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This study aims to investigate the impact of varying the number of minimum quantity lubrication (MQL) nozzles, wind pressure, spindle speed and type of lubrication on surface roughness, fatigue life and tool wear in the drilling of aluminum alloy 6061-T6.

The effect of using different lubricants such as palm oil, graphene/water nanofluid and SiO₂/water in the MQL method was compared with flood and dry methods. The lubricant flow and feed rate were kept constant throughout the drilling, while the number of nozzles, wind pressure and spindle speed varied. After preparing the parts, surface roughness, fatigue life and tool wear were measured, and the results were analyzed by ANOVA.

The results showed that using MQL with four nozzles and graphene/water nanofluid reduced surface roughness by 60%, followed by SiO₂ nanofluid at 56%, and then by palm oil at 50%. Increasing the spindle speed in MQL mode with four nozzles using graphene nanofluid decreased surface roughness by 52% and improved fatigue life by 34% compared to the dry mode. SEM results showed that tool wear and deformation rates significantly decreased. Increasing the number of nozzles caused the fluid particles to penetrate the cutting area, resulting in improved tool cooling with lubrication in all directions.

Numerous attempts have been made worldwide to eliminate industrial lubricants due to environmental pollution. In this research, using nanofluid with wind pressure in MQL reduces environmental impacts and production costs while improving the quality of the final workpiece more than flood and dry methods.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0021/

This research presents a technology roadmap for social banking in Iran. Technology roadmapping is a tool for decisionmakers to identify, assess and choose between different strategic options to achieve the best technological objectives and help companies and industries to better understand their market and technological choices. As social banking is in its infancy, it could embody different aspects. Therefore, to be successful in field of social banking, banks should define specific capabilities based on their capacities to create their own model. A social banking roadmap provides a comprehensive plan for banks to design products and services based on their capacities and create required programs for their implementation and improvement.

This paper outlines the steps for creating a technology roadmap to develop social banking services of one of Iran’s private banks. Different methods were used to implement each step mainly based on expert panels and carrying out polling and survey research among banking and IT experts.

Technology roadmaps pay special attention to the challenges and the level of capabilities (both technical and social) to develop technologies and services specially for developing countries. The level of capabilities and absorptive capacity will determine the direction of technology development. Hence, banks should design their business plan and roadmap based on their background and capabilities, state of market, their status and goals. Policymakers should help increase cooperation, financial transparency, information and payments security via appropriate legislations.

The number of banks that have entered the social banking field is limited, and as a result, activities that have been carried out in this area in the country are limited too. Therefore, there was limited access to information as well as related studies. This research has tried to extract all the contents of the roadmap. Some sub-topics such as technologies have been dealt with to a lesser depth because of the complexity in identifying and assigning each of technologies to the service features. The technology roadmap experiences in the country are limited, and it was not possible to study the existing roadmaps with regard to their confidentiality. Developing a technology roadmap requires using expert panels and conducting multiple workshops with stakeholders from private sectors, universities and industries. In this research, because of low resources, the panels were confronted with limited continuous attendance as well as the accumulation of different stakeholders.

The research results provided strategies to inform, encourage and finance banks and other businesses to use social networks appropriately and effectively. These strategies can be categorized into the actions banks should take to expand social banking in the country and the actions policymakers should take into account in this regard. They are described as follows. Banks’ strategic actions include: provide training to staff on how employees should interact with customers on social networks encompassing general information and education about services, benefits and how to use social banking services for customers and society; motivate customer participation in social banking networks; convergence and integration of various offline and online channels; focus on core banking to expand competitiveness; pay attention to sustainable and green development in providing social banking services; analysis of the competitive environment in banking and other financial industries; designing a portfolio of social services for customers and allocation of budget and resources for development of social banking services and participation with other institutions and operators in providing financial and non-financial services. Policymakers’ actions include: adopt motivational policies for participation and use of social networks; education and awareness for different stakeholders; review and update the policies and rules of IT and social networks; establish appropriate laws to protect rights of employees and customers; invest in market and university studies on social banking and related services; develop policies for using in-house software and update rules and policies for small- and medium-sized enterprises.

Social banking is in its infancy in Iran and few banks deliver services of social banking in a limited scope. There is no technology roadmap for this purpose in Iran. This research presents a technology roadmap for social banking in Iran (and can be adopted for banks of other developing countries) and gives a comprehensive plan for banks to design products and services based on their capacities and create required programs to implement and improve them. The application of technology roadmapping in the field of social banking is new.

The purpose of this study is to numerically examine the heat transfer and transport of space charges in the solid insulating materials [low density polyethylene (LDPE), flame retardant type 4 (FR4), Polytetrafluoroethylene (PTFE)] using the transmission line modeling (TLM) method. Besides, a comprehensive study is performed on the mutual influences of heat transfer and space charges transport within the solid dielectric bulk.

