Decision Sciences

Decision-making is a cognitive process stemming from the analysis of available courses of action related to a given problem. Rationally, potential courses of action are derived from deliberate analysis of available data related to a problem and its potential outcomes. Decisions are generally characterized as normative, descriptive or naturalistic. Normative decisions are based on evidence, logic and analysis; descriptive decisions are based on intuition and experience. Naturalistic decisions are formed as a hybrid of normative and descriptive processes.

For decision-makers the revolution in information technology and the amount and scope of the data they provide has become overwhelming, leading to cognitive overload, confusion and an inability to function effectively. Decision Support Systems (DSS) facilitate data analysis and selection of a viable course of action rapidly and effectively. However, like the human decision- makers they serve, DSS capabilities may also suffer from cognitive overload, inaccuracy, and complexity, especially in time-sensitive environments.

This study explores DSS employment for time-sensitive decision processes using Digitally Aided Close Air Support (DACAS) as a model. The study explores decision theory, models, DSS development and time-sensitive environments. Using DACAS as a model the paper reveals the obstacles and opportunities associated with the employment of DSS for time- sensitive processes. Finally, the study makes recommendations for improved employment of DSS in time-sensitive environments.

Some of Law and Economics’ basic claims have come to be criticized as a result of empirical findings that question their viability. Particularly, the premise that agents consistently act rationally and with their self-interest in mind seems problematic. What the consequences of the criticism mean for Law and Economics’ tenability depends largely on the questions whether (1) some elements are unassailable to the alternative’s objections and (2) the alternative is a systematic whole. It is argued that Law and Economics may be salvaged, if it is minimized and its ambitions are tempered. This means focusing on the stable, a priori, elements inherent to it.

In this study, we focus on papers published in a set of four premier journals, Journal of Operations Management, Production and Operations Management, Manufacturing and Service Operations Management, and Management Science over the 15-year period of 2001-2015. Using simple and weighted counts of papers along with network measures of Total Degree centrality and Bonacich Power centrality, we provide rankings of top authors and institutions in the field of Operations Management (OM) serving as hubs of research, connectivity, and productivity from across the world. In view of benefits that can accrue from increased research collaboration between academicians and practitioners, we examine the levels of practitioner participation in the research works published across these premier journals. We survey the extent to which the top ranked authors and institutions network with practitioners in producing joint publications in these journals. By identifying the top ranked authors and institutions in OM, this study provides information that can be useful to stakeholders who may wish to engage in collaborative research with the leading agents, or pursue educational opportunities with them. The study also presents a profile of productivity levels and what it takes for authors and institutions to rank among the top tiers. In so doing, it offers insights into yearly publication rates and underlying trends-insights that can be useful in the context of promotion and tenure, faculty evaluations, and in assessing the standings of individuals and institutions relative to leadership benchmarks. [

Make-to-order firms use different approaches for managing their lead-times and pricing in the face of changing market conditions. A particular firm's approach may be largely dictated by environmental constraints. For example, it makes little sense to carefully manage lead-time if its effect on demand is muted, as it can be in situations where leadtime is difficult for the market to gauge or requires investment to estimate. Similarly, it can be impractical to change capacity and price. However, environmental constraints are likely to become less of an issue in the future with the expanding e-business infrastructure, and this trend raises questions into how to manage effectively the marketing mix of price and lead-time in a more "friction-free'' setting.

Data obtained from the intention-to-buy scale often are used for early product screening. The authors discuss current procedures to evaluate these data and indicate the minor role that risk assessment has played. Evaluation rules that incorporate the risk factor are presented, and their usefulness for product selection is discussed. Subject Areas: Mwkeffng Management and Mwkeffng Research 65 'In some cases normal approximation could not be applied because of either a very small sample size in a specific category (nj) or a very small purchase probability @). In these cases the joint distribution could be derived by multiplying the independent binomial distributions. 'Note that the sum of normally distributed variables is a normal variable.

The purpose of the current study was to determine whether brand name can affect the public's evaluation of a product. All subjects smoked identical cigarettes. One group of subjects, however, knew the cigarettes by the name of “Frontiersman,” a masculine name, while the other group knew the cigarettes as “April,” a feminine name. Male and female subjects were asked to rate the cigarette on seven measures. Results show that women gave a more positive evaluation to the cigarette purportedly named “April,” while men gave a more positive evaluation to the identical cigarette when they thought it was named “Frontiersman.” In addition, women reacted more strongly than did men to brand name influence.

