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Article
Publication date: 30 November 2020

Roxanna Senyshyn and Ann Martinelli

The purpose of this paper is to report on a collaborative project and study implemented by two teacher educators in an elementary education program. To prepare teacher…

Abstract

Purpose

The purpose of this paper is to report on a collaborative project and study implemented by two teacher educators in an elementary education program. To prepare teacher candidates for field experiences and practicum in a diverse (bilingual) urban school, the program uses coursework to impart asset-based pedagogies and practices.

Design/methodology/approach

In this mixed-method case study, this paper examined the awareness and perspectives of preservice teachers (n = 26) to cultural and linguistic diversity and relevant teaching and learning practices. In particular, this study gauged their engagement with multicultural children’s literature in a collaborative interclass activity. The data sources included beginning and end of semester survey responses, notes on participant interactions during the mid-semester collaborative interclass activity and participant retrospective reflections about the activity.

Findings

This paper found that teacher candidates showed increased awareness and positive shifts in perspectives. This study also ascertaind that, in learning to become culturally (and linguistically) responsive and sustaining teachers, they benefited from collaborative peer work that focused on learning about multicultural children’s literature, analyzing it and planning to integrate it into their classrooms.

Originality/value

Studies show that culturally relevant literature in schools is beneficial; however, teacher candidates often lack knowledge of such literature and how to use it. This need is especially critical and relevant when learning about and implementing culturally relevant and sustaining practices. The collaborative undertaking discussed in this study fills this gap through co-teaching and interclass activity that brings preservice teachers as a cohort to collaboratively learn about, discuss, reflect on and plan lessons as they prepare to work with students from different backgrounds than their own.

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Article
Publication date: 1 March 1999

FARZAD KHOSROWSHAHI

The way in which clients or their consultants undertake to select firms to tender for a given project is a highly complex process and can be very problematic. This is also…

Abstract

The way in which clients or their consultants undertake to select firms to tender for a given project is a highly complex process and can be very problematic. This is also true for public authorities as, for them, ‘compulsory competitive tendering’ is a relatively new concept. Despite its importance, contractors' prequalification is often based on heuristic techniques combining experience, judgement and intuition of the decision makers. This, primarily, stems from the fact that prequalification is not an exact science. For any project, the right choice of the contractor is one of the most important decisions that the client has to make. Therefore, it is envisaged that the development of an effective decision‐support model for contractor prequalification can yield significant benefits to the client. By implication, such a model can also be of considerable use to contractors: a model of this nature is an effective marketing tool for contractors to enhance their chances of success to obtain new work. To this end, this work offers a decision‐support model that predicts whether or not a contractor should be selected for tendering projects. The focus is on local authorities because, in the absence of a viable universal selection system, there are significant variations in the way they conduct prequalification. The model is based on the use of artificial neural networks (ANN) and uses data relating to 42 local authorities (clients). With the aid of a questionnaire and a scaling system, the prequalification attributes that are considered to be important by clients are identified. The survey indicates significant variations in the level of importance given to different attributes. Statistical methods are adopted to generate additional data representing disqualified instances. Following a preprocessing exercise, the data form the basis of the input and output layers for training the neural‐net model. An independent set of data is subjected to a similar preprocessing for testing the model. Tests reveal that the model has a highly satisfactory predictive accuracy and that the ANN technique is a viable tool for the prediction of success or failure of the contractor to qualify to tender for local authority projects.

Details

Engineering, Construction and Architectural Management, vol. 6 no. 3
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 16 October 2019

Leandro D.B. dos Santos, Elsebeth Holmen and Ann-Charlott Pedersen

The purpose of this paper is to discuss key elements of lean supply (LS) in light of core concepts in the Industrial Marketing and Purchasing Group (IMP) perspective.

Abstract

Purpose

The purpose of this paper is to discuss key elements of lean supply (LS) in light of core concepts in the Industrial Marketing and Purchasing Group (IMP) perspective.

Design/methodology/approach

First, the authors examine the literature on LS and identify and discuss important characteristics and key elements of LS. Second, the authors present key concepts in the IMP Perspective, in particular the dyad versus network levels, and the ARA model, capturing activities, resources, and actors. Third, the authors cross-fertilize the concepts from these two streams of research.

