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The purpose of this paper is to explore and identify the potential outer space technologies that can be used in the construction industry to enhance sustainability in buildings.

Outer space technologies developed by the National Aeronautics and Space Administration (NASA) in the USA are explored for possible use in sustainable construction within the context of the Green Mark scoring system implemented by the Building and Construction Authority (BCA) in Singapore. NASA's voltage controller and self‐illuminating materials are identified and mapped with the energy efficiency criteria of the Green Mark Scheme. The mapping exercise suggests that Green Mark points can be enhanced through appropriate adoption of these technologies.

The Green Mark points that are re‐computed can show significant enhancements when the two potential outer space technologies are to be used in the building.

National security and patent issues as well as related cost implications associated with the use of outer space technologies are not considered in the study. This may be a limitation because developers often deem costs to be an important consideration.

Appropriate outer space technologies do appear to enhance the assessment criteria in the Green Mark Scheme.

This exploratory study provides a bridge between outer space technologies and sustainable buildings. The study is original in that the bridge is the first ever attempt to further enhance the sustainability agenda, through additional Green Mark points, using potential outer space technologies developed by NASA.

Alongside structural equation modeling (SEM), the complementary technique of partial least squares (PLS) path modeling helps researchers understand relations among sets of observed variables. Like SEM, PLS began with an assumption of homogeneity – one population and one model – but has developed techniques for modeling data from heterogeneous populations, consistent with a marketing emphasis on segmentation. Heterogeneity can be expressed through interactions and nonlinear terms. Additionally, researchers can use multiple group analysis and latent class methods. This chapter reviews these techniques for modeling heterogeneous data in PLS, and illustrates key developments in finite mixture modeling in PLS using the SmartPLS 2.0 package.

The purpose of this paper is to attempt to understand the frequent clothing purchase behavior of undergraduate urban college‐goers of India aged 18‐23 years and empirically prove the value‐psychographic traits‐clothing (VPC) purchase behavior hierarchy.

A stratified systematic sample of 275 respondents was used to test the hierarchy. The List of Values (LOV) scale was submitted to exploratory factor analysis (EFA) with principal components analysis and varimax rotation. Confirmatory factor analysis (CFA) was used to validate EFA results. Next, structural equation modeling (SEM) with maximum likelihood estimation (MLE) was used to empirically prove VPC of the urban Indian college‐goers.

The study finds that EFA of the LOV scale yielded two dimensions‐ outer‐directed values and inner‐directed values. Outer‐directed values influenced the psychographic traits – fashion‐consciousness and innovativeness positively, while fashion‐consciousness and innovativeness positively influenced clothing purchase frequency. Thus, VPC hierarchy is empirically proved with the help of SEM.

In the context of frequent clothing purchases of college‐goers, values affect behavior indirectly through psychographic traits of fashion‐consciousness and innovativeness. Psychographic traits of fashion‐consciousness and innovativeness act as intervening variables between values and clothing purchase behavior. EFA and CFA were done on the same sample thereby limiting the scope of the study.

The marketer of clothing for college‐goers should frame his/her product and communication strategy in such a way that it appeals to the fashion‐conscious and innovative consumers with outer‐directed values.

An attempt has been made for the first time to prove the VPC hierarchy empirically in the context of frequent clothing purchases of young college‐goers.

The purpose of this study is to develop and test a new customer satisfaction index model for Turkish mobile phone sector (TMPS).

Based on relevant literature and theoretical considerations on customer satisfaction, a new measurement model was developed. A survey based on the proposed model was conducted to 700 mobile phone users in Istanbul. Partial least squares method was employed to estimate the proposed structural equation model (SEM).

The general applicability of a SEM depends on the reliability and validity of the modeling results. The proposed satisfaction model exhibits strong explanatory power with its satisfactory reliability and validity results.

The proposed model was tested for the TMPS. It should ideally be tested periodically for different sectors with more data, and the index results should be compared.

The results of this study provide very important information for the managers in formulating competitive marketing strategies. The results show the critical points where the limited resources of the firms should be allocated to improve satisfaction and loyalty. Independent and uniform measurement characteristics of the studied model provide a useful tool for tracking performance and systematic benchmarking over time. It also provides information about the weaknesses and strengths of the company from the eyes of its customers.

This study is an attempt to develop and implement a satisfaction model for the TMPS. The proposed model consists of well‐established theories and approaches in customer behavior.

The set of compositional approaches to product space development is expanded to include confirmatory methods. Specifically, describes and compares product space development (perceptual mapping) via confirmatory factor analysis and partial least squares with the aid of an empirical example. Both of these procedures are widely used in causal or structural equation modelling. Since they tend to be confirmatory extensions to factor analysis and principal components analysis, the approaches are also well suited to the development of product spaces. Confirmatory approaches have several advantages over exploratory approaches including the incorporation of prior knowledge, the elimination of rotational indeterminacy, and the use of a wide variety of measurement tools to assess the reliability and validity of model results.

In the automotive industry, the high process complexity becomes an important issue because of the increased number of product and process variants demanded by the customers. To avoid quality defects in assembly and losses in such a complex manufacturing environment, new predictive support systems are required. This study aims to develop a multiple attribute decision support system (DSS) for the prediction and quantification of the risk of failures on the workstations of a leading Turkish automotive manufacturing company.

Initially, the factors affecting the failures in workstations and the attributes to evaluate the factors are identified. Subsequently, the relations among the attributes are specified and priorities of them are calculated. Finally, the risk of failures is calculated and tested in a pilot study and validated with real production data.

