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The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).

All of us are born critical thinkers; some perfect this talent; others ignore it as useful in daily life. This chapter follows those who perfected this talent in order to learn from them the art and models of critical thinking in terms of its optimal inputs, processes, and outputs. According to great critical thinkers in business management, critical thinking questions – or should question – the obsessive generalizations, constraints, and “best” practices of the prevailing system of management, and try to replace them with more valid assumptions and more meaningful generalizations that uphold the dignity, uniqueness, and inalienable rights of the individual person and the community. After setting out some cases illustrating the lack of critical thinking, in Part I of this chapter, we introduce some representative management thinkers on critical thinking, and in Part II, we introduce eight models or practical approaches for critical thinking.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

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.

The Internet of Things (IoT) is a cloud system that saves energy by being involved in the decision-making process of machines. By this means, machines create an environment of direct interaction without the need for explicit instructions. In this chapter, answers have been sought to the questions of what kind of research has been done on IoT-based technological devices, and how IoT-based technologies are effective in sustainable food production. The systematic literature review examined the scientific research on IoT and Food in the range of 2010–2022 in Scopus. The general framework of the research has been carried out in the context of 6Ws (who, when, where, what, why, and how), which is one of the systematic literature reviews. The results obtained have been analyzed and interpreted in the MAXQDA 2020 qualitative data analysis program. In the findings obtained, it has been determined that IoT and food have gained importance worldwide, especially in England, India, and China. Furthermore, it has been determined that most of the studies on IoT are based on case studies, and all the articles examined are collected in three main focus points. Subcodes have been created under the main codes ‘Food Supply Chain, Smart and Sustainable Agriculture ve Waste Management’, and problem points have been tried to be customized.

Purpose: Analysis and systematisation of global trends in the transformation of DSSs from the standpoint of solving their global and local problems and determining the central axioms of setting up and supporting business processes in DSSs.

Need of the Study: Decision Support Systems (DSSs) are the basis of doing business in an enterprise by automating business processes, keeping accounting and reducing various risks associated with complexity, labour-intensiveness, slow execution time and, therefore, potential loss of profit. In recent decades, the rapid development of DSSs has led to the emergence of complex enterprise information system architectures. At the same time, many local business processes are not implemented or are partially implemented. In Ukraine, such techniques include VAT accounting.

Methodology: The study is based on the literature analysis, Internet resources and practical experience obtained during the SAP ERP system implementation projects. Particular attention is paid to developing information systems architecture to solve the problems enterprises face during their growth. Thanks to the analysis of the example of the realisation of the Internet sales process and the induction method, the axioms of automation of business processes in accounting systems were formed.

Findings: Regardless of the qualitative and quantitative transformation, modern DSSs still cannot solve all the enterprise’s problems, mainly due to the use of paper documents and the diversity of national legislation. By the example of the SAP ERP system, the optimal implementation of the business process of VAT liabilities was proposed by Ukrainian legislation for sales below cost price.

Practical Implications: Compliance with the established axioms of automation of business processes will reduce the cost of resources for their implementation, maintenance and correction of potential errors and, therefore, will provide an opportunity to process more transactions. Implementing the proposed algorithm for calculating VAT liabilities in SAP ERP for sales below the cost price will simplify the existing process and enable the fulfilment of other requirements within the framework of current legislation.

The objective of this chapter is to discuss how different techniques in Regional Science and Peace Science and the emerging techniques in Management Science can be used in analysing Disaster Management and Global pandemic with special reference to developing countries. It is necessary for me to first discuss the subjects of Disaster Management, Regional Science, Peace Science and Management Science. The objective of this chapter is to emphasise that the studies of Disaster Management should be more integrated with socioeconomic and geographical factors. The greatest disaster facing the world is the possibility of war, particularly nuclear war, and the preparation of the means of destruction through military spending.

Common literature review methods such as systematic review and narrative review are poorly suited to the investigation of complex management phenomena. Systematic reviews are highly driven by protocol and procedure, and are oft-criticized as reductive and poorly equipped to examine the interaction between phenomena and context, nonlinear processes, and empirical outcomes that are less predictable. Narrative reviews, on the other hand, are pluralistic and iterative and thus better suited to descriptions of the complex and unpredictable; however, they tend to lack methodological transparency, trustworthiness, and pragmatism in application. The “realist synthesis” approach to literature review can be seen as the middle-ground between these two common methods, offering both methodological rigor alongside flexibility and nuance. Realist synthesis takes an explanatory frame, with a focus on unearthing the theorized causal mechanisms at play beneath a phenomenon of interest.