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Multiple length and time scales arise in a wide variety of practical and fundamental problems. It is important to obtain accurate and validated numerical simulation results, considering the different scales that exist, in order to predict, design and optimize the behavior of practical thermal processes and systems. The purpose of this paper is to present modeling at the different length scales and then addresses the question of coupling the different models to obtain the overall model for the system or process.

Both numerical and experimental methods to obtain results at the different length scales, particularly at micro and nanoscales, are considered. Even though the paper focusses on length scales, multiple time scales lead to similar concerns and are also considered. The two circumstances considered in detail are multiple length scales in different domains and those in the same domain. These two cases have to be modeled quite differently in order to obtain a model for the overall process or system. The basic considerations involved in such a modeling are discussed. A wide range of thermal processes are considered and the methods that may be used are presented. The models employed must be validated and the accuracy of the simulation results established if the simulation results are to be used for prediction, control and design.

Of particular interest are concerns like verification and validation, imposition of appropriate boundary conditions, and modeling of complex, multimode transport phenomena in multiple scales. Additional effects such as viscous dissipation, surface tension, buoyancy and rarefaction that could arise and complicate the modeling are discussed. Uncertainties that arise in material properties and in boundary conditions are also important in design and optimization. Large variations in the geometry and coupled multiple regions are also discussed.

The paper is largely focussed on multiple-scale considerations in thermal processes. Both numerical modeling/simulation and experimentation are considered, with the latter being used for validation and physical insight.

Several examples from materials processing, environmental flows and electronic systems, including data centers, are given to present the different techniques that may be used to achieve the desired level of accuracy and predictability.

Present state of the art and future needs in this interesting and challenging area are discussed, providing the impetus for further work. Different methods for treating multiscale problems are presented.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

The purpose of this paper is to consider how biophilic urbanism complements and potentially enhances approaches for the built environment profession to holistically integrate nature into cities. Urban nature – also referred to as urban greening and green infrastructure – has increasingly been considered from many perspectives to address challenges such as population pressures, climate change and resource shortages. Within this context, the authors highlight how “biophilic urbanism” complements and may enhance approaches and efforts for urban greening.

The paper provides a review of existing literature in “urban nature” to clarify and discuss the concept of biophilic urbanism. Drawing on this literature review, the authors present a systematic clustering and scaling of “biophilic elements” that could facilitate responding to twenty-first century challenges.

Biophilic urbanism can be applied at multiple scales in urban environments, through a range of multi-functional features that address the pervasive false dichotomy of urban development and environmental protection. Biophilic urbanism can complement urban greening efforts to enable a holistic approach, which is conducive to comprehensive, intentional and strategic urban greening.

This paper situates the emerging concept of biophilic urbanism within existing research from multiple disciplines, providing insight for how this can be applied in practice, particularly to the topical challenge of “urban renewal”.

This study aims to develop and empirically validate the concept of experience capability, which represents an organisation's ability to be adept at managing the customer experience. Organisations that build an experience capability develop an expertise in deploying a set of resources and routines to understand, evaluate and improve how they interact with customers across all the points of contact.

A rigorous process was employed to identify, operationally define, evaluate and validate six dimensions reflecting experience capability. The dimensions were developed and validated using relevant literature, expert interviews, item-sorting techniques, a pilot survey and two surveys, providing a degree of certainty that the intellectual insights are generalisable.

The experience capability concept is identified as comprising six dimensions that are informed by 27 measurement items. The six dimensions are employee training, employee empowerment, employee evaluation, experience performance management, cross-functional work and channel integration. The findings provide evidence suggesting that the multi-item measurement scale exhibits appropriate psychometric properties.

The empirically validated 27-item measurement scale provides practitioners with an approach to evaluate and improve their organisation's experience capability. It permits both longitudinal comparisons of individual organisations and competitive benchmarking both within and across industry sectors. The approach alerts managers to the critical operational areas that should be measured and provides a structured method to pursue competitive advantage through customer experience capability.

