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The primary objective of this chapter is to synthesize and organize prevailing theoretical perspectives on metacognition into a framework that can enhance understanding of metacognitive phenomena, with the aim of stimulating future research in the field of organizational behavior and human resources management (OBHRM). The author starts with a review of the history of metacognition research, distinguishing it from related theoretical constructs such as cognition, executive function, and self-regulation. Following this, the author outlines five constituent elements of metacognition – metacognitive knowledge, metacognitive experiences, metacognitive monitoring, a dynamic mental model, and metacognitive control – with discussions on their interrelationships and respective functions. Two approaches to metacognition, a process approach and an individual-difference approach, are then presented, summarizing key questions and findings from each. Finally, three broad directions for future research in OBHRM are proposed: examining metacognitive processes, considering mechanisms beyond learning to explain the effects of metacognition, and exploring both domain-specific and general metacognitive knowledge and skills. The implications of these research directions for personnel and human resources management practices are discussed.

This chapter discusses how the real options theory can be useful for understanding the adoption of human resources management (HRM) practices. The authors review how the real options theory has provided insights into the processes through which firms manage uncertainties involved in the adoption of HRM practices. The authors offer propositions for future HRM research from the real options perspective. The authors contend that analyzing HRM practice adoptions through the lens of real options theory can enhance our understanding of the mechanisms through which firms choose which HRM practices to adopt and how they adjust the timing, scale, and methods of investment in these practices. Specifically, the authors suggest that differences in information relevant to valuation of HRM options are the source of distinct choices of HRM options across firms. Finally, the authors propose advancing knowledge on HRM practice adoptions by using a portfolio of options approach, as well as considering factors like competitors, path dependence, and switching options.

This study aims to understand client food preferences and how pantry offerings can be optimized by those preferences.

This study develops and administers customized surveys to study three food pantries within the Second Harvest Food Bank of Northwestern North Carolina network. This study then categorizes food items by client preferences, identifies the key predictors of those preferences and obtains preference scores by fitting the data to a predictive model. The preference scores are subsequently used in an optimization model that suggests an ideal mix of food items to stock based upon client preferences and the item and weight limits imposed by the pantry.

This study found that food pantry clients prefer fresh and frozen foods over shelf-friendly options and that gender, age and religion were the primary predictors. The optimization model incorporates these preferences, yielding an optimal stocking strategy for the pantry.

This research is based on a specific food bank network, and therefore, the client preferences may not be generalizable to other food banks. However, the framework and corresponding optimization model is generalizable to other food aid supply chains.

This study provides insights for food pantry managers to make informed decisions about stocking the pantry shelves based on the client’s preferences.

An emerging topic within the humanitarian food aid community is better matching of food availability with food that is desired in a way that minimizes food waste. This is achieved by providing more choice to food pantry users. This work shows how pantries can incorporate client preferences in inventory stocking decisions.

This study contributes to the literature on food pantry operations by providing a novel decision support system for pantry managers to aid in stocking their shelves according to client preferences.

In his classic World Risk Society (1999) Ulrich Beck emphasised modernisation entails a relentless wave of human-made disasters—toxic spills, industrial accidents, transportation stoppages, and power outages, for example. Simultaneously these modern ‘risk societies’ must also withstand natural disasters such as floods, hurricanes, and earthquakes. Building on Beck’s principle that disaster risks accumulate as societies advance technologically, we explore the necessity of public health and political leadership to win over support of the traditional ethnic Black community to implement effectively COVID-19 pandemic policies. The term Black community used in this chapter has been used only for representation and must be interpreted broadly beyond ethnic and discriminatory limitations.

This chapter will show that, to reach their COVID-19 pandemic control objectives, US public health and political officials had to incorporate the longstanding ethnic and racial identity of Black communities. These authorities did this by utilising traditional cultural resources of Black communities such as churches and popular cultural figures. Political, corporate, and public health leadership was also heavily influenced by the Black protests in the months following the George Floyd police murder. Medical policy authorities publicly endorsed and advocated the health and social justice grievances of Black communities while the George Floyd riots raged. This US case study illustrates the power of the ethnic dimension and ideological anti-racism in society’s response to the increasingly complex web of disasters including the COVID-19 pandemic.

