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Cationic resin is widely used in decolouring of textile wastewaters. Tonnes of resin are used in sector, and disposal of resin is being a second waste problem. The purpose of this paper is to investigate the adsorption behaviour of the methylene blue cationic dye from aqueous solution on the cation exchanger Lewatit CNP80 to understand the regenerability of cation exchanger resin from textile wastewaters.

Cationic resin was used as an alternative low-cost adsorbent for removing methylene blue dye from textile wastewaters. The adsorption study was carried out in the batch mode. Batch adsorption studies were carried out to examine the effect of parameters such as methylene blue concentration, temperature, pH, resin dose, shaking speed and contact time.

It was observed that dye-removal capacity of resin was reached from 17 mgg⁻¹ to 19.4 mgg⁻¹ at 25 °C temperature, pH 5 in 15 min. At the appropriate range of parameters, it was observed that more than 98% removal efficiency was achieved for methylene blue dye, and also, this study was focussed on whether the resin regenerates. In regeneration studies, our purpose was to recover of non-regenerable exhausted cationic resin by NaOCl. Regeneration of Lewatit CNP80 was performed in five cycles. After regeneration, the authors tried to determine whether the adsorption capacity was affected by regeneration.

In this study, the authors focussed on regeneration studies. The aim is to find easy, low-cost regeneration agent. In conclusion, the authors found that NaOCl is eligible for regeneration studies. The exhausted resin was recovered by NaOCl, and the authors also tested 5th regeneration cycles. Sodium hypochlorite is not a common regeneration agent for adsorption studies. Generally, resin is regenerated by HCl or other regeneration agent products. As a result of that, operational cost was reduced, and the other thing that the authors want to emphasise is textile industry wastewater based high temperature; therefore, this regeneration study can easily work with textile industries.

This paper aims to present a positive analysis of the bidding process for private finance initiative (PFI) projects. The analysis attempts to unravel how value for money (VFM) changes in the bidding process and what factors influence this change. Bidding theory postulates that the winning bid price drops from the effect of competition when the number of bid-participating firms increases.

An instrumental variable analysis was conducted using a two-stage least-squares method to remove the influence of endogeneity in the number of bid participants, which, according to prior research and surveys of business operators, possibly explains some of the VFM change. The results were considered robust because no observable change was found in the positive effect of the number of participant firms.

This paper provides positive evidence of the relationship between the number of firms and the bidding result. The analysis shows that the number of bid-participating firms clearly has a significant positive effect on VFM change. Specifically, competition lowers the winning bid amount in line with the theoretical proposition.

This study confirms previous research based on bidding data of Japanese PFI projects, a segment not sufficiently researched so far. Further, increasing the number of participant firms, up to a maximum of six, is shown to raise the VFM, a result consistent with the fact that five major construction companies play a leading role in Japanese PFI projects.

Recent decade has witnessed exponential growth in e-commerce segment, leading to emergence of various online selling platforms catering to diverse product requirements of customers. Such a development has provided impetus to both existing businesses and newly established ventures to make available their offerings through online selling platforms with a view to improve the reach of their products. This study is an attempt to identify the experience of registered vendors with the online marketplaces. It aims to develop and validate a scale to measure vendor's experience with e-commerce platforms.

As a part of the scale development process, relevant literature sources were scanned to spot the precise knowledge gap and to put in place a sound theoretical background for the study. Thereafter, a scientific approach was adopted for scale creation. First, the scale items were identified through interviews of vendors registered with major online selling platforms and other academic experts pertaining to the marketing domain. Subsequently, major dimensions of seller experience were identified through exploratory factor analysis (EFA) applied on data collected from active vendors by the means of a structured survey instrument. The final data set was subjected to confirmatory factor analysis (CFA) in a bid to validate the scale.

The study’s outcomes reveal that seller experience in an online marketplace can be best captured by a multidimensional scale characterized by six major dimensions. These are “Registration,”; “Product Listing”; “Pricing Autonomy”; “Ease of Pick-up and Delivery”; “Credit of Receivables” and “Vendor Assistance.” A proper emphasis to continually improve upon these dimensions by the e-commerce platforms is expected to enhance the utility and overall experience of vendors from such platforms. Existence of a mutually beneficial relationship between vendors and online marketplaces will help marketplaces to mitigate concerns like nonfulfillment of orders and dispatch of substandard products.

Sustainable long-term relations between vendors and online marketplaces hold the key for such marketplaces to render error-free and delightful service on each individual order received. Seller experience of registering and operating on such e-marketplaces inspite of playing a defining role in vendor–marketplace relations has received scant attention of researchers, both in academia and industry till date. The present research is a seminal attempt to address this gap in marketing literature and offer additional know-how.

