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The purpose of this paper is to establish a combined forecasting model to predict regional logistics demand, which is an important procedure on decision making of regional logistics planning.

There are several kinds of mathematical models often used in forecasting regional logistics demand. Trend extrapolation method extrapolates the future development trends bases on the hypothesis that the regional logistics will develop steadily. Grey system method predicts the change of logistics demand by the generation and development of original data sequence and excavation of inherent rules of the original data. Regression method obtains the change rules through the analysis between explained variable and explanatory variables. Each method has unique characteristics. In order to improve the accuracy of the prediction, combined methods are established. Genetic algorithm is used to determine the weights of different single models.

The results show that the combined forecasting model optimised by genetic algorithm can improve the accuracy.

Combined forecasting model can integrate the advantages of different single forecasting models. The key of improving the accuracy is to determine the weights of single forecasting models. Genetic algorithm can do well in finding suitable weights of each single forecasting model.

The paper succeeds in providing a combined forecasting model using genetic algorithm to determine the weights of each single prediction model, which helps to the decision making of regional logistics demand.

Traditional methods of capturing and determining logistics attribute importance have serious research limitations. The purpose of this paper is to introduce maximum difference (MD) scaling as a new research methodology that will improve validity in measuring logistics attribute importance, overcoming many of the limitations associated with traditional methods. In addition, this new research method will allow logistics researchers to identify meaningful need‐based segments, an important goal of logistics research.

This paper provides an overview of MD scaling along with important research advantages, limitations, and practical applications. Additionally, a detailed research process is put forth so that this technique can be implemented by logistics researchers. Finally, an application of this technique is presented to illustrate the research method.

The importance of truck driver satisfaction attributes was analyzed using bivariate correlation analysis as well as MD scaling analysis. The two sets of results are compared and contrasted. The resulting rank order of attributes is very different and MD scaling results are shown to possess important advantages. As a result of this analysis, MD scaling analysis allows for meaningful, need‐based segmentation analysis, resulting in two unique need‐based driver segments.

From a practitioner viewpoint, knowing which attributes are most important will help in investing scarce resources to improve decision making and raise a firm's ROI. Although a number of relevant applications exist, the most important may include examining: the importance of customer service attributes; the importance of logistics service quality attributes; and the importance of customer satisfaction attributes.

MD scaling is a relatively new research technique, a technique that has yet to be utilized or even explored in existing logistics and supply chain literature. Yet, evidence is mounting in other fields that suggest this technique has many important and unique advantages. This paper is the first overview, discussion, and application of this technique for logistics and supply chain management and creates a strong foundation for implementing MD scaling in future logistics and supply chain management research.

The purpose of this paper is to provide an insight to the outsourcing decision-making through investigating if the old evaluation/selection criteria and methods still fit with current business priorities or not and, therefore, to identify the appropriate criteria and methods to develop a new selection framework. Since the economic recession of 2008, logistics outsourcing decisions have become more prominent to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages.

This is a focused literature review prepared after analyzing 56 articles related to the logistics service provider (LSP) evaluation and selection methods and criteria during 2008-2013. The academic articles are analyzed based on research focus/area, evaluation and selection methodology/methods and evaluation and selection criteria. Then reviewed result is compared with previous literature studies for the periods (1991-2008) to identify any possible shifts.

The review reveals that: several problems in current LSPs literature have been identified; the reviewed papers can be categorized into seven groups, the usage and importance of evaluation and selection criteria fluctuate during different periods; 12 crucial criteria have been identified, increasing the importance of specific selection methods and the integrated models and fuzzy logic in logistics literature. Then, a comprehensive LSPs’ evaluation and selection framework has been developed.

To the best of our knowledge, this is the first focused logistics outsourcing study that reviews the 2008-2013 period in detail, comparing results with previous literature studies, identifies current LSPs literature problems/gaps, new trends and shifts in the way that LSPs are evaluated and selected, identifies crucial selection criteria and proposes a new holistic LSPs evaluation and selection framework. In addition, it identifies important issues for future research.

This paper aims to examine the use of a qualitative data analysis technique, the documentary method, in the development of knowledge in logistics. The value of the method is illustrated through an example of its application in a study of in‐store logistics processes at six leading European retail stores.

