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This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

Hazel Kyrk, one of the first women economists at the Economic Department of the University of Chicago and author of A Theory of Consumption (1923), conducted groundbreaking research for the Bureau of Home Economics of the US Department of Agriculture and the Bureau of Labor Statistics. Kyrk made a considerable contribution to the development of standards for a “decent living,” the Consumer Price Index, and the conceptualization of what would later turn into the definition of the poverty line. This chapter evaluates Kyrk’s use of eugenic notions of gender and race that were widely used in Kyrk’s day. This chapter shows that eugenic reasoning impacts Kyrk’s theoretical work only superficially but does structure her research on consumption standards through her focus on the white middle-class family as the unit of analysis for consumer behavior. This chapter also makes clear that the American Institutionalist approach to consumer behavior, rather than marginalized and side-tracked due to a lack of theoretical progress, was relegated to the margins of economics science together with the research of women economists into Home Economics departments and policy research at government institutions.

Sentiment analysis is a text analysis method that is developed for systematically detecting, identifying, or extracting the emotional intent of words to infer if the text expresses a positive or negative tone. Although this novel method has opened an exciting new avenue for organizational research – mainly due to the abundantly available text data in organizations and the well-developed sentiment analysis techniques, it has also posed a serious challenge to many organizational researchers. This chapter aims to introduce the sentiment analysis method in the text mining area to the organizational research community. In this chapter, the authors first briefly discuss the central role of sentiment in organizational research and then introduce the traditional and modern approaches to sentiment analysis. The authors further delineate research paradigms for text analysis research, advocating the iterative research paradigm (cf., inductive and deductive research paradigms) that is more suitable for text mining research, and also introduce the analytical procedures for sentiment analysis with three stages – discovery, measurement, and inference. More importantly, the authors highlight both the dictionary-based and machine learning (ML) approaches in the measurement stage, with special coverage on deep learning and word embedding techniques as the latest breakthroughs in sentiment and text analyses. Lastly, the authors provide two illustrative examples to demonstrate the applications of sentiment analysis in organizational research. It is the authors’ hope that this chapter – by providing these practical guidelines – will help facilitate more applications of this novel method in organizational research in the future.

Purpose of This Chapter: This study explores the positive chain effects of Employee-Centered CSR (ECCSR) in harmonizing the current challenges of The Great Resignation from the perspective of employees’ well-being.

Design / Methodology / Approach: The quantitative approach was used to test the proposed research model by using a self-responded questionnaire. Purposive judgemental sampling was applied to qualify the respondents based on the criteria that they are gainfully employed now and during the pandemic. The responses gathered were analyzed using structural equation modelling (SEM).

Findings: The findings show that ECCSR significantly and positively influences employees’ well-being, specifically workplace well-being (β = 0.793), social well-being (β = 0.761), psychological well-being (β = 0.712), and subjective well-being (β = 0.611). The PLSpredict results reveal that the proposed research model possesses the predictive relevance of ECCSR in reflecting the reality of employees’ well-being.

Research Limitations: The data were collected in the post-pandemic phase to capture the employees’ state of mind. Hence, the findings may not represent the normal business cycle challenges.

Practical Implications: The empirical evidence suggests that depressing organizations to consider implementing ECCSR for employees’ well-being which in turn enables the organizations to navigate through turbulent times a little easier.

Originality: The novelty of this study is attributed to the positive and detailed findings of ECCSR in the context of employee well-being for organizational resilience.

Purpose: The purpose of this study is to identify the elements that can enhance financial inclusion (FI) in a nation, which in turn promotes economic development and growth.

Need for the Study: FI is crucial in providing people with the skills and resources to manage their money effectively and make informed financial decisions. Accessible, reliable and secure financial services play a significant role in achieving sustainable development goals (SDGs) and fostering economic progress.

Methodology: Data from 571 respondents were collected for analysis. The study utilises Statistical Package for Social Sciences SPSS and Analysis of Moment Structures AMOS software to analyse data and achieve the study’s objectives. The researchers employ these tools to obtain substantial results.

Findings: The findings indicate that FI contributes to economic growth (84%) and helps in accomplishing SDGs. Access, usage, affordability, technology, availability and technology adoption all play a vital role in increasing FI in the nation.

Practical Implications: The study’s outcomes have practical implications for policymakers and stakeholders, emphasising the importance of promoting FI through various measures such as enhancing access, affordability and technological advancements in financial services.

The aim of this chapter is to stimulate debate and critical thinking about the relevance and effectiveness – especially for ‘non-core’ areas – of prevailing methodological approaches to entrepreneurial ecosystems (EE) research and policy development and to argue for the exploration of critical realism (CR) as a potential framework for researchers, practitioners and policymakers. I argue that prevailing theoretical and methodological frameworks are insufficient to enable researchers to adequately understand the dynamics of diverse EE or for policymakers to act appropriately on research findings. I posit CR as an alternative framework, providing a ‘lens’ through which researchers, policymakers and other ecosystem stakeholders can collaboratively explore the role of context and its interplay with agency. CR addresses the disadvantages associated with deterministic models of entrepreneurship and ‘Valley envy’ policy prescriptions, thus generating more meaningful insights for policy and practice, especially in relation to ‘non-core’ areas.

This study investigates the impact of corporate social responsibility (CSR) on corporate innovation. We selected the listed nonfinancial firms of South Asian Economies. The sample of the study comprised a total of 426 listed manufacturing firms of South Asian Countries for period spans 10 years from 2012 to 2021. In this study, descriptive statistics, multicollinearity diagnostic tests, correlation analysis and two-step dynamic panel system generalized method of moments (GMM) were applied to analyze the data. CSR measured with three proxies' social indicators, environmental indicators, and CSR composite index of social and environmental indicators. However, corporate innovation is captured with number of citations received in a year and number of patents filed in the year. Overall, findings of the study using all measures of CSR shows that CSR significantly and positively related with corporate innovation. Our results find support for CSR-innovation view with all measures of CSR. The findings suggest that the current study is helpful for managers, regulators, policymakers, and researchers. For managers, the study helps them to make the CSR and innovation decision. The policymakers should take appropriate innovative decision while considering factors such as CSR. This study can also be extended by considering this study for developed and emerging economies sample.

Introduction: Cost competitiveness, customer focus, and sustainability compliance are essential for new-age firms to survive and succeed in the VUCA market environment. This study examines how automobile corporations have improved cost competitiveness, productivity, and product quality.

Purpose: This study examines the importance of cost competitiveness, customer focus, and sustainability compliance for the long-term survival of organisations in VUCA markets, looking at the practical efforts made by automobile corporations to enhance cost competitiveness, productivity, and quality.

Methodology: The study utilises a comprehensive analysis of the strategies and initiatives implemented by the selected automobile companies. It involves a review of relevant literature, case studies, financial data analysis, and interviews with key industry experts, providing a holistic understanding of the actions taken by these organisations to achieve their goals.

Findings: The study reveals that cost competitiveness, customer focus, and sustainability compliance are critical factors for the long-term survival and success of organisations in the automotive industry. The analysed automobile companies have undertaken practical efforts to improve cost competitiveness, enhance productivity, and ensure high-quality products, enabling them to navigate the challenges and maintain a competitive edge.

Significance: The findings of this study contribute to a deeper understanding of the importance of cost competitiveness, customer focus, and sustainability compliance in the automotive industry. It highlights the need for organisations to constantly monitor both qualitative and quantitative profit to avoid complacency and ensure long-term efficiency. The study’s insights are relevant to businesses operating in other sectors, as they face similar challenges in the VUCA market environment.