, but those based on public opinion polls are the most common. However, there are challenges to using opinion polls, especially because they neglect undecided voters. Due to the significant number of undecided participants and their impact on voting outcomes, we analyze the potential behavior of undecided voters by considering opinion polls and sentiment based on voter expectation from the perspective of the bandwagon effect and the spiral of silence. We establish a hierarchical Bayesian forecasting model to predict voting results, and apply it to the 2016 United States presidential election and the 2016 Brexit referendum. The results of our model suggest that voting outcomes are more predictable when fully utilizing the impact of undecided voters. The results indicate that integrating aggregated polls into the hierarchical Bayesian framework is a strong predictor for forecasting outcomes, and they provide evidence for the influence of sentiment based on voter expectation in forecasting election results.     

Financial nowcasts and their usefulness in macroeconomic forecasting

Financial data often contain information that is helpful for macroeconomic forecasting, while multi-step forecast accuracy benefits from incorporating good nowcasts of macroeconomic variables. This paper considers the usefulness of financial nowcasts for making conditional forecasts of macroeconomic variables with quarterly Bayesian vector autoregressions (BVARs). When nowcasting quarterly financial variables’ values, we find that taking the average of the available daily data and a daily random walk forecast to complete the quarter typically outperforms other nowcasting approaches. Using real-time data, we find gains in out-of-sample forecast accuracy from the inclusion of financial nowcasts relative to unconditional forecasts, with further gains from the incorporation of nowcasts of macroeconomic variables. Conditional forecasts from quarterly BVARs augmented with financial nowcasts rival the forecast accuracy of mixed-frequency dynamic factor models and mixed-data sampling (MIDAS) models.     

Profit, productivity and distribution: Differences across organizational forms - The case of Spanish banks

We examine variations in financial and economic performance as a function of organizational form, and, over time. The forms we consider include Spanish commercial banks, savings banks, and financial cooperatives. We decompose multilateral variation in operating profit, our measure of financial performance, into price and quantity effects. We then decompose the latter into a margin effect and productivity change. Our measure of economic performance, productivity variation, is subsequently disaggregated into technical, cost efficiency, and scale. We find that deregulation and liberalization have acted to narrow performance gaps among organizational forms; this, despite less-than compelling evidence that increased competition has contributed to this convergence. For the Spanish banking system as a whole, the margin effect appears to deliver twice as much financial benefit as do improvements in productivity. Importantly, this finding does not vary across organizational form. Such regularity has an important implication: Incentives for growth are apparently provided by a positive margin rather than by the more elusive benefits of economies of scale and improved cost efficiency.     

Forecasting in humanitarian operations: Literature review and research needs

Forecasting research in the humanitarian context is scarce. In this literature review, our goal is not only to show why forecasting research is important for the humanitarian sector, but also to identify what has been done so far, and where are the needs for further research. We conducted a structured literature search in Scopus, Web of Science, ABI Inform, and Google Scholar resulted in only 38 papers published between 1990 and 2018. Based on our findings we highlight three case studies as exemplary research in forecasting within the humanitarian context and list seven future research streams with specific research needs identified in each stream.     

旧城区文物建筑再利用的可行性探讨——以北京段祺瑞府旧址为例

由于各种历史原因,中国现存的旧城区文物建筑缺乏有效的政策引导和必要的资金保障,普遍存在日趋衰败的现象。文章以段祺瑞府旧址为例,对衰败原因进行调研分析,探讨保护性再利用的可行性,并从建筑保护、城市发展等不同层面,提出了在保护文物建筑的前提下,一系列改造再利用的方法和经营策略,意在探寻一条保护历史文脉与当今城市发展相结合的新道路,并使其带来良好的社会效益和经济效益。     

Forecasting by factors,by variables,by both or neither?

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation. A forecast-error taxonomy for factor models highlights the impacts of location shifts on forecast-error biases. Forecasting US GDP over 1-, 4- and 8-step horizons using the dataset from Stock and Watson (2009) updated to 2011:2 shows factor models are more useful for nowcasting or short-term forecasting, but their relative performance declines as the forecast horizon increases. Forecasts for GDP levels highlight the need for robust strategies, such as intercept corrections or differencing, when location shifts occur as in the recent financial crisis.     