In industrial buyer–supplier relationships, being an attractive customer has been found to result in superior supplier performance. However, there is a limited understanding of how these benefits transfer to the public domain. This study aims to explore the influence of customer attractiveness on supplier resource mobilization efforts toward the public sector.

A qualitative approach was used, focusing on in-depth interviews with 23 informants from 3 critical and complex supplier markets. The data were processed using inductive coding and thematic analysis.

The findings indicate that customer attractiveness in the public sector influences suppliers’ mobilization efforts on several dimensions. In addition to stimulating competition in the tender phase, customer attractiveness can yield important benefits to quality, supply stability and innovation during the business relationship. It appears imperative for the public sector to improve its standings with suppliers to both mitigate the apparent risk of sub-par treatment and to unlock the preferential supplier treatment associated with being an attractive customer.

Receiving increased mobilization from suppliers will result in better use of public money and help improve resilience and innovation in public procurement.

This study extends the research on customer attractiveness in the public sector by being the first to explore the range and nature of its influence on supplier mobilization efforts.

This paper aims to investigate the fatigue life and dynamic loads of an arresting cable when a landing aircraft passes through a runway.

The cable is assumed to be under tension and with bending rigidity. The normal modes and natural frequencies of the vibrating wire are obtained analytically. The response of the arresting cable owing to the impact of the landing aircraft is modelled as a problem of initial conditions. The maximum normal and tangential stresses are determined for different landing conditions and landing aircraft sizes. The fatigue life of the wire is determined based on classical theories.

The results show that maximum shear stresses occur at the end of the cable. These shear stresses increased with higher off-centre landing position and decreased tyre width. Between 50 and 70% of the service life of the cable is reduced due to the dynamic loading effects.

A novel technique based on the solution of a continuous elastic system is proposed for analysing the displacements and stresses on an arresting cable due to the impact of a landing aircraft. The derived stresses can be used to calculate the service life of the cable.

This study aims to discover whether COVID-19 phobia has a positive and significant effect on the stress, depression and anxiety levels of industrial consumers in addition to reveal whether environmental awareness plays a mediating role between COVID-19 phobia and stress, depression and anxiety.

In this study, a quantitative method was used to reveal the role of anxiety, depression and stress (psychological effects) and environmental awareness caused by covid-19 phobia on industrial consumers. The universe of the study is small and medium-sized enterprises operating in the province of Sanliurfa, which is located in the southeast region of Turkey and the second largest city in the region, and are industrial customers. Questionnaire method was used in the study. In addition, data were collected from 406 people who agreed to participate in the study. In the study, in which intermediary and regulatory analyzes were made, the process macro program was used.

The results show that there is a medium relationship between COVID-19 phobia and environmental awareness; and COVID-19 phobia and stress, depression and anxiety. No relationship was found between environmental awareness and stress, depression and anxiety. COVID-19 phobia was found to have a positive and significant effect on environmental awareness and stress, depression and anxiety, while environmental awareness was found to have no effect on stress, depression and anxiety. Finally, environmental awareness was found to play a mediating role between COVID-19 phobia and stress, depression and anxiety.

In this study, four hypotheses were developed. Of these hypotheses, three are for the simple effect and one for the mediation effect. Out of four hypotheses, three were supported. The most important inference obtained from the study was finding the mediation effect of environmental awareness between COVID-19 phobia and anxiety, depression and stress.

To the best of the authors’ knowledge, no studies in the literature were made on the relationship among COVID-19 phobia, environmental awareness, stress, depression and anxiety. This study also examines the mediating effect of environmental awareness in the relationship between COVID-19 phobia and stress, depression and anxiety. The fact that the study is on the negative effects of the pandemic on one of the most affected occupational group also increases its original value.

The purpose of this paper is to identify the effect of radical innovation and incremental innovation on the competitive advantage of Jordanian industrial companies and identify the moderating role of technological intensity.

For this study’s purposes, 303 questionnaires from employees of 30 manufacturing firms were analysed. Convergent validity and discriminant validity tests were performed through structural equation modelling in the Smart-PLS programme. Data reliability was confirmed. A bootstrapping technique was used to analyse the data. Multi-group analysis was performed to investigate the moderating role of technological intensity.

Empirical results showed that both radical innovation and incremental innovation explain 60.2% of the variance in competitive advantage and that both constructs have a statistically significant effect on competitive advantage. The results also revealed that the relationship between radical innovation and competitive advantage is modified through the high-tech industries. Meanwhile, the relationship between incremental innovation and competitive advantage is modified through the low-tech industries.

This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalization of its results and the results are limited to one country, Jordan.

This study promotes the idea of focusing on radical and incremental innovation to enhance competitive advantage in the Jordanian manufacturing sector and knowing the effect of technological intensity in this relationship.

