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Privacy and security concerns of consumers have been touted as one of the hindrances to the growth of e-commerce. These concerns increase the risk perception of consumers. Understanding the consequences of privacy and security concerns and their relationship to risk perceptions may provide a solution. The relationship between privacy and security is investigated using the theory of planned behavior. The study aims to examine the relationship of trust, privacy and security concerns to the risk perception adoption of e-commerce. The results from a survey validate the model.

Data were collected using survey from undergraduate business students. The respondents were requested to select a specific product that they plan to purchase in the next six months. After selecting a product, the respondents were requested to report an online company that they have recently visited which offers the selected product. The respondents were requested to fill out the survey with regard to their selected online company. Time given was approximately 20 min.

The results suggest that privacy and security concerns and trust beliefs had effects on risk perception. Among these effects, trust had the largest effect followed by privacy and security concerns. Furthermore, risk perception and trust beliefs had effects on attitude. The effect of trust beliefs on attitude was larger than the effect of risk perception on attitude. Similarly, subjective norm, perceived behavioral control and attitude had a positive and direct effect on intention to be involved in e-commerce.

The first limitation of this study is the use of student subjects. Because this study took place in an educational setting, its generalizability to the general population of consumers lacks to some degree. The second limitation of this study is mono-method bias.

The effect of privacy concerns on risk perception was larger than that of security concerns. Because the consumers get more experienced and sophisticated using the Web, the security concerns that they may have had at the beginning are not reflected in their risk perceptions. It is likely that they have adopted protective measures on their own to defend their privacy online. An example of such a measure would be providing false information to online companies when asked to submit personal information.

The major contributions of this study are developing and validating an integrative framework of e-commerce adoption at the individual level. The model includes privacy and security concerns, risk perception and trust beliefs. This study also highlighted the distinction of constructs of privacy and security concerns and showed their differential effects on other related constructs in the research model.

The purpose of this paper is to propose an automated machine learning (AutoML) and multi-agent system approach to improve overall product delivery satisfaction under limited resources.

An AutoML method is purposed to model delivery satisfaction of individual customer, and a heuristic method and multi-agent system are proposed to improve overall satisfaction under limited processing capability. A series of simulation experiments have been conducted to illustrate the effectiveness of the proposed methodology.

The simulated results show that the proposed method can effectively improve overall delivery satisfaction, especially when the demand of customer orders is highly fluctuating and when the customer satisfaction models are highly diversified.

The proposed framework provides a more dynamic and continuously improving way to model delivery satisfaction of individual customer, thereby supports companies to provide personalized services and develop scalable and flexible business at a lower cost, and ultimately improves the overall quality, efficiency and effectiveness of delivery services.

The proposed methodology utilizes AutoML and multi-agent system to model individual customer delivery satisfaction and improve the overall satisfaction. It can cooperate with the existing delivery resource planning methods to further improve customer delivery satisfaction. The authors propose an AutoML approach to model individual customer delivery satisfaction, which enables continuous update and improvements. The authors propose multi-agent system and a heuristic method to improve overall delivery satisfaction. The numerical results show that the proposed method can improve overall delivery satisfaction with limited processing capability.

Machine learning (ML) has recently gained momentum as a method for measurement in strategy research. Yet, little guidance exists regarding how to appropriately apply the method for this purpose in our discipline. We address this by offering a guide to the application of ML in strategy research, with a particular emphasis on data handling practices that should improve our ability to accurately measure our constructs of interest using ML techniques. We offer a brief overview of ML methodologies that can be used for measurement before describing key challenges that exist when applying those methods for this purpose in strategy research (i.e., sample sizes, data noise, and construct complexity). We then outline a theory-driven approach to help scholars overcome these challenges and improve data handling and the subsequent application of ML techniques in strategy research. We demonstrate the efficacy of our approach by applying it to create a linguistic measure of CEOs' motivational needs in a sample of S&P 500 firms. We conclude by describing steps scholars can take after creating ML-based measures to continue to improve the application of ML in strategy research.

Although there have been considerable discussions on the business value of adopting blockchain in supply chains, it is unclear whether such blockchain-enabled supply chains (BESCs) can help firms mitigate the negative impact resulting from the recent COVID-19 pandemic. This study aims to answer this important question.

The authors conduct an event study to quantify the financial effects of the COVID-19 pandemic and compare the differences in such effects between treatment firms that have adopted BESCs and matched control firms that have not adopted BESCs. The authors also perform a regression analysis to examine how the role of BESCs in mitigating COVID-19's negative impact varies across firms with different levels of supply chain leanness and complexity. The analysis is based on 88 treatment firms and 88 matched control firms, all of which are publicly listed on the US stock markets.

The test results suggest that although both the treatment and control firms are negatively affected by the COVID-19 pandemic, the effect is less negative for the treatment firms compared to the control firms, demonstrating the role of BESCs in mitigating the negative impact caused by the COVID-19 pandemic. Moreover, the mitigating role of BESCs is more pronounced for firms with lean and complex supply chains.

This study is among the first to provide empirical evidence on the mitigating role of BESCs during the COVID-19 pandemic, highlighting the importance of adopting blockchain in supply chains with high uncertainties and disruption risks.

This paper presents recently published resources on library instruction and information literacy. It provides an introductory overview and a selected annotated bibliography of publications covering various library types, study populations and research contexts. The selected bibliography is useful to efficiently keep up with trends in library instruction for busy practitioners, library science students and those wishing to learn about information literacy in other contexts.

This article annotates 424 English-language periodical articles, monographs, dissertations, theses and reports on library instruction and information literacy published in 2021. The sources were selected from the EBSCO platform for Library, Information Science, and Technology Abstracts (LISTA), Education Resources Information Center (ERIC), Scopus, ProQuest Dissertations and Theses, and WorldCat, published in 2021 that included the terms “information literacy,” “library instruction,” or “information fluency” in the title, abstract or keywords. The sources were organized in Zotero. Annotations summarize the source, focusing on the findings or implications. Each source was categorized into one of seven pre-determined categories: K-12 Education, Children and Adolescents; Academic and Professional Programs; Everyday Life, Community, and the Workplace; Libraries and Health Information Literacy; Multiple Library Types; and Other Information Literacy Research and Theory.

The paper provides a brief description of 424 sources and highlights sources that contain unique or significant scholarly contributions.

The information may be used by librarians, researchers and anyone interested as a quick and comprehensive reference to literature on library instruction and information literacy within 2021.

This issue is a selected bibliography covering the subject of leadership.

Little is known about how assistive technology standards have been implemented in preservice teacher preparation. This chapter provides a review of the literature concerning the importance of evidence-based practice and the research base supporting assistive technology in order to set the context for reporting the results of a comprehensive national study of the status of assistive technology state standards for teachers in all of the 50 states (plus Washington, DC). This chapter includes the findings of the study, the research that the study was based upon, and a review of relevant research in the fields of assistive technology, educational technology, and evidence-based practice. Only six states reported having AT standards and six states reported having AT competencies. Three states reported having both standards and competencies, yielding nine unique states (out of 51) with AT standards and/or AT competencies. Regression analyses to determine the relationship between the study variables and national reading and math performance of students with disabilities were inconclusive. The implications of the study findings and recommendations for future research are presented.