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A corrected attempt to determine the size of in‐process inventory and the manufacturing lead time for an n‐stage production system is made. This corrects the earlier model developed by Ornek and Collier by accurately deriving the model for determining the manufacturing cycle time.

In most manufacturing systems, a number of production stages are involved between which some in‐process inventory usually occurs. This inventory imposes a further cost on the overall system, not only in terms of investment charges but also shop floor congestion, additional material handling charges and loss of floor space. In attempting to optimise this in‐process inventory a necessary balance must be obtained with the associated manufacturing lead time. A mathematical model is devised to achieve the above in a multi‐stage production system and this is demonstrated by application to a set of actual industrial data.

Since lean manufacturing considers that “Inventory is evil”, the purpose of this paper is to find and quantify the relations between work-in-process inventory (WIP), manufacturing lead time (LT) and the operational variables they depend upon. Such relations provide guidelines and performance indicators in process management.

The authors develop equations to analyse how, in discrete deterministic serial batch processes, WIP and LT depend on parameters like performance time (of each workstation) and batch size. The authors extend those relations to processes with different lots and the authors create a multiple-lot box score.

In this paper, the relations among WIP, LT and the parameters they depend on are derived. Such relations show that when WIP increases, LT increases too, and vice versa, and the parameters they depend on. Finally, these relations provide a framework for WIP reduction and manufacturing LT reduction and agree with the empirical principles of lean manufacturing.

Quantitative results are only exact for discrete deterministic batch processes without any delays. Expected results might not be achieved in real manufacturing environments. However, qualitative results show the underlying relations amongst variables. Different expressions might be derived for other situations.

Understanding the relations between manufacturing variables allows operations managers better design, implement and control manufacturing processes. The box score, implemented on a spreadsheet, allows testing the effect of changes in different operational parameters on the manufacturing LT, total machine wait time and total lot queue time.

The paper presents a discussion about process performance based on the mutual influence between WIP and LT and other variables. The relation is quantified for the discrete deterministic case, complementing the models that exist in the literature. The box score allows mapping more complex processes.

Main constraints for an assembly line balancing problem (ALBP) are cycle time/number of stations and task precedence relations. However, due to the technological and organizational limitations, several other restrictions can be encountered in real production systems. These restrictions are called as assignment restrictions and can be task assignment, station, resource and distance limitations. The purpose of the study is to evaluate the effects of these restrictions on ALBP using constraint programming (CP) model.

A novel CP model is proposed and compared to mixed-integer programming (MIP) as a benchmark. The objective is to minimize the cycle time for a given number of stations. The authors also provide explicit anthology of the assignment restriction effects on line efficiency, the solution quality and the computation time.

The proposed approach is verified with the literature test instances and a real-life problem from a furniture manufacturing company. Computational experiments show that, despite the fact that additional assignment restrictions are problematic in mathematical solutions, CP is a versatile exact solution alternative in modelling and the solution quality.

Assembly line is a popular manufacturing system in the making of standardized high volume products. The problem of assembly line balancing is a crucial challenge in these settings and consists of assigning tasks to the stations by optimizing one or more objectives. Type-2 AR-ALBP is a specific case with the objective function of minimizing the cycle time for a given number of stations. It further assumes assignment restrictions that can be confronted due to the technological limitations or the strategic decisions of the company management. This is especially encountered in rebalancing lines.

Several solution approaches such as mathematical modelling, heuristic and meta-heuristic are proposed to solve the ALBP in the literature. In this study, a new approach has been presented using CP. Efficient models are developed for Type-2 ALBP with several assignment restrictions. Previous studies have not considered the problem to the presented extent. Furthermore, to the best of the authors’ knowledge, the paper is the first study that solves ALBP with assignment restrictions using CP.

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?

This paper aims to discuss the sequence-dependent forward setup time (FST) and backward setup time (BST) consideration for the first time in two-sided assembly lines. Sequence-dependent FST and BST values must be considered to compute all of the operational times of each station. Thus, more realistic results can be obtained for real-life situations with this new two-sided assembly line balancing (ALB) problem with setups consideration. The goal is to obtain the most suitable solution with the least number of mated stations and total stations.

The complex structure it possesses has led to the use of certain assumptions in most of the studies in the ALB literature. In many of them, setup times have been neglected or considered superficially. In the real-life assembly process, potential setup configurations may exist between each successive task and between each successive cycle. When two tasks are in the same cycle, the setup time required (forward setup) may be different from the setup time required if the same two tasks are in consecutive cycles (backward setup).

Algorithm steps have been studied in detail on a sample solution. Using the proposed algorithm, the literature test problems are solved and the algorithm efficiency is revealed. The results of the experiments revealed that the proposed approach finds promising results.

The sequence-dependent FST and BST consideration is applied in a two-sided assembly line approach for the first time. A genetic algorithm (GA)-based algorithm with ten different heuristic rules was used in this proposed model.

This paper aims to explore the emerging relationship between Industry 4.0 (I4.0) digital technologies (e.g. blockchain, Internet of Things (IoT) and artificial intelligence (AI)) and the construction industry’s gradual transition into a circular economy (CE) system to foster the adoption of circular economy in the construction industry.

