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New technology can be a source of great optimism and a force for positive change in the research industry. As such, it is important to discuss the merits of emerging technology. In this research note, the emergent opportunity for qualitative research in the metaverse is discussed. This paper looks at how rich sensory virtual environments with multiple sensory modalities might help address some of the shortcomings of traditional online qualitative research. The importance of establishing social presence in virtual qualitative research is addressed. Then, how the metaverse might help remove some of the constraints of 'big qual' is debated. The potential for the metaverse to improve participant inclusivity is considered, before finally discussing the issue of research ethics in a decentralised virtual world. [ABSTRACT FROM AUTHOR]

Self-administered web surveys provide respondents only limited opportunities for feedback. Therefore, many web surveys include so-called "final comment questions" (FCQs) that allow respondents to elaborate on the survey in general and the survey questions in particular. Typing in open answers in text boxes is burdensome – especially via smartphones with virtual on-screen keypads – so that respondents frequently provide short or no answers at all. In this study, we make use of new technological advancements in web survey methodology and investigate FCQs with requests for written and oral answers. For this purpose, we conducted an experiment in a smartphone survey (N = 1,001) in a German online panel. The results reveal that FCQs with a request for written and oral answers do not differ with respect to item-nonresponse. However, oral answers are substantially longer than written answers pointing to more in-depth information. The oral answer condition also results in more positive comments than the written answer condition. This study is a methodological showcase for innovative web survey design that contributes to the improvement of data quality. [ABSTRACT FROM AUTHOR]

The fourth industrial revolution tempts manufacturing companies to transform into smart factories, which in turn affects the human work. We examine this complexity from the perspective of human factors and ergonomics (HF/E) by analysing the organisational capabilities needed when seeking and selecting new technology solutions, and designing and implementing them into local application. This qualitative study focuses on manufacturing companies that have pioneered adopting high technologies in their processes. Empirical material was collected from 15 Finnish manufacturing companies of different sizes. Particular attention is paid to how HF/E are present when companies (1) sense new opportunities for technological development of their production, (2) seise these opportunities through design actions, and (3) shift the solutions into use. Analyses revealed that companies, regardless of their size and the technology being implemented, do not fully understand the fundamentals and value of HF/E, resulting in technology and production-oriented solutions in which human skills and capabilities are often neglected. A novel road map is proposed for integrating HF/E expertise and knowledge when seeking, selecting, and utilising new production technologies. This study increases understanding of the role of HF/E when adopting new technologies in manufacturing. The road map improves possibilities for fact-based decision-making. [ABSTRACT FROM AUTHOR]

This study examines the metaphors used by 66 information professionals in Türkiye to conceptualize artificial intelligence (AI). Through qualitative metaphor analysis, rich insights emerged on perceptions of AI's nature, functioning, relationships with humans, roles, and societal impacts. Some of the metaphors used are child, human, artist, human intelligence, robot, assistant, doctor, weapon, terminator, something scary, closed box, black hole, Pandora's box, etc. Multiple, often contradictory metaphors like "child" and "uncontrollable power" indicate AI is viewed in a multidimensional way, evoking both promise and concern. Key findings suggest information professionals appreciate AI's transformative potential in enhancing services but also harbor anxieties related to human relevance, technocracy, and social issues like privacy. Understanding these complex cognitive and emotional orientations can facilitate responsible AI adoption to augment information services. Gesturing at AI's multifaceted connotations also foregrounds communication challenges complicating public debate and policymaking on emerging technologies. The value of this study lies in surfacing the nuanced perspectives of a stakeholder group positioned to mediate public understanding and direct integration of AI in information services. Mapping information professionals' rich construals of AI also highlights the need for public communication attuned to metaphorical reasoning around new technologies. [ABSTRACT FROM AUTHOR]

