Ying Kei Tse

Managing product quality risk in a multi-tier global supply chain

A series of product harm scandals, ranging from toxic toys to peanut butter indicates that firms and consumers alike are vulnerable to quality risks in a global supply chain. The matter is exacerbated with a low ‘visibility’ of quality risks hidden in the multi-tier global supply networks. The threat of quality risks could be from raw materials, manufacturing processes, or logistics operations in any tier of the supply network. This research argues that better visibility of risk in supply tiers could minimise the quality threat. A product quality risk and visibility assessment framework, integrating both the incremental calculus and marginal analysis, is proposed. Case study results indicate that the proposed approach has the following benefits: (a) enables firms to have a better ‘visibility’ of quality risks in a multi-tier supply network; (b) allows firms to establish risk indices for product components; and (c) a traceable justification path for supplier selection.

A hybrid OLAP-association rule mining based quality management system for extracting defect patterns in the garment industry

In todays garment industry, garment defects have to be minimized so as to fulfill the expectations of demanding customers who seek products of high quality but low cost. However, without any data mining tools to manage massive data related to quality, it is difficult to investigate the hidden patterns among defects which are important information for improving the quality of garments. This paper presents a hybrid OLAP-association rule mining based quality management system (HQMS) to extract defect patterns in the garment industry. The mined results indicate the relationship between defects which serves as a reference for defect prediction, root cause identification and the formulation of proactive measures for quality improvement. Because real-time access to desirable information is crucial for survival under the severe competition, the system is equipped with Online Analytical Processing (OLAP) features so that manufacturers are able to explore the required data in a timely manner. The integration of OLAP and association rule mining allows data mining to be applied on a multidimensional basis. A pilot run of the HQMS is undertaken in a garment manufacturing company to demonstrate how OLAP and association rule mining are effective in discovering patterns among product defects. The results indicate that the HQMS contributes significantly to the formulation of quality improvement in the industry.

Embracing supply chain agility: an investigation in the electronics industry

Purpose – This paper aims to identify the antecedents of firm’s supply chain agility (SC agility) and how SC agility impacts on firm’s performance. Design/methodology/approach – Based on a comprehensive literature review, a conceptual model was proposed, in which the interrelated hypotheses were tested by structural equation modelling methodology using a dataset collected from 266 Chinese electronics firms. Findings – Initially, it was found that SC integration and external learning positively influenced SC agility. Second, the results indicated that firm’s performance is positively impacted by SC agility. Moreover, SC agility also fully mediated the effect of SC integration on firm’s performance and the effect of external learning on firm’s performance. Research limitations/implications – The generalizability of this research sample might be the major limitation of this study. Therefore, future research can adopt other industry sectors samples, such as automobile manufacturing, or other country samples t...

Using a fuzzy association rule mining approach to identify the financial data association

Highlights? We study Hong Kong Stock Exchange which was the second largest stock market in Asia up to 2010. ? We examine association of Hang Seng Index with other economics indices. ? Increasing RMB-HK exchange rate and export value will highly increase the variation of Hang Seng Index. ? Increasing RMB-HK exchange rate, export value and GDP will also highly increase the variation of Hang Seng Index. ? The minded rules reveal interesting patterns between different economical indices and the individual stock market price. In the rapidly changing financial market, investors always have difficulty in deciding the right time to trade. In order to enhance investment profitability, investors desire a decision support system. The proposed artificial intelligence methodology provides investors with the ability to learn the association among different parameters. After the associations are extracted, investors can apply the rules in their decision support systems. In this work, the model is built with the ultimate goal of predicting the level of the Hang Seng Index in Hong Kong. The movement of Hang Seng Index, which is associated with other economics indices including the gross domestic product (GDP) index, the consumer price index (CPI), the interest rate, and the export value of goods from Hong Kong, is learnt by the proposed method. The case study shows that the proposed method is a feasible way to provide decision support for investors who may not be able to identify the hidden rules between the Hang Seng Index and other economics indices.

Price determinants for remanufactured electronic products: a case study on eBay UK

In this paper, we analyse the market determinants of price differentials between new and remanufactured products in Electronics using data on purchases made on eBay UK. The empirical analysis is carried out by means of linear regression methods, which are capable of controlling for the presence of collinearity among the explanatory variables. Our empirical results suggest that the seller reputation, length of warranties, proxies of demand and supply of remanufactured products, duration, end day of product listings as well as the availability of return policies are important determinants of price differentials. Most importantly, we find that the seller identity plays an important role, as our empirical results are predominantly driven by transactions carried out by non-manufacturer-approved vendors.

