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Purpose: With this study, the authors aim to highlight the application of machine learning in smart appliances used in our day-to-day activities. This chapter focuses on analysing intelligent devices used in our daily lives to examine various machine learning models that can be applied to make an appliance ‘intelligent’ and discuss the different pros and cons of the implementation.

Methodology: Most smart appliances need machine learning models to decrypt the meaning and functioning behind the sensor’s data to execute accurate predictions and come to appropriate conclusions.

Findings: The future holds endless possibilities for devices to be connected in different ways, and these devices will be in our homes, offices, industries and even vehicles that can connect each other. The massive number of connected devices could congest the network; hence there is necessary to incorporate intelligence on end devices using machine learning algorithms. The connected devices that allow automatic control appliance driven by the user’s preference would avail itself to use the Network to communicate with devices close to its proximity or use other channels to liaise with external utility systems. Data processing is facilitated through edge devices, and machine learning algorithms can be applied.

Significance: This chapter overviews smart appliances that use machine learning at the edge. It highlights the effects of using these appliances and how they raise the overall living standards when smarter cities are introduced by integrating such devices.

The purpose of this paper is to design and fabricate a three-dimensional (3D) bionic airflow sensing array made of two multi-electrode piezoelectric metal-core fibers (MPMFs), inspired by the structure of a cricket’s highly sensitive airflow receptor (consisting of two cerci).

A metal core was positioned at the center of an MPMF and surrounded by a hollow piezoceramic cylinder. Four thin metal films were spray-coated symmetrically on the surface of the fiber that could be used as two pairs of sensor electrodes.

In 3D space, four output signals of the two MPMFs arrays can form three “8”-shaped spheres. Similarly, the sensing signals for the same airflow are located on a spherical surface.

Two MPMF arrays are sufficient to detect the speed and direction of airflow in all three dimensions.

The purpose of this paper is to examine the effectiveness of the “Made in China, Made with the World” advertisement broadcast on the US television station CNN in 2009 and derives recommendations for China's further efforts in promoting the image of products made in China (PMC).

Through a survey based on the Solomon four‐group design, this study collected primary data from 546 students at an American university in 2010 and used the data to test the effectiveness of the CNN advertisement and identify factors that affect the respondents' perceptions about PMC.

Statistical tests indicate that the TV advertisement did not result in the expected effects and even had some boomerang effects on the perceptions about PMC and China's developments, and regression analysis confirms these conclusions. Also, the TV advertisement received low ratings from the respondents in credibility, trustworthiness, rationality, information, stimulation, and excitability.

As exports continue to play an important role in the Chinese economy and PMC are likely to face more challenges in the global markets, China needs to understand both consumer preferences and product safety regulations in the foreign markets, focus more on quality and safety over low prices, and improve the effectiveness of its promotion efforts on the basis of scientifically sound studies.

While the CNN TV advertisement was China's first TV campaign abroad to enhance the image of PMC, this paper presents one of the first studies for assessing the effectiveness of the advertisement and deriving recommendations for China's further efforts in promoting PMC.

As an exploratory study on rural and urban consumers in an emerging market like China, this paper presents empirical evidence about the impacts of economic development on consumer lifestyles. Chinese rural and urban consumers were found to be statistically different in terms of their attitudes toward the whole marketing mix: product price, brand names, promotions and distribution. Possibly as a result of these disparate attitudes, rural and urban consumers were found to use different products to reflect the improvement of their living standards. All of these previous differences might be due to the fact that rural and urban Chinese consumers have different needs, as indicated by the words they chose to describe their ideal image. These lifestyle differences reveal huge marketing potentials for MNCs and other foreign investors, who will ultimately move into China's relatively untapped rural regions for marketing opportunities.

The purpose of this research is to introduce and test a path model that explores the effects of Hofstede's cultural value dimensions on consumers' intention to eat a healthy diet, through the mediation of their public self‐consciousness.

A total of 21,974 subjects from 25 nations were surveyed in this cross‐cultural consumer study.

As the model demonstrated, individualism and uncertainty avoidance had negative impacts on public self‐consciousness, while power distance and masculinity positively affected public self‐consciousness, which in turn had a positive influence on consumers' intention to eat a healthy diet.

The study measured each nation's cultural values by assigning the national culture index scores originally computed by Hofstede. This operational approach made it possible to develop and test a hierarchical path model on the relationships among cultural values, mediating variables and consumer behaviors. It also used the 3M model as a theoretical structure for investigating the nomological validity of two new constructs that are relevant to the field of consumer marketing (i.e. public self‐consciousness and intention to eat a healthy diet). Managerial implications are provided.

Purpose – Study the potential implications of sovereign wealth funds (SWFs) on financial stability.