Previous experimental research demonstrates that inefficient replenishment decision making in the supply chain can be caused by specific judgment and decision biases. Based on the literature we use controlled experiments involving both student subjects and supply chain managers to test debiasing interventions that provide declarative knowledge, which is theorized to enhance the acquisition of procedural knowledge. We first investigate the effects of three debiasing components in a single-echelon setting: knowledge of bullwhip, inventory position (IP), and use of a target order-up-to quantity. Experiment 1 (N = 1,608 decisions by 67 student subjects) using a 2 × 2 × 2 factorial design for the three components finds that the conceptual understanding of IP is salient for efficient replenishment decisions. We next examine the effects of the components in a simulated, multi-echelon, serial supply chain, which introduces the additional complexity of coordination risk. Experiment 2 (N = 3,072 decisions by 128 student subjects) using a 2 × 2 × 2 factorial design finds that although subjects benefit from training components, there is evidence of cognitive overload with an increased quantity of information. Finally we test whether these debiasing components may be an effective training program for practicing supply chain managers who can be expected to have higher levels of procedural knowledge through experience gained in the field. Experiment 3 (N = 864 decisions by 36 supply chain managers) using a 2 × 1 design investigates the effects of an instructional training intervention which includes all three debiasing components and finds the intervention to reduce costs by 14%. We provide avenues for future research and successful practice.

One of the more difficult but intriguing problems in the tax field is the decision of when (and how) to settle tax disputes with the Internal Revenue Service (IRS) and when (and how) to litigate. Research in this area of decision making is limited and has concentrated on the probability of winning in the judicial system. This paper examines the tax litigation decision for suits in the Small Claims Division of the US. ' Itur Court. Four examples are presented which involve varying degrees of information regarding the likelihood of a settlement and differing risk attitudes. The maximum amount the taxpayer should be willing to spend in pursuing litigation is derived for each case

... In particular, environments that elicit feelings of pleasure are likely to be ones where ... a predictable pattern of emotional scripts along the dimensions of pleasantness, arousal, and power ... Customers' evaluations of physical context play a significant role in customer's evaluation of ...

This paper examines the effect of product endorsement claims on a consumer's decision making processes. A simulated endorsement claim was made for a product after which a consumer was presented with the product. Endorsements tested were the three most common types in ...

The identification and location of materials losses in nuclear facilities is an important issue. Many complexities arise in monitoring such losses. These complexities include the dependency among materials balance observations and the influence of errors (outliers) on parameter estimates of various monitoring methods. The proposed Joint Estimation procedure is superior to standard methods (control chart and CUSUM) and to methods that build in correlation (ARMA control chart, ARMA CUSUM, and the Generalized M procedure) in the detection of nuclear materials losses. The Joint Estimation procedure is robust to the influence of outliers, is flexible in accommodating a range of dependencies among observations, and provides information on the type of loss. Further, the procedure is reliable in that it yields a probability of false alarms and a probability of detecting losses closer to specifications. Subject Areas: Energy, Quality Control, and Statistical Techniques. *We would like to thank Jack Markins for providing insight into the safeguards systems at nuclear facilities.

The standard approach to inventory policy ignores the effect of inflation. This paper investigates a model that includes both inflationary trends and time discounting. The paper compares this model with the standard EOQ model and the analysis for a one-time change, found in previous literature.

There have been many applications of the maximal covering location problem (MCLP). An underlying assumption of the MCLP is that demand not covered (i.e., not within a prespecified maximal distance of a facility) is not served. This may be an unrealistic assumption in many location planning scenarios, especially in the public sector. For example, in cases such as fire protection or ambulance service, calls not technically covered will still be serviced. The MCLP, however, does not consider the distances or travel times necessary to service such demand.This paper presents a bicriterion locational covering model which explicitly considers the travel distance or time necessary to service demand not within the maximal covering distance of a facility. The model may be used to generate noninferior (Pareto optimal) siting configurations which demonstrate the inherent trade-offs between a siting scheme designed to maximize total coverage and one designed to minimize total travel time for uncovered demand to reach its nearest facility. In addition, it is shown that for any particular weighting scheme on the two objectives, the problem can be solved as a p-median problem; a problem for which several efficient solution methods exist.

