Search results

The purpose of this paper is to analyze numerically the blowup in finite time of the solutions to a one-dimensional, bidirectional, nonlinear wave model equation for the propagation of small-amplitude waves in shallow water, as a function of the relaxation time, linear and nonlinear drift, power of the nonlinear advection flux, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of three types of initial conditions.

An implicit, first-order accurate in time, finite difference method valid for semipositive relaxation times has been used to solve the equation in a truncated domain for three different initial conditions, a first-order time derivative initially equal to zero and several constant wave speeds.

The numerical experiments show a very rapid transient from the initial conditions to the formation of a leading propagating wave, whose duration depends strongly on the shape, amplitude and width of the initial data as well as on the coefficients of the bidirectional equation. The blowup times for the triangular conditions have been found to be larger than those for the Gaussian ones, and the latter are larger than those for rectangular conditions, thus indicating that the blowup time decreases as the smoothness of the initial conditions decreases. The blowup time has also been found to decrease as the relaxation time, degree of nonlinearity, linear drift coefficient and amplitude of the initial conditions are increased, and as the width of the initial condition is decreased, but it increases as the viscosity coefficient is increased. No blowup has been observed for relaxation times smaller than one-hundredth, viscosity coefficients larger than ten-thousandths, quadratic and cubic nonlinearities, and initial Gaussian, triangular and rectangular conditions of unity amplitude.

The blowup of a one-dimensional, bidirectional equation that is a model for the propagation of waves in shallow water, longitudinal displacement in homogeneous viscoelastic bars, nerve conduction, nonlinear acoustics and heat transfer in very small devices and/or at very high transfer rates has been determined numerically as a function of the linear and nonlinear drift coefficients, power of the nonlinear drift, viscosity coefficient, viscous attenuation, and amplitude, smoothness and width of the initial conditions for nonzero relaxation times.

The nose length is the key design parameter affecting the aerodynamic performance of high-speed maglev train, and the horizontal profile has a significant impact on the aerodynamic lift of the leading and trailing cars Hence, the study analyzes aerodynamic parameters with multi-objective optimization design.

The nose of normal temperature and normal conduction high-speed maglev train is divided into streamlined part and equipment cabin according to its geometric characteristics. Then the modified vehicle modeling function (VMF) parameterization method and surface discretization method are adopted for the parametric design of the nose. For the 12 key design parameters extracted, combined with computational fluid dynamics (CFD), support vector machine (SVR) model and multi-objective particle swarm optimization (MPSO) algorithm, the multi-objective aerodynamic optimization design of high-speed maglev train nose and the sensitivity analysis of design parameters are carried out with aerodynamic drag coefficient of the whole vehicle and the aerodynamic lift coefficient of the trailing car as the optimization objectives and the aerodynamic lift coefficient of the leading car as the constraint. The engineering improvement and wind tunnel test verification of the optimized shape are done.

Results show that the parametric design method can use less design parameters to describe the nose shape of high-speed maglev train. The prediction accuracy of the SVR model with the reduced amount of calculation and improved optimization efficiency meets the design requirements.

Compared with the original shape, the aerodynamic drag coefficient of the whole vehicle is reduced by 19.2%, and the aerodynamic lift coefficients of the leading and trailing cars are reduced by 24.8 and 51.3%, respectively, after adopting the optimized shape modified according to engineering design requirements.

The purpose of this paper is to explore earlier stages of complex products and systems (CoPS) innovations, investigating how technology development can be coordinated.

This paper uses a case study methodology, adopting an abductive logic, characterized by a nonlinear and iterative process of systematic confrontations between theoretical framework, empirical fieldwork and case analysis. Specifically, the authors study the Swedish aerospace network, which distinctly represents the CoPS characteristics of intense technology development with long-term goals and project-based activities with universities, research institutes, small medium enterprises and leading firms.

By adding the network perspective in the CoPS literature, the authors found that technology development can be coordinated within the technological and the business dimensions and according to different strategic nets. Also, the authors found that strategic nets co-evolve when their related projects are connected and advance in maturity, and their actors change their network position.

Current research on CoPS often recognizes that the survival and growth of a firm depend on its ability to coordinate innovative projects that are usually implemented during technology development. The findings contribute to this literature by showing how such projects can be implemented through agenda construction and the simultaneous coordination of strategic nets, leading to the synchronization of resources and activities. As such, this study’s framework offers a novel and integrative view of how the short-run and long-run strategies of leading firms can be aligned, and how other actors can contribute to the direction of the innovation path.

