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The main purpose of the present study was to improve and develop previously proposed models for Iran telecommunication networks. It should be noted that the six-dimensional (6D) sustainability model used in this study will be a useful and comprehensive model for industries. Since, the new dimension of IT along with the five well-known economic, social, environmental, technical and institutional aspects of organizations is considered to have great impacts on supply chain sustainability; the proposed framework can be practical.

According to the related literature review, there are two research streams in supply chain management. The first stream is exploratory research, seeking out conceptual discussions in this area. The second one is associated with mathematical models and techniques, aiming to set decision-making rules in this regard (Agrell et al., 2004). In this study, evaluation was performed using the FMEA method as an analytical technique based on the principle of pre-occurrence prevention to identify potential failure factors in sensitive systems (Mohammadfam and Kianfari, 2008).

After identifying the risks and causes of the incidence and effects and consequences of risks, preventive and risk control measures and advisory strategies were presented. Customers with 45.76% share in critical risks are threatening to maintain supply chain in these companies. During this study, it was found that 33.9% of the main source of supply chain critical risks was customers, constituting 45.76% of such risks, accompanied by organization, having a 38.88% share of critical risk generation. The study findings also revealed that 33.9% of critical risks were mainly (equally) related to economic and technical aspects of supply chain sustainability in telecommunication networks. Moreover, as a newly-introduced sixth dimension, IT represented 10.17% of critical risks threatening supply chain sustainability in such networks. Critical risks are mainly related to the economic and technical aspects (equally) with the sustainability of the telecommunication networks supply chain. Also, as a new finding and the sixth dimension, 10.17% of the critical risks that threaten the sustainability of the telecommunication networks supply chain have the information technology dimension.

The internet and fixed and mobile data services are provided by several private companies in Iran, which are relatively similar in terms of their supply chains. In order to manage the sustainability of Iran's telecommunication supply chain, telecommunication networks affiliated to Iran Telecommunication Company (ITC), operating in the field of data and internet services and fixed telephone were selected in 31 provinces. The intended networks were also providing an important part of the country's needs including Mobile Telecommunication Company of Iran, a subsidiary of Iran's telecommunication networks, as one of the top companies in this industry. Accordingly, all the networks studied in this study needed to be identified with regard to communication sustainability risks, since they provide management solutions to each other by segregating risks. In this study, 68 managers and 72 experts participated in different work teams of telecommunication networks.

The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.

Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.

The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.

The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.

The purpose of this study is to present and explain a new customer segmentation approach inspired by failure mode and effect analysis (FMEA) which can help classify customers into more accurate segments.

The present study offers a look at the three most commonly used approaches to assessing customer loyalty:net promoter score, loyalty ladder and loyalty matrix. A survey on the quality of restaurant services compares the results of categorizing customers according to these three most frequently used approaches.

A new way of categorizing customers through loyalty priority number (LPN) is proposed. LPN was designed as a major segmentation criterion consisting of customer loyalty rate, frequency of purchase of products or services and value of purchases. Using the proposed approach allows to categorize customers into four more comprehensive groups: random, bronze, silver and gold – according to their loyalty and value to the organization.

Survey will bring a more accurate way of categorizing customers even in those sectors where transaction data are not available. More accurate customer categorization will enable organizations to use targeting tools more effectively and improve product positioning.

The most commonly used categorization approaches such as net promoter score, loyalty ladder or loyalty matrix offer relatively general information about customer groups. The present study combines the benefits of these approaches with the principles of FMEA. The case study not only made it possible to offer a view of the real application of the proposed approach but also made it possible to make a uniform comparison of the accuracy of customer categorization.

Student retention is important in the management of any university especially one which is not financially independent. Administrators in such institutions need to investigate ways to improve the retention rate in order to avoid the loss of revenue. One of the methods is to ensure that students are able to follow their study pathway and complete their study on time instead of dropping out. The purpose of this paper is to establish a system that allows the university to monitor the progression of these students and highlight the need for counselling when necessary. It is also hoped that this paper helps to improve the student retention rate using quality analysis tools and add knowledge into factual-based problem-solving methodology.

This paper is a co-relational study based on secondary data. It is a continuous improvement method adopting the “plan-do-check-action” model. Quality analysis tools adopted are failure modes and effects analysis and process mapping, where both are the quality analysis tools commonly used in solving product design or assembly process issues in manufacturing. Using the case study of Wawasan Open University, the authors will adapt the aforesaid quality analysis tools from design and manufacturing sectors into an open distance learning education design. It is hoped that the identified process facilitates certain functions of the departments of the organisation to be more effective.

