Technology Adoption Decisions Research Articles

Field observation and verbal exchange as different peer effects in farmers’ technology adoption decisions

AbstractFarmers’ adoption of novel technologies is influenced by other farmers’ behavior, a phenomenon known as peer effects. Although such effects have been studied intensively, the literature does not clearly distinguish between those that result (1) from verbal exchanges with other farmers and (2) from field observations, including the application of technology, its outcomes, and field conditions. We extend existing theoretical concepts and hypothesize that verbal information exchanges and field observations are two types of peer effects. Using data from an online survey of German sugar beet farmers’ application of mechanical weeding from early 2022, we find that the likelihood of adopting mechanical weeding increases across all model specifications by around 26%–28% if at least one adopter is known and by approximately 30%–32% if at least one field is observed. The two types of peer effects complement and reinforce each other in explaining adoption decisions. The effects increase with the number of adopters known and fields observed but decrease with larger distances to the observed fields. The findings can support designing extension services and future peer effects research that should consider the distinction between peer effects arising from verbal exchanges and field observations.

A tutorial on value-based adaptive designs: Could a value-based sequential two-arm design have created more health economic value for the Big CACTUS trial?

Value-based trials aim to maximize the expected net benefit by balancing technology adoption decisions and clinical trial costs. Adaptive trials offer additional efficiency. This paper provides guidance on determining whether a value-based sequential design is the best option for an adaptive two-arm trial, illustrated through a case study. We outline four steps for the value-based sequential approach. The case study re-evaluates the Big CACTUS trial design using pilot trial data and a model-based health economic analysis. Expected net benefit is computed for (a) original fixed design, (b) value-based design with fixed sample size, and (c) optimal value-based sequential design with adaptive stopping. We compare pre-trial modelling with actual Big CACTUS trial results. Over ten years, the adoption decision would impact approximately 215,378 patients. Pre-trial modelling shows that the expected net benefit minus costs is (a) £102m for the original fixed design, (b) £107m (+5.3% higher) for the value-based design with optimal fixed sample size, and (c) £109m (+6.7% higher) for the optimal value-based sequential design with maximum sample size of 435 per arm. Post hoc analysis using actual Big CACTUS trial data indicates that the value-adaptive trial with a maximum sample size of 95 participant pairs wouldn't have stopped early. Bootstrap simulations reveal a 9.76% probability of early completion with n=95, compared to 31.50% with n=435. The four-step approach to value-based sequential two-arm design with adaptive stopping was successfully implemented. Further application of value-based adaptive approaches could be useful to assess efficiency of alternative study designs.

Sales mode selection and blockchain technology adoption decisions in a platform supply chain

In recent years, some large-scale e-commerce platforms have established blockchain systems (BSs) to improve consumer product quality trust degrees (QTDs). However, whether the BSs work eventually depends on the upstream manufacturer strategic decision on whether to join the BSs to provide product quality information authentication. The impacts of the platform sales mode selection between the agency and the reselling modes on the manufacturer blockchain technology (BT) adoption decision are examined, and the equilibrium strategy combinations between the platform sales mode selection and the manufacturer BT adoption decisions are obtained. Furthermore, the impacts of the platform and the manufacturer strategic decisions on the product quality decision are analyzed. The results show that the manufacturer may have more incentive to join the BS under the agency mode than under the reselling mode. In addition, the manufacturer should set a higher product quality level under the agency mode than under the reselling mode, after joining the BS only if the unit BT adoption cost is low. Finally, the QTD, the quality improvement cost and the unit BT adoption cost determine the equilibrium strategy combinations. The double marginalization effect in the channel and the platform channel power advantage are used to explain the above findings. Several extensions are provided to verify the robustness of the results and to broaden the applicability of the model and method.

Examining Factors Influencing the Integration of Blockchain Technology in the Freight Logistics Sector of Pakistan

This study examines the blockchain usage of Pakistan's freight logistics industry. A structural equation model is used to explore latent dimensions such as perceived ease of use, perceived usefulness, subjective norm, perceived behavioral control, attitude, and behavioral intention. To understand the specific factors impacting technology adoption decisions in this geographical and industrial location, a diverse sample of 245 Pakistan goods logistics sector operators will be explored. The findings reveal that perceived ease of use influences logistics professionals' behavioral intentions. The significance of clever and user-friendly interfaces emphasizes technology experiences that satisfy the expectations of Pakistani goods logistics workers. However, the perceived utility has a complicated relationship with behavioral intention, emphasizing the need for targeted actions to boost the perceived value of Blockchain technology in Pakistan's logistics business. Subjective norm is a major predictor of behavioral intention. This demonstrates how social and cultural factors influence Pakistani logistics workers' ambitions to use Blockchain. The correlation matrix and covariance analysis demonstrate that there are significant positive relationships between attitude, behavioral intention, perceived ease of use, perceived usefulness, and subjective norm. This detailed examination of the adoption environment offers practitioners, policymakers, and academics context-specific insights, setting the framework for informed freight logistics technology adoption and innovation activities in Pakistan.

