INVESTMENT IN SETUP COST,LEAD TIME,AND DEMAND PREDICTABILITY IMPROVEMENT IN THE EOQ MODEL

We study an economic order quantity/reorder point (EOQ/ROP) model with stochastic demand and backorders where options of investing in reducing setup cost, lead time, and variance of demand forecast errors are available. The model is quite comprehensive relative to previous models since it simultaneously addresses the strategic decisions associated with these three investment opportunities as well as the tactical decisions of determining both the lot size and the safety stock. We develop a simple search procedure to obtain the optimal values of setup cost, lead time, variance of demand forecast errors, order quantity, and safety stock multiplier. Computational studies are performed to determine the sensitivity of the optimal solution of the model to changes in the model's parameters.     

Competitive supply chain network design: An overview of classifications,models, solution techniques and applications

Supply chain network design (SCND) determines the structure of a chain and affects its costs and performance. SCND deals with a variety of decisions such as determining number, size and location of facilities in a supply chain (SC) and may include tactical decisions (such as distribution, transportation and inventory management policies) as well as operational decisions (such as fulfilling customers demand). SCND has a voluminous literature. Most of the literature deals with a single SC and ignores the existing competitor SCs and future emerging ones. However, SCs compete together to capture more market shares. Even if there is not any competitor at the moment, SCs should be prepared for possible future competitive situation at the SCND stage. On the other hand, many competitive models assume that the supply chain network (SCN) and its structure already exist. Few research papers consider both aspects of design and competition. In this paper, we provide a review of SCND literature and highlight the effects of competitive environment on SCND. We review, classify, and introduce the major features of the proposed models in both SCND and competition literature. After investigating proposed competitive SCND models we develop a general framework for modeling the competitive SCND problems considering managerial insight and propose potential areas for future research.     

The problem of the last bed: Contextualization and a new simulation framework for analyzing physician decisions

Faced with a full Intensive Care Unit (ICU), physicians need to decide between turning away a new patient in need of critical care and creating a vacancy by prematurely discharging a current occupant. This dilemma is widely discussed in the medical literature, where the influencing factors are identified, the patient discharge process described and the patient health consequences analyzed. Nevertheless, the existing mathematical models of ICU management practices overlook many of the factors considered by physicians in real-world triage decisions.This paper offers a review of the medical and mathematical literature on patient discharge decisions, and a proposal for a new simulation framework to enable more realistic mathematical modeling of the real-world patient discharge process. Our model includes a) the times at which discharge decisions are made and setup times for patient transfer from the ICU to a general ward and preparation of an ICU bed for an incoming patient, in order to capture the impossibility of an immediate switch of patients; b) advance notice of the number of patients due to arrive from elective surgery requiring intensive postoperative care and potentially triggering the need for early discharges to avoid surgery cancelations; and c) patient health status (to reflect the dependency of physicians’ discharge decisions on health indicators) by modeling length of stay with a phase-type distribution in which a medical meaning is assigned to each state.A simulation-based optimization method is also proposed as a means to obtain optimal discharge decisions as a function of the health status of current patients, the bed occupancy level and the number of planned arrivals from elective surgery over the following days. Optimal decisions should strike a balance between patient rejection and LoS reduction.This new simulation framework generates an optimal discharge policy, which closely resembles real decision-making under a cautious discharge policy, where the frequency of early discharge increases with the ICU occupancy level. This is a contrast with previous simulation models, which consider only the triage of the last bed, disregarding the pressures on physicians faced with high bed occupancy levels.     

Crafting business models for conflicting goals: Lessons from creative service firms

The business model construct has become attractive to both managers and academics. It reflects how the most important organization's strategic and tactical choices regarding the allocation of resources interact in order to create and capture value. Yet with the growing entrepreneurial complexity, managers often end up pursuing conflicting and even paradoxical strategic goals, thus rendering the business modelling processes more complex, too. Well-known examples are profit versus social value, stakeholder versus company interests, exploration versus exploitation and environmental sustainability versus economic returns. The academic business model literature so far has provided limited insights on how to implement business models beyond a single goal and focused mainly on the initial strategic choice of a business model, ignoring that such salient tensions are often persistent and resurface within the business practice. In this study we leverage paradox theory to investigate how managers of creative firms make tactical choices to accommodate (not solve) salient tensions within their business models, focusing on the domains like services provided, choice of clients, networking and resourcing practices, revenue models and new venture creation. Based on qualitative case study research, we found four integrating and three differentiating decision-making tactics that managers deploy to create both economic and creative value through their business models. Adding to the business model theory, we show how business models are crafted in managerial practices by making tactical decisions to solve conflicts and paradoxes. The results equally enrich the paradox literature by providing for tactical-level approaches toward working through the paradox.     

