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The suppliers are recognized as important external sources who can significantly contribute by working together with the buyer during the innovation process. Operational capabilities of suppliers can be one of the considerable factors when selecting them to participate in the activities at the front-end of innovation. However, proper understanding of the influence of operational capabilities of suppliers on front-end decision-making in apparel product innovation is still very limited particularly in the context of the Sri Lankan apparel industry. Therefore, this study aims to explore the influence of operational capabilities of suppliers on the front-end decision making in apparel product innovation in Sri Lanka.

Both semi-structured interviews and a questionnaire survey were used as data collection techniques. Six senior managers for the interviews and 60 participants for the questionnaire were randomly selected. All those who participated in interviews and the questionnaire respondents have been involved in the front-end of innovation in different apparel manufacturing organizations in Sri Lanka.

The results indicated that the operational capabilities of suppliers had a direct positive influence on front-end decision-making, and the suppliers’ production flexibility was found to be the most influential. Further, the results highlighted that 27.3% of the front-end decisions associated with apparel product innovation in Sri Lanka were influenced by the factors governing operational capabilities of suppliers.

The findings of the research will be beneficial for both academia and industry. The findings will be useful to extend the current understanding and make a noteworthy contribution to this topic and to provide useful and practical guidance to material suppliers and supporting industries who work with Sri Lankan apparel manufacturing.

Organization’s core competencies are acknowledged as most valuable assets and skills which contribute to enhance the ability of innovation, the competitive advantage and commercial success of the business. Although several researchers have studied the effects of core competencies on the success of an organization, no enough work has been carried out to investigate the effect of core competencies onfront-end decision-making. Apparel-specific studies in the area of core competencies relating to front-end decision-making are rarely found. Therefore, this paper aims to determine the impact of organizational core competencies on front-end decision-making in the apparel innovation.

A conceptual framework was developed focusing four groups of competencies; technological/ technical, customer, network/ partnership and financial competences and hypothesis were derived. Sixty participants in different companies across Sri Lanka were randomly selected based on their involvement in the front-end of the apparel innovation for questionnaire survey. The data were analyzed using the SPSS version 20 statistical software package. Spearman's rho correlation and Linear regression analysis were used to quantify the impact of the competencies on front-end decisions.

The factors of network competencies are found to be the most influentialon effective front-end decision-making in apparel innovation in Sri Lanka. These results strongly suggests strengthening companies’ ability to interact with partners who possess raw materials, machineries and technology know-how to facilitate efficient front-end decision-making. The next most influential are the factors of technological competencies. It highlights the importance of strengthening the companies’ own technical/ technological competencies to facilitate effective front- end decision-making in apparel innovation.

The findings of this research are of main interest to extend the current understanding on how different factors of organization’s core competencies influence on effective front-end decision-making in apparel innovation. Particularly, apparel domain practitioners will be motivated in implementing and nurturing these important/ and most influential competencies within their firms to facilitate front-end decision-making to achieve better results consistently.

The purpose of this paper is to develop mathematical relationships to calculate the loop length to knit compact plain knitted fabrics and to validate the model using the fabric parameters of commercial fabrics.

Ellipse defines the shape of the head of a knitted loop and straight lines define the arms of a knitted loop. The mathematical relationships developed relate the yarn count to the loop length of compact knitted fabrics. The experimental data and the data from previous similar research validate the accuracy of the mathematical model.

The model can calculate loop lengths to knit compact plain knitted fabrics in terms of thickness of the yarn and the coefficient defined to express the ratio of minor axis to major axis of the ellipse that defines the shape of the head of the loop. The mathematical model can deliver several loop lengths to produce compact plain knitted fabrics for different values of this coefficient. For commercial fabrics the error of the model was 0.53%.

The present model defines the head of the loop as an ellipse. The uniqueness of the present model is that several ellipses can exist for any given yarn thickness for a range of values assigned to the minor axis of the ellipse. The accuracy of the model against experimental data ascertains that the model is closer to the reality for commercial fabrics and proves the uniqueness of the model. Further, this model is an ideal and a simple model to introduce knitted loop configurations in teaching knitted fabric geometry.

Thermoplastic polymer fabrics are normally heat set to make them dimensionally stable. These fabrics in garment panel form may again be exposed to heat during the processes such as bonding, sublimation printing and cause to change their dimensions. The purpose of this paper is to investigate the response of polyester yarns in knitted fabrics to heat setting and post-heat treatments.

In this study, the thermal shrinkage behaviour of heat set polyester knitted fabrics when subjected to post-heat treatment processes are analyzed using differential scanning calorimetry (DSC) and analysis of fabric shrinkage. DSC is a thermo-analytical technique that measures the difference in the amount of heat needed to increase the temperature of the sample and the reference. A heat flux versus temperature curve is one of the results of a DSC experiment. The polymer structure and morphology of polyester heat-treated and post-heat–treated fabrics were determined by examining the DSC thermograms.

Heat setting and post-heat setting causes the effective temperature of polyester to change. Effective temperature occurred around 160°C for fabrics heat set at low temperatures and increases as the heat setting temperature increases. Post-heat treatments cause to elevate the effective temperature. Shrinkage of fabrics below the effective temperature is not statistically significant while the shrinkage at higher temperatures is significant. Effective temperature is the main determinant of thermal shrinkage behaviour of polyester.

The study reveals the significance of the effective temperature of polyester on heat treatments and post-heat treatments. The study revealed that heat-setting temperature is a primary determinant of the thermal stability of polyester fabric that are subjected to heat treatments.