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Although studies have demonstrated the importance of supply chain integration (SCI) strategies in improving firm performance, very little is understood about how the organizational structure (OS) of focal firms affects the successful implementation of SCI initiatives across supply chains (SCs). Taking into consideration the importance of the oil and gas (O&G) industry, as well as the impact of uncertainties on OS and strategy choices, it is important to understand how OS and SCI affect the operational performance of O&G SCs. The paper aims to discuss this issue.

Taking a contingency approach and using a global sample of 181 O&G firms, this study examines the mediating role of internal, customer, and supplier integration on the relationship between three main dimensions of OS – the degree of centralization, formalization, and hierarchical relationships and operational performance, using structural equation modeling.

Findings reveal that OS dimensions negatively impact operational performance. Further testing for the mediation found that by increasing SCI, O&G SCs can mitigate the negative effect of high centralization, formalization, and hierarchical relationship on operational performance.

Classifying OS into “structuring” and “structural,” this research provides evidence on which of the two has a stronger negative impact on operational performance. This is significant since it may be difficult for O&G companies to restructure and reform their OS.

This study examines the impact of OS and SCI on improving the operational performance of the O&G SCs. Theoretical and practical contributions to the field of operations management and organizational studies are also discussed.

Drawing on the systems theory and the natural resource-based view, the purpose of this paper is to advance an integrated resource efficiency view (IREV) and derive a composite “integrated resource efficiency index” (IRE-index) for assessing the environmental, economic, and social resource efficiencies of production economies.

Using sub-national input-output data, the IRE-index builds on the human development index (HDI) and the OECD green growth indicators by including functions for environmental resource efficiency, energy, and material productivity. The study uses multiple regressions to examine and compare the IRE-index of 40 countries, including 34 OECD nations. The study further compares the IRE-index to similar composite indicators such as the human sustainable development index (HSDI) and the ecological footprint.

The IRE-index reveals a discrepancy between social development and resource efficiency in many of the world’s wealthiest production economies. Findings also show that material productivity has been the key driver for observed improvements in IRE over time. The index is a robust macro-level methodology for assessing resource efficiency and sustainability, with implications for production operations in global supply chains.

The IREV and IRE-index both contribute towards advancing green supply chain management and sustainability, and country-level resource efficiency accounting and reporting. The IRE-index is a useful composite for capturing aggregate environmental, economic, and social resource efficiencies of production economies. The paper clearly outlines the managerial, academic, and policy implications of the IREV and resulting index.

In response to calls for conceptual frameworks and generic theory building toward the advancement of sustainability in supply chain resource utilization and management, the purpose of this paper is to advance a circular framework for supply chain resource sustainability (SCRS), and a decision-support methodology for assessing SCRS against the backdrop of five foundational premises (FPs) deduced from the literature on resource sustainability.

Taking a conceptual theory-building approach, the paper advances a set of SCRS decision-support criteria for each of the theoretical premises advanced, and applies the theory of constraints to illustrate the conceptual and practical applications of the framework in SCRS decision making.

This study uses recent conceptualizations of supply chains as “complex adaptive systems” to provide a robust and novel frame and a set of decision rules with which to assess the interconnectedness of environmental, economic, and social capital of supply chain resources from pre-production to post-production.

The paper contributes to theory building in sustainability research, and the SCRS decision framework developed could be applied in tandem with existing quantitative hybrid life-cycle and input-output approaches to facilitate targeted resource sustainability assessments, with implications for research and practice.

The novel SCRS framework proposed serves as a template for evaluating SCRS and provides a decision-support methodology for assessing SCRS against the five theorized FPs.

This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.

The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.

It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.

The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.

This paper aims to integrate zero defect manufacturing (ZDM) with process mining (PM) to avoid defect occurrence during production and improve sustainability.

The method is developed based on literature review in ZDM and PM. It uses PM for process discovery as an initial strategy in priority to predict-prevent strategies of ZDM.

It presents the applicability of the proposed approach in observing manufacturing process behavior, identifying dynamic causes of defects during production, predicting the time of defect occurrence and preventing defective products. It also identifies, explains and measures criteria for environmental, social and economic pillars of sustainability affected by defects and presents the impacts of the proposed approach on sustainability improvement.

The extended view of this research, as well as its analytical approach, helps practitioners to develop their ZDM and PM approaches more holistically. The practical application of this research is illustrated through implementing it in a real-life manufacturing case, where the outcomes prove its applicability in avoiding defect occurrence and improving all three pillars of sustainability.

This paper aims to recommend a method entitled “lean process mining (LPM)” for mapping, analyzing and improving the material/information flows in the value stream of manufacturing processes.

The method is developed based on literature review and in-depth explorative research in value stream mapping and process mining approaches. The proposed LPM framework consists of three phases including as-realized process state, improvement strategies and reengineered process state. Hence, firstly, extracts the as-realized model, measures the identified wastes and identifies the sources of wastes. Secondly, implements prediction-recommendation-prevention strategies. Thirdly, reengineers the process model and measures the improved wastes.

It presents the applicability of the proposed approach in (1) online observation of manufacturing process behavior and tracing the process deviations dynamically in real time to identify the sources of waste; (2) avoiding defective products occurring during the production and eliminating the relevant derived wastes including wasted material, wasted energy, waste of labor, excess inventory, increased production lead time and wasted operational costs.

The practical application of LPM is illustrated through implementing it in a real-life manufacturing case. The outcomes prove the remarkable applicability of this method in lean manufacturing to avoid waste occurrence in the value stream.

Tourism industry is a profitable resource for countries and considered one of the main sources of income and job creation for economic development. Among the various types of tourism, medical tourism and its subsets are of great significance owing to their capabilities and competitive advantages. In this regard, the purpose of this research is to provide a framework to categorize customers based on the Zeithaml pyramid and then identify and provide strategies to create loyalty and attract customers of this industry.

This study proposed a framework for medical tourists' satisfaction and loyalty. First, by studying the literature and data gathering from Yazd (one of the cities of Iran), the effective factors on the loyalty and attraction of medical tourists were identified. These factors have been prioritized for the medical tourists who are in the platinum category by the Pareto technique and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. Next, the strategies provided by experts for loyalty and attraction of medical tourists were examined. Finally, the house of quality (HOQ) as the first matrix in quality functional deployment (QFD) was used to provide operational strategies for medical tourism satisfaction. The statistical population of this research consists of medical tourists, academic experts and active physicians of medical tourism in Yazd, one of the cities of Iran.

The study results indicate the importance of “hospital reputation” in medical tourists' satisfaction. Also, “achieving international standards”, “periodic customer satisfaction assessment” and “paying attention to social responsibilities” are recognized as the most important strategies to achieve the loyalty of the most profitable group of customers, namely platinum.

This study covers both theoretical and practical aspects. Theoretically, this study developed a new framework for medical tourists' satisfaction by the Zeithaml matrix, TOPSIS, Pareto technique and QFD method. Furthermore, practically this study helps practitioners of medical tourism in medical tourists' satisfaction and loyalty.

In this study, in addition to identifying the effective factors on the loyalty and attracting medical tourists, a new framework was developed for medical tourists' satisfaction by segmentation the tourism by the Zeithaml matrix and providing operational strategies by the QFD technique.