This paper presents an integrated framework for designing profit-maximizing products/ services, which can also be produced at reasonable operating difficulty levels. Operating difficulty is represented as a function of product and process attributes, and measures a firm's relative ease or difficulty in meeting customer demand patterns under specified operating conditions. Earlier optimum product design procedures have not considered operational difficulty. We show that optimum profit, market share, cost, and product profiles are dependent on operating difficulty level. Empirical results from the pizza delivery industry demonstrate the value of the proposed Effective ProductBervice Design approach.

In the literature of cooperative (co-op) advertising, the focus of the research is on a relationship in which a manufacturer is the leader and retailers are followers. This relationship implies the dominance of the manufacturer over retailers. Recent market trends have shown a shift in power from manufacturers to retailers. Retailers, as aresult, may now possess equal or even greater power than a manufacturer in some instances when it comes to retailing. Based on this new market phenomenon, we intend to explore the role of co-op advertising in a manufacturer-retailer supply chain through brand name investments, local advertising expenditures, and sharing rules of advertising expenses. Two co-op advertising models are developed and compared. The first co-op advertising model is based on the traditional leader-follower relationship of a manufacturer and a retailer. The second model incorporates partnership into co-op advertising coordination. Business examples and managerial implications of the models have been discussed. A cooperative bargaining technique is utilized to implement the partnership co-op advertising model.

Is the use of an online course delivery format, when compared with the more traditional face-to-face format, good or bad in the context of university education? Those who subscribe to the no-significant-difference perspective argue that online delivery is good, because it allows students with time and geographic distance constraints to obtain the education that they need, with no significant negative impact on the quality of the learning experience. Others argue that online delivery is bad, advocating a version of the competing significant-difference perspective, because the electronic communication media used for online delivery are not rich or natural enough to enable effective learning. This study contrasted students perceptions and grades in two different sections of the same course: one delivered entirely online and the other delivered face to face. Data were collected and analyzed at two points in time, namely, at the middle and end of a long semester. The study found support for both the no-significant-and significant-difference perspectives. At the middle of the semester, students in the online condition perceived communication ambiguity as significantly higher, and also obtained significantly lower grades, than students in the face-to-face condition. At the end of the semester, no significant differences were found.

Business Process Reengineering (BPR) has been a major catalyst of the pervasive organizational change we have witnessed over the past decade. Although one can speculate on the reasons for the popularity of this phenomenon, it is important that we carefully examine its underlying antecedents for initiation, implementation, and ultimately success, if we are to add value to practitioners of this concept. This study empirically examines the importance of facets of the organizational structure, IT knowledge resources and infrastructure, and the IS function in the initiation of BPR. Data from 313 corporations were gathered using a carefully validated survey, and initiators were compared with noninitiators. The results strongly suggest that client-server architectures, the strategic integration of IS, and cross departmental interaction are among the more important factors facilitating initiation and can be important inputs in a BPR decision-making process. The study attempts to build a contingent theory for BPR, and the more sustainable notion of fundamental process change.

Recently a good deal of interest and effort has been directed toward making statistics courses more effective in business schools. It is believed that a key to success in this arem involves giving a more prominent role to statistical took which are useful in actual business practice. If the research literature is any indication, discriminant analysis (DA) has many potential applications in virtually all areas of business. Yet, DA is rarely taught in undergraduate business and/or M.B.A. statistics courses. This is partially due to the fact that most presentations of DA are relegated to multivariate statistics texts that assume an advanced knowledge of linear algebra. This paper attempts to rectify this situation by proposing a simplified pedagogical approach for introducing linear DA in undergraduate and/or M.B.A. business statistics cou~ses.

