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This paper aims to clarify the impact of the entrepreneurial training on a Tunisian trainee’s entrepreneurial cognitions and intention. An interactive cognitive perspective was adopted to test the interaction effect between the entrepreneurial cognitions: the perceived entrepreneurial self-efficacy, the perceived entrepreneurial feasibility and entrepreneurial desirability. A research model was built showing several relationships between entrepreneurial training, cognitions and intention.

A survey was conducted on a convenience sample of 240 participants in four business incubators. The maximum-likelihood test was used as a structural equation modeling method to test the model.

The results show the importance of the entrepreneurial training in the development of entrepreneurial cognitions. Further, the findings, to some extent, validate the interaction between the entrepreneurial cognitive patterns. However, entrepreneurial intention was only predicted through the entrepreneurial desirability. Several implications are discussed at the end of this paper.

The findings seem interesting insofar, as they show the importance of entrepreneurial trainings in the entrepreneurial intention development through the enhancement of desirability. This process can be triggered by a training program that contains case studies, success stories and conferences to make the youth enthusiastic about self-employment.

The significant impact of the entrepreneurial training on trainees’ cognitions should encourage governments and incubators to promote entrepreneurial training programs to enhance the youths’ willingness to create their own businesses. The findings in this paper seem interesting insofar as they show the importance of entrepreneurial trainings in the entrepreneurial intention development through the enhancement of desirability. This process can be triggered by a training program that contains case studies, success stories and conferences to make the youth enthusiastic about self-employment.

This paper aims to examine an investigation of high-pressure coolant (HPC) drilling process with regard to experimental models of output parameters, effect of input parameters on output parameters and simultaneous optimization of the output parameters.

Experimental plan was designed using response surface method and experiments were conducted on HPC drilling set up. Measurements for output parameters were carried out and mathematical models were obtained. Multi response optimization using a composite desirability function approach was used to obtain optimum values of input parameters for simultaneous optimization of output parameters.

Optimal value of input parameters for optimization of HPC drilling process were obtained as; coolant pressure: 21 bar, spindle speed: 3,970 rpm, feed rate: 0.084 mm/rev and peck depth: 5.50 mm. The composite desirability obtained is 0.9412, which indicates that the performance of HPC drilling process was significantly optimized. Developed mathematical models of the output parameters accurately represent the entire design space under investigation.

This is the first study that involves variation of higher coolant pressure and investigation of HPC drilling process using response surface methodology and multi response optimization technique with desirability function.

The purpose of this study is to provide a method for Lean Six Sigma (LSS) improvement projects that may aid LSS practitioners to plan and conduct robust and lean product/process optimization studies for complex and constrained products, such as those encountered in food industry operations.

The technique is to be used for replicated LSS product experimentation on multiple effects elicited on several product traits. The authors compress replicated information reducing each response to simpler lean and robust median and range response components. Then, the desirability method is utilized to optimize concurrently location and dispersion contributions.

The suggested method is demonstrated with a case study drawn from the area of food development where cocoa-cream filling for a large-scale croissant production operation undergoes a robust screening on two crucial characteristics – viscosity and water activity – that influence product and process performance as well as product safety.

The proposed method amalgamates concepts of fractional factorial designs for expedient experimentation along with robust multi-factorial inference methods easily integrated to the desirability function for determining significant process and product effects in a synchronous multi-characteristic improvement effort. The authors show that the technique is not hampered by ordinary limitations expected with mainstream solvers, such as MANOVA. The case study is unique because it brings in jointly lean, quality and safety aspects of an edible product. The showcased responses are unique because they influence both process and product behavior. Lean response optimization is demonstrated through the paradigm.