Planning a sustainable reverse logistics system: Balancing costs with environmental and social concerns

The present work aims to support tactical and operational planning decisions of reverse logistics systems while considering economic, environmental and social objectives. In the literature, when addressing such systems economic aspects have been often used, while environmental concerns have emerged only recently. The social component is the one less studied and rarely the combination of the three concerns has been analyzed. This work considers the three objectives and was motivated by the challenge of supporting decision makers when managing a real case study of a recyclable waste collection system, where strategic decisions on the number and location of depots, vehicles and containers were taken beforehand. Tactical and operational decisions are studied involving the establishment of service areas for each depot and the definition and scheduling of collection routes for each vehicle. Such decisions should represent a compromise solution between the three objectives translating a sustainable reverse logistics plan. The problem is modeled as a multi-objective, multi-depot periodic vehicle routing problem with inter-depot routes. A mathematical formulation and a solution approach are proposed. An approximation to the Pareto front is obtained for the case study and the trade-offs between the objectives are discussed. A balanced solution is proposed.     

一种策略层项目计划的双目标优化方法

针对产品开发项目管理的实际情况,对策略层计划优化方法进行研究。以工作包的工作量估算为基础,以资源投入水平和工期最小化为目标,考虑各种约束条件,提出一种策略层项目计划问题的混合整数规划问题模型。以非支配遗传算法NSGA-II为基础框架,设计了一种改进的双目标遗传算法。该算法针对问题的特点,提出了基于资源平滑的解码算法。参考NSGA-III的关键特征,对拥挤密度计算方法进行改进。通过企业实际项目案例,验证了算法的性能和所提出的策略层项目计划方法的有效性。     

Integration of Critical Infrastructure and Societal Consequence Models: Impact on Swedish Power System Mitigation Decisions

Critical infrastructures provide society with services essential to its functioning, and extensive disruptions give rise to large societal consequences. Risk and vulnerability analyses of critical infrastructures generally focus narrowly on the infrastructure of interest and describe the consequences as nonsupplied commodities or the cost of unsupplied commodities; they rarely holistically consider the larger impact with respect to higher‐order consequences for the society. From a societal perspective, this narrow focus may lead to severe underestimation of the negative effects of infrastructure disruptions. To explore this theory, an integrated modeling approach, combining models of critical infrastructures and economic input–output models, is proposed and applied in a case study. In the case study, a representative model of the Swedish power transmission system and a regionalized economic input–output model are utilized. This enables exploration of how a narrow infrastructure or a more holistic societal consequence perspective affects vulnerability‐related mitigation decisions regarding critical infrastructures. Two decision contexts related to prioritization of different vulnerability‐reducing measures are considered—identifying critical components and adding system components to increase robustness. It is concluded that higher‐order societal consequences due to power supply disruptions can be up to twice as large as first‐order consequences, which in turn has a significant effect on the identification of which critical components are to be protected or strengthened and a smaller effect on the ranking of improvement measures in terms of adding system components to increase system redundancy.     

COST-VOLUME-PROFIT ANALYSIS IN STOCHASTIC PROGRAMMING MODELS

This paper applies mathematical programming to cost-volume-profit (CVP) analysis under contribution margin uncertainty. Three CVP probabilistic chance-constraint models based on various safety-first criteria for decisions under uncertainty are presented and compared. It is shown that a break-even segment of the mean-standard deviation frontier is a set of optimal solutions for the proposed models. An operational parametric quadratic programming (QP) model is constructed, and the efficiency frontier is generated. The procedures for locating an optimal solution on the efficiency frontier are then presented. The recommended QP procedure offers both technical relief from the computational difficulties posed by the probabilistic constraints and a desired flexibility in generating and presenting the relevant information for decisions under uncertainty.     

On the product selection and plant dimensioning problem under uncertainty

We present a two-stage full recourse model for strategic production planning under uncertainty, whose aim consists of determining product selection and plant dimensioning. The main uncertain parameters are the product price, demand and production cost. The benefit is given by the product net profit over the time horizon minus the investment depreciation and operation costs. The Value-at-Risk and the reaching probability are considered as risk measures in the objective function to be optimized as alternatives to the maximization of the expected benefit over the scenarios. The uncertainty is represented by a set of scenarios. The problem is formulated as a mixed 0–1 Deterministic Equivalent Model. The strategic decisions to be made in the first stage are represented by 0–1 variables. The tactical decisions to be made in the second stage are represented by continuous variables. An approach for problem solving based on a splitting variable mathematical representation via scenario is considered. The problem uses the Twin Node Family concept within the algorithmic framework known as Branch-and-Fix Coordination for satisfying the nonanticipativity constraints. Some computational experience is reported.     

