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The purpose of this study is to develop a multi‐criteria hierarchical maintenance performance measurement framework, which is balanced, holistic and integrated to various levels of the organization.

Consolidation of published research and current practices are combined to study, identify and develop this proposed framework.

A framework for maintenance performance measurement is proposed for developing and implementing a relevant, timely, reliable, cost and time‐effective and user‐friendly system for stakeholders at various levels. The indicators at the subsystem/component level, plant level and corporate level are linked with the MPIs for the organizational objectives and strategy.

Management of maintenance performance is critical for long term economic viability of business and industry. Development of an integrated, balanced and holistic MPM system needs to consider various issues to measure the contribution of maintenance towards total business goals. In this paper, a multi‐criteria hierarchical MPM framework has been developed. This framework can be used by the operating managers for their maintenance decisions at various levels of an organization.

The paper presents a proposed MPM framework, which is integrated, and focuses on both internal and external effectiveness.

The purpose of the paper is to develop a methodological framework for supply chain risk management using the hierarchical holographic modeling approach. It analyses supply chain risks in a systematic manner and develops a hierarchical methodology for identifying, prioritizing and managing the potential supply chain risks.

This research reviews supply chain risk management literature and develops a conceptual framework, which outlines general principles and guidelines for managing risks in a systematic manner. Through decomposition, the complexity of supply chain risk can be identified by analyzing smaller subsystems.

The paper provides a conceptual framework to identify supply chain risks from multiple overlapping perspectives. The structured filtering and ranking procedure enables decision-makers to focus on the most critical risks. The research shows that the supply chain risks associated with the sub-systems within the hierarchical structure contribute to and ultimately determine the risks of the overall supply chain system.

The risks associated with each sub system within the hierarchical structure can contribute to and determine the risks of the overall supply chain system. Further applications in various companies and industry sectors would benefit supply chain managers on a case-by-case basis.

The hierarchical risk identification framework can serve as guidance for applications to specific supply chain systems and processes. The framework from a holistic overlapping perspective can efficiently and effectively help supply chain managers identify supply chain risks and facilitate the evaluation of the subsystem risks.

The paper applies system thinking in supply chain management and presents an efficient and practical framework for supply chain risk identification and evaluation.

The purpose of this research is to develop a method for automatic construction of multi‐document summaries of sets of news articles that might be retrieved by a web search engine in response to a user query.

Based on the cross‐document discourse analysis, an event‐based framework is proposed for integrating and organizing information extracted from different news articles. It has a hierarchical structure in which the summarized information is presented at the top level and more detailed information given at the lower levels. A tree‐view interface was implemented for displaying a multi‐document summary based on the framework. A preliminary user evaluation was performed by comparing the framework‐based summaries against the sentence‐based summaries.

In a small evaluation, all the human subjects preferred the framework‐based summaries to the sentence‐based summaries. It indicates that the event‐based framework is an effective way to summarize a set of news articles reporting an event or a series of relevant events.

Limited to event‐based news articles only, not applicable to news critiques and other kinds of news articles. A summarization system based on the event‐based framework is being implemented.

Multi‐document summarization of news articles can adopt the proposed event‐based framework.

An event‐based framework for summarizing sets of news articles was developed and evaluated using a tree‐view interface for displaying such summaries.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.

The proposed definitional framework can be used to define housing typologies of cities in developing countries. It aims to define housing typologies in the capital city of Albania, Tirana, using the proposed hierarchical framework within the dynamics of four political periods: Ottoman, establishment, socialist and postsocialist.

This study proposes a new definitional approach for the housing typologies through a hierarchical framework that defines the typologies based on their political period and legality statuses departing from the case of Tirana, which is featured by a heterogeneous context. Such context is characterized by uncontrollable urban development, making typology definition problematic. Furthermore, beyond the form, spatial and functional features, it presents their exterior distinctiveness as an innovative element. The methodology used in the study includes archival research, image documentation, spatial, functional and exterior distinctiveness analysis of housing typologies and exploration of housing form features in different political periods.

The study identifies urban formal housing typologies in Tirana detached houses, apartments, mass housing, social housing, gated communities, informal detached houses and housing with in/formal additions.

