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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

There are four categories of ABM in economics.

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

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.

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.

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.

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

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

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

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

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.

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.

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.

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.

The purpose of this article is to provide an overview of agent-based modeling as an alternative method for public administration research. It is focused on encouraging public administration scholars to come to better understanding of the method.

This article performed a comprehensive review of methodological issues relative to agent-based modeling.

After reviewing the current research themes in public administration and the methodological nature of agent-based modeling, we found that agent-based modeling can help researchers to advance theories by means of sophisticated thought experiment which is not possible by formal modeling and verbal reasoning. We also pointed out that agent-based modeling does not substitute empirical research, but can add much value through being part of a mixed-method and multidisciplinary research.

We suggested that interested researchers may need to take a strategic approach in developing and describing a pertinent model and reporting its results.

Agent-based modeling has rarely been used in public administration research. The article provides an introductory overview for researchers not familiar with ABM and suggests to the academic community future venues that would unfold from agent-based modeling.

The present study aims to explore how various doings, strategic actions and power relations stemming from internal agents are instrumental in (re)constituting the different forms and meanings of budgeting in a specific field.

The paper uses a single-case study method based on a Sri Lankan public university. Data are collected using interviews, documentary evidence and observations.

The empirical evidence suggested that internal agents are crucial, and they are the producers of budgetary practice as they possess practical knowledge and power relations in the field where they operate. The case data demonstrate that organisational agents do have real essence as active and acting to produce effects in budgeting practices, and the significance of exploring the singularity of multiple agents in terms of their viewpoints, trajectories, dispositions and power relations, who may form, sustain or interrupt budgetary practices in a given setting.

As the research is directed towards the selection of in-depth enquiry of specific setting infused with culture, values, perception and ideology, it might cause to diminish the researcher's analytical objectivity and independence of the research.

As budgetary practices are product of human interaction, it is important to note that practitioners should be concerned with what agents do in actual practice and their inactions, influences and power relations in budgeting practices, which might not align with the structural forces enlisted in the budgeting. It would be of interest for future empirical research to explore the interplay between the diverse interests of organisational agents and agents beyond the individual organisations.

This study contributes to the literature on management control practices by documenting the importance of understanding the “practice” through relational thinking of all three concepts is emphasised, such interrelated theoretical insights are seldom used to understand accounting practices. This research emphasises the importance of bringing out the microprocessual facets of management control to open up its non-conscious, non-strategic and non-rationalist forms.