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The purpose of this paper is to investigate the factors effecting ultrasonic seam tensile properties.

In this study, 100 percent polypropylene and 100 percent polyester spunbond and meltblown nonwoven fabrics were sewn by using ultrasonic sewing machine with different rollers which have two, three and four rows. Seam tensile properties of the sewn nonwoven fabrics were investigated. Four-Level Nested Anova Design was applied to the data by using Minitab 15 software program.

Higher seam strength values were obtained by using four rows roller, PP fiber, spunbond fabric and 50 g/m2 fabric area density for all nonwoven fabrics. Statistical significance was found between fabric area density, roller rows and seam tensile strength properties and between fabric type, roller rows and seam elongation at break values.

When the authors look at the studies related to ultrasonic sewing, several researchers studied on welding parameters of ultrasonic sewing but very limited studies were performed on assembling of nonwoven fabrics with ultrasonic sewing. Therefore effect of production methods of nonwoven fabrics on the properties of ultrasonic sewing such as seam strength and elongation at break should be investigated.

The purpose of this article is to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the analysis of variance (ANOVA) application after the preliminary test on the model specification.

A new approach is proposed to study the link between mean shift and inflation coefficient when the underlying null hypothesis is rejected in the ANOVA application. First, we determine this relationship from the general perspective of Six Sigma methodology under the normality assumption. Then, the approach is extended to a balanced two-stage nested design with a random effects model in which a preliminary test is used to fix the main test statistic.

The features of mean-shifted and inflated (but centred) processes with the same specification limits from the perspective of Six Sigma are studied. The shift and inflation coefficients are derived for the two-stage balanced ANOVA model. We obtained good predictions for the process shift, given the inflation coefficient, which has been demonstrated using numerical results and applied to case studies. It is understood that the proposed method may be used as a tool to obtain an efficient variance estimator under mean shift.

In this work, as a new research approach, we studied the link between mean shift and inflation coefficients when the underlying null hypothesis is rejected in the ANOVA. Derivations for these coefficients are presented. The results when the null hypothesis is accepted are also studied. This needs the help of preliminary tests to decide on the model assumptions, and hence the researchers are expected to be familiar with the application of preliminary tests.

After studying the proposed approach with extensive numerical results, we have provided two practical examples that demonstrate the significance of the approach for real-time practitioners. The practitioners are expected to take additional care before deciding on the model assumptions by applying preliminary tests.

The proposed approach is original in the sense that there have been no similar approaches existing in the literature that combine Six Sigma and preliminary tests in ANOVA applications.

Recently, manufacturing companies have been evaluating measurement equipment used for in‐process inspection. The precision and accuracy of the measurement operation are a major factor of an overall quality control programme. Compares two measurement systems of scales and callipers in three laboratory settings for the purpose of identifying sources of significant differences in measurements. The experimental design used was a nested and crossed design with blocking on manufactured parts. Operators and types of equipment (digital and analogue) were nested within laboratories and crossed with one another. Finds, at a significance level of 0.001, that variation exists among laboratories and between types of scales, while, for callipers, significant variation occurred among laboratories, between types of callipers and between operators.

Most multi-level studies are cross-sectional and focus on a certain point in time, though various changes within levels may occur over time. This chapter presents a statistical method for assessing whether the degree of interdependency within a group has changed over time, using the intraclass correlation coefficient (ICC) as an indicator of the degree of homogeneity within the groups. It then shows how to apply this method using the SAS MIXED procedure. The problem was motivated by a study in which 120 subjects were divided into 40 groups of three. In a portion of the study, collective efficacy was the dependent variable measured for each subject under four different conditions (two levels of task interdependence at two points in time). ICC was used as a measure of group homogeneity with respect to collective efficacy, and the problem was how to compare the dependent ICCs associated with the different conditions.

The present paper aims to present the results of a simulation study on the behavior of the four 95 percent bootstrap confidence intervals for estimating C_pk when collected data are from a multiple streams process.

