Search results

The proliferation of ride-hailing businesses brings significant considerations for improving the driver's operational performance. Informed by the literature on sharing economy, general deterrence theory and protection motivation theory this research investigates the behavioral factors impacting ride-hailing drivers' operational performance.

The authors empirically test the antecedents impacting a ride-hailing driver's operational performance using an online survey dataset comprising 513 ride-hailing drivers working for Uber and Lyft in the United States.

Ride-hailing drivers' intention to comply with the ride-hailing company guidelines results in better operational performance for the driver. Moreover, drivers believe that ride-hailing companies have effective penalties to deter drivers from violating company guidelines. However, drivers also believe that the chances of being caught while ignoring the company guidelines are low.

The results of this research support the decision-making processes of ride-hailing company managers and offer insights on how managers can enhance the operational performance of their drivers.

This study provides unique contributions to emerging research at the intersection of peer-to-peer asset sharing, behavioral studies and technology management. This research is one of the first to explore the role of behavioral factors such as coping mechanisms on the operational performance of sharing economy workers.

The purpose of this paper is to deal with the practical challenge faced by modern logistics enterprises to accurately evaluate driving performance with high computational efficiency under the disturbance of road smoothness and to identify significantly associated performance influence factors.

The authors cooperate with a logistics server (G7) and establish a driving grading system by constructing real-time inertial navigation data-enabled indicators for both driving behaviour (times of aggressive speed change and times of lane change) and road smoothness (average speed and average vibration times of the vehicle body).

The developed driving grading system demonstrates highly accurate evaluations in practical use. Data analytics on the constructed indicators prove the significances of both driving behaviour heterogeneity and the road smoothness effect on objective driving grading. The methodologies are validated with real-life tests on different types of vehicles, and are confirmed to be quite effective in practical tests with 95% accuracy according to prior benchmarks. Data analytics based on the grading system validate the hypotheses of the driving fatigue effect, daily traffic periods impact and transition effect. In addition, the authors empirically distinguish the impact strength of external factors (driving time, rainfall and humidity, wind speed, and air quality) on driving performance.

This study has good potential for providing objective driving grading as required by the modern logistics industry to improve transparent management efficiency with real-time vehicle data.

This study contributes to the existing research by comprehensively measuring both road smoothness and driving performance in the driving grading system in the modern logistics industry.

The innovation of business model (BM) is a strategic process for many firms, from which depends competitiveness and sustainability. Despite its theoretical relevance in management sciences, research on business model innovation is in its infancy and lacks of research consistency and theoretical connections to the theme of “performance”. With the aim to contribute in bridging this gap, this paper aims to identify and analyse drivers of business model innovation performance.

This research is based on an integrative literature review methodology.

BMI performance drivers are conditions related to various dimensions (i.e. processes, resources, market, BM structure, etc). that, when fulfilled, allow the BMI to have higher performance. BMI performance drivers are antecedents of BMI performance, and their identification is of both theoretical and practical value. The authors find and report a set of 35 BMI performance drivers.

The value of this research is both theoretical and practical. From a theoretical point of view, the identified “Business Model Innovation performance drivers” define and identify a variable of BMI performance, from a practical perspective, and they provide a comprehensive set of key conditions whose attainment should be planned, pursued and monitored by managers.

Many factors have been identified that may drive a firm’s decision to offshore production activities. The actual performance effects of offshoring, however, depend on the extent to which these drivers are realized. Furthermore, the question is how risk management helps mitigating the risk involved in offshoring ventures, thus leading to better performance outcomes. The purpose of this study is to investigate the extent to which realized offshoring drivers and risk management mediate the relationship between offshoring experience and firm performance.

Data from the Global Operations Networks project, a cross-sectional survey administered in Denmark and Sweden, are used to test two hypotheses on the mediating role of realized offshoring drivers and risk management in the relationship between offshoring experience and firm performance. AMOS version 23 is used to perform the analyses.

The results demonstrate that realized offshoring drivers fully mediate the relationship between offshoring experience and firm performance. However, risk management does not mediate the relationship between offshoring experience and firm performance.

This study develops new theory on, and managerial insight into, the mediating role of realized offshoring drivers and risk management in the relationship between offshoring experience and firm performance.

This research examines what key performance indicators (KPIs) and drivers should be applied at the post-contract phase of construction development to monitor and drive project outcomes in sustainable design and construction. It supplements the previous research which focuses on pre-contract sustainable procurement of competent professionals. Consequently, optimal sustainability can be achieved for the overall sustainable development process.

A review of empirical work was conducted to consolidate the holistic aspects of sustainability that should be considered for design and construction and their project outcome KPI measures. Based on a country-wide questionnaire survey of the university estate sector in the UK, a quantitative hierarchical regression analysis was conducted to identify the performance drivers for those KPIs.

