18,698 research outputs found
Using Intelligent Agents to Understand Management Practices and Retail Productivity
Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agent-based modeling and simulation to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents could offer potential for fostering sustainable organizational capabilities in the future. The project is still at an early stage. So far we have conducted a case study in a UK department store to collect data and capture impressions about operations and actors within departments. Furthermore, based on our case study we have built and tested our first version of a retail branch simulator which we will present in this paper
A Multi-Agent Simulation of Retail Management Practices
We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of
problems in a retail context. Specifically, we are working to understand the
relationship between human resource management practices and retail
productivity. Despite the fact we are working within a relatively novel and
complex domain, it is clear that intelligent agents do offer potential for
developing organizational capabilities in the future. Our multi-disciplinary
research team has worked with a UK department store to collect data and capture
perceptions about operations from actors within departments. Based on this case
study work, we have built a simulator that we present in this paper. We then
use the simulator to gather empirical evidence regarding two specific
management practices: empowerment and employee development
Towards the Development of a Simulator for Investigating the Impact of People Management Practices on Retail Performance
Often models for understanding the impact of management practices on retail
performance are developed under the assumption of stability, equilibrium and
linearity, whereas retail operations are considered in reality to be dynamic,
non-linear and complex. Alternatively, discrete event and agent-based modelling
are approaches that allow the development of simulation models of heterogeneous
non-equilibrium systems for testing out different scenarios. When developing
simulation models one has to abstract and simplify from the real world, which
means that one has to try and capture the 'essence' of the system required for
developing a representation of the mechanisms that drive the progression in the
real system. Simulation models can be developed at different levels of
abstraction. To know the appropriate level of abstraction for a specific
application is often more of an art than a science. We have developed a retail
branch simulation model to investigate which level of model accuracy is
required for such a model to obtain meaningful results for practitioners.Comment: 24 pages, 7 figures, 6 tables, Journal of Simulation 201
A First Approach on Modelling Staff Proactiveness in Retail Simulation Models
There has been a noticeable shift in the relative composition of the industry in the developed countries in recent years; manufacturing is decreasing while the service sector is becoming more important. However, currently most simulation models for investigating service systems are still built in the same way as manufacturing simulation models, using a process-oriented world view, i.e. they model the flow of passive entities through a system. These kinds of models allow studying aspects of operational management but are not well suited for studying the dynamics that appear in service systems due to human behaviour. For these kinds of studies we require tools that allow modelling the system and entities using an object-oriented world view, where intelligent objects serve as abstract \'actors\' that are goal directed and can behave proactively. In our work we combine process-oriented discrete event simulation modelling and object-oriented agent based simulation modelling to investigate the impact of people management practices on retail productivity. In this paper, we reveal in a series of experiments what impact considering proactivity can have on the output accuracy of simulation models of human centric systems. The model and data we use for this investigation are based on a case study in a UK department store. We show that considering proactivity positively influences the validity of these kinds of models and therefore allows analysts to make better recommendations regarding strategies to apply people management practices.Retail Performance, Management Practices, Proactive Behaviour, Service Experience, Agent-Based Modelling, Simulation
EDI and intelligent agents integration to manage food chains
Electronic Data Interchange (EDI) is a type of inter-organizational information system, which permits the automatic and structured communication of data between organizations. Although EDI is used for internal communication, its main application is in facilitating closer collaboration between organizational entities, e.g. suppliers, credit institutions, and transportation carriers. This study illustrates how agent technology can be used to solve real food supply chain inefficiencies and optimise the logistics network. For instance, we explain how agribusiness companies can use agent technology in association with EDI to collect data from retailers, group them into meaningful categories, and then perform different functions. As a result, the distribution chain can be managed more efficiently. Intelligent agents also make available timely data to inventory management resulting in reducing stocks and tied capital. Intelligent agents are adoptive to changes so they are valuable in a dynamic environment where new products or partners have entered into the supply chain. This flexibility gives agent technology a relative advantage which, for pioneer companies, can be a competitive advantage. The study concludes with recommendations and directions for further research
Understanding Retail Productivity by Simulating Management Practise
