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Information and communications technologies promote change in the service sector, and the banking sector is not an exception. Finding what factors impact consumer satisfaction with service and lead to loyalty is invariably important for business. However, it is important to begin with evaluating the aspects that are specific to the market and service. The purpose of this study was to investigate the factors affecting customer loyalty in Mobile Banking. Following the model designed by the researchers, consideration was given to mediator variables of satisfaction, trust, and customer service to examine how factors such as perceived risk, relative advantages, and usability affect customer loyalty. In this study, customers of an Iranian bank (Shahr Bank) based in the city of Tehran constituted the statistical population. The descriptive survey method was used on a sample that was selected through a cluster-convenience method and included 411 Shahr Bank's customers resident in the east, west, north, south, and centre of the city of Tehran. Structural Equation Modelling (SEM) test and the LISREL 8.8 software were used to analyse the data and to determine what role each factor plays on loyalty. The results showed that such factors as relative advantages, satisfaction, and trust have the most significant impact on customer loyalty. However, the effect of usability on customer service was not confirmed. Furthermore, it was identified that perceived risk has a negative impact on loyalty.

Root rot is an important disease of field pea (Pisum sativum L.) on the Canadian Prairies. The composition and alternative crop hosts of fungal and oomycete communities colonizing pea residues from Alberta and Manitoba were studied in field trials over two years. Standing pea residues were sampled from diseased and asymptomatic patches of 17 commercial fields in 2013 and 2014 after harvest and again in early spring the following year prior to seeding. The pea residue was ground to a powder and mixed with sterile Cornell potting mix. Plants of pea, wheat, and canola were grown in this mixture under controlled conditions. The root rot severity on each plant was evaluated and sections from diseased roots were plated on agar medium. Fungal and oomycete communities isolated from symptomatic roots were identified based on culture morphology and PCR analysis. About 3000 fungal isolates, belonging to some 50 species, were identified. Canola was less susceptible to infection than pea or wheat. Fusarium avenaceum (Fr.) Sacc. was the most abundant species infecting the three hosts; F. culmorum (Wm.G.Sm.) Sacc. and Bipolaris sorokiana (Sacc.) Shoemaker were more frequently isolated from wheat, and F. solani (Mart.) Sacc., F. oxysporum Schlecht. and Aphanomyces euteiches Drechsler were more frequently isolated from pea. Pathogen communities from asymptomatic and diseased patches of fields were similar. Overall, composition of the fungal community changed over winter, but the most abundant species did not change. The results show that multiple pathogens, and particularly Fusarium spp., can survive overwinter on pea residue.

The urgent concerns for environmental issues and growing demand for green products have made companies pay much more attention to green marketing. Although, many companies invest in green marketing, but not all of them gain as much as they invest. Most of failures of investments in green marketing are rooted in the fact that customers doubt both the real green performance of these products and the real intention of companies regarding green products. This research, being quantitative in nature, attempts to investigate the impact of traditional branding constructs (perceived quality of the brand, credibility of the brand) and green branding constructs (perceived value of a green brand, the green brand image, and brand equity) on the green purchase intention of customers. The hypotheses have been developed in the form of a conceptual model to investigate the relationship of these constructs. The research focuses on consumers of certain liquid washing detergent products. All the data were collected using questionnaires and the analysis of the data was conducted utilizing LISREL 8 and SPSS 16. The results indicate that perceived brand quality has a positive impact on the perceived value of a green brand, brand credibility, and brand image. In addition, green brand value and green brand image have a positive impact on brand equity. This research can serve as validation of the constructs to fi ll the gap in the investigation of green brand dimensions. Further analysis shows that green brand equity has a meaningful impact on the green purchase intention of the customers, however the impact of brand credibility on brand equity has not been proved.