This article is motivated by the gap between the growing demand and available supply of high-quality, cost-effective, and timely health care, a problem faced not only by developing and underdeveloped countries but also by developed countries. The significance of this problem is heightened when the economy is in recession. In an attempt to address the problem, in this article, first, we conceptualize care as a bundle of goods, services, and experiences-including diet and exercise, drugs, devices, invasive procedures, new biologics, travel and lodging, and payment and reimbursement. We then adopt a macro, end-to-end, supply chain-centric view of the health care sector to link the development of care with the delivery of care. This macro, supply chain-centric view sheds light on the interdependencies between key industries from the upstream to the downstream of the health care supply chain. We propose a framework, the 3A-framework, that is founded on three constructs-affordability, access, and awareness-to inform the design of supply chain for the health care sector. We present an illustrative example of the framework toward designing the supply chain for implantable device-based care for cardiovascular diseases in developing countries. Specifically, the framework provides a lens for identifying an integrated system of continuous improvement and innovation initiatives relevant to bridging the gap between the demand and supply for high-quality, cost-effective, and timely care. Finally, we delineate directions of future research that are anchored in and follow from the developments documented in the article.

This paper reviews the current Corona virus situation, then examines the legal definitions of negligence and fiduciary duty in an attempt to determine whether closing a university because of health concerns over the Corona virus might result in legal liability for the university's board members and relevant university administrators.

Decision Support Systems (DSSs) originally were proposed as interactive problem-solving vehicles through which models and analytical techniques could be made available to decision makers. Model management represents a line of research within the Dss field that focuses on the design and implementation of software environments to support the use of DSSs for this purpose. This paper describes the tasks that must be supported within these environments and illustrates how existing prototype Model Management Systems (MMSs) implementations provide this support. The use of artificial intelligence techniques in such implementations are reveiwed, and three scenarios are presented to show how future MMSs could be constructed using these techniques.

Decision makers often face scheduling problems in which processing times are not known with Certainty. Non-regular performance measures, in which both earliness and tardiness are penalii, are also becoming more common in both manufacturing and service operations. We model a managerial environment with task processing times (which include sequenceindependent set-up times) prescribed by three-parameter lognormal distributions. Upon completion, each task &rives a reward given by a particular piecewise-linear reward function. The objective is to select a sequence of tasks maximizing the expected total reward.

This article examines how customer value may be affected by deploying radio frequency identification (RFID) technologies within service environments. Business articles promote operational cost savings and improved inventory management as key benefits of deploying RFID. In response, service firms are using RFID to reengineer service transactions and customer touchpoints. Customers may view these RFID applications to offer both benefits and drawbacks. This article demonstrates that individuals will recognize far more value from RFID service applications than just cost savings and inventory availability. The article analyzes qualitative survey responses on the value gained from RFID to identify a broad list of value objectives-benefits and drawbacks-associated with RFID service applications. The article contributes to academic literature by providing salient value dimensions for return on investment models of service RFID applications and for future empirical analyses of means-ends and value-profit chain models. Managers can use the list of dimensions to develop rich business cases for evaluating the benefits and costs from enhancing service operations with RFID. The identified drawbacks also provide managers with a resource for understanding potential risks of RFID applications.

... The problem of controlling this flow so that summary information is reliable is central to any system of accounting ... The responsibility for developing an effective AIC system rests with the firm ... This responsibility might be fixed with executives from the controllership, internal auditing. ...

The purpose of this article is to emphasize the importance of corporate governance, information systems and their theoretical and practical knowledge in the upcoming years. It does not only offer an analysis of the use of information and knowledge in universities, but also explains its main significance. Another objective is to join some specific fields such as artificial intelligence, information systems, marketing, marketing research and knowledge management so that sharing, distribution and creation can be transmitted to the undergraduate student of business administration as well. In order to write this paper, the available bibliography was reviewed and a quantitative exploratory research was conducted in some universities in São Paulo, Brazil. The study showed that students of the undergraduate courses in Business Administration had low level of knowledge in Information System and Marketing Research while they are in the school and this fact permit analytical vision of risks in the treatment of governance.

This comment is part of a comprehensive study to develop a contingency model of simulation success. The current study focuses on the psychometric stability of the end-user computing satisfaction (EUCS) instrument by Doll and Torkzadeh (1988) when applied to users of computer simulation. Using a survey of 411 users, the researchers provide evidence that the EUCS instrument is a valid and reliable measure of computer simulation success. Given this evidence, managers and simulation software product developers can confidently apply the instrument in the investigation of competing tools, features, and technologies.