Extant literature is outlined regarding philosophical underpinnings of the documentary method and is followed by an explanation of the method and its application. Finally, an illustration is provided of its adaptation and use in a logistics research project.

Drawing on a social constructionist approach, the documentary method can add to the development of logistics research by providing rich descriptions of actual practice, problems and issues in logistic processes – compared with the stated goals of such processes.

The documentary method is not suitable for all areas of logistics research and will need certain adaptations and adjustments when transferred into particular research contexts. In addition, the research question, philosophical stance, and knowledge of qualitative methodologies will ultimately determine the appropriateness of the technique.

The paper presents the first application of the documentary method in the field of logistics.

This paper describes how qualitative research methods, particularly action research case studies, can contribute to further advance and develop logistics research. The paper also describes limitations with the current dominance of quantitative (especially survey) research in logistics. However, the paper is not a pure criticism of the use of quantitative research methods in general or in logistics in specific. Rather, the argument is that it is necessary to use both quantitative and qualitative methods if we really want to develop and advance logistics research. Logistics problems are often ill‐structured, even messy, real‐world problems. Modern logistics is based on holistic and systemic thinking and uses multi‐disciplinary and cross‐functional approaches. Thus action research case studies are especially suited for an applied field such as logistics since they strive to advance both science and practice. This should also be reflected in published logistics research, which it is not. In order to change this situation, we first have to understand paradigms and their influence on how we approach and evaluate research. Second, we have to define what case studies in journal articles mean. Third, we need to develop criteria for evaluating action research case studies.

To examine the state of logistics and supply chain management (SCM) research in the last five years from the standpoint of existing methodologies. The state of research is assessed by examining the research design, number of hypothesis testing, research methods, data analysis techniques, data sources, level of analysis and country of authors.

The review of SCM and logistics research is based on 442 papers published from 1999 to 2003 in the following three academic journals Journal of Business Logistics, International Journal of Physical Distribution & Logistics Management, and Supply Chain Management: An International Journal.

Major findings show that there is an increase in the direct observation methods like case studies. In general, the research is more interpretive in nature. Survey method is still holding the highest position. More advanced techniques are being used for data analysis in empirical studies and there has been an increase in hypothesis testing. The trend in survey research is moving from exploratory to model building and testing.

The gaps identified in the review were: there are very few inter disciplinary studies; innovative application of secondary data is lacking, (c) research at inter organisation level is scanty; and the current state of research has failed to integrate all the firms in the value chain and treat them as a single entity.

The methodological review will provide increased understanding of the current state of research in the discipline.

Based on a framework developed by Kovács and Spens, this paper seeks to assess the use of the three different research approaches in logistics research; discuss the use of different research methods within the three research approaches; find and discuss applications of the abductive research approach to logistics problems.

Content analysis is used in order to categorize the different research approaches. While content analysis commonly uses smaller units such as paragraphs, sentences, words or characters, this study used entire articles as the unit of analysis. The scope of the review encompassed five years (1998‐2002) of articles in IJLM, IJPDLM and JBL. A total of 378 articles was reviewed and categorized.

The findings of the study corroborate earlier studies regarding the main research approach used in logistics. Published logistics research is hypothetico‐deductive, with a strong emphasis on using survey methods. Nevertheless, inductive as well as abductive research is gaining importance. However, most logistics articles do not explicitly discuss the research process, nor the approach used. Therefore, a call for more explicit statements of the research approach is suggested.

The review of the articles is limited to three main journals in the field. A more comprehensive view of research approaches could be obtained by broadening the review to include also other types of research.

The paper provides a framework and guidelines to researchers for explicitly discussing the research approach used in logistics articles.

The paper provides an overview of the research approaches used in logistics research.

The purpose of this paper is to provide a structured literature review (SLR) and systematic insight into logistics outsourcing research, in order to identify gaps in knowledge, and provide future research direction in the logistics outsourcing discipline.

This paper identifies and synthesises information from academic journals and examines research designs and methods, data analysis techniques, geographic locations, industry engagements, year of publication, publishers, university and author affiliations. A collection of online databases from 1991 to 2016 were explored, using the keywords “third-party”, “logistics” and “outsourcing” in their title and/or abstract, to deliver an inclusive listing of journal articles in this discipline area. Based on this approach, a total of 263 articles were found and data were derived from a succession of variables.

