Adoption Patterns Research Articles

Self-Regulation for Reputation-Sensitive Buyers: SA8000 in China

Industries and firms have diverse motives for adopting self-regulatory institutions. This research develops and tests propositions about one motive—exploiting opportunities to do business with reputation-sensitive buyers—as distinct from self-regulation to defend against regulatory or activist threats. To study the adoption and effects of self-regulation for reputation-sensitive buyers, we study the SA8000 socially responsible employment certification among large firms in China in the early 2000s. Using official longitudinal industrial microdata, we test hypotheses generated by this assumed motive for self-regulation and find that (a) despite concerns about the corruptibility of certification bodies, SA8000 adopters in China exhibited higher precertification worker wages than comparable nonadopters, (b) self-regulation led to increased employment and sales to foreign markets, where reputation-sensitive buyers are concentrated, (c) the positive effect on exports was greater than the (insignificant, negatively signed) effect on domestic sales, and (d) there is no evidence that self-regulation increased worker wages beyond the initial high start. Contrasting these findings with prior research on industry self-regulation for other motives, this study highlights how both adoption patterns and downstream effects differ according to the audience for self-regulation. This paper was accepted by Olav Sorenson, organizations. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2020.01306 .

The Impact of Farmers' Social Lifestyles on Agricultural Sustainability in Rural Area of Turkey

This study investigates how farmers' social lifestyles influence agricultural sustainability in rural Turkey. Through data analysis from 312 producers across five provinces, we examine how participation in social activities such as religious gatherings, café meetings, and agricultural fairs shapes farming decisions and sustainability outcomes. Using logistic regression modeling, we find that social network participation significantly impacts agricultural performance and sustainability practices. Results reveal that different types of social engagement lead to distinct patterns of innovation adoption and resource management. Coffee-house and religious gatherings influence not only sales decisions but also agronomic practices, such as adopting new technologies and innovative methods. The lack of female involvement and potential pathways for their integration are also important. This research provides crucial insights for policymakers seeking to leverage existing social networks to promote sustainable agricultural practices in rural communities.

Integrative Review-Based Conceptual Modeling: An Agent-Based Modeling Synthesis of Dynamic Energy Tariff Research and Models

Adoption of dynamic energy tariffs by households is crucial for the transition to carbon-neutral energy systems. Influencing the adoption patterns of these tariffs necessitates an examination of the drivers, decision components, and contextual factors influencing household decisions. Few computational models address this comprehensively, often omitting non-financial decision variables. Moreover, methodologically robust integrative reviews on this topic are scarce. To address this gap, this paper develops a concept-centered integrative review methodology aimed at deriving computer models for socio-techno-economic simulations of household adoption of sustainable technologies. The methodology encompasses five sequential phases: Setup, Literature Search, Analysis, Synthesis and Conceptual Model, and Discussion. To illustrate the methodology, it is applied to the case of household adoption of dynamic energy tariffs, resulting in an abstract conceptual model adaptable to local contexts. The review reveals a lack of consensus on modeled tariffs but highlights the significance of tariff complexity, relative advantage, household heterogeneity, and various agent properties. It also identifies potential improvements in model fundamentals, particularly spatial modeling. The developed process model focuses on the stages ‘knowledge’, ‘decision’, and ‘reevaluation’. The article contributes by presenting a comprehensive review scheme and delivering a concept-centered integrative review along with an explicit conceptual model derived from it.

Building Information Modeling Adoption in the Palestinian Construction Industry: Influencing Factors, External Determinants, and Technology Acceptance

ABSTRACT Building Information Modeling (BIM) is a worldwide spreading technology for the Architecture, Engineering, and Construction (AEC) industry that allows for continuous modification and improvement of building models, resulting in improved quality and cost savings in the project. The study aims to investigate the adoption pattern of BIM in the Palestinian market and identify significant factors that influence the adoption process, including top management support, organizational culture, and the number of experts and technicians. A structured questionnaire was developed, distributed electronically, and 168 valid responses were received, leading to a margin error of 4.4% and a response rate of 67.2%. A model, based on the Technology Acceptance Model (TAM) was developed and partial least squares structural equation modeling (PLS-SEM) was utilized to evaluate the measurement model’s reliability and validity, test hypotheses regarding the relationships between constructs, and assess the impact of various factors on the intention to adopt BIM within the construction industry. Six external influences on acceptance are highlighted. Individual and organizational acceptance drivers are identified, including top management support, ease of use, and competitive landscape. Government policies impact adoption and results stress internal and external considerations for BIM adoption.

