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The aim of this study is to examine the agency problems that arise between retail property owners and outsourced facility management (FM) service vendors in Ghana.

This study was carried out using telephone and face-to-face interviews. Nine facility managers (n =9) and six retail property owners (n = 6) purposively selected participated in the interviews. The responses from the interviews were analysed using content analysis. To begin with the analysis, the recorded audio for each respondent during the interviews was transcribed to augment what was written during the interviews. The next step was the development of a coding framework where each of the agency problems was assigned unique codes and grouped under themes. Each response was assigned a predefined code based on the agency problems identified in the literature. The research team discussed the consistency of the thematic codes assigned to each of the responses to ensure that each response was captured under the appropriate agency problem theme it best represents.

The results showed that agency problems in FM outsourcing in the Ghanaian retail sector are related to disagreement on expenditure associated with maintenance and repairs and improper tenant information sharing and use by FM service providers. Based on the findings, it is recommended that property owners explore the mixed approach to FM to mitigate the risks of complete outsourcing of FM services. It is also recommended that a clear path on how tenant information can be shared be pre-agreed in FM contracts.

This study provides new literature relating to agency problems in outsourcing and may be the first of its kind for FM in the Ghanaian retail industry. The findings could serve as a starting point for service providers and their principals to find common grounds to understand each other and mitigate the agency problems that could arise and their overall impact on performance.

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.

Supply chain disruptions have a significant impact on overall project delivery. This study aims to identify the supply chain disruptive factors and develop a framework to mitigate the disruptive effects on the supply chain. Covid-19 and Brexit disruption and their longevity effects in the short, medium and long term on the supply chain are relied upon to develop the framework.

The study adopted a mixed-method approach with a sequential explanatory design. The main disruptive factors were identified through a literature review, and key factors were selected through a focus group exercise. A questionnaire survey was carried out to sample opinions from the practitioners; 41 questionnaires were received and analysed using the relative importance index (RII) method for ranking the factors and percentage frequency distribution to determine the longevity effects. Five follow-up semi-structured interviews were conducted over the telephone and later transcribed.

The results of Covid-19 disruption indicate that material cost increase ranked first (RII: 0.863), logistics cost increase and supply chain interaction ranked second and third, respectively. They have long-term, medium-term and short-term longevity effects, respectively. The lowest-rated factors were communication (RII: 0.561), staff shortages (RII: 0.629) and impact on relationships (RII: 0.639). The three most ranked Brexit disruptive factors are supply chain interaction (RII: 0.775), material cost increase (RII: 0.766) and logistic and haulage delay (RII: 0.717). The first two factors have long-term effects, and the logistics and haulage delays have a medium-term impact. The mitigating solutions suggested in the framework are collaborative working, stronger resilience to external forces and better transparency and communication that will lead to good relationships among the supply chain members.

The scope of the study was limited to the UK construction industry; however, the pandemic effect on supply chain can serve as critical learning curve in other developed and developing countries.

The study will help the government and construction firms to understand the focal areas of importance in solving the supply chain disruption problems based on the effects of Brexit and Covid-19. The research would be useful in ensuring the proactive involvement of the government and contracting firms in their preparedness for similar events in the future. The results could be interpreted for critical learning in other developed/developing countries.

Identifying and ranking the supply chain disruptive factors affecting the small‐ and medium‐sized enterprises (SMEs) in the UK construction industry has been the focal point of this study. The study also proposes a simple but effective framework comprising the highly ranked factors, their longevity effects and mitigating measures. This will help the SMEs manage future/similar external events affecting the supply chain.

This research studies the development of the evolving dynamic system model and explores the important elements or factors and what detailed attributes are the main influences model in achieving the success of a business, industry and management. It also identifies the real and major differences between static and dynamic business management models and the detailed factors that influence them. Later, this research investigates the benefits/advantages and limitations/disadvantages of some research studies. The studies conducted in this research put more emphasis on the capabilities of system dynamics (SD) in modeling and the ability to measure, analyse and capture problems in business, industry, manufacturing etc.

The research presented in this work is a qualitative research based on a literature review. Publicly available research publications and reports have been used to create a research foundation, identify the research gaps and develop new analyses from the comparative studies. As the literature review progressed, the scope of the literature search was further narrowed down to the development of SD models. Often, references to certain selected literature have been examined to find other relevant literature. To do so, a supporting tool (that connects related articles) provided by Google Scholar, Scopus, and particular journals has been used.

The dynamic business and management model is very different from the static business model in complexity, formality, flexibility, capturing, relationships, advantages, innovation model, new goals, updated information, perspective and problem-solving abilities. The initial approach of a static system was applied in the canvas business model, but further developments can be continued with a dynamic system approach.

