Sandra S. Liu and Yi‐Zheng Shi
The past two decades have witnessed significant changes in China as it has moved from a centrally planned economy to a more market‐oriented one. As a socialist nation, state owned…
Abstract
The past two decades have witnessed significant changes in China as it has moved from a centrally planned economy to a more market‐oriented one. As a socialist nation, state owned enterprises (SOEs) continue to comprise a dominant part of economic activity in China. While many SOEs are inefficient and incur losses, economic reforms since the late 1970s have brought about irrevocable changes in the manner in which Chinese SOEs conduct their business. The important agenda for the Chinese government now is how to “vitalize” state sectors and ensure that SOEs are able to strive for their own survival. SOEs therefore are exploring ways to improve the productivity of their current operation and to enhance innovativeness in their business development, including seeking financial and technological resources overseas. The varying levels of market‐orientation in SOEs present diverse outcomes for the SOEs. This study attempts to evaluate the extent to which the SOEs have adopted market‐based organizational learning (Sinkula, Baker, and Noordewier 1997), market orientation (Deshpande and Farley 1998), entrepreneurial orientation (Smart and Conant 1994), and learning and innovativeness (Hurley and Hult 1998).
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Alan J. Dubinsky, Lucette B. Comer and Sandra S. Liu
Charts the rise of women into sales manager positions in the US and looks at the general traits which help females in such roles. Cites that women have more trouble being accepted…
Abstract
Charts the rise of women into sales manager positions in the US and looks at the general traits which help females in such roles. Cites that women have more trouble being accepted in sales roles when selling to other countries. Focuses upon the People’s Republic of China and presents the finding of a study of 266 field sales personnel across the republic. Suggests that there are still a number of difficulties for businesses, but provides some ideas for consideration.
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Evergreen Marine Corp (EMC) started as a privately‐owned single vessel company and became a global ocean carrier giant with 240 service locations; its shipping network now covers…
Abstract
Evergreen Marine Corp (EMC) started as a privately‐owned single vessel company and became a global ocean carrier giant with 240 service locations; its shipping network now covers 80 countries. The success of the company’s global expansion has been well recognized. This article will explore the journey of Evergreen’s globalization through an interview with one of the senior managers who has been involved in every stage of the company’s globalization process.
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This paper aims to provide an example of how to use data mining techniques to identify patient segments regarding preferences for healthcare attributes and their demographic…
Abstract
Purpose
This paper aims to provide an example of how to use data mining techniques to identify patient segments regarding preferences for healthcare attributes and their demographic characteristics.
Design/methodology/approach
Data were derived from a number of individuals who received in‐patient care at a health network in 2006. Data mining and conventional hierarchical clustering with average linkage and Pearson correlation procedures are employed and compared to show how each procedure best determines segmentation variables.
Findings
Data mining tools identified three differentiable segments by means of cluster analysis. These three clusters have significantly different demographic profiles.
Practical implications
The study reveals, when compared with traditional statistical methods, that data mining provides an efficient and effective tool for market segmentation. When there are numerous cluster variables involved, researchers and practitioners need to incorporate factor analysis for reducing variables to clearly and meaningfully understand clusters.
Originality/value
Interests and applications in data mining are increasing in many businesses. However, this technology is seldom applied to healthcare customer experience management. The paper shows that efficient and effective application of data mining methods can aid the understanding of patient healthcare preferences.
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The pharmaceutical industry applies the marketing dichotomy ofindustrial/consumer goods in formulating its marketing strategies. HongKong has both prescription and dispensing…
Abstract
The pharmaceutical industry applies the marketing dichotomy of industrial/consumer goods in formulating its marketing strategies. Hong Kong has both prescription and dispensing markets, whereas China is mostly a prescription market with regard to Western medicine. Although the patient is generally the ultimate user in both cases, medical practitioners in each of these countries have a rather unique and often multiple role in the purchasing process of pharmaceutical products. Examines the relative importance of various factors which influence the prescribing decisions of medical practitioners in Hong Kong and China. Findings indicate a similar perception about the extent of influence for interpersonal/organizational factors but different perceptions regarding marketing/promotional tools among medical practitioners in different types of practice/market segment.
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Sandra S. Liu and Michael Cheng
The pharmaceutical industry in the People’s Republic of China (PRC) has been highly regulated, particularly ethical products. Promulgation of the socialist market economy and the…
Abstract
The pharmaceutical industry in the People’s Republic of China (PRC) has been highly regulated, particularly ethical products. Promulgation of the socialist market economy and the recent reforms in national healthcare industry have compelled impetuses for change in the distribution systems, forms of investment of multinational pharmaceutical companies, and product/market strategies. The conventional wisdom on pioneer marketing may be challenged by these situations in the PRC. This study examines four markets that encompass both specialty and general pharmaceuticals so as to explore whether there is a product category effect on entry strategies. The findings indicate a possible synergistic effect of product category and order of entry. In addition, product life cycle has a direct impact on order of entry whereas brand position has an effect on product category. Both government policies and corporate strategies have implications on product categories and order of entry. The recent reforms in China have helped to build a foundation for pharmaceutical companies to conduct business in a manner that is similar to that of the developed countries. The entry strategies for pharmaceuticals may therefore involve more complicated considerations in accordance with these new arrangements in the legal and regulatory environments. Further research into relationships among these variables and the mediation effect is therefore indicated.