The Evolution of Data Visualization Tools and Their Impact on Business Decision-Making : A Historical Analysis

This article examines the transformative evolution of data visualization tools and their profound impact on business decision-making processes. Through a comprehensive analysis of historical developments, theoretical frameworks, and technological advancements, the article explores how visualization tools have progressed from basic manual charts to sophisticated AI-powered analytical platforms. The investigation encompasses the cognitive foundations of visual information processing, the emergence of first-generation Business Intelligence tools, and the current landscape of modern visualization platforms. Particular attention is given to the integration of artificial intelligence in data visualization, including automated generation, pattern recognition, and predictive analytics capabilities. The article presents both quantitative and qualitative assessments of these tools' impact on organizational decision-making, highlighting significant improvements in decision speed, accuracy, and user engagement. The article reveal substantial benefits in terms of ROI, decision-making efficiency, and organizational adoption patterns. The article concludes by examining emerging trends, including the potential of extended reality technologies and edge computing, while acknowledging current limitations and providing recommendations for future research directions in this rapidly evolving field.

The eMoney revolution: how culture and technology drive adoption and use?

Purpose The use of electronic money (eMoney) as a noncash payment method is gaining popularity globally. However, the usages of eMoney are culturally influenced and can vary within a country. These cultural disparities can result in divergent patterns of eMoney adoption and use. This study aims to investigate the factors influencing the adoption and use of eMoney in Indonesia. This study integrated the unified theory of acceptance and use of technology model with Hofstede’s cultural dimensions to develop a framework examining both technological and cultural perspectives. Design/methodology/approach Data was collected through an online survey of 484 Indonesians and analyzed using partial least squares structural equation modeling. Findings The results showed that the constructs of the unified theory of acceptance and use of technology model, namely, performance expectancy, effort expectancy, social influence and facilitating conditions, all had a significant impact on behavioral intention to adopt eMoney as well as actual usage. However, not all of Hofstede’s cultural dimensions moderated these relationships as hypothesized. Surprisingly, masculinity/femininity and power distance emerged as important moderators of eMoney usage. Practical implications This integrated model provides valuable insights into how to consider cultural influences when designing strategies to promote new payment technologies in Indonesia. The findings point to both technological and cultural factors shaping patterns of adoption and use of eMoney in the country. Originality/value Although many research has looked at how culture affects the acceptability of technology in banking, few studies have looked at how culture affects the use of mobile money. This study offers a valuable contribution by investigating how Indonesian culture moderates the relationship between behavioral intentions and actual use of eMoney. The findings provide guidance for practitioners seeking to facilitate eMoney services in developing markets by elucidating the cultural factors that most influence customer adoption. As such, this research fills an important gap regarding the understudied domain of mobile money and its intersection with national culture.

Strategic Formation of Agricultural Market Clusters in Ukraine: Emerging as a Global Player

This study investigates the cluster approach to optimize strategies for agricultural enterprises in Ukraine, emphasizing geographical proximity as a key factor in cluster formation. The research applies Kohonen Self-Organizing Maps (SOMs) and Ward’s hierarchical clustering to classify enterprises based on storage capabilities, transport logistics, crop yields, and military risk exposure. By analyzing these factors, this study identifies distinct patterns of innovation adoption, strategic management, and economic resilience among the clusters. The findings highlight variations in competitiveness and resource efficiency, providing a detailed understanding of regional economic performance. Unlike previous research, this study offers a novel integration of conflict-related risks into the clustering methodology, revealing new insights into how military factors influence cluster dynamics. Comprehensive maps and diagrams illustrate the spatial and economic distribution of clusters, aiding in visual interpretation. The results propose strategic measures tailored to enhance agricultural productivity and competitiveness, particularly in Ukraine’s current military context. This approach offers a more adaptive framework for managing agricultural enterprises, promoting resilience and long-term sustainability in global markets.