This study has important implications for leaders in the Jordanian manufacturing sector in general, as the study highlights the importance of radical innovation and incremental innovation to enhance the competitive advantage, especially in light of the technological intensity in this sector, and thus, increase the innovative capabilities of this firms, which leads to an increase in the level of competitive advantage.

The heat transfer within a heat exchanger is highly influenced by geometry of the components especially those with hollow structures like tubes. This paper aims to intend toward the study of efficient and optimized heat transfer in the bends of superheater tubes, with different curvature ratio at constant Reynolds Number.

The effect of changing curvature ratio on enthalpy of the fluid passing through the superheater tubes for multi-pass system has been studied with the aid of computational fluid dynamics (CFD) using ANSYS 14.0. Initially a superheater tube with two pass system has been examined with different curvature ratios of 1.425, 1.56, 1.71, 1.85 and 1.99. An industry specified curvature ratio of 1.71 with two pass is investigated, and a comparative assessment has been carried out. This is intended toward obtaining an optimized radius of curvature of the bend for enhancement of heat transfer.

The results obtained from software simulation revealed that the curvature ratio of 1.85 provides maximum heat transfer to the fluid flowing through the tube with two pass. This result has been found to be consistent with higher number of passes as well. The effect of secondary flow in bends of curvature has also been illustrated in the present work.

The study of heat transfer in thermodynamic systems is a never-ending process and has to be continued for the upliftment of power plant performances. This study has been conducted on steady flow behavior of the fluid which may be upgraded by carrying out the same in transient mode. The impact of different curvature ratios on some important parameters such as heat transfer coefficients will certainly upgrade the value of research.

This computational study provided comprehensive information on fluid flow behavior and its effect on heat transfer in bends of curvature of superheater tubes inside the boiler. It also provides information on optimized bend of curvature for efficient heat transfer process.

This paper aims to present the studies which were carried out to determine building typology in Northern Pakistan, which is a seismically active region.

A total of 41 towns and cities were surveyed to collect the data of building types. Help was also taken from global positioning system and satellite imagery.

In total, 14 different types of buildings were identified in the region based on the structural system and combination of wall and roof materials; each of them was assigned an appropriate designation. The walls in these buildings were made of block, stone or brick, whereas the roof consisted of corrugated galvanised iron sheet, thatched roof, precast concrete planks or reinforced concrete (RC). Only 6 per cent buildings were found to be engineered RC buildings; this indicates a significance proportion of non-engineered building stock in Northern Pakistan.

The surveys were conducted in some of the selected areas. Other areas are beyond the scope of this work.

The presence of a huge deficient building stock in Pakistan indicates a major seismic risk. The seismic losses are largely dependent on the earthquake resistance of existing buildings and building stock. An inventory of existing buildings and their types can help in assessing seismic vulnerability of the built environment, which may lead to the development of policies for seismic risk reduction.

Presently, housing encyclopaedia does not exist in Pakistan. As a result, housing typology in the country is not known. The presented study addresses this gap in part. Housing typology surveys were conducted to study the typical construction practices in the selected areas and to determine the proportions of different building types in the overall building stock.

This paper conducts a Systematic Literature Review (SLR) of Machine Learning (ML) in Supply Chain Management through bibliometric and network analysis, the authors are able to grasp key features of the contemporary literature. The study makes use of state-of-the-art analytical framework based on a unified approach to reveal insights from the present body of knowledge and the potentials for future research developments.

Unlike standard literature reviews, in SLR, a structured approach is followed. The approach enables utilizing contemporary tools and software packages such as R-package “bibliometrix” and Gephi for exploratory and visual analytics. A number of clustering methods are employed to form clusters. Later, multivariate analysis methodologies are adopted to determine the dominant clusters for the influential co-cited references.

Using contemporary tools from Bibliometric Analysis (BA), the authors identify in an exploratory analysis, the influential authors, sources, regions, affiliations and papers. In addition, the use of network analysis tools reveals research clusters, topological analysis, key research topics, interrelation and authors’ collaboration along with their patterns. Finally, the optimum number of clusters computed for cluster analysis is decided using a systematic procedure based on multivariate analysis such as k-means and factor analysis.

Modern-day supply chains increasingly depend on developing superior insights from large amounts of data available from diverse sources in unstructured and semi-structured formats. In order to maintain a competitive edge, the supply chains need to perform speedy analysis of big data using efficient tools that provide real-time decision-making insights. Such an analysis necessitates automated processing using intelligent ML algorithms. Through a BA followed by a detailed data visualization in a network analysis enabled grasping key features of the contemporary literature. The analysis is based on 155 documents from the period 2008 to 2018 selected using a systematic selection procedure.