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In the recent scenario, there has been an increasing trend toward lean practices and implementation in production systems for the improvement of an organization’s performance as its basic nature is to eliminate the wastes. The increasing interest of customers in customized products and the fulfillment of customers’ demand with good productivity and efficiency within time are the challenges for the manufacturing organization; that is why adopting lean manufacturing concept is very crucial in the current scenario.

In this paper, the authors considered three different methodologies for fulfilling the objective of our research. The analytical hierarchy process, best–worst method and fuzzy step-wise weight assessment ratio analysis are the three methods employed for weighting all the enablers and finding the priority among them and their final rankings.

Further, the best results among these methodologies could be used to analyze their interrelationships for successful lean supply chain management implementation in an organization. In this paper, 35 key enablers were identified after the rigorous analysis of literature review and the opinion of a group of experts consisting of academicians, practitioners and consultants. Thereafter, the brainstorming sessions were conducted to finalize 28 lean supply chain enablers (LSCEs).

For lean manufacturing practitioners, the result of this study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process.

This paper is the first of the research papers that considered deep literature review of identified LSCEs as the initial step, followed by finding the best priority weightage and developing the ranking of various lean enablers of supply chain with the help of various methodologies.

Multi-manned assembly lines are designed to produce large-sized products, such as automobiles. In this paper, a multi-manned assembly line balancing problem (MALBP) is addressed in which a group of workers simultaneously performs different tasks on a workstation. The key idea in this work is to improve the workstation efficiency and worker efficiency of an automobile plant by minimizing the number of workstations, the number of workers, and the cycle time of the MALBP.

A mixed-integer programming formulation for the problem is proposed. The proposed model is solved with benchmark test problems mentioned in research papers. The automobile case study problem is solved in three steps. In the first step, the authors find the task time of all major tasks. The problem is solved in the second step with the objective of minimizing the cycle time for the sub-tasks and major tasks, respectively. In the third step, the output results obtained from the second step are used to minimize the number of workstations using Lingo 16 solver.

The experimental results of the automobile case study show that there is a large improvement in workstation efficiency and worker efficiency of the plant in terms of reduction in the number of workstations and workers; the number of workstations reduced by 24% with a cycle time of 240 s. The reduced number of workstations led to a reduction in the number of workers (32% reduction) working on that assembly line.

For assembly line practitioners, the results of the study can be beneficial where the manufacturer is required to increased workstation efficiency and worker efficiency and reduce resource requirement and save space for assembling the products.

This paper is the first to apply a multi-manned assembly line balancing approach in real life problem by considering the case study of an automobile plant.

Today the role of industry 4.0 plays a very important role in enhancing any supply chain network, as the industry 4.0 supply chain uses Big Data and advanced analytics to inform the complete visibility. Latest data are available to bring clarity and support real-time decision-making in the entire supply chain that’s why adopting optimization techniques such as lean manufacturing and lean supply chain concept for enhancing the supply chain network of the organizations is a good idea and would benefit them in increasing their cost efficiency and productivity. The purpose of this work is to develop a technique, which may be useful for future researchers and managers to identify and classification of the significant lean supply chain enablers.

In this paper, the authors considered hybrid analytical hierarchy process to find the ranking of the identified lean supply chain enablers by calculating their weightage. Interpretive structural modeling (ISM) is applied to develop the structural interrelationship among various lean supply chain management enablers. Considering the results obtained from ISM the Matrices d'Impacts Croises Multiplication Appliqué a un Classement (MICMAC) analysis is done to identify the driving and dependence power of Lean Supply Chain Management Enablers (LSCMEs).

Further, the best results applying these methodologies could be used to analyze their inter-relationships for successful Lean supply chain management implementation in an organization. The authors developed an integrated model after the identification of 20 key LSCMEs, which is very helpful to identify and classify the important enablers by ISM methodology and explore the direct and indirect effects of each enabler by MICMAC analysis on the LSCM implementation. This will help organizations optimize their supply chain by selective control of lean enablers.

For lean manufacturing practitioners, the result of the study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process, as well as in enhancing the supply chain.

This paper is the first research paper that considered firstly deep literature review of identified lean supply chain enablers and second developed structured modeling of various lean enablers of supply chain with the help of various methodologies.

Parallel two-sided assembly lines are usually designed to produce large-sized products such as trucks and buses. In parallel two-sided assembly lines, both left and right sides of the line are used for manufacturing one or more products on two or more assembly lines located parallel to each other. The purpose of this paper is to develop a new mathematical model for the parallel two-sided assembly line balancing problem that helps to evaluate and validate the balancing operations of the machines such as removal of tools and fixtures and reallocating the operators.

