Search results

The purpose of this paper is to analyse dynamic drape behaviours of 100% wool woven suiting fabrics considering real-time usage.

Dynamic drape coefficients of 100% wool woven fabrics were measured at different rotation speeds (25, 75, 125 and 175 rpm) with a commercially used fabric drape tester which works on image processing principle. Average daily walking speed of male and female volunteers was determined and the closest rotation speed was selected to calculate dynamic drape coefficient at walking (DDCw). Besides, bending rigidity and shear deformation properties, which are known to be related to the static drape behaviours of the fabrics, were also measured and the relationships between these parameters and DDCw were examined.

As a result of the experimental study, it was found that dynamic drape coefficients become greater, which means the fabrics take flatter position, with the increase of the rotation speed. In addition, it was also seen that parameters known to be related to static drape behaviours such as unit weight and bending stiffness have less effect on the dynamic drapes of fabrics. For the estimation of dynamic drape behaviour of fabrics, parameters such as static perimeter, dynamic perimeter, etc. are found more significant.

To date, although studies about dynamic drape behaviours of the fabrics claimed that dynamic drape gives more realistic results for in wearer experience, few of them focused on the rotation speed of dynamic drape tester for real-time usage. As dynamic drape behaviours of fabrics may differ for different rotation speed, determining appropriate speed in accordance with real-time usage gives more realistic results.

This paper aims to develop an assembly behaviour dynamic model of reheat stop valve assembly under run‐time situations and combined (assembly error, friction, fluid dynamics and thermal load behaviour) and to carry out assembly process evaluation and optimisation.

The fluid dynamic behaviour analysis is carried out for the dynamic torque characteristics of reheat stop valve and for the thermal load distribution of the valve shaft‐bush subassembly, which is used for evaluating the thermal deformation of valve shaft by using of finite elements method. The assembly behaviour dynamic model is developed by multibody dynamics theory, which is as the basis of developing virtual prototyping platform for analysing and evaluating the current assembly process.

It is revealed that the deformation (ε) of valve shaft due to the thermal load, and the assembly coaxial error (e) can change the motion clearance remarkably, which lead the dynamic properties and performance of reheat stop valve changed greatly. The current assembly behaviour variable are not optimum and the initial design clearance between valve shaft and bush 4# can be optimised by the developed virtual prototyping platform on the basis of ADAMS® API. The results of evaluation for the assembly behaviour reveal the well dynamic characteristics of reheat stop valve with the optimum assembly behaviour variable. This will be useful for improving the current assembly process of reheat stop valve.

The present assembly behaviour dynamic model based on virtual prototyping for optimum assembly process design uses only single objective optimisation (the most important clearance between valve shaft and bush 4#). For a complete optimum assembly process design has to be carried out with other three clearance variables (the clearance between valve shaft and bush 1#, bush 2# and bush 3#) together.

The present analysis provides some benchmarks for improving the current assembly process. In practice, the assembly coaxial tolerance of valve shaft‐bush subassembly and the initial design clearances must be limited strictly.

This paper provides a methodology for analysis and evaluation of reheat stop valve assembly behaviour with the consideration of combined environmental behaviours. Based on this methodology, it is possible to develop an assembly behaviour dynamic model, and further, to develop a virtual prototyping platform for analysing and evaluating the assembly process which will offer help to designers for improving the reheat stop valve assembly process.

The purpose of this study is to explore the effect of stitch type and stitch direction on the dynamic drape behavior of the woven fabric.

In this paper, the effectiveness of stitch type and stitch directions on dynamic drape behaviors were investigated. Fabric parts were sewn together with two types of the stitch (lockstitch and overlock stitch) on three different stitch directions (warp, weft and bias (45°)). The static drape coefficients (SDC) of unsewn and sewn fabrics were measured according to the image process method. Dynamic drape coefficients (DDC) of fabrics were also measured using the same method at six different (25, 50, 75, 100, 125, 150 rpms) rotation speeds. Additionally, bending length and bending rigidity were measured using the Cantilever test method.

Experimental results showed that stitch type and stitch directions are effective on the dynamic drape behaviors of the fabric. Overlock stitch resulted in greater DDC than the lock stitch. For both of the stitch type, DDC for the stitch on the warp direction are greater than the stitch on the weft and bias direction for all speeds. In addition, bending length, hence the bending rigidity, are greater for overlock stitch type and always weft direction resulted in greater than the warp and bias direction.