A computer simulation study is developed to present the behavior of four 95 percent bootstrap confidence intervals, i.e. standard bootstrap (SB), percentile bootstrap (PB), biased‐corrected percentile bootstrap (BCPB), and biased‐corrected and accelerated (BCa) bootstrap for estimating the capability index C_pk of a multiple streams process. An analysis of variance using two factorial and three‐stage nested designs is applied for experimental planning and data analysis.

For multiple process streams, the relationship between the true value of C_pk and the required sample size for effective experiment is presented. Based on the simulation study, the two‐stream process always gives a higher coverage percentage of bootstrap confidence interval than the four‐stream process. Meanwhile, BCPB and BCa intervals lead to better coverage percentage than SB and PB intervals.

Since a large number of process streams decreases the coverage percentage of the bootstrap confidence interval, it may be inappropriate to use the bootstrap method for constructing the confidence interval of a process capability index as the number of process streams is large.

The present paper is the first work to explore the behavior of bootstrap confidence intervals for estimating the capability index C_pk of a multiple streams process. It is concluded that the number of process streams definitively affects the performance of bootstrap methods.

The purpose of this study is to examine how status‐seeking and fashion‐innovative young consumers evaluate diffusion brands. The influence of brand naming techniques and country of origin on brand image and product quality of diffusion brands is also examined.

Two well‐known luxury brands and two product categories were identified as the stimulus for the study through pretests. Data were collected using a convenience sampling method in a large Australian university. A self‐administered questionnaire was distributed and 603 usable responses were returned with the sample falling between the ages of 18‐24.

The results revealed that sub‐brands and nested brands have similar product quality and brand image evaluation when compared with the parent brand. Furthermore, sub‐brands and nested brands have demonstrated product quality fit and brand image fit with the parent brand. The findings suggest that a new brand is not a good substitute for the parent brand to express status. In addition, brand origin is a greater indication of product or brand quality than country of origin.

Replication of study on other segments is worthy of future research. Only the influence of fashion innovativeness and status consumption on diffusion brands was examined. Other external factors can be identified and explored.

Marketers or brand strategists can consider establishing sub‐brands or a nested brand in the early stages of product innovation as status symbols to attract young consumers. There should also be greater emphasis on brand name instead of product involvement when marketing a diffusion brand.

There is limited research that examines how young status‐seeking and fashion‐innovative consumers evaluate diffusion brands. Furthermore, the study is conducted in an Australian context. Two product categories were also studied.

Among the gold standards in human resource development (HRD) research are studies that test theoretically developed hypotheses and use experimental designs. A somewhat typical experimental design would involve collecting pretest and posttest data on individuals assigned to a control or experimental group. Data from such a design that considered if training made a difference in knowledge, skills or attitudes, for example, could help advance practice. Using simulated datasets, situated in the example of a scenario-planning intervention, this paper aims to show that choosing a data analysis path that does not consider the associated assumptions can misrepresent findings and resulting conclusions. A review of HRD articles in a select set of journals indicated that some researchers reporting on pretest-posttest designs with two groups were not reporting associated statistical assumptions and reported results from repeated-measures analysis of variance that are considered of minimal utility.

Using heuristic datasets, situated in the example of a scenario-planning intervention, this paper will show that choosing a data analysis path that does not consider the associated assumptions can misrepresent findings and resulting conclusions. Journals in the HRD field that conducted pretest-posttest control group designs were coded.

The authors' illustrations provide evidence for the importance of testing assumptions and the need for researchers to consider alternate analyses when assumptions fail, particularly the homogeneity of regression slopes assumption.

This paper provides guidance to researchers faced with analyzing data from a pretest-posttest control group experimental design, so that they may select the most parsimonious solution that honors the ecological validity of the data.

The purpose of this paper is to examine the magnitude of country, industry and firm‐specific effects for firms competing in emerging economies and also explore differences between high and low performers.

The authors use ANOVA methodologies on samples from firms competing in Latin America between 1990‐2006.