Based on this study, which shows that businesses are developing more towards digitalisation, wanting the ability to keep up with the era that is moving so fast and the desire to increase profits, an instrument is needed that can help describe the difficulties of the needs and developments of the future world. This instrument, or tool of SD, is also expected to assist in drawing future models and in building a business with complex variables that can be predicted from the beginning.

This study will contribute to the SD study for many business incubator research studies. Many practical in business incubator management to have a benefit how to achieve the business performance management (BPM) in SD review.

The significant differences between static and dynamics to be used for business research and strategic performance management. This comparative study analyses some SD models from many authors worldwide. Their goals behind their strategic business models and encounter for their respective progress.

This study aims to prevent occupational accidents occurring in the manufacturing industry by means of touch sensors. When the occupational accidents occurring in the manufacturing industry around the world are examined, it is seen that approximately 88% of occupational accidents occur from “dangerous movement” and 10% from “dangerous situation.” Although some studies related to safety culture studies, safety studies in design and collective or personal protective measures have been started, they have not been brought to an adequate level. It is observed that studies on dangerous movements continue even in many developed countries. In this study, first of all, a literature study was conducted. Occupational accidents experienced in the manufacturing sector in Turkey have been examined. In line with these investigations, a prototype circuit protection system has been developed that can prevent accidents caused by dangerous movement. With the circuit, its applicability and effectiveness were measured by conducting experiments on different manufacturing machines. The prototype circuit applied in this paper was made based on the logic of protective measures made on sawstop machines used in different sectors. In the experimental study conducted, it was observed that in 30 experiments conducted with a prototype on ten separate manufacturing machines, it stopped the machines 26 times at minimum and 29 times at maximum. On average, when looking at the system efficiency values, it was seen that the system was 81.6% effective, and it was observed that positive results could be obtained when converted into a real product.

In this study, their contribution to the prevention of work accidents caused by presses and rotary accents from machines used in the manufacturing industry by means of touch sensors used in Industry 4.0 was examined.

With Industry 4.0, different automation systems began to be switched in many areas and sectors. Studies have started on different sensors used also in Industry 4.0 in occupational health and safety studies, but it is seen that they have not been applied at an adequate level. It should be designed in such a way as to prevent errors or stop these errors in the studies performed. Today, sensors are produced at much lower costs than before. In addition, the constantly developing technology provides great convenience for these applications.

This study was applied for press and cylinder machines from manufacturing machines. This study has been tried for machines producing a maximum pressure of 300 tons.

A prototype was designed. Trials were done on some machines by prototype. There could be improve and find different solutions for safety problems in the industry with this perspective.

The aim of this article states that in each stage of the industrial revolution, only a few initiatives have been real game changers. In Industry 3.0, “Internet of Information” has transformed the business landscape via connectivity and communications. Enterprises could come together to spur innovation in a cooperative or competitive manner. In Industry 4.0, the “Internet of Value” has shown considerable benefits; and, blockchain technology is expected to touch all layers of a business ecosystem, and the construction industry is not an exception.

This study aims to answer the “How do enterprise blockchain solutions contribute to the vibrancy of the construction ecosystem from social, economic, and environmental aspects?” Following a comprehensive literature review, the Grey Ordinal Priority Approach (OPA-G) is employed in multiple criteria decision analysis (MCDA). OPA-G can select functionally rich enterprise blockchain solutions that meet the needs of the future construction industry, while there is uncertainty in the input data.

The results from the case study show that organization under observation welcomes an enterprise blockchain solution that delivers services related to “renewable energy certificates” in the context of “smart cities and built environment”. Employing high-ranked blockchain solutions brings vibracy and sustainability to construction ecosystem in terms of “C₆. decentralized finance and investment,” “C₃. multi-party and cross-industry collaboration,” and “C₈. data-driven value creation”.

At the micro level, blockchain solutions automate processes, streamline operations, and build new capacities on a new business model. At the macro level, blockchain creates a vibrant ecosystem based on transparency, decentralization, consensus-based democracy, interoperability, etc. Indeed, the capability of blockchain solutions at an enterprise scale (enterprise blockchain solutions) can shape a new construction ecosystem. The practical implications of current research are preparing executives for a fundamentally different next normal in construction.

Through the use of the Markov Decision Model (MDM) approach, this study uncovers significant variations in the availability of machines in both faulty and ideal situations in small and medium-sized enterprises (SMEs). The first-order differential equations are used to construct the mathematical equations from the transition-state diagrams of the separate subsystems in the critical part manufacturing plant.

