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This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

Industrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a competitive edge to the business. This paper focusses on the selection of green suppliers while simultaneously balancing economic, environmental and social issues.

In this study, it is assumed that two types of decision-makers (DMs), namely, the first level and second-level DMs operate at two separate groups in GSC. The first-level DMs always empathise to optimize carbon emissions, per unit energy consumption per product and per unit waste production, while the second-level DMs seek to optimize ordering costs, number of rejected units and number of late delivered units in the entire GSCM. In this paper, fuzzy goal programming (FGP) approach has been adopted to obtain compromise solution of the formulated problem by attaining the uppermost degree of each membership goal while reducing their deviational variables. Furthermore, demand has also been forecasted using exponential smoothing analysis. The model is verified on a real-time industrial case study.

This research enables DMs to analyse uncertainty scenarios in GSCM when information about different parameters are not known precisely.

The proposed model is restricted to vagueness only, however, DMs may need to consider probabilistic multi-choice scenarios also.

The proposed model is generic and can be applied for large-scale GSC environments with little modifications.

No prior attempt is made till date to present interval type-2 fuzzy sets in a multi-objective GSC environment where the DMs are at hierarchical levels. Interval type-2 fuzzy sets are considered as better ways to represent inconsistencies of human judgements, its incompleteness and imprecision more accurately and objectively. Also, crisp or deterministic forms of uncertain parameters have been obtained by taking expected value of the fuzzy parameters.

Logistics is the part of the supply chain (SC) that plans, executes and handles forward and reverse movement and storage of products, services and related information, in order to respond to customers' needs effectively and efficiently. The main concern for logistics is to ensure that the correct product is placed at the right time. This paper introduces a linear model of shipping focused on decision-making, which includes configuration of shipping network, choosing of transport means and transfer of individual customer shipments through a particular transport system.

In this study, authors try to address the problem of supply chain network (SCN) where the primary goal is to determine the appropriate order allocation of products from different sources to different destinations. They also seek to minimize total transportation cost and inventory cost by simultaneously determining optimal locations, flows and shipment composition. The formulated problem of getting optimal allocation turns out to be a problem of multi-objective programming, and it is solved by using the max-addition fuzzy goal programming approach, for obtaining optimal order allocation of products. Furthermore, the problem demand and supply parameters have been considered random in nature, and the maximum likelihood estimation approach has been used to assess the unknown probabilistic distribution parameters with a specified probability level (SPL).

A case study has also been applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. Results of this study are very relevant for the manufacturing sector in particular, for those facing logistics issues in SCN. It enables researchers and managers to cope with various types of uncertainty and logistics risks associated with SCN.

The principal contribution of the proposed model is the improved modelling of transportation and inventory, which are affected by different characteristics of SCN. To demonstrate computational information of the suggested methods and proposed model, a case illustration of SCN is provided. Also, environmentalism is increasingly becoming a significant global concern. Hence, the concept proposed could be extended to include environmental aspects as an objective function or constraint.

Efficient integration of logistical cost components, such as transportation costs, inventory costs, with mathematical programming models is an important open issue in logistics optimization. This study expands conventional facility location models to incorporate a range of logistic system elements such as transportation cost and different types of inventory cost, in a multi-product, multi-site network. The research is original and is focused on case studies of real life.

The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).

To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.

The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).

This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.

This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.

This study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.

In dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.

The research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.

This study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.

This research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.

Explains that a common problem of cost control at design stage is the firm’s (manager’s) desire for the lowest cost compatible with supporting innovation and the designer’s preference for the optimal design, which may be unnecessarily sophisticated. Develops a mathematical model to represent this situation, pointing out that the manager is usually unaware of the design alternatives unless they are revealed by the designer, but can use budgetary limits and “load” costs onto certain cost drivers (e.g. number of parts) to influence the designer’s choice and align his/her interests with those of the firm. Suggests that the difference between actual and “loaded” costs is a function of the non‐cost benefits from design choice (e.g. competitive edge) and the degree of information asymmetry between manager and designer. Considers the implications for costing activities and the limitations of the model.

The case captures the origin and initial years of two restaurants Mirchi & Mime and Madeira & Mime, which exclusively employed Speech and Hearing Impaired persons (SHI) as servers (often called “waiters” in India). It documents how the restaurants were set up, captures significant incidents during this initial period and the impact of these incidents on the working of the restaurants. Further, it describes the challenge of opening a fine dining restaurant and a gastropub staffed exclusively by SHI persons as servers. The case narrates the reactions and impact on the SHIs and their families, co-workers within the outlets and the customers visiting these outlets. Finally, the case lists the recognition received by the organisation and outlines plans for the immediate future.

This case attempts to study one of the key problems faced by a multinational organisation in the globalised environment that exists today: whether to outsource or insource. Outsourcing deals with getting into a contract with an outside vendor/supplier (local to the region in question) to deliver services to the parent company as per the agreed deliverables. On the other hand, insourcing deals with setting up operations in the destination country and hiring local staff on behalf of the company to do the same tasks.

