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Factors that affect the use of carbon credit trading (CCT) by industries include as follows: avoiding carbon taxes, international expansion, venture capital, competitive advantage and clean technology. The impact of these factors is examined here in relation to the profile of 14 Canadian organizations to investigate factors that influence CCT practices.

This research involves a survey of 150 employees at 14 industries in British Columbia (BC) Canada to review and analyze their perceptions of factors that impact CCT.

Results demonstrate the potential for enhancing the use of CCT by organizations. It was shown that organizations perceive that CCT enhances their competitive advantage, which is an incentive that needs further investigation as having potential for encouraging CCT and greenhouse gas (GHG) reduction.

Due to limited funding and workforce, as well as geographical constraints, only 14 industrial organizations were engaged in this research in BC Canada. The scope of future research needs to be enlarged by considering neighboring countries such as the USA and Mexico. This research regarding factors that impact organizations in adopting carbon crediting trading has the potential to provide and shape inter-continental comparisons.

This study illustrates how CCT has the potential to enhance competitive advantage and may impact the industry toward reducing GHG emissions through CCT. This concept adds a new environmental protection factor and dimension to trade and industry. As organizations plan to invest funds in different carbon reduction projects this may result in expanded employment opportunities.

Organizations are interested in CCT but may hesitate in engaging in CCT as it can be a complex procedure. In addition to further research, workshops and seminars regarding CCT and dissemination of research should be organized by the universities, related authorities and government organizations to make CCT more known and feasible. This study shows that financial and non-financial benefits may be gained by any organization when involved in CCT. Larger advertising and information campaigns may motivate more organizations in this regard.

This study extends the study of Garg et al. (2017) regarding challenges for CCT practices. International Journal of Management, 10(1), 85–96. It contributes evidence that the size (revenue) of an organization does not affect the level of carbon credits traded and shows potential for smaller organizations to be encouraged to take part in CCT.

The purpose of the paper is to investigate the effect of TQM principles on organisational performance in Small and Medium Enterprises (SMEs) in Indian Auto Component Sector.

The paper is based on survey data collected from quality heads of 120 Auto component SMEs in India and uses correlation and regression analysis to test the relationships between quality management principles and organizational performance.

The study provides evidence that application of TQM principles such as ‘Process Approach’, ‘Mutually Beneficial Supplier Relationship’ and ‘Factual Approach to Decision-Making’ has a positive influence on the performance of Indian Auto component SMEs.

This study presents a number of managerial implications, specifically for quality managers in Indian Auto component SMEs. The focus of these organizations should be on strengthening the supply chain and operations. The quality managers need to align processes and resources based on factual approach to decision making for achieving higher organizational performance. Management of the organizations should also analyse why the soft aspects of TQM namely, Involvement of People, Customer Focus and Leadership are not contributing to the organizational performance in Indian Auto component SMEs.

This paper identifies the key quality management principles that can influence organizational performance in SMEs in the Indian Auto component sector whereas most existing studies have focussed only on Tier-1 organization in this sector. Unlike previous studies on this subject, the present study highlights the significant impact of predominantly hard factors of TQM such as ‘Process Approach’ and ‘Factual Approach to Decision-Making’ with only one soft factor of TQM namely, ‘Mutually Beneficial Supplier Relationship’ being significant.

The purpose of this paper is to examine the impact of Organisational Culture (OC) on total quality management (TQM) implementation in Indian small and medium enterprises (SMEs) in the auto component sector. Specifically; it attempts to propose a model linking OC and TQM for this sector.

Survey method was used for data collection by targeting the whole population of 482 Indian auto component SMEs drawn from Auto Component Manufacturers Association members’ database. Out of 482, 150 completely filled questionnaires were taken for data analysis. Proposed relationships among identified dimensions of OC and TQM interventions have been validated through parameter estimation statistics and goodness-of-fit statistics using path analysis technique of structural equation modelling using AMOS 18.0.

Based on the results, a culture influenced TQM model has been developed. The model demonstrates a linkage between cultural dimensions and TQM interventions, thereby suggesting that OC characterised by “openness”, “confrontation”, “trust”, “authenticity”, “proaction”, “autonomy”, “collaboration” and “experimentation” has a significant and positive impact on TQM implementation.

