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This paper aims to forecast inbound and outbound container throughput for Bangkok Port to 2041 and uses the results to inform the future planning and management of the port’s container terminal.

The data used cover a period of 16 years (192 months of observations). Data sources include the Bank of Thailand and the Energy Policy and Planning Office. Cause-and-effect forecasting is adopted for predicting future container throughput by using a vector error correction model (VECM).

Forecasting future container throughput in Bangkok Port will benefit port planning. Various economic factors affect the volume of both inbound and outbound containers through the port. Three cases (scenarios) of container terminal expansion are analyzed and assessed, on the basis of which an optimal scenario is identified.

The economic characteristics of Thailand differ from those of other countries/jurisdictions, such as the USA, the EU, Japan, China, Malaysia and Indonesia, and optimal terminal expansion scenarios may therefore differ from that identified in this study. In addition, six particular countries/jurisdictions are the dominant trading partners of Thailand, but these main trading partners may change in the future.

There are only two major projects that have forecast container throughput volumes for Bangkok Port. The first project, by the Japan International Cooperation Agency, applied both the trend of cargo volumes and the relationship of volumes with economic indices such as population and gross domestic product. The second project, by the Port Authority of Thailand, applied a moving average method to forecast the number of containers. Other authors have used time-series forecasting. Here, the authors apply a VECM to forecast the future container throughput of Bangkok Port.

The article is a description of the real-life experience based on the implementation of a financial forecasting model to inform budgeting and strategic planning. The organization is a charity-based health system that has hospitals and medical centers that provide care to the community. The health system performs a central budgeting process which is typically based on aggregation of individual budgets from the various hospitals and medical centers within the system. All financial data are reported to a central financial information system. Traditionally budgeting was done based on prior year's financial performance with a slight adjustment based on the hospital or medical center finance department's educated guess. This article describes the new forecasting method instituted to predict revenue and expenses, and to improve the budget planning process. Finally, the forecasts from the model are compared with real data to demonstrate accuracy of the financial forecasts. The model is since then being used in the budgeting process.

To show how we can turn cost management practices around and look forward, concentrate on managing risks and costs before they occur.

The paper expands my PhD work, which was a synthesis of three major ideas (life‐cycle costing, activity‐based costing and Monte Carlo methods), design of an approach and testing the approach in many real‐life cases. This paper is to show how this method adds utility in strategic cost management.

My research so far shows that the approach adds the intended value in cost management in general and in strategic cost management in particular.

Since the method has been tested in many settings and rests on well‐tested theory serious limitations are avoided. However, future research should focus on how the method can be simplified and applied in budgeting, i.e. become more operational/tactical.

The main practical implication is that cost management practices need to become less historically oriented and more forward looking so that costs can be eliminated and not just reported. How this can be achieved is shown in practical application.

Both researchers and practitioners can benefit from this paper in that they can see how the merger of Monte Carlo methods, life‐cycle costing and activity‐based costing reduce the need for accurate numbers and improve the quality of cost management in general.

The purpose of this paper is to present the conceptual model of an innovative methodology (SAT) to assess the social acceptance of technology, especially focusing on artificial intelligence (AI)-based technology.

After a review of the literature, this paper presents the main lines by which SAT stands out from current methods, namely, a four-bubble approach and a mix of qualitative and quantitative techniques that offer assessments that look at technology as a socio-technical system. Each bubble determines the social variability of a cluster of values: User-Experience Acceptance, Social Disruptiveness, Value Impact and Trust.

The methodology is still in development, requiring further developments, specifications and validation. Accordingly, the findings of this paper refer to the realm of the research discussion, that is, highlighting the importance of preventively assessing and forecasting the acceptance of technology and building the best design strategies to boost sustainable and ethical technology adoption.

Once SAT method will be validated, it could constitute a useful tool, with societal implications, for helping users, markets and institutions to appraise and determine the co-implications of technology and socio-cultural contexts.

New AI applications flood today’s users and markets, often without a clear understanding of risks and impacts. In the European context, regulations (EU AI Act) and rules (EU Ethics Guidelines for Trustworthy) try to fill this normative gap. The SAT method seeks to integrate the risk-based assessment of AI with an assessment of the perceptive-psychological and socio-behavioural aspects of its social acceptability.

The systems approach is an exemplar of design science research (DSR), whereby specific designs yield generic knowledge. DSR is increasingly being adopted in logistics and operations management research, but many point to neglect of the human aspects of solutions developed. The authors argue that it is possible to look back at the history of the systems movement to seek precedent for ‘dealing’ with the social components, providing a methodologically pluralistic ‘research design’ framework. Thereby, systems approaches are foundational to providing a design-based ‘science’ to progressing the logistics and supply chain management field, dealing with contemporary topics such as resilience.

The authors undertake a discursive assessment of relevant streams of engineering, social science and systems research, with a conceptual development of how the latter influences supply chain design approaches.

Building on a phenomenological framework, the authors create a generic design science research design (DSRD) that enables researchers to choose and integrate the right tools and methods to address simple, complicated and complex problems, dealing with technological, process and social problems.

The DSRD provides a framework by which to exploit a range of methodological stances to problem solving, including quantitative modelling perspectives and ‘soft’ systems social science approaches. Four substantive gaps are identified for future research – establishing the root cause domain of the problem, how to deal with the hierarchy of systems within systems, establishing appropriate criteria for the solution design and how best to deal with chaotic and disordered systems.

