Search results

This paper aims to investigate the pattern of dependence between crude oil price and energy consumption of the most important economic sectors in the USA, over different time periods, using monthly data set from January 1986 to July 2014 and a comparative study between linear correlation versus copula correlation as a measure of dependence over the single scale and the multiscale analysis.

The proposed method is based on the multiresolution analysis which gives more extensive and detailed description of the dependence price-consumption pattern over different periods of time.

The empirical results show that the dependence between variables is strongly sensitive to the time varying and generally increasing with time scale. In particular, the Pearson coefficients are less than the dependence copula measures. The single-scale analysis covers many time-varying dependences which are made clear, flexible and comprehensive by the description given by the multiscale approach. It explains better the structure of relationships between variables and helps understand the variations and improve forecasts of the crude oil price and energy consumption over different time scales.

The proposed methodology offers the opportunity to construct dynamic management strategies by taking into account the multiscale nature of crude oil price and consumption relationship. Moreover, the paper uses wavelets as a relatively new and powerful tool for statistical analysis in addition to the copula technique that allows a new understanding of variable correlation. The paper will be of interest not only for academics in the field of data dependencies analysis but also for fund managers and market investors.

Quasi‐static boundary value problems are formulated for the isothermal linear theory of swelling porous elastic soils in the case that the fluid is incompressible. First, some general theorems (uniqueness, reciprocal and continuous dependence) are established in the general case. Then, in the case that solid matrix is saturated with fluid and occupies a semi‐infinite cylinder of smooth cross section, a time‐weighted cross‐sectional area measure is used in order to establish spatial decay estimates for the quasi‐static solutions.

Firms have been adopting lean manufacturing to improve their business performances. However, they are facing failures or less success in implementation, mainly due to lack of understanding in relating the lean practices (LPs) from the required performance measures perspective. In view of the lack of research and the importance of understanding them, the purpose of this paper is to prioritize LPs.

As LPs are scattered in the literature and a variety of performance measures are used, an extensive literature review is first carried out to identify the LPs and performance measures. The blend of interpretive structural modeling and interpretive ranking process interpretive tools is adopted in establishing the contextual relationship among LPs and then ranking them based on the performance measures. A three-dimensional priority matrix is proposed for better explanation of the results.

The proposed framework can help firms better understand LPs and their levels of importance in lean implementation.

The involvement of lean experts may produce some bias in evaluating the LPs.

The proposed framework can help practitioners to develop an industry-specific road-map for the result-oriented LP implementation. Based on the area of performance to be improved, practitioners can prioritize LPs for implementation.

This is the first study that provides a comprehensive review of LPs available in the literature and prioritizes them in accordance with performance with interpretive tools.

Supply chain management plays an important role in sustaining businesses in today's competitive environment. Therefore, industrial managers are focusing on exploring the key performance improvement attributes of supply chain management to achieve a better position in the global market. Aimed at ensuring best supply chain management practices, this study presents the key performance improvement attributes, known as critical success factors (CSFs), within the context of the apparel supply chain of Bangladesh.

In this paper, the interpretive structural modeling method (ISM) has been applied to develop a structural framework to analyze the contextual relationship among the factors under consideration. MICMAC (Matriced' Impacts Croise´s Multiplication Applique´e a´ unClassement) analysis has also been performed to define the classification of the CSFs in terms of their driving and dependence power.

The research findings reveal that supply chain collaboration/partnership and customer satisfaction are of crucial importance to success in the context of supply chain management of the readymade (RMG) garments industry of Bangladesh. Further evidence suggests that these, along with other success factors, can assist in achieving a competitive advantage and better market position. A number of theoretical and managerial implications have been provided for managers and practitioners, and for further evaluation of the study.

This paper considers a new supply chain problem which identifies and evaluates critical success factors. This paper also develops a new structural model for evaluating critical success factors.

The purpose of this paper is to develop a theoretical framework involving dependence, relationship commitment, logistics outsourcing and service quality to exhibit the roles of the relational factors involved in logistics outsourcing and their outcomes.

Based on data collected from 361 companies in Greater China, the authors use the structural equation model approach to examine the hypothesized relationships.

Both normative and instrumental relationship commitment are necessary for third party logistics (3PL) users to cope with their goal dependence on 3PL providers. However, only normative relationship commitment is necessary when users perceive switch dependence. Normative relationship commitment also plays a more important role than instrumental relationship commitment in facilitating the adoption of 3PL logistic outsourcing. In addition, both basic and advanced outsourcing practices have a positive effect on service quality.

