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Open Access
Article
Publication date: 5 September 2023

Simone Guercini

This paper examines the relationship between marketing automation emergence and the marketers' use of heuristics in their decision-making processes. Heuristics play a role for the…

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Abstract

Purpose

This paper examines the relationship between marketing automation emergence and the marketers' use of heuristics in their decision-making processes. Heuristics play a role for the integration of human decision-making models and automation in augmentation processes, particularly in marketing where automation is widespread.

Design/methodology/approach

This study analyzes qualitative data about the impact of marketing automation on the scope of heuristics in decision-making models, and it is based on evidence collected from interviews with twenty-two experienced marketers.

Findings

Marketers make extensive use of heuristics to manage their tasks. While the adoption of new automatic marketing tools modify the task environment and field of use of traditional decision-making models, the adoption of heuristics rules with a different scope is essential to defining inputs, interpreting/evaluating outputs and control the marketing automation system.

Originality/value

The paper makes a contribution to research on the relationship between marketing automation and decision-making models. In particular, it proposes the results of in-depth interviews with senior decision makers to assess the impact of marketing automation on the scope of heuristics as decision-making models adopted by marketers.

Details

Management Decision, vol. 61 no. 13
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 8 June 2015

Elisabeth Ilie-Zudor, Anikó Ekárt, Zsolt Kemeny, Christopher Buckingham, Philip Welch and Laszlo Monostori

– The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution.

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Abstract

Purpose

The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution.

Design/methodology/approach

The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments.

Findings

Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes.

Practical implications

The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept.

Originality/value

The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

Details

Supply Chain Management: An International Journal, vol. 20 no. 4
Type: Research Article
ISSN: 1359-8546

Keywords

Open Access
Article
Publication date: 13 February 2024

Felipa de Mello-Sampayo

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these…

Abstract

Purpose

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

Design/methodology/approach

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Findings

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

Practical implications

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Social implications

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

Originality/value

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

Details

Journal of Economic Studies, vol. 51 no. 9
Type: Research Article
ISSN: 0144-3585

Keywords

Open Access
Article
Publication date: 25 March 2024

Florian Follert and Werner Gleißner

From the buying club’s perspective, the transfer of a player can be interpreted as an investment from which the club expects uncertain future benefits. This paper aims to develop…

Abstract

Purpose

From the buying club’s perspective, the transfer of a player can be interpreted as an investment from which the club expects uncertain future benefits. This paper aims to develop a decision-oriented approach for the valuation of football players that could theoretically help clubs determine the subjective value of investing in a player to assess its potential economic advantage.

Design/methodology/approach

We build on a semi-investment-theoretical risk-value model and elaborate an approach that can be applied in imperfect markets under uncertainty. Furthermore, we illustrate the valuation process with a numerical example based on fictitious data. Due to this explicitly intended decision support, our approach differs fundamentally from a large part of the literature, which is empirically based and attempts to explain observable figures through various influencing factors.

Findings

We propose a semi-investment-theoretical valuation approach that is based on a two-step model, namely, a first valuation at the club level and a final calculation to determine the decision value for an individual player. In contrast to the previous literature, we do not rely on an econometric framework that attempts to explain observable past variables but rather present a general, forward-looking decision model that can support managers in their investment decisions.

Originality/value

This approach is the first to show managers how to make an economically rational investment decision by determining the maximum payable price. Nevertheless, there is no normative requirement for the decision-maker. The club will obviously have to supplement the calculus with nonfinancial objectives. Overall, our paper can constitute a first step toward decision-oriented player valuation and for theoretical comparison with practical investment decisions in football clubs, which obviously take into account other specific sports team decisions.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 30 April 2012

Afzal Mohammad Khaled and Yong Jin Kim

Logistical facility location decisions can make a crucial difference in the success or failure of a company. Geographical Information Systems (GIS) have recently become a very…

Abstract

Logistical facility location decisions can make a crucial difference in the success or failure of a company. Geographical Information Systems (GIS) have recently become a very popular decision support system to help deal with facility location problems. However, until recently, GIS methodologies have not been fully embraced as a way to deal with new facility location problems in business logistics. This research makes a framework for categorizing empirical facility location problems based on the intensity of the involvement of GIS methodologies in decision making. This framework was built by analyzing facility location models and GIS methodologies. The research results revealed the depth of the embracement of GIS methodologies in logistics for determining new facility location decisions. In the new facility location decisions, spatial data inputs are almost always coupled with the visualization of the problems and solutions. However, the usage of GIS capability solely (i.e. suitability analysis) for problem solving has not been embraced at the same level. In most cases, the suitability analysis is used together with special optimization models for choosing among the multiple alternatives.