Closed‐Loop Supply Chains: A Critical Review,and Future Research*

In this article, I present a review and tutorial of the literature on closed‐loop supply chains, which are supply chains where, in addition to typical forward flows, there are reverse flows of used products (postconsumer use) back to manufacturers. Examples include supply chains with consumer returns, leasing options, and end‐of‐use returns with remanufacturing. I classify the literature in terms of strategic, tactical, and operational issues, but I focus on strategic issues (such as when should an original equipment manufacturer (OEM) remanufacture, response to take‐back legislation, and network design, among others) and tactical issues (used product acquisition and disposition decisions). The article is written in the form of a tutorial, where for each topic I present a base model with underlying assumptions and results, comment on extensions, and conclude with my view on needed research areas.     

Adaptive Tactical Pricing in Multi‐Agent Supply Chain Markets Using Economic Regimes

In today's complex and dynamic supply chain markets, information systems are essential for effective supply chain management. Complex decision making processes on strategic, tactical, and operational levels require substantial timely support in order to contribute to organizations' agility. Consequently, there is a need for sophisticated dynamic product pricing mechanisms that can adapt quickly to changing market conditions and competitors' strategies. We propose a two‐layered machine learning approach to compute tactical pricing decisions in real time. The first layer estimates prevailing economic conditions—economic regimes—identifying and predicting current and future market conditions. In the second layer, we train a neural network for each regime to estimate price distributions in real time using available information. The neural networks compute offer acceptance probabilities from a tactical perspective to meet desired sales quotas. We validate our approach in the trading agent competition for supply chain management. When competing against the world's leading agents, the performance of our system significantly improves compared to using only economic regimes to predict prices. Profits increase significantly even though the prices and sales volume do not change significantly. Instead, tactical pricing results in a more efficient sales strategy by reducing both finished goods and components inventory costs.     

Measuring the quality of economic forecasts

Most evaluations of forecasts have hitherto been primarily based on measure of statistical accuracy. Attention is drawn to the need for concentrating instead on the forecast components bearing on managerial decisions and on the economic effects of such decisions. The method suggested highlights the changing locus of the most influential errors over various time horizons. It also takes account of the economic consequences of under-estimates and over-estimates in forecasting, as well as of the penalties of belated correcting actions. Finally, some broader implications of this approach are discussed.     

Multi-time scale Markov decision process approach to strategic network growth of reverse supply chains

This paper addresses a complex set of decisions that surround the growth over time of reverse supply chain networks that collect used products for reuse, refurbishment, and/or recycling by processors. The collection network growth problem is decomposed into strategic, tactical and operational problems. This paper focuses on the strategic problem which is to determine how to allocate capital budget resource effectively to grow the network to meet long term collection targets and collection cost constraints. We model the strategic problem as a Markov decision process which can also be posed as multi-time scale Markov decision problem. The recruitment problem in a tactical level appears as a sub-problem for the strategic model. Using dynamic programming, linear programming and Q-Learning approaches, an heuristic is implemented to solve realistically sized problems. A numerical study demonstrates that the heuristic can obtain a good solution for the large-scale problem in reasonable time which is not possible when trying to obtain the optimal solution with the exact DP approach.     

Navigating institutional change: An historical perspective of firm responses to pro-market reversals

We explore the strategic responses of multinational enterprises (MNEs) in the context of protracted institutional change. Analyzing the long-run trajectory of three British MNEs during the setting of Indian independence, we find that these firms engaged in a series of tactical and strategic responses to address uncertain institutional changes in the form of pro-market reversals. Our findings reveal how MNE responses are characterized by path dependence and path creation in that they are historically conditioned by patterns of previous decisions and actions. We demonstrate how tactical responses to earlier institutional changes coalesce to shape dominant strategic responses in later periods. Our paper contributes to a more holistic conceptualization of how MNEs strategize in response to pro-market reversals by integrating a business history lens.     

Unweaving leaving: the use of models in the management of employee turnover

This paper offers a review of the literature on labour turnover in organizations. Initially, the importance of the subject area is established, as analyses of turnover are outlined and critiqued. This leads to a discussion of the various ways in which turnover and its consequences are measured. The potentially critical impact of turnover behaviour on organizational effectiveness is presented as justification for the need to model turnover, as a precursor to prediction and prevention. Key models from the literature of labour turnover are presented and critiqued.     

