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The use of natural resources by organizations has a significant impact on society, resulting in business firms playing a vital role in developing sustainable development. As a result, corporate sustainability has become an integral aspect of a company’s vision and policy in the modern days. Companies issue sustainability reports based on various criteria and metrics, thereby attempting to gain a competitive edge. This study aims to assess and prioritize the numerous factors that influence corporate sustainability performance.

The analytic hierarchy process (AHP) is used to prioritize the identified determinants of corporate sustainability performance based on the literature. Several experts from business and academia were engaged to build a comparison matrix for assessing the various aspects of corporate sustainability performance. As a result, various corporate sustainability determinants were determined and prioritized following an extensive literature review using the AHP.

The most critical component for companies is an economic indicator. Developing environmentally and socially responsible suggestions must be a priority for the organization’s economic performance. Economic performance is believed to be most heavily influenced by innovation and in the other category like environmental and social performance are highly influenced by environment management policies and shareholder responsibility, respectively. Researchers’ findings suggest that to promote sustainability, top executives should devote all of their attention to innovation, environment management policies and shareholder responsibility.

These studies are primarily concerned with developed countries. And, the other fundamental constraint of the AHP study is that the rating scale adopted in the analysis is conceptual. Therefore, pairwise comparisons with a variety of indicators have the potential to introduce bias into the results.

This paper proposes a methodical and operational technique for selecting the ultimate priority of sustainability indicators when it comes to exploiting competitive information on business performance. The paper also recommended sustainability rating technique might be carried out once every six months to improve the overall quality and performance of the organization.

The advantages of adopting and executing corporate sustainability are enormous, and managers must determine whether sustainability is profitable or not. This question prompts further inquiries. For example, what are the numerous critical determinants of corporate sustainability performance? Several scholars throughout the world are looking at it for this reason. As a result, it is essential to comprehend and prioritize the various determinants of corporate sustainability performance.

Today the role of industry 4.0 plays a very important role in enhancing any supply chain network, as the industry 4.0 supply chain uses Big Data and advanced analytics to inform the complete visibility. Latest data are available to bring clarity and support real-time decision-making in the entire supply chain that’s why adopting optimization techniques such as lean manufacturing and lean supply chain concept for enhancing the supply chain network of the organizations is a good idea and would benefit them in increasing their cost efficiency and productivity. The purpose of this work is to develop a technique, which may be useful for future researchers and managers to identify and classification of the significant lean supply chain enablers.

In this paper, the authors considered hybrid analytical hierarchy process to find the ranking of the identified lean supply chain enablers by calculating their weightage. Interpretive structural modeling (ISM) is applied to develop the structural interrelationship among various lean supply chain management enablers. Considering the results obtained from ISM the Matrices d'Impacts Croises Multiplication Appliqué a un Classement (MICMAC) analysis is done to identify the driving and dependence power of Lean Supply Chain Management Enablers (LSCMEs).

Further, the best results applying these methodologies could be used to analyze their inter-relationships for successful Lean supply chain management implementation in an organization. The authors developed an integrated model after the identification of 20 key LSCMEs, which is very helpful to identify and classify the important enablers by ISM methodology and explore the direct and indirect effects of each enabler by MICMAC analysis on the LSCM implementation. This will help organizations optimize their supply chain by selective control of lean enablers.

For lean manufacturing practitioners, the result of the study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process, as well as in enhancing the supply chain.

This paper is the first research paper that considered firstly deep literature review of identified lean supply chain enablers and second developed structured modeling of various lean enablers of supply chain with the help of various methodologies.

This paper aims to define a hierarchical and multi-criteria framework based on pillars of the Modernization of Higher Education to evaluate European Accounting Doctoral Programmes (EADE-Model).

The authors applied a quali-quantitative methodology based on the analytic hierarchy process and the survey approach. The authors conducted an extensive literature and regulation review to identify the dimensions affecting the quality of Doctoral Programmes, choosing accounting as the relevant and pivotal field. The authors also used the survey to select the most critical quality dimensions and derive their weight to build EADE Model. The validity of the proposed model has been tested through the application to the Italian scenario.

The findings provide a critical extension of accounting ranking studies constructing a multi-criteria, hierarchical and updated evaluation model recognizing the role of doctoral training in the knowledge-based society. The results shed new light on weak areas apt to be improved and propose potential amendments to enhance the quality standard of ADE.

Theoretical and practical implications of this paper are directed to academics, policymakers and PhD programmes administrators.

The research is original in drafting a hierarchical multi-criteria framework for evaluating ADE in the Higher Education System. This model may be extended to other fields.