The empirical work review demonstrates that holistic sustainability for development can be measured by project outcome KPIs: economic sustainability by cost KPIs; functional, social and environmental sustainability by quality KPIs. The quantitative hierarchical regression analysis confirmed that these four aspects of sustainability could be significantly driven by task performance and contextual performance drivers, as supported by the job performance theory.

The investigation was undertaken within the context of university estates forming a unique public sector in the UK. The findings form a baseline upon which further research can be conducted in other organisations in the wider public and private sectors. Ultimately, holistic sustainability can be fully driven by construction professionals to achieve government and corporate construction strategy for the benefits of sustainable built environment.

The findings inform project managers and construction professionals that they should apply clear, measurable cost and quality KPIs and focus on significant performance drivers in tandem to drive holistic sustainability for design and construction. Project staff should have a high commitment, technical expertise and experience, execute the project with proper design and management methods and provide a high level of trust and collaboration to the client. Clients, designers and contractors are key stakeholders in the development process so they should be consulted for forming the contract KPIs to monitor the sustainable project outcomes.

The generalised results confirm that task and contextual performance drivers can be applied as project management tools for managing the professional team members to achieve sustainability deliverables in terms of KPIs. Such findings will enhance the government or corporate construction strategy for managing and achieving holistic sustainability for construction developments.

This research identifies post-contract performance monitoring measures (cost and quality KPIs as well as task and contextual performance drivers) that can be adopted for driving sustainable design and construction for sustainable development.

This meta-analysis aims to explore the true effect sizes of major channel performance drivers from different theoretical perspectives and how these true effects are organized in a theoretically integrated structural analysis to predict performance.

First, it offers a quantitative summary on the drivers of channel performance through pairwise correlation analysis. Second, it tests an integrative framework of various performance drivers based on the relational view by using structural equation modeling. Last, it examines the potential moderation on the effects of performance drivers.

The synthesized effects of various channel performance drivers confirm the effectiveness of underlying theoretical perspectives of channel performance. The relational view is effective to identify immediate interorganizational drivers of channel performance. The contexts and methods of performance assessment have an impact on the appraisal of performance drivers.

The performance drivers included in this meta-analysis are constrained to variables that exist in empirical channels literature and have sufficient primary data for analysis. Moderation tests are constrained by the report of research contexts and methods in original studies. Future research should broaden the theoretical perspectives on channel performance.

First, leveraging key routines and processes embedded in marketing channel relationships is critical to improve channel performance. Second, more targeted effort to manage channels in different markets may improve the efficiency of channel performance enhancement. Last, a comprehensive performance assessment process is necessary to avoid biased estimation of performance drivers.

This meta-analysis provides a systematic review of factors influencing marketing channel performance by synthesizing and correcting the effect sizes of performance drivers from different theoretical perspectives. It further develops and tests an integrative model of four immediate interorganizational drivers of channel performance.

Drawing on ego depletion theory, this study aims to provide insights into the effect of work-family conflict on the high-speed railway (HSR) drivers’ safety performance by examining the mediating role of ego depletion and the moderating roles of work-family centrality and supervisor safety support.

In total, 243 HSR drivers from 7 railway bureaus in China were surveyed. Structural equation modeling was used to test the hypotheses.

Both work-to-family conflict and family-to-work conflict have direct and positive effects on HSR drivers’ ego depletion and indirect effects on both safety compliance and safety participation via ego depletion. Moreover, both the direct effect of work-family conflict on ego depletion and its indirect effect on safety performance are moderated by work-family centrality. Supervisor safety support plays a buffering role in the relationship between ego depletion and safety performance.

This study examined the relationship between work-family conflict and safety performance based on the perspective of ego depletion theory. The findings testify to the importance of reducing work-family conflict among HSR drivers pursuant to maximizing safety.

Construction frameworks are recognised by the UK Government as an integrated procurement path to deliver efficiency, collaboration and sustainability. This research paper aims to develop a performance-driving model for framework procurement to align with the government construction policy objectives.

A quantitative hierarchical regression analysis was conducted to examine the causal relationships between project outcomes and performance drivers. A successive qualitative multiple-case study involving eight typical construction framework projects was examined to further explain casual relationships.

Conclusive results from the quantitative and qualitative analyses validated the performance-driving model, generalising a framework procurement principle that project outcomes of time, cost, quality, sustainability and closer relationships are significantly driven by supplier's task and contextual performance drivers, and client's organisational drivers.

The investigation followed two major public-sector organisations in the UK: infrastructure offices of local authorities and estate offices of universities. Further research should be extended to other public-sector situations to enhance the model further.

Using this model, framework managers can drive project outcomes by applying task and contextual performance drivers in order to select the best suppliers at the procurement phase, and by adopting the client's organisational factors at both procurement and construction monitoring phases.

The empirical evidence supports the use of frameworks by public sector policymakers as a key strategy to develop the performance drivers further and improve efficiency and quality outcomes.

The results will be of value to support the policy of public-sector works organisations contemplating using framework procurement for executing continuing construction activities.