Intelligent agents offer a new and exciting way of understanding the world of
work. In this paper we apply agent-based modeling and simulation to investigate
a set of problems in a retail context. Specifically, we are working to
understand the relationship between human resource management practices and
retail productivity. Despite the fact we are working within a relatively novel
and complex domain, it is clear that intelligent agents could offer potential
for fostering sustainable organizational capabilities in the future. Our
research so far has led us to conduct case study work with a top ten UK
retailer, collecting data in four departments in two stores. Based on our case
study data we have built and tested a first version of a department store
simulator. In this paper we will report on the current development of our
simulator which includes new features concerning more realistic data on the
pattern of footfall during the day and the week, a more differentiated view of
customers, and the evolution of customers over time. This allows us to
investigate more complex scenarios and to analyze the impact of various
management practices
A first approach on modelling staff proactiveness in retail simulation models
There has been a noticeable shift in the relative composition of the industry in the developed countries in recent years; manufacturing is decreasing while the service sector is becoming more important. However, currently most
simulation models for investigating service systems are still built in the same way as manufacturing simulation
models, using a process-oriented world view, i.e. they model the flow of passive entities through a system. These
kinds of models allow studying aspects of operational management but are not well suited for studying the dynamics that appear in service systems due to human behaviour. For these kinds of studies we require tools that
allow modelling the system and entities using an object-oriented world view, where intelligent objects serve as
abstract âactorsâ that are goal directed and can behave proactively.
In our work we combine process-oriented discrete event simulation modelling and object-oriented agent based
simulation modelling to investigate the impact of people management practices on retail productivity. In this paper,
we reveal in a series of experiments what impact considering proactivity can have on the output accuracy of
simulation models of human centric systems. The model and data we use for this investigation are based on a case study in a UK department store. We show that considering proactivity positively influences the validity of these kinds of models and therefore allows analysts to make better recommendations regarding strategies to apply people management practises
Determinants of technology adoption in the retail trade industry - the case of SMEs in Spain
This paper analyzes the determinants of small and medium-sized enterprisesâ technology adoption in the retail trade industry. From the theoretical perspective, two types of influential factors are differentiated in this respect: the personal characteristics of the manager/business owner and the businessâs organizational characteristics. The empirical analysis is based on a survey of 268 small and medium-sized enterprises in the Spanish retail trade sector. A logistic regression specification is used as an econometric method.
The results indicate that both the acquisition of new technical and electronic equipment and the obtaining of new software are affected by the two types of determinants previously pointed out. The manager/business ownerâs entrepreneurial motivation and educational background have significant influences on technology adoption in this type of companies. Furthermore, being part of a business group, carrying out training activities for the employees and inter-firm cooperation also positively influence technology adoption in the retail trade industry
Indian Organised Apparel Retail Sector and DSS (Decision Support Systems)
Indian apparel retail sector poses interesting challenges to a manager as it is evolving and closely linked to fashions. Appealing mainly to youth, the sector has typical information requirements to manage its operations. DSS (Decision Support Systems) provide timely and accurate information & it can be viewed as an integrated entity providing management with the tools and information to assist their decision making. The study exploratory in nature, adopts a case study approach to understand practices of organized retailers in apparel sector regarding applications of various DSS tools. Conceptual overview of DSS is undertaken by reviewing the literature. The study describes practices and usage of DSS in operational decisions in apparel sector and managerial issues in design and implementation of DSS. A multi brand local chain and multi brand national chain of apparel was chosen for the study. Varied tools were found to be used by them. It was also found that for sales forecasting and visual merchandising decisions, prior experience rather than any DSS tool was used. The benefits realized were; âhelp as diagnostic toolâ, âaccuracy of records and in billingâ, âsmooth operationsâ. The implementation issues highlighted by the store managers were; more initial teething problems rather than resistance on the part of employees of the store, need for investment of time & money in training, due to rapid technological advancements, time to time updation in DSS tools is required . Majority of operational decisions like inventory management, CRM, campaign management were handled by ERP (Enterprise Resource Planning) or POS (Point of Sale). Prioritization as well as quantification of benefits was not attempted. The issues of coordination, integration with other systems in case of ERP usage, training were highlighted. Future outlook of DSS seems bright as apparel retailers are keen to invest in technology.
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