Comparing automated text classification methods

Online social media drive the growth of unstructured text data. Many marketing applications require structuring this data at scales non-accessible to human coding, e.g., to detect communication shifts in sentiment or other researcher-defined content categories. Several methods have been proposed to automatically classify unstructured text. This paper compares the performance of ten such approaches (five lexicon-based, five machine learning algorithms) across 41 social media datasets covering major social media platforms, various sample sizes, and languages. So far, marketing research relies predominantly on support vector machines (SVM) and Linguistic Inquiry and Word Count (LIWC). Across all tasks we study, either random forest (RF) or naive Bayes (NB) performs best in terms of correctly uncovering human intuition. In particular, RF exhibits consistently high performance for three-class sentiment, NB for small samples sizes. SVM never outperform the remaining methods. All lexicon-based approaches, LIWC in particular, perform poorly compared with machine learning. In some applications, accuracies only slightly exceed chance. Since additional considerations of text classification choice are also in favor of NB and RF, our results suggest that marketing research can benefit from considering these alternatives.     

Managing service employees: literature review,expert opinions,and research directions

This article reviews the service management and marketing literature on managing people with a particular emphasis on managerial relevance. This review explores the market and financial results of managing people effectively, emphasizing that it is probably harder to duplicate high-performing human assets than any other corporate resource. The challenges inherent in boundary-spanning frontline jobs are discussed, including role conflict and emotional labor. Next, recommended human resources (HR) strategies and practices related to recruitment, training, empowerment, service delivery teams, and employee motivation are reviewed. The literature review concludes with a section on service culture, climate, and leadership. Each section is complemented with further research suggestions that emerged from interviews with eight academic and practitioner experts. The last section outlines six themes for new research opportunities with high potential managerial relevance; they relate to (1) the financial impact of HR practices and strategies, (2) motivating service employees, (3) training, (4) emotional labor, (5) dealing with rude customers, and (6) the impact of technology on managing service employees.     

Modeling of CPDOs – Identifying optimal and implied leverage

When the subprime crisis started to emerge, collateralized products based on credit default swap (CDS) exposures combined with security features seemed to be a more rational alternative to classic asset backed securities. Constant Proportion Collateralized Debt Obligations (CPDOs) are a mixture of Collateralized Debt Obligations (CDOs) and CPPIs with inverse mechanism. This new asset aims at meeting the investors’ demand for credit derivatives with security enhancements, but to our knowledge quantitative approaches for pricing other than simulation algorithms do not exist yet. CPDOs became famous notably by Standard & Poor’s rating model error which illustrated that closed-form analytical pricing is necessary in order to evaluate and understand complex derivatives. This article aims to shed a light on CPDOs’ specific structural enhancements and mechanisms. We quantify inherent risks and provide a dynamic closed-form pricing formula.     

Staging of Venture Financing, Investor Opportunism and Patent Law

Abstract:  Stage financing provides a real option that is valuable when facing external uncertainty. However, it may also induce investor hold-up, if the property rights on an invention are not sufficiently protected. As a consequence, the entrepreneur may not work hard. Investor opportunism is less likely to occur, if investors' residual cash-flow-rights are contingent on verifiable 'milestones' in the previous stage. Equity-linked financing also provides high-powered incentives to the investor not to 'steal the idea' because his payoff becomes sensitive to the project value. The paper provides a new explanation for both types of contractual provisions.     

A number‐of‐modes reference rule for density estimation under multimodality

We consider kernel density estimation for univariate distributions. The question of interest is as follows: given that the data analyst has some background knowledge on the modality of the data (for instance, ‘data of this type are usually bimodal’), what is the adequate bandwidth to choose? We answer this question by extending Silverman's idea of ‘normal‐reference’ to that of ‘reference to a Gaussian mixture’. The concept is illustrated in the light of real data examples.     

Control and co-ordination of Japanese subsidiaries in China: problems of an expatriate-based management system

This paper analyses the international management control (IMC) system that Japanese multinational companies (MNCs) employ to co-ordinate the activities of their subsidiaries in China. It focuses on the role of Japanese expatriates in this IMC system and assesses their performance. In the process, it offers a comprehensive evaluation of the organizational fit of the Japanese IMC model within the current Chinese business environment. Taking Japanese firms as the subject, the analysis identifies areas of incongruity and explains the underlying reasons for problems with expatriate-focused IMC models. In doing so, this paper argues that the Japanese expatriate-based control system in China (as in many other parts of the world) continues to be characterized by an insider-outsider mentality that prevents a real internationalization of overseas operations in the 'transnational' sense.     

Siemens: Maßhalten beim Moralisieren

Ohne Zusammenfassung Prof. Dr. Jochen Zimmermann ist Professor für Betriebswirtschaftslehre an der Universit?t Bremen