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The manufacturing sector is witnessing the need to continuously improve overall performance by eliminating inefficiencies in the supply chain. The adoption of lean concepts to address wasteful or non-value-adding activities in the supply chain is crucial. This article determines key factors of lean supply chain management (LSCM) for continuous improvement in the manufacturing sector.

The methodology comprises three steps. The first step identifies critical factors of LSCM in manufacturing from prior research and a series of expert consultations. Critical factors are identified and validated that industries can leverage to attain their lean goals. The second step uses the decision-making and trial evaluation laboratory (DEMATEL) method to determine the causal relationship among the factors. DEMATEL analysis categorizes factors into cause and effect, which will assist industry personnel in decision-making. The third step involves further data analysis to visualize the importance of the most critical factors. It develops a machine learning (ML) model in the form of a decision tree that helps in assessing the factors into cause or effect groups via a threshold value of expert ratings.

IT tools, JIT manufacturing and material handling and logistics form the most critical factors for LSCM implementation.

The analysis from DEMATEL and ML together will be beneficial for manufacturing practitioners to improve the supply chain performance based on the identified factors and their criticality towards LSCM implementation.

The purpose of this paper is to identify and prioritise supply chain finance (SCF) adoption enablers and develop a novel comprehensive framework to select supplier firms based on their SCF adoption capability.

The study deploys a three-phase method to identify and prioritise SCF adoption enablers, followed by developing a model to select suppliers according to their SCF adoption capability. An extensive literature review, followed by a Delphi approach-based expert interview, has been used to finalise the enablers. Using the Best Worst Method and the VIsekriterijumsko KOmpromisno Rangiranje technique, a supplier selection model has been developed in the context of a case company.

The financial health and technological advancement variables received the top priority, followed by collaborative efficiency, whereas the human resources and organisational variables received the slightest significance. A supplier selection framework has also been developed by using the adoption capability of these factors by the supplier partners. In this study’s model, Supplier 4 exhibited better SCF adoption capability and received the top priority.

Manufacturing supply chains in a developing country are the scope of the current study. Extensive future studies are required to derive a global consensus.

The proposed framework of this study can be used to select supplier firms based on their SCF adoption capability. Policymakers can emphasise the most critical enablers of SCF adoption to assist small supplier firms to be a part of the advanced global supply chains.

The current study established a novel comprehensive framework for supplier selection based on the Supply Chain Finance adoption capability of MSME supplier firms.

This paper seeks to establish design quality indicators (DQIs) that can be utilized for assessing the design of community centers, with an emphasis on the technical, functional, and behavioral performance domains.

A comprehensive literature review resulted in identifying 79 DQIs for community centers. A three round Delphi evaluation approach was utilized to rate the importance of the DQIs through their relative importance index (RII) values. The assessment of the DQIs involved a diverse group of stakeholders including facilities managers, architects/engineers (A/Es), community centers’ staff, and regular visitors of community centers.

The majority of the established DQIs were considered to be either “Very Important” or “Important”.

The established DQIs can be utilized to identify best practices in the design of community centers and benchmark the performance of different community centers.

The design quality of community centers could significantly impact the community's quality of life and user experience. The development of DQIs provides for enhanced accountability and improved service delivery for the communities they serve. This enables community centers to be more effective, efficient, and responsive to the needs of the users they support.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

This study aims to enhance the success of Sponsored Institutional R&D Projects (SIRPs) by investigating the influence of risk dimensions over four criteria Cost overrun, Time overrun, Schedule overrun, and Quality of projects. The study identifies risk dimensions and prioritizes and explores causal relationships to guide risk mitigation strategies during project execution.

This study was conducted with qualitative data obtained through a systematic questionnaire from 10 domain experts associated with SIRPs. Through an extensive literature review, the study identifies the ten risk dimensions, Fuzzy TOPSIS was employed for prioritizing the explored risk dimensions and Fuzzy DEMATEL explored the qualitative causal relationships among these dimensions. The sensitivity analysis was conducted to validate the robustness of findings by adjusting the weightage assigned to experts.

The findings reveal financial risk as the highest ranked and business risk as the least influential among identified dimensions. The study also highlights management risk as the most significant, followed by business risk and sensitivity analysis concludes that the findings are robust, lacking significant judgment bias.

This study contributes to risk management strategies for SIRPs, to ensure timely completion within the allocated budget. The findings of the study can be implemented in other such SIRPs. The study also informs funding agencies' policies and project monitoring mechanisms and advancing project management practices

Its originality lies in being the first to systematically identify and prioritize risk dimensions, adding significant value to SIRP management and academic discourse on project management and risk analysis.

