Search results

This research aims to develop a blockchain smart contract–enabled framework to resolve power imbalance problems in construction payment.

This research adopts a design science research method to develop the blockchain smart contract–enabled framework. The authors then develop a prototype system. Finally, the authors evaluate its performance in solving power imbalance-induced payment problems.

The results show that the prototype system can resolve power imbalance problems in construction payment by allowing project participants to make transparent and decentralized decisions that are self-enforceable by blockchain smart contracts.

This study provides theoretical explanations for how blockchain smart contracts can resolve power imbalances in construction payment; based on that, it proposes a novel blockchain smart contract–enabled method to rebalance the power of stakeholders in construction payment. Thus, it contributes to the body of knowledge on blockchain technology and construction payment.

This study moves beyond a conceptual framework and develops a practical blockchain smart contract system for resolving power imbalances in construction payment, strengthening construction project members' confidence in using blockchain technology.

The proposed blockchain smart contract–enabled solution helps mitigate negative social impacts associated with late payment and non-payment. Furthermore, the research maximizes trust among participants in payment processes to inspire collaborative culture in the construction industry.

This paper introduces a novel blockchain smart contract integrated method, allowing project stakeholders to resolve power imbalance problems in construction payment through decentralized decision-making.

Participation in global value chains (GVCs) is increasingly related to the economic growth of any country. The conceivable beneficial impact of GVCs on economic growth differs across countries and could be modified with the countries' domestic institutional arrangements. However, ignoring the complementarity between the components of institutional quality led to ignorance of the institutional imbalance present in the country. Hence, the primary purpose of this study is to examine the role of institutional imbalance as a moderating variable between GVC participation and economic growth from 2000 to 2018.

To address the issue of endogeneity among the variables in the model, the study employs the generalized methods of moments (GMM) as an econometric analysis method.

The study finds that well-functioning domestic institutions facilitate the positive impact of GVC participation on economic growth. Conversely, an increased institutional imbalance harms the relationship between GVC participation and economic growth. These findings emphasize a balanced portfolio of institutional components. It advocates the holistic development of each component to reap greater benefits for GVC participation for any country. The study highlights that the weakness in one of the components must be addressed rather than substituted by increasing the strength of another component.

The policies should be framed to improve the weakest component first, followed by other components of institutional quality. Simultaneous reforms involving all the dimensions of institutional quality would smoothen the path of transforming GVCs trade to the country's economic development. Additionally, the high institutional imbalance can provide a bird's eye view to policymakers to work on specific aspects of institutional quality more rigorously.

The existing literature has used a combined measure of institutional quality as a mediator variable while measuring the impact of GVC participation on economic growth. While using a combined measure, it ignores the complementarity among its components. Assuming substitutability among various components may lead to an incorrect estimation. Using the arguments proposed by Bolen and Sobel (2020), the present study considers the existence of complementarity among various components of institutional quality. It calculates the institutional imbalance used as a moderating variable while estimating the impact of GVC participation on economic growth.

Leveraging Emerson’s theory of power and motivated reasoning, this study aims to explore how the net power of an individual and actual, instead of perceived, vulnerability results in asymmetric trust and distrust development in a dyadic relationship.

Based on extant literature and gaps in the literature, this conceptual paper hypothesises and proposes trust formation based on power dynamics and vulnerability.

This research extends the knowledge base by exploring the role of actual vulnerability over perceived vulnerability in trust formation and distrust formation.

The research propositions imply that the dyadic trust formation process is not rational, and trust itself is not symmetrical but asymmetrical. The net power possessed by one individual over the other drives trust. Net power balance determines the actual vulnerability of the focal individual, and then the individual, through motivated reasoning, trusts or distrusts another individual. Scholars, going forward, could explore how trust formation varies at group and firm levels.

Extant literature has not explored the role of power imbalance in determining actual (versus perceived) vulnerability that influences trust formation between parties. The conceptual paper fills this gap.

Recommendation systems are a fundamental tool for hotels to adopt a differentiating competitive strategy. The main purpose of this work is to use machine learning techniques to treat imbalanced data sets, not applied until now in the tourism field. These techniques have allowed the authors to analyse the influence of imbalance data on hotel recommendation models and how this phenomenon affects client dissatisfaction.

An opinion survey was conducted among hotel customers of different categories in 120 different countries. A total of 135.102 surveys were collected over eleven quarters. A longitudinal design was conducted during this period. A binary logistic model was applied using the function generalized lineal model (GLM).

Through the analysis of a representative amount of data, the authors empirically demonstrate that the imbalance phenomenon is systematically present in hotel recommendation surveys. In addition, the authors show that the imbalance exists independently of the period in which the survey is done, which means that it is intrinsic to recommendation surveys on this topic. The authors demonstrate the improvement of recommendation systems highlighting the presence of imbalance data and consequences for marketing strategies.

The main contribution of the current work is to apply to the tourism sector the framework for imbalanced data, typically used in the machine learning, improving predictive models.

While prior research has established that traumatic brain injury (TBI) is a risk factor for violent offending, there is little understanding of mechanisms that may underpin this relationship. This is problematic, as a better understanding of these mechanisms could facilitate more effective targeting of treatment. This study aims to address these gaps in the extant literature by examining TBI as a predictor of violent offending and test for mediation effects through cognitive constructs of dual systems imbalance and hostility among a sample of justice-involved youth (JIY).

