A multicriteria decision analysis model for faculty evaluation

In the context of increasing demands for social and financial accountability of universities, the required implementation of transparent faculty evaluation systems constitutes a challenge and an opportunity for universities strategically aligning the activity of academic staff with the university goals. However, despite growing interest in the performance appraisal of faculty, only a few reported studies propose models that cover the full range of academic activities and the models in use are typically based on ad hoc scoring systems that lack theoretical soundness. This article approaches faculty evaluation from an innovative comprehensive perspective. Based on the concepts and methods of multiple criteria value measurement, it proposes a new faculty evaluation model that addresses the whole range of academic activities and can be applied within and across distinct scientific areas, while respecting their specificities. Constructed through a socio-technical process, the model was designed for and adopted by the Instituto Superior Técnico, the engineering school of the Technical University of Lisbon. The model has a two-level hierarchical additive structure, with top-level evaluation areas specified by second-level evaluation criteria. A bottom non-additive third level accounts for the quantitative and qualitative dimensions of academic activity related to each evaluation criterion. The model allows (a) the comparison of the performance of academic staff with performance targets reflecting the strategic policy concerns of university management; (b) the definition of the multicriteria value profile of each faculty member at the top level of the evaluation areas; (c) the computation of an overall value score for each faculty member, through an optimisation procedure that makes use of a flexible system of weights and (d) the assignment of faculty members to rating categories.     

Power planning in ICT infrastructure: A multi-criteria operational performance evaluation approach

It is critical for information and communications technology (ICT) companies to carry our effective power planning, in order to support the growing number of services they provide, and this traditionally relies on the tacit knowledge and experience of senior staff. The loss of such domain knowledge resulting from the retirement of staff is an important issue for organizations such as Chunghwa Telecom (CHT), the largest ICT operator in Taiwan. This study thus develops a systematic power planning model using a multi-criteria operational performance evaluation. A group version of the fuzzy repertory grid and fuzzy TOPSIS approaches is applied to elicit a set of evaluation criteria that senior staff agree on, and then the priorities of the telecom rooms are evaluated against this. In addition, a new factor, reflecting the attitudes of the decision makers with respect to the degree of strictness, is defined to determine the superiority and inferiority of each alternative compared to the others. Furthermore, a novel decision aggregation strategy regarding the degree of variation among decision makers is proposed, and a quantitative assessment is carried out to analyze its impact on the ranking results in an objective manner. The proposed model may help ICT organizations to more effectively manage their power resources, and thus obtain competitive advantages.     

A Multiperiod Audit Staff Planning Model Using Multiple Objectives: Development and Evaluation*

The audit staff planning problem, a specific type of manpower planning problem, has been modeled using goal programming and, more recently, multiple objective linear programming. Prior studies developed single-period models and did not go beyond the model building stage. This study develops a multiperiod audit staff planning model and evaluates the model using a test application involving actual decision makers (partners in public accounting firms). The multiperiod model includes seven objectives to be optimized: profit (to be maximized), late completion of work, work declined, staff augmentation, staff reduction, underutilization of the work force, and shortfall in meeting professional development targets (all to be minimized). Over a four-quarter planning horizon with one “busy season,” the model is subject to constraints with respect to the projected audit work load, ability to substitute personnel and to perform interim audit work, available staff hours (including overtime limitations), supervisory requirements, and professional development targets. Results of the test application showed that the model was capable of producing a range of values for each objective. The participants were exposed to much of that range when making their decisions. The results also showed that all objectives were important and that participants were consistent in choosing their preferred level of each objective over several runs of the model. These results and the reactions of the participants demonstrate that the model is usable by actual decision makers and has potential for a number of specific applications.     

K?nnen Studienbeitr?ge die Lehre in der BWL verbessern?

