Selling Time: Swatch Group and the Global Watch Industry

This illustrative case analyzes and evaluates Swatch Group and its core competencies and global strategies in the changing and highly segmented watch industry. Originating from Switzerland, the Group is a major watch manufacturer in the world with a unique brand portfolio that includes low priced as well as luxury watches such as Breguet, Blancpain, Longines, Rado, Omega, and the like. Swatch Group, formerly known as Socitéde Microélectronique et d'Horlogerie (SMH), sells its products through 500 Swatch watch shops, uses 15,000 retailers and 1,000 shop‐in‐shops, and over 140 kiosks in global markets. The Group is vertically integrated and supplies virtually all the components and parts for its line of watches. In 2009, Swatch Group's sales stood at $5.37 billion and the company continues to be an entrepreneurial entity with efficient research and development (R&D), creating many technological breakthroughs and marketing campaigns. Swatch Group is expected to grow in the coming years although the 2008 financial crisis, competition, and changing markets remain some of the major hurdles for the company. The article ends with selected developments and future changes that may impact the company in the coming years. © 2012 Wiley Periodicals, Inc.     

Interactive Mining of Strong Friends from Social Networks and Its Applications in E-Commerce

Social networks are generally made of individuals who are linked by some types of interdependencies such as friendship. Most individuals in social networks have many linkages in terms of friends, connections, and/or followers. Among these linkages, some of them are stronger than others. For instance, some friends may be acquaintances of an individual, whereas others may be friends who care about him or her (e.g., who frequently post on his or her wall). In this study, we integrate data mining with social computing to form a social network mining algorithm, which helps the individual distinguish these strong friends from a large number of friends in a specific portion of the social networks in which he or she is interested. Moreover, our mining algorithm allows the individual to interactively change his or her mining parameters. Furthermore, we discuss applications of our social mining algorithm to organizational computing and e-commerce     

Determinants of employee willingness to use feedback for performance improvement: cultural and organizational interpretations

This study was designed to identify determinants of employee willingness to use feedback for performance improvement. The proposed determinants included objectives of appraisal, supervisor's knowledge of subordinate's job, agreed plan for performance improvement, trust in supervisor and perceived fairness and accuracy of performance evaluation. Data were collected in two phases. The first phase consisted of a questionnaire survey among 100 Hong Kong Chinese employees working in public and private sector organizations. Regression analysis of questionnaire data indicated that agreed plan for performance improvement and perceived fairness and accuracy of performance evaluation had significant positive effects on employee willingness to use performance feedback. In the second phase, focus group interviews were held to triangulate survey findings. Interview data suggested that Chinese cultural characteristics of paternalism and personalism influenced the underlying dynamics of the evaluation process. Findings are interpreted in the context of employees cultural and organizational background.     

Macroeconomic consequences of increased productivity in less developed economies

This paper examines the impact of improvements in productivity on prices, output, the real wage rate and the balance of payments. Within the context of the model used in this paper, an improvement in productivity can take two alternative forms: (1) a cost saving for a given output and (2) an increase in production without a direct decrease in employment. The results presented are based on a simple model of a small open economy that includes some key features of less developed economies. It is shown that, in the presence of monetary and fiscal restraints, an improvement in productivity leads to increases in output, employment and the real wage and the effect on the balance of payments, in the short and the medium runs, is also positive. We find that whether or not improvement in productivity is import saving plays a crucial role in both comparative static and simulation exercises.     

Engineered nanomaterials: risk perception,regulation and insurance

Concerns surrounding the health risk of engineered nanomaterials, effective regulation and the lack of specifically tailored insurance products for the nanotechnology sector are putting the industry’s long-term economic viability at risk. From the perspective of the underwriter, this article speculates on the relationship between risk perception, regulation and insurability. In the nanotechnology sector, regulators are currently failing to keep pace with innovation, and insurers generally lack guiding principles for underwriting occupational risk from nanomaterial exposure. Such vulnerabilities when combined with misguided risk perceptions can lead to the overpricing of risk transfer and ill-conceived regulatory initiatives, thus potentially exhausting resources and stifling innovation in the sector. In the absence of well-developed regulatory protocols, the insurance industry has, and will continue, to occupy a key role as an effective lobby in terms of improved risk management practice. We suggest that the insurance industry will increasingly rely on control banding frameworks and ‘risk mitigation at source’ methods developed in conjunction with their clients to manage severe acute diversifiable risks. Long tail risk will continue to represent a serious challenge to insurers and regulators. In the meantime, insurers will have to bridge their current needs with improvised solutions. As an example of one possible solution, we outline a framework that utilizes financial instruments to hedge an insurer’s exposure to uncertain estimates of these long-term risks.     

