Sensory analysis in the food industry as a tool for marketing decisions

In the food industry, sensory analysis can be useful to direct marketing decisions concerning not only products, for example product positioning with respect to competitors, but also market segmentation, customer relationship management, advertising strategies and price policies. In this paper we show how interesting information useful for marketing management can be obtained by combining the results from cub models and algorithmic data mining techniques (specifically, variable importance measurements from Random Forest). A case study on sensory evaluation of different varieties of Italian espresso is presented.     

Attributing Meanings to Representations of Data: The Case of Statistical Process Control

This article is concerned with the meanings that employees in industry attribute to representations of data and the contingencies of these meanings in context. Our primary concern is to more precisely characterize how the context of the industrial process is constitutive of the meaning of graphs of data derived from this process. We draw on data from a variety of sources, including ethnographic studies of workplaces and reflections on the design of prototype learning activities, supplemented by insights obtained from trying out these activities with a range of employees. The core of this article addresses how different groups of employees react to graphs used as part of statistical process control, focusing on the meanings they ascribe to mean, variation, target, specification, trend, and scale as depicted in the graphs. Using the notion of boundary crossing, we try to characterize a method that helps employees to communicate about graphs and come to data-informed decisions.     

Attributing Meanings to Representations of Data: The Case of Statistical Process Control

This article is concerned with the meanings that employees in industry attribute to representations of data and the contingencies of these meanings in context. Our primary concern is to more precisely characterize how the context of the industrial process is constitutive of the meaning of graphs of data derived from this process. We draw on data from a variety of sources, including ethnographic studies of workplaces and reflections on the design of prototype learning activities, supplemented by insights obtained from trying out these activities with a range of employees. The core of this article addresses how different groups of employees react to graphs used as part of statistical process control, focusing on the meanings they ascribe to mean, variation, target, specification, trend, and scale as depicted in the graphs. Using the notion of boundary crossing, we try to characterize a method that helps employees to communicate about graphs and come to data-informed decisions.     

A real options approach to labour shifts planning under different service level targets

Firms that experience uncertainty in demand as well as challenging service levels face, among other things, the problem of managing employee shift numbers. Decisions regarding shift numbers often involve significant expansions or reductions in capacity, in response to changes in demand. In this paper, we quantify the impact of treating shifts in workforce expansion as investments, while considering required service level improvements. The decision to increase shifts, whether by employing temporary workers or hiring permanent employees, is one that involves significant risks. Traditional theories typically consider reversible investments, and thus do not capture the idiosyncrasies involved in shift management, in which costs are not fully reversible. In our study, by using real options theory, we quantify managers’ ability to consider this irreversibility, aiming to enable them to make shift decisions under conditions of uncertainty with the maximum level of flexibility. Our model aims to help managers make more accurate decisions with regard to shift expansion under service level targets, and to defer commitment until future uncertainties can be at least partially resolved. Overall, our investigation contributes to studies on the time required to introduce labour shift changes, while keeping the value of service level improvements in mind.     

Modeling employees behavior in workplace dynamics

During the past years, Cellular Automata (CAs) have been extensively used for modeling of many complex systems and processes with great success. In this paper, we study a Cellular Automaton (CA) model for the influence of employees’ behavior in a parameterized workplace environment taking into account different behavioral characteristics. In specific, we model employees’ interactions based on their influence radius, the degree of their willingness on adaption of organizational norms and the employee's attitude in general in the under study workplace. The proposed CA model is taking into account employee loyalty, a combined statistic of the employee behavior and her/his insistence and company policies applied to the employees so as to restrain unwanted or impose desirable behavioral patterns in correspondence to the organization norms. Conclusively, the CA model facilitates the presentation and simulation of a workplace with a variety of employee behavioral characteristics and under adaptable company policies. Different workplaces were used to illustrate the simulation of employee behavior with CA model. As a result, the proposed model was practically used on two levels, firstly to estimate the workplace robustness and secondly to illustrate workspace dynamics. Finally, the CA model has been utilized to simulate behavioral patterns at a small enterprise in Greece. In specific, based on the employees answers to detailed surveys the CA model was initialized and then applied to describe the behavioral traits of the under study company employees. Finally, the proposed model, in all the examined cases can be utilized in conjunction with applied employee management techniques to facilitate managerial decisions and forecast the impact of employee behavioral changes and company decisions.     

