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The aim of this study is to evaluate the potential geographic locations for ecotourism activities and to select the best one among alternatives.

The proposed model consists of four sequential phases. In the first phase, different geographic criteria are determined based on existing literature, and data are gathered using GIS. On equal criteria weighing, alternative locations are determined using GIS in the second phase. In the third phase, the identified criteria are weighted using analytical hierarchy process (AHP) by various stakeholders of potential ecotourism sites. In the fourth phase, the PROMETHEE method is applied to determine the best alternative based on the weighted criteria.

A framework including four sequential steps is proposed. Using real data from the Black Sea region in Turkey, the authors test the applicability of the evaluation approach and compare the best alternative obtained by the proposed method for nine cities in the region. Consequently, west of Sinop, east of Artvin and south of the Black Sea region are determined as very suitable locations for ecotourism.

The first limitation of the study is considered the number of included criteria. Another limitation is the use of deterministic parameters that do not cope with uncertainty. Further research can be conducted for determining the optimum locations for different types of tourism, e.g. religion tourism, hunting tourism and golf tourism, for effective tourism planning.

The proposed approach can be applied to all area that cover the considered criteria. The approach has been tested in the Black Sea region (nine cities) in Turkey.

Using the proposed approach, decision-makers can determine locations where environmentally responsible travel to natural areas to enjoy and appreciate nature that promotes conservation have a low visitor impact and provide for beneficially active socioeconomic involvement of local individuals.

To the best knowledge of the authors, this is the first study which applies a GIS-based multi-criteria decision-making approach for ecotourism site selection.

With the escalation of economic and environmental concerns, there is growing interest in electric automobiles. Increased interest has led to the need for electric car-charging stations. The strategic placement of an appropriate number of electric vehicle charging stations is crucial for sustainability. A literature search was first undertaken to establish the criterion. This study aims to determine the number and variety of charging stations in several alternative districts according to the defined criteria.

Geographic Information System is utilized to collect data on the specific criteria of the selected research region. MACBETH was used to establish criterion weights. A mixed-integer mathematical model was developed to determine the optimal number of charging stations in a specified location based on the acquired data and criterion weights while adhering to predefined limits.

The results provided an integrated method for determining a sufficient number of charging stations by considering the chosen criteria and restrictions. This study seeks to enhance the existing literature on decision-making frameworks for determining the number of charging stations by utilizing an integrated Geographic Information System based on MACBETH, together with mixed-integer programming.

This study integrates qualitative and quantitative data to enhance managerial and practical implications. The application of MCDM and mathematical modeling presents managerial implications that affect growth, operational efficiency and sustainability objectives. Regarding practical implications, the proposed method helps managers evaluate potential locations based on factors, such as cost, geography, resource proximity, traffic patterns and power grid capacity.

Currently, the majority of cars powered by petroleum oil and its by-products have a substantial adverse effect on sustainability due to heightened emissions of hydrocarbons, contributing to global warming and noise pollution. In addition, with the rise in gasoline costs, alternative energy sources are being explored.

Saudi Arabia's 2030 vision targets an increase of 34% in non-oil revenue participation in the GDP, thus the need for automation and digital transformation. The Company ER is a market leader producing high-quality dairy products in the Kingdom and is a pioneer in the production industry. The company has recently increased the capacity of its milk factory to meet its vision. An investment was made to automate the pallet handling procedures at the milk factory to provide increased production for daily consumption. The new automation transition in Company ER's milk factory provides a unique opportunity to utilize lean management tools to improve the current automated processes before commercialization.

OEE (overall equipment effectiveness) will monitor losses for different operational losses in the new automated system and indicate system improvements, with 85% as the target. Based on DMADV (design, measure, analyze, design and validate) methodology, this study analyzes the entire automated pallet handling system. It uses lean tools to identify areas for improvement, identify waste elements and propose solutions to achieve Company ER's OEE targets.

In this paper, the outcomes will be presented as documented solutions that address the losses encountered in the production system, showing a 12.8% increase in the system's OEE.

Owing the time and resource constraint, this study only involved automated pallet handling procedures in a milk production facility. Hence, the generalization of the result is slightly limited. More studies in several different processes and sectors are required.

This study provided a valuable tool for researchers for gaining deeper understanding regarding the lean manufacturing and its implementation. For practitioners, it is useful to evaluate the degree of lean manufacturing tools in their material handling systems.

