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Article
Publication date: 29 July 2021

Timothy G. Hawkins, Michael J. Gravier and Suman Niranjan

The purpose of this study is to better understand the effectiveness of buyers’ defensive measures to thwart bid protests in government procurements.

Abstract

Purpose

The purpose of this study is to better understand the effectiveness of buyers’ defensive measures to thwart bid protests in government procurements.

Design/methodology/approach

A sample of 240 sourcing professionals concerning government source selections is used to analyze a logistic regression model exploring 6 antecedents of bid protests.

Findings

This research implicates the importance of oral presentations of offers, the type of value procured (i.e. services), protest experience, the quantity of document revisions, transaction costs and cost reimbursement contracts in receiving a bid protest.

Originality/value

To the best of the authors’ knowledge, this research is the first to explore sourcing strategy decisions that can contribute to the receipt of a bid protest. It adds clarity to an understudied market of business – the public sector.

Details

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

Keywords

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Article
Publication date: 12 February 2018

Suman Niranjan, Stephen R. Spulick and Katrina Savitskie

The purpose of this paper is to conduct an exploratory study that will assist supply chain firms in the development of partner satisfaction, flexibility, and supply chain…

Abstract

Purpose

The purpose of this paper is to conduct an exploratory study that will assist supply chain firms in the development of partner satisfaction, flexibility, and supply chain performance. The authors examine how the interaction of information exchange, partner interaction, knowledge sharing and flexibility as mediated through partner satisfaction effectuates firm performance. The goal of this research is to answer the supply chain managers’ need to better understand where to invest their time and effort to get improved firm performance.

Design/methodology/approach

The model was tested with panel data from 105 experienced, US-based supply chain managers. Structural equation modeling using partial least squares approach was utilized to conduct the analysis.

Findings

The results provide crucial evidence that simple information exchange among supply chain partners does not result in improvements in firm performance or partner satisfaction, but, when mediated through the flexibility construct, it does. Further, the use of integration tools has a moderating effect on the relationship between flexibility and firm performance. The results suggest that working closely with supply chain partners helps ensure improved relationship satisfaction, and can reduce issues that can impact firm performance.

Research limitations/implications

The empirical research presented requires additional validation though larger sample data from supply chain managers.

Practical implications

This study stresses on the importance of managers using information exchange, partner interaction, and knowledge sharing as a means of improving their firm’s indirect influence on firm performance through flexibility and integration tools.

Originality/value

This is one of the few studies in the supply chain literature that integrates flexibility as a mediator variable. Additionally, this study introduces the new construct of integration tools to the supply chain literature.

Details

Journal of Enterprise Information Management, vol. 31 no. 1
Type: Research Article
ISSN: 1741-0398

Keywords

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Article
Publication date: 17 April 2020

Rajasekhar B, Kamaraju M and Sumalatha V

Nowadays, the speech emotion recognition (SER) model has enhanced as the main research topic in various fields including human–computer interaction as well as speech…

Abstract

Purpose

Nowadays, the speech emotion recognition (SER) model has enhanced as the main research topic in various fields including human–computer interaction as well as speech processing. Generally, it focuses on utilizing the models of machine learning for predicting the exact emotional status from speech. The advanced SER applications go successful in affective computing and human–computer interaction, which is making as the main component of computer system's next generation. This is because the natural human machine interface could grant the automatic service provisions, which need a better appreciation of user's emotional states.

Design/methodology/approach

This paper implements a new SER model that incorporates both gender and emotion recognition. Certain features are extracted and subjected for classification of emotions. For this, this paper uses deep belief network DBN model.

Findings

Through the performance analysis, it is observed that the developed method attains high accuracy rate (for best case) when compared to other methods, and it is 1.02% superior to whale optimization algorithm (WOA), 0.32% better from firefly (FF), 23.45% superior to particle swarm optimization (PSO) and 23.41% superior to genetic algorithm (GA). In case of worst scenario, the mean update of particle swarm and whale optimization (MUPW) in terms of accuracy is 15.63, 15.98, 16.06% and 16.03% superior to WOA, FF, PSO and GA, respectively. Under the mean case, the performance of MUPW is high, and it is 16.67, 10.38, 22.30 and 22.47% better from existing methods like WOA, FF, PSO, as well as GA, respectively.

Originality/value

This paper presents a new model for SER that aids both gender and emotion recognition. For the classification purpose, DBN is used and the weight of DBN is used and this is the first work uses MUPW algorithm for finding the optimal weight of DBN model.

Details

Data Technologies and Applications, vol. 54 no. 3
Type: Research Article
ISSN: 2514-9288

Keywords

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