The use of wearables in the workplace allows for close monitoring of work processes and might also have consequences for work content and skill requirements. Past research has emphasized the detrimental effects of wearables, particularly those caused by the standardization of work and monitoring of workers. By contrast, this study asks under what conditions the implementation of wearables as part of digital assistance systems is beneficial for workers. Based on recent contributions in the field of labor process theory, this study analyzes the implementation of new technologies using the concepts of the regulatory regime, organizational first-order factors, and workplace second-order choices. The analysis is based on findings from 48 interviews with 83 interviewees in 16 German manufacturing workplaces along with making site visits. It examines the implementation of wearables and the impacts on work content, skills, working conditions, and employment. Besides showing how labor agency affects the implementation of new technologies, the particular contribution of this study lies in analyzing the differences in the implementation of wearables in capital- and labor-intensive organizations. While standardization of work and reduction of work content prevailed in labor-intensive processes, capital-intensive processes were most often characterized by the extension of skill requirements and the risk of work intensification. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is becoming a critical engine that powers a range of technology solutions. It is rapidly playing a vital role in supply chain and operations management. In this paper, we present a research agenda of how researchers and practitioners alike can study the potential adoption of AI-powered tools for benefits in the supply chain. We draw on the unified theory of acceptance and use of technology and suggest directions for research that leverage a mixed-methods research approach. Because these technologies are in a nascent stage and evolving rapidly, a mixed-methods approach will allow for a careful examination of potential features and how their adoption can be fostered, with specific benefits in mind. We present three-specific research directions rooted in the developmental, completeness, and expansion purposes of mixed-methods research. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

While recent technological advancements have enabled improved performance in warehouse operations, companies still struggle with eliminating errors such as incorrect/damaged items or the wrong quantity sent to customers. Such errors result in inefficient resource use, costly returns handling, and customer dissatisfaction. Despite the importance of errors, current knowledge of the underlying causes is limited. This paper addresses the gap by investigating error causes through a relatively new technology - intelligent video analysis (IVA), an additional tool for analysing warehouse operations. A multiple case study involving companies that have implemented IVA in their outbound warehouse operations (i.e. order picking, packing, and sorting) was conducted. This study is the first to investigate implementations of IVA, offering novel empirical insights into error root causes. It shows how many errors reported by customers are actually not made by humans in outbound warehouse operations but are attributable to faulty customer claims, inbound warehouse operation errors, and malfunctioning technology. This study offers interesting insights into the interaction of various technical, organisational, and human factors, thereby contributing to the literature on sociotechnical systems and the human-centric Industry 5.0. Finally, the study outlines a way forward for managers to address and further reduce errors occurring in warehouse operations. [ABSTRACT FROM AUTHOR]

This paper deals with the complex relationship between innovation and the labor market, analyzing the impact of new technological advancements on overall employment, skills, and wages. After a critical review of the extant literature and the available empirical studies, novel evidence is presented on the distribution of labor-saving automation [namely robotics and artificial intelligence (AI)], based on natural language processing of US patents. This mapping shows that both upstream high-tech providers and downstream users of new technologies—such as Boeing and Amazon—lead the underlying innovative effort. [ABSTRACT FROM AUTHOR]

We investigate the impact of "routinization" on the labor outcomes of displaced workers. We use a rich Brazilian panel dataset and an occupation-task mapping to examine the effect of job displacement in different groups, classified according to their tasks. Our main result is that following a layoff, workers previously employed in routine-intensive occupations suffer a more significant decline in wages and more extended periods of unemployment. As expected, job displacement has a negative and lasting impact on wages. Still, workers in routine-intensive occupations are more impacted than those in non-routine occupations in terms of wages (an increase of one point in the routine-intensity index results in a further decline of 2% in workers' relative wages) and employment. Furthermore, our results indicate that workers in routine-intensive occupations are more likely to change occupations after the shock, and those who do not switch occupational fields suffer a more significant decline in wages. Lastly, even though the loss of employer-specific wage premiums explains 13% of displaced workers' drop in wages, it does not explain routine-intensive workers' more substantial losses. [ABSTRACT FROM AUTHOR]