Managing disruption risk in express logistics via proactive planning

Purpose – The purpose of this paper is to carry out a comprehensive review for state-of-the-art works in disruption risk management of express logistics mainly supported by air-transportation. The authors aim to suggest some new research directions and insights for express logistics practitioners to develop more robust planning in air-transportation. Design/methodology/approach – The authors mainly confined the research to papers published over the last two decades. The search process was conducted in two dimensions: horizontal and vertical. In the horizontal dimension, attention was paid to the evolution of disruption management across the timeline. In the vertical dimension, different foci and strategies of disruption management are employed to distinguish each article. Three keywords were used in the full text query: “Disruption management”, “Air transportation”, and “Airline Operations” in all database searches listed above. Duplications due to database overlap, articles other than those from academic...

Insight from the horsemeat scandal: Exploring the consumers’ opinion of tweets toward Tesco

– Social media has become an important part of daily interpersonal communication in contemporary society. The purpose of this paper is to explore the attitudes of UK consumers by identifying the hidden information in tweets, and provide a framework which can assist industry practitioners in managing social media data. , – Using a large-scale dataset of tweets relating to the Horsemeat scandal of 2013, a comprehensive data analysis framework, which comprises multidimensional scaling and sentiment analysis, alongside other methods, was applied to explore customers’ opinions. , – Making jokes in social media was a main trend in the tweets relating to Tesco during the Horsemeat scandal. Consumer sentiments were overall negative and burgers were the most mentioned product in the week-long period after the story broke. The posting of tweets was correlated with the timing of news coverage, which indicates that the traditional media is still crucial to public opinion formation. , – This paper presents a progressive tweet-mining framework that can serve as a tool for academia and practitioners in crisis management. The proposed framework indicates the significant importance of timely categorising the topics, identifying the sentiment of tweets and understanding the changes of consumer opinions over time in a crisis. , – The research presented in this paper is one of the limited social media research to focus on a UK food fraud issue and adds to the limited body of literature investigating consumer social media use from the side of industry practitioners.

Fuzzy association rule mining for fashion product development

Purpose – The emergence of the fast fashion trend has exerted a great pressure on fashion designers who are urged to consider customers’ preferences in their designs and develop new products in an efficient manner. The purpose of this paper is to develop a fuzzy association rule mining (FARM) approach for improving the efficiency and effectiveness of new product development (NPD) in fast fashion. Design/methodology/approach – The FARM identifies the hidden relationships between product styles and customer preferences. The knowledge discovered help the fashion industry design new products which are not only fashionable, but are also saleable in the market. Findings – To evaluate the proposed approach, a case study is conducted in a Hong Kong-based fashion company in which a real-set of data are tested to generate fuzzy association rules. The results reveal that the FARM approach can provide knowledge support to the fashion industry during NPD, shorten the NPD cycle time, and increase customer satisfaction....

Unlocking supply chain disruption risk within the Thai beverage industry

Purpose – A growing need for global sourcing of business has subjected firms to higher levels of uncertainty and increased risk of supply disruption. Differences in industry and infrastructure make it more difficult for firms to manage supply disruption risks effectively. The purpose of this paper is to extend developing research in this area by addressing gaps within existing literature related to environmental turbulence and uncertainties. Design/methodology/approach – The authors test the model using data collected from 253 senior managers and directors in the Thai beverage industry using advanced statistical techniques to explore the relationship between representations of supply disruption risk and uncertainty. Findings – The results show that both magnitude and probability of risk impact on the disruption risk, but the probability of loss is a dominant determinant. The authors also find that demand uncertainty and quality uncertainty affect the risk perception of purchasing managers, and are related...

Impact of Information Technology on the Performance of Logistics Industry: The Case of Hong Kong and Pearl Delta Region

Over the last decade, a number of research studies have advocated the use of information technology (IT) in different aspects of logistics and distribution operations. This study examines the current state of the use of IT and its impact on logistics service performance through a survey of 210 logistics companies in Hong Kong and the Pearl River Delta region. A hypothetical model is also proposed in which the theories of the market-based view and the resource-based view are applied to link up the implications of IT capabilities with logistic performance. The model was tested using structural equation modelling. The findings suggested that (i) IT implementation directly enhances the service quality of the logistics companies; (ii) the impact of IT implementation improves service quality thereby creating competitiveness.