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The purpose of this paper is to examine the relationship between customer order lead time (COLT) and the price sensitivity of an electrical equipment manufacturer company. In consequence, it examines two research questions in terms of COLT, price and profitability level and to ensure the validity and practical justification of these research questions.

In this research the authors have used a case study approach where three business measures, namely COLT, price and the profitability level of a case company were investigated and analyzed critically. These measures were implemented through four different customer segments with two production lines of the case company. Data were collected from the company's order delivery database from the period 2006 to 2008. In addition, different experimental data were collected through interviewing and reviewing the results of the data analysis with the unit managers.

In this paper the authors have observed the correlation between the price, profit and COLT with all four customer segments in both the production lines of the case company. From the case data, the authors concluded that the customer did not pay more when the COLT is shorter than with the average time. It is also noticeable that the profit margin is higher for the case company to handle COLT with shorter lead time than the average order delivery lead time.

More case examples might be helpful to motivate the managers to accept the research outcomes.

The concept of the company's COLT in relation to the price and profitability level supports organizational managers in their decision‐making process in terms of productivity level and the company's growth. It will motivate the managers to make tradeoffs among various developmental measures.

This paper implemented a unique approach for measuring the significant level of price and profitability level over COLT. From the outcomes of this study, it is observed that the price correlated positively with the COLT and has a direct and significant impact on it. When the price is increased the COLT is also increased. It is also noticed that the products of the case company which offered shorter lead times were on average also more profitable, even though there were no significant differences in average pricing between the customer segments.

Mechanisms to adjust planned lead times based on current work loads are desirable for time‐phased planning systems. This paper investigates the use of exponentially smoothed order flow time feedback in setting planned lead times dynamically. The system studied is a supply chain with capacity‐constrained processing stations and transit times between stations. Lot sizes are based on the minimization of flow times using queuing approximations. Both seasonal and level demand patterns with uncertainty are considered. Since both dependent and independent demands are assumed at each station, customer delivery performance depends on the distribution of inventory along the supply chain. Results show that dynamic planned lead time setting can be used effectively to control delivery performance along the supply chain. Performance is also influenced significantly by appropriate lot size selection.

This article presents the results of a simulation study of implementation practices for material requirements planning systems. In particular, the role of safety lead times in ensuring effective delivery performance is analysed and some general guidelines are suggested.

Generic product offerings in a boundaryless competitive environment do not support economic viability. Time‐based dimensions of a product are becoming an increasingly important component in assessing strategic advantage. A generalized framework is provided for analyzing product environments based on production/consumption gaps that can lead to an augmented product. Traditional long lead times and high inventory levels are less appropriate and more costly endeavours that may not even achieve product parity.

The objective of this study is to revise and enhance existing inventory control models in a way that allows them to be used more efficiently in environments with short lead times.

A simulation approach has been chosen to assess the efficiency of the developed model. This simulation is based on randomly generated demand data with a compound Poisson type of distribution.

Results from the simulation show that traditionally used inventory control methods fail to ensure that desired service levels are attained in environments with short lead times. The simulation also shows that, by using the developed model, the differences between desired and attained service levels can be reduced to fall within limits acceptable in practice.

The study provides an enhanced inventory control model that can be used in environments with short lead time to increase service level performance.

The purpose of this paper is to examine the impact of supply chain lead‐time averages and variability on an organization's financial performance.

The “executive” list for manufacturers, consisting of 1,264 individuals of the Institute of Supply Management provided the study's sampling frame, with surveys sent to 402 firms and responses obtained from 210 firms. The empirical model is tested using LISREL.

The results show that as variance in supply chain lead‐times increases, the financial performance of the organization decreases. Of equal significance, the results show that average supply chain lead‐times have no direct impact on financial performance. The results also indicate that demand uncertainty associates with greater supply chain lead‐time variance and that production technology routineness associates with lower supply chain lead‐time variance. Product complexity and organizational size have no impact on supply chain lead‐time variance or supply chain lead‐time average.

The research is an initial effort to understand variance in supply chain systems. An ongoing challenge in this area is operationalization of measures and data collection techniques that go beyond a single firm and examine a network of organizations cooperating in a value‐added supply chain.

The results suggest that managing the variance in a supply chain system may be more important to an organization's financial performance than managing averages.

This is particularly significant since organizations often act contrary to these findings, focusing scarce resources on reducing average lead‐times rather than on reducing variability in supply chain lead‐times.