A critical and thematic analysis conducted on 115 scientific papers reveals a noticeable growth in adopting digital technologies to leverage a CE system. Moreover, a conceptual framework is developed to show the interrelationship between different I4.0 technologies to foster the implantation of CE in the construction industry.

Most of the existing bodies of research provide conceptual solutions rather than developing workable applications and the future of smart cities. Moreover, the coalescence of different technologies is highly recommended to enable tracking of building assets’ and components’ (e.g. fixtures and fittings and structural components) performance, which enables users to optimize the salvage value of components reusing or recycling them just in time and extending assets’ operating lifetime. Finally, circular supply chain management must be adopted for both new and existing buildings to realise the industry's CE ambitions. Hence, further applied research is required to foster CE adoption for existing cities and infrastructure that connects them.

This paper investigates the interrelationships between most emerging digital technologies and circular economy and concludes with the development of a conceptual digital ecosystem to integrate IoT, blockchain and AI into the operation of assets to direct future practical research applications

Introduction: Monetary policy resolutions issued by central banks play effective role in economy when accompanied with interest variable. In Keynesian approach to finance, interest is treated as the main determinant underlying financial policy resolutions. Thus interest is a pivotal factor in monetary transmission mechanism. Tight monetary policy practices, essentially decreasing money supply, eventually lead to a slump in investments, total demand and national income due to the increase in real interest rates.

Objective: The aim of this study is to determine what type of effects do monetary policy practitioner in Turkey have on macroeconomic variables via the interest channel of monetary transmission mechanism.

Methodology: Based on this objective, variables that could help in unveiling CBT overnight interest rates, direct fixed capital investment (GSSO), real gross domestic product (RGDP), industry production index (SUE) and domestic producer price index (YUFE) variables and that could explain monetary functions of transmission mechanism’s interest channel were selected. For the variables constituting the research topic, collected data belong the period of 2003Q1–2018Q3.

Findings: In the study relation between the variables has been analyzed under two parts via harnessing Toda–Yamamoto casualty test. In the first part, results of Toda–Yamamoto causality test from RGDP, GSSO and interest rate (FO) variables have been presented. The results manifest that interest channel directly affects direct fixed capital investment and RGDP. Interest channel was found to be effective on these variables of the analysis. In the second part, Toda–Yamamoto causality test was harnessed for SUE, YUFE and FO variables. Interest channel did not provide a result that affected YUFE and SUE.

This paper aims to, by having a marketing perspective, assess the potential of Manisa for religious tourism and shed some light on the ways of increasing that potential and to add to the religious tourism literature and practice in general.

A number of depth interviews were conducted with the experts of culture, tourism, religion and religious assets in Manisa. People and institutions regarding religious tourism were called, visited and asked for the names of right interviewees. As a result, a total of 14 interviews were arranged and successfully accomplished. In addition to depth interviews, top 15 most popular travel Web sites (www.ebizmba.com/articles/travel-websites) are examined for tourist and guide opinions toward Manisa’s religious sites and its surroundings.

The findings indicate that Manisa has highly important religious monuments belonging to three major religions, including three of the seven churches mentioned in the Apocalypse section of the Bible. Many suggestions have been made regarding possible changes in products, referring to religious monuments and sites in this study, and other marketing mix elements like possible ways of promoting the product.

The findings are based on a qualitative study, which limit their generalizability. Yet, the sample of interviewees is fairly large and utmost attention is given to the selection of them. In the future, more stakeholders can be involved in the data collection process. Also, the views of general public on the topic can be investigated through surveys to determine the details of religious tourism activities.

Preparations for selling souvenirs (like miniatures of religious monuments) and other religious and cultural goods near the sites of attraction can be made. In addition to selling souvenirs (e.g. miniatures, postcards), local food (i.e. Mesir paste, Mesir delight) and local drinks (i.e. Mesir tea, Sübye) can be offered at gift shops or stores to be opened next to religious monuments.

With the rising popularity of experiential and event marketing, tourists coming to Manisa to see religious monuments will be better off experiencing the atmosphere of these monuments. A specific team of experts from each related organization can be formed and an action plan be prepared to determine the steps to be taken regarding religious tourism. A wise planning and an effective implementation of religious tourism efforts require an intense coordination.

Policy makers and managers who want to promote religious tourism need to determine the tourism products and services which appeal to a diverse types of tourists visiting any religious destination. Religious tourism products and services in other destinations can be offered in combination with such activities as camping, hiking and sightseeing or such other types of tourism as social and group tourism and adventure. Standard marketing strategies may not work for religious tourism because spiritual travel will take different forms and have different meanings. Promotional activities are utilized to make potential customers aware of products, induce demand and provide incentives to purchase.

The aim of this study is to analyse the factors that contribute to the disclosure of relational liabilities (RLs) of the US companies.

The study uses content analysis to examine the disclosure of RLs in annual reports of the US companies listed on the Nasdaq-100 index from 2013 to 2015.

The study finds a positive correlation between the disclosure of RLs and gender diversity of the board of directors as well as the education level of the CEO. By contrast, the disclosure of RLs is negatively associated with the age of the CEO. Companies in knowledge-intensive industries also tend to disclose more information about their RLs than those in other industries.

This study focuses on the determinants of RLs, whereas previous research has mainly examined the positive impact of voluntary disclosure of intellectual capital on financial performance. The main objective of this study is to shed light on the factors that influence the disclosure of RLs.