Developing valid and reliable measurement scales is an essential first step in effective theory-building. The paper proposes a theoretical foundation for the experience capability construct and validates a corresponding measurement scale. The scale was developed carefully to achieve the specificity required to undertake meaningful practitioner-centric assessment while maintaining relevance across sectorial contexts. The results complement existing customer-centric experience research by providing distinct intellectual insights from a practitioner perspective. The developed scale permits future intellectual investigation through capability comparisons both within and between companies in different industries/sectors.

This paper aims to identify religiosity scale usage in academic marketing articles and compare the effectiveness of different religiosity scales in predicting marketing and consumer behavior outcomes.

Articles (n = 397) in the top 20 marketing journals are reviewed and a follow-up study is conducted that compares 22 religiosity scales in predicting 18 marketing variables.

Most scales are from preexisting sources (64.3%), only 20% are multi-dimensional and over 58% are used in only one journal article. Only 22.5% of possible regressions in the follow-up study predicting marketing variables from religiosity scales were significant.

This research is limited by the journals and dependent variables chosen. Implications include diversify research topics, expand publication outlets, decrease use of author-generated scales, increase use of multi-item and multi-dimensional measures, replicate findings methodologically and conceptually and make cultural context adaptations.

Marketers would benefit from using preexisting scales, ensuring that religiosity is measured using a multi-item measure that contains appropriate items for the dominant religious beliefs of the sample, as well as consider multi-dimensional measures to best guide marketing strategy decisions, such as target market definition.

This is the first research study to compare the use of religiosity scales in marketing. This offers key value to the marketing literature by highlighting tactics to take to improve consistency in research practices to increase the comparability and accuracy of findings.

The purpose of this paper is to examine whether single-item measures of job stressor facets were as valid as multiple-item measures in predicting psychological strain. Single-item measures are more time and cost efficient than multiple-item measures and may also have psychometric benefits.

Data from 3,166 hospital employees were used to evaluate the validity of 11 single-item job stressor facet measures by applying five criteria for content and criterion validity.

Based on this data, six single-item measures of job stressors met all criteria, supporting their use as single-item facet measures.

The use of a sample of employees from one female-dominated industry may limit the generalizability of the results to other industries. Future research should replicate the results of the current study in other industries and use longitudinal designs to examine the predictive validity of the single-item measures. Future studies may also develop single-item measures of each facet a priori and examine their validity.

Results support the use of single-item measures for the assessment of significance, recognition, workload, work-family conflict, skill use, and coworker relations, which can be included in research where a shorter survey is necessary. These six measures may facilitate more frequent assessment of job stressors, the assessment of job stressors as control variables, and the assessment of multiple job stressors simultaneously, while still minimizing survey space and cost.

This is the first study to examine the validity of single-item measures of job stressors, which is a construct that is frequently assessed in organizations.

The purpose of this paper is to analyze the dimensionality of the consumer perceived value (CPV) concept, development of a CPV scale and its measurement in the Indian healthcare sector.

The data on consumer perceived value are gathered from 515 inpatients. The scale development is performed through exploratory factor analysis, reliability and validity analysis, and confirmatory analysis.

CPV scale in healthcare sector is a multidimensional scale represented by 27 items spread over six dimensions that are significant for consumer value measurement. The dimensions include acquisition value (AV), transaction value (TV), efficiency value (EV), aesthetic value (ESV), social interaction value (SI) and self gratification value (SG).

The study is theoretically limited to value and its antecedents. Research work on relationship of consumer perceived value with service quality, customer relationship management, internal marketing orientation, external marketing orientation and financial performance need to be pursued further for richer insight into the inter‐related service marketing concepts. The study is limited to indoor patients only and the perceptions of employees and other stakeholders are important to understand their overall affect on CPV.

