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Mesh Parameterization is central to reverse engineering, tool path planning, etc. This work synthesizes parameterizations with un-constrained borders, overall minimum angle plus area distortion. This study aims to present an assessment of the sensitivity of the minimized distortion with respect to weighed area and angle distortions.

A Mesh Parameterization which does not constrain borders is implemented by performing: isometry maps for each triangle to the plane Z = 0; an affine transform within the plane Z = 0 to glue the triangles back together; and a Levenberg–Marquardt minimization algorithm of a nonlinear F penalty function that modifies the parameters of the first two transformations to discourage triangle flips, angle or area distortions. F is a convex weighed combination of area distortion (weight: α with 0 ≤ α ≤ 1) and angle distortion (weight: 1 − α).

The present study parameterization algorithm has linear complexity [𝒪(n), n = number of mesh vertices]. The sensitivity analysis permits a fine-tuning of the weight parameter which achieves overall bijective parameterizations in the studied cases. No theoretical guarantee is given in this manuscript for the bijectivity. This algorithm has equal or superior performance compared with the ABF, LSCM and ARAP algorithms for the Ball, Cow and Gargoyle data sets. Additional correct results of this algorithm alone are presented for the Foot, Fandisk and Sliced-Glove data sets.

The devised free boundary nonlinear Mesh Parameterization method does not require a valid initial parameterization and produces locally bijective parameterizations in all of our tests. A formal sensitivity analysis shows that the resulting parameterization is more stable, i.e. the UV mapping changes very little when the algorithm tries to preserve angles than when it tries to preserve areas. The algorithm presented in this study belongs to the class that parameterizes meshes with holes. This study presents the results of a complexity analysis comparing the present study algorithm with 12 competing ones.

Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications. In the literature, several approaches have been proposed to solve this problem. However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k), and point sample size (r) on the optimized curve reconstruction measured by a penalty function (f). The paper aims to discuss these issues.

A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed. Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored.

It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m. Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks. The authors were able to detect the presence of such spurious features with spectral analysis. Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample.

The authors have addressed important voids of previous works in this field. The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how. Also, the authors performed a characterization of the curve fitting problem from the optimization perspective. And finally, the authors devised a method to detect spurious features in the fitting curve.

This paper provides a methodology to select the important tuning parameters in a formal manner.

Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.).

This paper aims to identify the relationships among critical success factors (CSFs) for lean six sigma (LSS) implementation in higher education institutions (HEIs).

An extensive literature review was conducted to design the survey instrument, which the authors later administered in Mexican public HEIs to identify the existing relationships among the CSFs and their impact on the benefits obtained from implementing LSS projects. The data were empirically and statistically validated using exploratory and confirmatory factor analysis. Additionally, the authors applied the structural equation modeling (SEM) technique on SPSS Amos to validate the nine hypotheses supporting the research.

The results suggest that the success of LSS projects in HEIs is highly bound to a serious commitment from top management and several interrelated factors.

The main limitations of the study are that the research is cross-sectional in nature and regional in focus. Namely, the data used to validate the structural model were gathered from a small representative subset of the study population – i.e. Mexican public HEIs – and at a specific point in time.

The results reported here represent a reference framework for HEIs worldwide that wish to continuously improve their processes through LSS improvement projects.

This study proposes a statistically validated model using the SEM technique that depicts the relationships among LSS CSFs in HEIs.

The objective of the study is to design and validate an instrument that allows organizations to assess their status regarding the adoption of the critical success factors (CSFs) that enable lean six sigma (LSS) implementation in order to achieve the expected benefits.

An extensive literature review was conducted to define the LSS CSFs that have to be considered for the development of the questionnaire that would later be applied across all manufacturing companies on the Northern Mexican border. Once the database was built, a statistical verification of the assumptions required for factor analysis took place. Finally, the due construct validation was carried out to verify whether the proposed instrument measured reliably what it is intended to.

A questionnaire measuring nine CSFs, as well as the benefits associated with the implementation of LSS, was designed and validated through 61 items.

The main limitations of this study are that the research is cross-sectional and that the study was carried out taking as a reference only exporting manufacturing companies located in the border area between Mexico and the United States.

The validated instrument is expected to serve as a useful tool for companies interested in the implementation of LSS.

This study introduces a validated tool for the analysis of LSS CSFs while providing evidence of construct validity and the solid structure of the factors.

In this chapter, the authors analyze the academic field of comparative education in Spanish speaking Latin America as a contested construction both in epistemological and political dimensions. First, the authors provide a brief historical account of the origin and development of comparative education in the region since the nineteenth century. Next, they focus on the current state of the field by addressing three aspects: (1) the institutional basis, specially the development of comparative education societies; (2) an account of the contributions of international organizations, both in terms of studies that have been recently conducted and of the development of data bases; and (3) an analysis of prevailing topics as well as theoretical and methodological approaches in a sample of articles published during the 2010-2017 period. The authors conclude by summarizing the main aspects of the current situation, and pointing to future epistemological and political challenges for the field in the region.