The proposed approach is explained with the help of an example problem. In all, 22 test problems are formed using the benchmark problems P9, P12, P16 and P24. The results obtained are compared among approaches of the task(s) shared, tool(s) shared and both tool(s) and task(s) shared for effect on efficiency as the performance measure. The solution presented here follows the exact solution procedure that is solved by Lingo 16 solver.

Based on the experiments, line efficiency decreases when only tools are shared and increases when only tasks are shared. Results indicate that by sharing tasks and tools together, better line efficiency is obtained with less cost of tools and fixtures.

According to the industrial aspect, the result of the study can be beneficial for assembly of the products, where tools and tasks are shared between parallel workstations of two or more parallel lines.

According to the author’s best knowledge, this paper is the first to address the tools and tasks sharing between any pair of parallel workstations.

Today the mobile apps are helping customers in every means of their life by exploring information related to electronic items and even for food items also. Therefore, the main aim of this study is to examine the influencing role of psychological and technological attributes on customer conversion to use food ordering apps.

Convenience sampling method was used to collect responses from the customer's age between 18 and 35 years to get more representation of society. 374 customer's data has been used for structural equation model analysis with the help of SmartPLS 3.0 and SPSS-20 software.

Findings showed that customer conversions are positively influenced by perceived ease of use, perceived usefulness, perceived incentives, perceived information, customer relationship management and order management system. In contrast, the perceived price and visual design show insignificant influence.

Research outcome provides some valuable insights to provide direction to all online food aggregators to design their apps according to customers need. Thus, the authentic customer reviews and the facility of providing feedbacks are very fruitful for attracting new user while using and placing orders through theses apps.

Study suggested that observing satisfaction and dissatisfaction levels of the customer helps in enhancing the facilities of food ordering apps, so that the customer would enjoy the whole order process seamlessly, which automatically leads to customer conversions.

Major contribution of this study is the empirical analysis of psychological and technological attributes on customer's conversion towards food ordering app.

The objective of this paper is to examine whether there are significant variations in the profile of debt‐financing as a result of differences in industry, size and age group of the sample corporate enterprises in India. It also ascertains the trend in debt financing practices among the various groups during the period 1992‐2003 and finds out the impact of the liberalized environment, in terms of the significant changes, if any, in phase‐2 (year 1998‐2003) of the liberalized business scenario vis‐à‐vis phase‐1 (year 1992‐1997) in the debt financing decisions of different group of the sample firms. The study covers a stratified representative sample of 601 corporate enterprises, consisting of fourteen industry groups, and is segregated into four size classes and two age categories. The study brings to fore that while industry and size have been observed to be a significant factor influencing composition and maturity structure of debt financing, the empirical evidence does not support the hypotheses that the debt financing decisions vary significantly across age categories.

E-commerce refers to the facilitation and delivery of goods and services to the customers employing an electronic arrangement. For an e-commerce firm, the customer service level provided by its suppliers can make or break the firm. The purpose of this research is to help e-commerce enterprises in addressing the vast challenge of complex supplier selection and evaluation process that must be performed vigilantly.

The present study utilizes a three-pronged approach that integrates supplier management practices with the operational business practices of an e-commerce enterprise. In the first step, key performance factors for e-commerce capable suppliers are identified through an expert opinion and existing supplier management literature. Further, Data Envelopment Analysis (DEA) is employed to obtain the efficiency score for each supplier that enables their ranking on various performance parameters. Lastly, the suppliers are classified into different categories based on their performance and efficiency.

Under the proposed classification scheme, top five suppliers, i.e. supplier 1, 7, 9, 11 and 17 are categorized as HE (High Performance and Efficient). It is suggested that e-commerce enterprises must build long-term relationship with the identified top performing suppliers. The study also provides real insights into supplier's performance on a number of objective criteria. Further, the present study enhances the overall performance and productivity of an e-commerce firm by achieving input cost minimization and output quality maximization, simultaneously.

The results are valid for e-commerce enterprises in general. However, the present DEA model can be further evolved when applied in case of any particular e-commerce enterprise depending upon the internal capabilities of that firm. The nuances related to a firm's own supply capability development can be further explored by practitioners and researchers.

The proposed approach is expected to motivate decision-makers to consider using more sophisticated approached like DEA in supplier evaluation processes. Also, as a benchmarking technique, the proposed supplier classification approach is expected to be highly useful for practitioners in real-life settings.