Shopfloor control practices in three Pacific basin countries: a comparative view of small machine tool industry

The strategic importance of manufacturing decisions to the competitive position of a firm is well known. As the sphere of competition has expanded from regional to national to international, successful manufacturing decisions have become ever more complex. The success of manufacturing strategics ultimately rests on proper tactical implementation at the shopfloor level. In order to explore various operating policies and procedures at a basic level, and to contrast them with some commonly held beliefs, this paper examines and compares the shopfloor practices of companies in the small machines too! industry in selected countries in the Pacific rim, namely; Japan,

China and South Korea. While many popular views on manufacturing practices in these countries are supported by the study, the results challenge other commonly held views.     

Game Theory and Risk Analysis

Risk analysts often analyze adversarial risks from terrorists or other intelligent attackers without mentioning game theory. Why? One reason is that many adversarial situations—those that can be represented as attacker‐defender games, in which the defender first chooses an allocation of defensive resources to protect potential targets, and the attacker, knowing what the defender has done, then decides which targets to attack—can be modeled and analyzed successfully without using most of the concepts and terminology of game theory. However, risk analysis and game theory are also deeply complementary. Game‐theoretic analyses of conflicts require modeling the probable consequences of each choice of strategies by the players and assessing the expected utilities of these probable consequences. Decision and risk analysis methods are well suited to accomplish these tasks. Conversely, game‐theoretic formulations of attack‐defense conflicts (and other adversarial risks) can greatly improve upon some current risk analyses that attempt to model attacker decisions as random variables or uncertain attributes of targets (“threats”) and that seek to elicit their values from the defender's own experts. Game theory models that clarify the nature of the interacting decisions made by attackers and defenders and that distinguish clearly between strategic choices (decision nodes in a game tree) and random variables (chance nodes, not controlled by either attacker or defender) can produce more sensible and effective risk management recommendations for allocating defensive resources than current risk scoring models. Thus, risk analysis and game theory are (or should be) mutually reinforcing.     

Tactical and operational planning of express intra-city package services

In this paper, we focus on routing and load planning associated with the tactical and operational planning of an express intra-city courier service provider that receives a large number of shipments on a daily basis and is committed to delivering them to their destinations given a short service guarantee. Tactical planning relies on high-level aggregated demand rates over long time periods and takes the form of a multi-commodity service network design where the goal is to identify one path per commodity while maximizing consolidation opportunities in the network. Commodities are transported on their paths by means of a series of continuously operating vehicle cycles, where the structure and number of such cycles are determined concurrently with commodity path assignment decisions in a mixed integer programming. A second model is designed to refine the time allocation along different segments of a commodity path allowing a potential reduction in the number of vehicles required to meet the service guarantee. In operational planning, the focus is narrowed down to a shorter time period, and the baseline plan obtained from the tactical planning phase is adjusted to better fit potential deviations in observed demand patterns compared to the aggregate patterns. Through an extensive computational study designed on the topology of a major US city, we observe that the plans designed at the tactical level guarantee high service levels, which are improved at the operational level by customizing the plan to the special characteristic of a day of operation.     

Disputes and the Tactics of Industrial Action in UK Manufacturing in the 1980s

ABSTRACT: This paper provides an analysis of the tactics of industrial action using data from pay settlements in UK manufacturing in the 1980s. The relative importance and determinants of different forms of action are examined. A deductive model of factors influencing the tactical decisions post impasse is developed and tested, incorporating three elements: the feasibility of different forms of action; the organizational capacity to take action; and the willingness to use particular sanctions. The paper includes a critique of the applicability of North American strike theories to the UK industrial relations context.     

Performance Metric Portfolios: A Framework and Empirical Analysis

The widespread adoption of supply chain management principles suggests that managers recognize the importance of evaluating operational decisions holistically. However, it is often difficult to link specific operational practices to strategic level outcomes and in turn to corporate financial results. This presents problems for both managers and academic researchers attempting to justify the often high cost of operational improvement initiatives in terms of objective accounting metrics. This study provides evidence that it is possible to demonstrate linkages between carefully chosen portfolios of tactical, strategic, and financial metrics. Survey data from 118 manufacturers are used to evaluate hypotheses linking multilevel metrics of performance across three well‐established strategic foci. We present portfolios of metrics drawn from the literature and from the Supply Chain Counciľs supply‐chain operations reference model and related design and customer chain models. Our analysis suggests that metric portfolios in which tactical metrics are designed to match strategic‐level metrics, based on alignment with a specific strategic focus, provide clearer mechanisms for understanding performance linkages.