Uncertainty in competitive bidding – a framework for product–service systems

Owing to servitisation, manufacturing companies are increasingly required to compete through the provision of services around their products. The contracts for these services are often allocated through competitive bidding where the potential suppliers submit a price bid to the customer. The pricing decision is influenced by various uncertainties. This article proposes a conceptual framework depicting these influencing uncertainties on the bidding strategy. This framework is based on three empirical studies with industry investigating different viewpoints on the decision-making process. The intention is to support the pricing decision when competitively bidding for a service contract. The framework can be applied to specific competitive bidding situations to identify the influencing uncertainties, model them and depict their influences on the pricing decision.     

面向角色的多agent 工作流模型研究

目前的工作流建模工具大多是面向活动、面向产品、面向目标或面向决策的,没有强调工作流 是多个角色主体协作的过程,工作流的绩效最终依赖员工及其角色的作用. 从角色及其合作的角 度,分析了面向角色的工作流模型及其表示方法,为工作流的管理提供新的思路. 在此基础上,研究 了角色、agent 和工作流的关系,给出了一种面向角色的工作流多agent 管理系统模型和原型.     

Risk Assessment and Alternatives Assessment: Comparing Two Methodologies

The selection and use of chemicals and materials with less hazardous profiles reflects a paradigm shift from reliance on risk minimization through exposure controls to hazard avoidance. This article introduces risk assessment and alternatives assessment frameworks in order to clarify a misconception that alternatives assessment is a less effective tool to guide decision making, discusses factors promoting the use of each framework, and also identifies how and when application of each framework is most effective. As part of an assessor's decision process to select one framework over the other, it is critical to recognize that each framework is intended to perform different functions. Although the two frameworks share a number of similarities (such as identifying hazards and assessing exposure), an alternatives assessment provides a more realistic framework with which to select environmentally preferable chemicals because of its primary reliance on assessing hazards and secondary reliance on exposure assessment. Relevant to other life cycle impacts, the hazard of a chemical is inherent, and although it may be possible to minimize exposure (and subsequently reduce risk), it is challenging to assess such exposures through a chemical's life cycle. Through increased use of alternatives assessments at the initial stage of material or product design, there will be less reliance on post facto risk‐based assessment techniques because the potential for harm is significantly reduced, if not avoided, negating the need for assessing risk in the first place.     

面向角色的多agent 工作流模型研究

目前的工作流建模工具大多是面向活动、面向产品、面向目标或面向决策的,没有强调工作流是多个角色主体协作的过程,工作流的绩效最终依赖员工及其角色的作用.从角色及其合作的角度,分析了面向角色的工作流模型及其表示方法,为工作流的管理提供新的思路.在此基础上,研究了角色、agent和工作流的关系,给出了一种面向角色的工作流多agent管理系统模型和原型.     

PROJECT IPMA: APPLYING DECISION SUPPORT SYSTEM DESIGN PRINCIPLES TO BUILDING EXPERT-BASED SYSTEMS*

There currently is no widely accepted design framework for building expert systems. Knowledge engineers describe the process in terms of a set of heuristics or as a series of phases. Most paradigms are based on post-development reflections. This paper explores an expert-based system constructed using decision support system design techniques. An actual system in experimental use at the Department of Entomology, Oregon State University, was designed using the approach presented. The system, Integrated Pest Management Assistant (IPMA), will be used by extension agents to help orchard owners make decisions regarding pear tree pest infestations and to offer remedial strategies for eradicating potentially destructive insects.     

A statistical framework for strategic decision making with AHP: Probability assessment and Bayesian revision

A probability assessment framework is outlined for an organizational decision involving a conditioning event (CE). The decision may, for example, involve a new-product launch (strategic decision) dependent on the outcome of market research (CE). The framework illustrates how Bayesian revision could be employed as related “news” arrives intermittently to revise current probabilities prior to decision implementation. A unique contribution of this paper is its utilization of the analytic hierarchy process to ascertain a set of consistent and coherent probabilities for the event/sample spaces at all stages of the decision process.     