Examining Factors Influencing the Integration of Blockchain Technology in the Freight Logistics Sector of Pakistan

This study examines the blockchain usage of Pakistan's freight logistics industry. A structural equation model is used to explore latent dimensions such as perceived ease of use, perceived usefulness, subjective norm, perceived behavioral control, attitude, and behavioral intention. To understand the specific factors impacting technology adoption decisions in this geographical and industrial location, a diverse sample of 245 Pakistan goods logistics sector operators will be explored. The findings reveal that perceived ease of use influences logistics professionals' behavioral intentions. The significance of clever and user-friendly interfaces emphasizes technology experiences that satisfy the expectations of Pakistani goods logistics workers. However, the perceived utility has a complicated relationship with behavioral intention, emphasizing the need for targeted actions to boost the perceived value of Blockchain technology in Pakistan's logistics business. Subjective norm is a major predictor of behavioral intention. This demonstrates how social and cultural factors influence Pakistani logistics workers' ambitions to use Blockchain. The correlation matrix and covariance analysis demonstrate that there are significant positive relationships between attitude, behavioral intention, perceived ease of use, perceived usefulness, and subjective norm. This detailed examination of the adoption environment offers practitioners, policymakers, and academics context-specific insights, setting the framework for informed freight logistics technology adoption and innovation activities in Pakistan.

Economic Crisis and its Effects on ERP Adoption in Sri Lanka

ERP (Enterprise Resource Planning) systems are comprehensive software platforms that are specifically designed to manage a wide range of a business's essential processes, including finance, accounting, human resources, procurement, inventory management and project management. In the event of a country facing forthcoming economic collapse, organizations often find it challenging to determine the technological innovation activities they should engage in. The proliferation of the IT industry and its associated value proposition has led to the adoption of ERP systems becoming a popular strategic decision for businesses in the contemporary world. However, organizations' perception affects their inclination to adopt new technologies during economic crises. Hence, identifying factors influencing ERP adoption and assessing crises' impact on such systems is crucial. This research endeavor aims to examine the factors that are likely to exert a significant influence on the adoption of ERP systems within the context of Sri Lanka. The study adopts the Technological - Organizational – Environmental (TOE) framework to provide a comprehensive understanding of the factors that affect the adoption of ERP systems in organizations in Sri Lanka. This study seeks to investigate how the factors identified impact the adoption of ERP systems and how the turbulent economic condition in Sri Lanka has affected it. Existing scholarly literature on ERP adoption during an economic crisis is relatively scarce, and thus, this study will fill a critical gap in the body of knowledge. Furthermore, this study will offer invaluable insights into the importance of the identified factors, ICT Infrastructure, Human Capital, Competitive Pressure, Demand for Products or Services and Trading Partners’ Readiness for business communities in Sri Lanka. Also, this will provide insights into how a country's finance affects ERP adoption, helping organizations make informed technology adoption decisions. Keywords: Economic crisis, Enterprise Resource Planning systems, ERP adoption, Innovation and Technology, Technology adoption and PLS-SEM.

The impacts of anxiety emotion and behavioral control on student learning management system adoption

PurposeThe COVID-19 global pandemic reframed the argument for the importance of learning management systems (LMS) in unprecedented ways. Meanwhile, LMS users were forced to use these technologies despite the heightened anxiety compounded by the pandemic, very little technical preparation and the postpandemic learning environment that cannot depend on these pandemic-imposed regulations and adoptions. This study aims to examine the impacts of behavioral control and anxiety emotions on adoption decisions.Design/methodology/approachThis quantitative research uses structural equation modeling to test the hypothesized relationships.FindingsResults showed that perceived behavioral control is very important in boosting ease of use perceptions while computer anxiety exhibited a negative impact on perceived ease of use.Research limitations/implicationsThis research used cross-sectional data from a medium-sized university. Results must, therefore, be interpreted with this understanding in mind. Nonetheless, this research demonstrates the critical roles of control and emotions in technology adoption decisions among students in an online learning environment.Originality/valueThis research highlights the importance of behavioral control and anxiety emotions in technology adoption decisions. It reveals that to drive adoption, students’ control perceptions must be increased while simultaneously keeping anxiety emotions at bay. This understanding is key to communicating buy-in of LMS to students.