Historically, outsourcing has been considered a better choice because of several benefits such as the ease of setting up operations, a predictable costing model and reduced capital investment. However, it comes with its own set of disadvantages as well, including a high attrition rate and a sub-standard level of quality in the deliverables. Apart from the quantifiable parameters, there are several qualitative parameters as well, which encompasses the employees' passion/commitment towards the company, sense of achievement and performance management process.

This case considers an existing situation in First Telecom (henceforth, referred as FT), where they have outsourced one part of their operations to multiple providers in India and are now facing huge issues with the quality of the deliverables; as a result, FT are now looking to explore if an insourced solution would be more cost-effective and productive. It evaluates the two models against various parameters and makes a recommendation on the preferred model.

This case can be used as a teaching tool in the following courses: MBA/postgraduate programme in strategic decision-making; MBA/postgraduate programme in management in management accounting and management control systems; and executive training programme for middle- and senior-level employees to look at the various factors involved (in addition to cost) that should be taken into account while comparing outsourcing versus insourcing.

FT is a communication service provider and has presence in more than 170 countries around the world. The company is considered among the top three telecom companies around the globe and offers solutions to multinational customers in the areas of networks, IP telephony, security services and other managed services.

The company has more than 100,000 employees around the globe. In addition to the regular (on rolls) employees, the company also outsources a lot of its operations in various countries to local service providers. The services that this company outsources include software/tools development, solution pricing and in-life service management. Historically, the company has believed that outsourcing is a better alternative because of the ease of setting up operations and lower cost.

However, because of the recent changes in the global market, there is a huge pressure within the company to reconsider all the functions and find ways to contain costs to help the company's bottom line.

There have been numerous complaints about the quality of output from one of the outsourced functions, namely, the “Pricing Team”, which is being presently outsourced to two service providers in India. The lack of accuracy has cost the company a key opportunity valued at more than USD5 million and the COO is furious at this loss. He has tasked the head of business improvement to do a full review of the function and look at the possible alternatives the company can explore to avoid these issues in future.

FT now wants to do a cost-comparison analysis of the existing set-up with a new insourced set-up considering all costs that would come into play. This would help FT to decide the future course of action to ensure reduced costs and enhanced operational efficiency from the process.

Understanding of cost-comparison parameters involved as an effective tool for strategy development and achieving organisational objectives; understanding of SWOT analysis (organisation level and decision level) and its applicability in the organisation context; understanding the Porter's five competitive forces model to illustrate the effect of environment on an organisation; and understanding of outsourcing and insourcing models and the pros and cons of each model, which is a key management decision in most multinational organisations.

Historical reports of the concerned unit in terms of the costs incurred, rate of attrition and operational efficiency achieved. Cost Accounting: A Managerial Emphasis, 14th ed., Charles T. Horngren, Srikant M. Datar and Madhav Rajan, Publisher: Prentice-Hall, 2012.Practical implications Based on the option (outsourcing versus insourcing) found to be better, appropriate actions would need to be taken in terms of either renewing the contracts with the outsourcing partners or preparing to terminate the existing contracts and hiring of talent from the market to replace the outsourced staff.

For nearly two decades, India as a country has grown considerably and one of the key contributors in that growth has been “Business Process Outsourcing” from all across the world to India. While the outsourcing wave has provided the initial push to the economy of India, it would not be able to help sustain the momentum primarily because of two reasons: the first is the growth of other countries, such as Hungary, the Philippines and China, as alternatives for outsourcing (and equally may be more cost-effective at times); and the second reason is the shift in various companies towards an insourcing model for critical functions.

Therefore, as a country, India needs to move ahead and, instead of only focusing on providing resources to do the tasks outsourced by global companies, focus should now shift to promoting innovation and creativity among the workforce. A lot of companies nowadays are realising the importance of product innovation and are investing huge amounts in R&D to come up with breakthrough technologies that can help them create a sustainable development model. However, this should in no way be considered an end of the outsourcing era. Although there needs to be an effort towards improving the interlock process, outsourcing is here to stay because of the benefits it brings.

The primary aim in this paper is to develop and demonstrate a theory of constraints (TOC) model in which constraint resource prevents the throughput of the organization.

In this paper, the authors propose an integrated model by combining Laplace criterion and TOC into a single evaluation model in a multiproduct constraint resource environment. A case study is illustrated to demonstrate the effectiveness of this model. The outsourcing decision model compares three alternatives: standard cost accounting, standard theory‐of‐constraints, and our own solution.

The numerical results show that the new approach is superior to Standard cost accounting and Theory of Constraints and presents a more realistic state of optimum allocation of resources and measures the performance of the model.

This research is limited to the production processes that do not have multiple constraints.

This is the first time that the integrated model comprising of Laplace‐TOC model has been used to maximize the product throughput. Instead of calculating $return per constraint minute, this method decides the priority of product that maximizes the product throughput in the constraint resource environment. It makes a significant contribution to the manufacturing Organization where one can compare the financial performance of the Organization by selecting the right decision model.