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This chapter aims to answer whether foreign multinational corporations (MNCs) operating within the Chinese context differ from indigenous firms on several essential labor standards indicators: white- and blue-collar salaries, pension insurance, and working hours. In drawing upon neo-institutional and organizational imprinting theories and applying these to the Chinese context, the study addresses competing arguments regarding the expected effects of ownership type on these indicators. We employ seemingly unrelated regressions (SURs) to empirically examine a novel national survey of 1,268 firms in 12 Chinese cities. The regression results show that foreign MNCs do not provide uniquely beneficial labor practice packages to workers when compared with various indigenous firm types, including state-owned enterprises (SOEs), affiliate businesses of Hong Kong, Macau, and Taiwan, and domestic private enterprises (DPEs). Specifically, although MNCs provide relatively higher wage rates, they underperform relative to SOEs concerning social insurance. However, DPEs consistently underperform relative to MNCs across most indicators. The mixture of the results contributes important nuances to the application of neo-institutional and organizational imprinting theories to the Chinese context.

Allocating risk in public–private partnership (PPP) projects based on public–private parties’ risk management (RM) capabilities is a condition for success of these projects. In practice, however, risks are allocated to these parties beyond their respective RM capabilities. Too much risk is often assigned to the private or public party, resulting in poor RM and costly contract renegotiations and terminations. This chapter proposes a methodology based on fuzzy set theory (FST) in which decision makers (DMs) use linguistic variables to assess and calculate RM capability values of public–private parties for risk events and to arrive at risk allocation (RA) decisions. The proposed methodology is based on integrating RA decision criteria, the Delphi method and the fuzzy synthetic evaluation (FSE) technique. The application of FSE allows for the introduction of linguistic variables that express DMs’ evaluations of RM capabilities. This provides a means to deal with the problems of qualitative, multi-criteria analysis, subjectivity and uncertainty that characterise decision-making in the construction domain. The methodology is outlined and demonstrated based on empirical data collected through a three-round Delphi survey. The public–private parties’ RM capability values for land acquisition risk are calculated using the proposed methodology. The methodology is helpful for performing fuzzy-based analysis in PPP projects, even in the event of limited or no data. This chapter makes the contribution of presenting a RA decision-making methodology that is easy to understand and use in PPP contracting and that enables DMs to track calculations of RM capability values.

Using the Analytical Hierarchy Process, this study aims to identify organizational and market factors that prevent hoteliers from adopting greener management systems. This study first constructs a list of critical factors based on expert judgments reported in the literature and the responses from a select group of experienced managers. Then, the list is further refined by six hotel managers who consolidate the factors, which results in four categories explained by 20 items. Subsequently, this study draws from surveys on an expert panel consisting of 20 study subjects who are familiar with hotel operations. The survey results show that hoteliers’ abilities to create a greener image are the most important factor influencing the managers’ decisions to adopt environmentally friendly management schemes. Nevertheless, their motivation of adopting a green strategy seems to be associated with a marketing strategy, instead of generic environmental stewardship.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

Over the last few decades, information technology (IT) has significantly altered the nature of work and organizational structures in many industries, including health care. The purpose of this analysis is to compare how system-level differences affect IT implementation in health care (HIT) and the implications of these differences for health care equity.

We critically analyzed selected claims concerning the capacity of HIT to provide better care to more individuals at lower costs, thus contributing to health care equity, in the context of current health care reform efforts in the United States. We used the case of HIT implementation in Taiwan’s National Health Insurance system as a contrasting case.

We argue that however much HIT may yield in quality improvements or savings in the context of a universal and publicly financed single payer system, such savings simply cannot be accrued by a system of multiple health plans competing for better customers (i.e., less costly patients) and driven by profit.

It is important to define the level of analysis in debates about the potential of HIT to produce better health care at lower costs and the equity implications of this potential. In these debates, US policy makers should consider the commitment to health care equity that informed the design of Taiwan’s health care system and of HIT implementation in that country. HIT merely provides enabling tools that are of little value without major systemic changes

To our knowledge, the health IT expert literature has overlooked when not ignored the ethical principles informing health care systems, an omission which makes it difficult if not impossible to evaluate the potential of HIT to increase equity in health care.

Complementary and alternative medicine (CAM) as a topic of research and as an approach within the health care delivery system has become increasingly accepted. Aided by the holistic movement, and after a century and a half of striving for legitimacy, CAM is also increasingly becoming more accepted by mainstream medicine. This chapter reviews the social sources of disparities in use of CAM, with a greater focus on English-speaking countries, and especially the US. This chapter will briefly highlight the basic underlying principles of CAM as linked to its history and discuss types of CAM. The major focus of this chapter will be a review of the literature on social factors and use of CAM, looking at such factors as age, gender, socioeconomic status, race/ethnicity and immigration status, and health status. As part of this, we will also discuss the integration of CAM and conventional care. In conclusion, future directions for social science research in CAM will be discussed, specifically elaborating on the importance of the social sciences linking CAM with other growing interests in health and wellness.

This research is to identify how user-generated contents (UGC) affect a pre-trip decision on the booking of a guesthouse among international travelers. Online surveys are conducted among social network users who have booked an ecolodge in the past year. A snowball sampling is used, which posts a questionnaire link in social networks including Twitter, Facebook, and Instagram in addition to travel blogs. This study indicates a positive relationship between UGC and lodging selection. UGC is considered as a significant predictor of booking an environmentally friendly guesthouse. Among the UGCs, travelers' review is the most important one influencing guesthouse selection. Future studies may focus on other IT potentials such as “Gamification” or other types of content such as “Podcasts” or “live videos” to engage independent travelers.

Importance sampling is a popular Monte Carlo method used in a variety of areas in econometrics. When the variance of the importance sampling estimator is infinite, the central limit theorem does not apply and estimates tend to be erratic even when the simulation size is large. The authors consider asymptotic trimming in such a setting. Specifically, the authors propose a bias-corrected tail-trimmed estimator such that it is consistent and has finite variance. The authors show that the proposed estimator is asymptotically normal, and has good finite-sample properties in a Monte Carlo study.