A comparison of outbound dispatch policies for integrated inventory and transportation decisions

This paper investigates the impact of alternative outbound dispatch policies on integrated stock replenishment and transportation decisions. The logistics literature reports that two different types of such policies are popular in current practice. These are time-based and quantity-based dispatch policies. Considering the case of stochastic demand, the paper presents analytical and numerical results showing that the cost savings obtained through quantity-based policies can be substantial. However, under a quantity-based policy, a specific delivery time cannot be quoted when the customer places an order. Hence, the paper also investigates the cost and customer waiting time implications of hybrid policies and demonstrates that hybrid policies are superior to time-based policies in terms of the resulting costs. Furthermore, although hybrid policies are not superior to quantity-based policies in terms of the resulting costs, they are superior in terms of a service measure which is quantified by the long-run average cumulative waiting time.     

A constructive heuristic for staff scheduling in the glass industry

In this paper a constructive heuristic for solving the staff scheduling problem of a glass manufacture unit is proposed. Based on simple calculations and algorithms, the developed procedure assigns working shifts and days-off to teams of employees, ensuring the satisfaction of a mandatory sequence of working shifts and the balance of the workload between employees. The computational times for the experiments with the case study company, with three eight-hour working shifts and five teams of employees, fell consistently below 5 seconds for a set of different planning periods. Results are compared with the ones achieved with an optimization model (MIP), demonstrating the good performance of the heuristic, also in terms of the quality of the achieved solutions. The heuristic rarely fails to produce a feasible solution and whenever the solution is feasible then it is also optimal. When tackling problems with a large number of teams, the heuristic maintains the good performance while the MIP model is not able to find any solution within 16 hours of running time. Although it was designed for a particular problem of the glass industry, tests show that the heuristic is flexible enough to be applied to problems with different features, from other activity sectors, encouraging further extensions of this work.     

集成突变论和演化博弈的企业员工冲突行为研究

对企业员工冲突行为的动态分析是开展冲突管理的前提和关键。本文从突变理论和演化博弈相结合的全新视角,构建了企业员工冲突突变行为演化模型,解释了员工冲突行为在利益与情感两类至因变量的作用下变化过程。随后在此基础上结合演化博弈理论,探讨了组织与员工冲突决策的演化规律及冲突局势的发展特征,提出了冲突管理的策略及措施。研究结果表明:员工冲突行为在利益和情感影响下可能发生突变,利益因素决定是否发生突变,情感因素决定发生突变的时间点及突变程度;企业对员工群体的合理诉求采取强硬态度是一种短视行为,应本着人本管理思想让利于员工;在极端冲突事件出现后,企业即便将冲突得益全部让给员工也不可能平息争端,必须付出额外的代价;在员工出现极端行为后,企业应依照法规按原则处理,若为了消除影响而一味退让反而会使恶性冲突趋于扩大;企业倡导积极统一的文化价值观对冲突管理是十分有益的。     

Donation management for menu planning at soup kitchens

The food industry is confronted with a pressure to reduce waste and to make agreements on donating surplus food to charitable organizations. Charitable organizations such as food banks and soup kitchens can use these donations in preparing food parcels or meals for their clients. For soup kitchens, donation management is strongly influencing menu planning, and conversely, menu planning considerations have a strong impact on donation management decisions. To make the best use of (mostly highly perishable) food donations, we develop an MILP model for integrated donation management and menu planning that proposes a menu plan and suggests which (part of the) donations to accept. The combination of menu planning and donation management is essential for soup kitchens, but has not been studied before.The model is used to assess the impact of contracts on a strategic or tactical level, and captures operational decision making due to the integration of donation management and menu planning. To deal with meal variety considerations and to resemble planning practices, the developed model is solved in a rolling horizon. The results show that (i) the use of donations reduces overall costs for the soup kitchen; (ii) despite the short shelf life of donations, most donations can be used efficiently; and (iii) meal variety can be easily ensured and food donations increase this variety. In addition to the benefits for soup kitchens, the approach has implications for waste reduction in food supply chains, by structural/contractual donations of surplus food by retailers.     

Soft modelling in risk communication and management: examples in handling food risk

Our aim in this paper is to explore the use of soft modelling in an integrated risk communication and management process for managing uncertainties and ‘scares’ in the public domain, particularly in the area of food risk and safety. Much has been written in the past 20 years on the issues relating to the management and communication of food risks and safety issues to the public. Most of this research has been based upon post hoc studies of what went wrong—or, occasionally, right. Here we survey those findings briefly, and draw these into a general framework for risk management and communication. By integrating these into a coherent common framework, we believe that public authorities, food producers and industry may develop more effective strategies for managing and communicating risks which, in turn, will enable the public to make more informed decisions on their diet.     