A Public Transportation Decision‐Making Model within a Metropolitan Area

Understanding the decision‐making factors associated with public transportation is essential in strategic development of public transportation to improve acceptance and utilization of mass transit systems. This research analyzes factors affecting attitudes toward public transportation and the choice of transportation mode by investigating the public transportation decision‐making process of working professionals using a survey methodology. The objectives of this research are to model the transportation decision‐making process of public transportation users in a metropolitan area and to determine key factors that affect the public transportation choices made by potential public transportation users. This study contributes to the literature by developing and testing an integrated theoretical framework for modeling an individual's public transportation decision‐making process using four independent variables: Perceived Public Transportation Security, Knowledge, Price, and Convenience. We develop the proposed theoretical framework based upon the extant literature and tested it using partial least squares structural equation modeling (PLS‐SEM). Based on the Theory of Reasoned Action, the Theory of Planned Behavior, and utility theory, we develop the factors and refine associated items using confirmatory factor analysis.     

Entscheidungsfreiheit als Grundlage wirtschaftswissenschaftlicher Forschung – Bezüge zwischen Betriebswirtschaftslehre, Ethik und Neurobiologie

This paper analyses whether freedom of decision as a crucial precondition of normative decision theory is questioned by ethics and neurobiology. It argues for an understanding of business ethics which sees the economic agents’ freedom of decision as the necessary basis for handling ethical questions in business practice, rather than as a limitation to this end. Analysing free will as a main object of scrutiny in neurobiology, it is hypothesised that acting in reality lies between plain determination on the one extreme and complete autonomy on the other. It supports the proposition in decision theory that managerial decisions are taken within the conditions of a certain framework. However, in the light of the recent developments in behavioural economics, ethics and neurobiology, it argues for the extension of this concept by consciously or unknowingly anchored norms.     

Eight Motivational Forces and Voluntary Turnover: A Theoretical Synthesis with Implications for Research

In this study, we synthesize, from the attitude and turnover literatures, a framework of eight (8) distinctive motives, or “Forces”. We then illustrate how the “8 Forces” framework can be utilized by turnover researchers as clarification of reported reasons for turnover, as causal mediators of turnover predictors, and as factors related to the type of turnover decision process. Finally, we discuss further implications of this framework.     

Managing the Risk of Uncertain Threshold Responses: Comparison of Robust, Optimum, and Precautionary Approaches

Many commentators have suggested the need for new decision analysis approaches to better manage systems with deeply uncertain, poorly characterized risks. Most notably, policy challenges such as abrupt climate change involve potential nonlinear or threshold responses where both the triggering level and subsequent system response are poorly understood. This study uses a simple computer simulation model to compare several alternative frameworks for decision making under uncertainty -- optimal expected utility, the precautionary principle, and three different approaches to robust decision making -- for addressing the challenge of adding pollution to a lake without triggering unwanted and potentially irreversible eutrophication. The three robust decision approaches -- trading some optimal performance for less sensitivity to assumptions, satisficing over a wide range of futures, and keeping options open -- are found to identify similar strategies as the most robust choice. This study also suggests that these robust decision approaches offer a quantitative, decision analytic framework that captures the spirit of the precautionary principle while addressing some of its shortcomings. Finally, this study finds that robust strategies may be preferable to optimum strategies when the uncertainty is sufficiently deep and the set of alternative policy options is sufficiently rich.     

Supply Networks as a Complex Adaptive System: Toward Simulation‐Based Theory Building on Evolutionary Decision Making

In this article, we examine how the firms embedded in supply networks engage in decision making over time. The supply networks as a complex adaptive system are simulated using cellular automata (CA) through a dynamic evolution of cooperation (i.e., “voice” decision) and defection (i.e., “exit” decision) among supply network agents (i.e., firms). Simple local rules of interaction among firms generate complex patterns of cooperation and defection decisions in the supply network. The incentive schemes underlying decision making are derived through different configurations of the payoff‐matrix based on the game theory argument. The prisoner's dilemma game allows capturing the localized decision‐making process by rational agents, and the CA model allows the self‐organizing outcome to emerge. By observing the evolution of decision making by cooperating and defecting agents, we offer testable propositions regarding relationship development and distributed nature of governance mechanisms for managing supply networks.     

