Search results

The purpose of this study is to investigate hybrid brand positioning strategies for emerging market brands based on two positioning elements: brand country-of-origin (COO) and brand globalness.

Researchers conducted two studies. In Study 1, a survey of 128 brand managers of emerging market brands were used to examine whether asymmetric positioning strategies improve brand preference more than symmetric strategies, and if so, which type of asymmetric strategies improves brand preference more. In Study 2, a consumer experiment in the USA was conducted to identify the positioning strategy for emerging market brands that improve brand preference the most.

For emerging market brands, at any given value of COO or global elements, asymmetric strategies outperform symmetric strategies in terms of brand preference. On average, the best hybrid positioning strategy is the one that highlights brand COO and de-emphasizes brand globalness.

A large body of branding literature examines COO and globalness separately without considering their co-presence in the same brand positioning strategy. Few studies that examine the joint influence of brand COO and globalness focus on established brands from developed markets and do not examine whether highlighting both brand COO and global elements equally is an effective positioning strategy for emerging market brands. This study introduces a framework to systematically examine the various combinations of COO and global elements in a brand’s positioning strategies for emerging market brands. By conducting two studies, the authors empirically test the influence of various combinations of COO and global elements on brand preference for emerging market brands from both firm and consumer perspectives.

South Africa is the highest consumer of commercial energy per capita in Africa, ranking 16th in the world for primary energy consumption. It is also ranked among the bottom 50 of the 150 countries regarding energy efficiency. The cold chain is a large contributor through refrigerated transport vehicles. To comply with the changing climate regulations, cryogenic and eutectic systems are systems with great potential for small distance refrigerated transport. The purpose of this paper is to introduce eutectic system to medium distance refrigerated transport.

This study presents the potential use of Eutectic plates inside a medium refrigerated transport vehicle, by numerically investigating the characteristics of phase change material eutectic plates applied at low-temperature ranges. A physical model and a mathematical model for three-dimensional transient natural flow were developed as proposed by Xiaofeng and Zhang. Using the governing equation of mass, momentum and energy conservation, three Eutectic plate configurations were modeled and simulated in ANSYS Fluent for 5 h.

A uniform heat transfer and airflow condition inside a refrigerated compartment were predicted using the Reynolds stress model. The configuration with eutectic plates placed at the top and side showed great potential for the system functioning in the South African climate.

Medium refrigerated transport vehicle.

This configuration had a high-temperature distribution across the compartment and promoted high air circulations, showing that it could be ideal for medium refrigerated transport vehicles delivering perishable foodstuffs or non-food goods.

This paper aims to quantify atmospheric corrosion by image analyses. The corrosion extent, form and distribution of corrosion product on Q235B and T91 steels exposed to a Zhoushan marine atmosphere over one year are characterized by image analysis.

Image analysis of corrosion images were achieved using the gray value, wavelet analysis and fuzzy Kolmogorov–Sinai (K–S) entropy.

As corrosion becomes extensive, the gray value of corrosion images decreases, and the energy value of nine subimages after wavelength decomposition decreases. Fuzzy K–S entropy increases as localized corrosion propagates but decreases as uniform corrosion spreads.

The methods proposed in this work open a new way for fast corrosion evaluation of metallic materials exposed to atmospheric conditions.

Since the beginning of the new millennium, Confucian doctrines on one’s self-cultivation have been re-introduced to curriculum in China. The revived cherish of the Confucian legacy in the twenty-first century is a reverse from the official rejection of Confucianism in the Mao era (1950–1976). It also appears as a counterweight to the individualism proliferating among the Chinese youths born at the beginning of the new millennium (Gen Z). The re-introduction of Confucianism is thus ideologically purposeful. Yet how does the mixed exposure to Confucius’ legacy and the modern idea of self-awareness impact this cohort of young people, in particular their way of learning? This chapter focusses on Chinese Gen Z studying in Australia. Using the Bourdieuan theory of human habitus, this chapter examines how these students negotiate between the ideas of self-cultivation and self-awareness, and what implications such experiences have in an intercultural academic community.

The purpose of this study is to develop a cylindrical capacitive sensor that has the advantages of high resolution, small size and designability and can be easily installed on lubricant pipeline to monitor lubricant oil debris.