The introduction of tuition fees by some German universities raised fears about possible negative effects, which scientific research has not substantiated, though. Meanwhile, little attention has been paid to positive effects tuition fees might entail. This is surprising as universities are obliged to use tuition fees to improve study conditions. Business programs are highly frequented with limited academic staff. More assistance would therefore improve study conditions substantially. Tutorials funded by fees can be introduced quickly and, unlike faculty positions, do not tie up money in the long run. This makes them ideal to cope with the one-time enrollment peak due to the shortening of secondary education. We show that tutorials improve both satisfaction and study outcomes. We use data from an introductory course characteristic of business programs, where tutorials have been introduced. This course is attended by about 750 students per term and the data cover several terms. We control for a number of effects, including general academic ability. Increased satisfaction and improved study outcomes show that tutorials enhance both the objective and perceived study conditions. This makes tutorials an example of how tuition fees can be used to produce positive effects.     

Development and analysis of mathematical and simulation models of decision-making tools for remanufacturing

This article presents decision-making tools for remanufacturing. The first decision-making tool was used to address inventory lot-sizing problems in a hybrid remanufacturing–manufacturing system with varying remanufacturing fraction. In this article, the new inventory lot-sizing model with variable remanufacturing lot sizes has been shown to exhibit better performance than the benchmark model with fixed remanufacturing lot sizes. The new inventory lot-sizing model is anticipated to become a valuable decision-making tool in companies that are planning to adopt remanufacturing. The second decision-making tool was applied to address a production and inventory planning problem in a remanufacturing system considering different remanufacturing policies for a given remanufacturing strategy. For a remanufacture-to-stock system with two quality remanufacturables groups four alternative policies were examined, a policy which specifies simultaneous processing utilising dedicated resources was shown to be the best policy to achieve a shorter remanufacturing cycle time. For a remanufacture-to-order system with two quality remanufacturables groups, the three relevant policies of the four alternative policies were examined, a policy which specifies sequential processing and switching between various quality remanufacturables groups was shown to be the best policy to achieve a shorter remanufacturing cycle time. The production and inventory planning simulation models in a remanufacturing system are expected to become significant decision-making tools in remanufacturing operations.     

An Evaluation of Staff Preference for Graphic Characteristics

The purpose of the current study was to assess staff preference for how data were displayed on graphs. Specifically, preference for line versus bar graphs was assessed, as well as preference for data displayed as one date in time versus multiple dates showing performance trends. A secondary purpose of the study was to assess staff comprehension of the data presented across different graphic displays. Participants included 60 entry-level direct care staff and 25 seasoned therapists. Therapists had more advanced training in applied behavior analysis than the direct care staff. The vast majority of direct care staff preferred data depicted as a bar graph versus data depicted as a line graph, even preferring a single bar graph over a time-series line graph. The therapists preferred time-series line graphs to bar graphs. Most staff demonstrated understanding of the data, regardless of how it was depicted.     

Tactical and operational planning of express intra-city package services

In this paper, we focus on routing and load planning associated with the tactical and operational planning of an express intra-city courier service provider that receives a large number of shipments on a daily basis and is committed to delivering them to their destinations given a short service guarantee. Tactical planning relies on high-level aggregated demand rates over long time periods and takes the form of a multi-commodity service network design where the goal is to identify one path per commodity while maximizing consolidation opportunities in the network. Commodities are transported on their paths by means of a series of continuously operating vehicle cycles, where the structure and number of such cycles are determined concurrently with commodity path assignment decisions in a mixed integer programming. A second model is designed to refine the time allocation along different segments of a commodity path allowing a potential reduction in the number of vehicles required to meet the service guarantee. In operational planning, the focus is narrowed down to a shorter time period, and the baseline plan obtained from the tactical planning phase is adjusted to better fit potential deviations in observed demand patterns compared to the aggregate patterns. Through an extensive computational study designed on the topology of a major US city, we observe that the plans designed at the tactical level guarantee high service levels, which are improved at the operational level by customizing the plan to the special characteristic of a day of operation.     