The study presents many practical implications, specifically for quality managers in Indian auto component SMEs. The study has developed a culture influenced TQM model which identifies dimensions of OC that promote TQM implementation. The study also identifies various interventions of TQM in their order of significance, which can be used by SMEs in mapping the critical links between OC and TQM through this model. Thus, findings of the present study will help SMEs in this sector to move up the value chain and sustain their global competitiveness.

The study provides a culture influenced TQM model which would assist managers in quality implementation in Indian auto component SMEs.

The purpose of this paper is to compile a comprehensive status report on pipes/piping networks across different industrial sectors, along with specifications of materials and sizes, and showcase welding avenues. It further extends to highlight the promising friction stir welding as a single solid-state pipe welding procedure. This paper will enable all piping, welding and friction stir welding stakeholders to identify scope for their engagement in a single window.

The paper is a review paper, and it is mainly structured around sections on materials, sizes and standards for pipes in different sectors and the current welding practice for joining pipe and pipe connections; on the process and principle of friction stir welding (FSW) for pipes; identification of main welding process parameters for the FSW of pipes; effects of process parameters; and a well-carved-out concluding summary.

A well-carved-out concluding summary of extracts from thoroughly studied research is presented in a structured way in which the avenues for the engagement of FSW are identified.

The implications of the research are far-reaching. The FSW is currently expanding very fast in the welding of flat surfaces and has evolved into a vast number of variants because of its advantages and versatility. The application of FSW is coming up late but catching up fast, and as a late starter, the outcomes of such a review paper may support stake holders to expand the application of this process from pipe welding to pipe manufacturing, cladding and other high-end applications. Because the process is inherently inclined towards automation, its throughput rate is high and it does not need any consumables, the ultimate benefit can be passed on to the industry in terms of financial gains.

To the best of the authors’ knowledge, this is the only review exclusively for the friction stir welding of pipes with a well-organized piping specification detailed about industrial sectors. The current pipe welding practice in each sector has been presented, and the avenues for engaging FSW have been highlighted. The FSW pipe process parameters are characteristically distinguished from the conventional FSW, and the effects of the process parameters have been presented. The summary is concise yet comprehensive and organized in a structured manner.

This paper aims to report the friction and wear characteristics of refined soybean oil (RSBO) blended with copper oxide (CuO) nanoparticles and zinc dialkyldithiophosphate (ZDDP) as additives.

Four different concentrations 0.04, 0.05, 0.1 and 0.2 Wt.% of CuO nanoparticles were added with ZDDP in RSBO. The friction and wear characteristics of lubricants have been investigated on a pin-on-disc tribotester under loads of 120 and 180 N, with rotating speeds of 1,200 and 1,500 rpm in half hour of operating time. The dispersion stability of CuO nanoparticles has been analyzed using ultraviolet visible (UV-Vis) spectroscopy. The wearout surface of pins has been examined by using a scanning electron microscope.

The results revealed that there is a reduction in the friction and wear by the addition of CuO nanoparticles and ZDDP in RSBO. Coefficient of friction increases at a high sliding speed for RSBO with ZDDP. From UV-Vis spectroscopy, it is observed that 100 ml of oleic acid surfactant per gram of CuO nanoparticles has stable dispersion in RSBO.

The addition of ZDDP and CuO nanoparticles in RSBO is more efficient to reduce the friction and wear in comparison to base oil. The optimum concentration of CuO nanoparticles in RSBO is 0.05 Wt.%.

The purpose of this paper is to investigate the influence of low-cost chemical vapour treatment process on geometric accuracy and surface roughness of different curved and freeform surfaces of fused deposition modelling (FDM) specimens build at different part building orientations.

Parts with different primitive and curved surfaces are designed and modelled to build at three different part orientations along X orientation (vertical position resting on side face), Y orientation (horizontal position resting on base) and Z orientation (upright position). Later, the parts are post-processed by cold vapours of acetone. Geometric accuracy and surface roughness are measured both before and after the chemical treatment to investigate the change in geometric accuracy, surface roughness of FDM parts.