The Pathways to Desistance data were analyzed. The first three waves of this data set comprising the responses of 1,354 JIY were analyzed. Generalized structural equation modeling was used to test for direct and indirect effects of interest. A bootstrap resampling process was used to compute unbiased standard errors for determining the statistical significance of mediation effects.

Lifetime experience of TBI was associated with increased violent offending frequency at follow-up. Hostility significantly mediated this relationship, but dual systems imbalance did not. This indicated that programming focused on reducing hostility among JIY who have experienced TBI could aid in reducing violent recidivism rates.

To the best of the author’s knowledge, this study was the first to identify significant mediation of the relationship between TBI and violent offending through hostility.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

The purpose of this paper is to advance the understanding of paradoxes, underlying tensions and potential management strategies when integrating digital technologies into existing lean-based production systems (LPSs), with the aim of achieving synergies and fostering the development of production systems.

This study adopts a collaborative management research (CMR) approach to identify patterns of organisational tensions and paradoxes and explore management strategies to overcome them. The data were collected through interviews and focus group interviews with experts on lean and/or digital technologies from the companies, from documents and from workshops with the in-case researchers.

The findings of this paper provide insights into the salient organisational paradoxes embraced in the integration of digital technologies in LPS by identifying different aspects of the performing, organising, learning and belonging paradoxes. Furthermore, the findings demonstrate the intricacies and relatedness between different paradoxes and their resolutions, and more specifically, how a resolution strategy adopted to manage one paradox might unintentionally generate new tensions. This, in turn, calls for either re-contextualising actions to counteract the drift or the adoption of new resolution strategies.

This paper adds perspective to operations management (OM) research through the use of paradox theory, and we (1) provide a fine-grained perspective on why integration sometimes “fails” and label the forces of internal drift as mechanisms of imbalances and (2) provide detailed insights into how different management and resolution strategies are adopted, especially by identifying re-contextualising actions as a key to rebalancing organisational paradoxes in favour of the integration of digital technologies in LPSs.

The venture capital industry is an important provider of capital to start-ups and has grown considerably in recent decades. This study explores how investors' gender perceptions influence venture capital investment decisions in an industry that remains highly gender imbalanced, both amongst the venture capital decision-makers and with respect to the allocation of capital to entrepreneurs.

The authors' approach was informed by a thorough literature review and in-depth qualitative interviews with ten decision-makers at some of the foremost venture capital funds in Norway. Interviews were recorded, transcribed and coded using NVivo.

The authors' findings demonstrate that the Norwegian venture capital industry is influenced by homophily and role congruity. The authors highlight the challenges entrepreneurs face in gaining access to venture capital if they are not already members of the investors' network, a situation that results in a recycling effect that helps maintain the industry’s gender imbalance. Moreover, it appears that venture capitalists (VCs) favour masculine characteristics when assessing entrepreneurs, revealing a potential incongruence between female characteristics and perceived entrepreneurial attributes.

The authors' study contributes to and extends the extant literature on homophily and role congruity. Indeed, through investigating the gender-based perceptions of VCs, the authors shed new light on the mechanisms involved in their assessment of entrepreneurs, as well as on the drivers and barriers affecting female entrepreneurs.

The purpose of this paper is to study the role of psychosocial safety climate (PSC) on job satisfaction and emotional exhaustion among employees and to examine the mediating role of effort–reward imbalance (ERI) in this relationship.

This study investigated a mediation model with ERI explaining the relationship between PSC and the outcome variables using a sample of 441 employees of information technology (IT) organizations in India. The data were analyzed using structural equation modeling (SEM) techniques with LISREL (linear structural relations) 8.72 software.

The results suggest that PSC significantly influences the employees' experiences of job satisfaction and emotional exhaustion. Also, ERI was demonstrated as a significant intervening construct with full mediation of the PSC–emotional exhaustion relationship and partial mediation of the PSC–job satisfaction relationship.

The study provides substantial results and arguments to encourage organizational-level commitment for psychosocial risk management through distributive fairness and reciprocity in the form of ERI to foster positive attitudes and prevent negative health and psychological outcomes. The cross-sectional nature of the study limits generalizability but contributes to the literature on work stress in a developing country's context.

The study demonstrates how employee outcomes like job satisfaction and emotional exhaustion often result from their perceptions of inequity and imbalance at the workplace. Further, the study builds a strong case for helping organizations contribute to the United Nations (UN) 2030 sustainability goals by empirically establishing the crucial role of top management's commitment and prioritization of employee psychosocial health and safety for designing primary stress-management initiatives for sustainable psychosocial risk prevention and management.

The purpose of this paper is to study the relationship between trait self-control (TSC) and emotional exhaustion, and to examine the mediating role of effort–reward imbalance (ERI) and emotional demands.

A quantitative study was conducted using data from 441 employees working in different organizations in the information technology sector in India. PROCESS macro with a bootstrap sample size of 5,000 was used for mediation analysis.

TSC demonstrated a significant negative relationship with emotional exhaustion. Results indicated the crucial role played by ERI and emotional demands in influencing the emotional exhaustion of employees with higher TSC.

This study adds substantially to our knowledge of the role of TSC in employee experiences of emotional exhaustion. Results suggest how employees’ ERI perceptions and experiences of emotional demands determine whether higher TSC would reduce experiences of exhaustion. This adds to the knowledge of positive outcomes of self-control while throwing some light on why the use of self-control does not always incur a psychological cost, as suggested by some studies. The findings suggest that self-control is an individual resource that has the ability to alleviate emotional exhaustion through its influence on employees‘ effort–reward perceptions and experiences of emotional demands.