A NEW LEARNING APPROACH TO PROCESS IMPROVEMENT IN A TELECOMMUNICATIONS COMPANY

Redesigning and improving business processes to better serve customer needs has become a priority in service industries as they scramble to become more competitive. We describe an approach to process improvement that is being developed collaboratively by applied researchers at US WEST, a major telecommunications company, and the University of Colorado. Motivated by the need to streamline and to add more quantitative power to traditional quality improvement processes, the new approach uses an artificial intelligence (AI) statistical tree growing method using customer survey data to identify operations areas where improvements are expected to affect customers most. This AI/statistical method also identifies realistic quantitative targets for improvement and suggests specific strategies predicted to have high impart. This research, funded in part by the Colorado Advanced Software Institute (CASI) to stimulate profitable innovations, has resulted in a practical methodology used successfully at US WEST to help set process improvement priorities and guide resource allocation decisions throughout the company.     

LEARNING TO REOPTIMIZE CONSUMPTION AT NEW INCOME LEVELS: A RATIONALE FOR PROSPECT THEORY

This paper provides a theoretical rationale for three experimental results of Prospect Theory: risk preferences are over gains and losses, loss aversion, and diminishing sensitivity. We consider a (boundedly rational) decision maker who does not find her new optimal consumption bundle with certainty when she is faced with a new income level. This alters her indirect utility function and makes her more risk averse at her current reference income level and less risk averse for a range of incomes below her reference income level. (JEL: D11)     

JEEA‐FBBVA LECTURE 2013: THE NEW EMPIRICAL ECONOMICS OF MANAGEMENT

Over the last decade the World Management Survey (WMS) has collected firm‐level management practices data across multiple sectors and countries. We developed the survey to try to explain the large and persistent total factor productivity (TFP) differences across firms and countries. This review paper discusses what has been learned empirically and theoretically from the WMS and other recent work on management practices. Our preliminary results suggest that about a quarter of cross‐country and within‐country TFP gaps can be accounted for by management practices. Management seems to matter both qualitatively and quantitatively for performance at the level of the firm and the nation. Competition, governance, human capital, and informational frictions help account for the variation in management. We make some suggestions for both policy and future research.     

Why good practice of OR is not enough—Ethical challenges for the OR practitioner

This paper develops the idea that following rules of good OR practice is necessary, but not sufficient for ethical OR. Several challenges of introducing ethical aspects into OR are discussed, evidencing difficulties and ambiguities in the relationship to be established between the OR practitioner and his/her clients, decision-makers or stakeholders. It shows that neither analysis nor modelling work nor the choice of analytical tools is entirely ethically neutral; incomparability, incommensurability and incertitude must be dealt with. The purpose of this article is to detail several difficulties or dilemmas an OR practitioner may be confronted with in the course of his or her assignment. In such situations, following rules of good practice may not be sufficient to indicate how to act in a morally good way. This paper aims at stimulating reflection by structuring the debate; it may leave the reader unsettled—unsettlement being a result and even aim of many discussions in moral philosophy.     

ON FUZZY GOAL PROGRAMMING—SOME COMMENTS

This paper pertains to goal programming with fuzzy goals and fuzzy priorities. Hannan [1], in his paper on fuzzy goal programming, alludes to the difficulty of handling fuzzy priorities and further notes that a method that this author proposed [2] may lead to incorrect results. In this note, the general problem of goal programming with fuzzy priorities is reexamined, along with the solution to the specific example presented in my original paper [2]. It is shown that the method for handling fuzzy priorities originally proposed by this author does indeed capture the relative importance of goals.     

Soft OR comes of age—but not everywhere!

Over the last forty years, new methods and methodologies have been developed to deal with wicked problems or “messes”. They are structured and rigorous but non-mathematical. Prime examples are: soft systems methodology (SSM), cognitive mapping/SODA and the strategic choice approach (SCA). Collectively they are known as Soft OR, Soft Systems, or Problem Structuring Methods (PSMs). Soft OR has now come of age in terms of both dealing with complex practical situations and having a presence in the academic literature. However, Soft OR is not recognized, or even seen as a legitimate part of an OR, everywhere and this is especially so in the US, where top journals such as Operations Research and Management Science do not publish Soft OR papers. The purpose of this paper is to generate an informed discussion and debate, which may lead to a greater recognition of the contribution of Soft OR, and to it being seen to be a proper part of the OR discipline worldwide. In order to achieve this, the first section outlines the nature of Soft OR and describes briefly some of the main methods. The second section demonstrates that Soft OR has been successful both in practice and within the academic literature. The third section documents the invisibility of Soft OR within important sections of the OR literature, and the final section then suggests some explanations for this, and also proposes practical actions to try and alleviate the problem. It is not suggested that Soft OR is an alternative to traditional, mathematical OR but, rather, a complement.     

SOVEREIGN DEBT RESTRUCTURINGS: PREEMPTIVE OR POST‐DEFAULT

Sovereign debt restructurings can be implemented preemptively—prior to a payment default. We code a comprehensive new data set and find that preemptive restructurings (i) are frequent (38% of all deals 1978–2010), (ii) have lower haircuts, (iii) are quicker to negotiate, and (iv) see lower output losses. To rationalize these stylized facts, we build a quantitative sovereign debt model that incorporates preemptive and post‐default renegotiations. The model improves the fit with the data and explains the sovereign's optimal choice: preemptive restructurings occur when default risk is high ex ante, while defaults occur after unexpected bad shocks. Empirical evidence supports these predictions.     

