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This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?

A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.

The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.

The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.

The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?

The purpose of this paper is to develop a dynamic control method to improve bus schedule adherence under connected bus system.

The authors developed a dynamic programming model that optimally schedules the bus operating speed at road sections and multiple signal timing plans at intersections to improve bus schedule adherence. First, the bus route was partitioned into three types of sections: stop, road and intersection. Then, transit agencies can control buses in real time based on all collected information; i.e. control bus operating speed on road sections and adjust the signal timing plans through signal controllers to improve the schedule adherence in connected bus environment. Finally, bus punctuality at the downstream stop and the saturation degree deviations of intersections were selected as the evaluation criteria in optimizing signal control plans and bus speeds jointly.

An illustrative case study by using a bus rapid transit line in Jinan city was performed to verify the proposed model. It revealed that based on the proposed strategy, the objective value could be reduced by 73.7%, which indicated that the punctuality was highly improved but not to incur excessive congestion for other vehicular traffic.

In this paper, the authors applied speed guidance and the adjustment of the signal control plans for multiple cycles in advance to improve the scheduled stability; furthermore, the proposed control strategy can reduce the effect on private traffics to the utmost extend.

The aim of this paper is to explore the rationale and findings of the implementation of a Chinese lesson study (CLS)-informed model of mathematics teacher education in Italian schools. The study focuses on the modifications and invariance when introducing CLS in a different culture.

In a previous work (Bartolini Bussi et al., 2017), the authors focused on a single case of activity inspired by the CLS in Italy, and identified some conflicts emerging between the cultures of teaching in China and Italy and explored the way to overcome the conflicts. In the following years, the authors implemented lesson study (LS) experimentations with dozens of in-service primary school teachers and pre-service teachers who were gradually introduced to the model of CLS. The tensions/constraints occurred prominently when extending the experiments with many dozens of other in-service teachers and pre-service teachers.

The authors highlighted how the process of deconstruction allowed the participants in the study to either appropriate or reject some features of the CLS, linking this process to the cultural differences.

The authors believe and argue that LS, and CLS in particular, must be modified in the transfer from one culture to another, considering the cultural beliefs of the involved teachers.

The authors claim that the features of CLS compels the Western researchers to adopt local and culturally determined choices and to be aware of the rationale of these choices.

The purpose of this paper is to develop propositions explaining the influence of individual goals and social preferences on human decision making in transport planning. The aim is to understand which individual goals and social preferences planners pursue and how these influence planners’ decisions.

Propositions are developed based on investigation of decision making of transport planners in a Dutch logistics service provider using multiple data collection methods.

The study shows how decision making of transport planners is motivated by individual goals as well as social preferences for reciprocity and group identity.

Further research including transaction data analysis is needed to triangulate findings and to strengthen conclusions. Propositions are developed to be tested in future research.

Results suggest that efforts to guide planners in their decision making should go beyond traditional (monetary) incentives and consider their individual goals and social preferences. Moreover, this study provides insight into why transport planners deviate from desired behaviour.

While individual decision making plays an essential role in operational planning, the factors influencing how individuals make operational planning decisions are not fully understood.

This study investigates a mediational model between legitimated elements, financial resource mobilisation and subsequent early firm growth among New Technology-Based Firms (NTBFs) using conformity and control perspectives of legitimacy.

To test the hypotheses, a longitudinal database of 303 NTBFs from Sweden, Finland and France is used. The ordinary least square regression analysis method is applied, and the proposed mediation relationships are studied by employing the four-step approach developed by Baron and Kenny (1986).

This study finds that based on the conformity principle, two out of three legitimated elements (business plan and incubator relationship, but not start-up experience) have an impact on financial resource mobilisation, which in turn, is associated with early growth in NTBFs based on the control principle. Thus, financial resource mobilisation positively mediates the relationships among the two legitimated elements and early growth in NTBFs.

This study has several limitations, which also generate promising pathways for future research. Future research should study the relationship between the three legitimacy elements and financial resource mobilisation and early growth across a wider range of firms and settings. The questionnaire was also based on a single point in time and could not capture the evolving nature of the legitimacy elements and fundraising. Hence, future research can examine the multidimensionality of these processes; longitudinal qualitative studies can be a complement, allowing for a better understanding of the impact of legitimacy on NTBFs.

The findings offer implications for managers of NTBFs because developing legitimacy is critical to NTBFs early growth and development. The findings indicate that NTBFs' founders must systematically develop business plans and that incubators help enhance legitimacy through a signalling.

It is believed that the study meaningfully contributes to the collective understanding of the role of legitimacy in driving the development of NTBFs. Given the importance of NTBFs in our economies, coupled with the lack of attention given to the role of mobilisation of external resources in explaining NTBF early growth, it is believed that the study is both timely and important.

