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The purpose of this paper is to propose an integrated approach to process integration, automation, and optimization through enhanced business process models.

The approach is based on a framework of process integration for functional applications, automation for business workflows, and additional functionalities for process optimization. The proposed approach is illustrated using enhanced process models over business integration, automation, and optimization with data elements, structures, and organizational elements. The standard sales order process cycle, quotation approval process, and production order cycle are chosen for illustrating process integration, automation, and optimization, respectively.

The proposed approach combines applications and workflows using integrated process/data models and forms a foundation for business process optimization. It is shown that the integrated approach can improve existing business processes in enterprise resource planning (ERP), beyond business process re‐engineering (BPR) principles, once enhanced business process models are implemented. This approach eliminates need for a hierarchical representation of business processes and highlights the flexibility and visibility of business process implementation in ERP system environment.

Although process integration, automation, and optimization are illustrated using selected business process examples, it requires generalization of these enhancements over entire business blueprint of ERP system. Thus, one key limitation of this research is that it is not generalized for the entire business blueprint of ERP. This also requires changes to data structures beyond current relational data in many ERP systems.

This research provides an integrated approach to business process modeling beyond traditional functional and workflow applications by eliminating hierarchical nature of process and data elements.

The paper aims to give a quantitative assessment of the benefits obtainable by using information and communication technologies to integrate the order‐to‐payment process involving manufacturers and specialized retailers in the home appliances industry.

Standard business processes were defined and activity base costing was applied to develop the cost model with the support, i.e. validation and data provision of most of the companies operating in the Italian home appliances market.

The bottom line is €96 per order‐to‐payment cycle in the conventional, paper‐based scenario, compared to €23 in the integrated scenario involving the exchange of structured electronic documents. The potential savings amount to about 80 per cent of the costs, almost equally shared between the retailer and the manufacturer. A significant part of the benefits comes from the reduction in the management costs of non‐conformity issues.

The assessment considers only tangible benefits and does not include more intangible advantages, such as cycle time reduction, compliance with regulation and easier and faster accessibility to documents.

The paper measures the benefits of using trade process integration technologies and presents a methodology that can be applied to other industries and to particular supply chains. The difficulties in assessing the benefits have been claimed to be one of the main barriers to adoption.

The paper provides a model to assess the order‐to‐payment cycle costs, considering both the costs of the “perfect cycle” (where no errors occur) and the cost of managing non‐conformities. At present, there is no benchmark available in the literature for the order‐to‐payment cycle costs in conventional and integrated conditions that could help companies to assess the expected benefits of integration.

A Process Model During the last five years, American businesses have increasingly accepted the notion that product quality is necessary for them to compete in today′s world markets. Product quality, in the context here, can be defined by an agreed set of standards and tolerance limits between the firm and its customers. Quality is achieved through the successful creation of form, possession, time, place, and quantity utilities for the firm′s products. Control must be implemented in order to ensure that these utilities are created to meet the standards and tolerance limits agreed upon by the firm and its customers. The purpose of exercising control is to ensure that desired results are attained from an activity or process. As such, it is important to exercise control over the logistics activities to make sure that time, place, and quantity utilities are created in accordance with customer needs. The purpose of this monograph is to present a rather comprehensive discussion of the concept of control. Specific control concepts presented include a discussion of the link between control and quality, the development of the characteristics of control and levels of sophistication of control, the presentation of an eclectic process control model, and suggestions to managers on how to implement the control process over logistics activities.

This article aims to quantify and analyse empirically how the geographic dispersion of a firm's supply chain impacts on intra‐firm supply chain performance.

Generalised linear modelling is utilised to analyse a sample of 95 large manufacturing companies operating in Finland.

