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Open Access
Article
Publication date: 5 July 2024

M. Alperen Yasar

This study explores the emergence of discrimination based on observable characteristics. In many instances, agents presume differences arising from traits such as race or gender…

Abstract

Purpose

This study explores the emergence of discrimination based on observable characteristics. In many instances, agents presume differences arising from traits such as race or gender, even when these parameters are irrelevant to the situation at hand. This paper intends to reveal an emergent behavior and a persistent culture of discrimination caused by miscategorization in strategic interactions.

Design/methodology/approach

We assume that agents occasionally engage in conflicts modeled as asymmetric hawk and dove games, where boundedly rational agents may categorize their opponents based on observable traits to make effective decisions. Three categorization strategies are considered: fine-grained, regular, and coarse-grained. Subsequently, an evolutionary agent-based model is employed to examine the performance of these strategies in a dynamic environment.

Findings

The results demonstrate that fine-grained categorization provides an advantage when the cost of fighting is low, while coarse-grained categorizers exhibit more peaceful behavior, gaining an advantage when the cost of conflict is high. Our primary finding indicates the emergence of discrimination based on non-relevant traits, manifested through consistent aggressive behavior towards individuals possessing these traits.

Originality/value

This paper is the first to investigate the emergence of discrimination without assuming prior differences between groups. Previous studies have assumed either an initial population difference or a homophily-based approach. In contrast, we demonstrate that discrimination can emerge even in the absence of such assumptions. Discrimination between two groups may arise as long as there are agents who label these categories.

Details

International Journal of Organization Theory & Behavior, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1093-4537

Keywords

Open Access
Article
Publication date: 15 February 2024

Jari Huikku, Elaine Harris, Moataz Elmassri and Deryl Northcott

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the…

Abstract

Purpose

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

Design/methodology/approach

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

Findings

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

Research limitations/implications

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

Originality/value

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

Details

Journal of Accounting & Organizational Change, vol. 20 no. 6
Type: Research Article
ISSN: 1832-5912

Keywords

Open Access
Article
Publication date: 9 October 2023

Mingyao Sun and Tianhua Zhang

A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing…

Abstract

Purpose

A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing process is always accompanied by order splitting and merging; besides, in each stage of the process, there are always multiple machine groups that have different production capabilities and capacities. This paper studies a multi-agent based scheduling architecture for the radio frequency identification (RFID)-enabled semiconductor back-end shopfloor, which integrates not only manufacturing resources but also human factors.

Design/methodology/approach

The architecture includes a task management (TM) agent, a staff instruction (SI) agent, a task scheduling (TS) agent, an information management center (IMC), machine group (MG) agent and a production monitoring (PM) agent. Then, based on the architecture, the authors developed a scheduling method consisting of capability & capacity planning and machine configuration modules in the TS agent.

Findings

The authors used greedy policy to assign each order to the appropriate machine groups based on the real-time utilization ration of each MG in the capability & capacity (C&C) planning module, and used a partial swarm optimization (PSO) algorithm to schedule each splitting job to the identified machine based on the C&C planning results. At last, we conducted a case study to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

Originality/value

This paper proposes a multi-agent based real-time scheduling framework for semiconductor back-end industry. A C&C planning and a machine configuration algorithm are developed, respectively. The paper provides a feasible solution for semiconductor back-end manufacturing process to realize real-time scheduling.

Details

IIMBG Journal of Sustainable Business and Innovation, vol. 1 no. 1
Type: Research Article
ISSN: 2976-8500

Keywords

Open Access
Article
Publication date: 4 September 2024

Raphael José Pereira Freitas

This study aims to elucidate the dynamics of monetary and fiscal policy interactions in Brazil, focusing on the impacts of positive shocks in government consumption and interest…

Abstract

Purpose

This study aims to elucidate the dynamics of monetary and fiscal policy interactions in Brazil, focusing on the impacts of positive shocks in government consumption and interest rates. By comparing rational and behavioral agent responses, it clarifies how these frameworks influence gross domestic product (GDP), inflation, private and government consumption and nominal interest rates.

Design/methodology/approach

The study employs a new Keynesian dynamic stochastic general equilibrium (DSGE) model with Bayesian estimation from 2000Q1 to 2022Q4, capturing rational and behavioral behaviors with adjustments for Brazilian economic idiosyncrasies. Impulse response functions (IRF) assess the dynamic effects of policy shocks, providing a comparative analysis of the two frameworks.

Findings

Behavioral agents show greater initial sensitivity to policy shocks, causing more pronounced fluctuations in GDP, inflation and private consumption compared to rational agents. Over time, the behavioral approach leads to a more robust recovery, while the rational approach results in a quicker return to equilibrium but less pronounced long-term recovery. The study also finds fiscal policy can partially offset the negative impacts of monetary tightening, with a more delayed effect in the behavioral model.

Originality/value

This paper provides insights into the interplay between monetary and fiscal policies under different agent expectations, emphasizing the importance of incorporating behavioral elements into macroeconomic models to better capture policy dynamics in emerging markets.