The main goal of green supply chain management (GSCM) is to reduce the negative environmental impacts in all activities and stages of a supply chain. Evaluation of suppliers in a supply chain according to environmental criteria can help us to achieve this goal of GSCM. Since this evaluation usually comprises some alternatives and some criteria, green supplier selection (GSS) could be considered as a multi-criteria decision-making (MCDM) problem. To handle the uncertainty of information in an MCDM problem, the theory of fuzzy sets is an effective tool. Interval type-2 fuzzy sets (IT2FSs), which are characterized by an interval membership function, is very flexible to model the uncertainty of the MCDM problems. In this study, a new integrated approach based on Weighted Aggregated Sum Product Assessment (WASPAS) method, is proposed to deal with multi-criteria group decision-making problems with IT2FSs. This approach is based on the operators of IT2FSs, some modifications in the classical WASPAS method and a new procedure for calculation of criteria weights. In the procedure of calculation of criteria weights, we combine the subjective weights expressed by decision-makers with objective weights resulted from an entropy method to obtain more realistic weights. To show the applicability of the proposed approach in the real-world MCDM problems, a green supplier selection problem is used. We perform a sensitivity analysis with different weights of criteria and different values of method's parameters to show the stability of the proposed approach. This analysis shows that combining the subjective and objective weights can help to increase the stability of the proposed approach with different weights of criteria. A comparison is also made between the results of the proposed approach and some existing methods for validating the proposed approach. This analysis shows that the proposed approach is efficient and well consistent with the other methods.

The benefit provided by chickpea ( Cicer arietinum L.) to the following durum wheat [ Triticum turgidum L. subsp. durum (Desf.) Husn.] crop is smaller than that provided by pea ( Pisum sativum L.) in the Great Plains of America. Rotation crops and the specific cropping practices associated with them may impact soil fungal communities, which in turn could affect the productivity of subsequent crops. Two separate field experiments were carried out to test the effect of pea and chickpea crops and of foliar fungicide use in chickpea on the community of fungi hosted in the roots of a subsequent durum wheat crop. The fungal communities in the healthy and diseased roots of durum wheat at maturity were characterized using plate culture and PCR-based identification. The effect of cropping practices on root-associated fungal communities depended on root type and varied with year. Functionally important fungal taxa were affected by specific cropping practices. Endophytic fungal antagonists were less abundant after chickpea than after pea and after fungicide-treated chickpea than after untreated chickpea. The chickpea cultivar CDC Vanguard increased the abundance of highly virulent pathogens in durum wheat roots in comparison with the chickpea cultivar CDC Luna and pea. We conclude that the negative impact of chickpea on durum wheat yield could be due in part to an increase in fungal pathogens resulting from the suppression of endophytic fungal antagonists by chickpea.

The uncertain stand in terms of product and service quality invites customers to get the advantage of other customers’ experiences in order to make a purchase decision. It has been discussed that word-of-mouth (WOM) influences consumer purchase behavior and it could create a robust tie like relatives and could also tie as close friends, acquaintances, and strangers. This paper intends to define the concepts of WOM and customer equity and study the terminology of current purchase intention, customer loyalty and correlates to consumer decision making. The data was collected utilizing self-administrated questionnaires. The results are obtained using Smart PLS 2.0, then using bootstrap algorithm the t-statistics are analyzed. The results indicate that customer equity drivers increase the customer loyalty and consequently ends in WOM by the customers. Despite the literature which has investigated the influence of customer equity drivers on the loyalty and purchase intention of the customers, this study contributes the analysis of drivers on WOM. Also, it reveals that if a firm invests on the customer equity drivers, the result will be loyalty and accordingly, the easiest way of advertisement that would be WOM. This study only focuses on a unique industry that can impact the generalizability of the contexts. Also, it relates only to the positive WOM effects. Future studies could strengthen the literature by taking in negative WOM with a broader population.DOI: http://dx.doi.org/10.5755/j01.ee.29.2.17718