To obtain the lowest investment cost, one of the non-traditional optimization strategies is employed in maintenance operations in SMEs in this research. It will use the particle swarm optimization (PSO) algorithm to optimize machine maintenance parameters and find the best solutions, thereby introducing the best decision-making process for optimal maintenance and service operations.

The major goal of this study is to identify critical subsystems in manufacturing plants and to use an optimal decision-making process to adopt the best maintenance management system in the industry. The optimal findings of this proposed method demonstrate that in problematic conditions, the availability of SME machines can be enhanced by up to 73.25%, while in an ideal situation, the system's availability can be increased by up to 76.17%.

The proposed new optimal decision-support system for this preventive maintenance management in SMEs is based on these findings, and it aims to achieve maximum productivity with the least amount of expenditure in maintenance and service through an optimal planning and scheduling process.

The proposed model aims to consider the flying hours as a criterion to initiate maintenance operation. Based on this condition, aircraft must be checked before flying hours threshold is met. After receiving maintenance service, the model ignores previous flying hours and the aircraft can keep on flying until the threshold value is reached again. Moreover, the model considers aircraft age and efficiency to assign them to flights.

The aircraft maintenance routing problem (AMRP), as one of the most important problems in the aviation industry, determines the optimal route for each aircraft along with meeting maintenance requirements. This paper presents a bi-objective mixed-integer programming model for AMRP in which several criteria such as aircraft efficiency and ferrying flights are considered.

As the solution approaches, epsilon-constraint method and a non-dominated sorting genetic algorithm (NSGA-II), including a new initializing algorithm, are used. To verify the efficiency of NSGA-II, 31 test problems in different scales are solved using NSGA-II and GAMS. The results show that the optimality gap in NSGA-II is less than 0.06%. Finally, the model was solved based on real data of American Eagle Airlines extracted from Kaggle datasets.

The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.

This study aims to provide a new overview and opportunities of blockchain (BCT), financial technology (fintech) and knowledge management (KM) over the past ten years. Its focus is on their potential to drive new value creation and innovation processes within the digital landscape of the tourism and hospitality.

This systematic literature review and sociotechnical approach employs a literature analysis, analyzing and synthesizing 62 relevant articles published in the past decade form e-databases (Web of Science and Scopus).

This study reveals that researchers frequently discuss the potential advantages and challenges of BCT, fintech and KM in this industry. These include establishing systems that prioritize transparency and traceability, addressing blockchain security concerns, enhancing financial transaction efficiency and trustworthiness, and promoting innovation and improvement through KM strategies. Furthermore, this review suggests that the application of blockchain, fintech and KM has the potential to create new markets and opportunities in the tourism and hospitality industry. This study provides insights into the state and implementation of technology-based and knowledge-based for tourism and hospitality in times of crisis and digitization era.

Shifting to new lens (refers to sociotechnical theory), from technology adoption strategy, it is important to stay updated with emerging technologies such as BCT and fintech and upcoming technologies trends must align with tourism and hospitality business objectives, customer expectations and market demands. From the socio-dimension, KM is not confined to technological tools alone. Instead, it is a strategic approach that emphasizes fostering a culture of open communication, collaboration and knowledge sharing within the team of tourism and hospitality industry.

Through a literature review approach, this study establishes a new foundation in tourism and hospitality such as analyzing research gaps, understanding benefits and challenges, supporting methodologies/theoretical frameworks and informing the future research opportunities. Additionally, a novel contribution is the inclusion of sociotechnical approach that is allocated into socio or knowledge resources perspective (knowledge management), and technical or technology perspective (blockchain and fintech) that drives tourism and hospitality innovation.

This paper aims to explore the optimization process involved in the aircraft maintenance allocation and packing problem. The aircraft industry misses a part of the optimization potential while developing maintenance plans. This research provides the modeling foundation for the missing part considering the failure behavior of components, costs involved with all maintenance tasks and opportunity costs.

The study models the cost-effectiveness of support against the availability to come up with an optimization problem. The mathematical problem was solved with an exact algorithm. Experiments were performed with real field and synthetically generated data, to validate the correctness of the model and its potential to provide more accurate and better engineered maintenance plans.

The solution procedure provided excellent results by enhancing the overall arrangement of the tasks, resulting in higher availability rates and a substantial decrease in total maintenance costs. In terms of situational awareness, it provides the user with the flexibility to better manage resource constraints while still achieving optimal results.

This is an innovative research providing a state-of-the-art mathematical model and an algorithm for efficiently solving a task allocation and packing problem by incorporating components’ due flight time, failure probability, task relationships, smart allocation of common preparation tasks, operational profile and resource limitations.