This definitional approach can be used to define housing typologies for cities featured by heterogeneous urban context.

To improve accuracy and efficiency of multi‐fault recognition and localization for large‐scale system such as satellite.

First, fault propagations of a system are modeled by a digraph, which composes of nodes and arcs. Each arc is associated with information about propagation probability and propagation strength. Then, based on consistency‐based theory and semantic theory of abstractions, hierarchical diagnosis model of a system is built. Finally, according to a two‐way hierarchical diagnosis strategy, two incorporated algorithms are adopted which are the Lagrangian relaxation algorithm and the “method of propagation strength”.

Hierarchical model can greatly improve efficiency of diagnosis compared with un‐hierarchical one. The combined qualitative and quantitative knowledge can improve fault resolution.

The propagation probability and propagation strength must been known.

The method shows its superiority when it is applied to complex system such as spacecraft.

A novel hierarchical framework for large‐scale system multi‐fault diagnosis, which include some new ideas and algorithm is put forward.

This study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.

Based on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.

The results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.

The hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.

This study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.

Quality function deployment (QFD) is a structured approach to seek out customers, understand their needs, and ensure that their needs are met. QFD is probably the most important management tool developed to assure quality in new or improved products and services. As with any other tool, the quantum of benefits obtained from the use of QFD is proportional to the effectiveness of its use. To enhance the effectiveness and efficiency of QFD as a means to transfer the “voice of the customer” into design and production, a new comprehensive hierarchical framework for QFD planning process and a zero‐one goal programming model for the selection of design requirements are proposed. The hierarchical framework contributes to the strategic guidance and provides clear direction for QFD teams during the construction of the house of quality. The decision model assists in determining a set of design requirements that most effectively meet customer needs subject to limited resources and other organizational restrictions. An illustrative example is also provided to demonstrate the practical usage of the design selection model.

In the domain of information science, affordance is a relatively new concept that deserves further exploration. It may serve as a bridge to narrow the research-practice gap that has persisted in information studies. Building upon previous research, we call for a broader concept of affordance that would help researchers understand information practices from an ecological perspective.

The study focuses on conceptualizing affordances for information practices in order to theorize engagement among people, technology, and sociocultural environments. We develop a hierarchical model and a component model to illustrate how key tenets of affordances can be linked with the decomposition of activities and its mechanism. Following this, we describe an illustrative case of a popular Chinese cloud-based music platform to demonstrate the utility of our conceptual frameworks in guiding studies of information practices.

The study proposes to shift the focus of technology affordances, which highlights the features and functions of particular technologies, to the affordances for practices that are enacted through technology and social construction within a sociocultural environment. The illustrative case of the cloud-based music platform shows that the proposed models can provide a structured view of operations, actions and motives for music information practices. The processes of internalization and externalization offer insight into the decomposition of information practice as a chain of activity-action-operation.

This study contributes to the literature on theorizing engagement among people, technology and sociocultural environments through the theoretical lens of affordances and sheds new light on the challenges of information practice.

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies like India.

Around nine growth-accelerating enablers of green financing were found through literature and unstructured interviews and analysed using the total interpretive structural modelling (TISM) method. The hierarchical link between each factor is established using TISM, and further to evaluate the driver-dependent relationship the Matriced’ Impacts Croises Appliquee Aaun Classement (MICMAC) approach is utilised.

The findings demonstrate an interrelationship between growth-accelerating factors, where the political environment and information and communication technology (ICT), have minimal dependency but a strong driving force. Political environment and ICT are found as strategic-level factors lying at the bottom of the model driving towards the dependent variables. The government should focus on enacting effective policies such as the green credit guarantee scheme and carbon credit and establishing a regulatory framework to enhance green financing.

This study examines the literature to generalise the findings and focus on the primary motivators for developing green financing. To increase green financial activity, practitioners must concentrate on aspects with significant driving forces. Furthermore, it makes organisations more profitable, efficient and competitive and promotes long-term growth.

The study is the first in the literature which identifies the growth-accelerating factors of green financing using the TISM and MICMAC-based hierarchical models.