Research has found that stereotypes affect occupational choices, but there has been almost no research on how they specifically affect the choice of becoming an entrepreneur. This study bridges different fields of research by combining theories on entrepreneurial intent, self-esteem, and stereotypes. The author argues that in situations of insufficient information individuals assess prospective careers in commercial and social entrepreneurship by means of stereotypes, and the author is the first to explore the influence of commercial and social entrepreneurial stereotypes on an individual’s intention to start a commercial (for-profit) or social (not for-profit) venture. The author uses the framework outlined by the stereotype content model to disclose the existence of distinct stereotypes for commercial and social entrepreneurs exist and, thereafter, the author analyzes the influences of both entrepreneurial stereotypes on the specific startup intentions. The author test the hypotheses with unique survey data from a sample of German non-entrepreneurs which reveals that commercial entrepreneurs are seen as competent but cold, whereas social entrepreneurs are regarded as warm but incompetent. Using structural equation modeling and multi-group analysis, the data implies that higher levels of perceived warmth and competence of commercial entrepreneurs have a positive indirect effect on commercial startup intentions. No such effect was found for social startup intentions; however, the results indicate that a higher societal status of social entrepreneurs exerts a positive indirect impact on the intention to start a social business. The author discusses the practical implications of our approach and point out avenues for future research.

There are process uncertainties and material property variations during laminated steel sheet forming, and those fluctuations may result in non-reliable forming quality issues such as fracture and delamination. Additionally, the optimization of sheet forming process is a typical multi-objective optimization problem. The target is to find a multi-objective design optimization and improve the process design reliability for laminated sheet metal forming. The paper aims to discuss these issues.

Desirability function approach is adopted to conduct deterministic multi-objective optimization, and response surface is used as meta-model. Reliability analysis is conducted to evaluate the robustness of the multi-objective design optimization. The proposed method is implemented in a step-bottom square cup drawing process. First, forming process parameters and three noise factors are assumed as probability variables to conduct reliability assessment of the laminated steel sheet forming process using Monte Carlo simulation. Next, only two forming process parameters, blank holding force and frictional coefficient, are considered as probability variables to investigate the influence of the forming parameter deviation on the variance of the response using the first-order second-moment method.

The results indicate that multi-objective design optimization using desirability function method has high efficiency, and an optimized robust design can be obtained after reliability assessment.

The proposed design procedure has potential as a simple and practical approach in the laminated steel sheet forming process.

To reduce environmental impact caused by excessive use of ordinary Portland cement (OPC) and to mitigate scarcity of base materials such as natural coarse aggregate (NCA), industrial by-products can be carefully used as alternatives to OPC and NCA, in production of concrete. This paper aims to describe the performance of using ground granulated blast furnace slag (GGBS), fly ash (FA) as a complete replacement to OPC and ferrochrome slag (FCS) as replacement to NCA in production of novel FCS based alkali activated slag/fly ash concretes (AASFC) and evaluate their performance at elevated temperatures.

Two control factors with three levels each i.e. FA (0, 25 and 50 per cent by weight) and FCS (0, 50 and 100 per cent by volume) as a GGBS and NCA replacement, respectively, were adopted in AASFC mixtures. Further, AASFC mixture specimens were subjected to different levels of elevated temperature, i.e. 200°C, 400°C, 600°C and 800°C. Compressive strength and residual compressive strength were considered as responses. Three different optimization techniques i.e. gray relational analysis, technique for order preference by similarity to ideal solution and Desirability function approach were used to optimize AASFC mixtures subjected to elevated temperatures.

As FA replacement increases in FCS based AASFC mixtures, workability increases and compressive strength decreases. The introduction of FCS as replacement to NCA in AASFC mixture did not show any significant change in compressive strength under ambient condition. AASFC produced with 75 per cent GGBS, 25 per cent FA and 100 per cent FCS was found to have excellent elevated temperature enduring properties among all other AASFC mixtures studied.

Although several studies are available on using GGBS, FA and FCS in production of OPC-based concretes, present study reports the performance of novel FCS based AASFC mixtures subjected to elevated temperatures. Further, GGBS, FA and FCS used in the present investigation significantly reduces CO₂ emission and environmental degradation associated with OPC production and NCA extraction, respectively.

The purpose of this paper is to optimise the process parameters, namely, fibre orientation angle, helix angle, spindle speed, and feed rate in milling of glass fibre-reinforced plastic (GFRP) composites using grey relational analysis (GRA) and desirability function analysis (DFA).