Leximin population ethics

This paper concerns the ethical issues that arise when policy decisions have to be taken that affect population size and characteristics. Such policies include social security systems, intertemporal resource allocation decisions, and policies designed to influence fertility rates. The authors provide characterizations of Leximin principles for social evaluation in an intertemporal framework, so that they can be used to compare social alternatives with different population sizes. "The main axioms used in our characterizations are Hammond Equity together with Independence of the Utilities of the Dead (a plausible intertemporal consistency requirement) for the Critical-Level Leximin principles, and Positional Leximin Consistency (an axiom that allows non-constant critical levels) for the Positional-Extension Leximin principle. The performance of these principles is compared in the pure population problem and we argue that the Critical-Level Leximin principles are ethically more attractive than Positional-Extension Leximin."     

Optimum service capacity and demand management with price incentives

Service firms periodically face fluctuating demand levels. They incur high costs to handle peak demand and pay for under-utilized capacity during low demand periods. In this paper, we develop a mixed integer programming (MIP) model based on the real life experience of a Brazilian telecommunications firm. The model determines the optimum staffing requirements with different seniority levels for employees, as well as the distribution and balancing of workload utilizing flexibility of some customers in their service completion day. The proposed MIP uses monetary incentives to smooth the workload by redistributing some of the peak demand, thereby increasing capacity utilization. Due to the intractable nature of optimizing the proposed MIP model, we present a heuristic solution approach. The MIP model is applied to the case of the examined Brazilian Telecommunications firm. The computational work on this base case and its extensions shows that the proposed MIP model is of merit, leading to approximately seventeen percent reduction in the base case operating costs. Extensive computational work demonstrates that our heuristic provides quality solutions in very short computational times. The model can also be used to select new customers based on the workload, the revenue potential of these new customers and their flexibility in accepting alternate service completion dates. The generic structure of the proposed approach allows for its application to a wide variety of service organizations facing similar capacity and demand management challenges. Such wide applicability enhances the value of our work and its expected benefits.     

Dynamic Scheduling of a Multiclass Fluid Model with Transient Overload

We study the optimal dynamic scheduling of different requests of service in a multiclass stochastic fluid model that is motivated by recent and emerging computing paradigms for Internet services and applications. In particular, our focus is on environments with specific performance guarantees for each class under a profit model in which revenues are gained when performance guarantees are satisfied and penalties are incurred otherwise. Within the context of the corresponding fluid model, we investigate the dynamic scheduling of different classes of service under conditions where the workload of certain classes may be overloaded for a transient period of time. Specifically, we consider the case with two fluid classes and a single server whose capacity can be shared arbitrarily among the two classes. We assume that the class 1 arrival rate varies with time and the class 1 fluid can more efficiently reduce the holding cost. Under these assumptions, we characterize the optimal server allocation policy that minimizes the holding cost in the fluid model when the arrival rate function for class 1 is known. Using the insights gained from this deterministic case, we study the stochastic fluid system when the arrival rate function for class 1 is random and develop various policies that are optimal or near optimal under various conditions. In particular, we consider two different types of heavy traffic regimes and prove that our proposed policies are strongly asymptotically optimal. Numerical examples are also provided to demonstrate further that these policies yield good results in terms of minimizing the expected holding cost.     

Online scheduling policies for multiclass call centers with impatient customers

We consider a call center with two classes of impatient customers: premium and regular classes. Modeling our call center as a multiclass GI/GI/s+M$\mathit{GI}/\mathit{GI}/s+M$ queue, we focus on developing scheduling policies that satisfy a target ratio constraint on the abandonment probabilities of premium customers to regular ones. The problem is inspired by a real call center application in which we want to reach some predefined preference between customer classes for any workload condition. The motivation for this constraint comes from the difficulty of predicting in a quite satisfying way the workload. In such a case, the traditional routing problem formulation with differentiated service levels for different customer classes would be useless. For this new problem formulation, we propose two families of online scheduling policies: queue joining and call selection policies. The principle of our policies is that we adjust their routing rules by dynamically changing their parameters. We then evaluate the performance of these policies through a numerical study. The policies are characterized by simplicity and ease of implementation.     

