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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.

The purpose of this study was to investigate how and through which social-cognitive constructs, emotions influence healthy food shopping behaviors. Direct effects of those constructs, as well as indirect effects of consumer emotions are considered.

An altered version of the Social Cognitive Theory, including intention, socio-structural factors, outcome expectancies and self-efficacy with the addition of consumer emotions was analyzed using structural equation modeling. Data of 1,181 volunteers were collected in Germany in 2021 through an online survey.

Intention was the most important positive predictor of food choice, while socio-structural factors had the biggest impact on intentions. Those were mostly influenced by self-efficacy, which was strongly predicted by consumer emotions. Outcome expectancies did not influence the current model in any way. Consumer emotions did not directly influence intention, nor actual choice, however showed to be influencing those variables through indirect effects.

Marketers could benefit from these results by incorporating the current findings into existing marketing strategies through targeting a combination of social cognitive constructs, as well as consumer emotions to facilitate healthier food shopping behavior.

Affect has received increasing attention in regards to its impact on healthy eating behaviors in recent years. Less attention has been paid to the mechanisms through which emotions influence healthy nutrition behavior, specifically how consumer emotions influence healthy food shopping behavior.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

The purpose of this study was to investigate the impact of Corona virus disease on the perceived values of urban green landscapes in a developing country setting. To achieve this objective, the author investigated changes in the preferences for urban green space services among city residents who use nature areas for recreation.

This study applied the best–worst scaling technique to elicit changes in the preferences for ecosystem services from urban recreational sites in Malawi. The study also used a fractional logit model to examine factors that motivate visitors’ willingness to donate/contribute to improve the quality of nature’s recreational services.

This study finds that the COVID-19 pandemic changed visitors’ perceptions of urban woodlands, but leisure/recreation remained the most important service with or without the Corona virus outbreak. However, the perceived value of air pollution control and cultural/religious functions gained more prominence (+3%), whereas biodiversity conservation became less prominent (−2%) during the pandemic period. The mean willingness to pay (WTP) was estimated to be US$28.73, and WTP is positively influenced by education, income status and the user’s satisfaction with the recreation site.

The study substantiated the impact of Corona virus disease on the perceived values of urban green landscapes, using Malawi as a case study. This was demonstrated through the changes in preferences for urban green space services among city residents who use nature areas for recreation.