In this study, the deployment of an integrated Quality Function Deployment (QFD) decision framework is presented to help cities design targeted strategies to become “smart”. Arguably smart cities leverage advanced technologies to enhance their smartness to improve everyday urban life. To this end, a QFD – Analytic Hierarchy Process – Analytic Network Process (QFD-AHP-ANP) framework is proposed to deliver guidance for selecting the appropriate mix of smart technologies based on the specific smart needs of each city.

The AHP and ANP methods are incorporated into QFD to enhance its methodological robustness in formulating the decision problem. AHP accurately captures and translates the “Voice of the Experts” into prioritized “Smart City” dimensions, while establishing inter-relationships between these dimensions and “Smart City Technologies”. Meanwhile, ANP explores tradeoffs among the technologies, enabling well-informed decisions. The framework’s effectiveness is evaluated through an illustrative application in the city of Thessaloniki.

Applying the framework to this real-world context confirms its practicality and utility, demonstrating its ability to particularize local, social, political, environmental and economic trends through the resulting mix of technologies in smart urban development strategies.

The importance of this study lies in several aspects. Firstly, it introduces a novel QFD decision framework tailored for smart city strategic planning. Secondly, it contributes to the operationalization of the smart city concept by providing guidance for cities to effectively adopt smart technologies. Finally, this study represents a new field of application for QFD, expanding its scope beyond its traditional domains.

For construction organisations to be effective at implementing an integrated safety, health and environmental (SHE) management system, they require the right level of organisational capability. This capability includes the policies, systems and resources of the organisation. However, within the academic literature, it is unclear which organisational attributes of construction companies are important for implementing integrated SHE management. This study aims to explore the organisational attributes that determine integrated SHE management capability and their relative priorities.

The study used a literature review supported by expert verification and a subsequent three-round expert Delphi technique accompanied by applying the voting analytical hierarchy process.

The study identified 20 attributes grouped under five main thematic categories. These are strategy (the organisation’s vision and top management commitment); process (the organisation’s procedures and processes for SHE management); people (organisation’s human resources, their competence, roles, responsibilities and involvement in SHE management); resources (organisation’s physical and financial resources for SHE management) and information (SHE related documents, data, records and their communication across an organisation). While these thematic categories and the attributes within carry different weights of importance, the strategy-related attributes are the most important, followed by the people-related attributes.

The results of this study should enable construction companies and key industry stakeholders to understand construction companies’ capability to successfully implement an integrated SHE management system. Furthermore, construction companies should be able to prioritise efforts or investments to enhance their SHE management capability.

While providing users with important innovation resources, an enterprise's open innovation community also encounters numerous challenges. The purpose of this study is to develop and implement a set of evaluation systems that can identify the ecological characteristics of open innovation communities. The ultimate goal is to provide guidance for the construction and establishment of these communities.

Firstly, from the perspective of information ecology, according to the connotation requirements of the four information elements of “people, information, technology and environment” in the information ecosystem, this paper determines the evaluation indicators of enterprise's open innovation community from the aspects of integrity and dynamics. Then, based on the improved analytic hierarchy process, the weight of each index is calculated, and a complete evaluation system of open innovation community is established. Finally, the fuzzy comprehensive evaluation method is used to conduct empirical research on Haier Open Partnership (HOPE) platform, analyze its ecological situation and existing problems and put forward the corresponding construction recommendations.

The application of HOPE platform shows that the evaluation index system built in this study has good applicability, and the whole research process and research method have certain reference value for future studies. At the same time, the study found that the HOPE platform has good ecological characteristics, but there are also some problems. This study can directly promote the construction of the platform.

This paper, for the first time, combines the information ecology theory with the open innovation community. The results demonstrate that the open innovation community is an information ecosystem, which can be evaluated ecologically. Furthermore, to ensure the calculation's scientific accuracy, the index weight is determined by constructing a judgment matrix based on expert questionnaires.

The study aims to introduce a cloud-based virtual reality (VR) approach and investigate its applicability and performance in aiding the remote design evaluation process by assessing the clients' convenience perception toward cloud-based VR-aided design evaluation (Cloud-based VR Approach) compared to 3D model-aided design evaluation (3D Model Approach) and rendering images-aided design evaluation (Image Approach).

A multicriteria comparative study was conducted with 26 university students using the “analytic hierarchy process” technique to compare the three approaches applied to home finishing material selection tasks based on the five “service convenience” dimensions, consisting of access convenience, decision convenience, transaction convenience, benefit convenience and post-benefit convenience.

