Using a design structure matrix to support technology roadmapping for product–service systems

In light of the increasing trend of the use of the product–service system (PSS), tools that can help to analyse complex relationships among products, services and technologies and furthermore support decision-making during their planning are needed. To meet these needs, this study proposes a design structure matrix (DSM)-based technology roadmap (TRM) approach and a case study on mobile services is conducted. While PSS planning may involve a number of teams and organisations, the DSM-based TRM can help with such complex collaborative technology planning and hence lead to better performance. Methodologically, this is one of the first attempts to link DSM and TRM, both of which are widely used in planning stages, and thus is expected to contribute to the advances in TRM methodologies. In practice, this study describes an overall roadmapping process for the PSS, thus providing worthwhile guidelines available to organisations that are in charge of the TRM.     

Penalized h-likelihood approach for variable selection in AFT random-effect models

Survival models allowing for random effects (e.g., frailty models) have been widely used for analyzing clustered time-to-event data. Accelerated failure time (AFT) models with random effects are useful alternatives to frailty models. Because survival times are directly modeled, interpretation of the fixed and random effects is straightforward. Moreover, the fixed effect estimates are robust against various violations of the assumed model. In this paper, we propose a penalized h-likelihood (HL) procedure for variable selection of fixed effects in the AFT random-effect models. For the purpose of variable selection, we consider three penalty functions, namely, least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), and HL. We demonstrate via simulation studies that the proposed variable selection procedure is robust against the misspecification of the assumed model. The proposed method is illustrated using data from a bladder cancer clinical trial.     

Toward a circular economy: Understanding consumers' moral stance on corporations' and individuals' responsibilities in creating a circular fashion economy

For long, the fashion industry has adopted the linear economy's “take-make-use-throwaway” system, an approach that has adverse side effects, such as economic loss, environmental destruction, and threats to human society. To address these adverse consequences from fashion's linear system, governments and business leaders are advocating the societal need for a shift from the linear economy to the circular economy, which endorses the “take-make-use-reuse” system. Despite the growing demand for changing to a circular economy in the fashion business (circular fashion [CF]), two critical issues remain understudied in the current literature. First, although academic research on CF has increased in the past 5 years, the lack of scalable CF research has hindered the industry's ability to increase its adoption of a truly circular economy. Second, although the fashion industry faces complex challenges in instituting CF in that just one supply chain member's (a fashion retailer's) commitment is not sufficient to create a truly CF without the involvement of others (consumers), there is yet no empirical research that investigates whether consumers morally support the idea of a CF and feel obliged to take part in fashion businesses' CF offerings. Thus, we investigate whether and how morally grounded traits—corporate moral responsibility (H1+), consumer moral responsibility (H2+), their interaction effect (H3), and corporate hypocrisy (H4−)—influence consumers' attitudes and engagement (H5+) toward fashion corporations' CF offerings. Our empirical evidence, using a U.S. consumer survey dataset of 351 responses, shows that all of these hypotheses are supported. The results provide important theoretical and managerial implications.     

Credit ratings and convertible bond prices: a simulation-based valuation

This study presents a simulation-based model of convertible bond prices under the assumption of stochastic interest rates. The model is developed such that the convertible bond price explicitly depends on the credit rating at the time of issuance. Key ideas explored in this study include terminating the simulated sample path immediately when the issuer defaults on the bond at time t, which is the same as the investor and the issuer optimally exercising their options and discounting the resulting cash flows at a risk-free rate. In turn, the defaulted group of sample paths belongs to the bottom xth percentile of the realized stock prices at each time, which is exogenously given by the cumulative or marginal default probability of a firm that has the same rating as the issuer. Upon calibrating the model, we can see that the moneyness of convertible bonds is strongly responsible for influencing the convertible bond price when the rating changes. Furthermore, the effects of stochastic interest rates are shown to be possibly significant when the interest rate risk’s market price is not zero.     

An exploratory study of examining students’ expectations of training in a laboratory class: Factor analysis of affective heuristic features

When developing effective training programs, it is important to know students’ expectations of laboratory classes. The authors collected 170 surveys from students in one laboratory class to investigate the underlying dimensions of their expectations of training. Factor analysis identified the following six dimensions of students’ expectations: climate, courtesy, credibility, entertainment, relevance, and structure. These dimensions of training expectations were used to cluster students into two groups: serious and enthusiastic. Thereafter, these two clusters were compared using chi-square tests to determine whether there were statistical differences among them. The findings suggest instructors should consider students expectations to improve students’ learning from laboratory classes.     

MFN vs Tariff Discrimination in the Presence of Cross Ownership

We develop a three‐country two‐firm model to examine the superiority of most favored nation (MFN) vs tariff discrimination in global welfare by taking into account the cross ownership between exporters. We obtain several interesting results as follows. First, given cross ownership of financial interests and linear demand, the government of the importing country will impose a lower (higher) tariff on the low‐cost (high‐cost) firm and the global welfare under tariff discrimination will be higher than that under MFN, regardless of whether the mode of competition is Cournot or Bertrand competition, when the magnitude of cross ownership is relatively large compared with the cost difference. Second, given the cross ownership of corporate control and linear demand, the global welfare under tariff discrimination will be identical to that under MFN.     

Imperfect information and labor market bias against small and medium-sized enterprises: a Korean case

We examine the labor market’s bias against small and medium-sized enterprises focusing on the Seoul Digital Industrial Complex case. We adopt Heckman’s approach to control selection bias, and use primary data from questionnaire surveys conducted at both firm and employee levels. We find that conventional firm-specific factors, such as wages, fringe benefits, and weekly work hours, primarily explain the labor market bias, but imperfect information is also positively associated with the bias. For example, a firm’s inadequate ability to identify a pool of potential employee candidates or to provide them comprehensive firm- or job-specific information tends to worsen labor shortages, and an employee’s ex-ante incomplete knowledge of on-the-job training or education opportunities tends to increase ex-post turnover intentions. Our results suggest that reducing the market bias requires improving imperfect information as well as conventional firm-specific conditions.     

Are Investment Promotion Agencies Effective in Promoting Outward Foreign Direct Investment? The Cases of Japan and Korea

In this paper we examine the role of investment promotion agencies (IPA) in promoting outward foreign direct investment (FDI) from Japan and Korea. Looking at two home countries enables us to control for both country‐pair time‐invariant characteristics and host‐country time‐varying characteristics. Our empirical results suggest that home‐country IPA tend to be more effective in promoting outward FDI in politically risky host countries. However, this finding depends on whether the home‐country firm is listed or unlisted. More specifically, we find that the positive effect of home‐country IPA on outward FDI in politically risky countries is limited to unlisted home‐country firms, which tend to be less productive.     

Examining the international internet using multiple measures: new methods for measuring the communication base of globalized cyberspace

This article examines the network structure of the international internet using four different sources of data: (1) bilateral bandwidth between countries; (2) hyperlink connections among nations’ domain names; (3) structural equivalence of nations from the perspective of websites, measured by the percentage of specific websites’ traffic from individual countries; and (4) structural equivalence of nations from the national perspective, using the proportion of a country’s 100 most-visited websites shared with other countries. Results indicate that the international internet network appears to consist of series of small worlds determined by language, geography, and historical circumstances. Therefore, one cannot depict the internet only through an examination of the hyperlink connections among nations. There is a need for multiple indicators to accurately describe the global internet.