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In this chapter, the authors critically examine the application of unmeasured latent method factors (ULMFs) in human resource and organizational behavior (HROB) research, focusing on addressing common method variance (CMV). The authors explore the development and usage of ULMF to mitigate CMV and highlight key debates concerning measurement error in the HROB literature. The authors also discuss the implications of biased effect sizes and how such bias can lead HR professionals to oversell interventions. The authors provide evidence supporting the effectiveness of ULMF when a specific assumption is held: a single latent method factor contributes to the data. However, the authors dispute this assumption, noting that CMV is likely multidimensional; that is, it is complex and difficult to fix with statistical methods alone. Importantly, the authors highlight the significance of maintaining a multidimensional view of CMV, challenging the simplification of a CMV as a single source. The authors close by offering recommendations for using ULMFs in practice as well as more research into more complex forms of CMV.

For decades, consumer identification and motivation, either alone or jointly, have been essential constructs for behavioral researchers. The resultant output is significant in terms of both quality and quantity. However, at a deeper level, a lack of conceptual clarity in the relationship between these constructs has led to theoretical and practical irregularities, which this study aims to address.

An online questionnaire was distributed to sport consumers aged over 18 participating in an online panel, prompted 293 completed responses. Structural equations modeling was used to examine the data.

Findings show that identification mediates the effects of intrinsic and extrinsic motivation on sport supporters’ loyalty and explain 90% of the variance in that construct. In addition, identification mediates the adverse effects of extrinsic motivation on loyalty and strengthens loyalty when levels of satisfaction decline.

This study extends previous work by providing a theoretical perspective that clarifies the relationship between motivation and consumer identification; deepens theory by empirically observing the relationship at different levels of consumer satisfaction; and presents a parsimonious, valid and reliable method that managers can leverage to strengthen sport supporters’ loyalty.

Disruptive events caused by cyber incidents, such as supply chain (SC) cyber incidents, can affect firms’ SC operations on a large scale, causing disruptions in material, information and financial flows and impacting the availability, integrity and confidentiality of SC assets. While SC resilience (SCRES) research has received much attention in recent years, the purpose of this study is to investigate specific capabilities for building SCRES to cyber risks. Based on a nuanced understanding of SC cyber risk characteristics, this study explores how to build SC cyber resilience (SCCR) using the perspective of dynamic capability (DC) theory.

Based on 79 in-depth interviews, this qualitative study examines 28 firms representing 4 SCs in Central Europe. The researchers interpret data from semistructured interviews and secondary data using the DC perspective, which covers sensing, seizing and transforming.

The authors identify SCRES capabilities, in general, and SCCR-specific capabilities that form the basis for the realignment of DCs for addressing cyber risks in SCs. The authors argue that SCRES capabilities should, in general, be combined with specific capabilities for SCCR to deal with SC cyber risks. Based on these findings, 10 propositions for future research are provided.

Practitioners should collaborate specifically to address cyber threats and risks in SCs, integrate new SC partners and use new approaches. Furthermore, this study shows that cyber risks need to be treated differently from traditional SC risks.

This empirical study enriches the SC management literature by examining SCRES to cyber risks through the insightful lens of DCs. It identifies DCs for building SCCR, makes several managerial contributions and is among the few that apply the DC approach to address specific SC risks.

To achieve the Sustainable Development Goals (SDGs) in the era of Logistics 4.0, machine learning (ML) techniques and simulations have emerged as highly optimized tools. This study examines the operational dynamics of a supply chain (SC) in Vietnam as a case study utilizing an ML simulation approach.

A robust fuel consumption estimation model is constructed by leveraging multiple linear regression (MLR) and artificial neural network (ANN). Subsequently, the proposed model is seamlessly integrated into a cutting-edge SC simulation framework.

This paper provides valuable insights and actionable recommendations, empowering SC practitioners to optimize operational efficiencies and fostering an avenue for further scholarly investigations and advancements in this field.

This study introduces a novel approach assessing sustainable SC performance by utilizing both traditional regression and ML models to estimate transportation costs, which are then inputted into the discrete event simulation (DES) model.

We examine how superstition shapes corporate tax avoidance and do so by taking a risk perspective and focusing on the zodiac-year belief prevalent in China.

We adopt a difference-in-differences research design to compare the degree of corporate tax avoidance in the CEOs’ zodiac year with that in the adjacent years. We do propensity-score matching to form a sample of Chinese listed firms for the regression analysis.

We find causal evidence that firms exhibit a greater magnitude of tax avoidance in the CEOs’ zodiac years, a result attributable to relatively weak tax enforcement in the Chinese context. We also find that the zodiac-year effect on corporate tax avoidance is more pronounced for firms with tight financial constraints, firms with high business risk, firms headquartered in regions with a high degree of superstition and non-state-owned firms.

This study is the first to show that superstition is a determinant factor of tax avoidance and contributes to the tax literature by shedding light on the behavioral risk factors that shape corporate tax avoidance. We take the perspective of CEOs’ risk appetite to analyze how tax avoidance is influenced by the CEOs’ trade-off between the costs and benefits of avoiding taxes. Our results suggest that, when CEOs are more risk-averse, they attach more importance to financial risk than the risk of reputational losses and litigation associated with corporate tax avoidance. The findings imply that tax avoidance can be curbed by increasing (or decreasing) the tax (financial) risk confronting the CEOs.

High levels of child obesity alongside rising stunting and the absence of a coherent food policy have deemed UK’s food system to be broken. The National Food Strategy (NFS) was debated intensely in media, with discussions on how and who should fix the food system.

Using a mixed methods approach, the authors conduct framing analysis on traditional media and sentiment analysis of twitter reactions to the NFS to identify frames used to shape food system policy interventions.

The study finds evidence that the media coverage of the NFS often utilised the tropes of “culture wars” shaping the debate of who is responsible to fix the food system – the government, the public or the industry. NFS recommendations were portrayed as issues of free choice to shift the debate away from government action correcting for market failure. In contrast, the industry was showcased as equipped to intervene on its own accord. Dietary recommendations made by the NFS were depicted as hurting the poor, painting a picture of helplessness and loss of control, while their voices were omitted and not represented in traditional media.

British media’s alignment with free market economic thinking has implications for food systems reform, as it deters the government from acting and relies on the invisible hand of the market to fix the system. Media firms should move beyond tropes of culture wars to discuss interventions that reform the structural causes of the UK’s broken food systems.

As traditional media coverage struggles to capture the diversity of public perception; the authors supplement framing analysis with sentiment analysis of Twitter data. To the best of our knowledge, no such media (and social media) analysis of the NFS has been conducted. The paper is also original as it extends our understanding of how media alignment with free market economic thinking has implications for food systems reform, as it deters the government from acting and relies on the invisible hand of the market to fix the system.