Fabric drape is vital for garment appearance and is gaining popularity with the advancement of virtual technology, enabling virtual visualization of garments. While previous studies have predominantly examined either the static or dynamic drape behavior of individual fabric panels, or solely focused on the static drape behavior of sewn fabrics, this study acknowledges the significance of incorporating the influence of stitch type and direction on dynamic drape behaviors. Considering that fabrics are sewn together to create garments and that DDC provides a more accurate representation of real-time fabric behavior compared to SDC, this research makes a valuable contribution to the existing literature by investigating the impact of stitch type and direction specifically on DDC.

This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.

The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.

The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.

It uncovers subjects' intelligent interactively trading behaviors.

The purpose of this paper is to examine whether heterogeneity in alliance capability development can be attributed to the use of certain intra-firm leadership behaviors. The author suggests that transformational leadership behaviors have a stronger influence on the development of innovation (dynamic) capabilities of a strategic alliance than on the development of operational (substantive) capabilities, and that transactional leadership behaviors mainly preserve operational capabilities.

The author used in-depth expert interviews and a questionnaire survey comprising 369 strategic business alliances to develop and test the theoretical framework.

The data confirm the positive relationship between transformational leadership and the development of innovation and operational capabilities. Yet, transactional leadership behaviors are not only associated with operational capability development, but notably contribute to the development of innovation capabilities.

While the study focusses on leadership, there are many more factors that impact on the strategic ability of alliances to deliver innovation outcomes. Other limitations are the multiple levels of analysis in the theoretical model, newly developed measurement scales and that responses for the empirical study only come from one partner of the alliance.

The study suggests advantages of exercising the full range of leadership behaviors when seeking innovation alliance outcomes.

This research contributes to the strategic management, innovation, leadership, and alliances literature by providing new and empirical validation of the effectiveness of particular leadership behaviors in collaborative settings.

While awareness of social, health and environmental consequences of our collective action are growing, additional efforts are required to deliver the changes needed to affect the greater good. A review of the literature indicates that research efforts may be misdirected. Drawing from empirical data where a total of 161 caregivers reported changes in their child’s walking behaviour following a month long social marketing program, the purpose of this paper is to illustrate differences between behaviour and behaviour change.

Data analyses involved use of multiple linear regression on static followed by dynamic measures of behaviour and behavioural change and their respective determinants. The static model used variables reported by caregivers after program participation, while the dynamic measures used change scores for all variables reported (T2-T1).

Results from the static model showed that only intentions and barriers explained behaviour at Time point 2. In contrast, findings from the dynamic data analysis indicated that a change in injunctive norms (important others’ approval of the child walking to school) explained a change in walking to and from school behaviour. Taken together, the results of the current paper suggest research attention needs to be directed towards dynamic methodologies to re-centre research attention on behavioural change and not behaviour, which dominates current practice.

This paper offers a foundational step to support the research community to redirect research efforts from understanding behaviour to focussing research design and theoretical development on behavioural change. Theories of behaviour change are needed to affect the greater good.

The authors advance a model theorizing how new ventures elicit citizenship behaviors to cultivate dynamic capabilities that help bolster survival in their nascent years of operations—a characteristically resource-scarce and turbulent context.

Drawing on and integrating research on citizenship behaviors with dynamic capabilities, the authors develop a theory that new ventures that are better able to evoke a combination of affiliative and challenging citizenship behaviors from their wider entrepreneurial team (i.e. internal, and external stakeholders) are more adept at mitigating the liabilities of smallness and newness. As these behaviors are spontaneous and not explicitly remunerated, new ventures become stronger at utilizing their limited resource base for remaining lean and agile. Further, key boundary conditions are theorized that the sociocultural norms the venture is embedded within serve to heighten/attenuate the degree to which entrepreneurs can effectively cultivate dynamic capabilities from their team's “extra mile” behaviors.

The propositions extend a rich body of research on citizenship behaviors into the new venture domain. As all new ventures face the challenge of overcoming liabilities of newness, models that help understand why some are more adept at overcoming this and why others fail, hold substantive practical utility.

This research is the first to unpack how citizenship behaviors manifest among an extended range of stakeholders traditionally overlooked in new venture teams research and the mechanism for how this links to venture survival.

The purpose of this paper is to construct a proportion-integral-type (PI-type) memristor, which is different from that of the previous memristor emulator, but the constructing memristive chaotic circuit possesses line equilibrium, leading to the emergence of the initial conditions-related dynamical behaviors.

