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This paper examines the possible cooperation options in terms of empty container repositioning across alliances for shipping lines based in the Greater China Region (China, Taiwan and Hong Kong SAR), after the three global shipping alliances reformed in April 2017.

This paper offers a comprehensive review to the latest shipping alliances and introduces a new cooperative dimension among shipping lines based in the Greater China Region which are member of different shipping alliances.

Cooperation among shipping lines in the Greater China Region in terms of empty container handling is possible in terms of resource sharing among shipping lines across alliances that fosters mega shipping line formation in the future.

Shipping lines should review their current empty container repositioning strategies and explore cooperation among non-alliance members having headquarters in proximity for quick responsiveness in empty container repositioning plan and execution.

This is a research directly analyzing the empty repositioning plan of the major shipping lines and their major service routes, fleet and containers.

The purpose of this paper is to put forward a demand chain management (DCM) framework underpinned by the alignment theory and applies it to investigate the fashion apparel (FA) industry in China under the impacts of the latest economic transition.

An exploratory multiple case study methodology involving five Chinese FA firms, each with a different business model and ownership type, was employed. Semi-structured interviews, onsite observations and review of company documents were conducted to collect information for analysis.

Using a conceptual DCM framework as a guide for analysis, the study finds that companies with a higher level of alignment with the external market situation and among the three internal DCM dimensions, namely, market management, supply chain management (SCM), and organization management, appear to perform better under the rapidly changing economic conditions in China.

This study contributes to knowledge by reviewing thoroughly the literature on SCM evolution and develops a DCM framework based on alignment theory that represents the state of the art in this area. By extending the administration-integration-production-development (A-I-P-D) logic set adopted in the alignment theory, this study has also equipped the proposed framework with an empirical tool to measure alignment.

By applying the framework to examine the Chinese apparel industry under the impacts of the latest economic transition, this study provides practitioners in the industry with a framework to help formulate strategies and a tool to measure alignment. The findings of the case study also offer insights to the industry to thrive in the rapidly changing businesses environment with dynamic uncertainties.

This study extends the application of the A-I-P-D logic set under the alignment theory to the SCM field. This endeavor successfully transforms the proposed DCM framework from a theoretical concept to a practical tool to help evaluate empirically the alignment and strategic fit of a firm and potential relationship with firm performance. As the Chinese FA market has increasingly evolved under the impact of the globalization, the findings of this study not only assist the local FA companies in coping with the dynamic uncertainties but also shed light on the future developments of the global FA industry. Besides, the alignment measurement tool embedded in the proposed DCM framework can help enhance the chances of business success during implementation.

Investigates the evolution of mass rapid transit (MRT) in relation to the Hong Kong market and analyses the effect of surrounding land values. Outlines the unique features of Hong Kong which make an urban railway system ideal and discusses the changes brought about by MRT. Summarizes the growth of commercial development on Hong Kong island and gives case studies on the Admiralty, Sheung Wan and Taikooshing/Kornhill areas in respect of their development with the advent of MRT. Notes that the shortening of travelling time for workers has increased demand for, and hence the price of, sites immediately adjacent to MRT stations.

The purpose of this paper is to examine ladies' buying behaviour during shoes sales promotions in Malaysia, using the highly validated Belk's Model.

Using this validated model, the main research framework consists of Social Surroundings (SS), Temporal Perspective (TP), Task Definition (TD), Physical Surrounding (PS), used as predictors for Sales Promotion Purchase (SPP). Ethnic groups are used as a moderator for this study.

The results identify few key predictors during shoes sales promotion. Ladies expressed the importance of first day sales for first buyer's advantage, and they preferred large shops with music. Moreover, due to the multi‐racial society in the country, ethnic group interaction on the model did not indicate impact of consumer differences affecting the sales promotion purchase. That is, during a specific festive season sale, all ethnic groups take full advantages of the sale.

This implies that Belk's Model is still applicable even in multi sales promotions for a specific product – shoes. However, the study may have the slight possibility of biases due to the retrospective accounts of recalling purchase involvement in retails shop(s) during sale promotions. Nevertheless, it is assumed that these biases are minimal as there are six sales per year in the country, averaging one sale per two months.

This study provides an insight of ladies' purchasing behaviour and their preferred types of retail outlets, which contributes to retail owners' sales promotional strategies to attract consumers during festive seasons.

This study has two aims: first, to develop a conceptual model for infused drinks innovation using the subjective norm and lifestyle as predictors; and second, to adapt the beverage science experimental variables and assess young consumers' experience of the taste, mood and health of infused drinks using the moderated mediation method.

Using quota sampling, the data were collected from three faculties in a private university. The conceptual model was developed using structural equation modelling (SEM). The model was validated by the first‐ and second‐order confirmatory factor analysis (CFA) of SEM. The multi‐dimensional variables of the taste, mood and health of the infused drinks were computed by the moderated mediation process and the final mediation effects were confirmed using Aroian tests.