The purpose of this paper is to derive monetary benchmarks and managerial implications for omni-channel retailers’ B2C e-fulfillment strategies by investigating the trade-offs between lead time, delivery convenience and total price including shipment in the context of online electronics retailing.

Based on a choice-based conjoint analysis among 550 US online shoppers, the monetary values of lead time and convenience were calculated in a log-log regression model. In addition, latent class segmentation was applied to identify consumer segments according to their differing e-fulfillment preferences.

From a consumer perspective, the analysis suggests that price is the most important criteria in omni-channel retailer selection, followed by lead time and convenience. The value of time is, on average, $3.61 per day. Regarding convenience, the results indicate that delivery to the home is highly preferred over pick-up options. The value of the consumer’s travel time was estimated at $10.62 per hour. The latent class segmentation identified four segment groups with different preferences.

To validate the findings, future research could analyze real data from omni-channel retailers’ customers’ buying behavior. It should also be interesting to extend the research to other price ranges, market segments and e-fulfillment factors, such as return options, shop ratings and membership programs aiming for further generalization.

The findings guide omni-channel retailers to focus on efficient B2C e-fulfillment strategies. Considerable competitive advantages may be gained by reducing lead times and offering convenient delivery in line with the lead time valuation of the identified customer segment.

This study fills gaps in the academic research of consumer behavior in retailer selection, which has primarily concentrated on the choice between “brick-and-mortar” and online sales channels. It paves the way for a more service-oriented perspective in omni-channel retailing research.

Increased demand and the pressure to reduce health-care costs have led to longer waiting time for patients to make appointments and during the day of hospital visits. The purpose of this study is to identify opportunities to reduce waiting time using lean techniques and discrete-event simulation (DES).

A five-step procedure is proposed to facilitate the effective utilization of lean and DES to improve the performance of the Otolaryngology Head and Neck Surgery Outpatient Clinic at Cleveland Clinic Abu Dhabi. While lean techniques were applied to reduce the potential sources of waste by aligning processes, a DES model was developed to validate the proposed solutions and plan patient arrivals under dynamic conditions and different scenarios.

Aligning processes resulted in an efficient patient flow reducing both waiting times. DES played a complementary role in verifying lean solutions under dynamic conditions, helping to plan the patient arrivals and striking a balance between the waiting times. The proposed solutions offered flexibility to improve the clinic capacity from the current 176 patients up to 479 (without violating the 30 min waiting time policy) or to reduce the patient waiting time during the visit from the current 33 min to 4.5 min (without violating the capacity goal of 333 patients).

Proposing and validating lean solutions require reliable data to be collected from the clinic and such a process could be laborious as data collection require patient and resource tracing without interfering with the regular functions of the clinic.

The work enables health-care managers to conveniently conduct a trade-off analysis and choose a suitable inter-arrival time – for every physician – that would satisfy their objectives between resource utilization (clinic capacity) and average patient waiting time.

Successful implementation of lean requires a supportive and cooperative culture from all stakeholders involved.

This study presents an original and detailed application of lean techniques with DES to reduce patient waiting times. The adopted approach in this study could be generalized to other health-care settings with similar objectives.

Time is a business commodity which has an enormous opportunity cost. Yet normal business controls make no attempt to value or identify the scale or nature of this. In this paper Professor Martin Christopher and Alan Braithwaite introduce the concept of Strategic Lead Time Management as a means of measuring and valuing the time efficiency of business.

This study examines the moderating role of information sharing on the effect of lead-time management on the performance of firms in the Zimbabwean motor industry.

Data were collected using Likert-based structured questionnaires from a sample of 105 employees in Zimbabwe. In addition, Pearson Correlation, Linear Regression and Moderation Regression analysis were employed to test the relationship between study variables.

The study found that fixed lead time, preprocessing lead time, processing lead time and postprocessing lead time significantly influence the performance of firms in the motor industry. The results also demonstrate that information sharing moderates the effect of lead-time management on firm performance in the motor industry.

Firms in the motor industry should establish long-term relationships with their suppliers and implement effective communication channels for timely and frequent information exchange regarding production schedules, inventory levels, quality standards and potential disruptions.

The current study aims to contribute to the scientific discourse on lead-time management, information sharing and performance in the motor industry. Furthermore, it extends knowledge on the performance of the motor industry in the African region.