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Article
Publication date: 12 October 2023

Richa Chugh, Valerie J. Lindsay, Nicholas J. Ashill and Dave Crick

This study explores the influence of informal “psychological contracts” (PCs), (as opposed to formal contractual relationships) on exporter–distributor relationships.

Abstract

Purpose

This study explores the influence of informal “psychological contracts” (PCs), (as opposed to formal contractual relationships) on exporter–distributor relationships.

Design/methodology/approach

Data were obtained from a sample of 127 exporting small and medium-sized enterprises (SMEs) in New Zealand. The authors employed partial least squares structural equation modeling (PLS-SEM) for analyzing the measurement and structural models.

Findings

Psychological contract fulfillment (PCF) enhances affective commitment and calculative commitment. Moreover, affective and calculative commitments mediate the relationship between PCF and export venture performance (EVP). The authors also find that institutional distance (ID) weakens the relationship between PCF and both affective and calculative commitment. Additionally, ID moderates the strength of the mediating mechanism for affective commitment; thus, the authors present a moderated-mediation model.

Originality/value

To date, international relationship marketing (IRM) literature has focused on PC breach, and business-to-business (B2B) marketing literature has focused on the effects of PCs on affective/relational commitment. This study offers novel insights by demonstrating the positive indirect effect of PCF on EVP via the mediating variables – affective and calculative commitment. The authors' findings also present a conditioning role of ID on the micro-level relationships of PCs.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 36 no. 3
Type: Research Article
ISSN: 1355-5855

Keywords

Open Access
Article
Publication date: 29 July 2020

Mahmood Al-khassaweneh and Omar AlShorman

In the big data era, image compression is of significant importance in today’s world. Importantly, compression of large sized images is required for everyday tasks; including…

Abstract

In the big data era, image compression is of significant importance in today’s world. Importantly, compression of large sized images is required for everyday tasks; including electronic data communications and internet transactions. However, two important measures should be considered for any compression algorithm: the compression factor and the quality of the decompressed image. In this paper, we use Frei-Chen bases technique and the Modified Run Length Encoding (RLE) to compress images. The Frei-Chen bases technique is applied at the first stage in which the average subspace is applied to each 3 × 3 block. Those blocks with the highest energy are replaced by a single value that represents the average value of the pixels in the corresponding block. Even though Frei-Chen bases technique provides lossy compression, it maintains the main characteristics of the image. Additionally, the Frei-Chen bases technique enhances the compression factor, making it advantageous to use. In the second stage, RLE is applied to further increase the compression factor. The goal of using RLE is to enhance the compression factor without adding any distortion to the resultant decompressed image. Integrating RLE with Frei-Chen bases technique, as described in the proposed algorithm, ensures high quality decompressed images and high compression rate. The results of the proposed algorithms are shown to be comparable in quality and performance with other existing methods.

Details

Applied Computing and Informatics, vol. 20 no. 1/2
Type: Research Article
ISSN: 2634-1964

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