The objective of this article is to identify the relationships between the enablers in the implementation of Green Lean Six Sigma (GLSS) in the Mexican manufacturing industry (MMI).

To create the survey instrument, the authors did an extensive literature research, which they then applied in the MMI to find the relationships between enablers and their impact on the positive effects of implementing GLSS projects. Using exploratory and confirmatory factor analyses (EFA and CFA), the data were empirically and statistically corroborated. Furthermore, the authors validated the hypotheses that support the research using the structural equation modeling (SEM) approach in SPSS Amos.

The findings reveal that leadership has a positive impact on social and economic benefits (EcB), as well as an indirect impact on the environmental benefits (EB) of GLSS projects, with organizational involvement (OI) and performance measurement (PM) functioning as mediators.

This study represents an empirical reference for practitioners and researchers pursuing high-quality, low-cost, environmentally and socially sustainable products or processes through the implementation of GLSS projects in the manufacturing industry.

This study provides a statistically validated model using the SEM technique to represent the relationships between GLSS enablers in the MMI.

Despite the significance of knowledge sharing for competitive advantage in networked businesses like franchising systems, there is a lack of comprehensive understanding regarding the strategic value of knowledge sharing in the context of franchising. In particular, the specific contribution of information and communication technologies (ICTs) in facilitating interorganizational knowledge exchange among franchising members remains inadequately understood, particularly in emerging economies. Therefore, this study aims to explore the mechanisms involved in the knowledge-sharing process facilitated by a virtual learning environment (VLE) within franchising networks and examine the role of VLEs in facilitating knowledge.

This study uses a multiple-case study approach involving 24 franchisees and the franchisor within a Brazilian franchising network operating in the furniture market to examine the role played by a VLE.

The results of the study reveal that the introduction of a VLE has played a significant role in fostering enhancements in the knowledge-sharing process among the franchisor and franchisees in the network. Moreover, the results indicate that VLEs play a significant role in overcoming geographical obstacles, thereby enabling efficient knowledge sharing between franchisees and franchisors operating in extensive territorial contexts. Finally, findings indicate that intracommercial competition acts as a prominent barrier, leading to low levels of cooperation and knowledge-sharing intent among franchisees within the network.

This study contributes to the existing knowledge by enhancing the understanding of how ICTs can facilitate knowledge sharing in organizations operating within franchising systems. Furthermore, this paper advances the comprehension of the role of networking franchising configuration and governance in supporting organizational improvements. Additional actionable insights are provided.

The purpose of this research is to determine the convenience of using a contract model as an integration mechanism for decision-making in a decentralized supply chain of small agricultural producers in a developing country, taking as hypothesis coordinated chain achieves better management. The analysis is based on information obtained by direct inquiry to 99 small producers in the region, about planning, production, marketing and distribution in the chain, supplemented with secondary information sources.

As a methodology an analysis of maturity in the chain based on the Capability Maturity Model Integration is done, whose evaluation is later analyzed as a fuzzy logic model, with the support of the fuzzy logic of the MATLAB toolbox, to study the convenience of the use of the contract against the other mechanisms, and to establish an approximation to the level of readiness of the chain toward integration.

Results obtained show that the small farmer supply chain studied, from a maturity perspective, has a strong disposition for the use of contracts as an integration mechanism.

The supply chain for small producers presents a high dispersion, little consolidated offer capacity and lack of coordination. Limitations in terms of information and criteria unification are a challenge for future research. Results have socioeconomic implications for small producers and can serve as a guide to formulate policies by the governments in Latin American countries.

As practical implications, it can be stated that the use of supply contracts is a real mechanism that can be implemented in this type of chain, to break the mistrust between the echelons and improve the supply chain performance. This research will allow to establish support programs from local governments for the sustainability and improving income of small producers. In addition, contracts will allow to formalize the linkage of small producers to a sustainable commercial network.

Small agricultural producers in developing countries live in unfavorable conditions, with socioeconomic limitations. This work offers an alternative for their productive activity development that will allow them access to marketing chains in a safe way and improve their living conditions.

Previous studies related to the maturity toward the chain integration and fuzzy logic as a hybrid methodology, were not found in the literature, and less even applied to a chain of small agricultural products.

In this chapter, we examine employee prosocial rule breaking as a response to organizations’ unfair treatment of customers. Drawing on the deontic perspective and research on third-party reactions to unfairness, we suggest employees engage in customer-directed prosocial rule breaking when they believe their organizations’ policies treat customers unfairly. Additionally, we consider employee, customer, and situational characteristics that enhance or inhibit the relationship between employees’ perceptions of organizational policy unfairness and customer-directed prosocial rule breaking.