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Searching for a job is an important process that influences short- and long-term career outcomes as well as well-being and psychological health. As such, job search research has grown tremendously over the last two decades. In this chapter, the authors provide an overview of prior research, discuss important trends in current research, and suggest areas for future research. The authors conceptualize the job search as an unfolding process (i.e., a process through which job seekers navigate through stages to achieve their goal of finding and accepting a job) in which job seekers engage in self-regulation behaviors. The authors contrast research that has taken a between-person, static approach with research that has taken a within-person, dynamic approach and highlight the importance of combining between- and within-person designs in order to have a more holistic understanding of the job search process. Finally, authors provide some recommendations for future research. Much remains to be learned about what influences job search self-regulation, and how job self-regulation influences job search and employment outcomes depending on individual, contextual, and environmental factors.

This paper aims to collect and compile the historical data of Guanfu Salt Farm, officially built by the Song Dynasty (960–1279) within modern Hong Kong territories, to reconstruct its history for the reflection of Hong Kong society of the time.

This paper is largely based on identification and analysis of historical documents, including keyword search on electronic databases and verification with the original sources, with reference to archaeological findings when necessary.

This paper reconstructs the history of Guanfu Salt Farm based on documentary sources with reference to archaeological findings. English translation of Chinese sources is also provided when necessary.

There has been an absence of systematic compilation of historical data of Hong Kong during the Song Dynasty, which are limited in quantity and scattered across different sources. This paper seeks to fill the vacuum of knowledge about pre-colonial Hong Kong, with a more comprehensive reconstruction of the history of Guanfu Salt Farm.

House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.

We specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.

Multiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.

We demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.

To the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.

This paper aims to develop a house price forecasting model to investigate the impact of neighbourhood effect on property value.

Multi-level modelling (MLM) method is used to develop the house price forecasting models. The neighbourhood effects, that is, socio-economic conditions that exist in various locations, are included in this study. Data from the local government area in Greater Sydney, Australia, has been collected to test the developed model.

Results show that the multi-level models can account for the neighbourhood effects and provide accurate forecasting results.

It is believed that the impacts on specific households may be different because of the price differences in various geographic areas. The “neighbourhood” is an important consideration in housing purchase decisions.

While increasing housing supply provisions to match the housing demand, governments may consider improving the quality of neighbourhood conditions such as transportation, surrounding environment and public space security.

The demand and supply of housing in different locations have not behaved uniformly over time, that is, they demonstrate spatial heterogeneity. The use of MLM extends the standard hedonic model to incorporate physical characteristics and socio-economic variables to estimate dwelling prices.

This paper aims to investigate the stigma effect on property valuation/sale price for remediated residential leaky buildings constructed in New Zealand during the 1990s and 2000s. In particular, the authors want to know whether meeting the regulatory standards for remediation work will totally eliminate the negative stigma effect on remediated properties.

Property transaction data for remediated leaky homes are often limited and not well recorded. Thus, it is very difficult or even impossible to identify those remediated properties in a standard property transaction data set. Moreover, a vast amount of information regarding the nature of property defects, remediation process and method is very difficult to obtain. In this study, members of the Property Institute of New Zealand (PINZ) and the Real Estate Institute of New Zealand were invited to participate in an online website survey. The results were then analysed using the principal component analysis, ordinary least squares and multinomial logit regressions.

This study indicates that for monolithic-clad dwellings, the price discount due to leaky building stigma is significant. Depending on the severity of the leaking problems, this is about 11 per cent on average for general market stigma and an additional 5-10 per cent for post-remediation stigma. The results highlight that meeting the regulatory standards for remediation work cannot totally eliminate the negative stigma effect on remediated properties. The findings are in line with the lemon theory introduced by Akerlof (1970) and robust to individual characteristics of the survey respondent.

General market stigma has been widely researched and documented in the literature. In contrast, there is a lack of research as to whether remediation will eliminate stigma, particularly in the presence of general market stigma. The authors are the first to show that post-remediation stigma can cause value loss in addition to general market stigma based on the lemon theory proposed by Akerlof (1970).

Supply chain integration (SCI) is key to implementing omni-channel retailing (OCR) strategy. In this paper, the authors explore the role of digitalization as a driver of SCI, as well the role of human capital (HC) in digitalization, using a knowledge management (KM) perspective.

An empirical study was conducted using survey research. A sample of 188 omni-channel retailers in the Chinese market was analyzed using factor analysis and structured equation modeling (SEM) to examine the hypotheses presented in the conceptual model.