In this work, experiments were carried out as per the Taguchi experimental design and an L27 orthogonal array was used to study the influence of various combinations of process parameters on surface roughness and delamination factor. As a dynamic approach, the multiple response optimisation was carried out using GRA and DFA for simultaneous evaluation. These two methods are best suited for multiple criteria evaluation and are also not much complicated.

The process parameters were found optimum at a fibre orientation angle of 15°, helix angle of 25°, spindle speed of 6,000 rpm, and a feed rate of 0.04 mm/rev. Analysis of variance was employed to classify the significant parameters affecting the responses. The results indicate that the fibre orientation angle is the most significant parameter preceded by helix angle, feed rate, and spindle speed for GFRP composites.

An attempt to optimise surface roughness and delamination factor together by combined approach of GRA and DFA has not been previously done.

The design of a cellular manufacturing system requires that a machine population be partitioned into machine groups called manufacturing cells. A new graph partitioning heuristic is proposed to solve the manufacturing cell formation problem (MCFP). In the proposed heuristic, The MCFP is represented by a graph whose node set represents the machine cluster and edge set represents the machine‐pair association weights. A graph partitioning approach is used to form the manufacturing cells. This approach offers improved design flexibility by allowing a variety of design parameters to be controlled during cell formation. The effectiveness of the heuristic is demonstrated by comparing it to two MCFP published solution methods using several problems from the literature.

The main purpose of the present work is to study the multi response optimization of dissimilar friction stir welding (FSW) process parameters using Taguchi-based grey relational analysis and desirability function approach (DFA).

The welded sheets were fabricated as per Taguchi orthogonal array design. The effects of tool rotational speed, transverse speed and tool tilt angle process parameters on ultimate tensile strength and hardness were analyzed using grey relational analysis, and DFA and optimum parameters combination was determined.

The tensile strength and hardness values were evaluated from the welded joints. The optimum values of process parameters were estimated through grey relational analysis and DFA methods. Similar kind of optimum levels of process parameters were obtained through two optimization approaches as tool rotational speed of 1150 rpm, transverse speed of 24 mm/min and tool tilt angle of 2° are the best process parameters combination for maximizing both the tensile strength and hardness. Through these studies, it was confirmed that grey relational analysis and DFA methods can be used to find the multi response optimum values of FSW process parameters.

In the present study, the FSW is performed with L9 orthogonal array design with three process parameters such as tool rotational speed, transverse speed and tilt angle and three levels.

Aluminium alloys are widely using in automotive and aerospace industries due to holding a high strength to weight property.

Very limited work had been carried out on multi objective optimization techniques such as grey relational analysis and DFA on friction stir welded joints made with dissimilar aluminium alloys sheets.

There is reason to believe that an ethically minded approach to hiring and the development of an ethical context should be associated with incremental decreases in employees’ perceptions of ethical conflict. It is also likely that the selection of ethical employees, and the reduced ethical conflict that follows, are positively related to employees’ positive work attitudes. The purpose of this paper is to test these relationships.

Using a self-report questionnaire, information was collected from 187 employees working for a medium-sized financial services organization with offices located primarily in the Midwestern USA.

Results of structural equation modeling indicated that employees’ perceptions of ethics-related selection were negatively related to perceived ethical conflict, and that reduced ethical conflict and enhanced ethics-related selection were associated with an increased positive work attitude, which was comprised of job satisfaction, an intention to stay, and organizational commitment.

The results cannot prove causal association between the constructs, and the use of one focal firm limits generalizability.

Organizational leaders and HR professionals should develop ethics-based hiring practices to reduce ethical conflict and strengthen a company's ethical context.

This investigation is relevant because strong relationships among ethics-related hiring, ethical conflict, and positive work attitudes would suggest that companies must use ethical selection criteria and maintain an ethical culture/climate that meets or exceeds employees’ expectations about ethics. Furthermore, this study adds to the relatively few published works exploring the relationship between ethical conflict and work attitudes.