THE IMPACT OF USING SMART WATCHES ON STUDENTS’ EFFORT CAPACITY: A COMPARATIVE STUDY

The increasing use of smartwatch technology among university students has raised questions about its potential impact on physical health and effort capacity. This study aims to evaluate the influence of smartwatch usage on the physical performance and effort capacity of students, focusing on those who utilize these devices for monitoring physical activity and health functions. In this comparative study, we employed a questionnaire to assess the adoption and usage patterns of smartwatches among students. The research sample was divided into two groups: a control group and an experimental group. Both groups participated in weekly aerobic gymnastics classes. However, the experimental group, equipped with smartwatches, was tasked with achieving a daily goal of 13,000-15,000 steps or expending 600 kcal. At the conclusion of the experiment, we evaluated the exercise capacity of all students using the Ruffier and Harvard tests. The results revealed significant differences between the two groups, with the experimental group demonstrating notably higher effort capacity. This suggests that the regular use of smartwatches, combined with specific fitness targets, can enhance physical performance and overall health among students. Our findings underscore the potential benefits of integrating wearable technology into student lifestyles, particularly in promoting physical activity and improving exercise capacity. This study contributes to the growing body of literature on the impact of smartwatches on health and fitness, highlighting their role as valuable tools for monitoring and enhancing physical performance in an academic setting. In conclusion, smartwatches can be useful tools for students, but they must be used with discernment. It is important to strike a balance between the benefits and distractions these devices bring. Students' effort capacity may be influenced by how they integrate smartwatches into their daily routine.

Seeing and believing: behavioural insights from implementing an artificial intelligence-enabled stethoscope in primary care

Abstract Background • Early detection and treatment of cardiovascular disease (CVD) improves survival, quality of life and health economic outcomes (1) • Despite evidence of effectiveness, health systems fail to implement technologies for early detection of CVD sustainably, limiting their public health impact (2). This challenge may limit the full potential of artificial intelligence (AI) in healthcare (3). • An AI-enabled stethoscope can detect reduced left ventricular ejection fraction (LVEF), atrial fibrillation (AF) and structural cardiac murmurs during fifteen seconds of conventional cardiac examination (4) • The determinants of uptake, sustained use and clinical impact of implementing the AI-stethoscope in primary care are unknown. Purpose • To implement the AI-stethoscope in a UK primary care system • To measure rates of utilisation and their association with potential disease detection • To characterise the adoption patterns of an AI technology in primary care Methods • TRICORDER is a cluster randomised controlled trial and implementation study. • Clinicians in the intervention arm receive in-person training in use of the AI-stethoscope and are remunerated for this training time. • Clinicians using the AI-stethoscope in routine care are supported by a clinical guideline and data privacy approvals from the regional health service executive board. • GP practices are not remunerated for using the AI-stethoscope • Anonymised utilisation and AI disease detection rates were extracted from the manufacturer’s cloud database from 31st October 2023 to 25th February 2024. We performed linear regression to characterise use over time. Results • 59 practices were randomised and onboarded to the intervention arm between 31st October and 3rd December 2023, all using the stethoscope at least once, for a total of 1,555 unique patient examinations (3,253 total recordings), over a median of 90 days. • The mean (±SD) number of recordings per practice per week was 5.45 (±5.68). • There were 32 practices with utilisation data for at least 12 weeks. There was a weakly positive utilisation trend (r = 0.042; P= >0.05, Figure 1A), with no significant difference in rates of utilisation at 4, 8 and 12 weeks (Figure 1B). • There were 159 (4.88%), 89 (2.74%) and 102 (3.13%) abnormal AI flags for reduced LVEF, AF and structural murmurs, respectively. • We characterised three groups by patterns of use (Table 1). There were no significant differences between mean rates of abnormal AI findings between groups (ANOVA p = 0.43). Conclusions • Implementation of an AI-stethoscope in primary care is feasible and was associated with stable utilisation. • The proportion of abnormal AI findings are consistent with modelled detection gap of the target conditions in the UK, and would not consequentially overwhelm downstream health services. •The proportion of abnormal AI findings did not significantly differ between low and high-utilisation groups.Table 1Figure 1

