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The purpose of this paper is to test and develop a method for generation and selection of six sigma projects. This is done by testing the use of the generation and selection method for six sigma projects (GSM_SSP) in a Brazilian manufacturing industry with the participation of managers, aiming to gather the user’s perspective and improvement opportunities for the approach itself.

The work adopts the action research (AR) approach once the researchers were busily involved in the training, implementation and use of the GSM_SSP. The intervention was performed in on a series of 15 workshops, with a group of managers, during six months.

The application of the eight steps of the GSM_SSP approach assisted the company’s management team to generate nine project candidates and also to select three six sigma projects. This study also finds and discusses barriers and lessons learned used to improve the GSM_SSP.

This study presents an example of how six sigma project generation and selection has been applied to a manufacturing industry by adapting AR to the process using the eight steps of GSM_SSP, demonstrating how the management team was involved. This study should be replicated in different companies because AR is limited in its generalization.

To the best of the authors’ knowledge, this study represents the first use of AR methodology in six sigma project selection. This study contributes a method that can generate and select six sigma projects. In doing so, the research offers a simple approach that can be used by managers. In addition, the steps of the approach before selection were explored.

The purpose of this study is to analyze the aspects of the organizational culture (OC) of companies operating in the Brazilian oil, gas and biofuels (O&G) sector based on semistructured interviews with managers of these organizations and its content analysis.

This research was conducted based on semistructured interviews with 12 managers of Brazilian O&G companies and analyzed with a computer-assisted qualitative data analysis software, namely, MAXQDA™.

The results make it possible to obtain the perception of managers about OC, generally understood as a set of attributes and variables of social order, supported by the historical–culturalist theoretical approach. Information about the explicit and implicit manifestation of culture, as well as the evaluation of the most appropriate research instruments and metrics, were also obtained after the interviews.

This study presents detailed results about OC and its characteristics in the perception of managers of the O&G companies that operate in the Brazilian market.

The authors propose the concept of “Autonomic Cycle for innovation processes,” which defines a set of tasks of data analysis, whose objective is to improve the innovation process in micro-, small and medium-sized enterprises (MSMEs).

The authors design autonomic cycles where each data analysis task interacts with each other and has different roles: some of them must observe the innovation process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the innovation process.

In this article, the authors identify three innovation sub-processes which can be applied to autonomic cycles, which allow interoperating the actors of innovation processes (data, people, things and services). These autonomic cycles define an innovation problem, specify innovation requirements, and finally, evaluate the results of the innovation process, respectively. Finally, the authors instance/apply the autonomic cycle of data analysis tasks to determine the innovation problem in the textile industry.

It is necessary to implement all autonomous cycles of data analysis tasks (ACODATs) in a real scenario to verify their functionalities. Also, it is important to determine the most important knowledge models required in the ACODAT for the definition of the innovation problem. Once determined this, it is necessary to define the relevant everything mining techniques required for their implementations, such as service and process mining tasks.

ACODAT for the definition of the innovation problem is essential in a process innovation because it allows the organization to identify opportunities for improvement.

The main contributions of this work are: For an innovation process is specified its ACODATs in order to manage it. A multidimensional data model for the management of an innovation process is defined, which stores the required information of the organization and of the context. The ACODAT for the definition of the innovation problem is detailed and instanced in the textile industry. The Artificial Intelligence (AI) techniques required for the ACODAT for the innovation problem definition are specified, in order to obtain the knowledge models (prediction and diagnosis) for the management of the innovation process for MSMEs of the textile industry.

This study aims to conduct a pertinent assessment of the concept of business competitiveness and how Portugal can progress in that field, for the sake of becoming a more sustainable and wealth-creator economy.

The research was elaborated with 65 in-depth interviews with expert persons from the Portuguese business ecosystem, who were asked to reflect on the state of the economy and competitiveness of the country.

There is much room for improvement in almost all areas of activity, in particular by promoting an innovative, value-adding and exporting private sector and a lighter and more efficient public sector. The conclusions point to modernisation of the Portuguese economy as a way of making it more competitive in a highly competitive and demanding global scenario.

To the best of the authors’ knowledge, it is the first time that a reflection with experts of the local Portuguese economy has been carried out, especially after a difficult period of COVID.

Manufacturers increasingly resort to digital transformation to shape their competitiveness in the digital economy era, while supply chain (SC) collaborative innovation helps them cope with market uncertainties. However, whether and how digital transformation can facilitate SC collaborative innovation remain unclear. To address this gap, we aims to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

We use partial least squares-structural equation modelling (PLS-SEM) with a sample of 210 Chinese manufacturers to investigate the effects of digital transformation (strategy and capability) on SC collaborative (process and product) innovation and market performance.