Trust is a vital relationship concept that needs further conceptual analysis, not just empirical testing. Trust has been defined in so many ways by so many different researchers across disciplines that a typology of the various types of trust is sorely needed. This paper ...

Effects of perceived merchandise and service quality, relative to competition, on retail store performance are investigated using store traffic and revenue growth as outcome variables. A model is proposed and tested using aggregate customer data and store performance outcomes from a group of stores owned by a national retail organization. Results suggest that both service and merchandise quality exert significant influence on store performance, measured by sales growth and customer growth, and their impact is mediated by customer satisfaction. Implications of the results and future research directions are discussed.

A neural network model that processes input data consisting of financial ratios is developed to predict the financial health of thrift institutions. The network's ability to discriminate between healthy and failed institutions is compared to a traditional statistical model. The differences and similiarities in the two modelling approaches are discussed. The neural network, which uses the same financial data, requires fewer assumptions, achieves a higher degree of prediction accuracy, and is more robust. Subject Areas: Banking and Finance, Computer Applications, and Statistical Decision Theory. Decision Sciences [Vol. 23

Thirty empirically assessed utility functions on changes in wealth or return on investment were examined for general features and susceptability to fits by linear, power, and exponential functions. Separate fits were made to below-target data and above-target data. The usual “target” was the no-change point.The majority of below-target functions were risk seeking; the majority of above-target functions were risk averse; and the most common composite shape was convex-concave, or risk seeking in losses and risk averse in gains. The least common composite was concave-concave. Below-target utility was generally steeper than above-target utility with a median below-to-above slope ratio of about 4.8. The power and exponential fits were substantially better than the linear fits. Power functions gave the best fits in the majority of convex below-target and concave above-target cases, and exponential functions gave the best fits in the majority of concave below-target and convex above-target cases. Several implications of these results for decision making under risk are mentioned.

This paper reports the results of simulation experiments that compared the inventory efficiency (i.e., the customer service level provided by a given level of inventory) for two different inventory policies. One of these policies uses time-phased information on future demands like that found in material requirements planning (MRP) systems, while the other (the reorder point or ROP policy) relies on forecasts implicitly based on average past demands. After establishing that the MRP policies dominate for reasonable conditions, the uncertainty of the forecasts was manipulated until the policy preference was reversed. It requires a very perverse relationship between the forecast and actual demand before ROP beats MRP on inventory efficiency. Subject Areus: 111 vetrtory Managertietit, Material Reqrrirettreirts Platinitig, atid Sittrulatioti.

Order picking, the assembly of a customer's order from items in storage, is an essential link in the supply chain and is the major cost component of warehousing. The critical issue is to simultaneously reduce the cost and increase the speed of the order picking activity. This study departs from the limited prior research that focused on either routing of workers or storage of warehoused items. The main objectives are to (1) evaluate various routing heuristics versus an optimal routine in a volume-based storage environment, (2) propose several methods of implementing volume-based storage, and (3) examine the interaction of the routing and storage policies under different operating conditions of pick list size and demand skewness. The experimental results show statistically significant differences in the mean route distance for the routing policies, storage policies, and their interactions. Further testing indicates that the choice of certain routing and storage policies in combination can result in increased picking efficiency.

This paper presents a normative, multidisciplinary approach for evaluating market entry strategies with concern for the effects of spatial assumptions on performance expectations. An assessment framework is linked to a series of models that show the value of adding spatial and competitive perspectives to typical baseline conceptualizations of market opportunity. Criteria for assessing market attractiveness are discussed with special concern for the problems of field service firms whose market boundaries are not limited by fixed facility locations. The problem is conceptualized as the managerial decision to locate a new brokerage office in a highly competitive regional market area. Realistic constraints are established by focusing the market entry decision through aggregate data from secondary sources that are readily available to an outsider who had not been active in the geographic markets considered. A simple model based on market potential is progressively enhanced with spatially adjusted measures of market attractiveness and competitive resistance. Empirical tests highlight the impact of alternative model formulations and choice criteria on the decision-making process.

Much of the research on quality practices and performance reflects a resource-based perspective of the firm, dealing primarily with internal issues of managerial and technological competence in developing and executing an effective TQM strategy. The neoclassical perspective on the influence of the competitive environment on quality practices and performance remains conspicuously absent in the empirical quality literature. Our study aims to address this gap by examining the contingent role of international competition on quality management and performance.