Strategic contexts, strategic orientations and organisational technology adoption: A configurational approach

AbstractDespite the broad application of the technology–organisation–environment (TOE) framework to explain firms' adoption of technology, prior research tends to over‐emphasise the independent effects of TOE elements while neglecting decision makers' strategic orientations when making organisational technology adoption decisions. This over‐simplistic interpretation of the TOE framework has culminated in inconsistent findings within extant literature. Considering the interdependencies among the three TOE elements in shaping organisational technology adoption and also decision‐makers' inclination to weigh the three TOE elements differently based on their strategic orientations, this study views organisational technology adoption from a systems standpoint based on a configurational approach. Particularly, we differentiate between two types of strategic orientations, namely functional orientation, which accentuates the technology‐induced efficiency gains and symbolic orientation, which stresses the image or reputation afforded through technology adoption. We advance a configurational model for organisational technology adoption that: (1) conceptualises organisational technology adoption as an outcome arising from distinct configurations of TOE elements, and; (2) extends the TOE framework by incorporating strategic orientation as an inevitable aspect of decision‐making for organisational technology adoption. To validate our proposed model, we conducted a field survey of 183 firms to collect data on their considerations underpinning organisational technology adoption before employing fuzzy‐set Qualitative Comparative Analysis to derive configurations of TOE elements responsible for driving such adoption. Analytical results reveal that the TOE configurations vary across three types of organisations (namely performance enhancer, image builder and strategic transformer). The theoretical and practical implications of our study are also discussed.

Does bundling credit with index insurance boost agricultural technology adoption? Evidence from Ghana

AbstractThe adoption of advanced agricultural technologies in Sub‐Saharan Africa remains disappointingly low, particularly among the millions of poor smallholders who account for most of the agricultural production. We conducted a randomized control trial in Ghana to assess the impact of easing drought‐risk constraints in the agricultural credit market, by bundling joint liability agricultural loans with index insurance, on smallholder farmers’ agricultural technology adoption decisions. In the micro‐insurance treatment, any index insurance payouts go directly to farmers, while in the meso‐insurance treatment, payouts are issued to banks to be used to expunge farmers’ debts. We find evidence that bundling joint liability lending with micro‐insurance increases adoption of fertilizer.

Localized Knowledge Spillovers and Organizational Capabilities: Evidence from the Canadian Manufacturing Sector

Purpose - This study empirically investigates how the effects of localized knowledge spillovers on technology adoption are conditional on the organizational capabilities of potential adopters.
 Design/methodology - The empirical model utilized in this study examines how the presence of prior adopters of advanced manufacturing technologies affects a plant’s technology adoption decision differently based on its organizational capabilities, measured by plant size and plant status (single- plant firm vs. multi-plant firm). Moreover, this study investigates how the scope of knowledge spillovers from prior adopters, both in terms of geographical and functional proximities, differ for plants with different organizational capabilities.
 Findings - The main findings of this study are as follows: 1. Although plants with lower organizational capabilities are less likely to adopt advanced technologies, such plants receive greater marginal benefits from knowledge spillovers from prior adopters in their region. 2. Plants with greater organizational capabilities can benefit from knowledge spillovers from a wider set of prior adopters. In other words, while plants with lower organizational capabilities tend to benefit from knowledge spillovers from “similar” and “local” adopters, plants with greater organizational capabilities can also benefit from knowledge spillovers from “not-too-similar” or are geographically distant prior adopters.
 Originality/value - While existing studies mainly focus on the effects of the various kinds of regional agglomeration, few studies investigate localized knowledge spillovers in technology adoption. Moreover, no prior studies have explored how the effects of knowledge spillovers on technology adoption depend on a plant’s organizational capabilities and how the scope of knowledge spillovers differs for plants with different organizational capabilities. This study is the first to empirically investigate this topic.