The results indicated that the “Cloud-based VR Approach” was perceived to be more convenient than the “3D Model Approach” and the “Image Approach” based on the aspects of “decision convenience”, “transaction convenience”, “benefit convenience” and “post-benefit convenience”. The only aspect that the Cloud-based VR Approach was comparatively less convenient than the 3D Model Approach and Image Approach for the user was “access convenience”. Overall, the findings showed that the developed Cloud-based VR Approach had more potential than the conventional approaches in aiding the design evaluation process under ongoing social distancing measures requiring designers and clients to work remotely.

The disastrous impacts of the COVID-19 pandemic on logistical systems have resulted in massive disruptions to the construction industry worldwide. Various construction activities have been halted and most meetings moved online. Design evaluation conducted between clients and designers is one of the important activities affected by such an impact. Thus, this study presents the Cloud-based VR Approach as an innovative means to maintain essential ongoing activities and meeting of the current design evaluation approach with respect to the social distancing measures.

Significant developments in the service sector have been brought about by Industry 4.0. Automated digital technologies make it possible to upgrade existing services and develop modern industrial services. This study prioritizes critical factors for adopting Industry 4.0 in the Indian service industries.

The author identified four criteria and fifteen significant factors from the relevant literature that have been corroborated by industry experts. Models are then developed by the analytical hierarchy process (AHP) and analytical network process (ANP) approach to ascertain the significant factors for adopting Industry 4.0 in service industries. Further, sensitivity analysis has been conducted to determine the sensitivities of the rank of criteria and sub-factors to corroborate the results.

The outcome reveals the top significant criteria as organizational criteria (0.5019) and innovation criteria (0.3081). This study prioritizes six significant factors information technology (IT) specialization, digital decentralization of all departments, organizational size, smart services through customer data, top management support and Industry 4.0 infrastructure in the transition toward Industry 4.0 in the service industries.

The potential factors identified in this study will assist managers in determining strategies to effectively manage the Industry 4.0 transition by concentrating on top priorities when leveraging Industry 4.0. The significance of organizational and innovation criteria given more weight will lay the groundwork for future Industry 4.0 implementation guidelines in service industries.

Our research is novel since, to our knowledge, no previous study has investigated the potential critical factors from organizational, environmental, innovation and cost dimensions. Thus, the potential critical factors identified are the contributions of this study.

The poor capacity of prefabricated construction cost estimation is the essential reason for the low profitability of the general contractor. Therefore, this study aims to focus on the cost estimation of prefabricated construction as the research object. This research aims to enhance the accuracy of total project cost estimation for general contractors, ultimately leading to improved profitability.

This study used Vensim PLE software to establish a system dynamics model. In the modeling process, a systematic research review was used to identify cost-influencing factors; ABC classification and the analytic hierarchy process were used to score and determine the weights of influencing factors.

The total cost error obtained by the model is less than 2% compared with the actual value. It can be used to cost estimation and analysis. The analysis results indicate that there are 7 key factors, among which the prefabrication rate has the most significant impact. Furthermore, the model can provide the extreme range cost; the minimum cost can reduce by 13% from the value in the case. The factor's value can compose a cost control strategy for general contractors.

The cost of prefabricated buildings can be estimated well, and deciding the prefabrication rate is crucial. The cost can be declined by correct cost control strategies when bidding and subcontracting are in process. The strategies can follow the direction of the model.

A systemic, quantitative and qualitative analysis of cost estimation of prefabricated buildings for general contractors has been conducted. A mathematical model has been developed and validated to facilitate more effective cost-control measures.

The purpose of the present work is identification and prioritization of barriers to Lean Six Sigma (LSS) implementation in Indian manufacturing industries in the context of Industry 4.0 (I4.0) to surmount the impediments in the path of successful implementation.

In total, 27 barriers identified through critical review of literature and expert's opinion are evaluated with Cronbach's alpha values including item-total correlations or corrected item-total correlations (CITC) using statistical tool. Finally, 20 barriers were analyzed and ranked employing Fuzzy Analytical Hierarchy Process (FAHP).

The study depicts that “Lack of leadership, advisory and monitoring,” “Lack of clarity about economic benefits” and “Lack of integration of LSS with smart tools/I4.0” are potential barriers to drive the path for proper implementation of LSS in Industry 4.0 with due consideration of its technologies in Indian manufacturing industries.

The study provides better knowledge platform for academicians and researchers about hidden aspects of LSS implementation barriers in view of advanced manufacturing technologies. This research will help the practitioners to design their business plans in implementing new quality improvement tools to get advantage in current competitive environment.

The barriers are selected based on literature and opinion from industry and academic experts. Five major criteria are decided after incorporating inputs. The ranking of the barriers is attained by well standard mathematical technique. This will enable the practitioners to design strategies to eliminate the hindrances in order to shape the right path for effective implementation of LSS approach in view of advanced manufacturing technologies.