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Changes frequently made to material delivery schedules (MDSs) accumulate upstream in the supply chain (SC), causing a bullwhip effect. This article seeks to elucidate how dynamic complexity generates MDS instability at OEMs in the automotive industry.

An exploratory multiple-case study methodology involved in-depth semistructured interviews with informants at three automotive original equipment manufacturers (OEMs).

Dynamic complexity destabilizes MDSs primarily via internal horizontal interactions between product and process complexities and demand and SC complexities. A network of complexity interactions causes and moderates such instability through complexity absorption and generation and complexity importation and exportation.

The multiple-case study contributes to empirical knowledge about the dynamics of MDS instability. Deductive research to validate the identified relationships remains for Future research.

In revealing antecedents of complexity’s effect on MDS instability, the findings imply the need to develop strategies, programs, and policies dedicated to improving capacity scalability, supplier flexibility, and the flexibility of material order fulfillment.

Building on complexity literature, the authors operationalize complexity transfer and develop a framework for analyzing dynamic complexity in SCs, focusing on complexity interactions. The identification and categorization of interactions provide a granular view of the dynamic complexity that generates MDS instability. The identified and proposed importance of readiness of the SC to absorb complexity challenges the literature focus on external factors for explaining complexity outcomes. The results can be used to operationalize such dynamic interactions by introducing new variables and networks of relationships. Moreover, the work showcases how a complexity perspective could be used to discern the root causes of a complex phenomenon driven by non-linear relationships.

Schedule instability is a major problem in companies using material requirements planning (MRP) systems. The effectivenesss of using buffer stock to combat nervousness in the master production schedule (MPS) of an MRP system is investigated. An example scenario illustrates the need for caution in using buffer stock for reducing schedule instability. Detailed simulation results are presented which suggest the need for further research to understand the role of buffer stock in achieving stable master production schedules.

This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

There is a relative dearth of literature which examines the implications for suppliers which deliver on a just‐in‐time (JIT) basis. Some authors suggest that there are significant benefits for both the buyer and the supplier through participation in JIT procurement, although there are other reports which claim that the suppliers are being forced to increase their stock holding. Reports on a series of semi‐structured interviews conducted with 18 Scottish‐based JIT suppliers. Claims the results indicate that those suppliers which were able to manufacture JIT themselves were, unless subject to substantial schedule instability, able to resist the transfer of inventory, while the non‐JIT manufacturers experienced an increase in inventory. Finds that all the suppliers had experienced an increase in their administrative burden, as a result of JIT delivery.

Organizational scholars studying compensation often place an emphasis on certain employee groups (e.g., executives). Missing from this discussion is research on the compensation systems for low-wage jobs. In this review, the authors argue that workers in low-wage jobs represent a unique employment group in their understanding of rent allocation in organizations. The authors address the design of compensation strategies in organizations that lead to different outcomes for workers in low-wage jobs versus other workers. Drawing on and integrating human resource management (HRM), inequality, and worker literatures with compensation literature, the authors describe and explain compensation systems for low-wage work. The authors start by examining workers in low-wage work to identify aspects of these workers’ jobs and lives that can influence their health, performance, and other organizationally relevant outcomes. Next, the authors explore the compensation systems common for this type of work, building on the compensation literature, by identifying the low-wage work compensation designs, proposing the likely explanations for why organizations craft these designs, and describing the worker and organizational outcomes of these designs. The authors conclude with suggestions for future research in this growing field and explore how organizations may benefit by rethinking their approach to compensation for low-wage work. In sum, the authors hope that this review will be a foundational work for those interested in investigating organizational compensation issues at the intersection of inequality and worker and organizational outcomes.

Recently several authors have concentrated their efforts in developing models to determine the economic lot size for multi‐stage systems. This is due to the fact that an increasing number of organisations are implementing material requirements planning systems. Numerous models have been developed and tested on problems with finite and rolling horizons and with deterministic time varying demand patterns.

The sources and consequences of schedule instability at an automotive assembler producing two models on the same assembly track are described. One model was produced under conditions of relatively lengthy stable schedules, the other under more unstable schedule conditions. The two logistics processes were compared, and measures of schedule uncertainty identified. The relative impact on human resources was explored by investigating constructs of the two production systems according to people who worked in the processes. Relative quality and productivity of the two systems were evaluated. It was concluded that there were advantages in both of these measures for the more stable production system, and that the supply chain and core manufacturing process were relatively lean. But the less stable production system provided greater responsiveness to the market and greater discretion to people working in the process.

The purpose of this paper is to present the result of using process mining to model the production planning (PP) process of a manufacturing company that is supported by enterprise resource planning (ERP) systems.

This paper uses event logs obtained from the case company’s ERP database. The steps for this research are planning process mining implementation, extraction and construction of event log, discovering process model with Heuristic Miner and analysis.

Process model obtained from process mining shows how the PP is actually conducted. It shows the loop in materials requirement planning and create plan order process. Furthermore, the occurrences of changing plan order date and production line indicate the schedule instability in the case company. Further analysis of the material management (MM) event log shows the implication of production plan changes on MM. Continuous change in the plan affects material allocation priority and may result in a mismatch between production needs and the materials available.

The study is only conducted in a single and specific case. Therefore, even though the findings provide good insight, the use of solitary case study does not imply a general result applied to other cases. Hence, there is a need to conduct similar studies on various cases so that a more generic conclusion can be drawn.

The result provides insights into how the current company’s policy of adjusting the production plan to accommodate changing demand impacts their operation. It can help the company to consider a better balance between flexibility and efficiency to improve their process.

The paper demonstrates the use of process mining to capture the real progression of PP based on the data stored in the company’s ERP database, which give an insight into how a real company conducts their PP process, the implication of schedule instability on MM and production. The novelty of this research lies in the use of process mining to attest to the schedule nervousness issue at a process level.

The drug logistics play a crucial role in the hospital service performance. It has been proved that modern logistics concept is a valid access to competitiveness. In order to enhance the comprehensive capability and core competence of hospitals, including the internal support system, there is a great need to have an in-depth and systematic study on the drug logistics system in hospitals. The purpose of this paper is to explore the current situation of the drug logistics and the drug centres operations in public hospitals in China; specifically how the organizational partnerships with the supply chain partners can affect the operational performance.

In this study, the possibility of correlations between schedule instability, partnerships with supply chain partners, and internal drug logistics operation is investigated by modelling, with reference to the previous work of Law et al. (2009), in which collective efficacy of the performance is incorporated into the model.

The findings of this study show that the drug logistics working teams in public hospitals in China have a high level of efficacy and self-confidence, while they perceive they provide good operations even at a low level of schedule nervousness. The study also reinforces the significant correlation between internal operation and partnership with customers. This is definitely useful for the development of an appropriate framework for drug logistics operation improvement in the long run.

The study thus offers a good reference for the administrators and practitioners who are keen on improving the service operations in the healthcare sector in the region.