This historical example of the creation of the arms industry in the Connecticut River Valley in the 1800s provides new insights into the value of government venture capital (GVC) and government demand in creating a new industry. Since current theoretical explanations of the best uses of governmental venture capital are still under development, there is considerable need for further theory development to explain and predict the creation of an industry and especially those industries where failures in private capital supply necessitates governmental involvement in new firm creation. The purpose of this paper is to provide an in depth historical review of how the arms industry evolved spurred by GVC and government created demand.

This study uses abductive inference as the best way to build and test emerging theories and advancing theoretical explanations of the best uses of GVC and governmental demand to achieve socially required outcomes.

By observing this specific historical example in detail, the authors add to the understanding of value creation caused by governmental venture capital funding of existing theory. A major contribution of this paper is to advance theory based on detailed observation.

The relatively limited research literature and theory development on governmental venture capital funding and the critical success factors in startups are enriched by this abductive investigation of the creation of the historically important arms industry and its spillover into creating the specialized machine industry.

In this chapter, I will outline the labels of giftedness and underachievement and present the theoretical debates surrounding these labels. A historicist examination of these labels follows, highlighting how the gifted underachievement (GUA) label emerges through the negation of “giftedness.” Subsequently, I explore the concept of GUA and its negative connotations, stemming from the positive valuation inherent in the term “giftedness” and its implications for what is considered “normal.” This chapter also reviews perspectives on shifting the focus away from the individual within the current paradigm of labeling giftedness and explores insights from systemic thinking and symbolic interactionism (SI). The conclusion underscores the necessity of a symbolic interactionist perspective to address the gaps in research on the labeling of giftedness and underachievement. Finally, I propose a generic definition that can be used in GUA research in the light of SI.

This study aims to bring together the available scattered knowledge about teaching and learning in Living Labs within higher education, and to explore their potential for supporting students’ sustainability-oriented transformative learning.

A literature review was conducted, applying a realist approach. A sample of 35 articles was analyzed qualitatively, mapping the data according to the realist constructs “context,” “intervention,” “mechanism” and “outcome” and using the constant comparison method for data analysis.

This study identified multiple characteristics of teaching and learning in sustainability-oriented Living Labs, namely, two socio-physical teaching and learning contexts, two pedagogical approaches as interventions therein, four learning processes as (potential) mechanisms and six sustainability-related learning outcomes. Two main challenges were also identified.

To the best of the authors’ knowledge, this is the first study that brings together the scattered results from previous studies into a comprehensive description of characteristics and challenges of teaching and learning in Living Labs as sustainability-oriented learning spaces in higher education. The findings can support educators in making scientifically grounded informed choices for teaching and learning in Living Labs and inform future empirical studies to examine when, how and why certain characteristics of teaching and learning in Living Labs, as identified in this study, can support sustainability-oriented transformative learning in higher education.

This study aims to clarify the direct impact of digitalization on export performance (EP) by synthesizing previous research and testing this relationship empirically. Furthermore, the study investigates digitalization types, contextual moderators and method moderators affecting the impact of digitalization on EP.

The study uses meta-analysis to test the digitalization–EP relationship (k = 81) using data from 106 independent samples involving 62,082 respondents across nearly 30 countries.

The study finds digitalization’s positive and significant effect on EP (r = 0.36). The impact of digitalization on EP is also subject to different moderators, including digitalization type (i.e. digital capabilities), contextual factors (i.e. institutions, export experience, development of the region and industry) and method factors (i.e. back translation and strategy measurement).

Scholars have initiated studies on the impacts of diverse digitalization types on EP, while empirical findings on these effects remain inconclusive. Based on resource-based theory, the study develops and validates a comprehensive meta-analytic framework, revealing the important influence of digitalization on EP. The moderator findings further highlight the impact of internal and external contingencies on the outcomes of exporting firms’ digitalization.