Algorithmic governance or extortion? Everyday experiences of fintech for loans in Nigeria

ABSTRACT This paper aims to understand the everyday experiences of financialised inclusion amongst fintech users in Nigeria. Concerns about the use of fintech to drive financial inclusion in the global south have led social scientific scholars to argue that it extends processes of financialisation by employing opaque algorithms to extract the behavioural data of users in order to inundate them with unsecured credit and monetise their data through resale. The consequences of these practices are not fully understood across various contexts. Using a variety of ethnographic methods, this paper examines patterns of fintech adoption and usage in Jimeta, Nigeria. It demonstrates that while fintech allows people to sort out their personal issues amidst precarity, it is also entangled in algorithmic governance issues that facilitate algorithmic extortion to the detriment of user populations. Ultimately, the paper argues that fintech, contrary to claims about its potential to unlock prosperity, is one that opens up novel possibilities for profit making and accumulation, albeit with severe consequences on user populations.

Adoption of smart energy apps and household energy practices: empirical insights from Norway

ABSTRACT This study examines the adoption and usage patterns of household energy apps among a sample of Norwegian households to explore their potential in visualising and controlling home energy consumption and influencing sustainable energy practices. Through a questionnaire survey of 150 respondents using energy apps, this study gathers empirical insights into adoption motivations, user perceptions and factors associated with self-reported changes in household energy practices. Findings indicate that app-related factors, such as perceived app insights applicability, ease of use, and appealing user interface, are more positively associated with self-reported changes in daily energy habits than demographic factors. This research underscores the importance of prioritising user experience and data security in app development to foster sustainable energy practices. It also offers practical recommendations for targeted engagement strategies and policy interventions to promote the wider adoption of smart energy apps and maximise their potential to facilitate household energy transitions.

Unlocking Business Intelligence and Data Analytics Adoption Patterns: Insights from Jordanian Higher Education Institutions

Unlocking Business Intelligence and Data Analytics Adoption Patterns: Insights from Jordanian Higher Education Institutions

Use Patterns, Technical Challenges and Patient Selection Associated With Single Use Duodenoscopes & Duodenoscopes With Single Use Endcaps In The United States & Canada

Background & AimsThe extent of adoption, patient selection and use patterns of single use duodenoscopes and duodenoscopes with single use endcaps have not yet been characterized, nor have large scale assessments of endoscopist-reported function and challenges. MethodsAn anonymous 6-minute electronic survey assessing use and experience with single use duodensocopes and duodenoscopes with novel design features was distributed to US and Canadian endoscopy centers and responses were analyzed using descriptive statistics. ResultsThe survey was notable for a 70.2% response rate, with representation from academic (68.9%), community (18%) and veterans affairs (8.2%) centers. Most institutions use standard reprocessable duodenoscopes and duodenoscopes with single use endcaps (34.4%), or a mix of standard reprocessable duodenoscopes, duodenoscopes with single use endcaps and single use duodenoscopes (29.5%). No center used only single use duodenoscopes (0%). 10.3% planned to transition to the duodenoscope with a single use endcap, 10.3% to a mix of single use duodenoscopes and duodenoscopes with single use endcap, and 1.7% to single use duodenoscopes alone. Challenges were reported with each type of novel duodenoscope and selection patterns for use were characterized. ConclusionsThis first-of-its-kind large scale survey of use patterns and functionality of newly introduced duodenoscopes is notable for fairly widespread use of the duodenoscopes with single use endcaps and more limited use of the single use duodenoscope. Both novel duodenoscope designs are associated with mechanical limitations that respondents indicate represent challenges to successful completion of ERCPs.