This paper presents a PI-type memristor emulator-based canonical Chua’s chaotic circuit. With the established mathematical model, the stability region for the line equilibrium is derived, which mainly consists of stable and unstable regions, leading to the emergence of bi-stability because of the appearance of a memristor. Initial conditions-related dynamical behaviors are investigated by some numerically simulated methods, such as phase plane orbit, bifurcation diagram, Lyapunov exponent spectrum, basin of the attraction and 0-1 test. Additionally, PSIM circuit simulations are executed and the seized results validate complex dynamical behaviors in the proposed memristive circuit.

The system exhibits the bi-stability phenomenon and demonstrates complex initial conditions-related bifurcation behaviors with the variation of system parameters, which leads to the occurrence of the hyperchaos, chaos, quasi-periodic and period behaviors in the proposed circuit.

These memristor emulators are simple and easy to physically fabricate, which have been increasingly used for experimentally demonstrating some interesting and striking dynamical behaviors in the memristor-based circuits and systems.

The purpose of this paper is to explore the dynamic nature of behaviour change over time and to gain insights into the effectiveness of social marketing efforts at three different intervention points under three different delay time conditions.

A system dynamics simulation modelling approach was used.

The findings showed that the effectiveness of social marketing interventions at different points of intervention and delay times is dependent on complex dynamic system interactions and feedback loops.

As the dynamic simulation model was an abstraction or simplified representation, it was only useful to gain insights into generalised patterns of behaviour over time.

The paper provided practical guidance to social marketers’ intent on gaining insights into “where to do” and “when to do” social marketing rather than “how to do” social marketing.

The paper provided theoretical and practical insights into the temporal nature of behaviour change and the effectiveness of social marketing interventions in influencing behaviour over time.

The purpose of this paper is to identify potential competitive relationships among brands by analyzing the dynamic clicking behavior of consumers.

Consumer sequential online click data, collected from JD.com, is used to analyze the dynamic competitive relationship between brands. It is found that the competition intensity across categories of products can differ considerably. Consumers exhibit big differences in purchasing time of durable-like goods, that is, the purchasing probability of such products changes considerably over time. The local polynomial regression model (LPRM) is used to analyze the relationship between brand competition of durable-like goods and the purchasing probability of a particular brand.

The statistical results of collective behaviors show that there is a 90/10 rule for the category durable-like goods, implying that ten percent of the brands account for 90 percent market share in terms of both clicking and purchasing behavior. The dynamic brand cognitive process of impulsive consumers displays an inverted V shape, while cautious consumers display a double V shaped cognitive process. The dynamic consumers’ cognition illustrates that when the brands capture a half of the click volume, the brands’ competitiveness reaches to its peak and makes no significant different from brands accounting for 100 percent of the click volume in terms of the purchasing probability.

There are some limitations to the research, including the limitations imposed by the data set. One of the most serious problems in the data set is that the collected click-stream is desensitized severely, restricting the richness of the conclusions of this study. Second, the data set consists of many other consumer behavioral data, but only the consumer’s clicking behavior is analyzed in this study. Therefore, in future research, the parameters brand browsing by consumers and the time of browsing in each brand should be added as indicators of brand competitive intensity.

The authors study brand competitiveness by analyzing the relationship between the click rate and the purchase likelihood of individual brands for durable-like products. When the brand competitiveness is less than 50 percent, consumers tend to seek a variety of new brands, and their purchase likelihood is positively correlated with the brand competitiveness. Once consumers learn about a particular brand excessively among all other brands at a period of time, the purchase likelihood of its products decreases due to the thinner consumer’s short-term loyalty the brand. Till the brand competitiveness runs up to 100 percent, consumers are most likely to purchase a brand and its product. That indicates brand competitiveness maintain 50 percent of the whole market is most efficient to be profitable, and the performance of costing more to improve the brand competitiveness might make no difference.

There are many studies on brand competition, but most of these research works analyze the brand’s marketing strategy from the perspective of the company. The limitation of this research is that the data are historical and failure to reflect time-variant competition. Some researchers have studied brand competition through consumer behavior, but the shortcoming of these studies is that it does not consider sequentiality of consumer behavior as this study does. Therefore, this study contributes to the literature by using consumers’ sequential clicking behavior and expands the perspective of brand competition research from the angle of consumers. Simultaneously, this paper uses the LPRM to analyze the relationship between consumer clicking behavior and brand competition for the first time, and expands the methodology accordingly.