Samir Barman

Perceived relevance and quality of POM journals: a decade later

This research is a 10-year update on the rankings of perceived relevance and quality of selected Production and Operations Management (POM) journals that was reported by Barman et al. (1991) [Journal of Operations Management 10 (2), 194‐212)]. The results show some changes in the perceptions of journals over the past decade. Some journals are perceived to be extremely relevant to POM research, but not particularly of “high” quality. For other journals, the reverse is true — “high” quality is perceived but the published studies are not considered particularly relevant to POM. The Journal of Operations Management remained atop the relevance rankings and retained its position among the top three journals for quality. The study identifies factors that the respondents say influence their perception of journal quality. Finally, the paper finds some evidence that association with the editorial board of a journal affects one’s perceptions of the quality and relevance of that journal.

An empirical assessment of the perceived relevance and quality of POM-related journals by academicians

Abstract As in other fields, promotion and tenure decisions of academicians in POM are very closely related to their publication achievements. Such achievements are generally measured by where academicians publish rather than just what they publish. Therefore, the perceived quality or image of POM journals is important to the faculty and researchers in this field. Not surprisingly, several previous studies have attempted to rank order journals belonging to related fields such as accounting, finance, economics and management. Unfortunately, for POM journals, there exist little published data accepted and shared by all in this respect. The primary objectives of the study are to establish the perceived relevancy and quality ratings of 20 selected journals that are frequently used to disseminate POM-related research work. The results are based on a questionnaire survey of those Decision Sciences Institute members who listed POM as their primary area of interest (DSI code N). Regarding relevancy, the Journal of Operations Management is rated as the most relevant journal for POM research. Other journals that received high relevance ratings are: International Journal of Production Research, International Journal of Operations and Production Management, Journal of Manufacturing and Operations Management, Decision Sciences, and Production and Inventory Management Journal . Based on the quality ratings. Management Science, Journal of Operations Management , and Decision Sciences appear to be the “best” journals publishing POM-related research. IIE Transactions, International Journal of Production Research, Harvard Business Review, Operations Research, Naval Research Logistics , and Journal of Manufacturing and Operations Management form the group of next best journals. The results provide some evidence of an apparent incongruity between the notions of journal relevancy and journal quality, as perceived by the respondents. Some journals that received high quality ratings were found only moderately relevant to POM research. On the other hand, some journals received poor quality ratings but were rated highly for relevancy. The opinions of the associate and full professors, as well as those with better publication associations with the included journals, were found strikingly similar to those of the entire sample surveyed. Some discrepancy was evident as to what the respondents and their administrative evaluators think are the top journals. The faculty evaluators tend to consider Management Science and Operations Research as the top two journals in the POM field. Such an observation, along with other pertinent data, suggests that there still exists a tendency to equate POM with OR, and the field, to an extent, is suffering from an identity crisis.

The impact of priority rule combinations on lateness and tardiness

Several recent studies have explored the concurrent deployment of different priority rules at different processing stages of a manufacturing system. This study investigates the same issue by combining three popular simple priority rules with a combinatorial rule. In a three-stage flow shop, these rules are combined into 64 combination schemes and their performance compared under two shop load levels with two due date setting methods. The performance criteria considered are: mean lateness; mean tardiness; maximum tardiness; and per cent of tardy jobs. The results indicate that the rule combinations are a better strategy than their pure forms when various performance measures are jointly evaluated. Particularly, selected combinations of the Modified Shortest Processing Time, Shortest Processing Time, and the Earliest Due Date rules appear to be very effective. While the extent of shop load level shows little impact on the relative performance of the schemes, the endogenous method of due date setting consistently yields better results than the exogenous method.

Sensitivity of cost coefficient errors in aggregate production planning

The cost implications of cost parameter estimation errors for an aggregate production planning problem are investigated. Three popular aggregate planning models (the Linear Decision Rule, the Linear Programming model, and the Production Switching Heuristic) are evaluated for the effects of a range of errors over a finite planning horizon. Analysis of different cost functions indicates that the accuracy of the coefficients related to regular production capacity per employee, target ending inventory level, and regular employment cost per employee are critical regardless of the model chosen.