Muon radiography, which relies on measuring the absorption and attenuation of muons as they pass through matters, offers a new imaging technique capable of revealing the internal structure of large objects. Recent technological advancement allows for the application or testing of muon radiography in various fields, including mining, civil engineering, security check, etc. This study investigates the factors that influence muon radiography, which is used in density inversion, through simulations and experiments. The materials considered for density inversion include water, standard rock, and iron. Our simulation studies show that the number of events detected and selected has an impact on the reconstruction results, and several factors, such as multiple Coulomb scattering processes, recording time, and spatial resolution, which influence the number of muons, must be taken into account when measuring the rock density. We design and conduct a laboratory scale experiment based on the simulation results. We filter the 220 h of recording signals through time coincidence and straight-line fitting to obtain the selected events. Our results reveal that the statistical error of muons survival ratio in recording time significantly impacts the inversion result and decreases the error can improve accuracy greatly. In the experiment, the deviation between the inversion mean value and the expected value can be reduced to 2.4%–2.9% for iron, 7% for water, and 1.5% for standard rock. This density inversion approach provides insight into future density detection of underground structures. [ABSTRACT FROM AUTHOR]

The discovery of advanced thermal materials with exceptional phonon properties drives technological advancements, impacting innovations from electronics to superconductors. Understanding the intricate relationship between composition, structure, and phonon thermal transport properties is crucial for speeding up such discovery. Exploring innovative materials involves navigating vast design spaces and considering chemical and structural factors on multiple scales and modalities. Artificial intelligence (AI) is transforming science and engineering and poised to transform discovery and innovation. This era offers a unique opportunity to establish a new paradigm for the discovery of advanced materials by leveraging databases, simulations, and accumulated knowledge, venturing into experimental frontiers, and incorporating cutting-edge AI technologies. In this perspective, first, the general approach of density functional theory (DFT) coupled with phonon Boltzmann transport equation (BTE) for predicting comprehensive phonon properties will be reviewed. Then, to circumvent the extremely computationally demanding DFT + BTE approach, some early studies and progress of deploying AI/machine learning (ML) models to phonon thermal transport in the context of structure–phonon property relationship prediction will be presented, and their limitations will also be discussed. Finally, a summary of current challenges and an outlook of future trends will be given. Further development of incorporating AI/ML algorithms for phonon thermal transport could range from phonon database construction to universal machine learning potential training, to inverse design of materials with target phonon properties and to extend ML models beyond traditional phonons. [ABSTRACT FROM AUTHOR]

As an emerging technology in liquid inactivation, one of the main challenges of pulsed electric fields (PEFs) inactivation lies in quantitatively describing and predicting its lethality to microorganisms. However, due to its cross-scaled complexity and the consequent numerous regulatory factors, there is currently still no unified framework to understand the PEF dose–response relationship and the population dynamics theoretically. In this study, a simple yet powerful model from multiscale coarse-graining method is proposed to simulate the bacterial inactivation in suspensions during PEF processing. The complex dose–response effects at the macroscale are successfully reconstructed from simple evolution rules and several coarse-graining parameters, while considering the damage and death of a single bacterium at the microscale. Our model uncovers the seemingly chaotic and even controversial dose–response relationship of PEF in literatures and systematically explores the regulatory effect of experimental parameters in a unified framework. One of the interesting findings is that PEF with shorter pulsed width enhances lethality and reduces the minimal inhibitory time at a constant energy output per pulse, owing to the phase transitions in three bacterial population dynamics (Bistability mode, Avalanche mode, and Hybrid mode). Our study provides a new insight for numerically modeling PEF lethality in liquid inactivation and could serve as a guide for dosage management in practical applications. [ABSTRACT FROM AUTHOR]

