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Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.

Although outcome sharing in construction is a well-established concept in the literature, there is still an ongoing debate on the most effective approach for distributing project outcomes between an owner and downstream contracting parties (DCPs). To address this issue, this paper aims to investigate an optimal framework for distributing project outcomes among various levels of subcontracting in construction projects. The framework includes contractors, subcontractors, sub-subcontractors and other related parties.

To formulate the optimization problem, the principal–agent model is utilized. The theoretical development is validated through an experiment conducted with employees from road construction companies.

When distributing outcomes among various levels of subcontracting, the sharing should be determined by their contribution to the outcome, effort costs, level of outcome uncertainty and risk preference.

This paper expands on the existing principal–agent theory by incorporating multiple levels of agents, transforming the conventional view of outcome sharing among downstream subcontracting levels into testable hypotheses and well-defined concepts. The paper has practical implications for industry practitioners seeking to effectively allocate benefits and costs throughout a project's subcontracting chain.

People usually try to avoid uncertainty. Recently, however, uncertainty has become an emerging marketing tool in the hedonic product industry. In the case of blind box consumption, for example, the consumers become addicted to the uncertainty created by businesses, leading to repeat purchases and even indulgences. Previous research has, yet, to focus on the impact of uncertainty on indulgence and the role of emotions.

This paper constructs and validates a chain mediation model of uncertainty triggering indulgent consumption based on the information gap theory, positive emotion theory and uncertainty resolution theory and examines the difference between resolved and unresolved uncertainty. This study also explores differences in the impact of whether uncertainty is resolved on emotions. The uncertainty-resolved group elicited a more positive emotional response than the uncertainty-unresolved group, leading to a more indulgent consumption.

The results of three studies show that uncertainty influences indulgent consumption through curiosity and positive emotion, and that curiosity and positive emotion play separate and chain mediating roles between uncertainty and indulgent consumption, respectively. We validate our central hypothesis with questionnaires among blind box consumer groups, examining the moderating role of perceived luck and risk preferences.

The findings shed new light on firms' use of uncertainty to promote consumer purchases.

The paper’s purpose is to consider, using a transaction cost economics (TCE) framework, the mechanisms used by space agencies to encourage private investment in the commercial spaceflight sector.

The authors conducted a content analysis of 554 pages of news articles, relating to issues pertaining to partnerships between national government-based space agencies and private space travel providers, published over a 20-year period. Leximancer was used to initially screen the data and then the authors manually analysed the content to identify themes.

The data analysis revealed three themes, relating to: the uncertainty of space travel; National Aeronautics and Space Administration (NASA) stimulating innovation in the private sector; and risk, insurance and regulation. These themes informed by TCE reveal the “hierarchical” organisational forms used to achieve human spaceflight and then the “hybrids”, insurance and regulations used to stimulate private sector investment and innovation.

This paper contributes to the accounting literature by answering the calls of Alewine (2020) and Tucker and Alewine (2022a, b) for more research into accounting in the space context. Specifically, the paper contributes by identifying mechanisms used by NASA to stimulate private investment in the space travel sector, as well as issues that have affected the implementation of these mechanisms. The paper also contributes to the literature by, based on the analysis, identifying a series of reflections designed to stimulate further management accounting research in the space context.

This study aims to investigate the impact of organizational external environmental factors on strategic management accounting (SMA) usage in an emerging economy.

The study collected data from 79 public limited companies listed with the Dhaka Stock Exchange (Bangladesh) through a questionnaire survey. Multiple regression analysis is employed to test the impact of external environmental variables such as perceived environmental uncertainty and intensity of competition on SMA usage.

The study finds a significant positive impact of environmental uncertainty (fluctuation in the external environmental factors) and intensity of competition (domination by few companies) on SMA usage. However, the direction and magnitude of this impact vary considerably for specific groups of SMA practices such as costing, competitor accounting, customer accounting and planning and performance measurement techniques.

This study shows the impact of several facets of environmental uncertainty (i.e. unpredictability, fluctuation, ambiguity, lack of information and uncertainty of the outcome of decision) and intensity of competition (i.e. stressfulness and domination) in the empirical-based SMA research.

Economic policy uncertainty has increased around the world since the financial crisis of 2007–2008. While scholars have devoted a lot of time and energy to investigating the impact of economic policy uncertainty (EPU) on firm innovation, they have not reached consistent research conclusions. This study aimed to clarify the above research differences by exploring the impact of EPU on firms' relative exploitative innovation emphasis, so as to provide a more comprehensive and granular understanding of the relationship between EPU and firm innovation.

This study obtained 17,165 firm-year data points from 3,107 listed companies in China. It analyzed the above data with a fixed effects model. In addition, this study used an instrumental variables method to solve potential endogeneity problems.

Based on real options theory and contingency theory, the authors proposed and found that EPU has a significant positive effect on relative exploitative innovation emphasis. In addition, the authors proposed and found that this effect is more pronounced in industries with high technological uncertainty, low competitive intensity, and low state monopolization.

This study is the first to explore why firms prefer exploitative innovation over exploratory innovation from the perspective of EPU. In doing so, this study expands and enriches the EPU literature and the innovation literature. Furthermore, by introducing the moderating role of industry environment, this study deepens the authors' understanding of how complex interactions between industry and institutional environments work together to shape firm strategic choices, and especially firm innovation. Finally, the conclusions of this study have important practical implications for shareholders to take measures to balance exploitative innovation and exploratory innovation to achieve better development.

