Discrete forecast horizons for two-product variants of the dynamic lot-size problem

Motivated by the recent success of integer programming based procedures for computing discrete forecast horizons, we consider two-product variants of the classical dynamic lot-size model. In the first variant, we impose a warehouse capacity constraint on the total ending inventory of the two products in any period. In the second variant, the two products have both individual and joint setup costs for production. To our knowledge, there are no known procedures for computing forecast horizons for these variants.Under the assumption that future demands are discrete, we characterize forecast horizons for these two variants as feasibility/optimality questions in 0–1 mixed integer programs. A detailed computational study establishes the effectiveness of our approach and enables us to gain valuable insights into the behavior of minimal forecast horizons.     

Egalitarian equivalence and strategyproofness in the queueing problem

We investigate the implications of egalitarian equivalence (Pazner and Schmeidler in Q J Econ 92:671–687, 1978) together with queue efficiency and strategyproofness in the context of queueing problems. We completely characterize the class of mechanisms satisfying the three requirements. Though there is no mechanism in this class satisfying budget balance, feasible mechanisms exist and we characterize the set of all such mechanisms. We also show that it is impossible to find a mechanism satisfying queue efficiency, egalitarian equivalence, and a stronger notion of strategyproofness called weak group strategyproofness. In addition, we show that generically there is no mechanism satisfying both egalitarian equivalence and no-envy.     

A dynamic measure of inaccuracy between two past lifetime distributions

In the present communication we introduce a dynamic measure of inaccuracy between two past lifetime distributions over the interval (0, t). Based on proportional reversed hazard rate model (PRHRM), a characterization problem for this dynamic inaccuracy measure has been studied. An upper bound to the dynamic measure of inaccuracy H*(f, g; t) has also been derived.     

A Structural VAR (SVAR) analysis of fiscal shocks on current accounts in India

The stimulus packages announced to deal with the economic slowdown has increased the fiscal deficit of many countries and it spurred the debate on the possible effect of these fiscal shocks on other economic variable especially the current account. In this study, we examine the effect of fiscal deficit on current account of India using the VAR as well as the Structural VAR (SVAR) analysis. Our analysis indicates that the fiscal deficit is positively affecting the current account deficit in India, as predicted by the twin deficit hypothesis. Therefore, the historical data indicates the presence of the twin deficits phenomenon in Indian context.     

Leveraging the social welfare chain to provide resilience during disaster

Due to the rampant increase in disasters globally, resilience in supply chain and logistics is receiving greater research attention in various parts of the world. This paper considers the role and contribution of social welfare supply chains in providing resilience. This is a causal phenomenon which has been studied through an exploratory research by building a framework from extant literature, a case study on an Indian non-governmental organization and tested through a social network analysis. We show how in the wake of a disaster, these social welfare supply chains become enablers. The paper provides an inkling into how to improve community resilience in times of disaster. Further, we show how these supply chains use social cohesion embedded in the structure to provide efficiency, diversity and adaptability, thereby bringing resilience into the supply system. Another contribution of this study is the use of visualisation and analysis of social media representation tools for social network analysis in operations.     

Shall One Sit “Longer” for a Free Lunch? Impact of Trading Durations on the Realized Variances and Volatility Spillovers

This study examines the effect of trading durations on the realized variance of rupee futures traded in national stock exchange (NSE), India and Dubai Gold & Commodities Exchange (DGCX), Dubai as there exists a difference in the trading durations at these exchanges, where DGCX has longer trading duration. The empirical results suggest that longer trading duration has significantly higher realized variance, and also non-trading durations at NSE account for higher overall realized variance of Rupee Futures. We model the impact of trading durations on intraday and overnight realized variance for rupee futures and estimate a reduced realized volatility of 40–70 bps due to shorter trading duration. We find that non-trading durations at National Stock Exchange account for 60–70% of the overall realized variance of rupee futures. Using MGARCH model with BEKK parameterization, we find evidence of bidirectional volatility spillover from Offshore to Onshore Rupee markets.

     

Mountain City Transit: Management Control and Performance Measurement

Mountain City Transit (MCT) is a short in‐class case based on a real‐life city transit department, a context with which students are very familiar. The case allows three delivery options for instructors. A first option is for instructors to use the case to introduce various elements of management control—the case is rich, thereby allowing students to identify multiple issues facing the organization. As a second option, instructors can use it as a performance management case wherein students build a balanced scorecard and receive a completed strategy map to analyze. As a third delivery option, the case can be used twice during the course, both to introduce management control and to discuss performance measurement. Students will also discuss real life implementation challenges that MCT and other organizations face.     

Managing information sharing and stewardship for public-sector collaboration: a management control approach

Information sharing is essential for public-sector collaboration but needs to be balanced with information stewardship obligations. There is little research on how public-sector managers can influence the attitudes and behaviours of their employees to achieve these competing objectives. To investigate this, the study applies a management control framework to a case study of a law enforcement organization attempting to improve its information sharing and stewardship. The study extends prior literature by providing insights into the specific effects that different management controls have for the information sharing and stewardship behaviours of employees involved in public-sector collaboration.     

Strategy and environment as determinants of performance: Evidence from the Japanese machine tool industry

This study examines the roles played by the environment and realized strategies on firm-level performance in the Japanese machine tool industry. We examine the effect of environment and strategy on performance using longitudinal data on a sample of 25 Japanese machine tool firms over the period 1979-92. Our results indicate that both firm strategies and the environment play significant roles in influencing profitability and growth. More specifically, whereas both strategy and environmental variables are significantly related to firm profitability, only environmental variables are associated with firm growth. Additionally, in contrast to U.S. based studies, we find that capital expenditures and technological change are not negatively associated with profitability. Rather technological change has a positive impact on firm growth. We discuss the implications of these results for strategic management and provide suggestions for future research.     

Detection of Management Fraud: A Neural Network Approach

The detection of management fraud is an important issue facing the auditing profession. A major contributor to this issue is the Loebbecke and Willingham (1988) conceptual model for the detection of management fraud. A cascaded Logit approach using the Loebbecke and Willingham model was developed in Bell et al. (1993). The present study offers an alternative approach using Artificial Neural Networks (ANNs). This paper develops a successful discriminator of management fraud using both the generalized adaptive neural network architectures (GANNA) and the Adaptive Logic Network (ALN) approaches to designing neural networks. The discriminant functions can distinguish between fraudulent and non-fraudulent companies with superior accuracy to the cascaded Logit results of Bell et al. (1993). Finally, the discriminant function provides a parsimonious set of questions useful for detecting management fraud.