Portfolio-based airline fleet planning under stochastic demand

Airlines operate their fleet of aircraft over a relatively long time horizon during which the realized stochastic demand has the potential to profoundly impact the airlines’ financial performance. This makes the investment in a fleet of aircraft a highly capital-intensive long-term commitment, associated with inherent risks. We propose an innovative three-step airline fleet planning methodology with the primary objective of identifying fleets that are robust to stochastic demand realizations. The methodology presents two main innovation aspects. The first one is the use of the mean reverting Ornstein–Uhlenbeck process to model the long-term travel demand, which is then combined with discrete-time Markov chain transitions to generate demand scenarios. The second innovative aspect is the adoption of a portfolio-based fleet planning perspective that allows for an explicit comparison of different fleets, in size and composition. Ultimately, the methodology yields for each fleet in the portfolio a distribution of net present values of operating profit across the planning horizon and a list of key financial and operational metrics per year. The robustest fleet can be selected based on the operating profit generating capability across different realizations of stochastic demand. An illustrative case study is presented as a proof of concept. The case study is used to demonstrate the type of results obtained and to discuss the usefulness of the methodology proposed.     

A robust optimization model for stochastic aggregate production planning

The aggregate production planning (APP) problem considers the medium-term production loading plans subject to certain restrictions such as production capacity and workforce level. It is not uncommon for management to often encounter uncertainty and noisy data, in which the variables or parameters are stochastic. In this paper, a robust optimization model is developed to solve the aggregate production planning problems in an environment of uncertainty in which the production cost, labour cost, inventory cost, and hiring and layoff cost are minimized. By adjusting penalty parameters, decision-makers can determine an optimal medium-term production strategy including production loading plan and workforce level while considering different economic growth scenarios. Numerical results demonstrate the robustness and effectiveness of the proposed model. The proposed model is realistic for dealing with uncertain economic conditions. The analysis of the tradeoff between solution robustness and model robustness is also presented.     

MODELS FOR OPTIMAL LEAD TIME REDUCTION

Most inventory and production planning models in the academic literature treat lead times either as constants or random variables with known distributions outside of management control. However, a number of recent articles in the popular press have argued that reducing lead times is a dominant issue in manufacturing strategy. The benefits of reducing customer lead times that are frequently cited include increased customer demand, improved quality, reduced unit cost, lower carrying cost, shorter forecast horizon, less safety stock inventory, and better market position. Although the costs of reducing lead times in the long term may be relatively insignificant compared with the benefits, in the short term these costs can have a significant impact on the profitability of a firm. This article develops a conceptual framework within which the costs and benefits of lead time reduction can be compared. Mathematical models for optimal lead time reduction are developed within this framework. The solutions to these models provide methods for calculating optimal lead times, which can be applied in practice. Sensitivity analysis of the optimal solutions provides insight into the structure of these solutions.     

A model for new product planning

A model is proposed for long term budget planning of new products. The model makes use of the Project Stage Survival Rate and Project Stage Cost Rate concepts discussed previously in Part I of this paper. published in our August edition.

The methodology utilizes the special attributes of the stages encountered during the R & D process. For this purpose, the project stage is used as a budgeting module. The model is oriented to satisfy the company growth objective by considering a continuous flow of new projects. The process aims at the successful completion of a planned number of projects within given time periods.

A hypothetical application of the model is presented in the form of a Budget Planning Chart.     