Drawing upon the importance of research and development (R&D) alliances in driving firm innovation performance, extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance. Despite such analyzes, research has generally underestimated the configurations of partner attributes leading to firm innovation performance. This research gap is interesting to explore, as firms involved in R&D alliances usually face a combination of partner attributes. Moreover, gaining a better understanding of how R&D partner attributes tie into configurations is an issue that is attracting particular interest in coopetition research and alliance literature. This paper aims to obtain a better knowledge of this underrated, but important, aspect of alliances by exploring what configurations of R&D alliance partner attributes lead firms involved in R&D alliances to achieve high innovation performance. To tackle this question, first, this study reviews the extant literature on R&D alliances by relying on the knowledge-based view of alliances to identify the most impactful partner attributes on firms’ innovation performance. This paper then applies a fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of R&D alliance partner attributes that lead firms involved in R&D alliances to achieve high innovation performance.

This study selects 27 R&D alliances formed worldwide in the telecom industry. This paper explores the multiple configurations of partner attributes of these alliances by conducting a fsQCA.

The findings of the fsQCA show that the two alternate configurations of partner attributes guided the firms involved in these alliances to achieve high innovation performance: a configuration with extensive partner technological relatedness and coopetition, but no experience; and a configuration with extensive partner experience and competition, but no technological relatedness.

The research highlights the importance of how partner attributes (i.e. partner technological relatedness, partner competitive overlap, partner experience and partner relative size) tie, with regard to the firms’ access to external knowledge and consequently to their willingness to achieve high innovation performance. Moreover, this paper reveals the beneficial effect of competition on the innovation performance of the firms involved in R&D alliances when some of the other knowledge-based partner attributes are considered. Despite these insights for alliance and coopetition literature, some limitations are to be noted. First, some of the partners’ attributes considered could be further disentangled into sub-partner attributes. Second, other indicators might be used to measure firms’ innovation performance. Third, as anticipated this study applies fsQCA to explore the combinatory effects of partner attributes in the specific context of R&D alliances in the telecom industry worldwide and in a specific time window. This condition may question the extensibility of the results to other industries and times.

This study also bears two interesting implications for alliance managers. First, the paper suggests that R&D alliance managers need to be aware that potential alliance partners have multiple attributes leading to firm innovation performance. In this regard, partner competitive overlap is particularly important for gaining a better understanding of firm innovation performance. When looking for strategic partners, managers should try to ally with highly competitive enterprises so as to access their more innovative knowledge. Second, the results also highlight that this beneficial effect of coopetition in R&D alliances can be amplified in two ways. On the one hand, when the partners involved in the alliance have not yet developed experience in forming alliances. Partners without previous experience supply ideal stimuli to unlock more knowledge in the alliance because new approaches to access and develop knowledge in the alliance could be explored. On the other hand, this paper detects the situation when the allied partners are developing technologies and products in different areas. When partnering with firms coming from different technological areas, the knowledge diversity that can be leveraged in the alliances could drive alliance managers to generate synergies and economies of scope within the coopetitive alliance.

Extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance but has concurrently underestimated the configurations of partner attributes leading to firm innovation performance. Therefore, this paper differs from previous studies, as it provides an understanding of the specific configurations of R&D alliance partner attributes leading firms involved in R&D alliances to achieve high innovation performance.

The purpose of this paper is to know which growth-impeding constraints are perceived to act upon operations of small- to medium-sized (SME) companies by their owner-managers and to recommend transitionary paths to elevate constraints and increase contribution levels made by SMEs’ operations. To do so, this research has been primarily founded upon Hayes et al.’s (2005) operations contribution model for differentiating between different levels of operations’ contribution, and secondarily on the theory of constraints philosophy to explain the perceptions of constraints found at each level – current and future.

An open-ended survey and a series of group workshops have gathered new empirical data about these perceptions, which were coded using the relational content analysis to identify a parsimonious set of perceptual growth-impeding constraint categories. The most popular transitions were identified and a correlation of frequency rank orders between “perceived current” and “perceived future” constraints categories was calculated, and likely transitionary paths for growth are discussed. Three SME case studies were documented in related action research to contextualise survey findings.

The most popular transition was from “neutral” to “leading”. A lack of people capability was perceived to be the most commonly reported growth-impeding constraint category, followed by a combined lack of process competence and product and service innovation, further followed by a lack of skills in information technology automation. In addition, a new conceptual model has been generated inductively to address shortcomings found in the original operations contribution model (Hayes et al., 2005) during its application to UK SMEs. The new model is referred to in this paper as the “Operations Growth Rocket”.

This research only used data from UK SMEs.

This work should help SME owner-managers to overcome growth-impeding constraints that act upon their operations and assist them to develop more effective actions and paths to increase the contribution levels made by their operations. This in turn should support growth of their organisations. Findings will also inform teaching about more effective operations management in SMEs.

This work should help UK SMEs to grow, which in turn will strengthen the UK economy.

A novel approach and new data from 208 SMEs modify a classical operations contribution model (Hayes et al., 2005). This is achieved by considering transitionary paths to be meta-categories continua abstracted from constraint categories combined with case data for moving towards higher levels of operations contribution, rather than using discrete growth-impeding and growth-constraining “levels”. This research has inductively generated a new version of the classical contribution model that should be more suitable for stimulating growth in (UK) SMEs.

