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This study statistically examines the shifting distribution channels in the American wine industry based on the growth trajectory of sales, seasonality and disruption due to consumers switching to online platforms. The purpose of this paper is to design a model that will have general applicability beyond the wine industry.

The research uses regression-based additive decomposition of time series data to predict the trajectory of the market share for the digital distribution channel. The study develops a statistical prediction model using time series data between 2007 and 2020, inclusive, sourced from US Annual Wine Reports and Bureau of Alcohol, Tobacco and Firearms databases.

The results show an increasing trajectory of wine sales through the online distribution channel with predictable seasonality. The disruptive effects of consumer switching behavior point to a steady increase in sales due both to increasing demand and accelerating switching. Nevertheless, the model shows that bricks and mortar purchases will remain strong and continue to account for the bulk of wine sales. COVID-19 has caused a step function increase in online sales but this should moderate after the crisis subsides and can be tested further.

This study is original in developing a model for an industry where bricks and mortar sales are growing and are expected to remain strong while there is still identifiable switching to online sales. The wine industry presents a classic case of accelerating switching behavior where there is still a strong franchise for in-store purchases. The model should have general applicability to distribution channels beyond the wine industry where steady growth, marked seasonality and disruptive consumer switching are in evidence.

Supplier selection and evaluation are arguably one of the most critical functions for the success of an organization. Several approaches exist in the literature to objectively evaluate suppliers, including analytic hierarchy process and total cost of ownership. Analytic hierarchy process provides a framework to cope with multiple criteria situations involving supplier selection, while the total cost of ownership is a methodology and philosophy, which look beyond just the price of a purchase to better understand and manage costs in selecting and maintaining relationships with suppliers. This paper illustrates the two approaches and provides a comparison.

Presents an alternative framework to resolve the initial problems encountered in implementing a cellular manufacturing (CM) project. There are not a large number of case studies available detailing the same. The main thrust is on identifying some of the problems which arose in implementing a CM project at Otis Engineering, a business unit of Halliburton Corporation located in Carrollton, Texas. The project was implemented at one of Otis′s four plants and only the product line manufactured by that plant was considered. The extensive literature on scheduling in CM was drawn on to resolve problems in reducing set‐up times and increasing throughput. Set‐up‐time reduction, process capability, operator training and scheduling strategies were deemed to be critical to the successful operation of the cell.

It has been suggested that much of the potential inefficiencies associated with supply chain management (SCM) costs can be traced to wasteful practices such as inefficient, unnecessary, or redundant stocking practices, or inefficient transportation. The purpose of this paper is to develop a model which reconciles many of these inefficiencies by integrating production factors, purchasing, inventory, and trucking decisions for optimizing supply chain costs between first‐, and second‐tier suppliers and subsequent OEM customers.

The modeling technique is mathematical programming tested in a simulation model. In an effort to determine the significance of the transportation component of the proffered model, the fully developed model is differentially tested, including standard production variables varying transportation costs, paired with similar instances of the model in which the transportation costs are fixed.

Significant differences are found in the predictive abilities of the respective models, and this supplies pragmatic evidence of the important role that transportation issues play in the consideration of integrated SCM costs.

The key limitation to this finding lies in the validation process. As suggested by Sargent, Monte‐Carlo studies are useful for validation purposes, and the supply chain optimization model (MHSCM) is certainly confirmed through this particular simulation.

The managerial focus on transportation management and cost control in SCM can be highlighted as a critical implication of the study.

The structure of the MHSCM is robust, and may be useful for cost‐control planning purposes in a dynamic environment, subject to certain limitations accruing to the methodology.

The purpose of this study is to present a discussion on the most commonly accepted benchmarking norms in the USA, the lessons learned from benchmarking experiences and see how they are translated to benchmarking projects by French managers.

A survey questionnaire is developed, based on the ten‐step Xerox benchmarking process, to identify the perceived and/or experienced benchmarking best practices amongst French managers. Large, medium and small companies are surveyed and managers who have participated in or are in the middle of a benchmarking project contributed to the information in developing the conclusions about the perceived best practices, steps and pitfalls for a benchmarking project in French companies.

The survey result showed uniformity amongst French managers from large companies and their opinion on what is important in bringing a benchmarking project to a successful conclusion. There was however lack of uniformity of opinion when it came to what is important in the benchmarking process amongst French managers from companies of different size.

Caution should be exercised when interpreting these findings since the paper only used data from an exploratory survey of French managers from companies of varying sizes. The limitation of the study is that the conclusions are applicable to French managers only. In order to compare them one would need survey data, using the same questionnaire from managers in other countries.

Indeed, the authors' findings provide a persuasive argument for what French managers consider important in a benchmarking project. It provides valuable insights into the lessons learned from the years of benchmarking experiences and how these experiences have been translated across cultures.

Based on the French experience with the benchmarking process, the critical success factors for benchmarking were identified. Importance of each step in the benchmarking process varies amongst companies, critical issues are company and industry specific. In order to compete successfully in today's global marketplace, the French managers recognize the importance of benchmarking, although their perceptions of the important steps in the process vary depending on company size.