The global resolution of embracing dynamic and intertwined production systems has made it necessary to adopt viable systems like circular economy (CE) to ensure excellency in the business. However, in emerging countries, it is challenging to implement the CE practices due to the existing problems in the supply chain network, as well as due to the vulnerable financial condition of the business after the deadly hit of COVID-19. The main aim of this research is to determine the barriers to implementing CE considering the recent pandemic and suggest strategies to organizations to ensure CE for a cleaner environment and greener economy.

After an extensive literature review and validation from experts, 24 sub-barriers under the class of 6 main barriers are finalized by Pareto analysis, which is further analyzed via the best-worst method to determine the weight and rank of the barriers Further, fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the proposed startegies to overcome the analysed barriers.

The results identified “unavailability of initial funding capital”, “need long time investment”, “lack of integrating production system using advance technology” and “lack of strategic planning” as the most acute sub-barriers to CE implementation. Further, fuzzy TOPSIS method is used to suggest the best strategy to mitigate the ranked barriers. The results indicated “integrated design facility to CE”, “ensuring large scale funding for CE facility” as the best strategy.

This study will motivate managers to implement CE practices to enjoy proper utilization of the resources, sustainable benefits in business, and gain competitive advantage.

Periodically, a lot of work is done on CE practices but none of them highlighted the issues in the domain of the leather products industry (LPI) and COVID-19 toward achieving sustainability in production and consumption. Thus, some significant barriers and strategies to implement CE for achieving sustainability in LPI are highlighted in this study, which is a unique contribution to the literature.

The author identifies the traits of consumer resilience in emerging markets, classifies these major traits into five categories and analyses the influence relationships among them with distinctive focus on the psychological and personal resilience aspects.

The influence relations among the traits of consumer resilience from an expert perspective were identified with typical focus on electronic supply chains, and later the same was analysed through an intelligent influence modelling method, the grey causal modelling (GCM).

The major traits were analysed using the GCM, where the cause–consequence relations were observed for various objectives and the situational effects are noted. By constructing a magnitude plot and further a causal magnitude table, the important influence traits of consumer resilience for the considered case were observed and the same were auxiliary validated using an interpretive structural modelling (ISM) based approach.

As perceived from the results, it is evident that social support and recommendations from customers emerge as the principal influence traits of consumer resilience from an expert perspective, considering the case. The study can be further extended empirically to validate the findings.

Altogether, the author can recommend for practitioners that the influence of family, society, friends, peers as well as ratings from the customers can determine the level of consumer resilience. Hence, practitioners of customer relationship management can focus on improving the product and brand awareness among customers, so that more customers may recommend for typical products.

Consumer resilience depend on several factors, where the author has identified 25 major traits of the same and classified them into five major categories, including individual psychological factors, individual attitudes, individual socio demographic factors, micro environmental factors and macro environmental factors and the influence relations among them were studied from an expert perspective.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

There is an ongoing discussion on tools that can lead to sustainable tourism, as well as attempts to implement them. In the selection of tools, the attitudes of residents – local stakeholders and their degree of acceptance of such tools should be analysed and taken into account. Some cause conflicts, and hence, the purpose of this study is the comparative analysis of three cities (Prague, Krakow and Braga).

Analysis of the basic types of conflicts was conducted using the division proposed by Moore. The research was conducted among residents – experts representing the tourism sector. Based on the literature review, three hypotheses were formulated. Statistical tests were used to analyse the results.

The results showed a strong impact of the conflict of information and the interests of those dependent on the degree of development of the city’s tourist function. It was established that in the process of achieving sustainable tourism, to minimize conflicts, the following are necessary: paying attention to communication and the involvement of local communities, creating attractions that benefit both residents and visitors, measuring and monitoring tourist traffic, supporting initiatives for new tourist offers and initiating discussions on development problems, and setting common goals for all residents.

The research was conducted during the pandemic and is based on the opinions of experts indicated by the city authorities. While the attitudes of the inhabitants towards the development of tourism were recognized in earlier studies, the awareness of tourists and their readiness to accept limitations related to respecting the needs of the inhabitants were not examined. This aspect may be an interesting direction for further research. A limitation of this research is the small scope of the study, caused both by the restrictions in force during the research period (related to the COVID-19 pandemic) and also by the inability to conduct in-depth interviews with experts. It should also be noted that among the experts participating in the research were tourist entrepreneurs directly interested in rebuilding tourism after the pandemic. Due to this, their opinions may have been biased, but there is no way to prove or disprove this. However, the answers gathered were considered collectively; therefore, the opinions obtained were considered to be objective. Attempts to balance tourism so far have focused mainly on limiting the access of tourists to attractions and tourist areas and introducing (or increasing) admission fees. It is still too early to assess the effectiveness of such tools, hence the lack of scientific analyses of implemented tourism policies.

