A generic accounting model to support operations management decisions

Information systems are generally unable to generate information about the financial consequences of operations management decisions. This is because the procedures for determining the relevant accounting information for decision support are not formalised in ways that can be implemented in information systems. This paper describes a formalised procedure, which is based on the following theoretical propositions: (i) cost behaviour is described on the basis of a company's contracts for purchasing and selling resources, and (ii) hierarchical relationships between decisions are recognised, because some decisions have to be made earlier than others. Earlier decisions determine the feasible alternatives for later decisions (e.g. through constraints in available production capacity or components), and the plans that supported the earlier decisions serve as instructions for later decisions. The procedure can be implemented in information systems to provide accounting information in case later decisions deviate from these instruc tions (within the limits of the real-world constraints) because new information becomes available.     

Supporting the allocation of software development work in distributed teams with multi-criteria decision analysis

In the fast moving software industry, projects have been increasingly developed by distributed teams, which are located in geographically remote offices and collaborate using information communication technologies. In such environments, project distribution presents specific challenges, as work in distributed teams increases project technical complexity, communication lines multiply and stakeholders’ interests may be divergent. Despite the importance and complexity of this type of problem, it seems that there is a lack of reports, in the literature, of systems that could support these decisions. This paper presents a real-world case study, where we developed a multi-criteria model for supporting the distributed team work allocation decision for a major global software company. It was developed with a group of software development project managers, using decision conferencing and multi-attribute value analysis. The model deals not only with software engineering attributes, but also “soft” and strategic issues, like team satisfaction and training opportunities. We also discuss some issues and challenges faced during this modelling process.     

MASCOT: An agent-based architecture for dynamic supply chain creation and coordination in the internet economy

The emerging global internet economy will increasingly put a premium on the ability of companies to quickly and accurately evaluate new market opportunities, new product/ subcomponent designs, and other strategic business decisions (e.g. make-or-buy) in coordination with potential supply chain partners. It also requires that companies be able to effectively and efficiently coordinate activities, e.g. production and transportation across supply chains that are dynamically set up in response to constantly changing and increasingly customized market requirements. This paper provides an overview of MASCOT ('multi-agent supply chain cordination tool'), a reconfigurable, multi-level, agent-based planning and scheduling architecture aimed at supporting these functionalities. It reviews key innovative elements of the MASCOT architecture with a special emphasis on its support of realtime mixed-initiative 'what-if' functionalities, enabling endusers at different levels within the architecture to rapidly     

Positioning a company in enterprise collaborations: Vertical integration and make-or-buy decisions

During any strategic development, a firm has to position itself in its supply chain. The decision as to how many activities in the chain to occupy is known as vertical integration and is termed as make-or-buy when an individual activity is considered. Because of its very nature, this category of decisions may be made only within the framework of an extended enterprise. To support such a decision-making process, a model is described that defines all key elements needed to make such critical decisions. More precisely, a set of rules must present all items which have to be defined and valued, and the relationships between them, in order to conclude if an activity must be processed internally (Make) or supplied externally (Buy). This paper details such a hierarchy of rules.     

An agent-based approach to modelling virtual enterprises

This paper describes how virtual enterprises (VEs) can be modelled using the AGORA multi-agent architecture, designed for modelling and supporting cooperative work among distributed entities. The model consists of a structure of AGORAs and agents, where AGORAs are facilitators of cooperative work for agents and the agents represent the partners of the VE, the cooperative mechanisms and the service providers. The distributed and goal-oriented nature of the VE provides a strong motivation for the use of agents to model VEs. The main advantages of this approach are that the structure of AGORAs provides a homogeneous modelling environment throughout the life cycle of the VE, traceability of the VE activities and a history of the VE. In addition to these, it is important to point out that, agents being computational entities, the resulting model provides an easy and efficient passage from the model to the computational support that is required by the VE.     

Flexible reasoning using sensible agent-based systems: A case study in job flow scheduling

Planning and control systems for highly dynamic and uncertain manufacturing environments require adaptive flexibility and decision-making capabilities. Modern distributed manufacturing systems assess the utility of planning and executing solutions for both system goals (e.g. minimize manufacturing production time for all parts or minimize WIP) and local goals (e.g. expedite part A production schedule or maximize machine X utilization). Sensible Agents have the ability to alter their autonomy levels to choose among a set of decision models in order to handle the differences between local and system goals. In this paper, Sensible Agents are applied to a production planning and control problem in the context of job shop scheduling and decision model theory. Sensible Agents provide for trade-off reasoning mechanisms among system and local utilities that are flexible and responsive to an agent's abilities, situational context and position in the organizational structure of the system.     

