Benefit segmentation of the container shipping market in Turkey

ABSTRACT

Marketing policies have gained more importance in container shipping as the industry experiences challenges arising from commoditization. Market segmentation is fundamental to marketing policies, yet it needs a detailed analysis in container shipping. Accordingly, this paper aims to explore homogenous customer groups in container shipping by conducting a segmentation analysis, which can help container lines apply more efficient marketing policies. A survey study is conducted on 356 shippers in Turkey. The study develops five reliable and valid selection criteria factors and applies cluster analysis based on the selection criteria factors. The cluster analysis produces a total of six benefit segments which are differentiable. The segments are significantly identified by the demographic characteristics of shippers. The paper suggests several implications for the marketing policies of container lines.     

数字图象识别技术综述

本文对图象传感器件、图象识别的基本方法、国家分割与图象特征提取等方面作了简要的评述,指出了图象识别技术所面临的问题及发展方向。     

Consumer intentions for alternative fuelled and autonomous vehicles: A segmentation analysis across six countries

Rapid advances in the development of autonomous and alternative-fuel vehicles (AFVs) are likely to transform the future of mobility and could bring benefits such as improved road safety and lower emissions. Achieving these potential benefits requires widespread consumer support for these disruptive technologies. To date, research to explore consumer perceptions of transport innovations has tended to consider them in isolation (e.g., driverless cars, electric vehicles). The current paper examines the predictors of consumer interest in and willing to pay for both AFVs and autonomous vehicles through a choice experiment conducted in six diverse markets: Germany, India, Japan, Sweden, UK and US. Using Latent Class Discrete Choice Models, we observe significant heterogeneity both within and across the country samples. For example, while Japanese consumers are generally willing to pay for autonomous vehicles, in most European countries, consumers need to be compensated for automation. Within countries, though, we found some segments – typically, those with a university degree, and self-identifying as having a pro-environmental identity and as being innovators– are more in favour of automation. Significantly, we also found that support for autonomous vehicles is associated with support for AFVs, perhaps, due to common demographic or socio-psychological predictors of both types of innovative technology. These findings are valuable for policymakers and the automotive industry in identifying potential early adopters, as well as consumer segments or cultures less convinced to adopt these innovative transport technologies.     

A line-based skid mark segmentation system using image-processing methods

We developed a line-based skid mark segmentation and measurement system to solve issues related to randomness from pavement texture and measurement subjectivity at car accident scenes. The system was designed to operate along the longer straight lines that exist in boundaries between skid marks and pavement at the scene of an accident. The operational system consists of two processes: preprocessing and feature extraction. Preprocessing steps include skid mark positioning, slope angle detection, and segmentation, whereas feature extraction involves detecting light striations, striation segmentation, and calculating the widths of striations from images. Experimental validation and objective measurements illustrate that this system saves operation time and cost while performing with accuracy similar to that of manual methods.