The role and tasks of institutions managing tourism in cities will probably also change, in particular, so-called destination management organizations. The current declarations indicate the need to respect inhabitants and take measures to limit conflicts arising in the context of the development of the tourist function. However, there is no empirical evidence of the positive results achieved.

The results will allow the implementation of tourism balancing tools that are accepted by the local community.

The selection of the historical cities and the posing of a research problem based on the same tool allowed for comparative inference. The results can help shape tourism management in cities and the choice of tools for their sustainable development.

关于实现可持续旅游的工具以及运用这些工具的尝试始终是学界热议的话题。 在选择工具时, 应当分析和考虑居民和当地利益相关者的态度以及他们对工具的接受程度, 因为有些会引起冲突。基于此, 本文的目的是对三个城市（布拉格、克拉科夫、布拉加）的居民-当地利益相关者冲突进行比较分析。

本文采用摩尔提出的划分方法对冲突的基本类型进行了分析。 该研究是在居民——代表旅游部门的专家中进行的。文章基于文献综述提出了三个假设, 并 使用统计测试来分析结果。

结果表明, 信息冲突和利益冲突的强烈影响取决于城市旅游功能的发展程度。在实现可持续旅游的过程中, 为了尽量减少冲突, 有必要采取以下措施：注重当地社区的参与和沟通, 创造有利于居民和游客双方的景点, 测量和监测旅游流量, 支持旅游产品创新并发起针对发展问题的讨论, 同时为所有居民设定共同目标。

本文选择历史名城作为案例地, 加之基于同一工具提出的研究问题, 使得本研究具备用于比较推断的条件。 研究结果有助于塑造城市的旅游管理以及引导可持续发展工具的选择。

Hay un debate en curso sobre las herramientas que pueden conducir al turismo sostenible, así como los intentos de implementarlas. En la selección de herramientas, se deben analizar y tener en cuenta las actitudes de los residentes – agentes interesados locales y su grado de aceptación de dichas herramientas. Algunas provocan conflictos, de ahí que el objetivo de este artículo sea el análisis comparativo de tres ciudades (Praga, Cracovia, Braga).

El análisis de los tipos básicos de conflictos se realizó utilizando la división propuesta por Moore. La investigación se llevó a cabo entre residentes, expertos que representan el sector turístico. A partir de la revisión de la literatura se formularon tres hipótesis. Se utilizaron pruebas estadísticas para analizar los resultados.

Los resultados mostraron un fuerte impacto del conflicto de información y los intereses de quienes dependen del grado de desarrollo de la función turística de la ciudad. Se estableció que en el proceso de lograr un turismo sostenible, para minimizar los conflictos es necesario: prestar atención a la comunicación y a la implicación de las comunidades locales, crear atractivos que beneficien tanto a los residentes como a los visitantes, medir y monitorear el tráfico turístico, apoyar iniciativas de nuevas ofertas turísticas e iniciar debates sobre los problemas de desarrollo, y establecer objetivos comunes para todos los residentes.

La selección de las ciudades históricas y el planteamiento de un problema de investigación basado en la misma herramienta permitieron realizar una inferencia comparativa. Los resultados pueden ayudar a configurar la gestión del turismo en las ciudades y la elección de herramientas para su desarrollo sostenible.

Exploring the determinants of a winery brand reputation (BR) and how those determinants interact is vital for the sustainable development of wineries as well as the growth of the wine industry as a whole. This study aims to test an integrated model to better understand the observed measurement constructs of winery brand reputation, including collective reputation (CR), wine label (WL), expert opinion (EO), social media advertising (SMA) and consumer wine knowledge (CWK).

In-depth interviews, an expert panel review and a pilot study were conducted to examine and improve the observed variables. A questionnaire survey was conducted as the main data source for the study. A total of 616 valid questionnaire responses were collected from 102 cities in mainland China and Hong Kong, Macao and Taiwan from December 2021 to April 2022. Structural equation modeling was conducted for the data analysis.

This study supported 9 of the 18 proposed theoretical hypotheses. WL, EO and SMA had positive effects on BR. CWK was found to have a moderating effect on the relationship between expert opinions/social media advertising and brand reputation.

The results of this study can guide wine practitioners, researchers and administrators in brand development, label regulation and consumer education.

To the best of the authors’ knowledge, this is the first attempt to examine the determinants of winery brand reputation among Chinese wine consumers. This study explains the mechanism of winery brand reputation, demonstrating the dynamics and effects of the observed measurement constructs on brand reputation.