Freeway work zones have been traffic bottlenecks that lead to a series of problems, including long travel time, high-speed variation, driver’s dissatisfaction and traffic congestion. This research aims to develop a collaborative component of connected and automated vehicles (CAVs) to alleviate negative effects caused by work zones.

The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations.

Simulation results show that, with the proposed component and penetration of CAVs, the average performances (travel time, safety and emission) can all be improved and the stochasticity of performances will be minimized too.

To the best of the authors’ knowledge, this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.

Professionals from the dairy sector commonly believe that the results of Global Dairy Trade (GDT) auctions are a good leading indicator for prices of dairy commodities. The purpose of this paper is to test that hypothesis for prices of key dairy commodities (skimmed milk powder (SMP), whole milk powder (WMP), butter and cheddar) in the main dairy markets (the US, EU and Oceania).

The leading properties of the GDT auctions are investigated using vector error correction models (VECM).

The results show that prices at GDT auctions may be treated as a benchmark for global prices of WMP and SMP as they affect prices in all considered markets. However, in case of EU market the relationship with the GDT is bidirectional. GDT prices reveal some leading properties also in cheddar market, however price relationships in this market are much more complex. In case of butter market, GDT can be regarded as a benchmark only for Oceania.

The results of this paper improve knowledge on price transmission in dairy markets, show the role of the GDT auctions in the price setting process, and thus may help professionals from the dairy sector to formulate their price expectations more precisely.

Despite the fact that many professionals from the dairy sector treat GDT auctions as a benchmark, so far their leading properties have not been scientifically proven.

The rapid advancement of digital technologies has fundamentally changed the competitive dynamics of the logistics service industry and forced incumbent logistics service providers (LSPs) to digitalize. As many LSPs still struggle in advancing their digital transformation (DT), the purpose of this study is to discover barriers and identify organizational elements and associated leading practices for DT success at LSPs.

This study utilizes a two-stage approach. Stage 1 is devoted to a literature review. Stage 2, based on multiple case studies, analyzes information collected across nine international and global LSPs.

This research derives a practice-based definition of DT in the logistics service industry, and it has identified five barriers, eight success factors and associated leading practices for DT. The main obstacles LSPs struggle with, are the complexity of the logistics network and lack of resources, while the main success factor is a leader having and executing a DT vision, and creating a supportive organizational culture.

The results contribute to the emerging field of DT within the logistics and supply chain management literature and provide insights for practitioners regarding how to effectively implement it in a complex industry.

The authors analyze DT from the perspective of LSPs, traditionally not viewed as innovative companies. This study compares their DT with that of other companies.

This study aims to examine the entrepreneurship profiles of migrants and refugees relying on a neo-configurational approach that increases understanding of causal complexity, equifinality and causal asymmetry patterns to high entrepreneurial intentions in the two groups.

Using a fuzzy set qualitative comparative analysis method, the authors analysed 52 respondents – migrants and refugees. The findings show the existence of equifinality in which different configurations can lead to high and low entrepreneurial intentions, underlying that traumatic experiences have a major role in entrepreneurial intention. It also demonstrates that core conditions are associated with refugee’s configurations and causal asymmetry. The cross-sectional character of this research impedes the searching for a better causal relationship. The lack of studies that approach the subject of refugees makes it challenging to develop a robust theory in this sense.

The paper highlights five main configurations – two related to migrants’ profile and three related to refugees’ profile – that enable expanding the current knowledge and practices to better customize practices to increase entrepreneurial intention.

To the best of the authors’ knowledge, this is the first research using a configurational approach to explore migrant and refugee entrepreneurship intention profiles.

The purpose of this paper is to describe how first-line managers (FLMs) in home care (HC) reason about the opportunities and obstacles to lead the work according to the individual’s needs and goals.

In this participatory appreciative action reflection project, eight managers within one Swedish municipality were interviewed. The data were analysed using a thematic analysis.

The results showed a polarization between two different systems that FLMs struggle to balance when attempting to lead HC that adapts to the needs and goals of individuals. One system was represented by the possibilities of a humane system, with human capital in the form of the individual, older persons and the co-workers in HC. The second system was represented by obstacles in the form of the economic needs of the organization in which the individual receiving HC often felt forgotten. In this system, the organization’s needs and goals governed, with FLMs needing to adapt to the cost-effectiveness principle and keep a balanced budget. The managers had to balance an ethical conflict of values between the human value and needs-solidarity principles, with that of the cost-effectiveness principle.

The FLMs lack the opportunity to lead HC according to the needs and goals of the individuals receiving HC. There is a need for consensus and a value-based leadership model based on ethical principles such as the principles of human value and needs-solidarity to lead the HC according to the individual’s needs and goals.