The results indicate that surface roughness is reduced immensely after cold vapour treatment with minimum variation in geometric accuracy of parts. Parts build vertically over its side face (X orientation) provides the overall better surface finish and geometric accuracy.

The present study provides an approach of post-built treatment for FDM parts and observes a significant improvement in surface finish of the components. The present approach of post-built treatment can be adopted to enhance the surface quality as well as to achieve desired geometric accuracy for different primitive, freeform/curved surfaces of FDM samples suitable for functional components as well as prototypes.

The scope of this study is to explore and summarize the pool of dimensions, models and measurement techniques of service quality used in healthcare services and to propose a comprehensive conceptual model for practitioners and researchers.

This research employs a comprehensive review of available literature by using multiple keywords on different electronic repositories using the recommendations of the PRISMA approach for the selection of articles. A critical analysis of available studies helped in compiling a list of core service quality dimensions in healthcare services.

This paper presents a comprehensive account of different dimensions and their measurement items used by various researchers to assess service quality in healthcare systems. Most of the researchers have used SERVQUAL model either in its original or modified form while the others have proposed and used totally different dimensions to assess the service quality in healthcare. Many dimensions are just an existing dimension of SERVQUAL that has undergone a name change while others are completely new. The dimensions used by many researchers have items drawn from more than one dimension of SERVQUAL model. The availability of so many dimensions and models adds to the confusion that researchers and practicing managers experience when determining the appropriate model to be used in their work. To mitigate this confusion, there is a need to develop a comprehensive model; the current work is an attempt to meet this need. Through our analysis, we identify four major service quality dimensions: clinical quality, infrastructural quality, relationship and managerial quality and propose a model named CIRMQUAL.

After exploring all available models in the domain of healthcare, this research presents the best possible areas to enhance the quality of healthcare services. It also enhances the research insights for academicians and working professionals by developing and proposing a comprehensive model for measuring healthcare service quality. The proposed model covers almost all of the service quality dimensions used by other researchers and will make the choice of dimensions/model easy for the future researchers/practitioners interested in measuring and improving the quality of services offered by their healthcare units. Such a comprehensive model has not been developed by any researcher thus far.

Sustainable manufacturing practices are excessively being practised in the industry today. The impact on sustainability is ever more visible to the stakeholders because of faster and more efficient communication due to social media and the internet. This paper aims to study the impact of greenwashing by corporations and the stakeholders’ environmental concerns on consumers’ sustainable purchase behaviour.

The relationships between the impression of “greenwash”, sustainable purchasing behaviour, green word-of-mouth and green brand loyalty were investigated in this quantitative study. Participants who made up a representative sample filled out written surveys. The variables of interest were evaluated using scales that have undergone validation. Structural equation modelling was used in mediation analysis to investigate the mediating impacts of green word-of-mouth and green brand loyalty. The goal of the study was to offer empirical proof of how these factors affected consumers’ choices for sustainable products.

Analysis of the mediating relationship of perceived customer effectiveness in the relationship between environmental concern and sustainable purchase behaviour has been studied.

This study implicates that a company that primarily markets basic green and sustainable products or services must invest in informing people about environmental concerns and that by proper practices, a lot of the harm to the environment can be reduced.

Corporate greenwashing, also called false greening, has received much public attention recently. The unethical practices by the corporations, which previously majorly went unnoticed, have also recently gained a lot of visibility. This paper is one of the early attempts towards establishing the effect of corporate greenwashing on sustainable consumer behaviour.

The objective of this work is twofold: firstly, to develop a model for assessing healthcare service quality (HSQ), and secondly, to evaluate the effectiveness of machine learning algorithms in predicting the quality of healthcare services.

In this study, a comprehensive literature review has been performed to identify key quality dimensions in the healthcare services domain. Delphi’s method has been used to confirm the criticality of these dimensions based on experts’ opinions and proposed a novel CIRMQUAL model. Factor analysis techniques have been used to further validate the CIRMQUAL model. Using the data collected through a questionnaire survey, a number of machine learning models have been developed to predict the customer satisfaction level based on the service quality (SQ) performance of a healthcare unit on different dimensions of the CIRMQUAL model.