Utilizing the theoretical foundation of the stimulus-organism-response framework, the present work developed and investigated a conceptual model. The work explores the effects of perceived risk of COVID-19 on tourists' choice hesitation and choice confidence. Furthermore, it examines the impacts of choice hesitation and choice confidence on psychological distress, which, in turn, influences purchase intentions and risk-protective behavior. Additionally, the study assesses the boundary effects of vulnerability on the association between choice hesitation, choice confidence, and psychological distress.

An online survey was administered in China during COVID-19 to assess the postulated hypotheses. We collected 491 responses using purposive sampling, and covariance-based structural equation modeling (CB-SEM) was performed to investigate the relationships.

Results show that the perceived risk of COVID-19 positively influences the choice hesitation and negatively impact choice confidence. It was also found that choice hesitation and choice confidence positively developed psychological distress, which, in turn, negatively triggered purchase intentions and positively developed risk-protective behavior. Additionally, perceived vulnerability had a significant moderating impact on the proposed relationships, strengthening psychological distress.

In the current context, this study measures bipolar behavioral outcomes using the S-O-R model. Because cognitive processes influence participation in health preventative behavior during the spread of diseases, we highlighted how the perception of risk and vulnerability to a pandemic serves as a reliable indicator of certain behaviors. This study advances understanding of how the psychological mindset of tourists copes with such circumstances. Due to the pandemic, tourists face limitations in their choices and are placing greater emphasis on adopting protective measures to mitigate associated risks.

This study examines the motivational processes of charged behavior and collective efficacy driving interdependence and agency in new product development (NPD) teams and the moderating impact of team risk-taking propensity as affective, cognitive and behavioral social processes support team innovation.

Data were collected from 92 NPD teams engaged in B2C and B2B product and service development. Mediating and moderating effects are examined using partial least squares structural equation modeling, referencing social cognitive and collective agency theories as the research framework.

The analysis validates collective self-efficacy and charged behavior as interdependent motivational–affective processes that align cognitive resources and govern team effort toward innovativeness. Teams' risk-taking propensity regulates behavior, and collective efficacy facilitates self-regulated motivational engagement. Charged behavior cultivates the emotional contagion, team identification, cohesion and adaptation required for team functioning. Team potency fosters cohesiveness, while team learning improves adaptability along the innovation journey. The resulting theory asserts that motivational drivers enhance the interplay between cognitive and behavioral processes.

Managers should consider NPD teams as social systems with a capacity for collective agency nurtured through interdependence, which requires collective efficacy and shared competencies to generate motivational purpose and innovativeness. Managers must remain mindful of teams' risk tolerance as regulating the impact of motivational factors on innovativeness.

This study contributes to research on the motivational–affective drivers of NPD charged behavior and collective efficacy as complementary to cognitive and behavioral processes sustaining team innovativeness.

The construction industry is a major economic driver in Malaysia, playing a pivotal role in the developing nations economic growth. Malaysia's reliance on labor-driven construction practices often sees local industry lagging in adopting technological advancements common to the construction sector on a global scale. This study investigates the challenges faced by project players in using new construction industrial revolution (IR) 4.0 technologies and the difficulties in implementing these technologies in construction projects.

A quantitative survey was distributed to 183 practitioners in the Malaysian construction industry. The collected data (N = 121) has been analyzed using statistical software to calculate relative importance index values for the identified factors. A triangulation approach to validate the factors obtained from the survey was conducted with an expert group to ensure there were no additional considerations identified in the study.

The study results show that the main factors in adopting construction IR 4.0 technologies are 1) high implementation costs, 2) hesitation to adopt technologies, 3) lack of standards, 4) legal and contractual uncertainty and 5) complexity. By investigating these factors, cost and regulation issues can gradually be resolved, with construction firms implementing new technologies, educating workers and ensuring government involvement in training for skill development to support IR 4.0.

The outcome of these efforts to resolve construction productivity would be beneficial in their industry impact on practice and digital transformation. Additionally, the results add to the body of knowledge for construction practitioners and technology developers to work together efficiently on the implementation of construction 4.0 technologies.

This paper aims to propose a simulation-based performance evaluation model for the drone-based delivery of aid items to disaster-affected areas. The objective of the model is to perform analytical studies, evaluate the performance of drone delivery systems for humanitarian logistics and can support the decision-making on the operational design of the system – on where to locate drone take-off points and on assignment and scheduling of delivery tasks to drones.

This simulation model captures the dynamics and variabilities of the drone-based delivery system, including demand rates, location of demand points, time-dependent parameters and possible failures of drones’ operations. An optimization model integrated with the simulation system can update the optimality of drones’ schedules and delivery assignments.

An extensive set of experiments was performed to evaluate alternative strategies to demonstrate the effectiveness for the proposed optimization/simulation system. In the first set of experiments, the authors use the simulation-based evaluation tool for a case study for Central Florida. The goal of this set of experiments is to show how the proposed system can be used for decision-making and decision-support. The second set of experiments presents a series of numerical studies for a set of randomly generated instances.

The goal is to develop a simulation system that can allow one to evaluate performance of drone-based delivery systems, accounting for the uncertainties through simulations of real-life drone delivery flights. The proposed simulation model captures the variations in different system parameters, including interval of updating the system after receiving new information, demand parameters: the demand rate and their spatial distribution (i.e. their locations), service time parameters: travel times, setup and loading times, payload drop-off times and repair times and drone energy level: battery’s energy is impacted and requires battery change/recharging while flying.