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Digital Twin (DT) is a concept of growing interest, driven by the technological advancements related to Industry 4.0. DT combines innovative technologies to create a virtual model replicating the physical system and allowing bi-directional data flow. However, to use DTs in support of decision-making, it is essential to have trust in the model and all components of the DT throughout its development. Verification and Validation (V&V) have traditionally been employed to assess models' credibility, providing a venue for the development of trust. Therefore, V&V are essential foundations for developing DTs that can support decisions in real-world environments. Through a systematic literature review, this research investigated whether and how researchers are employing V&V in DTs for manufacturing applications. It was concluded that very little research was reported to have performed both verification and validation of the developed DTs. The study also examined the most commonly used V&V techniques and explored their relationship with DT capability level and application areas. It was concluded that there is a lack of standard procedures to conduct V&V and a lack of agreement on the V&V objectives. This research uncovers the main challenges to verifying and validating DTs and future research directions to develop trusted DTs. [ABSTRACT FROM AUTHOR]

We evaluate the effect of online versus in-person visits on analysts' forecast performance. Our results show that online visits significantly improve the timeliness of analysts' forecasts but have a negative impact on their quality, as evidenced by inferior forecast thoroughness and accuracy. We further document that the positive association between online visits and forecast timeliness is stronger when the cost of analysts traveling to visited firms is high. The negative association between online visits and forecast quality is stronger for firms with more complex information and fewer managers interacting with analysts. In addition, we find that managers' communication style is more cautious and more vague when interacting online, indicating that issues of trust worsen the online communication environment. We also find that, in contrast to nonvisits, online visits provide analysts with an idiosyncratic informational advantage. Overall, our results provide an empirical evaluation of the economic consequences of analysts' online versus in-person visits. [ABSTRACT FROM AUTHOR]

Purpose: This systematic review aimed at identifying, categorizing, and analyzing peer-reviewed literature on organized before- and after-school (B&ASP) physical activity programs from 2000 to 2020. Methods: We analyzed 291 articles that fit the inclusion criteria from five databases. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines were followed. Results: Research on B&ASPs has increased and been published in 157 journals across 26 countries. Most studies were quantitative. Most studies used a theoretical or conceptual framework and reported reliability, validity, and trustworthiness. Varied additional foci of impact were reported through different physical activities. However, physical activity was usually not measured. Interventions were 1–520 weeks long and conducted in different study contexts. Many studies targeted marginalized groups but did not utilize critical theory. Conclusion: Further studies should aim to better understand the nuances of B&ASPs, and critical theories could be useful. The lack of journals for B&ASP research limits scholars' ability to move the field forward. [ABSTRACT FROM AUTHOR]

Food products' quality information is advertised on labels but do customers trust them? This study investigates how the consumers' Willingness-To-Pay (WTP) for food products can be increased by deploying managerial effort and advanced technologies, such as the Blockchain Technology (BT). Our model explains how revealing verified information about product quality throughout the supply chain will generate optimal consumers' WTP and maximise profit. At each echelon of a multi-echelon supply chain, a buyer holds a Bayesian belief about the quality of the input to be procured. This belief is shaped by the accuracy and veracity of the information about this quality. Managerial effort is required both to enhance quality as well as ensure full and verified information. We show why this effort must be made across the chain and how opportunistic behaviour may be circumscribed. Using empirically grounded analytics and real prices of olive oil intermediate produce from various official bodies, we show how the application of BT may be financially justified. This research shows how trust and WTP can be further enhanced through the use of BT and additional smart technologies in a supply chain, which may be projected on other supply chains of organic and sustainable food products. [ABSTRACT FROM AUTHOR]

People have conflicting responses for support from algorithms or humans in decision-making. On the one hand, they fail to benefit from algorithms due to algorithm aversion, as they reject decisions provided by algorithms more frequently than those made by humans. On the other hand, many prefer algorithmic over human advice, an effect of algorithm appreciation. However, currently, we lack a shared understanding of these constructs’ meaning and measurements, resulting in a lack of theoretical integration of empirical findings. Thus, in this research note, we conceptualize algorithm aversion as the preference for humans over algorithms in decision-making and analyze approaches in current research to measure this preference. First, we outline the implications of focusing on a specific understanding of algorithms as computational procedures or as embedded in material or nonmaterial objects. Then, we classify four decision configurations that distinguish individuals’ evaluations of algorithms, human advisors, their own judgments, or combinations of these. Consequently, we develop a classification scheme that provides guidance for future research to develop more specific hypotheses on the direction of preferences (aversion vs. appreciation) and the effect of moderators. [ABSTRACT FROM AUTHOR]

The rise of digital technologies and open innovation has revolutionized innovation practices, creating new opportunities for moving born-physical open innovation settings to metaverse-like virtual environments. This study explores a virtual corporate-startup collaboration program in the energy industry to understand how digital feature usage facilitates trusted relationships and enables successful pilots. This article presents a framework that emphasizes the strategic use of digital information and interaction features for targeting and bonding with partners. Program managers can tackle the unrealized metaverse through ubiquitous program management and overcome social barriers through adaptive social engineering of digital interactions. This article also provides an outlook on evolving technologies and hybrid designs. [ABSTRACT FROM AUTHOR]