The study developed a CIRMQUAL model with 14 dimensions (quality of care, safety and security, skill and conduct, staff attitude, tangibles, quality of the atmosphere, patient rights, follow-up, communication, cost of treatment, availability of resources, accessibility, waiting time and services), and these dimensions have been clubbed into four major dimensions, i.e. clinical quality, infrastructural quality, relationship and managerial quality. Furthermore, the application of machine learning algorithms has demonstrated significant accuracy in predicting SQ, highlighting its ability to improve healthcare services and the satisfaction level of patients.

Managers of healthcare units work hard to identify and address the pain points of the patients and improve the working of the healthcare units being managed by them. The availability of many scales with numerous dimensions adds to their confusion in selecting a suitable scale. The current work addresses this confusion and provides four clear areas for assessing the quality of healthcare units. By using this scale, managers can assess the quality of services provided by them, identify the dimensions of low performance, plan and take suitable corrective actions to improve the performance of their healthcare units.

A comprehensive SQ model, i.e. CIRMQUAL has been proposed as a new scale to assess SQ in healthcare units. The model has been developed after analyzing the dimensions used by many researchers available in the literature. This model can be used by future researchers to assess the SQ in healthcare units. Moreover, an attempt has been made to use artificial intelligence-based techniques for predicting customer satisfaction. Such attempts are in the initial stage for healthcare sector. Future researchers can take this concept forward and test the applicability of different machine learning techniques in different functional areas of healthcare.

Good health is of utmost importance for all human beings. In spite of the expenditure of substantial time and efforts by various stakeholders, the service delivery doesn’t match the expectations of patients. Many times, the service providers are not aware of this dissatisfaction and specific aspects of service delivery that need to be improved to reduce dissatisfaction. The model proposed will help the service providers in this regard and the service providers will be able to take focused steps. Such initiatives will definitely improve patient’s satisfaction and their social well-being.

This work is unique because it uses a novel technique to redefine the quality of services in healthcare by using a dual methodology. The research presents a model that includes various factors and it is specially developed to evaluate the quality of services in healthcare settings. This study advances the area’s progress by implementing computational tools for accurate evaluation of HSQ. The healthcare decision-makers may use this novel perspective to evaluate and enhance the quality of service.

Continued quest for business improvement in terms of enhanced productivity and cost cuts is the most valued strategic function in an organization. Towards this endeavor, there have been evolutions of many problem-solving techniques like Lean, quality control (QC) tools, Six Sigma, total productive maintenance (TPM), etc. This paper introduces a different problem-solving methodology for quality improvement – prepare, measure, define, establish, control and stabilize (PMDECS) approach of Red Bin Analysis (RBA) – and presents empirical evidence of its effectiveness in eliminating the defectives at source (parts per million [PPM]) and improving the process capability (Cp).

An attempt has been made to compare RBA with the Six Sigma methodology in terms of number of defects, defectives, process capabilities, project duration, etc. Data validation with more than 2000 data points was conducted based on empirical data collected over multiple problem-solving projects conducted in six manufacturing industries of India to compare the effectiveness of both the methods. Finally, fuzzy AHP (analytical hierarchy process) model was proposed to identify the Quality Improvement Index for both the methods to address the manager’s dilemma in selecting an appropriate problem-solving method.

The paper provides empirical insights in establishing that the PMDECS approach of RBA is at par and sometimes better for problem-solving if the problem is not chronic and is at the initial stages, it requires less duration than Six Sigma projects and except casting process and it can yield better results in case of PPM rejection or Cp/Cpk improvement in other processes.

Because of the chosen research approach, the research results may lack generalizability. This research has been specifically conducted in automotive manufacturing industries. Therefore, researchers are encouraged to test the proposed propositions further.

The paper includes implications for the usage of alternative problem-solving methods, like PMDECS approach of RBA.

This paper intends to compare how the results of six sigma projects in manufacturing industries are effective against a different methodology, PMDECS approach of RBA.