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Fibrous porous media have a wide variety of applications in insulation, filtration, acoustics, sensing, and actuation. To design such materials, computational modeling methods are needed to engineer the properties systematically. There is a lack of efficient approaches to build and modify those complex structures in computers. The paper aims to discuss these issues.

In this paper, the authors generalize a previously developed periodic surface (PS) model so that the detailed shapes of fibers in porous media can be modeled. Because of its periodic and implicit nature, the generalized PS model is able to efficiently construct the three-dimensional representative volume element (RVE) of randomly distributed fibers. A physics-based empirical force field method is also developed to model the fiber bending and deformation.

Integrated with computational fluid dynamics (CFD) analysis tools, the proposed approach enables simulation-based design of fibrous porous media.

In the future, the authors will investigate robust approaches to export meshes of PS models directly to CFD simulation tools and develop geometric modeling methods for composite materials that include both fibers and resin.

The proposed geometric modeling method with implicit surfaces to represent fibers is unique in its capability of modeling bent and deformed fibers in a RVE and supporting design parameter-based modification for global configuration change for the purpose of macroscopic transport property analysis.

This chapter’s aim is to present the key elements of marketing of tourism services and experiences by taking the perspective of a new tourism entrepreneur. The chapter’s focus is on better understanding and efficient implementation of marketing principles.

This chapter was built on literature review of marketing of tourism services at business level. A practical approach has been adopted and implemented in illustrating the variables of marketing mix.

This chapter highlights the fact that in order to be successful in the field of marketing, tourism entrepreneurs should consider and implement all elements of marketing mix as an integral and comprehensive set; all marketing variables are interlinked and interrelated.

This chapter is explorative in nature, based on a literature review. It takes more entrepreneurial/practical than academic approach.

A marketing plan for tourism services/experiences constitutes a chain of strong bonds that guide the tourism business forward in making the chain stronger and more efficient. When an entrepreneur/manager is considering adding a new feature or changing existing elements, he/she has to consider the whole picture of the actions and the resulting outputs.

This chapter discusses an extended marketing model; the model of 10 Ps – Product, Place, Pricing, Promotion, Partners, Presentation, People, Process, Physical evidence and Passion under two stages, before and during the experience consumption/encounter.

This paper aims to report an analysis of the graphical representations of 14 corporate real estate (CRE) models. It does this to establish the systematic, metatheoretical requirements for modelling CRE alignment which to date have been disguised in a multitude of models.

This meta study of CRE alignment models used a qualitative hermeneutic method to inductively develop understanding of the models’ constituent parts. Several iterations of graphical and textual analysis were required to do this. Further deductive analysis sought to understand the individual models relative to this new understanding.

The analysis showed that a total of 12 components have been used to model CRE alignment. These are divided into four Building Blocks: understanding corporate strategy; understanding real estate performance; making real estate strategy; and implementing real estate strategy. While every model’s representation contained the four Building Blocks, few models contained all 12 components, though all contained at least seven. Completeness of representation in this study should not be inferred as equating to effectiveness as an alignment process. Various feedback mechanisms were also evident between the components.

The analysis provides the most complete map of the modelling requirements for CRE alignment. It differs from previous theoretical work on alignment by synthesising a metatheory of alignment representation. By providing a more coherent theory by which to model CRE alignment the metatheory provides a consistent basis on which to investigate and theorise aspects of CRE alignment.

Standard estimation of ARMA models in which the AR and MA roots nearly cancel, so that individual coefficients are only weakly identified, often produces inferential ranges for individual coefficients that give a spurious appearance of accuracy. We remedy this problem with a model that uses a simple mixture prior. The posterior mixing probability is derived using Bayesian methods, but we show that the method works well in both Bayesian and frequentist setups. In particular, we show that our mixture procedure weights standard results heavily when given data from a well-identified ARMA model (which does not exhibit near root cancellation) and weights heavily an uninformative inferential region when given data from a weakly-identified ARMA model (with near root cancellation). When our procedure is applied to a well-identified process the investigator gets the “usual results,” so there is no important statistical cost to using our procedure. On the other hand, when our procedure is applied to a weakly identified process, the investigator learns that the data tell us little about the parameters – and is thus protected against making spurious inferences. We recommend that mixture models be computed routinely when inference about ARMA coefficients is of interest.

The purpose of this study is to investigate the influence of brand equity on corporate financial performance across various institutional factors in China, encompassing macro (regional economic development and product market development), meso (industry uncertainty), and micro (CEO overseas experience) levels.

Using archival data related to Chinese listed companies, this study employs standard error combined with fixed effect regression for model estimation to empirically evaluate the impact of brand equity on financial performance (Tobin’s q) and its boundary effects.

This study reveals that in China, the influence of brand equity on Tobin’s q isn’t significant. However, when considering institutional factors across various levels, its impact becomes significant. Specifically, the positive effect of brand equity on Tobin’s q in China is more pronounced in regions with higher economic or product market development, industries with high uncertainty, or when the CEO has overseas experience.

This study enriches the brand-related marketing literature in China and highlights the potential underperformance of brand equity within this context. Furthermore, this study advances the integration of resource-based view with institutional theory by combining brand equity with institutional factors at the macro-, meso-, and micro-level in China.

This study focuses on brand performance in China, the largest emerging market, emphasizing the importance of integrating brand equity with diverse institutional factors to amplify its beneficial influence on financial performance.