Although public–private collaboration abounds in addressing societal grand challenges, little is known about its performance relative to private-sector collaboration. Drawing from the innovation collaboration literature, and qualitative insights from interviews and contracts, we argue that collaboration risk impairs task performance of public–private versus private–private collaboration. We attribute this to two collaboration risk mechanisms: cooperation problems arising from misaligned social versus economic incentives, and coordination problems due to differences in organizational governance and processes. We test our hypotheses using the development history of 2,496 antimicrobial drugs from 1995–2019. After accounting for endogenous selection into collaboration, we find that public–private collaboration is less effective than private–private collaboration. However, this performance gap reduces for innovation tasks under high technological uncertainty (i.e., in the discovery stage and for developing new drug action mechanisms). To probe the distinctive cooperation and coordination mechanisms, we also examine innovation task efficiency. Findings reveal a wider gap in task effectiveness but not efficiency between public–private and private–private collaboration, suggesting more significant cooperation than coordination problems. Our theoretical and practical insights pertain to whether, when, and how public–private and private–private collaboration offer viable pathways for socially beneficial innovation tasks. [ABSTRACT FROM AUTHOR]

Unlike previous research that suggests a predominant preference for older brands, this research takes a contingent perspective to examine how consumers' preference for older brands is affected by their expectations of category innovativeness. Results from the analysis of sales data from Amazon and seven experimental studies demonstrate that consumers' preference for older brands decreases with their expectations of category innovativeness. The rationale is that with expectations of category innovativeness, consumers place less importance on consistency-related brand traits (e.g., stability, reliability) and more on excitement-related brand traits (e.g., dynamic, adventurous). Because older brands are associated with consistency, preference for older brands diminishes with expectations of category innovativeness. Further, this research identifies two factors that moderate the effects of category innovativeness on preference for older (vs. younger) brands. First, familiarity with the older brand moderates the effect of category innovativeness on brand preferences such that category innovativeness increases preferences for younger brands only when consumers are choosing between unfamiliar brands. Second, consumers' need for uniqueness reduces the effect of category innovativeness on preferences for younger brands. Together, the findings suggest that the dominance of older brands reduces with expectations of category innovativeness. The findings are important from both theoretical and managerial perspectives. [ABSTRACT FROM AUTHOR]

In this paper, a high precision detection method of copper ion (C u 2 + ) concentration based on weak measurement is proposed. The ternary complex formed by C u 2 + with L-tryptophan and phenanthroline reagents has circular dichroism (CD) signal at 605 nm in visible light. The CD signal can be obtained using the intensity contrast as a pointer in the imaginary weak-value amplification scheme. The measured sensitivity and resolution are 0.3417 mrad l/mg and 0.058 mg/l, respectively, which is improved by an order of magnitude compared to the traditional CD measurement method. It is also more accurate and less costly than commonly used C u 2 + detection methods. The C u 2 + concentration detection based on the weak measurement of CD signal detection proposed in this paper not only brings technological breakthroughs in the field of heavy metal ion detection, but also is of great significance in promoting the cross-development of chemistry, biomedicine, and life sciences. [ABSTRACT FROM AUTHOR]

Copyright of Contemporary Accounting Research is the property of Canadian Academic Accounting Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Order picking in warehouses is a labour- and time-intensive logistical process that significantly impacts the efficiency of supply chains. Although technical progress facilitates the automation of specific order picking tasks, human workers remain the primary actors of order picking. Owing to high operating costs associated with manual order picking, its design and management have been increasingly researched for decades. Because manual order picking systems are socio-technical systems, human factors and workers' interaction with technology are essential for operational success. As innovative technologies become increasingly utilised, such as augmented reality or exoskeletons, warehouse managers need to consider the effects of supportive and substitutive technologies on operational outcomes. However, the potentials and obstacles of using technologies in manual order picking require further investigations. Therefore, this study analyses literature content on supportive and substitutive technologies in manual warehouse order picking and investigates the existing state of research in this field. Text mining is employed to enhance the insights regarding the content analysis. Additionally, future research opportunities on the integration of supportive and substitutive technologies are proposed for manual order picking improvement and development of sustainable and human-centered logistics systems, according to the Industry 5.0 vision. [ABSTRACT FROM AUTHOR]