Pilot to scale: Implementing a digital triage solution across a large comprehensive cancer centre.

225 Background: Princess Margaret Cancer Centre (PM) sees over 80,000 patients annually and primarily operates using an outpatient model. Historically patients use a phone/voicemail triage service to communicate with their care team between scheduled visits. Many patient queries lack critical information necessary for effective screening, assessment, and processing. In turn leading to delays or missed calls that negatively impact patient experience, system efficiency, and safety. To address these challenges, we piloted a digital triage service and subsequently implemented in sixteen clinics. This project evaluated initial adoption, usage, care patterns and satisfaction in the first 5 months post-implementation. Methods: We used human-centred service design to develop the digital triage service within the EMR (Epic). Implementation strategies to scale across all outpatient clinics included leadership buy-in, co-design with key stakeholders, a phased implementation approach, and improvement cycles. To evaluate initial adoption, usage and care patterns, we used EMR system data. To assess patient satisfaction, we surveyed patients who used the service during the first three months. We conducted semi-structured interviews with staff to understand their experience integrating digital triage into their workflow. Results: Following the go-live period, patients sent an average of 1096 digital requests per month, representing 16% of all triage requests (phone + digital). The most common requests were symptom management (36% of nursing requests) and appointment change requests (40% of administrative requests). The algorithm automatically routed 93% of requests to the most appropriate care team member, compared to 74% pre-implementation. When asked if they were satisfied with their experience, most patients agreed or were neutral (69% and 10%, respectively), while 21% disagreed. In semi-structured interviews, nurses and administrative staff described improved efficiency by having triage requests integrated within the EMR, while have challenges related to prioritizing requests across multiple channels (e.g. digital, phone, others). Conclusions: Digital triage is foundational for better cataloguing and understanding our patients' unmet needs at home and between visits, enabling a continuous learning process to understand when and why people struggle throughout their care journey. Ongoing analyses will explore disease site-specific trends, compare phone to digital triage, and identify differences between users of each method. The data will inform further improvement cycles on the build and workflows, while enabling appropriate resourcing of this critical service and shifts towards proactive care.

Modeling Ride-Hailing and Carsharing Adoption & Use Patterns: Deciphering the Substitutive and Complementary Impacts of Built Environment, Transit Accessibility, & Active Travel.

Modeling Ride-Hailing and Carsharing Adoption & Use Patterns: Deciphering the Substitutive and Complementary Impacts of Built Environment, Transit Accessibility, & Active Travel.

Banking in the cloud: mapping big tech’s global digital technology networks

ABSTRACT Witnessing the inroads of big tech into finance, this paper maps the growing dependence of incumbent banks on public cloud infrastructures. Although ‘cloud interfacing’ has become crucial amid platform finance, the intersections between what we conceptualise as global digital technology networks and global financial networks have received little attention. We mobilise social network analysis to map: (1) the geographically variegated patterns of public cloud adoption in banking and their geopolitical implications; (2) the corporate networks supporting banks’ cloud migration; and (3) the urban networks of command and control undergirding cloud banking, connecting established financial centres with tech valleys old and new.

The constitutional codification of academic freedom over time and space

Abstract This article explores the global spread of domestic codifications of academic freedom norms by mapping constitutional provisions over time and space. Drawing on the new Academic Freedom in Constitutions dataset, the study evaluates several hypotheses that may explain the norm’s geographically diverse, yet comparatively limited, adoption in 52 per cent of constitutions today. The descriptive analysis of constitutional adoption patterns suggests that the as yet large pockets of absence are a result of the fact that academic freedom was not included as a fundamental right from the early days of constitution-making, combined with its close link to higher education development, thus locking many countries into a path dependency of early constitutions exclusive of academic freedom norms. The availability of relevant models in nearby countries, together with higher education expansion, are key facilitators of academic freedom adoption at the critical time of a constitutional reform process. Diverse countries in different regions acted as norm entrepreneurs, often motivated to domestically protect academic freedom, thus leading to the emergence of regional and other clusters of academic freedom reference types. A sizeable proportion of insincere adopters further suggests that, in some regions, academic freedom serves as a legitimizing international norm.