基于多级模糊综合评价法的房地产企业财务预警研究

随着国内经济形势的不断变化和国家房地产相关政策的出台,房地产企业在经营中各种不确定因素不断增加,财务风险也与日俱增。房地产企业的财务风险具有模糊性和复杂性,它受到财务和非财务等多种因素的影响。以财务指标为变量建立的预警模型无法全面预测企业的财务风险。为提高财务预警系统的有效性,本文以房地产企业这一微观群体为视角,在以财务指标为主体的财务预警系统基础上,结合房地产企业的特征选取非财务指标,对影响房地产企业财务预警的非财务指标进行分层研究,运用多级模糊综合评价法构建房地产企业的财务预警模型。这将对房地产企业构建财务预警体系大有裨益。     

Balancing dual missions for social venture growth: a comparative case study

ABSTRACT

Balancing social and economic missions in the pursuit of growth is one of the greatest challenges faced by social ventures. Although social ventures strive for growth to scale their social impact, pursuing growth often results in mission drift and the sacrifice of social objectives, which in turn eventually undermine the ventures’ raison d’être. In this study, we investigate how and with what outcomes social ventures that pursue growth can manage the balance of social and economic missions. Through a comparative case study of six for-profit social ventures, we find significant differences in how dual missions are selected, connected, and intertwined, leading to varying degrees of mission spillover effects between social and economic missions. Our findings show that two-sided mission spillover effects are a central mechanism in dual mission management, enabling social ventures to pursue balanced growth, avoid mission drift, and achieve social impact. With these findings, this study adds to the emergent literature on social entrepreneurship, dual mission management, and social venture growth.     

Environmental Upgrading of Developing Country Firms in Global Value Chains

While the strategic management literature on corporate social responsibility (CSR) is abundant, it tends to consider the context of developed countries, with a focus on certain specific issues such as the strategic behaviour of firms with regard to sustainable development and the economic benefits of CSR practices. The present study examines the influence of western organizations on responsible corporate behaviour in developing countries, an issue that has been somewhat neglected in the existing academic literature. In particular, it explores the environmental upgrading of developing country firms in global value chains. This research, conducted with the analytic hierarchy process (AHP) method, involves 24 Tunisian olive oil companies. The findings indicate that exporting companies have indeed benefited from environmental upgrading, but, because of the cooperation strategy adopted by leading western firms (imposition of standards) and the absence of financial and technical assistance, the extent of environmental upgrading remains limited. Copyright © 2015 John Wiley & Sons, Ltd and ERP Environment     

浅谈财务分析指标在中小企业中的运用

在竞争日益激烈的市场经济中,经济活动追求实现经济利润最大化的目标。多年来,企业财务分析指标体系作为企业信息分析的重要资源,为企业决策者提供财务分析数据资料,做出科学的决策,把握正确的企业发展方向,实现经济效益最大化的目标,发挥了支撑和保障作用。因此,充实和完善适应现代经济发展需求的中小企业财务分析指标体系就显现出紧迫性和必要性。     

No excuses: forecasting can be managed

Originally written for manufacturers, the forecasting concepts presented in this article are easily applied to a hospital or health care facility with a supply function or central distribution center. Forecasting can offer a method of managing the control of medical supplies, pharmaceuticals, or maintenance items. A statistical based forecasting approach with seasonality testing could be useful in analyzing patient census data, calculating trends, and then recommending staffing levels. Cost containment and efficiency of operations are priorities in any industry. Forecasting the demand of medical supplies and services in today's hectic health care environment can have a significant effect on both customer service and financial results. The bottom line is happy patients and healthy profits.     

Public entrepreneurship: desiring social change,creating sociality

In this paper we want to affirm the desiring-social-change that we find in practices presently represented by theorists and policy-makers as examples of ‘social entrepreneurship’ (SE). We do this as an attempt to intensify the presence of the social and sociality in today's discourse on the entrepreneurship–society relationship. SE, as all entrepreneurship practices, operates by social and economic forces (limiting ourselves to those here), and generates social and economic outcomes (amongst others). Its second half, however, dominates the concept of SE, and our analysis seek to remedy this imbalance by focusing on the social productivity of entrepreneurship, on entrepreneurship desiring social change. We suggest ‘public entrepreneurship’ might grasp this as a more balanced concept that will also support a more precise analysis of the entrepreneurship–society relationship.