Performance appraisal based on distance function methods

Performance appraisal is a process used by some firms to evaluate their employees’ efficiency and productivity in order to plan their promotion policy, salary policy, layoffs policy, etc. Initially this process was just carried out by the executive staff, but recently it has evolved into an evaluation process based on the opinion of different reviewers, supervisors, collaborators, customers and the employees themselves (360-degree method). In such an evaluation process the reviewers evaluate some indicators related to employees performance appraisal. In this paper we propose an evaluation framework where there are different sets of reviewers taking part in the evaluation process. Since reviewers have a different knowledge about the evaluated employee, it seems suitable to offer a flexible framework in which different reviewers can express their assessments in different finite scales according to their knowledge. The final aim is to compute a global evaluation for each employee, that can be used by the management team to make their decisions regarding their human resources policy. In this way, to obtain a global evaluation for each employee, we propose a methodology able to aggregate individual valuation in a metric L_p framework. In this context, the associated optimization problems can be reduced to an Extended Goal Programming formulation that is very easy to compute.     

Buffer sizing in multi-product multi-reactor batch processes: Impact of allocation and campaign sizing policies

This paper studies the impact of management policies, such as product allocation and campaign sizing, on the required size of the finished goods inventories in a multi-product multi-reactor batch process. Demand, setup and batch processing times for these products are assumed to be stochastic, and the inventory buffer for every product type needs to be such that target customer service levels are met. To perform this analysis, we develop a queueing model that allows us to explicitly estimate service levels as a function of the buffer size, and the allocation/campaign sizing policies. This model can be used to evaluate the service level given an existing buffer configuration, as well as to determine the buffer sizes required across products to meet a pre-specified service level. It also allows us to formulate a number of insights into how product allocation decisions and campaign planning policies affect buffer sizing decisions in symmetric production systems.     

Strategic and operational decisions in restaurant revenue management

The paper addresses restaurant revenue management from both a strategic and an operational point of view. Strategic decisions in restaurants are mainly related to defining the most profitable combination of tables that will constitute the restaurant. We propose new formulations of the so-called “Tables Mix Problem” by taking into account several features of the real setting. We compare the proposed models in a computational study showing that restaurants, with the capacity of managing tables as renewable resources and of combining different-sized tables, can improve expected revenue performances. Operational decisions are mainly concerned with the more profitable assignment of tables to customers. Indeed, the “Parties Mix Problem” consists of deciding on accepting or denying a booking request from different groups of customers, with the aim of maximizing the total expected revenue. A dynamic formulation of the “Parties Mix Problem” is presented together with a linear programming approximation, whose solutions can be used to define capacity control policies based on booking limits and bid prices. Computational results compare the proposed policies and show that they lead to higher revenues than the traditional strategies used to support decision makers.     

KIBS员工需求驱动下行为决策的模拟——基于风险偏好视角

随着经济全球化的发展,知识密集型服务业(KIBS)越来越受到学术界的关注。本文研究员工的风险偏好对KIBS员工合作与冲突行为的影响演化规律,目的在于为KIBS的管理决策提供支持。为了发现风险偏好对员工合作与冲突行为的影响,设计效用函数,并建立了风险规避和风险中性下KIBS员工合作与冲突行为决策模型,给出了KIBS员工在不同风险假定下的最优行为决策,对风险规避员工组织应当给予适度的激励,这样能够提高员工的合作程度。之后使用MATLAB2010进行模拟,并使用EXCEL对数据进行分析,发现:(1)风险偏好程度不同对员工的决策行为的影响程度不同;(2)对于员工应该给予适当的激励措施,以便提高员工的合作程度;(3)当任务的工作量达到一定程度,应当增加的是员工的固定收益而不是激励程度。     

Joint employee weekly timetabling and daily rostering: A decision-support tool for a logistics platform

To deal with their highly variable workload, logistics companies make their task force flexible using multi-skilled employees, flexible working hours or short-term contracts. Together with the legal constraints and the handling equipments’ capacities, these possibilities make personnel scheduling a complex task. This paper describes a model to support their chain of decisions from the weekly timetabling to the daily rostering (detailed task allocation).     

安全生产下政府、煤矿企业、员工的决策行为演化研究

安全生产对于煤矿企业至关重要,本研究将政府、煤矿企业和员工纳入演化博弈模型中,探究三方主体间决策的博弈关系和演化路径。研究表明:政府、煤矿企业和员工的决策向理想状态的演化过程受到诸多因素的影响,不同因素取值范围对三方主体向理想状态收敛速度产生差异化影响;当满足一定条件时,三方主体的决策行为能够演化为理想状态,政府有效监管能够促进企业由惩罚型向激励型模式转化,激励型模式能够有效激发员工安全主动行为。以期为政府制定安全监管决策、企业转化安全生产管理模式、员工激发安全主动行为提供有益的建议。