The findings meaningfully contribute to the collective understanding of NTBF growth. While there are studies that have examined the antecedents of growth and finance separately, this study proposes a novel mediational model that integrates both and tests it empirically.

The literature on the past triggering learning in strategy practice is scant. To fill this gap, this study aims to examine the meaning of the past to learning in strategy practice and expands on the strategy-as-practice (SAP) literature. Understanding the relationship between the past and learning in strategy practice is important because learning is what keeps strategy practice in motion and remains in place, even if organizations and strategy practitioners change.

The authors used a longitudinal case study design combined with historical methods to examine how the past is embedded in present strategy practice. To capture learning in strategy practice over time, the authors applied a four-stage methodology in our analysis of document and interview data.

The authors identified four dimensions of the past embedded in the present strategy practice. These dimensions emerged from the analysis of the interviews and document data. The study’s results showed that the past appears in structures and routines, materiality, positioning and reflecting over repeated rounds of strategic planning. According to the study’s results, reflecting on strategy practice draws on past structures and routines, positioning and materiality. The past facilitates reflecting and reflecting on the past enables learning in strategy practice.

The authors constructed a conceptual model and showed that in strategy practice, reflection triggers learning. The authors contributed to theory development by demonstrating how the past is embedded in present strategy practice and is available for use by strategy practitioners. The authors showed that strategy practice is a continuous learning process.

The purpose of this paper is to investigate US noncombatant evacuation operations (NEO) in South Korea and devise planning and management procedures that improve the efficiency of those missions.

It formulates a time-staged network model of the South Korean noncombatant evacuation system as a mixed integer linear program to determine an optimal flow configuration that minimizes the time required to complete an evacuation. This solution considers the capacity and resource constraints of multiple transportation modes and effectively allocates the limited assets across a time-staged network to create a feasible evacuation plan. That solution is post-processed and a vehicle routing procedure then produces a high resolution schedule for each individual asset throughout the entire duration of the NEO.

This work makes a clear improvement in the decision-making and resource allocation methodology currently used in a NEO on the Korea peninsula. It immediately provides previously unidentifiable information regarding the scope and requirements of a particular evacuation scenario and then produces an executable schedule for assets to facilitate mission accomplishment.

The significance of this work is not relegated only to evacuation operations on the Korean peninsula; there are numerous other NEO and natural disaster related scenarios that can benefit from this approach.

The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.

The authors develop and validate a conceptual model, the retirement engagement model (REM), to understand the relationships between behavioral engagement (retirement information search), cognitive factors and engagement (e.g. beliefs and financial knowledge), emotional engagement (e.g. anxiety), and socio-demographic factors. Approach: The authors derive the REM through a three-step procedure: (1) an extensive literature review, (2) interactive feedback sessions with experts to confirm the model's academic and managerial relevance, and (3) an empirical test of the REM with field data (N = 583). The authors use a partial least squares (PLS) structural equation model and examine heterogeneity through a finite mixture model.

Around the globe, people are insufficiently engaged with retirement planning. The customer engagement literature offers rich insights into antecedents, outcomes, and barriers to engagement. However, customer engagement literature lacks insights into cognitive, emotional and behavioral factors that drive engagement in retirement planning, a utilitarian service context, which is important for financial well-being.

Beliefs such as perceived susceptibility, severity, benefits, barriers, and self-efficacy, together with trust and retirement anxiety, explain people's search for pension information. These factors can be used to define three clear, actionable segments of consumers.

The findings advance the customer engagement and transformative service research literature by generating insights on engagement with retirement planning, a utilitarian rather than hedonic service context that is especially relevant for financial well-being. The findings inform managerial practice and emphasize the relevance of including cognitive and emotional engagement factors that trigger behavioral engagement. The REM can help to improve pension communication. For example, the results indicate that marketers should stress the benefits of, rather than the barriers to, acquiring information.

The purpose of this paper is to develop a real-time trajectory planner with optimal maneuver for autonomous vehicles to deal with dynamic obstacles during parallel parking.

To deal with dynamic obstacles for autonomous vehicles during parking, a long- and short-term mixed trajectory planning algorithm is proposed in this paper. In long term, considering obstacle behavior, A-star algorithm was improved by RS curve and potential function via spatio-temporal map to obtain a safe and efficient initial trajectory. In short term, this paper proposes a nonlinear model predictive control trajectory optimizer to smooth and adjust the trajectory online based on the vehicle kinematic model. Moreover, the proposed method is simulated and verified in four common dynamic parking scenarios by ACADO Toolkit and QPOASE solver.

Compared with the spline optimization method, the results show that the proposed method can generate efficient obstacle avoidance strategies, safe parking trajectories and control parameters such as the front wheel angle and velocity in high-efficient central processing units.

It is aimed at improving the robustness of automatic parking system and providing a reference for decision-making in a dynamic environment.