Details

EconomiA, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1517-7580

Keywords

Open Access
Article
Publication date: 22 August 2023

Sabina Kołodziej, Ewa Wanda Maruszewska and Małgorzata Niesiobędzka

This paper aims to present a study on the effect of income and expense shifting on the corporate income tax evasion – an example of intentional noncompliance practiced by tax…

1544

Abstract

Purpose

This paper aims to present a study on the effect of income and expense shifting on the corporate income tax evasion – an example of intentional noncompliance practiced by tax agents. The authors expected that the tool used would differentiate the extent of understatement of tax liability.

Design/methodology/approach

Two experiments were conducted in which young (N = 62) and experienced (N = 68) tax agents read a scenario placing them in a position of an employee responsible for tax planning and calculations of tax liabilities. The respondents’ task was to decide about the extent of the tax liability understatement using income or expense shifting.

Findings

Research demonstrated significantly higher extent of corporate income tax understatement when using income shifting compared to expense shifting in case of experienced tax agents (Study 2) and on tendency level among young tax agents (Study 1).

Research limitations/implications

Results of the studies might be of interest to managers paying attention to tax procedures within the company, governmental agencies investigating corporate tax evasion, as well as educators responsible for tax agents’ initial training and lifelong learning.

Originality/value

This study concentrates on tax agents who are employed in companies and corporate income tax evasion, which has not been analyzed in the literature so far.

Details

Central European Management Journal, vol. 31 no. 3
Type: Research Article
ISSN: 2658-0845

Keywords

Open Access
Article
Publication date: 26 June 2023

David Leiño Calleja, Jeroen Schepers and Edwin J. Nijssen

The impact of frontline robots (FLRs) on customer orientation perceptions remains unclear. This is remarkable because customers may associate FLRs with standardization and…

1897

Abstract

Purpose

The impact of frontline robots (FLRs) on customer orientation perceptions remains unclear. This is remarkable because customers may associate FLRs with standardization and cost-cutting, such that they may not fit firms that aim to be customer oriented.

Design/methodology/approach

In four experiments, data are collected from customers interacting with frontline employees (FLEs) and FLRs in different settings.

Findings

FLEs are perceived as more customer-oriented than FLRs due to higher competence and warmth evaluations. A relational interaction style attenuates the difference in perceived competence between FLRs and FLEs. These agents are also perceived as more similar in competence and warmth when FLRs participate in the customer journey's information and negotiation stages. Switching from FLE to FLR in the journey harms FLR evaluations.

Practical implications

The authors recommend firms to place FLRs only in the negotiation stage or in both the information and negotiation stages of the customer journey. Still then customers should not transition from employees to robots (vice versa does no harm). Firms should ensure that FLRs utilize a relational style when interacting with customers for optimal effects.

Originality/value

The authors bridge the FLR and sales/marketing literature by drawing on social cognition theory. The authors also identify the product categories for which customers are willing to negotiate with an FLR. Broadly speaking, this study’s findings underline that customers perceive robots as having agency (i.e. the mental capacity for acting with intentionality) and, just as humans, can be customer-oriented.

Details

Journal of Service Management, vol. 34 no. 6
Type: Research Article
ISSN: 1757-5818

Keywords

Open Access
Article
Publication date: 26 June 2019

Christophe Schinckus

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different…

4853

Abstract

Purpose

The term “agent-based modelling” (ABM) is a buzzword which is widely used in the scientific literature even though it refers to a variety of methodologies implemented in different disciplinary contexts. The numerous works dealing with ABM require a clarification to better understand the lines of thinking paved by this approach in economics. All modelling tasks are a means and a source of knowledge, and this epistemic function can vary depending on the methodology. this paper is to present four major ways (deductive, abductive, metaphorical and phenomenological) of implementing an agent-based framework to describe economic systems. ABM generates numerous debates in economics and opens the room for epistemological questions about the micro-foundations of macroeconomics; before dealing with this issue, the purpose of this paper is to identify the kind of ABM the author can find in economics.

Design/methodology/approach

The profusion of works dealing with ABM requires a clarification to understand better the lines of thinking paved by this approach in economics. This paper offers a conceptual classification outlining the major trends of ABM in economics.

Findings

There are four categories of ABM in economics.

Originality/value

This paper suggests a methodological categorization of ABM works in economics.

Details

Journal of Asian Business and Economic Studies, vol. 26 no. 2
Type: Research Article
ISSN: 2515-964X

Keywords

Open Access
Article
Publication date: 16 August 2022

Juri Matinheikki, Katri Kauppi, Alistair Brandon–Jones and Erik M. van Raaij

Contemporary supply chain relationships inherently rely on delegation of work between organizations and, thus, are subject to agency problems for which a wide range of governance…

6801

Abstract

Purpose

Contemporary supply chain relationships inherently rely on delegation of work between organizations and, thus, are subject to agency problems for which a wide range of governance mechanisms exist. This review of agency theory (AT), across four distinct fields, explains the connection between governance mechanisms and supply chain relationship types.

