Industry 4.0 technologies are causing a paradigm shift in supply chain process management. The digital transformation of the supply chains provides enormous benefits to organizations by empowering collaboration among multiple internal and external organizations and systems. This study presents a narrative review explaining the existing knowledge on digital transformation in supply chain process management using text mining. It summarizes the existing literature to explain the current state of the art in supply chain digitalization. This comprehensive review identifies the most important topics and technologies and determines the future trends in this emerging field. We investigate the articles published in Web of Science and Scopus databases and use text mining techniques (clustering and topic modeling) on the article contents. Using VOS viewer, a bibliometric analysis of 395 articles with 12,700 references is analyzed. The contents of the articles are explored using text mining approaches. The synthesized results reveal that the most important topics in digital transformation are “sustainable supply chain management” and “circular economy and industry 4.0 technologies”. The study further discovers big data, data analytics, blockchain, artificial intelligence, machine learning, and the Internet of Things as the most critical technologies for facilitating supply chain digital transformation. Finally, an overlay heatmap analysis of the research articles found that digital transformation, supply chain management, industry 4.0, decision-making, and sustainability are emerging trends in supply chain digitalization.

Purpose: Delivering premium services and quality products are critical strategies for success in manufacturing. Continuous improvement (CI), as an underlying foundation for quality management, is an ongoing effort allowing manufacturing companies to see beyond the present to create a bright future. We propose a novel integrated fuzzy framework for analyzing the barriers to the implementation of CI in manufacturing companies.Design/methodology/approach: We use the fuzzy failure mode and effect analysis (FMEA) and a fuzzy Shannon's entropy to identify and weigh the most significant barriers. We then use fuzzy multi-objective optimization based on ratio analysis (MOORA), the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy simple additive weighting (SAW) methods for prioritizing and ranking the barriers with each method. Finally, we aggregate these results with Copeland's method and extract the main CI implementation barriers in manufacturing.Findings: We show “low cooperation and integration of the team in CI activities” is the most important barrier in CI implementation. Other important barriers are “limited management support in CI activities,” “low employee involvement in CI activities,” “weak communication system in the organization,” and “lack of knowledge in the organization to implement CI projects.”Originality/value: We initially identify the barriers to the implementation of CI through rigorous literature review and then apply a unique integrated fuzzy approach to identify the most important barriers based on the opinions of industry experts and academics.

Supplier selection is a strategic decision for reducing risk, maximising overall value, and establishing strong, mutually beneficial long-term relationships between the members in supply chain management. Identifying and prioritising the risks and benefits from each supplier enables managers to consider these factors and select the most suitable supplier. We propose an integrated approach for supply chain risk-benefit assessment and supplier selection by combining the fuzzy analytic hierarchy process (AHP) with the fuzzy multiplicative multi-objective optimisation based on ratio analysis (MULTIMOORA). The fuzzy AHP is used to measure the importance of the supply chain risks and benefits and the fuzzy MULTIMOORA is used to rank the suppliers. We present a case study to demonstrate the applicability and exhibit the efficacy of the proposed integrated framework. We also study the uncertainty in the output of our proposed framework using sensitivity analysis.

The managerial and environmental studies conducted in the energy research area reflect its substantial importance, particularly when optimizing and modifying consumption patterns, transitioning to renewable sources away from fossil ones, and designing plans and systems. The aim of this study is to provide a systematic review of the literature allowing us to identify which research subjects have been prioritized in the fields of energy and sustainability in recent years, determine the potential reasons explaining these trends, and categorize the techniques applied to analyze the uncertainty faced by decision-makers. We review articles published in highly ranked journals through the period 2003–2020 and apply text analytics to cluster their main characteristics; that is, we rely on pre-processing and text mining techniques. We analyze the title, abstract, keywords, and research methodology of the articles through clustering and topic modeling and illustrate what methods and fields constitute the main focus of researchers. We demonstrate the substantial importance of fuzzy-related methods and decision-making techniques such as the Analytical Hierarchy Process and Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS). We also show that subjects such as renewable energy, energy planning, sustainable energy, energy policy, and wind energy have gained relevance among researchers in recent years.

In order to have new product development and attract customers' involvement, a holistic approach is required within which consumers, manufacturers, sellers, designers and other stakeholders are gathered together effectively. Understanding the related factors that influence involvement of each stakeholder is crucial for achieving a sustainable competitive advantage. Therefore, this study is aimed to examine the effect and importance of customer involvement in new product development. The theoretical model is proposed based on a rigorous literature review and hypotheses are developed. In this survey - solidarity and cross sectional sampling is selected for considering the judgment of 150 managers, suppliers; and sellers (wholesalers and retailers) in Yazd tile and ceramic industry. The data is collected through questionnaires and the partial least squares-structural equation modelling (PLS-SEM) approach is applied. Research results indicated that two variables of marketing strategy and contextual factors explain changes in customer involvement as much as 24%, 34%, and the relationship between customer involvement and new product development is positively significant. The relationship between customer involvement and new product performance is also supported.

New digital technologies are evolving and the process of digitization has led to a broader phenomenon of “digital transformation” in most industries (Kretschmer & Khashabi, 2020; Steiber et al., 2020). Digital transformation is one of the main priorities of many organizations active in various business fields. To compete and survive, large economic organizations and companies must consider appropriate digital transformation as a key strategy, such as using technology to fundamentally improve performance (Heavin & Power, 2018).