A theoretical model of the cylindrical capacitive sensor is presented to analyze several parameters’ effectiveness on the performance of sensor. Numerical simulations are then conducted to determine the optimal parameters for preliminary experiments. Experiments are finally carried out to demonstrate the detectability of developed capacitive sensors.

It is clear from experimental results that the developed capacitive sensor can monitor the debris in lubricant oil well, and the capacitance values increase almost linearly when the number and size of debris increase.

There is lot of further work to do to apply the presented method into the application. Especially, it is necessary to consider several factors’ influence on monitoring results. These factors include the flow rate of the lubricant oil, the temperature, the debris distribution and the vibration. Moreover, future work should consider the influence of the oil degradation to the capacitance change and other contaminations (e.g. water and dust).

This work conducts a feasibility study on application of capacitive sensing principle for detecting debris in aero engine lubricant oil.

The novelty of the presented capacitance sensor can be summarized into two aspects. One is that the sensor structure is simple and characterized by two coaxial cylinders as electrodes, while conventional capacitive sensors are composed of two parallel plates as electrodes. The other is that sensing mechanism and physical model of the presented sensor is verified and validated by the simulation and experiment.

The purpose of this paper is to utilize a multi-method design for research on corruption in China. Corruption in any society is inimical to good governance. Singapore, despite her size, is argued to be a plausible model for China.

Taking a multi-method approach, the phenomena of corruption is investigated from: etymological analyses for corruption (European roots) and its Chinese equivalent, 贪污 (pinyin: tan wu) case studies taken from three periods: current, Qing Dynasty and to founding of China (zhong guo, Qin Dynasty) to ground our policy recommendation of China be modeling after Singapore on the basis of our analysis of statistical (2013 and longitudinal) data. In the process, the authors embark on inter-country comparisons (mainly Confucian China, Hong Kong, Taiwan, South Korea and Japan).

Here are the key insights: scholars are unaware the English word corruption is narrower in scope than the Chinese equivalent tan wu贪污. As far back as 3,000 years, the Chinese had attributed wu, 污 as filthy, polluting, dirty to psychological concept of greed tan, 贪. In English, corruption does not denote greed per se. Falsification of facts as a political ploy dates back to Qin dynasty. Destabilizing corrupt cases occurred in China today as in Qing Dynasty. Singapore rather Hong Kong is a better model for China in reforming society.

This paper illustrates a distinctively, in-depth approach to research on Chinese management. It shows why it is important to clarify key concepts: corruption in the West and tan wu贪污in the East. Historical cases are utilized to show the presence of a continuing Chinese mind set. The authors argued for China to embark on a city-by-city strategy (modeling after Singapore) toward becoming a corruption-free society. Now, as 3,000 years ago, the Chinese conceptualization of corruption embeds the psychology of greed.

China is at a crossroad of her economic development. There is a possible risk of China being destabilized through the corruption of the top rung of leadership. Chinese authorities must with urgency, rein in corruption. An approach is proposed in this paper.

In terms of style, approach and method of research, this paper is highly original. The integrative research here provides a rationale and basis for the Chinese leaders to implement a policy for a less corrupt society.

In high-speed processing, the influence on the machining accuracy of a machine tool is greatly caused by the thermal deformation of the motorized spindle; a further study on the thermal characteristics of the spindle is given in this paper. This study aims to reduce the thermal error and improve the performance of the machine tool by discussing the relationships between the temperature distributions and rotating accuracy caused by the thermal deformations of the spindle.

The paper opted for a method combining the theoretical analysis and the experimental study to study the thermal stability of the high-speed motorized spindle. First of all, a finite element model of the spindle was built with ANSYS, whereby temperature distributions and the thermal deformations were successively obtained at different speeds. And then, both the temperature field and the rotating accuracy of the motorized spindle were measured simultaneously by the thermal stability experiment. Finally, the experimental and theoretical results were compared and validated.

The thermal stability of the motorized spindle was studied in this paper, and some findings from the study were as follows: the spindle’s rotating accuracy maintained good in X direction but bad in Y and Z directions in terms of the deformations; the higher front-end temperature of the spindle which can significantly affect the rotating accuracy is needed to be controlled mainly; the recovery speed of the spindle deformation lagged behind the temperature’s fallback speed; the vibration graph about radial rotating sensitivity synthesized by X1 and X2 presented a trifoliate shape.