This study reveals that HC is positively related to the level of a firm's digitalization in OCR, and that digitalization is positively related to the retailer's SCI. Moreover, the authors found that employees' capital has a greater impact on digitalization than managers' capital, while digitalization has a stronger driving effect on internal and customer integration.

The findings suggest that although digitalization requires retailers to accept the long-term investment challenges, it has a significant positive effect on the key of OCR strategy implementation, i.e. SCI. The findings also provide evidence for the application of KM in OCR, as this theoretical lens enriches our understanding of the phenomena of SCI in OCR and provides explanation to our results by linking digitalization and HC.

Digitalization is quantified and examined in OCR. Moreover, this study reveals the importance of HC on the implementation of digitalization and the different effects of digitalization on each dimension of SCI.

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.

The purpose of this study was to investigate the effect of electrolyte compounds on the anodizing process. Magnesium and its alloys have low corrosion resistance. Anodizing operation is performed to increase the corrosion resistance of magnesium. Anodizing solution compounds have a great effect on the oxide coating formed on the substrate. The effect of anodizing electrolyte composition on the corrosion behavior of magnesium was investigated in the simulated body fluid.

Three pure magnesium samples were anodized separately at 15 min, a constant voltage of 9 volts and room temperature. Three different solutions were used, which are the anodizing solution by the Harry A. Evangelides (HAE) method, the sodium hydroxide solution and the anodizing solution of the HAE method without potassium permanganate. Field emission scanning electron microscope (FE-SEM) was used to examine the surface of the anodized oxide layer and electrochemical impedance spectroscopy (EIS) was used for electrochemical corrosion evaluations.

The results of corrosion tests showed that the sample anodized in the solution without potassium permanganate has had the highest corrosion resistance. Also, microscopic images showed that the surface of the oxide layer of this sample had a uniform structure and is somewhat smooth. It seems that in the anodizing process by HAE method at 9 volts and for 15 min, the absence of potassium permanganate improves the corrosion resistance of magnesium. Also, anodizing in HAE solution gives more positive results than anodizing in sodium hydroxide solution.

The solution without potassium permanganate was studied for the first time and also the effect of these three anodizing electrolytes was compared together for the first time. Effect of anodizing at 15 min and constant voltage of 9 volts. Sample’s electrochemical behavior in the body's simulation environment has been investigated. Improvement of electrochemical properties in the solution of the HAE method without potassium permanganate.

This paper aims to investigate the stress corrosion cracking (SCC) process of sensitized 304 stainless steel during the slow strain rate test by using the electrochemical noise (EN) technique.

EN data are interpreted based on chaos and wavelet analyses, and correlation dimension and wavelet energy distribution are used as indicators for SCC process identification.

Experimental results reveal that the corrosion potential abruptly decreases from 180 to 100 mV at 6,300 s and the current increases from 10 to 100 nA accordingly, which is attributed to passive film breakdown and crack initiation. Chaos and wavelet analyses results reveal that, as crack initiates, the correlation dimensions increase from 1.2 to 1.9, and the corresponding distribution frequencies of maximum relative wavelet energy change from high frequency to low frequency.

SCC is monitored in lab, and crack initiation and propagation are identified by chaos and wavelet analyses. This work lays the foundation for SCC detection in field using EN.

In the pursuit of competitive advantage, an increasing number of firms are adopting open innovation (OI) strategies. However, previous studies have often overlooked the role of strategic human resource management (SHRM) in promoting OI. This study aims to fill this gap by examining how SHRM impacts OI through the mediating factors of intellectual capital (IC) and supply chain integration (SCI). This research sheds light on the critical interplay between SHRM, IC and SCI in driving OI success. The findings underscore the importance of adopting a comprehensive and integrated approach to OI that encompasses both resources and dynamic capabilities.

By integrating resource-based view with the dynamic capability perspective, the hypotheses were tested with a survey sample of 136 Chinese manufacture firms using hierarchical regression and bootstrap method.

The results show that SHRM has a positive effect on OI, and both IC and SCI are partial mediators of the relationship between SHRM and OI. In addition, the chain mediation effect of “SHRM-IC-SCI-OI” has further been verified.

This study uncovers the “black box” between SHRM and OI, and responds to the call for strengthening research on the relationship between SHRM and OI. The study indicates that firms should implement HR practices, including extensive training, team reward and internal promotion to promote the implementation of OI strategy.