It was found that the firm‐specific effect is the most important one, and relatively equivalent in magnitude to the firm‐specific effects found in developed countries. Country and industry effects are less important than the firm‐specific effect. Contrary to previous studies that indicate that the country effect is relatively more important in emerging economies, the authors found that it is even less important than the industry effect, a result that has important implications for strategic management and international business theory. The source behind the strong firm‐specific effects might stem from their resources and capabilities to manage and take advantage of the institutional and macroeconomic environments. Further analysis indicates that the firm‐specific effect is relatively more important for firms showing high performance than for those firms showing low performance.

Through these findings the authors feel that further research is needed so as to arm future managers with a more clear and comprehensive strategy when doing business in a Latin American country. The paper's findings are specific for large public corporations in Latin America.

The paper allows managers to think about sources of competitive advantages in emerging economies.

The paper shows that, despite weak institutional contexts and highly volatile macroeconomic environments, managers in the region should be able to obtain substantial differences in economic performances within the region. Activities needed for such differentiation might differ from those carried out in developed countries, with more emphasis on managing institutional voids and periods of economic and political cycles but the result should be the same.

The purpose of this study is to explore the role of anticipatory procedural justice, seriousness/type of conflict, and design of ombudsman processes with intentions to use ombudsman processes to resolve disputes.

The study was a 3 (type of conflict with three scenarios nested in each type)×3 (design of ombuds system). Subjects read scenarios and filled out Likert type survey items related to seriousness of conflict, anticipatory procedural justice, and intentions to use ombuds processes.

Perceived seriousness and anticipatory procedural justice were significantly related to intention to use ombuds process, but design of ombuds process was not.

This study was limited to scenarios of academic conflict. Research should be extended to experienced conflicts and conflicts in other contexts.

Potential users of ombuds processes are more concerned with principles of fairness and justice than the specific elements of how dispute systems are designed. While the design of a system needs to insure disputants perceive it to be fair, institutions concerned with resolving disputes between/among members should be more concerned with having a system than about promoting specific details about the design of that system.

This study advances both the study of ombuds processes/design and anticipatory procedural justice. This study provides unique findings related to both the design of ombuds processes and the conditions under which disputants might utilize the process. Additionally, procedural justice is demonstrated to be useful in forming decisions about use of processes, not just evaluations after processes have been used.

The purpose of this paper is to examine the potential for eXtensible Business Reporting Language (XBRL) to go beyond static reporting. A taxonomy structure of information is developed for providing a knowledge base and insights for an XBRL taxonomy for integrated reporting (IR).

Design Science (DS) research, as a pragmatic exploratory research approach, is embraced to create a new “artefact” and thematic content analysis is used to analyse IR in practice.

Using XBRL for IR allows a shift from static and periodic reporting to more relevant and dynamic corporate disclosure for stakeholders, who can navigate and retrieve customised disclosure information according to their interest by exploiting the multidimensionality of IR and overcome some of its criticisms. The bi-dimensional taxonomy structure the authors’ present allows users to navigate disclosure from two different perspectives (content elements (CE) and capitals), display specific themes of interest, and drill down to more detailed information. Because of its evidence-based nature and levels of disaggregation, it provides flexibility to preparers and users of information. Additionally, the findings demonstrate the need to codify sector-specific information for the CE, so that to direct the efforts toward the development of sector-specific taxonomy extensions in developing an XBRL taxonomy for IR.

The limitations of DS research are, first, the artefact design and, second, its effects in practice. The first limitation stems from the social actors’ perspective taken into account to develop the taxonomy structure, which derives from the analysis of the reporting practices rather than a pluralistic approach and dialogic engagement. The second limitation relates to the XBRL taxonomy development process because, since the study is limited to the “design” phase being codification and structuring the knowledge base for an XBRL taxonomy, there is a need to develop a taxonomy in XBRL and then apply it in practice to empirically demonstrate the potential and benefits of XBRL in the IR context.

The taxonomy structure is targeted at entities interested in designing an XBRL taxonomy for IR. This is a call for academics and practitioners to explore the potential of technology to improve corporate disclosure and open up new projections for resurging themes on intellectual capital (IC) reporting with prospects for IC “fourth-stage” research focused on IC disclosure.

This is an interdisciplinary research employing the DS approach, which is rooted in information systems research. It is the first academic study providing pragmatic results for using XBRL in the context of IC and IR.