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Sandra S. Liu and Alan J. Dubinsky
University administrators are facing increasingly difficult times as public funds are contracting and accountability for the use of such moneys is increasing. With these financial…
Abstract
University administrators are facing increasingly difficult times as public funds are contracting and accountability for the use of such moneys is increasing. With these financial exigencies, universities must seek alternative means of generating revenues to support their mission. One such approach involves the use of institutional entrepreneurship. This paper describes how institutional entrepreneurship complements strategic marketing management and strategic management, how it can ultimately generate funds for universities‐in‐transition, and provides a case illustration of how universities have successfully employed entrepreneurial activities to their advantage.
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Lina Gharaibeh, Sandra Matarneh, Kristina Eriksson and Björn Lantz
This study aims to present a state-of-the-art review of building information modelling (BIM) in the Swedish construction practice with a focus on wood construction. It focuses on…
Abstract
Purpose
This study aims to present a state-of-the-art review of building information modelling (BIM) in the Swedish construction practice with a focus on wood construction. It focuses on examining the extent, maturity and actual practices of BIM in the Swedish wood construction industry, by analysing practitioners’ perspectives on the current state of BIM and its perceived benefits.
Design/methodology/approach
A qualitative approach was selected, given the study’s exploratory character. Initially, an extensive review was undertaken to examine the current state of BIM utilisation and its associated advantages within the construction industry. Subsequently, empirical data were acquired through semi-structured interviews featuring open-ended questions, aimed at comprehensively assessing the prevailing extent of BIM integration within the Swedish wood construction sector.
Findings
The research concluded that the wood construction industry in Sweden is shifting towards BIM on different levels, where in some cases, the level of implementation is still modest. It should be emphasised that the wood construction industry in Sweden is not realising the full potential of BIM. The industry is still using a combination of BIM and traditional methods, thus, limiting the benefits that full BIM implementation could offer the industry.
Originality/value
This study provided empirical evidence on the current perceptions and state of practice of the Swedish wood construction industry regarding BIM maturity.
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Maria Gravari-Barbas, Sandra Guinand, Yue Lu and Xinyu Li
Between 1840s and 1940s, 27 occidental concessions have been created in several cities in China which represented difficult signs and memories for Chinese. Nowadays, these…
Abstract
Purpose
Between 1840s and 1940s, 27 occidental concessions have been created in several cities in China which represented difficult signs and memories for Chinese. Nowadays, these territories are experiencing a joint phenomenon of heritagization and tourismification which makes them experimental theaters for modern urban life and identity. Taking the former concessions of Tianjin as place study, the purpose of this study is to analyze the role of the heritage and tourism in the former concessions in city branding and more specifically the actors, approaches and products of this phenomenon.
Design/methodology/approach
This research draws on the comparison and analysis of two place studies in China. The authors base their analysis on semi-structured interviews in Chinese with previously identified stakeholders. In all, 20 individuals, including developers, public authority representatives, business owners, academics and conservation association members, were interviewed. This research was completed, updated and triangulated by content analysis of Web-based materials; official documents such as urban plans, guidelines and urban and tourism strategies collected during the fieldwork, as well as non-intrusive spatial observations of the concession and its various developments.
Findings
The results of this study show that the heritage in the former concessions has become an attractive tool for the city branding through tourism development, often led by the public actors with the participation of private entrepreneurs.
Originality/value
This study looks at the hybrid dimensions of the former concessions in China. It provides a better understanding of the co-action of heritage and tourism in the processes of territorial rehabilitation, which contributes to both the practitioners and researchers in this domain.
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Faris Elghaish, Sandra Matarneh, Essam Abdellatef, Farzad Rahimian, M. Reza Hosseini and Ahmed Farouk Kineber
Cracks are prevalent signs of pavement distress found on highways globally. The use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly…
Abstract
Purpose
Cracks are prevalent signs of pavement distress found on highways globally. The use of artificial intelligence (AI) and deep learning (DL) for crack detection is increasingly considered as an optimal solution. Consequently, this paper introduces a novel, fully connected, optimised convolutional neural network (CNN) model using feature selection algorithms for the purpose of detecting cracks in highway pavements.
Design/methodology/approach
To enhance the accuracy of the CNN model for crack detection, the authors employed a fully connected deep learning layers CNN model along with several optimisation techniques. Specifically, three optimisation algorithms, namely adaptive moment estimation (ADAM), stochastic gradient descent with momentum (SGDM), and RMSProp, were utilised to fine-tune the CNN model and enhance its overall performance. Subsequently, the authors implemented eight feature selection algorithms to further improve the accuracy of the optimised CNN model. These feature selection techniques were thoughtfully selected and systematically applied to identify the most relevant features contributing to crack detection in the given dataset. Finally, the authors subjected the proposed model to testing against seven pre-trained models.
Findings
The study's results show that the accuracy of the three optimisers (ADAM, SGDM, and RMSProp) with the five deep learning layers model is 97.4%, 98.2%, and 96.09%, respectively. Following this, eight feature selection algorithms were applied to the five deep learning layers to enhance accuracy, with particle swarm optimisation (PSO) achieving the highest F-score at 98.72. The model was then compared with other pre-trained models and exhibited the highest performance.
Practical implications
With an achieved precision of 98.19% and F-score of 98.72% using PSO, the developed model is highly accurate and effective in detecting and evaluating the condition of cracks in pavements. As a result, the model has the potential to significantly reduce the effort required for crack detection and evaluation.
Originality/value
The proposed method for enhancing CNN model accuracy in crack detection stands out for its unique combination of optimisation algorithms (ADAM, SGDM, and RMSProp) with systematic application of multiple feature selection techniques to identify relevant crack detection features and comparing results with existing pre-trained models.