This study contributes to both 3PL theories and practices by clarifying how relationships between 3PL users and providers in China are managed.

The purpose of this paper is to propose that simple measures of linear association are unable to capture accurately the dependence between the survival of hedge funds and funds of funds, respectively. The paper then aims to advocate the use of copulas to model the joint survival of hedge funds and funds of funds managed by the same manager.

The paper uses both a one‐step approach where the margins and the copula parameters are estimated jointly, and a two‐step approach where the margins are fitted first and the copula parameter is estimated thereafter given the fixed margins. The margins are estimated non‐parametrically, semi‐parametrically, and parametrically, respectively.

First, the paper finds that Kendall's tau and Spearman's rho are anywhere between three and eight times larger than the corresponding sample based measures when various families of copulas are employed. Second, additional tests show that the two survival functions are strongly dependent, with the degree of nonlinear association increasing in the lower left quadrant.

This is the first paper to use copulas to model the joint survival of hedge funds and funds of funds. The results highlight the asymmetric dependence between hedge funds and funds of funds, which has implications for risk management practices.

Grounded on resource dependence theory, the authors explored how power and dependence affect sustainability adoption in an artisanal fishing supply chain (AFSC) in Mexico.

An in-depth longitudinal case study was conducted to identify relationships among fishers, a cooperative and intermediaries using a content analysis of data gathered from a combination of interviews, focus groups, observations, participatory workshops and secondary data.

As a result of the existing power imbalance among AFSC members, mediated forces (e.g. rewards for intermediary–fishers relationship) were the most prominent observed. In addition, a close and high dependence on resources affecting supply chain sustainability (SCS) adoption was identified. For example, within intermediary–cooperative relationships, a power imbalance caused mostly by financial resource dependence generated a negative impact on economic sustainability related to unfair prices and unfair trade. The results, thus, showed the detrimental influence of intermediaries among AFSC members on SCS adoption.

A greater understanding of power imbalance and dependence can help AFSC members to identify their weaknesses and develop actions to adopt sustainability.

Unlike previous research, the authors go beyond the often positive research focus of SCS studies and provide, through the resource dependence theory, a longitudinal view on how power imbalance negatively affects SCS adoption.

In this paper, we study a Cauchy-type problem for Hilfer fractional integrodifferential equations with boundary conditions. The existence of solutions for the given problem is proved by applying measure of noncompactness technique in an abstract weighted space. Moreover, we use generalized Gronwall inequality with singularity to establish continuous dependence and uniqueness of ϵ-approximate solutions.

We discuss a class of copula-based ordered probit models with endogenous switching. Such models can be useful for the analysis of self-selection in subjective well-being equations in general, and job satisfaction in particular, where assignment of regressors may be endogenous rather than random, resulting from individual maximization of well-being. In an application to public and private sector job satisfaction, and using data on male workers from the German Socio-Economic Panel for 2004, and using two alternative copula functions for dependence, we find consistent evidence for endogenous sector selection.

The linear regression technique is widely used to determine empirical parameters of fatigue life profile while the results may not continuously depend on experimental data. Thus Tikhonov-Morozov method is utilized here to regularize the linear regression results and consequently reduces the influence of measurement noise without notably distorting the fatigue life distribution. The paper aims to discuss these issues.

Tikhonov-Morozov regularization method would be shown to effectively reduce the influences of measurement noise without distorting the fatigue life distribution. Moreover since iterative regularization methods are known to be an attractive alternative to Tikhonov regularization, four gradient iterative methods called as simple iteration, minimum error, steepest descent and conjugate gradient methods are examined with an appropriate initial guess of regularized coefficients.

It has been shown that in case of sparse fatigue life measurements, linear regression results may not have continuous dependence on experimental data and measurement error could lead to misinterpretations of the solution. Therefore from engineering safety point of view, utilizing regularization method could successfully reduce the influence of measurement noise without significantly distorting the fatigue life distribution.

An excellent initial guess for mixed iterative-direct algorithm is introduced and it has been shown that the combination of Newton iterative approach and Morozov discrepancy principle is one of the interesting strategies for determination of regularization parameter having an excellent rate of convergence. Moreover since iterative methods are known to be an attractive alternative to Tikhonov regularization, four gradient descend methods are examined here for regularization of the linear regression problem. It has been found that all of gradient decent methods with an appropriate initial guess of regularized coefficients have an excellent convergence to Tikhonov-Morozov regularization results.