A unifying framework for duality and modeling in robust linear programs

In this paper, our major theme is a unifying framework for duality in robust linear programming. We show that there are two pair of dual programs allied with a robust linear program; one in which the primal is constructed to be “ultra-conservative” and one in which the primal is constructed to be “ultra-optimistic.” Furthermore, as one would expect, if the uncertainly in the primal is row-based, the corresponding uncertainty in the dual is column-based, and vice-versa. Several examples are provided that illustrate the properties of these primal and dual models.     

Socio-cognitive processes in strategy formation – A conceptual framework

This paper should set the frame for the management focus by introducing the cognitive perspective in management research. The cognitive view has become a considerable perspective in describing and explaining strategic processes and significant advances have been provided especially in the last decade. However, the primary concern of cognitive-oriented strategy process research is still on strategic decision-making and therefore lags behind encompassing conceptional developments in process research. By drawing on the “genesis” approach of Kirsch, this paper develops a framework for explaining the formation of shared strategic orientations from a socio-cognitive perspective, which should broaden the “dominant research design”.     

Challenges and solutions for marketing in a digital era

Internet usage continues to explode across the world with digital becoming an increasingly important source of competitive advantage in both B2C and B2B marketing. A great deal of attention has been focused on the tremendous opportunities digital marketing presents, with little attention on the real challenges companies are facing going digital. In this study, we present these challenges based on results of a survey among a convenience sample of 777 marketing executives around the globe. The results reveal that filling “talent gaps”, adjusting the “organizational design”, and implementing “actionable metrics” are the biggest improvement opportunities for companies across sectors.     

Integrating multicriteria decision analysis and scenario planning—Review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of “metacriteria” (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country.     

A real option theoretic fuzzy evaluation model for enterprise resource planning investment

The high failure rate of ERP implementation is due to a common pitfall that ERP projects are often enacted as merely investment into installation of IT infrastructure, rather than systematic planning of operation changes, business process re-engineering and a paradigm shift for the operation and management. To manage ERP investment in a changing environment for high payoff, this paper adopts a real option theoretic method. Fuzzy payoff valuation is introduced to deal with uncertainties in order to minimize the risk of failure. The proposed ERP evaluation model is geared towards small and medium enterprises. A case study is presented to validate the proposed fuzzy real options. The results indicate the potential of modeling ERP investment as “Expand”, “Contain” and “Abandon” options in different scenarios. The fuzzy real option model bestows a novel ex-ante cost analysis for justifying ERP investment in the implementation cycle.     

Using partially observed Markov processes to select optimal termination time of TV shows

This paper presents a method for optimal control of a running television show. The problem is formulated as a partially observed Markov decision process (POMDP). A show can be in a “good” state, i.e., it should be continued, or it can be in a “bad” state and therefore it should be changed. The ratings of a show are modeled as a stochastic process that depends on the show's state. An optimal rule for a continue/change decision, which maximizes the expected present value of profits from selling advertising time, is expressed in terms of the prior probability of the show being in the good state. The optimal rule depends on the size of the investment in changing a show, the difference in revenues between a “good” and a “bad” show and the number of time periods remaining until the end of the planning horizon. The application of the method is illustrated with simulated ratings as well as real data.     

The design of socially optimal decisions in a consensus scenario

Several situations of conflict between basic social principles can crop up during a consensus searching process. The majority principle and respect for minority groups is a possible example of a conflictive situation between two social principles. In this paper, we outline a specific consensus searching scenario, where individual preferences are expressed by “pairwise” comparison matrices. The set of compromise consensuses between the majority and minority principles is determined using a procedure based upon an adaptation of Yu's p-metric distances. Finally, we use three different theoretical approaches – utility theory, p-metric distance functions and bargaining theory – to obtain the social optimum from the set of compromise consensuses. The links and differences among the three approaches are analysed. Finally, the working of the proposed theoretical framework is illustrated with the help of a forestry case study.     