Occupational stress in universities: Staff perceptions of the causes,consequences and moderators of stress

In recent years, the Australian university sector has undergone large-scale organizational change, including restructuring, downsizing and government funding cuts. At the same time, research from across the globe reports an alarming increase in the occupational stress experienced by university staff. We report on the first phase of a longitudinal investigation of occupational stress. A total of 22 focus groups were conducted with a representative sample of 178 academic and general staff from 15 Australian universities. The groups focused on understanding staff 's experience of occupational stress, and perceptions of the sources, consequences and moderators of stress. Both general and academic staff reported a dramatic increase in stress during the previous 5 years. As a group, academic staff reported higher levels of stress than general staff. Five major sources of stress were identified including: insufficient funding and resources; work overload; poor management practice; job insecurity; and insufficient recognition and reward. The majority of groups reported that job-related stress was having a deleterious impact on their professional work and personal welfare. Aspects of the work environment (support from co-workers and management, recognition and achievement, high morale, flexible working conditions), and personal coping strategies (stress management techniques, work/ non-work balance, tight role boundaries and lowering standards), were reported to help staff cope with stress. The findings provide a timely insight into the experience of stress within universities.     

Supply chain configuration for diffusion of new products: An integrated optimization approach

We develop an integrated/hybrid optimization model for configuring new products’ supply chains while explicitly considering the impact of demand dynamics during new products’ diffusion. The hybrid model simultaneously determines optimal production/sales plan and supply chain configuration. The production and sales plan provides decisions on the optimal timing to launch a new product, as well as the production and sales quantity in each planning period. The supply chain configuration provides optimal selection of options and safety stock level kept at each supply chain function. Extensive computational experiments on randomly generated testbed problems indicate that the hybrid modeling and solution approach significantly outperforms non-hybrid alternative modeling and solution approaches under various diffusion and supply chain topologies. We provide insights on optimal production/sales plan and supply chain configuration for new products during their diffusion process. Also, managerial implications relevant to effectiveness of the hybrid approach are discussed.     

The Impact of Product Lifecycle on Capacity Planning of Closed‐Loop Supply Chains with Remanufacturing

Product recovery operations in reverse supply chains face rapidly changing demand due to the increasing number of product offerings with reduced lifecycles. Therefore, capacity planning becomes a strategic issue of major importance for the profitability of closed‐loop supply chains. This work studies a closed‐loop supply chain with remanufacturing and presents dynamic capacity planning policies developed through the methodology of System Dynamics. The key issue of the paper is how the lifecycles and return patterns of various products affect the optimal policies regarding expansion and contraction of collection and remanufacturing capacities. The model can be used to identify effective policies, to conduct various “what‐if” analyses, and to answer questions about the long‐term profitability of reverse supply chains with remanufacturing. The results of numerical examples with quite different lifecycle and return patterns show how the optimal collection expansion/contraction and remanufacturing contraction policies depend on the lifecycle type and the average usage time of the product, while the remanufacturing capacity expansion policy is not significantly affected by these factors. The results also show that the collection and remanufacturing capacity policies are insensitive to the total product demand. The insensitivity of the optimal policies to total demand is a particularly appealing feature of the proposed model, given the difficulty in obtaining accurate demand forecasts.     

A Comparison of Pyramidal Staff Training and Direct Staff Training in Community-Based Day Programs

This study evaluated two methods of training staff who were working with individuals with developmental disabilities: pyramidal training and consultant-led training. In the pyramidal training, supervisors were trained in the principles of applied behavior analysis (ABA) and in delivering feedback. The supervisors then trained their direct-care staff and, subsequently, provided ongoing performance feedback. In the consultant-led training, the direct-care staff was trained in the principles of ABA. Both groups learned similar amounts of knowledge of ABA principles, but pyramidal training was more effective in teaching staff to use correct teaching procedures with consumers. In addition, the pyramidal training group maintained the improvement in their teaching procedures at a 3-month follow up, while the consultant-led training group's performance declined.     

Electric-Utility Resource Planning and Decision-Making: The Importance of Uncertainty

Uncertainty is a critical factor that pervades all aspects of electric-utility planning. Uncertainties about future load growth, about the continued performance of existing supply and demand resources, and about the costs, construction times, and operations of new resources greatly complicate utility resource acquisition. This paper discusses the factors that lead to uncertainty, reviews the methods that utilities use in planning and in acquiring resources, and suggests future research to help deal with these uncertainties. This review is based on assessments of the long-term resource plans prepared by 10 utilities and one Public Service Commission, telephone interviews with staff at these 11 organizations and with staff at three consulting firms, and reviews of many other related publications.     