This study is the first attempt to develop lean manufacturing constructs for evaluating the automated pallet handling procedures in a milk production facility.

The purpose of this study is to measure the R&D performance of 81 cities in Turkey by using a scientific approach.

A four-step solution approach is developed for this problem. In the first step, a hierarchical structure of 14 indicators (including number of patents, publications, R&D expense, etc.) in three dimensions is constructed. In the second step, explicitly and implicitly spatial indicators such as university location and R&D manpower are mapped by using geographic information system (GIS). In the third step, a hybrid multi-criteria decision making model, namely, DANP that combines decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (ANP) techniques is applied to assign different level of importance to the indicators. In the last step, Višekriterijumska Optimizacijai kompromisno Rešenje (VIKOR) method is used to rank the performance of 81 cities. Obtained results are visualized using GIS to show the pros and cons of each city in terms of R&D performance.

Results of the paper show that Istanbul, Ankara and Konya are ordered as contenders of best R&D performances and on the contrary, Igdir, Sirnak and Tunceli are ordered as the worst R&D performances among 81 cities.

One limitation of the study can be the considered criteria. However, all the criteria are obtained from literature and experts; thus, the paper covers as much criteria as possible.

The proposed study may allow Ministry of Science, Industry and Technology of Turkey to formulate more effective strategies to improve cities’ R&D performance. In addition, any country can apply the same methodology for measuring the R&D performance of their cities by using their related data. As the worst R&D city performances belong to the eastern part of Turkey, it can be deducted that the socio-cultural structure of the eastern part of the country needs improvement.

To the best of the author’s knowledge, this is the first study which applies a GIS-based MCDM approach for R&D performance measurement. Thus, the value of this paper belongs to both literature and real life.

The purpose of this paper is to conduct a systematic literature review for industry 4.0 maturity modeling research studies to obtain a clear view of the current state-of-the-art. Identifying characteristics of the studies; gaps, limitations and highlighted features has been aimed to guide future research studies.

The study includes a systematic literature review conducted on Scopus, IEEE Xplore and Web of Science databases and 90 publications have been reviewed. A novel qualitative taxonomy has been constructed which aims to reduce the cognitive load of the readers.

While industry 4.0 maturity modeling is an emerging concept and taking researchers’ attraction, review studies are still in infancy. Current review papers are inadequate in getting a clear idea about the concept, especially from the perspective of guiding future researchers. By the conducted approach of classification conducted in this paper, it has been seen that there are some challenges for improving the industry 4.0 maturity modeling.

Findings represented in this study can serve academicians and practitioners to develop and/or improve industry 4.0 maturity models.

The study includes a novel classification for the reviewed papers. Constructed taxonomy is among the first and tabular representations instead of prose analogy that aims to simplify the review of papers.

The purpose of the paper is to investigate the effect of religiosity and culture on Nigerian Muslim consumer’s intention to purchase luxury goods.

The survey included a sample of 372 Nigerian Muslims from the middle and upper-income groups who live in Lagos and Kano in Nigeria.

Plenty of luxury brands are seeking to find ways to overgrow in emerging markets. Focussing on Nigeria, this study identifies Nigerian people’s cultural orientation, religious beliefs and examines the social and personal variables affecting the consumers’ purchasing intention for luxury goods. This study stresses that Nigerian consumers’ intention to purchase luxury products are impacted by attitude, subjective norms and culture. However, Nigerian people’s intention to purchase luxury goods is not influenced by religious beliefs and Islam morals. While culture has a significant relationship with both attitudes towards behaviour and subjective norms, the religious beliefs encourage both subjective norms and a positive attitude towards the behaviour.

This study has limitations in connection with two of its major objectives. The study applied the perspective of Nigerian Muslims. Thus, the research will not be able to clarify the fact that beyond this limited geographical area. Future research may widen the focus on cultural and religious beliefs on the intention to purchase luxury goods by adding other elements, such as normative beliefs and attitudinal beliefs.

The findings of the research define some implications for marketers with regard to the importance of social norms and religion in point of increasing the purchasing intention for luxury goods. Findings reflect that Nigerian consumers are impacted by subjective norms and cultural orientation. This means that luxury consuming is seen to achieve social recognition in the society. These results show that improving social acceptance through luxury goods consumption may create profitable outcomes for luxury brand firms.