The subjective norm and lifestyle variables predict innovation in infused soft drinks. The results from the moderated mediation analyses indicate that both male and female young consumers prefer the innovation of drinks to suit local tastes and be produced locally; the drinks should also have health and well‐being benefits.

The sample size of 350 students was sufficient but the generalisability of the result was limited by the students being recruited from one university.

Parents may influence their children to change their favourite drinks if they are expensive. For this reason, the pricing strategy is important to price‐sensitive consumers. Offering favourite infused drinks to friends is often part of the lifestyle in Malaysia. In practice, implied recommendation is possible. If this happens, there is the likelihood that it may be communicated through the social network. Marketers should use this platform for promoting new drinks. Beverage innovators should learn from the local popular infused drinks as the baseline for drinks innovation and should innovate to suit local tastes. In particular, beverage manufacturers should consider satisfying the market segmentations for flavour lovers and health seekers. Lastly, for effective soft drinks advertising, it is recommended that beverage marketers should use trendy components in promotions.

The study highlights the possibility of conducting social research by incorporating variables from experimental studies. By using this method, external validation is possible when the measures are applied in an uncontrived setting. In addition, it could provide a better assessment of consumers' needs for product innovation.

Presents, at some length, the story of the writer’s father, sharing the history and experiences of a generation who prospered in the Chinese laundry industry. Chronicles the introduction of the wholesale shirt laundry, presenting new innovations and ideas and branching out into new regulated businesses in other fields, showing how emerging problems were tackled and overcome. Cites that most of the information is from memory, observation, letters and manuals. Considers the development and changes in the industry from 1930 to 1970, looking also at the accompanying changes in standards of living.

In the face of complex and challenging economic and business environments, developing and implementing approaches to predict bankruptcy has become important for firms. Bankruptcy prediction can be regarded as a grey system problem because while factors such as the liquidity, solvency and profitability of a firm influence whether it goes bankrupt, the precise manner in which these factors influence the discrimination between failed and non-failed firms is uncertain. In view of the applicability of multivariate grey prediction models (MGPMs), this paper aimed to develop a grey bankruptcy prediction model (GBPM) based on the GM (1, N) (BP-GM (1, N)).

As the traditional GM (1, N) is designed for time series forecasting, it is better to find an appropriate permutation of firms in the financial data as if the resulting sequences are time series. To solve this challenging problem, this paper proposes GBPMs by integrating genetic algorithms (GAs) into the GM (1, N).

Experimental results obtained for the financial data of Taiwanese firms in the information technology industries demonstrated that the proposed BP-GM (1, N) performs well.

Among artificial intelligence (AI)-based techniques, GBPMs are capable of explaining which of the financial ratios has a stronger impact on bankruptcy prediction by driving coefficients.

Applying MGPMs to a problem without relation to time series is challenging. This paper focused on bankruptcy prediction, a crucial issue in financial decision-making for businesses, and proposed several GBPMs.

The implied assembly constraints of a computer-aided design (CAD) model (e.g. hierarchical constraints, geometric constraints and topological constraints) represent an important basis for product assembly sequence intelligent planning. Assembly prior knowledge contains factual assembly knowledge and experience assembly knowledge, which are important factors for assembly sequence intelligent planning. This paper aims to improve monotonous assembly sequence planning for a rigid product, intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge is proposed.

A spatio-temporal semantic assembly information model is established. The internal data of the CAD model are accessed to extract spatio-temporal semantic assembly information. The knowledge system for assembly sequence intelligent planning is built using an ontology model. The assembly sequence for the sub-assembly and assembly is generated via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge. The optimal assembly sequence is achieved via a fuzzy comprehensive evaluation.

The proposed spatio-temporal semantic information model and knowledge system can simultaneously express CAD model knowledge and prior knowledge for intelligent planning of product assembly sequences. Attribute retrieval and rule reasoning of spatio-temporal semantic knowledge can be used to generate product assembly sequences.

The assembly sequence intelligent planning example of linear motor highlights the validity of intelligent planning of product assembly sequences based on spatio-temporal semantic knowledge.

The spatio-temporal semantic information model and knowledge system are built to simultaneously express CAD model knowledge and assembly prior knowledge. The generation algorithm via attribute retrieval and rule reasoning of spatio-temporal semantic knowledge is given for intelligent planning of product assembly sequences in this paper. The proposed method is efficient because of the small search space.

The visit to Aberdeen of Her Majesty The Queen on June 27 confirmed what had been obvious for a little time—that the epidemic of typhoid fever in the city is over, notwithstanding that sporadic “secondaries” may continue to occur from time to time. The number of confirmed cases admitted to hospital exceed 400 and the outbreak is among the largest of this century in Britain. The largest number of cases on any one day was 64 on June 1, but by the second week in June, cases had begun to fall and the outbreak was on the decline. The total included about 90 children and there were 38 suspected cases which proved not to be typhoid fever. The infection spread beyond Aberdeen and on June 8, the Secretary of State for Scotland said in the House of Commons that 31 patients (29 in Scotland and two in (England) were in hospital with typhoid contracted in Aberdeen and that 40 other cases were under investigation.