Digitalization & Covid-19: An institutional-contingency theoretic analysis of supply chain digitalization

Black Swan external contingencies like the COVID-19 pandemic or Suez Canal blockage have a significant impact on the technology adoption decisions in firms. At a firm level, supply chains are the segments that are most prone to disruption due to these shocks. Hence the need to study the role of these contingencies in enabling digitalization in supply chains. Modern supply chains operate in a strong institutional environment that influences various aspects like technology adoption and digitalization. In this study, we bring these two aspects together by applying an institutional and contingency theory perspective. We investigate the institutional forces and the effect of environmental contingencies on the digitalization of supply chains. We propose a generalizable model to investigate digitalization readiness independent of the technological artefact being implemented. To achieve the same, we identify the forces of digitalization in the supply chains from the review of the extant literature. We then model the forces of digitalization into a Bayesian Belief Network (BBN). The study finds that organizational readiness and people readiness are critical elements of digitalization readiness. Our study reports the importance of top management's involvement and employees' training as the critical forces aiding digitalization.

Intrahousehold preference heterogeneity and demand for labor‐saving agricultural technology

AbstractEvaluations of agricultural technologies rarely consider the implications of how adoption may alter the labor allocation of different individuals within a household. We examine intrahousehold decision‐making dynamics that shape smallholder households' decision to use mechanical rice transplanting (MRT), a technology that disproportionately influences demand for women's labor. To study the adoption decision, we experimentally estimate the willingness to pay for MRT services both at the individual and household level. We find that women value MRT more than men, especially when they participate in transplanting on their own farms. This preference heterogeneity is evident in the unconditional differences between women's and men's valuation and differences conditional on their individual observable characteristics. Despite having stronger preferences for MRT, women have less influence on the household's technology adoption decision than men. This differential influence over the MRT adoption decision reflects the intrahousehold power structure: in households where women have less control over assets, they also have less influence over the MRT adoption decision. Our results highlight how technological changes interact with unobserved, gender‐based intrahousehold power relations to influence agricultural production decisions and, by extension, the gendered allocation of labor and welfare of women.

How Do Risk Preferences Affect Golf Course Superintendents’ Adoption of Precision Irrigation Technologies? Implications from Prospect Theory

AbstractPrecision irrigation is a potential viable strategy for water use reductions on golf courses by making variable or site-specific irrigation applications. A group of US golf course superintendents were surveyed to examine whether and how superintendents’ risk preferences (attitudes) affect the adoption decisions of precision irrigation technologies on their golf courses. Under the prospect theory (PT) framework, a lottery experiment was used to elicit the measures of three risk attitudes, that is, risk curvature, probability distortion, and loss aversion. Using these three measures and other questions in the survey, we found that risk curvature has a significant positive effect on the precision irrigation technologies adoption on golf courses, while probability distortion affects the adoption negatively. Compared to the golf course in low precipitation areas, superintendents’ risk attitudes are more likely to affect the precision irrigation technologies adoption in the golf course in high precipitation areas. Additionally, risk curvature dominates the adoption decisions for newer technologies, while probability distortion dominates the older technologies adoption decisions. Our research enriches the literature on the decision-making behaviors of managers by considering how probability distortion, a factor typically ignored by other studies, affects technology adoption decisions and adds to the literature on examining the technology adoption behaviors under PT by focusing on golf course superintendents, a group that has not been studied.

Health Technology Reassessment: Addressing Uncertainty in Economic Evaluations of Oncology Drugs at Time of Reimbursement Using Long-Term Clinical Trial Data.

The evidence base to support reimbursement decision making for oncology drugs is often based on short-term follow-up trial data, and attempts to address this uncertainty are not typically undertaken once a reimbursement decision is made. To address this gap, we sought to conduct a reassessment of an oncology drug (pembrolizumab) for patients with advanced melanoma which was approved based on interim data with a median 7.9 months of follow-up and for which long-term data have since been published. We developed a three-health-state partitioned survival model based on the phase 3 KEYNOTE-006 clinical trial data using patient-level data reconstruction techniques based on an interim analysis. We used a standard survival analysis and parametric curve fitting techniques to extrapolate beyond the trial follow-up time, and the model structure and inputs were derived from the literature. Five-year long-term follow-up data from the trial were then used to re-evaluate the cost-effectiveness of pembrolizumab versus ipilimumab for treatment of advanced melanoma. The best fitting parametric curves and corresponding survival extrapolations for reconstructed interim data and long-term data reconstructed from KEYNOTE-006 were different. An analysis of the 5 year long-term follow-up data generated a base case incremental cost-effectiveness ratio (ICER) that was 28% higher than the ICER based on interim trial data. Our findings suggest that there may be a trade-off between certainty and the ICER. Conducting health technology re-assessments of certain oncology products on the basis of longer-term data availability, especially for those health technology adoption decisions made based on immature clinical data, may be of value to decision makers.

Technology adoption behaviors of farmers during crises: What are the key factors to consider?