This paper provides a practical approach on the methods to improve the retention rate in a private higher education institute. Stakeholders are more willing to embrace the improvement when there is proper factual analysis to support the plans. A cross-departmental team is formed to brainstorm the various aspects of the process and the potential failure modes. In a resource-constrained environment, prioritisation is important to identify the high-impact problems. It is also important that a mechanism is available to deliver information to the area where decisions and actions can be made. The failure modes are prioritised systematically and the corresponding solutions installed. The end result is a system with the process that reduces interdepartmental inconsistency thus providing students with a clearer visibility of their study pathway so that they can complete their study on time instead of dropping out.

This study is performed within the context of an institute. The generalisation is low. Other researchers are encouraged to explore further.

This paper provides some practical actions for the improvement of student retention in the university. It is hoped that other researchers will be attracted to explore further on using quality analysis tools to solve non-technical problems.

This paper provides a structured problem-solving method in a service-oriented organisation.

The purpose of this paper is to generalize the traditional risk evaluation methods and to specify a multi-level risk evaluation framework, in order to prepare customized risk evaluation and to enable effectively integrating the elements of risk evaluation.

A real case study of an electric motor manufacturing company is presented to illustrate the advantages of this new framework compared to the traditional and fuzzy failure mode and effect analysis (FMEA) approaches.

The essence of the proposed total risk evaluation framework (TREF) is its flexible approach that enables the effective integration of firms’ individual requirements by developing tailor-made organizational risk evaluation.

Increasing product/service complexity has led to increasingly complex yet unique organizational operations; as a result, their risk evaluation is a very challenging task. Distinct structures, characteristics and processes within and between organizations require a flexible yet robust approach of evaluating risks efficiently. Most recent risk evaluation approaches are considered to be inadequate due to the lack of flexibility and an inappropriate structure for addressing the unique organizational demands and contextual factors. To address this challenge effectively, taking a crucial step toward customization of risk evaluation.

The aim of this study is to develop an in-depth case study on the implementation on Lean six sigma (LSS) in Schnell S.p.A., Italian company leader of an important multinational industrial group, highlighting the benefits that can be achieved from a careful application of this method, the main challenges and organizational learning from its implementation.

The study has been developed with a qualitative approach, creating a single in-depth case study, with the participant observation of researchers in the project which lasted 4 months. Periodic weekly meetings were done with the working group to exchange feedback on the development of the project to share opinions and data.

A project has been developed to stabilize the procurement process of a pull-type production cell, which experienced delays in supply lead times. The causes of the problems in their process of managing the supply of the production cell were found and some inefficiencies in the internal process of fulfillment of supply orders have been intercepted, the optimization of which has allowed the generation of an automatic system for sending supply orders, coming directly from the production line.

This study described the path and dynamics of the transformation process that business organizations undertake for optimizing their profitability and competitive advantage, placing emphasis on an innovative methodology for conducting business process improvement projects, which constitutes its operating philosophy on the effective and efficient use of company resources and skills, to guarantee to the company the achievement of a lasting and defensible competitive advantage over time.

This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.

The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.

The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities.

The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

The purpose of this paper is to increase productivity through smart maintenance planning by including productivity as one of the objectives of the maintenance organization. Therefore, the goals of the paper are to investigate existing machine criticality assessment and identify components of the criticality assessment tool to increase productivity.

An embedded multiple case study research design was adopted in this paper. Six different cases were chosen from six different production sites operated by three multi-national manufacturing companies. Data collection was carried out in the form of interviews, focus groups and archival records. More than one source of data was collected in each of the cases. The cases included different production layouts such as machining, assembly and foundry, which ensured data variety.

The main finding of the paper is a deeper understanding of how manufacturing companies assess machine criticality and plan maintenance activities. The empirical findings showed that there is a lack of trust regarding existing criticality assessment tools. As a result, necessary changes within the maintenance organizations in order to increase productivity were identified. These are technological advancements, i.e. a dynamic and data-driven approach and organizational changes, i.e. approaching with a systems perspective when performing maintenance prioritization.

Machine criticality assessment studies are rare, especially empirical research. The originality of this paper lies in the empirical research conducted on smart maintenance planning for productivity improvement. In addition, identifying the components for machine criticality assessment is equally important for research and industries to efficient planning of maintenance activities.

The major economies of East Asia, namely Japan and the Four Asian Tigers, have always prioritized the WTO-led multilateral trade liberalization over other trade arrangements primarily due to their unique economic structure with a high dependency on the world’s major markets such as the US. Along the same line, even the huge blow from the Asian Financial Crisis in 1997 only managed to trigger a few initiatives to aide East Asian regional integration while being led by different centering bodies, APEC and ASEAN. These dispersed efforts naturally resulted in no realistically significant achievements in the light of ‘integration’ until the present day. Under these circumstances, East Asia now faces a second opportunity to achieve its economic independence from the extra-regional influences via regionalization: the 2009 Global Credit Crunch. This paper hereupon critically reviews the actual progress and the likely impacts of the current global recession on the East Asian region.

The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).

The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.

A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.

HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.

The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.