The results show that digital strategy and capability positively impact SC collaborative process and product innovation, which enhances market performance. In addition, SC collaborative innovation mediates the relationship between digital transformation and market performance.

This study contributes to the literature by identifying how digital transformation drives SC collaborative innovation towards improving market performance and providing practical guidance for enterprises in promoting digital transformation and SC collaborative innovation.

To know the digital competence of rural teachers to carry out the tutoring process with members of the educational community through digital resources (teacher-student, teacher-families and teacher-teaching team). As specific objectives, gender, teaching specialties, interaction between gender*teaching speciality, and significant predictors were analysed.

The research was quantitative, with a non-experimental, cross-sectional, descriptive and inferential design.

The results showed an explorer-expert teacher, where the generalist teachers had a superior competence compared to the rest of the specialties. Gender and teaching speciality were significant predictors in the communication that the teacher has with all the agents involved, while the interaction of both predictors was only significant between the teacher-teaching team and teacher-families.

Another issue worth considering relates to the development of the classification tree for the use of digital resources in tutorial action. Due to lack of space, the proposal has focused on gender and particular subjects, but it would be interesting to focus on the dimensions of the instrument with regard to tutorial action with the different agents (students, teaching staff and families).

After reviewing the literature, the authors can conclude that very little quantitative research is focused on the level of self-perception of digital competence of teachers in rural schools. Furthermore, the teaching speciality of teachers has up until now hardly been taken into account as a variable that can determine the levels of digital competence. Not many studies have analysed the use of digital resources to communicate with the different members of the educational community.

The aim of this study reported in this paper was to explore the application of operational excellence methodologies in a global context.

A qualitative interview approach was used to understand the current state, benefits, challenges, success factors, tools and techniques of operational excellence methodology implementation with relevance to logistics companies worldwide. About 16 interviews were undertaken with practitioners working in leading companies and with leading academics in Asia, Europe, Africa, North America, South America and Australia.

The findings show that operational excellence methodologies including Lean, Six Sigma, Lean Six Sigma and Agile can apply in logistics firms to improve operations and productivity and save costs. Top management support and involvement play an important role in the success of operational excellence projects in the logistics service.

The findings will be of interest to top and middle managers and logistics practitioners, with a dual aim of improving logistics performance and saving costs.

The present study has been one of the first global study attempts to explore the implementation of operational excellence methodologies in the logistics sectors.

In the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0) concept.

The study employs a comprehensive methodology that includes a systematic literature review, workshop, grounded theory and interpretive structural modeling. Various dimensions concerning I4.0 sustainability are tested and evaluated using a questionnaire design followed by hypothesis formulation. Further, grounded theory is used to extract the key solution dimensions that capture the essence of I4.0 implementation in SMEs. Finally, the solution dimensions for I4.0 sustainability are modeled using the ISM approach to understand the structural interdependencies among them, and Matrice d'Impacts Croisés Multiplication Applied to a Classification (MICMAC) analysis is done to understand the driving and dependence power among these dimensions.

The study identified 14 solution dimensions for the implementation of I4.0 in SMEs for sustainable development. Out of the 14 solution dimensions, human resource training programs (D4) appear at level 11, followed by top management commitment (D1), strategic collaborations (D3) and coordination among key stakeholders (D5) at level 2 in the hierarchical interpretive structural modeling (ISM) model. Also, these dimensions have an effect size of more than 0.50 which indicates a substantial correlation between the sustainability dimensions and Industry 4.0 implementation in SMEs.

The study contributes to the overall goal of fostering sustainability within the SME sector, which can pave the way for various stakeholders for the successful implementation of I4.0 sustainable solution dimensions.

This paper examines the factors which impact the behavioral intentions toward cryptocurrency based on signaling theory.

Data were collected through online questionnaire, and responses from 223 individuals in Lebanon were analyzed through SEM technique using Amos 24.

The outcomes portrayed the positive effect of perceived benefits and trust in cryptocurrency on behavioral intentions toward cryptocurrency; while not supporting the hypothesized influence of herd behavior and regulatory support.

This paper is among the first studies to adopt Signaling Theory (ST) in the cryptocurrency behavioral intentions research. Moreover, it is of the initial efforts in Lebanon and Middle East in evaluating behavioral intentions to use cryptocurrency, and it provide insights for future researchers, crypto project owners, crypto investors and crypto trading platforms.

The paper aims to evaluate drying performance of earth mortar by solar drying for more durability, minimize pathologies in traditional construction and determine the influence of temperature and humidity on the microstructure of earth mortar using static gravimetric method.

A convective solar dryer was used for the pretreatment of building and solid materials for construction.

The humidity influences the mortar sorption – surface water sorption of earth mortar increased with increasing temperature.

The study used a novel method for pretreatment building materials by using solar dryer.