Results indicate that the increased geographic dispersion of the upstream supply chain results in higher costs of warehousing and logistics administration. On the downstream side, inventory costs, inventory days of supply, and cash‐to‐cash cycle time tend to increase due to geographically dispersed sales network. Increased geographic dispersion in the upstream and downstream supply chain results in the decline of perfect orders, and increases order fulfilment cycle time. However, the increased dispersion of the production network reduces order fulfilment cycle time. The results also indicate that the larger the firm, the better it can alleviate the negative implications of dispersion on perfect order fulfilment. Make‐to‐stock companies suffer less from the supply chain dispersion related delays in comparison to companies that utilise more pull‐type production and inventory strategies.

Research limitations include the cross‐sectional nature of the data, the concentrated geographic origin of the respondents, and the small sample size.

Building on the multidisciplinary body of prior literature on geographic dispersion, the research provides quantified insights into the general principles of international supply chain design in the presence of a performance related trade‐off between the dispersion and centralisation of operations across the tiers of the supply chain. Contributions are made to the discussions on supply chain complexity, international sales portfolio diversification and international purchasing.

This article provides a discussion of key components for the decisionmaker concerned with the logistical issues of implementing a Just‐in‐Time (JIT) manufacturing philosophy. A JIT philosophy promotes reduced cycle times that provide benefits not normally considered in traditional inventory models and presents new concerns for the purchasing and logistics functions. The ramifications are investigated of a JIT implementation using an inventory‐theoretic modelling procedure modified and expanded to incorporate these considerations. The resulting cost comparisons indicate that the lead time variability associated with uncertain transit times in JIT is critical in the determination of order cycle time, order point, safety stock and the holding cost of the safety stock.

In order to improve the computation efficiency of the four-point rainflow algorithm, a new fast four-point rainflow cycle counting algorithm (FFRA) using a novel loop iteration mode is proposed.

In this new algorithm, the loop iteration mode is simplified by reducing the number of iterations, tests and deletions. The high efficiency of the new algorithm makes it a preferable candidate in fatigue life online estimation of structural health monitoring systems.

The extensive simulation results show that the extracted cycles by the new FFRA are the same as those by the four-point rainflow cycle counting algorithm (FRA) and the three-point rainflow cycle counting algorithm (TRA). Especially, the simulation results indicate that the computation efficiency of the FFRA has improved an average of 12.4 times compared to the FRA and an average of 8.9 times compared to the TRA. Moreover, the equivalence of cycle extraction results between the FFRA and the FRA is proved mathematically by utilizing some fundamental properties of the rainflow algorithm. Theoretical proof of the efficiency improvement of the FFRA in comparison to the FRA is also given.

This merit makes the FFRA preferable in online monitoring systems of structures where fatigue life estimation needs to be accomplished online based on massive measured data. It is noticeable that the high efficiency of the FFRA attributed to the simple loop iteration, which provides beneficial guidance to improve the efficiency of existing algorithms.

Cycle time reduction is important for order fulling process but often subject to resource constraints. This study considers an unrelated parallel machine environment where orders with random demands arrive dynamically. Processing speeds are controlled by resource allocation and subject to diminishing marginal returns. The objective is to minimize long-run expected order cycle time via order schedule and resource allocation decisions.

A stochastic optimization algorithm named CAP is proposed based on particle swarm optimization framework. It takes advantage of derived bound information to improve local search efficiency. Parameter impacts including demand variance, product type number, machine speed and resource coefficient are also analyzed through theoretic studies. The algorithm is evaluated and benchmarked with four well-known algorithms via extensive numerical experiments.

First, cycle time can be significantly improved when demand randomness is reduced via better forecasting. Second, achieving processing balance should be of top priority when considering resource allocation. Third, given marginal returns on resource consumption, it is advisable to allocate more resources to resource-sensitive machines.

A novel PSO-based optimization algorithm is proposed to jointly optimize order schedule and resource allocation decisions in a dynamic environment with random demands and stochastic arrivals. A general quadratic resource consumption function is adopted to better capture diminishing marginal returns.