This paper examines the effect of product endorsement claims on a consumer's decision making processes. A simulated endorsement claim was made for a product after which a consumer was presented with the product. Endorsements tested were the three most common types in use: celebrity, expert, and typical consumer, with two control groups for experimental design. Three scales of measurement were used to assess the effect of the endorsement: a consumer's intent to purchase, his overall attitude towards the product, and his expected price of the product. The results show the strength of celebrity and typical consumer endorsers. They also show that the endorser effect is dramatically weaker than hypothesized. The Lavidge-Steiner hierarchy of advertising effects model is introduced in an attempt to explain this phenomenon. Guidelines for further research are provided.

Prior research has provided valuable insights into how and why employees make a decision about the adoption and use of information technologies (ITs) in the workplace. From an organizational point of view, however, the more important issue is how managers make informed decisions about interventions that can lead to greater acceptance and effective utilization of IT. There is limited research in the IT implementation literature that deals with the role of interventions to aid such managerial decision making. Particularly, there is a need to understand how various interventions can influence the known determinants of IT adoption and use. To address this gap in the literature, we draw from the vast body of research on the technology acceptance model (TAM), particularly the work on the determinants of perceived usefulness and perceived ease of use, and: (i) develop a comprehensive nomological network (integrated model) of the determinants of individual level (IT) adoption and use; (ii) empirically test the proposed integrated model; and (iii) present a research agenda focused on potential pre- and postimplementation interventions that can enhance employees' adoption and use of IT. Our findings and research agenda have important implications for managerial decision making on IT implementation in organizations.

The concept of marketing literature, especially innovation diffusion concept, plays a pivotal role in developing EOQ models in the field of inventory management. The integration of marketing parameters, especially the idea of diffusion of new products with the inventory models, makes the models more realistic which is most essential while building the economic ordering policies of the products. Also, because of rapid technological development, the diffusion of technology can also be viewed as an evolutionary process of replacement of an old technology by a new one. Therefore, the effect of technological substitution along with the diffusion of new products must be taken into account while formulating economic ordering policies in an inventory model. In this paper, a mathematical model has been developed for obtaining the Economic Order Quantity (EOQ) in which the demand of the product is assumed to follow an innovation diffusion process as proposed by Fourt and WoodLock (1960). The ...

When constructing linear programming models one is frequently faced with the restriction that all variables must be integer valued. Integer restrictions are generally required because of the indivisible nature of the items t o be optimized e.g., in hiring it is meaningless to hire fractional people.

Information technology (IT) a common and costly problem. While much is known about the factors that promote escalation behavior, little is known about the actual escalation process. This article uses an in-depth case study to construct a process model of escalation, consisting of three phases: drift, unsuccessful incremental adaptation, and rationalized continuation. Each phase encompasses several within-phase escalation catalysts and the model also identifies triggering conditions that promote transition from one phase to the next: project framing (antecedent condition), problem emergence, increased problem visibility, and imminent threat to project continuation (triggering the outcome deescalation). The results show that escalation is not necessarily the result of collective belief in the infallibility of a project. Rather, escalation results from continued unsuccessful coping with problems that arise during a project. Furthermore, the results suggest that the seeds of escalation are sown early: the very manner in which a project is framed contributes to whether or not the project will become prone to escalation. As problems ensue, repeated mismatches between attempted remedies and underlying problems contribute to fueling the escalation process. Implications for research and practice are discussed.

In an increasingly service-centered economy, service innovation is crucial to maintaining a firm's competitive advantage. While service innovation has attracted much attention and has resulted in the development of several service innovation typologies, these attempts remain rooted in the goods-versus-services perspective. In addition, limited attention has been devoted to theoretically anchoring these typologies in the key determinants of service innovation. Our study aims to close these gaps by developing a service innovation typology that is embedded in the service-dominant logic (SDL) and anchored by contextually relevant dimensions-environmental uncertainty, strategic orientation, and market orientation. This article presents an eight-cell service innovation typology and discusses its managerial and research implications. It is our belief that framing the typology along three contextually important dimensions and embedding in the SDL provides a richer and more appropriately specified articulation that is theoretically robust and will be useful to managers responsible for service innovation.