Planning for retail change: a survey of municipal governments in Washington State

Effectively managing retail is essential for municipalities in terms of meeting land use planning goals, developing revenue sources through taxation, furthering economic growth and providing access to goods and services for residents. In 2013, a survey was conducted to examine the retail planning practices of all the 110 small- and medium-sized municipalities in Washington State. The online survey addressed data collection and analysis, land use, retail recruitment, inter-jurisdictional cooperation and evaluation. A large majority of respondents had retail planning goals in their comprehensive plans, yet only 30% dedicated staff for implementation. Jurisdictions would benefit from regional retail planning (especially in light of changes underway from e-commerce), yet the state tax structure places municipalities in competition.     

控股股东代理成本、纳税筹划方案抉择及其市场价值:基于J有限公司的案例研究

纳税筹划是实务界与学术界共同关心的领域,现有研究大量讨论了公司纳税筹划行为的决定因素及其经济后果,但仍存在巨大争议。一方面,纳税筹划节约了现金流,提升股东价值;另一方面,代理问题使企业的纳税筹划方案更可能有利于控股股东或管理层,而非上市公司利益最大化,从而可能降低企业价值,最终纳税筹划方案的经济后果取决于上述两方面的共同作用。本文基于某上市公司(J有限公司)收购大股东土地案例,分析了代理成本影响公司税务决策的路径及其经济后果。本文发现,控股股东构造了较为复杂的股权转移交易方式,为上市公司和控股股东节约了大量税务成本。但由于代理成本的存在,在多种纳税筹划方案中,控股股东并未选择对上市公司最为有利的方案,而选择了能够取得现金最多,控股股东利益最大化的方案。进一步的研究发现,市场非常关注该企业的纳税筹划行为,与本文搜集的对照样本相比,尽管J公司的控股股东未选择最优的方案,但投资者仍给予了该纳税筹划行为以积极反应,提升了企业价值。本文为研究代理成本影响公司税务决策的机理提供了重要参考。     

Modelling a make or buy decision at ICI

Many of the long term problems facing management are so large that either a shorter term view is taken or they are split up into smaller components and analyzed independently. This paper describes a problem for which such approaches would have been invalid. To overcome this, Operations Research was used and a long range planning model was set up. This enabled exhaustive analysis over a planning period much longer than is usually attempted. The results of the study included a stable strategy, detailed operating plans and timetables of expenditures, and a readily accessed management information and planning review system.     

The Value of Quality Grading in Remanufacturing

In this paper we consider a tactical production‐planning problem for remanufacturing when returns have different quality levels. Remanufacturing cost increases as the quality level decreases, and any unused returns may be salvaged at a value that increases with their quality level. Decision variables include the amount to remanufacture each period for each return quality level and the amount of inventory to carry over for future periods for both returns (unremanufactured), and finished remanufactured products. Our model is grounded with data collected at Pitney‐Bowes from their mailing systems remanufacturing operations. We derive some analytic properties for the optimal solution in the general case, and provide a simple greedy heuristic to computing the optimal solution in the case of deterministic returns and demand. Under mild assumptions, we find that the firm always remanufactures the exact demand in each period. We also study the value of a nominal quality‐grading system in planning production. Based on common industry parameters, we analyze, via a numerical study, the increase in profits observed by the firm if it maintains separate inventories for each quality grade. The results show that a grading system increases profit by an average of 4% over a wide range of parameter values commonly found in the remanufacturing industry; this number increases as the returns volume increases. We also numerically explore the case where there are capacity constraints and find the average improvement of a grading system remains around 4%.