Robustness of linear models in dynamic multivariate predictions

Linear aggregation models employing unit and equal weights have been shown to be superior to human decisions in a surprising range of decision situations. In addition, decisions based on these models have often been found to be superior to those based on linear regression models (LRMs). This general issue was explored for repetitive decisions in production planning. The problem considered differs in several aspects from the types of problems investigated previously: (1) the problem is dynamic rather than static; (2) a set (or vector) of interactive decisions dependent on previous decisions is required to be made, where a decision in stage t, the dependent variable, becomes an independent variable in stage t + 1; and (3) the criterion function is cost with a quadratic loss function (rather than the correlation measure of R²). Moreover, since repetitive decisions were involved, the parameters of the models were estimated using past human decisions. These were used to predict specific values of the decision variables (rather than rank order), which in turn were employed recursively to predict values of the decision variables at subsequent stages. While decisions from equal weighting rules were found to be superior to human decisions and not greatly inferior to decisions from linear regression models, decisions from unit weighting rules performed poorly. The rationale for such performance is discussed, indicating that previous theoretical and empirical research on linear weighting models is not generally applicable to dynamic, multivariate interactive decisions problems with lagged variables.     

A global meaning of supply chain social sustainability

Abstract

The purpose of this research is to help reduce tensions in supply chain social sustainability (SCSS) decisions by providing a common global, contextual definition of social sustainability. This exploratory study utilised an inductive structured interview method to capture SCSS concept meanings. Those interviewed are from, have lived, and worked in developed economies, emerging economies and the base of the pyramid (BOP) economies. The results present a new global baseline definition of SCSS to inform theory and practice by finding that SCSS meanings differ not only between the different levels of economic development, but also within the levels as well. Culture, community and whether basic human needs are met all weigh into perspectives of what this concept is and should entail; a broad, contingent definition is most appropriate moving forward for sustainability planning and execution. Further research with stakeholders in more countries and communities is needed to validate our proposal.     

Distributed Decision‐Making in Supply Chains and Private E‐Marketplaces

This paper develops a distributed decision‐making framework for the players in a supply chain or a private e‐marketplace to collaboratively arrive at a global Pareto‐optimal solution. In this model, no player has complete knowledge about all the costs and constraints of the other players. The decision‐making framework employs an iterative procedure, based on the Integer L‐shaped method, in which a master problem is solved to propose global solutions, and each player uses his local problems to construct feasibility and optimality cuts on the master problem. The master problem is modeled as a mixed‐integer program, and the players' local problems are formulated as linear programs. Collaborative planning scenarios in private e‐marketplaces and in supply chains were formulated and solved for test data. The results show that this distributed model is able to achieve near‐optimal solutions considerably faster than the traditional centralized approach.     

Rush and Be Wrong or Wait and Be Late? A Model of Information in Collaborative Processes

Business processes have become more simultaneous and collaborative in the recent past. In simultaneous processes, multiple parties must adapt to one another in real time as decisions evolve. For example, New Product Development (NPD) requires collaboration in the context of Concurrent Engineering, and Supply Chain Management (SCM) in the context of collaborative planning. In both cases, parties must modify decisions based on preliminary information, information that is not fully precise or stable, about what the other parties are doing. This article develops a generalized model of real‐time decision making based on preliminary information, which applies both to NPD and SCM. The model offers insights into when to commit to a course of action, and we derive seven principles that help in dealing with preliminary information.     

An integrated supplier-buyer model for improving supply chain coordination

This study develops a decision support model that can be used by a supplier in making production and price decisions at contract renewal times in a supply chain environment. The supplier first makes aggregate production decisions with a special attempt to estimate buyer commitments, and then determines the price of the item so as to satisfy his own profit and buyer cost reduction expectations simultaneously. Mathematical programming models are designed to achieve these in accordance with the contract terms. The main emphasis is placed upon the conceptual and negotiation aspects of the models, and some solution procedures are cited from previous studies. Then the approach is implemented in the biggest electric motor manufacturer in Turkey which has a large number of buyers in household appliances sector, and it is shown to be a useful tool for developing fair partnership.     

