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Introduction: A company or organisation must resolve various problems in the business environment for better operation in any corporate environment. Such issues are traditionally handled in multiple ways. A small sector unit with many employees encounters this corporate issue, for example, the handicraft sector. The impact of handicraft issues and their intensity, speed, and regularity is growing in our system.

Purpose: This chapter studies how small businesses might succeed in the handcraft industry in a volatile, uncertain, complex, and ambiguous (VUCA) environment. There is a lack of proper knowledge of how the VUCA affects business proficiency in the Indian handicraft sector. A novel business strategy for the handicraft sector, like other business proficiency called best practices in handicraft business in a VUCA environment, will be presented along with a discussion about VUCA environments. This considers both the individual influences of each particular word and the overall impact of VUCA.

Methodology: The study included a thorough literature analysis for three learning areas: performance improvement, including VUCA, and the leadership incorporation of risk and quality. Awareness in the trade will be examined in further sections, as the mastery of VUCA is achieved with various traditional and digital management ideas.

Findings: The research defined a new unorganised firm concept to maintain and succeed in a high VUCA environment in the handicraft sector, identifying 18 important success characteristics through a comprehensive literature review. The authors proposed a conceptual framework for fusing quality management to attain proficiency in the handicraft sector VUCA environment.

Purpose: Preserving a country’s culture is crucial for its sustainability. Handicraft is a key draw for tourism destinations; it protects any civilisation’s indigenous knowledge and culture by managing the historical, economic, and ecological ecosystems and perfectly aligns with sustainable development. It has a significant role in creating employment, especially in rural regions and is an essential contributor to the export economy, mainly in developing nations. The study focuses on the skills required and existing gaps in the handicraft industry, its development and prospects by considering women and their role in preserving and embodying the traditional art of making handicrafts.

Approach: A framework has been developed for mapping and analysing the skills required in the handicraft sector using econometric modelling; an enormous number of skills have been crowdsourced from the respondents, and machine learning techniques have been used.

Findings: The findings of the study revealed that employment in this area is dependent not only on general or specialised skills but also on complex matrix skills ranging from punctuality to working in unclean and unsafe environments, along with a set of personal qualities, such as taking initiatives and specific skills, for example polishing and colour coding.

Implications: The skills mapping technique utilised in this study is applicable globally, particularly for women indulged in casual work in developing nations’ handicrafts industry. The sustainable development goals, tourism, and handicrafts are all interconnected. The research includes understanding skills mapping, which provides insights into efficient job matching by incorporating preferences and studying the demand side of casual working by women in the handicraft sector from a skills perspective.

The purpose of this paper is to provide a way to analyze satellite images using various clustering algorithms and refined bitplane methods with other supporting techniques to prove the superiority of RIFCM.

A comparative study has been carried out using RIFCM with other related algorithms from their suitability in analysis of satellite images with other supporting techniques which segments the images for further process for the benefit of societal problems. Four images were selected dealing with hills, freshwater, freshwatervally and drought satellite images.

The superiority of the proposed algorithm, RIFCM with refined bitplane towards other clustering techniques with other supporting methods clustering, has been found and as such the comparison, has been made by applying four metrics (Otsu (Max-Min), PSNR and RMSE (40%-60%-Min-Max), histogram analysis (Max-Max), DB index and D index (Max-Min)) and proved that the RIFCM algorithm with refined bitplane yielded robust results with efficient performance, reduction in the metrics and time complexity of depth computation of satellite images for further process of an image.

For better clustering of satellite images like lands, hills, freshwater, freshwatervalley, drought, etc. of satellite images is an achievement.

The existing system extends the novel framework to provide a more explicit way to analyze an image by removing distortions with refined bitplane slicing using the proposed algorithm of rough intuitionistic fuzzy c-means to show the superiority of RIFCM.

This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.

In the present study, we examined how effectively online travel agencies (OTAs) handle negative e-word-of-mouth on social media platforms like Facebook, Twitter, and Instagram. We collected data from 497 participants using survey method. To test the hypotheses formulated from the existing literature, structural equation modeling was adopted in this study. The results from structural equation modeling indicate effective handling of the negative e-word of mouth (e-WOM) on social media websites significantly affects customer satisfaction and repurchase intention. The current research work provides insight into social media recovery efforts and service fairness when handling negative e-WOM. The study recommends that customers can distinguish the differences between general efforts and adaptive complaint-handling efforts, and dissimilarities may influence satisfaction, repurchase intentions, etc. Although empathy, apology, responsiveness, and paraphrasing are considered pioneer strategies in complaint handling, customers' negative e-WOM, and firms' recovery management, but the current study is among a few to categorize OTAs' handling of negative e-WOM and complaint handling efforts in the social media environment.

Purpose: This chapter investigates the current skill gap in small-scale industries, the need for skill development and digital training in micro, small, and medium enterprises (MSME), and reviews policies for skill development and solutions.

Need for the Study: While the legislature and organisations have initiated various considerations for the successful implementation of the Skill Development System in the country’s MSMEs, there are significant challenges that must be addressed quickly to fill the skill gap in workers in this digital era.

Research Methodology: Secondary data has been used for the chapter review. Analysis has been done based on review data from women handloom and handicraft workers in the micro or craft industry who received a Star rating from the National Skill Development Corporation (NSDC) partners in Lucknow. For data collection, a questionnaire based on random sampling was used. The data were analysed using a rudimentary weighted average and a percentage technique.

Findings: The studies provide answers to some fundamental problems: are small industry employees indeed mobilised to be skilled outside the official schooling system? Is the training delivery mechanism adequate to prepare pupils for employment? Would industries be willing to reduce minimum qualification criteria to foster skill development?

Practical Implication: Non-technical aptitudes digital and soft skills for workers in this sector should be emphasised in MSMEs, and significant reforms in MSME sectors and capacity-building education and training programmes should be implemented in the Indian industry to generate small and medium enterprises production and employment.

In recent times, there has been a lot of research focused on performance measurement (PM) in project-based sectors. However, there are very few studies that were reported on the significance of PM in the construction sector. Keeping track of an organization in achieving organizations goals and objectives seems an important way. One of the major challenges faced by the industry is unavailable of an appropriate PM system for assessing organizational performance. Most of the PM approaches consider the traditional project triangle assessment of project success. Based on the limitations identified in existing PM models, the purpose of this paper is to develop a comprehensive PM model, i.e. Modified Project Quarter Back Rating (MPQR) applicable for construction projects.

A detailed list of performance areas as a method for PM is analyzed in the construction industry context. Also, industry-specific professionals conducted semi-structured interviews to assess whether these performance areas are sufficient to measure and understand the PM systems.

The research finding focuses on developing the MPQR model that considers both financial and non-financial areas for performance assessment to provide a holistic assessment of project performance.

MPQR model provides an opportunity to set the benchmark for overall performance for construction organizations.

The findings of the study are expected to provide guidelines to construction professionals for implementing the performance model that will improve performance in the construction industry.