Two organizations that focus on tech-based health innovation have partnered to improve the mental health of young adults. In this "tech for good" project, Hopelab and Grit Digital Health worked together to create an app using human-centered product design. With the core needs of users at the forefront, the team developed an app both with and for college students to combat loneliness, a prevalent issue that can lead to other problems such as depression, anxiety, and even dropping out of college. The team also applied systems thinking to address the root causes of this "wicked problem," resulting in their Nod app, which has improved outcomes for college students. This article is based on the author's award-winning case study. [ABSTRACT FROM AUTHOR]

Cloud computing is widely applied in modern industrial areas due to its technological advancement, cost reduction, and applicability. Packets (tasks) belonging to different applications (agents) compete to share the common cloud resource through a series of edge nodes (processors) in pursuit of fast transmission. This paper abstracts the cloud computing system as a multi-agent flow-shop scheduling (MAFS) problem. The objective is to minimise the total completion time of several agents with the restriction that the maximum lateness cannot exceed a given bound. Given the complexity of the considered problem, a branch and bound algorithm combined with several pruning rules and lower bounds is proposed to obtain optimal solutions. Furthermore, the considered problem is generalised to a bi-scenario version, and a bi-population cooperative co-evolutionary (BCCE) algorithm is proposed to solve it. A reinforcement learning-based method is presented to generate the initial population. Several problem-specific intensification strategies are constructed to explore promising solutions. Comprehensive experiments verified the effectiveness of the proposed algorithms. The industrial data from the China Earthquake Network Centre further confirmed the superiority of the BCCE algorithm. Overall, the MAFS model and the proposed algorithms effectively enhance the user experience and reasonably guarantee revenue. [ABSTRACT FROM AUTHOR]

In contrast with the accelerating trend of boundary-spanning (horizontal) technological innovation, the current Cooperative Patent Classification (CPC) scheme applies a hierarchical (vertical) structure to innovation output in terms of patents. For this reason, we argue that the CPC can be complemented with dynamic technological innovation system (TIS) discovery through machine learning that accounts for horizontal relationships across seemingly disparate technologies. Using a design science approach, we propose a framework to discover boundary-spanning TISs by leveraging the textual information from millions of patents. We validate our framework in terms of the ability of discovered relationships to predict future innovation quantity and quality in different technology classes. Our novel TIS-based innovation metrics that leverage patenting activity in related technology classes are significantly associated with future innovation intensity in focal technologies. We conduct experiments with machine learning models to further tease out the predictive utility of our TIS discovery framework. [ABSTRACT FROM AUTHOR]

The Journal of Management Information Systems (JMIS) is celebrating its fifth decade of publication and is committed to publishing research papers that make significant contributions to the field of information systems. The journal's editors have an inclusive understanding of the field and aim to reflect and shape its growth and evolution. Over the years, JMIS has published papers on various topics, including the economics of IS, strategic deployment of IT, design research, neuroscience in IS research, behavioral cybersecurity, health informatics, and AI-human collaboration. The journal also recognizes its responsibility to support the well-being of society and explores the societal impacts of IT-driven change. The current issue features papers on topics such as the use of body-worn cameras in policing, technological innovation, crowdfunding, chatbots, sentiment analysis, cloud storage and security breaches, cybersecurity risk management, software architecture, and turnover of IT professionals. [Extracted from the article]

This article is an interview with Anthony Edgar, a former Head of International Olympic Committee (IOC) Media Operations and Chair of the IOC Press Committee. Edgar discusses the relationship between the IOC Press Commission, Media Operations Department, and the Radio and Television Commission. The interview also addresses the commercialization and mediatization of Olympic broadcasting, as well as the use of emerging technologies to enhance the viewer experience. The article highlights the impact of new media on Olympic broadcasting, with multiple rights holders in different territories and the Olympic Broadcasting Services (OBS) adapting to provide finished products in the language of the territories. The article also addresses the question of politicalization or nationalism within Olympic media, stating that the IOC is not interested in increasing the nationalistic aspect. Lastly, the article discusses the successful Olympic Young Reporter Program, which involves young people in Olympic media outlets and provides journalism training. [Extracted from the article]