Performance evaluation of the LDR and the PSH with forecast errors

Abstract Despite its ability to produce optimal solutions, the Linear Decision Rule (LDR) has not had a significant impact in the business environment. The Production Switching Heuristic (PSH), which has shown promising results when compared with the LDR, has experienced some business application because of its practicability and flexibility. During aggregate production planning, forecast errors are almost unavoidable, but the sensitivity of these models to such errors has not been thoroughly tested. Insufficient attention has been paid to truly understand the cost effects of forecast errors and other important interactions. The study investigates these issues by analyzing the results of 740 simulated problems. Using the famous “paint factory” cost data, the sensitivity of the LDR and the PSH are examined under various experimental conditions. The factors controlled at different levels are: forecast error mean, forecast error standard deviation, demand pattern, demand variability, and cost coefficients. The results show that 1) the PSH is generally less sensitive than the LDR to forecast errors, 2) both forecast error mean and standard deviation effectively measure the severity of forecast errors, and 3) underforecasts cause less cost penalty than overforecasts. The outcome of the study has helpful managerial implications for aggregate planning related decisionmaking. It suggests that the use of the PSH could result in potential cost savings even if significant forecast errors are envisioned as long as the period-to-period demand variability is not substantially high. Also, BIAS warrants more attention than MSE in evaluating the extent of forecast errors and their eventual cost impact on aggregate production planning.

Value stream mapping for improving academic advising

Value stream mapping (VSM) is a popular tool to identify opportunities for improving process efficiency. Originally designed to streamline manufacturing processes, VSM can also be applied to service processes. In this research, VSM is applied to academic advising of undergraduate students in a large department of a major university. Improvements to the advising processes are suggested following a VSM analysis of the current procedures.

Cost performance of simple priority rule combinations

Purpose – Several prior studies have investigated the strategy of concurrently deploying different priority rules at different processing stages of a manufacturing system. The purpose of this paper is to investigate the advantage of using such a strategy over that of using priority rules in their pure forms.Design/methodology/approach – Three priority rules were combined in all possible ways in a simulated, three‐stage, flow‐dominated manufacturing system. The performances of these combinations, along with three other simple priority rules in their pure forms, were compared using both mean and variability in waiting, earliness, tardiness, and total costs under two shop load levels and several tardiness to earliness cost ratios.Findings – The results indicate that the combinations between SIX and shortest processing time (SPT) rules perform well in reducing both mean and variability of waiting cost but do poorly on tardiness cost. On the other hand, the due date rule in its pure form or in conjunction with...

A blueprint for mass customisation in higher education

Societal pressure for cost reduction has created an environment ripe for change in the value delivery system of higher education. When taken together, recent developments including massive open online courses (MOOCs), a strategy of flipping the classroom, and a changing focus from effective teaching to assurance of student learning, create an opportunity to address this societal pressure through mass customisation (MC). We use three elements of mass customisation (elicitation, process flexibility, and infrastructural logistics) and four approaches to MC (collaborative, adaptive, cosmetic, and transparent), to develop and discuss a blueprint for mass customisation in higher education.

Comparing two aggregate planning models

The sensitivity of the linear programming (LP) model to forecast errors in aggregate planning (AP) is evaluated and its performance compared with that of the production switching heuristic (PSH) model. Two versions of the PSH, the popular three-level model and a two-level extension, are considered. While the LP tends to outperform the PSH in situations with high forecast errors, the performances of the models are comparable for low to moderate forecast errors. The use of an additional production and workforce level in the PSH is not justified unless forecast errors are high. A variation in the forecast error distribution had no significant effect on these findings.

Controlled release location of jobs in a hybrid of job and flow shops

The study investigates whether the location at which the order review and release (ORR) strategy is applied in a hybrid of job shop and flow shop influences its performance. Five different ORR strategies were applied at two different locations of the simulated shop in conjunction with four dispatching rules used at two shop utilisation levels and two due date tightness levels. The shop performance was evaluated by several job due date and shop related measures, including both mean and variability statistics. The results confirm that the effectiveness of an ORR strategy can be enhanced by controlling the location of its application. Furthermore, the ORR strategies based on the backward infinite loading (BIL) criterion outperformed those based on the modified infinite loading (MIL) criterion. With regard to the dispatching rule performance, the due date (EDD) rule yielded the best results on most of the variability measures, while the shortest processing time (SPT) rule did better on the mean measures.