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Open Access
Article
Publication date: 24 May 2022

Michela Arnaboldi, Hans de Bruijn, Ileana Steccolini and Haiko Van der Voort

The purpose of this paper is to introduce the papers in this special issue on humans, algorithms and data. The authors first set themselves the task of identifying the main…

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Abstract

Purpose

The purpose of this paper is to introduce the papers in this special issue on humans, algorithms and data. The authors first set themselves the task of identifying the main challenges arising from the adoption and use of algorithms and data analytics in management, accounting and organisations in general, many of which have been described in the literature.

Design/methodology/approach

This paper builds on previous literature and case studies of the application of algorithm logic with artificial intelligence as an exemplar of this innovation. Furthermore, this paper is triangulated with the findings of the papers included in this special issue.

Findings

Based on prior literature and the concepts set out in the papers published in this special issue, this paper proposes a conceptual framework that can be useful both in the analysis and ordering of the algorithm hype, as well as to identify future research avenues.

Originality/value

The value of this framework, and that of the papers in this special issue, lies in its ability to shed new light on the (neglected) connections and relationships between algorithmic applications, such as artificial intelligence. The framework developed in this piece should stimulate scholars to explore the intersections between “technical” as well as organisational, social and individual issues that algorithms should help us tackle.

Details

Qualitative Research in Accounting & Management, vol. 19 no. 3
Type: Research Article
ISSN: 1176-6093

Keywords

Article
Publication date: 9 November 2021

Mian M. Ajmal, Mehmood Khan, Muhammad Kashif Shad, Haseena AlKatheeri and Fauzia Jabeen

This paper explores the new normal activities and strategic responses of the service industry towards the challenges created by the coronavirus disease 2019 (COVID-19) outbreak…

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Abstract

Purpose

This paper explores the new normal activities and strategic responses of the service industry towards the challenges created by the coronavirus disease 2019 (COVID-19) outbreak and other constructs and validates the measurement scale for socio-economic and technological new normal activities following lockdown and social distancing practices.

Design/methodology/approach

First, structured interviews with 28 participants helped us generate items and develop survey instruments for cross-sectional data collection in the second phase. So, the authors received 256 complete responses from the top and middle management of the services industry. Exploratory factor analysis helped us explore the factors and reliability of the items. Confirmatory factor analysis aided us in generating and confirming the factorial structure of the constructs.

Findings

Results indicated that amid COVID-19's pandemic, new normal activities are emerging in which organizations are deploying crisis strategies to safeguard their business and stakeholders. Organizations are re-opening swiftly, focusing on digital transformation, developing digital platforms for ease in working and improved consumer services, to name a few operational changes.

Practical implications

Discussion on empirical analysis revolves around the guidelines to service industry's managers and top management to improve shortcomings in combating the challenges they face in their operations.

Originality/value

Prior studies have provided substantial insights on the COVID-19 pandemic, but relatively little research exists on new normal activities in the supply chain network of the service industry. Among other reasons for such less empirical evidence on new normal activities is the unavailability of a comprehensive tool for measuring the socio-economic and technological new normal activities. This paper is a contribution to bridging this knowledge gap.

Details

The International Journal of Logistics Management, vol. 33 no. 4
Type: Research Article
ISSN: 0957-4093

Keywords

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