Computerising inventory control procedures is usually an attempt to gain better control over stock availability. The effectiveness of the procedures depends on the time delays imparted by such events as order processing and delivery. Through these time delays, much of a finished goods physical distribution system is linked together through the inventory control procedures. Changing the length of any one time element through changes in inventory stocking rules, order processing methods or selected transportation services impacts on the economics of the entire physical distribution system. Little is understood about the effects of time change in such complex systems. In this article, the actual computer inventory control procedures of a chemical company were computer simulated. Physical distribution system design decisions and their associated time delay effects were explored by interrogating the model. Surprising effects were discovered, some of them being counter‐intuitive to what simple theory would predict. Management guidelines were provided as to the system‐wide economic consequences of change in individual elements of a physical distribution system.

Study in supply chain performance research on the shipbuilding industry is lacking. The purpose of this research is to study and provide guidelines to improve the performance of traditional shipbuilding supply chains in Indonesia.

The paper develops an empirical study gathered from a traditional shipbuilding industry, its suppliers, and customers. This study consists of three sections: the traditional shipbuilding industry, the suppliers, and the individual supplier scores. The internal and external performances in this study are measured using Supply Chain Operations Reference (SCOR) metrics. The SCOR model identifies five performance measurement attributes, including reliability, flexibility, responsiveness, cost and assets. Instead of using “responsiveness,” this study applies the schedule performance index, and supplements “cost” with the cost performance index in order to accurately reflect the traditional shipbuilding supply chains processes.

By analyzing SCOR metrics in the traditional shipbuilding industry, it has been found that the ideal shipbuilding supply chain metrics are order fulfillment, flexibility, asset turnover and total supply chain costs. The lowest performance metric value in the traditional shipbuilding industry is the cost of goods. Some improvements are proposed to lower the high cost of ship building. An integrated economic ordering system in collaboration with all the suppliers is one of the most effective ways to reduce the cost of the traditional shipbuilding supply chains. The implementation of SCOR metrics enables management to identify the critical issues to improve.

The study applies SCOR metrics to improve the traditional shipbuilding supply chains performance. The study is limited because the data collected are based on one shipbuilding industry only.

To the author's knowledge, this is the first empirical analysis on the implementation of SCOR metrics to the traditional shipbuilding industry. The analysis to improve the traditional shipbuilding supply chains performance can provide managerial insights to other industries.

Recently, star variables and the post-crisis nature of cyclical fluctuations have attracted a great deal of interest. In this chapter, the authors investigate different methods of assessing business cycles (BCs) for the European Union in general and the euro area in particular. First, the authors conduct a Monte Carlo (MC) experiment using a broad spectrum of univariate trend-cycle decomposition methods. The simulation aims to examine the ability of the analysed methods to find the observed simulated cycle with structural properties similar to actual macroeconomic data. For the simulation, the authors used the structural model’s parameters calibrated to the euro area’s real gross domestic product (GDP) and unemployment rate. The simulation outcomes indicate the sufficient composition of the suite of models (SoM) consisting of popular Hodrick–Prescott, Christiano–Fitzgerald and structural trend-cycle-seasonal filters, then used for the real application. The authors find that: (i) there is a high level of model uncertainty in comparing the estimates; (ii) growth rate (acceleration) cycles have often the worst performances, but they could be useful as early-warning predictors of turning points in growth and BCs; and (iii) the best-performing MC approaches provide a reasonable combination as the SoM. When swings last less time and/or are smaller, it is easier to pick a good alternative method to the suite to capture the BC for real GDP. Second, the authors estimate the BCs for real GDP and unemployment data varying from 1995Q1 to 2020Q4 (GDP) or 2020Q3 (unemployment), ending up with 28 cycles per country. This analysis also confirms that the BCs of euro area members are quite synchronized with the aggregate euro area. Some major differences can be found, however, especially in the case of periphery and new member states, with the latter improving in terms of coherency after the global financial crisis. The German cycles are among the cyclical movements least synchronized with the aggregate euro area.