Reducing differences between profiles of weights: A “peer-restricted” cross-efficiency evaluation

This paper deals with the selection of the profiles of weights to be used in cross-efficiency evaluations. In an attempt to prevent unrealistic weighting schemes, one of the issues of main interest that we address here is that of the zero weights, since their use implies that some of the variables considered are excluded from the assessments to be made. In the calculation of cross-efficiency scores, we propose to ignore the profiles of weights of the DMUs that cannot make a choice of non-zero weights among their alternate optima. The different units are therefore assessed in a peer-evaluation that does not consider the profiles of weights of some inefficient DMUs. This approach is referred to as “peer-restricted” cross-efficiency evaluation. Aside from avoiding zero weights, the choice of weights that we make also seeks to reduce the differences between the weights profiles selected as much as possible. Thus, in the “peer-restricted” cross-efficiency evaluation in the present paper we also try to avoid that the different DMUs attach very different weights to the same variable. Finally, we extend this approach to derive a common set of weights by exploiting the idea of similarity between profiles of weights.     

Knowledge dissemination in operations management: Published perceptions versus academic reality

The channels for knowledge generation and dissemination in the business disciplines are many: presenting research at conferences, writing books, distributing working papers, offering insights in society newsletters, giving invited talks, publishing studies in academic journals, and many other venues, including even blogs and perhaps Facebook^®. But the most important venue is probably published research in “top-level” academic journals. In the discipline of Operations Management, many studies and lists have been published that attempt to determine which of these journals are supposedly the “top” according to either citation analyses, the opinion of recognized experts, author affiliations, bibliometric studies, and other approaches. These lists may then, in turn, be used in different degrees to evaluate research. However, what really counts is what the academic institutions actually use for guidance in evaluating faculty research. Based on a new source of ranking data from AACSB-accredited schools, we compare published journal-ranking studies against that of academe to determine the degree to which the studies reflect academic “reality”. We present rankings of OM journals based on this new source of data and on an aggregate of the stream of published studies, and evaluate their consistency.     

Decision making in the newsvendor problem: A cross-national laboratory study

In this paper, we conduct a laboratory experiment using the classic newsvendor problem to examine cross-national differences in inventory ordering patterns between Chinese and American decision makers based on a theoretical examination of the role of the Doctrine of the Mean in Chinese decision making. Drawing on the theory of context-dependent preferences (specifically extremeness aversion), we also revisit the flat-maximum hypothesis of Bolton and Katok [12], i.e., “thinning the set of order options leads to newsvendor decisions that achieve a higher proportion of maximum expected profit.” The results show that the “pull-to-center” effect is more prominent for Chinese than Americans, i.e., average order quantities of Chinese subjects are closer to the anchor of mean demand than those of American subjects. Furthermore, we find that thinning the set of order options such that the optimal order quantity is a middle option, not an extreme option in the choice set, leads to better performance in newsvendor decisions, which complements the flat-maximum hypothesis.     

Towards a global economy

The author, a well known consultant on planning for technology, argues cogently for planning on a global scale. The alternative to widespread recognition and acceptance of the need for global planning is, he says: “the choice of which of the weapons existing we, as a species, shall use to commit suigenicide.”     

Understanding Knowledge Activists’ Successes and Failures

Firms are increasingly relying on “knowledge activists” to facilitate the flow of knowledge. This paper discusses which initiatives by activists are most likely to succeed. It identifies a conceptual framework that illustrates the conditions essential to full knowledge sharing and illustrates its effectiveness through a selection of case studies. It concludes by saying that the rigidity and priorities of organisations often preclude the flexibility and entrepreneurism necessary for successful knowledge initiatives.     

Improving Environmental Leadership: Asking Better Questions about Existing Inefficiencies

Physicist John Wheeler once commented that, “we shape the world by the questions we ask.” By asking better questions about how we can more efficiently produce our nation's goods and services, environmental leadership no longer means ratcheting down the economy. Rather, it becomes more an issue of how we can put our technological know-how and leadership to work. When we think about encouraging more investment in more productive technologies, we are taking the first step that will both save money and reduce environmental impacts. And it appears that more businesses are beginning to ask those tougher and better questions. The remaining question is whether we can sufficiently increase the number of businesses who are willing to ask those harder questions, and who are willing to explore new ways to turn missed opportunities into real world savings – to the benefit of the environment. Paraphrasing the great English economist, John Maynard Keynes, “the difficulty lies not with the new ideas, but in escaping the old ones.”     

