Eugene D. Hahn

Conceptual Issues in Services Offshoring Research: A Multidisciplinary Review

Offshoring has emerged as an important economic and social phenomenon that has generated intense interest from practitioners, the popular media, and policy makers. In addition, there is a nascent but rich research literature on offshoring developing in management, international business (IB), and related fields. In this review, we survey and integrate offshoring literature from several disciplines and draw implications of this review for management and IB research. We conclude that offshoring may challenge some aspects of established management and IB theory or require revision and/ or modification of those theories. We adopt a multilevel coevolutionary perspective as one potential integrative approach to offshoring research and identify important future areas for further enrichment of this emerging area.

Decision Making with Uncertain Judgments: A Stochastic Formulation of the Analytic Hierarchy Process

In the analytic hierarchy process (AHP), priorities are derived via a deterministic method, the eigenvalue decomposition. However, judgments may be subject to error. A stochastic characterization of the pairwise comparison judgment task is provided and statistical models are introduced for deriving the underlying priorities. Specifically, a weighted hierarchical multinomial logit model is used to obtain the priorities. Inference is then conducted from the Bayesian viewpoint using Markov chain Monte Carlo methods. The stochastic methods are found to give results that are congruent with those of the eigenvector method in matrices of different sizes and different levels of inconsistency. Moreover, inferential statements can be made about the priorities when the stochastic approach is adopted, and these statements may be of considerable value to a decision maker. The methods described are fully compatible with judgments from the standard version of AHP and can be used to construct a stochastic formulation of it.

Mixture densities for project management activity times: A robust approach to PERT

PERT is a widely utilized framework for project management. However, as a result of underlying assumptions about the activity times, the PERT formulas prescribe a light-tailed distribution with a constant variance conditional on the range. Given the pervasiveness of heavy-tailed phenomena in business contexts as well as inherently differing levels of uncertainty about different activities, there is a need for a more flexible distribution which allows for varying amounts of dispersion and greater likelihoods of more extreme tail-area events. In particular, we argue that the tail-area decay of an activity time distribution is a key factor which has been insufficiently considered previously. We provide a distribution which permits varying amounts of dispersion and greater likelihoods of more extreme tail-area events that is straightforward to implement with expert judgments. Moreover, the distribution can be integrated into the PERT framework such that the classic PERT results represent an important special case of the method presented here.

Link function selection in stochastic multicriteria decision making models

A stochastic formulation of the Analytic Hierarchy Process (AHP) using an approach based on Bayesian categorical data models has been developed. However, in categorical data models it is known that the selection of the link function may have an impact on the model estimates. In particular, the selection of the probit link implies an assumption that model error terms are normally distributed and this normality assumption is regularly utilized in other related methods such as the multiplicative AHP. We examine model performance with respect to the choice of two model link functions. With regard to point estimates, it is found that the logit formulation is better able to replicate the estimates obtained by the eigenvector decomposition associated with the original formulation of the AHP. By contrast, the probit link produces priorities which are consistently more moderate than those of the AHP. The results suggest that the logit formulation will be preferred by decision makers who wish to replicate the AHP priorities as closely as possible. The results also suggest that the unexamined use of the normality assumption in other stochastic AHP methods may have an impact on priority estimates and thus is worthy of further attention.

Using Spatial Methods in Strategy Research

Spatial and geographic constructs have been incorporated into strategy research since its inception. Yet, strategy researchers have been slow to take advantage of methods designed specifically for these variables. This is despite the fact that spatial methods can be used to identify and remediate spatial autocorrelation—eliminating a potentially important source of bias in empirical results—and more broadly, to test hypotheses about spatial phenomena in novel ways. This article reviews the use of spatial constructs and variables in strategy research, summarizes spatial methods relevant to the strategy field, and shows how these approaches can enhance strategy research. The authors demonstrate the utility of these methods for a wide range of empirical inquiries into the role of geographic space in firm location, competition, and other phenomena, and offer three specific illustrations of their usefulness in the context of international strategy research.

Convergence and Its Implications for a Common Currency in ASEAN

The successful introduction of the euro brings renewed interest to the topic of whether similar approaches might be successfully implemented in other regions. One region that may be a promising candidate for this process is Southeast Asia, comprising the ASEAN member countries. These nations have long seen the value of co-operation in order to promote peace, stability, and economic growth. Nonetheless, important differences between the euro area and the ASEAN zone suggest that a wholesale importation of the European approach may be inopportune at the moment. The issues are examined by using economic convergence modelling perspectives. In general, the findings clearly suggest that further work remains before ASEAN will be able to fully benefit from having a single currency area.

Judgmental consistency and consensus in stochastic multicriteria decision making

Stochastic multicriteria decision making methods are a class of multicriteria decision making methods in which judgments are not taken to be certain. Recently, this class of models has generated increasing interest in the literature. We unify the notions of judgmental consistency and intra-group consensus under a framework of preference homogeneity in the context of this class of models. We propose new methods and measures for examining departures from consistency by using the Kullback-Leibler divergence. We also propose a new method, the jackknifed Kullback-Leibler divergence, that characterizes the extent to which a group member exhibits preference consensus with the remaining members of the group.

Assessing quality improvement initiatives when expert judgements are uncertain

A new approach for examining quality improvement initiatives regarding errors in the US Census Bureaus Master Address File (MAF) and the Topologically Integrated Geographic and Referencing System (TIGER) databases is presented. A stochastic multi-criteria decision-making method involving Bayesian weighted hierarchical multinomial logit models is used to conduct inference on the priorities in a multiple-expert decision scenario. Quality initiatives regarding basic street address-level address matching, geocoding completeness, and geocoding quality were judged to be the most important for MAF/TIGER improvement at the 95% probability level. The approach allows managers to go one step further in understanding the relative impact of various types of errors on overall quality and thus be better prepared to select approaches to reduce these errors.

Offshoring of Services from Developing Countries: The New Wave of Emerging Offshorers

Offshore outsourcing of services accelerated at the end of 1990s in developed countries. Recently developing countries have also increasingly offshored services, not only to developed countries but also to other developing countries. Yet, to date little attention has been paid to the emergence of this reverse offshoring. This paper examines the determinants of offshoring of services from developing countries; as such the authors investigate what location factors drive these firms from developing countries to offshore services. Using data on service offshoring projects during 2001-2007 originating from developing countries, the authors found that the determinants of offshoring of services from developing countries followed similar patterns of conventional offshoring yet for different reasons. In addition, the authors also found that services offshoring from developing countries in some sectors appeared to occur because of the desire to be closer to customers.