Frequent application of foliar fungicide is essential for chickpea production due to the susceptibility of this plant to ascochyta blight. Chlorothalonil, pyraclostrobin, and boscalid are commonly used to control the disease in Saskatchewan. While fungicides are meant to target specific fungal pathogens, they may impact non-target organisms and alter soil microbial community structure. The effects of the typical 5-time foliar fungicide application program to chickpea CDC Vanguard on the fungal communities associated with seminal and adventitious roots of the following durum wheat crop were studied in a 2 yr field experiment. Root fungal communities were characterized through analysis of the ITS1 region of root metagenomic DNA at the genus level. One hundred and seven fungal genera were detected in durum wheat roots. Fusarium was predominant in both years. A three-way interaction of fungicide application, root type and year on fungal community structure was detected. Unlike Fusarium , the relative abundances of the genera Olpidium , Alternaria , and Cryptococcus were greater in 2010, a very wet year. Fungicide application to chickpea increased the relative abundance of Fusarium in the seminal roots of a subsequent durum crop in 2009, but did not affect the relative abundance of Fusarium in 2010. We could not detect a significant impact of fungicide application to chickpea on durum wheat yield in the subsequent year. The effect of changes in root fungal communities on durum wheat grain yield is discussed.

The internal and external environment of all organizations challenges them adapt to the best practices and reconsider their relationship throughout the supply chain. In this paper, the authors have tried to propose an agile strategy for the supply chain of a steel company, which ranks 3rd in Iran in Gross Sale with 16,000 employees, in order to respond quickly to ever-changing needs. To do this, through the literature review the framework of balanced scorecard was utilized to structure agility factors in the supply chain of the steel industry. Then the experts were interviewed to reconcile on the factors identified. Utilizing 24 questionnaires by the use of Interpretive Structural Modeling framework, the relationship and sequence of factors were obtained from experts. The final model developed in the paper presents the agility factors for the steel industry supply chain. Also, these factors are grouped within the four perspectives of the BSC to better enhance the results and pursue action. The ISM method identifies the priority of each factor which provides a better understanding of the underlying relationship of the factors for the managers to implement the strategies more reliably. The proposed model for strategy formulation can be utilized in strategy formulation problems over various types of supply chain.

Fusarium redolens [syn: F. oxysporum var. redolens] is pathogenic on a wide range of plant species. Fusarium redolens was frequently isolated from necrotic and discolored root and crown tissues of chickpea, pea, lentil and durum wheat in Saskatchewan. The fungus was identified using distance analysis of the translation elongation factor-1 alpha sequences. Comparative pathogenicity tests showed that F. redolens, like Fusarium graminearum and Cochliobolus sativus, caused lesions and/or discolorations on the root, crown and shoot of durum wheat, pea and chickpea, although it had a different host preference. While F. redolens was most virulent on pea, the other two fungi were more virulent on durum wheat. It appears that F. redolens is common in the Prairie Ecozone of Saskatchewan and it may cause yield reduction in pea, chickpea and durum crops. This warrants a closer look at the biology and ecology of F. redolens in the Canadian Prairies.

Nowadays, sustainable development has been introduced and integrated into production and operation management field through the concept of the green supply chain. Green regulations and principles have gained the interest of managers and practitioners in selecting innovative practices for suppliers and organisations. Accordingly, the present study aims to evaluate the relationship between a green supplier, green innovation, environmental performance, and competitive advantage in the cement industry, which is an important industry for Iran. This study is descriptive in nature and conducted based on correlation and structural equation modelling. Managers and experts of cement companies in Fars Province are selected as samples for the study. A questionnaire and Smart-PLS software were used as research tools. The results of data analysis show that there is a positive and significant relationship between a green supplier, green innovations and environmental performance of an organisation, while there is a negative yet significant relationship between a green supplier, green innovations and environmental performance of an organisation. There is also a significant positive relationship between green innovation and environmental performance on one hand, and environmental performance and competitive advantage on the other. First published online:01 Nov 2015

Differentiation, growing competitive advantage, and excellence has been proved to be the result of service quality. At the same time, measuring attributes of service quality and customer satisfaction is fuzzy and ambiguous, and methods available for their measurement are generally classical. This paper proposes a fuzzy method to identify the service quality attributes. This approach was developed using crisp assessment methods in a logistics company. Applying the proposed fuzzy approach, service quality attributes and indicators are identified and then organized into 8 categories, to see the uncertainty level of each. The proposed method was successfully conducted in a real logistics company. The results show the membership degree of each indicator, suggesting customer expectations regarding quality. Also, the membership degrees of the service quality attributes suggest the ability of each to describe service quality in logistics industry.