Findings

The authors identify 12 key LS elements. Relating these to core IMP frameworks, they identify areas of LS that can be expanded. First, the authors found that key elements in LS mainly focus on the dyadic level and that the network level is addressed to a much lesser extent and primarily captures serial “chain” connections among relationships. Second, it was found that key elements in LS predominantly focus on the activity layer and pay much less attention to resources and actors.

Research limitations/implications

The authors suggest that LS theory and practice can benefit from taking a network perspective, and by paying more attention to resource and actor concepts and issues. The study is purely theoretical.

Originality/value

To the best of the authors’ knowledge, no previous studies combine LS and the IMP perspective. The authors add to LS by elaborating how 12 key elements in LS can be expanded.

Details

Journal of Business & Industrial Marketing, vol. 35 no. 1
Type: Research Article
ISSN: 0885-8624

Keywords

Content available
Book part
Publication date: 17 August 2017

Abstract

Details

No Business is an Island
Type: Book
ISBN: 978-1-78714-550-4

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Article
Publication date: 10 June 2014

Lei Zhang, Fengchun Tian, Xiongwei Peng, Xin Yin, Guorui Li and Lijun Dang

The purpose of this paper is to present a novel concentration estimation model for improving the accuracy and robustness of low-cost electronic noses (e-noses) with metal…

Abstract

Purpose

The purpose of this paper is to present a novel concentration estimation model for improving the accuracy and robustness of low-cost electronic noses (e-noses) with metal oxide semiconductor sensors in indoor air contaminant monitoring and overcome the potential sensor drift.

Design/methodology/approach

In the quantification model, a piecewise linearly weighted artificial neural network ensemble model (PLWE-ANN) with an embedded self-calibration module based on a threshold network is studied.

Findings

The nonlinear estimation problem of sensor array-based e-noses can be effectively transformed into a piecewise linear estimation through linear weighted neural networks ensemble activated by a threshold network.

Originality/value

In this paper, a number of experimental results have been presented, and it also demonstrates that the proposed model has very good accuracy and robustness in real-time indoor monitoring of formaldehyde.

Details

Sensor Review, vol. 34 no. 3
Type: Research Article
ISSN: 0260-2288

Keywords

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Article
Publication date: 1 January 1977

Hannelore B. Rader

This bibliography covers materials published during 1976, with some 1975 entries omitted from last year's listing. Citations from a number of foreign countries are…

Abstract

This bibliography covers materials published during 1976, with some 1975 entries omitted from last year's listing. Citations from a number of foreign countries are included if published in English. A few items were not available for annotation. The growing interest in library use instruction is evident from the fact that the number of entries has doubled over those included in the bibliography for 1975.

Details

Reference Services Review, vol. 5 no. 1
Type: Research Article
ISSN: 0090-7324

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Book part
Publication date: 19 May 2015

Abstract

Details

Inquiry-Based Learning for Multidisciplinary Programs: A Conceptual and Practical Resource for Educators
Type: Book
ISBN: 978-1-78441-847-2

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Book part
Publication date: 19 May 2015

Abstract

Details

Inquiry-Based Learning for Multidisciplinary Programs: A Conceptual and Practical Resource for Educators
Type: Book
ISBN: 978-1-78441-847-2

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Article
Publication date: 6 May 2021

Anbesh Jamwal, Rajeev Agrawal, Monica Sharma, Anil Kumar, Vikas Kumar and Jose Arturo Arturo Garza-Reyes

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of…

Abstract

Purpose

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of data generated from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM).

Design/methodology/approach

In the present study, the authors use a bibliometric review approach that is focused on the statistical analysis of published scientific documents with an unbiased objective of the current status and future research potential of ML applications in sustainable manufacturing.

Findings

The present study highlights how manufacturing industries can benefit from ML techniques when applied to address SM issues. Based on the findings, a ML-SM framework is proposed. The framework will be helpful to researchers, policymakers and practitioners to provide guidelines on the successful management of SM practices.

Originality/value

A comprehensive and bibliometric review of opportunities for ML techniques in SM with a framework is still limited in the available literature. This study addresses the bibliometric analysis of ML applications in SM, which further adds to the originality.

Details

Journal of Enterprise Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0398

Keywords

Content available
Article
Publication date: 12 June 2017

Alexandra Waluszewski and Ivan Snehota

Abstract

Details

IMP Journal, vol. 11 no. 2
Type: Research Article
ISSN: 2059-1403

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