Mapping the changes in management science: A review of ‘soft’ OR/MS articles published in Omega (1973–2008)

The paper proposes a framework to map the development of management science (MS) and uses it to survey the MS literature published in Omega, the International Journal of Management Science. The management science discourse over the last 35 years is mapped in four paradigms: (1) optimisation/normative; (2) interpretative/learning; (3) critical; and (4) a post-modern management science approach. Using a set of keywords and authors’ names associated with the main features of each MS discourse, articles published between 1973 and 2008 are grouped. Results seem to suggest that Omega, a US-based journal, has been mainly developing publications under the optimisation paradigm; only very few papers adhering to the interpretative/learning and critical paradigms have been given space in Omega. The handful of papers from the interpretative paradigm are seen as attempts of UK-based academics to open some space for ‘soft’ operational research (OR) or ‘problem structuring methods’ in a positivistic outlook that seems to pervade US management science practice. Results of the survey and features of MS literature published in Omega are discussed. The paper aims to raise awareness amongst management scientist, systems and operational researchers of the differences between the MS/OR practice in both countries.     

Market segmentation: A multiple criteria approach combining preference analysis and segmentation decision

We propose a new multiple criteria decision aiding approach for market segmentation that integrates preference analysis and segmentation decision within a unified framework. The approach employs an additive value function as the preference model and requires consumers to provide pairwise comparisons of some products as the preference information. To analyze each consumer’s preferences, the approach applies the disaggregation paradigm and the stochastic multicriteria acceptability analysis to derive a set of value functions according to the preference information provided by each consumer. Then, each consumer’s preferences can be represented by the distribution of possible rankings of products and associated support degrees by applying the derived value functions. On the basis of preference analysis, a new metric is proposed to measure the similarity between preferences of different consumers, and a hierarchical clustering algorithm is developed to perform market segmentation. To help firms serve consumers from different segments with targeted marketing policies and appropriate products, the approach proposes to work out a representative value function and the univocal ranking of products for each consumer so that products that rank in the front of the list can be presented to her/him. Finally, an illustrative example of a market segmentation problem details the application of the proposed approach.     

The Positive Effects of Easy Goals on Decision Quality and Risk Propensity in an MCPLP Task

In this study the potential performance benefits of easy goals were examined within the multiple cue probability learning paradigm (MCPLP). Specifically, the effects of varying levels of goal difficulty on performance and risk propensity (used to define a form of commitment) were investigated. With few exceptions, previous studies demonstrated support for difficult goals. In this study, contrary to the majority of past evidence, as goals became easier decision quality significantly improved. Moreover, risk propensity increased with easier goals and, as suggested by a post-hoc analysis, had more direct impact on decision makers’ behaviors than goal levels. Goal-related behavior in complex MCPLP tasks appears to significantly differ from the majority of goal evidence in other types of research due to the tendency for subjects to view complex task properties in the same context as goal levels.     

The Role of Contracts on Quality and Returns to Quality in Offshore Software Development Outsourcing

In this study, we examine how the different incentive structures inherent in two primary contract types—time and materials (T&M) and fixed price (FP)—influence the quality provided by the vendor in the software development outsourcing industry. We argue that the incentive structure of FP contracts motivates a vendor to be more efficient in the software development process, which results in higher quality as compared to projects executed under a T&M contract. We thus argue that vendors consistently staff FP projects with better trained personnel because they face the most risk on these contracts, resulting in better outcomes on these projects. We extend our analysis to propose that providing higher quality is associated with higher profit margins for the vendor only for FP contracts. We develop and test these hypotheses on data collected from 100 software projects completed by a leading Indian offshore vendor. The results provide strong support for our fundamental thesis that the drivers of and returns to quality vary by contract type. We discuss the implications of our research for both researchers and practitioners.     

Boredom in the workplace: More than monotonous tasks

Boredom is an emotional state that has a long history in organizational research. Despite recent changes in technology and the organization of work, boredom remains a part of the experience of work. The available evidence indicates that boredom is associated mainly with negative individual and organizational outcomes. The authors organize the review of the antecedents of boredom around four major themes in the literature: boredom in relation to jobs; individual differences; social context; and goals and coping. The authors conclude that the major challenge for researchers is to provide an integrative account of boredom which subsumes multiple areas of research, and that one most promising avenue for future research requires further attention to boredom in relation to coping processes, pursuit and attainment of personal goals.     

基于Fisher聚类算法的航班飞行高度偏差分析研究

目前计算机飞行计划(Computerized Flight Plan,CFP)中的计划飞行高度与实际飞行高度之间存在偏差.为了能识别出航路中易发生显著偏差的子航段,便于对其进行重点监控,本文提出一种基于Fisher有序样本聚类算法的航班飞行高度偏差分析方法,采用修正的Fisher有序样本聚类算法对航路进行分段,在分段的基础上,对每个子航段上的高度偏差平均水平及波动情况进行统计分析,作为高度偏差的评价指标.分析结果可帮助识别航路上易发生显著实际与计划飞行高度偏差的子航段,为签派人员制作飞行计划以及在机组人员进行航前准备提供决策依据,具有较好的实践意义.     