The authors argue that the systems approaches offer methodological pluralism by which a generic DSRD may be applied to enhance supply chain design. The authors show the relevance of the DSRD to supply chain design problems including in reducing supply chain dynamics and enhance resilience. In doing so, the study points towards an integrated perspective and future research agenda for designing resilient supply chains.

Deals with the future of service management in specific service management terms but also in broader, societal terms, from both a practitioner and a scholarly perspective. Claims that service management concerns not only what is traditionally known as service organizations, but also constitutes a future paradigm for organizations in general. The goods‐services division in its traditional sense is outdated; it represents a myopic production view, while the service economy is an expression for customer‐oriented and citizen‐oriented, value‐enhancing offering. Although service management has taken a giant step since the late 1970s, we are just beginning to see a new era of management that will fight the battle for economic survival in the future service society.

This paper aims to examine the factors that drive the exporter’s influence toward halal meat supply chain adoption by encompassing the diffusion of innovation (DOI) theory in the context of Pakistan.

Using DOI as an underpinning theory, this study evaluates halal supply chain adoption by collecting data from the members of associations from Pakistan. A total of 258 useable responses were received, and PLS-SEM was adopted using SmartPLS.

The exporter’s adoption of the halal supply chain is determined not only by perceived relative advantage and perceived compatibility but also by perceived complexity, religious beliefs and awareness.

Though this study has practical and managerial implications, it has few limitations. Further studies need to be conducted in other contexts as well with a larger population.

There are limited studies that have tested DOI theory in the context of the halal meat supply chain in Pakistan. Therefore, the author extends the diffusion theory of innovation in the current work. Further, this paper will be a helpful reference guide for academicians, practitioners and researchers.

Different stakeholders frequently disagree on what the true problem is that must be solved and what specific actions must be taken during a change exercise. This article demonstrates a visual method for getting buy-in from stakeholders on the specifics of change using a systems thinking tool known as the current reality tree (CRT).

This study illustrates the use of a systems-thinking methodology to achieve consensus among stakeholders on “what is the real problem?” when envisioning a change. The authors illustrate the effectiveness of the proposed approach using a real-life case study in the context of contract catering.

The CRT enables diverse stakeholders to visualize the cause-and-effect relationships between various problems in a given system and assists them in identifying the set of actions that can address a large number of problems through the change program.

There is little discussion in the literature on change management of a systematic approach to get agreement from stakeholders regarding what the real problem is. This article demonstrates, by way of a case study, how change agents can not only determine which actions will have the greatest impact, but also garner the support of diverse stakeholders.

Selecting an appropriate partner is a vital and strategic decision-making process in any supply chain collaboration initiative. The purpose of this paper is to introduce and explore the key factors considered by manufacturers in the selection of an appropriate retailer(s) for collaboration and collaborative planning, forecasting and replenishment (CPFR) implementation and the relationships between these factors.

A comprehensive literature review and experts’ views are applied to identify the main retailer selection and evaluation factors for CPFR implementation. A fuzzy decision-making trial and evaluation laboratory approach is then used to rank and analysis the interaction among identified factors. The findings are finally evaluated using a case study from a high-tech industry.

The most important partner selection factors comprising of five dimensions and 24 factors are introduced. Of the identified criteria, three factors: manufacturer’s familiarity with the retailer, workforce skills and training and customer service orientation and capability have been identified as critical when selecting retailers for CPFR implementation. The technological capabilities dimensions are identified as the only net cause dimension which affects all other dimensions and its importance and role in simplifying and enhancing the speed and flexibility of CPFR implementation.

The paper identifies practical retailer selection factors for CPFR implementation and the causal relationships between factors. Developed retailer selection dimensions and criteria will assist manufacturers and retailers in understanding the role these factors play in CPFR implementation. This will also assist in appropriate retailer(s) selection by manufacturers.

This paper contributes to the literature on CPFR and tackles the important issue of selecting appropriate partners by developing retailer selection dimensions and criteria in CPFR implementation.

The purpose of this paper is to empirically analyze the determinants of arable crop farmers’ awareness to causes and effects of climate change in south western Nigeria.

Using primary data, 150 arable crop farmers in Ogun State were selected through a multi stage sampling technique. Survey method was used to elicit information on farmers’ socioeconomic, production characteristics, and their level of awareness to causes and effects of climate change. The data collected were analyzed using descriptive statistics, environmental awareness index (EAI), and Tobit regression analysis.

Most (81.08 percent) of the arable crop farmers were males with an average household size of eight persons, farming experience of 24 years and farm size of approximately 1 ha. The computed climate change EAI showed that only 47 percent of the respondents were aware of causes of climate change, while 68 percent were aware of its effects. Results further revealed that age, income from secondary occupation (p < 0.10), marital status, household size (p < 0.05), years of farming experience, frequency of extension contact, land size in hectare, and farm revenue (p < 0.01) were the determinants of respondents awareness to causes and effects of climate change.

The study recommended among others that, awareness should be created among arable crop farmers on climate change causes and effects for appropriate mitigation actions to be taken for improved agricultural productivity.

The study provided new empirical evidence on the awareness level of respondents to causes and effects of climate change on their production activities and livelihood in general. Implications for policy will be to provide a public education program that will target females, the poor, the illiterate, and the people in the economically active age group among others in order to create awareness and provide information and adequate knowledge on the causes and effects of climate change for proper mitigation and adaptation options.