To the best of authors’ knowledge, this is a unique study that computes the risk scores on the workstations via DSS. The DSS has various advantages for improvements of the manufacturing quality: the risk of failures can be detectable and comparable, the effect of changes in the design of new workstations can be observed. Stations that have medium or high complexity scores demonstrated strong correlation with failure rates. A sensitivity analysis is conducted to predict the effect of improvement actions on the riskiness of the workstations.

High level of production complexity becomes a crucial issue for companies that use various production processes. Considering this fact, it is a requirement for companies to observe and monitor the risk factors, especially in the assembly lines to be able to eliminate failures derived from complexity. Accordingly, to measure risk scores of the workstations in the assembly lines, a decision support for companies aids executives to manage the complexity level in a reliable and effective way. In this study, the authors develop such a DSS for TOFAS, a leading Turkish automotive company. The proposed DSS is verified and applied through a pilot study on a specific basic production unit. A sensitivity analysis is also conducted to see the effects of potential improvements on the risk scores. Additionally, the trend of risk scores for the stations can also give valuable information for tracing the changes in the time horizon. The proposed DSS also enables an opportunity for the executives in their decision of design processes of new production lines by allocating limited resources in an appropriate way based on the risk scores of possible workstations. The proposed DSS is the first and unique proactive failure prevention model developed in a Fiat Chrysler Automobiles (FCA) plant across the world. TOFAS executives also plan to introduce and enlarge the usage of the model to other FCA plants. It may also be possible to apply the model to other assembly lines in any sector. Another plan of the executives of TOFAS is developing a software, which manages each parameter, to constitute data to the DSS to run this system more instantly and effectively. Moreover, they can take integration actions of the software with world-class manufacturing problem management system that is currently in use in TOFAS.

The purpose of this paper is to answer the question “will China overtake the USA in the space race?” This paper reviews China’s recent progress in aerospace while developing a wind theory of change to underline the geographic spread of various empires over the past thousand years, a topic studied by one of China’s most prestigious historians, Sima Qian, with a specific interest in 2,500 years of the rise and fall of Chinese kingdoms. Based on the wind theory, China is geared to overtake the USA in the twenty-first century space race. Historically, Chinese have always been fascinated with outer space, and it is felt by many Chinese that the USA, despite its current lead in the field, should work with China to explore outer space.

This paper introduces the philosophy and methodology of Sima Qian for Chinese management, in particular his analytical approach and drawing of lessons from past cases (dynasties) for managing the future which can be considered clearly reminiscent of the Harvard case approach. Evolving from this broad study of patterns by Sima Qian, a wind theory methodology is suggested using an overview of patterns over vast stretches of time, in this case from the Tang dynasty. Etymological analyses are embarked upon to illustrate how the ancient Chinese were interested in learning more about the outer space. Conceptual models are developed to map the current nascent space industry.

After outlining the current developments made by China in aerospace, the overall analysis suggests the following: based on the wind theory of change, China will overtake the USA even in race into space. Given their historical fascination with outer space, Chinese are likely to enter the business of space at the opportune time. When will that be? Most likely when appropriate technologies have been developed, in particular developing safe moon tours for tourists.

Suggests a futuristic look at the space industry that China can enter the market at the opportune time. With their long-term fascination with outer space, China may potentially be the largest market for those in space business.

Introduces a new idea of looking into the future possibilities as embedded in the wind theory of change: the geographical patterns in the rise and fall of empires. If this pattern holds, China will overtake the USA including in the race for outer space. For the first time, this paper draws the relevance of Sima Qian’s analytical, case-based methods for management.

In order to determine the status quo of PLS path modeling in international marketing research, we conducted an exhaustive literature review. An evaluation of double-blind reviewed journals through important academic publishing databases (e.g., ABI/Inform, Elsevier ScienceDirect, Emerald Insight, Google Scholar, PsycINFO, Swetswise) revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis. We assessed what the main motivation for the use of PLS was in respect of each article. Moreover, we checked for applications of PLS in combination with one or more additional methods, and whether the main reason for conducting any additional method(s) was mentioned.

This chapter presents a contextual model of human resources management (HRM). The hallmarks of this model are that (1) the most advantageous HRM practices vary conditionally upon strategic considerations; (2) each organization has multiple substrategies within it, and each substrategy is aligned with a unique bundle of HRM practices; (3) within each organization, three substrategies are associated with three subsystems; and (4) in terms of contributing to sustainable competitive advantage, the innovation subsystem is the most valuable regardless of the organization in question.

The purpose of this paper is to investigate the efficacy of cabbage powder as a source of natural antioxidants and dietary fibre for the development of functional mutton patties. Antioxidants are the first line of defence against the oxidative damage to body’s macromolecules resulting in pathogenesis of various diseases including cancers and cardiovascular diseases. The supply of antioxidants from vegetative sources along with different meat products may serve as an excellent alternative for the synthetic antioxidants which may have harmful effects.

Cabbage powder was prepared and evaluated for antioxidant potential and total dietary fibre content. Cabbage powder was incorporated at three different levels in mutton patties formulation; optimum level was selected on the basis of sensory analysis. The developed product was evaluated for detailed profile and storage stability under aerobic and vacuum packaging.

Cabbage powder may serve as a good source of natural antioxidant and dietary fibre for the development of functional mutton patties. On the basis of sensory scores, optimum incorporation level of cabbage powder was adjudged as 6 per cent. The functional mutton patties had very good storage life under refrigeration.

Future research may stress on identifying the specific compounds with antioxidant effect and their metabolism inside the body.

This paper may popularize the cabbage powder as a source of natural antioxidant and dietary fibre in different food products.

Development of functional mutton patties incorporated with cabbage powder having oxidative stability, good nutritive, sensory, textural, and colour properties.