Enhancing knowledge construction processes within multicriteria decision analysis: The Collaborative Value Modelling framework

This paper proposes a new Collaborative Value Modelling framework, that combines Delphi and multicriteria decision conferencing, to build widely informed evaluation models. Multicriteria Decision Analysis (MCDA) is commonly used to help decision-makers and other stakeholders in complex evaluation contexts. Further to the technical soundness and meaningfulness of the methods and tools used, it is critical to design adequate social processes to promote shared understanding around key evaluation issues while capturing multiple stakeholders’ values and perspectives. Multicriteria decision conferencing processes have been typically adopted for collaborative modelling using MCDA methods in decision conferences with relatively small groups. Such a socio-technical approach has proven to be effective, in a variety of contexts, in creating a collaborative environment that enables surfacing individual beliefs, identifying common concerns, managing eventual value conflicts and promoting agreement in group model building. But, extending this framework to broader participatory contexts requires a different design of the social process, in order to ensure that model building captures the full panoply of points of view. This challenge can be tackled by enhancing multicriteria decision conferencing with an all-embracing (Web-)Delphi participatory process. We depart from the existing collaborative knowledge acquisition methodology to design, with the Delphi method, a participatory knowledge construction process that elicits and analyses individual judgemental knowledge from a (very) large and diverse number of stakeholders. The knowledge acquired is then digested by a small group of key-players, in a subsequent decision conferencing, to collaboratively develop a widely informed multicriteria evaluation model. This new Web-Delphi-decision conferencing social setting has been tested already in real complex evaluation contexts using a specific multicriteria method, the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH), to develop a variety of value modelling activities. We call this socio-technical design the Collaborative Value Modelling framework. Here, we describe its real use to support the construction of value functions, focusing on how the judgemental knowledge collected flows between the participatory and collaborative stages of the framework. Results validate that enhancing MACBETH decision conferencing with an ex ante Web-Delphi process fosters higher participation and collaboration in multicriteria modelling.     

Project risk management using multiple criteria decision-making technique and decision tree analysis: a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.     

Decision Making in Cross‐Functional Teams: The Role of Decision Power*

Through a series of game‐theoretical models, this study systematically examines decision making in cross‐functional teams. It provides a framework for the design of an organization‐specific decision‐making process and for the alignment of a team's microdecision with the “optimal” decision that maximizes the firm's payoff. This study finds that even without changing the team leader, firms could change and even dictate the team's microdecision outcome via adjusting the team member's seniority, empowering team members with veto power or involving a supervisor as a threat to overrule the team decision. This finding implies that to reposition products in the marketplace, structuring cross‐functional teams’ microdecision‐making processes is essential.     

Moral Utility Theory: Understanding the motivation to behave (un)ethically

Moral Utility Theory provides an integrative framework for understanding the motivational basis of ethical decision making by modeling it as a process of subjective expected utility (SEU) maximization. The SEUs of ethical and unethical behavioral options are proposed to be assessed intuitively during goal pursuit, with unethical conduct emerging when the expected benefits of moral transgressions outweigh the expected costs. A key insight of the model is that any factors that increase the value of a goal—including incentives, framings, and mindsets—can motivate misbehavior by increasing the SEU of unethical conduct. Although Moral Utility Theory emphasizes the automatic and habitual nature of most SEU appraisals, it also describes a mechanism for initiating the deliberative moral reasoning process: the experience of moral uncertainty. Moral uncertainty is proposed to occur when the SEUs of ethical and unethical behaviors are similar in magnitude, thereby activating the behavioral inhibition system and motivating the allocation of attentional resources toward the decision process. This framework bridges the gap between affective and cognitive perspectives on ethical decision making by identifying automatic evaluations as a central driver of moral decisions while also specifying when and how moral reasoning processes are initiated. By combining dual-process models of morality with well-validated principles from the science of motivation, Moral Utility Theory provides theoretical parsimony and formal modeling potential to the study of ethical decision making. The framework also suggests practical strategies—from employee selection and training to goal setting and compensation systems—for encouraging ethical behavior in organizations.     