Environmentally sustainable activities have received an increasing interest among the firms to improve their practices in the supply chain. Although environmental regulations force firms consider these issues, but, green issues are new, evolving every day, and requires a continuous study in the field to gain a complete understanding of the problems. In this study, we illustrate the case of a laptop manufacturer in Malaysia that pursues to evaluate green supply chain management (GSCM) indicators among its practitioners. This paper develops a quantitative evaluation model to measure the uncertainty of GSCM activities and applies an approach based on Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method which is an extension of intuitionistic fuzzy environment aiming to solve the green multi-criteria decision making (GMCDM) problem. The triangular fuzzy numbers (TFNs) were used to handle imprecise numerical quantities. Then, a hierarchical multiple criteria decision making (MCDM) model was proposed based on fuzzy sets theory and VIKOR method to deal with the problem. The results show the alternative ranks of the four evaluated companies which was based on their performance in GSCM initiatives. The results also indicated that the main criteria of the research ranked as follows respectively: eco-design, green production, green purchasing, green recycling, green transportation and green warehousing. Finally, a comparative analysis of results by fuzzy VIKOR is presented. Additionally the scope for future studies is provided at the end of the paper.

Communities are basic units of complex networks and understanding of their structure help us to understand the structure of a network. Communities are groups of nodes that have many links inside and few links outside them. Community detection in a network can be modeled as an optimization problem. We can use some measures such as Modularity and Community Score for evaluating the quality of a partition of nodes. In this paper, we present a new algorithm for detecting communities in networks based on an Estimation of Distribution Algorithm (EDA) with the assumption that the problem variables are independent. EDAs are those evolutionary algorithms that build and sample the probabilistic models of selected solutions instead of using crossover and mutation operators. In this paper, we assess our algorithm by synthetic and real data sets and compare it with other community detection algorithms.

A networked multi-agent system is a group of intelligent agents structured in a social network induced by agent interactions. As the size and diversity of the multi-agent system increase, the interactions and mutual influence of the agents in the structure become more complicated, and this makes the coordination of the system hard to deal with. Holonic models for multi-agent systems have been considered as one of promising models to manage large scale problems. This paper tackles one of the key problems in the design of holonic multi-agent systems. Here we propose a method to construct a multi-level holonic structure for a multi-agent network based on the centrality of the agents. The proposed method is applied to an urban traffic problem and the evaluation results prove its effectiveness.

Soil fungi are a critical component of agroecosystems and provide ecological services that impact the production of food and bioproducts. Effective management of fungal resources is essential to optimize the productivity and sustainability of agricultural ecosystems. In this review, we (i) highlight the functional groups of fungi that play key roles in agricultural ecosystems, (ii) examine the influence of agronomic practices on these fungi, and (iii) propose ways to improve the management and contribution of soil fungi to annual cropping systems. Many of these key soil fungal organisms (i.e., arbuscular mycorrhizal fungi and fungal root endophytes) interact directly with plants and are determinants of the efficiency of agroecosystems. In turn, plants largely control rhizosphere fungi through the production of carbon and energy rich compounds and of bioactive phytochemicals, making them a powerful tool for the management of soil fungal diversity in agriculture. The use of crop rotations and selection of optimal plant genotypes can be used to improve soil biodiversity and promote beneficial soil fungi. In addition, other agronomic practices (e.g., no-till, microbial inoculants, and biochemical amendments) can be used to enhance the effect of beneficial fungi and increase the health and productivity of cultivated soils.

Particle Swarm Optimization (PSO), a new promising evolutionary optimization technique, has a wide range of application in optimization problems including training of artificial neural networks. In this paper, an attempt is made to completely train a RBF neural network architecture including the centers, optimum spreads, and the number of hidden units. The proposed method has been evaluated on some benchmark problems: Iris, Wine, Glass, New-thyroid and its accuracy was compared with other algorithms. The results show its strong generalization ability.