Evaluating the Applicability of the Miles and Snow Typology in a Regulated Public Utility Environment

This paper examines and evaluates the applicability of the Miles and Snow organizational strategy, structure and process model to the electricity distribution and supply industry of England and Wales (ESI), and specifically the regional electricity companies (RECs). In the past such generic strategy models have principally been applied to industries that conform to the traditional free-market paradigm, and doubt has been cast upon their applicability in non-traditional environments. This paper argues in contrast that generic strategies are of considerable value in the regulated industries, especially those developing new strategies to address major change, such as the approach of full competition. As a feature of this process, the paper also examines some of the differences and similarities between the ESI and the traditional free-market paradigm. However, having argued for the use of such strategies, it is necessary to make various amendments to enhance the applicability of the model. These amendments and the characteristics of new generic strategies are described.     

What guides subjective performance evaluation: Incentive alignment or norm enforcement?

This paper investigates the objectives guiding a superior’s subjective evaluation of subordinate performance. In a laboratory experiment, we implement a team production setting under uncertainty, where subordinates contribute to the organization’s output by choosing effort levels, but individual contributions are subject to random shocks. After observing joint output, the superior can invest into additional (perfect or imperfect) information about effort levels. We test two competing hypotheses about objectives guiding a superior’s subjective performance evaluation. The incentive alignment hypothesis states that the superior is guided by the objective to establish financial incentives that align a subordinate’s preferences with the organization’s goals such that it is in the subordinate’s self-interest to provide effort. In contrast, the norm enforcement hypothesis states that the superior has a focus on subordinate behavior and wants to enforce the norm of cooperation by rewarding high and punishing low effort. Our results reject the incentive alignment hypothesis and provide support for the norm enforcement hypothesis.     

具有风险传导特征的信息加工业务薪酬激励研究

企业员工通过对信息进行加工处理得到支持企业决策的信息产品，然而由于业务本身的风险传导性，前序环节的错误会随着业务流程向后传递，在为企业创造价值的同时，也为企业带来风险。基于委托代理理论，建立企业与员工之间产出相关的多代理人薪酬激励模型，得到9种情形下的薪酬激励方案及员工的最优决策。研究表明，有效的薪酬激励方法可以促使员工选择使企业净收益最大的努力水平，从而达到降低企业风险的目的，并通过算例得到部分因素对员工及企业决策的影响。     

管理非合作博弈机制式表述

根据管理激励与约束机制具有多因素、多目标、多阶段特征,本文作者提出了管理博弈机制式表述方法。本文建立了单阶段和多阶段管理激励与约束非合作博弈机制式表述的基本模型及方法,这些基本模型及方法大大扩展了管理博弈问题的研究深度及研究范围,从而为人们研究复杂管理博弈问题提供了新的理论工具。     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

Questioning the reliability of market segmentation techniques

Market segmentation techniques and analyses have received considerable attention in the academic literature. This paper compares and contrasts the results from conducting cluster analysis and factor analysis on two data sets, one which is genuine and the other which has been randomly generated. This analysis helps test claims about the validity and effectiveness of such techniques and looks at the reliability of the output. The findings suggest that researchers need to be careful to carry out valid preliminary work before presenting their results. Without such preliminary work it may be difficult to justify the segments which emerge.     

Dual Objective Segmentation to Improve Targetability: An Evolutionary Algorithm Approach**

Cluster‐based segmentation usually involves two sets of variables: (i) the needs‐based variables (referred to as the bases variables), which are used in developing the original segments to identify the value, and (ii) the classification or background variables, which are used to profile or target the customers. The managers’ goal is to utilize these two sets of variables in the most efficient manner. Pragmatic managerial interests recognize the underlying need to start shifting from methodologies that obtain highly precise value‐based segments but may be of limited practical use as they provide less targetable segments. Consequently, the imperative is to shift toward newer segmentation approaches that provide greater focus on targetable segments while maintaining homogeneity. This requires dual objective segmentation, which is a combinatorially difficult problem. Hence, we propose and examine a new evolutionary methodology based on genetic algorithms to address this problem. We show, based on a large‐scale Monte Carlo simulation and a case study, that the proposed approach consistently outperforms the existing methods for a wide variety of problem instances. We are able to obtain statistically significant and managerially important improvements in targetability with little diminution in the identifiability of value‐based segments. Moreover, the proposed methodology provides a set of good solutions, unlike existing methodologies that provide a single solution. We also show how these good solutions can be used to plot an efficient Pareto frontier. Finally, we present useful insights that would help managers in implementing the proposed solution approach effectively.     