Blockchain (BC) applications in supply chain management (SCM) have recently received extensive attention. It is important to synthesise the extant literature on the field to identify key research themes and navigate potential future directions. This study thus develops an efficient, scalable data-driven review approach that uses text mining and Latent Dirichlet Allocation (LDA)-based topic modelling for automatic content analysis of full-text documents. Our method overcomes the drawbacks of traditional systematic literature reviews using either manual coding or bibliographic analysis for article classifications, which are highly time-consuming and biased when dealing with large amounts of text. 108 papers published between 2017 and 2022 were analysed which identified 10 key research themes, including revenue management, sustainability, traceability, manufacturing system, scheduling in cloud manufacturing, healthcare SCM, anti-counterfeit system, logistics and transportation, system architecture development, and food & agriculture SC. Five future directions are then suggested, including (1) integration of BC and other emerging technologies for global and scalable SCM, (2) crypto-X applications in SCM, (3) BC-enabled closed-loop SCM, (4) the environmental and social impacts of BC-based SCM and (5) decentralised autonomous organisations in SCM. [ABSTRACT FROM AUTHOR]

This systematic literature review synthesises the literature on human centric IN 4.0 and IN 5.0 while exploring driving forces behind the transition from technocentric IN 4.0 to value centric IN 5.0 using the principles of the multiple level perspective (MLP). Works that discuss contextual, regime and niche level factors which impact on the transition were explored. The Covid- 19 pandemic and Climate change are identified as key contextual, 'Landscape', factors impacting the transition while Trust, Mass personalisation and Autonomy are highlighted as key Regime factors. In terms of Niche innovations, Advanced Extended reality technologies, Cobots/ Advanced Robotics, and Advanced AI are often connected with landscape or regime issues. Drawing on MLP theory, the study demonstrates that the transition from IN 4.0 towards IN 5.0 is occurring through a reconfiguration pattern. The paper further emphasises aspects that both practitioners and academics need to be cognisant of in order to affect a transition from IN 4.0 to IN 5.0. [ABSTRACT FROM AUTHOR]

We examine innovation following the Great Depression using data on a century's worth of U.S. patents and a difference-in-differences design that exploits regional variation in the crisis severity. Harder-hit areas experienced large and persistent declines in independent patenting, mostly reflecting the disruption in access to finance during the crisis. This decline was larger for young and inexperienced inventors and lower-quality patents. In contrast, innovation by large firms increased, especially among young and inexperienced inventors. Overall, the Great Depression contributed to the decline in technological entrepreneurship and accelerated the shift of innovation into larger firms. [ABSTRACT FROM AUTHOR]

Technologies are becoming increasingly autonomous, able to complete tasks on behalf of consumers without human intervention. For example, robot vacuums clean the floor while cooking machines implement recipes on their own. These autonomous products free consumers from daily chores that they used to perform manually. The current research suggests that some consumers derive meaning from completing such manual tasks, and that this meaning of manual labor acts as a barrier to the adoption of autonomous products. A series of field and experimental studies shows that consumers who score high (vs. low) on the meaning of manual labor construct tend to evaluate autonomous products less favorably and adopt them less frequently. However, making alternative sources of meaning in life salient can serve as a remedy to increase autonomous product adoption among these consumers. One such strategy is to emphasize that the time gained through the use of autonomous products can be spent on meaningful activities, thus offsetting the detrimental effects of meaning of manual labor on autonomous product adoption. The findings suggest effective interventions for firms that offer autonomous products while stressing the need to provide meaningful experiences to consumers. [ABSTRACT FROM AUTHOR]