The novel contribution of this study includes the supplier evaluation, ranking and classification for e-commerce enterprises based on the real-life data. The insights would help the practitioners to formulate novel strategies for appropriately investing in supplier relationships.

Amid the COVID-19 contamination, people are bound to use contactless FinTech payment services. Because of restrictions on physical movement and avoidance of touching physical money, people willingly choose mobile payment, resulting in enormous growth in FinTech payment service industries. Because of this, this study aims to examine the effect of factors affecting Gen X and Millennials users to use FinTech payment services.

The authors used 328 responses collected through convenience sampling of Indian users aged between 26 and 57 years in the Delhi-NCR region who are users of FinTech payment services.

The authors’ findings verified that in India, perceived COVID-19 risk, perceived severity for COVID, individual mobility, subjective norms, perceived ease of use and perceived usefulness have statistically significant impacts on FinTech payment services during the COVID-19 pandemic. Structural equation modelling was used to study the proposed research model. Overall, the model predicted 76.9 % of the variation in intention to use FinTech payment services by the abovesaid variables by Indian users during a pandemic.

This study will provide valuable insight to all FinTech service providers and stakeholders in planning and designing the concerned policy. It will be able to draw the attention of users more.

This research added a valuable theory to the existing technology adoption model (TAM) theory. It demonstrated the utility of the above variables in adopting and using FinTech payment services, which will help service providers to develop future strategies because of the COVID-19 pandemic.

At any one time, 76 million people have an alcohol use disorder. Detoxification is a common intervention for alcohol dependence. There is a need regularly to assess and evaluate detoxification practice. The aim and objective of this paper is to describe the findings of audits which assessed the quality and safety of the detoxification experience and to implement changes to improve practice.

All community detoxifications in March 2009 and 2010 were included for the successive audits. Notes were inspected retrospectively three months post completion of detoxification using the audit standard.

A total of 50 and 59 people were eligible in respective audits. At 3 months post‐detoxification 23 per cent of patients had dropped out of treatment compared to 15 per cent in the re‐audit. In 2009, 31 per cent of patients remained completely abstinent and 10 per cent were drinking within safe limits but in 2010 figures improved to 36 per cent and 22 per cent, respectively. Disulfiram was continued by 66 per cent of abstinent patients in the initial audit and 89 per cent in the reaudit. Improved follow‐up protocol, regular advice and monitoring of disulfiram resulted in better abstinence and reduced drop out rates over successive years. Social and Behavioral Network Therapy and disulfiram taken under medical supervision after detoxification play a pivotal role in relapse prevention.

The study considers the importance of the post‐detoxification period, in terms of maintaining a patient's abstinence from alcohol.

Block chain technology (BCT) has emerged as a promising solution for the co-ordination and aid mechanism issues in the context of humanitarian supply chain (HSC). However, implementation of BCT in HSC discerns several barriers. Therefore, the purpose of this study is to identify and model the block chain implementation barriers in the context of HSC.

In the present study, 14 potential barriers to BCT adoption in HSC have been identified through literature survey. The survey comprises white papers, pilot studies, conference proceedings and journal articles. Further, the identified barriers were finalised in consultation with a team of experts. The team comprised experienced stakeholders working in the humanitarian domain and BCT development. The barriers were categorised into four (technological, organisational, exogenous and economic) perspectives adopting the kappa statistics. Further, the barriers were prioritised using fuzzy best worst method (FBWM) approach. Later, sensitivity analysis was performed to check the robustness and viability of the model.

The findings from the study indicate that the barriers, such as “data privacy, ownership, and security issues” (B1), “funding issues and cost complexity” (B3) and “technological complexities” (B8), are relatively more influential. The HSC stakeholders and BCT developers are required to identify the safety mechanism against the misuse of victim’s data. The funding issues and technological complexities are interrelated and need synergetic cooperation between blockchain developers, donors, humanitarian organisations (HOs) and other HSC stakeholders. Further, “lack of awareness and understanding among stakeholders” (B6) and “interoperability, collaboration and cross-pollination among HOs” (B5) were identified as least influential barriers to BCT adoption in HSC.

In literature, limited study has been observed on determining barriers to BCT implementation. A more systematic method and statistical confirmation is necessary to establish further new confronting barriers. This study is limited to Indian context.

To the best of the authors’ knowledge, this study is first of its kind to use an FBWM approach for prioritising the barriers to BCT adoption in the context of HSC. The study provides potential barriers to BCT and categorises them into four different perspectives, along with their degree of influence.