The Contribution of Formal Planning Systems to Strategic Investment Decisions1

This paper aims to investigate linkages between formal planning systems (FPSs) and characteristics of the processes followed in making strategic investment decisions (SIDs). The empirical testing was based on a sample of 70 SIDs drawn from 38 industrial enterprises operating in Greece. Primary data on FPSs and SIDs were provided by key participants in the decision-making process, using a combination of structured interviews and questionnaire completion. Contrary to the argument raised by several academics that much decision making takes place outside FPSs, the findings of this paper support the view that at least for decisions of a clearly strategic nature this may not be valid. Results consistently show that strong associations exist between characteristics of SID processes and dimensions of FPSs. More specifically: The degree of rationality-comprehensiveness as well as degree of financial reporting in the process of making SIDs is positively associated with FPSs. Particularly strong is the association between the existence of a set of formalized rules guiding the process of strategic decision making and FPSs. Furthermore, the association between both hierarchical decentralization and lateral communication in advancing SIDs and FPSs appears to be fairly strong. Finally, results failed to support any statistical significant relationship between duration timing of SID processes and dimensions of FPSs.     

COMPUTER-BASED SUPPORT OF ORGANIZATIONAL DECISION MAKING*

The central issue of this research is the extent to which computer facilities can be used to support organizational decision-making processes beyond mere performance of information retrieval. This depends upon the extent to which computers can be made to emulate human perceptual and judgmental processes. We present a framework for understanding these cognitive processes and examine how it applies to organizational decisions. Moreover, the framework furnishes a basis for the design of a generalized, intelligent problem processor. This processor is general in the sense of its ability to support a decision maker's activities, regardless of the decision maker's application area (e.g., urban planning, water-quality planning, etc.). It is intelligent in the sense of its ability to comprehend English-like queries and subsequently formulate models, interface appropriate data with those models, and execute the models to produce some facts or expectations about the problem under consideration.     

Generating Explanations for Goal-Based Decision Making*

As information systems make the transition from decision support to decision making, there will be a concomitant need for the programs to explain or justify their actions. Without such explanations, humans will not readily cede authority to a machine. This paper describes an automated decision-making program, VOTE, which generates natural language explanations for its decisions in both English and French. The program domain is Congressional roll call voting. VOTE simulates voting decisions of specific members of the United States House of Representatives on given bills. VOTE's natural language generation facility is also used by the underlying databases to interpret the knowledge representations. These underlying knowledge representations are described and applications of this decision making model to the general business domains of strategic planning, investment, and marketing are suggested.     

A Simulation of Partial Information Use in Decision Making: Implications for DSS Design

Information matrices are often the output produced by a decision support system. These matrices are a common method for expressing a decision situation under different decision-making scenarios. The decisions involved in designing a decision support system to generate the information matrix are important and involve several cost and benefit components. A designer needs guidance in making effective design decisions in this context. Such guidance can be provided by considering the relationships among specific design decisions, costs, and benefits. The general objective of this study is to provide a comprehensive framework for this purpose. This study is the first to develop and present a comprehensive cost-benefit framework for evaluating design decisions for a variety of scenarios. The specific objective of this research is to provide guidance regarding the number of available information dimensions to incorporate in a computer-based decision aid. Simulation experiments are conducted with a completely specified model based on the cost-benefit framework (including needed assumptions) to evaluate how many information dimensions to include for a specific information matrix size to achieve a balance between information use costs and decision quality. Based upon extensive simulation analyses for a hypothetical decision maker, the practical guideline found for designers is to include only the top half of the relevant information dimensions in any specific decision support system. Over a large number of repeating choice decisions, the savings in cognitive effort and information gathering costs clearly offset relatively minor losses in decision quality.     

Decision support system for the batching problems of steelmaking and continuous-casting production

This paper investigates two batching problems for steelmaking and continuous-casting (SCC) production in an integrated iron and steel enterprise. The tasks of the problems are to make the decisions as how to consolidate ordered slabs into charges, and then how to group charges into casts. The effective decisions on these batching problems can help to balance the requirements of materials in downstream production lines, improve the customer satisfaction levels, and reduce production costs (including reduction of open ordered slabs, less slabs quality upgrading, reduction of steel-grade changeovers, and reduction of inefficient utilization of tundishes lives). We first formulate the problems as integer-programming models by consider practical constraints and requirements, and then develop the two heuristic algorithms for the corresponding batching problems. By embedding above models and algorithms, we develop decision support system (DSS) software with interactive planning editor. The DSS has been tested by using practical data set collected from the steelmaking plant in Baosteel which is one of the most advanced iron and steel enterprises in China. Computational experiments demonstrate that the models and algorithms developed can generate the satisfactory solutions when they work together with the planning editor in the DSS.     