The study has unique value to the healthcare literature, both from theoretical and managerial perspectives. The study produced a standardized scale of consumer perceived value which can be used in both public and private healthcare sectors. It incorporates valuation of functional and affective aspects, and provides overall quantification of the value perceived by Indian healthcare consumers.

This study seeks to illuminate the managerial tensions inherent in implementing scaled agile (on the organizational, top management, middle management and team levels) and to frame these challenges within the broader context of project management.

The study adopts a grounded theory approach and delves into a qualitative dataset sourced from 34 interviews with subject matter experts actively engaged in scaling agile initiatives within large organizations spanning various industries. Additionally, the data have been enriched through a comprehensive literature review of the existing body of knowledge on scaling agile.

As a result of our investigation, we propose a framework of managerial tensions in scaling agile in large corporate settings and a series of research propositions and questions that may contribute significantly to the body of knowledge surrounding the phenomenon of “deprojectification” and propose agenda for the future studies in the field of project management.

The study also carries significant managerial implications. Firstly, based on the insights from the practice of scaling agile in large corporate setting, management can build awareness of the challenges inherent of transitioning to agile practices. This may help to anticipate the possible problems and proactively develop strategies how to address them. Secondly, management can be instructed about contingencies inherent in scaling agile, along with the potential disfunctions and side effects (unintended outcomes) that may emerge during the transition process. Thirdly, project management practitioners can gain insights on how scaling agile may cause shifts in the approach to managing projects, project team management and competencies that need to be developed to cope with environments where various approaches to managing projects coexist.

These insights can aid in the agile transition process, beginning with directing managerial attention toward contextual factors and progressing through potential challenges at the organizational, top management, middle management and team levels. Furthermore, the study highlights possible dysfunctionalities and side effects of scaling agile, shedding light on the “dark side” of agile.

The study contributes to the expansion of the empirical database on the implementation of agile practices in large organizational settings. It plays a role in defining and delineating the phenomenon of scaling agile within the context of project management and outlines a research agenda for future project management studies. Additionally, our study adds to the ongoing discourse surrounding the “deprojectification” effect that can occur during the scaling of agile. Lastly, it establishes connections between project management and software development literature regarding the implementation of agile at scale.

This research aims to explore factors influencing accountants' usage of enterprise resource planning (ERP) at a global development agency. The paper tests a model, which hypothesised that attitudes, performance expectancy, effort expectancy, social influence and self-efficacy would have significant and positive effects on behavioural intention to use, and facilitating conditions and behavioural intention would have significant and positive effects on frequency of use (actual usage).

The study utilised a quantitative approach through an online survey of 104 respondents from the different countries that the organisation operates within.

Using multiple regression analysis, the findings showed that attitudes towards use, performance expectancy, self-efficacy and effort expectancy were significant predictors of behavioural intention to use the ERP system. Behavioural intentions and facilitating conditions significantly and positively influenced actual ERP usage. Social influence was found to be non-significant.

The study used a small sample drawn from a single organization.

The paper tests a model of usage of ERP and identifies those factors that are likely to influence ERP usage in a global development agency.

The paper supplements the existing literature on ERP usage in global organizations.

The purpose is to assess current construct measurement in social entrepreneurship and provide recommendations for future construct measurement on the topic.

We use content analysis to assess the construct measurement practices in social entrepreneurship research. Prior studies were coded and analyzed to assess the way social entrepreneurship researchers have developed measures for key constructs in the social entrepreneurship literature. The content analysis allows for the examination of the number, type, and measures associated with social entrepreneurship research and for the comparison with the construct measurement practices in entrepreneurship research, in general.

We suggest that, while initial quantitative research has provided a useful start for empirical analysis of social entrepreneurship, future research can be improved by developing and applying stronger measures of key constructs, such as social value, mission consistency, and performance of social enterprises.

This chapter takes a content analytic approach to provide evidence regarding how a foundational element such as construct measurement has developed within social entrepreneurship research. We also propose directions for improving future research by validating and strengthening measurements of core constructs in social entrepreneurship.