An Examination of Long-Term Abnormal Stock Returns and Operating Performance Following R&D Increases

We examine a sample of 8,313 cases, between 1951 and 2001, where firms unexpectedly increase their research and development (R&D) expenditures by a significant amount. We find consistent evidence of a misreaction, as manifested in the significantly positive abnormal stock returns that our sample firms' shareholders experience following these increases. We also find consistent evidence that our sample firms experience significantly positive long‐term abnormal operating performance following their R&D increases. Our findings suggest that R&D increases are beneficial investments, and that the market is slow to recognize the extent of this benefit (consistent with investor underreaction).     

Consumer intentions to engage in s-commerce: a cross-national study

Social media has reached global proportions; yet, little is known about how consumers engage with firms in ways that lead to social commerce (s-commerce) – an emerging area of importance in the literature. This study addresses this gap and extends previous research by examining factors that influence consumers’ intentions to engage in s-commerce in four countries: Chile, Spain, South Africa and Australia. Specifically, this study develops and tests a model of consumers’ intentions to engage in s-commerce through brands’ Facebook pages incorporating personal variables (involvement in brands’ products and services, satisfaction with brands’ Facebook page), trust variables (message credibility of Facebook posts, trust in firms’ Facebook) and social variables (peer communication, social media dependency, online social interaction propensity) on predicting intentions to purchase products and services through brands’ Facebook pages if s-commerce was available to them. The findings show that the main drivers of s-commerce engagement are message credibility, trust in the brands’ Facebook, involvement, peer communication and online social interaction propensity, as influencers of consumer satisfaction with brands’ Facebook and social media dependency, which in turn drive intentions to engage in s-commerce. Contributing to theory and practice, these relationships are discussed for the four countries involved in the study.     

Alibaba: Entrepreneurial growth and global expansion in B2B/B2C markets

The purpose of this case-based research is to analyze and discuss Alibaba Group (hereafter Alibaba) and its entrepreneurial growth and global expansion in B2B/B2C markets. The paper uses company and industry-specific data and surveys to analyze a fast growing Chinese B2B/B2C firm and its internationalization and expansion in global markets. Findings of the work reveal that in a short time, Alibaba has become a major entrepreneurial icon and global player and continues to grow worldwide because of its well-planned business initiatives and B2B/B2C-based business models. The paper also provides implications in the area of international entrepreneurship and its related areas. International entrepreneurs need to learn from Alibaba’s fast growing business model and dynamic growth because of its competitive platforms and Web-based strategies which helped the company to target small and medium-sized enterprises (SMEs) in global markets. Within the areas of international entrepreneurship and international business, the paper also provides discussion which deals with the changing e-commerce industry and its future growth and developments.     

The product life cycle and sample representativity bias in price indexes

Official price indexes are usually calculated using matched samples of products. If products exhibit systematic price trends at different points in their life cycle then matched sample methods may introduce bias if the life cycle movement in the sample does not adequately reflect that in the population. This article explores the extent of these life cycle pricing effects and then examines the bias it can introduce in measured inflation. A large US supermarket scanner data set for six cities and six products over 12 years is used. Using hedonic methods we find that the life cycle component of price change is important across a range of products and cities. To explore the bias introduced by these movements, we use simulations that construct indexes with different sample update frequency. For indexes that are never completely resampled, we find an annual absolute bias of 0.88 and 0.59 percentage points depending upon whether we use the actual prices or prices imputed from our hedonic model. This compares with absolute biases of 0.34 and 0.10 percentage points for the corresponding cases for samples, which are re-selected annually. Thus our results provide strong support for more frequently updating index samples.