Methodology/approach – By assessing whether and how stock markets react to the announcements of investments and divestments to firms by SWFs, this chapter takes advantage of a hand-collected database on investments and divestments by major SWFs to evaluate the short-term financial impact of SWFs on selected public equity markets in which they invest.

Findings – Results show that there was no significant destabilizing effect of SWFs on equity markets, which is consistent with anecdotal evidence.

Social implications – SWFs could promote financial stability and should be given more development space.

Originality/value of the chapter – This study contributes to the emerging academic literature that seeks to analyze the behavior of SWFs in financial markets.

Based on a multi‐national lifestyle survey, this study investigated consumer lifestyle differences between individualist cultures (Britain and the USA) and collectivist cultures (China and Japan). Congruent with previous findings on values and lifestyles differences between idiocentrics (individualists) and allocentrics (collectivists) at the emic level (USA), this etic‐level (cross‐cultural) study found that consumers in the individualist cultures, compared with those in the collectivist cultures, were more brand‐savvy, travel‐oriented, satisfied with their lives, financially satisfied and optimistic. They were also more likely to consider themselves better managers of finances. Findings that were incongruent with those at the emic level were also discussed (e.g. dressing behavior, opinion leadership and impulsive buying). Additional findings were provided as well (e.g. family orientation, gender roles, safety/security). The findings carry practical implications for international marketers whose products/services cut across both individualist and collectivist cultures.

Environmental and operational restrictions increasingly drive modern aircraft design due to the growing impact of global warming on the ecology. Regulations and industrial measures are being introduced to make air traffic greener, including restrictions and environmental targets for aircraft design that increase aerodynamic efficiency. This study aims to maximize aerodynamic efficiency by identifying optimal values for sweep angle, taper ratio, twist angle and wing incidence angle parameters in wing design while keeping wing area and span constant.

Finding optimal wing values by using gradient-based and evolutionary algorithm methods is very time-consuming. Therefore, an artificial neural network-based surrogate model was developed. Computational fluid dynamics (CFD) analyses were carried out by using Reynolds-averaged Navier–Stokes equations to create a properly trained data set using a feedforward neural network.

The results showed how a wing could be optimized by using a CFD-based surrogate model. The two optimum results obtained resulted in increases of 10.7397% and 10.65% in the aerodynamic efficiency of the baseline design ONERA M6 wing.

The originality of this study lies in the combination of sweep angle, taper ratio, twist angle and wing incidence angle within the scope of wing optimization calculations.

Cyber physical system (CPS) has attracted much attention from industry, government and academia due to its dramatic impact on society, economy and people’s daily lives. Scholars have conducted a number of studies on CPS. However, despite of the dynamic nature of this research area, a systematic and extensive review of recent research on CPS is unavailable. Accordingly, this paper conducts an intensive literature review on CPS and presents an overview of existing research on CPS. The purpose of this paper is to identify the challenges of studying CPS as well as the directions for future studies on CPS.

This paper examines existing literatures about CPS from 2006 to 2018 in Compendex, presenting its definition, architectures, characteristics and applications.

This study finds that CPS is closely integrated, diversified and large-scale network with complex multiple time scales. It requires dynamic reorganization/reconfiguration, mass computing, and closed, automated and control circuits. Currently, CPS has been applied in smart manufacturing, medical systems, smart city and smart libraries. The main challenges in designing CPS are to develop, to modify, to integrate abstractions and to set predictable timing of openness and physical interconnection of physical devices. Furthermore, security is a key issue in CPS.

This study adds knowledge to the existing literature of CPS by answering what the current level of development on CPS is and what the potential future research directions of CPS are.

Institutional investors have increasingly gained importance since the early 1990s. The assets under management in these funds have increased threefold since 1990 to reach more than US$45 trillion in 2005, including over US$20 trillion in equity (Ferreira & Matos, 2008). Further, the value of institutional investors' assets represents roughly 162.6% of the OECD gross domestic product in 2005 (Gonnard, Kim, & Ynesta, 2008). Given the magnitude of institutional investors' holdings relative to the world market capitalization, challenging questions on the economic role of these investors have been raised. One such question concerns their impact on the stability of stock markets. On the one hand, active strategies of buying and selling shares by these investors may contribute to moving stock prices away from their fundamental values. On the other hand, if all institutional investors react to the same information in a timely manner, they are in fact helping to increase market efficiency by speeding up the adjustment of prices to new fundamentals (for competing theories on the role of institutional investors, see, e.g., Lakonishok, Shleifer, & Vishny, 1992). This view of institutional investors as “efficiency drivers” generated considerable debate for many years (see, e.g., Ferreira & Laux, 2007; French & Roll, 1986).