A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter

In this paper, we propose a simple bias–reduced log–periodogram regression estimator, ^d_r, of the long–memory parameter, d, that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k=1,…,r, for some positive integer r, as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean–squared error (MSE) of ^d_r, determine the asymptotic MSE optimal choice of the number of frequencies, m, to include in the regression, and establish the asymptotic normality of ^d_r. These results show that the bias of ^d_r goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. We show that the bias–reduced estimator ^d_r attains the optimal rate of convergence for a class of spectral densities that includes those that are smooth of order s≥1 at zero when r≥(s−2)/2 and m is chosen appropriately. For s>2, the GPH estimator does not attain this rate. The proof uses results of Giraitis, Robinson, and Samarov (1997). We specify a data–dependent plug–in method for selecting the number of frequencies m to minimize asymptotic MSE for a given value of r. Some Monte Carlo simulation results for stationary Gaussian ARFIMA (1, d, 1) and (2, d, 0) models show that the bias–reduced estimators perform well relative to the standard log–periodogram regression estimator.     

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.     

Discrete–Time Approximations of the Holmström–Milgrom Brownian–Motion Model of Intertemporal Incentive Provision

This paper studies the relation between discrete–time and continuous–time principal–agent models. We derive the continuous–time model as a limit of discrete–time models with ever shorter periods and show that optimal incentive schemes in the discrete–time models approximate the optimal incentive scheme in the continuous model, which is linear in accounts. Under the additional assumption that the principal observes only cumulative total profits at the end and the agent can destroy profits unnoticed, an incentive scheme that is linear in total profits is shown to be approximately optimal in the discrete–time model when the length of the period is small.     

DETERMINANTS OF TECHNOLOGY ADOPTION: PEER EFFECTS IN MENSTRUAL CUP TAKE‐UP

We estimate the role of peer effects in technology adoption using data from a randomized distribution of menstrual cups in Nepal. Using individual randomization, we estimate causal effects of peer exposure on adoption. We find strong evidence of peer effects: two months after distribution, one additional friend with access to the menstrual cup increases usage by 18.6 percentage points. Using the fact that we observe both trial and usage of the product over time, we examine the mechanisms that drive peer effects. We show evidence that peers impact learning how to use the technology, but find less evidence that peers impact an individual desire to use the menstrual cup.     

Factors Affecting the Job–to–joblessness Turnover and Gender

This paper explores gender differences with respect to the factors affecting the job–to–joblessness turnover. It casts light on the characteristics of those men and women who experience the highest propensity of their job ending in joblessness, taking into account the reasons for the job loss. The findings highlight the determinants of gender differences in labour turnover patterns.     

MANAGING A FLOW LINE WITH SINGLE‐KANBAN,DUAL‐KANBAN OR CONWIP

To control the production of different parts on a single flow line, managers can choose between the Single‐kanban, Dual‐kanban, and Conwip. This paper therefore compares the three different systems. The results show that Conwip consistently produces the shortest mean customer wait time and lowest total work‐in‐process. Our results also contradict the finding of a previous study, which showed that Dual‐kanban performed better than Single‐kanban. The different findings can, however, be attributed to the use of a material transfer policy, which favors the Dual‐kanban modeled in the previous study. Our study shows that transferring replenished containers immediately to downstream stations, increasing the number of cards, and reducing the withdrawal cycle reduce the mean customer wait time significantly.     

DETERMINISTIC TIME‐VARYING DEMAND LOT‐SIZING MODELS WITH LEARNING AND FORGETTING IN SETUPS AND PRODUCTION

We study the deterministic time‐varying demand lot‐sizing problem in which learning and forgetting in setups and production are considered simultaneously. It is an extension of Chiu's work. We propose a near‐optimal forward dynamic programming algorithm and suggest the use of a good heuristic method in a situation in which the computational effort is extremely intolerable. Several important observations obtained from a two‐phase experiment verify the goodness of the proposed algorithm and the chosen heuristic method.     

Operations management – from Taylor to Toyota – and Beyond?

This paper sets out to review past and current research in operations management, and to explore current and future issues facing the area. It reviews the history of the area, and the patterns of research content and type. It reviews the evolution of lean production connecting the work of Taylor to its development at Toyota, and uses this to propose three key elements of operations management in the 1990s, namely, the core, interfaces and convergence. Current issues relating to research in operations management are explored and it is argued that there is a need for aggressive research agendas. Finally, possible future agendas for the area are explored.     

TOWARD A “NEW ARCHITECTURE” FOR POM

The field of POM is steadily expanding its scope. This allows us to pursue interesting new fields of inquiry and makes us ever more relevant to the needs of practitioners. But it also increases the risk that over time our efforts will become fragmented and unfocused, causing us to slowly lose our sense of community and break up into separate camps. In this paper I ask, “What kind of new organizing framework, or ‘architecture,’ will allow us to maintain our sense of community as our interests diverge?” I describe the experience of one academic organization that faced a similar problem several years ago and how the situation was resolved. This experience leads us to propose a possible solution to Pom's emerging problem: engage with real operations managers and focus our efforts on helping them deal with the actual problems they are facing in today's complex and fast‐changing world.