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Drawing on accounts from 22 lesbian couples with children conceived using donor insemination, this chapter explores how the respondents’ selection of parent terms, such as “momma” and “mommy,” influences day-to-day negotiation of parenthood. Term selection was affected by personal meanings respondents associated with terms as well as how they anticipated terms would be publicly received. Couples utilized personalized meanings associated with terms, such as terms used by families of origin or reflected in a parent’s cultural background, to help non-biological mothers feel comfortable and secure in their parenting identities. Some families also avoided terms that non-biological mothers associated too strongly with biological motherhood and felt uncomfortable using for themselves. Families also considered whether parent terms, and subsequently their relationships to their children, would be recognizable to strangers or cause undue scrutiny to their family. However, not all of the families selected terms that were easily decipherable by strangers and had to negotiate moments in which the personal meanings and public legibility of terms came into conflict. Overall, these accounts illustrate the importance of parent terms for lesbian-parent families, and other nontraditional families, as a family practice negotiating both deeply personal meanings surrounding parent–child relationships and how these terms, and the families, are normatively recognizable in public spaces.

PM10 is one of the most dangerous air pollutants which is harmful to the ecological system and human health. Accurate forecasting of PM10 concentration makes it easier for the government to make efficient decisions and policies. However, the PM10 concentration, particularly, the emerging short-term concentration has high uncertainties as it is often impacted by many factors and also time varying. Above all, a new methodology which can overcome such difficulties is needed.

The grey system theory is used to build the short-term PM10 forecasting model. The Euler polynomial is used as a driving term of the proposed grey model, and then the convolutional solution is applied to make the new model computationally feasible. The grey wolf optimizer is used to select the optimal nonlinear parameters of the proposed model.

The introduction of the Euler polynomial makes the new model more flexible and more general as it can yield several other conventional grey models under certain conditions. The new model presents significantly higher performance, is more accurate and also more stable, than the six existing grey models in three real-world cases and the case of short-term PM10 forecasting in Tianjin China.

With high performance in the real-world case in Tianjin China, the proposed model appears to have high potential to accurately forecast the PM10 concentration in big cities of China. Therefore, it can be considered as a decision-making support tool in the near future.

This is the first work introducing the Euler polynomial to the grey system models, and a more general formulation of existing grey models is also obtained. The modelling pattern used in this paper can be used as an example for building other similar nonlinear grey models. The practical example of short-term PM10 forecasting in Tianjin China is also presented for the first time.

Copper-graphite (Cu/C) is a type of seal material that has been widely used in liquid rocket engines and with normal metal pairs, has a high wear rate under liquid oxygen lubrication. In this study, bearing steel disks were subjected to a high-temperature oxidization and phosphating progress to create an oxidized tricresyl phosphating film (OTCP) film, using tricresyl phosphate (TCP) as the phosphating solvent. It is hoped that the surface wear rate and friction coefficient can be reduced by this method.

This study aim to form an anti-wear film on the surface of bearing steel, which can significantly improve the lubrication performance of Cu/C and bearing steel. The surfaces of bearing steel disks were dried to remove surface water and then put on a heating plate with a magnetic stirrer and a blue glazed oxide film obtained by heating the disks in the air at 200°C for 1 h. To create the OTCP film, bearing steel disks with a blue glazed oxide film were cleaned ultrasonically three times in ethanol and then placed in baths of TCP. After heating for 2 h at 120°C, excess TCP liquid was removed from the disks using ethanol, leaving an OTCP film on the disk surface.

It was found that steel coated with an OTCP film demonstrated better tribological performance (lower coefficient of fiction and wear rate) when pairing with Cu/C than either oxidized or untreated bearing steel. Additional chemical reactions occur when the oxide disk is immersed in TCP and the FePO₄ film is formed after heating. Additionally, the OTCP film coated steel displayed good corrosion resistance, as confirmed by electrochemical corrosion tests. This finding demonstrates the potential for this process in the aerospace industry.

