Forecasting models for developing control scheme to improve furnace run length

In petrochemical industries, the gaseous feedstock like ethane and propane are cracked in furnaces to produce ethylene and propylene as main products and the inputs for the other plant in the downstream. A problem of low furnace run length (FRL) increases furnace decoking and reduces productivity along with the problem of reducing life of the coil. Coil pressure ratio (CPR) and tube metal temperature (TMT) are the two most important performance measures for the FRL to decide upon the need for furnace decoking. This article, therefore, makes an attempt to develop the prediction models for CPR and TMT based on the critical process parameters, which would lead to take the necessary control measures along with a prior indication for decoking. Regression-based time series and double exponential smoothing techniques are used to build up the models. The effective operating ranges of the critical process parameters are found using a simulation-based approach. The models are expected to be the guiding principles eventually to increase the average run length of furnace.     

A two-stage unrelated randomized response model for estimating a rare sensitive attribute in probability proportional to size sampling using Poisson distribution

This paper describes the estimating procedures of mean number of entities that possess a rare sensitive attribute using the Mangat (1992) randomized device, when the population consists of some clusters and the population is again stratified with some clusters in each stratum. Unbiased estimation procedures for the mean number of individuals have been discussed and their properties are described when the parameter of a rare unrelated attribute is assumed to be known and unknown. An empirical study is carried out to show the dominance of the proposed estimator over Lee et al. (2013) estimator.     

Determining Optimal Advertising Strategies: A Markov Decision Model Approach*

This study falls in the class of models in which advertising wearout and the differences between the learning and forgetting of advertisements are explicitly included. A discrete time Markov decision modeling approach is used to obtain optimal control limit policies, and an algorithm is provided to identify these policies. A control limit policy specifies whether or not to advertise in a specific time period on the basis of the level of awareness in that time period. Thus, the duration for which advertising is not done is determined endogenously, and the algorithm helps determine this duration for a given set of parameters. This is a particularly desirable feature, since advertising practitioners are interested in determining the optimal duration of advertising pulses. Computational experience suggests that the algorithm is very fast and easy to implement. Also, conditions on model parameters indicating the relative efficacy of pulsing versus uniform advertising are provided.     

Theoretical and Interpretation Challenges to Using the Author Affiliation Index Method to Rank Journals

We formally review the Author Affiliation Index (AAI) method as originally conceived by David Harless and Robert J. Reilly from the Economics Department at the Virginia Commonwealth University School of Business and as subsequently developed and interpreted by Gorman and Kanet in their 2005 article. Through this formal review, we first highlight and discuss two important informational inputs that can impact the stability of the AAI scores for journals in any given set of to‐be‐evaluated journals. We then identify and challenge interpretations related to these scores (one theoretical, one statistical) offered by Gorman and Kanet that result in misleading conclusions about journal quality and that may potentially motivate inappropriate editorial behavior. For important professional decisions of hiring, performance evaluation, promotion, and tenure, we conclude by cautioning against sole reliance on the AAI method for ranking journals and against exclusive interpretation of the score computed via the AAI method as an indicator of journal quality.     

Optimal Enhancement and Lifetime of Software Systems: A Control Theoretic Analysis

We develop an optimal control model to maximize the net value provided by a software system over its useful life. The model determines the initial number of features in the system, the level of dynamic enhancement effort, and the lifetime of the system. The various factors affecting these optimal choices are systems characteristics (e.g., complexity, age, quality), user learning, and process maturity. We also consider that there is a time lag between the addition of a feature and the realization of its benefit to users. The basic model is extended to consider the decision of replacing the existing system by a new one.     

IMPACT OF PARTICIPATION IN THE BUDGETARY PROCESS ON MANAGERIAL ATTITUDES AND PERFORMANCE: UNIVERSALISTIC AND CONTINGENCY PERSPECTIVES*

Data from responsibility-center managers reveal that greater budgetary participation contributes to managerial performance and attitudes in high-environmental-uncertainty situations but hampers performance and attitudes in low-uncertainty situations. Higher budgetary participation reduces managers' propensity to create slack in high- (but not in low-) uncertainty conditions.     

Critical Dimensions of Strategic Information Systems Planning

Strategic information systems planning (SISP) is the process whereby an organization establishes a long-range plan of computer-based applications in order to achieve its goals. A number of problems can potentially impede information systems planners as they carry out the process. A survey of 80 firms who completed the SISP process revealed that the problems constitute five factors: the organization, implementation, database, hardware, and cost. A discriminant analysis showed that three factors—the organization, implementation, and database—best distinguished satisfied from dissatisfied information systems planners. A research application of the five factors suggested that organizations with more sophisticated business planning endure significantly less severe hardware and implementation problems.     

The Design of Feature‐Limited Demonstration Software: Choosing the Right Features to Include

Today, software supports many important tasks in a variety of industries. In the specialized nature of these environments, a common problem faced by software vendors is to correctly signal the true value of a software product to the end users. For example, telecommunications equipment manufacturers design complex software for important functions like provisioning new users in the network. These software products automate various functions that would otherwise need to be done manually. In order to enable potential customers—telecommunications providers—to evaluate and recognize the full value of the product, equipment vendors often provide a free, feature‐limited version of the product to the customer. As the specific features included in the feature‐limited version influence whether the full product is purchased or not, it is essential that the features included in the feature‐limited version be selected judiciously. While the importance of identifying the best set of features has been well recognized, there has been little research to date that systematically addresses this fundamental business decision. This study fills this gap in the literature by providing an objective approach to the design of demonstration software. We illustrate the benefits of our approach through a case study involving the design of a feature‐limited demo for a wireless telecommunications equipment manufacturer.