Get more for less? Experimental evidence on repeated decision making under non-monotone incentives

Summary  This paper presents experimental results of a benchmark study to analyze the incentive effects of non-monotone pay schemes. An incentive compatible contract that does not award the highest pay to the highest possible output combination was tested in a neutral, framing, and two framing-with-principal settings, respectively. The results confirm the model in a statistically significant way. Principals select the non-monotone contract over a monotone contract that would give them ex ante a lower expected surplus. Agents predominantly select the income-maximizing strategy, i.e. select the effort level that should be implemented by the contract. Given the widespread view that non-monotone output-contingent incentives are not plausible labor contracts, it seems worthwile to extend the experimental study to include aspects which are common in labor relations, such as an option to quit for the employee and repeated interaction between employer and employee. This would help answer the question whether theoretically optimal non-monotone contracts may be used as labor contracts. The author acknowledges insightful comments by Jeannette Brosig, Alexis Kunz, Thomas Riechmann, Dirk Sliwka, Joachim Weimann and two anonymous referees. Financial support by MaxLab is gratefully acknowledged. Any remaining errors are my own.     

A PENSION DECISION MODEL FOR THE EMPLOYER*

Recently, the Financial Accounting Standards Board (FASB) reevaluated accounting for pension plans. The issue is emotional and highly political in nature. The FASB attempted to justify its approach on the basis of measuring economic activity, but it failed to provide much in the way of analytical support. This paper provides a managerial decision model and an economic basis for the existence of pension plans. A pension plan is described as a cost-saving, risk-sharing, incentive contract. The analysis is developed using agency theory. The model presented here meets three suggested objectives of an employer: 1. Maximization of utility through the maximization of profit 2. Ability to conform the risk characteristics of an employment contract to the risk characteristics of the employer 3. Diversification of the risk inherent in the employment contract Profit is maximized by producing cost savings associated with employee tenure and loyalty. Sharing cost savings with employees (i.e., offering a pension plan) meets the above objectives. The employer determines the optimal sharing rate for the expected cost savings. An examination of the employer's underlying decision process reveals implications for pension plan accounting which generally are consistent with and support the FASB's Statement of Financial Accounting Standards No. 87 [5].     

The global “war for talent”

In this paper we examine the “global war for talent,” the factors that impact it, and organizations' responses to it. Using a comprehensive search of more than 400 contemporary academic and business press articles, the paper reviews relevant research and reassesses the “talent war.” We posit that the dominant approaches to the “talent war” based on a scarcity state of mind and action, often characterized by a tactical and exclusive top talent or “star” focus, are being challenged by the emergence of a more evolutionary paradigm. This new paradigm adopts more strategic, innovative, cooperative and generative approaches which we describe as creative ‘talent solutions.’ The paper also highlights implications for future research, teaching and development in the field.     

Causal Linkages in Supply Chain Management: An Exploratory Study of North American Manufacturing Firms

In this paper we investigate the key causal linkages in supply chain management. We propose a conceptual framework and test this framework on data from 215 North American manufacturing firms using structural equation modeling techniques. Three major research issues are addressed in this study: Do sourcing decisions affect the degree to which firms achieve manufacturing goals of cost, flexibility, dependability, and quality? Does the degree of manufacturing goal achievement lead to higher customer responsiveness? Does the degree of manufacturing goal achievement lead to higher internal manufacturing performance? The study examines the relationship among sourcing decisions, manufacturing goals, customer responsiveness, and manufacturing performance. The results support the notion that an integrated supply chain involves aligning sourcing decisions to achieve manufacturing goals that are set to respond favorably to the needs of customers.     

A Note on the Growth of Research in Service Operations Management

We present an empirical assessment of the productivity of individuals and institutions in terms of service operations management (SOM) research. We reviewed five mainstream operations management journals over a 17‐year time period to generate a sample of 463 articles related to service operations. The results indicate that SOM research has been growing and key contributions are being made by an array of researchers and institutions.     

Quality of Service Based Pricing Schemes for Content Sharing in Peer‐to‐Peer Networks

In this paper, we study quality‐of‐service (QoS) based pricing schemes that serve as incentive mechanisms to induce sharing behaviors in Peer‐to‐Peer (P2P) networks. We incorporate operational QoS metrics into users’ utility functions and demonstrate how they affect individual users’ content sharing decisions. Using a game‐theoretic model, our study reveals how organizations respond to the changes of operational QoS metrics in their design of pricing schemes for various business objectives at different stages of network evolution. Our results show that a higher upload capacity can foster rational sharing to start when the network is small; however, it also discourages sharing behaviors when the network becomes large. In order to induce a socially optimal behavior, a pricing scheme will not charge users for requesting content while compensating them for sharing content. Such compensation is found to increase faster with the network size when the network is large. In order to maximize the profit of a monopolistic provider, however, a pricing scheme will charge content requests with a positive price while providing less compensation to sharing users compared to the socially optimal scheme. When the network size is small, such compensation can be even negative, which implies that a monopolistic provider discourages content sharing when the network is small, but encourages it when the network becomes larger. In addition, we find that more information about peer upload capacity discourages peers to share.