Details

Journal of International Logistics and Trade, vol. 10 no. 1
Type: Research Article
ISSN: 1738-2122

Keywords

Open Access
Article
Publication date: 12 October 2023

Jianchang Fan, Zhun Li, Fei Ye, Yuhui Li and Nana Wan

This study aims to focus on the optimal green R&D of a capital-constrained supply chain under different channel power structures as well as the impact of capital constraint…

Abstract

Purpose

This study aims to focus on the optimal green R&D of a capital-constrained supply chain under different channel power structures as well as the impact of capital constraint, financing cost, channel power structure and cost-reducing efficiency on green R&D and supply chain profitability.

Design/methodology/approach

A two-echelon supply chain is considered. The upstream firm engages in green R&D but has capital constraints that can be overcome by external financing. Green R&D is beneficial to reduce production costs and increase consumer demand. Based on whether or not the upstream firm is capital constrained and dominates the supply chain, four models are developed.

Findings

Capital constraints significantly lower green R&D and supply chain profitability. Transferring leadership from the upstream to the downstream firms leads to higher green R&D levels and downstream firm profitability, whereas the upstream firm's profitability is increased (decreased) if green R&D investment efficiency is high (low) enough. Greater financing costs reduce green R&D and downstream firm profitability; however, the upstream firm's profitability under the model in which it functions as the follower increases if the initial capital is sufficient. More importantly, empirical analysis based on practice data is used to verify the theoretical results reported above.

Practical implications

This study reveals how upstream firms in supply chains decide green R&D decisions in situations with capital constraints, providing managers and governments with an understanding of the impact of capital constraint, channel power structure, financing cost and cost-reducing efficiency on supply chain green R&D and profitability.

Originality/value

The major contributions are the exploration of supply chain green R&D by taking into consideration channel power structures and cost-reducing efficiency and the validation of theoretical results using practice data.

Details

Modern Supply Chain Research and Applications, vol. 5 no. 3
Type: Research Article
ISSN: 2631-3871

Keywords

Open Access
Article
Publication date: 31 July 2023

Mohsen Anvari, Alireza Anvari and Omid Boyer

This paper aims to examine the integration of lateral transshipment and road vulnerability into the humanitarian relief chain in light of affected area priority to address…

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Abstract

Purpose

This paper aims to examine the integration of lateral transshipment and road vulnerability into the humanitarian relief chain in light of affected area priority to address equitable distribution and assess the impact of various parameters on the total average inflated distance traveled per relief item.

Design/methodology/approach

After identifying comprehensive critical criteria and subcriteria, a hybrid multi-criteria decision-making framework was applied to obtain the demand points’ weight and ranking in a real-life earthquake scenario. Direct shipment and lateral transshipment models were then presented and compared. The developed mathematical models are formulated as mixed-integer programming models, considering facility location, inventory prepositioning, road vulnerability and quantity of lateral transshipment.

Findings

The study found that the use of prioritization criteria and subcriteria, in conjunction with lateral transshipment and road vulnerability, resulted in a more equitable distribution of relief items by reducing the total average inflated distance traveled per relief item.

Research limitations/implications

To the best of the authors’ knowledge, this study is one of the first research on equity in humanitarian response through prioritization of demand points. It also bridges the gap between two areas that are typically treated separately: multi-criteria decision-making and humanitarian logistics.

Practical implications

This is the first scholarly work in Shiraz focused on the equitable distribution system by prioritization of demand points and assigning relief items to them after the occurrence of a medium-scale earthquake scenario considering lateral transshipment in the upper echelon.

Originality/value

The paper clarifies how to prioritize demand points to promote equity in humanitarian logistics when the authors have faced multiple factors (i.e. location of relief distribution centers, inventory level, distance, lateral transshipment and road vulnerability) simultaneously.

Details

Journal of Humanitarian Logistics and Supply Chain Management, vol. 13 no. 4
Type: Research Article
ISSN: 2042-6747

Keywords

Open Access
Article
Publication date: 25 October 2021

Yun Bai, Saeed Babanajad and Zheyong Bian

Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces…

Abstract

Purpose

Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces budgetary limitations. Managing a network of transportation infrastructure assets, especially when the number is large, is a multifaceted challenge. This paper aims to develop a life-cycle cost analysis (LCCA) based transportation infrastructure asset management analytical framework to study the impacts of a few key parameters/factors on deterioration and life-cycle cost. Using the bridge as an example infrastructure type, the framework incorporates an optimization model for optimizing maintenance, repair, rehabilitation (MR&R) and replacement decisions in a finite planning horizon.

Design/methodology/approach

The analytical framework is further developed through a series of model variations, scenario and sensitivity analysis, simulation processes and numerical experiments to show the impacts of various parameters/factors and draw managerial insights. One notable analysis is to explicitly model the epistemic uncertainties of infrastructure deterioration models, which have been overlooked in previous research. The proposed methodology can be adapted to different types of assets for solving general asset management and capital planning problems.