The attractive findings of the study proposed that luxury brand managers should balance their investment in terms of the use of word-of-mouth, reference groups and fashion magazines to develop a favourable attitude towards luxury brands through. Although cultural values, references groups and consumer’s beliefs critically matter for luxury consuming, religious beliefs of Nigerian consumers have no effect on consumer’ purchase intention for a luxury product.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

Since Industry 4.0 (I4.0) is a new idea in Bangladesh, this study supports I4.0 adoption. Companies struggle to implement I4.0 and fully profit from the fourth industrial revolution’s digital transformation due to its novelty. Although barriers to I4.0 adoption are thoroughly studied, the literature has hardly examined the many aspects that are crucial for I4.0 adoption in Bangladesh’s Ready-Made Garment (RMG) industry. So, the purpose of this study is to investigate the barriers of adopting I4.0 in relation to Bangladesh’s RMG industries to enhance the adoption of I4.0 by developing a framework. Ultimately, the goal of this research is to improve the adoption of I4.0 in Bangladesh.

Through a comprehensive analysis of the existing research, this paper aims to reveal the barriers that must be overcome for I4.0 to be adopted. For evaluating those barriers, a decision analysis framework based on the combination of Delphi technique and Decision-Making Trial and Evaluation Laboratory (DEMATEL) method has been developed. The use of DEMATEL has led to a ranking model of those barriers and a map of how the barriers are connected to each other.

The findings reveal that “I4.0 training”, “Lack of Motivation” and “Resistance to Change” are the most significant barriers for adopting Industry 4.0 in RMG sector of Bangladesh based on their prominence scores.

These findings will help the people who make decisions in the RMG industry of Bangladesh, such as company owners, managers and the executive body, come up with a plan for putting I4.0 practices into place successfully. The decision-making framework developed in this research can be utilized by the RMG industry of Bangladesh and other similar industries in developing countries to figure out how important each barrier is for them and how to get rid of them in order of importance.

As far as the authors are aware, there has not been a comprehensive study of the barriers inhibiting the adoption of I4.0 within the scope of Bangladeshi RMG industry. This work is the first to uncover these barriers and analyze them using the combination of Delphi technique and DEMATEL.

Industry 4.0 is characterised by the exponential pace of technological innovations compelling organisations to transform or be displaced. Industry 4.0 transformation of construction enterprises lacks systematic guidance and notable earlier studies have utilised maturity models to map transformation of enterprises. This paper proposes a conceptual maturity model for construction enterprises for business scenarios leading to Industry 4.0.

The requirements for designing maturity models, including comparison with existing models and scientifically documenting the design process, make Systematic Literature Reviews (SLR) appropriate. Two systematic literature reviews (SLRs) are conducted to shortlist a total of 95 papers, which are subjected to subsequent content analysis.

The first SLR identifies the following process categories as critical levers of industry 4.0 maturity; data management, people and culture, leadership and strategy, collaboration and communication, automation, innovation and change management. The second SLR ascertains that the existing maturity models in construction literature do not adequately correspond to Industry 4.0 business scenarios with limited emphasis on data management, automation, change management and innovation. The findings are assimilated to propose a conceptual Smart Modern Construction Enterprise Maturity Model (SMCeMM).

The paper systematises the transformation of construction enterprises in Industry 4.0 and leads to state-of-the-art development of Industry 4.0 and maturity model research in construction. The proposed conceptual model addressed both the demands of the construction industry as well as what is required to navigate Industry 4.0 better.

This paper aims to identify potential barriers to Industry 4.0 adoption for manufacturers and examine the changes that must be made to production processes to implement Industry 4.0 successfully. It aims to develop technology by assisting with the successful implementation of Industry 4.0 in the manufacturing process by using smart system techniques.

Multiple case studies are used in this paper by using the smart system and Matlab, and semi-structured interviews are used to collect qualitative data.

Standardization, management support, skills, and costs have been cited as challenges for most businesses. Most businesses struggle with data interoperability. Complexity, information security, scalability, and network externalities provide challenges for some businesses. Environmental concerns are less likely to affect businesses with higher degrees of maturity. Additionally, it enables the Technical Director’s expertise to participate in the measurement using ambiguous input and output using language phrases. The outcomes of the numerous tests conducted on the approaches are extensively studied in the provided method.

In this research, a multiple-case study aims to carry out a thorough investigation of the issue in its actual setting.