Design/methodology/approach

The study uses a systematic literature review (SLR) of articles using AT in a supply chain context from the operations and supply chain management, general management, marketing, and economics fields.

Findings

The authors categorize the governance mechanisms identified to create a typology of agency relationships in supply chains.

Research limitations/implications

The developed typology provides parsimonious theory on different forms of supply chain agency relationships and takes a step towards a “supply chain-oriented agency theory” explaining and predicting relationship types and governance in supply chains. Furthermore, a future research agenda calls for more accurate measuring of agency costs, to examine residual gains alongside residual losses, to take a dual-sided perspective of agency relations and to adopt AT to examine more complex supply networks.

Practical implications

The review provides a menu of governance mechanisms and describes situations under which these mechanisms could be deployed to guide managers when developing their supply chain relationships.

Originality/value

The first review to combine and elaborate views from four major disciplines using AT as a lens to supply chain relationships. Expanding the traditional set of governance mechanisms provides academics and practitioners with a bigger “menu” of options to consider.

Details

International Journal of Operations & Production Management, vol. 42 no. 13
Type: Research Article
ISSN: 0144-3577

Keywords

Open Access
Article
Publication date: 2 April 2021

Jean Claude Mutiganda and Janne T. Järvinen

Research was conducted to investigate whether, and how, political accountability might stabilise when agents are faced with profound changes in external structures such as…

6381

Abstract

Purpose

Research was conducted to investigate whether, and how, political accountability might stabilise when agents are faced with profound changes in external structures such as competition laws and austerity policies.

Design/methodology/approach

We performed a field study from 2007 to 2015 in a regional hub in Finland and worked with data from document analysis, interviews and meeting observations. We have used embedded research design, where we apply methodological bracketing as well as composite sequence analysis for field research.

Findings

Accountability declined when irresistible external structures were the dominant influence on the unreflective actions of agents-in-focus. With time, however, the agents started acting critically by drawing on structures that could facilitate strategic actions to stabilise political accountability.

Research limitations/implications

The field research and interpretation of the data were limited to the organisation analysed; however, the theoretical arguments allow for analytical generalisations.

Practical implications

The research demonstrates how public officials and political decision-makers can eventually adopt a strategic approach when faced with irresistible change in external structures.

Social implications

The research demonstrates how public officials and political decision-makers can eventually adopt a strategic approach when faced with irresistible changes in external structures.

Originality/value

The study locates political accountability in the context of strong structuration theory and discusses how it is redefined by external structures.

Details

Accounting, Auditing & Accountability Journal, vol. 34 no. 9
Type: Research Article
ISSN: 0951-3574

Keywords

Open Access
Article
Publication date: 11 May 2020

Zhizhao Zhang, Tianzhi Yang and Yuan Liu

The purpose of this work is to bridge FL and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. and blockchain…

2398

Abstract

Purpose

The purpose of this work is to bridge FL and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. and blockchain technology through designing a blockchain-based smart agent system architecture and applying in FL. FL is an emerging collaborative machine learning technique that trains a model across multiple devices or servers holding private data samples without exchanging their data. The locally trained results are aggregated by a centralized server in a privacy-preserving way. However, there is an assumption where the centralized server is trustworthy, which is impractical. Fortunately, blockchain technology has opened a new era of data exchange among trustless strangers because of its decentralized architecture and cryptography-supported techniques.

Design/methodology/approach

In this study, the author proposes a novel design of a smart agent inspired by the smart contract concept. Specifically, based on the proposed smart agent, a fully decentralized, privacy-preserving and fair deep learning blockchain-FL framework is designed, where the agent network is consistent with the blockchain network and each smart agent is a participant in the FL task. During the whole training process, both the data and the model are not at the risk of leakage.

Findings

A demonstration of the proposed architecture is designed to train a neural network. Finally, the implementation of the proposed architecture is conducted in the Ethereum development, showing the effectiveness and applicability of the design.

Originality/value

The author aims to investigate the feasibility and practicality of linking the three areas together, namely, multi-agent system, FL and blockchain. A blockchain-FL framework, which is based on a smart agent system, has been proposed. The author has made several contributions to the state-of-the-art. First of all, a concrete design of a smart agent model is proposed, inspired by the smart contract concept in blockchain. The smart agent is autonomous and is able to disseminate, verify the information and execute the supported protocols. Based on the proposed smart agent model, a new architecture composed by these agents is formed, which is a blockchain network. Then, a fully decentralized, privacy-preserving and smart agent blockchain-FL framework has been proposed, where a smart agent acts as both a peer in a blockchain network and a participant in a FL task at the same time. Finally, a demonstration to train an artificial neural network is implemented to prove the effectiveness of the proposed framework.

Details

International Journal of Crowd Science, vol. 4 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

1 – 10 of over 7000