Findings

The experiments and case studies revealed several findings. First, the authors showed the importance of the deterioration model parameter (i.e. Markov transition probability). Inaccurate information of p will lead to suboptimal solutions and results in excessive total cost. Second, both agency cost and user cost of a single facility will have significant impacts on the system cost and correlation between them also influences the system cost. Third, the optimal budget can be found and the system cost is tolerant to budge variations within a certain range. Four, the model minimizes the total cost by optimizing the allocation of funds to bridges weighing the trade-off between user and agency costs.

Originality/value

On the path forward to develop the next generation of bridge management systems methodologies, the authors make an exploration of incorporating the epistemic uncertainties of the stochastic deterioration models into bridge MR&R capital planning and decision-making. The authors propose an optimization approach that does not only incorporate the inherent stochasticity of bridge deterioration but also considers the epistemic uncertainties and variances of the model parameters of Markovian transition probabilities due to data errors or modeling processes.

Open Access
Article
Publication date: 16 October 2017

Pawel Sitek, Jaroslaw Wikarek and Peter Nielsen

The purpose of this paper is the need to build a novel approach that would allow flexible modeling and solving of food supply chain management (FSCM) problems. The models

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Abstract

Purpose

The purpose of this paper is the need to build a novel approach that would allow flexible modeling and solving of food supply chain management (FSCM) problems. The models developed would use the data (data-driven modeling) as early as possible at the modeling phase, which would lead to a better and more realistic representation of the problems being modeled.

Design/methodology/approach

An essential feature of the presented approach is its declarativeness. The use of a declarative approach that additionally includes constraint satisfaction problems and provides an opportunity of fast and easy modeling of constrains different in type and character. Implementation of the proposed approach was performed with the use of an original hybrid method in which constraint logic programming (CLP) and mathematical programming (MP) are integrated and transformation of a model is used as a presolving technique.

Findings

The proposed constraint-driven approach has proved to be extremely flexible and efficient. The findings obtained during part of experiments dedicated to efficiency were very interesting. The use of the constraint-driven approach has enabled finding a solution depending on the instance data up to 1,000 times faster than using the MP.

Research limitations/implications

Due to the limited use of exact methods for NP-hard problems, the future study should be to integrate the CLP with environments other than the MP. It is also possible, e.g., with metaheuristics like genetic algorithms, ant colony optimization, etc.

Practical implications

There is a possibility of using the approach as a basis to build a decision support system for FSCM, simple integration with databases, enterprise resource planning systems, management information systems, etc.

Originality/value

The new constraint-driven approach to FSCM has been proposed. The proposed approach is an extension of the hybrid approach. Also, a new decision-making model of distribution and logistics for the food supply chain is built. A presolving technique for this model has been presented.

Open Access
Article
Publication date: 10 January 2020

Xi Jiao, Yuan Zheng and Zhen Liu

A better understanding of the processes that shape households’ adaptation decisions is essential for developing pertinent policies locally, thereby enabling better adaptation…

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Abstract

Purpose

A better understanding of the processes that shape households’ adaptation decisions is essential for developing pertinent policies locally, thereby enabling better adaptation across scales and multiple stakeholders. This paper aims to examine the determinants of household decisions to adapt, it is also possible to target factors that facilitate or constrain adaptation. This helps to identify key components of current adaptive capacity, which leads to important insights into households’ competence to adapt in the future.

Design/methodology/approach

This paper takes a full-pledged approach examining factors and processes that shape households’ climate adaptation decision-making in rural Cambodia at three levels: adaptation status, adaptation intensity and choices of adaptation strategy. The three-stage analyses are materialized by applying the double hurdle model and multivariate probit model, which provides a potential way to systematically assess household adaptation decision-making in rural settings.

Findings

Results show a high level of involvement in adaptation among local households who are facing multiple stressors including climatic risks. The findings suggest that perceived climate change influence households’ decisions in both adaptation status and intensity. Access to financial credit, farmland size, water availability and physical asset holdings are identified as key factors promoting the adoption of more adaptation measures. To facilitate adaptation, collective effort and support at community level is important in providing knowledge based climate information dissemination and early warning systems. Public sector support and development aid programs should focus on positive triggers for targeted community and household adaptation.

Originality/value

The study, to the authors’ best knowledge, is one of the first studies to investigate the determinants of local adaptation decision-making systematically in Cambodia. It also provides a comprehensive approach to improve understanding of adaptation decision-making processes by exploring how various capital assets are associated with different stages of adaptation decisions. The findings contribute to policy implications enlightening adaptation planning at multi-scales with knowledge of key factors, which enhance local adaptive capacity to reduce climate change vulnerability.

Details

International Journal of Climate Change Strategies and Management, vol. 12 no. 1
Type: Research Article
ISSN: 1756-8692

Keywords

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