The Covid-19 pandemic required economic agents, in this case farmers, to make immediate decisions with an eye on a future characterized by high level of uncertainty. Using a multivariate probit, this paper examines the factors that farmers, as economic agents, considered at the peak of the pandemic in their digital (e-service) technology adoption decisions. The results indicate that the key factors that influence digital technology adoption behaviors of farmers are age, gender, education, level of dependency, experience in farming, access to credit and perceived possible impact of the pandemic on production activities. These factors were found to have different levels of influences on the adoption of different digital technologies that could help reduce physical contacts in line with nationally determined Covid-19 protocols whiles sustaining agricultural production activities. Digital technologies that facilitate easy access to good agronomic practices, weather information services, input and output market information services and financial services were identified as crucial. The general conclusion of this paper is that farmers are willing to adopt technologies that add value to their welfare through timely resolution of problems that confront them. Thus, value propositions – such as relevance, effectiveness, efficiency, sustainability, and impact – must be the key considerations in policy interventions that promote positive technology adoption behaviors.

The Role of IT Governance in Shaping Organizations’ Technology Adoption Decision

The Role of IT Governance in Shaping Organizations’ Technology Adoption Decision

MSR34 Is the Usage of Immature Survival Data Surviving the HTA Decision?

In health technology appraisal (HTA) submissions for oncology, decision-makers are often presented with incomplete survival data on new treatments, making it difficult to evaluate the long-term benefits of the treatment amidst uncertainty and posing challenges to technology adoption decisions. This study aims to understand how often National Institute for Health and Care Excellence (NICE) UK informs its decisions for cancer treatments using immature overall survival (OS) data alongside understanding its impact on decision-making.

Firms and Technology Adoption: The Role of Political Institutions and Market Size

The study presents a political economy model and analyses how firms behave towards technology up-gradation given the different dynamics of political and market institutions. The model presented here depicts that political power is controlled by the elite, who formulate trade policy to consolidate power. While the middle-class access the production technology and the labour class provides labour inelastically. The model shows that the technology adoption decision of a firm essentially depends upon the political institutions and the market size of the country. Firms in a country with strong democratic institutions adopt new technology more rapidly. While in a weak democracy, firms successfully persuade the elite policymaker to impose higher trade restrictions and obtain higher protection from technologically advanced foreign firms. Moreover, the model also shows that firms operating in a large market adopt technology more rapidly since a large market has a high price elasticity of demand and supports a large number of larger firms. Furthermore, firms adopt technologies more swiftly when the productivity gains from the adoption are relatively large.

When businesses go digital: The role of CEO attributes in technology adoption and utilization during the COVID-19 pandemic

COVID-19 has prompted a rush of technology adoption as businesses turned to digital technologies to avert closure in the face of an unprecedent pandemic. This study examines the adoption and utilization of e-commerce and remote work technologies among small and medium enterprises (SMEs) during the pandemic. Building on various streams of research on technology adoption and utilization, we elaborate how CEO gender and experience can shape risk-taking attitude and crisis responsiveness, influencing technology adoption and utilization decisions. Analysis using a rich dataset of >20,000 enterprises across 42 countries revealed that female CEOs were significantly less likely to adopt remote work technologies; moreover, female CEOs leading small-sized enterprises were less likely to adopt e-commerce. However, CEO gender was not associated with the utilization intensity of remote work and e-commerce technologies. CEOs' industry experience was found to have an inverted U-shaped relationship with the adoption and utilization of both e-commerce and remote work technologies. These results reveal that top management decisions attributable to CEO experience, and to a lesser degree to CEO gender, can help explain divergent levels of digital technology adoption and utilization during the pandemic.

The source of uncertainty influences technology adoption

AbstractWe shed light on Florida citrus growers’ decisions regarding their adoption of scientifically untested antibiotic sprays over insecticide spray coordination for dealing with the devastating impact of a pernicious plant disease. Using data from a framed field economic experiment, we examine growers’ preferences towards two types of uncertain outcomes, the first resulting from a game against nature and the second involving strategic interaction. We find evidence that, on average, growers prefer the game against nature. Moreover, we find that they prefer such a game even for ranges over which the game involving strategic interaction has a higher likelihood of success. The results and insights we obtain help better understand growers’ preferences over different types of uncertainty, which can play a key role in their technology adoption decisions. Our findings should be useful for policymakers to realise the implications of allowing the use of uncertain technologies and the detrimental impact they can have in dealing with issues that involve externalities such as those present in pest and disease management.