The [R]Evolving Relationship Between Risk Assessment and Risk Management

In Science and Decisions: Advancing Risk Assessment, the National Research Council recommends improvements in the U.S. Environmental Protection Agency's approach to risk assessment. The recommendations aim to increase the utility of these assessments, embedding them within a new risk‐based decision‐making framework. The framework involves first identifying the problem and possible options for addressing it, conducting related analyses, then reviewing the results and making the risk management decision. Experience with longstanding requirements for regulatory impact analysis provides insights into the implementation of this framework. First, neither the Science and Decisions framework nor the framework for regulatory impact analysis should be viewed as a static or linear process, where each step is completed before moving on to the next. Risk management options are best evaluated through an iterative and integrative procedure. The extent to which a hazard has been previously studied will strongly influence analysts’ ability to identify options prior to conducting formal analyses, and these options will be altered and refined as the analysis progresses. Second, experience with regulatory impact analysis suggests that legal and political constraints may limit the range of options assessed, contrary to both existing guidance for regulatory impact analysis and the Science and Decisions recommendations. Analysts will need to work creatively to broaden the range of options considered. Finally, the usefulness of regulatory impact analysis has been significantly hampered by the inability to quantify many health impacts of concern, suggesting that the scientific improvements offered within Science and Decisions will fill an crucial research gap.     

A Framework and Case Study for Exposure Assessment in the Voluntary Children''s Chemical Evaluation Program

A conceptual framework is presented for conducting exposure assessments under the U.S. EPA's Voluntary Children's Chemical Evaluation Program (VCCEP). The VCCEP is a voluntary program whereby companies that manufacture chemicals of potential concern are asked to conduct hazard, exposure, and risk assessments for the chemicals. The VCCEP is unique in its risk-based, tiered approach, and because it focuses on children and requires a comprehensive consideration of all reasonably foreseeable exposure pathways for a particular chemical. The consideration of all potential exposure pathways for some commonly used chemicals presents a daunting challenge for the exposure assessor. This article presents a framework for managing this complicated process, and illustrates the application of the framework with a hypothetical case study. The framework provides guidance for interpreting multiple sources of exposure information and developing a plausible list of exposure pathways for a chemical. Furthermore, the framework provides a means to process all the available information to eliminate pathways of negligible concern from consideration. Finally, the framework provides guidance for utilizing the tiered approach of VCCEP to efficiently conduct an assessment by first using simple, screening-level approaches and then, if necessary, using more complex, refined exposure assessment methods. The case study provides an illustration of the major concepts.     

Dimensions of Market Attractiveness: Competitively Interactive Spatial Models*

This paper presents a normative, multidisciplinary approach for evaluating market entry strategies with concern for the effects of spatial assumptions on performance expectations. An assessment framework is linked to a series of models that show the value of adding spatial and competitive perspectives to typical baseline conceptualizations of market opportunity. Criteria for assessing market attractiveness are discussed with special concern for the problems of field service firms whose market boundaries are not limited by fixed facility locations. The problem is conceptualized as the managerial decision to locate a new brokerage office in a highly competitive regional market area. Realistic constraints are established by focusing the market entry decision through aggregate data from secondary sources that are readily available to an outsider who had not been active in the geographic markets considered. A simple model based on market potential is progressively enhanced with spatially adjusted measures of market attractiveness and competitive resistance. Empirical tests highlight the impact of alternative model formulations and choice criteria on the decision-making process.