The obtained governing equations including continuity and circuit equations are coupled with heat transfer equations, and they are solved via fourth-order Runge–Kutta method.

The electric potential and field, current density and temperature distribution are calculated. It is shown that compared with FR4 and PTFE, the temperature increment rate in LDPE is much lower. Moreover, the heat transfer in the solid insulating materials bulk increases the homo-charges density and temperature in the vicinity of electrodes. Hence, the reduction in electric field is reflected in the potential deformations in the proximity of electrodes. Furthermore, where the electric field is maximized, the temperature is minimized.

This study is restricted to two-dimensional problems.

Interestingly, because of the lower temperature in LDPE, the current density and their increment rates in LDPE are much lower than that in FR4 and PTFE dielectric materials.

In this study, superhydrophobic fabric is prepared with a wet-chemical coating technique that uses a coating solution synthesized by the co-hydrolysis and co-condensation of tetraethyl orthosilicate and fluoroalkyl silane (tridecafluorooctyl triethoxysilane) under an alkaline condition. The treated fabric shows stable superhydrophobicity with a water contact angle as high as 171°, and a sliding angle as low as 2°. The coated fabric has higher repellency to saline water, and its repellency increases with increases in the salt content in the solution. The contact angle is reduced with increases in liquid temperature. When the water temperature is 90°C, the contact angle on the superhydrophobic fabric is 153°. The superhydrophobic treatment slightly reduces the air permeability, but increases the water vapor permeability of the fabric. The treatment considerably increases the liquid breakthrough pressure, but has little effect on fabric pore size and thermal conductivity. The air gap membrane distillation process is used to evaluate the desalination performance of the superhydrophobic fabric. When the feed and the condenser are kept at 90°C and 20°C, respectively, the membrane distillation (MD) system with the superhydrophobic fabric yields a permeate flux of water up to 13.8 kg m^-2 hour^-1, which is slightly higher than that with the use of polymer and inorganic MD membranes reported. Superhydrophobic fabrics may thus be considered as effective MD membranes for water desalination applications.

The purpose of this paper is to propose the application of artificial neural networks (ANN) to predict overall bank customer satisfaction and to prioritize influencing factors on customer satisfaction.

Data are collected from 436 randomly selected customers at ten different branches of an Iranian bank using a questionnaire consisting of 51 questions. An exploratory factor analysis (EFA) is done on the collected data to determine those factors that influence customer satisfaction. A multilayer perceptron ANN model is developed using the factor scores from the EFA. The ANN model is trained and validated to predict overall bank customer satisfaction. In addition, a linear regression model is developed to predict customer satisfaction. Prediction accuracy of the ANN model is compared with that of the linear regression model. The developed ANN is then used to compare sensitivity of customer satisfaction to each influencing factor.

Nine different influencing factors are extracted by EFA. The factors include Fees and Loans, Prompt Service, Appearance, Technological Service, Responsiveness, Reliability and Trustworthiness, Employees’ Attitudes and Behaviors, Accessibility to Bank and Availability of Service, and Interest Rates. Training and validation results show that the ANN model has 73 percent higher accuracy compared to the linear regression model in predicting overall bank customer satisfaction. Factor prioritization results show that Fees and Loans, Appearance, and Prompt Service have the highest impact on customer satisfaction, respectively; interest rate and accessibility to bank and availability of service are the least dominant factors influencing overall bank customer satisfaction.

This study proposes a more reliable and accurate methodology to predict customer satisfaction when compared with regression-based methods. ANN can also be utilized by bank management systems to prioritize different influencing factors that affect the satisfaction level of bank customers.

This paper advances the knowledge on bank customer satisfaction by proposing application of artificial intelligence methods. A case study is discussed and results of the application of an ANN are compared with those of a commonly used statistical regression model.

Britain's Lord Strathalmond puts his signature to the document that ended the momentous OPEC negotiations. John Lawless, in Tehran for the talks, interviews the Shah of Persia and cabinet ministers about the Gulf's economic hopes, already backed by Iran's 10 per cent annual growth rate, and views the prospects for international business.

After reading and analyzing the case study, the students will be able to recognize the role of the mega environment in shaping business strategy, explore the challenges and opportunities in a mature industry (Foam), understand the business context of a family-owned firm and assess the implications and recommend managerial strategies.