An adverse health event can affect women’s work capacity as they need time to recover. The institutional framework in the Netherlands provides employment protection during the first two years after the diagnosis. In this study, we have assessed the extent to which women’s employment is affected in the short- and long term by an adverse health event. We have used administrative Dutch data which follow women aged 25 to 55 years for four years after a medical diagnosis. We found that diagnosed women start leaving employment during the protection period and four years later they were about one percentage point less likely to be employed. Women in permanent employment did not reduce their employment during the protection period and reduced their employment with less than 0.5 percentage points thereafter. Furthermore, we found minor adjustments in the working hours in the short term and no adjustments in the long term. Lastly, we found that for wages, and not for employment and hours, adjustments could be related to the severity of the health condition: women diagnosed with temporary health conditions experienced a short-term wage penalty of about 0.5–1.7 percent and those diagnosed with chronic and incapacitating conditions experienced a long-term wage penalty of about 0.5 percent, while women diagnosed with some chronic and nonincapacitating conditions, such as respiratory conditions, experienced no wage changes in the short or long term.

Resource scheduling is the study of how to effectively measure, evaluate, analyze, and dispatch resources in order to meet the demands of corresponding tasks. Aiming at the problem of resource scheduling in the private cloud environment, the purpose of this paper is to propose a resource scheduling approach from an efficiency priority point of view.

To measure the computational efficiencies for the resource nodes in a private cloud environment, the data envelopment analysis (DEA) approach is incorporated and a suitable DEA model is proposed. Then, based on the efficiency scores calculated by the proposed DEA model for the resource nodes, the 0-1 programming technique is introduced to build a simple resource scheduling model.

The proposed DEA model not only has the ability of ranking all the decision-making units into different positions but also can handle non-discretionary inputs and undesirable outputs when evaluating the resource nodes. Furthermore, the resource scheduling model can generate for the calculation tasks an optimal resource scheduling scheme that has the highest total computational efficiency.

The proposed method may also be used in studies of resource scheduling studies in the environments of public clouds and hybrid clouds.

The proposed approach can achieve the goal of resource scheduling in private cloud computing platforms by attaining the highest total computational efficiency, which is very significant in practice.

This paper uses an efficiency priority point of view to solve the problem of resource scheduling in private cloud environments.

To determine the role of status information conveyance in a negative reward allocation setting.

Using previously published experimental data, we test the relative effects of status information conveyed by expressive and indicative status cues on the allocation of a negative reward. Further, we construct an alternative graph theoretic model of expectation advantage which is also tested to determine its model fit relative to the classic model of Reward Expectations Theory.

Results provide strong support for the conclusion that status information conveyed by expressive status cues influences reward allocations more than information conveyed by indicative cues. We also find evidence that our alternative graph theoretic model of expectation advantage improves model fit.

This research is the first to test the relative impact of expressive versus indicative status cues on the allocation of negative rewards and shows that status characteristics can have differential impacts on these allocations contingent on how characteristics are conveyed. Furthermore, the research suggests a graph theoretic model that allows for this differentiation based on information conveyance and provides empirical support for its structure in a negative reward allocation environment.

Future research is required to validate the results in positive reward situations.

The results show that an individual’s expectations are altered by varying the manner in which status information is presented, thereby influencing the construction and maintenance of status hierarchies and the inequalities those structures generate. Thus, this research has implications for any group or evaluative task where status processes are relevant.

Are White and Asian job applicants advantaged in access to professional jobs relative to Black and Latinx job applicants at the initial screening stage of the hiring process? And, are the mechanisms of advantage for White applicants different than the mechanisms for Asian applicants? In this chapter, the author proposes a theoretical framework of “parallel mechanisms” of White and Asian advantage during hiring screening – that White and Asian applicants are advantaged compared to Black and Latinx applicants, but that the mechanisms of advantage subtly differ. The author focuses specifically on mechanisms related to two important factors at the hiring interface: referrals and educational attainment. The author applies the concept of parallel mechanisms to a case study of software engineering hiring at a midsized high technology firm in Silicon Valley. The author finds that at this firm, White applicants are advantaged at initial screening relative to Black and Latinx applicants due to average racial differences in applicant characteristics – namely having a referral – as well as differences in treatment by recruiters. For Asian applicants, average racial differences in possession of elite educational credentials, as well as racial differences in recruiter treatment, explain the racial disparity in callbacks. The author discusses the implications of parallel mechanisms of advantage for racial inequality in a multiracial context, and for organizational policy meant to address racial disparities during organizational hiring processes.

This study assesses how relational factors and buyer-supplier relationship commitment (BSRC) influence supply chain integration (SCI) and firm performance in Bangladesh's apparel manufacturing sector. Firm performance includes operational performance and innovation performance.

Grounded in the social exchange theory, a survey data-based structural equation modeling (SEM) approach is applied. Based on two experts and four executives' opinions and an in-depth literature review, 28 measurement items were identified in the close-ended questionnaire design. Further, 144 valid questionnaires from the manufacturer-supplier dyads in Bangladesh were collected and used for SEM analysis.

Our study reveals that relational factors positively influence BSRC. BSRC directly impacts SCI, operational, and innovation performance, whereas SCI is significantly related to operational and innovation performance. Besides, SCI mediates the two relationships: BSRC and operational performance; and BSRC and innovation performance.

Our results contribute to the literature and offer a new way to understand relationships that connect relational factors of BSRC, BSRC, and outcomes not only by examining the focal firm but also by examining its dyadic supplier partner separately. Separate assessment in the dyad displays some similar and dissimilar results. Moreover, we suggest practical implications for managers to enhance firm performance by focusing on the significance of linking relational factors, BSRC, and SCI.