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This paper aims to present the Difference-in-Differences (DiD) method in an accessible language to a broad research audience from a variety of management-related fields.

The paper describes the DiD method, starting with an intuitive explanation, goes through the main assumptions and the regression specification and covers the use of several robustness methods. Recurrent examples from the literature are used to illustrate the different concepts.

By providing an overview of the method, the authors cover the main issues involved when conducting DiD studies, including the fundamentals as well as some recent developments.

The paper can hopefully be of value to a broad range of management scholars interested in applying impact evaluation methods.

The purpose of this paper is to lay out the data competence maturity model (DCMM) and discuss how the application of the model can serve as a foundation for a measured and deliberate use of data in secondary education.

Although the model is new, its implications, and its application are derived from key findings and best practices from the software development, data analytics and secondary education performance literature. These principles can guide educators to better manage student and operational outcomes. This work builds and applies the DCMM model to secondary education.

The conceptual model reveals significant opportunities to improve data-driven decision making in schools and local education agencies (LEAs). Moving past the first and second stages of the data competency maturity model should allow educators to better incorporate data into the regular decision-making process.

Moving up the DCMM to better integrate data into their decision-making process has the potential to produce profound improvements for schools and LEAs. Data science is about making better decisions. Understanding the path laid out in the DCMM to helping an organization move to a more mature data-driven decision-making process will help improve both student and operational outcomes.

This paper brings a new concept, the DCMM, to the educational literature and discusses how these principles can be applied to improve decision making by integrating them into their decision-making process and trying to help the organization mature within this framework.

Farmers often decide simultaneously on crop production or input use without knowing other farmers' decisions. Anticipating the behavior of other farmers can increase financial performance. This paper investigates the role of other famers' behaviors and other contextual factors in farmers' simultaneous production decisions.

Market entry games are a common method for investigating simultaneous production decisions. However, so far they have been conducted with abstract tasks and by untrained subjects. The authors extend market entry games by using three real contexts: pesticide use, animal welfare and wheat production, in an incentivized framed field experiment with 323 German farmers.

The authors find that farmers take different decisions under identical incentive structures for the three contexts. While context plays a major role in their decisions, their expectations about the behavior of other farmers have little influence on their decision.

The paper offers new insights into the decision-making behavior of farmers. A better understanding of how farmers anticipate the behavior of other farmers in their production decisions can improve both the performance of individual farms and the allocational efficiency of agricultural and food markets.

The purpose of this study was to create an air movement operations planning model to rapidly generate air mission request (AMR) assignment and routing courses of action (COA) in order to minimize unsupported AMRs, aircraft utilization and routing cost.

In this paper, the US Army Aviation air movement operations planning problem is modeled as a mixed integer linear program (MILP) as an extension of the dial-a-ride problem (DARP). The paper also introduces a heuristic as an extension of a single-vehicle DARP demand insertion algorithm to generate feasible solutions in a tactically useful time period.

The MILP model generates optimal solutions for small problems (low numbers of AMRs and small helicopter fleets). The heuristic generates near-optimal feasible solutions for problems of various sizes (up to 100 AMRs and 10 helicopter team fleet size) in near real time.

Due to the inability of the MILP to produce optimal solutions for mid- and large-sized problems, this research is limited in commenting on the heuristic solution quality beyond the numerical experimentation. Additionally, the authors make several simplifying assumptions to generalize the average performance and capabilities of aircraft throughout a flight.

This research is the first to solve the US Army Aviation air movement operations planning problem via a single formulation that incorporates multiple refuel nodes, minimization of unsupported demand by priority level, demand time windows, aircraft team utilization penalties, aircraft team time windows and maximum duration and passenger ride time limits.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

This paper presents a critical review of the economic network analysis methods and their applications to maritime transport. A network can be presented in terms of its structure, topology, characteristics as well as the connectivity with different measures such as density, degree distribution, centrality (degree, betweenness, closeness, eigenvector and strength), clustering coefficient, average shortest path length and assortative. Various models such as the random graph model, block model, and ERGM can be used to analyse and explore the formation of a network and interaction between nodes. The review of the existing theories and models has found that, while these models are rather computationally intensive, they are based on some rather restrictive assumption on network formation and relationship between ports in the network at the local and global levels that require further investigation. Based on the review, a conceptual framework for maritime transport network research is developed, and the applications for future research are also discussed.