In July 2019, Unifoam, a leading foam manufacturer, found itself at a crossroads as the company leadership grappled with diverging vision and future course of action. The newly appointed chief executive, Mr Faraz Khalid Shaikh, had overseen significant investments in expanding production capacity, and the time had come to reap the rewards. However, a series of unexpected events had unfolded, presenting the company with a unique set of challenges. Unifoam relied heavily on imported raw materials from China. Unifoam had high hopes of capitalizing on the opportunities presented by the China Pakistan Economic Corridor. However, the newly formed government had made significant policy changes regarding currency valuation and borrowing rates. This had increased the company’s working capital cost by 40%. This unexpected development had divided the board on the future direction and had forced the leadership to confront a crucial question: Should they hit the brakes or accelerate their growth strategies? This case study explored into the dynamic interplay between external factors, internal divisions and the family-owned nature of Unifoam. The analysis recognized the influence of the mega environment on the company’s strategy, exploring the challenges and opportunities within the mature foam industry and assessing the implications of conflicting approaches. This case study also offered valuable insights and managerial recommendations to guide the company’s path forward. Through embracing discomfort and confronting strategic dilemmas head-on, Unifoam sought to navigate uncharted waters and emerge as a resilient player in the evolving foam industry.

This is suitable for BBA or at the very start of MBA in the strategy courses, mainly business strategy and strategic management, and the case study can be positioned during the initial weeks in the course to provide a quick review of the basic analysis frameworks used in strategic decision-making.

Teaching notes are available for educators only.

CSS 11: Strategy.

The purpose of this study is to examine the relationships between market mavenism, tourists’ cocreation experience, loyalty and the mediating role of travel incentives in the post-COVID-19 tourism environment in the context of vaxication intentions in Turkey.

This study used covariance-based structural equation modeling to empirically test the proposed hypotheses. A total of 348 respondents participated in the survey.

The findings of this study support the assumption that market mavenism (MM) engage in cocreating and sharing travel experiences (CCTE). Furthermore, the study reveals that market mavens tend to demonstrate loyalty (LTY) toward service providers when engaging in cocreation with travel industry professionals. In addition, the study establishes the significant mediating effect of travel incentives (TI) between MM and vaxication intention (VI).

The study uses the theory of planned behavior to examine tourists’ intentions for vaxication and the psychological factors influencing their decisions, while also using the macro–micro theory to explore industry-level factors like market mavens and customer engagement, leading to a comprehensive understanding of COVID-19 vaccination and tourism behavior. Further research is needed to address limitations such as country diversity, multiple locations and service providers, online behavior analysis, authenticity perception and identification of market mavens’ personality traits and travel preferences.

This study contributes to the scholarly literature in several ways. First, it explores the influence of market mavens on tourism experience cocreation and customer loyalty during the postpandemic era. Second, it empirically examines the mediating role of travel incentives, adding to the understanding of market mavens and vaccination intentions. Lastly, the study addresses the implications during and after the COVID-19 for managers and service providers in the tourism industry.

The American agricultural economist Marion Clawson advised the Israeli government during 1953–1955. Clawson, a protégé of John D. Black and Mordecai Ezekiel, criticized the government for ignoring economic considerations, and stated that Israel’s national goals – defense, Negev Desert irrigation, immigrant absorption via new agricultural settlements, and economic independence – were mutually contradictory. His major recommendations were to improve the realism of Israel’s agricultural plan; end expensive Negev irrigation; enlarge irrigated farms eightfold; freeze new settlements until the number of semi-developed settlements falls from 300 to 100; and limit new Negev settlements to 10 over 5–7 years. Thus, Clawson ignored political feasibility and made value judgments. Minister of Finance Levi Eshkol and Minister of Agriculture Peretz Naphtali rejected Clawson’s recommendations because they ignored Israel’s national goals. By September 1954, Clawson shifted towards greater pragmatism: He acknowledged that foreign advisors should not question the national goals or make value judgments, and sought common ground with the Ministry of Agriculture. At his initiative, he wrote Israel Agriculture 1953/54 in collaboration with the Ministry of Agriculture. Israel Agriculture was a consensus document: Clawson eschewed recommendations and accepted that the government might prioritize non-economic goals. In proposing Israel Agriculture, Clawson made a pragmatic decision to relinquish some independence for (potentially) greater influence. Ultimately, Clawson was largely unsuccessful as an advisor. Clawson’s failure was part of a general pattern: Over 1950–1985, the Israeli government always rejected foreign advisors’ recommendations unless it was facing a severe crisis.

Offshore structures are among the structures exposed to fire more often. Most of these structures are likely to be associated with flammable materials. In this research, some of the structures constructed on top of marine decks have been studied.

For this purpose, the upper-bound theory of plastic analysis has been used to investigate its collapse behavior. In this way, genetic algorithm has been used for application of the combination of elementary mechanisms in the classic plastic analysis problem.

The studied structures are optimized by plastic analysis theory before and after the fire and their failure modes are compared with each other. The comparison of the results indicates significant changes in the load factor value, as well as the critical collapse mode of the structure before and after the fire.

Results indicate that the combination of plastic analysis and a genetic algorithm can predict the collapse mode of the structure before and after the fire accurately.