Search results

This chapter of the book aims to achieve sustainability and productivity in light of the interaction between managers and engineers in a lean and agile supply chain management system in today’s organizations. The main innovation of this chapter is the use of the balanced scorecard (BSC) model and fuzzy analysis network process (FANP) to create a suitable platform for the realization of this interaction between managers and engineers and to identify exactly which expert system is ideal for the main purpose. Indeed, this chapter introduces its readers to the application of strategic management tools such as the BSC accompanied by FANP in the elements of supply chain management where data analysis of lean and agile networks in supply chain management can create a competitive advantage in the organization.

Quality management is high on the reform agenda of both universities and hospitals. This paper studies how quality management is implemented: who is responsible for QM and which instruments are used? The guiding research question is whether these two very distinct professional organizations respond in similar or different ways to a common reform trend. To analyze the extent of isomorphic tendencies a cross-sectoral, descriptive data analysis with data from 135 hospitals and 83 universities in Germany has been conducted. The results show that QM in hospitals is more elaborated in terms of quality instruments and at the same time more standardized. Universities, in contrast, follow quite individualistic ways to organize quality management.

The academic library is an important component of any university and is responsible for providing academic and research support to all members of the university community. At present, higher education institutions in Thailand are trying to evaluate and improve their quality by implementing quality assurance models/mechanisms. Libraries, as critical supporting organizations in these institutions, also need to improve their quality. As a service organization, academic libraries are faced with the need to satisfy their clientele and to measure and evaluate their services. There is a need, therefore, for librarians to take positive steps to insure that their clients receive quality services.

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.

How should economists incorporate culture into their economic analysis? What empirical approaches to identifying, measuring, and analyzing the relationship between culture and economic action are most appropriate for economists? In particular, what can experimental economists learn from the methods of economic anthropologists, sociologists, and historians who study culture? We argue that while both quantitative and qualitative approaches can reveal interesting relationships between culture and economic actions/outcomes, especially in experimental research designs, qualitative methods help economists better understand people’s economic choices and the economic outcomes that emerge from those choices. This is because qualitative studies conceptualize culture as a pattern of meaning, take the relevant cultural data to be people’s thoughts and feelings, treat the market as a cultural phenomenon, and allow for novel explanations.

Conventional wisdom regarding the gains from globalization states that, if managed correctly, it can lead to increased market opportunities for firms to grow and prosper, including small and medium enterprises (SMEs). Nevertheless, some sectoral case studies raise questions regarding the terms under which SMEs in developing countries participate in global production systems and the scope of opportunities that globalized markets actually do offer for industrial development and SME upgrading in developing countries.

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.