Trends in pre-biopsy MRI usage for prostate cancer detection, 2007-2022.

Clinical guidelines favor MRI before prostate biopsy due to proven benefits. However, adoption patterns across the US are unclear. This study used the Merative™ Marketscan® Commercial & Medicare Databases to analyze 872,829 prostate biopsies in 726,663 men from 2007-2022. Pre-biopsy pelvic MRI within 90 days was the primary outcome. Descriptive statistics and generalized estimating equations assessed changes over time, urban-rural differences, and state-level variation. Pre-biopsy MRI utilization increased significantly from 0.5% in 2007 to 35.5% in 2022, with faster adoption in urban areas (36.1% in 2022) versus rural areas (28.3% in 2022). Geographic disparities were notable, with higher utilization in California, New York, and Minnesota, and lower rates in the Southeast and Mountain West. The study reveals a paradigm shift in prostate cancer diagnostics towards MRI-guided approaches, influenced by evolving guidelines and clinical evidence. Disparities in access, particularly in rural areas and specific regions, highlight the need for targeted interventions to ensure equitable access to advanced diagnostic techniques.

How do Startups use AI? A Q-methodology approach to understanding adoption patterns.

Artificial Intelligence (AI) can move beyond mere task automation and can actively foster the very process of innovation. As startups are the organizational entities which rely heavily on creativity and innovation, it is intriguing to evaluate the use of AI in startups and in the entrepreneurship field. As AI is already becoming increasingly pervasive and indispensable in the startup ecosystem, the question arises, how exactly startups are using AI. We used the Q-methodology to investigate this topic empirically. This methodology was chosen because it combines the strengths of both qualitative and quantitative methods. The Q-samples (i.e., set of statements) were developed from secondary sources like literature and primary sources like interviews. In this context three in-depth-interviews with entrepreneurs were conducted to comprehensively cover the topic. The concourse comprised a set of 43 statements, that each provided one aspect of “How do startups use AI?”. The collection of the Q-Samples was then followed by the Q-sorting, in which participants were asked to rank the items according to their degree of agreement. In this study 30 entrepreneurs from different startups in Germany were interviewed. The interviews were conducted online via a video chat to give participants the chance to comment on their ranking. We used the QMethod Software for data collection and analysis. The research illuminates current AI practices among startups, identifies common fields and highlights areas for further development. The findings of this study reveal the prioritization of operational efficiency as the driving force behind AI implementation. However, it is quite concerning that ethical considerations are largely ignored, posing risks of potential ethical oversights in AI utilization. Furthermore, most startups see AI as a facilitator of human creativity rather than a replacement. Overall, this paper is relevant to a diverse audience interested in understanding the current landscape, challenges, and opportunities associated with the usage of AI technologies within the startup ecosystem. This audience includes entrepreneurs, investors, researchers, educators, and policy makers.

Selection and adoption of water purification technologies in the bottled water industry in India

Today, more than sixty per cent of the global bottled water manufacturing takes place in the countries of the global south. Despite being a low-tech sector, the industry is heavily influenced by the advancement and adoption of new water purification technologies and science-based regulations introduced by regulatory agencies. This paper examines the factors and mechanisms through which selection and adoption take place in this sector. The study draws upon firm-level surveys, expert interviews, ethnographic data, and select court cases and policy reports. We find that economic (firm’s size, firm’s age, and ownership structure) and socio-environmental factors (environmental subjectivities of major actors, regulatory (in-) capacity, role of supporting institutions) shape the pattern and combinations of technological adoption and technological changes at the firm level to meet the goals of “safety” and “quality”. However, the use of certain technologies are not devoid of serious environmental and public health concerns. The regulatory actors need to pay closer attention to the direct and indirect impacts of technology use on public health, the economy and the environment to make public policies more just and to meet sustainable development goals.