Sustainable planning strategies in supply chain systems: proposal and applications with a real case study in fashion

Abstract

Pollution generated by the fashion industry drives people to pay attention to fashion companies’ sustainability practice. This increase in attention has induced vast literature studying the related area. Since the fashion apparel supply chain is complicated which involves a lot of interrelated steps and decisions, how fashion companies can identify the demand in sustainable fashion and make the right decision in resource allocation throughout the supply chain becomes a critical issue. As a result, this paper examines how a fashion company can develop a successful sustainable planning strategy throughout the sustainable fashion supply chain. The sustainability attributes and the sustainable planning strategy mechanism are also discussed. Based on the institutional theory and resource-based theory, we first analyse the external pressure and internal motivations for companies to adopt a sustainable planning strategy in the fashion supply chain. We then identify the core stakeholders related to the sustainable planning strategy and propose how the decision-making theory can help develop the sustainable supply chain management mechanism. Next, we establish a sustainable planning strategy framework. Finally, via a case study with public data on the fashion giant brand Nike, we explore the application of our proposed sustainable planning strategy framework. The finding suggests that the strategic planning of fashion companies on sustainability can improve the performance of the stakeholders throughout the whole sustainable fashion supply chain.     

Cloud manufacturing system for sheet metal processing

Abstract

Cloud computing is changing the way industries and enterprises run their businesses. Cloud manufacturing is emerging as an approach to transform the traditional manufacturing business model, while helping the manufacturer to align production efficiency with its business strategy, and creating intelligent factory networks that enable collaboration across the whole enterprise. Many production planning and control (PPC) problems are essentially optimisation problems, where the objective is to develop a plan that meets the demand at minimum cost or maximum profit. Because the underlying optimisation problem will vary in the different business and operation phases, it is important to think about optimisation in a dynamic mechanism and in a number of interlinked sub-problems at the same time. Cloud manufacturing has the potential to offer decision support as a service and medium of communication in PPC. To solve these problems and produce collaboration across the supply chain, this paper provides an overview of the state of the art in cloud manufacturing and presents a model of cloud-based production planning and production system for sheet metal processing.     

Improving throughput for an electronic assembly line using a constraint analysis methodology

Electronic assembly operations are vital to industries such as telecommunications, computers and consumer electronics. This paper presents a constraint analysis methodology for planning and improving electronic assembly operations that draws on concepts from queueing theory, simulation and production planning. The proposed methodology identifies the operational bottleneck and predicts the utilization, throughput and lead time of the assembly line. It also quantifies the relationship between yields and utilization for the assembly operations. A case study is presented that applies the methodology at an Ericsson, Inc., telecommunications equipment assembly facility. The constraint analysis methodology provided valuable decision support as the managers of Ericsson evaluated the costs and benefits of additional production capacity. Although the focus of this paper is electronic assembly operations, the methodology can be applied to general flow line assembly systems with feedback loops for test and rework under dedicated high-volume production.     

The Quality of Stakeholder-Based Decisions

The increased use of stakeholder processes in environmental decision making has raised concerns about the quality of decisions these processes produce. Some claim that stakeholders make inadequate use of scientific information and analysis and are all too ready to sacrifice technical quality for political expediency. This article looks to the case study record to examine the quality of the decisions from stakeholder-based processes. The data for the analysis come from a "case survey," in which researchers coded information from 239 published case studies of stakeholder involvement in environmental decision making. These cases reflect a diversity of planning, management, and implementation activities carried out by environmental and natural resource agencies at many levels of government. Overall, the case-study record suggests that there should be little concern that stakeholder processes are resulting in low-quality decisions. The majority of cases contain evidence of stakeholders improving decisions over the status quo; adding new information, ideas, and analysis; and having adequate access to technical and scientific resources. Indeed, data suggest that it is the more intensive stakeholder processes--precisely those that have aroused recent concern--that are more likely to result in higher-quality decisions.