The key to radical innovation lies in technological breakthroughs, and the key to technical breakthroughs lies in the application of cross-domain knowledge. However, in the conceptual design stage of new product development, the designer's cognition and knowledge are limited and the retrieval and evaluation of cross-domain technologies is often subjective, making it difficult to generate radical concepts. To address the above issues, this paper proposes a method for cross-domain technology recommendation based on patent analysis. In this method, feature words in various domains of patents are used to generalise the abstract functions of product core subsystems, where designers can obtain more comprehensive cross-domain technologies. This is conducive to breaking the design fixation of designers. Subject–Action–Object structural and functional similarity are combined to quickly extract cross-domain technologies in patents. Then multiple technical indicators are used to objectively evaluate and rank cross-domain technologies. This approach helps designers objectively select cross-domain technologies to change the way next-generation products work, enabling early planning of production conditions and a head start in the market. The method has been verified in a new product development project on peeling equipment, a new product that meets radical indicators is finally obtained. [ABSTRACT FROM AUTHOR]

A perennial challenge for executives in established firms is deciding how and when to respond to emerging technologies. This article demonstrates that the way emerging technologies play out in established industries differs according to how the business system is affected. Some have primarily a supply-side effect (on how a firm in the industry creates its product), while others have a primarily demand-side effect (on how users consume the product). Supply-side effects play out over relatively long periods of time in a predictable way, with incumbent firms executing similar strategies though at different speeds. Demand-side effects are faster-acting and more volatile, with incumbents often experimenting with a range of different business models as they seek a viable way forward in a changing market. By understanding these important differences between supply-side and demand-side effects and being able to anticipate the typical patterns of responses from incumbents, executives can make better choices in how and when to invest in emerging technologies. [ABSTRACT FROM AUTHOR]

By comparing management in 1987 with today, this column examines the differences for library managers as technology including computers and the Internet has become an integral part of their lives. Technology has made completing many managerial functions easier and erased the barriers of time and space. Communication has become almost instantaneous. Opportunities for learning are now global. On the other hand, the time required to manage and effectively use technology has reduced time devoted to other tasks. The work-free weekend has disappeared; products must have a slick professional look; and form has sometimes become more important than content. Contemporary library managers must focus both for themselves and for their staff on ways to use technology effectively in meeting library goals. Returning to an idyllic fictionalized past is impossible, especially now that artificial intelligence will likely bring another cycle of radical changes. Library managers will need flexibility, experimentation, and harsh critical evaluation of results to achieve success. [ABSTRACT FROM AUTHOR]

The adoption of new Information Technology (IT) innovations has led to increased uncertainty among employees, a greater demand for security measures, and more entry points for cyber-attacks, which all increase the risk of data breaches for firms. Despite the prevalence of discussions around this issue, there has been a lack of empirical research examining the data breach risk associated with IT innovations. To address this gap, we have developed arguments based on an organizational learning theoretical framework that explains how IT innovativeness can exacerbate data breach risk. Through our analysis of a sample of data breaches that occurred between 2013 and 2021, we have discovered that there is a positive association between firm IT innovativeness and the risk of data breaches. We also find that the effects of IT innovativeness can vary under certain conditions. For example, we find that the positive relationship between IT innovativeness and data breach risk is mitigated when managers possess IT expertise or when firms have established extensive board connections with cybersecurity managers. Moreover, we find that the relationship between IT innovativeness and data breach risk is amplified in complex environments but not in dynamic or munificent ones. This study takes the lead in advancing the theoretical understanding and empirical validation of security-related risks associated with IT innovations. Moreover, our findings serve as a timely reminder for research and practice to carefully consider the implications of introducing novel technologies into firms and the potential dark side consequences that may arise. Additionally, this study underscores the importance of understanding organizational learning in risk assessment and change management, as well as the critical role of contextual factors in moderating the unintended security-related consequences linked to IT innovations. [ABSTRACT FROM AUTHOR]