The preparation of OTCP films via high-temperature oxidization and phosphating of bearing steel was demonstrated, with the tribological properties of the OTCP film being investigated alongside those of the original surface and an oxidized film surface. The fabrication of OTCP films is easily scaled up and exhibits significant advantages as a new technology for applications in mechanical contact seal lubrication.

In any organization there are main goals, with lots of projects designed to achieve these goals. It is important for any organization to determine how much these projects affect the achievement of these goals. The purpose of this paper is to develop a fuzzy multiple attribute-based group decision-support system (FMAGDSS) to evaluate projects’ performance in promoting the organization's goals utilizing simple additive weighting (SAW) algorithm and technique for order of preference by similarity to ideal solution (TOPSIS) algorithm. The proposed FMAGDSS deals with choosing the most appropriate fuzzy ranking algorithm for solving a given fuzzy multi attribute decision making (FMADM) problem with both qualitative and quantitative criteria (attributes), and uncertain judgments of decision makers.

In this paper, a FMAGDSS model is designed to determine scores and ranks of every project in promoting the organization's goals. In the first step of FMAGDSS model, all projects are assessed by experts based on evaluation criteria and the organization's goals. The proposed FMAGDSS model will then choose the most appropriate fuzzy ranking method to solve the given FMADM problem. Finally, a sensitivity analysis system is developed to assess the reliability of the decision-making process and provide an opportunity to analyze the impacts of “criteria weights” and “projects” performance’ on evaluating projects in achieving the organizations’ goals, and to assess the reliability of the decision-making process. In addition, a software prototype has been developed on the basis of FMAGDSS model that can be applied to solve every FMADM problem that needs to rank alternatives according to certain attributes.

The result of this study simplifies and accelerates the evaluation process. The proposed system not only helps organizations to choose the most efficient projects for sustainable development, but also helps them to assess the reliability of the decision-making process, and decrease the uncertainty in final decision caused by uncertain judgment of decision makers.

Future studies are suggested to expand this system to evaluate and rank the project proposals. To achieve this goal, the efficiency of the projects in line with organization's goals, should be predicted.

This study contributes to the relevant literature by proposing a FMAGDSS model to evaluate projects in promoting organization's goals. The proposed FMAGDSS has ability to choose the most appropriate fuzzy ranking algorithm to solve a given FMADM problem based on the type and the number of attributes and alternatives, considering the least computation and time consumption for ranking alternatives.

The purpose of this paper is to investigate the impacts of strategic control and operational control on new venture performance in the China context.

This study tests the hypotheses in a sample of 83 new ventures that have equity investment by established firms and are founded between 1993 and 2007 that issued initial public offerings while not more than eight years old.

The results of this study show that: strategic control has a significantly negative relationship with new venture performance; operational control has a significantly positive relationship with new venture performance; industry relatedness between the corporate investor and the new venture and the new venture’s political ties moderate the relationships between the two types of control and new venture performance. The results are robust to alternative measurements of new venture performance.

The management control that the corporate investor exercises over the new venture is a significant determinant of the new venture success. Managers have to distinguish between strategic control and operational control and understand their impacts on new ventures.

This study highlights the issue of management of corporate venturing capital relationships from the new venture’s perspective. In addition, this study separates strategic and operational control within management control and examines how they influence new venture performance.

Live streaming commerce becomes increasingly popular, and some special shopping behaviors existing in traditional e-commerce also emerge in this new context. The current research mainly focuses on determinants of compulsive buying in live streaming commerce by taking fear of missing out (FOMO) and social influence into account.

Using the data collected from 242 experienced consumers in live streaming commerce, the proposed model was empirically assessed by partial least squares based structural equation model.

The results show that both informational and normative social influences have positive effects on FOMO, which in turn exert an influence on compulsive buying. In addition, informational social influence also directly and positively affects compulsive buying.

This study provides a deeper understanding of FOMO and social influence in the process of compulsive buying. It offers a new avenue to analyze the mechanism regarding why compulsive buying occurs in live streaming commerce.