Based on a built test-bed which can synchronously measure the motorized spindle’s temperature distribution and rotating accuracy with five-point method, the coupling effects of the thermal deformation and temperature are embodied, and not only the vibration graph but also the thermal tilt angles can be gained. Therefore, considering the influence of the thermal deformation on the heat generated by the bearings, the paper fulfilled a study by which it was obtained that the front-end temperature of the spindle, which was higher and could significantly affect the rotating accuracy, needed to be controlled mainly.

A smart city is a potential solution to the problems caused by the unprecedented speed of urbanization. However, the increasing availability of big data is a challenge for transforming a city into a smart one. Conventional statistics and econometric methods may not work well with big data. One promising direction is to leverage advanced machine learning tools in analyzing big data about cities. In this paper, the authors propose a model to learn region embedding. The learned embedding can be used for more accurate prediction by representing discrete variables as continuous vectors that encode the meaning of a region.

The authors use the random walk and skip-gram methods to learn embedding and update the preliminary embedding generated by graph convolutional network (GCN). The authors apply this model to a real-world dataset from Manhattan, New York, and use the learned embedding for crime event prediction.

This study’s results show that the proposed model can learn multi-dimensional city data more accurately. Thus, it facilitates cities to transform themselves into smarter ones that are more sustainable and efficient.

The authors propose an embedding model that can learn multi-dimensional city data for improving predictive analytics and urban operations. This model can learn more dimensions of city data, reduce the amount of computation and leverage distributed computing for smart city development and transformation.

The goal of this research is to develop a dynamic step path planning algorithm based on the rapidly exploring random tree (RRT) algorithm that combines Q-learning with the Gaussian distribution of obstacles. A route for autonomous vehicles may be swiftly created using this algorithm.

The path planning issue is divided into three key steps by the authors. First, the tree expansion is sped up by the dynamic step size using a combination of Q-learning and the Gaussian distribution of obstacles. The invalid nodes are then removed from the initially created pathways using bidirectional pruning. B-splines are then employed to smooth the predicted pathways.

The algorithm is validated using simulations on straight and curved highways, respectively. The results show that the approach can provide a smooth, safe route that complies with vehicle motion laws.

An improved RRT algorithm based on Q-learning and obstacle Gaussian distribution (QGD-RRT) is proposed for the path planning of self-driving vehicles. Unlike previous methods, the authors use Q-learning to steer the tree's development direction. After that, the step size is dynamically altered following the density of the obstacle distribution to produce the initial path rapidly and cut down on planning time even further. In the aim to provide a smooth and secure path that complies with the vehicle kinematic and dynamical restrictions, the path is lastly optimized using an enhanced bidirectional pruning technique.

Purpose of study: Indian fibre cement industry is at crossroads on account of the dropping margins attributed to the dynamic internal and external challenges faced by it. The ever-changing technology, the increasing availability of substitutes and changing demographic consumption profiles have questioned the survival of this industry. Internal and external factors affecting an organization provide inputs to the strategic decision-making. Diversity of factors and prioritization is a major challenge encountered for developing a strategy for the organization.

Strategic analysis in the paper proposes to rank important key variables through SWOT-AHP methodology affecting a fibre cement company. Computed priorities of SWOT factor could help in formation of management approach to key decisions facing the firm. It is a descriptive research design. The problem itself has multiple SWOT criteria that have been evaluated in three phases with the help of industry experts and AHP criteria.

SWOT-AHP analysis has been a strategic fit for qualitative analysis of factors. The important ranked factors affecting the organization have been found to be brand name, capability of both the management and technical, quality of the product, and the efficient customer service and marketing reach/distribution.

Ranking of key SWOT factors found through AHP methodology will help the firm under study to develop and plan strategic alternatives to counter all challenges faced by them.

The management of the firm under study shall be benefited in fine-tuning the overall strategy of the organization.

This paper proposes a hybrid SWOT-AHP strategic analysis first time in this sector. The affecting factors have been quantified and ranked to identify priority factors for the firm to focus.