DEA with streaming data

DEA can be interpreted as a tool for the identification of “frontier outliers” among data points. These are points that are potentially interesting because they exhibit extreme properties in that the values of their attributes, either alone or combined, are at the upper or lower limits of the data set to which they belong. A real challenge for this type of frontier analysis arises when data stream in at high rates and the DEA analysis needs to be performed quickly. This paper extends DEA into this dynamic data environment. The purpose is to propose a formal theoretical framework to handle streaming data and to answer the question of how fast data can be processed using this new framework. Potential applications involving large data sets include auditing, appraisals, fraud detection, and security. In such settings the situation is likely to be dynamic with the data domain constantly changing as new entities arrive in the course of time. New specialized tools to adapt DEA to deal with streaming data will be explored.     

An assessment framework based on social perspectives and Analytic Hierarchy Process: A case study on sustainability in the Japanese concrete industry

This research introduces a framework for assessing concrete sustainability which is based upon the concept that technology is defined by stakeholders’ perspectives and which applied Analytic Hierarchy Process to translate these perspectives into quantifiable assessment values. A survey was conducted to identify important criteria, and several “design scenarios” were introduced which represent different value systems by varying criteria importance. Concrete materials with varying environmental impact were then assessed to observe the effect of different value systems and material properties, and it was found that the concrete with better properties was generally selected as most sustainable regardless of the design scenario.     

Parenting in Complex Structures

In complex, interdependent corporate structures, there is overlap and sharing of responsibilities between the operating units and the corporate parent. As a result, the distinction between “business” and “parent” is blurred and a focus on the role and added-value of the parent is less obviously relevant. This article explores the nature of corporate parenting in complex structures and draws out the particular demands placed on parent managers in these structures. It also examines the role of the parent’s functional support staff and the complications that result from having more than one level of parenting. It concludes that there are some special parenting challenges in complex structures, but that the quest for “parenting advantage” should remain a fundamental driver of corporate strategy and structure.     

Cooperation in the formative years: Evidence from small enterprises in Europe

We empirically analyze factors that might affect the willingness of young small enterprises in several European countries to participate in collaborative agreements. These factors include the characteristics of the firm, of the entrepreneurs, and of the market environment the firm operates in. Within this age group – the “formative” years between 2 and 8 – firms are more likely to engage in collaboration as they grow larger, they are more innovative, they are led by educated and network-experienced entrepreneurs, and they perceive significant market risk, rapidly changing technology, and adequate IPR enforcement. They are more likely to search for collaborative opportunities when their counterparts in the same country and sector tend to do the same.     

Multi-choice goal programming

The situation of multi-choice aspiration levels (MCAL) may exist in many decision/management problems. However, the problem cannot be solved by current goal programming (GP) techniques. In order to improve the utility of GP and solve the MCAL problem, this paper proposes a new idea for programming the MCAL problem. The proposed method allows decision-makers (DMs) to set multiple aspiration levels for their problems in which “the more/higher is better” and “the less/lower is better” in the aspiration levels are addressed. In addition, illustrative examples are given to demonstrate the correctness of the proposed model.     

Stochastic simulation based genetic algorithm for chance constrained data envelopment analysis problems

Genetic algorithm (GA) approach is developed for solving the P-model of chance constrained data envelopment analysis (CCDEA) problems, which include the concept of “Satisficing”. Problems here include cases in which inputs and outputs are stochastic, as well as cases in which only the outputs are stochastic. The basic solution technique for the above has so far been deriving “deterministic equivalents”, which is difficult for all stochastic parameters as there are no compact methods available. In the proposed approach, the stochastic objective function and chance constraints are directly used within the genetic process. The feasibility of chance constraints are checked by stochastic simulation techniques. A case of Indian banking sector has been presented to illustrate the above approach.