The research discussed in this paper aims to study the impact of video footages on the academic performance of students. Video footages are usually inserted into video lectures — in addition to the verbal narration of any examples by the teachers — to explain and simplify concepts. Similarly, in conventional classrooms, teachers verbally narrate examples to clarify concepts — but, in this case, students have to rely on their imagination and previous exposure to similar situations to develop an understanding of the concepts.

A two-phase experiment was designed to compare these two teaching methods. A sample of 70 participants was drawn from non-psychology students in the Virtual University of Pakistan; and two groups, Group A and Group B, each with 35 participants, were formed through random assignment of the students. In the first phase of the experiment, members of Group A were taught through a 24-minute video lecture on psychology, which had four chunks of video footage in it. After the lecture, the students' academic learning was measured through a multiple-choice test with 27 items, which was developed by incorporating an equal number of questions on three levels of Bloom's taxonomy (viz. understanding, comprehension and application). The item levels were decided after agreement by three examiners who had at least three years of experience of developing such questions. In the second phase, a lecture with similar content was taught to Group B. The only difference was in the mode of delivery: in this case, the content was conveyed verbally and no video footages were used. The same test of students' learning was employed to get the scores of Group B. In addition, a qualitative study, involving data gathered through participants' feedback on the performance of the learning facilitators and weaknesses in both teaching modes was collected in order to explore the participants' perceptions and experiences of the phenomenon being studied. The results indicated that the two groups were significantly different in terms of academic achievement. The mean values suggested that those who were taught through video footages showed a higher level of academic learning than those who received a traditional verbal narration lecture. In addition, the students reported that the video footages and examples facilitated their learning, and helped them to remain focused and motivated in class. The findings have broad implications for teachers, content developers, academic policy-makers and producers involved in the production of academic content.

The lecture method has been compared with teaching methods such as flip learning, cooperative learning and simulations to establish which holds the key to students' understanding of concepts. What is bereft in the education literature is its comparative efficiency with the culturo-techno contextual approach (CTCA) in the teaching of computer science education.

This study adopted the quasi-experimental design to determine the efficacy of the CTCA in breaking difficulties related to the study of spreadsheets as a difficult concept in the Nigerian computer science education curriculum. Junior high school students studying computer science education participated in the study. The control group had 30 students, with 35 students in the experimental group. The experimental group was taught using CTCA, while the control group used the lecture method. The spread sheet achievement test, which had 40 items on spreadsheet, was used to collect data.

The results showed that the experimental group significantly outperformed the control group [F (1,60) = 41.89; p < 0.05]. The findings showed the potential of CTCA in improving students' performance in spreadsheets in the computer science education curriculum.

The originality of this study is hinged on its ground-breaking test of the CTCA to the study of the spreadsheet. The findings of this study indicate its efficacy in improving students' understanding of spreadsheet and computer science education.

The use of queueing network models was stimulated by the appearance (1975) of the exact product form solution of a class of open, closed and mixed queueing networks obeying the local balance principle and solved, a few years later, by the popular mean value analysis algorithm (1980). Since then, research efforts have been produced to approximate solutions for non-exponential services and non-pure random mechanisms in customer processing and routing. The purpose of this paper is to examine the suitability of modeling choices and solution approaches consolidated in other domains with respect to two key logistic processes in container terminals.

In particular, the analytical solution of queueing networks is assessed for the vessel arrival-departure process and the container internal transfer process with respect to a real terminal of pure transshipment.

Numerical experiments show the extent to which a decomposition-based approximation, under fixed or state-dependent arrival rates, may be suitable for the approximate analysis of the queueing network models.

The limitation of adopting exponential service time distributions and Poisson flows is highlighted.

Comparisons with a simulation-based solution deliver numerical evidence on the companion use of simulation in the daily practice of managing operations in a finite-time horizon under complex policies.

Discussion of some open modeling issues and encouraging results provide some guidelines on future research efforts and/or suitable adaption to container terminal logistics of the large body of techniques and algorithms available nowadays for supporting long-run decisions.