Much of the research literature in job shop scheduling deals with pure job shop environments. However, currently most processes involve a hybrid of both the job shop and a flow shop with a combination of flexible and conventional machine tools. Presents a study of such a job shop under varying conditions and performance criteria. Argues that for scheduling in this environment, certain combinations of scheduling rules should be utilized under different arrival rates and for different job types. A simulation model is developed using a hypothetical hybrid job shop to study the performance of rule combinations with variations in arrival rates and processing times. The performance criteria used are flowtime as a measure of work‐in‐process inventory, tardiness for JIT, and throughput for completed items inventory. It was found that rule combination performance varied with the performance criteria. Furthermore, it was found that the combinations were sensitive to arrival rates and processing times. Concludes, from the insights gained in the study, that the rule combination to be implemented should depend on the performance objective and the arrival rate/processing time condition of the hybrid job shop.

Presents a simulation model of the “Contract change process” for an aerospace manufacturing firm. The model was developed to simulate the activities from the time when a customer’s request is received to the two points in time where a preliminary schedule and a formal proposal is returned to the customer. The model was developed in a two‐stage approach. First, the process was studied and documented in US Air Force integrated computer aided manufacturing definition language for function modeling an IDEF₀ model which defined the relationships between each pair of activities. Second, using the structural information provided by the IDEFo model, a simulation model using simulation language for alternative modeling (SLAMII) was developed. Data were obtained from archival sources in the department’s database. The data were analyzed according to the quarter in which they were received. From this, arrival time data distributions were estimated for each of the four quarters to capture the seasonality element in the company’s business. Next, the data were separated into three levels of difficulty to define complex, routine and simple tasks. From this, three distributions of activity times were developed for each set of tasks. The results will allow for the study of reengineering and downsizing decisions for the contract change process in the aerospace industry, under conditions of seasonal and task complexity variations.

This paper aims to discuss a simulation study for a multi‐product, two‐echelon inventory replenishment system. The paper compares a one‐warehouse N‐retailer replenishment system to a two‐warehouse, N‐retailer system with cost per unit of distribution and delivery lead‐times as the performance measures. The purpose is to demonstrate that under specific circumstances a two warehouse N‐retailer inventory replenishment system provides better customer service without significant changes in the cost.

Mathematical modeling and simulation methodology is used to test the performance of the proposed two warehouse N‐retailer system and statistical analysis is used to compare the performance of several scenarios.

The two warehouse replenishment system indeed reduces delivery lead‐times, used as a measure of customer service, under specific conditions such as controllable freight costs.

Caution should be exercised when interpreting these findings as the historical data used was from a single source. The paper did not investigate the effects of variable shipping costs from the manufacturing plant, warehouse and retailer. Future research could also consider multiple second level warehouses.

The findings provide a persuasive argument for manufacturers struggling with performance issues and channel relationships. Moreover, in addition to contributing to efficiency of distribution, two level systems can also enhance ability to adapt to local market conditions and to unexpected demand variations.

The model examined in this paper addressed a specific case for one company. While freight costs and warehousing costs will vary across companies, the cost represented here may be used as a gauge for evaluating systems with cost structures in the vicinity of those for the company represented in this paper. Additionally, the model is amenable to substitution of other firms' cost structures.

Inventory control models for perishable products have primarily used a FIFO issuing policy with the objective of minimizing the number of outdated units. This paper aims to develop a model to evaluate an issuing policy for a single product with a fixed shelf life in single echelon inventory system. The issuing policy considers the remaining shelf life of the in‐stock inventory and the expected time that the product will spend in inventory as the decision driver.

The model developed has an objective of maximizing expected revenue over time with a budget constraint. A heuristic algorithm is proposed to iteratively arrive at the best solution to the formulation. The heuristic is tested by employing a simulation model of the system.

The proposed heuristic is tested against both the FIFO and the random allocation approaches and found to be superior for all the in‐stock with remaining shelf life distribution means of above 40 percent. No significant performance differences were found for the three approaches for remaining shelf life distribution.

The research is focused on a single product with multiple expiration dates and further research is necessary to determine the best policies for the multi‐product multi‐expiration date environment where the items are substitutable..

Retailers stock items with multiple expiration dates. The customer, for obvious reasons, is more likely to choose the item with the longer remaining shelf life. Therefore, the supply to the retailer's shelves and issuing policies for making available the particular items to the customers affect product outdating and related costs. Revenues will be affected by the extent to which more can be charged for items with a longer remaining shelf life or by the impact of the remaining shelf life on demand. This paper provides for a practical approach to that end.

The proposed issuing policy has not been tested before and thus makes a contribution to the body of knowledge. The flexibility of using different values for acquisition costs, selling prices, salvage value and penalty functions is a particular strength of the proposed model. Moreover, its potential application to inventory control problems for a wide range of perishable products is substantial.

Contrasts functional layouts and cellular layouts with regard to the effects of set‐up time reduction and lot size on flow time and through‐put. The structural environment for the functional analysis is an efficient functional system with a staged sequence of four machine centers with unidirectional flow and no backtracking. The structural environment for the cellular analysis is a partitioned cell consisting of one machine from each of the four machine types with unidirectional flow and no backtracking. Simulation models produce robust results for eight lot size levels and one (functional model) and seven (cellular model) set‐up time reduction levels. The results contrast the effectiveness of the two manufacturing approaches under differing input conditions. Shows that the choice between the functional structure and the cellular structure significantly affects through‐put at lot sizes up to 55, while for lot sizes of 60 and above there is no significant effect. The study also confirms previous results regarding the effect of manufacturing structure choice on flow time.