Based on the linkage-leverage-learning (LLL) framework developed by Mathews (2006), the purpose of this paper is to examine how linking, leveraging and learning capabilities influence the choice of foreign-entry mode, and the way such influences are contingent on context factors in the emerging markets.

Contrary to a prior literature applying the LLL framework, which mainly used case studies, this paper adopts a quantitative approach and is based on a sample of 321 Chinese listed companies to test the hypotheses.

The results show that multinational firms from emerging markets (EMFs) with stronger LLL capabilities are more likely to choose the wholly owned mode in foreign entries. In addition, the relationship between linking capability and wholly owned entry mode choice is weaker at higher levels of cultural distance between home and host country. At the same time, the relationship between learning capability and wholly owned entry mode choice is weaker at higher levels of cultural distance between home and host country, and of institutional distance between prior entries and the focal entry.

An entry mode strategy for firms without ownership advantages and the identification of boundary conditions for applying different LLL capabilities are recommended. The generalizability of the findings from a single-country setting still needs further validation with other emerging economies.

This paper treats internationalization of firms from emerging countries with a different perspective. The underlying idea in this study is that internationalization is not only a process for EMFs to utilize externally accessible assets abroad, but also a process of simultaneously combining internationalization with experiential learning and capability utilization in overseas markets. In addition, the authors also contribute to the literature by providing strong empirical evidence for validating the LLL model and extending the existing entry mode studies.

It is difficult to develop an overall picture of the practice of management accounting (MA) in farms and farm enterprises (FEs) because little research has been published on the topic, and these studies are mostly discrete and unconnected to the others. The purpose of this paper is to provide an overview of the available research, develop an explanatory framework for MA practices in farming entities and identify some major avenues for future research on the topic.

This paper uses systematic literature review methods. After an extensive database search and an examination of references/citations, 41 empirical journal articles published between 1964 and 2016 are identified, described and analyzed in this research paper.

The findings reveal that the practice of MA in farms is subject to information problems and that the empirical research on this topic largely lacks a theoretical explanation. Therefore, the explanatory framework of MA practices in farming entities reveals that these practices are subject to influencing factors such as familism, government farm policies, market competition, technological changes, the seasons and the weather/climate.

The overall limited findings on the practice of MA in FEs indicate that caution should be taken when generalizing the current knowledge on the use of MA practices in other organizational forms to farming entities. Moreover, future research should draw on explicit theories to explain empirical results.

This paper is the first comprehensive literature review of studies on MA practices in farms and FEs.

Long regarded as a far-fetched notion, companies from post-socialist economies (PSEs) increasingly compete with companies from advanced economies in their domestic markets and abroad. This study identifies PSE companies' motives and determinants of outward foreign direct investment (OFDI) in advanced economies.

This study analyses Slovenian business activities in Germany by juxtaposing eight Slovenian investors and three exporters using a multiple case study approach. The authors use content analysis to examine rich data from semi-structured interviews, databases and internal and external documents to provide comprehensive and in-depth insights into PSE investments in advanced economies.

The authors identify market-seeking motives and competitive advantages which differ from those of other emerging economy companies and offer theoretical suggestions. In contrast to findings from other emerging economies, the authors identify firm- and country-specific advantages, such as high technology, high service quality, a highly educated labour force, and European Union membership, which Slovene companies have employed to enter the advanced German market.

This study represents the first application of springboard theory to explain PSE company investment in advanced economies. The authors offer contextualised explanations of PSE investments in advanced host economies, which have been lacking thus far. The authors also contribute to the scarcity of studies on the effects of supranational institutions on OFDI from emerging economies.

Highlights the importance of education and training for women as an integral part of local and national development. Using Nicaragua as a leading example, outlining the recent history of the country in order to explain its particular approach to education. Presents the organizational model of multiplication of learning, the philosophical model of participative learning and the communication model of accessibility of learning materails. Concludes that through such education, women in Nicaragua reflect a high level of political awareness, defining issues and implementing creative solutions with a courage which should be envied by others.