There has been a significant increase and concentration by researchers over the past 25 years focussing on logistics outsourcing. A need to implement best practice has been universally identified, owing to increasing global supply chain complexity. This analysis shows that only seven literature reviews were published in the logistics outsourcing discipline. Additionally, this study revealed that 42 per cent of the work in this field was found to be survey based and this trend in research indicates the development of the structural equation modelling and multi-criterion decision-making methods. Investigations between 2010–2012 and 2015–2016 accounted for 151 of the total 263 articles published. Finally, reverse logistics is an area that requires special attention.

This paper is limited to a review of academic articles obtainable from online databases, containing the words “logistics” and “outsourcing” in the title and/or abstract. Additionally, only papers from high quality, peer-reviewed journals were evaluated. Other academic sources such as books and conference papers were not included in this study.

This review will provide an increased understanding of the existing state of current research, trends and future research directions in the logistics outsourcing discipline.

Much of the research conducted in logistics/SCM has focused on satisfaction/retention of customers. This has left a critical gap for managers: before customers can be satisfied and ultimately retained, a purchase choice of logistics services has to occur. To date, very little research has addressed how logistics customers make purchase choice decisions about logistics services. The purpose of this paper, using logistics research methods, is to introduce adaptive choice modelling (ACM) to address this gap and put forth a research method that is useful for academic researchers and logistics/SCM managers.

This paper provides an overview of ACM, along with a discussion of its important research advantages, limitations, and practical applications. Additionally, an empirical demonstration of this research technique is provided to illustrate how academic researchers and logistics managers can use ACM to better understand the decision‐making process of customers when selecting logistics services.

In order to demonstrate this research technique, a research project was designed and implemented that analyzed the choice process of consumers selecting parcel carriers to ship a textbook. The results show that price, speed of delivery, and tracking are the three most important variables in the selection decision. The results also show that consumers are not homogeneous, but can be divided into five distinct need‐based segments. Recognizing and understanding the nature of these segments should help managers better meet the needs of parcel shippers.

The main research limitation with this study is that it is based on a convenience sample; thus future research will need to replicate this study to confirm the research findings. However, the ultimate purpose of the study is to present a new research method and discuss how to apply this method, so that logistics/SCM practitioners and academic researchers can better understand customers of logistics/SCM services. Thus, while the nature of the sample is a limitation, it should be viewed in this context.

While conjoint analysis has existed for decades, this technique has rarely been implemented by logistics/SCM researchers and practitioners. Instead, logistics/SCM researchers and practitioners have focused more on retention methods and have virtually ignored modelling the actual purchase choice of logistics/SCM services. New advancements in conjoint analysis, specifically the ACM approach, have many important and unique advantages and applications for logistics/SCM researchers and practitioners. ACM has not been used in a logistics/SCM context.

The purpose of this paper is to present a methodology for research through game design and discuss how simulation games can be used to bridge the gap between operational exercises and simulation or analytical modelling and to provide guidelines on how simulation games can be designed for different research purposes in the context of humanitarian logistics.

This paper combines a literature review on gaming as a research method with an analysis of requirements for humanitarian logistics research methods. Starting from this theoretical framework, the authors develop a design thinking approach that highlights how games can be used for different research purposes. To illustrate the approach, the authors develop two different game set-ups that are of increasing fidelity and complexity. Finally, the authors discuss the results of the evaluation of both approaches, reflect on the design choices and provide recommendations for research and practice.

Gaming is a suitable research method to explore and analyse behaviour and decisions in emergent settings that require team work and collaborative problem solving. Especially when safety and security concerns may hinder access and experimentation on site, gaming can offer a realistic and engaging quasi-experimental environment. The aspects of engagement and realism also make gaming a suitable tool to combine training and research.

Although the use of games has attracted some attention in commercial supply chain management and crisis response, there is no systematic overview of gaming as a research method in humanitarian logistics. This paper is set to make a headway in addressing this gap by proposing a concrete approach to design games for humanitarian logistics research.